2024-03-28T11:13:42Z
https://ijicis.journals.ekb.eg/?_action=export&rf=summon&issue=3408
International Journal of Intelligent Computing and Information Sciences
IJICIS
1687-109X
1687-109X
2014
14
2
A NEW METHODOLOGY FOR DETECTING WEB APPLICATIONS ERRORS AND BOTTLENECKS IN STRESS TESTING
A
Ibrahim
O
Nomair
A
fahmy
Stress testing is a type of performance testing designed to determine the performance of system and to predict system’s behavior under stressful loads. In this paper, we focus on this type of performance testing. We create a realistic performance test plan by identifying the key scenario for the application, the navigation paths for each scenario, the unique data for navigation paths, and user distribution along web applications scenario. In our proposed test, we determine the total number of users, application navigation paths, and then we distribute users along these navigation paths. We take in our account users think time, and data input and output. Once test begins, the users begin to send their requests to the web application the determined navigation paths; also it increases steeply as we planned in our proposed test plan. During that, the performance critical metrics like response time, throughputs, error rates and resource utilizations are automatically recorded then analyzed. Our experimental results show that our proposed algorithm is robust for detections of errors location, percentages and reasons. It also detects the bottlenecks if exit. The experimental results also show with comparison the advantages of user load distribution on reducing the error percentage, the response time and the resource utilization.
2014
04
01
1
13
International Journal of Intelligent Computing and Information Sciences
IJICIS
1687-109X
1687-109X
2014
14
2
A NOVEL IMAGE RETRIEVAL FRAMEWORK BASED ON KNOWLEDGE BASED SYSTEM
Ahmed
Amin
This paper present a novel image retrieval framework depend on a knowledge base system. The proposed framework composed of three techniques namely; feature extraction technique, image clustering technique and rule base technique respectively. The first one extracts the features from the images database using wavelet transform (WT). Therefoe, each image can be characterized by a few coefficients which are independent on the image resolution. The second technique clusters the images database according to four phases called; features' division, mixture of Gaussian model, relevance feedback and pruning model. Consequently, at the end of the clustering technique each image in the database has been belonged to a specific cluster (supervised learning). The third technique makes use a genetic algorithm (GA) as a tool for extracting a set of rules from these images and the corresponding classes. The fitness function of the genetic algorithm is evaluated according to the support and the confidence measures. Finally, the results presented in this paper demonstrate that the proposed model provides accurate retrieval results and achieve improvement in performance with significantly less computation time compared with other models.
2014
04
01
15
38
International Journal of Intelligent Computing and Information Sciences
IJICIS
1687-109X
1687-109X
2014
14
2
DEVELOPMENT OF AUTOMATED EXPERT SYSTEM FOR A NUTRITIONAL GUIDANCE APPLICATION BASED ON ROUGH SETS
M
Rokaya
Rough set theory methodology is concerned with the classification and analysis of imprecise, uncertain or incomplete information and knowledge, and is considered one of the first non-statistical approaches in data analysis. An expert system provides advice derived from its knowledge base, using a reasoning process embedded in its inference engine. Expert system seeks to embed the knowledge of a human expert in a computerized consulting service. Nutritional guidance importance increases as well as nutritional problems increase. In this paper an expert system that based on rough theory is presented and tested. In this paper, a rule induction method is introduced, which extracts not only classification rules but also other knowledge needed for guidance. This system is evaluated on a nutritional database. Results show that our proposed method correctly induces guidance rules and estimates the statistical measures of rules.
2014
04
01
39
52
International Journal of Intelligent Computing and Information Sciences
IJICIS
1687-109X
1687-109X
2014
14
2
ENHANCEMENTS IN SCUM FRAMEWORK USING EXTREME PROGRAMMING PRACTICES
N
Darwish
This paper is concerned with providing an enhanced Scrum framework that combines some practices of eXtreme Programming (XP) approach in Scrum framework to produce quality software on time. XP and Scrum are two agile software development methods. While Scrum is focused on project management, XP is focused on Software development; nevertheless, they both can be used to participate in the development of any software project independently or together. This paper presents the main concepts, features, phases, artifacts, and roles of Scrum as well as a brief introduction to XP and its practices. In this paper, the researcher presents how to combine some XP practices into Scrum activities. The researcher exploits the features and best practices of the two methods to propose an enhanced Scrum framework that includes an elaborated set of guidelines for achieving each Scrum activity. Therefore, the enhanced Scrum framework is more applicable than many previous attempts in this domain. The enhanced Scrum framework has been validated by a group of 17 experts and specialists in software projects.
2014
04
01
53
67
International Journal of Intelligent Computing and Information Sciences
IJICIS
1687-109X
1687-109X
2014
14
2
PARTICLE SWARM OPTIMIZATION TO IMPROVE A HYBRID HEURISTIC ALGORITHM FOR SOLVING CAPACITATED VEHICLE ROUTING PROBLEM
M
abdelaziz
H
El-Ghareeb
M
Ksasy
Capacitated Vehicle Routing Problem is the most elementary version of the vehicle routing problem, where it represents a generalization of vehicle routing problems. It is an important problem in the fields of transportation, distribution and logistics which involves finding a set of routes, starting and ending at a depot, that together cover a set of customers. The proposed methodology in this research was based on Cluster-First Route-Second method. There are two proposed hybrid algorithms used to implement that methodology, the Sweep-Nearest Neighbour algorithm and the Sweep-Particle Swarm Optimization algorithm. The Particle Swarm Optimization algorithm was used instead of Nearest Neighbour algorithm to enhance the performance in finding the shortest routes. The two hybrid proposed algorithms were applied in a real case study and the results were compared. From the experimental results, it observed that particle swarm optimization was added more enhancement for finding the best route with the minimum travelling costs.
2014
04
01
69
77