Performance Analysis of Digital Signal Processors Using SMV Benchmark

Unlike general-purpose processors, digital signal processors (DSP processors) are strongly application-dependent. To meet the needs for diverse applications, a wide variety of DSP processors based on different architectures ranging from the traditional to VLIW have been introduced to the market over the years. The functionality, performance, and cost of these processors vary over a wide range. In order to select a processor that meets the design criteria for an application, processor performance is usually the major concern for digital signal processing (DSP) application developers. Performance data are also essential for the designers of DSP processors to improve their design. Consequently, several DSP performance benchmarks have been proposed over the past decade or so. However, none of these benchmarks seem to have included recent new DSP applications. In this paper, we use a new benchmark that we recently developed to compare the performance of popular DSP processors from Texas Instruments and StarCore. The new benchmark is based on the Selectable Mode Vocoder (SMV), a speech-coding program from the recent third generation (3G) wireless voice applications. All benchmark kernels are compiled by the compilers of the respective DSP processors and run on their simulators. Weighted arithmetic mean of clock cycles and arithmetic mean of code size are used to compare the performance of five DSP processors. In addition, we studied how the performance of a processor is affected by code structure, features of processor architecture and optimization of compiler. The extensive experimental data gathered, analyzed, and presented in this paper should be helpful for DSP processor and compiler designers to meet their specific design goals.

Comparison of Classical and Ultrasound-Assisted Extractions of Hyphaene thebaica Fruit and Evaluation of Its Extract as Antibacterial Activity in Reducing Severity of Erwinia carotovora

Erwinia carotovora var. carotovora is the main cause of soft rot in potatoes. Hyphaene thebaica was studied for biocontrol of E. carotovora which inhibited growth of E. carotovora on solid medium, a comparative study of classical and ultrasound-assisted extractions of Hyphaene thebaica fruit. The use of ultrasound decreased significant the total time of treatment and increase the total amount of crude extract. The crude extract was subjected to determine the in vitro, by a bioassay technique revealed that the treatment of paper disks with ultrasound extraction of Hyphaene thebaica reduced the growth of pathogen and produced inhibition zones up to 38mm in diameter. The antioxidant activity of ultrasound-ethanolic extract of Doum fruits (Hyphaene thebaica) was determined. Data obtained showed that the extract contains the secondary metabolites such as Tannins, Saponin, Flavonoids, Phenols, Steroids, Terpenoids, Glycosides and Alkaloids.

Harmonics Elimination in Multilevel Inverter Using Linear Fuzzy Regression

Multilevel inverters supplied from equal and constant dc sources almost don-t exist in practical applications. The variation of the dc sources affects the values of the switching angles required for each specific harmonic profile, as well as increases the difficulty of the harmonic elimination-s equations. This paper presents an extremely fast optimal solution of harmonic elimination of multilevel inverters with non-equal dc sources using Tanaka's fuzzy linear regression formulation. A set of mathematical equations describing the general output waveform of the multilevel inverter with nonequal dc sources is formulated. Fuzzy linear regression is then employed to compute the optimal solution set of switching angles.

A Longitudinal Study of the Readability of the Chairman’s Narratives in Corporate Reports: Malaysian Evidence

This paper examines the readability of the chairman’s narratives, as determined by the Flesch score, of a Malaysian public listed company’s corporate reports from 1962 to 2009. It partially supports earlier studies which demonstrated that corporate reports were difficult to read, and had shown very negligible decrease in difficulty over time. Net profit to sales and readability was significantly positively correlated but number of financial statements was significantly negatively correlated with readability.

Studies on Seasonal Variations of Physico- Chemical Parameters of Fish Farm at Govt. Nursery Unit, Muzaffargarh, Punjab, Pakistan

The present study was designed to demonstrate the seasonal variations in physico-chemical parameters of fish farm at Govt. Nursery Unit, Muzaffargarh, Department of Fisheries Govt. of Punjab, Pakistan for a period of eight months from January to August 2008. Water samples were collected on fifteen days basis and have been analyzed for estimation of Air temperature, Water temperature, Light penetration, pH, Total dissolved oxygen, Clouds, Carbonates, Bicarbonates, Total carbonates, Total dissolved solids, Chlorides, Calcium and Hardness. Seasonal fluctuations were observed in all the physico-chemical parameters of fish farm. The overall physicochemical parameters of fish pond water remained within the tolerable range throughout the study period.

