ppxscal/embedding_network huggingface dataset:
An e-market framework to determine the strength of business relationships between intelligent agents
Authors: Khandaker Shahidul Islam
Venue: Proceedings of the sixth Australasian conference on Data mining and analytics - Volume 70 (2007)

When an agent enters in an e-Market for the first time, it has no historical information that can be used to determine the strength of business relationship with participant agent, and must therefore rely on the reporting of other agents to prepare for negotiation with that agents. Beliefs of individual agents change through interaction with participant agents and are reflected in their on-going relationships. An understanding of business relationships is fundamental to understanding trade between both human agents in traditional markets and software agents in electronic markets. Two parties in the market establish agreement for mutual beneficial deals or contracts and therefore execute that deal or contract. Contextual information e.g., constraints, preferences, deadlines etc., during execution of the contract are unknown to each of the parties while they established the contract. Deviations between signed contract and executed contract are observed and used to measure the strength of relationship between two parties. We have presented an E-Market framework to describe how Institution Agent can assist for mining Outcome of Contract Execution by observing Argumentation Dialogues to determine how business relationship develops and evolves. In this work, development of an argumentation system is going on where Institution Agent observes the argumentation dialogue between buyer and seller agents. The results of observation are used to determine the strength of business relationship for future interactions between buyer agent and seller agent.
On Boundary Recognition without Location Information in Wireless Sensor Networks
Authors: Olga Saukh, Robert Sauter, Matthias Gauger, Pedro José Marrón, Kurt Rothermel
Venue: Proceedings of the 7th international conference on Information processing in sensor networks (2008)

Boundary recognition is an important and challenging issue in wireless sensor networks when no coordinates or distances are available. The distinction between inner and boundary nodes of the network can provide valuable knowledge to a broad spectrum of algorithms. This paper tackles the challenge of providing a scalable and range-free solution for boundary recognition that does not require a high node density. Our solution approximates the boundary of the sensor network by determining the inner nodes using geometric constructions that guarantee that, for a given d, a node lies inside of the construction for a d-quasi unit disk graph model of the wireless sensor network. Moreover, such geometric constructions make it possible to compute a guaranteed distance from a node to the boundary. We provide a thorough evaluation of our approach and show that it is applicable to dense as well as sparse deployments.
A Hybrid Approach to Selecting Susceptible Single Nucleotide Polymorphisms for Complex Disease Analysis
Authors: Pengyi Yang, Zili Zhang
Venue: Proceedings of the 2008 International Conference on BioMedical Engineering and Informatics - Volume 01 (2008)

An increasingly popular and promising way for complex disease diagnosis is to employ artificial neural networks(ANN). Single Nucleotide Polymorphisms (SNP) data from individuals is used as the inputs of ANN to find out specific SNP patterns related to certain disease. Due to the large number of SNPs, it is crucial to select optimal SNP subset and their combinations so that the inputs of ANN can be reduced. With this observation in mind, a hybrid approach –a combination of genetic algorithms (GA) and ANN (called GANN) is used to automatically determine optimal SNP set and optimize the structure of ANN. The proposed GANN algorithmis evaluated by using both a synthetic dataset and a real SNP dataset of a complex disease.
RSFQ technique for generation of ultra-fast pulse chains having controlled and variable time-domain parameters
Authors: Boyko Dimov, Valery Todorov, Valeri Mladenov, F. Hermann Uhlmann
Venue: Proceedings of the 9th International Conference on Circuits (2005)

A novel RSFQ circuit allowing the generation of an SFQ pulse chain containing a fixed number of pulses and precisely controlled picosecond variable time interval between them is presented. The generation of such SFQ pulse chains is necessary in many applications, but especially by the high-speed on-chip testing of RSFQ digital devices. The proposed circuit can be extended to a generator of an ultra high-speed rectangular voltage pulses with controlled and variable duration, suitable for readout by the conventional semiconductor electronics. Thus, an ultra high-speed digital data generation can be performed.
Something for everyone: AI lab assignments that span learning styles and aptitudes
Authors: Christopher League
Venue: Journal of Computing Sciences in Colleges (2008)

One of the great challenges of teaching is managing a wide range of educational backgrounds, learning styles, aptitudes, and time/energy constraints in the same classroom. Aiming down the middle is a poor strategy; it is unacceptable to write off the lower half of a class, and we risk extinguishing the enthusiasm of the best and brightest by moving too slowly. We present a set of workbook-style lab assignments for an undergraduate course on artificial intelligence. By designing them carefully in accordance with Bloom's taxonomy, they can span learning styles and aptitudes. With them, we hope to establish a disciplinary commons -- a public repository of source code, notes, questions, and exercises.
Proof of a conjecture of Alan Hartman
Authors: Q. Z. Liu, H. P. Yap
Venue: Journal of Graph Theory (1999)

