title: On the derivation of coseismic displacement fields using differential radar interferometry: The Landers earthquake

text: We present a map of the coseismic displacement field resulting from the Landers, California, June 28, 1992, earthquake derived using data acquired from an orbiting high-resolution radar system. We achieve results more accurate than previous space studies and similar in accuracy to those obtained by conventional field survey techniques. Data from the ERS 1 synthetic aperture radar instrument acquired in April, July, and August 1992 are used to generate a high-resolution, wide area map of the displacements. The data represent the motion in the direction of the radar line of sight to centimeter level precision of each 30-m resolution element in a 113 km by 90 km image. Our coseismic displacement contour map gives a lobed pattern consistent with theoretical models of the displacement field from the earthquake. Fine structure observed as displacement tiling in regions several kilometers from the fault appears to be the result of local surface fracturing. Comparison of these data with Global Positioning System and electronic distance measurement survey data yield a correlation of 0.96; thus the radar measurements are a means to extend the point measurements acquired by traditional techniques to an area map format. The technique we use is (1) more automatic, (2) more precise, and (3) better validated than previous similar applications of differential radar interferometry. Since we require only remotely sensed satellite data with no additional requirements for ancillary information, the technique is well suited for global seismic monitoring and analysis.


title: Accuracy of topographic maps derived from ERS-1 interferometric radar

text: A interferometric radar technique for topographic mapping of surfaces promises a high-resolution approach to the generation of digital elevation models. We present here analyses of data collected by the synthetic aperture radar instrument on-board the ERS-1 satellite on successive orbits. Use of a single satellite in a nearly repeating orbit is attractive for reducing cost and spaceborne hardware complexity; also it permits inference of changes in the surface from the correlation properties of the radar echoes. The data have been reduced to correlation maps and digital elevation models. The correlation maps show that temporal correlation decreases significantly with time, but not necessarily at a constant well-defined rate, likely depending on environmental factors. When correlation among passes remains high, however, it is possible to form digital elevation models. Analyses of noise expected in ERS-1 interferometric data collected over Alaska and the southwestern United States indicate that maps with relative errors less than 5 m rms are possible in some regions. However, orbit uncertainties imply that tie points are required in order to reduce absolute height errors to a similar magnitude. We find that about 6 tie points per 40 X 40 km scene with 5 m rms or better height accuracy are needed to keep systematic map height errors below 5 m rms. The performance of the ERS-1 radar system for topographic applications, though useful for a variety of regional and local discipline studies, may be improved with respect to temporal decorrelation errors and absolute height acuity by modifying the orbit repeat period and incorporating precise orbit determination techniques. The resulting implementation will meet many, but not all, objectives of a global mapping mission.


title: Satellite radar interferometry for monitoring ice sheet motion: application to an antarctic ice stream.

text: Satellite radar interferometry (SRI) provides a sensitive means of monitoring the flow velocities and grounding-line positions of ice streams, which are indicators of response of the ice sheets to climatic change or internal instability. The detection limit is about 1.5 millimeters for vertical motions and about 4 millimeters for horizontal motions in the radar beam direction. The grounding line, detected by tidal motions where the ice goes afloat, can be mapped at a resolution of approximately 0.5 kilometer. The SRI velocities and grounding line of the Rutford Ice Stream, Antarctica, agree fairly well with earlier ground-based data. The combined use of SRI and other satellite methods is expected to provide data that will enhance the understanding of ice stream mechanics and help make possible the prediction of ice sheet behavior.


title: Towards the enhancement of e-democracy: identifying the notion of the 'middleman paradox'

text: The challenge towards e-democracy, through the electronic transformation of political systems, has become increasingly evident within developed economies. It is regarded as an approach for increased and better quality citizen participation in the democratic processes. E-democracy forms a component of overall e-government initiatives where technology adoption and diffusion, to enhance wider access to, and the delivery of, government services, are apparent. However, previous research demonstrates that very few e-democracy proposals survive the stage of formal political decision-making to become substantive egovernment projects within national or international agendas. Furthermore, the implementation of e-democracy projects is undertaken at a much slower pace and with dramatically less support than the implementation of other, so-called e-administration, activities in the public sector. The research in this paper considers the notion of the ‘middleman paradox’, presenting theoretical and empirical evidence that further investigates the phenomenon associated with potential e-democracy improvements. Specifically, the paper adds a new dimension to existing theories on the hesitant evolution of e-democracy that clearly identifies politicians as an inhibiting factor. Proposals are made for an enhancement of these processes, and suggestions for further applicable research are demonstrated.


title: Burden of Depressive Disorders by Country, Sex, Age, and Year: Findings from the Global Burden of Disease Study 2010

text:
BACKGROUND
Depressive disorders were a leading cause of burden in the Global Burden of Disease (GBD) 1990 and 2000 studies. Here, we analyze the burden of depressive disorders in GBD 2010 and present severity proportions, burden by country, region, age, sex, and year, as well as burden of depressive disorders as a risk factor for suicide and ischemic heart disease.

METHODS AND FINDINGS
Burden was calculated for major depressive disorder (MDD) and dysthymia. A systematic review of epidemiological data was conducted. The data were pooled using a Bayesian meta-regression. Disability weights from population survey data quantified the severity of health loss from depressive disorders. These weights were used to calculate years lived with disability (YLDs) and disability adjusted life years (DALYs). Separate DALYs were estimated for suicide and ischemic heart disease attributable to depressive disorders. Depressive disorders were the second leading cause of YLDs in 2010. MDD accounted for 8.2% (5.9%-10.8%) of global YLDs and dysthymia for 1.4% (0.9%-2.0%). Depressive disorders were a leading cause of DALYs even though no mortality was attributed to them as the underlying cause. MDD accounted for 2.5% (1.9%-3.2%) of global DALYs and dysthymia for 0.5% (0.3%-0.6%). There was more regional variation in burden for MDD than for dysthymia; with higher estimates in females, and adults of working age. Whilst burden increased by 37.5% between 1990 and 2010, this was due to population growth and ageing. MDD explained 16 million suicide DALYs and almost 4 million ischemic heart disease DALYs. This attributable burden would increase the overall burden of depressive disorders from 3.0% (2.2%-3.8%) to 3.8% (3.0%-4.7%) of global DALYs.

CONCLUSIONS
GBD 2010 identified depressive disorders as a leading cause of burden. MDD was also a contributor of burden allocated to suicide and ischemic heart disease. These findings emphasize the importance of including depressive disorders as a public-health priority and implementing cost-effective interventions to reduce its burden. Please see later in the article for the Editors' Summary.


title: Enhance emotional and social adaptation skills for children with autism spectrum disorder: A virtual reality enabled approach

text: Deficits in social-emotional reciprocity, one of the diagnostic criteria of Autism Spectrum Disorder (ASD), greatly hinders children with ASD from responding appropriately and adapting themselves in various social situations. Although evidences have shown that virtual reality environment is a promising tool for emotional and social adaptation skills training on ASD population, there is a lack of large-scale trials with intensive evaluations to support such findings. This paper presents a virtual reality enabled program for enhancing emotional and social adaptation skills for children with ASD. Six unique learning scenarios, of which one focuses on emotion control and relaxation strategies, four that simulate various social situations, and one that facilitates consolidation and generalization, are designed and developed with corresponding psychoeducation procedures and protocols. The learning scenarios are presented to the children via a 4-side immersive virtual reality environment (a.k.a., half-CAVE) with non-intrusive motion tracking. A total number of 94 children between the ages of 6 to 12 with clinical diagnosis of ASD participated in the 28-session program that lasted for 14 weeks. By comparing preand post-assessments, results reported in this paper show significant improvements in the project’s primary measures on children’s emotion expression and regulation and social-emotional reciprocity but not on other secondary measures.


title: Real time Sign Language Recognition using PCA

text: The Sign Language is a method of communication for deaf-dumb people. This paper presents the Sign Language Recognition system capable of recognizing 26 gestures from the Indian Sign Language by using MATLAB. The proposed system having four modules such as: pre-processing and hand segmentation, feature extraction, sign recognition and sign to text and voice conversion. Segmentation is done by using image processing. Different features are extracted such as Eigen values and Eigen vectors which are used in recognition. The Principle Component Analysis (PCA) algorithm was used for gesture recognition and recognized gesture is converted into text and voice format. The proposed system helps to minimize communication barrier between deaf-dumb people and normal people.


title: Noninvasive diagnosis of fetal aneuploidy by shotgun sequencing DNA from maternal blood.

text: We directly sequenced cell-free DNA with high-throughput shotgun sequencing technology from plasma of pregnant women, obtaining, on average, 5 million sequence tags per patient sample. This enabled us to measure the over- and underrepresentation of chromosomes from an aneuploid fetus. The sequencing approach is polymorphism-independent and therefore universally applicable for the noninvasive detection of fetal aneuploidy. Using this method, we successfully identified all nine cases of trisomy 21 (Down syndrome), two cases of trisomy 18 (Edward syndrome), and one case of trisomy 13 (Patau syndrome) in a cohort of 18 normal and aneuploid pregnancies; trisomy was detected at gestational ages as early as the 14th week. Direct sequencing also allowed us to study the characteristics of cell-free plasma DNA, and we found evidence that this DNA is enriched for sequences from nucleosomes.


title: Design and Implementation of Phalanges Based on Iteration of a Prosthesis

text: In this work an electromechanical hand is implemented based on the study and implementation of the phalanges of the five fingers of the hand, a control system based on a microcontroller was implemented that takes as feedback signals coming from flexosensors and strain gauges. The movement of the fingers was made based on myoelectric signals in real time, these signals were acquired through an innovative method of acquisition based on patterns. The tests performed were measurements with extended hand, closed hand and pressing an object that validates the present proposal.


