BUSINESS INTELLIGENT AGENTS FOR ENTERPRISE APPLICATION

Fierce competition in a market increasingly crowded and frequent changes in consumer requirements are the main forces that will cause companies to change their current organization and management. One solution is to move to open architectures and virtual type, which requires addressing business methods and technologies using distributed multi-agent systems. Intelligent agents are one of the most important areas of artificial intelligence that deals with the development of hardware and software systems able to reason, learn to recognize natural language, speak, make decisions, to recognize objects in the working environment etc. Thus in this paper, we presented some aspects of smart business, intelligent agents, intelligent systems, intelligent systems models, and I especially emphasized their role in managing business processes, which have become highly complex systems that are in a permanent change to meet the requirements of timely decision making. The purpose of this paper is to prove that there is no business without using the integration Business Process Management, Web Services and intelligent agents.business intelligence, intelligent agents, intelligent systems, management, enterprise, web services

EDI and intelligent agents integration to manage food chains

Electronic Data Interchange (EDI) is a type of inter-organizational information system, which permits the automatic and structured communication of data between organizations. Although EDI is used for internal communication, its main application is in facilitating closer collaboration between organizational entities, e.g. suppliers, credit institutions, and transportation carriers. This study illustrates how agent technology can be used to solve real food supply chain inefficiencies and optimise the logistics network. For instance, we explain how agribusiness companies can use agent technology in association with EDI to collect data from retailers, group them into meaningful categories, and then perform different functions. As a result, the distribution chain can be managed more efficiently. Intelligent agents also make available timely data to inventory management resulting in reducing stocks and tied capital. Intelligent agents are adoptive to changes so they are valuable in a dynamic environment where new products or partners have entered into the supply chain. This flexibility gives agent technology a relative advantage which, for pioneer companies, can be a competitive advantage. The study concludes with recommendations and directions for further research

Experimental and simulation analysis for performance enhancement of elliptical savonius wind turbine by modifying blade shapes

Savonius turbines are drag-based rotors which operate due to a pressure difference between the advancing and retreating blades. After going through an exhaustive literature review, it was realized that the Savonius wind turbines are an applicable option at low wind speed areas, where the counterpart of these turbines cannot work efficiently. Nevertheless, the existing design is still under research to make it more applicable in urban areas. Therefore, the research objective was to develop and test an elliptical Savonius wind turbine to improving its performance in terms of power and torque coefficients by modifying blade shapes and overlap ratio. In the beginning, a series of 2D unsteady simulations (CFD-Fluent version 19.1) of the Savonius elliptical turbine has been performed to study the overlap ratio of blades and the effect of the turbulence models. Conventional elliptical Savonius turbine was modified by changing the overlap ratio from the value (OR=0.15) to (OR=0.2) and called as the Model-A. Then, the concave surface of the blade Model-A was modified (as zigzag shape) and called as Model-B. The blade shape of the Model-B was modified by adding bypass channels for each blade to creating new configuration was called the Model-C. The experimental work begins with the manufacturing of the models (A, B and C) of the blade using 3D printing technology. Models were tested by the wind tunnel in Aerodynamic laboratory (UTHM) with four cases of wind velocity. 2D simulation result for Model-A at OR= 0.2, where the increase in maximum power coefficient value obtained was 3.85% and 7.69% compared to overlap ratio (0.15 and 0.1), respectively. The result of the experimental test was obtained the maximum power coefficient (0.296, 0.292, 0.291, and 0.295) at wind velocity (6 m/s, 8 m/s, 9 m/s, and 10 m/s), respectively for Model-B. The Model-C result in the maximum power coefficient (0.28) compared with Model-A (0.26). The 3D unsteady simulation also has been done to visualisation the behaviour of flow around Model-B and it show a good agreement with experimental test results

Investigation into Mobile Learning Framework in Cloud Computing Platform

Abstract—Cloud computing infrastructure is increasingly used for distributed applications. Mobile learning applications deployed in the cloud are a new research direction. The applications require specific development approaches for effective and reliable communication. This paper proposes an interdisciplinary approach for design and development of mobile applications in the cloud. The approach includes front service toolkit and backend service toolkit. The front service toolkit packages data and sends it to a backend deployed in a cloud computing platform. The backend service toolkit manages rules and workflow, and then transmits required results to the front service toolkit. To further show feasibility of the approach, the paper introduces a case study and shows its performance

PlanetOnto: from news publishing to integrated knowledge management support

Given a scenario in which members of an academic community collaboratively construct and share an archive of news items, several knowledge management challenges arise. The authors' integrated suite of tools, called PlanetOnto, supports a speedy but high quality publishing process, allows ontology-driven document formalization and augments standard browsing and search facilities with deductive knowledge retrieva

An Intelligent Knowledge Management System from a Semantic Perspective

Knowledge Management Systems (KMS) are important tools by which organizations can better use information and, more importantly, manage knowledge. Unlike other strategies, knowledge management (KM) is difficult to define because it encompasses a range of concepts, management tasks, technologies, and organizational practices, all of which come under the umbrella of the information management. Semantic approaches allow easier and more efficient training, maintenance, and support knowledge. Current ICT markets are dominated by relational databases and document-centric information technologies, procedural algorithmic programming paradigms, and stack architecture. A key driver of global economic expansion in the coming decade is the build-out of broadband telecommunications and the deployment of intelligent services bundling. This paper introduces the main characteristics of an Intelligent Knowledge Management System as a multiagent system used in a Learning Control Problem (IKMSLCP), from a semantic perspective. We describe an intelligent KM framework, allowing the observer (a human agent) to learn from experience. This framework makes the system dynamic (flexible and adaptable) so it evolves, guaranteeing high levels of stability when performing his domain problem P. To capture by the agent who learn the control knowledge for solving a task-allocation problem, the control expert system uses at any time, an internal fuzzy knowledge model of the (business) process based on the last knowledge model.knowledge management, fuzzy control, semantic technologies, computational intelligence