Key Success Factors for Managing Projects

The use and management of projects has risen to a new prominence, with projects seen as critical to economic in both the private and public sectors due challenging and dynamic business environment. However, failure in managing project is encountered regularly, which cause the waste of company resources. The impacts of projects that failed to meet stakeholders expectations have left behind long lasting negative consequences in organization. Therefore, this research aims to investigate on key success factors of project management in an organization. It is believed that recognizing important factors that contribute to successful project will help companies to increase the overall profitability. 150 questionnaires were distributed to respondents and 110 questionnaires were collected and used in performing the data analysis. The result has strongly supported the relationship between independent variables and project performance.

The Design of PIP Controller for a Thermal System with Large Time Delay

This paper will first describe predictor controllers when the proportional-integral-derivative (PID) controllers are inactive for procedures that have large delay time (LDT) in transfer stage. Therefore in those states, the predictor controllers are better than the PID controllers, then compares three types of predictor controllers. The value of these controller-s parameters are obtained by trial and error method, so here an effort has been made to obtain these parameters by Ziegler-Nichols method. Eventually in this paper Ziegler-Nichols method has been described and finally, a PIP controller has been designed for a thermal system, which circulates hot air to keep the temperature of a chamber constant.

Multi Switched Split Vector Quantizer

Vector quantization is a powerful tool for speech coding applications. This paper deals with LPC Coding of speech signals which uses a new technique called Multi Switched Split Vector Quantization, This is a hybrid of two product code vector quantization techniques namely the Multi stage vector quantization technique, and Switched split vector quantization technique,. Multi Switched Split Vector Quantization technique quantizes the linear predictive coefficients in terms of line spectral frequencies. From results it is proved that Multi Switched Split Vector Quantization provides better trade off between bitrate and spectral distortion performance, computational complexity and memory requirements when compared to Switched Split Vector Quantization, Multi stage vector quantization, and Split Vector Quantization techniques. By employing the switching technique at each stage of the vector quantizer the spectral distortion, computational complexity and memory requirements were greatly reduced. Spectral distortion was measured in dB, Computational complexity was measured in floating point operations (flops), and memory requirements was measured in (floats).

The Investigation of 5th Grade Turkish Students- Comprehension Scores According to Different Variables

The aim of this study is to examine the reading comprehension scores of Turkish 5th grade students according to the variables given in the student questionnaire. In this descriptive survey study research participated 279 5th grade students, who studied at 10 different primary schools in four provinces of Ankara in 2008-2009 academic year. Two different data collection tools were made use of in the study: “Reading Comprehension Test" and “Student Information Questionnaire". Independent sample t-test, oneway Anova and two-way Anova tests were used in the analyses of the gathered data. The results of the study indicate that the reading comprehension scores of the students differ significantly according to sex of the students, the number of books in their houses, the frequency of summarizing activities on the reading text of free and the frequency reading hours provided by their teachers; but, differ not significantly according to educational level of their mothers and fathers.

Development of Maximum Entropy Method for Prediction of Droplet-size Distribution in Primary Breakup Region of Spray

Droplet size distributions in the cold spray of a fuel are important in observed combustion behavior. Specification of droplet size and velocity distributions in the immediate downstream of injectors is also essential as boundary conditions for advanced computational fluid dynamics (CFD) and two-phase spray transport calculations. This paper describes the development of a new model to be incorporated into maximum entropy principle (MEP) formalism for prediction of droplet size distribution in droplet formation region. The MEP approach can predict the most likely droplet size and velocity distributions under a set of constraints expressing the available information related to the distribution. In this article, by considering the mechanisms of turbulence generation inside the nozzle and wave growth on jet surface, it is attempted to provide a logical framework coupling the flow inside the nozzle to the resulting atomization process. The purpose of this paper is to describe the formulation of this new model and to incorporate it into the maximum entropy principle (MEP) by coupling sub-models together using source terms of momentum and energy. Comparison between the model prediction and experimental data for a gas turbine swirling nozzle and an annular spray indicate good agreement between model and experiment.

