ppxscal/embedding_network huggingface dataset:
Constraining and summarizing association rules in medical data
Authors: Carlos Ordonez, Norberto Ezquerra, Cesar A. Santana
Venue: Knowledge and Information Systems (2006)

Association rules are a data mining technique used to discover frequent patterns in a data set. In this work, association rules are used in the medical domain, where data sets are generally high dimensional and small. The chief disadvantage about mining association rules in a high dimensional data set is the huge number of patterns that are discovered, most of which are irrelevant or redundant. Several constraints are proposed for filtering purposes, since our aim is to discover only significant association rules and accelerate the search process. A greedy algorithm is introduced to compute rule covers in order to summarize rules having the same consequent. The significance of association rules is evaluated using three metrics: support, confidence and lift. Experiments focus on discovering association rules on a real data set to predict absence or existence of heart disease. Constraints are shown to significantly reduce the number of discovered rules and improve running time. Rule covers summarize a large number of rules by producing a succinct set of rules with high-quality metrics.
An Overall Specification of a Meta-Model of Computation For Model-Driven Embedded System Modeling
Authors: Mokhoo Mbobi, Frederic Boulanger
Venue: Proceedings of the International Symposium on Collaborative Technologies and Systems (2006)

The prototyping of embedded systems being long and expensive, software models are often defined to be used as a behavioral reference for better exploration and evaluation of the systems properties. However, embedded systems being naturally heterogeneous, they require the coexistence of several models of computation. In software engineering, the great challenge is how to specify heterogeneous interfaces for ensuring well defined communications because various semantic properties are mixed. Therefore, some existing approaches use only a set of few models of computation to reduce this complexity. Some others can use an open set of models of computation but reduce the complexity by forbidding to use different models of computation in the same hierarchical level. This paper proposes a modeling approach based on the meta-modeling of models of computation. It allows to mix different models of computation by using a meta-model of computation which provides a common semantic description at a higher abstraction level. This makes easier to specify the interactions between models of computation.
Dorian: Grid Service Infrastructure for Identity Management and Federation
Authors: Stephen Langella, Scott Oster, Shannon Hastings, Frank Siebenlist, Tahsin Kurc, Joel Saltz
Venue: Proceedings of the 19th IEEE Symposium on Computer-Based Medical Systems (2006)

Identity management and federation is becoming an ever present problem in large multi-institutional environments. By their nature, Grids span multiple institutional administration boundaries and aim to provide support for the sharing of applications, data, and computational resources in a collaborative environment. One underlying problem is to enable participating institutions to manage the identities of their own members by leveraging existing institutional identity management systems, while at the same time facilitating the participation in larger Grids through the deployment of grid-wide user credentials. Those grid-wide identities are used for features such as single sign-on, secure communication, and are the basis for authorization decisions. In this paper we will present the design and implementation of Dorian, a grid service infrastructure component that enables the federation of users across the collaboration.
Evaluating the Association of Mitochondrial SNP Haplotypes with Disease Phenotypes using a Novel in silico Tool E-MIDAS
Authors: Anshu Bhardwaj, Shrish Tiwari
Venue: Proceedings of the 9th International Conference on Information Technology (2006)

Results of association studies using individual single nucleotide polymorphisms (SNPs) or SNPhaplotypes have been inconsistent. Possible reasons could be attributed to poor experimental design, generalization of results from a single population or inappropriate choice of markers. Here we explore the possibility that the sequence context of a SNP may be responsible for its poor association with the phenotype. An analysis of the Human_MitBASE data helped in the prediction of association between SNP haplotypes with disease phenotypes. A novel computational tool E-MIDAS was developed to automate this analysis. Based on our results, we propose omission of SNPs in CpG dinucleotides which have a mutation predisposing flank and those present at sites of recurrent mutation, from association studies.
ACC in Consideration of Visibility with Sensor Fusion Technology
Authors: Yukimasa Tamatsu, Hiroaki Kumon, Takashi Ogawa
Venue: Proceedings of the 21st International Conference on Data Engineering Workshops (2005)

This paper focuses on a relationship between factors of a bad visibility and driver's behavior, for example, driver tend to keep a long distance when a large preceding truck that blocks driver's frontal view and a long following distance. This driving characteristic was analyzed to build a driver's model. This driver's model including this driving characteristic was developed and validated in an actual ACC system by emulating this behavior by using this model and a recognition sensor that detects the size of the preceding vehicle.
Mindless Intelligence
Authors: Jordan B. Pollack
Venue: IEEE Intelligent Systems (2006)

