Query: Solving Constraint Satisfaction Problems through Belief Propagation-guided decimation

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Factor graphs and the sum-product algorithm <=SEP=> Algorithms that must deal with complicated global functions of many variables often exploit the manner in which the given functions factor as a product of “local” functions, each of which depends on a subset of the variables. Such a factorization can be visualized with a bipartite graph that we call afactor graph. In this tutorial paper, we present a generic message-passing algorithm, the sum-product algorithm, that operates in a factor graph. Following a single, simple computational rule, the sum-product algorithm computes—either exactly or approximately—various marginal functions derived from the global function. A wide variety of algorithms developed in artificial intelligence, signal processing, and digital communications can be derived as specific instances of the sum-product algorithm, including the forward/backward algorithm, the Viterbi algorithm, the iterative “turbo” decoding algorithm, Pearl’s belief propagation algorithm for Bayesian networks, the Kalman filter, and certain fast Fourier transform (FFT) algorithms.

Survey propagation: An algorithm for satisfiability <=SEP=> We study the satisfiability of randomly generated formulas formed by M clauses of exactly K literals over N Boolean variables. For a given value of N the problem is known to be most difficult when α = M/N is close to the experimental threshold αc separating the region where almost all formulas are SAT from the region where all formulas are UNSAT. Recent results from a statistical physics analysis suggest that the difficulty is related to the existence of a clustering phenomenon of the solutions when α is close to (but smaller than) αc. We introduce a new type of message passing algorithm which allows to find efficiently a satisfying assignment of the variables in this difficult region. This algorithm is iterative and composed of two main parts. The first is a message-passing procedure which generalizes the usual methods like Sum-Product or Belief Propagation: It passes messages that may be thought of as surveys over clusters of the ordinary messages. The second part uses the detailed probabilistic information obtained from the surveys in order to fix variables and simplify the problem. Eventually, the simplified problem that remains is solved by a conventional heuristic. © 2005 Wiley Periodicals, Inc. Random Struct. Alg., 27, 201–226, 2005

The generalized distributive law <=SEP=> In this semitutorial paper we discuss a general message passing algorithm, which we call the generalized distributive law (GDL). The GDL is a synthesis of the work of many authors in the information theory, digital communications, signal processing, statistics, and artificial intelligence communities. It includes as special cases the Baum–Welch algorithm, the fast Fourier transform (FFT) on any finite Abelian group, the Gallager–Tanner–Wiberg decoding algorithm, Viterbi’s algorithm, the BCJR algorithm, Pearl’s “belief propagation” algorithm, the Shafer–Shenoy probability propagation algorithm, and the turbo decoding algorithm. Although this algorithm is guaranteed to give exact answers only in certain cases (the “junction tree” condition), unfortunately not including the cases of GTW with cycles or turbo decoding, there is much experimental evidence, and a few theorems, suggesting that it often works approximately even when it is not supposed to.

A recursive approach to low complexity codes <=SEP=> A bstruciA method is described for constructing long error-correcting codes from one or more shorter error-correcting codes, referred to as subcodes, and a bipartite graph. A graph is shown which specifies carefully chosen subsets of the digits of the new codes that must be codewords in one of the shorter subcodes. Lower bounds to the rate and the minimum distance of the new code are derived in terms of the parameters of the graph and the subcodes. Both the encoders and decoders proposed are shown to take advantage of the code’s explicit decomposition into subcodes to decompose and simplify the associated computational processes. Bounds on the performance of two specific decoding algorithms are established, and the asymptotic growth of the complexity of decoding for two types of codes and decoders is analyzed. The proposed decoders are able to mahe effective use of probabilistic information supplied by the channel receiver, e.g., reliability information, without greatly increasing the number of computations required. It is shown that choosing a transmission order for the digits that is appropriate for the graph and the subcodes can give the code excellent burst-error correction abilities. The construction principles are illustrated by several examples.