SeqWord Gene Island Sniffer: a Program to Study the Lateral Genetic Exchange among Bacteria

SeqWord Gene Island Sniffer, a new program for the identification of mobile genetic elements in sequences of bacterial chromosomes is presented. This program is based on the analysis of oligonucleotide usage variations in DNA sequences. 3,518 mobile genetic elements were identified in 637 bacterial genomes and further analyzed by sequence similarity and the functionality of encoded proteins. The results of this study are stored in an open database http://anjie.bi.up.ac.za/geidb/geidbhome. php). The developed computer program and the database provide the information valuable for further investigation of the distribution of mobile genetic elements and virulence factors among bacteria. The program is available for download at www.bi.up.ac.za/SeqWord/sniffer/index.html.

Modeling and Simulation of a Hybrid Scooter

This paper presents a hybrid electric scooter model developed and simulated using Matlab/Simulink. This hybrid scooter modeled has a parallel hybrid structure. The main propulsion units consist of a two stroke internal combustion engine and a hub motor attached to the front wheel of the scooter. The methodology used to optimize the energy and fuel consumption of the hybrid electric scooter is the multi-mode approach. Various case studies were presented to check the model and were compared to the literatures. Results shown that the model developed was feasible and valuable.

SySRA: A System of a Continuous Speech Recognition in Arab Language

We report in this paper the model adopted by our system of continuous speech recognition in Arab language SySRA and the results obtained until now. This system uses the database Arabdic-10 which is a corpus of word for the Arab language and which was manually segmented. Phonetic decoding is represented by an expert system where the knowledge base is translated in the form of production rules. This expert system transforms a vocal signal into a phonetic lattice. The higher level of the system takes care of the recognition of the lattice thus obtained by deferring it in the form of written sentences (orthographical Form). This level contains initially the lexical analyzer which is not other than the module of recognition. We subjected this analyzer to a set of spectrograms obtained by dictating a score of sentences in Arab language. The rate of recognition of these sentences is about 70% which is, to our knowledge, the best result for the recognition of the Arab language. The test set consists of twenty sentences from four speakers not having taken part in the training.

Requirements Management in a Distributed Agile Environment

The importance of good requirements engineering is well documented. Agile practices, promoting collaboration and communications, facilitate the elicitation and management of volatile requirements. However, current Agile practices work in a well-defined environment. It is necessary to have a co-located customer. With distributed development it is not always possible to realize this co-location. In this environment a suitable process, possibly supported by tools, is required to support changing requirements. This paper introduces the issues of concern when managing requirements in a distributed environment and describes work done at the Software Technology Research Centre as part of the NOMAD project.

A Note on Penalized Power-Divergence Test Statistics

In this paper, penalized power-divergence test statistics have been defined and their exact size properties to test a nested sequence of log-linear models have been compared with ordinary power-divergence test statistics for various penalization, λ and main effect values. Since the ordinary and penalized power-divergence test statistics have the same asymptotic distribution, comparisons have been only made for small and moderate samples. Three-way contingency tables distributed according to a multinomial distribution have been considered. Simulation results reveal that penalized power-divergence test statistics perform much better than their ordinary counterparts.

Image Segmentation Using the K-means Algorithm for Texture Features

This study aims to segment objects using the K-means algorithm for texture features. Firstly, the algorithm transforms color images into gray images. This paper describes a novel technique for the extraction of texture features in an image. Then, in a group of similar features, objects and backgrounds are differentiated by using the K-means algorithm. Finally, this paper proposes a new object segmentation algorithm using the morphological technique. The experiments described include the segmentation of single and multiple objects featured in this paper. The region of an object can be accurately segmented out. The results can help to perform image retrieval and analyze features of an object, as are shown in this paper.

A Semi-Fragile Signature based Scheme for Ownership Identification and Color Image Authentication

In this paper, a novel scheme is proposed for ownership identification and authentication using color images by deploying Cryptography and Digital Watermarking as underlaying technologies. The former is used to compute the contents based hash and the latter to embed the watermark. The host image that will claim to be the rightful owner is first transformed from RGB to YST color space exclusively designed for watermarking based applications. Geometrically YS ÔèÑ T and T channel corresponds to the chrominance component of color image, therefore suitable for embedding the watermark. The T channel is divided into 4×4 nonoverlapping blocks. The size of block is important for enhanced localization, security and low computation. Each block along with ownership information is then deployed by SHA160, a one way hash function to compute the content based hash, which is always unique and resistant against birthday attack instead of using MD5 that may raise the condition i.e. H(m)=H(m'). The watermark payload varies from block to block and computed by the variance factorα . The quality of watermarked images is quite high both subjectively and objectively. Our scheme is blind, computationally fast and exactly locates the tampered region.

