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Effects of Various Earth Grid Configurations on Ground Potential Rise Caused by Lightning Strike
No full textGround Potential Rise (GPR) caused by lightning strike is a potential hazard for electrical equipment inside an oil and gas refinery plant. In order to mitigate the risk, horizontal grounding grid is applied. The best mitigation is to install a grounding grid with mesh size as small as possible. This condition requires a high cost. In order to obtain the optimal mesh size, a series of simulation of a grounding grid with mesh size variations on GPR caused by lightning strike has been carried out. CDEGS software was used to observe the GPR with various mesh size from 6.5 x 6.5 m to 20 x 20 m. Simulation results show that the maximum transient GPR rises as the grounding grid mesh size is increased, while the GPR distribution throughout the grounding grid area does not change much for different mesh sizes. In the other hand, decreasing the grid size would mean that more conductors are required, hence the cost would increase accordingly. The result shows that grid sizes from 6.5 x 6.5 m up to 20 x 20 m have no significant difference in term of GPR. In term of cost, 10 x 10 m does not show significant difference with 20 x 20 m, on the other hand, there is a significant difference for grid sizes 1 x 1 m to 10 x 10 m. From the results, grid sizes between 10 x 10 m up to 20 x 20 m are still applicable as stated in Petronas Technical. To comply with proper GPR value, additional protection devices are needed to protect the electrical equipment from potential damage.
Manuscript received: 12 Jun 2019 | Revised: 25 Sep 2019 | Accepted: 20 Oct 2019 | Published: 13 Nov 201
A Survey on Crypto-Steganographic Schemes and A Use Case in Healthcare System
No full textInformation sharing has become prevalent due to the expansion of social networking in this 21st century. However, electronic devices are vulnerable to various kinds of attacks. Information might be disclosed, modified and accessed by an unauthorised third party which consequently leads to the breach of confidentiality, integrity and availability of the information. Therefore, it is of utmost importance to employ the technology of cryptography and steganography to protect information assets. Cryptography and steganography have weaknesses when they are working alone. Therefore, crypto-steganography, the combination of cryptography and steganography are introduced to overcome the weaknesses in order to provide a double layer of security and protection. This paper provides a general overview of steganography and cryptography as well as a comparison analysis of different crypto-steganographic schemes. A secure crypto-steganographic system for healthcare is then developed with the implementation and integration of the secure crypto-steganographic scheme proposed by Juneja and Sandhu. This healthcare system enables users to store and deliver message in a more secure way while achieving the main goals of both cryptography and steganography
The Integrated Simulation and Processing Tool for Ground Based Synthetic Aperture Radar (GBSAR)
No full textGround-based Synthetic Aperture Radar (GBSAR) is a tremendous example of the extended applications of Synthetic Aperture Radar (SAR). GBSAR is extremely useful in human-made structure observations, terrain mapping, landslide monitoring and many more. However, the process of designing and developing the GBSAR system is rather costly and time-consuming. It would be of a great advantage for system designers to have a realistic simulation and designing tool to anticipate the results before the implementation of the final design. In this paper, we are going to present the integrated simulation and designing tool that we have developed for a generic GBSAR system. We named it iSIM v2.0
Chronic Kidney Disease Risk Estimation Using Artificial Neural Network
No full textChronic kidney disease (CKD) is the most common disease of the urinary system that can threaten the survival of the human body. Early detection and lifestyle changes can prevent kidney failure and improve the chance of survival. In West Malaysia, the prevalence of chronic kidney disease is estimated to be 9% of the population. However, screening for chronic kidney disease is still neglected at the early stages. Many equations for risk estimation of kidney failure have been developed. Some of the limitations of these equations are that they may require many laboratory tests, static and not updated. In this study, a new risk estimation model for kidney disease is developed. The risk factors of kidney disease are first identified according to their energy levels, which are Low, Medium and High. The new equation is then developed based on the relationship and the estimated weight of these risk factors.Artificial Neural Network (ANN) is utilized in this study as an alternative to classic risk equations. The MATLAB software is used to train the neural network. Retrospective data from 20 subjects are used to compare the output for the conventional equation and ANN. Another 20 samples have also been generated and compared with “Kidney Disease: Improving Global Outcomes” (KDIGO) 2012 clinical guideline heat map. The results show a slight difference between the methods. The conventional method shows its capability to estimate the risk. The result also shows the potential of the artificial neural network (ANN) to improve the accuracy of chronic kidney disease risk estimation.
Manuscript received: 3 May 2019 | Revised: 10 Sept 2019 | Accepted: 14 Oct 2019 | Published: 13 Nov 201