ppxscal/embedding_network huggingface dataset:
Improve peer cooperation using social networks
Authors: Victor Ponce, Jie Wu, Xiuqi Li
Venue: International Journal of Parallel, Emergent and Distributed Systems (2009)

Due to the dynamic nature of peer-to-peer (P2P) systems, it is impossible to keep an accurate history of the transactions that take place while avoiding security attacks such as whitewashing and collusion, and abuse such as freeriding. This is why it is important to develop a mechanism that both rewards cooperative peers and punishes misbehaving peers. Modelling P2P networks as social structures can allow incentive mechanisms to be developed that prevent the negative behaviours mentioned. In a social structure, peers make and receive payments for services provided to and from each other. In this paper, we extend a social network algorithm to include the transfer of credit between peers to reduce the path length in queries. We also develop a selection strategy that involves different aspects of peer interactions in P2P networks and a credit transfer mechanism that helps to discourage misbehaving peers by taking away credits that they have with good peers and transferring them to more cooperative ones. The simulation results show that our algorithm is effective in reducing the amount of debt between peers, meaning that peers become more cooperative, and shortening the average path length to a satisfied query, while increasing delivery ratio.
A wearable real-time image processor for a vision prosthesis
Authors: D. Tsai, J. W. Morley, G. J. Suaning, N. H. Lovell
Venue: Computer Methods and Programs in Biomedicine (2009)

Rapid progress in recent years has made implantable retinal prostheses a promising therapeutic option in the near future for patients with macular degeneration or retinitis pigmentosa. Yet little work on devices that encode visual images into electrical stimuli have been reported to date. This paper presents a wearable image processor for use as the external module of a vision prosthesis. It is based on a dual-core microprocessor architecture and runs the Linux operating system. A set of image-processing algorithms executes on the digital signal processor of the device, which may be controlled remotely via a standard desktop computer. The results indicate that a highly flexible and configurable image processor can be built with the dual-core architecture. Depending on the image-processing requirements, general-purpose embedded microprocessors alone may be inadequate for implementing image-processing strategies required by retinal prostheses.
Modular Equivalence for Normal Logic Programs
Authors: Emilia Oikarinen, Tomi Janhunen
Venue: Proceeding of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy (2006)

A Gaifman-Shapiro-style architecture of program modules is introduced in the case of normal logic programs under stable model semantics. The composition of program modules is suitably limited by module conditions which ensure the compatibility of the module system with stable models. The resulting module theorem properly strengthens Lifschitz and Turner's splitting set theorem [17] for normal logic programs. Consequently, the respective notion of equivalence between modules, i.e. modular equivalence, proves to be a congruence relation. Moreover, it is shown how our translation-based verification method [15] is accommodated to the case of modular equivalence; and how the verification of weak/visible equivalence can be optimized as a sequence of module-level tests.
Argumentation mining: the detection, classification and structure of arguments in text
Authors: Raquel Mochales Palau, Marie-Francine Moens
Venue: Proceedings of the 12th International Conference on Artificial Intelligence and Law (2009)

Argumentation is the process by which arguments are constructed and handled. Argumentation constitutes a major component of human intelligence. The ability to engage in argumentation is essential for humans to understand new problems, to perform scientific reasoning, to express, to clarify and to defend their opinions in their daily lives. Argumentation mining aims to detect the arguments presented in a text document, the relations between them and the internal structure of each individual argument. In this paper we analyse the main research questions when dealing with argumentation mining and the different methods we have studied and developed in order to successfully confront the challenges of argumentation mining in legal texts.
Current trends in research in the field of computer education and instructional technologies
Authors: Adile Askim Kurt, Özden Sahin Izmirli, Ferit Karakoyun
Venue: Proceedings of the international conference on Computational and information science 2009 (2009)

This study was conducted to determine the trend in studies carried out in department of Computer Education and Instructional Technologies (CEIT) at postgraduate level. For this purpose, a total of 106 documents of theses completed in the department of CEIT - 90 M.A. theses and 16 PhD. Theses - were examined focusing on their subject matters. It was concluded in the present study that the most-studied subject area was online learning, which was followed by technology, teaching-learning approaches, multimedia, individual differences and evaluation, respectively. The least-studied subject area was found to be special education. It was also revealed that the studies were mostly conducted through quantitative paradigm. In addition, according to the results of the present study, the most-studied universe included higher education students followed by adults and elementary school students, respectively. Lastly, most of the studies were found to have a survey design. Especially the M.A. theses involved basic statistical techniques at the beginning, while they included advanced statistical techniques today.
Correspondence: Comments on "H∞ filtering for discrete-time systems with randomly varying sensor delays"
Authors: Yueyang Li, Qiang Ding, Huihong Zhao
Venue: Automatica (Journal of IFAC) (2009)