AI was founded on a mistaken goal. Trying to create human-level intelligence by simulating cognitive architecture, often discovered via introspective protocols, is practically impossible owing to the limits of software engineering. However, many processes in nature are much more powerful than human symbolic thought. These exquisitely iterative systems, such as evolution and embryogenesis, don't require logic, grammar, or other accoutrements of anthropomorphic cognitive architecture. Successfully studying intelligence as it arises outside the human mind, rather than failing to deliver on the old promises of human-level performance, will put the field on a sturdier scientific and fiscal foundation.This article is part of a special issue on the Future of AI.
Unsupervised learning techniques for fine-tuning fuzzy cognitive map causal links
Authors: Elpiniki I. Papageorgiou, Chrysostomos Stylios, Peter P. Groumpos
Venue: International Journal of Human-Computer Studies (2006)

Fuzzy Cognitive Maps (FCMs) constitute an attractive knowledge-based methodology, combining the robust properties of fuzzy logic and neural networks. FCMs represent causal knowledge as a signed directed graph with feedback and provide an intuitive framework which incorporates the experts' knowledge. FCMs handle available information and knowledge from an abstract point of view. They develop behavioural model of the system exploiting the experience and knowledge of experts. The construction of FCMs is based mainly on experts who determine the structure of FCM, i.e. concepts and weighted interconnections among concepts. But this methodology may not be a sufficient model of the system because the human factor is not always reliable. Thus the FCM model of the system may requires restructuring which is achieved through adjustment the weights of FCM interconnections using specific learning algorithms for FCMs. In this article, two unsupervised learning algorithms are presented and compared for training FCMs; how they define, select or fine-tuning weights of the causal interconnections among concepts. The implementation and results of these unsupervised learning techniques for an industrial process control problem are discussed. The simulations results of training the process system verify the effectiveness, validity and advantageous characteristics of those learning techniques for FCMs.
Language and compiler design for streaming applications
Authors: Saman Amarasinghe, Michael I. Gordon, Michal Karczmarek, Jasper Lin, David Maze, Rodric M. Rabbah, William Thies
Venue: International Journal of Parallel Programming (2005)

High-performance streaming applications are a new and distinct domain of programs that is increasingly important. The StreamIt language provides novel high-level representations to improve programmer productivity and program robustness within the streaming domain. At the same time, the StreamIt compiler aims to improve the performance of streaming applications via stream-specific analysis and optimizations. In this paper, we motivate, describes and justify the StreamIt language which include a structured model of streams, a messaging system for control, and a natural textual syntax.
Forecasting the term structure of natural gas constant maturity futures using a seasonal principal components-based post-weighted monte carlo simulation
Authors: Elias A. Demetriades, Deborah Cernauskas
Venue: Proceedings of the 37th conference on Winter simulation (2005)

Given the increasing demand for natural gas, a number of industry participants have attempted to value their storage contracts. Such valuation involves both a forecasting of forward prices, as well as an optimization of spreads and/or options. Leading industry firms have utilized Principal Component Analysis and simulation to develop future values for forward contracts, using a covariance matrix of forward returns generated by historical data. We developed an improved procedure for applying the evolution of the historical covariance matrix. Our methodology involves the determination of a set of weights and the ensuing application of those weights on the results of Monte Carlo simulations under a variable-period switching of the VCV matrices. Out-of-sample results significantly improved the approximation of actual values of forwards and spreads. Furthermore, its deviations from market prices varied considerably less than those resulting from current techniques, allowing future users to calibrate their models to the market easier.
Integration of Visual and Auditory Information by Superior Temporal Sulcus Neurons Responsive to the Sight of Actions
Authors: Nick E. Barraclough, Dengke Xiao, Chris I. Baker, Mike W. Oram, David I. Perrett
Venue: Journal of Cognitive Neuroscience (2005)

Processing of complex visual stimuli comprising facial movements, hand actions, and body movements is known to occur in the superior temporal sulcus (STS) of humans and nonhuman primates. The STS is also thought to play a role in the integration of multimodal sensory input. We investigated whether STS neurons coding the sight of actions also integrated the sound of those actions. For 23% of neurons responsive to the sight of an action, the sound of that action significantly modulated the visual response. The sound of the action increased or decreased the visually evoked response for an equal number of neurons. In the neurons whose visual response was increased by the addition of sound (but not those neurons whose responses were decreased), the audiovisual integration was dependent upon the sound of the action matching the sight of the action. These results suggest that neurons in the STS form multisensory representations of observed actions.
An overview of business process adaptations via protocols
Authors: Nirmit Desai, Amit K. Chopra, Munindar P. Singh
Venue: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (2006)