Diagnosing the Cause and its Timing of Changes in Multivariate Process Mean Vector from Quality Control Charts using Artificial Neural Network

Quality control charts are very effective in detecting out of control signals but when a control chart signals an out of control condition of the process mean, searching for a special cause in the vicinity of the signal time would not always lead to prompt identification of the source(s) of the out of control condition as the change point in the process parameter(s) is usually different from the signal time. It is very important to manufacturer to determine at what point and which parameters in the past caused the signal. Early warning of process change would expedite the search for the special causes and enhance quality at lower cost. In this paper the quality variables under investigation are assumed to follow a multivariate normal distribution with known means and variance-covariance matrix and the process means after one step change remain at the new level until the special cause is being identified and removed, also it is supposed that only one variable could be changed at the same time. This research applies artificial neural network (ANN) to identify the time the change occurred and the parameter which caused the change or shift. The performance of the approach was assessed through a computer simulation experiment. The results show that neural network performs effectively and equally well for the whole shift magnitude which has been considered.

Delay-Distribution-Dependent Stability Criteria for BAM Neural Networks with Time-Varying Delays

This paper is concerned with the delay-distributiondependent stability criteria for bidirectional associative memory (BAM) neural networks with time-varying delays. Based on the Lyapunov-Krasovskii functional and stochastic analysis approach, a delay-probability-distribution-dependent sufficient condition is derived to achieve the globally asymptotically mean square stable of the considered BAM neural networks. The criteria are formulated in terms of a set of linear matrix inequalities (LMIs), which can be checked efficiently by use of some standard numerical packages. Finally, a numerical example and its simulation is given to demonstrate the usefulness and effectiveness of the proposed results.

A Fitted Random Sampling Scheme for Load Distribution in Grid Networks

Grid networks provide the ability to perform higher throughput computing by taking advantage of many networked computer-s resources to solve large-scale computation problems. As the popularity of the Grid networks has increased, there is a need to efficiently distribute the load among the resources accessible on the network. In this paper, we present a stochastic network system that gives a distributed load-balancing scheme by generating almost regular networks. This network system is self-organized and depends only on local information for load distribution and resource discovery. The in-degree of each node is refers to its free resources, and job assignment and resource discovery processes required for load balancing is accomplished by using fitted random sampling. Simulation results show that the generated network system provides an effective, scalable, and reliable load-balancing scheme for the distributed resources accessible on Grid networks.

Comparison of Frequency Converter Outages: A Case Study on the Swedish TPS System

The purpose of this paper isunavailability of the two main types of conveSwedish traction power supply (TPS) system, i.e.static converter. The number of outages and the ouused to analyze and compare the unavailability oconverters. The mean cumulative function (MCF)analyze the number of outages and the unavailabthe forced outage rate (FOR) concept has been uoutage rates. The study shows that the outagesfailure occur at a constant rate by calendar timconverter stations, while very few stations havedecreasing rate. It has also been found that the stata higher number of outages and a higher outage ratcompared to the rotary converter types. The resultsthat combining the number of outages and the fgives a better view of the converters performasupport for the maintenance decision. In fact, usingdoes not reflect reality. Comparing these two indein identifying the areas where extra resources are maintenance planning and where improvementsoutage in the TPS system.KeywordsFrequency Converter, Forced OuCumulative Function, Traction Power Supply, ESystems.

Jobs Scheduling and Worker Assignment Problem to Minimize Makespan using Ant Colony Optimization Metaheuristic

This article proposes an Ant Colony Optimization (ACO) metaheuristic to minimize total makespan for scheduling a set of jobs and assign workers for uniformly related parallel machines. An algorithm based on ACO has been developed and coded on a computer program Matlab®, to solve this problem. The paper explains various steps to apply Ant Colony approach to the problem of minimizing makespan for the worker assignment & jobs scheduling problem in a parallel machine model and is aimed at evaluating the strength of ACO as compared to other conventional approaches. One data set containing 100 problems (12 Jobs, 03 machines and 10 workers) which is available on internet, has been taken and solved through this ACO algorithm. The results of our ACO based algorithm has shown drastically improved results, especially, in terms of negligible computational effort of CPU, to reach the optimal solution. In our case, the time taken to solve all 100 problems is even lesser than the average time taken to solve one problem in the data set by other conventional approaches like GA algorithm and SPT-A/LMC heuristics.

