ppxscal/embedding_network huggingface dataset:
A Genetic-Based Feature Construction Method for Data Summarisation
Authors: Rayner Alfred
Venue: Proceedings of the 4th international conference on Advanced Data Mining and Applications (2008)

The importance of input representation has been recognised already in machine learning. This paper discusses the application of genetic-based feature construction methods to generate input data for the data summarisation method called Dynamic Aggregation of Relational Attributes (DARA). Here, feature construction methods are applied in order to improve the descriptive accuracy of the DARA algorithm. The DARA algorithm is designed to summarise data stored in the non-target tables by clustering them into groups, where multiple records stored in non-target tables correspond to a single record stored in a target table. This paper addresses the question whether or not the descriptive accuracy of the DARA algorithm benefits from the feature construction process. This involves solving the problem of constructing a relevant set of features for the DARA algorithm by using a genetic-based algorithm. This work also evaluates several scoring measures used as fitness functions to find the best set of constructed features.
Data Fusion Assurance for the Kalman Filter in Uncertain Networks
Authors: Bonnie Zhu, Shankar Sastry
Venue: Proceedings of the 2008 The Fourth International Conference on Information Assurance and Security (2008)

Due to standardization and connectivity to other networks, networked control systems, a vital component of many nations' critical infrastructures, face potential disruption. Its possible manifestation can affect Kalman filter, the primary recursive estimation method used in control engineering field. Whereas to improve such estimation, data fusion may take place at a central location to fuse and process multiple sensor measurements delivered over the network. In a uncertain networked control system where the nodes and links are subject to attacks, false or compromised or missing individual readings can produce skewed result. To assure the validity of data fusion, this paper proposes a centralized trust rating system that evaluates the trustworthiness of each sensor reading on top of the fusion mechanism. The ratings are represented by Beta distribution, the conjugate prior of the binomial distribution and its posterior. Then an illustrative example demonstrates its efficiency.
Efficient Content Authentication in Peer-to-Peer Networks
Authors: Roberto Tamassia, Nikos Triandopoulos
Venue: Proceedings of the 5th international conference on Applied Cryptography and Network Security (2007)

We study a new model for data authentication over peer-to-peer (p2p) storage networks, where data items are stored, queried and authenticated in a totally decentralized fashion. The model captures the security requirements of emerging distributed computing applications. We present an efficient construction of a distributed Merkle tree (DMT), which realizes an authentication tree over a p2p network, thus extending a fundamental cryptographic technique to distributed environments. We show how our DMT can be used to design an authenticated distributed hash table that is secure against replay attacks and consistent with the update history. Our scheme is built on top of a broad class of existing p2p overlay networks and achieves generality by using only the basic functionality of object location. We use this scheme to design the first efficient distributed authenticated dictionary.
Explorative Data Mining on Stock Data --- Experimental Results and Findings
Authors: Lay-Ki Soon, Sang Ho Lee
Venue: Proceedings of the 3rd international conference on Advanced Data Mining and Applications (2007)

This paper presents our preliminary explorative data mining experiments on stock data. The experiments are performed using information gain evaluation, chi-square test and decision tree, which aim to explore the underlying patterns of the stock dataset. The explorative patterns obtained show some unexpected outliers in deriving the influential stocks with regard to Kuala Lumpur Composite Index.
Online Communities: A Social Computing Perspective
Authors: Xiarong Li, Daniel Zeng, Wenji Mao, Fei-Yue Wang
Venue: Proceedings of the IEEE ISI 2008 PAISI, PACCF, and SOCO international workshops on Intelligence and Security Informatics (2008)

In recent years, the growth of the Internet has facilitated the rapid emergence of online communities. In this paper, we survey key research issues on online communities from the perspectives of both social science and computing technologies. We also sample several major online community applications, and propose some directions for future research.
Visual Mathematics: Diagrammatic Formalization and Proof
Authors: John Howse, Gem Stapleton
Venue: Proceedings of the 9th AISC international conference, the 15th Calculemas symposium, and the 7th international MKM conference on Intelligent Computer Mathematics (2008)

Diagrams have been used for centuries in the visualization of mathematical concepts and to aid the exploration and formalization of ideas. This is hardly surprising given the intuitive appeal of visual languages. Thus it seems very natural to establish how diagrams can play an integral part of mathematical formalization and reasoning, giving them the same status as the symbolic languages that they are used alongside. Indeed, recently we have seen the emergence of diagrammatic reasoning systems that are defined with sufficient mathematical rigour to allow them to be used as formal tools in their own right. Some of these systems have been designed with particular application areas in mind, such as number theory and real analysis, or formal logics. This paper focuses on the use of diagrammatic logics to formalize mathematical theories with the same level of rigour that is present in their corresponding predicate logic axiomatizations. In particular, extensions to the constraint diagram logic are proposed to make it more suitable for use in mathematics. This extended logic is illustrated via the diagrammatic formalization of some commonly occurring mathematical concepts. Subsequently, we demonstrate its use in the proofs of some simple theorems.
A Privacy-Preserving eHealth Protocol Compliant with the Belgian Healthcare System
Authors: Bart Decker, Mohamed Layouni, Hans Vangheluwe, Kristof Verslype
Venue: Proceedings of the 5th European PKI workshop on Public Key Infrastructure: Theory and Practice (2008)