Business process management in open environments poses special challenges. In particular, such environments are dynamic, thereby requiring frequent changes in business processes. Current business process modeling approaches handle such changes in an ad hoc manner, and lack a principled means of determining what needs to be changed and where.This paper provides an overview of process adaptability through a novel application of business protocols, especially of protocol composition, introduced in our previous work. Through a real business scenario of auto-insurance claim processing, this paper briefly describes how a wide range of adaptations can be handled naturally and systematically via protocol composition. The illustrated adaptations have been evaluated via a prototype.
Preserving Patterns in Bipartite Graph Partitioning
Authors: Tianming Hu, Chao Qu, Chew Lim Tan, Sam Yuan Sung, Wenjun Zhou
Venue: Proceedings of the 18th IEEE International Conference on Tools with Artificial Intelligence (2006)

This paper describes a new bipartite formulation for word-document co-clustering such that hyperclique patterns, strongly affiliated documents in this case, are guaranteed not to be split into different clusters. Our approach for pattern preserving clustering consists of three steps: mine maximal hyperclique patterns, form the bipartite, and partition it. With hyperclique patterns of documents preserved, the topic of each cluster can be represented by both the top words from that cluster and the documents in the patterns, which are expected to be more compact and representative than those in the standard bipartite formulation. Experiments with real-world datasets show that, with hyperclique patterns as starting points, we can improve the clustering results in terms of various external clustering criteria. Also, the partitioned bipartite with preserved topical sets of documents naturally lends itself to different functions in search engines.
Large Scale Detection of Irregularities in Accounting Data
Authors: Stephen Bay, Krishna Kumaraswamy, Markus G. Anderle, Rohit Kumar, David M. Steier
Venue: Proceedings of the Sixth International Conference on Data Mining (2006)

In recent years, there have been several large accounting frauds where a company's financial results have been intentionally misrepresented by billions of dollars. In response, regulatory bodies have mandated that auditors perform analytics on detailed financial data with the intent of discovering such misstatements. For a large auditing firm, this may mean analyzing millions of records from thousands of clients. This paper proposes techniques for automatic analysis of company general ledgers on such a large scale, identifying irregularities - which may indicate fraud or just honest errors - for additional review by auditors. These techniques have been implemented in a prototype system, called Sherlock, which combines aspects of both outlier detection and classification. In developing Sherlock, we faced three major challenges: developing an efficient process for obtaining data from many heterogeneous sources, training classifiers with only positive and unlabeled examples, and presenting information to auditors in an easily interpretable manner. In this paper, we describe how we addressed these challenges over the past two years and report on experiments evaluating Sherlock.
Can Integer Factorization be in P?
Authors: Song Y. Yan, Glyn James
Venue: Proceedings of the International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (2006)

Can the integer factorization problem be solved in poly- nomial time? or is the RSA public-key cryptosystem breakable in polynomial time? Answers to these ques- tions are not only important in mathematics but also important in network and information security. In this paper, a motivation for solving IFP from RSA will be introduced, and then some methods for IFP will be dis- cussed. Finally, some ideas, comments and advice on the practical use of RSA will be presented.
Bringing Industrial Methods to the Classroom
Authors: Dennis J. Frailey
Venue: Proceedings of the 19th Conference on Software Engineering Education and Training Workshops (2006)

Effective, professional quality work is expected of software engineering graduates, but may be difficult to teach via normal academic programs. This paper postulates that, in order to effectively prepare students for professional work, several key elements from the industrial world are beneficial: teamwork rather than a focus on individual accomplishments; setting an expectation for professional grade student work products; fairly rigorous guidelines for the format and general content of work products; knowledge of up-to-date work practices, and opportunities for rigorous review of interim work products. Although teamwork has frequently been discussed in software engineering education forums, the others have generally not been. They can be greatly enhanced by industry involvement.
Shape Topics: A Compact Representation and New Algorithms for 3D Partial Shape Retrieval
Authors: Yi Liu, Hongbin Zha, Hong Qin
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2 (2006)

This paper develops an efficient new method for 3D partial shape retrieval. First, a Monte Carlo sampling strategy is employed to extract local shape signatures from each 3D model. After vector quantization, these features are represented by using a bag-of-words model. The main contributions of this paper are threefold as follows: 1) a partial shape dissimilarity measure is proposed to rank shapes according to their distances to the input query, without using any timeconsuming alignment procedure; 2) by applying the probabilistic text analysis technique, a highly compact representation "Shape Topics" and accompanying algorithms are developed for efficient 3D partial shape retrieval, the mapping from "Shape Topics" to "object categories" is established using multi-class SVMs; and 3) a method for evaluating the performance of partial shape retrieval is proposed and tested. To our best knowledge, very few existing methods are able to perform well online partial shape retrieval for large 3D shape repositories. Our experimental results are expected to validate the efficacy and effectiveness of our novel approach.
Ajax timelines and the semantic web
Authors: Ben Martin
Venue: Linux Journal (2007)

