Query: A Novel Fast Framework for Topic Labeling Based on Similarity-preserved Hashing

Relevant passages:
Latent Dirichlet Allocation <=SEP=> We propose a generative model for text and other collections of discrete data that generalizes or improves on several previous models including naive Bayes/unigram, mixture of unigrams [6], and Hofmann's aspect model , also known as probabilistic latent semantic indexing (pLSI) [3]. In the context of text modeling, our model posits that each document is generated as a mixture of topics, where the continuous-valued mixture proportions are distributed as a latent Dirichlet random variable. Inference and learning are carried out efficiently via variational algorithms. We present empirical results on applications of this model to problems in text modeling, collaborative filtering, and text classification.

Similarity estimation techniques from rounding algorithms <=SEP=> (MATH) A locality sensitive hashing scheme is a distribution on a family $\F$ of hash functions operating on a collection of objects, such that for two objects <i>x,y</i>, <b>Pr</b><sub><i>h</i></sub>εF[<i>h</i>(<i>x</i>) = <i>h</i>(<i>y</i>)] = sim(<i>x,y</i>), where <i>sim</i>(<i>x,y</i>) ε [0,1] is some similarity function defined on the collection of objects. Such a scheme leads to a compact representation of objects so that similarity of objects can be estimated from their compact sketches, and also leads to efficient algorithms for approximate nearest neighbor search and clustering. Min-wise independent permutations provide an elegant construction of such a locality sensitive hashing scheme for a collection of subsets with the set similarity measure <i>sim</i>(<i>A,B</i>) = \frac{|A &Pgr; B|}{|A &Pgr B|}.(MATH) We show that rounding algorithms for LPs and SDPs used in the context of approximation algorithms can be viewed as locality sensitive hashing schemes for several interesting collections of objects. Based on this insight, we construct new locality sensitive hashing schemes for:<ol><li>A collection of vectors with the distance between → \over <i>u</i> and → \over <i>v</i> measured by Ø(→ \over <i>u</i>, → \over <i>v</i>)/π, where Ø(→ \over <i>u</i>, → \over <i>v</i>) is the angle between → \over <i>u</i>) and → \over <i>v</i>). This yields a sketching scheme for estimating the cosine similarity measure between two vectors, as well as a simple alternative to minwise independent permutations for estimating set similarity.</li><li>A collection of distributions on <i>n</i> points in a metric space, with distance between distributions measured by the Earth Mover Distance (<b>EMD</b>), (a popular distance measure in graphics and vision). Our hash functions map distributions to points in the metric space such that, for distributions <i>P</i> and <i>Q</i>, <b>EMD</b>(<i>P,Q</i>) &xie; <b>E</b><sub>hε\F</sub> [<i>d</i>(<i>h</i>(<i>P</i>),<i>h</i>(<i>Q</i>))] &xie; <i>O</i>(log <i>n</i> log log <i>n</i>). <b>EMD</b>(<i>P, Q</i>).</li></ol>.

A probabilistic approach to spatiotemporal theme pattern mining on weblogs <=SEP=> Mining subtopics from weblogs and analyzing their spatiotemporal patterns have applications in multiple domains. In this paper, we define the novel problem of mining spatiotemporal theme patterns from weblogs and propose a novel probabilistic approach to model the subtopic themes and spatiotemporal theme patterns simultaneously. The proposed model discovers spatiotemporal theme patterns by (1) extracting common themes from weblogs; (2) generating theme life cycles for each given location; and (3) generating theme snapshots for each given time period. Evolution of patterns can be discovered by comparative analysis of theme life cycles and theme snapshots. Experiments on three different data sets show that the proposed approach can discover interesting spatiotemporal theme patterns effectively. The proposed probabilistic model is general and can be used for spatiotemporal text mining on any domain with time and location information.