A tree T is said to be bad, if it is the vertex-disjoint union of two stars plus an edge joining the center of the first star to an end-vertex of the second star. A tree T is good, if it is not bad. In this article, we prove a conjecture of Alan Hartman that, for any spanning tree T of K2m, where m &ge; 4, there exists a (2m - 1)-edge-coloring of K2m such that all the edges of T receive distinct colors if and only if T is good. &copy; 1999 John Wiley & Sons, Inc. J Graph Theory 30: 7&ndash;17, 1999
A control theoretical approach to self-optimizing block transfer in Web service grids
Authors: Anastasios Gounaris, Christos Yfoulis, Rizos Sakellariou, Marios D. Dikaiakos
Venue: ACM Transactions on Autonomous and Adaptive Systems (TAAS) (2008)

Nowadays, Web Services (WS) play an important role in the dissemination and distributed processing of large amounts of data that become available on the Web. In many cases, it is essential to retrieve and process such data in blocks, in order to benefit from pipelined parallelism and reduced communication costs. This article deals with the problem of minimizing at runtime, in a self-managing way, the total response time of a call to a database exposed to a volatile environment, like the Grid, as a WS. Typically, in this scenario, response time exhibits a concave, nonlinear behavior depending on the client-controlled size of the individual requests comprising a fixed size task. In addition, no accurate profiling or internal state information is available, and the optimum point is volatile. This situation is encountered in several systems, such as WS Management Systems (WSMS) for DBMS-like data management over wide area service-based networks, and the widely spread OGSA-DAI WS for accessing and integrating traditional DBMS. The main challenges in this problem apart from the unavailability of a model, include the presence of noise, which incurs local minima, the volatility of the environment, which results in moving optimum operating point, and the requirements for fast convergence to the optimal size of the request from the side of the client rather than of the server, and for low overshooting. Two solutions are presented in this work, which fall into the broader areas of runtime optimization and switching extremum control. They incorporate heuristics to avoid local optimal points, and address all the aforementioned challenges. The effectiveness of the solutions is verified via both empirical evaluation in real cases and simulations, which show that significant performance benefits can be provided rendering obsolete the need for detailed profiling of the WS.
Identifying Functional Groups by Finding Cliques and Near-Cliques in Protein Interaction Networks
Authors: Kyungsook Han, Guangyu Cui, Yu Chen
Venue: Proceedings of the 2007 Frontiers in the Convergence of Bioscience and Information Technologies (2007)

Many cellular processes are performed by a group of proteins rather than by individual proteins. When visualized in a protein-protein interaction network, proteins in a same biological unit often form a highly connected subgraph but loosely connected to the rest of the network. Therefore, finding a highly connected subgraph provides useful information to predict the function or protein complex of uncharacterized proteins in the highly connected subgraph. We have developed an efficient algorithm and program for finding cliques and near-cliques in a protein-protein interaction network. Analysis of the interaction network of yeast proteins demonstrates that 77% of the near-cliques identified by our algorithm have at least one function shared by all the proteins within a near-clique, and that 68% of the near-cliques show a good agreement with experimentally determined protein complexes catalogued in MIPS.
Evaluating the extent to which sociability and social presence affects learning performance
Authors: Terence Charlton, Lindsay Marshall, Marie Devlin
Venue: ACM SIGCSE Bulletin (2008)

Active Learning in Computing (ALiC) is the first Centre for Excellence in Teaching and Learning (CETL) project for Computing Science in England. Funded by HEFCE, the initiative seeks to prepare students for the realities of working in their chosen field by aligning their learning experiences and transferable skill sets with those sought by today's software engineering industry. One way ALiC achieves this is by introducing cross-site, collaborative group-programming tasks into the curriculum. Running over an academic year, this approach encourages active interaction and dialogue between student teams at Newcastle and Durham universities, and develops strong, real-world problem solving skills in participants. The ALiC project has thus far generated a great deal of positive feedback from undergraduates, and we feel our approach to inter-institutional teamwork offers students a realistic and relevant "real world" experience [2]. However, we are also becoming increasingly aware that time and resource pressures can make it difficult for students to maintain adequate levels of communication for any length of time [4], and once a team disperses it becomes difficult for its members to preserve the channels needed to interact and collaborate effectively. Consequently, an emerging area of research at Newcastle University concerns how learning can be enhanced through the use of computer-mediated social networking environments - online communities such as Facebook, Friendster and Bebo - through which registered users connect with friends and colleagues to explore similar interests and activities. In a collaborative educational context, these online social networking services offer an attractive means to foster student interaction and community building by providing a means to explore the common ground that exists between participants. [1] To that end, we intend to embed the communication and "social awareness" affordances - profile creation, synchronous and asynchronous chat, status updates, etc. - of popular social networking sites into our undergraduate, cross-site software engineering projects [3]. Social network analysis will be used to identify, map and analyse the flow of information and resources between distributed team members. The pedagogic motivation behind this work is to foster greater group-oriented interaction by filling the communication void that often arises between face-to-face meetings [5]. By reducing the geographic and temporal barriers to interaction and community formation (especially where 'peripheral', passive team members are concerned), team members will become increasingly aware of each others' skills, personalities, work rhythms and needs - both online and off - within a pre-existing, persistent, convenient infrastructure.
Kernelized fuzzy attribute C-means clustering algorithm
Authors: Jingwei Liu, Meizhi Xu
Venue: Fuzzy Sets and Systems (2008)