title: Resilience and Sustainable Development : Theory of resilience , systems thinking and adaptive governance

text:  Basic information on SD  Country profiles  Quarterly reports  Policy briefs  Case studies  Conference papers  Workshop papers  Getting in touch with us The European Sustainable Development Network (ESDN) is an informal network of public administrators and other experts who deal with sustainable development strategies and policies. The network covers all 27 EU Member States, plus other European countries. The ESDN is active in promoting sustainable development and facilitating the exchange of good practices in Europe and gives advice to policy-makers at the European and national levels. This ESDN Quarterly Report (QR) provides a condensed overview of the concept of resilience. Despite the complexity of the theory behind resilience, this QR tries to communicate the main notions behind this concept in a way that is understandable and not overly technical. The intention of this QR is to serve as a guide through the concept of resilience. The report does not aim at being exhaustive but intends to provide an overview on the links which are particularly relevant for sustainable development (SD) in general and SD governance in particular. A multitude of diverse sources have been used, mainly from the academic literature. It has to be mentioned the significant and decisive role that the Resilience Alliance has in providing extensive knowledge: the website that they are running, is an exceptionally good source of information for those who are interested and want to deepen their knowledge of resilience. Additionally, among all the scientific publications cited throughout the report, a special mention goes to the book by Walker and Salt (2006) entitled " Resilience thinking: sustaining ecosystems and people in a changing world " , which is very much suggested as a practical source of information on resilience. As a first chapter, an executive summary is provided with a short overview of the report with the essential notions that are depicted throughout the QR. The second chapter then introduces the concept of resilience and gives an extensive background on the notions behind it. It intends to provide guidance, especially to understand the linkages between the concept of resilience and sustainable development, and the importance of resilience and systems thinking for policy-makers and for those who work on SD governance. The third chapter summarizes the relationships among resilience, society, governance and policy. Therefore, the concept of 'adaptive governance' is advanced as a more appropriate way to deal with …


title: GRID-CLUSTERING: A FAST HIERARCHICAL CLUSTERING METHOD FOR VERY LARGE DATA SETS

text: This paper presents a new approach to hierarchical clustering of very large data sets, named GridClustering. The method organizes unlike the conventional methods the space surrounding the patterns and not the patterns. It uses a multidimensional grid data structure. The resulting block partitioning of the value space is clustered via a topological neighbor search. The Grid-Clustering method is able to deliver structural pattern distribution information for very large data sets. It superceeds all conventional hierarchical algorithms in runtime behavior and memory space requirements. The algorithm was analyzed within a testbed and suitable values for the tunable parameters of the algorithm are proposed. A comparison of the executions times to other commonly used clustering algorithms and a heuristic runtime analysis is given.


title: Optimal Parallel Algorithms for Computing the Sum, the Prefix-Sums, and the Summed Area Table on the Memory Machine Models

text: The main contribution of this paper is to show optimal parallel algorithms to compute the sum, the prefix-sums, and the summed area table on two memory machine models, the Discrete Memory Machine (DMM) and the Unified Memory Machine (UMM). The DMM and the UMM are theoretical parallel computing models that capture the essence of the shared memory and the global memory of GPUs. These models have three parameters, the number p of threads, and the width w of the memory, and the memory access latency l. We first show that the sum of n numbers can be computed in O(n w + nl p + l log n) time units on the DMM and the UMM. We then go on to show that Ω(n w + nl p + l log n) time units are necessary to compute the sum. We also present a parallel algorithm that computes the prefix-sums of n numbers in O( n w + nl p + l log n) time units on the DMM and the UMM. Finally, we show that the summed area table of size √ n × √n can be computed in O( n w + nl p + l log n) time units on the DMM and the UMM. Since the computation of the prefix-sums and the summed area table is at least as hard as the sum computation, these parallel algorithms are also optimal. key words: Memory machine models, prefix-sums computation, parallel algorithm, GPU, CUDA


title: From checking on to checking in: designing for low socio-economic status older adults

text: In this paper we describe the design evolution of a novel technology that collects and displays presence information to be used in the homes of older adults. The first two iterations, the Ambient Plant and Presence Clock, were designed for higher socio-economic status (SES) older adults, whereas the Check-In Tree was designed for low SES older adults. We describe how feedback from older adult participants drove our design decisions, and give an in-depth account of how the Check-In Tree evolved from concept to a final design ready for in situ deployment.


title: Design of dual-polarized waveguide slotted antenna array for Ka-band application

text: A dual polarized waveguide slotted array for Ka band application is designed. Vertical polarization (VP) is realized by longitudinal slots on broad wall of the ridge waveguide sub array, while horizontal polarization (HP) is realized by tilted slot pairs in the narrow wall of the rectangular waveguide sub array. The feed networks are also designed for each polarization. Especially that for VP, a method to improve the coupling is presented. The antenna has low cross-polarization level and high degree of isolation between two ports.


title: Analysis and Support of Lifestyle via Emotions Using Social Media

text: Using recent insights from Cognitive, Affective and Social Neuroscience this paper addresses how affective states in social interactions can be used through social media to analyze and support behaviour for a certain lifestyle. A computational model is provided integrating mechanisms for the impact of one’s emotions on behaviour, and for the impact of emotions of others on one’s own emotion. The model is used to reason about and assess the state of a user with regard to a lifestyle goal (such as exercising frequently), based on extracted information about emotions exchanged in social interaction. Support is provided by proposing ways to affecting these social interactions, thereby indirectly influencing the impact of the emotions of others. An ambient intelligent system incorporating this has been implemented for the social medium Twitter.


title: Is Proof More Cost-Effective Than Testing?

text: ÐThis paper describes the use of formal development methods on an industrial safety-critical application. The Z notation was used for documenting the system specification and part of the design, and the SPARK subset of Ada was used for coding. However, perhaps the most distinctive nature of the project lies in the amount of proof that was carried out: proofs were carried out both at the Z levelÐapproximately 150 proofs in 500 pagesÐand at the SPARK code levelÐapproximately 9,000 verification conditions generated and discharged. The project was carried out under UK Interim Defence Standards 00-55 and 00-56, which require the use of formal methods on safety-critical applications. It is believed to be the first to be completed against the rigorous demands of the 1991 version of these standards. The paper includes comparisons of proof with the various types of testing employed, in terms of their efficiency at finding faults. The most striking result is that the Z proof appears to be substantially more efficient at finding faults than the most efficient testing phase. Given the importance of early fault detection, we believe this helps to show the significant benefit and practicality of large-scale proof on projects of this kind. Index TermsÐSafety-critical software, formal specification, SPARK, specification proof, code proof, proof vs. testing, industrial case study.


title: An Immune Genetic Algorithm for Software Test Data Generation

text: This paper aims at incorporating immune operators in genetic algorithms as an advanced method for solving the problem of test data generation. The new proposed hybrid algorithm is called immune genetic algorithm (IGA). A full description of this algorithm is presented before investigating its application in the context of software test data generation using some benchmark programs. Moreover, the algorithm is compared with other evolutionary algorithms.


title: High speed and low power preset-able modified TSPC D flip-flop design and performance comparison with TSPC D flip-flop

text: Positron emission tomography (PET) is a nuclear functional imaging technique that produces a three-dimensional image of functional organs in the body. PET requires high resolution, fast and low power multichannel analog to digital converter (ADC). A typical multichannel ADC for PET scanner architecture consists of several blocks. Most of the blocks can be designed by using fast, low power D flip-flops. A preset-able true single phase clocked (TSPC) D flip-flop shows numerous glitches (noise) at the output due to unnecessary toggling at the intermediate nodes. Preset-able modified TSPC (MTSPC) D flip-flop have been proposed as an alternative solution to alleviate this problem. However, the MTSPC D flip-flop requires one extra PMOS to suspend toggling of the intermediate nodes. In this work, we designed a 7-bit preset-able gray code counter by using the proposed D flip-flop. This work involves UMC 180 nm CMOS technology for preset-able 7-bit gray code counter where we achieved 1 GHz maximum operation frequency with most significant bit (MSB) delay 0.96 ns, power consumption 244.2 μW (micro watt) and power delay product (PDP) 0.23 pJ (Pico joule) from 1.8 V power supply.


title: Multifocal planes head-mounted displays.

text: Stereoscopic head-mounted displays (HMD's) provide an effective capability to create dynamic virtual environments. For a user of such environments, virtual objects would be displayed ideally at the appropriate distances, and natural concordant accommodation and convergence would be provided. Under such image display conditions, the user perceives these objects as if they were objects in a real environment. Current HMD technology requires convergent eye movements. However, it is currently limited by fixed visual accommodation, which is inconsistent with real-world vision. A prototype multiplanar volumetric projection display based on a stack of laminated planes was built for medical visualization as discussed in a paper presented at a 1999 Advanced Research Projects Agency workshop (Sullivan, Advanced Research Projects Agency, Arlington, Va., 1999). We show how such technology can be engineered to create a set of virtual planes appropriately configured in visual space to suppress conflicts of convergence and accommodation in HMD's. Although some scanning mechanism could be employed to create a set of desirable planes from a two-dimensional conventional display, multiplanar technology accomplishes such function with no moving parts. Based on optical principles and human vision, we present a comprehensive investigation of the engineering specification of multiplanar technology for integration in HMD's. Using selected human visual acuity and stereoacuity criteria, we show that the display requires at most 27 equally spaced planes, which is within the capability of current research and development display devices, located within a maximal 26-mm-wide stack. We further show that the necessary in-plane resolution is of the order of 5 microm.


