ppxscal/embedding_network huggingface dataset:
Designed to Fit: Challenges of Interaction Design for Clothes Fitting Room Technologies
Authors: Bo Begole, Takashi Matsumoto, Wei Zhang, Nicholas Yee, Juan Liu, Maurice Chu
Venue: Proceedings of the 13th International Conference on Human-Computer Interaction. Part IV: Interacting in Various Application Domains (2009)

This paper uncovers issues in the design of camera-based technologies to support retail shopping in a physical store, specifically clothes shopping. An emerging class of technology is targeting the enhancement of retail shopping, including the trying on of clothing. Designing such systems requires careful considerations of physical and electronic design, as well as concerns about user privacy. We explore the entire design cycle using a technology concept called the Responsive Mirror through its conception, prototyping and evaluation. The Responsive Mirror is an implicitly controlled video technology for clothes fitting rooms that allows a shopper to directly compare a currently worn garment with images from the previously worn garment. The orientation of images from past trials is matched to the shopper's pose as he moves. To explore the tension between privacy and publicity, the system also allows comparison to clothes that other people in the shoppers' social network are wearing. A user study elicited a number of design tradeoffs regarding privacy, adoption, benefits to shoppers and merchants and user behaviors in fitting rooms.
On the Capacity of Hybrid Wireless Networks with Opportunistic Routing
Authors: Tan Le, Yong Liu
Venue: Proceedings of the 4th International Conference on Wireless Algorithms, Systems, and Applications (2009)

This paper studies the capacity of hybrid wireless networks with opportunistic routing (OR). We first extend the opportunistic routing algorithm to exploit high speed data transmissions in infrastructure network through base stations. We then develop linear programming models to calculate the end-to-end throughput bounds from multiple source nodes to single, as well as, multiple destination nodes. The developed models are applied to study several hybrid wireless network examples. Through case studies, we investigate several factors that have significant impacts on the hybrid wireless network capacity under opportunistic routing, such as node transmission range, density and distribution pattern of base stations (BTs), number of wireless channels on wireless nodes and base stations, etc. Our numerical results demonstrate that opportunistic routing could achieve much higher throughput on both ad-hoc and hybrid networks than traditional unicast routing (UR). Moreover, opportunistic routing can efficiently utilize base stations and achieve significantly higher throughput gains in hybrid wireless networks than in pure ad-hoc networks especially with multiple-channel base stations.
Research of Tools Rapid Preparation Technology for Aerospace Manufacturing Enterprise
Authors: Fang Yadong, Du Laihong, Chen Hua
Venue: Proceedings of the 2009 Second International Symposium on Electronic Commerce and Security - Volume 01 (2009)

To improve manufacturing capability of national defense industry, the paper brings forward tools preparation problem by analyzing tools management business, and then discusses how to select appropriate tools preparation methods according to cost, time, quality and server. Further more, the key technology about manufacturing resources information integration technology based on XML,tools classification and code technology,tools marking and identifying technology and distribute numeric control technology is researched to realize tools rapid preparation. Lastly, the framework of tools rapid preparation system is studied in terms of the aerospace enterprise production feature and present information system relevant to tools
Neural network based constraint satisfaction in ontology mapping
Authors: Ming Mao, Yefei Peng, Michael Spring
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 2 (2008)

Ontology mapping seeks to find semantic correspondences between similar elements of different ontologies. Ontology mapping is critical to achieve semantic interoperability in the WWW. Due to the fact that ubiquitous constraints (e.g., hierarchical restrictions in RDFS) caused by the characteristics of ontologies and their representations exist in ontologies, constraints satisfaction has become an intriguing research problem in ontology mapping area Though different techniques have been examined to find mappings, little work is made to solve constraint satisfaction problem for ontology mapping. Currently most approaches simply validate ontology constraints using isolate heuristic rules instead of comprehensively considering them in a global view. This paper proposes a neural network based approach to search for a global optimal solution that can satisfy ontology constraints as many as possible. Experimental results on OAEI benchmark tests #248-#266 show the approach is promising. It dramatically improves the performance of preliminary mapping results.
Web and corpus methods for Malay count classifier prediction
Authors: Jeremy Nicholson, Timothy Baldwin
Venue: Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers (2009)

We examine the capacity of Web and corpus frequency methods to predict preferred count classifiers for nouns in Malay. The observed F-score for the Web model of 0.671 considerably outperformed corpus-based frequency and machine learning models. We expect that this is a fruitful extension for Web-as-corpus approaches to lexicons in languages other than English, but further research is required in other South-East and East Asian languages.
MARS: Metamodel Recovery from Multi-tiered Models Using Grammar Inference
Authors: Qichao Liu, Faizan Javed, Marjan Mernik, Barrett R. Bryant, Jeff Gray, Alan Sprague, Dejan Hrncic
Venue: Proceedings of the 2009 Third IEEE International Symposium on Theoretical Aspects of Software Engineering (2009)

