ppxscal/embedding_network huggingface dataset:
A descriptive study of Turkish high school students' game-playing characteristics and their considerations concerning the effects of games
Authors: Turkan Karakus, Yavuz Inal, Kursat Cagiltay
Venue: Computers in Human Behavior (2008)

The purpose of this study is to examine high school students' preferences, playing habits, expectations, and thoughts concerning computer games. One-thousand two hundred and twenty-four (1224) vocational high school students, studying at eight different schools in six cities within four different regions in Turkey, participated in the study. The results reveal that female students expect games to have instructive elements, while males desire elements that are entertaining, competitive, and multi-player. Females complained about negative aspects of computer games, such as causation of laziness and motivation for aggressive behavior, more than males. The students suggested that computer games might be used in education for Mathematics or History courses, and that they can be used to improve mental skills. Females also stated a preference to play in ''convenient'' places, such as their homes or schools, rather than in Internet cafes or other outside places, which were more strongly favored by males.
Mobile Robot Self-localization Based on Feature Extraction of Laser Scanner Using Self-organizing Feature Mapping
Authors: Jinxia Yu, Zixing Cai, Zhuohua Duan
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

This paper investigates the use of SOM to process the signal of a 2D laser scanner encountered in feature extraction (corner) and mobile robot self-localization in indoor environments. It presents the method of combining SOM with occupancy grid matching to improve the self-localization performance at the lower computational cost. Experimental results demonstrate that this method can reliably extract the feature of corner point and can effectively improve the self-localization performance of mobile robot.
Lessons from an evaluation of a domestic well-being indicator system
Authors: Nubia M. Gil
Venue: Proceedings of the 10th international ACM SIGACCESS conference on Computers and accessibility (2008)

The objective of this study was to find out whether a domestic well-being indicator system might support the dialogue of care between the older person and his or her carer. Ten evaluation sessions, each one with three parts, were run with ten older people and ten carers. Peoples' attitudes and feelings, perceptions, and preferences were compared. Both qualitative and quantitative data were collected. In conclusion the prototype could be used as a tool to improve the dialogue of care between the older person and the carer.
Introduction to Programming Multicores
Authors: Chris Jesshope
Venue: Proceedings of the 8th international workshop on Embedded Computer Systems: Architectures, Modeling, and Simulation (2008)

Already our technology is able to accommodate hundreds of cores on a single chip. The embedded market is already embracing this but the wider market is back-peddling. There is no doubt however that these markets will converge and that the processor will become the new building block of our chips and systems. The big problem problem however, will be in turning this technology into large complex systems. There are no lack of contenders for concurrent programming languages but the problem with most paradigms is that they mix algorithmic and concurrency engineering and do little to promote safe and composable parallel programs. The question that must be asked is whether there are programming models or combinations of models that are ubiquitous enough to form the basis for a co-ordinated solution to the problems of programming MPSOC. This special session has succeeded in bringing bringing together a number of key researchers working in the area of programming models for the next generation of complex systems based on multi- and many-core chips. Collectively they are developing models, languages and compilers to enable a paradigm shift in this important area. The scope of the contributions will cover deterministic approaches, such as functional languages and data-parallel languages as well as extracting concurrency from sequential code. In addition, a number of new co-ordination languages will be presented that range from static to dynamic mapping of components to resources. These are challenging problems but we are pleased to present some significant progress from invited and contributed papers in this session.
A Friend Mechanism for Mobile Ad Hoc Networks
Authors: Shukor Abd Razak, Normalia Samian, Mohd Aizaini Maarof
Venue: Proceedings of the 2008 The Fourth International Conference on Information Assurance and Security (2008)

In the autonomous environment of mobile ad hoc network (MANET) where nodes are free to move around and depend on each other to initiate communication, cooperation among nodes is an essential component of a successful data transmission process. Since there is no central controller such as router to determine the communication paths in MANET, each node in the ad hoc network has to rely on each other in order to forward packets, thus highly cooperative nodes are required to ensure that the initiated data transmission process does not fail. However, it is hard to encourage cooperativeness among nodes for each node owns limited resources that need to be preserved. These particular nodes which are also known as selfish nodes refuse to help other nodes in forwarding packets due to the anxiety of having resource degradation such as exhausted battery power and limited processor capability. This problem has aroused several issues in MANET: routing, security, Quality of Service (QoS), resource management and auto-configuration. Hence, there is a need to provide a mechanism that can encourage cooperation among nodes without jeopardizing their resources. In this paper, we provide evidence through simulation experiments on how a friendship concept could be used to minimize the number of false alarms raised in MANET Intrusion Detection System (IDS). We also discuss on how the similar friendship concept could be used to address several challenges faced in MANET environment.
Structural Support Vector Machine
Authors: Hui Xue, Songcan Chen, Qiang Yang
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks (2008)

