title: Optimal Dynamic Hotel Pricing ∗

text: We analyze a confidential reservation database provided by a luxury hotel, ”hotel 0”, based in a major US city that enables us to observe individual reservations and cancellations at a daily frequency over a 37 month period. We show how the hotel sets prices for various classes of customers and how its prices vary over time. Hotel pricing is a challenging high-dimensional problem since hotels must not only set prices for each current date, but they must also quote prices for a range of future dates, room types and customer types. Our data reveal the full path of room rates quoted for different types of rooms and customers in advance of the arrival date. We find large within and between week variability in room prices, as well as huge seasonal variations in average daily rates and occupancy rates, not only for the hotel we study but also for its direct competitors. We formulate and estimate a structural model of optimal dynamic hotel pricing using the Method of Simulated Moments (MSM). The estimated model provides accurate predictions of the actual prices set by this firm and resulting paths of bookings and cancellations. Prices quoted for bookings generally decline as the arrival date approaches on nonbusy days, but can increase dramatically in the final days before arrival on busy days when there is a high probability of sell-out. Hotel 0’s prices co-move strongly with its competitors’ prices and we show that a simple price-following strategy where hotel 0 undercuts its competitors’ average price by a fixed percentage provides a good first approximation to its pricing behavior. However we show that simple price-following is suboptimal: when hotel 0 expects to sell out, it is optimal to depart from price-following and increase its price significantly above its competitors. On non-busy days, it is not optimal for hotel 0 to cut its prices in the final days before arrival to try to increase occupancy unless its competitors cut their prices. Though price-following has the superficial appearance of collusive behavior mediated by the use of a commercial revenue management system (RMS), our results suggest that hotel 0’s pricing is competitive and is best described as a rational best response to its beliefs about demand and the prices set by its competitors. In fact hotel 0 regularly disregards the recommended prices of its RMS, which it regards as too low compared to the prices it actually sets.


title: Boosting Recurrent Neural Networks for Time Series Prediction

text: We adapt a boosting algorithm to the problem of predicting future values of time series, using recurrent neural networks as base learners. The experiments we performed show that boosting actually provides improved results and that the weighted median is better for combining the learners than the weighted mean.


title: Establishing rigour in qualitative research: the decision trail.

text: The aim of this paper is to show the way in which the decision trail of a qualitative research process can be maintained. It is argued that the trustworthiness (rigour) of a study may be established if the reader is able to audit the events, influences and actions of the researcher. The actual study containing the recording of this decision trail aimed to express the concerns of older patients who were admitted to the acute care sector. The study took place in two care of the elderly wards in a 1000-bed National Health Service hospital in the UK, in 1991. Eventually, 14 patients were interviewed, each on several occasions, and their concerns are expressed in themes, namely: routine geriatric style of care, depersonalization, care deprivation and geriatric segregation. I describe the preparations that were undertaken before patient interviews could commence. The literature recording the process of the interviewer's experience as data in qualitative research is scarce. I show the researcher's participation in making the data as part of an existential phenomenological research process. Existential phenomenology relies on recording influences while generating data such as significant literature, media reports, my value position and journal data.


title: A balanced psychology and a full life.

text: Psychology since World War II has been largely devoted to repairing weakness and understanding suffering. Towards that end, we have made considerable gains. We have a classification of mental illness that allows international collaboration, and through this collaboration we have developed effective psychotherapeutic or pharmacological treatments for 14 major mental disorders. However, while building a strong science and practice of treating mental illness, we largely forgot about everyday well-being. Is the absence of mental illness and suffering sufficient to let individuals and communities flourish? Were all disabling conditions to disappear, what would make life worth living? Those committed to a science of positive psychology can draw on the effective research methods developed to understand and treat mental illness. Results from a new randomized, placebo-controlled study demonstrate that people are happier and less depressed three months after completing exercises targeting positive emotion. The ultimate goal of positive psychology is to make people happier by understanding and building positive emotion, gratification and meaning. Towards this end, we must supplement what we know about treating illness and repairing damage with knowledge about nurturing well-being in individuals and communities.


title: Clustering versus faceted categories for information exploration

text: Information seekers often express a desire for a user interface that organizes search results into meaningful groups, in order to help make sense of the results, and to help decide what to do next. A longitudinal study in which participants were provided with the ability to group search results found they changed their search habits in response to having the grouping mechanism available [2]. There are many open research questions about how to generate useful groupings and how to design interfaces to support exploration using grouping. Currently two methods are quite popular: clustering and faceted categorization. Here, I describe both approaches and summarize their advantages and disadvantages based on the results of usability studies. Clustering refers to the grouping of items according to some measure of similarity. In document clustering, similarity is typically computed using associations and commonalities among features, where features are typically words and phrases [1]. One of the better implementations of clustering of Web results can be found at Clusty.com. The greatest advantage of clustering is that it is fully automatable and can be easily applied to any text collection. Clustering can also reveal interesting and potentially unexpected or new trends in a group of documents. A query on “New Orleans”’ run on Clusty.com on Sept. 16, 2005 (shortly after the devastation wreaked by Hurricane Katrina), revealed a top-ranked cluster titled Hurricane, followed by the more standard groupings of Hotels, Louisiana, University, and Mardi Gras. Clustering can be useful for clarifying and sharpening a vague query, by showing users the dominant themes of the returned results [2]. Clustering also works well for disambiguating ambiguous queries; particularly acronyms. For example, ACL can stand for Anterior Cruciate Ligament, Association for Computational Linguistics, Atlantic Coast Line Railroad, among others. Unfortunately, because clustering algorithms are imperfect, they do not neatly group all occurrences of each acronym into one cluster, nor do they allow users to issue follow-up queries that only return documents from the intended sense (for example, “ACL meeting” will return meetings for multiple senses of the term). By Marti A. Hearst


title: Management Dimension for Assessing Organizations' Readiness toward Business Intelligence Systems

text: The improvements and capabilities of Business Intelligence (BI) systems are making them highly required by organizations in many of the fields. Day by day, the demand is increasing on these systems. Figures show that billions of US dollars are spent annually on BI systems. However, half of these BI projects are ending with unrealized benefit, according to some studies. As a participation to reduce this failure rate, the authors have developed a conceptual model, based on the existing studies in the field, which may help organizations to assess their readiness toward BI systems. The conceptual model is tested empirically on the Context of Malaysian Organizations(CMOs) as they are emerging widely to BI systems and they lack for this kind of studies to be done them. The conceptual model is consisting of seven dimensions. Depending on the results of the conducted study, this paper will disclose the results of management dimension, which will help to know the degree of its importance for organizations' to be ready for such systems. A brief introduction on BI systems and the challenges of their implementation will be presented. In Addition, this paper will go through some important studies have been done in the field. The details of the study will be provided as well.


title: A Meta-Model for the Analysis and Design of Organizations in Multi-Agent Systems

text: This paper presents a generic meta-model of multi-agent systems based on organizational concepts such as groups, roles and structures. This model, called AALAADIN, defines a very simple description of coordination and negotiation schemes through multi-agent systems. Aalaadin is a meta-model of artificial organization by which one can build multi-agent systems with different forms of organizations such as market-like and hierarchical organizations. We show that this meta-model allows for agent heterogeneity in languages, applications and architectures. We also introduce the concept of organizational reflection which uses the same conceptual model to describe systemlevel tasks such as remote communication and migration of agents. Finally, we briefly describe a platform, called MADKIT, based on this model. It relies on a minimal agent kernel with platform-level services implemented as agents, groups and roles.


title: Coreference in Spoken vs. Written Texts: a Corpus-based Analysis

text: This paper describes an empirical study of coreference in spoken vs. written text. We focus on the comparison of two particular text types, interviews and popular science texts, as instances of spoken and written texts since they display quite different discourse structures. We believe in fact, that the correlation of difficulties in coreference resolution and varying discourse structures requires a deeper analysis that accounts for the diversity of coreference strategies or their sub-phenomena as indicators of text type or genre. In this work, we therefore aim at defining specific parameters that classify differences in genres of spoken and written texts such as the preferred segmentation strategy, the maximal allowed distance in or the length and size of coreference chains as well as the correlation of structural and syntactic features of coreferring expressions. We argue that a characterization of such genre dependent parameters might improve the performance of current state-of-art coreference resolution technology.


title: HOW THE EYE MEASURES REALITY AND VIRTUAL REALITY

text: tures throughout our history. The paintings at Niaux, Altamira, and Lascaux (Clottes, 1995; Ruspoli, 1986), for example, are known to be about 14,000 years old, but with the recently discovered paintings in the Grotte Chauvet, the origin of representational art appears to have been pushed back even further (Chauvet, Brunel Deschamps, & Hillaire, 1995; Clottes, 1996), to 20,000 years ago if not longer.1 Thus, these paintings date from about the time at which homo sapiens sapiens first appeared in Europe (Nougier, 1969). We should remember these paintings in the context of virtual reality; our fascination with pictures is by no means recent. My intent is threefold: first, to discuss our perception of the cluttered layout, or space, that we normally find around us; second, to discuss the development of representational art up to our current appreciation of it; and third, to apply this knowledge to virtual reality systems. The first discussion focuses on the use of multiple sources of information specifying ordinal depth relations, within the theoretical framework that I have called directed perception (Cutting, 1986, 1991). The second discussion is embedded within the first, but it is steeped in neither history nor art history; instead, it is offered through the peculiar eyes of optics and psychology, particularly psychophysics. The third is addressed to one of the pressing problems of graphics and of virtual reality—how we perceive the layout of the environments that we simulate.