An H"~ filtering algorithm for communication networks with random delays has been proposed in [Zhou S. S., & Feng G., (2008). H"~ filtering for discrete-time systems with randomly varying sensor delays. Automatica 44, 1918-1922]. Unfortunately, there exists a mistake which is fundamental to the results of the paper.
A Logical Treatment for the Emergence of Control in Complex Self-Organising Systems
Authors: Martin Randles, Azzelarabe Taleb-Bendiab, Philip Miseldine
Venue: Proceeding of the 2005 conference on Self-Organization and Autonomic Informatics (I) (2005)

In a complex dynamic system the centralised control and local monitoring of system behaviour is not achievable by scaling up simple feedback adaptation and control models. This paper proposes using a variety of concepts from distributed artificial intelligence (DAI) to logically model an abstract system control using adaptable agent federations to induce self-organisation in a swarm type system. The knowledge acquisition and updates are handled through a modal logic of belief for team dynamics and the system as a whole evolves to learn from local failures that have minimal impact on the global system. Self-governance emerges from innate (given) action thresholds that are adapted dynamically to system demands. In this way it is shown that such a system conforms to the prerequisites that have been specified as necessary for a system to exhibit self-organisation and the intrinsic benefits of agent teamwork are established for a robust, reliable and agile system. The approach is illustrated by looking at team formation in a swarm scenario from a proposed NASA project. The Situation Calculus is used to formalise the dynamic nature of such systems with a dynamic logic implementation to reason about the ensuing programs. Subsequently the model is encoded using the Neptune scripting language and compiled to an object-oriented system for its deployment on distributed systems architecture.
Using XML data integration and ontology reuse to share agricultural data
Authors: Ousmane Sall, Moussa Lo, Fabien Gandon, Cheikh Niang, Ibrahima Diop
Venue: International Journal of Metadata, Semantics and Ontologies (2009)

We present a data integration approach to enable multi-agency partners to share their agricultural data sources. We perform the integration in three phases. First, a structural integration phase, based on the use of XML documents warehouses (called dataweb), allows to create a warehouse for each partner. A second step consists in the integration of these dataweb by associating an ontology-based knowledge to each warehouse. That is done by a semi-automatic building of OWL ontology starting from dataweb and by re-use of the Agricultural Ontology Service. A third mediation phase permits to query in a uniform manner these different semantic dataweb.
A Secure Delegation Model Based on Multi-agent in Pervasive Environments
Authors: Kyu Il Kim, Won Gil Choi, Eun Ju Lee, Ung Mo Kim
Venue: Proceedings of the Third KES International Symposium on Agent and Multi-Agent Systems: Technologies and Applications (2009)

In pervasive environments, the connected devices can be aware the status of users and provide the information to users automatically in anytime, anywhere. However these require more security technologies to protect private information. The users must temporarily delegate some or all of their rights to agents in order to perform actions on their behalf. This results in the exposure of user privacy information by agents. We propose a delegation model for providing safety and user privacy in pervasive computing environments. In order to provide safety and user privacy, XML-based encryption and a digital signature mechanism needs to be efficiently integrated. In this paper, we propose access control mechanism based on eXtensible Access Control Markup Language (XACML) in order to manage the services and policies. We also extend SAML, in order to declare delegation assertions transferred to service providers by delegation among agents.
Multiscale traveling: crossing the boundary between space and scale
Authors: Xiaolong (Luke) Zhang
Venue: Virtual Reality (2009)

Adding multiscale interaction capabilities to 3D virtual environments may permit work with huge virtual worlds that might otherwise be too large to manage. Multiscale technology has shown potential to support user interactions. This paper reports an experimental study of two multiscale traveling techniques. Our results show that while allowing a flexible control on travel speed and accuracy is beneficial, directly traversing the space-scale could be a challenge for users, probably due to difficulties in perceiving scalable virtual space and executing scaling operations. The results suggest that more research is needed to improve the understanding of the coupling of space and scale in multiscale user interface and to harness the full potentials of multiscale traveling techniques.
An empirical comparison of throughput-maximizing wireless mesh routing protocols
Authors: Rupa Krishnan, Ashish Raniwala, Tzi-cker Chiueh
Venue: Proceedings of the 4th Annual International Conference on Wireless Internet (2008)

