query: Customer Purchase Behavior Prediction from Payment Datasets

positive: Who, where, when and what: discover spatio-temporal topics for twitter users Micro-blogging services, such as Twitter, and location-based social network applications have generated short text messages associated with geographic information, posting time, and user ids. The availability of such data received from users offers a good opportunity to study the user's spatial-temporal behavior and preference. In this paper, we propose a probabilistic model W4 (short for Who+Where+When+What) to exploit such data to discover individual users' mobility behaviors from spatial, temporal and activity aspects. To the best of our knowledge, our work offers the first solution to jointly model individual user's mobility behavior from the three aspects. Our model has a variety of applications, such as user profiling and location prediction; it can be employed to answer questions such as ``Can we infer the location of a user given a tweet posted by the user and the posting time?" Experimental results on two real-world datasets show that the proposed model is effective in discovering users' spatial-temporal topics, and outperforms state-of-the-art baselines significantly for the task of location prediction for tweets.

positive: Modelling the scaling properties of human mobility Individual human trajectories are characterized by fat-tailed distributions of jump sizes and waiting times, suggesting the relevance of continuous-time random-walk (CTRW) models for human mobility. However, human traces are barely random. Given the importance of human mobility, from epidemic modelling to traffic prediction and urban planning, we need quantitative models that can account for the statistical characteristics of individual human trajectories. Here we use empirical data on human mobility, captured by mobile-phone traces, to show that the predictions of the CTRW models are in systematic conflict with the empirical results. We introduce two principles that govern human trajectories, allowing us to build a statistically self-consistent microscopic model for individual human mobility. The model accounts for the empirically observed scaling laws, but also allows us to analytically predict most of the pertinent scaling exponents.

positive: Lévy flights and random searches In this work we discuss some recent contributions to the random search problem. Our analysis includes superdiffusive Lévy processes and correlated random walks in several regimes of target site density, mobility and revisitability. We present results in the context of mean-field-like and closed-form average calculations, as well as numerical simulations. We then consider random searches performed in regular lattices and lattices with defects, and we discuss a necessary criterion for distinguishing true superdiffusion from correlated random walk processes. We invoke energy considerations in relation to critical survival states on the edge of extinction, and we analyze the emergence of Lévy behavior in deterministic search walks. Finally, we comment on the random search problem in the context of biological foraging. PACS numbers: 05.50.Fb, 05.40.−a

positive: Fused Matrix Factorization with Geographical and Social Influence in Location-Based Social Networks Recently, location-based social networks (LBSNs), such as Gowalla, Foursquare, Facebook, and Brightkite, etc., have attracted millions of users to share their social friendship and their locations via check-ins. The available check-in information makes it possible to mine users’ preference on locations and to provide favorite recommendations. Personalized Point-of-interest (POI) recommendation is a significant task in LBSNs since it can help targeted users explore their surroundings as well as help third-party developers to provide personalized services. To solve this task, matrix factorization is a promising tool due to its success in recommender systems. However, previously proposed matrix factorization (MF) methods do not explore geographical influence, e.g., multi-center check-in property, which yields suboptimal solutions for the recommendation. In this paper, to the best of our knowledge, we are the first to fuse MF with geographical and social influence for POI recommendation in LBSNs. We first capture the geographical influence via modeling the probability of a user’s check-in on a location as a Multi-center Gaussian Model (MGM). Next, we include social information and fuse the geographical influence into a generalized matrix factorization framework. Our solution to POI recommendation is efficient and scales linearly with the number of observations. Finally, we conduct thorough experiments on a large-scale real-world LBSNs dataset and demonstrate that the fused matrix factorization framework with MGM utilizes the distance information sufficiently and outperforms other state-of-the-art methods significantly.

positive: The scaling laws of human travel The dynamic spatial redistribution of individuals is a key driving force of various spatiotemporal phenomena on geographical scales. It can synchronize populations of interacting species, stabilize them, and diversify gene pools. Human travel, for example, is responsible for the geographical spread of human infectious disease. In the light of increasing international trade, intensified human mobility and the imminent threat of an influenza A epidemic, the knowledge of dynamical and statistical properties of human travel is of fundamental importance. Despite its crucial role, a quantitative assessment of these properties on geographical scales remains elusive, and the assumption that humans disperse diffusively still prevails in models. Here we report on a solid and quantitative assessment of human travelling statistics by analysing the circulation of bank notes in the United States. Using a comprehensive data set of over a million individual displacements, we find that dispersal is anomalous in two ways. First, the distribution of travelling distances decays as a power law, indicating that trajectories of bank notes are reminiscent of scale-free random walks known as Lévy flights. Second, the probability of remaining in a small, spatially confined region for a time T is dominated by algebraically long tails that attenuate the superdiffusive spread. We show that human travelling behaviour can be described mathematically on many spatiotemporal scales by a two-parameter continuous-time random walk model to a surprising accuracy, and conclude that human travel on geographical scales is an ambivalent and effectively superdiffusive process.