Support Vector Machine (SVM) is one of the most popular classifiers in pattern recognition, which aims to find a hyperplane that can separate two classes of samples with the maximal margin. As a result, traditional SVM usually more focuses on the scatter between classes, but neglects the different data distributions within classes which are also vital for an optimal classifier in different real-world problems. Recently, using as much structure information hidden in a given dataset as possible to help improve the generalization ability of a classifier has yielded a class of effective large margin classifiers, typically as Structured Large Margin Machine (SLMM). SLMM is generally derived by optimizing a corresponding objective function using SOCP, and thus in contrast to SVM developed from optimizing a QP problem, it, though more effective in classification performance, has the following shortcomings: 1) large time complexity; 2) lack of sparsity of solution, and 3) poor scalability to the size of the dataset. In this paper, still following the above line of the research, we develop a novel algorithm, termed as Structural Support Vector Machine (SSVM), by directly embedding the structural information into the SVM objective function rather than using as the constraints into SLMM, in this way, we achieve: 1) to overcome the above three shortcomings; 2) empirically better than or comparable generalization to SLMM, and 3) theoretically and empirically better generalization than SVM.
Data-Driven Prediction of the Necessity of Help Requests in ILEs
Authors: Manolis Mavrikis
Venue: Proceedings of the 5th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems (2008)

This paper discusses the data-driven development of a model which predicts whether a student could answer a question correctly without requesting help. This model contributes to a broader piece of research, the primary goal of which was to predict affective characteristics of students working in ILEs. The paper presents the bayesian network which provides adequate predictions, and discusses how its accuracy is taken into account when the model is integrated in an ILE. Future steps to improve the results are briefly discussed.
Annotation Markers for Runtime Replication Protocol Selection
Authors: Hein Meling
Venue: Proceedings of the 5th international conference on Autonomic and Trusted Computing (2008)

This paper presents an architecture enabling developers to easily and flexibly assign replication protocols simply by annotating individual server methods. This avoids using costly replication protocols for all object methods, e.g. read-only methods can use less costly protocols, reserving the costly replication protocols for update methods. The architecture has been implemented in the Jgroup/ARM middleware, and enables addition of new replication protocols without modifying the core toolkit. It also supports runtime selection of replication protocol for individual methods. This can be used to support self-optimization of protocol selection by optimizing for the most appropriate configuration under a given system load.
Discovery and Integration of Organ-Failure Episodes in Mortality Prediction
Authors: Tudor Toma, Ameen Abu-Hanna, Robert-Jan Bosman
Venue: Proceedings of the 11th conference on Artificial Intelligence in Medicine (2007)

Current predictive models in the intensive care rely on summaries of data collected at patient admission. It has been shown recently that temporal patterns of the daily Sequential Organ Failure Assessment (SOFA) scores can improve predictions. However, the derangement of the six individual organ systems underlying the calculation of a SOFA score were not taken into account, thus impeding the understanding of their prognostic merits. In this paper we propose a method for model induction that integrates in a novel way the individual organ failure scores with SOFA scores. The integration of these two correlated components is achieved by summarizing the historic SOFA information and at the same time by capturing the evolution of individual organ system failure status. The method also explicitly avoids the collinearity problem among organ failure episodes. We report on the application of our method to a large dataset and demonstrate its added value. The ubiquity of severity scores and sub-scores in medicine renders our approach relevant to a wide range of medical domains.
Method of Extract Changing Scene in Animation
Authors: Young Jae Park, Youngsong Mun, Keun Su Lee, Gye Young Kim
Venue: Proceedings of the international conference on Computational Science and Its Applications, Part II (2008)

In this paper, we propose that method of extract changing scene in animation. A new method differed about attributes of animation based on already exist one. We mix histogram method and block method plus new things. We found it much improved than traditional method.
Reduction Techniques for Model Checking Markov Decision Processes
Authors: Frank Ciesinski, Christel Baier, Marcus Gröβer, Joachim Klein
Venue: Proceedings of the 2008 Fifth International Conference on Quantitative Evaluation of Systems (2008)

The quantitative analysis of a randomized system, modeled by a Markov decision process, against an LTL formula can be performed by a combination of graph algorithms, automata-theoretic concepts and numerical methods to compute maximal or minimal reachability probabilities. In this paper, we present various reduction techniques that serve to improve the performance of the quantitative analysis, and report on their implementation on the top of the probabilistic model checker \LiQuor. Although our techniques are purely heuristic and cannot improve the worst-case time complexity of standard algorithms for the quantitative analysis, a series of examples illustrates that the proposed methods can yield a major speed-up.
Efficient Fragmentation of Large XML Documents
Authors: Angela Bonifati, Alfredo Cuzzocrea
Venue: Proceedings of the 18th International Conference on Database and Expert Systems Applications (2007)