A tutorial on hidden Markov models and selected applications in speech recognition <=SEP=> 

Extraction of high confidence minutiae points from fingerprint images <=SEP=> Fingerprint is one of the well accepted biometric traits for building automatic human recognition system. These systems mainly involves matching of two fingerprints based on their minutiae points. Therefore, extraction of reliable or true minutiae from the fingerprint image is critically important. This paper proposed an novel algorithm for automatic extraction of highly reliable minutiae points from a fingerprint image. It utilizes frequency domain image enhancement and heuristics. Experiments have been conducted on two databases. FVC2002 which is a publicly available fingerprint database containing 800 fingerprint images of 100 persons and IITK-Sel500FP which is an in-house database containing 1000 fingerprint images of 500 persons. Minutiae points extracted by the proposed algorithm are benchmarked against the manually marked ones and the comparison is done with an open source minutiae extractor mindtct of NIST. Experimental results have shown that the proposed algorithm has significantly higher confidence of extracted minutiae points being true.

Exploiting Passive Dynamics with Variable Stiffness Actuation in Robot Brachiation <=SEP=> This paper explores a passive control strategy with variable stiffness actuation for swing movements. We consider brachiation as an example of a highly dynamic task which requires exploitation of gravity in an efficient manner for successful task execution. First, we present our passive control strateg y considering a pendulum with variable stiffness actuation. Then, we formulate the problem based an optimal control framework with temporal optimization in order to simultaneously find an appropriate stiffness profile and movement duration such that the resultant movement will be able to exploit the passive dynamics of the robot. Finally, numerical evaluations on a twolink brachiating robot with a variable stiffness actuator (VSA) model are provided to demonstrate the effectiveness of our approach under different task requirements, modelling errors and switching in the robot dynamics. In addition, we discuss the issue of task description in terms of the choice of cost function for successful task execution in optimal control.

Arabic Script Recognition : A Survey <=SEP=> Optical character recognition (OCR) is essential in various real-world applications, such as digitizing learning resources to assist visually impaired people and transforming printed resources into electronic media. However, the development of OCR for printed Arabic script is a challenging task. These challenges are due to the specific characteristics of Arabic script. Therefore, different methods have been proposed for developing Arabic OCR systems, and this paper aims to provide a comprehensive review of these methods. This paper also discusses relevant issues of printed Arabic OCR including the challenges of printed Arabic script and performance evaluation. It concludes with a discussion of the current status of printed Arabic OCR, analyzing the remaining problems in the field of printed Arabic OCR and providing several directions for future research. Keywords—Optical character recognition; arabic printed OCR; arabic text recognition; arabic OCR survey; feature extraction; segmentation; classification

SIFT-based local spectrogram image descriptor: a novel feature for robust music identification <=SEP=> Music identification via audio fingerprinting has been an active research field in recent years. In the real-world environment, music queries are often deformed by various interferences which typically include signal distortions and time-frequency misalignments caused by time stretching, pitch shifting, etc. Therefore, robustness plays a crucial role in music identification technique. In this paper, we propose to use scale invariant feature transform (SIFT) local descriptors computed from a spectrogram image as sub-fingerprints for music identification. Experiments show that these sub-fingerprints exhibit strong robustness against serious time stretching and pitch shifting simultaneously. In addition, a locality sensitive hashing (LSH)-based nearest sub-fingerprint retrieval method and a matching determination mechanism are applied for robust sub-fingerprint matching, which makes the identification efficient and precise. Finally, as an auxiliary function, we demonstrate that by comparing the time-frequency locations of corresponding SIFT keypoints, the factor of time stretching and pitch shifting that music queries might have experienced can be accurately estimated.

Improving the Coverage and Spectral Efficiency of Millimeter-Wave Cellular Networks Using Device-to-Device Relays <=SEP=> The susceptibility of millimeter waveform propagation to blockages limits the coverage of millimeter-wave (mmWave) signals. To overcome blockages, we propose to leverage two-hop device-to-device (D2D) relaying. Using stochastic geometry, we derive expressions for the downlink coverage probability of relay-assisted mmWave cellular networks when the D2D links are implemented in either uplink mmWave or uplink microwave bands. We further investigate the spectral efficiency (SE) improvement in the cellular downlink, and the effect of D2D transmissions on the cellular uplink. For mmWave links, we derive the coverage probability using dominant interferer analysis while accounting for both blockages and beamforming gains. For microwave D2D links, we derive the coverage probability considering both line-of-sight and non-line-of-sight (NLOS) propagation. Numerical results show that downlink coverage and SE can be improved using two-hop D2D relaying. Specifically, microwave D2D relays achieve better coverage because D2D connections can be established under NLOS conditions. However, mmWave D2D relays achieve better coverage when the density of interferers is large because blockages eliminate interference from NLOS interferers. The SE on the downlink depends on the relay mode selection strategy, and mmWave D2D relays use a significantly smaller fraction of uplink resources than microwave D2D relays.

