Latest Articles Rss

Enhancement of Voltage Stability by Optimal Location of Static Var Compensator Using Genetic Algorithm and Particle Swarm Optimization

Problem statement: Voltage instability and voltage collapse have been considered as a major threat to present power system networks due to their stressed operation. It is very important to do the power system analysis with respect to voltage stability. Approach: Flexible AC Transmission System (FACTS) is an alternating current transmission system incorporating power electronic-based and other static controllers to enhance controllability and increase power transfer capability. A FACTS device in a power system improves the voltage stability, reduces the power loss and also improves the load ability of the system. Results: This study investigates the application of Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) to find optimal location and rated value of Static Var Compensator (SVC) device to minimize the voltage stability index, total power loss, load voltage deviation, cost of generation and cost of FACTS devices to improve voltage stability in the power system. Optimal location and rated value of SVC device have been found in different loading scenario (115%, 125% and 150% of normal loading) using PSO and GA. Conclusion/Recommendations: It is observed from the results that the voltage stability margin is improved, the voltage profile of the power system is increased, load voltage deviation is reduced and real power losses also reduced by optimally locating SVC device in the power system. The proposed algorithm is verified with the IEEE 14 bus, IEEE 30 bus and IEEE 57 bus.

A Study of Network Traffic Pattern and its Impact on Performance in Implementation of Web Services

Problem statement: Currently it is evident that the web service is emerging as a solution for business applications and deployment of web services witnesses exponential growth. Web services rely on networks particularly internet for implementing and consuming them in different applications. Whenever a network is involved in a software system, network traffic payload measurement and communication pattern play a key role in determining and enhancing performance of the software system. Thus, this study emphasizes the need for network traffic payload measurement in evaluating performance of implementation of web services. Approach: Further empirical measurement of the network traffic payload in implementation of web services is carried out to analyze performance of realization of web services. In this work, the web service realization is done through a model with three-tier approach which is suitable for business applications. Results and Conclusion: This study reports empirical results of network traffic involved in different implementations of web services.

The Recovery of Used Palm Cooking Oil Using Bagasse as Adsorbent

Problem statement: The use and reduce cooking oil is a common phenomena in our society. While some of this cooking oil is further refine most of it however and not subject to any filtration in the refining process medium such as carbon active, silica are commonly use. Approach: The used of bagasse as adsorbent is not common. This is odd especially when structural component of bagasse which is made up of carbon material is suitable as adsorbent and the fact that, adsorbent bagasse further reduce solid waste disposal and hence reducing one source of environmental pollution. Results: This study was undertaken to explore the possibility of using bagasse as adsorbent. Specifically, bagasse is being experimented to reduce the harmful content such as Free Fatty Acid (FFA) and color density in used cooking oil. The variation of adsorbent weight and contact time are used in this research as parameters to determine the effective time and the amount of adsorbent that should be used in the oil refining process. From the experiment conducted, it can be established that bagasse when use as an adsorbent can reduce FFA to 82.14% which is lower the harmful limit. Conclusion/Recommendations: This result is obtained when using 7.5 gr of bagasse for 60 m contact time. Similarly, the color of oil is reduced to 75.67% which is significant and this is base on 10 gr of bagasse with 60 m of contact time.

Supplier Selection and Performance Evaluation of Telecommunication Company

Problem statement: In today�s manufacturing outsourcing of resources has significant importance. Efficient supplier selection process is a central part in supply chain management for enterprises for outsourcing. Approach: The nature of supplier selection is a multi criteria decision making problem and in the selection process multiple criteria must be considered. In this study a multiple attribute utility theory base on Data Envelopments Analysis (DEA) applied to tackle this problem with consideration of some inputs and outputs. Results: A real case study was implemented to show the application of DEA method and through this method the efficient and inefficent suppliers were identified to ranking them. Conclusion: DEA is a tactical model to cope with multiple criteria in purchasing decisions.