Automatic labeling of multinomial topic models <=SEP=> Multinomial distributions over words are frequently used to model topics in text collections. A common, major challenge in applying all such topic models to any text mining problem is to label a multinomial topic model accurately so that a user can interpret the discovered topic. So far, such labels have been generated manually in a subjective way. In this paper, we propose probabilistic approaches to automatically labeling multinomial topic models in an objective way. We cast this labeling problem as an optimization problem involving minimizing Kullback-Leibler divergence between word distributions and maximizing mutual information between a label and a topic model. Experiments with user study have been done on two text data sets with different genres.The results show that the proposed labeling methods are quite effective to generate labels that are meaningful and useful for interpreting the discovered topic models. Our methods are general and can be applied to labeling topics learned through all kinds of topic models such as PLSA, LDA, and their variations.

Automatic labeling hierarchical topics <=SEP=> Recently, statistical topic modeling has been widely applied in text mining and knowledge management due to its powerful ability. A topic, as a probability distribution over words, is usually difficult to be understood. A common, major challenge in applying such topic models to other knowledge management problem is to accurately interpret the meaning of each topic. Topic labeling, as a major interpreting method, has attracted significant attention recently. However, previous works simply treat topics individually without considering the hierarchical relation among topics, and less attention has been paid to creating a good hierarchical topic descriptors for a hierarchy of topics. In this paper, we propose two effective algorithms that automatically assign concise labels to each topic in a hierarchy by exploiting sibling and parent-child relations among topics. The experimental results show that the inter-topic relation is effective in boosting topic labeling accuracy and the proposed algorithms can generate meaningful topic labels that are useful for interpreting the hierarchical topics.

The Costs and Benefits of Pair Programming <=SEP=> Pair or collaborative programming is where two programmers develop software side by side at one computer. Using interviews and controlled experiments, the authors investigated the costs and benefits of pair programming. They found that for a development-time cost of about 15%, pair programming improves design quality, reduces defects, reduces staffing risk, enhances technical skills, improves team communications and is considered more enjoyable at statistically significant levels.

Comparing White-Box and Black-Box Test Prioritization <=SEP=> Although white-box regression test prioritization has been well-studied, the more recently introduced black-box prioritization approaches have neither been compared against each other nor against more well-established white-box techniques. We present a comprehensive experimental comparison of several test prioritization techniques, including well-established white-box strategies and more recently introduced black-box approaches. We found that Combinatorial Interaction Testing and diversity-based techniques (Input Model Diversity and Input Test Set Diameter) perform best among the black-box approaches. Perhaps surprisingly, we found little difference between black-box and white-box performance (at most 4% fault detection rate difference). We also found the overlap between black- and white-box faults to be high: the first 10% of the prioritized test suites already agree on at least 60% of the faults found. These are positive findings for practicing regression testers who may not have source code available, thereby making white-box techniques inapplicable. We also found evidence that both black-box and white-box prioritization remain robust over multiple system releases.

4G- A NEW ERA IN WIRELESS TELECOMMUNICATION <=SEP=> 4G – “connect anytime, anywhere, anyhow” promising ubiquitous network access at high speed to the end users, has been a topic of great interest especially for the wireless telecom industry. 4G seems to be the solution for the growing user requirements of wireless broadband access and the limitations of the existing wireless communication system. The purpose of this paper is to provide an overview of the different aspects of 4G which includes its features, its proposed architecture and key technological enablers. It also elaborates on the roadblocks in its implementations. A special consideration has been given to the security concerns of 4G by discussing a security threat analysis model proposed by International Telecommunication Union (ITU). By applying this model, a detailed analysis of threats to 4G and the corresponding measures to counter them can be performed.

Collocated photo sharing, story-telling, and the performance of self <=SEP=> This article reports empirical findings from four inter-related studies, with an emphasis on collocated sharing. Collocated sharing remains important, using both traditional and emerging image-related technologies. Co-present viewing is a dynamic, improvisational construction of a contingent, situated interaction between story-teller and audience. The concept of performance, as articulated differently by Erving Goffman and Judith Butler, is useful understand the enduring importance of co-present sharing of photos and the importance of oral narratives around images in enacting identity and relationships. Finally, we suggest some implications for both HCI research and the design of image-related technologies. & 2009 Elsevier Ltd. All rights reserved.

