BPR Effect on ERP Implementation: a Comparative Case Study

Business Process Reengineering (BPR) is an essential tool before an information system project implementation. Enterprise Resource Planning (ERP) projects definitely require the standardization and fixation of business processes from customer order to shipment. Therefore, ERP implementations are well proven to be coupled with BPR, although the extend and timing of BPR with respect to ERP implementation differ. This study aims at analyzing the effects of BPR on ERP implementation success. Basing on two Turkish ERP implementations in pharmaceutical sector, a comparative study is performed. One of the ERP implementations took place after a BPR implementation, whereas the other implementation was without a prior BPR application. Both implementations have been realized with the same consultant team, the case with prior BPR implementation going live first. The results of the case study reveal that if business processes are not optimized and improved before an ERP implementation, ERP live system would face with disharmony problems of processes and processes automated by ERP. This suggests a definite precedence relationship between BPR and ERP applications

An eighth order Backward Differentiation Formula with Continuous Coefficients for Stiff Ordinary Differential Equations

A block backward differentiation formula of uniform order eight is proposed for solving first order stiff initial value problems (IVPs). The conventional 8-step Backward Differentiation Formula (BDF) and additional methods are obtained from the same continuous scheme and assembled into a block matrix equation which is applied to provide the solutions of IVPs on non-overlapping intervals. The stability analysis of the method indicates that the method is L0-stable. Numerical results obtained using the proposed new block form show that it is attractive for solutions of stiff problems and compares favourably with existing ones.

An Accurate Computation of Block Hybrid Method for Solving Stiff Ordinary Differential Equations

In this paper, self-starting block hybrid method of order (5,5,5,5)T is proposed for the solution of the special second order ordinary differential equations with associated initial or boundary conditions. The continuous hybrid formulations enable us to differentiate and evaluate at some grids and off – grid points to obtain four discrete schemes, which were used in block form for parallel or sequential solutions of the problems. The computational burden and computer time wastage involved in the usual reduction of second order problem into system of first order equations are avoided by this approach. Furthermore, a stability analysis and efficiency of the block method are tested on stiff ordinary differential equations, and the results obtained compared favorably with the exact solution.

Statistical Study of Drink Markets: Case Study

An important official knowledge in each country is to have a comprehensive knowledge about markets of each group of products. Drink markets are one the most important markets of each country as a sub-group of nourishment markets. This paper is going to study these markets in Iran. To do so, first, two drink products are selected as pilot, including milk and concentrate. Then, for each product, two groups of information are estimated for the last five years, including 1) total consumption (demand) and 2) total production. Finally, the two groups of productions are compared statistically by means of two statistical tests called t test and Mann- Whitney test. The implemented Different related tables and figures are also illustrated to show the method more explicitly.

Multivalued Knowledge-Base based on Multivalued Datalog

The basic aim of our study is to give a possible model for handling uncertain information. This model is worked out in the framework of DATALOG. The concept of multivalued knowledgebase will be defined as a quadruple of any background knowledge; a deduction mechanism; a connecting algorithm, and a function set of the program, which help us to determine the uncertainty levels of the results. At first the concept of fuzzy Datalog will be summarized, then its extensions for intuitionistic- and interval-valued fuzzy logic is given and the concept of bipolar fuzzy Datalog is introduced. Based on these extensions the concept of multivalued knowledge-base will be defined. This knowledge-base can be a possible background of a future agent-model.

Attachment Styles of Children Raised in Nursery vs. Those Who are Raised in the Family in Iran

In studies on psychological health and children-s personality development and in researches on emotional distresses, children-s behavioral disorders associated with mother deprivation, are known as the major cause of mental disorders. Therefore, for identification of children-s attachment styles in nursery-s children are of significant importance. For this purpose, to compare the attachment styles between children of nursery with those provided care by their families, the Separation Anxiety Test (SAT) of Slough and et al was administered on 72 children (36 in nursery and 36 family-cared). The results indicated, almost half of children in both groups have insecure attachment styles. Tendency ratio of both groups of children towards Secure and Ambivalent Insecure styles are almost the same. However the avoidant style of attachment in children of nursery is more than those provided care by their families. The children under family care compared to the children of nursery, in the situations of separation from their mothers in the first day of school and sleeping in their room, have shown more self reliance.