negative: Estimating surface normals in noisy point cloud data In this paper we describe and analyze a method based on local least square fitting for estimating the normals at all sample points of a point cloud data (PCD) set, in the presence of noise. We study the effects of neighborhood size, curvature, sampling density, and noise on the normal estimation when the PCD is sampled from a smooth curve in R2 or a smooth surface in R3 and noise is added. The analysis allows us to find the optimal neighborhood size using other local information from the PCD. Experimental results are also provided.

negative: Big data: the next frontier for innovation in therapeutics and healthcare. Advancements in genomics and personalized medicine not only effect healthcare delivery from patient and provider standpoints, but also reshape biomedical discovery. We are in the era of the '-omics', wherein an individual's genome, transcriptome, proteome and metabolome can be scrutinized to the finest resolution to paint a personalized biochemical fingerprint that enables tailored treatments, prognoses, risk factors, etc. Digitization of this information parlays into 'big data' informatics-driven evidence-based medical practice. While individualized patient management is a key beneficiary of next-generation medical informatics, this data also harbors a wealth of novel therapeutic discoveries waiting to be uncovered. 'Big data' informatics allows for networks-driven systems pharmacodynamics whereby drug information can be coupled to cellular- and organ-level physiology for determining whole-body outcomes. Patient '-omics' data can be integrated for ontology-based data-mining for the discovery of new biological associations and drug targets. Here we highlight the potential of 'big data' informatics for clinical pharmacology.

negative: Forecasting Real Estate Prices ∗ This chapter reviews the evidence of predictability in US residential and commercial real estate markets. First, we highlight the main methodologies used in the construction of real estate indices, their underlying assumptions and their impact on the stochastic properties of the resultant series. We then survey the key empirical findings in the academic literature, including short-run persistence and long-run reversals in the log changes of real estate prices. Next, we summarize the ability of local as well as aggregate variables to forecast real estate returns. We illustrate a number of these results by relying on six aggregate indexes of the prices of unsecuritized (residential and commercial) real estate and REITs. The effect of leverage and monetary policy is also discussed.

negative: The Beta Generalized Exponential Distribution We introduce the beta generalized exponential distribution that includes the beta exponential and generalized exponential distributions as special cases. We provide a comprehensive mathematical treatment of this distribution. We derive the moment generating function and the rth moment thus generalizing some results in the literature. Expressions for the density, moment generating function and rth moment of the order statistics also are obtained. We discuss estimation of the parameters by maximum likelihood and provide the information matrix. We observe in one application to real data set that this model is quite flexible and can be used quite effectively in analyzing positive data in place of the beta exponential and generalized exponential distributions. keywords: Beta exponential distribution, Information matrix, Generalized exponential distribution, Maximum likelihood estimation.

negative: Motivation and job satisfaction The movement of workers to act in a desired manner has always consumed the thoughts of managers. In many ways, this goal has been reached through incentive programs, corporate pep talks, and other types of conditional administrative policy. However, as the workers adjust their behaviour in response to one of the aforementioned stimuli, is job satisfaction actualized? The instilling of satisfaction within workers is a crucial task of management. Satisfaction creates confidence, loyalty and ultimately improved quality in the output of the employed. Satisfaction, though, is not the simple result of an incentive program. Employees will most likely not take any more pride in their work even if they win the weekend getaway for having the highest sales. This paper reviews the literature of motivational theorists and draws from their approaches to job satisfaction and the role of motivation within job satisfaction. The theories of Frederick Herzberg and Edwin Locke are presented chronologically to show how Locke’s theory was a response to Herzberg’s theory. By understanding these theories, managers can focus on strategies of creating job satisfaction. This is followed by a brief examination of Kenneth Blanchard and Paul Hersey’s theory on leadership within management and how this art is changing through time. Herzberg and job satisfaction

negative: Recognizing Objects in Range Data Using Regional Point Descriptors Recognition of three dimensional (3D) objects in noisy and cluttered scenes is a challenging problem in 3D computer vision. One approach that has been successful in past research is the regional shape descriptor. In this paper, we introduce two new regional shape descriptors: 3D shape contexts and harmonic shape contexts. We evaluate the performance of these descriptors on the task of recognizing vehicles in range scans of scenes using a database of 56 cars. We compare the two novel descriptors to an existing descriptor, the spin image, showing that the shape context based descriptors have a higher recognition rate on noisy scenes and that 3D shape contexts outperform the others on cluttered scenes.

negative: How Smart is Smart Money ? An Empirical Two-Sided Matching Model of Venture Capital In capital markets, top-tier investors may have better abilities to monitor and manage their investments. In addition, there may be sorting in these markets, with top-tier investors investing in the best deals, second-tier investors investing in the second-best deals, and so forth. To separate and quantify these two effects, a structural model of the market for venture capital is developed and estimated. The model is a two-sided matching model that allows for sorting in equilibrium. It is found that more experienced venture capitalists make more successful investments. This is explained both by their value-adding influence on their investments, and by their access to late stage and biotechnology companies, companies that are more successful on average. Sorting is found to be prevalent and has general implications for the interpretation of empirical evidence of the impact of investors on their investments.