A novel kernelized fuzzy attribute C-means clustering algorithm is proposed in this paper. Since attribute means clustering algorithm is an extension of fuzzy C-means algorithm with weighting exponent m=2, and fuzzy attribute C-means clustering is a general type of attribute C-means clustering with weighting exponent m>1, we modify the distance in fuzzy attribute C-means clustering algorithm with kernel-induced distance, and obtain kernelized fuzzy attribute C-means clustering algorithm. Kernelized fuzzy attribute C-means clustering algorithm is a natural generalization of kernelized fuzzy C-means algorithm with stable function. Experimental results on standard Iris database and tumor/normal gene chip expression data demonstrate that kernelized fuzzy attribute C-means clustering algorithm with Gaussian radial basis kernel function and Cauchy stable function is more effective and robust than fuzzy C-means, fuzzy attribute C-means clustering and kernelized fuzzy C-means as well.
Memory bounded inference in topic models
Authors: Ryan Gomes, Max Welling, Pietro Perona
Venue: Proceedings of the 25th international conference on Machine learning (2008)

What type of algorithms and statistical techniques support learning from very large datasets over long stretches of time? We address this question through a memory bounded version of a variational EM algorithm that approximates inference in a topic model. The algorithm alternates two phases: "model building" and "model compression" in order to always satisfy a given memory constraint. The model building phase expands its internal representation (the number of topics) as more data arrives through Bayesian model selection. Compression is achieved by merging data-items in clumps and only caching their sufficient statistics. Empirically, the resulting algorithm is able to handle datasets that are orders of magnitude larger than the standard batch version.
Multishape-features and text-feature integration on 3D model similarity retrieval
Authors: Saiful Akbar, Josef Kung, Roland Wagner
Venue: International Journal of Innovative Computing and Applications (2008)

In this paper, we describe several 3D shape descriptors and integrate a textual descriptor with them for 3D model retrieval. We analyse five Shape-Feature Vector (FV) integration approaches, namely Pure FV Integration (PFI), Reduced FV Integration (RFI), Weight-Associated RFI (WRFI), Distance Integration (DI) and Rank Integration (RI). By running all possible-combinations of weighting factors on a training data set, the best weighting factor for each approach is obtained. Our experiments show that the best weighting factors improve the retrieval performance on not only the training data set, but also other data sets. This paper also shows that Distance Integration delivers the best retrieval effectiveness and Reduced FV Integration has the capability to deal with unknown query. In addition, the Distance Integration provides faster processing as it uses precomputed pair-wise distance and is more advantageous than PFI because of the dimension reduction. Hence, the use of both approaches (DI and RFI) is proposed. This paper also explains a use of the model file name as the only resource for text feature extraction. We study several textual similarity measures and then integrate multishape and text features into 3D model retrieval. Our experiments show that text feature can discriminate 3D models to each other in a certain degree of effectiveness, and integration text feature with multishape-feature improves retrieval effectiveness.
Modeling contextual security policies
Authors: Fr&#x00e9;d&#x00e9;ric Cuppens, Nora Cuppens-Boulahia
Venue: International Journal of Information Security (2008)

As computer infrastructures become more complex, security models must provide means to handle more flexible and dynamic requirements. In the Organization Based Access Control (OrBAC) model, it is possible to express such requirements using the notion of context. In OrBAC, each security rule (permission, prohibition, obligation or dispensation) only applies in a given context. A context is viewed as an extra condition that must be satisfied to activate a given security rule. In this paper, we present a taxonomy of different types of context and investigate the data the information system must manage in order to deal with these different contexts. We then explain how to model and evaluate them in the OrBAC model.
State Causality Analysis of Conservative Parallel Network Simulation
Authors: Siming Lin, Xueqi Cheng, Jianming Lv
Venue: Proceedings of the 41st Annual Simulation Symposium (anss-41 2008) (2008)

