9 results on '"Goran Trajkovski"'
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2. On IETAL, Algebraically
- Author
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Goran Trajkovski
- Subjects
Computer science ,Programming language ,computer.software_genre ,computer - Abstract
In this chapter, we formalize the Interactivist-Expectative Theory of Agency and Learning (IETAL) agent in an algebraic framework and focus on issues of learnability based on context.
- Published
- 2011
3. On a Software Platform for MASIVE Simulations
- Author
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Goran Trajkovski
- Subjects
Software ,Java ,business.industry ,Computer science ,Operating system ,Architecture ,computer.software_genre ,business ,computer ,computer.programming_language - Abstract
Pattern-Aided Simulated Interaction Context Learning Experiment (POPSICLE) Agent Simulator began as a sample project in object-oriented agent programming, but quickly grew into a complete framework for the simulation of agent behavior based upon an associative memory model. The system began its implementation as a Java 2 (J2SE 1.4) application, but was later migrated to a Java 5 application (J2SE 1.5) to utilize the type-safe collections and enumerated types that became available in the latest Java version. Various design patterns were employed in the development; the most predominate being the Model/Controller/View (MCV) architecture. As we will see later, the system also relies heavily on delegation and observers.
- Published
- 2007
4. Implementing artificial neural-networks in wireless sensor networks
- Author
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Goran Trajkovski, Danco Davcev, and Andrea Kulakov
- Subjects
Key distribution in wireless sensor networks ,Artificial neural network ,Computer science ,Robustness (computer science) ,Dimensionality reduction ,Unsupervised learning ,Data mining ,Sensor fusion ,computer.software_genre ,Cluster analysis ,Wireless sensor network ,computer - Abstract
The development of wireless sensor networks is accompanied by several algorithms for data processing which are modified regression techniques from the field of multidimensional data series analysis in other scientific fields, with examples like nearest neighbor search, principal component analysis and multidimensional scaling (Guestrin, C. et al., Proc. IPSN'04, 2004). We argue that some algorithms, well developed within the neural-networks tradition for over 40 years, are well suited to fit into the requirements imposed by sensor networks: simple parallel distributed computation; distributed storage; data robustness; auto-classification of sensor readings. As a result of the dimensionality reduction obtained easily from the outputs of neural-network clustering algorithms, lower communication costs, and thus bigger energy savings, can be obtained. We present two possible applications of the ART and FuzzyART algorithms, which are unsupervised learning methods for clustering or categorization of the sensory inputs, applied on data obtained from a set of 5 Smart-It units (sensor nodes or motes) equipped with 6 sensors each. Results from simulations of purposefully faulty sensors show that these architectures are data robust to errors
- Published
- 2006
5. Effects of Computer Competency on Usability and Learning Experience in Online Learning Environments
- Author
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Goran Trajkovski and G. Meiselwitz
- Subjects
Multimedia ,Online participation ,business.industry ,Computer science ,Learning environment ,Educational technology ,Usability ,computer.software_genre ,Experiential learning ,Learning sciences ,Synchronous learning ,Active learning ,ComputingMilieux_COMPUTERSANDEDUCATION ,Mathematics education ,business ,computer - Abstract
Many institutions in higher education are offering at least some of their curriculum online and use online course management systems to support these learning environments. Successful participation in online learning depends on many factors, and may especially be influenced by the degree of computer competency users bring with them to the learning environment. The purpose of this study is to evaluate the effects of several areas of computer competency on student learning experiences and learning environment usability in online learning environments. Subject of evaluation was a multi-section course consisting of eight sections taught in hybrid format; approximately 50% of course work was conducted using the World Wide Web. Results of the study have direct implications in online course design and development.
- Published
- 2006
6. Attack of the Rainbow Bots
- Author
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Goran Trajkovski and Samuel Gerald Collins
- Subjects
Engineering ,business.industry ,media_common.quotation_subject ,Multi-agent system ,Information system ,Rainbow ,Computer security ,computer.software_genre ,business ,computer ,Information technology education ,Diversity (politics) ,media_common - Abstract
Many in IT education—following on more than twenty years of multicultural critique and theory—have integrated “diversity” into their curricula. But while this is certainly laudable, there is an irony to the course “multiculturalism” has taken in the sciences in general. By submitting to a canon originating in the humanities and social sciences—no matter how progressive or well-intentioned—much of the transgressive and revolutionary character of multicultural pedagogies is lost in translation, and the insights of radical theorists become, simply, one more module to graft onto existing curricula or, at the very least, another source of authority joining or supplanting existing canons. In this essay, we feel that introducing diversity into IT means generating this body of creative critique from within IT itself, in the same way multiculturalism originated in the critical, transgressive spaces between literature, cultural studies, anthropology and pedagogy. The following traces our efforts to develop isomorphic critiques from recent insights into multi-agent systems using a JAVA-based, software agent we’ve developed called “Izbushka.”