From Characters to Understanding Natural Language ( C 2 NLU ) : Robust End-to-End Deep Learning for NLP Organized by <=SEP=> This report documents the program and the outcomes of Dagstuhl Seminar 17042 “From Characters to Understanding Natural Language (C2NLU): Robust End-to-End Deep Learning for NLP”. The seminar brought together researchers from different fields, including natural language processing, computational linguistics, deep learning and general machine learning. 31 participants from 22 academic and industrial institutions discussed advantages and challenges of using characters, i.e., “raw text”, as input for deep learning models instead of language-specific tokens. Eight talks provided overviews of different topics, approaches and challenges in current natural language processing research. In five working groups, the participants discussed current natural language processing/understanding topics in the context of character-based modeling, namely, morphology, machine translation, representation learning, end-to-end systems and dialogue. In most of the discussions, the need for a more detailed model analysis was pointed out. Especially for character-based input, it is important to analyze what a deep learning model is able to learn about language – about tokens, morphology or syntax in general. For an efficient and effective understanding of language, it might furthermore be beneficial to share representations learned from multiple objectives to enable the models to focus on their specific understanding task instead of needing to learn syntactic regularities of language first. Therefore, benefits and challenges of transfer learning were an important topic of the working groups as well as of the panel discussion and the final plenary discussion. Seminar January 22–27, 2017 – http://www.dagstuhl.de/17042 1998 ACM Subject Classification I.2 Artificial Intelligence, I.2.7 Natural Language Processing

Intentional behaviour in dog-human communication: an experimental analysis of “showing” behaviour in the dog <=SEP=> Despite earlier scepticism there is now evidence for simple forms of intentional and functionally referential communication in many animal species. Here we investigate whether dogs engage in functional referential communication with their owners. “Showing” is defined as a communicative action consisting of both a directional component related to an external target and an attention-getting component that directs the attention of the perceiver to the informer or sender. In our experimental situation dogs witness the hiding of a piece of food (or a favourite toy) which they cannot get access to. We asked whether dogs would engage in “showing” in the presence of their owner. To control for the motivational effects of both the owner and the food on the dogs’ behaviour, control observations were also staged where only the food (or the toy) or the owner was present. Dogs’ gazing frequency at both the food (toy) and the owner was greater when only one of these was present. In other words, dogs looked more frequently at their owner when the food (toy) was present, and they looked more at the location of the food (toy) when the owner was present. When both the food (toy) and the owner were present a new behaviour, “gaze alternation”, emerged which was defined as changing the direction of the gaze from the location of the food (toy) to looking at the owner (or vice versa) within 2 s. Vocalisations that occurred in this phase were always associated with gazing at the owner or the location of the food. This behaviour, which was specific to this situation, has also been described in chimpanzees, a gorilla and humans, and has often been interpreted as a form of functionally referential communication. Based on our observations we argue that dogs might be able to engage in functionally referential communication with their owner, and their behaviour could be described as a form of “showing”. The contribution of domestication and individual learning to the well-developed communicative skills in dogs is discussed and will be the subject of further studies.

Full-resolution interactive CPU volume rendering with coherent BVH traversal <=SEP=> We present an efficient method for volume rendering by raycasting on the CPU. We employ coherent packet traversal of an implicit bounding volume hierarchy, heuristically pruned using preintegrated transfer functions, to exploit empty or homogeneous space. We also detail SIMD optimizations for volumetric integration, trilinear interpolation, and gradient lighting. The resulting system performs well on low-end and laptop hardware, and can outperform out-of-core GPU methods by orders of magnitude when rendering large volumes without level-of-detail (LOD) on a workstation. We show that, while slower than GPU methods for low-resolution volumes, an optimized CPU renderer does not require LOD to achieve interactive performance on large data sets.