DoS and DDoS in Named Data Networking <=SEP=> With the growing realization that current Internet protocols are reaching the limits of their senescence, several on-going research efforts aim to design potential next-generation Internet architectures. Although they vary in maturity and scope, in order to avoid past pitfalls, these efforts seek to treat security and privacy as fundamental requirements. Resilience to Denial-of-Service (DoS) attacks that plague today's Internet is a major issue for any new architecture and deserves full attention. In this paper, we focus on DoS in Named Data Networking (NDN) - a specific candidate for next-generation Internet architecture designs. By naming data instead of its locations, NDN transforms data into a first-class entity and makes itself an attractive and viable approach to meet the needs for many current and emerging applications. It also incorporates some basic security features that mitigate classes of attacks that are commonly seen today. However, NDN's resilience to DoS attacks has not been analyzed to-date. This paper represents a first step towards assessment and possible mitigation of DoS in NDN. After identifying and analyzing several new types of attacks, it investigates their variations, effects and counter-measures. This paper also sheds some light on the debate about relative virtues of self-certifying, as opposed to human-readable, names in the context of content-centric networking.

Introducing Serendipity in a Content-Based Recommender System <=SEP=> Today recommenders are commonly used with various purposes, especially dealing with e-commerce and information filtering tools. Content-based recommenders rely on the concept of similarity between the bought/ searched/ visited item and all the items stored in a repository. It is a common belief that the user is interested in what is similar to what she has already bought/searched/visited. We believe that there are some contexts in which this assumption is wrong: it is the case of acquiring unsearched but still useful items or pieces of information. This is called serendipity. Our purpose is to stimulate users and facilitate these serendipitous encounters to happen. This paper presents the design and implementation of a hybrid recommender system that joins a content-based approach and serendipitous heuristics in order to mitigate the over-specialization problem with surprising suggestions.

Optimizing Dialogue Management with Reinforcement Learning: Experiments with the NJFun System <=SEP=> Designing the dialogue policy of a spoken dialogue system involves many nontrivial choices. This paper presents a reinforcement learning approach for automatically optimizing a dialogue policy, which addresses the technical challenges in applying reinforcement learning to a working dialogue system with human users. We report on the design, construction and empirical evaluation of NJFun, an experimental spoken dialogue system that provides users with access to information about fun things to do in New Jersey. Our results show that by optimizing its performance via reinforcement learning, NJFun measurably improves system performance.

ARROW: GenerAting SignatuRes to Detect DRive-By DOWnloads <=SEP=> A drive-by download attack occurs when a user visits a webpage which attempts to automatically download malware without the user's consent. Attackers sometimes use a malware distribution network (MDN) to manage a large number of malicious webpages, exploits, and malware executables. In this paper, we provide a new method to determine these MDNs from the secondary URLs and redirect chains recorded by a high-interaction client honeypot. In addition, we propose a novel drive-by download detection method. Instead of depending on the malicious content used by previous methods, our algorithm first identifies and then leverages the URLs of the MDN's central servers, where a central server is a common server shared by a large percentage of the drive-by download attacks in the same MDN. A set of regular expression-based signatures are then generated based on the URLs of each central server. This method allows additional malicious webpages to be identified which launched but failed to execute a successful drive-by download attack. The new drive-by detection system named ARROW has been implemented, and we provide a large-scale evaluation on the output of a production drive-by detection system. The experimental results demonstrate the effectiveness of our method, where the detection coverage has been boosted by 96% with an extremely low false positive rate.

