ppxscal/embedding_network huggingface dataset:
Fuzzy Kanerva-based function approximation for reinforcement learning
Authors: Cheng Wu, Waleed Meleis
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

Radial Basis Functions and Kanerva Coding can give poor performance when applied to large-scale multi-agent systems. In this paper, we attempt to solve a collection of predator-prey pursuit instances and argue that the poor performance is caused by frequent prototype collisions. We show that dynamic prototype allocation and adaptation can give better results by reducing these collisions. We then describe our novel approach, fuzzy Kanerva-based function approximation, that uses a fine-grained fuzzy membership grade to describe a state-action pair's adjacency with respect to each prototype. This approach completely eliminates prototype collisions. We conclude that adaptive fuzzy Kanerva Coding can significantly improve a reinforcement learner's ability to solve large-scale multi-agent problems.
Implementing a normalizer using sized heterogeneous types
Authors: Andreas Abel
Venue: Journal of Functional Programming (2009)

In the simply typed λ-calculus, a hereditary substitution replaces a free variable in a normal form r by another normal form s of type a, removing freshly created redexes on the fly. It can be defined by lexicographic induction on a and r, thus giving rise to a structurally recursive normalizer for the simply typed λ-calculus. We implement hereditary substitutions in a functional programming language with sized heterogeneous inductive types <inline-graphic mime-subtype="gif" xlink="S0956796809007266_inline1"><alt-text>$\Fhat$</alt-text></inline-graphic>, arriving at an interpreter whose termination can be tracked by the type system of its host programming language.
Enhancing tidal prediction accuracy in Singapore regional model using local model approach
Authors: Yabin Sun, Piyamarn Sisomphon, Vladan Babovic, Eng Soon Chan
Venue: Proceedings of the 10th WSEAS international conference on Mathematical methods, computational techniques and intelligent systems (2008)

With the objective to provide hydrodynamic information of the water around Singapore, the Singapore Regional Model (SRM) has been developed within the Delft3D numerical modelling system. The results of this large-domain numerical model are necessarily a balance between the choices about domain, local resolution, model parameter settings and representation of forcing. Especially in the complex nearshore area around Singapore Island, however, high accuracy in prediction of water levels is required. To further improve the results of the deterministic Singapore Regional Model in the coastal area, an error correction scheme based on the local model (LM) approach is carried out, which is inspired from chaos theory and capable of forecasting the time series based on the underlying mechanism that may not be revealed in the deterministic model simulation. The efficiency of the error correction scheme has been tested on 3 stations in the Singapore Regional Model domain with 4 prediction horizons ranging from 2 hours to 96 hours. It is found that the error correction scheme significantly improves the accuracy of the tidal prediction with more than 70% of the root mean square error removed for 2-hour tidal forecast and around 50% for 96-hour tidal forecast.
Backup Path Classification Based on Failure Risks for Efficient Backup Path Computation
Authors: Mohand Yazid Saidi, Bernard Cousin, Jean-Louis Roux
Venue: Proceedings of the 8th International IFIP-TC 6 Networking Conference (2009)

We propose a new approach exploiting the failure risk (node, link or Shared Risk Link Group) structures to enhance the backup path computation. Upon failure, our approach classifies the backup paths into two categories: operative backup paths and inoperative backup paths. An operative backup path is an active backup path which really receives traffic of some affected communications while an inoperative backup path does not receive any traffic.With the observation that only the operative backup paths really participate to the recovery procedure, we enhance the backup path computation (1) by limiting the concurrence for the protection bandwidth allocations to the operative backup paths (instead of all the active backup paths like in the classical approaches) and (2) by reducing the set of failure risks that a backup path must bypass.Simulations show that our approach improves the protection bandwidth allocations and decreases the ratio of rejected backup paths.
What's in a session: tracking individual behavior on the web
Authors: Mark Meiss, John Duncan, Bruno Gonçalves, José J. Ramasco, Filippo Menczer
Venue: Proceedings of the 20th ACM conference on Hypertext and hypermedia (2009)