negative: Supervised Topic Models We introduce supervised latent Dirichlet allocation (sLDA), a statistical model of labelled documents. The model accommodates a variety of response types. We derive a maximum-likelihood procedure for parameter estimation, which relies on variational approximations to handle intractable posterior expectations. Prediction problems motivate this research: we use the fitted model to predict response values for new documents. We test sLDA on two real-world problems: movie ratings predicted from reviews, and web page popularity predicted from text descriptions. We illustrate the benefits of sLDA versus modern regularized regression, as well as versus an unsupervised LDA analysis followed by a separate regression.

negative: A Circuit-Compatible SPICE model for Enhancement Mode Carbon Nanotube Field Effect Transistors This paper presents a circuit-compatible compact model for short channel length (5 nm~100 nm), quasi-ballistic single wall carbon nanotube field-effect transistors (CNFETs). For the first time, a universal circuit-compatible CNFET model was implemented with HSPICE. This model includes practical device non-idealities, e.g. the quantum confinement effects in both circumferential and channel length direction, the acoustical/optical phonon scattering in channel region and the resistive source/drain, as well as the real time dynamic response with a transcapacitance array. This model is valid for CNFET for a wide diameter range and various chiralities as long as the carbon nanotube (CNT) is semiconducting

negative: Fear bradycardia and activation of the human periaqueductal grey Animal models of predator defense distinguish qualitatively different behavioral modes that are activated at increasing levels of predation threat. A defense mode observed at intermediate threat levels is freezing: a cessation of locomotion that is characterized by a parasympathetically dominated autonomic nervous system response that causes heart rate deceleration, or fear bradycardia. Studies in rodents have shown that freezing depends on amygdalar projections to the periaqueductal grey (PAG). In humans, freezing-like behaviors are implicated in development and maintenance of psychopathology, but neural mechanisms underlying freezing or its characteristic autonomic response profile have not been identified. Here, we combined event-related blood oxygenation level-dependent functional MRI (BOLD-fMRI) with autonomic response measures in a picture viewing paradigm to probe activity and interconnectivity within the amygdala-PAG pathway and test for an association with parasympathetic as opposed to sympathetic activation. In response to negatively arousing pictures, we observed parasympathetic (bradycardia) and sympathetic (pupil dilation) autonomic responses, BOLD responses in the amygdala and PAG, and effective connectivity between these regions. Critically, BOLD responses in the PAG to negative pictures correlated on a trial-by-trial basis with bradycardia but not pupil dilation. This correlation with bradycardia remained significant when partialling out pupil dilation. Additionally, activity in regions associated with motor planning and inhibition mirrored the PAG response. Thus, our findings implicate the human PAG in a parasympathetically dominated defense mode that subserves a state of attentive immobility. Mechanistic insight into this qualitatively distinct defense mode may importantly advance translational models of anxiety disorders.

negative: RSSI informed phase method for distance calculations In an attempt to find an accurate, environmentally robust, and fast process for RFID distance estimations, a method was developed called RSSI Informed Phase. This method uses both phase and RSSI measurements to estimate the distance, and potentially location, of a moving RFID tag. RSSI is initially used to find an approximate reader to tag separation distance. This distance value is applied to find an approximate slope of the phase angle vs. frequency curve. The estimated slope can inform the phase distance calculation, meaning fewer reads are required to find the actual phase angle vs. frequency slope. The reduction in the number of necessary reads accelerates the localization process and makes this method more robust for dynamic environments.

negative: Teleoperated robot writing using EMG signals In this paper, we have developed a method to tele-control a robot arm to imitate human writing skills using electromyography (EMG) signals. The control method is implemented on the Baxter® robot with a brush attached on the endpoint of its arm to imitate human writing skills, and a MYO sensor is used to measure the surface electromyographic (sEMG) signals generated by contractions of human muscles involved in writing tasks. A haptic device Sensable® Omni is used to control the motion of the Baxter® robot arm, and V-Rep® is employed to simulate the movement of the arm and to calculate the inverse kinematic of Baxter® robot arm. All the communications for Baxter® robot, V-Rep simulator, Omni device and MYO are integrated in MATLAB®/Simulink®. The main test is to make the Baxter® arm following the movement of a human subject when writing with Omni stylus, and the EMG signals are processed using low pass filter and moving average technique to extract the smoothed envelope which is utilised to control the variation of position instead of variation of force along the vertical Z axis, so when the operator writes with force variations, the Baxter® can draw lines with variable thickness. This imitation system is successfully tested to make the Baxter® arm to follow the writing movement of the operator's hand and would have potential applications in more complicated human robot teleoperation tasks such as tele-rehabilitation and tele-surgery.

