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Traditionally, polyaniline was used for sensing ammonia (NH 3 ) gas due to the change of conductivity. By integrated with surface acoustic wave sensor (SAW) for sensing the amino-group type of gas, a novel bio-chemical sensor had been developed. The mechanism of the SAW sensor is that the change of gravity results in the change of physical characteristics of SAW sensor. In order to increase the absorbability of the polymer, we use the nano structure to increase the surface area ratio that can make gaseous molecular being absorbed onto the nano structure quickly. Three kinds of solvent vapor were tested: ammonium hydroxide, triethylamine, and acetone

['Da-Jeng Yao', 'Yong-Ruei Yang']

Bio-chemical sensor using polyaniline nanofibers for sensing amino-group type of gas

We describe a novel load-balancing method for sort-first parallel graphics rendering systems. It gives up geometry data which could be very large and tends to cause unacceptable cost. Instead it takes rendering time as the measurement of render nodes’ work load and produces new screen decomposition using a time-to-space algorithm. Test results show that the geometry data independent method is very effective.

['Zhefan Jin', 'Jiaoying Shi']

A Geometry Data Independent Load Balancing Method For Graphics Parallel Rendering

Factory Tour of Seiko Epson Corporation

['Kazuo Yamafuji', 'Takashi Kawamura']

Factory Tour of Seiko Epson Corporation

Activity recognition has applications in a variety of human-in-the-loop settings such as smart home health monitoring, green building energy and occupancy management, intelligent transportation, and participatory sensing. While fine-grained activity recognition systems and approaches help enable a multitude of novel applications, discovering them with non-intrusive ambient sensor systems pose challenging design, as well as data processing, mining, and activity recognition issues. In this paper, we develop a low-cost heterogeneous Radar based Activity Monitoring (RAM) system for recognizing fine-grained activities. We exploit the feasibility of using an array of heterogeneous micro-doppler radars to recognize low-level activities. We prototype a short-range and a long-range radar system and evaluate the feasibility of using the system for fine-grained activity recognition. In our evaluation, using real data traces, we show that our system can detect fine-grained user activities with 92.84% accuracy.

['Abdullah Al Hafiz Khan', 'Ruthvik Kukkapalli', 'Piyush Waradpande', 'Sekar Kulandaivel', 'Nilanjan Banerjee', 'Nirmalya Roy', 'Ryan Robucci']

RAM: Radar-based activity monitor

Distributed systems with different levels of dependence to central services have been designed and used during recent years. Pure peer-to-peer systems among distributed systems have no dependence on a central resource. DHT is one of the main techniques behind these systems resulting into failure tolerant systems which are also able to isolate continuous changes to the network to a small section of it and therefore making it possible to scale up such networks to millions of nodes. This survey takes a look at P2P in general and DHT algorithms and implementations in more detail.

['Siamak Sarmady']

A Survey on Peer-to-Peer and DHT

The construction of inter-visibility models for a terrain is an important tool for environmental and animal studies. Efficient crisp algorithms are known to address this problem directly on a raster digital elevation map (DEM) of the study area. Randomness plays an important role: several factors like vegetation, height of the observer, presence of unmapped human artifacts, etc. cannot be modeled in advance into a traditional DEM model. We propose the use of fuzzy terrain models to incorporate uncertainty and unpredictable variability of the landscape. Accordingly, we propose a suitable definition of visibility to obtain intervisibility models. An algorithm that uses approximation of fuzzy numbers with a discrete family of intervals is proposed.The proposed model produces sound results and can be extended to model complex situations like triangulating a radio source using two directional receivers. All of these situations are difficult to manage with a precise stochastic model and are a frequent occurrence in animal behavior studies under field conditions. The proposed techniques have been implemented inside a user-friendly software package that may easily exchange data with the most common GISs. We report also some experimental results obtained using over artificial terrain under controlled noise and under-sampling conditions.

['Marcello A. Anile', 'Primo Furno', 'Giovanni Gallo', 'Alessandro Massolo']

A fuzzy approach to visibility maps creation over digital terrains

We are interested in generating novel video sequences from a ball's point of view for sports domains. Despite the challenge of extreme camera motion, we show that we can leverage the periodicity of spinning cameras to generate a stabilized ball point-of-view video. We present preliminary results of image stabilization and view synthesis from a single camera being hurled in the air at 600 RPM.

['Kris M. Kitani', 'Kodai Horita', 'Hideki Koike']

BallCam!: dynamic view synthesis from spinning cameras

Recently, there has been a diffusion of smart phones in Korea and Japan. We investigated the driving forces behind this diffusion by analyzing smart phone driving usage by a component model. There were four main findings. 1) Driving usage of smart phones is very popular in both Korea and Japan. Both countries have the highest average smart phone traffic per user in the world. 2) The Korean government and private Korean companies support the diffusion of smart phones. People in both Korea and Japan have started using smart phones at work as well as for fun, and some companies even support their employees' smart phone purchases and share the monthly charge. 3) Telecommunication companies and smart phone manufacturers are currently trying to expand their application stores. Korea Telecom, Samsung, and NTT DoCoMo have set aside funds for application developers and the development of tools. 4) The bargaining power of telecommunication companies is beginning to wane against Apple and Google.

['Yousin Park', 'Masashi Ueda']

A Comparative Study on the Diffusion of Smartphones in Korea and Japan

Redirection techniques allow users to explore large virtual environments on foot while remaining within a limited physical space. However, research has primarily focused on redirection through manipulation of the visuals used to represent the virtual environment. We describe a within-subjects study (n=31) exploring if participants' ability to detect differences between real and virtual rotations is influenced by the addition of sound that is spatially aligned with its virtual source. The results revealed similar detection thresholds for conditions involving moving audio, static audio, and no audio. This may be viewed as an indication of visual dominance during scenarios such as the one used for the current study.

['Niels Christian Nilsson', 'Evan A. Suma', 'Rolf Nordahl', 'Mark T. Bolas', 'Stefania Serafin']

Estimation of detection thresholds for audiovisual rotation gains

How much do word embeddings encode about syntax

['Jacob Andreas', 'Daniel N. Klein']

How much do word embeddings encode about syntax

We review the rapidly evolving efforts to analyze, model, simulate, and engineer genetic and biochemical information processing systems within living cells. We begin by showing that the fundamental elements of information processing in electronic and genetic systems are strikingly similar, and follow this theme through a review of efforts to create synthetic genetic circuits. In particular, we describe and review the "silicon mimetic" approach, where genetic circuits are engineered to mimic the functionality of semiconductor devices such as logic gates, latched circuits, and oscillators. This is followed with a review of the analysis, modeling, and simulation of natural and synthetic genetic circuits, which often proceed in a manner similar to that used for electronic systems. We conclude by presenting examples of naturally occurring genetic and biochemical systems that recently have been conceptualized in terms familiar to systems engineers. Our review of these newly forming fields of research demonstrates that the expertise and skills contained within electrical and computer engineering disciplines apply not only to design within biological systems, but also to the development of a deeper understanding of biological functionality. This review of these efforts points to the emergence of both engineering and basic science disciplines following parallel paths.

['Michael L. Simpson', 'Chris D. Cox', 'Gregory D. Peterson', 'Gary S. Sayler']

Engineering in the biological substrate: information processing in genetic circuits

This paper proposes a novel biological vision-based facial description, namely Perceived Facial Images (PFIs), aiming to highlight intra-class and inter-class variations of both facial range and texture images for textured 3D face recognition. These generated PFIs simulate the response of complex neurons to gradient information within a certain neighborhood and possess the properties of being highly distinctive and robust to affine illumination and geometric transformation. Based on such an intermediate facial representation, SIFT-based matching is further carried out to calculate similarity scores between a given probe face and the gallery ones. Because the facial description generates a PFI for each quantized gradient orientation of range and texture faces, we then propose a score level fusion strategy which optimizes the weights using a genetic algorithm in a learning step. Evaluated on the entire FRGC v2.0 database, the rank-one recognition rate using only 3D or 2D modality is 95.5% and 95.9%, respectively; while fusing both modalities, i.e. range and texture-based PFIs, the final accuracy is 98.0%, demonstrating the effectiveness of the proposed biological vision-based facial description and the optimized weighted sum fusion.

['Di Huang', 'Wael Ben Soltana', 'Mohsen Ardabilian', 'Yunhong Wang', 'Liming Chen']

Textured 3D face recognition using biological vision-based facial representation and optimized weighted sum fusion

Recently, fourth-party logistics (4PL) is receiving considerable attention in the manufacturing and retail industries. However, due to the complexity, the research of routing problem in 4PL is in an initial stage. The existing study does not consider the complicated problem with node-edge property. This paper studies the node-to-node routing problem in 4PL. A mathematical model is set up based on nonlinear integer programming and multigraph. With respect to the problempsilas characteristics a hybrid immune algorithm is designed. The simulation shows that the hybrid immune algorithm is effective for solving the problem and provides an efficient method for making decision on routing in 4PL.

['Min Huang', 'Guihua Bo', 'Wei Tong', 'W. H. Ip', 'Xingwei Wang']

A hybrid immune algorithm for solving Fourth-Party Logistics routing optimizing problem

Task scheduling is widely studied in various environments such as cluster, grid and cloud computing systems. Moreover, it is NP-Complete as the optimization criteria is to minimize the overall processing time of all the tasks (i.e., makespan). However, minimization of makespan does not equate to customer satisfaction. In this paper, the authors propose a customer-oriented task scheduling algorithm for heterogeneous multi-cloud environment. The basic idea of this algorithm is to assign a suitable task for each cloud which takes minimum execution time. Then it balances the makespan by inserting as much as tasks into the idle slots of each cloud. As a result, the customers will get better services in minimum time. They simulate the proposed algorithm in a virtualized environment and compare the simulation results with a well-known algorithm, called cloud min-min scheduling. The results show the superiority of the proposed algorithm in terms of customer satisfaction and surplus customer expectation. The authors validate the results using two statistical techniques, namely T-test and ANOVA.