Real world healthcare systems are generally large and overly complex systems. Designing privacy-friendly protocols for such systems is a challenging task. In this paper we present a privacy-preserving protocol for the Belgian healthcare system. The proposed protocol protects the patients' privacy throughout the prescription handling process, while complying with most aspects of the current Belgian healthcare practise. The presented protocol relies on standard privacy-preserving credential systems, and verifiable public key cryptography, which makes it readily fit for implementation.
Parallel Grammatical Evolution for Circuit Optimization
Authors: Ondrej Popelka, Pavel Osmera
Venue: Proceedings of the 8th international conference on Evolvable Systems: From Biology to Hardware (2008)

This paper describes application of Parallel Grammatical Evolution (PGE) algorithm to combinatorial logic circuit generation. The grammar and algorithms used are described. To increase the efficiency of Grammatical Evolution (GE) the backward processing algorithm was used. Different approaches to create multiobjective fitness functions are described and tested. Specifically the fitness functions are defined as set of rules incorporating different comparison methods in each stage of the computation. The algorithm is internally parallel and consists of three different interconnected populations.
Stochastic search methods for nash equilibrium approximation in simulation-based games
Authors: Yevgeniy Vorobeychik, Michael P. Wellman
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2 (2008)

We define the class of games called simulation-based games, in which the payoffs are available as an output of an oracle (simulator), rather than specified analytically or using a payoff matrix. We then describe a convergent algorithm based on a hierarchical application of simulated annealing for estimating Nash equilibria in simulation-based games with finite-dimensional strategy sets. Additionally, we present alternative algorithms for best response and Nash equilibrium estimation, with a particular focus on one-shot infinite games of incomplete information. Our experimental results demonstrate that all the approaches we introduce are efficacious, albeit some more so than others. We show, for example, that while iterative best response dynamics has relatively weak convergence guarantees, it outperforms our convergent method experimentally. Additionally, we provide considerable evidence that a method based on random search outperforms gradient descent in our setting.
A New Myohaptic Device to Assess Wrist Function in the Lab and in the Clinic --- The Wristalyzer
Authors: Giuliana Grimaldi, Piet Lammertse, Niels Braber, Jos Meuleman, Mario Manto
Venue: Proceedings of the 6th international conference on Haptics: Perception, Devices and Scenarios (2008)

Wristalyzer is a portable robotic device combining haptic technology with electromyographic assessment. It allows to assess wrist motion in physiological and pathological conditions by applying loads and mechanical oscillations, taking into account the ergonomy and the angular positioning of the joints. The wristalyzer works in a free or loaded mode for assessment of metrics of motion and tremor, analyzes the behavior of the wrist joints and the associated muscle activities during delivery of mechanical oscillations, estimates the maximal voluntary contraction, assesses automatically the impedance of the wrist for assessment of rigidity or spasticity. Position, torques and electromyographic activities are analyzed in real time. The device characterizes the effects of damping on voluntary motion. A personal computer implements control loops and user application. This is the first standardized tool to assess wrist motion with high accuracy and reliability using the haptic technology with concomitant investigation of muscle activity.
Learning with Continuous Experts Using Drifting Games
Authors: Indraneel Mukherjee, Robert E. Schapire
Venue: Proceedings of the 19th international conference on Algorithmic Learning Theory (2008)

We consider the problem of learning to predict as well as the best in a group of experts making continuous predictions. We assume the learning algorithm has prior knowledge of the maximum number of mistakes of the best expert. We propose a new master strategy that achieves the best known performance for online learning with continuous experts in the mistake bounded model. Our ideas are based on drifting games, a generalization of boosting and online learning algorithms. We also prove new lower bounds based on the drifting games framework which, though not as tight as previous bounds, have simpler proofs and do not require an enormous number of experts.
Overview of the INEX 2007 Entity Ranking Track
Authors: Arjen P. Vries, Anne-Marie Vercoustre, James A. Thom, Nick Craswell, Mounia Lalmas
Venue: Focused Access to XML Documents: 6th International Workshop of the Initiative for the Evaluation of XML Retrieval, INEX 2007 Dagstuhl Castle, Germany, December 17-19, 2007. Selected Papers (2008)