negative: Parallel computations for controlling an arm. In order to control a reaching movement of the arm and body, several different computational problems must be solved. Some parallel methods that could be implemented in networks of neuron-like processors are described. Each method solves a different part of the overall task. First, a method is described for finding the torques necessary to follow a desired trajectory. The methods is more economical and more versatile than table look-up and requires very few sequential steps. Then a way of generating an internal representation of a desired trajectory is described. This method shows the trajectory one piece at a time by applying a large set of heuristic rules to a "motion blackboard" that represents the static and dynamic parameters of the state of the body at the current point in the trajectory. The computations are simplified by expressing the positions, orientations, and motions of parts of the body in terms of a single, non-accelerating, world-based frame of reference, rather than in terms of the joint-angles or an egocentric frame based on the body itself.

negative: TimeMachine: Timeline Generation for Knowledge-Base Entities We present a method called TIMEMACHINE to generate a timeline of events and relations for entities in a knowledge base. For example for an actor, such a timeline should show the most important professional and personal milestones and relationships such as works, awards, collaborations, and family relationships. We develop three orthogonal timeline quality criteria that an ideal timeline should satisfy: (1) it shows events that are relevant to the entity; (2) it shows events that are temporally diverse, so they distribute along the time axis, avoiding visual crowding and allowing for easy user interaction, such as zooming in and out; and (3) it shows events that are content diverse, so they contain many different types of events (e.g., for an actor, it should show movies and marriages and awards, not just movies). We present an algorithm to generate such timelines for a given time period and screen size, based on submodular optimization and web-co-occurrence statistics with provable performance guarantees. A series of user studies using Mechanical Turk shows that all three quality criteria are crucial to produce quality timelines and that our algorithm significantly outperforms various baseline and state-of-the-art methods.

negative:
Associations among Wine Grape Microbiome, Metabolome, and Fermentation Behavior Suggest Microbial Contribution to Regional Wine Characteristics UNLABELLED
Regionally distinct wine characteristics (terroir) are an important aspect of wine production and consumer appreciation. Microbial activity is an integral part of wine production, and grape and wine microbiota present regionally defined patterns associated with vineyard and climatic conditions, but the degree to which these microbial patterns associate with the chemical composition of wine is unclear. Through a longitudinal survey of over 200 commercial wine fermentations, we demonstrate that both grape microbiota and wine metabolite profiles distinguish viticultural area designations and individual vineyards within Napa and Sonoma Counties, California. Associations among wine microbiota and fermentation characteristics suggest new links between microbiota, fermentation performance, and wine properties. The bacterial and fungal consortia of wine fermentations, composed from vineyard and winery sources, correlate with the chemical composition of the finished wines and predict metabolite abundances in finished wines using machine learning models. The use of postharvest microbiota as an early predictor of wine chemical composition is unprecedented and potentially poses a new paradigm for quality control of agricultural products. These findings add further evidence that microbial activity is associated with wine terroir

IMPORTANCE
Wine production is a multi-billion-dollar global industry for which microbial control and wine chemical composition are crucial aspects of quality. Terroir is an important feature of consumer appreciation and wine culture, but the many factors that contribute to terroir are nebulous. We show that grape and wine microbiota exhibit regional patterns that correlate with wine chemical composition, suggesting that the grape microbiome may influence terroir In addition to enriching our understanding of how growing region and wine properties interact, this may provide further economic incentive for agricultural and enological practices that maintain regional microbial biodiversity.

negative: Sustainable construction: construction and demolition waste reconsidered. Construction activity in Europe has increased substantially in the past decade. Likewise, there has also been a commensurate rise in the generation of construction and demolition waste (C&DW). This, together with the fact that in many European countries the rate of recycling and reuse of C&DW is still quite low has engendered a serious environmental problem and a motivation to develop strategies and management plans to solve it. Due to its composition, there is a significant potential to reuse and/or recycle C&DW, and thereby, contribute to improving the sustainability of construction and development, but practical procedures are not yet widely known or practiced in the construction industry. This article (a) summarizes the different applications that are presently practiced to optimize the recovery and/or application of C&DW for reuse, and (b) proposes various measures and strategies to improve the processing of this waste. The authors suggest that to enhance environmental effectiveness, a conscious and comprehensive C&DW management plan should be implemented in each jurisdiction. More precisely, this study presents a holistic approach towards C&DW management, through which environmental benefits can be achieved through the application of new construction methods that can contribute to sustainable growth.