Integrated Electricity Planning Comprise Renewable Energy and Feed-In Tariff

Problem statement: Mitigation of global warming and energy crisis has called upon the need of an efficient tool for electricity planning. This study thus presents an electricity planning tool that incorporates RE with Feed in-Tariff (FiT) for various sources of Renewable Energy (RE) to minimize grid-connected electricity generation cost as well as to satisfy nominal electricity demand and CO2 emission reduction target. Approach: In order to perform these tasks, a general Mixed Integer Linear Programming (MILP) model was developed and implemented in General Algebraic Modeling System (GAMS). The RE options considered including landfill gas, municipal solid waste, palm oil residue and hydro power. While the model presents a general approach for electricity planning, Iskandar Malaysia is applied as a case study in this research. Results: By considering the cost, FiT, availability of the Renewable Energy Source (RES) and limit of RE fund for FiT remuneration in Malaysia. The optimization result indicates that Iskandar Malaysia can satisfy the set target of 40% carbon emission reduction by 2015 by implementing biomass RE. Conclusion: It�s revealed that a total of 875 MW of RE is required from Biomass Bubbling Fluidized Bed (BBFB) using various palm oil biomass fuel (mesofiber-215 MW, Empty Fruit Bunch (EFB)-424 MW and kernel-236 MW). However, this increases the Cost Of Electricity (COE) by 69-6.5% cents/kWh.

Sharp Transition Multiband Filter in Speech Processing Scheme for Hearing Impaired

Problem statement: A simple analytical approach to the synthesis of a sharp transition, linear phase, multiband FIR filter is presented. The filter magnitude response is modeled using trigonometric functions of frequency. Approach: Employing variable density of ripple cycles in passband and stopband regions with large density of ripples cycles at the sharp transition edges, reduces the abrupt discontinuities at these edges. Results: As a result, Gibb�s phenomenon is reduced in the filter implementation thus giving a flat passband and good stopband attenuation. A closed form expression for impulse response coefficients is obtained. The filter design is easily tunable and allows for variation in transition bandwidth of each band. A speech processing scheme is implemented using a pair of the proposed sharp transition multiband FIR filters to split the speech spectrum into complementary short time spectral bands. Conclusion: The adjacent speech formants are fed dichotically to the two ears to reduce the effect of spectral masking and hence improve speech perception in sensorineural hearing impaired.

Performance Analysis and Components Irreversiblities of a (25 MW) Gas Turbine Power Plant Modeled with a Spray Cooler

In this study the effect of inlet air cooling system and components irreversibilities on the performance of an active 25MW gas turbine power plant was investigated. The objective of this study was to establish the potential benefits of improving the performance of the current gas turbine plant into a more advanced cycle with high efficiency and power output through inlet air cooling. Problem statement: The hypothesis was that the low performance of the gas turbine plant was caused by high ambient temperature, the use of spray cooler was adopted to bring the air condition temperature close to ISO condition. Approach: In this study, performance characteristics were determined for a set of actual operational conditions including ambient temperature, relative humidity, turbine inlet temperature and pressure ratio. Results: The results obtained show that the use of a spray cooler on the existing gas turbine cycle gives a better thermal efficiency and less irreversibility rate in the components system and the entire plant. The power output of the gas turbine plant with spray cooler was found to have increased by over 7%, accompanied by 2.7% increase in machine efficiency with a reduction in specific fuel consumption of 2.05 and 10.03% increase in the energy of exhaust. Furthemore, a 0.32% reduction in the total irreversibility rate of the plant for the cooled cycle was obtained and a 0.39, 0.29 and 0.17% reduction in the irreversibility rate of compressor, turbine and combustion chamber respectively, were also obtained. Conclusion: The results show that retrofitting the existing gas turbine plant with inlet air cooling system gives a better system performance and may prove to be an attractive investment opportunity.

Cross Validation Evaluation for Breast Cancer Prediction Using Multilayer Perceptron Neural Networks