['Sohan Kumar Pande', 'Sanjaya Kumar Panda', 'Satyabrata Das']

A Customer-Oriented Task Scheduling for Heterogeneous Multi-Cloud Environment

Online users usually observe or refer to others' behaviors and discount their own information when purchasing products online. This research employed a fixed-effect regression model to elucidate how information cascades could influence online purchase behaviors and how they moderated the influence of online word-of-mouth and product prices. To uncover the underlying mechanisms behind informational cascades, we compare search products and experience products. In particular, we utilize publicly available data from a B2C e-commerce site in China, i.e., Tmall.com. Our results indicate that online users' choice of products was heavily driven by changes in product rankings after controlling for cumulative sales, online user reviews and product price, as predicted by informational cascades theory. Due to the information cascades effect, review volume had no impact on online users' choice of products with high rankings, whereas it did exert a significant positive impact on consumer purchase decisions of products with low rankings. User rating had no impact on online users' purchase decisions. Product price had a significant and negative impact for products with high rankings, but had a significant and positive influence on users' choice for products with low rankings. Moreover, information cascades were more prominent for experience goods than for search goods.

['Qihua Liu', 'Shan Huang', 'Liyi Zhang']

The influence of information cascades on online purchase behaviors of search and experience products

In this paper, we present a new, semi-automated methodology for mapping hydromorphological indicators of rivers at a regional scale using multisource remote sensing (RS) data. This novel approach is based on the integration of spectral and topographic information within a multilevel, geographic, object-based image analysis (GEOBIA). Different segmentation levels were generated based on the two sources of Remote Sensing (RS) data, namely very-high spatial resolution, near-infrared imagery (VHR) and high-resolution LiDAR topography. At each level, different input object features were tested with Machine Learning classifiers for mapping riverscape units and in-stream mesohabitats. The GEOBIA approach proved to be a powerful tool for analyzing the river system at different levels of detail and for coupling spectral and topographic datasets, allowing for the delineation of the natural fluvial corridor with its primary riverscape units (e.g., water channel, unvegetated sediment bars, riparian densely-vegetated units, etc.) and in-stream mesohabitats with a high level of accuracy, respectively of K = 0.91 and K = 0.83. This method is flexible and can be adapted to different sources of data, with the potential to be implemented at regional scales in the future. The analyzed dataset, composed of VHR imagery and LiDAR data, is nowadays increasingly available at larger scales, notably through European Member States. At the same time, this methodology provides a tool for monitoring and characterizing the hydromorphological status of river systems continuously along the entire channel network and coherently through time, opening novel and significant perspectives to river science and management, notably for planning and targeting actions.

['Luca Demarchi', 'S. Bizzi', 'Hervé Piégay']

Hierarchical Object-Based Mapping of Riverscape Units and in-Stream Mesohabitats Using LiDAR and VHR Imagery

Generating Routing-Driven Power Distribution Networks with Machine-Learning Technique

['Wen-Hsiang Chang', 'Chien-Hsueh Lin', 'Szu-Pang Mu', 'Li-De Chen', 'Cheng-Hong Tsai', 'Yen-Chih Chiu', 'Mango Chia-Tso Chao']

Generating Routing-Driven Power Distribution Networks with Machine-Learning Technique

In this paper we address the issues of using edge detection techniques on facial images to produce cancellable biometric templates and a novel method for template verification against tampering. With increasing use of biometrics, there is a real threat for the conventional systems using face databases, which store images of users in raw and unaltered form. If compromised not only it is irrevocable, but can be misused for cross-matching across different databases. So it is desirable to generate and store revocable templates for the same user in different applications to prevent cross-matching and to enhance security, while maintaining privacy and ethics. By comparing different edge detection methods it has been observed that the edge detection based on the Roberts Cross operator performs consistently well across multiple face datasets, in which the face images have been taken under a variety of conditions. We have proposed a novel scheme using hashing, for extra verification, in order to harden the security of the stored biometric templates.

['Manoj Krishnaswamy', 'G. Hemantha Kumar']

Enhancing Template Security of Face Biometrics by Using Edge Detection and Hashing

Modelling insight: The case of the nine-dot problem.

['Adrian Banks', 'Thomas C. Ormerod', 'P Rusconi', 'Jim MacGregor']

Modelling insight: The case of the nine-dot problem.

Motivation: The topology of the network induced by the neurons connectivity's in the Caenorhabditis elegans differs from most common random networks. The neurons positions of the C.elegans have been previously explained as being optimal to induce the required network wiring. We here propose a complementary explanation that the network wiring is the direct result of a local stochastic synapse formation process.#R##N##R##N#Results: We show that a model based on the physical distance between neurons can explain the C.elegans neural network structure, specifically, we demonstrate that a simple model based on a geometrical synapse formation probability and the inhibition of short coherent cycles can explain the properties of the C.elegans' neural network. We suggest this model as an initial framework to discuss neural network generation and as a first step toward the development of models for more advanced creatures. In order to measure the circle frequency in the network, a novel graph-theory circle length measurement algorithm is proposed.#R##N##R##N#Contact: [email protected]#R##N##R##N#Supplementary information: Supplementary data are available at Bioinformatics online.

['Royi Itzhack', 'Yoram Louzoun']

Random distance dependent attachment as a model for neural network generation in the Caenorhabditis elegans

In the past, several heuristic based programs have been reported to obtain an efficient sum of product (SOP) form expression for a given MVL function using the literal, min, and tsum set of operators. HAMLET, one of these programs, includes implementation of many earlier reported heuristic based algorithms. In HAMLET, the Gold heuristic chooses the best realization after applying all other heuristics implemented. A novel heuristic based program is reported for the realization of MVL functions in SOP form using the literal, cycle, complement of literal, complement of cycle, min, and tsum set of operators. It is known that the cost, in terms of the number of transistors, of realizing this set of operators (in current mode CMOS) and that of existing sets of operators is comparable. For a random sample of 4 valued, 2 variable functions the realizations have been compared for the developed program and HAMLET (Gold). The average number of PTs required by the developed program and HAMLET (Gold) were 5.53 and 6.62, respectively.

['A. K. Jain', 'Mostafa H. Abd-El-Barr', 'R.J. Bolton']

Current-mode CMOS multiple-valued logic function realization using a direct cover algorithm

For a simple finite graph G let C"o(G) and C"e(G) denote the set of odd cycle lengths and even cycle lengths in a graph G, respectively. We will show that the chromatic number @g(G) of G satisfies: @g(G)=< min{2r+2,2s+3}=

['Peter Mihók', 'Ingo Schiermeyer']

Cycle lengths and chromatic number of graphs

Acoustic imaging is effective in extreme environments to take images without being influenced by optical properties. However, such images tend to deteriorate rapidly because acoustic impedance in air is low. It is thus necessary to restore the image of the object from a deteriorated image so that the object can be recognized in a search. We used a neural network in the previous work as a postprocessor and tried to reconstruct the original object image. However, this method needs to learn the original object image. In this work, we propose combining Constructive Solid Geometry (CSG) with Genetic Programming (GP) as a new technique that does not require learning. To confirm the effectiveness of this technique, we reconstruct the image of an object from a deteriorated image created by applying a 2-dimensional sinc filter to the original image.

['Motoi Yamagiwa', 'Eiji Kikuchi', 'Minoru Uehara', 'Makoto Murakami', 'Masahide Yoneyama']

Reconstruction for Artificial Degraded Image Using Constructive Solid Geometry and Strongly Typed Genetic Programming

Ambulatory Electroencephalograph (AEEG) technology is becoming popular because it facilitates the continuous monitoring of epilepsy patients without interrupting their routine life. As long term monitoring requires low power processing on the device, a low power real time seizure detection algorithm suitable for AEEG devices is proposed herein. The performance of various classifiers was tested and the most effective was found to be the Linear Discriminant Analysis classifier (LDA). The algorithm presented in this paper provides 87.7 (100–70.2)% accuracy with 94.2 (100–78)% sensitivity and 77.9 (100–52.1)% specificity in patient dependent experiments. It provides 76.5 (79.0–73.3)% accuracy with 90.9 (96.2–85.8)% sensitivity and 59.5 (70.9–52.6)% specificity in patient independent experiments. We also suggest how power can be saved at the lost of a small amount of accuracy by applying different techniques. The algorithm was simulated on a DSP processor and on an ASIC and the power estimation results for both implementations are presented. Seizure detection using the presented algorithm is approximately 100% more power efficient than other AEEG processing methods. The implementation using an ASIC can reduce power consumption by 25% relative to the implementation on a DSP processor with reduction of only 1% of accuracy.

['Kunjan Patel', 'Chern-Pin Chua', 'Stephen Fau', 'Chris J. Bleakley']

Low power real-time seizure detection for ambulatory EEG

This paper proposes the optimal shortest path set problem in an undirected graph $$G=(V,E)$$ G = ( V , E ) , in which some vehicles have to go from a source node $$s$$ s to a destination node $$t$$ t . However, at most $$k$$ k edges in the graph may be blocked during the traveling. The goal is to find a minimum collection of paths for the vehicles before they start off to assure the fastest arrival of at least one vehicle, no matter which $$l$$ l $$(0\le l\le k)$$ ( 0 ≤ l ≤ k ) edges are blocked. We consider two scenarios for this problem. In the first scenario with $$k=1$$ k = 1 , we propose the concept of common replacement path and design the Least-Overlap Algorithm to find the common replacement path. Based on this, an algorithm to compute the optimal shortest path set is presented and its time complexity is proved to be $$O(n^2)$$ O ( n 2 ) . In the second scenario with $$k>1$$ k > 1 , we consider the case where the blocked edges are consecutive ones on a shortest path from $$s$$ s to $$t$$ t and the vertices connecting two blocked edges are also blocked (i.e., routes passing through these vertices are not allowed), and an algorithm is presented to compute the optimal shortest path set in this scenario with time complexity $$O(mn+k^2n^2\log n)$$ O ( m n + k 2 n 2 log n ) .