Combinatorial codes in ventral temporal lobe for object recognition: Haxby (2001) revisited: is there a “face” area? <=SEP=> Haxby et al. [Science 293 (2001) 2425] recently argued that category-related responses in the ventral temporal (VT) lobe during visual object identification were overlapping and distributed in topography. This observation contrasts with prevailing views that object codes are focal and localized to specific areas such as the fusiform and parahippocampal gyri. We provide a critical test of Haxby's hypothesis using a neural network (NN) classifier that can detect more general topographic representations and achieves 83% correct generalization performance on patterns of voxel responses in out-of-sample tests. Using voxel-wise sensitivity analysis we show that substantially the same VT lobe voxels contribute to the classification of all object categories, suggesting the code is combinatorial. Moreover, we found no evidence for local single category representations. The neural network representations of the voxel codes were sensitive to both category and superordinate level features that were only available implicitly in the object categories.

Machine-Learning Research Four Current Directions <=SEP=> Machine Learning research has been making great progress in many directions This article summarizes four of these directions and discusses some current open problems The four directions are a improving classi cation accuracy by learning ensembles of classi ers b methods for scaling up supervised learning algorithms c reinforcement learning and d learning complex stochastic models

A Study of Fonts Designed for Screen Display <=SEP=> This study examined the readabiity.and subjective preferences of a set of fonts designed for screen display. Two new binary bitmap fonts performed well, suggesting that designers hould consider incorporating similar attributes into default fonts for online type.

Recognizing human faces under disguise and makeup <=SEP=> The accuracy of automated human face recognition algorithms can significantly degrade while recognizing same subjects under make-up and disguised appearances. Increasing constraints on enhanced security and surveillance requires enhanced accuracy from face recognition algorithms for faces under disguise and/or makeup. This paper presents a new database for face images under disguised and make-up appearances the development of face recognition algorithms under such covariates. This database has 2460 images from 410 different subjects and is acquired under real environment, focuses on make-up and disguises covariates and also provides ground truth (eye glass, goggle, mustache, beard) for every image. This can enable developed algorithms to automatically quantify their capability for identifying such important disguise attribute during the face recognition We also present comparative experimental results from two popular commercial matchers and from recent publications. Our experimental results suggest significant performance degradation in the capability of these matchers in automatically recognizing these faces. We also analyze face detection accuracy from these matchers. The experimental results underline the challenges in recognizing faces under these covariates. Availability of this new database in public domain will help to advance much needed research and development in recognizing make-up and disguised faces.

2 Saddles in Deep Networks : Background and Motivation <=SEP=> Recent years have seen a growing interest in understanding deep neural networks from an optimization perspective. It is understood now that converging to low-cost local minima is sufficient for such models to become effective in practice. However, in this work, we propose a new hypothesis based on recent theoretical findings and empirical studies that deep neural network models actually converge to saddle points with high degeneracy. Our findings from this work are new, and can have a significant impact on the development of gradient descent based methods for training deep networks. We validated our hypotheses using an extensive experimental evaluation on standard datasets such as MNIST and CIFAR-10, and also showed that recent efforts that attempt to escape saddles finally converge to saddles with high degeneracy, which we define as ‘good saddles’. We also verified the famous Wigner’s Semicircle Law in our experimental results.

The happy and unhappy faces of narcissism <=SEP=> Several theorists have argued in favor of a distinction between overt and covert narcissism, and factor analytic studies have supported this distinction. In this paper I demonstrate that overt narcissists report higher self-esteem and higher satisfaction with life, whereas covert narcissists report lower self-esteem and lower satisfaction with life. I also present mediational models to explain why overt narcissists are relatively happy and covert narcissists are relatively unhappy. In analyses using both partial correlations and structural equation modeling, self-esteem consistently mediated the associations between both types of narcissism and happiness, whereas self-deception did not. These results further demonstrate some of the selfcentered benefits associated with overt narcissism and some of the strong psychological costs associated with covert narcissism. # 2002 Elsevier Science Ltd. All rights reserved.