Problem statement: The presence of metastasis in the regional lymph nodes is the most important factor in predicting prognosis in breast cancer. Many biomarkers have been identified that appear to relate to the aggressive behaviour of cancer. However, the nonlinear relation of these markers to nodal status and also the existence of complex interaction between markers have prohibited an accurate prognosis. Approach: The aim of this study is to investigate the effectiveness of a Multilayer Perceptron (MLP) for predicting breast cancer progression using a set of four biomarkers of breast tumors. The biomarkers include DNA ploidy, cell cycle distribution (G0G1/G2M), steroid receptors (ER/PR) and S-Phase Fraction (SPF). A further objective of the study is to explore the predictive potential of these markers in defining the state of nodal involvement in breast cancer. Two methods of outcome evaluation viz. stratified and simple k-fold Cross Validation (CV) are studied in order to assess their accuracy and reliability for neural network validation. Criteria such as output accuracy, sensitivity and specificity are used for selecting the best validation technique besides evaluating the network outcome for different combinations of markers. Results: The results show that stratified 2-fold CV is more accurate and reliable compared to simple k-fold CV as it obtains a higher accuracy and specificity and also provides a more stable network validation in terms of sensitivity. Best prediction results are obtained by using an individual marker-SPF which obtains an accuracy of 65%. Conclusion/Recommendations: Our findings suggest that MLP-based analysis provides an accurate and reliable platform for breast cancer prediction given that an appropriate design and validation method is employed.

Adaptive Channel Estimation for Multiuser Underwater Communication Systems

Problem statement: Multiple Access Interference (MAI) signals and poor estimation of the unknown channel parameters in the presence of limited training sequences are two of the major problems that degrade the systems� performance. Two synchronous multiuser receivers with Rake reception of Interleave Division Multiple Access (IDMA) and Code Division Multiple Access (CDMA) systems, in conjunction with channel estimation, are considered for communication over different short range shallow water acoustic channels. Approach: The proposed hard/soft chip channel estimation and carrier phase tracking are jointly optimized based on the Mean Square Error (MSE) criterion and adapted iteratively by the reconstructed MAI signal. This is generated from exchanged soft information in terms of Log-Likelihood Ratio (LLR) estimates from the single-users� channel decoders. The channel parameters and error estimation are used to enable the chip cancellation process to retrieve an accurate measurement of the detrimental effects of Intersymbol Interference (ISI) and MAI. Results: The performance of the proposed receiver structures with small processing gain are investigated and compare with 2 and 4 synchronous users using memoryless Quadrature Phase-Shift Keying (QPSK) at an effective rate of 439.5 bps per user. Conclusion: The results demonstrate that the performance is limited by MAI and ISI signals and the IDMA performance outperforms long code CDMA and short code CDMA.

FPGA-Based Architecture for a Generalized Parallel 2-D MRI Filtering Algorithm

Problem statement: Current Neuroimaging developments, in biological research and diagnostics, demand an edge-defined and noise-free MRI scans. Thus, this study presents a generalized parallel 2-D MRI filtering algorithm with their FPGA-based implementation in a single unified architecture. The parallel 2-D MRI filtering algorithms are Edge, Sobel X, Sobel Y, Sobel X-Y, Blur, Smooth, Sharpen, Gaussian and Beta (HYB). Then, the nine MRI image filtering algorithm, has empirically improved to generate enhanced MRI scans filtering results without significantly affecting the developed performance indices of high throughput and low power consumption at maximum operating frequency. Approach: The parallel 2-d MRI filtering algorithms are developed and FPGA implemented using Xilinx System Generator tool within the ISE 12.3 development suite. Two unified architectures are behaviorally developed, depending on the abstraction level of implementation. For performance indices comparison, two Virtex-6 FPGA boards, namely, xc6vlX240Tl-1lff1759 and xc6vlX130Tl-1lff1156 are behaviorally targeted. Results: The improved parallel 2-D filtering algorithms enhanced the filtered MRI scans to be edge-defined and noise free grayscale imaging. The single architecture is efficiently prototyped to achieve: high filtering performance of (11230 frames/second) throughput for 64*64 MRI grayscale scan, minimum power consumption of 0.86 Watt with a junction temperature of 52�C and a maximum frequency of up to (230 MHz). Conclusion: The improved parallel MRI filtering algorithms which are developed as a single unified architecture provide visibility enhancement within the filtered MRI scan to aid the physician in detecting brain diseases, e.g., trauma or intracranial haemorrhage. The high filtering throughput is feasibly nominee the nine parallel MRI filtering algorithms for applications such as real-time MRI potential future applications. Future Work: a set of parallel 3-D fMRI filtering algorithms will be investigated to be developed and fast FPGA prototyped for future research project.