Fragmentation techniques for XML data are gaining momentum within both distributed and centralized XML query engines and pose novel and unrecognized challenges to the community. Albeit not novel, and clearly inspired by the classical divide et impera principle, fragmentation for XML trees has been proved successful in boosting the querying performance, and in cutting down the memory requirements. However, fragmentation considered so far has been driven by semantics, i.e. built around query predicates. In this paper, we propose a novel fragmentation technique that founds on structural constraints of XML documents (size, tree-width, and tree-depth) and on special-purpose structure histograms able to meaningfully summarize XML documents. This allows us to predict bounding intervals of structural properties of output (XML) fragments for efficient query processing of distributed XML data. An experimental evaluation of our study confirms the effectiveness of our fragmentation methodology on some representative XML data sets.
Semantic Reflection --- Knowledge Based Design of Intelligent Simulation Environments
Authors: Marc Erich Latoschik
Venue: Proceedings of the 30th annual German conference on Advances in Artificial Intelligence (2007)

This paper introduces Semantic Reflection (SR), a design paradigm for intelligent applications which represents applications' objects and interfaces on a common knowledge representation layer (KRL). SR provides unified knowledge reflectivity specifically important for complex architectures of novel human-machine interface systems.
Formal Modeling of BeeAdHoc: A Bio-inspired Mobile Ad Hoc Network Routing Protocol
Authors: Muhammad Saleem, Syed Ali Khayam, Muddassar Farooq
Venue: Proceedings of the 6th international conference on Ant Colony Optimization and Swarm Intelligence (2008)

Design and development of routing protocols for Mobile Ad Hoc Networks (MANETs) is an active area of research. The standard practice among researchers working in this emerging domain is to evaluate the performance of their routing protocols in a network simulator. It is now a well known fact that the simulation studies are scenario specific and hence their results can not be generalized. In this paper, we present mathematical models of two key performance metrics, routing overhead and route optimality, of BeeAdHoc MANET routing protocol. One of the key components of our BeeAdHoc model is the collision model at Medium Access Control (MAC) layer. The mathematical expressions of the performance metrics provide valuable insight about the behavior of BeeAdHoc in particular, and a typical ad hoc routing protocol in general, without resorting to scenario specific time consuming simulations.
Correction
Venue: IEEE Computer Graphics and Applications (1983)

In the January/February issue of IEEE CG&A, an incorrect entry was in-advertently included in Carl Machover's ¿An Updated Guide to Sources of Information about Computer Graphics.¿ The correct address for Computer-Aided Design, a publication of Butterworth Scientific Ltd.¿ Journals Division, is PO Box 63, Westbury House, Bury St., Guildford, Surrey GU2 5BH, England. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Natural Conjugate Gradient in Variational Inference
Authors: Antti Honkela, Matti Tornio, Tapani Raiko, Juha Karhunen
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part II (2008)

Variational methods for approximate inference in machine learning often adapt a parametric probability distribution to optimize a given objective function. This view is especially useful when applying variational Bayes (VB) to models outside the conjugate-exponential family. For them, variational Bayesian expectation maximization (VB EM) algorithms are not easily available, and gradient-based methods are often used as alternatives. Traditional natural gradient methods use the Riemannian structure (or geometry) of the predictive distribution to speed up maximum likelihood estimation. We propose using the geometry of the variational approximating distribution instead to speed up a conjugate gradient method for variational learning and inference. The computational overhead is small due to the simplicity of the approximating distribution. Experiments with real-world speech data show significant speedups over alternative learning algorithms.
SlopeMiner: An Improved Method for Mining Subtle Signals in Time Course Microarray Data
Authors: Kevin Mccormick, Roli Shrivastava, Li Liao
Venue: Proceedings of the 2nd annual international workshop on Frontiers in Algorithmics (2008)

This paper presents an improved method, SlopeMiner, for analyzing time course microarray data by identifying genes that undergo gradual transitions in expression level. The algorithm calculates the slope for the slow transition between the expression levels of data, matching the sequence of expression level for each gene against temporal patterns having one transition between two expression levels. The method, when used along with StepMiner -an existing method for extracting binary signals, significantly increases the annotation accuracy.
Convex Hull of Arithmetic Automata
Authors: Jérôme Leroux
Venue: Proceedings of the 15th international symposium on Static Analysis (2008)

