2017 8th International Conference on Information Technology (ICIT)最新文献_第5页

A framework for detecting ambiguity in software requirement specification 一个用于检测软件需求规范中歧义的框架

2017 8th International Conference on Information Technology (ICIT) Pub Date : 2017-05-01 DOI: 10.1109/ICITECH.2017.8080002

A. A. Sabriye, W. Zainon

{"title":"A framework for detecting ambiguity in software requirement specification","authors":"A. A. Sabriye, W. Zainon","doi":"10.1109/ICITECH.2017.8080002","DOIUrl":"https://doi.org/10.1109/ICITECH.2017.8080002","url":null,"abstract":"The accomplishment of any software system success depends on how well it meets the requirements of the stakeholders. These requirements are elicited from the customers. Software requirements are unambiguous if and only if it has one meaning. The elicited requirements are documented in software requirements specification document and these requirements are written in natural languages. Natural languages are basically ambiguous which makes the requirements documented in software requirements specification document unclear. This unclear requirement causes that software developers develop software which is different from the expected software based on the customer needs. The objective of this paper is to propose a framework that are able to detect ambiguity in software requirements specification document automatically using parts of speech tagging technique. To validate the outcome of the proposed work, open source software requirements specification documents will be used and generated result of the proposed work will be evaluated and validated by making comparison between the proposed prototype results and human generated results to decide how the proposed prototype can solved the ambiguity problem.","PeriodicalId":102480,"journal":{"name":"2017 8th International Conference on Information Technology (ICIT)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115084489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 16

Better is the enemy of good: Unums — An alternative to IEEE 754 floats and doubles 更好是好的敌人:Unums——IEEE 754浮点数和双精度的替代品

2017 8th International Conference on Information Technology (ICIT) Pub Date : 2017-05-01 DOI: 10.1109/ICITECH.2017.8080000

T. Risse

引用次数: 0

JavaBST: Java backward slicing tool JavaBST: Java向后切片工具

2017 8th International Conference on Information Technology (ICIT) Pub Date : 2017-05-01 DOI: 10.1109/ICITECH.2017.8080067

Mohammad Abdallah, Basem Alokush, Mustafa Alrefaee, Mosa Salah, Rana Bader, Khalil Awad

引用次数: 8

A layered design approach for mobile tourism 移动旅游的分层设计方法

2017 8th International Conference on Information Technology (ICIT) Pub Date : 2017-05-01 DOI: 10.1109/ICITECH.2017.8079986

Abir Hoadjli, O. Kazar, Khaled Rezeg

引用次数: 1

Knowledge sharing among jordanian academicians: A case study of tafila technical university (TTU) and mutah university (MU) 约旦学者之间的知识共享:以塔菲拉技术大学(TTU)和穆塔大学(MU)为例

2017 8th International Conference on Information Technology (ICIT) Pub Date : 2017-05-01 DOI: 10.1109/ICITECH.2017.8080010

A. Alhawamleh, Amir Ngah

{"title":"Knowledge sharing among jordanian academicians: A case study of tafila technical university (TTU) and mutah university (MU)","authors":"A. Alhawamleh, Amir Ngah","doi":"10.1109/ICITECH.2017.8080010","DOIUrl":"https://doi.org/10.1109/ICITECH.2017.8080010","url":null,"abstract":"Knowledge has become a valuable asset and source for latest developments which is the cause of the emergence of new economy. The main concern in new economy is not just about what we learn, but also about the way we implement and capture in real life what we learn. Therefore, Knowledge sharing is one of the academic institution's widely practiced activities. In order to share knowledge, academic staffs conduct conferences, seminars, workshops and publications which signifies the eagerness, importance and kindness of knowledge sharing. This paper is mainly focused to identify the latest condition of activities related to knowledge sharing in Institutions of Higher Learning (IHLs), to highlight the important activities that have been conducted by academic staffs as well as to identify the widely used technologies that are used in effective knowledge sharing. It also highlights academic knowledge sharing attitude, to establish knowledge sharing incentives, and to determine the possible factors that cause problem in knowledge sharing among IHL academic staffs. The overall outcomes revealed that knowledge sharing is essential for successful knowledge management practices in IHLs as well as other organizations and sharing knowledge among academic staffs is the crucial part of IHLs.","PeriodicalId":102480,"journal":{"name":"2017 8th International Conference on Information Technology (ICIT)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126889702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Classification of massive noisy image using auto-encoders and convolutional neural network 基于自编码器和卷积神经网络的海量噪声图像分类

