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Anooj P.K.,Al Musanna College of Technology
2013 International Conference on IT Convergence and Security, ICITCS 2013 | Year: 2013

As people have interests in their health recently, development of medical domain application has been one of the most active research areas. One example of medical domain application is detection system for heart disease based on computer-aided diagnosis methods, were the data are obtained from some other sources and are evaluated based on computer based applications. At the earlier time, the use of computer is to build knowledge based clinical decision support system which uses knowledge from medical experts and transfers this knowledge into computer algorithms manually. This process is time consuming and really depends on medical expert's opinion which may be subjective. To handle this problem, machine learning techniques have been developed to gain knowledge automatically from examples or raw data. Here, a weighted fuzzy rule-based clinical decision support system (CDSS) is presented for the diagnosis of heart disease, automatically obtaining the knowledge from the patient's clinical data. The proposed clinical decision support system for risk prediction of heart patients consists of two phases, (1) automated approach for generation of weighted fuzzy rules, and (2) developing a fuzzy rule-based decision support system. In the first phase, we have used the mining technique, attribute selection and attribute weightage method to obtain the weighted fuzzy rules. Then, the fuzzy system is constructed in accordance with the weighted fuzzy rules and chosen attributes. Finally, the experimentation is carried out on the proposed system using the datasets obtained from the UCI repository and the performance of the system is compared with the neural network-based system utilizing accuracy, sensitivity and specificity. © 2013 IEEE. Source

Pervez T.,Sultan Qaboos University | Qamar S.Z.,Sultan Qaboos University | Al-Hiddabi S.A.,Sultan Qaboos University | Al-Jahwari F.K.,Al Musanna College of Technology | And 3 more authors.
Petroleum Science and Technology | Year: 2011

Recently, field engineers have tried to use a new technique using expandable tubular with elastomers to seal the annulus. Ultrasonic down-hole measurements carried out for evaluation of zonal isolation revealed that the tubular expanded to an oval x-section instead of the desired circular x-section at certain locations. This is a phenomenon previously unknown. It is believed to occur due to expansion in irregularly shaped boreholes. The ovalization of expanded tubular was studied to avoid such problems in future. The finite element method was used to predict tubular ovality and compare it to measured values. Results were then used to develop ready-to-use design curves in making decisions for running a completion tool in expanded tubular. Copyright © Taylor & Francis Group, LLC. Source

Ben George E.,Muscat College | Rosline G.J.,Muscat College | Rajesh D.G.,Al Musanna College of Technology
2015 IEEE 8th GCC Conference and Exhibition, GCCCE 2015 | Year: 2015

Nature enthused algorithms are the most potent for optimization. Cuckoo Search (CS) algorithm is one such algorithm which is efficient in solving optimization problems in varied fields. This paper appraises the basic concepts of cuckoo search algorithm and its application towards the segmentation of brain tumor from the Magnetic Resonance Images (MRI). The human brain is the most complex structure where identifying the tumor like diseases are extremely challenging because differentiating the components of the brain is complex. The tumor may sometimes occur with the same intensity of normal tissues. The tumor, edema, blood clot and some part of brain tissues appear as same and make the work of the radiologist more complex. In general the brain tumor is detected by radiologist through a comprehensive analysis of MR images, which takes substantially a longer time. The key inventiveness is to develop a diagnostic system using the best optimization technique called the cuckoo search, that would assist the radiologist to have a second opinion regarding the presence or absence of tumor. This paper explores the CS algorithm, performing a profound study of its search mechanisms to discover how it is efficient in detecting tumors and compare the results with the other commonly used optimization algorithms. © 2015 IEEE. Source

Abhishek K.,N.I.T. | Roshan S.,Al Musanna College of Technology | Kumar P.,N.I.T. | Ranjan R.,N.I.T.
Advances in Intelligent Systems and Computing | Year: 2013

In recent years, the development in Information technology has unleashed new challenges and opportunities for new authentication systems and protocols. Authentication ensures that a user is who they claim to be. The trust of authenticity increases exponentially when more factors are involved in the verification process. When security infrastructure makes use of two or more distinct and different category of authentication mechanisms to increase the protection for valid authentication, It is referred to as Strong Authentication or Multifactor Authentication. Multifactor authentication uses combinations of "Something you know," "Something you have," "Something you are" and "Somewhere you are"/"Someone you know", to provide stronger remote authentication than traditional, unreliable single-factor username and password authentication. In this paper we do a survey on the different aspects of multifactor authentication, its need, its techniques and its impact. © 2013 Springer-Verlag. Source

Khan M.E.,Al Musanna College of Technology
International Journal of Software Engineering and its Applications | Year: 2011

We can define software testing as a process or a series of processes, design to make sure that computer code does what it was actually design to do and it doesn't do anything unintended. Two of the most important software testing techniques are white box testing and black box testing. In my paper I have described one of the main software testing technique that is white box testing. We can define it as a test case design method that uses the control structure of the procedural design to derive test cases. I have also described briefly the working process of white box testing technique and some of its most frequently used techniques that are control flow testing, data flow testing, branch testing, basis path testing and loop testing. Source

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