In model-driven engineering, metamodels may get lost over time resulting in the inability to load and view existing model instances. MARS is a system that recovers metamodels from model instances using grammar inference. This paper discusses advances in MARS that improve accuracy and scalability.
Spoken dialogue systems for language learning
Authors: Stephanie Seneff, Chao Wang, Chih-yu Chao
Venue: Proceedings of Human Language Technologies: The Annual Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations on XX (2007)

This demonstration will illustrate interactive computer games intended to help a native speaker of English learn Mandarin. These systems provide users with humanlike conversational exercises with contextualized help mechanisms. Two distinctly different activities, a translation game and a dialogue game are illustrated. The level of difficulty can be manipulated, and the sentence variations covered by the systems familiarize users with different expressions of the same meaning. The systems preserve the qualities of a typical computer system, being infinitely patient and available any time of day. Students will be able to repeatedly practice conversation with no embarrassment.
Learning when training data are costly: the effect of class distribution on tree induction
Authors: Gary M. Weiss, Foster Provost
Venue: Journal of Artificial Intelligence Research (2003)

For large, real-world inductive learning problems, the number of training examples often must be limited due to the costs associated with procuring, preparing, and storing the training examples and/or the computational costs associated with learning from them. In such circumstances, one question of practical importance is: if only n training examples can be selected, in what proportion should the classes be represented? In this article we help to answer this question by analyzing, for a fixed training-set size, the relationship between the class distribution of the training data and the performance of classification trees induced from these data. We study twenty-six data sets and, for each, determine the best class distribution for learning. The naturally occurring class distribution is shown to generally perform well when classifier performance is evaluated using undifferentiated error rate (0/1 loss). However, when the area under the ROC curve is used to evaluate classifier performance, a balanced distribution is shown to perform well. Since neither of these choices for class distribution always generates the best-performing classifier, we introduce a "budget-sensitive" progressive sampling algorithm for selecting training examples based on the class associated with each example. An empirical analysis of this algorithm shows that the class distribution of the resulting training set yields classifiers with good (nearly-optimal) classification performance.
Classification using conditional probabilities and Shannon's definition of information
Authors: Andrew Borden
Venue: Proceedings of the 2007 International Lisp Conference (2007)

Our problem is to build a maximally efficient Bayesian classifier when each parameter has a different cost and provides a different amount of information toward the solution. This is an extremely computationally expensive problem. We accept a sub-optimal, although demonstrably good, solution based on Shannon's definition of Information and Uncertainty. Our solution scales up well and provides powerful diagnostics with no extra work. Our program has been used in Military Command and Control and in developing maintenance diagnostics for a very complex military electronic system. The elements of the solution to the problem are naturally computed recursively, so Lisp implementation is an effective approach.
Socio-scientific analysis of user requirements in mobile learning: a case study on marginalised young people
Authors: Elisabeth Unterfrauner, ilse Marschalek
Venue: Proceedings of the 11th International Conference on Human-Computer Interaction with Mobile Devices and Services (2009)

Although marginalised young people have been proved to have less access to Information and Communication Technologies such as the Internet, their access to mobile phones does not differ from non-marginalised young people. Since mobile phones seem to play an important role in youth's life, delivering learning programmes via this piece of technology seems a promising idea. Thereby, to analyse the requirement of the future users of learning programmes to be designed is fundamental since little about their characteristics and needs is known. A triangulation of data, consisting of academic literature review, expert interview data and focus group data, led to valuable conclusions.
A constraint-based approach to Enigma 1225
Authors: Hadrien Cambazard, Barry O'Sullivan, Barbara M. Smith
Venue: Computers Mathematics with Applications (2009)

This paper presents a constraint programming approach to the Enigma 1225, a mathematical puzzle published in the New Scientist magazine in February 2003. An approach based on Prolog was published recently. In this paper we give a constraint programming perspective on the problem, highlighting the differences between the two methodologies. We show how problem-specific knowledge can be easily incorporated into a constraint-based approach, giving an efficient constraint model for the generalized version of the puzzle. From the constraint programming point of view, the Enigma 1225 puzzle exhibits interesting symmetries, that can be eliminated using only a small number of constraints added to the model. Furthermore, properties of the puzzle can be used to derive a strong constraint propagation scheme that limits the search once an optimal solution has been found.
Lisp-based agent platform and applications for inter-domain network management
Authors: Osamu Akashi, Atushi Terauchi, Kensuke Fukuda, Toshio Hirotsu, Toshiharu Sugawara
Venue: Proceedings of the 2007 International Lisp Conference (2007)