title: The dynamic kinetochore-microtubule interface.

text: The kinetochore is a control module that both powers and regulates chromosome segregation in mitosis and meiosis. The kinetochore-microtubule interface is remarkably fluid, with the microtubules growing and shrinking at their point of attachment to the kinetochore. Furthermore, the kinetochore itself is highly dynamic, its makeup changing as cells enter mitosis and as it encounters microtubules. Active kinetochores have yet to be isolated or reconstituted, and so the structure remains enigmatic. Nonetheless, recent advances in genetic, bioinformatic and imaging technology mean we are now beginning to understand how kinetochores assemble, bind to microtubules and release them when the connections made are inappropriate, and also how they influence microtubule behaviour. Recent work has begun to elucidate a pathway of kinetochore assembly in animal cells; the work has revealed that many kinetochore components are highly dynamic and that some cycle between kinetochores and spindle poles along microtubules. Further studies of the kinetochore-microtubule interface are illuminating: (1) the role of the Ndc80 complex and components of the Ran-GTPase system in microtubule attachment, force generation and microtubule-dependent inactivation of kinetochore spindle checkpoint activity; (2) the role of chromosomal passenger proteins in the correction of kinetochore attachment errors; and (3) the function of microtubule plus-end tracking proteins, motor depolymerases and other proteins in kinetochore movement on microtubules and movement coupled to microtubule poleward flux.


title: Active compensation of current unbalance in paralleled silicon carbide MOSFETs

text: Current unbalance in paralleled power electronic devices can affect the performance and reliability of them. In this paper, the factors causing current unbalance in parallel connected silicon carbide (SiC) MOSFETs are analyzed, and the threshold mismatch is identified as the major factor. Then the distribution and temperature dependence of SiC MOSFETs' threshold voltage are studied experimentally. Based on the analysis and study, an active current balancing (ACB) scheme is presented. The scheme directly measures the unbalance current, and eliminates it in closed loop by varying the gate delay to each device. The turn-on and turn-off current unbalance are sensed and independently compensated to yield an optimal performance at both switching transitions. The proposed scheme provides robust compensation of current unbalance in fast-switching wide-band-gap devices while keeping circuit complexity and cost low. The performance of the proposed ACB scheme is verified by both simulation and experimental results.


title: Assessing The Impact Of Gender And Personality On Film Preferences

text: In this paper, the impact of gender and Big Five personality factors (Openness, Conscientiousness, Extraversion, Agreeableness and Neuroticism) on visual media preferences (for comedy, horror, action, romance and fantasy film genres) was examined. The analyses were carried out using data collected by Stillwell’s (2007) myPersonality application on Facebook; and focused on a sub-sample of British residents aged 16-25 (n=29,197). It was confirmed that females prefer romantic films, whereas males favour action films. As predicted, there was also a marked interaction between gender and personality characteristics: females score higher on Neuroticism and Agreeableness than males. Individuals scoring high on the dimension of Openness were more likely to prefer comedy and fantasy films than romantic films. Conscientious individuals were more inclined to enjoy action and romance genres. Individuals scoring high on Neuroticism tended to prefer romantic films. Finally, significant interactions were noted between gender and Openness with regard to preferences for comedy, action and romance genres. Overall, it is certain that the combination of gender and Big Five personality factors contributes substantially to an understanding of people’s film preferences. GENDER, PERSONALITY AND FILM PREFERENCES 3 Assessing the impact of Gender and Personality on Film Preferences Do comedies have a sexually differentiated public? Are males and females who enjoy horror films similar in terms of personality? Regardless of gender, do personality characteristics influence preference for the fantasy genre? In the present study, we have attempted to provide a meaningful answer to the aforementioned set of questions, based on the analysis of gender and personality interactions with regard to film preferences. In an attempt to complement previous research findings, we focused our analysis on the role of sex and personality in film preferences for British Facebook users aged 16-25. We paid attention to their scores on online Big Five personality questionnaires and their stated gender, using both single and multivariate measures to relate the two variables to film preferences, also listed on their profiles. The following hypotheses were tested: 1. Females and males differ with regard to film preferences. 2. Personality characteristics differ according to gender. 3. Film preferences vary in accordance with personality characteristics. 4. There is a significant interaction between gender and personality with regard to film preferences. the explanatory potential of online social networks Online social networks are mass repositories of valuable social and psychological information for researchers. Facebook, ranked as the most popular social network by worldwide monthly users, hosts for instance more than 400 million user profiles, in which individuals’ number of friends, media content preferences and socio-demographic background– amongst other things are displayed. Their systematic use for data collection purposes is a relatively recent trend in social psychological research; Stillwell’s creation of the myPersonality application (2007) on Facebook is a striking exemplar of the considerable explanatory potential of those online social networks. With myPersonality, users can take an online version of the Big Five personality questionnaire and agree to share their profile information for research purposes. As such, users’ personalities can be matched to any other single or collection of individual information available on Facebook, opening up an array of possible areas of investigation. GENDER, PERSONALITY AND FILM PREFERENCES 4 the predominance of visual media The appeal of visual media is easily demonstrated in terms of the importance it has in the lives of most individuals. Data from the National Survey of Culture, Leisure and Sport (2007) indicates that watching television is the most common leisure activity for over eight out of ten men and women in England, taking precedence over spending time with friends and family, sport, etc. Another intriguing finding relates to TV and movie watching online: the number of Britons visiting such websites reached 21 million in 2007. Although it is clear that many people enjoy visual media offerings, it is much more difficult to pinpoint the specific viewer characteristics that predict genre enjoyment. In other words, who prefers which type of content? visual media content: an explanation of viewer preferences Initially the domain of inquiry of communication theorists, media preferences and their determinants are increasingly studied from the vantage point of a variety of disciplines, amongst which psychology and sociology feature predominantly (Kraaykamp et al, 2005). Their combined explanatory potential finds its articulation in the uses and gratification approach (Blumler & Katz, 1974; Rosengreen & Windhal, 1989), according to which preferences for specific media and/or specific content result from an individual’s psychological and social attributes. gender differences in media content preferences Research on media preferences has paid notable attention to sex differences in responses to different types of film. It has been established that various movie genres elicit differentiated affective responses between the two sexes. Rather interestingly, the widespread gender – stereotyping running through entertainment products seems to correspond to actual viewer preferences. Males indeed prefer action/adventure genres typically associated with the masculine sex, whilst females have a soft spot for romance/drama. Oliver et al. (2000) point to the explanatory potential of differential gender-linked expectations, which can be conceptualized along two dimensions: (1) communality, typically associated with females and (2) agency, often associated with males (Eagly, 1987). Depending on whether they are communal or agency-consistent, the themes preponderant in each genre make up for a sexually differentiated public. A number of studies highlighted the importance of sex in social affiliation with media characters: viewers tend to affiliate more strongly with and GENDER, PERSONALITY AND FILM PREFERENCES 5 experience more intense emotional responses to same-sex characters (e.g. Deutsch, 1975; Hoffner & Cantor, 1991). Another potential explanation is that of sex differences in mean personality levels, which remain fairly constant across the lifespan (Feingold, 1994; McCrae & Costa, 1984). personality differences in media preferences Theorists have also focused considerable attention on the role of personality characteristics in modern mass communication theory (Blumler & Katz, 1974; Wober, 1986). In most personality/media use models, personality is conceptualized as the nexus of attitudes, beliefs and values that guide one’s cognitive and affective interactions with the social environment (Weaver et al, 1993). Personality characteristics are thus believed to influence media preferences, which are essentially evaluative judgements pertaining to the gratifications consumers anticipate from their interaction with the media (Palmgreen, 1984). The Big Five framework of personality is most frequently employed by researchers seeking to demonstrate empirical connections between media gratifications and their psychological roots (e.g. Kraaykamp, 2001; Kraaykamp et al, 2005). It includes the following domains: Openness (traits like originality and open-mindedness), Conscientiousness (traits like hardworking and orderly), Extraversion (traits like energetic and sociable), Agreeableness (traits like affectionate and considerate) and Neuroticism (traits like nervous and tense) (Donellan & Lucas, 2008). With regard to media preferences, individuals scoring high on the dimension of Openness seem to prefer original and serious media content, whilst conscientious individuals like predictable and structured formats (Kraaykamp et al, 2005). The findings for extroverts are less straightforward: they seemingly favour sensory stimulation because of relatively high arousal levels (Costa & McCrae, 1988). Agreeableness appears to be the second most important personality trait, after Openness, in predicting visual preferences. Friendly individuals tend to watch popular content, devoid of upsetting and unconventional images (Kraykaamp, 2001). Finally, emotionally unstable individuals are thought to find easy means of escape from feelings of tension and stress in watching TV (Conway & Rubin, 1991). Most studies on personality effects in media preferences tend to either overlook or control for participants’ gender (e.g. Weaver et al, 1993; Kraaykamp, 2001). As a result, it is difficult to tell in the former case whether the differentiated association between media GENDER, PERSONALITY AND FILM PREFERENCES 6 preferences and personality characteristics is partially caused by the fact that personality traits differ systematically between people of different sexes (Kraaykamp & Van Eijck, 2005). The latter design precludes the possibility of assessing the interaction between gender and personality when it comes to predicting media taste. It seemed to us as though no one has investigated gendered differences in personality in the context of similar genre preferences.


title: The Open University ’ s repository of research publications and other research outputs Learning analytics : drivers , developments and challenges

text: Learning analytics is a significant area of technology-enhanced learning that has emerged during the last decade. This review of the field begins with an examination of the technological, educational and political factors that have driven the development of analytics in educational settings. It goes on to chart the emergence of learning analytics, including their origins in the 20th century, the development of data-driven analytics, the rise of learningfocused perspectives and the influence of national economic concerns. It next focuses on the relationships between learning analytics, educational data mining and academic analytics. Finally, it examines developing areas of learning analytics research, and identifies a series of future challenges.


title: Color , Shape and Texture based Fruit Recognition System

text: The paper presents an automated system for classification of fruits. A dataset containing five different fruits was constructed using an ordinary camera. All the fruits were analyzed on the basis of their color (RGB space), shape and texture and then classified using different classifiers to find the classifier that gives the best accuracy. Gray Level Cooccurance Matrix(GLCM) is used to calculate texture features .Best accuracy was achieved by support vector machine (svm). All the processing was carried out in Matlab. Keywords—computer vision, pattern recognition, support vector machine, texture features.