title: Exemplar Guided Unsupervised Image-to-Image Translation

text: Image-to-image translation task has become a popular topic recently. Most works focus on either one-to-one mapping in an unsupervised way or many-to-many mapping in a supervised way. However, a more practical setting is many-to-many mapping in an unsupervised way, which is harder due to the lack of supervision and the complex inner and cross-domain variations. To alleviate these issues, we propose the Exemplar Guided UNsupervised Image-to-image Translation (EGUNIT) network which conditions the image translation process on an image in the target domain. An image representation is assumed to comprise both content information which is shared across domains and style information specific to one domain. By applying exemplar-based adaptive instance normalization to the shared content representation, EG-UNIT manages to transfer the style information in the target domain to the source domain. Experimental results on various datasets show that EG-UNIT can indeed translate the source image to diverse instances in the target domain with semantic consistency.


title: Usability Dimensions for Mobile Applications-A Review

text: Usability has been increasingly recognized as a significant quality dimension to determine the success of mobile applications. Due to its importance, a number of usability guidelines have been proposed to direct the design of usable applications. The guidelines are intended particularly for desktop and web-based applications. Mobile applications on the other hand are different in many ways from those applications due to the mobility nature of mobile devices. To date, the usability guidelines for mobile applications are very limited. They in fact are isolated, which makes usability evaluation for mobile devices more difficult. This study aims to address this issue by proposing a set of usability dimensions that should be considered for designing and evaluating mobile applications. The dimensions are illustrated as a model that considers four contextual factors: user, environment, technology and task/activity. The model was proposed based on the reviews of previous related studies, which were analyzed by using content analysis approach. Twenty-five dimensions were found from the analysis. The dimensions however were synthesized and prioritized based on their importance towards designing usable mobile applications. As a result, ten most important dimensions were outlined in the model. The model can be used by practitioners and researchers as a guideline to design usable mobile applications and further research can be conducted in the near future.


title: SMARTMUSEUM: A mobile recommender system for the Web of Data

text: Semantic and context knowledge have been envisioned as an appropriate solution for addressing the content heterogeneity and information overload in mobile Web information access, but few have explored their full potential in mobile scenarios, where information objects refer to their physical counterparts, and retrieval is context-aware and personalized for users. We present SMARTMUSEUM, a mobile ubiquitous recommender system for the Web of Data, and its application to information needs of tourists in context-aware on-site access to cultural heritage. The SMARTMUSEUM system utilizes Semantic Web languages as the form of data representation. Ontologies are used to bridge the semantic gap between heterogeneous content descriptions, sensor inputs, and user profiles. The system makes use of an information retrieval framework wherein context data and search result clustering are used in recommendation of suitable content for mobile users. Results from laboratory experiments demonstrate that ontology-based reasoning, query expansion, search result clustering, and context knowledge lead to significant improvement in recommendation performance. The results from field trials show that the usability of the system meets users’ expectations in real-world use. The results indicate that semantic content representation and retrieval can significantly improve the performance of mobile recommender systems in knowledge-rich domains.


title: A visitor's guide in an active museum: Presentations, communications, and reflection

text: Technology can play a crucial role in supporting museum visitors and enhancing their overall museum visit experiences. Visitors coming to a museum do not want to be overloaded with information, but to receive the relevant information, learn, and have an overall interesting experience. To serve this goal, a user-friendly and flexible system is needed. The design of such a system poses several challenges that need to be addressed in parallel. The user interface should be intuitive and let the visitors focus on the exhibits, not on the technology. Content and delivery must provide relevant information and at the same time allow visitors to get the level of detail and the perspectives in which they are interested. Personalization may play a key role in providing relevant information to individuals. Yet, since visitors tend to visit the museum in small groups, technology should also contribute to and facilitate during-the-visit communication or post-visit group interaction. The PIL project applied at the Hecht museum extended the research results of the PEACH project and tried to address all of these considerations. Evaluation involving users substantiated several aspects of the design.


title: Smart cities in Europe

text: Urban performance currently depends not only on the city’s endowment of hard infrastructure (‘physical capital’), but also, and increasingly so, on the availability and quality of knowledge communication and social infrastructure (‘human and social capital’). The latter form of capital is decisive for urban competitiveness. Against this background, the concept of the ‘smart city’ has recently been introduced as a strategic device to encompass modern urban production factors in a common framework and, in particular, to highlight the importance of Information and Communication Technologies (ICTs) in the last 20 years for enhancing the competitive profile of a city.


title: Verifiable source code documentation in controlled natural language

text: Writing documentation about software internals is rarely considered a rewarding activity. It is highly time-consuming and the resulting documentation is fragile when the software is continuously evolving in a multi-developer setting. Unfortunately, traditional programming environments poorly support the writing and maintenance of documentation. Consequences are severe as the lack of documentation on software structure negatively impacts the overall quality of the software product. We show that using a controlled natural language with a reasoner and a query engine is a viable technique for verifying the consistency and accuracy of documentation and source code. Using ACE, a state-of-the-art controlled natural language, we present positive results on the comprehensibility and the general feasibility of creating and verifying documentation. As a case study, we used automatic documentation verification to identify and fix severe flaws in the architecture of a non-trivial piece of software. Moreover, a user experiment shows that our language is faster and easier to learn and understand than other formal languages for software documentation.


title: Context-aware query suggestion by mining click-through and session data

text: Query suggestion plays an important role in improving the usability of search engines. Although some recently proposed methods can make meaningful query suggestions by mining query patterns from search logs, none of them are context-aware - they do not take into account the immediately preceding queries as context in query suggestion. In this paper, we propose a novel context-aware query suggestion approach which is in two steps. In the offine model-learning step, to address data sparseness, queries are summarized into concepts by clustering a click-through bipartite. Then, from session data a concept sequence suffix tree is constructed as the query suggestion model. In the online query suggestion step, a user's search context is captured by mapping the query sequence submitted by the user to a sequence of concepts. By looking up the context in the concept sequence sufix tree, our approach suggests queries to the user in a context-aware manner. We test our approach on a large-scale search log of a commercial search engine containing 1:8 billion search queries, 2:6 billion clicks, and 840 million query sessions. The experimental results clearly show that our approach outperforms two baseline methods in both coverage and quality of suggestions.


title: Spectral–Spatial Classification of Hyperspectral Imagery Based on Partitional Clustering Techniques

text: A new spectral-spatial classification scheme for hyperspectral images is proposed. The method combines the results of a pixel wise support vector machine classification and the segmentation map obtained by partitional clustering using majority voting. The ISODATA algorithm and Gaussian mixture resolving techniques are used for image clustering. Experimental results are presented for two hyperspectral airborne images. The developed classification scheme improves the classification accuracies and provides classification maps with more homogeneous regions, when compared to pixel wise classification. The proposed method performs particularly well for classification of images with large spatial structures and when different classes have dissimilar spectral responses and a comparable number of pixels.


title: Nonvolatile memory design based on ferroelectric FETs

text: Ferroelectric FETs (FEFETs) offer intriguing possibilities for the design of low power nonvolatile memories by virtue of their three-terminal structure coupled with the ability of the ferroelectric (FE) material to retain its polarization in the absence of an electric field. Utilizing the distinct features of FEFETs, we propose a 2-transistor (2T) FEFET-based nonvolatile memory with separate read and write paths. With proper co-design at the device, cell and array levels, the proposed design achieves non-destructive read and lower write power at iso-write speed compared to standard FERAM. In addition, the FEFET-based memory exhibits high distinguishability with six orders of magnitude difference in the read currents corresponding to the two states. Comparative analysis based on experimentally calibrated models shows significant improvement of access energy-delay. For example, at a fixed write time of 550ps, the write voltage and energy are 58.5% and 67.7% lower than FERAM, respectively. These benefits are achieved with 2.4 times the area overhead. Further exploration of the proposed FEFET memory in energy harvesting nonvolatile processors shows an average improvement of 27% in forward progress over FERAM.


title: Abstract Semantic Differencing for Numerical Programs

text: Semantic Differencing for Numerical Programs Nimrod Partush Eran Yahav


title: Comparative genomic analysis identifies structural features of CRISPR-Cas systems in Riemerella anatipestifer

text: Riemerella anatipestifer infection is a contagious disease that has resulted in major economic losses in the duck industry worldwide. This study attempted to characterize CRISPR-Cas systems in the disease-causing agent, Riemerella anatipestifer (R. anatipestifer). The CRISPR-Cas system provides adaptive immunity against foreign genetic elements in prokaryotes and CRISPR-cas loci extensively exist in the genomes of archaea and bacteria. However, the structure characteristics of R. anatipestifer CRISPR-Cas systems remains to be elucidated due to the limited availability of genomic data. To identify the structure and components associated with CRISPR-Cas systems in R. anatipestifer, we performed comparative genomic analysis of CRISPR-Cas systems in 25 R. anatipestifer strains using high-throughput sequencing. The results showed that most of the R. anatipestifer strains (20/25) that were analyzed have two CRISPR loci (CRISPR1 and CRISPR2). CRISPR1 was shown to be flanked on one side by cas genes, while CRISPR2 was designated as an orphan. The other analyzed strains harbored only one locus, either CRISPR1 or CRISPR2. The length and content of consensus direct repeat sequences, as well as the length of spacer sequences associated with the two loci, differed from each other. Only three cas genes (cas1, cas2 and cas9) were located upstream of CRISPR1. CRISPR1 was also shown to be flanked by a 107 bp-long putative leader sequence and a 16 nt-long anti-repeat sequence. Combined with analysis of spacer organization similarity and phylogenetic tree of the R. anatipestifer strains, CRISPR arrays can be divided into different subgroups. The diversity of spacer organization was observed in the same subgroup. In general, spacer organization in CRISPR1 was more divergent than that in CRISPR2. Additionally, only 8 % of spacers (13/153) were homologous with phage or plasmid sequences. The cas operon flanking CRISPR1 was observed to be relatively conserved based on multiple sequence alignments of Cas amino acid sequences. The phylogenetic analysis associated with Cas9 showed Cas9 sequence from R. anatipestifer was closely related to that of Bacteroides fragilis and formed part of the subtype II-C subcluster. Our data revealed for the first time the structural features of R. anatipestifer CRISPR-Cas systems. The illumination of structural features of CRISPR-Cas system may assist in studying the specific mechanism associated with CRISPR-mediated adaptive immunity and other biological functions in R. anatipestifer.


