ppxscal/embedding_network huggingface dataset:
Multimodality and parallelism in design interaction: co-designers' alignment and coalitions
Authors: Françoise Detienne, Willemien Visser
Venue: Proceeding of the 2006 conference on Cooperative Systems Design: Seamless Integration of Artifacts and Conversations -- Enhanced Concepts of Infrastructure for Communication (2006)

This paper presents an analysis of various forms of articulation between graphico-gestural and verbal modalities in parallel interactions between designers in a collaborative design situation. Based on our methodological framework, we illustrate several forms of multimodal articulations, that is, integrated and non-integrated, through extracts from a corpus on an architectural design meeting. These modes reveal alignment or disalignment between designers, with respect to the focus of their activities. They also show different forms of coalition.
Technological Empowerment: The Internet, State, and Society in China
Authors: Yongnian Zheng
Venue:  (2007)

Will new information technologies, especially the Internet, bring freedom and democracy to authoritarian China? This study argues that the Internet has brought about new dynamics of socio-political changes in China, and that state power and social forces are transforming in Internet-mediated public space. Its findings are fourfold. First, the Internet empowers both the state and society. The Internet has played an important role in facilitating political liberalization, and made government more open, transparent, and accountable. Second, the Internet produces enormous effects which are highly decentralized and beyond the reach of state power. Third, the Internet has created a new infrastructure for the state and society in their engagement with (and disengagement from) each other. Fourth, the Internet produces a recursive relationship between state and society. The interactions between the state and society over the Internet end up reshaping both the state and society. 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
Design and analysis of knowledge-base centric insider threat models
Authors: Qutaibah Althebyan
Venue:  (2008)

Many consider insider attacks to be more severe than outsider attacks because of the nature of these attacks that involve people who have knowledge of their own organization. According to several studies and statistics, between 61% and 80% of computer crimes are being performed by trusted insiders of organizations. Many techniques exist for defending against outsider attacks. However, not much work has been presented for defending insider attacks and threats. Although several techniques have been proposed to defend against insider threats, the authors of these techniques and models follow an approach that concentrates on tracking insiders' activities rather than concentrating on the insiders themselves.This research concentrates on modeling and analyzing the insider threat problem. In order to solve the above-mentioned problem, we considered the insider as our basic entity that should be dealt with before looking into his/her activities. We found that one of the main factors that distinguishes an insider from the outsider is the amount of knowledge he/she accumulates through his/her privileges and accesses of the resources of the system. Hence, we use the insider's accumulated knowledge to build several models for insider threat prediction, prevention, mitigation and evaluation. The prediction model utilizes graph theory approaches, which can give alarms of increasing risks, which might lead to compromises of systems resources. The prevention algorithm tries to prevent possible compromises by insiders before they take place. The mitigation and evaluation model tries to detect, evaluate, and mitigate the underlying system considering the fact that one or more of the systems' resources have been compromised.Using these models, many novel techniques have been presented. Several novel graphs have been also offered, namely, knowledge graphs (KGs), dependency graphs (DGs), and knowledge Bayesian attack graphs (KBAGs). Several simulation experiments have been conducted to prove our models and to measure the performance and accuracy of our proposed work. 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
Computer-Supported Content Analysis for Collaborative Knowledge Building in CSCL
Authors: Jian Liao, Yanyan Li, Ying Zhou, Ronghuai Huang, Jingjing Wang
Venue: Proceeding of the 2006 conference on Learning by Effective Utilization of Technologies: Facilitating Intercultural Understanding (2006)

Interaction analysis plays an important role in computer-supported collaborative learning. This paper proposes an interaction analysis model CSCAC composed of three dimensions: group building level, member contribution, member support, which lays the foundation for interaction content analysis. Based on the model and domain ontology, this paper explores the text mining and semantic analysis technologies to automatically analyze the interaction content for collaborative knowledge building. An experiment is conducted to compare the auto-analysis result with that of manual analysis, which shows the the proposed approach is feasible and effective mostly to automatically analyze the interaction content in CSCL.
Special non-linear filter and extension to Shannon's channel capacity
Authors: Man Feng, Lenan Wu
Venue: Digital Signal Processing (2009)

The well-known Shannon's channel capacity defines the maximum transmission rate of communications in band-limited AWGN channels. An extended channel capacity equation is proved under the assumption of the different signal and noise bandwidth. Then a special filter named as the geometric feature filter (GFF) and satisfied with this assumption is found. Results indicate that Shannon's channel capacity equation is just a special example of this extension in the case of the same signal and noise bandwidth, but in different signal and noise bandwidth, capacity bounds should be calculated by this extension, which is a very important supplement to information theory.
Active management of cache resources
Authors: Sudhakar Yalamanchili
Venue:  (2008)

