Graphical Analysis of Social Group Dynamics

Identifying communities in social networks becomes an increasingly important research problem. Several methods for identifying such groups have been developed, however, qualitative analysis (taking into account the scale of the problem) still poses serious problems. This paper describes a tool for facilitating such an analysis, allowing to visualize the dynamics and supporting localization of different events (such as creation or merging of groups). In the final part of the paper, the experimental results performed using the benchmark data (Enron emails) provide an insight into usefulness of the proposed tool.Comment: Fourth International Conference on Computational Aspects of Social Networks, CASoN 2012, Sao Carlos, Brazil, November 21-23, 2012, pp. 41-46; IEEE Computer Society, 201

Hybrid Neuro-Fuzzy Classifier Based On Nefclass Model

The paper presents hybrid neuro-fuzzy classifier, based on NEFCLASS model, which wasmodified. The presented classifier was compared to popular classifiers – neural networks andk-nearest neighbours. Efficiency of modifications in classifier was compared with methodsused in original model NEFCLASS (learning methods). Accuracy of classifier was testedusing 3 datasets from UCI Machine Learning Repository: iris, wine and breast cancer wisconsin.Moreover, influence of ensemble classification methods on classification accuracy waspresented

Tuning of agent-based computing

In this paper an Evolutionary Multi-agent system based computing processis subjected to detailed analysis of the parameters in order to ground a basefor better understanding this meta-heuristics from the practitioner's point of view.After reviewing the concepts of EMAS and its immunological variant, a series of experiments is shown and theresults of influencing of search outcomes by certain parameters are discussed

Adaptation of PyFlag to Efficient Analysis of Seized Computer Data Storage

Based on existing software aimed at investigation support in the analysis of computer data storage seized during investigation (PyFlag), an extension is proposed involving the introduction of dedicated components for data identification and filtering. Hash codes for popular software contained in NIST/NSRL database are considered in order to avoid unwanted files while searching and to classify them into several categories. The extension allows for further analysis, e.g. using artificial intelligence methods. The considerations are illustrated by the overview of the system\u27s design

GPGPU for Difficult Black-box Problems

AbstractDifficult black-box problems arise in many scientific and industrial areas. In this paper, efficient use of a hardware accelerator to implement dedicated solvers for such problems is discussed and studied based on an example of Golomb Ruler problem. The actual solution of the problem is shown based on evolutionary and memetic algorithms accelerated on GPGPU. The presented results prove that GPGPU outperforms CPU in some memetic algorithms which can be used as a part of hybrid algorithm of finding near optimal solutions of Golomb Ruler problem. The presented research is a part of building heterogenous parallel algorithm for difficult black-box Golomb Ruler problem

Classic and Agent-Based Evolutionary Heuristics for Shape Optimization of Rotating Discs

The article presents a metaheuristic solution for the problem of shape optimization of a rotating annular disc. Such discs are important structural components of e.g. jet engines, steam turbines or disc brakes. The design goal is to find the disc shape that would ensure its maximal carrying capacity (corresponding to the speed of rotation), which is a variational problem with the objective functional defined by L-infinity norm. Such a definition makes the problem impossible to solve using analytical methods so utilization of metaheuristics is necessary. We present different algorithms to solve the problem starting with a classic evolutionary one, followed by agent-based and hybrid agent-based memetic algorithms, which are the main focus of this paper. The reason for this is that agent-based computing systems proved to be versatile as an optimization technique being especially efficient for the problems with complex fitness functions. The obtained experimental results encourage further application of such an approach to similar engineering problems

A Crisis Management Approach To Mission Survivability In Computational Multi-Agent Systems

In this paper we present a biologically-inspired approach for mission survivability (consideredas the capability of fulfilling a task such as computation) that allows the system to be aware ofthe possible threats or crises that may arise. This approach uses the notion of resources usedby living organisms to control their populations.We present the concept of energetic selectionin agent-based evolutionary systems as well as the means to manipulate the configuration ofthe computation according to the crises or user’s specific demands

A CRISIS MANAGEMENT APPROACH TO MISSION SURVIVABILITY IN COMPUTATIONAL MULTI-AGENT SYSTEMS

In this paper we present a biologically-inspired approach for mission survivability (consideredas the capability of fulfilling a task such as computation) that allows the system to be aware ofthe possible threats or crises that may arise. This approach uses the notion of resources usedby living organisms to control their populations.We present the concept of energetic selectionin agent-based evolutionary systems as well as the means to manipulate the configuration ofthe computation according to the crises or user’s specific demands

Analysis of Distributed Systems Dynamics with Erlang Performance Lab

Modern, highly concurrent and large-scale systems require new methods for design, testing and monitoring. Their dynamics and scale require real-time tools, providing a holistic view of the whole system and the ability of showing a more detailed view when needed. Such tools can help identifying the causes of unwanted states, which is hardly possible with static analysis or metrics-based approach. In this paper a new tool for analysis of distributed systems in Erlang is presented. It provides real-time monitoring of system dynamics on different levels of abstraction. The tool has been used for analyzing a large-scale urban traffic simulation system running on a cluster of 20 computing nodes