Stochastic Subspace Modelling of Turbulence

Turbulence of the incoming wind field is of paramount importance to the dynamic response of civil engineering structures. Hence reliable stochastic models of the turbulence should be available from which time series can be generated for dynamic response and structural safety analysis. In the paper an empirical cross spectral density function for the along-wind turbulence component over the wind field area is taken as the starting point. The spectrum is spatially discretized in terms of a Hermitian cross-spectral density matrix for the turbulence state vector which turns out not to be positive definite. Since the succeeding state space and ARMA modelling of the turbulence rely on the positive definiteness of the cross-spectral density matrix, the problem with the non-positive definiteness of such matrices is at first addressed and suitable treatments regarding it are proposed. From the adjusted positive definite cross-spectral density matrix a frequency response matrix is constructed which determines the turbulence vector as a linear filtration of Gaussian white noise. Finally, an accurate state space modelling method is proposed which allows selection of an appropriate model order, and estimation of a state space model for the vector turbulence process incorporating its phase spectrum in one stage, and its results are compared with a conventional ARMA modelling method.

Identification Common Microbes Observed on Polyester Tufting

Tufting carpet is a very suitable substrate for growing microorganism such as pathogenic microbes, due to the direct touch with human body, long washing periods and laying on the floor; in fact there are 3 major problems: To risk human health, Prepare bad odors and Destruction of the products.. In the presented research, for investigation of presence most common microbes on polyester tufting, first goods laid in a public place (in the corridor fair) for 30 days and the existence of some microbes were investigate on it with two methods of enrichment in nutrient environments such as thioglycolate and noutrunt brath, and shake the dust off the polyester tufting onto cultivation mediums such as blood agar and noutrunt agar. After the microorganism colonics are grown, the colonies were separated and six microbial tests such as cataloes and sitrat were carried out in five phases on the colonics for identifying the varieties of bacteria. As a result of tests, 5 type of bacteria, such as Escherichia coli, staphylococcus saprophytic as were identified. Each of the mentioned bacteria can be seriously harmful for the heath of human.

Statistical Optimization of the Enzymatic Saccharification of the Oil Palm Empty Fruit Bunches

A statistical optimization of the saccharification process of EFB was studied. The statistical analysis was done by applying faced centered central composite design (FCCCD) under response surface methodology (RSM). In this investigation, EFB dose, enzyme dose and saccharification period was examined, and the maximum 53.45% (w/w) yield of reducing sugar was found with 4% (w/v) of EFB, 10% (v/v) of enzyme after 120 hours of incubation. It can be calculated that the conversion rate of cellulose content of the substrate is more than 75% (w/w) which can be considered as a remarkable achievement. All the variables, linear, quadratic and interaction coefficient, were found to be highly significant, other than two coefficients, one quadratic and another interaction coefficient. The coefficient of determination (R2) is 0.9898 that confirms a satisfactory data and indicated that approximately 98.98% of the variability in the dependent variable, saccharification of EFB, could be explained by this model.

First Studies of the Influence of Single Gene Perturbations on the Inference of Genetic Networks

Inferring the network structure from time series data is a hard problem, especially if the time series is short and noisy. DNA microarray is a technology allowing to monitor the mRNA concentration of thousands of genes simultaneously that produces data of these characteristics. In this study we try to investigate the influence of the experimental design on the quality of the result. More precisely, we investigate the influence of two different types of random single gene perturbations on the inference of genetic networks from time series data. To obtain an objective quality measure for this influence we simulate gene expression values with a biologically plausible model of a known network structure. Within this framework we study the influence of single gene knock-outs in opposite to linearly controlled expression for single genes on the quality of the infered network structure.

