Mujahid Tabassum

A GENETIC ALGORITHM ANALYSIS TOWARDS OPTIMIZATION SOLUTIONS

In today’s world, an optimal and intelligent problem solving approaches are required in every field, regardless of simple or complex problems. Researches and developers are trying to make machines and softwares more efficient and intelligent. This is where the Artificial Intelligence plays its role in developing efficient and optimal searching algorithm solutions. Genetic algorithm is one of most pervasive and advanced developed heuristic search technique in AI. Genetic algorithm (GA) is developed to find the most optimized solution for a given problem based on inheritance, mutation, selection and some other techniques. It was proved that genetic algorithms are the most powerful unbiased optimization techniques for sampling a large solution space. In this paper, we have used GA for the image optimization and Knapsack Problems, which are commonly found in a real world scenario. Furthermore, a research based on a tool that uses Genetic Algorithm, called the GA Playground is done to demonstrate the capability of solving the Knapsack Problem with the fitness function and a case study on how images can be reproduced using the optimal parameters. Lastly, a few methods such as the Hash Table and the Taguchi Method are suggested to improve the performance of the Genetic Algorithm.

Distributed Energy Generation—Is It the Way of the Future?

This research topic consists of the advantages of distributed energy generation, the different methods used to generate the energy (e.g. photovoltaic panel and wind turbine), how to store the energy (e.g. battery) and how it will be achieved. Other topics that are discussed are cost factor and performance of each method. Furthermore, differences between the traditional transmission and distribution grid are compared. Lastly, the implementation of a smart grid is discussed to show that “green power” can provide a significant environmental benefit.

Growth Analysis of Eclipse and NetBeans using Gini Coefficient

Software are developed according to the consumer need. However, the requirements changed time to time due to the advancement of the era, which make software more complex over the time. Therefore, software needs to be maintained properly to reduce complexity and increase productivity. This required a comprehensive growth analysis to be performed on a timely basis to understand the changes occurred in the software over the long time. In this paper, we have performed a growth analysis of two existing software Netbeans and Eclipse applications. Both of these softwares are used for programming Integrated Development Environment (IDE) to develop applications. This paper highlights the different versions of both softwares, their features and functions, features evolution, change log audit, growth and change analysis in context of Gini coefficient and the Lorenz curve. Both softwares have been analysed based on evolution metrics, and results are derived using Count Lines of Code (CLOC) an open source application.

Wireless Body Area Networks channel decongestion algorithm

Advances in MicroElectroMechanical Systems (MEMS), nanotechnology, and sensing technology have fueled the manufacture of small devices called body sensors. When worn on, in, or around the body, these sensors form a Wireless Body Area Network (WBAN) which senses and forwards physiological conditions to medical personnel and caregivers for remedial action. The ability of Wireless Body Area Networks (WBANs) to offer pre-emptive and curative services to mankind cannot be overemphasized. An increase in density of subjects wearing WBANs per unit area causes congestion of the transmission medium which results in the loss of transmitted data. This paper proposes the Selective Transmission algorithm which decongests the transmission medium by filtering irrelevant packets, reducing data packet loss, as well as reducing energy consumption and increasing the lifespan of WBANs. A comparison of the proposed Selective Transmission algorithm with the extant Value Reporting application portrayed an 83.33% channel decongestion and 44.56% drop in energy consumption for the former.

A study of open ports as security vulnerabilities in common user computers

The unprecedented growth in information technology and information explosion, with more and more data in electronic forms has put the computer into the hands of users with very little technical knowledge. The fact that the systems are not inherently immune, and that open up a number of vulnerabilities, leading to potential attacks, and the most prominent is in the form of open ports. This paper attempts to do a survey on common user computing devices including start devices to discover open ports and thereby explore vulnerabilities that can lead to potential attack targets.

Experimental comparison of uninformed and heuristic AI algorithms for N puzzle and 8 queen puzzle solution

This paper compares the performance of popular AI techniques, namely the Breadth First Search, Depth First Search, A* Search, Greedy Best First Search and the Hill Climbing Search in approaching the solution of a N-Puzzle of size 8, on a 3x3 matrix board and for the solution of the classic 8 Queen Puzzle. It looks at the complexity of each algorithm as it tries to approaches the solution in order to evaluate the operation of each technique and identify the better functioning one in various cases. The N Puzzle and the 8 Queen is used as the test scenario. An application was created to implement each of the algorithms to extract results for each of the cases. The paper also depicts the extent each algorithm goes through while processing the solution and hence helps to clarify the specific cases in which a technique may be preferred over another.