['Huili Zhang', 'Yinfeng Xu', 'Xingang Wen']

Optimal shortest path set problem in undirected graphs

Are RESTful APIs Well-Designed? Detection of their Linguistic (Anti)Patterns

['Francis Palma', 'Javier Gonzalez-Huerta', 'Naouel Moha', 'Yann-Gaël Guéhéneuc', 'Guy Tremblay']

Are RESTful APIs Well-Designed? Detection of their Linguistic (Anti)Patterns

P2P communication paradigm is a successful solution to the problem of resources sharing as shown by the numerous real overlay networks present on Internet. One of the issue of P2P networks is how a resource shared by a peer can be made known to the other peers or, in other words, how to advertise a resource on the network. In this paper we propose an advertising method for PROSA, a P2P architecture inspired by social relationships. In the paper we show that the introduction of our resources advertising method improves PROSA performance with a low overhead.

['Vincenza Carchiolo', 'Antonio Lima', 'Giuseppe Mangioni']

Resource advertising in PROSA P2P network

On the Kipnis-Shamir Method Solving the MinRank Problem.

['Xin Jiang', 'Lei Hu', 'Jintai Ding', 'Siwei Sun']

On the Kipnis-Shamir Method Solving the MinRank Problem.

Measuring the quality of a clustering algorithm has shown to be as important as the algorithm itself. It is a crucial part of choosing the clustering algorithm that performs best for an input data. Streaming input data have many features that make them much more challenging than static ones. They are endless, varying and emerging with high speeds. This raised new challenges for the clustering algorithms as well as for their evaluation measures. Up till now, external evaluation measures were exclusively used for validating stream clustering algorithms. While external validation requires a ground truth which is not provided in most applications, particularly in the streaming case, internal clustering validation is efficient and realistic. In this article, we analyze the properties and performances of eleven internal clustering measures. In particular, we apply these measures to carefully synthesized stream scenarios to reveal how they react to clusterings on evolving data streams using both k-means-based and density-based clustering algorithms. A series of experimental results show that different from the case with static data, the Calinski-Harabasz index performs the best in coping with common aspects and errors of stream clustering for k-means-based algorithms, while the revised validity index performs the best for density-based ones.

['Marwan Hassani', 'Thomas Seidl']

Using internal evaluation measures to validate the quality of diverse stream clustering algorithms

We propose a new router architecture that supports wormhole switching and circuit switching concurrently. This architecture has been designed to take advantage of temporal communication locality. This can be done by establishing a circuit between nodes that are going to communicate frequently. Messages using those circuits face no contention. By combining circuit switching, pre-established physical circuits and wave pipelining across channels and switches, it is possible to increase network bandwidth considerably, also reducing latency for communications that use pre-established physical circuits. This router architecture also allows to reduce the overhead of the software messaging layer in multicomputers by offering a better hardware support. Preliminary performance evaluation results show a drastic reduction in latency and increment in throughput when messages are long enough, even if circuits are established for a single transmission and locality is not exploited.

['José Duato', 'Pedro López', 'Federico Silla', 'Sudhakar Yalamanchili']

A high performance router architecture for interconnection networks

Diffusion-derived parameters find application in characterizing pathological and developmental changes in living tissues. Robust estimation of these parameters is important because they are used for medical diagnosis. An optimal gradient encoding scheme (GES) is one that minimizes the variance of the estimated diffusion parameters. This paper proposes a method for optimal GES design for two diffusion models: high-order diffusion tensor (HODT) imaging and diffusion kurtosis imaging (DKI). In both cases, the optimal GES design problem is formulated as a D-optimal (minimum determinant) experiment design problem. Then, using convex relaxation, it is reformulated as a semidefinite programming problem. Solving these problems we show that: 1) there exists a D-optimal solution for DKI that is simultaneously D-optimal for second- and fourth-order diffusion tensor imaging (DTI); 2) the traditionally used icosahedral scheme is approximately D-optimal for DTI and DKI; 3) the proposed D-optimal design is rotation invariant; 4) the proposed method can be used to compute the optimal design ( $b$ -values and directions) for an arbitrary number of measurements and shells; and 5) using the proposed method one can obtain uniform distribution of gradient encoding directions for a typical number of measurements. Importantly, these theoretical findings provide the first mathematical proof of the optimality of uniformly distributed GESs for DKI and HODT imaging. The utility of the proposed method is further supported by the evaluation results and comparisons with with existing methods.

['Mohammad Alipoor', 'Irene Y.H. Gu', 'Stephan E. Maier', 'Göran Starck', 'Andrew Mehnert', 'Fredrik Kahl']

Optimal Gradient Encoding Schemes for Diffusion Tensor and Kurtosis Imaging

Asperger's Syndrome (AS) is an autistic spectrum disorder characterised by normal to high IQ but with marked impairment in social skills. Successful social skills training appears to be best achieved either in situ or in role-play situations where users can explore different outcomes resulting from their social behaviour. Single user virtual environments (SVEs) provide an opportunity for users with AS to learn social interaction skills in a safe environment which they can visit as many times as they like.The use of game-like tasks can provide an incentive and can also be used to guide the user through progressive learning stages. Collaborative virtual environments (CVEs) allow several users to interact simultaneously within the virtual environment, each taking different perspectives or role-play characters. Within the AS interactive project a series of SVEs and CVEs have been developed in collaboration with users and professional groups with an overall aim of supporting social skills learning. Initial eva...

['Sue Cobb', 'Luke Beardon', 'Richard M. Eastgate', 'Tony Glover', 'Steven Kerr', 'Helen Neale', 'Sarah J. Parsons', 'Steve Benford', 'Eileen Hopkins', 'Peter Mitchell', 'Gail Reynard', 'John R. Wilson']

Applied virtual environments to support learning of social interaction skills in users with Asperger's Syndrome

Multilevel DRAM technology may become a cost effective way to increase semiconductor memory storage density. The authors develop an MLDRAM fault model using both manual analysis and analog simulation. They also propose several alternative testing strategies and possible design-for-testability enhancements.

['Michael Redeker', 'Bruce F. Cockburn', 'Duncan G. Elliott']

Fault models and tests for a 2-bit-per-cell MLDRAM

The paper presents a new steganographic method called RSTEG (retransmission steganography), which is intended for a broad class of protocols that utilises retransmission mechanisms. The main innovation of RSTEG is to not acknowledge a successfully received packet in order to intentionally invoke retransmission. The retransmitted packet carries a steganogram instead of user data in the payload field. RSTEG is presented in the broad context of network steganography, and the utilisation of RSTEG for TCP (transmission control protocol) retransmission mechanisms is described in detail. Simulation results are also presented with the main aim of measuring and comparing the steganographic bandwidth of the proposed method for different TCP retransmission mechanisms, as well as to determine the influence of RSTEG on the network retransmission level.

['Wojciech Mazurczyk', 'Milosz Smolarczyk', 'Krzysztof Szczypiorski']

Retransmission steganography and its detection

DESIGN OF A WEB-BASED INTERFACE FOR IMAGE RETRIEVAL SYSTEMS

['Liam M. Mayron', 'Oge Marques']

DESIGN OF A WEB-BASED INTERFACE FOR IMAGE RETRIEVAL SYSTEMS

It is well known that a negative feedback interconnection of passive systems is passive. However, the extension of this fundamental property to the case when there are time delays in communication, remains largely unaddressed. In this paper we demonstrate that a negative feedback interconnection of output strictly passive systems, under appropriate assumptions, is passive for non-increasing time delays and may loose passivity for increasing time delays. Passivity can be retained by inserting time-varying gains in the communication path, provided a bound on the maximum rate of change of delay is known. If the dynamical systems are passive, we appeal to the results in bilateral teleoperation, to recover passivity of the feedback interconnection.We show that by transforming the two systems into their scattering representation, transmitting the scattering variables as the new outputs, and using time-varying gains in the communication path, passivity of the feedback interconnection can be guaranteed independent of the time-varying delays. Finally we discuss the applicability of the proposed results for networked control of nonlinear mechanical systems.

['Nikhil Chopra']

Passivity results for interconnected systems with time delay

In recent years, importance on software security has been recognized. Along with the trend, to foster software engineers who possess software security technologies is expressed. The authors have been tackling software engineering education, and have lots of artifacts as the outcomes of the education. The authors propose a learning process that utilizes these artifacts as input for learning of software security and the learners create artifacts for secure software referring to various types of guidelines (methods for secure software development, patterns, standards, and so on). The authors also propose a learning environment to support the process, which adopts a knowledge management approach. The environment enables to store the artifacts, guidelines and rationale, and learners to associate relationships among them.

['Atsuo Hazeyama', 'Hiroto Shimizu']

A Learning Environment for Software Security Education

This paper presents HEALER, a software agent that recommends sequential intervention plans for use by homeless shelters, who organize these interventions to raise awareness about HIV among homeless youth. HEALER's sequential plans (built using knowledge of social networks of homeless youth) choose intervention participants strategically to maximize influence spread, while reasoning about uncertainties in the network. While previous work presents influence maximizing techniques to choose intervention participants, they do not address three real-world issues: (i) they completely fail to scale up to real-world sizes; (ii) they do not handle deviations in execution of intervention plans; (iii) constructing real-world social networks is an expensive process. HEALER handles these issues via four major contributions: (i) HEALER casts this influence maximization problem as a POMDP and solves it using a novel planner which scales up to previously unsolvable real-world sizes; (ii) HEALER allows shelter officials to modify its recommendations, and updates its future plans in a deviation-tolerant manner; (iii) HEALER constructs social networks of homeless youth at low cost, using a Facebook application. Finally, (iv) we show hardness results for the problem that HEALER solves. HEALER will be deployed in the real world in early Spring 2016 and is currently undergoing testing at a homeless shelter.