Optimization of Kinematics for Birds and UAVs Using Evolutionary Algorithms

The aim of this work is to present a multi-objective optimization method to find maximum efficiency kinematics for a flapping wing unmanned aerial vehicle. We restrained our study to rectangular wings with the same profile along the span and to harmonic dihedral motion. It is assumed that the birdlike aerial vehicle (whose span and surface area were fixed respectively to 1m and 0.15m2) is in horizontal mechanically balanced motion at fixed speed. We used two flight physics models to describe the vehicle aerodynamic performances, namely DeLaurier-s model, which has been used in many studies dealing with flapping wings, and the model proposed by Dae-Kwan et al. Then, a constrained multi-objective optimization of the propulsive efficiency is performed using a recent evolutionary multi-objective algorithm called є-MOEA. Firstly, we show that feasible solutions (i.e. solutions that fulfil the imposed constraints) can be obtained using Dae-Kwan et al.-s model. Secondly, we highlight that a single objective optimization approach (weighted sum method for example) can also give optimal solutions as good as the multi-objective one which nevertheless offers the advantage of directly generating the set of the best trade-offs. Finally, we show that the DeLaurier-s model does not yield feasible solutions.

Observations about the Principal Components Analysis and Data Clustering Techniques in the Study of Medical Data

The medical data statistical analysis often requires the using of some special techniques, because of the particularities of these data. The principal components analysis and the data clustering are two statistical methods for data mining very useful in the medical field, the first one as a method to decrease the number of studied parameters, and the second one as a method to analyze the connections between diagnosis and the data about the patient-s condition. In this paper we investigate the implications obtained from a specific data analysis technique: the data clustering preceded by a selection of the most relevant parameters, made using the principal components analysis. Our assumption was that, using the principal components analysis before data clustering - in order to select and to classify only the most relevant parameters – the accuracy of clustering is improved, but the practical results showed the opposite fact: the clustering accuracy decreases, with a percentage approximately equal with the percentage of information loss reported by the principal components analysis.

A New Technique for Multi Resolution Characterization of Epileptic Spikes in EEG

A technique proposed for the automatic detection of spikes in electroencephalograms (EEG). A multi-resolution approach and a non-linear energy operator are exploited. The signal on each EEG channel is decomposed into three sub bands using a non-decimated wavelet transform (WT). The WT is a powerful tool for multi-resolution analysis of non-stationary signal as well as for signal compression, recognition and restoration. Each sub band is analyzed by using a non-linear energy operator, in order to detect spikes. A decision rule detects the presence of spikes in the EEG, relying upon the energy of the three sub-bands. The effectiveness of the proposed technique was confirmed by analyzing both test signals and EEG layouts.

High Speed Video Transmission for Telemedicine using ATM Technology

In this paper, we study statistical multiplexing of VBR video in ATM networks. ATM promises to provide high speed realtime multi-point to central video transmission for telemedicine applications in rural hospitals and in emergency medical services. Video coders are known to produce variable bit rate (VBR) signals and the effects of aggregating these VBR signals need to be determined in order to design a telemedicine network infrastructure capable of carrying these signals. We first model the VBR video signal and simulate it using a generic continuous-data autoregressive (AR) scheme. We carry out the queueing analysis by the Fluid Approximation Model (FAM) and the Markov Modulated Poisson Process (MMPP). The study has shown a trade off: multiplexing VBR signals reduces burstiness and improves resource utilization, however, the buffer size needs to be increased with an associated economic cost. We also show that the MMPP model and the Fluid Approximation model fit best, respectively, the cell region and the burst region. Therefore, a hybrid MMPP and FAM completely characterizes the overall performance of the ATM statistical multiplexer. The ramifications of this technology are clear: speed, reliability (lower loss rate and jitter), and increased capacity in video transmission for telemedicine. With migration to full IP-based networks still a long way to achieving both high speed and high quality of service, the proposed ATM architecture will remain of significant use for telemedicine.