Exploring the relationships between college students' cell phone use, personality and leisure


title: A New ADS-B Authentication Framework Based on Efficient Hierarchical Identity-Based Signature with Batch Verification

text: Automatic dependent surveillance-broadcast (ADS-B) has become a crucial part of next generation air traffic surveillance technology and will be mandatorily deployed for most of the airspaces worldwide by 2020. Each aircraft equipped with an ADS-B device keeps broadcasting plaintext messages to other aircraft and the ground station controllers once or twice per second. The lack of security measures in ADS-B systems makes it susceptible to different attacks. Among the various security issues, we investigate the integrity and authenticity of ADS-B messages. We propose a new framework for providing ADS-B with authentication based on three-level hierarchical identity-based signature (HIBS) with batch verification. Previous signature-based ADS-B authentication protocols focused on how to generate signatures efficiently, while our schemes can also significantly reduce the verification cost, which is critical to ADS-B systems, since at any time an ADS-B receiver may receive lots of signatures. We design two concrete schemes. The basic scheme supports partial batch verification and the extended scheme provides full batch verification. We give a formal security proof for the extended scheme. Experiment results show that our schemes with batch verification are tremendously more efficient in batch verifying <inline-formula><tex-math notation="LaTeX">$n$ </tex-math><alternatives><inline-graphic xlink:href="yang-ieq1-2459709.gif"/></alternatives></inline-formula> signatures than verifying <inline-formula><tex-math notation="LaTeX">$n$</tex-math><alternatives> <inline-graphic xlink:href="yang-ieq2-2459709.gif"/></alternatives></inline-formula> signatures independently. For example, the running time of verifying 100 signatures is 502 and 484 ms for the basic scheme and the extended scheme respectively, while the time is 2500 ms if verifying the signatures independently.


title: Dual-Band and Dual-Polarized SIW-Fed Microstrip Patch Antenna

text: A new dual-band and dual-polarized antenna is investigated in this letter. Two longitudinal and transverse slots on the broad wall of the substrate integrated waveguide (SIW) are responsible for creating two different frequency bands with distinct polarization. A frequency selective surface (FSS) is placed on top of the microstrip patches to reduce the cross-polarization level of the antenna. The resonance frequencies of the patch and slot are set near to each other to get a wider impedance bandwidth. Bandwidth of more than 7% is achieved in each band. SIW feeding network increases the efficiency of the antenna. The simulated radiation efficiency of the antenna is better than 87% over the impedance bandwidth .


title: Simulation of lightning impulse voltage stresses in underground cables

text: The goal of this work is to study the transient behavior of the cable against the application of standard and non-standard lightning impulse voltage waveforms. A 66 kV cable model has been developed in MATLAB Simulink and standard and non-standard impulse voltages are applied to it. A preliminary comparative study on the obtained voltages indicated that non-standard impulse voltage waveform developed higher voltage stress in the cable. Simulation results helped to investigate which impulses (standard or non-standard) represent the worst possible voltage stresses on the cables. This study provides the basis for further study of effects of non-standard impulse voltage waveforms and make necessary correction in the existing impulse testing standards.


title: Skeletal Quads: Human Action Recognition Using Joint Quadruples

text: Recent advances on human motion analysis have made the extraction of human skeleton structure feasible, even from single depth images. This structure has been proven quite informative for discriminating actions in a recognition scenario. In this context, we propose a local skeleton descriptor that encodes the relative position of joint quadruples. Such a coding implies a similarity normalisation transform that leads to a compact (6D) view-invariant skeletal feature, referred to as skeletal quad. Further, the use of a Fisher kernel representation is suggested to describe the skeletal quads contained in a (sub)action. A Gaussian mixture model is learnt from training data, so that the generation of any set of quads is encoded by its Fisher vector. Finally, a multi-level representation of Fisher vectors leads to an action description that roughly carries the order of sub-action within each action sequence. Efficient classification is here achieved by linear SVMs. The proposed action representation is tested on widely used datasets, MSRAction3D and HDM05. The experimental evaluation shows that the proposed method outperforms state-of-the-art algorithms that rely only on joints, while it competes with methods that combine joints with extra cues.


title: Pedestrian detection and tracking with night vision

text: This paper presents a method for pedestrian detection and tracking using a single night-vision video camera installed on the vehicle. To deal with the nonrigid nature of human appearance on the road, a two-step detection/tracking method is proposed. The detection phase is performed by a support vector machine (SVM) with size-normalized pedestrian candidates and the tracking phase is a combination of Kalman filter prediction and mean shift tracking. The detection phase is further strengthened by information obtained by a road-detection module that provides key information for pedestrian validation. Experimental comparisons (e.g., grayscale SVM recognition versus binary SVM recognition and entire-body detection versus upper-body detection) have been carried out to illustrate the feasibility of our approach.


title: Video Google: A Text Retrieval Approach to Object Matching in Videos

text: We describe an approach to object and scene retrieval which searches for and localizes all the occurrences of a user outlined object in a video. The object is represented by a set of viewpoint invariant region descriptors so that recognition can proceed successfully despite changes in viewpoint, illumination and partial occlusion. The temporal continuity of the video within a shot is used to track the regions in order to reject unstable regions and reduce the effects of noise in the descriptors. The analogy with text retrieval is in the implementation where matches on descriptors are pre-computed (using vector quantization), and inverted file systems and document rankings are used. The result is that retrieval is immediate, returning a ranked list of key frames/shots in the manner of Google. The method is illustrated for matching on two full length feature films.


title: Multi-Granularity Chinese Word Embedding

text: This paper considers the problem of learning Chinese word embeddings. In contrast to English, a Chinese word is usually composed of characters, and most of the characters themselves can be further divided into components such as radicals. While characters and radicals contain rich information and are capable of indicating semantic meanings of words, they have not been fully exploited by existing word embedding methods. In this work, we propose multi-granularity embedding (MGE) for Chinese words. The key idea is to make full use of such word-character-radical composition, and enrich word embeddings by further incorporating finer-grained semantics from characters and radicals. Quantitative evaluation demonstrates the superiority of MGE in word similarity computation and analogical reasoning. Qualitative analysis further shows its capability to identify finer-grained semantic meanings of words.


title: When is a linguistic metaphor a conceptual metaphor ?

text: Volume 24 New Directions in Cognitive Linguistics Edited by Vyvyan Evans and Stéphanie Pourcel Editorial Advisory Board Melissa F. Bowerman Nijmegen Wallace Chafe Santa Barbara, CA Philip R. Cohen Portland, OR Antonio Damasio Iowa City, IA Morton Ann Gernsbacher Madison, WI David McNeill Chicago, IL Eric Pederson Eugene, OR François Recanati Paris Sally Rice Edmonton, Alberta Benny Shanon Jerusalem Lokendra Shastri Berkeley, CA Paul !agard Waterloo, Ontario Human Cognitive Processing (HCP)


Spam, Phishing, and Fraud Detection Using Random Projections, Adversarial Learning, and Semi-Supervised Learning


title: Pathways for irony detection in tweets

text: Posts on Twitter allow users to express ideas and opinions in a very dynamic way. The volume of data available is incredibly high in this support, and it may provide relevant clues regarding the judgement of the public on certain product, event, service etc. While in standard sentiment analysis the most common task is to classify the utterances according to their polarity, it is clear that detecting ironic senses represent a big challenge for Natural Language Processing. By observing a corpus constitued by tweets, we propose a set of patterns that might suggest ironic/sarcastic statements. Thus, we developed special clues for irony detection, through the implementation and evaluation of a set of patterns.


title: Developing an Ontology of the Cyber Security Domain

text: This paper reports on a trade study we performed to support the development of a Cyber ontology from an initial malware ontology. The goals of the Cyber ontology effort are first described, followed by a discussion of the ontology development methodology used. The main body of the paper then follows, which is a description of the potential ontologies and standards that could be utilized to extend the Cyber ontology from its initially constrained malware focus. These resources include, in particular, Cyber and malware standards, schemas, and terminologies that directly contributed to the initial malware ontology effort. Other resources are upper (sometimes called 'foundational') ontologies. Core concepts that any Cyber ontology will extend have already been identified and rigorously defined in these foundational ontologies. However, for lack of space, this section is profoundly reduced. In addition, utility ontologies that are focused on time, geospatial, person, events, and network operations are briefly described. These utility ontologies can be viewed as specialized super-domain or even mid-level ontologies, since they span many, if not most, ontologies -including any Cyber ontology. An overall view of the ontological architecture used by the trade study is also given. The report on the trade study concludes with some proposed next steps in the iterative evolution of the


title: The Painting Fool Sees! New Projects with the Automated Painter

text: We report the most recent advances in The Painting Fool project, where we have integrated machine vision capabilities from the DARCI system into the automated painter, to enhance its abilities before, during and after the painting process. This has enabled new art projects, including a commission from an Artificial Intelligence company, and we report on this collaboration, which is one of the first instances in Computational Creativity research where creative software has been commissioned directly. The new projects have advanced The Painting Fool as an independent artist able to produce more diverse styles which break away from simulating natural media. The projects have also raised a philosophical question about whether software artists need to see in the same way as people, which we discuss briefly.