We examine the properties of all HTTP requests generated by a thousand undergraduates over a span of two months. Preserving user identity in the data set allows us to discover novel properties of Web traffic that directly affect models of hypertext navigation. We find that the popularity of Web sites--the number of users who contribute to their traffic--lacks any intrinsic mean and may be unbounded. Further, many aspects of the browsing behavior of individual users can be approximated by log-normal distributions even though their aggregate behavior is scale-free. Finally, we show that users' click streams cannot be cleanly segmented into sessions using timeouts, affecting any attempt to model hypertext navigation using statistics of individual sessions. We propose a strictly logical definition of sessions based on browsing activity as revealed by referrer URLs; a user may have several active sessions in their click stream at any one time. We demonstrate that applying a timeout to these logical sessions affects their statistics to a lesser extent than a purely timeout-based mechanism.
Argument-Based Negotiation and Conflict Resolution through Enactive Role Play in Second Life
Authors: Azilawati Jamaludin, Caroline Mei Lin Ho, Yam San Chee
Venue: Proceeding of the 2007 conference on Supporting Learning Flow through Integrative Technologies (2007)

This paper proposes the use of an immersive virtual environment, Second Life, for enactive role play to help students recognize and solve conflicts through argument-based negotiation. An important core of the epistemology of negotiation is that stakeholders in a dispute have legitimate conflicting interests, and the goal of negotiation is to reconcile those interests in an equitable manner given the constraints of the situation. In this study, students role-play as lead negotiators for parties in a dispute concerning a fictitious island which seeks to join the community of regional and international democracies after decades of totalitarian government. The discourse corpora of five student groups across two enactment sessions were analyzed using an adapted collaborative argumentation framework. We present the results of a two-step analysis approach that involves an initial single dialectical move analysis and a sequential analysis for pertinent moves and patterns within the virtual interaction. We discuss how these dialectical and sequential moves impact upon students' acceptance or non-acceptance of a conflict resolution. We conclude with a discussion on related pedagogical implications.
Multicast congestion control for content distribution
Authors: Oscar Martinez-Bonastre, Carlos E. Palau
Venue: Proceedings of the 4th edition of the UPGRADE-CN workshop on Use of P2P, GRID and agents for the development of content networks (2009)

Content Delivery Networks (CDNs) provide an efficient support for serving http and streaming media content while minimizing the network impact of content delivery as well as overcoming the server overload problem. Not too much research effort has been placed in the analysis of the access network and the impact and benefits of multicast. This paper proposes an innovative real-time protocol offering an hybrid congestion control algorithm called Scalable Reliable Multicast Stair Hybrid (SRMSH) which combines the benefits of TCP AIMD with Rate-based (STAIR) [2] for layered multicast with Scalable Reliable Multicast (SRM) [6] in order to offer loss recovery methods if receivers detect loss events. The mechanism has been simulated and implemented to proof its benefits.
Extracting hypernym pairs from the web
Authors: Erik Tjong Kim Sang
Venue: Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions (2007)

We apply pattern-based methods for collecting hypernym relations from the web. We compare our approach with hypernym extraction from morphological clues and from large text corpora. We show that the abundance of available data on the web enables obtaining good results with relatively unsophisticated techniques.
Collision course by transformation of coordinates and plane decomposition
Authors: K. Bendjilali, F. Belkhouche
Venue: Robotica (2009)

This paper deals with the problem of collision course checking in a dynamic environment for mobile robotics applications. Our method is based on the relative kinematic equations between moving objects. These kinematic equations are written under polar form. A transformation of coordinates is derived. Under this transformation, collision between two moving objects is reduced to collision between a stationary object and a virtual moving object. In addition to the direct collision course, we define the indirect collision course, which is more critical and difficult to detect. Under this formulation, the collision course problem is simplified, and complex scenarios are reduced to simple scenarios. In three-dimensional (3D) settings, the working space is decomposed into two planes: the horizontal plane and the vertical plane. The collision course detection in 3D is studied in the vertical and horizontal planes using 2D techniques. This formulation brings important simplifications to the collision course detection problem even in the most critical and difficult scenarios. An extensive simulation is used to illustrate the method in 2D and 3D working spaces.
Distributing content updates over a mobile social network
Authors: Stratis Ioannidis, Augustin Chaintreau, Laurent Massoulié
Venue: ACM SIGMOBILE Mobile Computing and Communications Review (2009)

We study the dissemination of content updates, such as news or traffic information, over a mobile social network. In this application, mobile users receive content updates from their service provider. To improve coverage and increase capacity, we assume that they also share such updates, opportunistically, whenever they meet. We show that the service provider can allocate its downlink bandwidth so that it maximizes the aggregate utility over all users, i.e., the social welfare. Moreover, we specify a condition under which the system is highly scalable: even if the total bandwidth dedicated by the service provider remains fixed, the expected content age at each user grows slowly (as log(n)) with the number of users n.
IUTAM Symposium on Discretization Methods for Evolving Discontinuities: Proceedings of the IUTAM Symposium held Lyon, France, 4 7 September, 2006, 1st edition
Authors: Alain Combescure, Rena, de Borst, Ted Belytschko
Venue: Iutam Bookseries (2007)