title: Neural network-based reputation model in a distributed system

text: Current centralized trust models are inappropriate to apply in a large distributed multi-agent system, due to various evaluation models and partial observations in local level reputation management. This paper proposes a distributed reputation management structure, and develops a global reputation model. The global reputation model is a novel application of neural network techniques in distributed reputation evaluations. The experimental results showed that the model has robust performance under various estimation accuracy requirements. More important, the model is adaptive to changes in distributed system structures and in local reputation evaluations.


title: Infants' preferences for toys, colors, and shapes: sex differences and similarities.

text: Girls and boys differ in their preferences for toys such as dolls and trucks. These sex differences are present in infants, are seen in non-human primates, and relate, in part, to prenatal androgen exposure. This evidence of inborn influences on sex-typed toy preferences has led to suggestions that object features, such as the color or the shape of toys, may be of intrinsically different interest to males and females. We used a preferential looking task to examine preferences for different toys, colors, and shapes in 120 infants, ages 12, 18, or 24 months. Girls looked at dolls significantly more than boys did and boys looked at cars significantly more than girls did, irrespective of color, particularly when brightness was controlled. These outcomes did not vary with age. There were no significant sex differences in infants' preferences for different colors or shapes. Instead, both girls and boys preferred reddish colors over blue and rounded over angular shapes. These findings augment prior evidence of sex-typed toy preferences in infants, but suggest that color and shape do not determine these sex differences. In fact, the direction of influence could be the opposite. Girls may learn to prefer pink, for instance, because the toys that they enjoy playing with are often colored pink. Regarding within sex differences, as opposed to differences between boys and girls, both boys and girls preferred dolls to cars at age 12-months. The preference of young boys for dolls over cars suggests that older boys' avoidance of dolls may be acquired. Similarly, the sex similarities in infants' preferences for colors and shapes suggest that any subsequent sex differences in these preferences may arise from socialization or cognitive gender development rather than inborn factors.


title: On The Architecture Scheduling Problem Of Industry 4.0

text: The recently emerged Fourth Industrial Revolution (Industry 4.0) is characterised by the introduction of the new Cyber-Physical System (CPS) concepts and the Internet of Things (IoT) paradigm. These new collaborating computational entities offer a broad range of opportunity to consider with a different perspective. One of the perennial problems of the manufacturing operation is the scheduling problem of typical job-shop manufacturing systems. Starting from a comparison with the typical architecture of an operating systems scheduler module, we introduce a new manufacturing scheduling architecture. Overcoming the typical Full-Hierarchical configuration defined in the ANSI/ISA 95 in favour of a SemiHeterarchical one, the introduced scheduling architecture leads to a mixture of proactive and reactive approach to the Job-shop Scheduling Problem (JSP), taking advantage from both the common decentralised and the centralised methodology. Keywords— Industry 4.0; Cyber-Physical System (CPS); JobShop Scheduling Problem; Manufacturing System; System of


title: Path integral guided policy search

text: 3Sergey Levine is with Google Brain, Mountain View, CA 94043, USA. We present a policy search method for learning complex feedback control policies that map from high-dimensional sensory inputs to motor torques, for manipulation tasks with discontinuous contact dynamics. We build on a prior technique called guided policy search (GPS), which iteratively optimizes a set of local policies for specific instances of a task, and uses these to train a complex, high-dimensional global policy that generalizes across task instances. We extend GPS in the following ways: (1) we propose the use of a model-free local optimizer based on path integral stochastic optimal control (PI2), which enables us to learn local policies for tasks with highly discontinuous contact dynamics; and (2) we enable GPS to train on a new set of task instances in every iteration by using on-policy sampling: this increases the diversity of the instances that the policy is trained on, and is crucial for achieving good generalization. We show that these contributions enable us to learn deep neural network policies that can directly perform torque control from visual input. We validate the method on a challenging door opening task and a pick-and-place task, and we demonstrate that our approach substantially outperforms the prior LQR-based local policy optimizer on these tasks. Furthermore, we show that on-policy sampling significantly increases the generalization ability of these policies.


title: Transcutaneous measurement of glomerular filtration rate using FITC-sinistrin in rats.

text:
BACKGROUND
Inulin/sinistrin (I/S) clearance is a gold standard for an accurate assessment of glomerular filtration rate (GFR). Here we describe and validate an approach for a transcutaneous determination of GFR by using fluorescein-isothiocyanate-labelled sinistrin (FITC-S) in rats.

METHODS
Using a small animal imager, fluorescence is measured over the depilated ear of a rat after the injection of FITC-S. The decay curve of fluorescence is used for the calculation of half-life and GFR. The thus obtained transcutaneous data were validated by simultaneously performed enzymatic and fluorometric measurements in plasma of both FITC-S and sinistrin.

RESULTS
The results of enzymatic sinistrin determination versus transcutaneous half-life of FITC-S or plasma fluorescence correlated well with each other (R(2) > 0.90). Furthermore, Bland-Altman analyses proved a good degree of agreement of the three methods used. The measurements performed in healthy animals as well as different models of renal failure demonstrate its appropriateness in a wide range of renal function.

CONCLUSIONS
The transcutaneous method described offers a precise assessment of GFR in small animals. As neither blood and/or urine sampling nor time-consuming lab work is required, GFR can be determined immediately after the clearance procedure is finished. This method, therefore, simplifies and fastens GFR determinations in small lab animals compared to conventional bolus clearance techniques based on blood sampling. A low-cost device for the measurement of transcutaneous fluorescence intensity over time is under construction.


title: Periodontal diseases.

text: The periodontal diseases are highly prevalent and can affect up to 90% of the worldwide population. Gingivitis, the mildest form of periodontal disease, is caused by the bacterial biofilm (dental plaque) that accumulates on teeth adjacent to the gingiva (gums). However, gingivitis does not affect the underlying supporting structures of the teeth and is reversible. Periodontitis results in loss of connective tissue and bone support and is a major cause of tooth loss in adults. In addition to pathogenic microorganisms in the biofilm, genetic and environmental factors, especially tobacco use, contribute to the cause of these diseases. Genetic, dermatological, haematological, granulomatous, immunosuppressive, and neoplastic disorders can also have periodontal manifestations. Common forms of periodontal disease have been associated with adverse pregnancy outcomes, cardiovascular disease, stroke, pulmonary disease, and diabetes, but the causal relations have not been established. Prevention and treatment are aimed at controlling the bacterial biofilm and other risk factors, arresting progressive disease, and restoring lost tooth support.


title: Artificial neural networks in time series forecasting: a comparative analysis

text: Artificial neural networks (ANN) have received a great deal of attention in many fields of engineering and science. Inspired by the study of brain architecture, ANN represent a class of non-linear models capable of learning from data. ANN have been applied in many areas where statistical methods are traditionally employed. They have been used in pattern recognition, classification, prediction and process control. The purpose of this paper is to discuss ANN and compare them to non-linear time series models. We begin exploring recent developments in time series forecasting with particular emphasis on the use of non-linear models. Thereafter we include a review of recent results on the topic of ANN. The relevance of ANN models for the statistical methods is considered using time series prediction problems. Finally we construct asymptotic prediction intervals for ANN and show how to use prediction intervals to choose the number of nodes in the ANN.


title: ntology matching with semantic verification ves

text: Automated Semantic Matching of Ontologies with Verification (ASMOV) is a novel algorithm that uses lexical and structural characteristics of two ontologies to iteratively calculate a similarity measure between them, derives an alignment, and then verifies it to ensure that it does not contain semantic inconsistencies. In this paper, we describe the ASMOV algorithm, and then present experimental results that measure vailable online xxx eywords: ntology ntology alignment ntology matching its accuracy using the OAEI 2008 tests, and that evaluate its use with two different thesauri: WordNet, and the Unified Medical Language System (UMLS). These results show the increased accuracy obtained by combining lexical, structural and extensional matchers with semantic verification, and demonstrate the advantage of using a domain-specific thesaurus for the alignment of specialized ontologies. © 2009 Elsevier B.V. All rights reserved.


title: Reputation , Trust , and Rebates : How Online Auction Markets Can Improve Their Feedback Mechanisms

text: Trust and trustworthiness are crucial to the survival of online markets, and reputation systems that rely on feedback from traders help sustain trust. However, in current online auction markets only half of the buyers leave feedback after transactions, and nearly all of it is positive. In this paper, I propose a mechanism whereby sellers can provide rebates to buyers contingent on buyers provision of reports. Using a game theoretical model, I show how the rebate incentive mechanism can increase reporting. In both a pure adverse selection model, and a model with adverse selection and moral hazard, there exists a pooling equilibrium where both good and bad sellers choose the rebate option, even though their true types are revealed through feedback. In the presence of moral hazard, the mechanism induces bad sellers to improve the quality of the contract.


