Solving Inhomogeneous Wave Equation Cauchy Problems using Homotopy Perturbation Method

In this paper, He-s homotopy perturbation method (HPM) is applied to spatial one and three spatial dimensional inhomogeneous wave equation Cauchy problems for obtaining exact solutions. HPM is used for analytic handling of these equations. The results reveal that the HPM is a very effective, convenient and quite accurate to such types of partial differential equations (PDEs).

An Analytical Electron Mobility Model based on Particle Swarm Computation for Siliconbased Devices

The study of the transport coefficients in electronic devices is currently carried out by analytical and empirical models. This study requires several simplifying assumptions, generally necessary to lead to analytical expressions in order to study the different characteristics of the electronic silicon-based devices. Further progress in the development, design and optimization of Silicon-based devices necessarily requires new theory and modeling tools. In our study, we use the PSO (Particle Swarm Optimization) technique as a computational tool to develop analytical approaches in order to study the transport phenomenon of the electron in crystalline silicon as function of temperature and doping concentration. Good agreement between our results and measured data has been found. The optimized analytical models can also be incorporated into the circuits simulators to study Si-based devices without impact on the computational time and data storage.

Design of a DCT-based Image Compression with Efficient Enhancement Filter

The algorithm represents the DCT coefficients to concentrate signal energy and proposes combination and dictator to eliminate the correlation in the same level subband for encoding the DCT-based images. This work adopts DCT and modifies the SPIHT algorithm to encode DCT coefficients. The proposed algorithm also provides the enhancement function in low bit rate in order to improve the perceptual quality. Experimental results indicate that the proposed technique improves the quality of the reconstructed image in terms of both PSNR and the perceptual results close to JPEG2000 at the same bit rate.

Towards Development of Solution for Business Process-Oriented Data Analysis

This paper proposes a modeling methodology for the development of data analysis solution. The Author introduce the approach to address data warehousing issues at the at enterprise level. The methodology covers the process of the requirements eliciting and analysis stage as well as initial design of data warehouse. The paper reviews extended business process model, which satisfy the needs of data warehouse development. The Author considers that the use of business process models is necessary, as it reflects both enterprise information systems and business functions, which are important for data analysis. The Described approach divides development into three steps with different detailed elaboration of models. The Described approach gives possibility to gather requirements and display them to business users in easy manner.

Neural Network Based Approach for Face Detection cum Face Recognition

Automatic face detection is a complex problem in image processing. Many methods exist to solve this problem such as template matching, Fisher Linear Discriminate, Neural Networks, SVM, and MRC. Success has been achieved with each method to varying degrees and complexities. In proposed algorithm we used upright, frontal faces for single gray scale images with decent resolution and under good lighting condition. In the field of face recognition technique the single face is matched with single face from the training dataset. The author proposed a neural network based face detection algorithm from the photographs as well as if any test data appears it check from the online scanned training dataset. Experimental result shows that the algorithm detected up to 95% accuracy for any image.

Enhancing Cache Performance Based on Improved Average Access Time

A high performance computer includes a fast processor and millions bytes of memory. During the data processing, huge amount of information are shuffled between the memory and processor. Because of its small size and its effectiveness speed, cache has become a common feature of high performance computers. Enhancing cache performance proved to be essential in the speed up of cache-based computers. Most enhancement approaches can be classified as either software based or hardware controlled. The performance of the cache is quantified in terms of hit ratio or miss ratio. In this paper, we are optimizing the cache performance based on enhancing the cache hit ratio. The optimum cache performance is obtained by focusing on the cache hardware modification in the way to make a quick rejection to the missed line's tags from the hit-or miss comparison stage, and thus a low hit time for the wanted line in the cache is achieved. In the proposed technique which we called Even- Odd Tabulation (EOT), the cache lines come from the main memory into cache are classified in two types; even line's tags and odd line's tags depending on their Least Significant Bit (LSB). This division is exploited by EOT technique to reject the miss match line's tags in very low time compared to the time spent by the main comparator in the cache, giving an optimum hitting time for the wanted cache line. The high performance of EOT technique against the familiar mapping technique FAM is shown in the simulated results.