A theorem on polygon cutting with applications <=SEP=> Let P be a simple polygon with N vertices, each being assigned a weight ∈ {0,1}, and let C, the weight of P, be the added weight of all vertices. We prove that it is possible, in O(N) time, to find two vertices a,b in P, such that the segment ab lies entirely inside the polygon P and partitions it into two polygons, each with a weight not exceeding 2C/3. This computation assumes that all the vertices have been sorted along some axis, which can be done in O(Nlog N) time. We use this result to derive a number of efficient divide-and-conquer algorithms for: 1. Triangulating an N-gon in O(Nlog N) time. 2. Decomposing an N-gon into (few) convex pieces in O(Nlog N) time. 3. Given an O(Nlog N) preprocessing, computing the shortest distance between two arbitrary points inside an N-gon (i.e., the internal distance), in O(N) time. 4. Computing the longest internal path in an N-gon in O(N2) time. In all cases, the algorithms achieve significant improvements over previously known methods, either by displaying better performance or by gaining in simplicity. In particular, the best algorithms for Problems 2,3,4, known so far, performed respectively in O(N2), O(N2), and O(N4) time.

A meta-analysis of continuing medical education effectiveness. <=SEP=> INTRODUCTION
We undertook a meta-analysis of the Continuing Medical Education (CME) outcome literature to examine the effect of moderator variables on physician knowledge, performance, and patient outcomes.


METHODS
A literature search of MEDLINE and ERIC was conducted for randomized controlled trials and experimental design studies of CME outcomes in which physicians were a major group. CME moderator variables included the types of intervention, the types and number of participants, time, and the number of intervention sessions held over time.


RESULTS
Thirty-one studies met the eligibility criteria, generating 61 interventions. The overall sample-size weighted effect size for all 61 interventions was r = 0.28 (0.18). The analysis of CME moderator variables showed that active and mixed methods had medium effect sizes (r = 0.33 [0.33], r = 0.33 [0.26], respectively), and passive methods had a small effect size (r = 0.20 [0.16], confidence interval 0.15, 0.26). There was a positive correlation between the effect size and the length of the interventions (r = 0.33) and between multiple interventions over time (r = 0.36). There was a negative correlation between the effect size and programs that involved multiple disciplines (r = -0.18) and the number of participants (r = -0.13). The correlation between the effect size and the length of time for outcome assessment was negative (r = -0.31).


DISCUSSION
The meta-analysis suggests that the effect size of CME on physician knowledge is a medium one; however, the effect size is small for physician performance and patient outcome. The examination of moderator variables shows there is a larger effect size when the interventions are interactive, use multiple methods, and are designed for a small group of physicians from a single discipline.

Prediction of Yelp Review Star Rating using Sentiment Analysis <=SEP=> Yelp aims to help people find great local businesses, e.g. restaurants. Automated software is currently used to recommend the most helpful and reliable reviews for the Yelp community, based on various measures of quality, reliability, and activity. However, this is not tailored to each customer. Our goal in this project is to apply machine learning to predict a customer’s star rating of a restaurant based on his/her reviews, as well as other customers’ reviews/ratings, to recommend other restaurants to the customer, as shown in Figure 1.

An efficient algorithm for the "optimal" stable marriage <=SEP=> In an instance of size n of the stable marriage problem, each of n men and n women ranks the members of the opposite sex in order of preference. A stable matching is a complete matching of men and women such that no man and woman who are not partners both prefer each other to their actual partners under the matching. It is well known [2] that at least one stable matching exists for every stable marriage instance. However, the classical Gale-Shapley algorithm produces a marriage that greatly favors the men at the expense of the women, or vice versa. The problem arises of finding a stable matching that is optimal under some more equitable or egalitarian criterion of optimality. This problem was posed by Knuth [6] and has remained unsolved for some time. Here, the objective of maximizing the average (or, equivalently, the total) “satisfaction” of all people is used. This objective is achieved when a person's satisfaction is measured by the position of his/her partner in his/her preference list. By exploiting the structure of the set of all stable matchings, and using graph-theoretic methods, an O(n4) algorithm for this problem is derived.

