Thursday, April 2, 2020

CLASSIFICATION ALGORITHMS FOR THE DETECTION OF THE PRIMARY TUMOR BASED ON MICROSCOPIC IMAGES OF BONE METASTASES

Author :  Slađan Kantar

Affiliation :  Master student at “The Faculty of Computer Science"University of Belgrade

Country :  Serbia

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  7, 8, June, 2017

Abstract

This paper presents the analysis of techniques for microscopic images in order to find a primary tumor based on the of bone metastases. Was done algorithmic classification into three groups, kidney, lung and breast. In order to speed up the treatment of the patient and easier for doctors and therefore reduce room for human error. Digital microscope images of bone metastases were analyzed, for which it is known that the primary tumor is in one of the three human organs: kidney, lung or breast. We tested several solutions for classification, were tested two methods of image analysis. Multifractal analysis and convolutional neural network. Both methods were tested with and without preprocessing image. Results of multifractal analysis were then classified using different algorithms. Images were processed using CLAHE and kmeans algorithm. At the end, the results obtained using a variety of techniques are presented.

Keyword :  Cancer classification, Microscopic images, Image preprocessing, Multifractal analysis, Classification algorithms

For More Details :  https://airccj.org/CSCP/vol7/csit77004.pdf


SCALABLE AND EFFICIENT PATHSENSITIVE ANALYSIS TECHNIQUE SCANNING MANY TYPES OF VULNERABILITY

Author :  Dongok Kang and Minsik Jin

Affiliation :  PA Division, Fasoo.com R&D Center, Seoul

Country :  Korea

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  7, 8, June, 2017

Abstract

The goal of this paper is to present an efficient and effective path-sensitive analysis technique for many types of security vulnerability. We propose two analysis techniques. The first is a scalable path-sensitive analysis technique for security vulnerability with high precision and recall. Our strategies are to allow flexible design of path state and to make an effective path navigation heuristic which achieves both scalability and high recall. Experimental results show that a vulnerability scanner implemented through this technique get precision 100% and recall 93% on OWASP Benchmark. The vulnerability scanner is able to analyze 1 million lines of code. The second is a pre-analysis technique to improve the efficiency of the above analysis technique. The pre-analysis technique improves the path navigation by using an additional cheap anlysis. Despite the additional cost, experimental results show that the total analysis time is reduced by 2.5 times. Simultaneously recall of the analysis is improved by the pre-analysis technique.

Keyword :  Secure coding, Security, Static analysis, Vulnerability scanner, Summary-based, Path-sensitive, Information flow Analysis, Pre-analysis

For More Detailshttps://airccj.org/CSCP/vol7/csit77003.pdf

Wednesday, April 1, 2020

GÖDEL THEOREM IS INVALID

Author :  J. Ulisses Ferreira

Affiliation :  Trv Pirapora 36 Costa Azul, 41770-220, Salvador

Country :  Brazil

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  7, 8, June, 2017

Abstract

This short and informal article shows that there exists some deductive system that proves that arithmetic is both sound and complete. First, it shows that there exists some four-valued logical system that plays the same role, by presenting a four-valued logic and informally introducing a four-valued Prolog programming language. Finally, it observes that some Boolean formal system can also prove that arithmetic is both sound and complete.

Keyword :  Gödel, incompleteness theorem, four-valued logic, logic, computability theory, philosophy of computer science

For More Details https://airccj.org/CSCP/vol7/csit77002.pdf

Tuesday, March 31, 2020

AUTOMATED USABILITY EVALUATION OF E-LEARNING WEBSITES IN SAUDI ARABIA

Author :  Khalid Al-Omar

Affiliation :  Department of Information Systems, King Abdulaziz University, Jedda

Country :  Kingdom of Saudi Arabia

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  7, 8, June, 2017

Abstract

Web usability is a significant factor in increasing user satisfaction, performance, trust, and loyalty. Web usability is particularly important for people who mostly depend on the website and for one reason or other cannot visit an institution, such as online distance education students. Accordingly, universities and educational websites need to determine the types of usability problems they have on their websites. However, far too little attention has been paid to providing detailed information regarding the types of specific usability problems that could be found on e-learning websites in general, and specifically, in the Kingdom of Saudi Arabia (KSA). The aim of this paper is to study and analyse the usability of university websites that offer distance education courses in the KSA. A total of 12 universities in Saudi Arabia were considered, which include 11 affiliated and one private university. The analysis of the data represents the level of usability of distance education websites. Results reveal that in Saudi Arabia, distance education websites are reliable, but violate basic usability guidelines.