Many realistic user tasks involve the retrieval of specific entities instead of just any type of documents. Examples of information needs include `Countries where one can pay with the euro' or `Impressionist art museums in The Netherlands'. The Initiative for Evaluation of XML Retrieval (INEX) started the XML Entity Ranking track (INEX-XER) to create a test collection for entity retrieval in Wikipedia. Entities are assumed to correspond to Wikipedia entries. The goal of the track is to evaluate how well systems can rank entities in response to a query; the set of entities to be ranked is assumed to be loosely defined either by a generic category (entity ranking) or by some example entities (list completion). This track overview introduces the track setup, and discusses the implications of the new relevance notion for entity ranking in comparison to ad hoc retrieval.
eSurvey: A Survey Record Based eLearning System for Research Degree Study
Authors: Joseph Fong, Herbert Shiu
Venue: Proceedings of the 1st international conference on Hybrid Learning and Education (2008)

In research studies, a student starts with writing a research proposal, followed up by intensive literature and industrial survey in his/her own research area. The student must perform his/her own research with validation under supervisor's guidance. The student's own research work must be differentiated from others work in order to demonstrate the unique originality and significance of the students' contribution. The information explosion on the Internet makes the survey analysis much more difficult. This paper suggests a solution by recording both the students' own research work and others work into a meta data, and compare them for further analysis as part of student's dissertation. The record based eLearning system can track the progress of student's research studies in, problem statement, proposed solution, analysis, findings, publication and feedback, in an eLearning system.
Temporal Conformance of Federated Choreographies
Authors: Johann Eder, Amirreza Tahamtan
Venue: Proceedings of the 19th international conference on Database and Expert Systems Applications (2008)

Web service composition is a new way for implementing business processes. In particular, a choreography supports modeling and enactment of interorganizational business processes consisting of autonomous organizations. Temporal constraints are important quality criteria. We propose a technique for modeling temporal constraints in choreographies and orchestrations, checking whether the orchestrations satisfy the temporal constraints of a choreography and compute internal deadlines for the activities in an interorganizational workflow.
Compiling self-adjusting programs with continuations
Authors: Ruy Ley-Wild, Matthew Fluet, Umut A. Acar
Venue: ACM SIGPLAN Notices (2008)

Self-adjusting programs respond automatically and efficiently to input changes by tracking the dynamic data dependences of the computation and incrementally updating the output as needed. In order to identify data dependences, previously proposed approaches require the user to make use of a set of monadic primitives. Rewriting an ordinary program into a self-adjusting program with these primitives, however, can be difficult and error-prone due to various monadic and proper-usage restrictions, some of which cannot be enforced statically. Previous work therefore suggests that self-adjusting computation would benefit from direct language and compiler support. In this paper, we propose a language-based technique for writing and compiling self-adjusting programs from ordinary programs. To compile self-adjusting programs, we use a continuation-passing style (cps) transformation to automatically infer a conservative approximation of the dynamic data dependences. To prevent the inferred, approximate dependences from degrading the performance of change propagation, we generate memoized versions of cps functions that can reuse previous work even when they are invoked with different continuations. The approach offers a natural programming style that requires minimal changes to existing code, while statically enforcing the invariants required by self-adjusting computation. We validate the feasibility of our proposal by extending Standard ML and by integrating the transformation into MLton, a whole-program optimizing compiler for Standard ML. Our experiments indicate that the proposed compilation technique can produce self-adjusting programs whose performance is consistent with the asymptotic bounds and experimental results obtained via manual rewriting (up to a constant factor).
On the minimum common integer partition problem
Authors: Xin Chen, Lan Liu, Zheng Liu, Tao Jiang
Venue: ACM Transactions on Algorithms (TALG) (2008)

We introduce a new combinatorial optimization problem in this article, called the minimum common integer partition (MCIP) problem, which was inspired by computational biology applications including ortholog assignment and DNA fingerprint assembly. A partition of a positive integer n is a multiset of positive integers that add up to exactly n, and an integer partition of a multiset S of integers is defined as the multiset union of partitions of integers in S. Given a sequence of multisets S1, S2, &hellip;, Sk of integers, where k &ge; 2, we say that a multiset is a common integer partition if it is an integer partition of every multiset Si, 1 &le; i &le; k. The MCIP problem is thus defined as to find a common integer partition of S1, S2, &hellip;, Sk with the minimum cardinality, denoted as MCIP(S1, S2, &hellip;, Sk). It is easy to see that the MCIP problem is NP-hard, since it generalizes the well-known subset sum problem. We can in fact show that it is APX-hard. We will also present a 5/4-approximation algorithm for the MCIP problem when k &equals; 2, and a 3k(k&minus;1)/3k&minus;2-approximation algorithm for k &ge; 3.
State space optimization using plan recognition and reinforcement learning on RTS game
Authors: Jaeyong Lee, Bonjung Koo, Kyungwhan Oh
Venue: Proceedings of the 7th WSEAS International Conference on Artificial intelligence, knowledge engineering and data bases (2008)