Increasing The Speed of Convergence of an Artificial Neural Network based ARMA Coefficients Determination Technique

In this paper, novel techniques in increasing the accuracy and speed of convergence of a Feed forward Back propagation Artificial Neural Network (FFBPNN) with polynomial activation function reported in literature is presented. These technique was subsequently used to determine the coefficients of Autoregressive Moving Average (ARMA) and Autoregressive (AR) system. The results obtained by introducing sequential and batch method of weight initialization, batch method of weight and coefficient update, adaptive momentum and learning rate technique gives more accurate result and significant reduction in convergence time when compared t the traditional method of back propagation algorithm, thereby making FFBPNN an appropriate technique for online ARMA coefficient determination.

Modeling of PZ in Haunch Connections Systems

Modeling of Panel Zone (PZ) seismic behavior, because of its role in overall ductility and lateral stiffness of steel moment frames, has been considered a challenge for years. There are some studies regarding the effects of different doubler plates thicknesses and geometric properties of PZ on its seismic behavior. However, there is not much investigation on the effects of number of provided continuity plates in case of presence of one triangular haunch, two triangular haunches and rectangular haunch (T shape haunches) for exterior columns. In this research first detailed finite element models of 12tested connection of SAC joint venture were created and analyzed then obtained cyclic behavior backbone curves of these models besides other FE models for similar tests were used for neural network training. Then seismic behavior of these data is categorized according to continuity plate-s arrangements and differences in type of haunches. PZ with one-sided haunches have little plastic rotation. As the number of continuity plates increases due to presence of two triangular haunches (four continuity plate), there will be no plastic rotation, in other words PZ behaves in its elastic range. In the case of rectangular haunch, PZ show more plastic rotation in comparison with one-sided triangular haunch and especially double-sided triangular haunches. Moreover, the models that will be presented in case of triangular one-sided and double- sided haunches and rectangular haunches as a result of this study seem to have a proper estimation of PZ seismic behavior.

Intention to Use Digital Library based on Modified UTAUT Model: Perspectives of Malaysian Postgraduate Students

Unified Theory of Acceptance and Use of Technology (UTAUT) model has demonstrated the influencing factors for generic information systems use such as tablet personal computer (TPC) and mobile communication. However, in the context of digital library system, there has been very little effort to determine factors affecting the intention to use digital library based on the UTAUT model. This paper investigates factors that are expected to influence the intention of postgraduate students to use digital library based on modified UTAUT model. The modified model comprises of constructs represented by several latent variables, namely performance expectancy (PE), effort expectancy (EE), information quality (IQ) and service quality (SQ) and moderated by age, gender and experience in using digital library. Results show that performance expectancy, effort expectancy and information quality are positively related to the intention to use digital library, while service quality is negatively related to the intention to use digital library. Age and gender have shown no evidence of any significant interactions, while experience in using digital library significantly interacts with effort expectancy and intention to use digital library. This has provided the evidence of a moderating effect of experience in the intention to use digital library. It is expected that this research will shed new lights into research of acceptance and intention to use the library in a digital environment.

Chattering-free Sliding Mode Control for an Active Magnetic Bearing System

In this paper, a few chattering-free Sliding Mode Controllers (SMC) are proposed to stabilize an Active Magnetic Bearing (AMB) system with gyroscopic effect that is proportional to the rotor speed. The improved switching terms of the controller inherited from the saturation-type function and boundary layer control technique is shown to be able to achieve bounded and asymptotic stability, respectively, while the chattering effect in the input is attenuated. This is proven to be advantageous for AMB system since minimization of chattering results in optimized control effort. The performance of each controller is demonstrated via result of simulation in which the measurement of the total consumed energy and maximum control magnitude of each controller illustrates the effectiveness of the proposed controllers.

Retina Based Mouse Control (RBMC)

The paper presents a novel idea to control computer mouse cursor movement with human eyes. In this paper, a working of the product has been described as to how it helps the special people share their knowledge with the world. Number of traditional techniques such as Head and Eye Movement Tracking Systems etc. exist for cursor control by making use of image processing in which light is the primary source. Electro-oculography (EOG) is a new technology to sense eye signals with which the mouse cursor can be controlled. The signals captured using sensors, are first amplified, then noise is removed and then digitized, before being transferred to PC for software interfacing.