title: Socializing by Gaming: Revealing Social Relationships in Multiplayer Online Games

text: Multiplayer Online Games (MOGs) like Defense of the Ancients and StarCraft II have attracted hundreds of millions of users who communicate, interact, and socialize with each other through gaming. In MOGs, rich social relationships emerge and can be used to improve gaming services such as match recommendation and game population retention, which are important for the user experience and the commercial value of the companies who run these MOGs. In this work, we focus on understanding social relationships in MOGs. We propose a graph model that is able to capture social relationships of a variety of types and strengths. We apply our model to real-world data collected from three MOGs that contain in total over ten years of behavioral history for millions of players and matches. We compare social relationships in MOGs across different game genres and with regular online social networks like Facebook. Taking match recommendation as an example application of our model, we propose SAMRA, a Socially Aware Match Recommendation Algorithm that takes social relationships into account. We show that our model not only improves the precision of traditional link prediction approaches, but also potentially helps players enjoy games to a higher extent.


title: Private Collaborative Neural Network Learning

text: Machine learning algorithms, such as neural networks, create better predictive models when having access to larger datasets. In many domains, such as medicine and finance, each institute has only access to limited amounts of data, and creating larger datasets typically requires collaboration. However, there are privacy related constraints on these collaborations for legal, ethical, and competitive reasons. In this work, we present a feasible protocol for learning neural networks in a collaborative way while preserving the privacy of each record. This is achieved by combining Differential Privacy and Secure Multi-Party Computation with Machine Learning.


title: Supervised Hashing with Deep Neural Networks

text: In this paper, we propose training very deep neural networks (DNNs) for supervised learning of hash codes. Existing methods in this context train relatively “shallow” networks limited by the issues arising in back propagation (e.g. vanishing gradients) as well as computational efficiency. We propose a novel and efficient training algorithm inspired by alternating direction method of multipliers (ADMM) that overcomes some of these limitations. Our method decomposes the training process into independent layer-wise local updates through auxiliary variables. Empirically we observe that our training algorithm always converges and its computational complexity is linearly proportional to the number of edges in the networks. Empirically we manage to train DNNs with 64 hidden layers and 1024 nodes per layer for supervised hashing in about 3 hours using a single GPU. Our proposed very deep supervised hashing (VDSH) method significantly outperforms the state-of-theart on several benchmark datasets.


title: Treatment of thoracolumbar burst fractures without neurologic deficit by indirect reduction and posterior instrumentation: bisegmental stabilization with monosegmental fusion

text: This study retrospectively reviews 20 sequential patients with thoracolumbar burst fractures without neurologic deficit. All patients were treated by indirect reduction, bisegmental posterior transpedicular instrumentation and monosegmental fusion. Clinical and radiological outcome was analyzed after an average follow-up of 6.4 years. Re-kyphosis of the entire segment including the cephaled disc was significant with loss of the entire postoperative correction over time. This did not influence the generally benign clinical outcome. Compared to its normal height the fused cephalad disc was reduced by 70% and the temporarily spanned caudal disc by 40%. Motion at the temporarily spanned segment could be detected in 11 patients at follow-up, with no relation to the clinical result. Posterior instrumentation of thoracolumbar burst fractures can initially reduce the segmental kyphosis completely. The loss of correction within the fractured vertebral body is small. However, disc space collapse leads to eventual complete loss of segmental reduction. Therefore, posterolateral fusion alone does not prevent disc space collapse. Nevertheless, clinical long-term results are favorable. However, if disc space collapse has to prevented, an interbody disc clearance and fusion is recommended.


title: Socioeconomic disparities in health: pathways and policies.

text: Socioeconomic status (SES) underlies three major determinants of health: health care, environmental exposure, and health behavior. In addition, chronic stress associated with lower SES may also increase morbidity and mortality. Reducing SES disparities in health will require policy initiatives addressing the components of socioeconomic status (income, education, and occupation) as well as the pathways by which these affect health. Lessons for U.S. policy approaches are taken from the Acheson Commission in England, which was charged with reducing health disparities in that country.


title: Human wayfinding in information networks

text: Navigating information spaces is an essential part of our everyday lives, and in order to design efficient and user-friendly information systems, it is important to understand how humans navigate and find the information they are looking for. We perform a large-scale study of human wayfinding, in which, given a network of links between the concepts of Wikipedia, people play a game of finding a short path from a given start to a given target concept by following hyperlinks. What distinguishes our setup from other studies of human Web-browsing behavior is that in our case people navigate a graph of connections between concepts, and that the exact goal of the navigation is known ahead of time. We study more than 30,000 goal-directed human search paths and identify strategies people use when navigating information spaces. We find that human wayfinding, while mostly very efficient, differs from shortest paths in characteristic ways. Most subjects navigate through high-degree hubs in the early phase, while their search is guided by content features thereafter. We also observe a trade-off between simplicity and efficiency: conceptually simple solutions are more common but tend to be less efficient than more complex ones. Finally, we consider the task of predicting the target a user is trying to reach. We design a model and an efficient learning algorithm. Such predictive models of human wayfinding can be applied in intelligent browsing interfaces.


title: Designing and Packaging Wide-Band PAs: Wideband PA and Packaging, History, and Recent Advances: Part 1

text: In current applications such as communication, aerospace and defense, electronic warfare (EW), electromagnetic compatibility (EMC), and sensing, among others, there is an ever-growing demand for more linear power with increasingly greater bandwidth and efficiency. Critical for these applications are the design and packaging of wide-band, high-power amplifiers that are both compact in size and low in cost [1]. Most such applications, including EW, radar, and EMC testers, require high 1-dB compression point (P1dB) power with good linearity across a wide band (multi-octave to decade bandwidth) [2]. In addition to linear power, wide bandwidth is essential for high-data-rate communication and high resolution in radar and active imagers [3]. In modern electronics equipment such as automated vehicles, rapidly increasing complexity imposes strict EMC regulations for human safety and security [4]. This often requires challenging specifications for the power amplifier (PA), such as very high P1dB power [to kilowatt, continuous wave (CW)] across approximately a decade bandwidth with high linearity, reliability, and long life, even for 100% load mismatch [5].


title: Grid-Connected Photovoltaic Generation System

text: This study addresses a grid-connected photovoltaic (PV) generation system. In order to make the PV generation system more flexible and expandable, the backstage power circuit is composed of a high step-up converter and a pulsewidth-modulation (PWM) inverter. In the dc-dc power conversion, the high step-up converter is introduced to improve the conversion efficiency of conventional boost converters and to allow the parallel operation of low-voltage PV modules. Moreover, an adaptive total sliding-mode control system is designed for the current control of the PWM inverter to maintain the output current with a higher power factor and less variation under load changes. In addition, an adaptive step-perturbation method is proposed to achieve the objective of maximum power point tracking, and an active sun tracking scheme without any light sensors is investigated to make PV plates face the sun directly in order to capture maximum irradiation and enhance system efficiency. Experimental results are given to verify the validity of the high step-up converter, the PWM inverter control, the ASP method, and the active sun tracker for a grid-connected PV generation system.


title: Development of the Perceived Stress Questionnaire: a new tool for psychosomatic research.

text: A 30-question Perceived Stress Questionnaire (PSQ) was validated, in Italian and English, among 230 subjects. Test-retest reliability was 0.82 for the General (past year or two) PSQ, while monthly Recent (past month) PSQs varied by a mean factor of 1.9 over 6 months; coefficient alpha > 0.9. General and/or Recent PSQ scores were associated with trait anxiety (r = 0.75), Cohen's Perceived Stress Scale (r = 0.73), depression (r = 0.56), self-rated stress (r = 0.56), and stressful life events (p < 0.05). The General PSQ was higher in in-patients than in out-patients (p < 0.05); both forms were correlated with a somatic complaints scale in a non-patient population (r > 0.5), and were higher, among 27 asymptomatic ulcerative colitis patients, in the seven who had rectal inflammation than in those with normal proctoscopy (p = 0.03). Factor analysis yielded seven factors, of which those reflecting interpersonal conflict and tension were significantly associated with health outcomes. The Perceived Stress Questionnaire may be a valuable addition to the armamentarium of psychosomatic researchers.


title: Dynamically pre-trained deep recurrent neural networks using environmental monitoring data for predicting PM2.5

text: Fine particulate matter ( $$\hbox {PM}_{2.5}$$ PM 2.5 ) has a considerable impact on human health, the environment and climate change. It is estimated that with better predictions, US$9 billion can be saved over a 10-year period in the USA (State of the science fact sheet air quality. http://www.noaa.gov/factsheets/new , 2012). Therefore, it is crucial to keep developing models and systems that can accurately predict the concentration of major air pollutants. In this paper, our target is to predict $$\hbox {PM}_{2.5}$$ PM 2.5 concentration in Japan using environmental monitoring data obtained from physical sensors with improved accuracy over the currently employed prediction models. To do so, we propose a deep recurrent neural network (DRNN) that is enhanced with a novel pre-training method using auto-encoder especially designed for time series prediction. Additionally, sensors selection is performed within DRNN without harming the accuracy of the predictions by taking advantage of the sparsity found in the network. The numerical experiments show that DRNN with our proposed pre-training method is superior than when using a canonical and a state-of-the-art auto-encoder training method when applied to time series prediction. The experiments confirm that when compared against the $$\hbox {PM}_{2.5}$$ PM 2.5 prediction system VENUS (National Institute for Environmental Studies. Visual Atmospheric Environment Utility System. http://envgis5.nies.go.jp/osenyosoku/ , 2014), our technique improves the accuracy of $$\hbox {PM}_{2.5}$$ PM 2.5 concentration level predictions that are being reported in Japan.


