ppxscal/embedding_network huggingface dataset:
Computer-Supported Structured Cooperative Learning
Authors: Leen-Kiat Soh, Nobel Khandaker, Xuli Liu, Hong Jiang
Venue: Proceeding of the 2005 conference on Towards Sustainable and Scalable Educational Innovations Informed by the Learning Sciences: Sharing Good Practices of Research, Experimentation and Innovation (2005)

In this paper we describe computer-supported structured cooperative learning, applied to the laboratories of an introductory CS1 course. We extended I-MINDS, a multiagent system that supports student-teacher and student-student real-time interactions, to support a cooperative learning paradigm called Jigsaw. Jigsaw considers of several phases of activities, including dividing students into different groups for focused exploration, reporting and reshaping, and integration and evaluation. I-MINDS supports the formation of teams and monitors the interaction. We have deployed I-MINDS in the hands-on programming laboratories in CS1, comparing student performance in the lab using only Jigsaw (where students carried out the Jigsaw process with face-to-face interactions) and in the lab using I-MINDS supported Jigsaw (where students could interact only through I-MINDS). We report the results of our study on the design of I-MINDS to support Jigsaw and the impact of I-MINDS in student performance.
Two dimensional simulation and analytical modeling of a novel ISE MOSFET with gate stack configuration
Authors: Ravneet Kaur, Rishu Chaujar, Manoj Saxena, R. S. Gupta
Venue: Microelectronic Engineering (2009)

In this paper, the electrical characteristics of dielectric stack ISE MOSFET have been discussed in conjunction with long term requirements of ITRS. The key factors affecting the device performance and the physics behind it are also scrutinized. In addition, an analytical model using a computationally efficient Evanescent Mode Analysis (EMA), supplemented by extensive device simulation, has been presented. Drain Induced Barrier Lowering (DIBL) has been included in the model in a physically consistent manner, using Voltage Doping Transformation (VDT) method. The obtained analytical results have been verified by ATLAS 2D: device simulation software. For ultra thin gate dielectric oxide, analytical description of invoking quantum effects has also been given consideration in this paper.
Impact of supply voltage variations on full adder delay: analysis and comparison
Authors: Massimo Alioto, Gaetano Palumbo
Venue: IEEE Transactions on Very Large Scale Integration (VLSI) Systems (2006)

In this paper, some of the most practically interesting full adder topologies are analyzed in terms of their delay dependence on the supply voltage fluctuations, which are a major contribution to the delay uncertainty, which in turn limits the speed performance of current VLSI circuits. Analytical models of the delay sensitivity with respect to supply variations are derived by following a simplified circuit analysis, and the resulting expressions are simple enough to afford a deeper insight into the impact of supply voltage variations on each topology. The models are shown to be sufficiently accurate through simulations with CMOS technologies having a minimum feature size ranging from 90 nm to 0.35 µm. Several interesting properties and design considerations are derived from these models, and the effect of the supply voltage scaling, technology scaling, transistor sizing, and input transition time is discussed. Strategies to evaluate the delay sensitivity since the early design phases (e.g., from ring oscillator measurements) are also introduced. As a fundamental result, it is shown that the delay sensitivity to supply variations will increase in the next technology nodes, thus, it is expected that controlling the supply variations will be an increasingly important issue in the design of the next generation VLSI circuits. The proposed methodology is also analyzed in the case of more general digital circuits, and is used to estimate the impact of the inter-die threshold voltage variations on the delay of the considered full adder topologies.
Optimal solutions for moving target search
Authors: Carsten Moldenhauer, Nathan R. Sturtevant
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

Moving target search or the game of cops and robbers has been given much attention during the last two decades. It is known that optimal solutions, given a n-cop-win graph, are computable in polynomial time in the size of the input graph. However, a first practical polytime algorithm was only given recently by Hahn et al. [3]. All other known approaches are learning and anytime algorithms that try to approximate the optimal solution. In this work we present four algorithms: an adaptation of Two-Agent IDA*, Proof-Number Search, alpha-beta, and Reverse Minimax A*, a new algorithm. We show how these techniques can be applied to compute optimal moving target search solutions and give benchmarks on their performance for the one cop one robber problem.
An overview of different wideband direction of arrival (DOA) estimation methods
Authors: Sandeep Santosh, O. P. Sahu, Monika Aggarwal
Venue: WSEAS Transactions on Signal Processing (2009)

The Direction of Arrival (DOA) estimation methods are useful in Sonar, Radar and Advanced Satellite and Cellular Communication systems. In this paper different Direction of Arrival(DOA) methods such as Coherent Signal Subspace Processing (CSSM), the Weighted Average of Signal Subspaces (WAVES) and Test of Orthogonality of Projected Subspaces (TOPS) and Incoherent MUSIC(IMUSIC) is presented and their performance is also compared. The TOPS method performs better than others in mid signal--to-noise ratio (SNR) ranges, while CSSM and WAVES work better in low SNR. Incoherent methods like IMUSIC works best at high SNR.
Program efficiency and high temperature retention of SiN/high-K based memories
Authors: E. Vianello, M. Bocquet, F. Driussi, L. Perniola, G. Molas, L. Selmi
Venue: Microelectronic Engineering (2009)