title: iVAT and aVAT: Enhanced Visual Analysis for Cluster Tendency Assessment

text: Given a pairwise dissimilarity matrix D of a set of n objects, visual methods (such as VAT) for cluster tendency assessment generally represent D as an n × n image I(D̃) where the objects are reordered to reveal hidden cluster structure as dark blocks along the diagonal of the image. A major limitation of such methods is the inability to highlight cluster structure in I(D̃) when D contains highly complex clusters. To address this problem, this paper proposes an improved VAT (iVAT) method by combining a path-based distance transform with VAT. In addition, an automated VAT (aVAT) method is also proposed to automatically determine the number of clusters from I(D̃). Experimental results on several synthetic and real-world data sets have demonstrated the effectiveness of our methods.


title: Deep Learning for Nonlinear Diffractive Imaging

text: Image reconstruction under multiple light scattering is crucial for a number of important applications in cell microscopy and tissue imaging. The reconstruction problem is often formulated as a nonconvex optimization, where a nonlinear measurement model is used to account for multiple scattering and a regularizer is used to enforce the prior on the object. In this letter, We propose a powerful alternative to this optimization-based view of image reconstruction by designing and training a deep convolutional neural network (CNN) for inverting multiple scattering. Simulations show that the proposed formulation is substantially faster and achieves higher imaging quality compared to the state-of-the-art methods based on optimization.


title: B2W2: N-Way Concurrent Communication for IoT Devices

text: The exponentially increasing number of internet of things (IoT) devices and the data generated by these devices introduces the spectrum crisis at the already crowded ISM 2.4 GHz band. To address this issue and enable more flexible and concurrent communications among IoT devices, we propose B2W2, a novel communication framework that enables N-way concurrent communication among WiFi and Bluetooth Low Energy (BLE) devices. Specifically, we demonstrate that it is possible to enable the BLE to WiFi cross-technology communication while supporting the concurrent BLE to BLE and WiFi to WiFi communications. We conducted extensive experiments under different real-world settings and results show that its throughput is more than 85X times higher than the most recently reported cross-technology communication system [22], which only supports one-way communication (i.e., broadcasting) at any specific time.


title: A study of big data processing constraints on a low-power Hadoop cluster

text: Big Data processing with Hadoop has been emerging recently, both on the computing cloud and enterprise deployment. However, wide-spread security exploits may hurt the reputation of public clouds. If Hadoop on the cloud is not an option, an organization has to build its own Hadoop clusters. But having a data center is not worth for a small organization both in terms of building and operating costs. Another viable solution is to build a cluster with low-cost ARM system-on-chip boards. This paper presents a study of a Hadoop cluster for processing Big Data built atop 22 ARM boards. The Hadoop's MapReduce was replaced by Spark and experiments on three different hardware configurations were conducted to understand limitations and constraints of the cluster. From the experimental results, it can be concluded that processing Big Data on an ARM cluster is highly feasible. The cluster could process a 34 GB Wikipedia article file in acceptable time, while generally consumed the power 0.061-0.322 kWh for all benchmarks. It has been found that I/O of the hardware is fast enough, but the power of CPUs is inadequate because they are largely spent for the Hadoop's I/O.


title: Selective Intervention and Internal Hybrids: Interpreting and Learning from the Rise and Decline of the Oticon Spaghetti Organization

text: Infusing hierarchies with elements of market control has become a much-used way of simultaneously increasing entrepreneurialism and motivation in firms. However, this paper argues that such “internal hybrids,” particularly in their radical forms, are inherently hard to successfully design and implement, because of fundamental credibility problems related to managerial promises to not intervene in delegated decision-making  an incentive problem that is often referred to as the “problem of selective intervention.” This theoretical theme is developed and illustrated, using the case of the world-leading Danish hearing aids producer, Oticon. In the beginning of the 1990s, Oticon became famous for its radical internal hybrid, the ”spaghetti organization.” Recent work has interpreted the spaghetti organization as a radical attempt to foster dynamic capabilities by imposing loose coupling on the organization, neglecting, however, that about a decade later, the spaghetti organization has given way to a more traditional matrix organization. This paper presents an organizational economics interpretation of organizational changes in Oticon, and argues that a strong liability of the spaghetti organization was the above incentive problem. Motivation in Oticon was strongly harmed by selective intervention on the part of top-management Changing the organizational structure was one means of repairing these motivational problems. Refutable implications are developed, both for the understanding of efficient design of internal hybrids, and for the more general issue of the distinction between firms and markets, as well as the choice between internal and external hybrids.


title: Optimizing 360 video delivery over cellular networks

text: As an important component of the virtual reality (VR) technology, 360-degree videos provide users with panoramic view and allow them to freely control their viewing direction during video playback. Usually, a player displays only the visible portion of a 360 video. Thus, fetching the entire raw video frame wastes bandwidth. In this paper, we consider the problem of optimizing 360 video delivery over cellular networks. We first conduct a measurement study on commercial 360 video platforms. We then propose a cellular-friendly streaming scheme that delivers only 360 videos' visible portion based on head movement prediction. Using viewing data collected from real users, we demonstrate the feasibility of our approach, which can reduce bandwidth consumption by up to 80% based on a trace-driven simulation.


title: Investigation of safety in human-robot-interaction for a series elastic, tendon-driven robot arm

text: This paper presents the design of the lightweight BioRob manipulator with spring-loaded tendon-driven actuation developed for safe physical human-robot interaction. The safety of the manipulator is analyzed by an analytical worst-case estimation of impact and clamping forces in the absence of collision detection. As intrinsic joint compliance can pose a threat by storing energy, a safety evaluation method is proposed taking the potential energy stored in the elastic actuation into account. The evaluation shows that the robot arm design constrains the worst case clamping forces to only 25 N, while being able to handle loads up to 2 kg, and inherits extremely low impact properties, such as an effective mass of less than 0.4 kg in non near-singular configurations, enabling safe operation even in case of high velocities. The results are validated in simulation and experiments.


title: Accidental scald burns in sinks.

text: Scald burns to the feet and lower extremities in children are described in the literature as often resulting from forced immersions. This report illustrates 3 cases of burns whose distribution and historical factors identify them as accidental. The location of these accidental burns is similar to those found in inflicted injury, but the patterns were indicative of flowing water burns, not forced immersions. Burns in these locations may be confused with abuse. Medical providers need to be aware of information that may enable them to distinguish the 2 causes. Effective caregiver education regarding the importance of lowering the temperature of water heaters and discouraging play in household sinks is critical to prevent additional tap water scald burn injuries.


title: A Reconfigurable Antenna With Frequency and Polarization Agility

text: A new antenna with both frequency and polarization reconfigurability is presented. The antenna consists of a square microstrip patch with a single probe feed located along the diagonal line. The center of each edge of the patch is connected to a shorting post via a p-i-n diode for polarization switching and two varactor diodes for frequency tuning. By switching between the different states of the p-i-n diodes, the proposed antenna can produce radiation patterns with horizontal, vertical, or 45° linear polarization. By varying the dc bias voltage, the operating frequency of each polarization of the antenna can be independently tuned. The frequency tuning range is from 1.35 to 2.25 GHz (|S11| <; -10 dB) for either horizontal or vertical polarization and from 1.35 to 1.9 GHz for the 45° linear polarization. Measured results on frequency tuning ranges and radiation patterns agree well with numerical simulations.


title: Wideband Circular Polarization Reconfigurable Antenna

text: This communication introduces a polarization reconfigurable wideband circularly polarized (CP) antenna, which consists of four radiating arms connected to a reconfigurable feeding network. The four radiating arms excited by the feeding network are able to generate wideband CP waves with bidirectional radiation patterns in free space. In order to increase the gain and obtain a broadside radiation pattern, the proposed antenna is placed above a metallic reflector with the distance of quarter wavelength at the center frequency. In addition, polarization reconfigurability is realized by utilizing PIN diodes in the feeding transmission lines such that left-handed circular polarization (LHCP) and right-handed circular polarization (RHCP) modes can be selectively excited by controlling the on/off states of the PIN diodes. The proposed antenna exhibits a wide impedance bandwidth of 80% and an overlapped axial ratio (AR) bandwidth of 23.5% for both modes. The antenna gain is stable across the operating bandwidth with the peak gain of 4.8 dBic. The antenna has a wide AR beamwidth of 90°. The presented work is suitable for GPS, CNSS, or RFID applications.


of Aperture Coupled Microstrip Antennas : History , Operation , Development , and Applications


title: Reconfigurable Antennas

text: Reconfigurable antennas change polarization, operating frequency, or far-field pattern in order to cope with changing system parameters. This paper reviews some of the past and current technology applicable to reconfigurable antennas, with several examples of implementations. Mechanically movable parts and arrays are discussed, as well as more-recent semiconductor-component and tunable-material technologies applicable to reconfigurable antennas.


