Proposed a Method for Increasing the Delivery Performance in Dynamic Supply Network

Supply network management adopts a systematic and integrative approach to managing the operations and relationships of various parties in a supply network. The objective of the manufactures in their supply network is to reduce inventory costs and increase customer satisfaction levels. One way of doing that is to synchronize delivery performance. A supply network can be described by nodes representing the companies and the links (relationships) between these nodes. Uncertainty in delivery time depends on type of network relationship between suppliers. The problem is to understand how the individual uncertainties influence the total uncertainty of the network and identify those parts of the network, which has the highest potential for improving the total delivery time uncertainty.

Quantification of Periodicities in Fugitive Emission of Gases from Lyari Waterway

Periodicities in the environmetric time series can be idyllically assessed by utilizing periodic models. In this communication fugitive emission of gases from open sewer channel Lyari which follows periodic behaviour are approximated by employing periodic autoregressive model of order p. The orders of periodic model for each season are selected through the examination of periodic partial autocorrelation or information criteria. The parameters for the selected order of season are estimated individually for each emitted air toxin. Subsequently, adequacies of fitted models are established by examining the properties of the residual for each season. These models are beneficial for schemer and administrative bodies for the improvement of implemented policies to surmount future environmental problems.

Improved Feature Processing for Iris Biometric Authentication System

Iris-based biometric authentication is gaining importance in recent times. Iris biometric processing however, is a complex process and computationally very expensive. In the overall processing of iris biometric in an iris-based biometric authentication system, feature processing is an important task. In feature processing, we extract iris features, which are ultimately used in matching. Since there is a large number of iris features and computational time increases as the number of features increases, it is therefore a challenge to develop an iris processing system with as few as possible number of features and at the same time without compromising the correctness. In this paper, we address this issue and present an approach to feature extraction and feature matching process. We apply Daubechies D4 wavelet with 4 levels to extract features from iris images. These features are encoded with 2 bits by quantizing into 4 quantization levels. With our proposed approach it is possible to represent an iris template with only 304 bits, whereas existing approaches require as many as 1024 bits. In addition, we assign different weights to different iris region to compare two iris templates which significantly increases the accuracy. Further, we match the iris template based on a weighted similarity measure. Experimental results on several iris databases substantiate the efficacy of our approach.

A New Fast Skin Color Detection Technique

Skin color can provide a useful and robust cue for human-related image analysis, such as face detection, pornographic image filtering, hand detection and tracking, people retrieval in databases and Internet, etc. The major problem of such kinds of skin color detection algorithms is that it is time consuming and hence cannot be applied to a real time system. To overcome this problem, we introduce a new fast technique for skin detection which can be applied in a real time system. In this technique, instead of testing each image pixel to label it as skin or non-skin (as in classic techniques), we skip a set of pixels. The reason of the skipping process is the high probability that neighbors of the skin color pixels are also skin pixels, especially in adult images and vise versa. The proposed method can rapidly detect skin and non-skin color pixels, which in turn dramatically reduce the CPU time required for the protection process. Since many fast detection techniques are based on image resizing, we apply our proposed pixel skipping technique with image resizing to obtain better results. The performance evaluation of the proposed skipping and hybrid techniques in terms of the measured CPU time is presented. Experimental results demonstrate that the proposed methods achieve better result than the relevant classic method.

Potential of Solar Energy in Zarqa Region

The purpose of this work is to present the potential of solar energy in Zarqa region. The solar radiation along year 2009 was obtained from Pyranometer which measures the global radiation over horizontal surfaces. Solar data in several different forms, over period of 5 minutes, hour-by-hour, daily and monthly data radiation have been presented. Briefly, the yearly global solar radiation in Zarqa is 7297.5 MJ/m2 (2027 kWh/m²) and the average annual solar radiation per day is 20 MJ/m2 (5.5 Kwh/m2). More specifically, the average annual solar radiation per day is 12.9 MJ/m2 (3.57 Kwh/m2) in winter and 25 MJ/m2 (7 Kwh/m2) in summer.

Order Statistics-based “Anti-Bayesian“ Parametric Classification for Asymmetric Distributions in the Exponential Family

Although the field of parametric Pattern Recognition (PR) has been thoroughly studied for over five decades, the use of the Order Statistics (OS) of the distributions to achieve this has not been reported. The pioneering work on using OS for classification was presented in [1] for the Uniform distribution, where it was shown that optimal PR can be achieved in a counter-intuitive manner, diametrically opposed to the Bayesian paradigm, i.e., by comparing the testing sample to a few samples distant from the mean. This must be contrasted with the Bayesian paradigm in which, if we are allowed to compare the testing sample with only a single point in the feature space from each class, the optimal strategy would be to achieve this based on the (Mahalanobis) distance from the corresponding central points, for example, the means. In [2], we showed that the results could be extended for a few symmetric distributions within the exponential family. In this paper, we attempt to extend these results significantly by considering asymmetric distributions within the exponential family, for some of which even the closed form expressions of the cumulative distribution functions are not available. These distributions include the Rayleigh, Gamma and certain Beta distributions. As in [1] and [2], the new scheme, referred to as Classification by Moments of Order Statistics (CMOS), attains an accuracy very close to the optimal Bayes’ bound, as has been shown both theoretically and by rigorous experimental testing.