Primary, Secondary, and Meta-Analysis of Research <=SEP=> 

Efficient AUV navigation fusing acoustic ranging and side-scan sonar <=SEP=> This paper presents an on-line nonlinear least squares algorithm for multi-sensor autonomous underwater vehicle (AUV) navigation. The approach integrates the global constraints of range to and GPS position of a surface vehicle or buoy communicated via acoustic modems and relative pose constraints arising from targets detected in side-scan sonar images. The approach utilizes an efficient optimization algorithm, iSAM, which allows for consistent on-line estimation of the entire set of trajectory constraints. The optimized trajectory can then be used to more accurately navigate the AUV, to extend mission duration, and to avoid GPS surfacing. As iSAM provides efficient access to the marginal covariances of previously observed features, automatic data association is greatly simplified — particularly in sparse marine environments. A key feature of our approach is its intended scalability to single surface sensor (a vehicle or buoy) broadcasting its GPS position and simultaneous one-way travel time range (OWTT) to multiple AUVs. We discuss why our approach is scalable as well as robust to modem transmission failure. Results are provided for an ocean experiment using a Hydroid REMUS 100 AUV co-operating with one of two craft: an autonomous surface vehicle (ASV) and a manned support vessel. During these experiments the ranging portion of the algorithm ran online on-board the AUV. Extension of the paradigm to multiple missions via the optimization of successive survey missions (and the resultant sonar mosaics) is also demonstrated.

Understanding the perceived logic of care by vaccine-hesitant and vaccine-refusing parents: A qualitative study in Australia <=SEP=> In terms of public health, childhood vaccination programs have benefits that far outweigh risks. However, some parents decide not to vaccinate their children. This paper explores the ways in which such parents talked about the perceived risks and benefits incurred by vaccinating (or not vaccinating) their children. Between 2013-2016 we undertook 29 in-depth interviews with non-vaccinating and/or 'vaccine hesitant' parents in Australia. Interviews were conducted in an open and non-judgmental manner, akin to empathic neutrality. Interviews focused on parents talking about the factors that shaped their decisions not to (or partially) vaccinate their children. All interviews were transcribed and analysed using both inductive and deductive processes. The main themes focus on parental perceptions of: 1. their capacity to reason; 2. their rejection of Western medical epistemology; and 3. their participation in labour intensive parenting practices (which we term salutogenic parenting). Parents engaged in an ongoing search for information about how best to parent their children (capacity to reason), which for many led to questioning/distrust of traditional scientific knowledge (rejection of Western medical epistemology). Salutogenic parenting spontaneously arose in interviews, whereby parents practised health promoting activities which they saw as boosting the natural immunity of their children and protecting them from illness (reducing or negating the perceived need for vaccinations). Salutogenic parenting practices included breastfeeding, eating organic and/or home-grown food, cooking from scratch to reduce preservative consumption and reducing exposure to toxins. We interpret our data as a 'logic of care', which is seen by parents as internally consistent, logically inter-related and inter-dependent. Whilst not necessarily sharing the parents' reasoning, we argue that an understanding of their attitudes towards health and well-being is imperative for any efforts to engage with their vaccine refusal at a policy level.

Computational Thinking in Practice : How STEM Professionals Use CT in Their Work <=SEP=> The goal of this study is to bring current computational thinking in STEM educational efforts in line with the increasingly computational nature of STEM research practices. We conducted interviews with STEM practitioners in various fields to understand the nature of CT as it happens in authentic research settings and to revisit a first iteration of our definition of CT in form of a taxonomy. This exploration gives us insight into how scientists use computers in their work and help us identify what practices are important to include in high school STEM learning contexts. Our findings will inform the design of classroom activities to better prepare today’s students for the modern STEM landscape that awaits them.

Wavelet filter evaluation for image compression <=SEP=> Choice of filter bank in wavelet compression is a critical issue that affects image quality as well as system design. Although regularity is sometimes used in filter evaluation, its success at predicting compression performance is only partial. A more reliable evaluation can be obtained by considering an L-level synthesis/analysis system as a single-input, single-output, linear shift-variant system with a response that varies according to the input location module (2(L),2(L)). By characterizing a filter bank according to its impulse response and step response in addition to regularity, we obtain reliable and relevant (for image coding) filter evaluation metrics. Using this approach, we have evaluated all possible reasonably short (less than 36 taps in the synthesis/analysis pair) minimum-order biorthogonal wavelet filter banks. Of this group of over 4300 candidate filter banks, we have selected and present here the filters best suited to image compression. While some of these filters have been published previously, others are new and have properties that make them attractive in system design.