Communication quality of wireless network links is heavily dependent on various external factors such as physical geometry of environmental objects and interference among radio signal sources. As a result, the radio channel quality of real-world wireless networks tends to exhibit both short-term and long-term temporal variations that are in general difficult to model analytically. There has been a large body of research on maximizing the overall throughput of wireless mesh networks through dynamic load/capacity measurement and adaptive routing. However, so far there is no comprehensive evaluation of different protocol mechanisms on a real wireless network testbed. In this paper we first identify the major design dimensions of throughput-maximizing wireless mesh network routing protocols: wireless link capacity estimation, routing path selection, and adaptation to temporal link quality fluctuation, and empirically quantify the performance comparison of various alternatives in each dimension using both software simulations and a miniaturized multi-hop wireless network testbed-MiNT-m.
Distributed data source verification in wireless sensor networks
Authors: Mauro Conti, Roberto Di Pietro, Luigi V. Mancini, Alessandro Mei
Venue: Information Fusion (2009)

In-network data aggregation is favorable for wireless sensor networks (WSNs): It allows in-network data processing while reducing the network traffic and hence saving the sensors energy. However, due to the distributed and unattended nature of WSNs, several attacks aiming at compromising the authenticity of the collected data could be perpetrated. For example, an adversary could capture a node to create clones of the captured one. These clones disseminated through the network could provide malicious data to the aggregating node, thus poisoning/disrupting the aggregation process. In this paper we address the problem of detecting cloned nodes; a requirement to be fulfilled to provide authenticity of the data fusion process. First, we analyze the desirable properties a distributed clone detection protocol should meet. Specifically: It should avoid having a single point of failure; the load should be totally distributed across the nodes in the network; the position of the clones in the network should not influence the detection probability. We then show that current solutions do not meet the exposed requirements. Next, we propose the Information Fusion Based Clone Detection Protocol (ICD). ICD is a probabilistic, completely distributed protocol that efficiently detects clones. ICD combines two cryptographic mechanisms: The pseudo-random key pre-distribution, usually employed to secure node pairwise communications, with a sparing use of asymmetric crypto primitives. We show that ICD matches all the requirements above mentioned and compare its performance with current solutions in the literature; experimental results show that ICD has better performance than existing solutions for all the cost parameters considered: Number of messages sent, per sensor storage requirement, and signature verification. These savings allow to increase the network operating lifetime. Finally, note that ICD protocol could be used as an independent layer by any data aggregation mechanism.
Statistical identification of articulation constraints in the production of speech
Authors: Philip J. B. Jackson, Veena D. Singampalli
Venue: Speech Communication (2009)

We present a statistical technique for identifying critical, dependent and redundant roles played by the articulators during production of English phonemes using articulatory (EMA) data. It identifies a list of critical articulators for each phone based on changes in the distribution of articulator positions. The effect of critical articulation on dependent articulators is derived from inter-articulator correlation. Articulators unaffected or not correlated with the critical articulators are regarded as redundant. The technique was implemented on 1D and 2D distributions of midsagittal articulator coordinates, and the results of this data-driven approach are analyzed in comparison with the phonetic descriptions from the IPA chart. The results using the proposed method gave a closer fit to measured data than those estimated from IPA information alone and highlighted significant factors in the phoneme-to-phone transformation. The proposed algorithm was evaluated against an exhaustive search of critical articulators, and found to be as effective as the exhaustive search in modeling phone distributions with the added advantage of faster execution times. The efficiency of the approach in generating a parsimonious yet accurate representation of the observed articulatory constraints is described, and its potential for applications in speech science and technology discussed.
Volume visualization using advanced graphics hardware shaders
Authors: Roger Crawfis
Venue:  (2008)

Graphics hardware based volume visualization techniques have been the active research topic over the last decade. With the more powerful computation ability, the availability of large texture memory, and the high programmability, modern graphics hardware has been playing a more and more important role in volume visualization. In the first part of the thesis, we focus on the graphics hardware acceleration techniques. Particularly, we develop a fast X-Ray volume rendering technique using point-convolution. An X-ray image is generated by convolving the voxel projection in the rendering buffer with a reconstruction kernel. Our technique allows users to interactively view large datasets at their original resolutions on standard PC hardware. Later, an acceleration technique for slice based volume rendering (SBVR) is examined. By means of the early z-culling feature from the modern graphics hardware, we can properly set up the z-buffer from isosurfaces to gain significant improvement in rendering speed for SBVR. The high programmability of the graphics processing unit (GPU) incurs a great deal of research work on exploring this advanced graphics hardware feature. In the second part of the thesis, we first revisit the texture splat for flow visualization. We develop a texture splat vertex shader to achieve fast animated flow visualization. Furthermore, we develop a new rendering shader of the implicit flow. By careful tracking and encoding of the advection parameters into a three-dimensional texture, we achieve high appearance control and flow representation in real time rendering. Finally, we present an indirect shader synthesizer to combine different shader rendering effects to create a highly informative image to visualize the investigating data. One or more different shaders are associated with the voxels or geometries. The shader is resolved at run time to be selected for rendering. Our indirect shader synthesizer provides a novel method to control the appearance of the rendering over multi-shaders.
A Nash equilibrium solution in an oligopoly market: The search for Nash equilibrium solutions with replicator equations derived from the gradient dynamics of a simplex algorithm
Authors: Eitaro Aiyoshi, Atsushi Maki
Venue: Mathematics and Computers in Simulation (2009)