The Internet consists of several thousand interconnected autonomous systems (ASes). For enabling the autonomous network management that ensures stable access at the inter-AS level and flexible inter-domain routing control, it is important to know how the routing information originated from an AS spreads throughout the Internet and to control inter-AS routing information using feedback actions based on observed network status at multiple ASes. Because each AS is controlled by a single administrative authority based on that AS's own policy, a cooperative distributed problem solving is desirable. To cope with these requirements, we have proposed a multi-agent-based inter-AS diagnostic system called ENCORE and inter-AS routing adjustment system called AISLE / VR. They consist of a collection of intelligent agents that are located in multiple ASes and perform collective observation, analysis, and control. These systems are constructed on the agent platform that provides utility functions on distributed environments. For the purpose of flexibility for incremental design and modification through the development and application phases, we adopted Lisp as the base language and have constructed stable systems that can demonstrate the effectiveness of our basic design for autonomous inter-AS network management.
Compactness and Flow Minimization Requirements in Reforestation Initiatives: An Integer Programming (IP) Formulation
Authors: Pablo Vanegas, Dirk Cattrysse, Jos Orshoven
Venue: Proceedings of the International Conference on Computational Science and Its Applications: Part I (2009)

Identifying optimal sites on raster maps is a complex problem when the sites are larger than the cell size. Optimal sites involves a trade-off between the intrinsic characteristics of individual cells and the spatial configuration of the cells. Although there are a number of techniques to solve the site allocation problem, those solutions do not consider spatial interactions between the cells forming the site. This paper presents an Integer Programming Formulation (IP) for allocating a predefined number of cells satisfying the following criteria: 1) minimize flow (water, sediment) reaching the outlet of a watershed, 2) maximize/minimize intrinsic characteristics of the cells, and 3) form a compact patch. Although the core structure of the IP formulation can be applied for different sorts of flow and intrinsic characteristics, it is targeted to a reforestation application. The proposed approach is applied to perform several experiments in two watersheds in South Dakota in the USA for searching a given number of best cells (1) minimizing sediment reaching the watershed outlet,(2) maximizing the environmental criteria, and (3) forming a compact patch. The results obtained with the IP formulation are in agreement with expert assessments of erosion levels, slopes and distances to the riverbeds.
Arabic OCR error correction using character segment correction, language modeling, and shallow morphology
Authors: Walid Magdy, Kareem Darwish
Venue: Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing (2006)

This paper explores the use of a character segment based character correction model, language modeling, and shallow morphology for Arabic OCR error correction. Experimentation shows that character segment based correction is superior to single character correction and that language modeling boosts correction, by improving the ranking of candidate corrections, while shallow morphology had a small adverse effect. Further, given sufficiently large corpus to extract a dictionary and to train a language model, word based correction works well for a morphologically rich language such as Arabic.
An Electronic Economic Mechanism Based on Interpersonal Relationship
Authors: Takaaki Narabe, Yoshihito Saito, Satoshi Takahashi, Tokuro Matsuo
Venue: Proceedings of the 2009 IEEE Conference on Commerce and Enterprise Computing (2009)

Recently, electronic commerce has been increasing. In the electronic marketplace, buyers and sellers evaluate each item with each other, and buy/sell the item. The history of trading are stored in the database and can be used it by traders in subsequent trading. Human relationships information of traders can also be stored by applying and change the database in the electronic commerce system. In actual trade in real world, item's price is sometimes affected by the relationship between them. This paper focuses on the trading in which buyers and sellers have an asserted relationship such as friend on the Internet. This paper analyzes items' values which is defined by items' prices and the relationships. Also, we propose a trading protocol including the relationship between sellers and buyers based on the analysis. In the protocol, first, the seller and the buyer evaluate the relationship. Then, the successful trader is determined based on synthesis evaluations. Finally, the seller and successful buyers trade with each other in the calculated price. The Advantage of our protocol is that appropriate evaluations of trading partners can be obtained by various attributes based on Multi-Attribute Utility Theory.
Improving the Semantics of Imperfect Security
Authors: Niklas Broberg, David Sands
Venue: Foundations and Applications of Security Analysis: Joint Workshop on Automated Reasoning for Security Protocol Analysis and Issues in the Theory of Security, ARSPA-WITS 2009, York, UK, March 28-29, 2009, Revised Selected Papers (2009)

