ppxscal/embedding_network huggingface dataset:
Feasibility and Dominance Rules in the Electromagnetism-Like Algorithm for Constrained Global Optimization
Authors: Ana Maria Rocha, Edite M. Fernandes
Venue: Proceedings of the international conference on Computational Science and Its Applications, Part II (2008)

This paper presents the use of a constraint-handling technique, known as feasibility and dominance rules, in a electromagnetism-like (ELM) mechanism for solving constrained global optimization problems. Since the original ELM algorithm is specifically designed for solving bound constrained problems, only the inequality and equality constraints violation together with the objective function value are used to select points and to progress towards feasibility and optimality. Numerical experiments are presented, including a comparison with other methods recently reported in the literature.
The Role of Face Parts in Gender Recognition
Authors: Yasmina Andreu, Ramón A. Mollineda
Venue: Proceedings of the 5th international conference on Image Analysis and Recognition (2008)

This paper evaluates the discriminant capabilities of face parts in gender recognition. Given the image of a face, a number of subimages containing the eyes, nose, mouth, chin, right eye, internal face (eyes, nose, mouth, chin), external face (hair, ears, contour) and the full face are extracted and represented as appearance-based data vectors. A greater number of face parts from two databases of face images (instead of only one) were considered with respect to previous related works, along with several classification rules. Experiments proved that single face parts offer enough information to allow discrimination between genders with recognition rates that can reach 86%, while classifiers based on the joint contribution of internal parts can achieve rates above 90%. The best result using the full face was similar to those reported in general papers of gender recognition (>95%). A high degree of correlation was found among classifiers as regards their capacity to measure the relevance of face parts, but results were strongly dependent on the composition of the database. Finally, an evaluation of the complementarity between discriminant information from pairs of face parts reveals a high potential to define effective combinations of classifiers.
Stability and chaos in a class of finite-dimensional discrete spatiotemporal systems
Authors: Chuanjun Tian, Guanrong Chen, Shengli Xie
Venue: Computers Mathematics with Applications (2008)

This paper is concerned with a class of finite-dimensional discrete spatiotemporal systems of the form {x"1(m+1,n)=f"1(x"1(m,n-1),x"1(m,n),x"2(m,n),...,x"k(m,n),x"1(m,n+1))x"2(m+1,n)=f"2(x"2(m,n-1),x"1(m,n),x"2(m,n),...,x"k(m,n),x"2(m,n+1))............x"k(m+1,n)=f"k(x"k(m,n-1),x"1(m,n),x"2(m,n),...,x"k(m,n),x"k(m,n+1)), where k>0 is an integer, f"i:R^k^+^2->R is a real function for all i=1,2,...,k, m@?N"0={0,1,2,...} and n@?Z={...,-1,0,1,...} (or, n@?N"0 in some special cases). Definitions of chaos of this system in the sense of Devaney and of Li-Yorke are given. Some sufficient conditions for this system to be stable and some illustrative examples for this system to be chaotic in the sense of Devaney and of Li-Yorke, respectively, are derived.
Why Tutored Problem Solving May be Better Than Example Study: Theoretical Implications from a Simulated-Student Study
Authors: Noboru Matsuda, William W. Cohen, Jonathan Sewall, Gustavo Lacerda, Kenneth R. Koedinger
Venue: Proceedings of the 9th international conference on Intelligent Tutoring Systems (2008)

Is learning by solving problems better than learning from worked-out examples? Using a machine-learning program that learns cognitive skills from examples, we have conducted a study to compare three learning strategies: learning by solving problems with feedback and hints from a tutor, learning by generalizing worked-out examples exhaustively, and learning by generalizing worked-out examples only for the skills that need to be generalized. The results showed that learning by tutored problem solving outperformed other learning strategies. The advantage of tutored problem solving was mostly due to the error detection and correction that was available only when skills were applied incorrectly. The current study also suggested that learning certain kinds of conditions to apply rules only for appropriate situations is quite difficult.
Managing the Life Cycle of Access Rules in CEOSIS
Authors: Stefanie Rinderle-Ma, Manfred Reichert
Venue: Proceedings of the 2008 12th International IEEE Enterprise Distributed Object Computing Conference (2008)

The definition and management of access rules (e.g., to control the access to business documents and business functions) is an important task within any enterprise information systems (EIS). Many EIS apply role-based access control (RBAC) mechanisms to specify access rules based on organizational models. However, only little research has been spent on organizational changes even though they often become necessary in practice. Examples comprise the evolution of organizational models with subsequent adaptation of access rules or direct access rule modifications. In this paper, we present a change framework for the controlled evolution of access rules in EIS. Specifically, we define change operations which ensure correct modification of access rules. Finally, we define the formal semantics of access rule changes based on operator trees which enables their unambiguous application; i.e., we can precisely determine which effects are caused by respective adaptations. This is important, for example, to be able to efficiently adapt user worklists in process-aware information systems. Altogether this paper contributes to comprehensive life cycle support for access rules in (adaptive) EIS.
Matching for Graphs of Bounded Degree
Authors: Yijie Han
Venue: Proceedings of the 2nd annual international workshop on Frontiers in Algorithmics (2008)