Keyword :  University Websites, Credibility, Trustworthiness, Online Trust, Website Design, Saudi Arabia, Distance Education

For More Details :  https://airccj.org/CSCP/vol7/csit77001.pdf

Friday, March 27, 2020

A PROCESS OF LINK MINING


Author :  Dr. Zakea Il-agure

Affiliation :  Higher Colleges of Technology

Country :  United Arab Emirates

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  7, 5, April, 2017

Abstract

Many data mining and knowledge discovery methodologies and process models have been developed, with varying degrees of success, there are three main methods used to discover patterns in data; KDD, SEMMA and CRISP-DM. They are presented in many of the publications of the area and are used in practice. To our knowledge, there is no clear methodology developed to support link mining. However, there is a well known methodology in knowledge discovery in databases, known as Cross Industry Standard Process for Data Mining (CRISPDM), developed by a consortium of several industrial companies which can be relevant to the study of link mining. In this study CRISP-DM has been adapted to the field of Link mining to detect anomalies. An important goal in link mining is the task of inferring links that are not yet known in a given network. This approach is implemented through the use of a case study of real world data (co-citation data). This case study aims to use mutual information to interpret the semantics of anomalies identified in co-citation, dataset that can provide valuable insights in determining the nature of a given link and potentially identifying important future link relationships.

Keyword :  Link mining, anomalies, mutual information

For More Details  :  https://airccj.org/CSCP/vol7/csit76709.pdf


CLUSTERING HYPERSPECTRAL DATA


Author :  Arwa Alturki

Affiliation :  Department of Computer Science, King Saud University

Country :  Saudi Arabia

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  7, 5, April, 2017

Abstract

Spectroscopy or hyperspectral imaging consists in the acquisition, analysis, and extraction of the spectral information measured on a specific region or object using an airborne or satellite device. Hyperspectral imaging has become an active field of research recently. One way of analysing such data is through clustering. However, due to the high dimensionality of the data and the small distance between the different material signatures, clustering such a data is a challenging task.In this paper, we empirically compared five clustering techniques in different hyperspectral data sets. The considered clustering techniques are K-means, K-medoids, fuzzy Cmeans, hierarchical, and density-based spatial clustering of applications with noise. Four data sets are used to achieve this purpose which is Botswana, Kennedy space centre, Pavia, and Pavia University. Beside the accuracy, we adopted four more similarity measures: Rand statistics, Jaccard coefficient, Fowlkes-Mallows index, and Hubert index. According to accuracy, we found that fuzzy C-means clustering is doing better on Botswana and Pavia data sets, K-means and K-medoids are giving better results on Kennedy space centre data set, and for Pavia University the hierarchical clustering is better.

Keyword :  Image Processing, Hyperspectral Imaging, Imaging Spectroscopy, Clustering, FCM, K-means, K-medoids, hierarchical, DBSCAN

 For More Details :  https://airccj.org/CSCP/vol7/csit76708.pdf


Thursday, March 26, 2020

REDUCING FREQUENCY OF GROUP REKEYING OPERATION

Author :  YunSuk Yeo

Affiliation :  Computer Engineering, Sungkyunkwan University, Suwon

Country :  South Korea

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  7, 5, April, 2017

Abstract

In the past, Ad-hoc networks were used in limited areas which require secure group communication without Internet access, such as the army or emergencies. However, Ad-hoc networks currently are widely used in variety applications like group chat, smart applications, research testbed etc. Ad-hoc network is basically group based network in the absence of access point so it is prevalent to provide group key approach to prevent information leakage. When we use group key approach, we need to consider which group key management method is the most suitable for the architecture because the cost and frequency of the rekeying operation remain as an unresolved issue. In this paper, we present analysis about existing group key management solutions for Ad-hoc network and suggest a new approach to reduce frequency of the rekeying operation.  

Keyword :  Rekeying operation, Group key management, ad-hoc networks, Frequency of rekeying, Timedriven method

For More Details :  https://airccj.org/CSCP/vol7/csit76707.pdf