The Impact of Social Stratification to the Phenomenon of “Terrorism“

In this work social stratification is considered as one of significant factor which generate the phenomena “terrorism” and it puts the accent on correlation connection between them, with the object of creation info-logical model generation of phenomena of “terrorism” based on stratification process.

Effects of pH, Temperature, Enzyme and Substrate Concentration on Xylooligosaccharides Production

Agricultural residue such as oil palm fronds (OPF) is cheap, widespread and available throughout the year. Hemicelluloses extracted from OPF can be hydrolyzed to their monomers and used in production of xylooligosaccharides (XOs). The objective of the present study was to optimize the enzymatic hydrolysis process of OPF hemicellulose by varying pH, temperature, enzyme and substrate concentration for production of XOs. Hemicelluloses was extracted from OPF by using 3 M potassium hydroxide (KOH) at temperature of 40°C for 4 hrs and stirred at 400 rpm. The hemicellulose was then hydrolyzed using Trichoderma longibrachiatum xylanase at different pH, temperature, enzyme and substrate concentration. XOs were characterized based on reducing sugar determination. The optimum conditions to produced XOs from OPF hemicellulose was obtained at pH 4.6, temperature of 40°C , enzyme concentration of 2 U/mL and 2% substrate concentration. The results established the suitability of oil palm fronds as raw material for production of XOs.

Assessment of Sediment Quality in the West Port Based On the Index Analysis Approach

The coastal sediments of West Port of Malaysia was monitored from Nov. 2009 to Oct. 2010 to assess spatial distribution of heavy metals As, Cu, Cd, Cr, Hg, Ni, Zn and Pb. Sediment samples were collected from 10 stations in dry and rainy season in West Port. The range concentrations measured (Mg/g dry weight ) were from 23.4 to 98.3 for Zn, 22.3 to 80 for Pb, 7.4 to 27.6 Cu, 0.244 to 3.53 for Cd, 7.2 to 22.2 for Ni, 20.2 to 162 for As, 0.11 to 0.409 for Hg and 11.5 to 61.5 for Cr. The geochemical indexes used in this study were Geoaccumulation (Igeo), Contamination Factor (CF) and Pollution Load Index (PLI); these indexes were used to evaluate the levels of sediment contaminations. The results of these indexes show that, the status of West Port sediment quality are moderately polluted by heavy metals except in arsenic which shows the high level of pollution.

Performance Evaluation of AOMDV-PAMAC Protocols for Ad Hoc Networks

Power consumption of nodes in ad hoc networks is a critical issue as they predominantly operate on batteries. In order to improve the lifetime of an ad hoc network, all the nodes must be utilized evenly and the power required for connections must be minimized. In this project a link layer algorithm known as Power Aware medium Access Control (PAMAC) protocol is proposed which enables the network layer to select a route with minimum total power requirement among the possible routes between a source and a destination provided all nodes in the routes have battery capacity above a threshold. When the battery capacity goes below a predefined threshold, routes going through these nodes will be avoided and these nodes will act only as source and destination. Further, the first few nodes whose battery power drained to the set threshold value are pushed to the exterior part of the network and the nodes in the exterior are brought to the interior. Since less total power is required to forward packets for each connection. The network layer protocol AOMDV is basically an extension to the AODV routing protocol. AOMDV is designed to form multiple routes to the destination and it also avoid the loop formation so that it reduces the unnecessary congestion to the channel. In this project, the performance of AOMDV is evaluated using PAMAC as a MAC layer protocol and the average power consumption, throughput and average end to end delay of the network are calculated and the results are compared with that of the other network layer protocol AODV.