Should we create a timeline on how we implement Timeline?
Broad exploration or precise specificity: Two basic information seeking patterns among students: Research Articles
Authors: Jannica Heinström
Venue: Journal of the American Society for Information Science and Technology (2006)

This article investigates whether information seeking patterns can be related to discipline differences, study approaches, and personality traits. A quantitative study of 305 master's thesis students' information behavior found that their information seeking tended to be either exploratory or precise. Statistical analyses showed that inner traits seemed more influential than discipline characteristics on information behavior. Exploration or specificity was manifested in terms of both the level and scope of information students wished to retrieve and the way they searched for it. &copy; 2006 Wiley Periodicals, Inc.
An Enterprise Electronic Contract Management System using Dual XML and Secure PDF Documents
Authors: Thomas Kwok, Thao Nguyen
Venue: Proceedings of the 10th IEEE on International Enterprise Distributed Object Computing Conference Workshops (2006)

As most current electronic contract management systems work well for only a few but not all processes in a contract lifecycle because of their inabilities to handle electronic documents in more than one file format simultaneously. In this paper, we present an efficient and automated enterprise electronic contract management system using both XML and secure PDF documents. The advantages of such dual file formats are to provide the best capabilities and functionalities for contract creation, negotiation, execution and data mining. The structured XML document allows an easy and flexible way to create, negotiate, revise and finalize a contract while the PDF document permits adding signature as watermark on a secure signed contract. A novel conversion method to convert between these two file formats is also described.
Enhanced Extrastriate Activation during Observation of Distorted Finger Postures
Authors: Sari Avikainen, Sasu Liuhanen, Martin Schürmann, Riitta Hari
Venue: Journal of Cognitive Neuroscience (2003)

Hand and finger postures of other people are important body language cues that strongly contribute to the observer's decision about the person's intentions, thoughts, and attentional state. We compared neuromagnetic cortical activation elicited by color images of natural and distorted finger postures. The distorted postures contained computer-deformed joint angles and thereby easily caught the observer's attention. From about 260 msec onwards, extrastriate occipital areas of both hemispheres were activated more strongly by distorted than natural finger postures. We interpret this result as an early top-down effect of emotional valence on the processing of unusual hand shapes in the extrastriate visual cortex.
PastryStrings: A Comprehensive Content-Based Publish/Subscribe DHT Network
Authors: Ioannis Aekaterinidis, Peter Triantafillou
Venue: Proceedings of the 26th IEEE International Conference on Distributed Computing Systems (2006)

In this work we propose and develop a comprehensive infrastructure, coined PastryStrings, for supporting rich queries on both numerical (with range, and comparison predicates) and string attributes, (accommodating equality, prefix, suffix, and containment predicates) over DHT networks utilising prefix-based routing. As event-based, publish/ subscribe information systems are a champion application class, we formulate our solution in terms of this environment.
Improving Program Guides for Reducing TV Stream Structuring Problem to a Simple Alignment Problem
Authors: Jean-Philippe Poli, Jean Carrive
Venue: Proceedings of the International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (2006)

TV stream structuring is the first step in the description process of telecasts for TV archives holders like the French National Audiovisual Institute. It consists in breaking down automatically the stream into telecasts and advertisings. One can think TV stream structuring consists in a simple alignement of the TV guide (for example Electronic Program Guide or TV magazines) on the stream. But our study shows that only 34% of telecasts appear in program guides. In average, 2 hours per day, composed of short telecasts and advertisings, are missing. We propose in this article a way to model and predict TV schedules (one day or one week of telecasts on a channel) by using a new extension of Markov models and regression trees. The goal is that the improved schedules obtained by the prediction can be aligned on the stream.
On the Efficiency of Dynamic Load Balancing on P2P Irregular Network Topologies
Authors: Muhammad Waseem Akhtar, M-Tahar Kechadi
Venue: Proceedings of the Proceedings of The Fifth International Symposium on Parallel and Distributed Computing (2006)

In this paper we introduce a two-phase dynamic loadbalancing technique for P2P computing systems. The first phase consists of mapping a P2P network onto a hierarchical topology based on 1-D space tessellations. This hierarchy is called TreeP (Tree based P2P architecture). The second phase consists of balancing the load among the peers using the PSLB (Positional Scan Load-Balancing) technique, which is well suited for regular topologies. We study this technique and optimize its implementation on the TreeP topology. This technique is simple, efficient, scalable, and does not introduce a considerable overhead as shown in the experimental results and theoretical study.