['Amulya Yadav', 'Hau Chan', 'Albert Xin Jiang', 'Haifeng Xu', 'Eric Rice', 'Milind Tambe']

Using Social Networks to Aid Homeless Shelters: Dynamic Influence Maximization under Uncertainty

One of issue in generative approach for visual tracking is relates to computation time. It is because generative approach uses particle filter for modeling the motion and as a method to predict the state in the current frame. The system will be more accurate but slower computation if many particles are used. Recently, the combination between particle filter and sparse model is proposed to handle appearance variations and occlusion in visual tracking. Unfortunately, the issue about computation time still remains. This paper presents fast method for sparse generative approach in visual tracking. In this method, l1 minimization is used to calculate sparse coefficient vector for each candidate sample. Then, the maximum weighted is selected to represent the result. Based on simulations, our proposed method demonstrate good result in area under curve parameter and achieve four times faster than other methods with only use fifty particles.

['Suryo Adhi Wibowo', 'Hansoo Lee', 'Eun Kyeong Kim', 'Sungshin Kim']

Fast Generative Approach Based on Sparse Representation for Visual Tracking

The task of reconstructing a matrix given a sample of observed entries is known as the matrix completion problem. It arises in a wide range of problems, including recommender systems, collaborative filtering, dimensionality reduction, image processing, quantum physics or multi-class classification to name a few. Most works have focused on recovering an unknown real-valued low-rank matrix from randomly sub-sampling its entries. Here, we investigate the case where the observations take a finite number of values, corresponding for examples to ratings in recommender systems or labels in multi-class classification. We also consider a general sampling scheme (not necessarily uniform) over the matrix entries. The performance of a nuclear-norm penalized estimator is analyzed theoretically. More precisely, we derive bounds for the Kullback-Leibler divergence between the true and estimated distributions. In practice, we have also proposed an efficient algorithm based on lifted coordinate gradient descent in order to tackle potentially high dimensional settings.

['Jean Lafond', 'Olga Klopp', 'Éric Moulines', 'Jospeh Salmon']

Probabilistic low-rank matrix completion on finite alphabets

This paper proposes a methodology for reconstructing the possible transition firing sequences in a given Petri net based on asynchronous observations of token changes at different places of the Petri net. The observed sequences of token changes are provided by local sensors and are asynchronous, i.e., they only contain partial information about the ordering of the token changes that occur due to the firing of transitions. The task of a centralized observer is to optimally combine this information and reconstruct all transition firing sequences that are consistent with the structure of the Petri net. More specifically, given the observed sequences of token changes (for different sets of places in the net), the paper develops an algorithm that is able to reconstruct all firing sequences that are consistent with the asynchronous observations and the structure of the given Petri net. Since Petri nets are a powerful tool to model, analyze, and control large-scale dynamic systems, the proposed method is useful for event reconstruction and fault monitoring based on asynchronous observations.

['Lingxi Li', 'Christoforos N. Hadjicostis']

Reconstruction of Transition Firing Sequences Based on Asynchronous Observations of Place Token Changes

Users are finding themselves interacting with increasingly complex software systems and expanding information resources. However many of these systems have little to no awareness of the personally-understood user context which expresses why they are being used. In this paper we propose a framework for modelling and proactively retrieving previously accessed and created information objects and resources that are within the context of a user's current situation. We first consider theories of context to understand the discrete aspects of context that may delineate a user's composite situations. With this we develop a framework for modelling user interaction in context along with a re-configurable algorithm for making personal recommendations for desired information objects based upon the environmental, content-based and task sequence contextual similarity of the current situation to past situations. To measure the effectiveness of our approach we use a two week activity log from four real users in a preliminary lab-based evaluation methodology. Initial results suggest the framework as a static personal recommendation algorithm is effective to varying degrees during periods of interaction for users of various characteristics.#R##N##R##N#Categories and Subject Descriptors: H.3.3 [Information Storage and Retrieval]: Information Search and Retrieval

['Stewart Whiting', 'Joemon M. Jose']

Context modelling for situation-sensitive recommendations

The increase of machine-to-machine (M2M) communications over cellular networks imposes new requirements and challenges that current networks have to handle with. Many M2M UEs (User Equipment) may send small infrequent data, which suppose a challenge for cellular networks not optimized for such traffic, where signaling load could increase significantly and cause congestion over the network. This paper evaluates current proposals to manage small transmissions over the Long Term Evolution (LTE) cellular network. We also propose a new Random Access-based Small IP packet Transmission (RASIPT) procedure for M2M UEs small data transmissions. Its main feature is data transfer without establishment of Radio Resource Control (RRC) connection to reduce signaling overhead. In our design, we assume a Software Defined Networking-based architecture for 5G system. When compared with current LTE scheme, our procedure reduces significantly the signaling load generated by M2M UEs small transmissions.

['Pilar Andres-Maldonado', 'Pablo Ameigeiras', 'Jonathan Prados-Garzon', 'Juan J. Ramos-Munoz', 'Juan M. Lopez-Soler']

Reduced M2M signaling communications in 3GPP LTE and future 5G cellular networks

Automatic Impact Analysis of Software Architecture Migration on Model Driven Software Development.

['Joseba Andoni Agirre', 'Leire Etxeberria', 'Goiuria Sagardui']

Automatic Impact Analysis of Software Architecture Migration on Model Driven Software Development.

Presents methods and experiments of adaptive posture control for a four legged walking machine. Starting from the analysis of the implemented movement behaviour of BISAM we identify adequate tasks for adaptive control components and present adaptive posture control mechanisms for statically stable and dynamically stable movements. The reflex-based posture control is implemented via fuzzy control and reinforcement learning. The integration of the posture control in the control architecture is also described.

['J. Albiez', 'W. Ilg', 'Tobias Luksch', 'Karsten Berns', 'Rüdiger Dillmann']

Learning a reactive posture control on the four-legged walking machine BISAM

Abstract#R##N##R##N#An efficient and systematic methodology for the kinematic analysis of geared robot manipulators (GRMs) with a jointed unit is presented. It is shown that, by decomposing mechanical transmission lines of a GRM into serially connected jointed and disjointed units, kinematic relation between local inputs and local outputs of admissible jointed units can be systematically formulated. Accordingly, angular displacements of input links with respect to their associated primary links can be symbolically expressed in terms of joint angles by a unit-by-unit evaluation procedure. This unit-by-unit evaluation procedure provides better kinematic insights into how input torques are transmitted to various joints. It is also shown that an actuator in a GRM with a jointed unit can drive nonconsecutive joints by proper design of its gear train. A 3 degrees of freedom GRM with a jointed unit is used as an illustrative example. © 2001 John Wiley & Sons, Inc.

['Dar-Zen Chen', 'Yu-Chu Huang']

Geared robot manipulators with a jointed unit: Kinematic analysis and its application

Grid computing paradigm can be extended to include the sharing of sensor resources in sensor network. Sensor enabled grid may combine real time data about physical environment with vast computational resources derived from the grid architecture. One of the major challenges in the design of sensor enabled grid is how to efficiently schedule sensor resource to user jobs across the collection of sensor resources in a sensor grid. The paper studies optimal sensor resources allocation in sensor enabled grid computing environment. The paper presents an efficient mechanism to assign sensor resources to appropriate sensor grid users on the basis of negotiation results among participants. We model sensor allocation problem by introducing the sensor utility function. The goal is to find a sensor resource allocation that maximises the total profit. The paper proposes a distributed optimal sensor resource allocation algorithm. The performance evaluation of proposed algorithm is evaluated and compared with other resource allocation algorithm for sensor grid. The paper also gives the application example of proposed approach.

['Chunlin Li', 'Layuan Li']

An efficient approach for integration of sensor resources into the grid

Rapidly changing technology and business needs in the dynamic telecommunications field demands that Motorola employ a best-in-class and yet practical education and training program so that employees can work most effectively. This paper is an experience report that chronicles one of a number of Motorola training approaches: short course development (SCD) designed to meet software development organization training needs. Short courses present considerable challenges because they usually are developed by individuals under time pressures from regular work, and who frequently possess limited professional skills in course design and adult education philosophies. Lessons learned from SCD will help educators and internal training specialists improve this important aspect of a corporate training program.

['Craig Smith']

Achieving organizational training objectives with short course development

The traditional color-based mean shift tracking algorithm is unable to accurately track the object. To address the problems, this paper presents an improved tracking algorithm. The improved tracker integrates the color and motion cues which characterize the appearance and motion information of object respectively. During the tracking process, this integration strategy can dynamically adjust the weight of each visual cue according to their reliability, thus these two visual cues can complement each other and make for more precise target localization. The experimental results demonstrate that the proposed tracking algorithm improves the tracking performance of the traditional mean shift tracker in complicated real scenarios.