title: Feature selection in text classification

text: In recent years, text classification have been widely used. Dimension of text data has increased more and more. Working of almost all classification algorithms is directly related to dimension. In high dimension data set, working of classification algorithms both takes time and occurs over fitting problem. So feature selection is crucial for machine learning techniques. In this study, frequently used feature selection metrics Chi Square (CHI), Information Gain (IG) and Odds Ratio (OR) have been applied. At the same time the method Relevancy Frequency (RF) proposed as term weighting method has been used as feature selection method in this study. It is used for tf.idf term as weighting method, Sequential Minimal Optimization (SMO) and Naive Bayes (NB) in the classification algorithm. Experimental results show that RF gives successful results.


title: Design of a Multi-Sensor Cooperation Travel Environment Perception System for Autonomous Vehicle

text: This paper describes the environment perception system designed for intelligent vehicle SmartV-II, which won the 2010 Future Challenge. This system utilizes the cooperation of multiple lasers and cameras to realize several necessary functions of autonomous navigation: road curb detection, lane detection and traffic sign recognition. Multiple single scan lasers are integrated to detect the road curb based on Z-variance method. Vision based lane detection is realized by two scans method combining with image model. Haar-like feature based method is applied for traffic sign detection and SURF matching method is used for sign classification. The results of experiments validate the effectiveness of the proposed algorithms and the whole system.


title: 3D laser scan classification using web data and domain adaptation

text: Over the last years, object recognition has become a more and more active field of research in robotics. An important problem in object recognition is the need for sufficient labeled training data to learn good classifiers. In this paper we show how to significantly reduce the need for manually labeled training data by leveraging data sets available on the World Wide Web. Specifically, we show how to use objects from Google’s 3D Warehouse to train classifiers for 3D laser scans collected by a robot navigating through urban environments. In order to deal with the different characteristics of the web data and the real robot data, we additionally use a small set of labeled 3D laser scans and perform domain adaptation. Our experiments demonstrate that additional data taken from the 3D Warehouse along with our domain adaptation greatly improves the classification accuracy on real laser scans.


title: Detecting human activities in retail surveillance using hierarchical finite state machine

text: Cashiers in retail stores usually exhibit certain repetitive and periodic activities when processing items. Detecting such activities plays a key role in most retail fraud detection systems. In this paper, we propose a highly efficient, effective and robust vision technique to detect checkout-related primitive activities, based on a hierarchical finite state machine (FSM). Our deterministic approach uses visual features and prior spatial constraints on the hand motion to capture particular motion patterns performed in primitive activities. We also apply our approach to the problem of retail fraud detection. Experimental results on a large set of video data captured from retail stores show that our approach, while much simpler and faster, achieves significantly better results than state-of-the-art machine learning-based techniques both in detecting checkout-related activities and in detecting checkout-related fraudulent incidents.


title: COMPARING PROGRAMMER PRODUCTIVITY IN OPENACC AND CUDA: AN EMPIRICAL INVESTIGATION

text: OpenACC has been touted as a "high productivity" API designed to make GPGPU programming accessible to scientific programmers, but to date, no studies have attempted to verify this quantitatively. In this paper, we conduct an empirical investigation of program productivity comparisons between OpenACC and CUDA in the programming time, the execution time and the analysis of independence of OpenACC model in high performance problems. Our results show that, for our programs and our subject pool, this claim is true. We created two assignments called Machine Problem 3(MP3) and Machine Problem 4(MP4) in the classroom environment and instrumented the WebCode website developed by ourselves to record details of students’ coding process. Three hypotheses were supported by the statistical data: for the same parallelizable problem, (1) the OpenACC programming time is at least 37% shorter than CUDA; (2) the CUDA running speed is 9x faster than OpenACC; (3) the OpenACC development work is not significantly affected by previous CUDA experience


title: PROFITING FROM ARBITRAGE AND ODDS BIASES OF THE EUROPEAN FOOTBALL GAMBLING MARKET

text: A gambling market is usually described as being inefficient if there are one or more betting strategies that generate profit, at a consistent rate, as a consequence of exploiting market flaws. This paper examines the online European football gambling market based on 14 European football leagues over a period of seven years, from season 2005/06 to 2011/12 inclusive, and takes into consideration the odds provided by numerous bookmaking firms. Contrary to common misconceptions, we demonstrate that the accuracy of bookmakers' odds has not improved over this period. More importantly, our results question market efficiency by demonstrating high profitability on the basis of consistent odds biases and numerous arbitrage opportunities.


title: Low-cost, real-time obstacle avoidance for mobile robots

text: The goal of this project1 is to advance the field of automation and robotics by utilizing recently-released, low-cost sensors and microprocessors to develop a mechanism that provides depth-perception and autonomous obstacle avoidance in a plug-and-play fashion. We describe the essential hardware components that can enable such a low-cost solution and an algorithm to avoid static obstacles present in the environment. The mechanism utilizes a novel single-point LIDAR module that affords more robustness and invariance than popular approaches, such as Neural Networks and Stereo. When this hardware is coupled with the proposed efficient obstacle avoidance algorithm, this mechanism is able to accurately represent environments through point clouds and construct obstacle-free paths to a destination, in a small timeframe. A prototype mechanism has been installed on a quadcopter for visualization on how actual implementation may take place2. We describe experimental results based on this prototype.


title: Joint tracking and segmentation of multiple targets

text: Tracking-by-detection has proven to be the most successful strategy to address the task of tracking multiple targets in unconstrained scenarios [e.g. 40, 53, 55]. Traditionally, a set of sparse detections, generated in a preprocessing step, serves as input to a high-level tracker whose goal is to correctly associate these “dots” over time. An obvious short-coming of this approach is that most information available in image sequences is simply ignored by thresholding weak detection responses and applying non-maximum suppression. We propose a multi-target tracker that exploits low level image information and associates every (super)-pixel to a specific target or classifies it as background. As a result, we obtain a video segmentation in addition to the classical bounding-box representation in unconstrained, real-world videos. Our method shows encouraging results on many standard benchmark sequences and significantly outperforms state-of-the-art tracking-by-detection approaches in crowded scenes with long-term partial occlusions.


title: Parallel Formulations of Decision-Tree Classification Algorithms

text: Classification decision tree algorithms are used extensively for data mining in many domains such as retail target marketing, fraud detection, etc. Highly parallel algorithms for constructing classification decision trees are desirable for dealing with large data sets in reasonable amount of time. Algorithms for building classification decision trees have a natural concurrency, but are difficult to parallelize due to the inherent dynamic nature of the computation. In this paper, we present parallel formulations of classification decision tree learning algorithm based on induction. We describe two basic parallel formulations. One is based on Synchronous Tree Construction Approach and the other is based on Partitioned Tree Construction Approach. We discuss the advantages and disadvantages of using these methods and propose a hybrid method that employs the good features of these methods. We also provide the analysis of the cost of computation and communication of the proposed hybrid method. Moreover, experimental results on an IBM SP-2 demonstrate excellent speedups and scalability.


title: Genetic Algorithms in Search Optimization and Machine Learning

text: This book brings together-in an informal and tutorial fashion-the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems...


title: Indian Sign Language gesture classification as single or double handed gestures

text: The development of a sign language recognition system can have a great impact on the daily lives of humans with hearing disabilities. Recognizing gestures from the Indian Sign Language (ISL) with a camera can be difficult due to complexity of various gestures. The motivation behind the paper is to develop an approach to successfully classify gestures in the ISL under ambiguous conditions from static images. A novel approach involving the decomposition of gestures into single handed or double handed gesture has been presented in this paper. Classifying gesture into these subcategories simplifies the process of gesture recognition in the ISL due to presence of lesser number of gestures in each subcategory. Various approaches making use of Histogram of Gradients (HOG) features and geometric descriptors using KNN and SVM classifiers were tried on a dataset consisting of images of all 26 English alphabets present in the ISL under variable background. HOG features when classified with Support Vector Machine were found to be the most efficient approach resulting in an accuracy of 94.23%.


title: Estimation of the Mathematical Parameters of Double-Exponential Pulses Using the Nelder–Mead Algorithm

text: Transient pulses for electromagnetic compatibility problems, such as the high-altitude electromagnetic pulse and ultrawideband pulses, are often described by a double-exponential pulse. Such a pulse shape is specified physically by the three characteristic parameters rise time tr, pulsewidth tfwhm (full-width at half-maximum), and maximum amplitude Emax. The mathematical description is a double-exponential function with the parameters α, β, and E0. In practice, it is often necessary to transform the two groups of parameters into each other. This paper shows a novel relationship between the physical parameters tr and tfwhm on the one hand and the mathematical parameters α and β on the other. It is shown that the least-squares method in combination with the Nelder-Mead simplex algorithm is appropriate to determine an approximate closed-form formula between these parameters. Therefore, the extensive analysis of double-exponential pulses is possible in a considerably shorter computation time. The overall approximation error is less than 3.8%.


