Search results for "computer.software_genre"

Semantic Agent Programming Language (S-APL): A Middleware Platform for the Semantic Web

2008

The agent-based approach is an effective one for building middleware interconnecting distributed heterogeneous resources and providing semantic interoperability among them. On the other hand, agents need the semantic Web technologies for flexible yet effective coordination among them with a particular issue of enabling agents to communicate not only about the domain but also about their own abilities, goals, and present and intended actions. This paper describes semantic agent programming language (SAPL)intended to be a core middleware language for the semantic Web. S-APL integrates the semantic description of the domain resources with the semantic prescription of the agents' behaviors. Add…

Context-Awareness in Ensemble Recommender System Framework

2021

Recommender systems that provide recommendations based uniquely on information over users and items may not be very accurate in some situations. Therefore, adding contextual information to recommendations may be a good choice resulting in a system with increased precision. In an early work, we proposed an Ensemble Variational Autoencoders (EnsVAE) framework for recommendation. EnsVAE is adjusted to output interest probabilities by learning the distribution of each item's ratings and attempts to provide diverse novel items that are pertinent to users. In this paper, we propose and investigate a context awareness framework based on the Ensemblist Variational Autoencoders model with integratin…

Virtual Environment for Implementation and Testing Private Wide Area Network Solutions

2013

In this paper the concept of virtual environment for implementation and testing private Wide Area Network (WAN) solutions is presented. The VMware vSphere virtualization platform is used. The paper presents the ability to reflect the structure of any given WAN topology using Vyatta software routers and VMware virtualization platform and verifies its reliability regarding data transfer. The paper includes a number of performance tests to verify the dependability of the proposed solution and provide a proof-of-concept for the network topology during the Design phase of the PPDIOO methodology, right before the Implementation phase.

MEDiSN

2008

Staff shortages and an increasingly aging population are straining the ability of emergency departments to provide high-quality care. Moreover, there is a growing concern about the ability of hospitals to provide effective care during disaster events. Tools that automate patient monitoring would greatly improve efficiency, quality of care, and the volume of patients treated. Towards this goal, we have developed MEDiSN, a wireless sensor network for monitoring patients' vital signs in hospitals and disaster events. MEDiSN consists of Patient Monitors which are custom-built, patient-worn motes that sample, compress and secure medical data, and Relay Points that form a static multi-hop wireles…

Chapter 11. Computational representation of FrameNet for multilingual natural language generation

2021

Mining Interpretable Rules for Sentiment and Semantic Relation Analysis Using Tsetlin Machines

2020

Tsetlin Machines (TMs) are an interpretable pattern recognition approach that captures patterns with high discriminative power from data. Patterns are represented as conjunctive clauses in propositional logic, produced using bandit-learning in the form of Tsetlin Automata. In this work, we propose a TM-based approach to two common Natural Language Processing (NLP) tasks, viz. Sentiment Analysis and Semantic Relation Categorization. By performing frequent itemset mining on the patterns produced, we show that they follow existing expert-verified rule-sets or lexicons. Further, our comparison with other widely used machine learning techniques indicates that the TM approach helps maintain inter…

Clustering categorical data: A stability analysis framework

2011

Clustering to identify inherent structure is an important first step in data exploration. The k-means algorithm is a popular choice, but K-means is not generally appropriate for categorical data. A specific extension of k-means for categorical data is the k-modes algorithm. Both of these partition clustering methods are sensitive to the initialization of prototypes, which creates the difficulty of selecting the best solution for a given problem. In addition, selecting the number of clusters can be an issue. Further, the k-modes method is especially prone to instability when presented with ‘noisy’ data, since the calculation of the mode lacks the smoothing effect inherent in the calculation …

PerPot – a meta-model and software tool for analysis and optimisation of load-performance-interaction

2004

The Performance Potential meta-model PerPot simulates the interaction between load and performance in adaptive physiological processes like training in sport by means of antagonistic dynamics.The t...

A Sub-Symbolic Approach to Word Modelling for Domain Specific Speech Recognition

2006

In this work a sub-symbolic technique for automatic, data driven language models construction is presented. Such a technique can be used to arrange a language-modelling module, which can be easily integrated in existing speech recognition architectures, such as the well-found HTK architecture. The proposed technique takes advantages from both the traditional LSA approach and from a novel application of a probability space metric known as "Hellinger's distance". Experimental trials are also presented, in order to validate the proposed approach.

Structural Classification of Complex Molecules by Artificial Intelligence Techniques

2011

Algorithms for classification and taxonomy bases on criteria, e.g., information entropy. The feasibility of replacing a given molecule by similar ones in the composition of a complex drug is studied. Some local anaesthetics currently in use are classified using structural properties. In taxonomy the detailed comparison of the sequences of biomolecules, proteins or nucleic acids, allows the reconstruction of a molecular phylogenetic tree. The method is applied to the classifications of (1) indazolols (against Trichomonas vaginalis), (2) fullerenes and fullerite, (3) living and heat-inactivated lactic acid bacteria against cytokines, (4) phylogenesis of avian birds and 1918 influenza virus, (…