The present analysis applies continuous time replicator dynamics to the analysis of oligopoly markets. In the present paper, we discuss continuous game problems in which decision-making variables for each player are bounded on a simplex by equalities and non-negative constraints. Several types of problems are considered under conditions of normalized constraints and non-negative constraints. These problems can be classified into two types based on their constraints. For one type, the simplex constraint applies to the variables for each player independently, such as in a product allocation problem. For the other type, the simplex constraint applies to interference among all players, creating a market share problem. In the present paper, we consider a game problem under the constraints of allocation of product and market share simultaneously. We assume that a Nash equilibrium solution can be applied and derive the gradient system dynamics that attain the Nash equilibrium solution without violating the simplex constraints. Models assume that three or more firms exist in a market. Firms behave to maximize their profits, as defined by the difference between their sales and cost functions with conjectural variations. The effectiveness of the derived dynamics is demonstrated using simple data. The present approach facilitates understanding the process of attaining equilibrium in an oligopoly market.
Shallow discourse structure for action item detection
Authors: Matthew Purver, Patrick Ehlen, John Niekrasz
Venue: Proceedings of the HLT-NAACL 2006 Workshop on Analyzing Conversations in Text and Speech (2006)

We investigated automatic action item detection from transcripts of multi-party meetings. Unlike previous work (Gruenstein et al., 2005), we use a new hierarchical annotation scheme based on the roles utterances play in the action item assignment process, and propose an approach to automatic detection that promises improved classification accuracy while enabling the extraction of useful information for summarization and reporting.
Brief paper: Hand movement recognition based on biosignal analysis
Authors: Pawel Wojtczak, Tito G. Amaral, Octavio P. Dias, Andrzej Wolczowski, Marek Kurzynski
Venue: Engineering Applications of Artificial Intelligence (2009)

This paper proposes a methodology that analyses and classifies the electromyographic (EMG) signals using neural networks to control multifunction prostheses. The control of these prostheses can be made using myoelectric signals taken from surface electrodes. Finger motions discrimination is the key problem in this study. Thus the emphasis, in the proposed work, is put on myoelectric signal processing approaches. The EMG signals classification system was established using the linear neural network. The experimental results show a promising performance in classification of motions based on biosignal patterns.
SarsaLandmark: an algorithm for learning in POMDPs with landmarks
Authors: Michael R. James, Satinder Singh
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1 (2009)

Reinforcement learning algorithms that use eligibility traces, such as Sarsa(&lambda;), have been empirically shown to be effective in learning good estimated-state-based policies in partially observable Markov decision processes (POMDPs). Nevertheless, one can construct counterexamples, problems in which Sarsa(&lambda; < 1) fails to find a good policy even though one exists. Despite this, these algorithms remain of great interest because alternative approaches to learning in POMDPs based on approximating belief-states do not scale. In this paper we present SarsaLandmark, an algorithm for learning in POMDPs with "landmark" states (most man-made and many natural environments have landmarks). SarsaLandmark simultaneously preserves the advantages offered by eligibility traces and fixes the cause of the failure of Sarsa(&lambda;) on the motivating counterexamples. We present a theoretical analysis of SarsaLandmark for the policy evaluation problem and present empirical results on a few learning control problems.
Model Based ThoughtsCA∼EN and TIGER then and now
Authors: Louise Trave-Massuyes
Venue: Proceeding of the 2006 conference on Rob Milne: A Tribute to a Pioneering AI Scientist, Entrepreneur and Mountaineer (2006)

This paper is in memory of Rob Milne. It recalls the scientific experience of the TIGER and TIGER SHEBA European projects that he led through the presentation of CA∼EN, a model-based diagnosis software that was devised during the projects and integrated with the commercial tool TIGERTM. Several lines of more recent work that all build on CA∼EN are also presented. These developments are closely related to the Qualitative Reasoning and Model Based Diagnosis communities, represented by the MONET network of Excellence in Europe. Their theories inspired this work and I like to believe that this work inspired the communities in return. Rob Milne and myself were active members of MONET.