Suriayati Chuprat

Scheduling Divisible Real-Time Loads on Clusters with Varying Processor Start Times

Recent research in real-time divisible load theory (RT-DLT) has addressed the problem of distributing arbitrarily parallelizable real-time workloads among processors which become available at different instants in the future. Given a real-time job and the times as which the processors become available, we devise exact efficient algorithms to solve two important problems: (i) determine the smallest number of processors needed to complete this job by its deadline; and (ii) given a specific number of processors, determine the earliest completion time for the job on these processors.

A study on significance of adopting cloud computing paradigm in healthcare sector

Healthcare sector is information critical industry that deals with human lives. Transforming from traditional paper-based to Electronic Health Records (EHRs) was not efficient enough since EHRs require resources, integration, maintenance and high cost implementation. Cloud computing paradigm offers flexible, cost effective, collaborative, multi-tenant infrastructure which assists in transforming electronic healthcare to smart healthcare that consists on the use of latest technologies such as smart mobiles, smart cards, robots, sensors and Tele-health systems via internet on pay-per-use basis for best medical practices. Cloud computing reduces the cost of EHRs in terms of ownership and IT maintenance, also it offers sharing, integration and management of EHRs as well as tracking patients and diseases more efficiently and effectively. This review paper represents the significance and opportunities for implementing cloud computing in healthcare sector.

Identifying Benefits and Risks Associated with Utilizing Cloud Computing

Cloud computing is an emerging computing model where IT and computing operations are delivered as services in highly scalable and cost effective manner. Recently, embarking this new model in business has become popular. Companies in diverse sectors intend to leverage cloud computing architecture, platforms and applications in order to gain higher competitive advantages. Likewise other models, cloud computing brought advantages to attract business but meanwhile fostering cloud has led to some risks, which can cause major impacts if business does not plan for mitigation. This paper surveys the advantages of cloud computing and in contrast the risks associated using them. Finally we conclude that a well-defined risk management program that focused on cloud computing is an essential part of gaining value from benefits of cloud computing.

DESIGN AND IMPLEMENTATION OF A PRIVACY PRESERVED OFF-PREMISES CLOUD STORAGE

Despite several cost-effective and flexible charact eristics of cloud computing, some clients are reluc tant to adopt this paradigm due to emerging security and pr ivacy concerns. Organization such as Healthcare and Payment Card Industry where confidentiality of info rmation is a vital act, are not assertive to trust the security techniques and privacy policies offered by cloud service providers. Malicious attackers have violated the cloud storages to steal, view, manipul ate and tamper client’s data. Attacks on cloud storages are extremely challenging to detect and mi tigate. In order to formulate privacy preserved cloud storage, in this research paper, we propose a n improved technique that consists of five contributions such as Resilient role-based access c ontrol mechanism, Partial homomorphic cryptography, metadata generation and sound stegano graphy, Efficient third-party auditing service, Data backup and recovery process. We implemented these components using Java Enterprise Edition with Glassfish Server. Finally we evaluated our pro posed technique by penetration testing and the results showed that client’s data is intact and pro tected from malicious attackers.

Histogram matching for color detection: A preliminary study

Several similarity measures such as Euclidean Distance, Histogram Intersection, Cosine or Quadratic Distances are usually used to calculate the images similarity rating. However, each of the distances has their own limitations when used in particular situation or application. This paper reports a preliminary study of current similarity measures used based on histogram matching. Few experiments on image and color histograms are also presented and discussed. Images of Oil Palm Fruits are used to estimate for its ripeness. This paper will point out the use of existing similarity measures to find the most suitable and efficient one for that particular application

Cloud implementation security challenges

Cloud computing offers significant features such as resource pooling, scalability, on-demand self service, availability, and reliability to organizations to improve their quality of services. For example by using cloud computing services in healthcare it is possible to reach large population of people in isolated geographical areas which will assist in saving their lives in critical situations. It enables the use of latest technologies through its various service delivery and deployment models via the internet on pay-per-use billing pattern. However, cloud computing has dark side when it comes to security and privacy considerations. Critical industries such as healthcare and banking are reluctant to trust cloud computing due to the fear of losing their sensitive data, as it resides on the cloud with no knowledge of data location and lack of transparency of Cloud Service Providers (CSPs) mechanisms used to secure their data and applications which have created a barrier against adopting this agile computing paradigm. This paper addresses cloud computing security concerns that must be considered in order to adopt cloud services in information critical industries.