Dynamic Bayesian Networks Modeling for Inferring Genetic Regulatory Networks by Search Strategy: Comparison between Greedy Hill Climbing and MCMC Methods

Using Dynamic Bayesian Networks (DBN) to model genetic regulatory networks from gene expression data is one of the major paradigms for inferring the interactions among genes. Averaging a collection of models for predicting network is desired, rather than relying on a single high scoring model. In this paper, two kinds of model searching approaches are compared, which are Greedy hill-climbing Search with Restarts (GSR) and Markov Chain Monte Carlo (MCMC) methods. The GSR is preferred in many papers, but there is no such comparison study about which one is better for DBN models. Different types of experiments have been carried out to try to give a benchmark test to these approaches. Our experimental results demonstrated that on average the MCMC methods outperform the GSR in accuracy of predicted network, and having the comparable performance in time efficiency. By proposing the different variations of MCMC and employing simulated annealing strategy, the MCMC methods become more efficient and stable. Apart from comparisons between these approaches, another objective of this study is to investigate the feasibility of using DBN modeling approaches for inferring gene networks from few snapshots of high dimensional gene profiles. Through synthetic data experiments as well as systematic data experiments, the experimental results revealed how the performances of these approaches can be influenced as the target gene network varies in the network size, data size, as well as system complexity.

Improvement of Passengers Ride Comfort in Rail Vehicles Equipped with Air Springs

In rail vehicles, air springs are very important isolating component, which guarantee good ride comfort for passengers during their trip. In the most new rail–vehicle models, developed by researchers, the thermo–dynamical effects of air springs are ignored and secondary suspension is modeled by simple springs and dampers. As the performance of suspension components have significant effects on rail–vehicle dynamics and ride comfort of passengers, a complete nonlinear thermo–dynamical air spring model, which is a combination of two different models, is introduced. Result from field test shows remarkable agreement between proposed model and experimental data. Effects of air suspension parameters on the system performances are investigated here and then these parameters are tuned to minimize Sperling ride comfort index during the trip. Results showed that by modification of air suspension parameters, passengers comfort is improved and ride comfort index is reduced about 10%.

A New Framework for Evaluation and Prioritization of Suppliers using a Hierarchical Fuzzy TOPSIS

This paper suggests an algorithm for the evaluation and selection of suppliers. At the beginning, all the needed materials and services used by the organization were identified and categorized with regard to their nature by ABC method. Afterwards, in order to reduce risk factors and maximize the organization's profit, purchase strategies were determined. Then, appropriate criteria were identified for primary evaluation of suppliers applying to the organization. The output of this stage was a list of suppliers qualified by the organization to participate in its tenders. Subsequently, considering a material in particular, appropriate criteria on the ordering of the mentioned material were determined, taking into account the particular materials' specifications as well as the organization's needs. Finally, for the purpose of validation and verification of the proposed model, it was applied to Mobarakeh Steel Company (MSC), the qualified suppliers of this Company are ranked by the means of a Hierarchical Fuzzy TOPSIS method. The obtained results show that the proposed algorithm is quite effective, efficient and easy to apply.

Influence of Combined Drill Coulters on Seedbed Compaction under Conservation Tillage Technologies

All over the world, including the Middle and East European countries, sustainable tillage and sowing technologies are applied increasingly broadly with a view to optimising soil resources, mitigating soil degradation processes, saving energy resources, preserving biological diversity, etc. As a result, altered conditions of tillage and sowing technological processes are faced inevitably. The purpose of this study is to determine the seedbed topsoil hardness when using a combined sowing coulter in different sustainable tillage technologies. The research involved a combined coulter consisting of two dissected blade discs and a shoe coulter. In order to determine soil hardness at the seedbed area, a multipenetrometer was used. It was found by experimental studies that in loosened soil, a combined sowing coulter equally suppresses the furrow bottom, walls and soil near the furrow; therefore, here, soil hardness was similar at all researched depths and no significant differences were established. In loosened and compacted (double-rolled) soil, the impact of a combined coulter on the hardness of seedbed soil surface was more considerable at a depth of 2 mm. Soil hardness at the furrow bottom and walls to a distance of up to 26 mm was 1.1 MPa. At a depth of 10 mm, the greatest hardness was established at the furrow bottom. In loosened and heavily compacted (rolled for 6 times) soil, at a depth of 2 and 10 mm a combined coulter most of all compacted the furrow bottom, which has a hardness of 1.8 MPa. At a depth of 20 mm, soil hardness within the whole investigated area varied insignificantly and fluctuated by around 2.0 MPa. The hardness of furrow walls and soil near the furrow was by approximately 1.0 MPa lower than that at the furrow bottom