negative: Wireless image communication system for fire-fighting robots Recently, it has sometimes been impossible for fire-fighting personnel to access the site of a fire, even as the fire causes tremendous property damage and loss of human life, due to high temperatures or the presence of explosive materials. In such environments, fire-fighting robots can be useful for extinguishing a fire, and they should be controlled by remote operators. In order to help a remote operator who is located far away from the fire-fighting robot, wireless image communication systems have been investigated in this study. The developed system uses a High-Speed Downlink Packet Access (HSDPA) network to transmit images, showing the view from a fire-fighting robot. The fire-fighting robots and remote controllers are equipped with industrial computers, and image-transmitting and image-receiving programs function according to various protocols to allow communication between the robots and controllers

negative: Low voltage low power analog circuit design OTA using signal attenuation technique in universal filter application This paper presents a new configuration for a linear operational transconductance amplifier (OTA) using a signal attenuation technique. The OTA is designed to operate with a ±0.8V supply voltage and consumes 0.45mW power. All simulations are performed by ELDO model BSIM3v3 technology CMOS TSMC 0.18μm. The simulation results of this circuit showed a high DC gain of 73.6dB with a unity frequency of 50.19MHz and a total harmonic distortion of -60.81dB at 100 kHz for an input voltage of 1Vpp. Based on this circuit, a voltage mode universal filter has been implemented. The simulation results are in a good agreement with the theoretical calculations.

negative: Risk Factors in Adolescence: The Case of Gambling, Videogame Playing, and the Internet It has been noted that adolescents may be more susceptible to pathological gambling. Not only is it usually illegal, but it appears to be related to high levels of problem gambling and other delinquent activities such as illicit drug taking and alcohol abuse. This paper examines risk factors not only in adolescent gambling but also in videogame playing (which shares many similarities with gambling). There appear to be three main forms of adolescent gambling that have been widely researched. Adolescent gambling activities and general risk factors in adolescent gambling are provided. As well, the influence of technology on adolescents in the form of both videogames and the Internet are examined. It is argued that technologically advanced forms of gambling may be highly appealing to adolescents.

negative: Competitive intelligence: construct exploration, validation and equivalence Purpose – Little empirical research has been conducted on competitive intelligence (CI). This paper aims to contribute to the quantitative strand of the CI literature by exploring and validating the theoretical constructs of the CI process. Design/methodology/approach – Data from 601 questionnaires filled out by South African and Flemish exporters were subjected to exploratory factor analysis and construct equivalence analysis between the sub-samples. Findings – The results showed that the CI process consists of three constructs, while the context in which CI takes place consists of four constructs. This agrees to some extent with the literature. When verifying the constructs for both cultures it was found that all but one CI context construct can be viewed as equivalent in both groups. Bias analysis identified one item in the questionnaire that was biased. Via regression analysis it was also indicated that the context in which CI takes place influences the CI process to a large extent. The research identified size as an important influencing factor in a business’ CI process. Practical implications – Businesses involved in CI should take note that an improvement in their formal infrastructure, employee involvement and internal information processes could enhance their CI capability. Originality/value – This paper contributes towards the formalising of the constructs of competitive intelligence.

negative: Empirical studies of software engineering: a roadmap In this article we summarize the strengths and weaknesses of empirical research in software engineering. We argue that in order to improve the current situation we must create better studies and draw more credible interpretations from them. We finally present a roadmap for this improvement, which includes a general structure for software empirical studies and concrete steps for achieving these goals: designing better studies, collecting data more effectively, and involving others in our empirical enterprises.

negative: Hidost: a static machine-learning-based detector of malicious files Malicious software, i.e., malware, has been a persistent threat in the information security landscape since the early days of personal computing. The recent targeted attacks extensively use non-executable malware as a stealthy attack vector. There exists a substantial body of previous work on the detection of non-executable malware, including static, dynamic, and combined methods. While static methods perform orders of magnitude faster, their applicability has been hitherto limited to specific file formats. This paper introduces Hidost, the first static machine-learning-based malware detection system designed to operate onmultiple file formats. Extending a previously published, highly effective method, it combines the logical structure of files with their content for even better detection accuracy. Our system has been implemented and evaluated on two formats, PDF and SWF (Flash). Thanks to its modular design and general feature set, it is extensible to other formats whose logical structure is organized as a hierarchy. Evaluated in realistic experiments on timestamped datasets comprising 440,000 PDF and 40,000 SWF files collected during several months, Hidost outperformed all antivirus engines deployed by the website VirusTotal to detect the highest number of malicious PDF files and ranked among the best on SWF malware.

negative: Thinking in circuits: toward neurobiological explanation in cognitive neuroscience Cognitive theory has decomposed human mental abilities into cognitive (sub) systems, and cognitive neuroscience succeeded in disclosing a host of relationships between cognitive systems and specific structures of the human brain. However, an explanation of why specific functions are located in specific brain loci had still been missing, along with a neurobiological model that makes concrete the neuronal circuits that carry thoughts and meaning. Brain theory, in particular the Hebb-inspired neurocybernetic proposals by Braitenberg, now offers an avenue toward explaining brain–mind relationships and to spell out cognition in terms of neuron circuits in a neuromechanistic sense. Central to this endeavor is the theoretical construct of an elementary functional neuronal unit above the level of individual neurons and below that of whole brain areas and systems: the distributed neuronal assembly (DNA) or thought circuit (TC). It is shown that DNA/TC theory of cognition offers an integrated explanatory perspective on brain mechanisms of perception, action, language, attention, memory, decision and conceptual thought. We argue that DNAs carry all of these functions and that their inner structure (e.g., core and halo subcomponents), and their functional activation dynamics (e.g., ignition and reverberation processes) answer crucial localist questions, such as why memory and decisions draw on prefrontal areas although memory formation is normally driven by information in the senses and in the motor system. We suggest that the ability of building DNAs/TCs spread out over different cortical areas is the key mechanism for a range of specifically human sensorimotor, linguistic and conceptual capacities and that the cell assembly mechanism of overlap reduction is crucial for differentiating a vocabulary of actions, symbols and concepts.