Heavy Metals Transport in the Soil Profiles under the Application of Sludge and Wastewater

Heavy metal transfer in soil profiles is a major environmental concern because even slow transport through the soil may eventually lead to deterioration of groundwater quality. The use of sewage sludge and effluents from wastewater treatment plants for irrigation of agricultural lands is on the rise particularly in peri-urban area of developing countries. In this study soil samples under sludge application and wastewater irrigation were studied and soil samples were collected in the soil profiles from the surface to 100 cm in depth. For this purpose, three plots were made in a treatment plant in south of Tehran-Iran. First plot was irrigated just with effluent from wastewater treatment plant, second plot with simulated heavy metals concentration equal 50 years irrigation and in third plot sewage sludge and effluent was used. Trace metals concentration (Cd, Cu) were determined for soil samples. The results indicate movement of metals was observed, but the most concentration of metals was found in topsoil samples. The most of Cadmium concentration was measured in the topsoil of plot 3, 4.5mg/kg and Maximum cadmium movement was observed in 0-20 cm. The most concentration of copper was 27.76mg/kg, and maximum percolation in 0-20 cm. Metals (Cd, Cu) were measured in leached water. Preferential flow and metal complexation with soluble organic apparently allow leaching of heavy metals.

Face Localization Using Illumination-dependent Face Model for Visual Speech Recognition

A robust still image face localization algorithm capable of operating in an unconstrained visual environment is proposed. First, construction of a robust skin classifier within a shifted HSV color space is described. Then various filtering operations are performed to better isolate face candidates and mitigate the effect of substantial non-skin regions. Finally, a novel Bhattacharyya-based face detection algorithm is used to compare candidate regions of interest with a unique illumination-dependent face model probability distribution function approximation. Experimental results show a 90% face detection success rate despite the demands of the visually noisy environment.

Subpixel Detection of Circular Objects Using Geometric Property

In this paper, we propose a method for detecting circular shapes with subpixel accuracy. First, the geometric properties of circles have been used to find the diameters as well as the circumference pixels. The center and radius are then estimated by the circumference pixels. Both synthetic and real images have been tested by the proposed method. The experimental results show that the new method is efficient.

Problems that Impede Sustainable Tourism Development in Egypt

This paper analysis the tourism development on the Red Sea in Egypt (west bank) and the needed ongoing action toward a sustainable approach. It addresses, at the first, the development's evolution occurred in the coastal area, the environmental effects it left, and how to minimize those impacts in the future. The second main point is dealing with the most important issues that hinder the achievement of sustainable tourism development on the Red Sea coast and how we can overcome them in the future.

The Capacity of Government to Deliver Sustainable and Integrated Transport: The Case of Transit Oriented Development in Perth, Australia

There is a renewed interest in land use transport integration as a means of achieving sustainable accessibility. Such accessibility requires designing more than simply the transport network; it also requires attention to place (built form). Transitoriented development would appear to capture many of the criteria deemed important in land use transport integration. In Perth, Australia, there have been planning policies for the past 20 years requiring transit-oriented development around railway stations throughout the metropolitan area. While the policy intent, particularly at the State level, is clear the implementation of policy has been fairly ineffective. The first part of this paper provides an examination of state and local government planning and transport policies, evaluating them using a set of land use transport integration criteria considered all encompassing. This provides some insight into the extent of state and local government capacity to deliver land use transport integration. The second part of this paper examines the extent of implementation by examining existing and proposed land use around station precincts throughout metropolitan Perth. The findings of this research suggest that the capacity of state and local government to deliver land use transport integration is reasonable in a planning policy sense. Implementation, despite long policy lead times, has been lacking. It appears to be more effective where local planning controls have been suspended with new redevelopment authorities given powers to develop land around railway stations.

Study of Water Relations, Chlorophyll and their Correlations with Grain Yield in Wheat(Triticum aestivum L.) Genotypes

The objective of this experiment was to study of water relations and chlorophyll in different wheat genotypes and their correlations with grain and biological yields. 21 genotypes of bread wheat were compared in a field experiment as randomized complete blocks design with four replications. The results showed that relative water deficit, relative water loss, excised leaf water retention, cell membrane stability, chlorophyll-a, chlorophyll-b, total chlorophyll, grain yield and biological yield were different significantly among wheat genotypes, but SPAD-chlorophyll index, relative water content and chlorophyll florescence were not. Significant correlations were not observed among above mentioned water relations and chlorophyll characteristics with grain yield, but there was a positive and significant correlation between biological yield and grain yield.