title: An Error-Oriented Approach to Word Embedding Pre-Training

text: We propose a novel word embedding pretraining approach that exploits writing errors in learners’ scripts. We compare our method to previous models that tune the embeddings based on script scores and the discrimination between correct and corrupt word contexts in addition to the generic commonly-used embeddings pre-trained on large corpora. The comparison is achieved by using the aforementioned models to bootstrap a neural network that learns to predict a holistic score for scripts. Furthermore, we investigate augmenting our model with error corrections and monitor the impact on performance. Our results show that our error-oriented approach outperforms other comparable ones which is further demonstrated when training on more data. Additionally, extending the model with corrections provides further performance gains when data sparsity is an issue.


title: Single-Channel and Multi-Channel Sinusoidal Audio Coding Using Compressed Sensing

text: Compressed sensing (CS) samples signals at a much lower rate than the Nyquist rate if they are sparse in some basis. In this paper, the CS methodology is applied to sinusoidally modeled audio signals. As this model is sparse by definition in the frequency domain (being equal to the sum of a small number of sinusoids), we investigate whether CS can be used to encode audio signals at low bitrates. In contrast to encoding the sinusoidal parameters (amplitude, frequency, phase) as current state-of-the-art methods do, we propose encoding few randomly selected samples of the time-domain description of the sinusoidal component (per signal segment). The potential of applying compressed sensing both to single-channel and multi-channel audio coding is examined. The listening test results are encouraging, indicating that the proposed approach can achieve comparable performance to that of state-of-the-art methods. Given that CS can lead to novel coding systems where the sampling and compression operations are combined into one low-complexity step, the proposed methodology can be considered as an important step towards applying the CS framework to audio coding applications.


title: Knowledge Discovery in Biomedical Data Facilitated by Domain Ontologies

text: In some real-world areas, it is important to enrich the data with external background knowledge so as to provide context and to facilitate pattern recognition. These areas may be described as data rich but knowledge poor. There are two challenges to incorporate this biological knowledge into the data mining cycle: (1) generating the ontologies; and (2) adapting the data mining algorithms to make use of the ontologies. This chapter presents the state-of-the-art in bringing the background ontology knowledge into the pattern recognition task for biomedical data.


title: AUTOMATIC GENERATION OF PRESENTATION SLIDES FOR ACADEMIC PAPERS USING INTEGER LINEAR PROGRAMMING

text: Presentations are one of the most common and effective ways of communicating the overview of a work to the audience. Given a specialized paper, programmed era of introduction slides diminishes the exertion of the moderator and aides in making an organized synopsis of the paper. In this Project, we propose the structure of another framework that does this assignment. Any paper that has a theoretical and whose segments can be ordered under presentation, related work, model, examinations and conclusions can be given as info. This XML record is parsed and data in it is extricated. An inquiry particular extractive summarizer has been utilized to create slides. In numerous meetings and social occasions, a moderator takes the guide of slides to present his work deliberately (pictorial). The introduction slides for the paper are then made by utilizing the Integer Linear Programming (ILP) demonstrate with complicatedly organized target breaking points and goals to pick and adjust key expressions and sentences. The framework removed theme and non subject parts from the article in light of the basic talk structure. The isolated subject and non-topic parts were determined to the slides by giving fitting indents in perspective of the examination of their syntactic structure. Keywords— Abstracting methods, Integer Linear Programming, Support Vector Regression model, text mining.


title: Semi-Supervised Text Classification Using EM

text: For several decades, statisticians have advocated using a c ombination of labeled and unlabeled data to train classifiers by estimating parameters o f a generative model through iterative Expectation-Maximization (EM) techniques. Thi s chapter explores the effectiveness of this approach when applied to the domain of text class ification. Text documents are represented here with a bag-of-words model, which leads to a generative classification model based on a mixture of multinomials. This model is an ext remely simplistic representation of the complexities of written text. This chapter explains and illustrates three key points about semi-supervised learning for text classifi cat on with generative models. First, despite the simplistic representation, some text do mains have a high positive correlation between generative model probability and classifica tion accuracy. In these domains, a straightforward application of EM with the naive Bayes tex t model works well. Second, some text domains do not have this correlation. Here we can ad opt a more expressive and appropriate generative model that does have a positive c orrelation. In these domains, semi-supervised learning again improves classification ac curacy. Finally, EM suffers from the problem of local maxima, especially in high dimension do mains such as text classification. We demonstrate that deterministic annealing, a varia nt of EM, can help overcome the problem of local maxima and increase classification accurac y further when the generative model is appropriate.


title: Crown and post-free adhesive restorations for endodontically treated posterior teeth: from direct composite to endocrowns.

text: Coronal rehabilitation of endodontically treated posterior teeth is still a controversial issue. Although the classical crown supported by radicular metal posts remains widely spread in dentistry, its invasiveness has been largely criticized. New materials and therapeutic options based entirely on adhesion are nowadays available. They allow performing a more conservative, faster and less expensive dental treatment. All clinical cases presented in this paper are solved by using these modern techniques, from direct composite restorations to indirect endocrowns.


title: Advanced Safe PIN-Entry Against Human Shoulder-Surfing Ms

text: When users insert their passwords in a common area, they might be at risk of aggressor stealing their password. The PIN entry can be perceived by close by adversaries, more effectually in a crowded place. A new technique has been established to cope with this problem that is cryptography prevention techniques. Instead, there have been alternative approaches among them, the PIN entry was elegant because of its simplicity and accessibility. The basic BW method is focused to withstand a human shoulder surfing attack. In every round, a well ordered numeric keypad is colored at odd. A user who knows the accurate PIN digit can enter by pressing the separate color key. The IBW method is examined to be confidential against human nemesis due to the restricted cognitive abilities of humans. Also the IBW method is proven to be robust against any hacking attacks.


title: A recommender system using GA K-means clustering in an online shopping market

text: The Internet is emerging as a new marketing channel, so understanding the characteristics of online customers’ needs and expectations is considered a prerequisite for activating the consumer-oriented electronic commerce market. In this study, we propose a novel clustering algorithm based on genetic algorithms (GAs) to effectively segment the online shopping market. In general, GAs are believed to be effective on NP-complete global optimization problems, and they can provide good near-optimal solutions in reasonable time. Thus, we believe that a clustering technique with GA can provide a way of finding the relevant clusters more effectively. The research in this paper applied K-means clustering whose initial seeds are optimized by GA, which is called GA K-means, to a real-world online shopping market segmentation case. In this study, we compared the results of GA K-means to those of a simple K-means algorithm and self-organizing maps (SOM). The results showed that GA K-means clustering may improve segmentation performance in comparison to other typical clustering algorithms. In addition, our study validated the usefulness of the proposed model as a preprocessing tool for recommendation systems. 2007 Elsevier Ltd. All rights reserved.


title: Large-scale deep learning at Baidu

text: In the past 30 years, tremendous progress has been achieved in building effective shallow classification models. Despite the success, we come to realize that, for many applications, the key bottleneck is not the qualify of classifiers but that of features. Not being able to automatically get useful features has become the main limitation for shallow models. Since 2006, learning high-level features using deep architectures from raw data has become a huge wave of new learning paradigms. In recent two years, deep learning has made many performance breakthroughs, for example, in the areas of image understanding and speech recognition. In this talk, I will walk through some of the latest technology advances of deep learning within Baidu, and discuss the main challenges, e.g., developing effective models for various applications, and scaling up the model training using many GPUs. In the end of the talk I will discuss what might be interesting future directions.


title: SD-Layer: Stain Deconvolutional Layer for CNNs in Medical Microscopic Imaging

text: Convolutional Neural Networks (CNNs) are typically trained in the RGB color space. However, in medical imaging, we believe that pixel stain quantities offer a fundamental view of the interaction between tissues and stain chemicals. Since the optical density (OD) colorspace allows to compute pixel stain quantities from pixel RGB intensities using the Beer-Lambert’s law, we propose a stain deconvolutional layer, hereby named as SD-Layer, affixed at the front of CNN that performs two functions: (1) it transforms the input RGB microscopic images to Optical Density (OD) space and (2) this layer deconvolves OD image with the stain basis learned through backpropagation and provides tissue-specific stain absorption quantities as input to the following CNN layers. With the introduction of only nine additional learnable parameters in the proposed SD-Layer, we obtain a considerably improved performance on two standard CNN architectures: AlexNet and T-CNN. Using the T-CNN architecture prefixed with the proposed SD-Layer, we obtain 5-fold crossvalidation accuracy of 93.2% in the problem of differentiating malignant immature White Blood Cells (WBCs) from normal immature WBCs for cancer detection.


title: Principles of spatial database analysis and design

text: This chapter covers the fundamentals of spatial database analysis and design, It begins by defining the most important concepts: ‘spatial database’, ‘analysis’, ‘design’, and ‘model’; and continues with a presentation of the rationale supporting the use of formal methods for analysis and design. The basic elements and approaches of such methods are described, in addition to the processes used. Emphasis is placed on the particularities of spatial databases and the improvements needed for non-spatial methods and tools in order to enhance their efficiency. Finally, the chapter presents a set of tools, called CASE (computer-assisted software engineering), which are built to support the formal analysis and design methods.