The Household-Based Socio-Economic Index for Every District in Peninsular Malaysia

Deprivation indices are widely used in public health study. These indices are also referred as the index of inequalities or disadvantage. Even though, there are many indices that have been built before, it is believed to be less appropriate to use the existing indices to be applied in other countries or areas which had different socio-economic conditions and different geographical characteristics. The objective of this study is to construct the index based on the geographical and socio-economic factors in Peninsular Malaysia which is defined as the weighted household-based deprivation index. This study has employed the variables based on household items, household facilities, school attendance and education level obtained from Malaysia 2000 census report. The factor analysis is used to extract the latent variables from indicators, or reducing the observable variable into smaller amount of components or factor. Based on the factor analysis, two extracted factors were selected, known as Basic Household Amenities and Middle-Class Household Item factor. It is observed that the district with a lower index values are located in the less developed states like Kelantan, Terengganu and Kedah. Meanwhile, the areas with high index values are located in developed states such as Pulau Pinang, W.P. Kuala Lumpur and Selangor.

Toxicity of Copper and Cadmium to Freshwater Fishes

Two freshwater fishes, Rasbora sumatrana (Cyprinidae) and Poecilia reticulata (guppy) (Poeciliidae) were exposed for a four-day period in the laboratory condition to a range of copper (Cu) and cadmium (Cd) concentrations. Mortality was assessed and median lethal concentrations (LC50) were calculated. LC50 increased with decrease in mean exposure times for both metals. For R. sumatrana, LC50s for 24, 48, 72 and 96 hours for Cu were 54.2, 30.3, 18.9 and 5.6 μg/L and for Cd 1440.2, 459.3, 392.3 and 101.6 μg/L respectively. For P. reticulata, LC50s for 24, 48, 72 and 96 hours for Cu were 348.9, 145.4, 61.3 and 37.9 μg/L and for Cd 8205.6, 2827.1, 405.8 and 168.1 μg/L, respectively. Results indicated that the Cu was more toxic than Cd to both fishes (Cu>Cd) and R. sumatrana was more sensitive than P. reticulata to the metals.

Improving RBF Networks Classification Performance by using K-Harmonic Means

In this paper, a clustering algorithm named KHarmonic means (KHM) was employed in the training of Radial Basis Function Networks (RBFNs). KHM organized the data in clusters and determined the centres of the basis function. The popular clustering algorithms, namely K-means (KM) and Fuzzy c-means (FCM), are highly dependent on the initial identification of elements that represent the cluster well. In KHM, the problem can be avoided. This leads to improvement in the classification performance when compared to other clustering algorithms. A comparison of the classification accuracy was performed between KM, FCM and KHM. The classification performance is based on the benchmark data sets: Iris Plant, Diabetes and Breast Cancer. RBFN training with the KHM algorithm shows better accuracy in classification problem.

Improvement of Stator Slot Structure based on Electro-Thermal Analysis in HV Generator

High voltage generators are being subject to higher voltage rating and are being designed to operate in harsh conditions. Stator windings are the main component of generators in which Electrical, magnetically and thermal stresses remain major failures for insulation degradation accelerated aging. A large number of generators failed due to stator winding problems, mainly insulation deterioration. Insulation degradation assessment plays vital role in the asset life management. Mostly the stator failure is catastrophic causing significant damage to the plant. Other than generation loss, stator failure involves heavy repair or replacement cost. Electro thermal analysis is the main characteristic for improvement design of stator slot-s insulation. Dielectric parameters such as insulation thickness, spacing, material types, geometry of winding and slot are major design consideration. A very powerful method available to analyze electro thermal performance is Finite Element Method (FEM) which is used in this paper. The analysis of various stator coil and slot configurations are used to design the better dielectric system to reduce electrical and thermal stresses in order to increase the power of generator in the same volume of core. This paper describes the process used to perform classical design and improvement analysis of stator slot-s insulation.

Evaluation Biofilm Sewage Treatment Plant

The research study is carried out to determine the efficiency of the Biofilm sewage treatment plant which is located at the Engineering Complex-s. Wastewater analyses have been carried out at the Environmental Engineering laboratory to study the six parameters: Biochemical Oxygen Demand BOD, Chemical Oxygen Demand COD l, and Total Suspended Solids TSS, Ammoniac Nitrogen NH3-N and Phosphorous P which have been selected to determine the wastewater quality. The plant was designed to treat 750 Pe (population equivalent) at hydraulic retention time of 5 hours in the aerobic zone. The results show that Biofilm wastewater treatment plant was able to treat sewage successfully at different flow condition. The discharge has fulfilled the Malaysia Environmental of Standard A water quality. The achieved BOD removal is more than 85%, COD is more than 80%, TSS is more than 80%, NH3-N is more than 70%, and P was more than 70%. The Biofilm system provides a very efficient process for sewage treatment and it is compact in structure thus minimizes the required land area.