This paper presents an experimental and simulation study of the program efficiency and retention of SANOS memory cells. We analyzed the experimental curves of the available cells by a physics based model that includes drift-diffusion transport of carriers in the nitride conduction band. We evidenced how the gate stack dimensions impact the program efficiency; in particular, thicker Si"3N"4 layers allow for faster programming. However, the Si"3N"4 thickness hardly influence the high temperature retention, since charge loss due to thermal emission dominates. Good agreement of the model with a wide set of experiments makes us confident on the validity of the interpretation of data which is suggested by the modeling results.
Microsoft Office Word 2007 for Medical Professionals, 1st edition
Authors: Jennifer Duffy, Carol M. Cram
Venue:  (2007)

Designed for students in medical assisting, nursing and allied health programs, this title teaches introductory Microsoft Word 2007 skills. It includes real world examples, projects, and a case study related to the medical industry, providing students with the Word skills they need to be successful to support the front or back office of a clinic, hospital, or medical practice.
Barter Markets for Conjoint Analysis
Authors: Min Ding, Young-Hoon Park, Eric T. Bradlow
Venue: Management Science (2009)

We propose a new alternative preference measurement method, barter conjoint, to contrast with traditional choice-based conjoint (CBC) approaches. Barter conjoint collects a substantially larger amount of data compared to CBC and allows for information diffusion among respondents. We conducted two empirical studies that compare CBC (with and without incentive alignment) and barter conjoint. The studies employed a total of three product categories, each with two validation tasks (one follows immediately and one conducted two weeks later). Our results confirmed prior research that incentive alignment, in general, substantially improves out-of-sample predictive performance of CBC. Furthermore, we found barter conjoint performs substantially better than the incentive-aligned CBC. However, in the spirit of “no free lunch,” barter conjoint is more taxing (in various ways) than CBC, suggesting a potential trade-off between consumer resource allocation (at the time of the task) and (managerial) predictive accuracy downstream. Given that this is the first study on barter conjoint, we discuss various limitations of the current implementation and fruitful directions for future research.
Product Life Cycle Management: a solution to manage innovation for manufacturing Companies
Authors: Francis Bernard
Venue: Proceeding of the 2006 conference on Leading the Web in Concurrent Engineering: Next Generation Concurrent Engineering (2006)

The presentation describes the challenges that each enterprise is facing today, in the global market place, and what are the in initiatives that should be taken to address these challenges. PLM is then described as a combination of enterprise organization transformations, new business processes and IT solutions which allow addressing such initiatives. An overview of the main innovative PLM software technology is then shown. The presentation ends with a short update on Dassault Systemes and its commitment to the academic community.
A multi-level video annotation tool based on XML-dictionaries
Authors: Anastasis Kounoudes, Nicolas Tsapatsoulis, Zenonas Theodosiou, Marios Milis
Venue: Proceedings of the 10th WSEAS international conference on Mathematical methods, computational techniques and intelligent systems (2008)

Recent advances in digital video technology have resulted in an explosion of digital video data which are available through the Web or in private repositories. Efficient searching in these repositories created the need of semantic labeling of video data at various levels of granularity, i.e., movie, scene, shot, keyframe, video object, etc. Through multilevel labeling video content is appropriately indexed, allowing access from various modalities and for a variety of applications. However, despite the huge efforts for automatic video annotation human intervention is the only way for reliable semantic video annotation. Manual video annotation is an extremely laborious process and efficient tools developed for this purpose can make, in many cases, the true difference. In this paper we present a video annotation tool, which uses structured knowledge, in the form of XML dictionaries, for semantic labeling, and an efficient shot detection algorithm for automatic video segmentation. Furthermore, it allows hierarchical semantic annotation from the highest to the lowest level of granularity through a properly designed graphical user interface. Finally, XML dictionary creation and editing tools are available during annotation allowing the user to always use the semantic label she/he wishes.
Towards argumentation-based contract negotiation
Authors: Phan Minh Dung, Phan Minh Thang, Francesca Toni
Venue: Proceeding of the 2008 conference on Computational Models of Argument: Proceedings of COMMA 2008 (2008)