Field programmable gate array system for real-time IRIS recognition

Iris recognition is one of the most flawless recognition methods in biometrics. However, most of iris recognition algorithms are implemented based on sequential operations running on central processing units (CPUs). In this article we propose a prototype design for iris recognition based on field-programmable gate array (FPGA) in order to improve iris recognition performance by parallel computing. Time-consuming iris recognition sub-processes are fully implemented in parallel to achieve optimum performance. Unlike commonly used iris recognition methods that first capture a single image of an eye and then start the recognition process, we achieved to speed up the iris recognition process by localizing the pupil and the iris boundaries, unwrapping the iris image and extracting features of the iris image while image capturing was in progress. Consequently, live images from human eye can be processed continuously without any delay. We conclude that iris recognition acceleration by parallel computing can be a complete success when it is implemented on low-cost FPGAs.

Situational factors affecting Requirement Engineering process in Global Software Development

A most favorable Requirement Engineering process is considered to be subject of situational characteristics of Software Requirement Engineering settings. These characteristics are related to organizations, project, process, requirements, stakeholders etc. However, list of situational factors affecting the Requirement Engineering process during Global Software Development is presently not available. The lack of such study is challenging as it not only restrain the ability to improve Requirement Engineering process, but also it can undermine the competence of Requirement Engineering team to determine the core constraints and characteristics of developing software. To address this scarcity, we have merged a considerable related research into an initial list of situational factors that affect the Requirement Engineering Process during Global Software Development. We have performed Systematic Literature Review for situational factors identification. To carry on data merging, we have used thorough data coding techniques adopted from Grounded Theory. The initial list of situational factors consists of 37 factors, which is the sound initial reference list for Requirement Engineering process definition in Global Software Development environment. The outcome of this study symbolizes a significant contribution to the Requirement Engineering body of knowledge.

Parameters Consideration in Designing a Magnetorheological Damper

This paper presents a simulation study of electromagnetic circuit design for a mixed mode Magnetorheological (MR) damper. The magnetic field generated by electromagnetic circuit of the MR damper was simulated using Finite Element Method Magnetics (FEMM) software package. All aspects of geometry parameters were considered and adjusted efficiently in order to obtain the best MR damper performance. Eventually, six different parameters approach were proposed; the selection of materials, the polarity of coils, the diameter of piston, piston rod and core, the shear and squeeze gaps clearance, the piston pole length and the thickness of housing.

Nearest Neighbor For Histogram-based Feature Extraction

Manual grading process of Fresh Fruit Bunch (FFB) leads to misconduct and human error while inspecting the right category of fruits for the purpose of oil palm production at the mill. It is extremely important to identify the degree of ripeness of FFB are at 95% level of confidence as mentioned by Malaysian Palm Oil Board (MPOB). Therefore, wrong evaluation of graded fruits will result wrong report regarding the oil content. However, the most critical part of oil palm grading is the fruit classification. Error in classifying the right category of FFB will cause error in estimating the oil content. Research done by Federal Land Development Authority (FELDA) at mills show the estimated oil content for ripe fruit is 60%, while underripe is 40% and unripe is only 20% minus water and dirt. This indicates the importance of the right classification of FFB during grading process is essential to prevent from mistakenly claim low quality fruits as the good ones. Problem will occur while receiving the grading report claiming the high percentage of Basic Extraction Rate (BER) by the appointed graders while they have been proven to be poor quality fruits during oil production process. Fruit ripeness identification based on color is hard to measure especially when it involves the color intensity. The most suitable color space must be carefully selected to determine the right color especially when the color intensity is involved. HSV color space has proven to be a good choice because it has all the colors in the channel. Besides, it also offers color intensity which can be in variety level of intensity degrees. This paper explores the use of Nearest Neighbor Distance for histogram-based fruit ripeness identification. Promising results are obtained when value elements of HSV gives the highest recognition rate towards both ripe and unripe category.