Some Comments on Cp <=SEP=> 

A Research on Iron Loss of IPMSM With a Fractional Number of Slot Per Pole <=SEP=> In this paper, we investigated rotor iron loss of interior permanent magnet synchronous machine (IPMSM), which has distributed armature windings. In order to study the iron loss with the effect of slot-pole combination, two machines for high-speed operation such as electric vehicle were designed. One is fractional slot winding and the other is conventional one. In the analysis, we developed a new iron loss model of electrical machines for high-speed operation. The calculated iron loss was compared with the experimental data. It was clarified that the proposed method can estimate iron loss effectively at high-speed operation. Based on this newly proposed method, we analyzed iron loss of the two machines according to their driving conditions. From the analysis results, it was shown that rotor iron loss of machine employing fractional slot-winding is definitely large at load condition. In addition, it is interesting that the ratio (rotor iron loss/stator iron loss) becomes larger as the speed of the machines increase if the number of slot per pole is fractional.

Accelerometer based wireless air mouse using Arduino micro-controller board <=SEP=> With the day to day advancements in technology, the interaction between the human and the digital world is diminishing. Lot of improvement has taken place in the mobile technology from button keypads to touch screens. However the current PCs still need a pad to operate its mouse and are wired most of the time. The idea is to develop a wireless mouse which works on the hand gestures of the user without the need of a pad making an effortless interaction between the human and the computer. The implementation is done using a sensor named accelerometer to sense the hand gestures. Accelerometer is a motion sensor which sense changes in motion in any of the three axes. In here the accelerometer will be at the users side, attached to the hand to sense the movement and gives the output to a micro-controller to process it. Necessary modifications are done by the microcontroller to these values and are transmitted through a RF module to the PC. At the receiving end a mouse control program which contains functions to control the mouse reads these values and performs the necessary action.

Multisensor Fusion and Integration: A Review on Approaches and Its Applications in Mechatronics <=SEP=> The objective of this paper is to review the theories and approaches of multisensor fusion and integration (MFI) with its application in mechatronics. MFI helps the system perceiving changes of the environment and monitoring the system itself. Since each individual sensor has its own inherent defects and limitations, MFI merges the redundant information acquired by multiple sensors synergistically to provide a more accurate perception and make an optimal decision in further. The wide application spectrum of MFI in mechatronics includes the industrial automation, the development of intelligent robots, military applications, biomedical applications, etc. In this paper, the architecture and algorithms of MFI are reviewed, and some implementation examples in industrial automation and robotic applications are presented. Furthermore, sensor fusion methods at different levels, namely, estimation methods, classification methods and inference methods, the most frequently used algorithms in previous researches with their advantages and limitations are summarized. Applications of MFI in robotics and mechatronics are discussed. Future perspectives of MFI deployment are included in the concluding remarks.