title: High Beam Steering in Fabry–Pérot Leaky-Wave Antennas

text: A high-gain low-profile Fabry-Perot (FP) leaky-wave antenna (LWA) presenting one-dimensional high beam steering properties is proposed in this letter. The structure consists of a ground plane and a varying inductive partially reflective surface (PRS). A microstrip patch antenna is embedded into the cavity to act as the primary feed. As design examples, antennas are designed to operate at 9.5 GHz. Subwavelength FP cavities with fixed overall thickness of λ0 /6 (where λ0 is the free-space operating wavelength) are fabricated and measured. The impact of varying the PRS inductance is analyzed. It is shown that a high beam steering angle from broadside toward endfire direction close to 60 can be obtained when judiciously designing the inductive grid of the PRS.


title: Giving voice to office customers: Best practices in how office handles verbatim text feedback

text: Microsoft Office users submit hundreds of thousands of pieces of verbatim feedback per month. How can an engineer or manager in Office find the signal in this data to make business decisions? This paper presents an overview of the Office Customer Voice (OCV) system. OCV combines classification, on-demand clustering and other machine learning techniques with a rich web UI to solve this problem. In this paper, we describe the different types of feedback received. Next, we outline the architecture used to build OCV. We then detail the text processing, classification and clustering done to reason on the data. Finally, we present challenges, future plans, and best practices that may be relevant to other teams analyzing customer feedback. We argue that this multi-pronged approach to handling customer feedback presents a pattern that other organizations can use to mature their handling of customer feedback.


title: Evaluating data storage structures of MapReduce

text: MapReduce framework and its open-source implementation Hadoop, a scalable and fault-tolerant infrastructure for big data analysis on large clusters, can achieve different performance with different data storage structures. This paper evaluates the performance about three kinds of data storage structures of MapReduce, namely row-store, column-store, and RCFile. The evaluating experiments are designed to test three data storage structures in terms of data loading time, data storage space, and query execution time. The experimental results show that RCFile data storage structure can achieve better performance in most cases.


title: An Optimal Algorithm for Mutual Exclusion in Computer Networks

text: An algorithm is proposed that creates mutual exclusion in a computer network whose nodes communicate only by messages and do not share memory. The algorithm sends only 2*(N 1) messages, where N is the number of nodes in the network per critical section invocation. This number of messages is at a minimum if parallel, distributed, symmetric control is used; hence, the algorithm is optimal in this respect. The time needed to achieve mutual exclusion is also minimal under some general assumptions. As in Lamport's "bakery algorithm," unbounded sequence numbers are used to provide first-come firstserved priority into the critical section. It is shown that the number can be contained in a fixed amount of memory by storing it as the residue of a modulus. The number of messages required to implement the exclusion can be reduced by using sequential node-by-node processing, by using broadcast message techniques, or by sending information through timing channels. The "readers and writers" problem is solved by a simple modification of the algorithm and the modifications necessary to make the algorithm robust are described.


title: M2U-Net: Effective and Efficient Retinal Vessel Segmentation for Resource-Constrained Environments

text: In this paper, we present a novel neural network architecture for retinal vessel segmentation that improves over the state of the art on two benchmark datasets, is the first to run in real time on high resolution images, and its small memory and processing requirements make it deployable in mobile and embedded systems. The M2U-Net has a new encoder-decoder architecture that is inspired by the U-Net. It adds pretrained components of MobileNetV2 in the encoder part and novel contractive bottleneck blocks in the decoder part that, combined with bilinear upsampling, drastically reduce the parameter count to 0.55M compared to 31.03M in the original U-Net. We have evaluated its performance against a wide body of previously published results on three public datasets. On two of them, the M2U-Net achieves new state-of-the-art performance by a considerable margin. When implemented on a GPU, our method is the first to achieve real-time inference speeds on high-resolution fundus images. We also implemented our proposed network on an ARM-based embedded system where it segments images in between 0.6 and 15 sec, depending on the resolution. Thus, the M2U-Net enables a number of applications of retinal vessel structure extraction, such as early diagnosis of eye diseases, retinal biometric authentication systems, and robot assisted microsurgery.


title: GIS METHODS IN TIME-GEOGRAPHIC RESEARCH: GEOCOMPUTATION AND GEOVISUALIZATION OF HUMAN ACTIVITY PATTERNS

text: Over the past 40 years or so, human activities and movements in space-time have attracted considerable research interest in geography. One of the earliest analytical perspectives for the analysis of human activity patterns and movements in spacetime is time geography. Despite the usefulness of time geography in many areas of geographical research, there are very few studies that actually implemented its constructs as analytical methods up to the mid-1990s. With increasing availability of geo-referenced individual-level data and improvement in the geo-computational capabilities of Geographical Information Systems (GIS), it is now more feasible than ever before to operationalize and implement time-geographic constructs. This paper discusses recent applications of GIS-based geo-computation and three-dimensional (3-D) geo-visualization methods in time-geographic research. The usefulness of these methods is illustrated through examples drawn from the author’s recent studies. The paper attempts to show that GIS provides an effective environment for implementing timegeographic constructs and for the future development of operational methods in time-geographic research.


title: SHiP: Signature-based Hit Predictor for high performance caching

text:
The shared last-level caches in CMPs play an important role in improving application performance and reducing off-chip memory bandwidth requirements. In order to use LLCs more efficiently, recent research has shown that changing the re-reference prediction on cache insertions and cache hits can significantly improve cache performance. A fundamental challenge, however, is how to best predict the re-reference pattern of an incoming cache line.
 This paper shows that cache performance can be improved by correlating the re-reference behavior of a cache line with a unique signature. We investigate the use of memory region, program counter, and instruction sequence history based signatures. We also propose a novel Signature-based Hit Predictor (SHiP) to learn the re-reference behavior of cache lines belonging to each signature. Overall, we find that SHiP offers substantial improvements over the baseline LRU replacement and state-of-the-art replacement policy proposals. On average, SHiP improves sequential and multiprogrammed application performance by roughly 10% and 12% over LRU replacement, respectively. Compared to recent replacement policy proposals such as Seg-LRU and SDBP, SHiP nearly doubles the performance gains while requiring less hardware overhead.


Discrete-time signal processing (2nd ed.)


title: A Multiband Dual-Polarized Omnidirectional Antenna for 2G/3G/LTE Applications

text: A multiband dual-polarized omnidirectional antenna for 2G/3G/Long Term Evolution (LTE) mobile communications is proposed in this letter, which consists of horizontal polarization (HP) and vertical polarization (VP) element with separate feeds. The VP element consists of three polygonal radiation patches with three equally spaced legs shorted to the ground plane. The HP element consists of three wideband slot loop structures, which is nested on the top of the VP element. Three slot loop structures provide a 360° coverage for HP and enhance its bandwidth. Both the simulated and measured results indicate that the frequency bands of 1650–2900 MHz for HP and 780–2700 MHz for VP can be achieved. The reflection of VP improves the gain of the HP element at least 1 dBi after nesting. The gain of HP element is more than 3 dBi for LTE, and the gain of VP element is more than 5 dBi in the LTE band and 1.5 dBi in the 2G band. Port isolation larger than 30 dB and low-gain variation levels are also obtained. The proposed antenna can be applied in mobile communications.


title: Automatic Detection and Quantification of WBCs and RBCs Using Iterative Structured Circle Detection Algorithm

text: Segmentation and counting of blood cells are considered as an important step that helps to extract features to diagnose some specific diseases like malaria or leukemia. The manual counting of white blood cells (WBCs) and red blood cells (RBCs) in microscopic images is an extremely tedious, time consuming, and inaccurate process. Automatic analysis will allow hematologist experts to perform faster and more accurately. The proposed method uses an iterative structured circle detection algorithm for the segmentation and counting of WBCs and RBCs. The separation of WBCs from RBCs was achieved by thresholding, and specific preprocessing steps were developed for each cell type. Counting was performed for each image using the proposed method based on modified circle detection, which automatically counted the cells. Several modifications were made to the basic (RCD) algorithm to solve the initialization problem, detecting irregular circles (cells), selecting the optimal circle from the candidate circles, determining the number of iterations in a fully dynamic way to enhance algorithm detection, and running time. The validation method used to determine segmentation accuracy was a quantitative analysis that included Precision, Recall, and F-measurement tests. The average accuracy of the proposed method was 95.3% for RBCs and 98.4% for WBCs.


title: Social Honeypots: Making Friends With A Spammer Near You

text: Social networking communities have become an important communications platform, but the popularity of these communities has also made them targets for a new breed of social spammers. Unfortunately, little is known about these social spammers, their level of sophistication, or their strategies and tactics. Thus, in this paper, we provide the first characterization of social spammers and their behaviors. Concretely, we make two contributions: (1) we introduce social honeypots for tracking and monitoring social spam, and (2) we report the results of an analysis performed on spam data that was harvested by our social honeypots. Based on our analysis, we find that the behaviors of social spammers exhibit recognizable temporal and geographic patterns and that social spam content contains various distinguishing characteristics. These results are quite promising and suggest that our analysis techniques may be used to automatically identify social spam.


title: Monolithic DC-DC boost converter with current-mode hysteretic control

text: A monolithic DC-DC boost converter with current-mode hysteretic control is designed and simulated in 0.18-μm CMOS technology. The system is simple, robust, and has a fast response to external changes. It does not require an external clock, and the output is regulated by voltage feedback in addition to limiting the inductor current by sensing it. A non-overlapping clock is internally generated to drive the power switches using buffers designed to minimize power dissipation. For conversion specifications of 1.8 V to 3.3 V at 150 mA, overall efficiency of 94.5% is achieved. Line regulation is 17.5 mV/V, load regulation is 0.33% for a 100 mA current step, while the output voltage ripple is below 30 mV for nominal conditions.