['Jiaqing Ma', 'Chongzhao Han', 'Yi Yang']

Visual tracking based on adaptive multi-cue integration

Neuron-Network Level Problem Decomposition Method for Cooperative Coevolution of Recurrent Networks for Time Series Prediction

['Ravneil Nand', 'Emmenual Reddy', 'Mohammed Naseem']

Neuron-Network Level Problem Decomposition Method for Cooperative Coevolution of Recurrent Networks for Time Series Prediction

On December 12, 2006, both the European Remote Sensing Satellite 2 and Environmental Satellite recorded a high-magnitude flood event on the River Dee in Wales (U.K.) only 28 min apart. This unique opportunity enables the creation of a very rare but extremely useful observed data set for flood inundation studies. For flood management purposes, hydrodynamic models are often run after an event but with field data gauged during the event to approximate both flood area and depth. As an adequate a priori definition of model parameters is difficult, they tend to be run with multiple parameter sets to generate a likelihood of inundation map. However, as field observations of events are often very scarce, these output maps cannot be validated with field-observed probabilities. This paper illustrates how this unique set of spaceborne radar images can be used in combination with five widely used image processing techniques to generate an event-specific inundation map that expresses a degree of belief that a given pixel is possibly flooded. It is expected that the value of this multialgorithm ensemble-based map opens up new ways to evaluate the performance of hydrodynamic models, as it contains information which has, to the authors' knowledge, not previously been available.

['G. Schumann', 'G. Di Baldassarre', 'Paul D Bates']

The Utility of Spaceborne Radar to Render Flood Inundation Maps Based on Multialgorithm Ensembles

Daily Activity Monitoring for Prevention of Pressure Ulcers in Long-Term Wheelchair Users

['Diego E. Arias', 'Esteban J. Pino', 'Pablo Aqueveque', 'Dorothy Curtis']

Daily Activity Monitoring for Prevention of Pressure Ulcers in Long-Term Wheelchair Users

This paper analyzes the interdependence between the I ub link characteristics and the HSDPA air interface performance using analytical and simulation techniques. The impact of the Node-B scheduling mechanisms are also investigated in this paper. A Markov chain based analytical model and a simulation model is used to obtain HSDPA air interface performance results.

['Xinzhi Yan', 'Jamil Y. Khan', 'Brendan Jones']

Study of Interdependency Between the HSDPA Air Interface and the Radio Access Network

We consider simplicial polytopes, and more general simplicial complexes, without missing faces above a fixed dimension. Sharp analogues of McMullen’s generalized lower bounds, and of Barnette’s lower bounds, are conjectured for these families of complexes. Partial results on these conjectures are presented.

['Eran Nevo']

Remarks on Missing Faces and Generalized Lower Bounds on Face Numbers

We define a new reduced model to represent coloured images. We propose to use two components for a full definition of a colour instead of three. To that end we take advantage of the geometrical structure of the HCL conical colour space and approximate its circular base by a spiral. We thus write chroma as a function of hue. The resulting spiral is therefore defined by one parameter only. This parameter is then combined with luminance in order to represent all the colour information. Our experiments show that our proposed model ensures an accurate representation of coloured digital images. Furthermore, it preserves the perceptual properties of the original HCL representation.

['Frederic Garcia', 'Djamila Aouada', 'Bruno Mirbach', 'Björn E. Ottersten']

Spiral colour model: Reduction from 3-D to 2-D

In this paper, we study the behavior of voice over IP (VoIP) traffic over IEEE 802.11 wireless networks. Specifically, we propose a QoS provisioning mechanism for VoIP traffic, and suggest a practical solution to configuring the 802.lie enhanced distributed control access (EDCA) parameter sets for different types of traffic. With our mechanism, the EDCA parameter sets can be easily configured via software interface in off-the-shelf WiFi phone products and it is not required to modify the operations of access points or 802.11 MAC layer protocols. The performance of our mechanism is evaluated via ns-2 simulations and via laboratory experiments over Quanta's 02 dual-mode handsets. The results show our mechanism can provide effective and efficient QoS provisioning for VoIP traffic over IEEE 802.11 WLANs.

['Jeng Farn Lee', 'Jie-Ming Chen', 'Wanjiun Liao', 'Hsiu-Hui Lee', 'Meng Chang Chen']

A Practical Cross-layer QoS Mechanism for Voice over IP in IEEE 802.11e WLANs

We consider the delivery of reliable and streaming services using application-level multicast (ALM) by means of UDP, where packet loss has to be recovered via retransmission in a timely manner in order to offer high level of service. Since packets may be lost due to congestion, tree-reconfiguration or node failure, the traditional "vertical" recovery, whereby upstream nodes retransmit the lost packet is no longer effective. We therefore propose and investigate lateral error recovery (LER). In LER, hosts are divided into a number of planes, each of which forms an independent ALM tree. Since the correlation of error among the planes is likely to be low, a node can effectively recover its error "laterally" from nearby nodes in other planes. We employ the technique of global network positioning (GNP) to map the hosts into a coordinate space and identify a set of close neighbors for error recovery by constructing a Voronoi diagram for each plane. We present centralized and distributed algorithm on how to construct the Voronoi diagrams. Using Internet-like topologies, we show via simulations that our system achieves low overheads in terms of relative delay penalty and physical link stress. For reliable service, lateral recovery greatly reduces the average recovery time as compared with vertical recovery schemes. For streaming applications, LER achieves much lower residual loss rate under a certain deadline constraint.

['K.-F.S. Wong', 'S.-H.G. Chan', 'Wan-Ching Wong', 'Qian Zhang', 'Wenwu Zhu', 'Ya-Qin Zhang']

Lateral error recovery for application-level multicast

We consider a class of discrete systems, with specifications stated in a certain modal temporal language (chosen for simplicity). We show that if the regulator can in some way guarantee satisfaction of a specification, then it can do so acting as a deterministic finite automaton, and we can effectively find an appropriate automaton, or determine that there is none. Our result is not really new. It (and similar results for more expressive languages) can be obtained easily from a result of Landweber and Buchi on regular games, together with the fact that our language gives rise to games of this sort (see the excellent surveys [T] and [E]). We use a result of Gurevich and Harrington [G-H] to show the existence of appropriate automata. The actual construction is explicit. The set of states is determined through elementary considerations of which partial records might be useful to the regulator.

['Julia F. Knight', 'Brian Luense']

Control Theory, Modal Logic and Games

Side Channel Attacks (SCA) have proven to be a practical threat to the security of embedded systems, exploiting the information leakage coming from unintended channels concerning an implementation of a cryptographic primitive. Given the large variety of embedded platforms, and the ubiquity of the need for secure cryptographic implementations, a systematic and automated approach to deploy SCA countermeasures at design time is strongly needed. In this paper, we provide an overview of recent compiler-based techniques to protect software implementations against SCA, making them amenable to automated application in the development of secure-by-design systems.

['Giovanni Agosta', 'Alessandro Barenghi', 'Gerardo Pelosi']

Automated instantiation of side-channel attacks countermeasures for software cipher implementations

Self-organized Multi-agent System for Service Management in the Next Generation Networks

['Mario Kusek', 'Gordan Jezic']

Self-organized Multi-agent System for Service Management in the Next Generation Networks

In this paper we address the question of defining and com-#N#puting Hausdorff distances between distributions in a general sense. We#N#exhibit some links between Prokhorov-Levy distances and dilation-based#N#distances. In particular, mathematical morphology provides an elegant#N#way to deal with periodic distributions. The case of possibility distribu-#N#tions is addressed using fuzzy mathematical morphology. As an illustra-#N#tion, the proposed approaches are applied to the comparison of spatial#N#relations between objects in an image or a video sequence, when these#N#relations are represented as distributions.

['Isabelle Bloch', 'Jamal Atif']

Hausdorff Distances Between Distributions Using Optimal Transport and Mathematical Morphology

In modern VLSI manufacturing processes, dummy fills are widely used to adjust local metal density in order to improve layout uniformity and yield optimization. However, the introduction of a large amount of dummy features also affects wire electrical properties. In this paper, we propose the first Coupling constrained Dummy Fill (CDF) analysis algorithm which identifies feasible locations for dummy fills such that the fill induced coupling capacitance can be bounded within the given coupling threshold of each wire segment. The algorithm also makes efforts to maximize ground dummy fills, which are more robust and predictable. The output of the algorithm can be treated as the upper bound for dummy fill insertion, and it can be easily adopted in density models to guide dummy fill insertion without disturbing the existing design.

['Hua Xiang', 'Liang Deng', 'Ruchir Puri', 'Kai-Yuan Chao', 'Martin D. F. Wong']

Dummy fill density analysis with coupling constraints

High dimensionality of text can be a deterrent in applying complex learners such as Support Vector Machines to the task of text classification. Feature clustering is a powerful alternative to feature selection for reducing the dimensionality of text data. In this paper we propose a new information-theoretic divisive algorithm for feature/word clustering and apply it to text classification. Existing techniques for such "distributional clustering" of words are agglomerative in nature and result in (i) sub-optimal word clusters and (ii) high computational cost. In order to explicitly capture the optimality of word clusters in an information theoretic framework, we first derive a global criterion for feature clustering. We then present a fast, divisive algorithm that monotonically decreases this objective function value. We show that our algorithm minimizes the "within-cluster Jensen-Shannon divergence" while simultaneously maximizing the "between-cluster Jensen-Shannon divergence". In comparison to the previously proposed agglomerative strategies our divisive algorithm is much faster and achieves comparable or higher classification accuracies. We further show that feature clustering is an effective technique for building smaller class models in hierarchical classification. We present detailed experimental results using Naive Bayes and Support Vector Machines on the 20Newsgroups data set and a 3-level hierarchy of HTML documents collected from the Open Directory project (www.dmoz.org).

['Inderjit S. Dhillon', 'Subramanyam Mallela', 'Rahul Kumar']

A divisive information theoretic feature clustering algorithm for text classification

The problem of determining invariance kernels for planar single-input nonlinear systems is considered. If K is a closed set, its invariance kernel is the largest subset of K with the property of being positively invariant for arbitrary measurable input signals. It is shown that the boundary of the invariance kernel is a concatenation of solutions of two so-called extremal vector fields. Moreover, only the solutions through a finite number of special points are of interest. This result makes it possible to devise an algorithm which determines the invariance kernel of a simply connected set in a finite number of steps.