Promoting Mental and Spiritual Health among Postpartum Mothers to Extend Breastfeeding Period

The purpose of this study was to study postpartum breastfeeding mothers to determine the impact their psychosocial and spiritual dimensions play in promoting full-term (6 month duration) breastfeeding of their infants. Purposive and snowball sampling methods were used to identify and recruit the study's participants. A total of 23 postpartum mothers, who were breastfeeding within 6 weeks after giving birth, participated in this study. In-depth interviews combined with observations, participant focus groups, and ethnographic records were used for data collection. The Data were then analyzed using content analysis and typology. The results of this study illustrated that postpartum mothers experienced fear and worry that they would lack support from their spouse, family and peers, and that their infant would not get enough milk It was found that the main barrier mothers faced in breastfeeding to full-term was the difficulty of continuing to breastfeed when returning to work. 81.82% of the primiparous mothers and 91.67% of the non-primiparous mothers were able to breastfeed for the desired full-term of 6 months. Factors found to be related to breastfeeding for six months included 1) belief and faith in breastfeeding, 2) support from spouse and family members, 3) counseling from public health nurses and friends. The sample also provided evidence that religious principles such as tolerance, effort, love, and compassion to their infant, and positive thinking, were used in solving their physical, mental and spiritual problems.

Matching Current Search with Future Postings

Online trading is an alternative to conventional shopping method. People trade goods which are new or pre-owned before. However, there are times when a user is not able to search the items wanted online. This is because the items may not be posted as yet, thus ending the search. Conventional search mechanism only works by searching and matching search criteria (requirement) with data available in a particular database. This research aims to match current search requirements with future postings. This would involve the time factor in the conventional search method. A Car Matching Alert System (CMAS) prototype was developed to test the matching algorithm. When a buyer-s search returns no result, the system saves the search and the buyer will be alerted if there is a match found based on future postings. The algorithm developed is useful and as it can be applied in other search context.

An Interval-Based Multi-Attribute Decision Making Approach for Electric Utility Resource Planning

This paper presents an interval-based multi-attribute decision making (MADM) approach in support of the decision process with imprecise information. The proposed decision methodology is based on the model of linear additive utility function but extends the problem formulation with the measure of composite utility variance. A sample study concerning with the evaluation of electric generation expansion strategies is provided showing how the imprecise data may affect the choice toward the best solution and how a set of alternatives, acceptable to the decision maker (DM), may be identified with certain confidence.

On the Dynamic Behaviour of a Four-Bar Linkage Driven by a Velocity Controlled DC Motor

The dynamic behaviour of a four-bar linkage driven by a velocity controlled DC motor is discussed in the paper. In particular the author presents the results obtained by means of a specifically developed software, which implements the mathematical models of all components of the system (linkage, transmission, electric motor, control devices). The use of this software enables a more efficient design approach, since it allows the designer to check, in a simple and immediate way, the dynamic behaviour of the mechanism, arising from different values of the system parameters.

An Effective Hybrid Genetic Algorithm for Job Shop Scheduling Problem

The job shop scheduling problem (JSSP) is well known as one of the most difficult combinatorial optimization problems. This paper presents a hybrid genetic algorithm for the JSSP with the objective of minimizing makespan. The efficiency of the genetic algorithm is enhanced by integrating it with a local search method. The chromosome representation of the problem is based on operations. Schedules are constructed using a procedure that generates full active schedules. In each generation, a local search heuristic based on Nowicki and Smutnicki-s neighborhood is applied to improve the solutions. The approach is tested on a set of standard instances taken from the literature and compared with other approaches. The computation results validate the effectiveness of the proposed algorithm.

Improvement in Performance and Emission Characteristics of a Single Cylinder S.I. Engine Operated on Blends of CNG and Hydrogen

This paper presents the experimental results of a single cylinder Enfield engine using an electronically controlled fuel injection system which was developed to carry out exhaustive tests using neat CNG, and mixtures of hydrogen in compressed natural gas (HCNG) as 0, 5, 10, 15 and 20% by energy. Experiments were performed at 2000 and 2400 rpm with wide open throttle and varying the equivalence ratio. Hydrogen which has fast burning rate, when added to compressed natural gas, enhances its flame propagation rate. The emissions of HC, CO, decreased with increasing percentage of hydrogen but NOx was found to increase. The results indicated a marked improvement in the brake thermal efficiency with the increase in percentage of hydrogen added. The improved thermal efficiency was clearly observed to be more in lean region as compared to rich region. This study is expected to reduce vehicular emissions along with increase in thermal efficiency and thus help in reduction of further environmental degradation.