negative: Face, Age and Gender Recognition using Local Descriptors This thesis focuses on the area of face processing and aims at designing a reliable framework to facilitate face, age, and gender recognition. A Bag-of-Words framework has been optimized for the task of face recognition by evaluating different feature descriptors and different bag-of-words configurations. More specifically, we choose a compact set of features (e.g., descriptors, window locations, window sizes, dictionary sizes, etc.) in order to produce the highest possible rate of accuracy. Experiments on a challenging dataset shows that our framework achieves a better level of accuracy when compared to other popular approaches such as dimension reduction techniques, edge detection operators, and texture and shape feature extractors. The second contribution of this thesis is the proposition of a general framework for age and gender classification. Although the vast majority of the existing solutions focus on a single visual descriptor that often only encodes a certain characteristic of the image regions, this thesis aims at integrating multiple feature types. For this purpose, feature selection is employed to obtain more accurate and robust facial descriptors. Once descriptors have been computed, a compact set of features is chosen, which facilitates facial image processing for age and gender analysis. In addition to this, a new color descriptor (CLR-LBP) is proposed and the results obtained is shown to be comparable to those of other pre-existing color descriptors. The experimental results indicates that our age and gender framework outperforms other proposed methods when examined on two challenging databases, where face objects are present with different expressions and levels of illumination. This achievement demonstrates the effectiveness of our proposed solution and allows us to achieve a higher accuracy over the existing state-of-the-art methods.

negative: Mate choice decisions: the role of facial beauty For most people, facial beauty appears to play a prominent role in choosing a mate. Evidence from research on facial attractiveness indicates that physical beauty is a sexually selected trait mediated, in part, by pubertal facial hormone markers that signal important biological information about the displayer. Such signals would be ineffective if they did not elicit appropriate cognitive and/or emotional responses in members of the opposite sex. In this article, I argue that the effectiveness of these hormonal displays varies with perceivers' brains, which have been organized by the degree of steroid hormone exposure in the uterus, and activated by varying levels of circulating steroids following puberty. I further propose that the methodology used for examining mate choice decisions has general applicability for determining how cognitive and emotional evaluations enter into decision processes.

negative: International Telecommunication Union. Systems Management: Summarization function. Recommendation X.738 Prepaid mobile phone plans are gaining in importance in the U.S. and are already well established in Europe. Aggregation of a certain number of Micropayments is the preferred business model for wireless carriers to leverage the existing payment infrastructure with a mobile payment solution. There exist various Payment Scenarios that are based on the Wallet metaphor, and in general, they can be used to implement flexible and scalable solutions. Person-to-person transactions are already very popular in the U.S. as a consequence of the widespread use a payment instrument for auctions at eBay. This scenario is most often discussed as a valuable alternative to check payments in the U.S. For several reasons, the U.S. has been slower to adopt wireless technology than Europe. First, landlines in the U.S. are dominant and high personal computer penetration prevents people from using mobile phones to communicate, either by voice calls or text messaging. Second, prices in the U.S. favor landlines, even though prices for mobile phone plans in the competitive market have been cut many times in the past. For mobile payment, the fact that social patterns matter could affect the adoption of this form of payment in Europe, because in several countries, solutions already exist. The factors that form the concept of Diffusion of Innovation Theory eventually can be seen as the critical success factors of mobile payment. ii Whereas some emerging and existing mobile payment systems will come along with their own processing infrastructure, several will be based on existing payment networks that have initially been designed for another purpose. In Europe, credit card operators launch mobile payment solutions to leverage their existing networks while in the U.S., operators of ATM networks and leading credit card processors even try to bypass existing networks. Unlike in Europe, where checks have de facto been banned from the market by charging high prices for the processing of this non-cash payment instrument, the U.S. partly supports innovative check processing solutions to leverage the ACH infrastructure. The European bank approach shows that customer's payment behavior can be influenced by a pricing policy. Meanwhile, European countries and the U.S. have switched to 2.5G networks. With the transition to 3G, interoperability within the U.S. should finally become reality. Commercial launches of 3G services have already started in both regions. Notably, the first U.S. carrier to launch a broadband wireless service seems to be attracting business customers and offering high …