We present an argumentation-based approach to contract negotiation amongst agents. Contracts are simply viewed as abstract transactions of items between a buyer agent and a seller agent, characterised by a number of features. Agents are equipped with beliefs, goals, and preferences. Goals are classified as either structural or contractual. In order to agree on a contract, agents engage in a two-phase negotiation process: in the first phase, the buyer agent decides on (a selection of) items fulfilling its structural goals and preferences; in the second phase, the buyer agent decides on a subset of the items identified in the first phase fulfilling its contractual goals and preferences. The first phase is supported by argumentation-based decision making taking preferences into account.
Feature selection and syndrome prediction for liver cirrhosis in traditional Chinese medicine
Authors: Yan Wang, Lizhuang Ma, Ping Liu
Venue: Computer Methods and Programs in Biomedicine (2009)

Traditional Chinese medicine (TCM) treatment is one of the safe and effective methods for liver cirrhosis. In the process of its treatment, a very important step, syndrome prediction is generally performed by physicians at present, which actually hinders the application prospects of TCM. Based on the data mining algorithm, a novel method called TCMSP (traditional Chinese medicine syndrome prediction) is proposed, which consists of two phases. In the first phase, based on an improved information gain method in multi-view, the critical features are filtered from the original features. In the second phase, the class label of a new case is predicted automatically based on accuracy-weighted majority voting. The proposed method is evaluated by the liver cirrhosis dataset, 20 critical features are selected from original 105 features and the corresponding syndromes of 138 new cases are identified respectively. The critical features are in sound agreement with those used by the physicians in making their clinical decisions. Finally, this new method is also demonstrated on three standard datasets (SPECT Heart, Lung Cancer and Iris) and the results are compared with some other methods. The experimental results show that TCMSP method performs well in the field of TCM diagnosis.
Application development using modeling and dynamical systems analysis
Authors: Eleanor O'Neill, Kris McGlinn, David Lewis, Eoin Bailey, Simon Dobson, Kevin McCartney
Venue: Proceedings of the 1st International Workshop on Context-Aware Middleware and Services: affiliated with the 4th International Conference on Communication System Software and Middleware (COMSWARE 2009) (2009)

Research on context aware systems is handicapped by the lack of readily available large scale data sets, as well as by the lack of tools by which researchers can interact effectively with such data sets across a range of scales and granularities. We show how virtual reality combined with a dynamical systems analysis approach can start to address these gaps. Simulation allows for generation of simulated sensor data at runtime and actuations of entities in the virtual world. The ease of sensor deployment and configurations in a simulated environment allows for rapid reconfigurations enabling generation of the required large scale data sets for analysis. Using these data sets, dynamical systems analysis can determine if a given application is functioning in a manner that is deemed to be correct.
Face Image Recognition Combining Holistic and Local Features
Authors: Chen Pan, Feilong Cao
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III (2009)

This paper introduces a method using the holistic and the local features for face image recognition. The holistic feature is extracted from spatial domain by 2DPCA and the local feature is taken from 2D-DCT-frequency domain by 2DNMF, respectively. 2D-DCT coefficients form the different frequency components and get energy concentrate at the same time, which may be suitable to preserve some useful puny features often ignored in global method. And it may avoid the correlation between global and local features and offer complementary frequency information to spatial one. Finally, LSSVM regression is used to weight the mixed feature vectors and classify images. Experimental results have demonstrated the validity of the new method, which outperforms the conventional 2D-based PCA and NMF methods on ORL and JAFFE face databases.
From the textual description of an accident to its causes
Authors: Daniel Kayser, Farid Nouioua
Venue: Artificial Intelligence (2009)

Every human being, reading a short report concerning a road accident, gets an idea of its causes. The work reported here attempts to enable a computer to do the same, i.e. to determine the causes of an event from a textual description of it. It relies heavily on the notion of norm for two reasons:*The notion of cause has often been debated but remains poorly understood: we postulate that what people tend to take as the cause of an abnormal event, like an accident, is the fact that a specific norm has been violated. *Natural Language Processing has given a prominent place to deduction, and for what concerns Semantics, to truth-based inference. However, norm-based inference is a much more powerful technique to get the conclusions that human readers derive from a text. The paper describes a complete chain of treatments, from the text to the determination of the cause. The focus is set on what is called ''linguistic'' and ''semantico-pragmatic'' reasoning. The former extracts so-called ''semantic literals'' from the result of the parse, and the latter reduces the description of the accident to a small number of ''kernel literals'' which are sufficient to determine its cause. Both of them use a non-monotonic reasoning system, viz. LPARSE and SMODELS. Several issues concerning the representation of modalities and time are discussed and illustrated by examples taken from a corpus of reports obtained from an insurance company.
Personalizing Trust in Online Auctions
Authors: John O'Donovan, Vesile Evrim, Barry Smyth, Dennis McLeod, Paddy Nixon
Venue: Proceeding of the 2006 conference on STAIRS 2006: Proceedings of the Third Starting AI Researchers' Symposium (2006)