Multimodal recognition of personality traits in social interactions <=SEP=> This paper targets the automatic detection of personality traits in a meeting environment by means of audio and visual features; information about the relational context is captured by means of acoustic features designed to that purpose. Two personality traits are considered: Extraversion (from the Big Five) and the Locus of Control. The classification task is applied to thin slices of behaviour, in the form of 1-minute sequences. SVM were used to test the performances of several training and testing instance setups, including a restricted set of audio features obtained through feature selection. The outcomes improve considerably over existing results, provide evidence about the feasibility of the multimodal analysis of personality, the role of social context, and pave the way to further studies addressing different features setups and/or targeting different personality traits.

Design Criteria for Electric Vehicle Fast Charge Infrastructure Based on Flemish Mobility Behavior <=SEP=> This paper studies the technical design criteria for fast charge infrastructure, covering the mobility needs. The infrastructure supplements the residential and public slow charging infrastructure. Two models are designed. The first determines the charging demand, based on current mobility behavior in Flanders. The second model simulates a charge infrastructure that meets the resulting fast charge demand. The energy management is performed by a rule-based control algorithm, that directs the power flows between the fast chargers, the energy storage system, the grid connection, and the photovoltaic installation. There is a clear trade-off between the size of the energy storage system and the power rating of the grid connection. Finally, the simulations indicate that 99.7% of the vehicles visiting the fast charge infrastructure can start charging within 10 minutes with a configuration limited to 5 charging spots, instead of 9 spots when drivers are not willing to wait.

A Field Study of Run-Time Location Access Disclosures on Android Smartphones <=SEP=> Smartphone users are increasingly using apps that can access their location. Often these accesses can be without users knowledge and consent. For example, recent research has shown that installation-time capability disclosures are ineffective in informing people about their apps’ location access. In this paper, we present a four-week field study (N=22) on run-time location access disclosures. Towards this end, we implemented a novel method to disclose location accesses by location-enabled apps on participants’ smartphones. In particular, the method did not need any changes to participants’ phones beyond installing our study app. We randomly divided our participants to two groups: a Disclosure group (N=13), who received our disclosures and a No Disclosure group (N=9) who received no disclosures from us. Our results confirm that the Android platform’s location access disclosure method does not inform participants effectively. Almost all participants pointed out that their location was accessed by several apps they would have not expected to access their location. Further, several apps accessed their location more frequently than they expected. We conclude that our participants appreciated the transparency brought by our run-time disclosures and that because of the disclosures most of them had taken actions to manage their apps’ location access.

Morphological and LSU rDNA sequence variation within the Gonyaulax spinifera-Spiniferites group (Dinophyceae) and proposal of G-elongata comb. nov and G-membranacea comb. nov <=SEP=> Cultures were established from cysts of the cyst-based taxa Spiniferites elongatus and S. membranaceus. Motile cells and cysts from both cultures and sediment samples were examined using light and scanning electron microscopy. The cyst­ theca relationship was established for S. elongatus. The motile cells have the tabulation pattern 2 pr, 4', 6", 6c, � 4s, 6"', I p, Inn, but they remain unattributable to previously described Gonyaulax species. There was large variation in process length and process morphology in cysts from both cultures and wild samples and there was variation in ornamentation and in the development of spines and flanges in motile cells. A new combination, G. elongata (Reid) Ellegaard et al. comb. nov. is proposed, following new rules of the International Code of Botanical Nomenclature that give genera based on extant forms priority over genera based on fossil forms. Extreme morphological variation in the cyst and motile stages of S. membranaceus is described and this species is also transferred to the genus Gonyaulax, as G. membranacea (Rossignol) Ellegaard et al. comb. nov. Approximately 1500 bp of large subunit (LSU) rDNA were determined for these two species and for G. baltica, G. cf. spinifera ( = S. ramosus) and G. digitalis ( = Bitectatodinium tepikiense). LSU rDNA showed sequence divergences similar to those estimated between species in other genera within the Gonyaulacales; a phylogeny for the Gonyaulacales was established, including novel LSU rONA sequences for Alexandrium margalefii, A. pseudogonyaulax and Pyrodinium bahamense var. compressum. Our results show that motile stages obtained from the germination of several cysts of the 'fossil-based' Spiniferites and B. tepikiense, which were previously attributed to 'Gonyaulax spinifera group undifferentiated', belong to distinct species of the genus Gonyaulax. These species show small morphological differences in the motile stage but relatively high sequence divergence. Moreover, this group of species is monophyletic, supported by bootstrap values of 100% in parsimony and maximum likelihood analyses.