negative: 154-2008: Understanding Your Customer: Segmentation Techniques for Gaining Customer Insight and Predicting Risk in the Telecom Industry The explosion of customer data in the last twenty years has increased the need for data mining aimed at customer relationship management (CRM) and understanding the customer. It is well known that the telecom sector consists of customers with a wide array of customer behaviors. These customers pose different risks, making it imperative to implement different treatment strategies to maximize shareholder profit and improve revenue generation. Segmentation is the process of developing meaningful customer groups that are similar based on individual account characteristics and behaviors. The goal of segmentation is to know your customer better and to apply that knowledge to increase profitability, reduce operational cost, and enhance customer service. Segmentation can provide a multidimensional view of the customer for better treatment targeting. An improved understanding of customer risk and behaviors enables more effective portfolio management and the proactive application of targeted treatments to lift account profitability. In this paper we outline several segmentation techniques using SAS Enterprise MinerTM. INTRODUCTION Rapid advances in computer technology and an explosion of data collection systems over the last thirty years make it more critical for business to understand their customers. Companies employing data driven analytical strategies often enjoy a competitive advantage. Many organizations across several industries widely employ analytical models to gain a better understanding of their customers. They use these models to predict a wide array of events such as behavioral risk, fraud, or the likelihood of response. Regardless of the predictive variable, a single model may not perform optimally across the target population because there may be distinct segments with different characteristics inherent in the population. Segmentation may be done judgmentally based on experience, but such segmentation schema is limited to the use of only a few variables at best. True multivariate segmentation with the goal of identifying the different segments in your population is best achieved through the use of cluster analysis. Clustering and profiling of the customer base can answer the following questions: ♦ Who are my customers? ♦ How profitable are my customers? ♦ Who are my least profitable customers? ♦ Why are my customers leaving? ♦ What do my best customers look like? This paper discusses the use of SAS Enterprise Miner to segment a population of customers using cluster analysis and decision trees. Focus is placed on the methodology rather than the results to ensure the integrity and confidentiality of customer data. Other statistical strategies are presented in this paper which could be employed in the pursuit of further customer intelligence. It has been said that statistical cluster analysis is as much art as it is science because it is performed without the benefit of well established statistical criteria. Data Mining and Predictive Modeling SAS Global Forum 2008

negative: Consumer Decision Making in Online Shopping Environments: The Effects of Interactive Decision Aids Despite the explosive growth of electronic commerce and the rapidly increasing number of consumers who use interactive media (such as the World Wide Web) for prepurchase information search and online shopping, very little is known about how consumers make purchase decisions in such settings. A unique characteristic of online shopping environments is that they allow vendors to create retail interfaces with highly interactive features. One desirable form of interactivity from a consumer perspective is the implementation of sophisticated tools to assist shoppers in their purchase decisions by customizing the electronic shopping environment to their individual preferences. The availability of such tools, which we refer to as interactive decision aids for consumers, may lead to a transformation of the way in which shoppers search for product information and make purchase decisions. The primary objective of this paper is to investigate the nature of the effects that interactive decision aids may have on consumer decision making in online shopping environments. While making purchase decisions, consumers are often unable to evaluate all available alternatives in great depth and, thus, tend to use two-stage processes to reach their decisions. At the first stage, consumers typically screen a large set of available products and identify a subset of the most promising alternatives. Subsequently, they evaluate the latter in more depth, perform relative comparisons across products on important attributes, and make a purchase decision. Given the different tasks to be performed in such a two-stage process, interactive tools that provide support to consumers in the following respects are particularly valuable: (1) the initial screening of available products to determine which ones are worth considering further, and (2) the in-depth comparison of selected products before making the actual purchase decision. This paper examines the effects of two decision aids, each designed to assist consumers in performing one of the above tasks, on purchase decision making in an online store. The first interactive tool, a recommendation agent (RA), allows consumers to more efficiently screen the (potentially very large) set of alternatives available in an online shopping environment. Based on self-explicated information about a consumer’s own utility function (attribute importance weights and minimum acceptable attribute levels), the RA generates a personalized list of recommended alternatives. The second decision aid, a comparison matrix (CM), is designed to help consumers make in-depth comparisons among selected alternatives. The CM allows consumers to organize attribute information about multiple products in an alternatives attributes matrix and to have alternatives sorted by any attribute. Based on theoretical and empirical work in marketing, judgment and decision making, psychology, and decision support systems, we develop a set of hypotheses pertaining to the effects of these two decision aids on various aspects of consumer decision making. In particular, we focus on how use of the RA and CM affects consumers’ search for product information, the size and quality of their consideration sets, and the quality of their purchase decisions in an online shopping environment. A controlled experiment using a simulated online store was conducted to test the hypotheses. The results indicate that both interactive decision aids have a substantial impact on consumer decision making. As predicted, use of the RA reduces consumers’ search effort for product information, decreases the size but increases the quality of their consideration sets, and improves the quality of their purchase decisions. Use of the CM also leads to a decrease in the size but an increase in the quality of consumers’ consideration sets, and has a favorable effect on some indicators of decision quality. In sum, our findings suggest that interactive tools designed to assist consumers in the initial screening of available alternatives and to facilitate in-depth comparisons among selected alternatives in an online shopping environment may have strong favorable effects on both the quality and the efficiency of purchase decisions—shoppers can make much better decisions while expending substantially less effort. This suggests that interactive decision aids have the potential to drastically transform the way in which consumers search for product information and make purchase decisions. (Decision Making; Online Shopping; Electronic Commerce; Decision Aids; Recommendation Agents; Consumer Behavior; Information Search; Consideration Sets; Information Processing)