2017 8th International Conference on Information Technology (ICIT) Pub Date : 2017-05-01 DOI: 10.1109/ICITECH.2017.8079976

S. Roy, Mahtab Ahmed, M. Akhand

{"title":"Classification of massive noisy image using auto-encoders and convolutional neural network","authors":"S. Roy, Mahtab Ahmed, M. Akhand","doi":"10.1109/ICITECH.2017.8079976","DOIUrl":"https://doi.org/10.1109/ICITECH.2017.8079976","url":null,"abstract":"Image processing tasks has found a new dimension with the improvement of learning feature representation from images using deep networks. Most of the research works are conducted over pre-possessed image data in the lab. But, these methods fail in the real world scenario as most of the time the image required to classify is subject to noise and other disfigurement. For the last three decades, many researches has been conducted and numerus algorithms have been proposed with varying performances to classify noisy images. But in recent times, various autoencoders have outperformed all traditional methods for reconstructing native image from it's noisy form and opened a new door for the research of noisy image classification. In this paper, we studied various auto encoders for reconstructing native images from noisy input images. We have applied convolutional neural network as classifier. Before classification task we have rectified noisy images using denoising autoencoder, convolutional denoising autoencoder and finally a hybrid of them as proposed in this paper. The proposed methods are evaluated by experimenting over benchmark dataset adulterated with noises of different proportionate. This method has outperformed some other prominent methods achieving satisfying classification accuracy even when the image is too much noisy (50% noise is added with the image data).","PeriodicalId":102480,"journal":{"name":"2017 8th International Conference on Information Technology (ICIT)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114343194","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 11

A survey on location based-services over cellular networks 蜂窝网络上基于位置的服务调查

2017 8th International Conference on Information Technology (ICIT) Pub Date : 2017-05-01 DOI: 10.1109/ICITECH.2017.8079978

M. S. Daoud, Hani Almimi

引用次数: 0

Semantic natural language translation based on ontologies combination 基于本体组合的语义自然语言翻译

2017 8th International Conference on Information Technology (ICIT) Pub Date : 2017-05-01 DOI: 10.1109/ICITECH.2017.8080019

K. Okba, Saouli Hamza, Benfanatki Hind, Alaoui Amira, B. Samir

引用次数: 3

Data mining for web vulnerability detection: A critical review web漏洞检测的数据挖掘:一个重要的回顾

2017 8th International Conference on Information Technology (ICIT) Pub Date : 2017-05-01 DOI: 10.1109/ICITECH.2017.8080011

Duha Al-Darras, Ja'far Alqatawna

{"title":"Data mining for web vulnerability detection: A critical review","authors":"Duha Al-Darras, Ja'far Alqatawna","doi":"10.1109/ICITECH.2017.8080011","DOIUrl":"https://doi.org/10.1109/ICITECH.2017.8080011","url":null,"abstract":"Developing software applications that are free of vulnerabilities is a necessity, especially if these applications are intended to operate over the World Wide Web. As the development of software applications is evolving in a quick manner the need to develop tools that can automatically detect vulnerabilities in a software has emerged. The main challenge in these tools is providing a high accuracy and low false positive or false negative rates. In this paper, we analyze how data mining techniques can be used to improve the quality of vulnerability detection. We start by discussing web Application vulnerabilities along with the static detection approach and its limitations. Then we explore data mining techniques and their potential to improve vulnerability detection. The results of using such techniques in the literature are reviewed and discussed. As a conclusion, we argue that with the growing body of research utilizing data mining for vulnerabilities detection we might get a better detection alternative, however, several aspects need to be further investigated including feature engineering, adaptive classifiers and feature selection.","PeriodicalId":102480,"journal":{"name":"2017 8th International Conference on Information Technology (ICIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130686513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Matching and retrieval of state machine diagrams from software repositories using Cuckoo Search Algorithm 用布谷鸟搜索算法从软件库中匹配和检索状态机图

2017 8th International Conference on Information Technology (ICIT) Pub Date : 2017-05-01 DOI: 10.1109/ICITECH.2017.8079998

Alhassan Adamu, W. Zainon

引用次数: 7