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Conference

International Conference on Information Technology 

About: International Conference on Information Technology is an academic conference. The conference publishes majorly in the area(s): The Internet & Information system. Over the lifetime, 5501 publications have been published by the conference receiving 22819 citations.


Papers
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Proceedings ArticleDOI
01 Nov 2014
TL;DR: The design of a sentiment analysis is reported on, extracting a vast amount of tweets, and results classify customers' perspective via tweets into positive and negative, which is represented in a pie chart and html page.
Abstract: Social media have received more attention nowadays. Public and private opinion about a wide variety of subjects are expressed and spread continually via numerous social media. Twitter is one of the social media that is gaining popularity. Twitter offers organizations a fast and effective way to analyze customers' perspectives toward the critical to success in the market place. Developing a program for sentiment analysis is an approach to be used to computationally measure customers' perceptions. This paper reports on the design of a sentiment analysis, extracting a vast amount of tweets. Prototyping is used in this development. Results classify customers' perspective via tweets into positive and negative, which is represented in a pie chart and html page. However, the program has planned to develop on a web application system, but due to limitation of Django which can be worked on a Linux server or LAMP, for further this approach need to be done.

362 citations

Proceedings Article
24 Sep 2008
TL;DR: This paper describes the new methodology to semi-automate BEP simulation preparation and execution, and identifies five steps that are critical to its implementation, and shows what part of the methodology can be applied today.
Abstract: Building energy performance (BEP) simulation is still rarely used in building design, commissioning and operations. The process is too costly and too labor intensive, and it takes too long to deliver results. Its quantitative results are not reproducible due to arbitrary decisions and assumptions made in simulation model definition, and can be trusted only under special circumstances. A methodology to semi-automate BEP simulation preparation and execution makes this process much more effective. It incorporates principles of information science and aims to eliminate inappropriate human intervention that results in subjective and arbitrary decisions. This is achieved by automating every part of the BEP modeling and simulation process that can be automated, by relying on data from original sources, and by making any necessary data transformation rule-based and automated. This paper describes the new methodology and its relationship to IFC-based BIM and software interoperability. It identifies five steps that are critical to its implementation, and shows what part of the methodology can be applied today. The paper concludes with a discussion of application to simulation with EnergyPlus, and describes data transformation rules embedded in the new Geometry Simplification Tool (GST).

171 citations

Proceedings ArticleDOI
02 Apr 2007
TL;DR: The simulation results show that the proposed intelligent hierarchical clustering technique is more energy efficient than a few existing cluster-based routing protocols.
Abstract: We use a genetic algorithm (GA) to create energy efficient clusters for routing in wireless sensor networks. The simulation results show that the proposed intelligent hierarchical clustering technique is more energy efficient than a few existing cluster-based routing protocols. Further, the gradual energy depletion in sensor nodes is also investigated

156 citations

Journal ArticleDOI
30 Apr 1999
TL;DR: This article tries to identify focal points of interest for researchers working in the area of distributed AI (DAI) and MAS as well as application-oriented researchers coming from related disciplines, e.g. electrical and mechanical engineering by presenting key research topics in DAI and MAS research and by identifying application domains in which the DAi and MAS technologies are most suitable.
Abstract: For sometime now agent-based and multi-agent systems (MASs) have attracted the interest of researchers far beyond traditional computer science and artificial intelligence (AI). In this article we try to identify focal points of interest for researchers working in the area of distributed AI (DAI) and MAS as well as application-oriented researchers coming from related disciplines, e.g. electrical and mechanical engineering. We do this by presenting key research topics in DAI and MAS research and by identifying application domains in which the DAI and MAS technologies are most suitable. The research topics we discuss are separated into agent architectures and organisations, negotiation among agents, and self-adaptation of MAS using learning techniques. Regarding the application domains for these techniques we distinguish the application domains according to whether the agents control a physical or virtual body (Gestalt) or not. This separation of the application domains is not strict; it represents two ends of a continuum. On the one end of this continuum we have autonomous robot systems which act in a physical environment (sometimes referred to as hardware agents), and on the other end, we have abstract environments, such as in workflow systems, which rarely display the geometrical and physical aspects of the environment we are used to living in.

149 citations

Proceedings Article
01 Jan 2004
TL;DR: In this paper, two machine learning paradigms, Artificial Neural Networks and Fuzzy Inference System, are used to design an Intrusion Detection System, which is used to perform real time traffic analysis and packet logging on IP network during the training phase of the system.
Abstract: The Intrusion Detection System architecture commonly used in commercial and research systems have a number of problems that limit their configurability, scalability or efficiency. In this paper, two machine-learning paradigms, Artificial Neural Networks and Fuzzy Inference System, are used to design an Intrusion Detection System. SNORT is used to perform real time traffic analysis and packet logging on IP network during the training phase of the system. Then a signature pattern database is constructed using protocol analysis and Neuro-Fuzzy learning method. Using 1998 DARPA Intrusion Detection Evaluation Data and TCP dump raw data, the experiments are deployed and discussed.

139 citations

Performance
Metrics
No. of papers from the Conference in previous years
YearPapers
202338
2022150
2021274
20201,100
2019619
2018432