Bassam Zafar

Semantic Image Retrieval: An Ontology Based Approach

Images / Videos are major source of content on the internet and the content is increasing rapidly due to the advancement in this area. Image analysis and retrieval is one of the active research field and researchers from the last decade have proposed many efficient approaches for the same. Semantic technologies like ontology offers promising approach to image retrieval as it tries to map the low level image features to high level ontology concepts. In this paper, we have proposed Semantic Image Retrieval: An Ontology based Approach which uses domain specific ontology for image retrieval relevant to the user query. The user can give concept / keyword as text input or can input the image itself. Semantic Image Retrieval is based on hybrid approach and uses shape, color and texture based approaches for classification purpose. Mammals domain is used as a test case and its ontology is developed. The proposed system is trained on Mammals dataset and tested on large number of test cases related to this domain. Experimental results show the efficiency / accuracy of the proposed system and support the implementation of the same.

Multi-Agent Modeling Toolkit – MAMT

Abstract Multi-agent system consists of two or more agents which cooperate/coordinate with each other in order to solve a complex problem which would be difficult or inappropriate if solved by single agent. Multi-agents are modeled using Agent Unified Modeling Language (AUML) as Unified Modeling Language (UML) notations do not fully express agent properties/behaviors. In this paper, we have proposed Multi-Agent Modeling Toolkit (MAMT) to help a designer in building rapid multi-agent based applications. The purpose of this toolkit is to create agent development environment where the developer can have various facilities like reusability of existing/developed agents, customize built-in agents, etc. MAMT provides the designer with built-in agents which are developed using Java Agent Development (JADE) framework, with the help of these designers can rapidly build multi-agent based applications. Creation and customization of built-in agents is based on the prototype inclusion design pattern and the designer can add or modify methods/behaviors according to their requirement(s); however the changes should be based on FIPA (Foundation of Intelligent Physical Agents) standards and compatible with JADE. MAMT has been evaluated on large number of sample applications; results were very promising and encourage the use of toolkit.

Communication delay guarantee for IEEE 802.11p/wave Vehicle networks with RSU control

The standard 802.11p/wave provides communication facilities to many vehicle applications. The safety application for vehicle collision avoidance is one of the most attractive issues for industrial and research concerns. However, medium access protocols proposed by standards and research works are not dedicated to this kind of real time applications. A deterministic medium access is needed to guarantee communication delay constraints. Thus, we propose an extension of the CSMA/CA medium access defined in the standard. It is an enhancement of the collision resolution procedure to be deterministic. An infrastructure with Road Side Units (RSUs) is used to manage the secured zone. It is also to complete and control communication for collision detection approach. This new protocol has the main advantage of low bandwidth utilization, low latency and deterministic communication. We have also proposed a worst case analysis model to predict communication delay in order to verify the real time constraints. Simulations are made to perform the efficiency of our protocol relative to other ones.

Enhanced EDCA with Deterministic Transmission Collision Resolution for Real-Time Communication in Vehicular Ad Hoc Networks

The collision prevention system is one of most important research issues on vehicle safety technology. Sending worming messages within the right time and reliable transmission will get prevention of a possible vehicle accident. The communication standards of vehicular networks (VANET) are unable to guarantee the delivery of critical messages within tight deadlines. Indeed, the transmission collisions are handled with probabilistic manner that can reduce the transmission latency; however, it is inept to predict an upper bound value of this delay to verify the deadline. In this paper, we propose a medium access protocol that ensures the delivery of critical messages within a deadline. It is a hard real-time system with delay constant guarantee. We are focusing on improving the EDCA medium access protocol to prioritize critical messages and to get access to the transmission channel within a predictable communication delay. We create a new enhanced access protocol that is compatible with the IEEE 802.11p VANET standards and adapted to real-time communication requirements related to the vehicle collision avoidance problem.

Dynamic response and efficiency improvement of hybrid autonomous power system

In this paper, a design of an autonomous hybrid power system combining a few components as solar energy, a backup system component based on proton membrane exchange fuel cell, namely Energy Recovery and two kinds of energy storage, one based on H2 gas production namely Energy Storage and the second specified by using an Ultracapacitor bank is described and modeled. The main goal of this work is to present and to improve the efficiency of such system using a smart energy management. This latter, based on multi-agents system modeling, used to ensure the smooth operation of such system dedicated to remote area application. The model is developed and tested by MATLAB/Simulink using mathematical and finite state models to follow the behavior of the proposed system. Hence, the simulation results clearly indicate and prove that the multi-agents control approach is a promising and effective method used for the control of the systems combining various energy sources.

An efficient control strategy for hybrid PEMFC/Supercapacitor power source applied for automotive application

This paper discusses an important research issue which is an attracting Hybrid Power System (HPS) using a Proton-Exchange-Membrane Fuel Cell (PEMFC) and a Supercapacitor (SC). This latter is considered as a short term storage device. The PEMFC is expected to become an excellent solution for several applications, even that its slow dynamic. So, the SC is proposed to minimize power fluctuations in the HPS and to generate a necessary power. In this paper, we propose also an Energy Management Unit (EMU) according to some constraints (e.g. Load demand, state of charge (SOC) of the SC, and energy balance of the system). The considered EMU offers several scenarios based on many power flow possibilities. Each operating mode scenario contains, in its turn, several scenarios to cover all the circumstances. A regulation for the PEMFC and the SC was given. Results and discussions are given based on MATLAB-Simulink using an electrical model which developed and treated for the proposed design.

A comparative analysis of multiple sequence alignments for biological data

Multiple sequence alignment plays a key role in the computational analysis of biological data. Different programs are developed to analyze the sequence similarity. This paper highlights the algorithmic techniques of the most popular multiple sequence alignment programs. These programs are then evaluated on the basis of execution time and scalability. The overall performance of these programs is assessed to highlight their strengths and weaknesses with reference to their algorithmic techniques. In terms of overall alignment quality, T-Coffee and Mafft attain the highest average scores, whereas K-align has the minimum computation time.

A multi-agent framework for efficient food distribution in disaster areas

Disasters have been causing huge damages to infrastructure as well as human life for a long time. The time immediately following a disaster needs to be managed efficiently to minimise the damage to the human population in that area. One of the key challenges faced when disaster hits an area is efficient distribution of resources such as medicine, food, water, etc. In this paper, we propose a solution particularly for distribution of food which can be extended for any other resource as well. We have proposed a solution in which a big disaster region is divided into smaller areas regions and multi-agent systems are used to deliver food in these regions. Agents use shortest path algorithms and coordination to deliver food within their particular region efficiently. In the experiment section, we have performed different experiments to verify how the proposed solution performs when one of the parameters is changed and how this system performs in different scenarios.