E-shopping in a multiple channel environment <=SEP=> In the present study, the authors propose a segmentation schema based on patterns of e-browsing and e-purchasing. We examine self-reports of browsing and purchasing using five specific non-store channels: the Internet, television infomercials, advertising that accompanies regular television programming, television shopping channels , and print catalogs. Our findings indicate that shoppers who browse and/or purchase on the Internet differ in their use of multi-channel options related to their perceptions of convenience . Some shoppers clearly want to purchase in the store setting and reject multiple forms of non-store shopping. Others like to browse various non-store media and have extended their browsing to the Internet, yet maintain their loyalty to in-store purchases. Retailers who attempt to `̀ convert’’ such shoppers to Internet-only purchasing may alienate the shoppers who rely on the Internet solely for information. Introduction The explosive growth of the Internet has revolutionized many aspects of daily life (Fetto, 1999; Rutledge, 2000). Recent statistics tell us that people the world over are using the Internet in ever-increasing numbers, with estimates ranging from 505 million (Global Reach, 2001) to 513.41 million people online throughout the world (NUA Ltd, 2001). There is much to be learned about how the Internet fits in people’s lives, how they use it as part of a set of choices, and what deters them from using it for certain purposes, such as making purchases. Despite increased use of the Web, recent industry studies have documented problems such as an ongoing trend in online shopping cart `̀ abandonment’’ in which apparent planned purchases are never completed online (Hurwicz, 1999). In fact, substantial numbers of online shoppers return to physical stores after experiencing problems with slow load times, an inability to locate items, incomplete information, lack of human interaction, and missed or late deliveries (Mardesich, 1999; McCarthy, 2000). Failures with account setups and confusing error messages also caused about 40 percent of shoppers to have problems during checkout (Enos, 2000). While consumers have verified these reasons, we argue that another reason may explain the apparent abandonment that takes place. That is, some Internet browsers may have never intended to complete their purchases online, preferring to shop in a bricks and mortar setting. Perhaps the notion of `̀ abandonment’’ is an oversimplification. Some consumers may simply use shopping carts to investigate and tally possible future purchases, with no intent to purchase at the specific time that they are online. The research register for this journal is available at http://www.emeraldinsight.com/researchregisters The current issue and full text archive of this journal is available at http://www.emeraldinsight.com/0736-3761.htm Explosive growth Failure to complete purchases JOURNAL OF CONSUMER MARKETING, VOL. 19 NO. 4 2002, pp. 333-350, # MCB UP LIMITED, 0736-3761, DOI 10.1108/07363760210433645 333 An executive summary for managers and executive readers can be found at the end of this article The purpose of the present study is to empirically investigate the connections among Internet `̀ use’’ and other non-store media options in a multi-channel environment. In the present study, the authors propose a segmentation schema based on patterns of e-browsing and e-purchasing, including browsing on the Internet with planned purchasing in an offline channel. Using that schema, our study examines the self-reports of browsing and purchasing of 250 Internet users with respect to five specific non-store media: the Internet, television infomercials, advertising that accompanies regular television programming, television shopping channels, and print catalogs. Our findings indicate that shoppers who browse and/or purchase on the Internet differ in their use of multi-channel options related to their perceptions of convenience. Some shoppers clearly want to purchase in the store setting and reject multiple forms of non-store shopping. Others like to browse various non-store media and have extended their browsing to the Internet, yet maintain their loyalty to in-store purchases. Background The growth and potential of the Internet There is a need for a `̀ better understanding of the Web user’’ and e-shopping (Korgaonkar and Wolin, 1999). Current studies vary in predicting the characteristics of Web users, ranging from male, well-educated, middle income and middle-aged or younger (Emmanouilides and Hammond, 2000; Korgaonkar and Wolin, 1999; Wilson, 2000), to substantial increases among women and the elderly (Harris, 1998; Rosen and Howard, 2000; Rosen and Weil, 1995). Recent studies by Media Metrix and Jupiter Communications indicate that more women are online than men, with the greatest increases among teenaged girls and women over 55 (Hamilton, 2000). Many studies have found that typical online buyers have used the Web for several years, and because of their familiarity, they search online for product information and purchase options (Bellman et al., 1999). In many cases, convenience and time-management are the key drivers among e-shoppers (Chang and McFarland, 1999), while some `̀ wired but wary’’ use the Internet for e-mail, but do not shop online. Still others have no regular Internet access at all. Many studies examine Internet shopping exclusively in determining consumer usage and satisfaction (Szymanski and Hise, 2000; VanTassel and Weitz, 1997). However, it is not likely that shoppers view the Internet as separate and distinct from other more familiar forms of shopping. We argue that it is more realistic to examine e-shopping in the context of multi-channel alternatives that are also available to shoppers (Grant, 2000; Greco, 1996). The interrelationships among various types of non-store methods are not well understood, nor are their impacts on `̀ bricks and mortar’’ retail outlets (Achenbaum, 1999). We also contend that insights can be gained by organizing the study of e-shopping based on sound theoretical relationships that have been used to describe other components of the multiple channel environment. We turn to the literature on recreational shopping and convenience in order to build a foundation for the study. Browsing and purchasing Some studies have attempted to understand whether browsing on the Internet is correlated with purchasing on the Internet (Lindquist and KaufmanScarborough, 2000). It is questionable whether a perfect match is possible, since some shoppers enjoy browsing as a separate activity, while others buy without browsing if their choice is clear and determined in advance. Because of problems like security fears, lack of skill with computers, slow response time by e-tailers, and confusing Web sites, studies report that numerous Segmentation schema Convenience and time management 334 JOURNAL OF CONSUMER MARKETING, VOL. 19 NO. 4 2002 shoppers use non-store methods to search and compare, while going to the `̀ bricks and mortar’’ setting to make their purchases (Koprowski, 2000; Levy and Nilson, 1999). Earlier pre-Internet studies investigated why people shop, why they go to the store, and why they look but do not buy. For instance, Tauber (1972, 1995) went beyond retail patronage and demonstrated that people have numerous motives for shopping that are unrelated to the actual purchasing of products. The shoppers in his sample reported that their shopping trips included carrying out expected roles, diversion from daily routine, self-gratification and response to moods, learning about new trends, physical activity, sensory stimulation, meeting others with similar interests, interaction with peer groups, and the pleasure of bargaining. Such motives are likely to result in browsing that does not necessarily lead to purchasing. Other studies have identified persons as `̀ recreational shoppers’’, who enjoy shopping as a leisure activity and tend to browse in retail outlets `̀ without an upcoming purchase in mind’’ (Bellinger and Korgaonkar, 1980; Ohanian and Tashchian, 1992). Such shoppers report being interested in gaining knowledge about specific product classes and actively seek information about topics such as merchandise, prices, and quality. Such shoppers do not generally gather such information in preparation for an upcoming purchase, but instead appear to enjoy gathering information for its own sake. They engage in word-of-mouth activities more than other shoppers (Bloch and Richins, 1983), and enjoy giving advice and influencing other consumers. These earlier researchers explicitly considered browsing and shopping behaviors in the `̀ bricks and mortar’’ setting. We suggest that `̀ recreational e-shoppers’’ are also likely to virtually `̀ stroll’’ through online shopping sites for learning, social, or diversion-related purposes. Recreational e-shoppers may also enjoy gathering online information and share their knowledge through online chat rooms and buyer forums. If a comparable pattern of information gathering and sharing exists, browsers who do not `̀ convert’’ to purchasers may be found to exhibit similar characteristics to in-store recreational shoppers who may be lonely, bored, or simply curious. Browsing convenience versus purchasing convenience Surveys of customers indicate their frustration with the lack of convenience provided by `̀ bricks and mortar’’ stores. They report problems with crowded store conditions, out of stock merchandise, and poorly-trained salespersons, prompting shoppers to search for more favorable ways to browse and to purchase. In fact, retailers have been criticized for developing in-store strategies based on their own convenience, rather than that of their customers (Seiders et al., 2000). Convenience is a more complex notion than simply providing quick checkouts or locations close to home. In fact, shoppers are thought to clearly differentiate among various dimensions of conve