title: Least-Squares Fitting of Circles and Ellipses ∗

text: Fitting circles and ellipses to given points in the plane is a problem that arises in many application areas, e.g. computer graphics [1], coordinate metrology [2], petroleum engineering [11], statistics [7]. In the past, algorithms have been given which fit circles and ellipses in some least squares sense without minimizing the geometric distance to the given points [1], [6]. In this paper we present several algorithms which compute the ellipse for which the sum of the squares of the distances to the given points is minimal. These algorithms are compared with classical simple and iterative methods. Circles and ellipses may be represented algebraically i.e. by an equation of the form F (x) = 0. If a point is on the curve then its coordinates x are a zero of the function F . Alternatively, curves may be represented in parametric form, which is well suited for minimizing the sum of the squares of the distances. 1 Preliminaries and Introduction Ellipses, for which the sum of the squares of the distances to the given points is minimal will be referred to as “best fit” or “geometric fit”, and the algorithms will be called “geometric”. Determining the parameters of the algebraic equation F (x) = 0 in the least squares sense will be denoted by “algebraic fit” and the algorithms will be called “algebraic”. We will use the well known Gauss-Newton method to solve the nonlinear least squares problem (cf. [15]). Let u = (u1, . . . , un) T be a vector of unknowns and consider the nonlinear system of m equations f(u) = 0. If m > n, then we want to minimize


title: Measures of retaining digital evidence to prosecute computer-based cyber-crimes

text: With the rapid growth of computer and network systems in recent years, there has also been a corresponding increase in cyber-crime. Cybercrime takes many forms and has garnered much attention in the media, making information security a more urgent and important priority. In order to fight cyber-crime, criminal evidence must be gathered from these computer-based systems. This is quite different from the collection of conventional criminal evidence and can confuse investigators attempting to deal with the forensics of cyber-crime, highlighting the importance of computer forensics. In this paper, we offer solutions to guard against cyber-crime through the implementation of software toolkits for computerbased systems. In this way, those who engage in criminal acts in cyber-space can be more easily apprehended. © 2006 Elsevier B.V. All rights reserved.


title: Obesity, fat distribution, and weight gain as risk factors for clinical diabetes in men.

text:
OBJECTIVE
To investigate the relation between obesity, fat distribution, and weight gain through adulthood and the risk of non-insulin-dependent diabetes mellitus (NIDDM).

RESEARCH DESIGN AND METHODS
We analyzed data from a cohort of 51,529 U.S. male health professionals, 40-75 years of age in 1986, who completed biennial questionnaires sent out in 1986, 1988, 1990, and 1992. During 5 years of follow-up (1987-1992), 272 cases of NIDDM were diagnosed among men without a history of diabetes, heart disease, and cancer in 1986 and who provided complete health information. Relative risks (RRs) associated with different anthropometric measures were calculated controlling for age, and multivariate RRs were calculated controlling for smoking, family history of diabetes, and age.

RESULTS
We found a strong positive association between overall obesity as measured by body mass index (BMI) and risk of diabetes. Men with a BMI of > or = 35 kg/m2 had a multivariate RR of 42.1 (95% confidence interval [CI] 22.0-80.6) compared with men with a BMI < 23.0 kg/m2. BMI at age 21 and absolute weight gain throughout adulthood were also significant independent risk factors for diabetes. Fat distribution, measured by waist-to-hip ratio (WHR), was a good predictor of diabetes only among the top 5%, while waist circumference was positively associated with the risk of diabetes among the top 20% of the cohort.

CONCLUSIONS
These data suggest that waist circumference may be a better indicator than WHR of the relationship between abdominal adiposity and risk of diabetes. Although early obesity, absolute weight gain throughout adulthood, and waist circumference were good predictors of diabetes, attained BMI was the dominant risk factor for NIDDM; even men of average relative weight had significantly elevated RRs.


title: A Highly Linear Two-Stage Amplifier Integrated Circuit Using InGaP/GaAs HBT

text: This paper presents a linearized two-stage amplifier integrated circuit (IC), having an output power level of about 1 Watt, used for general purpose applications. A predistortion method, based on alignment of the nonlinear characteristics between the first- and the second-stage amplifiers, has been proposed and analyzed in order to enhance the linearization aspects. The resistors in the active bias circuits of both the stages are optimized to achieve the best cancellation conditions for the third-order intermodulation components. The two-stage amplifier IC, which is based on an InGaP/GaAs hetero-junction bipolar transistor (HBT) technology, has been designed and implemented for the 900 MHz band. An output 1 dB compression point (P1dB) of 29.6 dBm, a maximum third-order output intercept point (OIP3) of as high as 48.7 dBm at a two-tone average output power of 21 dBm have been obtained while having a quiescent current of 375 mA and a single bias supply of 5.5 V. The implemented amplifier is able to maintain its IMD3 performance below -60 dBc up to an output power of 21 dBm.


title: REAL TIME HAND GESTURE RECOGNITION USING SIFT

text: The objective of the gesture recognition is to identify and distinguish the human gestures and utilizes these identified gestures for applications in specific domain. In this paper we propose a new approach to build a real time system to identify the standard gesture given by American Sign Language, or ASL, the dominant sign language of Deaf Americans, including deaf communities in the United States, in the English-speaking parts of Canada, and in some regions of Mexico. We propose a new method of improvised scale invariant feature transform (SIFT) and use the same to extract the features. The objective of the paper is to decode a gesture video into the appropriate alphabets.


title: Improved Training of Generative Adversarial Networks Using Representative Features

text: Despite the success of generative adversarial networks (GANs) for image generation, the trade-off between visual quality and image diversity remains a significant issue. This paper achieves both aims simultaneously by improving the stability of training GANs. The key idea of the proposed approach is to implicitly regularize the discriminator using representative features. Focusing on the fact that standard GAN minimizes reverse Kullback-Leibler (KL) divergence, we transfer the representative feature, which is extracted from the data distribution using a pre-trained autoencoder (AE), to the discriminator of standard GANs. Because the AE learns to minimize forward KL divergence, our GAN training with representative features is influenced by both reverse and forward KL divergence. Consequently, the proposed approach is verified to improve visual quality and diversity of state of the art GANs using extensive evaluations.


title: Functional inactivation of the amygdala before but not after auditory fear conditioning prevents memory formation.

text: Two competing theories predict different effects on memory consolidation when the amygdala is inactivated after fear conditioning. One theory, based on studies using inhibitory avoidance training, proposes that the amygdala modulates the strength of fear learning, and post-training amygdala manipulations interfere with memory consolidation. The other, based on studies using Pavlovian fear conditioning, hypothesizes that fear learning occurs in the amygdala, and post-training manipulations after acquisition will not affect memory consolidation. We infused the GABAA agonist muscimol (4.4 nmol/side) or vehicle into lateral and basal amygdala (LBA) of rats either before or immediately after tone-foot shock Pavlovian fear conditioning. Pre-training infusions eliminated acquisition, whereas post-training infusions had no effect. These findings indicate that synaptic activity in LBA is necessary during learning, but that amygdala inactivation directly after training does not affect memory consolidation. Results suggest that essential aspects of plasticity underlying auditory fear conditioning take place within LBA during learning.


title: BitDeposit: Deterring Attacks and Abuses of Cloud Computing Services through Economic Measures

text: Dependability in cloud computing applications can be negatively affected by various attacks or service abuses. To come ahead of this threat, we propose an economic measure to deter attacks and various service abuses in cloud computing applications. Our proposed defense is based on requiring a service user to pay a small deposit, using digital currency, before invoking the service. Once they are done using the service, and there has been no detected abuse or attack, the deposit is paid back by the service provider to the service user. If an attack or an abuse is detected, the service user is not paid back and the service provider gets to keep the deposit. We propose the use of micro payments with a decentralized nature and small transaction fees, such as the Bit coin digital currency. Moreover, thanks to the existence of money exchanges which convert the Bit coin currency to real world currency, service providers can recoup loses when they exchange the confiscated deposits for real world currency.


title: Multi-channel ECG classification using forests of randomized shapelet trees

text: Data series of multiple channels occur at high rates and in massive quantities in several application domains, such as healthcare. In this paper, we study the problem of multi-channel ECG classification. We map this problem to multivariate data series classification and propose five methods for solving it, using a split-and-combine approach. The proposed framework is evaluated using three base-classifiers on real-world data for detecting Myocardial Infarction. Extensive experiments are performed on real ECG data extracted from the Physiobank data repository. Our findings emphasize the importance of selecting an appropriate base-classifier for multivariate data series classification, while demonstrating the superiority of the Random Shapelet Forest (0.825 accuracy) against competitor methods (0.664 accuracy for 1-NN under cDTW).


title: Getting Physical with the Digital Investigation Process

text: In this paper, a process model for digital investigations is defined using the theories and techniques from the physical investigation world. While digital investigations have recently become more common, physical investigations have existed for thousands of years and the experience from them can be applied to the digital world. This paper introduces the notion of a digital crime scene with its own witnesses, evidence, and events that can be investigated using the same model as a physical crime scene. The proposed model integrates the physical crime scene investigation with the digital crime scene investigation to identify a person who is responsible for the digital activity. The proposed model applies to both law enforcement and corporate investigations.