negative: FACTORS INFLUENCING CONSUMERS ’ ATTITUDE TOWARDS E-COMMERCE PURCHASES THROUGH ONLINE SHOPPING Online shopping is the process of buying goods and services from merchants who sell on the internet. Shoppers can visit web stores from the comfort of their homes and shop as they sit in front of the computer. The main purpose of this study is to determine the factors influencing consumers’ attitude towards e-commerce purchases through online shopping. The study also investigate how socio-demographic (age, income and occupation), pattern of online buying (types of goods, e-commerce experience and hours use on internet) and purchase perception (product perception, customers’ service and consumers’ risk) affect consumers’ attitude towards online shopping. Convenience sampling method was conducted in this study and the sample comparison of 100 respondents in Taman Tawas Permai, Ipoh. Data were collected via self-administered questionnaire which contains 15 questions in Part A (respondents’ background and their pattern of using internet and online buying), 34 questions in Part B (attitude towards online purchase) and 36 questions in Part C (purchase perception towards online shopping). One-way ANOVA were used to assess the differences between independent variable such as age, income, occupation and pattern of online buying (type of goods) and dependant variable such as attitude towards online shopping. The findings revealed that there is no significant difference in attitude towards online shopping among age group (F = 1.020, p < 0.05) but there is a significant difference in attitude towards online shopping among income group (F = 0.556, p > 0.05). The research finding also showed that there is no significant difference in attitude towards online shopping among occupation group (F = 1.607, p < 0.05) and types of goods group (F = 1.384, p < 0.05). Pearson’s correlation were used to assess the relationship between independent variable such as e-commerce experience, hours spent on internet, product perception, customers’ service and consumers’ risk and dependant variable such as attitude towards online shopping. The findings revealed that there is a significant relationship between e-commerce experience and attitude towards online shopping among the respondents (r = -0.236**, p < 0.05). However, there is no significant relationship between hours spent on internet and attitude towards online shopping among the respondents (r = 0.106, p > 0.05). This study also indicated that there is a significant relationship between product perception and attitude towards online shopping among the respondents (r = 0.471**, p < 0.01) and there is also a significant relationship between customers’ service and attitude towards online shopping among the respondents (r = 0.459**, p < 0.01). Lastly, this result showed that there is no significant relationship between consumers’ risk and attitude towards online shopping among the respondents (r = 0.153, p > 0.05). Further study should explore other factors that influencing consumers’ attitude towards e-commerce purchases through online shopping with a broader range of population and high representative sampling method.

negative: LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection Mechanical devices such as engines, vehicles, aircrafts, etc., are typically instrumented with numerous sensors to capture the behavior and health of the machine. However, there are often external factors or variables which are not captured by sensors leading to time-series which are inherently unpredictable. For instance, manual controls and/or unmonitored environmental conditions or load may lead to inherently unpredictable time-series. Detecting anomalies in such scenarios becomes challenging using standard approaches based on mathematical models that rely on stationarity, or prediction models that utilize prediction errors to detect anomalies. We propose a Long Short Term Memory Networks based Encoder-Decoder scheme for Anomaly Detection (EncDec-AD) that learns to reconstruct ‘normal’ time-series behavior, and thereafter uses reconstruction error to detect anomalies. We experiment with three publicly available quasi predictable time-series datasets: power demand, space shuttle, and ECG, and two realworld engine datasets with both predictive and unpredictable behavior. We show that EncDecAD is robust and can detect anomalies from predictable, unpredictable, periodic, aperiodic, and quasi-periodic time-series. Further, we show that EncDec-AD is able to detect anomalies from short time-series (length as small as 30) as well as long time-series (length as large as 500).

negative: E-shopping in a multiple channel environment 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

negative: Cloning Cryptographic RFID We develop a new, custom-built hardware for emulating contactless smartcards compliant to ISO 14443. The device is based on a modern low-cost microcontroller and can support basically all relevant (cryptographic) protocols used by contactless smartcards today, e.g., those based on AES or Triple-DES. As a proof of concept, we present a full emulation of Mifare Classic cards on the basis of our highly optimized implementation of the stream cipher Crypto1. The implementation enables the creation of exact clones of such cards, including the UID. We furthermore reverse-engineered the protocol of DESFire EV1 and realize the first emulation of DESFire and DESFire EV1 cards in the literature. We practically demonstrate the capabilities of our emulator by spoofing several real-world systems, e.g., creating a contactless payment card which allows an attacker to set the stored credit balance as desired and hence make an infinite amount of payments.