A Neural Network Color Classifier in HSV Color Space <=SEP=> In this paper, a neural network approach for color classification in HSV color space based on color JND (just noticeable difference) is presented. The HSV color samples are generated using an interactive tool based on JND concept and these samples are used for supervised training. A four layer feed forward neural network is trained for classifying a given color pair as similar or dissimilar pair. An interactive tool for color pixel comparison is developed for testing the color classifier on real life images. Research shows that neural network classifier in HSV color space works better than RGB classifier in terms of efficiency for segmentation purposes. Thus the experimentation results can be used for segmenting real life images.

F-DES: Fast and Deep Event Summarization <=SEP=> In the multimedia era a large volume of video data can be recorded during a certain period of time by multiple cameras. Such a rapid growth of video data requires both effective and efficient multiview video summarization techniques. The users can quickly browse and comprehend a large amount of audiovisual data. It is very difficult in real-time to manage and access the huge amount of video-content-handling issues of interview dependencies significant variations in illumination and presence of many unimportant frames with low activity. In this paper we propose a local-alignment-based FASTA approach to summarize the events in multiview videos as a solution of the aforementioned problems. A deep learning framework is used to extract the features to resolve the problem of variations in illumination and to remove fine texture details and detect the objects in a frame. Interview dependencies among multiple views of video are then captured via the FASTA algorithm through local alignment. Finally object tracking is applied to extract the frames with low activity. Subjective as well as objective evaluations clearly indicate the effectiveness of the proposed approach. Experiments show that the proposed summarization method successfully reduces the video content while keeping momentous information in the form of events. A computing analysis of the system also shows that it meets the requirement of real-time applications.