With mechanics focusing on smaller and smaller length scales, the need to properly model discontinuities increases. Technically important interface problems appear in solid mechanics, at fluid-solid boundaries, e.g. in welding and casting processes, and in aeroelasticity. Discretization methods have traditionally been developed for continuous media and are less well suited for treating discontinuities. Indeed, they are approximation methods for the solution of the partial differential equations, which are valid on a domain. Discontinuities divide this domain into two or more parts and at the interface special solution methods must be employed. Also, fluid-solid interfaces cannot be solved accurately except at the expense of complicated and time-consuming remeshing procedures. In recent years, discretization methods have been proposed, which are more flexible and which have the potential of capturing (moving) discontinuities in a robust and efficient manner. This volume assembles contributions of leading experts with the most recent developments in this rapidly evolving field.
Developing a Practical Domain Knowledge Base and Problem Solving System for Intelligent Educational System of High School Chemistry
Authors: Nana Ishima, Toru Ueda, Tatsuhiro Konishi, Yukihiro Itoh
Venue: Proceeding of the 2006 conference on Learning by Effective Utilization of Technologies: Facilitating Intercultural Understanding (2006)

In this paper, we describe the development of our intelligent educational system for high school chemistry. Our goal is to put our system in practical use. To achieve our goal, the system must be usable for at least half a year or more. So we focus on the scale of a domain knowledge base (DKB) and a problem data base. We examine the framework of the chemical world model, and describe problem representation and knowledge representation. We tried to expand the DKBthe problem data base. We include an example of problem solving process using the DKB.
Privacy-preserving techniques for location-based services
Authors: Elisa Bertino
Venue: SIGSPATIAL Special (2009)

Recent advances in positioning techniques, small devices, GIS-based services, and ubiquitous connectivity, have enabled a large variety of location-based services able to tailor services according to the location of the individual requiring the service. Location information, however, if on one side is critical for providing customized services, on the other hand, if misused, can lead to privacy breaches. By cross-referencing location information about an individual with other information and by exploiting domain knowledge, an attacker may infer sensitive information about the individual, such as healthcare or financial information. To address such problems, different techniques have been proposed that are based on two main approaches: location cloaking, under which a suitable large region is returned to the service provider instead of the precise user location [1]; location k-anonymization, under which the location of an individual is returned to the service provider only if it is indistinguishable with respect to the location of other k-1 individuals [5, 6]. These techniques have, however, a major drawback in that they do not take into account domain knowledge, and are thus prone to location inference attacks [2]. Given a generalized location of an individual, obtained for example through location cloaking, such an attack exploits the knowledge about the semantics of spatial entities to infer bounds about the location of an individual that are more precise with respect to the generalized location. Another major drawback is that those approaches do not support personalized privacy preferences. We believe that supporting such preferences is crucial in that different individuals have different preferences with respect to which location are considered privacy-sensitive.
Analysis of Components for Generalization using Multidimensional Scaling
Authors: Robertas Damaševičius
Venue: Fundamenta Informaticae (2009)

To achieve better software quality, to shorten software development time and to lower development costs, software engineers are adopting generative reuse as a software design process. The usage of generic components allows increasing reuse and design productivity in software engineering. Generic component design requires systematic domain analysis to identify similar components as candidates for generalization. However, component feature analysis and identification of components for generalization usually is done ad hoc. In this paper, we propose to apply a data visualization method, called Multidimensional Scaling (MDS), to analyze software components in the multidimensional feature space. Multidimensional data that represent syntactical and semantic features of source code components are mapped to 2D space. The results of MDS are used to partition an initial set of components into groups of similar source code components that can be further used as candidates for generalization. STRESS value is used to estimate the generalizability of a given set of components. Case studies for Java Buffer and Geom class libraries are presented.
Rethinking Information Systems: Organizational Processes and How to Change Them, 1st edition
Authors: John Kawalek
Venue:  (2007)