['Manfredi Maggiore', 'Barry Rawn', 'Peter W. Lehn']

Invariance kernels of single-input planar nonlinear systems

The existing search engines sometimes give unsatisfactory search result for lack of any categorization. If there is some means to know the preference of user about the search result and rank pages accordingly, the result will be more useful and accurate to the user. In the present paper a web page ranking algorithm is proposed based onsyntactic classification of web pages. The proposed approach mainly consists of three steps: select some properties of web pages based on user's demand, measure them, and give different weightage to each property during ranking for different types of pages. The existence of syntactic classification is supported by running fuzzy c-means algorithm and neural network classifier on a set of web pages. It has been demonstrated that, for different types of pages, the same query string has produced different page ranking.

['Debajyoti Mukhopadhyay', 'Pradipta Biswas']

FlexiRank: an algorithm offering flexibility and accuracy for ranking the web pages

In grid computing environment the workload can be submitted by various grid users. Allocating a load to the resources from various grid users is a challenging task in grid scheduling process. So we need a better resource allocation framework to schedule the tasks from various sources to the dynamic resources. This paper introduces a new divisible load scheduling framework to map the task to the distributed resources in grid computing environment. We have developed a mathematical model to allocate tasks to resource when the task is submitted by various grid users sources with the aim of minimising the completion time of scheduling process with satisfying the budget allotted by the grid user based on divisible load theory. This model helps to estimate the resource usage cost of each source under the fluctuation of resource availability and the performance evaluation of three resource homogeneous resources and the link capacity is presented.

['G. Murugesan', 'C. Chellappan']

Multi-source task scheduling in grid computing environment using linear programming

We present an application of Monte-Carlo Tree Search (MCTS) to controlling ghosts in the game of Ms Pac-Man. We approach the problem by performing MCTS on each ghost's tree that represents the game state from the ghost's perspective. Our goal is to create a strong ghost team that is adaptable to a variety of Ms Pac-Man's play styles. This ghost team (ICE gUCT) won the CEC 2011 Ms Pac-Man vs Ghost Team Competition for the ghost side.

['Kien Quang Nguyen', 'Ruck Thawonmas']

Applying Monte-Carlo Tree Search to collaboratively controlling of a Ghost Team in Ms Pac-Man

An Analysis of Authentication for Passive RFID Tags.

['Gregory Stuart Smith', 'Marijke Coetzee']

An Analysis of Authentication for Passive RFID Tags.

In this paper we propose an approach that aims to build an automated task-oriented Arabic dialogue system which is capable to determine the topic of spoken question asked by telecom provider customers. The system is based on an Arabic adapted CMU sphinx ASR. In addition to formal Arabic speech, our implemented Arabic ASR is capable to recognize some Palestinian Arabic dialectal words. The recognized text is used to determine the question category using supervised machine learning techniques in order to take desired action such as routing customer call to the appropriate destination. The best performance of proposed overall system is 76.4% accuracy with random forest classifier provided by Weka toolkit tested on 750 questions recorded by 30 speakers with Palestinian dialect.

['Aziz Qaroush', 'Abualsoud Hanani', 'Bassam Jaber', 'Mohammed Karmi', 'Bashar Qamhiyeh']

Automatic Spoken Customer Query Identification for Arabic Language

Recently, with the advantages of peer tutoring, robot for education usage has been the new trend for new generation leaning technology. Robot is not only a toy, but also your learning partner. We considered integrating speech, position information and 3G cell phone to realize a highly-interactive learning platform.Teachers can design different scene with many stages for English or mathematic. Students send out his command to the robot with motions or speech the robot travels within the scene as an adventure. And the students assist the robot to solve any quizzes it meets If the adventure processes successfully, the robot will interact happily with student otherwise, it will encourage the student to keep trying. The parents or the teacher can observe all these activities with a 3G cell phone to give advises of learning at any time.

['Eric Hsiao-Kuang Wu', 'Yung-Lun Ding', 'Chi-Yun Liu', 'Yi-Kai Chiang']

A Context Aware Interactive Robot for Broadband Wireless Learning

A novel water quality monitoring method named WQMMFCE is proposed based on fuzzy comprehensive evaluation model to solve the issue of high energy consumption caused by centralized approach under the background of water quality monitoring. The weights of all factors which are necessary for fuzzy comprehensive evaluation can be obtained firstly by using the binary expert evaluation. The information needs to transmit is decided according to water quality grade which is quantitatively analyzed directly by using fuzzy comprehensive evaluation rather than transmitting large amount of raw data to the monitoring center. Simulation result shows that the method has a great advantage over the centralized one on energy saving and can prolong the lifetime of the network.

['Jian Shu', 'Ming Hong', 'Linlan Liu', 'Yebin Chen']

A Water Quality Monitoring Method Based on Fuzzy Comprehensive Evaluation in Wireless Sensor Networks

The current mobile network has been developed to a heterogeneous network that is coexistence of different wireless networks such as UMTS (3G), WIFI, WIMAX (4G) and LTE (4G). Since the demand of realtime multimedia services has significantly increased in recent years and Quality of Experience (QoE) becomes more and more important to users, any single wireless network is hardly to maintain good QoE of multimedia service at any time and in anywhere for any users. Hence, in order to achieve the goal, it is necessary to converge different wireless networks to take the advantages of different wireless networks. However, even though IEEE 802.21-Media Independent Handover (MIH) provides a framework for supporting seamless vertical handover (VHO), how to select an appropriate network and when to carry out handover are still the key challenges to maintain QoE of multimedia service. This paper addresses a QoE-driven VHO algorithm based on MIH that aims to maintain multimedia service with acceptable QoE and avoid unnecessary handover in the heterogeneous network. The performance evaluation was carried out to compare with default MIH bandwidth-based VHO algorithm on video service over UMTS and WIFI networks in Network Simulator 2 (NS2). The results showed that the QoE-driven VHO algorithm could maintain better QoE of multimedia service than the bandwidth-based VHO algorithm by considering video content, and initiated VHO immediately when the QoE of multimedia service became unacceptable. Furthermore, Block List (BL) and acceptable QoE policy could avoid unnecessary handover effectively.

['Li Liu', 'Lingfen Sun', 'Emmanuel C. Ifeachor']

A QoE-driven vertical handover algorithm based on media independent handover framework

Antenna selection strategies for multiple-input multiple-output (MIMO) wireless systems is presented. In our scheme, both transmit and receive antenna selection is done at the receiver, significantly reducing feedback information to the transmitter. Row/column probability density function (pdf) is used for antenna selection to reduce computational complexity without performance degradation. Unlike other schemes, we used two different antenna selection algorithms both for high SNR and low SNR regime, achieving additional performance gain in comparison with the single antenna selection algorithm. Simulation results show that our scheme nearly approaches to the optimal closed-loop capacity (known as water-filling capacity).

['In-Soo Hwang', 'Cheolwoo You', 'Yung-soo Kim', 'Vahid Tarokh']

Antenna Selection Strategies for MIMO Systems

An English text steganographic algorithm is presented that can be applied to plain text as information is embedded by modifying the orders of adjacent character pairs within the words. Matrix encoding is applied for higher embedding efficiency, and the algorithm is proposed to be used in online chat for better concealment. Experiments demonstrated the proposed method has favorable imperceptibility and security, as well as desirable capacity.

['Jen-Wen Ding', 'Guan-Wei Wu', 'Der-Jiunn Deng']

Optimal Rate Allocation and Admission Control Policy for P2P On-Demand Streaming Systems

Product line adoption is a key issue in product line development, as the right adoption approach is central to the overall success of product line de velopment. Thus, this is a strongly discussed area of product line engineering. While so far, guidelines and experiences on the best approach to product line adoption have been presented, no detailed quantitative model was provided. In this paper we present a quantitative model of the product line adoption problem. From this model we deduce general guidelines for product line adoption, particularly highlighting the role of the architecture in the cost-effective adoption of a product line.

['Klaus Schmid']

A quantitative model of the value of architecture in product line adoption

This paper presents a new procedure for fitting multiple geometric structures without having a priori knowledge of scale. Our method leverages on Consensus Clustering, a single-term model selection strategy relying on the principle of stability, thereby avoiding the explicit tradeoff between data fidelity i.e., modeling error and model complexity. In particular we tailored this model selection to the estimate of the inlier threshold of T-linkage, a fitting algorithm based on random sampling and preference analysis. A potential clustering is evaluated based on a consensus measure. The crucial inlier scale $$\epsilon $$ is estimated using an interval search. Experiments on synthetic and real data show that this method succeeds in finding the correct scale.

['Luca Magri', 'Andrea Fusiello']

Scale Estimation in Multiple Models Fitting via Consensus Clustering

We consider coded modulation with generalized selection combining (GSC) for bandwidth-efficient-coded modulation over Rayleigh fading channels. Our results show that reception diversity with generalized selection combining can conveniently trade off system complexity versus performance. We provide a number of new results by calculating the cutoff rate, and by deriving analytical upper bounds on symbol-interleaved trellis-coded modulation (TCM) and bit-interleaved-coded modulation (BICM) with GSC. All are verified by simulation. We show that our new bounds on TCM with GSC, which includes maximum ratio combining and selection combining as special cases, are tighter than the previously derived bounds. A new asymptotic analysis on the pairwise error probability, which can be used as a guideline for designing coded modulation over GSC channels, is also given. Finally, we show that BICM with iterative decoding (BICM-ID) can achieve significant coding gain over conventional coded modulation in a multiple-receiving-antenna channel.