This dissertation addresses two sets of challenges facing processor design as the industry enters the deep sub-micron region of semiconductor design. The first set of challenges relates to the memory bottleneck. As the focus shifts from scaling processor frequency to scaling the number of cores, performance growth demands increasing die area. Scaling the number of cores also places a concurrent area demand in the form of larger caches. While on-chip caches occupy 50&ndash;60% of area and consume 20&ndash;30% of energy expended on-chip, their performance and energy efficiencies are less than 15% and 1% respectively for a range of benchmarks! The second set of challenges is posed by transistor leakage and process variation (inter-die and intra-die) at future technology nodes. Leakage power is anticipated to increase exponentially and sharply lower defect-free yield with successive technology generations. For performance scaling to continue, cache efficiencies have to improve significantly. This thesis proposes and evaluates a broad family of such improvements.This dissertation first contributes a model for cache efficiencies and finds them to be extremely low - performance efficiencies less than 15% and energy efficiencies in the order of 1%. Studying the sources of inefficiency leads to a framework for efficiency improvement based on two interrelated strategies. The approach for improving energy efficiency primarily relies on sizing the cache to match the application memory footprint during a program phase while powering down all remaining cache sets. Importantly, the sized is fully functional with no references to inactive sets. Improving performance efficiency primarily relies on cache shaping, i.e., changing the placement function and thereby the manner in which memory shares the cache.Sizing and shaping are applied at different phase of the design cycle: (i) post-manufacturing offline, (ii) at compile-time, and at (iii) run-time. This thesis proposes and explores techniques at each phase collectively realizing a repertoire of techniques for future memory system designers. The techniques use a combination of HW-SW techniques and are demonstrated to provide substantive improvements with modest overheads.
Efficient and Type-Safe Generic Data Storage
Authors: Sjaak Smetsers, Arjen van Weelden, Rinus Plasmeijer
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2009)

In this paper we present an elegant method for sequentializing arbitrary data using the generic language extension of the functional programming language Clean. We show how the proposed operations can be used to store values of any concrete data type in several kinds of IO containers (such as files or arrays of characters), and how to manipulate stored data efficiently. Moreover, by extending stored data with encoded type information, data manipulation will be type-safe. Defining these operations generically has the advantage that specific instances for user defined data types can be generated fully automatically. Compared to traditional sequentialization methods (or to common data manipulation, using relational data bases) our operations are an order of magnitude faster.
Rapid adaptation of POS tagging for domain specific uses
Authors: John E. Miller, Michael Bloodgood, Manabu Torii, K. Vijay-Shanker
Venue: Proceedings of the Workshop on Linking Natural Language Processing and Biology: Towards Deeper Biological Literature Analysis (2006)

Part-of-speech (POS) tagging is a fundamental component for performing natural language tasks such as parsing, information extraction, and question answering. When POS taggers are trained in one domain and applied in significantly different domains, their performance can degrade dramatically. We present a methodology for rapid adaptation of POS taggers to new domains. Our technique is unsupervised in that a manually annotated corpus for the new domain is not necessary. We use suffix information gathered from large amounts of raw text as well as orthographic information to increase the lexical coverage. We present an experiment in the Biological domain where our POS tagger achieves results comparable to POS taggers specifically trained to this domain.
Exploiting parallel networks using dynamic channel scheduling
Authors: Lara B. Deek, Kevin C. Almeroth, Mike P. Wittie, Khaled A. Harras
Venue: Proceedings of the 4th Annual International Conference on Wireless Internet (2008)

Many researchers have been focusing on the outcomes and consequences of the rapid increase and proliferation of mobile wireless technologies. If it is not already the case, it will soon be rare for a user to be in a situation where absolutely no network connection exists. In fact, through numerous devices, users will soon expect to be connected in all places at all times. Through the great variety and increase in the capabilities of these devices, it is not a surprise to find a single user with many connection opportunities. As a result, we believe that the next major evolution of wireless mobile networks will be in the exploitation of multiple network connections in parallel. Due to network heterogeneity, the major challenge in such situations is to determine the way that these networks can be utilized to better serve different network applications. In this work, we propose a dynamic channel scheduling mechanism that adapts to the state of the available channels to provide more efficient usage of network connectivity. We do so by observing channel throughput, creating a set of channel usage combinations, and then choosing the most efficient combination. We evaluate an implementation of the proposed mechanism using emulation. Our results show that under realistic conditions our dynamic approach greatly improves cost delay metrics, and the overall user-perceived performance compared to a more static approach.
Position-based unicast routing for city scenarios
Authors: Sascha Schnaufer, Wolfgang Effelsberg
Venue: Proceedings of the 2008 International Symposium on a World of Wireless, Mobile and Multimedia Networks (2008)