Business / Management of Information Systems In Rethinking Information Systems in Organizations John Paul Kawalek challenges the current orthodoxy of information systems and proposes new alternatives. Bold and ambitious, this book tackles the thorny issues of integration of disciplines, cross over of functions, and negotiation of epistemological divides in IS. Historically, the IS discipline has struggled to embrace and integrate technical as well as organizational knowledge, skills and methods. Kawalek argues that there are now a new set of imperatives that will irrecoverably change IS, affecting the way many organizations deploy and access their information and technology. This book defines how the traditional practices of Information Systems are required to integrate into a process of organizational problem-solving. An essential read for students of business information systems, organizational theory and research methods, Kawaleks work also provides core methodological principles on organizational change and problem solving, and presents an effective rationale for their use in Information Systems contexts. John Paul Kawalek has a professional background is in IT and Management Consulting. He now lectures in Systems Theory, Change Management and Management Consultancy at the University of Sheffield, UK, and is also an associate Professor at the Grnoble Graduate School of Business, France. 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
A Reliable and Useful Information Distribution System: the “Kuchicomi Network”
Authors: Jun Sasaki, Tae Yoneda, Yutaka Funyu
Venue: Proceeding of the 2006 conference on Information Modelling and Knowledge Bases XVII (2006)

As the Internet and mobile Internet have been expanding widely, we can now obtain many kinds of information easily and in large quantities. However, it is still difficult, for example, for tourists to get reliable and useful information about locations that they have never visited. In this paper we propose a reliable and useful information distribution system, called the “Kuchicomi Network,” to provide “kuchicomi,” or word-of-mouth, information that is supplied by local informants through mobile phones or PCs connected to the Internet. We introduce the concept of, and business model for, a “Kuchicomi Network” and explain the system structure. We then describe features of the system and outline the development of a prototype system.
Grid-Enabled Adaptive Metamodeling and Active Learning for Computer Based Design
Authors: Dirk Gorissen
Venue: Proceedings of the 22nd Canadian Conference on Artificial Intelligence: Advances in Artificial Intelligence (2009)

Many complex, real world phenomena are difficult to study directly using controlled experiments. Instead, the use of computer simulations has become commonplace as a feasible alternative. However, due to the computational cost of these high fidelity simulations, the use of neural networks, kernel methods, and other surrogate modeling techniques have become indispensable. Surrogate models are compact and cheap to evaluate, and have proven very useful for tasks such as optimization, design space exploration, prototyping, and sensitivity analysis. Consequently, in many scientific fields there is great interest in techniques that facilitate the construction of such regression models, while minimizing the computational cost and maximizing model accuracy. This paper presents a fully automated machine learning toolkit for regression modeling and active learning to tackle these issues. A strong focus is placed on adaptivity, self-tuning and robustness in order to maximize efficiency and make the algorithms and tools easily accessible to other scientists in computational science and engineering.
Effect of Female Role Models in IT on Young Girls' Attitudes toward Computing---an Experimental Study
Authors: Pi-Chi Chen, Pei-Chi Chan
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)

This ongoing study investigates the effect of female role models in IT (information technology) on high school female students' attitude toward computers and their motivation to select computer-related study majors in the future. A website introducing female role models in Taiwan's IT industry, academia and public schools is being built. A quasi-experiment will be applied after the website is complete. The significance of this research and the expected outcomes are as follows: (1) this study is the first project presenting female IT role models in Taiwan. (2) This website not only attracts public attention on the issues of gender equity in IT, but also encourages young girls and women in Taiwan to pursue careers in IT-related field. (3) The experimental results will provide empirical evidence of the effect of female role models in IT on young girls' attitudes and decisions toward IT-related careers.
Image normalization techniques for robust face recognition
Authors: Vitomir Štruc, Nikola Pavešić
Venue: Proceedings of the 8th WSEAS international conference on Signal processing, robotics and automation (2009)

Histogram equalization has been the dominant image preprocessing technique in the field of face recognition for years now. With the property of increasing the global contrast of an image while simultaneusly compensating for the illumination conditions present at the image acquisition stage, it represents a useful preprocessing step, which can ensure enhaced and more robust recognition performance. Several, more elaborate techniques, such as the multiscale retinex approach or anisotropic smoothing, have been proposed by researchers to take the place of histogram equalization, but have ulitimately been found to be more of a complement than a real substitute. However, by closer examining the characteristics of histogram equalization, one can quickly discover that it represents only a specific case of a more general concept of histogram remapping techniques (which may have similar characteristics as histogram equalization does). While histogram equalization remapps the histogram of a given facial image to a uniform distribution, the target distribution could easily be replaced by an arbitrary one. With no theoretical proof of a specific distribution being particularly suited for the task of face recognition, at least the question arises of why the uniform distribution is commonly chosen for the histogram remapping. In this paper we present an empirical assessment of the concept of histogram remapping. We report comparative results obtained on the XM2VTS and YaleB databases for four target distributions, i.e., the uniform, the normal, the lognormal and the exponential distribution, and conclude that similar or even better recognition results can be achieved when other than the uniform distribution is considered for the histogram remapping.