['Aik Chindapol', 'James A. Ritcey']

Performance analysis of coded modulation with generalized selection combining in Rayleigh fading

This paper describes a new driving mechanism for a miniature robot hand. In developing miniature robot hands for dexterous manipulation, it is necessary to consider miniaturizing and minimizing. The proposed mechanism uses elastic torsion springs and hinges as joints, and the finger is wire-driven from actuators placed outside the robot hand. First, the driving mechanism of a one joint finger is described, and the mechanism is applied to a five-fingered miniature robot hand. The robot hand is one-half the size of the hand of an adult male, and has a total of eighteen degrees of freedom (DOF). The properties of the robot hand are discussed, and are shown to be an effective mechanism for miniature robot hands.

['Yoichi Ogahara', 'Yusuke Kawato', 'Kenjiro Takemura', 'Takashi Maeno']

A wire-driven miniature five fingered robot hand using elastic elements as joints

A considerable portion of software systems today are adopted in the embedded control domain. Embedded control software deals with controlling a physical system, and as such models of physical characteristics become part of the embedded control software. In current practices, usually general-purpose languages (GPL), such as C/C++ are used for embedded systems development. Although a GPL is suitable for expressing general-purpose computation, it falls short in expressing the models of physical characteristics as desired. This reduces not only the readability of the code but also hampers reuse due to the lack of dedicated abstractions and composition operators. Moreover, domain-specific static and dynamic checks may not be applied effectively. There exist domain-specific modeling languages (DSML) and tools to specify models of physical characteristics. Although they are commonly used for simulation and documentation of physical systems, they are often not used to implement embedded control software. This is due to the fact that these DSMLs are not suitable to express the general-purpose computation and they cannot be easily composed with other software modules that are implemented in GPL. This paper presents a novel approach to combine a DSML to model physical characteristics and a GPL to implement general-purpose computation. The composition filters model is used to compose models specified in the DSML with modules specified in the GPL at the abstraction level of both languages. As such, this approach combines the benefits of using a DSML to model physical characteristics with the freedom of a GPL to implement general-purpose computation. The approach is illustrated using two industrial case studies from the printing systems domain.

['Arjan de Roo', 'Hasan Sözer', 'Mehmet Aksit']

Composing domain-specific physical models with general-purpose software modules in embedded control software

2D discrete cosine transform (DCT) is widely used as the core of digital image and video compression. In this paper, the authors present a novel DCT architecture that allows aggressive voltage scaling by exploiting the fact that not all intermediate computations are equally important in a DCT system to obtain "good" image quality with peak signal to noise ratio (PSNR) > 30 dB. This observation has led us to propose a DCT architecture where the signal paths that are less contributive to PSNR improvement are designed to be longer than the paths that are more contributive to PSNR improvement It should also be noted that robustness with respect to parameter variations and low power operation typically impose contradictory requirements in terms of architecture design. However, the proposed architecture lends itself to aggressive voltage scaling for low-power dissipation even under process parameter variations. Under a scaled supply voltage and/or variations in process parameters, any possible delay errors would only appear from the long paths that are less contributive towards PSNR improvement, providing large improvement in power dissipation with small PSNR degradation. Results show that even under large process variation and supply voltage scaling (0.8V), there is a gradual degradation of image quality with considerable power savings (62.8%) for the proposed architecture when compared to existing implementations in 70 nm process technology

['Nilanjan Banerjee', 'Georgios Karakonstantis', 'Kaushik Roy']

Process variation tolerant low power DCT architecture

Optimization of Pitch Tracking and Quantization

['Oleg Basov', 'Andrey Ronzhin', 'Victor Budkov']

Optimization of Pitch Tracking and Quantization

This paper presents Customer Satisfaction (CS) based resource allocation strategy in orthogonal frequency- division multiplexing (OFDM) wireless system with multimedia traffic. The risk aversion utility functions are analyzed, based on which, the CS utility and the CS resource allocation strategy are proposed. Compared with the Proportional Fairness (PF) utility, the CS utility enables the system to adjust its resource allocation according to both the traffic requirements and the resource situation. Numerical results demonstrate that the CS resource allocation strategy outperforms the PF strategy in both real-time (RT) traffic and best effort (BE) traffic. I. INTRODUCTION Due to the scarce resources and fading channel, the allo- cation and management of resources are crucial in wireless networks. OFDM is a well accepted technology that combats the deficits of fading channel by converting a frequency selec- tive fading channel into several flat fading channels (1). In an OFDM wireless network, different subcarriers can be allocated to different users to provide a flexible multiuser access scheme and to exploit multiuser diversity. In addition, it is believed that supporting multimedia traffic is an indispensable requirement in future-generation wireless networks (2). Hence, it becomes necessary and significant to investigate the resource allocation in OFDM based wireless multimedia system. Traditionally, resource allocation focuses on improving spectral efficiency, which is unfair to those users under bad channel conditions. In contrast, absolute fairness may lead to low bandwidth efficiency. Therefore, an effective tradeoff be- tween efficiency and fairness is desired in radio resource allo- cation (3,4). These issues have been well studied in economics, where utility functions are used to quantify the effectiveness of the usage of certain resources. Similarly, utility theory can be used in communication networks to evaluate the capability a network owns to satisfy the service requirements of various applications. The introduction of utility theory is a milestone to the research of resource allocation and management. Proportional Fairness (PF) utility is originally proposed by Frank Kelly in the context of rate control in wired net- works (3). Maximizing the logarithmic utility function U = PK i=1 ln(Ti) ,w hereTi is the throughput of user i and K is the total number of users in the system, it yields a good balance between system efficiency and fairness. Based on Kelly's theory, many in-depth researches were carried out in the past decade (4-7). However, based on the survey on classical utility theory, we find out another utility function, which is more suitable for resource allocation, especially in multimedia traffic condition. That is negative exponential utility function, which is called Customer Satisfaction (CS) utility in this paper. Compared with the PF utility, it is proved that the CS utility achieves higher resource efficiency under the condition of relative inadequate resources, while achieves better fairness under the condition of relative adequate resources. The turning point of efficiency and fairness is figured out, which is determined by Customer Satisfaction factor (CSF). Based on the CS utility, the CS resource allocation strategy, namely CS strategy, is carried out. Through flexible design of the CSF according to different service requirements, the CS strategy performs better than the PF strategy in both real time (RT) and best effort (BE) traffic. The rest of this paper is organized as follows. Section II gives the concept of CS. Based on Pratt's research on risk aversion in 1964 (8), we compare the constant risk aversion and decreasing risk aversion utility functions, and figure out the meaning of risk aversion in resource allocation in Sections III. Section IV proposes the CS utility, and describes the CS resource allocation strategy. Then we compare the CS strategy with the PF strategy in both real time (RT) and best effort (BF) traffic in Section V. Finally, Section VI concludes this paper.

['Zhijie Hao', 'Xiaodong Xu', 'Linjun Li', 'Xiaofeng Tao', 'Yinghong Zhao', 'Zhongqi Zhang', 'Qiang Wang']

Customer Satisfaction Based Resource Allocation for OFDM System with Multimedia Traffic

Semi-structured processes are business workflows, where the execution of the workflow is not completely controlled by a workflow engine, i.e., an implementation of a formal workflow model. Examples are workflows where actors potentially have interaction with customers reporting the result of the interaction in a process aware information system. Building a performance model for resource management in these processes is difficult since the required information is only partially recorded. In this paper we propose a systematic approach for the creation of an event log that is suitable for available process mining tools. This event log is created by an incrementally cleansing of data. The proposed approach is evaluated in an experiment.

['Andreas Wombacher', 'Maria-Eugenia lacob']

Start time and duration distribution estimation in semi-structured processes

Wireless Sensor and Actuator Networks (WSANs) are highly heterogeneous regarding hardware, software, and application requirements. Developing WSAN applications is a hard task, as it requires domain and network knowledge and there is a lack of methodologies, architectures, and patterns to help software developers with such task. Moreover, non-functional requirements play an essential role to ensure the application and network performance, and must be taken into account from the early stages of application development. We propose a ModelDriven Architecture framework to develop WSAN applications that enables developers to express functional and non-functional requirements. The framework encompasses a generic middleware meta-model including: (i) features shared among different WSAN middleware, (ii) meta-model of a target middleware including features of a specific WSAN middleware, and (iii) model transformations. We evaluate our approach by verifying the support to specify non-functional requirements and the automatic code generation of a middleware tailored to the requirements ofa target application.

['Taniro Rodrigues', 'Thaís Vasconcelos Batista', 'Flávia Coimbra Delicato', 'Paulo F. Pires']

Architecture-Driven Development Approach for WSAN Applications

The missing feedback loop is considered the reason for broken Data Cycles on current Linked Open Data ecosystems. Read-Write platforms are proposed, but they are restricted to capture modifications after the data is released as Linked Data. Triggering though a new iteration results in loosing the data consumers' modifications, as a new version of the source data is mapped, overwriting the currently published. We propose a prime solution that interprets the data consumers' feedback to update the mapping rules. This way, data publishers initiate a new iteration of the Data Cycle considering the data consumers' feedback when they map a new version of the published data.

['Anastasia Dimou', 'Miel Vander Sande', 'Tom De Nies', 'Erik Mannens', 'Rik Van de Walle']

RDF mapping rules refinements according to data consumers' feedback

For about the last 10 years, virtual reality and related technologies have become more and more popular, especially in the manufacturing industry. In hundreds of papers and presentations, authors have claimed the usefulness, importance, and success of the technology. We will address to what degree the hype is truth.