In Vehicular Ad-Hoc Networks unicast packet forwarding can be separated into the one-dimensional highway case and the two-dimensional city case; in this paper, we deal with the latter. We survey existing position-based routing protocols and present GRANT, our own approach of greedy routing with an abstract neighbor table. We simulate each protocol in our city scenario of Karlsruhe, consisting of streets with a length of 66 km, 390 junctions, and radio obstacles derived from high-definition satellite images. We also simulate the protocols with a FACE-2- and a distance vector-based recovery strategy. As a result we propose GRANT as a routing protocol for unicast city scenarios.
Visualization and analysis methods for comparing agent behavior in TAC SCM
Authors: William Groves, John Collins, Maria Gini
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

We are targeting for analysis a complex, multi-agent, repeated market simulation in which agents compete to maximize overall profit over a finite time horizon. The Trading Agent Competition for Supply Chain Management (TAC SCM), which has been run annually as a tournament for five years, is designed to model realistic supply chain and market mechanisms. In this paper, we introduce our extensible analysis framework that can be used for posing and answering new questions related to understanding market mechanisms and agent behavior.
Graph labellings with variable weights, a survey
Authors: Jerrold R. Griggs, Daniel Král'
Venue: Discrete Applied Mathematics (2009)

Graph labellings form an important graph theory model for the channel assignment problem. An optimum labelling usually depends on one or more parameters that ensure minimum separations between frequencies assigned to nearby transmitters. The study of spans and of the structure of optimum labellings as functions of such parameters has attracted substantial attention from researchers, leading to the introduction of real number graph labellings and @l-graphs. We survey recent results obtained in this area.
Description of Temporal Constraints Using Semantic Web in Role-Based Access Control
Authors: Kazushi Tanihira, Yusuke Sakamoto, Hiromi Kobayashi
Venue: Proceeding of the 2006 conference on Knowledge-Based Software Engineering: Proceedings of the Seventh Joint Conference on Knowledge-Based Software Engineering (2006)

This paper presents a description of an access control list (ACL) used to conduct role-based access control (RBAC), with particular emphasis on temporal constraints using extensible markup language (XML) and Web ontology language (OWL). It is natural to use OWL for describing ACL because OWL is based on set theory. Set theory is useful in this case because RBAC maps privileges naturally to users from the viewpoint of users' functions. Comparison of XML and OWL in terms of their use as an ACL is described. A teaching management model is used to illustrate examples of these implementations.
Fast Conjugate Gradients with Multiple GPUs
Authors: Ali Cevahir, Akira Nukada, Satoshi Matsuoka
Venue: Proceedings of the 9th International Conference on Computational Science: Part I (2009)

The limiting factor for efficiency of sparse linear solvers is the memory bandwidth. In this work, we describe a fast Conjugate Gradient solver for unstructured problems, which runs on multiple GPUs installed on a single mainboard. The solver achieves double precision accuracy with single precision GPUs, using a mixed precision iterative refinement algorithm. To achieve high computation speed, we propose a fast sparse matrix-vector multiplication algorithm, which is the core operation of iterative solvers. The proposed multiplication algorithm efficiently utilizes GPU resources via caching, coalesced memory accesses and load balance between running threads. Experiments on wide range of matrices show that our matrix-vector multiplication algorithm achieves up to 11.6 Gflops on single GeForce 8800 GTS card and CG implementation achieves up to 24.6 Gflops with four GPUs.
Development of a Maintenance Environment that Enabling Users to Revise Existing Web Applications
Authors: Hidaka Yano, Sota Honda, Jun Sasaki, Michiru Tanaka, Keizo Yamada, Yutaka Funyu
Venue: Proceeding of the 2007 conference on New Trends in Software Methodologies, Tools and Techniques: Proceedings of the sixth SoMeT_07 (2007)

Recently, the number of Business to Consumer (B2C) web applications has increased yearly. In particular, the increase in participation in the B2C market by small companies has been noticeable. This paper focuses on the use of B2C web applications by small companies. These businesses, typically, have little money to maintain web applications and also lack the skills to do so. In this paper, we present a self-maintenance model for the implementation of web applications in small business environments. We have surveyed current technologies in this area and have developed an actual maintenance environment for a B2C web application. This paper describes three experimental results for the environment. Finally, issues for future work and a new architecture are proposed to realize an ideal maintenance environment.
A query-based cross-language diagnosis tool for distributed decision making support
Authors: Pilsung Choe, Mark R. Lehto, Hyung Jun Park, Jan Allebach
Venue: Computers and Industrial Engineering (2009)