- Published
- 2006
7. A Fuzzy Framework for Modelling Multiagent Societies
- Author
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G. Vincenti and Goran Trajkovski
- Subjects
Hierarchy (mathematics) ,business.industry ,Computer science ,Multi-agent system ,media_common.quotation_subject ,Fuzzy set ,Autonomous agent ,computer.software_genre ,Agent-based social simulation ,Intelligent agent ,Concept learning ,Artificial intelligence ,business ,Imitation ,computer ,media_common - Abstract
In the past several years, the work within the framework of the interactivist-expectative theory on agency and learning (IETAL), we have concentrated on exploring the concept of learning environment partitions in an autonomous agent, and the problems encountered during its stay in the environment. The key concepts in the uniagent version of the theory are the concepts of expectancy and learning through interactions with the environment, while building an intrinsic model of it. Depending on the set of active drives and their hierarchy (not necessarily ordered with a partial ordering, but rather a general relational structure), the agent uses its intrinsic model to navigate its quest to satisfy the active drive(s). In this paper, we start with the existing results of the theory and generalize it to a theory of multiple agent systems, via introducing imitation-based interaction between homogenous agents. While sensing each other, the agents exchange their contingency tables, built during the interaction with the environment. This approach is inspired by results from both neurophysiology and psychology on the phenomenon of imitation. The formalization of the agent, as well as of the environment is necessary for setting up a successful experimental and simulation environment for exploring the new paradigms. Our approach relies on new modeling strategies and structures from the domain of lattice (L-fuzzy), posets (P-fuzzy) and general relational-structure-valued (R-fuzzy) algebraic structures.
- Published
- 2005
8. Scouting for Imprecise Temporal Associations to Support Effectiveness of Drugs During Clinical Trials
- Author
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Goran Trajkovski, Robert J. Hammell, and Giovanni Vincenti
- Subjects
Apriori algorithm ,Computer science ,business.industry ,Market basket ,Fuzzy set ,Affinity analysis ,computer.software_genre ,Machine learning ,Health informatics ,Field (computer science) ,Data analysis ,Data mining ,Artificial intelligence ,business ,Cluster analysis ,computer - Abstract
The field of data mining is dedicated to the analysis of data to find underlying connections and the discovery of new patterns. This research targets the analysis of imprecise temporal associations through the modification of a standard market basket analysis approach by means of fuzzy set relations to classify the associations among different sources of data. The domain that is taken into consideration in this work is the one of medicine. We used data recorded within an Intensive Care Unit from a 8 month old infant that suffers from Acute Respiratory Distress Syndrome. In particular, we analyzed the response of the partial pressure of oxygen within the bloodstream to the application of a respirator. The results of this research show that it is possible to investigate such relations with the help of fuzzy set classification for temporal associations, and the result of such exploration is as easily understandable as the standard Market Basket algorithm. The findings support the physiological response, suggesting that this approach is worthy of notice. We are confident that such an algorithm will show its capabilities when applied to the clinical trials part of drug testing, given the results outlined in this article.
- Published
- 2005
9. Data Mining for Imprecise Temporal Associations
- Author
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Goran Trajkovski, Giovanni Vincenti, and Robert J. Hammell
- Subjects
Artificial neural network ,business.industry ,Computer science ,Fuzzy set ,Information analysis ,computer.software_genre ,Network topology ,Machine learning ,Data mining algorithm ,Field (computer science) ,Data analysis ,Algorithm design ,Artificial intelligence ,Data mining ,business ,computer - Abstract
The field of data mining is dedicated to the analysis of data in order to find underlying connections and the discovery of new patterns. Since the volume of data to be analyzed is sometimes quite significant, there is the need for efficient data mining algorithms to be implemented. The market-basket algorithm can represent a breakthrough in data mining techniques. As the associations that are to be analyzed grow more and more abstract, the market-basket approach is unable to deal with imprecise temporal associations, leaving a big area uncharted. This research is dedicated to the analysis of temporal imprecise associations through the modification of a standard a-priori approach by means of fuzzy set relations to classify the associations relating different sources of data. The results of this research show that it is possible to investigate such relations with the help of fuzzy set classification for temporal associations, and the result of such exploration is as easily understandable as the standard a-priori algorithm.
- Published
- 2005
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