CRESUS: A TOOL TO SUPPORT COLLABORATIVE REQUIREMENTS ELICITATION THROUGH ENHANCING SHARED UNDERSTANDING AND SIMULATION

Author :  Paul Stynes

Affiliation :  School of Computing, National College or Ireland, Dublin

Country :  Ireland

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  8, 2, January, 2018

Keyword :  Collaborative requirements elicitation, Shared Understanding, and Semantically enabled web services.

Abstract

Communicating an organisation's requirements in a semantically consistent and understandable manner and then reflecting the potential impact of those requirements on the IT infrastructure presents a major challenge among stakeholders. Initial research findings indicate a desire among business executives for a tool that allows them to communicate organisational changes using natural language and a simulation of the IT infrastructure that supports those changes. Building on a detailed analysis and evaluation of these findings, the innovative CRESUS tool was designed and implemented. The purpose of this research was to investigate to what extent CRESUS both aids communication in the development of a shared understanding and supports collaborative requirements elicitation to bring about organisational, and associated IT infrastructural, change. This paper presents promising results that show how such a tool can facilitate collaborative requirements elicitation through increased communication around organisational change and the IT infrastructure.

For More Details :  https://airccj.org/CSCP/vol8/csit88205.pdf

INCREASING THE ARCHITECTURES DESIGN QUALITY FOR MAS: AN APPROACH TO MINIMIZE THE EFFECTS OF COMPLEXITY

Author :  Howayda Abdallah Ali Elmarzaki

Affiliation :  Department of Software Engineering, Benghazi University

Country :  Libya

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  8, 2, January, 2018

Keyword :  Multi agent system (MAS), a general architectures, Quality attributes, Recommendations systems (RS).

Abstract

The efficiency of multi agent system design mainly relies on the quality of a conceptual

architecture of such systems. Hence, quality issues should be considered at an early stage in the

software development process. Large systems such as multi agents systems (MAS) require many communications and interactions to fulfil their tasks, and this leads to complexity of

architecture design (AD) which have crucial influence on architecture design quality. This work

attempts to introduce approach to increase the architecture design quality of MAS by

minimizing the effect of complexity. 

For More Details :  https://airccj.org/CSCP/vol8/csit88206.pdf

AN INVESTIGATION OF WATERMARKING MEDICAL IMAGES

Author :  Majdi Al-qdah

Affiliation :  Department of Computer Engineering, University of Tabuk

Country :  UAE

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  8, 2, January, 2018

Keyword :  Watermarking, medical images, DWT, DCT, SVD, visual metrics

Abstract

This paper presents the results of watermarking selected various medical cover images with simple string of letters image (patients' medical data) using a combination of the Discrete Wavelet Transform (DWT) Discrete Cosine Transform (DCT) and singular value decomposition (SVD). The visual quality of the watermarked images (before and after attacks) was analyzed using PSNR and four visual quality metrics (WSNR, MSSIM, PSNR-HVS-M, and PSNR-HVS). The PSNR, PSNR-HVS-M, PSNR-HVS, and WSNR average values of the watermarked medical images before attacks were about the 32 db, 35 db, and 42 db, 40 db respectively; while the MSSM index indicated a similarity of more than 97% between the original and watermarked images. The metric values decreased significantly after attacking the images with various operations but the watermark image could be retrieved after almost all attacks. Thus, the initial results indicate that watermarking medical images with the patients' data does not significantly affect their visual quality and they still can be utilized for their medical purpose.

For More Details :  https://airccj.org/CSCP/vol8/csit88209.pdf

MULTIPLE SCLEROSIS DIAGNOSIS WITH FUZZY C-MEANS

Author :  Saba Heidari Gheshlaghi

Affiliation :  Department of Electrical Engineering, Amirkabir University of Technology

Country :  Iran

Category :  Information Technology Management

Volume, Issue, Month, Year :  8, 2, January, 2018

Abstract

Magnetic resonance imaging (MRI) can support and substitute clinical information in the diagnosis of multiple sclerosis (MS) by presenting lesion. In this paper, we present an algorithm for MS lesion segmentation. We revisit the modification of properties of fuzzy c means algorithms and the canny edge detection. Using reformulated fuzzy c means algorithms, apply canny contraction principle, and establish a relationship between MS lesions and edge detection. For the special case of FCM, we derive a sufficient condition for fixed lesions, allowing identification of them as (local) minima of the objective function.

Keyword :  Multiple Sclerosis, MRI, T2, fuzzy c-means (FCM), Canny.

For More Details :  https://airccj.org/CSCP/vol8/csit88210.pdf

INFORMATIZED CAPTION ENHANCEMENT BASED ON IBM WATSON API AND SPEAKER PRONUNCIATION TIME-DB

Author :  Yong-Sik Choi

Affiliation :  Department of Computer Science and Engineering, Dongguk University

Country :  Korea

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  8, 2, January, 2018

Abstract 

This paper aims to improve the inaccuracy problem of the existing informatized caption in the noisy environment by using the additional caption information. The IBM Watson API can automatically generate the informatized caption including the timing information and the speaker ID information from the voice information input. In this IBM Watson API, when there is noise in the voice signal, the recognition results are not good, causing the informatized caption error. Especially, it is more easily found in movies such as background music and special sound. Specifically, to reduce caption error, additional captions and voice information are entered at the same time, and the result of the informatized caption of voice information from IBM Watson API is compared with the original text to automatically detect and modify the error part. Based on the database containing the average pronunciation time, each word for each speaker is changed into the informatized caption in this process. In this way, more precise informatized captions could be generated based on the IBM Watson API.

Keyword :  Informatized caption, Speaker Pronunciation Time, IBM Watson API, Speech to Text Translation

For More Details  :  https://airccj.org/CSCP/vol8/csit88211.pdf

MAMMOGRAPHY LESION DETECTION USING FASTER R-CNN DETECTOR

Author :  Reza Reiazi

Affiliation :  Department of Medical Physics, School of Medicine, Iran University of Medical Sciences

Country :  Iran

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  8, 2, January, 2018

Abstract

Recently availability of large scale mammography databases enable researchers to evaluates advanced tumor detections applying deep convolution networks (DCN) to mammography images which is one of the common used imaging modalities for early breast cancer. With the recent advance of deep learning, the performance of tumor detection has been developed by a great extent, especially using R-CNNs or Region convolution neural networks. This study evaluates the performance of a simple faster R-CNN detector for mammography lesion detection using a MIAS databases.

Keyword :  Mammography, Convolution Neural Network, R-CNN, lesion

For More Details :  https://airccj.org/CSCP/vol8/csit88212.pdf