Image segmentation via adaptive K-mean clustering and knowledge-based morphological operations with biomedical applications <=SEP=> Image segmentation remains one of the major challenges in image analysis. In medical applications, skilled operators are usually employed to extract the desired regions that may be anatomically separate but statistically indistinguishable. Such manual processing is subject to operator errors and biases, is extremely time consuming, and has poor reproducibility. We propose a robust algorithm for the segmentation of three-dimensional (3-D) image data based on a novel combination of adaptive K-mean clustering and knowledge-based morphological operations. The proposed adaptive K-mean clustering algorithm is capable of segmenting the regions of smoothly varying intensity distributions. Spatial constraints are incorporated in the clustering algorithm through the modeling of the regions by Gibbs random fields. Knowledge-based morphological operations are then applied to the segmented regions to identify the desired regions according to the a priori anatomical knowledge of the region-of-interest. This proposed technique has been successfully applied to a sequence of cardiac CT volumetric images to generate the volumes of left ventricle chambers at 16 consecutive temporal frames. Our final segmentation results compare favorably with the results obtained using manual outlining. Extensions of this approach to other applications can be readily made when a priori knowledge of a given object is available.

UTILIZING A GAME THEORETICAL APPROACH TO PREVENT COLLUSION AND INCENTIVIZE COOPERATION IN <=SEP=> Author: Arash Golchubian Title: Utilizing a Game Theoretical Approach to Prevent Collusion and Incentivize Cooperation in Cybersecurity Contexts Institution: Florida Atlantic University Thesis Advisor: Dr. Mehrdad Nojoumian Degree: Master of Science Year: 2017 In this research, a new reputation-based model is utilized to disincentivize collusion of defenders and attackers in Software Defined Networks (SDN), and also, to disincentivize dishonest mining strategies in Blockchain. In the context of SDN, the model uses the reputation values assigned to each entity to disincentivize collusion with an attacker. Our analysis shows that not-colluding actions become Nash Equilibrium using the reputationbased model within a repeated game setting. In the context of Blockchain and mining, we illustrate that by using the same socio-rational model, miners not only are incentivized to conduct honest mining but also disincentivized to commit to any malicious activities against other mining pools. We therefore show that honest mining strategies become Nash Equilibrium in our setting. This thesis is laid out in the following manner. In chapter 2 an introduction to game theory is provided followed by a survey of previous works in game theoretic network security, in chapter 3 a new reputation-based model is introduced to be used within the context of a Software Defined Network (SDN), in chapter 4 a reputation-based solution concept is introduced to force cooperation by each mining entity in Blockchain, and finally, in chapter 5, the concluding remarks and future works are presented. vii To: My loving wife, Sanaz. You inspire me to better myself. and My mother, Mina. You showed me that nothing is impossible. UTILIZING A GAME THEORETICAL APPROACH TO PREVENT COLLUSION AND INCENTIVIZE COOPERATION IN CYBERSECURITY CONTEXTS List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xii List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiii

Curing regular expressions matching algorithms from insomnia, amnesia, and acalculia <=SEP=> The importance of network security has grown tremendously and a collection of devices have been introduced, which can improve the security of a network. Network intrusion detection systems (NIDS) are among the most widely deployed such system; popular NIDS use a collection of signatures of known security threats and viruses, which are used to scan each packet's payload. Today, signatures are often specified as regular expressions; thus the core of the NIDS comprises of a regular expressions parser; such parsers are traditionally implemented as finite automata. Deterministic Finite Automata (DFA) are fast, therefore they are often desirable at high network link rates. DFA for the signatures, which are used in the current security devices, however require prohibitive amounts of memory, which limits their practical use.
 In this paper, we argue that the traditional DFA based NIDS has three main limitations: first they fail to exploit the fact that normal data streams rarely match any virus signature; second, DFAs are extremely inefficient in following multiple partially matching signatures and explodes in size, and third, finite automaton are incapable of efficiently keeping track of counts. We propose mechanisms to solve each of these drawbacks and demonstrate that our solutions can implement a NIDS much more securely and economically, and at the same time substantially improve the packet throughput.

On the hardness of approximating minimum vertex cover By <=SEP=> We prove the Minimum Vertex Cover problem to be NP-hard to approximate to within a factor of 1.3606, extending on previous PCP and hardness of approximation technique. To that end, one needs to develop a new proof framework, and to borrow and extend ideas from several fields.