title: A BiCMOS Ultra-Wideband 3.1–10.6-GHz Front-End

text: This paper presents a direct-conversion receiver for FCC-compliant ultra-wideband (UWB) Gaussian-shaped pulses that are transmitted in one of fourteen 500-MHz-wide channels within the 3.1-10.6-GHz band. The receiver is fabricated in 0.18-mum SiGe BiCMOS. The packaged chip consists of an unmatched wideband low-noise amplifier (LNA), filter, phase-splitter, 5-GHz ISM band switchable notch filter, 3.1-10.6-GHz local oscillator (LO) amplifiers, mixers, and baseband channel-select filters/buffers. The required quadrature single-ended LO signals are generated externally. The average conversion gain and input P1dB are 32 dB and -41 dBm, respectively. The unmatched LNA provides a system noise figure of 3.3 to 5 dB over the entire band. The chip draws 30 mA from 1.8 V. To verify the unmatched LNA's performance in a complete system, wireless testing of the front-end embedded in a full receiver at 100 Mbps reveals a 10-3 bit-error rate (BER) at -80 dBm sensitivity. The notch filter suppresses out-of-band interferers and reduces the effects of intermodulation products that appear in the baseband. BER improvements of an order of magnitude and greater are demonstrated with the filter


title: Information-theoretical label embeddings for large-scale image classification

text: We present a method for training multi-label, massively multi-class image classification models, that is faster and more accurate than supervision via a sigmoid cross-entropy loss (logistic regression). Our method consists in embedding high-dimensional sparse labels onto a lower-dimensional dense sphere of unit-normed vectors, and treating the classification problem as a cosine proximity regression problem on this sphere. We test our method on a dataset of 300 million high-resolution images with 17,000 labels, where it yields considerably faster convergence, as well as a 7% higher mean average precision compared to logistic regression.


title: Analysis of a microstrip patch array fed cylindric lens antenna for 77GHz automotive radar

text: Regarding gain and SLL, the new lens antenna concept has better focusing abilities compared to the column antenna. Pattern perturbations due to lens edge effects were analyzed with regard to digital array processing. They can be confined either with an appropriate choice for the lens length L and the xlscr,i of the radar sensorpsilas receiving ULA or with narrower feeding beams in the H-plane.


title: Towards Modelling Pedestrian-Vehicle Interactions: Empirical Study on Urban Unsignalized Intersection

text: The modelling and simulation of the interaction among vehicles and pedestrians during crosswalking is an open challenge for both research and practical computational solutions supporting urban/traffic decision makers and managers. The social cost of pedestrians’ risky behaviour pushes the development of a new generation of computational models integrating analytical knowledge, data and experience about the complex dynamics occurring in pedestrian/vehicle interactions, which are not completely understood despite recent efforts. This paper presents the results of a significant data gathering campaign realised at an unsignalized zebra crossing. The selected area of the city of Milan (Italy) is characterised by a significant presence of elderly inhabitants and pedestrian-vehicle risky interactions, testified by a high number of accidents involving pedestrians in the past years. The results concern the analysis of: (i) vehicular and pedestrian traffic volumes; (ii) level of service; (iii) pedestrian-vehicle interactions, considering the impact of ageing on crossing behaviour. Results showed that the phenomenon is characterised by three main phases: approaching, appraising (evaluation of the distance and speed of oncoming vehicles) and crossing. The final objective of the research is to support the development of a microscopic agent-based tool for simulating pedestrian behaviour at unsignalized crosswalks, focusing on the specific needs of the elderly pedestrians.


title: Status of market, regulation and research of genetically modified crops in Chile.

text: Agricultural biotechnology and genetically modified (GM) crops are effective tools to substantially increase productivity, quality, and environmental sustainability in agricultural farming. Furthermore, they may contribute to improving the nutritional content of crops, addressing needs related to public health. Chile has become one of the most important global players for GM seed production for counter-season markets and research purposes. It has a comprehensive regulatory framework to carry out this activity, while at the same time there are numerous regulations from different agencies addressing several aspects related to GM crops. Despite imports of GM food/feed or ingredients for the food industry being allowed without restrictions, Chilean farmers are not using GM seeds for farming purposes because of a lack of clear guidelines. Chile is in a rather contradictory situation about GM crops. The country has invested considerable resources to fund research and development on GM crops, but the lack of clarity in the current regulatory situation precludes the use of such research to develop new products for Chilean farmers. Meanwhile, a larger scientific capacity regarding GM crop research continues to build up in the country. The present study maps and analyses the current regulatory environment for research and production of GM crops in Chile, providing an updated overview of the current status of GM seeds production, research and regulatory issues.


title: A Machine Learning Approach to Software Requirements Prioritization

text: Deciding which, among a set of requirements, are to be considered first and in which order is a strategic process in software development. This task is commonly referred to as requirements prioritization. This paper describes a requirements prioritization method called Case-Based Ranking (CBRank), which combines project's stakeholders preferences with requirements ordering approximations computed through machine learning techniques, bringing promising advantages. First, the human effort to input preference information can be reduced, while preserving the accuracy of the final ranking estimates. Second, domain knowledge encoded as partial order relations defined over the requirement attributes can be exploited, thus supporting an adaptive elicitation process. The techniques CBRank rests on and the associated prioritization process are detailed. Empirical evaluations of properties of CBRank are performed on simulated data and compared with a state-of-the-art prioritization method, providing evidence of the method ability to support the management of the tradeoff between elicitation effort and ranking accuracy and to exploit domain knowledge. A case study on a real software project complements these experimental measurements. Finally, a positioning of CBRank with respect to state-of-the-art requirements prioritization methods is proposed, together with a discussion of benefits and limits of the method.


title: Novel Feed Network for Circular Polarization Antenna Diversity

text: In this letter, we propose a novel feed network for circular polarization (CP) diversity antennas to enhance communications performances. The previous CP diversity systems adopted dual polarization diversity using right-hand circular polarization (RHCP) and left-hand circular polarization (LHCP) within a small space. However, the same rotational CPs need further antenna distance. To overcome the space limitation for the same CP diversity antenna, we propose a feed network for CP antenna using conventional CP with orthogonal polarization radiation characteristics of a linear polarization (LP) diversity system without additional antennas. The port isolation characteristics and impedance matching conditions are numerically verified for the diversity system and antenna characteristics. The proposed feed network with CP patch antennas is fabricated and measured in a reverberation chamber for diversity performances, and their validity is verified.


title: Microcephaly and early-onset nephrotic syndrome —confusion in Galloway-Mowat syndrome

text: We report a 2-year-old girl with nephrotic syndrome, microcephaly, seizures and psychomotor retardation. Histological studies of a renal biopsy revealed focal glomerular sclerosis with mesangiolysis and capillary microaneurysms. Dysmorphic features were remarkable: abnormal-shaped skull, coarse hair, narrow forehead, large low-set ears, almond-shaped eyes, low nasal bridge, pinched nose, thin lips and micrognathia. Cases with this rare combination of microcephaly and early onset of nephrotic syndrome with various neurological abnormalities have been reported. However, clinical manifestations and histological findings showed a wide variation, and there is a lot of confusion in this syndrome. We therefore reviewed the previous reports and propose a new clasification of this syndrome.


title: Learning Parameterized Models of Image Motion

text: A f?umeworkfor learning parumeterized models oj‘optical flow from image sequences is presented. A class of motions is represented by U set of orthogonul basis $ow fields that are computed froni a training set using priiicipal component analysis. Many complex image motions can be represeiited by a linear combiriution of U small number of these basisjows. The learned motion models may be usedfilr optical flow estimation und for model-bused recognition. For optical flow estimation we describe a robust, multi-resolution scheme for directly computing the parameters of the learned flow models from image derivatives. As examples we consider learning motion discontinuities, non-rigid motion of human mouths, und urticulated human motion.


title: Teaching cryptography with open-source software

text:
Cryptography has become an important topic in undergraduate curricula in mathematics and computer science, not just for its intrinsic interest---``about the most fun you can have with mathematics''\cite{ferg04, but for its current standing as the basis for almost all computer security. From wireless networking to secure email to password protection, cryptographic methods are used to secure information, to protect users, and to protect data.
 At Victoria University, cryptography has been taught as part of a mathematics and computer science degree for several years. The students all have had at least a year of tertiary mathematics, and some exposure to a computer algebra system (Maple). However, the cost of Maple, and the current licensing agreement, means that students are unable to experiment with the software away from the computer laboratories at the University. For this reason we have decided to investigate the use of open-source computer algebra systems Maxima and Axiom. Although not as full-featured and powerful as the commercial systems Maple and Mathematica, we show they are in fact admirably suited for a subject such as cryptography. In some ways Maxima and Axiom even surpass Maple and Mathematica. Student response to the introduction of these systems has been very positive.


title: Web-based models for natural language processing

text: Previous work demonstrated that Web counts can be used to approximate bigram counts, suggesting that Web-based frequencies should be useful for a wide variety of Natural Language Processing (NLP) tasks. However, only a limited number of tasks have so far been tested using Web-scale data sets. The present article overcomes this limitation by systematically investigating the performance of Web-based models for several NLP tasks, covering both syntax and semantics, both generation and analysis, and a wider range of n-grams and parts of speech than have been previously explored. For the majority of our tasks, we find that simple, unsupervised models perform better when n-gram counts are obtained from the Web rather than from a large corpus. In some cases, performance can be improved further by using backoff or interpolation techniques that combine Web counts and corpus counts. However, unsupervised Web-based models generally fail to outperform supervised state-of-the-art models trained on smaller corpora. We argue that Web-based models should therefore be used as a baseline for, rather than an alternative to, standard supervised models.


title: Large Language Models in Machine Translation

text: This paper reports on the benefits of largescale statistical language modeling in machine translation. A distributed infrastructure is proposed which we use to train on up to 2 trillion tokens, resulting in language models having up to 300 billion n-grams. It is capable of providing smoothed probabilities for fast, single-pass decoding. We introduce a new smoothing method, dubbed Stupid Backoff, that is inexpensive to train on large data sets and approaches the quality of Kneser-Ney Smoothing as the amount of training data increases.