BUSINESS-TO-BUSINESS E-BUSINESS MODELS : CLASSIFICATION AND TEXTILE INDUSTRY IMPLICATIONS <=SEP=> Since the introduction of the Internet and e-commerce in the mid-1990s, there has been a lot of hype surrounding e-business, the impact that it will have on the way that companies do business, and how it will change the global economy as a whole. Since the crash of the dotcom companies in 2001, there has been much less hype surrounding the use of the Internet for business. There seems to have been a realization that e-business may not be the answer to all of a company’s problems, but can be a great asset in the struggle to increase efficiencies in daily business dealings, and that the Web is primarily a new way of relating to customers and suppliers. This paper categorizes and discusses the different types of business-to-business electronic business models currently being used by businesses and discussed in the academic literature, and shows how these business models are being implemented within the textile industry. This paper is divided into three parts. Part I gives an overview and some important definitions associated with businessto-business e-business, and discusses some characteristics that are unique to doing business on the Internet. Risks and benefits associated with doing business online are also discussed. Part II analyzes the different types of e-business models seen in the academic literature. Based on the analysis of the literature, a taxonomy of e-business models was developed. This new classification system organized e-business models into the following categories: sourcing models, ownership models, service-based models, customer relationship management models, supply chain models, interaction Models and revenue models. Part III reviews how these e-business models are currently being used within the textile industry. A preliminary analysis of 79 textile manufacturing companies was conducted to identify the applications of e-business.

Test Results and Torque Improvement of the 50-kW Switched Reluctance Motor Designed for Hybrid Electric Vehicles <=SEP=> A switched reluctance motor (SRM) has been developed as one of the possible candidates of rare-earth-free electric motors. A prototype machine has been built and tested. It has competitive dimensions, torque, power, and efficiency with respect to the 50-kW interior permanent magnet synchronous motor employed in the hybrid electric vehicles (Toyota Prius 2003). It is found that competitive power of 50-kW rating and efficiency of 95% are achieved. The prototype motor provided 85% of the target torque. Except the maximum torque, the most speed-torque region is found to be covered by the test SRM. The cause of discrepancy in the measured and calculated torque values is examined. An improved design is attempted, and a new experimental switched reluctance machine is designed and built for testing. The results are given in this paper.

Matching Curves to Imprecise Point Sets using Fréchet Distance <=SEP=> Let P be a polygonal curve in R of length n, and S be a point-set of size k. The Curve/Point Set Matching problem consists of finding a polygonal curve Q on S such that the Fréchet distance from P is less than a given ε. We consider eight variations of the problem based on the distance metric used and the omittability or repeatability of the points. We provide closure to a recent series of complexity results for the case where S consists of precise points. More importantly, we formulate a more realistic version of the problem that takes into account measurement errors. This new problem is posed as the matching of a given curve to a set of imprecise points. We prove that all three variations of the problem that are in P when S consists of precise points become NP-complete when S consists of imprecise points. We also discuss approximation re-

Common LISP: the language, 2nd Edition <=SEP=>