Real Time Strategy (RTS) Game has the same problem which has to be solved in decision making in the real world. These problems are on real-time performance, high complexity caused by the large state space and multi-agent, insufficient information and on-line learning. AI which has been applied to RTS Game is somewhat limited and has poor performance due to these problems. Recent research to apply AI to RTS Game has proposed Dynamic Scripting. This method is generating rule-based game script by using reinforcement learning. Dynamic Scripting, however, assuming arbitrary and limited state space, is not able to fully reflect characteristics of real-time environment. This paper suggests a method to optimize state space as a solution. For state space optimization Case-Based Plan Recognition (CBPR) is utilized to model behavior pattern of opponent agent, and abstract state space which was used in CBPR is also utilized as well. And it leads to simplify state space to decrease high complexity and enable RTS game to apply to real-time environment. This method is used in distributed RTS Game, WARGUS in this paper.
Passive Bilateral Control of a Teleoperation System Considering Hysteresis Nonlinearity of Slave Robot
Authors: Reza Seifabadi, Seyed Mehdi Rezaei, Saeed Shiry, Mozafar Saadat, Mohammad Zarei-Nejad, Kamran Razi, Hossein Habibollahi
Venue: Proceedings of the 6th international conference on Haptics: Perception, Devices and Scenarios (2008)

The slave robot of the macro-micro teleoperation system presented in this paper is a 1-DOF piezo actuator including hysteresis nonlinearity. This nonlinear behavior makes robot control a complex task. In this research the nonlinear and uncertain dynamics of the slave robot has been entered directly into the teleoperation control loop. The LuGre friction model is used as the estimator of the hysteresis loop to cancel out this undesirable term. A 2-DOF master-slave system is decomposed into two 1-DOF systems: a shape system representing the master-slave position coordination, and a locked system representing the dynamics of the coordinated system. For making the closed-loop teleoperation system passive against dynamic parameter uncertainty and force measurement inaccuracy, four virtual flywheels are designed. In this way, the energy generated by troublesome terms inside controllers (i.e. the terms which may endanger passivity of the controller) would be taken from the bounded kinetic energy deposited on these flywheels. Simulations are performed to show effectiveness of the proposed controllers.
DISC 20th Anniversary: Invited Talk Time, Clocks, and the Ordering of My Ideas About Distributed Systems
Authors: Leslie Lamport
Venue: Proceedings of the 21st international symposium on Distributed Computing (2007)

A guided tour through the labyrinth of my thoughts, from the Bakery Algorithm to arbiter-free marked graphs. This exercise in egotism is by invitation of the DISC 20th Anniversary Committee. I take no responsibility for the choice of topic.
Identification of Co-regulated Signature Genes in Pancreas Cancer- A Data Mining Approach
Authors: K. R. Seeja, M. A. Alam, S. K. Jain
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

Pancreas cancer is one of the most fatal among the cancers. The mortality rate is high due to the lack of tools for proper diagnosis and effective therapeutics. Identification of changes in gene expression in pancreas cancer may lead to the development of novel tools for diagnosis and effective treatment methodology. In this paper we present an association rule mining approach to identify the association between the genes that are either over expressed or under expressed in pancreas cancer compared to normal pancreas. We have used the SAGE data related to pancreas cancer. It is expected that the results will help in developing better treatment methodology for pancreas cancer and also for designing a low cost microarray chip for diagnosing pancreas cancer. The results have been validated in terms of Gene Ontology and the signature genes have been identified that match with published data.
3D Head Reconstruction and Color Visualization of Chinese Visible Human
Authors: Fan Bao, Yankui Sun, Xiaolin Tian, Zesheng Tang
Venue: Medical Imaging and Informatics: 2nd International Conference, MIMI 2007, Beijing, China, August 14-16, 2007 Revised Selected Papers (2008)

Since visible human visualization using cryosection images is still a challenge for its own difficulties such as color inhomogeneity between adjacent images, most visible human visualizations use pseudo color. In this paper, we propose a method to make cross-section image along human surface homogeneous, and provide a method to reconstruct and visualize 3D visible human with an approximate and reasonable real surface color. The visualization method consists of three components, which are preprocessing (registering image series, obtaining color checkers' color and removing background), color correction (global color correction with the help of the color checker and local color correction by using adjacent image) and 3D visualization with color (smoothing model and generating color). The experiment on head data of Chinese Visible Human shows that our method is successful for the 3D reconstruction and color visualization.