Arithmetic automata recognize infinite words of digits denoting decompositions of real and integer vectors. These automata are known expressive and efficient enough to represent the whole set of solutions of complex linear constraints combining both integral and real variables. In this paper, the closed convex hull of arithmetic automata is proved rational polyhedral. Moreover an algorithm computing the linear constraints defining these convex set is provided. Such an algorithm is useful for effectively extracting geometrical properties of the whole set of solutions of complex constraints symbolically represented by arithmetic automata.
Compiling pattern matching to good decision trees
Authors: Luc Maranget
Venue: Proceedings of the 2008 ACM SIGPLAN workshop on ML (2008)

We address the issue of compiling ML pattern matching to compact and efficient decisions trees. Traditionally, compilation to decision trees is optimized by (1) implementing decision trees as dags with maximal sharing; (2) guiding a simple compiler with heuristics. We first design new heuristics that are inspired by necessity, a concept from lazy pattern matching that we rephrase in terms of decision tree semantics. Thereby, we simplify previous semantic frameworks and demonstrate a straightforward connection between necessity and decision tree runtime efficiency. We complete our study by experiments, showing that optimizing compilation to decision trees is competitive with the optimizing match compiler of Le Fessant and Maranget (2001).
Facial Expression Recognition Based on Emotion Dimensions on Manifold Learning
Authors: Young-Suk Shin
Venue: Proceedings of the 7th international conference on Computational Science, Part II (2007)

This paper presents a new approach method to recognize facial expressions in various internal states using manifold learning (ML). The manifold learning of facial expressions reflects the local features of facial deformations such as concavities and protrusions. We developed a representation of facial expression images based on manifold learning for feature extraction of facial expressions. First, we propose a zero-phase whitening step for illumination-invariant images. Second, facial expression representation from locally linear embedding (LLE) was developed. Finally, classification of facial expressions in emotion dimensions was generated on two dimensional structure of emotion with pleasure/displeasure dimension and arousal/sleep dimension. The proposed system maps facial expressions in various internal states into the embedding space described by LLE. We explore locally linear embedding space as a facial expression space in continuous dimension of emotion. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Compliance Measurement Framework (CMF)
Authors: Virendra K. Varshney, Nanjangud C. Narendra, Anuradha Bhamidipaty, Shailabh Nagar
Venue: Proceedings of the 2008 IEEE Congress on Services - Part I (2008)

IT service delivery processes need to adhere to several regulations such as security, confidentiality and data integrity. These regulations are typically defined as policies, each of which contains a list of clauses. These are usually verified by periodic audits, which are usually ad-hoc, time-consuming and difficuly verify objectively. In this paper, we present a formal framework - Compliance Measurement Framework (CMF) -by which compliance of the instances of a process model to apolicy can be formally modeled and objectively measured. The primary element of CMF is Process Policy Compliance Index (PPCI). It is the compliance score of a set of execution traces of a process model against the set of clauses of a single policy. This can be further extended to Multi-PPCI - for multiple policies - and Organizational Compliance Index (OCI) - for an aggregate score across the entire organization. In this paper, we focus on dynamic compliance checks where the above indices are computed over several instances of process execution. By using enough instances of execution, the resulting index reflects the real state of non-compliance while also increasing the probability of all relevant paths within the process model being followed. In this paper, we focus on PPCI determination, leaving M-PPCI and OCI for future work.
Ethnic Identity and Engagement in Embodied Conversational Agents
Authors: Francisco Iacobelli, Justine Cassell
Venue: Proceedings of the 7th international conference on Intelligent Virtual Agents (2007)

In this paper we present the design, development and initial evaluation of a virtual peer that models ethnicity through culturally authentic verbal and non-verbal behaviors. The behaviors chosen for the implementation come from an ethnographic study with African-American and Caucasian children and the evaluation of the virtual peer consists of a study in which children interacted with an African American or a Caucasian virtual peer and then assessed its ethnicity. Results suggest that it may be possible to tip the ethnicity of a embodied conversational agent by changing verbal and non-verbal behaviors instead of surface attributes, and that children engage with those virtual peers in ways that have promise for educational applications.
Replica Placement Strategy Research in Education Resource Grid
Authors: Chang-ming Xing, Fang-ai Liu, Feng-juan Zhang
Venue: Proceedings of the 2008 International Symposiums on Information Processing (2008)

Replication mechanism is the efficient method of improving grid performances and reducing client delay. Replica placement strategy is the key problem of replication mechanism. This paper introduces the architecture of Education Resource Grid. According to the architecture, it presents three dynamic replica placement strategies. These strategies can optimize the system performance from different aspects and reduce client delay on the premise of keeping the storage space of replica. These strategies are proved to be effective by analyzing experiment data.