['P. Zimmermann', 'Timothy Jaeger', 'J. Krause', 'T. Steinborn', 'M. Sailer', 'Jean Lorisson']

Virtual technologies in the manufacturing industry

Urban land cover mapping has lately attracted a vast amount of attention as it closely relates to a broad scope of scientific and management applications. Late methodological and technological advancements facilitate the development of datasets with improved accuracy. However, thematic resolution of urban land cover has received much less attention so far, a fact that hampers the produced datasets utility. This paper seeks to provide insights towards the improvement of thematic resolution of urban land cover classification. We integrate existing, readily available and with acceptable accuracies datasets from multiple sources, with remote sensing techniques. The study site is Greece and the urban land cover is classified nationwide into five classes, using the RandomForests algorithm. Results allowed us to quantify, for the first time with a good accuracy, the proportion that is occupied by each different urban land cover class. The total area covered by urban land cover is 2280 km2 (1.76% of total terrestrial area), the dominant class is discontinuous dense urban fabric (50.71% of urban land cover) and the least occurring class is discontinuous very low density urban fabric (2.06% of urban land cover).

['Dimitrios Gounaridis', 'Sotirios Koukoulas']

Urban land cover thematic disaggregation, employing datasets from multiple sources and RandomForests modeling

Development of simple UV detection system using CdTe quantum dots QDs as primary detector with scintillating property on exposure to UV rays is reported. CdTe, CdTe/ZnS and CdTe/CdS QDs were synthesized in aqueous phase using mercaptosuccinic acid MSA as a capping agent and studied for its properties like crystallite size, band gap energy, fluorescence emission intensity and uniformity in size distribution. The prepared QDs were exposed to different radiations such as infrared IR, ultraviolet UV and X-rays. The fluorescent emission was recorded by an optoelectronic circuit in terms of electrical signal. The result of this study shows that CdTe/ZnS QDs is better suited for the detection and measurement of UV rays. Hence these QDs could be used as a sensing element while fabricating nanosensor for UV detection.

['A. Anbarasi', 'R. Kalpana', 'A. Arivarasan', 'R. Jayavel', 'B. Venkataraman']

Detection of UV Rays Using CdTe Quantum Dots

Towards a Geometrical Model for Polyrepresentation of Information Objects.

['Ingo Frommholz', 'C. J. van Rijsbergen']

Towards a Geometrical Model for Polyrepresentation of Information Objects.

Application of Independent Component Analysis Techniques in Speckle Noise Reduction of Single-Shot Retinal OCT Images

['Ahmadreza Baghaie', "Roshan M. D'Souza", 'Z. Yu']

Application of Independent Component Analysis Techniques in Speckle Noise Reduction of Single-Shot Retinal OCT Images

This paper presents a framework for the skeleton-driven animation of elastically deformable characters. A character is embedded in a coarse volumetric control lattice, which provides the structure needed to apply the finite element method. To incorporate skeletal controls, we introduce line constraints along the bones of simple skeletons. The bones are made to coincide with edges of the control lattice, which enables us to apply the constraints efficiently using algebraic methods. To accelerate computation, we associate regions of the volumetric mesh with particular bones and perform locally linearized simulations, which are blended at each time step. We define a hierarchical basis on the control lattice, so for detailed interactions the simulation can adapt the level of detail. We demonstrate the ability to animate complex models using simple skeletons and coarse volumetric meshes in a manner that simulates secondary motions at interactive rates.

['Steve Capell', 'Seth Green', 'Brian Curless', 'Tom Duchamp', 'Zoran Popović']

Interactive skeleton-driven dynamic deformations

This paper presents an architectural framework of a system utilising mobile technologies to enable continuous, wireless, electrocardiogram (ECG) monitoring of cardiac patients. The proposed system has the potential to improve patients' quality of life by allowing them to move around freely while undergoing continuous heart monitoring and to reduce healthcare costs associated with prolonged hospitalisation, treatment and monitoring.

['Sweta Sneha', 'Upkar Varshney']

A wireless ECG monitoring system for pervasive healthcare

Accelerated Stochastic Block Coordinate Gradient Descent for Sparsity Constrained Nonconvex Optimization.

['Jinghui Chen', 'Quanquan Gu']

Accelerated Stochastic Block Coordinate Gradient Descent for Sparsity Constrained Nonconvex Optimization.

In this paper, an integrated power system (IPS) based on fuel cell (FC), battery, photovoltaic panels (PV), and two diesel generators is proposed and modeled for an all-electric ship to address a solution for the high pollution resulting from conventional ships. Dual active bridge (DAB) converter and its nonlinear average model which is faster and more suitable for system-level studies has been used as power electronic interface. A decentralized model predictive control (MPC) strategy is also designed to control the modules of the IPS. A hierarchical control method with virtual droop control is proposed to control the power generation of diesel generators and regulate the DC link voltage of the IPS. Moreover, a power management strategy for efficient operation of diesel generators, FC and battery is considered in this study. It is important to note that, the diesel generators considered in this power system make this ship more applicable for longer voyages. The proposed system has been studied in various operational modes considering the battery and load conditions in MATLAB/SIMULINK environment and its validity is shown through the obtained results. Furthermore, the simulation results show good response in a long run which is a sign of its suitability for system-level studies.

['Mohamad Reza Banaei', 'Rana Alizadeh']

Simulation-Based Modeling and Power Management of All-Electric Ships Based on Renewable Energy Generation Using Model Predictive Control Strategy

On two extensions of abstract categorial grammars

['Philippe de Groote', 'Sarah Maarek', 'Ryo Yoshinaka']

On two extensions of abstract categorial grammars

Aiming to develop an efficient ray tracer for a mobile platform, we present an adaptive undersampling method that enhances the rendering speed by effectively replacing expensive ray-tracing operations with cheap interpolation whenever possible. Our method explores both object- and image-space information gathered during ray tracing to detect possibly problematic pixels. Rays are fired only for these pixels. We also present a postcorrection algorithm that minimizes annoying artifacts inevitably caused by undersampling. Our implementation on a mobile GPU demonstrates that this method can speed up the rendering computation significantly, while retaining almost the same visual quality of the rendering.

['Youngwook Kim', 'Woong Seo', 'Yongho Kim', 'Yeongkyu Lim', 'Jae-Ho Nah', 'Insung Ihm']

Adaptive undersampling for efficient mobile ray tracing

Biological networks are dynamic and modular. Identifying dynamic functional modules is key to elucidating biological insight and disease mechanism. In recent years, while most researchers have focused on detecting functional modules from static protein-protein interaction (PPI) networks where the networks are treated as static graphs derived from aggregated data across all available experiments or from a single snapshot at a particular time, temporal nature of context-specific transcriptomic and proteomic data has been recognized by researchers. Meanwhile, the analysis of dynamic networks has been a hot topic in data mining and social networks. Dynamic networks are structures with objects and links between the objects that vary in time. Temporary information in dynamic networks can be used to reveal many important phenomena such as bursts of activities in social networks and evolution of functional modules in protein interaction networks. In this talk, I will address several critical challenges to construct robust, dynamic gene interaction networks, and present our computational approaches to identify disease-relevant functional modules and to track the progression patterns of modules in dynamic biological networks. Significant modules which are correlated to phenotypes of interest can be identified, for example, those functional modules which form and progress across different stages of a cancer. Through identifying these functional modules in the progression process, we are able to detect the critical groups of proteins that are responsible for the transition of different cancer stages. Our approaches can also discover how the strength of each detected modules changes over the entire observation period. I will also demonstrate the application of our approach in a variety of biomedical applications.

['Aidong Zhang']

Trajectory analysis — Linking genomic and proteomic data with disease progression

Synthetic genetic circuits sometimes exhibit unexpected functionality or even fail entirely when implemented in vivo, due to the effects of interactions with the host cell that were not accounted for in the circuit's design. In this paper, we consider the effects that limitations in cellular resources have on the dynamics of a synthetic cellular oscillator. We show that incorporating these effects into a host-aware model of the synthetic oscillator results in significant changes in its dynamics, highlighting the need to take account of host-circuit interactions in mathematical models that are to be used as CAD tools for synthetic circuitry.

['Alexander P. S. Darlington', 'Declan G. Bates']

Host-aware modelling of a synthetic genetic oscillator

In a previous paper by the second author, two Markov chain Monte Carlo perfect sampling algorithms--one called coupling from the past (CFTP) and the other (FMMR) based on rejection sampling--are compared using as a case study the move-to-front (MTF) self-organizing list chain. Here we revisit that case study and, in particular, exploit the dependence of FMMR on the user-chosen initial state. We give a stochastic monotonicity result for the running time of FMMR applied to MTF and thus identify the initial state that gives the stochastically smallest running time; by contrast, the initial state used in the previous study gives the stochastically largest running time. By changing from worst choice to best choice of initial state we achieve remarkable speedup of FMMR for MTF; for example, we reduce the running time (as measured in Markov chain steps) from exponential in the length n of the list nearly down to n when the items in the list are requested according to a geometric distribution. For this same example, tile running time for CFTP grows exponentially in n.

['Robert P. Dobrow', 'James Allen Fill']

Speeding up the FMMR perfect sampling algorithm: a case study revisited

Facing diverse network attack strategies and overwhelming alters, much work has been devoted to correlate observed malicious events to pre-defined scenarios, attempting to deduce the attack plans based on expert models of how network attacks may transpire. Sophisticated attackers can, however, employ a number of obfuscation techniques to confuse the alert correlation engine or classifier. Recognizing the need for a systematic analysis of the impact of attack obfuscation, this paper models attack strategies as general finite order Markov models, and treats obfuscated observations as noises. Taking into account that only finite observation window and limited computational time can be afforded, this work develops an algorithm to efficiently inference on the joint distribution of clean and obfuscated attack sequences. The inference algorithm recovers the optimal match of obfuscated sequences to attack models, and enables a systematic and quantitative analysis on the impact of obfuscation on attack classification.

['Haitao Du', 'Shanchieh Jay Yang']

Probabilistic Inference for Obfuscated Network Attack Sequences