The amount of business taking place in online marketplaces such as eBay is growing rapidly. At the end of 2005 eBay Inc. reported annual growth rates of 42.5% [3] and in February 2006 received 3 million user feedback comments per day [1]. Now we are faced with the task of using the limited information provided on auction sites to transact with complete strangers with whom we will most likely only interact with once. People will naturally be comfortable with old fashioned “corner store” business practice [14], based on a person to person trust which is lacking in large-scale electronic marketplaces such as eBay and Amazon.com. We analyse reasons why the current feedback scores on eBay and most other online auctions are too positive. We introduce AuctionRules, a trust-mining algorithm which captures subtle indications of negativity from user comments in cases where users have rated a sale as positive but still voiced some grievance in their feedback. We explain how these new trust values can be propagated using a graph-representation of the eBay marketplace to provide personalized trust values for both parties in a potential transaction. Our experimental results show that AuctionRules beats seven benchmark algorithms by up to 21%, achieving up to 97.5% accuracy, with a false negative rate of 0% in comment classification tests compared with up to 8.5% from other algorithms tested.
Generating human-like soccer primitives from human data
Authors: Carlos A. Acosta Calderon, Rajesh E. Mohan, Lingyun Hu, Changjiu Zhou, Huosheng Hu
Venue: Robotics and Autonomous Systems (2009)

Recently, interest in analysis and generation of human and human-like motion has increased in various areas. In robotics, in order to operate a humanoid robot, it is necessary to generate motions that have strictly dynamic consistency. Furthermore, human-like motion for robots will bring advantages such as energy optimization. This paper presents a mechanism to generate two human-like motions, walking and kicking, for a biped robot using a simple model based on observation and analysis of human motion. Our ultimate goal is to establish a design principle of a controller in order to achieve natural human-like motions. The approach presented here rests on the principle that in most biological motor learning scenarios some form of optimization with respect to a physical criterion is taking place. In a similar way, the equations of motion for the humanoid robot systems are formulated in such a way that the resulting optimization problems can be solved reliably and efficiently. The simulation results show that faster and more accurate searching can be achieved to generate an efficient human-like gait. Comparison is made with methods that do not include observation of human gait. The gait has been successfully used to control Robo-Erectus, a soccer-playing humanoid robot, which is one of the foremost leading soccer-playing humanoid robots in the RoboCup Humanoid League.
Verification of Correspondence Assertions in a Calculus for Mobile Ad Hoc Networks
Authors: Jens Chr. Godskesen, Hans Hüttel, Morten Kühnrich
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2009)

We introduce a novel process calculus called DBSPI (distributed broadcast SPI-calculus) which models mobile ad hoc networks (MANET). The calculus is a cryptographic broadcast calculus with locations and migration. Communication and migration are limited to neighborhoods. Neighborhood definitions are explicitly part of the syntax allowing dynamic extension using bound identifiers. In this semantic setting we study authentication of agents in MANET protocols. A safety property dealing with authentication correspondence assertions is defined. Later a dependent type and effect system is given and it is shown to be sound, i.e. protocols which are typeable are also safe. This result is lifted to open systems which involves Dolev-Yao attackers. Our Dolev-Yao attacker may use public keys for encryption and can attack any neighborhood it wishes. Our technique is applied to the Mobile IP registration protocol - a type check shows it is safe. To our knowledge this is the first type system for a MANET calculus doing that.
Creating an argumentation corpus: do theories apply to real arguments?: a case study on the legal argumentation of the ECHR
Authors: Raquel Mochales, Aagje Ieven
Venue: Proceedings of the 12th International Conference on Artificial Intelligence and Law (2009)

Argumentation annotation is a crucial step in applying machine learning techniques to the argumentation field. However, there exist few argumentation corpora and their development has not been studied in depth. In this paper we present a study conducted during the creation of a legal argumentation corpus. It shows how well-known argumentation theories are used as the background framework of the annotation process and which difficulties are found when applying those theories to real argumentation. The aim of the paper is to highlight different critical points humans encounter when applying theory to real argumentation, allowing better and faster approaches in future annotation processes. Furthermore, we also highlight fundamental problems of the chosen argumentation theories and thereby offer ideas for future research on argumentation theory.
Theory on Software Diagnosis for Program Code Validation
Authors: Fumio Negoro, Hamido Fujita
Venue: Proceeding of the 2006 conference on New Trends in Software Methodologies, Tools and Techniques: Proceedings of the fifth SoMeT_06 (2006)

We have invented an axiomatic based theory as a methodology for software development. Our methodology has been used world wide for program generation based on intentional user requirement. Using such methodology we have developed a tool for program validation for diagnosis purposes. The tool is based on Lyee theory and sets of rules that interpret the logical semantics of the old program and verify it for design errors or possible security aspects. We explain the theory and also show some practical results reflect our practices on actual business project to show the effectiveness of our theory as it consumes less efforts and time to diagnose a program design and logical errors.