We show that there exists a matching with $\frac{4m}{5k+3}$ edges in a graph of degree k and m edges.
Hyponymy Patterns
Authors: Verginica Barbu Mititelu
Venue: Proceedings of the 11th international conference on Text, Speech and Dialogue (2008)

We present below an experiment in which we identified in corpora hyponymy patterns for English and for Romanian in two different ways. Such an experiment is interesting both from a computational linguistic perspective and from a theoretical linguistic one. On the one hand, a set of hyponymy patterns is useful for the automatic creation or enrichment of an ontology, for tasks such as document indexing, information retrieval, question answering. On the other hand, these patterns can be used in papers concerned with this semantic relation (hyponymy) as they are more numerous and are evaluated as opposed to those "discovered" through observation of text or, rather, introspection. One can see how hyponymy is realized in text, according to the stylistic register to which this belongs, and also a comparison between such patterns in two different languages is made possible.
Progress Appraisal as a Challenging Element of Coordination in Human and Machine Joint Activity
Authors: Paul J. Feltovich, Jeffrey M. Bradshaw, William J. Clancey, Matthew Johnson, Larry Bunch
Venue: Engineering Societies in the Agents World VIII: 8th International Workshop, ESAW 2007, Athens, Greece, October 22-24, 2007, Revised Selected Papers (2008)

Joint activity, as we define it, is a mutually interdependent social endeavor that requires sufficient predictability among participating parties to enable coordination. Coordination, in turn, sometimes requires the parties to appraise the state of progress of their activities so that, if necessary, they can adjust their actions to meet coordination needs and communicate their status to others as appropriate. A significant impediment as yet precluding the full participation of automation in joint activity with people is its inability to sense and communicate aspects of its state that would allow other participants to meaningfully assess progress toward (or anticipate failure with respect to) mutual objectives. In the current article, we address various issues associated with "progress appraisal" and the challenges it poses for human-machine systems. We point to promising directions for future work.
INES: network simulations on virtual environments
Authors: Ricardo Lent
Venue: Proceedings of the 1st international conference on Simulation tools and techniques for communications, networks and systems & workshops (2008)

The paper discusses the goals, design, models and implementation state of a new discrete-event simulator of computer networks. The Integrated Network-Environment Simulator (INES) aims at creating a suitable simulation tool for the evaluation of network algorithms and protocols operating on a virtual environment. This feature makes the simulator particularly useful for testing MANETs, VANETs, WSNs, situated communications, and other algorithms or technologies with realistic situations where the environment could significantly affect their operation. INES uses mesh geometries to model the objects of the desired environment, which may restrict node roaming and affect wireless communications during a simulation execution. Complementing INES development is the implementation of the Packet Animator, which can visualise INES traces through an OpenGL-based animation engine. Finally, the paper discusses examples that make use of the mobility and communication models currently supported by the simulator.
Letters: Recurrent neural network model for computing largest and smallest generalized eigenvalue
Authors: Lijun Liu, Hongmei Shao, Dong Nan
Venue: Neurocomputing (2008)

A continuous recurrent neural network model is presented for computing the largest and smallest generalized eigenvalue of a symmetric positive pair (A,B). Convergence properties to the extremum eigenvalues based upon Liapunov functional with the help of the generalized eigen-decomposition theorem is obtained. Compared with other existing models, this model is also suitable for computing the smallest generalized eigenvalue simply by replacing A by -A as well as maintaining invariant norm property. Numerical simulation further shows the effectiveness of the proposed model.
A Specification Language for Distributed Components Implemented in GCM/ProActive
Authors: Antonio Cansado, Denis Caromel, Ludovic Henrio, Eric Madelaine, Marcela Rivera, Emil Salageanu
Venue: The Common Component Modeling Example: Comparing Software Component Models (2007)

This chapter is based on a component model for distributed components called GCM for Grid Component Model. We present here this component model, its reference implementation based on the Java middleware ProActive, our specification language, JDC, adapted to distributed software components, and the associated specification platform: Vercors. From the specification of components and their behaviour, our aim is to both verify properties of this behaviour and generate code for real GCM components.
A framework for multi-region delay tolerant networking
Authors: Mirco Musolesi, Cecilia Mascolo
Venue: Proceedings of the 2008 ACM workshop on Wireless networks and systems for developing regions (2008)