title: Digital Forensic Model Based On Malaysian Investigation Process

text: Faculty Of Science & Technology Islamic Science University Of Malaysia Summary With the proliferation of the digital crime around the world, numerous digital forensic investigation models already being develop .In fact many of the digital forensic investigation model focus on technical implementation of the investigation process as most of it develop by traditional forensic expert and technologist. As an outcome of this problem most of the digital forensic practitioners focus on technical aspect and forget the core concept of digital forensic investigation model .In this paper we are introducing a new digital forensic model which will be capture a full scope of an investigation process based on Malaysia Cyber Law .The proposed model is also compared with the existing model which currently available and being apply in the investigation process.


title: A hierarchical, objectives-based framework for the digital investigations process

text: Although digital forensics investigations can vary drastically in their level of complexity, each investigative process must follow a rigorous path. Previously proposed frameworks are predominantly single-tier, higher order process models, focusing on the abstract, rather than more concrete principles of the investigation. We contend that these frameworks, although useful in explaining overarching concepts, require additional detail in order to be useful to investigators and researchers. We therefore propose a multi-tier, hierarchical framework to guide digital investigations. Our framework includes objectivesbased sub-phases that are applicable to various layers of abstraction.


title: An Extended Model of Cybercrime Investigations

text: A comprehensive model of cybercrime investigations is important for standardising terminology, defining requirements, and supporting the development of new techniques and tools for investigators. In this paper a model of investigations is presented which combines the existing models, generalises them, and extends them by explicitly addressing certain activities not included in them. Unlike previous models, this model explicitly represents the information flows in an investigation and captures the full scope of an investigation, rather than only the processing of evidence. The results of an evaluation of the model by practicing cybercrime investigators are presented. This new model is compared to some important existing models and applied to a real investigation.


title: Defining Digital Forensic Examination and Analysis Tool Using Abstraction Layers

text: This paper uses the theory of abstraction layers to describe the purpose and goals of digital forensic analysis tools. Using abstraction layers, we identify where tools can introduce errors and provide requirements that the tools must follow. Categories of forensic analysis types are also defined based on the abstraction layers. Abstraction layers are not a new concept, but their usage in digital forensic analysis is not well documented.


title: Faster Dual-Key Stealth Address for Blockchain-Based Internet of Things Systems

text: Stealth address prevents public association of a blockchain transaction’s output with a recipient’s wallet address and hides the actual destination address of a transaction. While stealth address provides an effective privacy-enhancing technology for a cryptocurrency network, it requires blockchain nodes to actively monitor all the transactions and compute the purported destination addresses, which restricts its application for resource-constrained environments like Internet of Things (IoT). In this paper, we propose DKSAP-IoT, a faster dual-key stealth address protocol for blockchain-based IoT systems. DKSAP-IoT utilizes a technique similar to the TLS session resumption to improve the performance and reduce the transaction size at the same time between two communication peers. Our theoretical analysis as well as the extensive experiments on an embedded computing platform demonstrate that DKSAPIoT is able to reduce the computational overhead by at least 50% when compared to the state-of-the-art scheme, thereby paving the way for its application to blockchain-based IoT systems.


title: The earth is flat (p > 0.05): significance thresholds and the crisis of unreplicable research

text: The widespread use of 'statistical significance' as a license for making a claim of a scientific finding leads to considerable distortion of the scientific process (according to the American Statistical Association). We review why degrading p-values into 'significant' and 'nonsignificant' contributes to making studies irreproducible, or to making them seem irreproducible. A major problem is that we tend to take small p-values at face value, but mistrust results with larger p-values. In either case, p-values tell little about reliability of research, because they are hardly replicable even if an alternative hypothesis is true. Also significance (p ≤ 0.05) is hardly replicable: at a good statistical power of 80%, two studies will be 'conflicting', meaning that one is significant and the other is not, in one third of the cases if there is a true effect. A replication can therefore not be interpreted as having failed only because it is nonsignificant. Many apparent replication failures may thus reflect faulty judgment based on significance thresholds rather than a crisis of unreplicable research. Reliable conclusions on replicability and practical importance of a finding can only be drawn using cumulative evidence from multiple independent studies. However, applying significance thresholds makes cumulative knowledge unreliable. One reason is that with anything but ideal statistical power, significant effect sizes will be biased upwards. Interpreting inflated significant results while ignoring nonsignificant results will thus lead to wrong conclusions. But current incentives to hunt for significance lead to selective reporting and to publication bias against nonsignificant findings. Data dredging, p-hacking, and publication bias should be addressed by removing fixed significance thresholds. Consistent with the recommendations of the late Ronald Fisher, p-values should be interpreted as graded measures of the strength of evidence against the null hypothesis. Also larger p-values offer some evidence against the null hypothesis, and they cannot be interpreted as supporting the null hypothesis, falsely concluding that 'there is no effect'. Information on possible true effect sizes that are compatible with the data must be obtained from the point estimate, e.g., from a sample average, and from the interval estimate, such as a confidence interval. We review how confusion about interpretation of larger p-values can be traced back to historical disputes among the founders of modern statistics. We further discuss potential arguments against removing significance thresholds, for example that decision rules should rather be more stringent, that sample sizes could decrease, or that p-values should better be completely abandoned. We conclude that whatever method of statistical inference we use, dichotomous threshold thinking must give way to non-automated informed judgment.


title: Bootstrapping Fine-Grained Classifiers : ! Active Learning with a Crowd in the Loop

text: We propose an iterative crowd-enabled active learning algorithm for building high-precision visual classifiers from unlabeled images. Our method employs domain experts to identify a small number of examples of a specific visual event. These expert-labeled examples seed a classifier, which is then iteratively trained by active querying of a non-expert crowd. These non-experts actively refine the classifiers at every iteration by answering simple binary questions about the classifiers’ detections. The advantage of this approach is that experts efficiently shepherd an unsophisticated crowd into training a classifier capable of fine-grained distinctions. This obviates the need to label an entire dataset to obtain high-precision classifiers. We find these classifiers are advantageous for creating a large vocabulary of visual attributes for specialized taxonomies. We demonstrate our crowd active learning pipeline by creating classifiers for attributes related to North American birds and fashion.


title: Outlooks and Insights on Group Decision and Negotiation

text: Community governance needs a small group discussion among community people to identify their concerns, to share them each other and to generate better alternatives for solving problems. A planner should manage the discussion to achieve these objectives. This study analyzed the small group discussion in the community disaster risk management by using text mining. Correspondence analysis was applied to the text data of the discussion. Analytical results revealed the characteristics and effects of small group discussion.


title: Validating Formative Partial Least Squares (PLS) Models: Methodological Review and Empirical Illustration

text: The issue of formative constructs, as opposed to th e more frequently used reflective ones, has recently gained momentum among IS and Management re searchers. Most researchers maintain that formative constructs have been understudied, a n that there is paucity in methodological literature to guide researchers on how such constru cts should be developed and estimated. A survey of IS research has revealed that about 29% o f constructs were misspecified as reflective rather than formative constructs. Furthermore, guid elines about how models containing formative constructs should be indentified and estimated are fragmented and inconsistent. Thus, this paper aims to present a methodological review of formativ e model identification and evaluation. We bring a brief theoretical overview of formative con structs, and put together a guideline for estimating formative measurement and structural mod els. We then present a simplified model composed of three formative constructs and illustra te how it is assessed and estimated using


title: Spatial Diversity 24-GHz FMCW Radar With Ground Effect Compensation for Automotive Applications

text: In automotive radar applications, a realistic road surface can cause multipath reflection, degrade the received power, and reduce detection probability. This paper proposes a one-transmitter–two-receiver (1T2R) 24-GHz frequency-modulation continuous-wave (FMCW) radar architecture with spatial diversity and ground effect compensation for automotive applications. A ray-tracing technique was developed to evaluate the multipath effect of the road surface. In the proposed design, suitable spacing between the two receiving antennas compensated for the multipath effect of the road surface and improved the signal-to-ground clutter ratio of the receivers by a minimum of 20 dB at certain distances. The measurement and calculation results of the proposed radar are in close agreement.


title: PLINK: a tool set for whole-genome association and population-based linkage analyses.

text: Whole-genome association studies (WGAS) bring new computational, as well as analytic, challenges to researchers. Many existing genetic-analysis tools are not designed to handle such large data sets in a convenient manner and do not necessarily exploit the new opportunities that whole-genome data bring. To address these issues, we developed PLINK, an open-source C/C++ WGAS tool set. With PLINK, large data sets comprising hundreds of thousands of markers genotyped for thousands of individuals can be rapidly manipulated and analyzed in their entirety. As well as providing tools to make the basic analytic steps computationally efficient, PLINK also supports some novel approaches to whole-genome data that take advantage of whole-genome coverage. We introduce PLINK and describe the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation. In particular, we focus on the estimation and use of identity-by-state and identity-by-descent information in the context of population-based whole-genome studies. This information can be used to detect and correct for population stratification and to identify extended chromosomal segments that are shared identical by descent between very distantly related individuals. Analysis of the patterns of segmental sharing has the potential to map disease loci that contain multiple rare variants in a population-based linkage analysis.


title: Future Shipboard MVdc System Protection Requirements and Solid-State Protective Device Topological Tradeoffs

text: The search for the optimum architecture for shipboard medium voltage dc integrated power systems must take into account the short-circuit protection in addition to overarching goals of efficiency, survivability, reliability of power, and cost effectiveness. Presently, accepted approaches to protection are “unit-based,” which means the power converter(s) feeding the bus coordinate with no-load electromechanical switches to isolate faulted portions of the bus. However, “breaker-based” approaches, which rely upon solid-state circuit breakers for fault mitigation, can result in higher reliability of power and potentially higher survivability. The inherent speed of operation of solid-state protective devices will also play a role in fault isolation, hence reducing stress level on all system components. A comparison study is performed of protective device topologies that are suitable for shipboard distribution systems rated between 4 and 30 kVdc from the perspectives of size and number of passive components required to manage the commutation energy during sudden fault events and packaging scalability to higher current and voltage systems. The implementation assumes a multichip silicon carbide (SiC) 10-kV, 240-A MOSFET/junction barrier Schottkey (JBS) diode module.


