Requirements engineers have been eliciting requirements using various techniques, methods and tools. This paper proposes a mobile application tool to facilitate requirements elicitation process supporting story-based ...
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Requirements engineers have been eliciting requirements using various techniques, methods and tools. This paper proposes a mobile application tool to facilitate requirements elicitation process supporting story-based technique. Conventional devices and tools used in RE process in order to gather information mostly are deploying desktop computers or notebooks. Owing to their size and less mobility feature, they are usually not brought to the work place of the stakeholders. The advancing capabilities of mobile devices and mobile tools can significantly contribute to the facilitation of RE activities. A "story based mobile application for requirements engineering process (SMAREP)" is a mobile based application tool to help requirements engineers and analysts in eliciting, documenting and validating information from stakeholders.
The need for survivability in optical networks is becoming more and more important because of the huge amount of aggregated traffic that is carried in an optical network. A number of protection schemes have been propo...
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The increasing demand of various networking applications such as Internet, voice, data, video and TV services inside large cities with large population requires the design and implementation of more effective metropol...
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In today's Web environment, many enterprises decide to implement and publish their applications on the Internet using Web services technology. In many cases, a single service is not sufficient to fulfill the user&...
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In today's Web environment, many enterprises decide to implement and publish their applications on the Internet using Web services technology. In many cases, a single service is not sufficient to fulfill the user's request. To solve this problem, services should be combined together. Therefore, composition of Web services is one of the recent critical issues. A number of approaches have been presented, to tackle this problem. In this paper, we categorize these approaches into four categories (workflow-based, AI-planning based, syntactic-based, and semantic-based). Then, we compare these approaches based on some criteria (like QoS, scalability, and correctness). Investigation of that classification will help researchers who are working on service composition to deliver more applicable solutions.
An increasingly popular and promising way for complex disease diagnosis is to employ artificial neural networks (ANN). Single nucleotide polymorphisms (SNP) data from individuals is used as the inputs of ANN to find o...
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An increasingly popular and promising way for complex disease diagnosis is to employ artificial neural networks (ANN). Single nucleotide polymorphisms (SNP) data from individuals is used as the inputs of ANN to find out specific SNP patterns related to certain disease. Due to the large number of SNPs, it is crucial to select optimal SNP subset and their combinations so that the inputs of ANN can be reduced. With this observation in mind, a hybrid approach - a combination of genetic algorithms (GA) and ANN (called GANN) is used to automatically determine optimal SNP set and optimize the structure of ANN. The proposed GANN algorithm is evaluated by using both a synthetic dataset and a real SNP dataset of a complex disease.
Transmitter-based linear precoders are considered for downlink multiple input multiple output (MIMO) systems. In this paper, performances of different types of linear precoding are investigated and compared over Ricea...
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Due to environmental mismatch, speech recognition systems often exhibit drastic performance degradation in noisy conditions. This paper presents a model based technique termed adaptive parallel model combination (APMC...
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Due to environmental mismatch, speech recognition systems often exhibit drastic performance degradation in noisy conditions. This paper presents a model based technique termed adaptive parallel model combination (APMC) which compensates the initial acoustic models to reduce the discrepancy. APMC used the well-known PMC technique to composite a set of corrupted speech models, while fine tuning the mean parameter of the models using a transformation-based adaptation technique called Maximum Likelihood Spectral Transformation (MLST). Evaluated on a context-independent phone recognition task, APMC was found to be superior to both PMC and MLST, especially in non-stationary noisy conditions. On average, APMC has achieved 48.81% improvement over the initial models, whereas PMC and MLST have improved the accuracy by 34.12% and 35.23% respectively.
Over decades, software model for improving the quality of software through management of the software process has became significant in the software industry. Many companies are now being assessed according to standar...
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Over decades, software model for improving the quality of software through management of the software process has became significant in the software industry. Many companies are now being assessed according to standards such as the CMM, SIX-SIGMA or ISO 9000, which have brought substantial profit to the companies that utilize them to improve the quality of software product. Several companies in Malaysia have been carried out software process improvement projects. However, a software process improvement initiative is still sometimes delayed, costs are over budgeted and some of them surrender before the project ends. Therefore, this paper attempt to analyze and identify the resistance factors which influence the implementation of the software process improvement project initiated by the company. This paper will serve as reference to the professionals in the area. In the other hand, it may also helping the other companies to manage future projects through the use of preventive actions that will eliminate or at least lessening the resistance factors’ consequences during the implementation of the software process improvement projects. This paper present a survey with 8 Malaysia’s companies around Kuala Lumpur and Selangor which have an experience in initiating and conducting software process improvement project. A total of 117 respondents from various background have participated this survey.
Certain requirements in requirements document are scattered and tangled. Often software developers neglect these requirements during implementation or repeat the same functionality throughout the codes. These requirem...
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Certain requirements in requirements document are scattered and tangled. Often software developers neglect these requirements during implementation or repeat the same functionality throughout the codes. These requirements are called crosscutting concerns. Identifying and analyzing these concerns manually is a hassle due to its ambiguous characteristics and massive volume of requirement sources. Aspect-oriented requirements engineering (AORE) supports crosscutting concern identification at various software development phases. However it is crucial at the requirements level; to avoid coupling between requirements, improve traceability among requirements, eases function modularization, reduce software complexity, enhance correctness of the software design, and most importantly it saves the cost. Many techniques have been developed for crosscutting concern identification at the requirements level such as Theme/Doc and Early Aspects. However all of these techniques in the existing studies are only supported by semi-automated tool whereby human intervention is required to achieve the desired results. In this paper, we describe a tool, 3CI that automatically identifies crosscutting concern as well as their crosscutting relationships at the requirement level. The tool utilizes NLP techniques to extract linguistic properties in each unique requirement and exploits these properties to identify crosscutting concerns and its influences in a requirements document. NLP techniques such as part-of-speech analysis, word frequency analysis and dominant verb analysis contribute in the processing of requirements phrases to assist aspects mining.
Since many organizations recently decide to implement and publish their applications over Internet, the number of Web services has dramatically increased. In many cases, a single service is not sufficient to respond t...
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Since many organizations recently decide to implement and publish their applications over Internet, the number of Web services has dramatically increased. In many cases, a single service is not sufficient to respond to the user’s request. In order to tackle this problem, services have to be combined together. Therefore, composition of Web services is one of the recent critical issues. Several approaches have been presented, to tackle this problem. In this paper, we classify these approaches into four categories namely Workflow-based, AI-planning based, Syntactic-based, and Ontology-based. Then, we describe and compare these approaches using some criteria (like QoS, scalability, and correctness). The overall results indicate that some AI-planning and Ontology based approaches like HTN-DL and WSMO satisfy most of the criteria.
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