Almost all the existing work on routing in delay tolerant networks has focussed on the problem of delivery of messages inside a single region, characterized by the same network infrastructure and namespace. However, many deployment scenarios, especially in developing regions, will probably involve routing among different regions composed of several heterogeneous types of network domains such as WiMAX or satellite networks and ad hoc networks composed of short-range radio enabled devices, like mobile phones with Bluetooth interface. In this paper, we introduce a proposal for inter-region routing based on both probabilistic and deterministic forwarding mechanisms, embedded in an architectural framework able to support it. We also compare our solution to existing approaches in delay tolerant networking, discussing the main requirements and possible solutions, and outlining the open research problems.
3-D Baseline Error Estimation for Distributed Small Satellites Based on Image Registration
Authors: Qing Xu, Gui-sheng Liao, Ying Liu
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 5 - Volume 05 (2008)

In distributed small satellites, the existence of the baseline error will affect the realization of the three functions: synthetic aperture radar imaging, ground moving target indication and altitude measure. A new 3-D baseline error estimation method for distributed small satellites is proposed in this paper. This method separates the along-track baseline and the cross-track baselines through image registration and estimates the two kinds of baseline error respectively. The effect that the correlative factors have on the estimation precision is also analyzed. Finally, its validity is testified through computer simulations.
Architectural Prototyping in Industrial Practice
Authors: Henrik Bærbak Christensen, Klaus Marius Hansen
Venue: Proceedings of the 2nd European conference on Software Architecture (2008)

Architectural prototyping is the process of using executable code to investigate stakeholders' software architecture concerns with respect to a system under development. Previous work has established this as a useful and cost-effective way of exploration and learning of the design space of a system, in addressing issues regarding quality attributes, in addressing architectural risks, and in addressing the problem of knowledge transfer and conformance. Little work has been reported so far on the actual industrial use of architectural prototyping. In this paper, we report from an ethnographical study and focus group involving architects from four companies in which we have focused on architectural prototypes. Our findings conclude that architectural prototypes play an important role in resolving problems experimentally, but less so in exploring alternative solutions. Furthermore, architectural prototypes include end-user or business related functionality rather than purely architectural functionality. Based on these observations we provide recommendations for effective industrial architectural prototyping.
Design issues in client-server software maintenance
Authors: Deepti Mishra, Alok Mishra
Venue: ACM SIGSOFT Software Engineering Notes (2008)

Software requires maintenance because there are often some errors remaining in the system that must be removed as they are discovered. Even without errors, software frequently undergoes change. The main reason is that software must be enhanced to include more features. Client-server software maintenance is not as simple as centralized software maintenance because client-server software systems are more complex than software for centralized systems. Cost associated with software maintenance is top most cost in software development, so there is a need to develop software which has maintainability i.e. the ease with which a system can be maintained. Therefore, the design and development of client-server software systems should be done keeping in mind the maintainability of the resultant software systems. There are various design issues related with the maintainability of the software. If we take care of these issues at the time of design, then the resultant system will have better maintainability and thus maintenance efforts of such system will be reduced.
Intersection of Parametric Surfaces and a Plane
Authors: Randy Lee, David Fredricks
Venue: IEEE Computer Graphics and Applications (1984)

This algorithm exploits basic differential geometry analysis to achieve high speed,low memory usage,reliability, and independence from surface type.
Looking Back at a New Hash Function
Authors: Olivier Billet, Matthew J. Robshaw, Yannick Seurin, Yiqun Lisa Yin
Venue: Proceedings of the 13th Australasian conference on Information Security and Privacy (2008)

We present two (related) dedicated hash functions that deliberately borrow heavily from the block ciphers that appeared in the final stages of the AES process. We explore the computational trade-off between the key schedule and encryption in a block cipher-based hash function and we illustrate our approach with a 256-bit hash function that has a hashing rate equivalent to the encryption rate of AES-128. The design extends naturally to a 512-bit hash function.
Probability Based Metrics for Locally Weighted Naive Bayes
Authors: Bin Wang, Harry Zhang
Venue: Proceedings of the 20th conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence (2007)