title: Informing the Design of Spoken Conversational Search: Perspective Paper

text: We conducted a laboratory-based observational study where pairs of people performed search tasks communicating verbally. Examination of the discourse allowed commonly used interactions to be identified for Spoken Conversational Search (SCS). We compared the interactions to existing models of search behaviour. We find that SCS is more complex and interactive than traditional search. This work enhances our understanding of different search behaviours and proposes research opportunities for an audio-only search system. Future work will focus on creating models of search behaviour for SCS and evaluating these against actual SCS systems.


title: Interference cancellation for cellular systems: a contemporary overview

text: Cellular networks today are interference-limited and only becomes increasingly so in the future due to the many users that need to share the spectrum to achieve high-rate multimedia communication. Despite the enormous amount of academic and industrial research in the past 20 years on interference-aware receivers and the large performance improvements promised by these multi-user techniques, today's receivers still generally treat interference as background noise. In this article, we enumerate the reasons for this widespread scepticism, and discuss how current and future trends increases the need for and viability of multi-user receivers for both the uplink, where many asynchronous users are simultaneously detected, and the downlink, where users are scheduled and largely orthogonalized; but the mobile handset still needs to cope with a few dominant interfering base stations. New results for interference cancelling receivers that use conventional front-ends are shown to alleviate many of the shortcomings of prior techniques, particularly for the challenging uplink. This article gives an overview of key recent research breakthroughs on interference cancellation and highlights system-level considerations for future multi-user receivers.


title: Active learning for online bayesian matrix factorization

text: The problem of large-scale online matrix completion is addressed via a Bayesian approach. The proposed method learns a factor analysis (FA) model for large matrices, based on a small number of observed matrix elements, and leverages the statistical model to actively select which new matrix entries/observations would be most informative if they could be acquired, to improve the model; the model inference and active learning are performed in an online setting. In the context of online learning, a greedy, fast and provably near-optimal algorithm is employed to sequentially maximize the mutual information between past and future observations, taking advantage of submodularity properties. Additionally, a simpler procedure, which directly uses the posterior parameters learned by the Bayesian approach, is shown to achieve slightly lower estimation quality, with far less computational effort. Inference is performed using a computationally efficient online variational Bayes (VB) procedure. Competitive results are obtained in a very large collaborative filtering problem, namely the Yahoo! Music ratings dataset.


title: Related Key Chosen IV Attack on Grain-128a Stream Cipher

text: The well-known stream cipher Grain-128 is a variant version of Grain v1 with 128-bit secret key. Grain v1 is a stream cipher which has successfully been chosen as one of seven finalists by European eSTREAM project. Yet Grain-128 is vulnerable against some recently introduced attacks. A new version of Grain-128 with authentication, named Grain-128a, is proposed by Ågren, Hell, Johansson, and Meier. The designers claimed that Grain-128a is strengthened against all known attacks and observations on the original Grain-128. So far there exists no attack on Grain-128a except a differential fault attack by Banik, Maitra, and Sarkar. In this paper, we give some observations on Grain-128a, and then propose a related key chosen IV attack on Grain-128a based on these observations. Our attack can recover the 128-bit secret key of Grain-128a with a computational complexity of <formula formulatype="inline"> <tex Notation="TeX">$2^{96.322} $</tex></formula>, requiring <formula formulatype="inline"> <tex Notation="TeX">$2^{96} $</tex></formula> chosen IVs and <formula formulatype="inline"><tex Notation="TeX">$2^{103.613} $</tex> </formula> keystream bits. The success probability of our attack is 0.632. This related key attack is “minimal” in the sense that it only requires two related keys. The result shows that our attack is much better than an exhaustive key search in the related key setting.


title: 16-Way Radial Divider/Combiner for Solid State Power Amplifiers in the K Band

text: This paper presents the design and measurement results of a 16-way radial power divider/combiner for solid state power amplifiers in the K band using an original assembly technique of the combined ways. The design is based on a radial non-resonant cavity connected to 8 peripheral rectangular waveguides with two waveguide-to-microstrip transitions inserted in each peripheral rectangular waveguide. Each combined way includes on the same tray the input and output waveguide-to-microstrip transitions and the MMIC amplifier location. The trays can be individually tested before mounting in the 16-way divider/combiner. The low insertion loss of the 16-way power divider/combiner leads to an estimated combining efficiency better than 86.5% from 16.5 GHz to 21 GHz with a maximum value about 88% from 17.2 to 19.2 GHz.


title: Accelerating and Compressing LSTM Based Model for Online Handwritten Chinese Character Recognition

text: With the development of deep learning tools, the online handwritten Chinese character recognition (HCCR) performance has been greatly improved by using deep neural networks (DNNs) especially for long short-term memory (LSTM). However, DNNs suffer from large consumption of computation and storage resources, which may cause problems for service providers, such as server pressure, longer service latency and higher energy consumption. To solve these problems, we propose a framework that combines singular value decomposition (SVD) and adaptive drop weight (ADW) to accelerate and compress LSTM based models. We first build an LSTM based model that achieves an accuracy of 97.83% on the ICDAR2013 online HCCR competition dataset. After restructuring the model with SVD and ADW, it can reduce the FLOPs (floating point operations per second) of the forward process by approximately 10 times and compress the model with 1/30 of the original size with only a 0.5% decrease in accuracy. Finally, integrated with our efficient forward implementation, the recognition of an online character requires only 2.7 ms in average on a CPU with a single thread, while requiring only 0.45 MB for model storage.


title: ASSESSMENT AND COLLABORATION IN ONLINE LEARNING

text: Assessment can be seen as the engine that drives student course activity, online or off. It is particularly important in encouraging and shaping collaborative activity online. This paper discusses three sorts of online collaborative activity—collaborative discussion, small group collaboration, and collaborative exams. In each of these areas, it provides both theoretical grounding and practical advice for assessing, and so encouraging, collaboration in online courses.


title: Statistical Parsing for harmonic Analysis of Jazz Chord Sequences

text: Analysing music resembles natural language parsing in requiring the derivation of structure from an unstructured and highly ambiguous sequence of elements, whether they are notes or words. Such analysis is fundamental to many music processing tasks, such as key identification and score transcription. The focus of the present paper is on harmonic analysis. We use the three-dimensional tonal harmonic space developed by [4, 13, 14] to define a theory of tonal harmonic progression, which plays a role analogous to semantics in language. Our parser applies techniques from natural language processing (NLP) to the problem of analysing harmonic progression. It uses a formal grammar of jazz chord sequences of a kind that is widely used for NLP, together with the statistically based modelling techniques standardly used in wide-coverage parsing, to map music onto underlying harmonic progressions in the tonal space. Using supervised learning over a small corpus of jazz chord sequences annotated with harmonic analyses, we show that grammar-based musical parsing using simple statistical parsing models is more accurate than a baseline Markovian model trained on the same corpus.


title: Smart-cap for pedestrian safety

text: In the last few decades, the use of mobile phones have increased rapidly. Safety experts have considered dependency on mobile phones as a threat to the pedestrian safety. In this paper, a wearable smart-cap has been proposed to detect an obstacle in the path of a pedestrian mobile user. The vision of the proposed system is to provide a user-friendly, cost effective and a quick way to avoid pedestrian accidents due to mobile phones. The volunteers' feedback and testing results have been outstanding. The volunteers have reported that the proposed system is user-friendly and accurate.


title: Towards a design generation methodology

text: Inspired by the recent advances of deep learning and computer graphics techniques in generating sophisticated artistic styles and architectural designs, we envision a general design generation methodology that uses various specification and generative methods and tools in an integral design cycle.


title: How data science can advance mental health research

text: Accessibility of powerful computers and availability of so-called big data from a variety of sources means that data science approaches are becoming pervasive. However, their application in mental health research is often considered to be at an earlier stage than in other areas despite the complexity of mental health and illness making such a sophisticated approach particularly suitable. In this Perspective, we discuss current and potential applications of data science in mental health research using the UK Clinical Research Collaboration classification: underpinning research; aetiology; detection and diagnosis; treatment development; treatment evaluation; disease management; and health services research. We demonstrate that data science is already being widely applied in mental health research, but there is much more to be done now and in the future. The possibilities for data science in mental health research are substantial. Russ et al. discuss the broad applications of data science to mental health research and consider future ways that big data can improve detection, diagnosis, treatment, healthcare provision and disease management.


title: Joint Embedding Models for Textual and Social Analysis

text: In online social networks, users openly interact, share content, and endorse each other. Although the data is interconnected, previous research has primarily focused on modeling the social network behavior separately from the textual content. Here we model the data in a holistic way, taking into account connections between social behavior and content. Specifically, we define multiple decision tasks over the relationships between users and the content generated by them. We show, on a real world dataset, that a learning a joint embedding (over user characteristics and language) and using joint prediction (based on intraand inter-task constraints) produces consistent gains over (1) learning specialized embeddings, and (2) predicting locally w.r.t. a single task, with or without constraints.