Critical path analysis is a traditional way to study the parallelism of conservative parallel simulation. In this paper, we propose a new technique called state causality analysis to accurately model the conservative parallel network simulation. A theorem of simulation time advancement is presented and proved. Different from critical path analysis, our method focuses on the dependency of the logical process states instead of the unpredictable events. The effects of many algorithm-independent factors, such as lookahead, I/O overhead, physical transfer delay, processor speed and event distribution, are all taken into consideration. With this method, the complicated relations between parallel performance and the algorithm-independent factors can be revealed distinctly, which however cannot be revealed by critical path analysis in most cases. The theoretical analyses and experiments show that our method always predict a stricter upper bound on the performance of a given network simulation task than critical path analysis, which may provide a baseline to evaluate the conservative synchronization algorithms excluding the effects of algorithm-independent factors.
Thermal characterization of embedded electronic features by an integrated system of CCD thermography and self-adaptive numerical modeling
Authors: Peter E. Raad, Pavel L. Komarov, Mihai G. Burzo
Venue: Microelectronics Journal (2008)

This work provides a practical application of a coupled experimental-computational system devised for the full characterization of the thermal behavior of complex three-dimensional active submicron electronic devices. A thermoreflectance thermography (TRTG) technique is used to non-invasively measure the 2D surface temperature field of an activated device, with submicron spatial resolution. The measured planar temperature distribution field is then used as input for an ultra-fast inverse computational solution to derive the three-dimensional temperature distribution throughout the device. For the purposes of this investigation, test micro-heater devices were constructed on epitaxial layers of natural (Si) and isotopically pure (Si^2^8) silicon. Then, all devices were activated and measured with the TRTG technique. In order to demonstrate the coupled experimental-computational system, the measured temperature fields of the samples whose thermal properties are known (Si) were used to extract critical physical parameters (the oxide layer thickness and the effective heater length). Then, since the devices with unknown thermal properties (Si^2^8) share the same construction with the Si devices, the extracted parameters were used together with the measured planar temperature fields to derive the thermal conductivity of Si^2^8. The extracted oxide layer thickness and thermal conductivity of Si^2^8 compared very closely to values obtained by other independent direct methods.
Exchange market for complex commodities: search for optimal matches
Authors: Eugene Fink, Jianli Gong, Josh Johnson
Venue: Journal of Experimental Theoretical Artificial Intelligence (2007)

The Internet has led to the development of online markets, and computer scientists have designed various auction algorithms, as well as automated exchanges for standardized commodities; however, they have done little work on exchanges for complex non-standard goods. We present an exchange system for trading complex goods, such as used cars or non-standard financial securities. The system allows traders to represent their buy and sell orders by multiple attributes; for example, a car buyer can specify a model, options, colour, and other desirable features. Traders can also provide complex price constraints, along with preferences among acceptable trades; for instance, a car buyer can specify dependency of an acceptable price on the model, year of production, and mileage. We describe the representation and indexing of orders, and give algorithms for fast identification of matches between buy and sell orders. The system identifies the most preferable matches, which maximize trader satisfaction, and it allows control over the trade-off between speed and optimality of matching. It supports markets with up to 300 000 orders, and processes hundreds of new orders per second.
Immix: a mark-region garbage collector with space efficiency, fast collection, and mutator performance
Authors: Stephen M. Blackburn, Kathryn S. McKinley
Venue: Proceedings of the 2008 ACM SIGPLAN conference on Programming language design and implementation (2008)

Programmers are increasingly choosing managed languages for modern applications, which tend to allocate many short-to-medium lived small objects. The garbage collector therefore directly determines program performance by making a classic space-time tradeoff that seeks to provide space efficiency, fast reclamation, and mutator performance. The three canonical tracing garbage collectors: semi-space, mark-sweep, and mark-compact each sacrifice one objective. This paper describes a collector family, called mark-region, and introduces opportunistic defragmentation, which mixes copying and marking in a single pass. Combining both, we implement immix, a novel high performance garbage collector that achieves all three performance objectives. The key insight is to allocate and reclaim memory in contiguous regions, at a coarse block grain when possible and otherwise in groups of finer grain lines. We show that immix outperforms existing canonical algorithms, improving total application performance by 7 to 25% on average across 20 benchmarks. As the mature space in a generational collector, immix matches or beats a highly tuned generational collector, e.g. it improves jbb2000 by 5%. These innovations and the identification of a new family of collectors open new opportunities for garbage collector design.