Information flow policies that evolve over time (including, for example, declassification) are widely recognised as an essential ingredient in useable information flow control system. In previous work ([BS06a, BS06b]) we have shown one approach to such policies, flow locks, which is a very general and flexible system capable of encoding many other proposed approaches.However, any such policy approach is only useful if we have a precise specification --- a semantic model --- of what we are trying to enforce. A semantic model gives us insight into what a policy actually guarantees, and defines the precise goals of any enforcement mechanism. Unfortunately, semantic models of declassification can be both inaccurate and difficult to understand. This was definitely the case for the flow locks system as presented in [BS06a, BS06b], and we have found that the main problem is one common to most proposed models to date. We will start by discussing the problem in general, and then go on to sketch its solution for the flow locks system specifically.
A Study on the Design of Voice Navigation of Car Navigation System
Authors: Chih-Fu Wu, Wan-Fu Huang, Tung-Chen Wu
Venue: Proceedings of the 13th International Conference on Human-Computer Interaction. Part III: Ubiquitous and Intelligent Interaction (2009)

This study tries to find the designing blind spots of the voice prompt function in the current car navigation systems and make improvement suggestions. The experimental plan was implemented through videotape analysis of the voice-prompt mode, referring to Urban Road Classification Regulations and the questionnaire survey results. Driving simulation tests were conducted with 15 experimental subjects, 13 road combinations, and 3 running speeds, and different prompt modes which were run synchronously were also included. Compared with the present mode (prompt time is determined by distance.), the newly-designed mode (prompt time is determined by running speed.) significantly improved driving performance and reduced mental workload. When driving on a main artery with fast lanes and slow lanes, adding a changing-lane prompt with a clear sound to the system can help increasing the driving accuracy rate.
Sign Bit Reduction Encoding For Low Power Applications
Authors: M. Saneei, A. Afzali-Kusha, Z. Navabi
Venue: Journal of Signal Processing Systems (2009)

In this paper, a low power technique, called SBR (Sign Bit Reduction), which reduces the energy consumption in multipliers as well as data buses is proposed. The technique reduces the number of sign bits in the data transfer as well as in the multiplication process. This feature enables us to use the encoding technique for both the transfer of the data and its multiplication at the destination without any need for an intermediate decoding step. Simple circuits are used as the SBR decoder and encoder. The efficacy of the technique is evaluated for both voice and random data. The results of applying the voice data to a 16-bit multiplier implemented with this scheme shows energy consumption up to 11.4% compared to those of a 2's complement implementation, while the number of required clock periods for the multiplication process is reduced up to 14.5%. The results of applying the SBR technique to a 30-tap FIR filter show up to 9.6% reduction in the energy consumption and up to 13.4% reduction in the required clock cycles. Finally, for voice data and random inputs, the use of the technique for a 16-bit data bus leads to an average energy consumption of up to 14.6%.
Adaptive treatment of epilepsy via batch-mode reinforcement learning
Authors: Arthur Guez, Robert D. Vincent, Massimo Avoli, Joelle Pineau
Venue: Proceedings of the 20th national conference on Innovative applications of artificial intelligence - Volume 3 (2008)

This paper highlights the crucial role that modern machine learning techniques can play in the optimization of treatment strategies for patients with chronic disorders. In particular, we focus on the task of optimizing a deep-brain stimulation strategy for the treatment of epilepsy. The challenge is to choose which stimulation action to apply, as a function of the observed EEG signal, so as to minimize the frequency and duration of seizures. We apply recent techniques from the reinforcement learning literature--namely fitted Q-iteration and extremely randomized trees--to learn an optimal stimulation policy using labeled training data from animal brain tissues. Our result, show that these methods are an effective means of reducing tile incidence of seizures, while also minimizing the amount ot stimulation applied. If these results Carry over to the human model of epilepsy, the impact for patients will be substantial.
A Comparative Study on Feature Window Selection in Text Filtering
Authors: Hu Quan, Xie Fang, Liu Xiaoguang
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 03 (2009)

Text representation is a preliminary step to text filtering, while VSM is the most commonly used method in this field. However, the document feature set, which produced by VSM, usually has a very high dimensionality. As a result, the distribution of feature value tends to be highly skewed. In this paper some new mechanisms are presented to abate such problems. Using these mechanisms, document features are extracted from some smaller feature windows rather than a full text, such as sentences, graphs and blocks, and the correlative texts are finally evaluated by local similarity. They are gotten by the analysis of document’s linguistics structures in documents. As a result, it can give a remarkable effect on the precision of text filtering.