A query translation-based Korean-English cross-language diagnosis (Q-KE-CLD) tool for assisting Korean users diagnosing print defects was developed and then evaluated as a case study of distributed decision making support for nonnative English users. The first step in developing the Q-KE-CLD tool involved collecting and analyzing print defect descriptions in Korean and English. A fuzzy Bayesian model was obtained from the descriptions and the Q-KE-CLD tool was developed. The tool was then experimentally evaluated in four different universities in South Korea. Results showed that Korean subjects generated Korean queries faster (p=0.008) when entering Korean queries. In addition, the subjects rated Korean queries as being easier to generate (p=0.004). Untrained subjects reported that use of the Korean language made it easier to generate queries and identify print defects. The overall results suggested that query translation-based cross-language diagnosis is a feasible approach for localizing troubleshooting websites.
Improved Statistical Machine Translation Using Monolingual Paraphrases
Authors: Preslav Nakov
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

We propose a novel monolingual sentence paraphrasing method for augmenting the training data for statistical machine translation systems “for free” --by creating it from data that is already available rather than having to create more aligned data. Starting with a syntactic tree, we recursively generate new sentence variants where noun compounds are paraphrased using suitable prepositions, and vice-versa --preposition-containing noun phrases are turned into noun compounds. The evaluation shows an improvement equivalent to 33%--50% of that of doubling the amount of training data.
Hedonic coalition nets
Authors: Edith Elkind, Michael Wooldridge
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1 (2009)

In hedonic games, players have the opportunity to form coalitions, and have preferences over the coalitions they might join. Such games can be used to model a variety of settings ranging from multi-agent coordination to group formation in social networks. However, the practical application of hedonic games is hindered by the fact that the naive representation for such games is exponential in the number of players. In this paper, we study hedonic coalition nets---a succinct, rule-based representation for hedonic games. This formalism is based on marginal contribution nets, which were developed by Ieong and Shoham for representing coalitional games with transferable utility. We show that hedonic coalition nets are universally expressive, yet are at least as succinct as other existing representation schemes for hedonic games. We then investigate the complexity of many natural decision problems for hedonic coalition nets. In particular, we provide a complete characterisation of the computational difficulty of problems related to coalitional stability for hedonic games represented with hedonic nets.
Technical communique: An observation algorithm for nonlinear systems with unknown inputs
Authors: Jean-Pierre Barbot, Driss Boutat, Thierry Floquet
Venue: Automatica (Journal of IFAC) (2009)

This paper deals with the design of unknown input observers for nonlinear systems. An algorithm which determines if the state and the unknown input of the system can be recovered in finite time is introduced. This algorithm leads to the transformation of the system into an extended block triangular observable form suitable for the design of finite time observers. The proposed method is useful to relax some restrictive conditions of the existing nonlinear unknown input observer design procedures.
Bernoulli Neural Network with Weights Directly Determined and with the Number of Hidden- Layer Neurons Automatically Determined
Authors: Yunong Zhang, Gongqin Ruan
Venue: Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks (2009)

Conventional back-propagation (BP) neural networks have some inherent weaknesses such as slow convergence and local-minima existence. Based on the polynomial interpolation and approximation theory, a special type of feedforward neural-network is constructed in this paper with hidden-layer neurons activated by Bernoulli polynomials. Different from conventional BP and gradient-based training algorithms, a weights-direct-determination (WDD) method is proposed for the Bernoulli neural network (BNN) as well, which determines the neural-network weights directly (just in one general step), without a lengthy iterative BP-training procedure. Moreover, by analyzing the relationship between BNN performance and its different number of hidden-layer neurons, a structure-automatic-determination (SAD) algorithm is further proposed, which could obtain the optimal number of hidden-layer neurons in a constructed Bernoulli neural network in the sense of achieving the highest learning-accuracy for a specific data problem or target function/system. Computer-simulations further substantiate the efficacy of such a Bernoulli neural network and its deterministic algorithms.
Weather Recognition Based on Images Captured by Vision System in Vehicle
Authors: Xunshi Yan, Yupin Luo, Xiaoming Zheng
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III (2009)

Weather recognition is widely required in many areas, and it is also a challenging and brand-new subject. This paper proposes an approach to recognize weather based on images captured by in-vehicle vision system. We bring three groups of features, including histogram of gradient amplitude, HSV color histogram, road information, and employ an algorithm based on Real AdaBoost, making use of the category structure to achieve the task of classification. Experiments confirm superior performances on our dataset collected from images captured by vision system.