Image Segmentation Based on Graph Theoretical Approach to Improve the Quality of Image Segmentation

Graph based image segmentation techniques are considered to be one of the most efficient segmentation techniques which are mainly used as time & space efficient methods for real time applications. How ever, there is need to focus on improving the quality of segmented images obtained from the earlier graph based methods. This paper proposes an improvement to the graph based image segmentation methods already described in the literature. We contribute to the existing method by proposing the use of a weighted Euclidean distance to calculate the edge weight which is the key element in building the graph. We also propose a slight modification of the segmentation method already described in the literature, which results in selection of more prominent edges in the graph. The experimental results show the improvement in the segmentation quality as compared to the methods that already exist, with a slight compromise in efficiency.

Learning Style and Learner Satisfaction in a Course Delivery Context

This paper describes the results and implications of a correlational study of learning styles and learner satisfaction. The relationship of these empirical concepts was examined in the context of traditional versus e-blended modes of course delivery in an introductory graduate research course. Significant results indicated that the visual side of the visual-verbal dimension of students- learning style(s) was positively correlated to satisfaction with themselves as learners in an e-blended course delivery mode and negatively correlated to satisfaction with the classroom environment in the context of a traditional classroom course delivery mode.

Decomposition Method for Neural Multiclass Classification Problem

In this article we are going to discuss the improvement of the multi classes- classification problem using multi layer Perceptron. The considered approach consists in breaking down the n-class problem into two-classes- subproblems. The training of each two-class subproblem is made independently; as for the phase of test, we are going to confront a vector that we want to classify to all two classes- models, the elected class will be the strongest one that won-t lose any competition with the other classes. Rates of recognition gotten with the multi class-s approach by two-class-s decomposition are clearly better that those gotten by the simple multi class-s approach.

Design and Implementation of TMS320C31 DSP and FPGA for Conventional Direct Torque Control (DTC) of Induction Machines

This paper introduces a new digital logic design, which combines the DSP and FPGA to implement the conventional DTC of induction machine. The DSP will be used for floating point calculation whereas the FPGA main task is to implement the hysteresis-based controller. The emphasis is on FPGA digital logic design. The simulation and experimental results are presented and summarized.

Identifying the Objectives of Outsourcing Logistics Services as a Basis for Measuring Its Financial and Operational Performance

Logistics outsourcing is a growing trend and measuring its performance, a challenge. It must be consistent with the objectives set for logistics outsourcing, but we have found no objective-based performance measurement system. We have conducted a comprehensive review of the specialist literature to cover this gap, which has led us to identify and define these objectives. The outcome is that we have obtained a list of the most relevant objectives and their descriptions. This will enable us to analyse in a future study whether the indicators used for measuring logistics outsourcing performance are consistent with the objectives pursued with the outsourcing. If this is not the case, a proposal will be made for a set of financial and operational indicators to measure performance in logistics outsourcing that take the goals being pursued into account.

Modified Fast and Exact Algorithm for Fast Haar Transform

Wavelet transform or wavelet analysis is a recently developed mathematical tool in applied mathematics. In numerical analysis, wavelets also serve as a Galerkin basis to solve partial differential equations. Haar transform or Haar wavelet transform has been used as a simplest and earliest example for orthonormal wavelet transform. Since its popularity in wavelet analysis, there are several definitions and various generalizations or algorithms for calculating Haar transform. Fast Haar transform, FHT, is one of the algorithms which can reduce the tedious calculation works in Haar transform. In this paper, we present a modified fast and exact algorithm for FHT, namely Modified Fast Haar Transform, MFHT. The algorithm or procedure proposed allows certain calculation in the process decomposition be ignored without affecting the results.

A 1.8 V RF CMOS Active Inductor with 0.18 um CMOS Technology

A active inductor in CMOS techonology with a supply voltage of 1.8V is presented. The value of the inductance L can be in the range from 0.12nH to 0.25nH in high frequency(HF). The proposed active inductor is designed in TSMC 0.18-um CMOS technology. The power dissipation of this inductor can retain constant at all operating frequency bands and consume around 20mW from 1.8V power supply. Inductors designed by integrated circuit occupy much smaller area, for this reason,attracted researchers attention for more than decade. In this design we used Advanced Designed System (ADS) for simulating cicuit.

Study of Effect of Removal of Shiftrows and Mixcolumns Stages of AES and AES-KDS on their Encryption Quality and Hence Security

This paper demonstrates the results when either Shiftrows stage or Mixcolumns stage and when both the stages are omitted in the well known block cipher Advanced Encryption Standard(AES) and its modified version AES with Key Dependent S-box(AES-KDS), using avalanche criterion and other tests namely encryption quality, correlation coefficient, histogram analysis and key sensitivity tests.