Locally weighted naive Bayes (LWNB) is a successful instance-based classifier, which first finds the neighbors of the test instance using Euclidean metric, and then builds a naive Bayes model in the local neighborhood. However, Euclidean metric is not the best choice for LWNB. For nominal attributes, Euclidean metric has to order and number the values of attributes, or judge whether the attribute values are identical or not. For numeric attributes, Euclidean metric is not appropriate for different attribute scales and variability, and encounters the problem of attribute value outliers when normalizing values. In this paper, we systematically study probability based metrics, such as Interpolated Value Difference Metric (IVDM), Extended Short and Fukunaga Metric (SF2), SF2 calibrated by logarithm (SF2LOG) and Minimum Risk Metric (MRM), and apply them to LWNB. These probability based metrics can solve the above problems of Euclidean metric since they depend on the difference between the probabilities to evaluate the distances between the instances. We conduct the experiments to compare the performances of LWNB classifiers using Euclidean metric and probability based metrics on UCI datasets. The results show that LWNB classifiers using IVDM outperform the ones using Euclidean metric and other probability based metrics. We also observe that SF2, SF2LOG and MRM do not perform well due to their inaccurate probability estimates. An artificial dataset is built by logical sampling in a Bayesian network, where accurate probability estimates can be produced. We conduct the experiment on the artificial dataset. The results show that SF2, SF2LOG and MRM using accurate probability estimates perform better than Euclidean metric and IVDM in LWNB.
Using Real-Valued Meta Classifiers to Integrate and Contextualize Binding Site Predictions
Authors: Mark Robinson, Offer Sharabi, Yi Sun, Rod Adams, Rene Boekhorst, Alistair G. Rust, Neil Davey
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part I (2007)

Currently the best algorithms for transcription factor binding site predictions are severely limited in accuracy. However, a non-linear combination of these algorithms could improve the quality of predictions. A support-vector machine was applied to combine the predictions of 12 key real valued algorithms. The data was divided into a training set and a test set, of which two were constructed: filtered and unfiltered. In addition, a different "window" of consecutive results was used in the input vector in order to contextualize the neighbouring results. Finally, classification results were improved with the aid of under and over sampling techniques. Our major finding is that we can reduce the False-Positive rate significantly. We also found that the bigger the window, the higher the F-score, but the more likely it is to make a false positive prediction, with the best trade-off being a window size of about 7.
Topic Extraction with AGAPE
Authors: Julien Velcin, Jean-Gabriel Ganascia
Venue: Proceedings of the 3rd international conference on Advanced Data Mining and Applications (2007)

This paper uses an optimization approach to address the problem of conceptual clustering. The aim of AGAPE, which is based on the tabu-search meta-heuristic using split, merge and a special "k-means" move, is to extract concepts by optimizing a global quality function. It is deterministic and uses no a priori knowledge about the number of clusters. Experiments carried out in topic extraction show very promising results on both artificial and real datasets.
A Rotated Image Matching Method Based on CISD
Authors: Bojiao Sun, Donghua Zhou
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

In the image registration process, there always exists rotation transformation. The ordinary methods such as NCC (Normalized Cross Correlation Algorithm), SD (Square Difference Algorithm), SSDA (Sequential Similarity Detection Algorithm), are not suitable for rotated image registration. In this paper, a method based on circular template, intensity distribution and SD is proposed for rotation image registration. Through the CPs (Control Points) got by the proposed method, transformation model and least square method, the rotation parameters are obtained. Experimental results verify its effectiveness. Compared with the existing feature-based approaches, it is easier to obtain CPs and needs no salient objects.
Trust Management for Host-Based Collaborative Intrusion Detection
Authors: Carol J. Fung, Olga Baysal, Jie Zhang, Issam Aib, Raouf Boutaba
Venue: Proceedings of the 19th IFIP/IEEE international workshop on Distributed Systems: Operations and Management: Managing Large-Scale Service Deployment (2008)

The accuracy of detecting an intrusion within a network of intrusion detection systems (IDSes) depends on the efficiency of collaboration between member IDSes. The security itself within this network is an additional concern that needs to be addressed. In this paper, we present a trust-based framework for secure and effective collaboration within an intrusion detection network (IDN). In particular, we define a trust model that allows each IDS to evaluate the trustworthiness of others based on personal experience. We prove the correctness of our approach in protecting the IDN. Additionally, experimental results demonstrate that our system yields a significant improvement in detecting intrusions. The trust model further improves the robustness of the collaborative system against malicious attacks.
Pre-determinants of Implementing IT Benefits Management in Norwegian Municipalities: Cultivate the Context
Authors: Tero Päivärinta, Willy Dertz
Venue: Proceedings of the 7th international conference on Electronic Government (2008)

The concept of benefits management addresses explicated practices to realize benefits from information technology investments. However, a minority of organizations have implemented those. We explored which pre-determinants affect the implementation of benefits management practices by conducting a Delphi process in the Norwegian municipality sector. The experts represented governmental organs, general management, and municipal service managers. They identified 59 pre-determinants of potential importance. However, the experts reached no significant consensus on the relative importance of the pre-determinants. Instead, we suggest that the identified pre-determinants should be holistically and contextually scrutinized. As a basis for that, we categorized the pre-determinants further into the areas of government-level policy, municipality-level policy, benefits management process, and benefits management toolbox of methods and techniques. Our study highlights areas of explicated managerial policies and actions in the municipal and inter-municipal contexts, in addition to the task of finding out a set of useful practices as such.