Nutritional Evaluation of Sorghum Flour (Sorghumbicolor L. Moench) During Processing of Injera

The present study was carried out to evaluate the nutritional value of sorghum flour during processing of injera (unleavened thick bread). The proximate composition of sorghum flour before and after fermentation and that of injera was determined. Compared to the raw flour and fermented one, injera had low protein (11.55%), ash (1.57%) and fat (2.40%) contents but high in fiber content. Moreover, injera was found to have significantly (P ≤ 0.05) higher energy (389.08 Kcal/100g) compared to raw and fermented sorghum flour. Injera contained lower levels of anti-nutritional factors (polyphenols, phytate and tannins) compared to raw and fermented sorghum. Also it was found to be rich in Ca (4.75mg/100g), Fe (3.95 mg/100g), and Cu (0.7 mg/100g) compared to that of raw and fermented flour. Moreover, both the extractable minerals and protein digestibility were high for injera due to low amount of anti-nutrients. Injera was found to contain an appreciable amount of amino acids except arginine and tyrosine.

Effect of Transglutaminase Cross Linking on the Functional Properties as a Function of NaCl Concentration of Legumes Protein Isolate

The effect of cross linking of the protein isolates of three legumes with the microbial enzyme transglutaminase (EC 2.3.2.13) on the functional properties at different NaCl concentration was studied. The reduction in the total free amino groups (OD340) of the polymerized protein showed that TGase treatment cross-linking the protein subunit of each legume. The solubility of the protein polymer of each legume was greatly improved at high concentration of NaCl. At 1.2 M NaCl the solubility of the native legumes protein was significantly decreased but after polymerization slightly improved. Cross linked proteins were less turbid on heating to higher temperature as compared to native proteins and the temperature at which the protein turns turbid also increased in the polymerized proteins. The emulsifying and foaming properties of the protein polymer were greatly improved at all concentrations of NaCl for all legumes.

Toward an Open Network Business Approach

The aim of this paper is to propose a dynamic integrated approach, based on modularity concept and on the business ecosystem approach, that exploit different eBusiness services for SMEs under an open business network platform. The adoption of this approach enables firms to collaborate locally for delivering the best product/service to the customers as well as globally by accessing international markets, interrelate directly with the customers, create relationships and collaborate with worldwide actors. The paper will be structured as following: We will start by offering an overview of the state of the art of eBusiness platforms among SME of food and tourism firms and then we discuss the main drawbacks that characterize them. The digital business ecosystem approach and the modularity concept will be described as the theoretical ground in which our proposed integrated model is rooted. Finally, the proposed model along with a discussion of the main value creation potentialities it might create for SMEs will be presented.

Deduction of Fuzzy Autocatalytic Set to Omega Algebra and Transformation Semigroup

In this paper, the Fuzzy Autocatalytic Set (FACS) is composed into Omega Algebra by embedding the membership value of fuzzy edge connectivity using the property of transitive affinity. Then, the Omega Algebra of FACS is a transformation semigroup which is a special class of semigroup is shown.

On a Discrete-Time GIX/Geo/1/N Queue with Single Working Vacation and Partial Batch Rejection

This paper treats a discrete-time finite buffer batch arrival queue with a single working vacation and partial batch rejection in which the inter-arrival and service times are, respectively, arbitrary and geometrically distributed. The queue is analyzed by using the supplementary variable and the imbedded Markov-chain techniques. We obtain steady-state system length distributions at prearrival, arbitrary and outside observer-s observation epochs. We also present probability generation function (p.g.f.) of actual waiting-time distribution in the system and some performance measures.

An Innovative Fuzzy Decision Making Based Genetic Algorithm

Several researchers have proposed methods about combination of Genetic Algorithm (GA) and Fuzzy Logic (the use of GA to obtain fuzzy rules and application of fuzzy logic in optimization of GA). In this paper, we suggest a new method in which fuzzy decision making is used to improve the performance of genetic algorithm. In the suggested method, we determine the alleles that enhance the fitness of chromosomes and try to insert them to the next generation. In this algorithm we try to present an innovative vaccination in the process of reproduction in genetic algorithm, with considering the trade off between exploration and exploitation.

Survival of Neutrino Mass Models in Nonthermal Leptogenesis

The Constraints imposed by non-thermal leptogenesis on the survival of the neutrino mass models describing the presently available neutrino mass patterns, are studied numerically. We consider the Majorana CP violating phases coming from right-handed Majorana mass matrices to estimate the baryon asymmetry of the universe, for different neutrino mass models namely quasi-degenerate, inverted hierarchical and normal hierarchical models, with tribimaximal mixings. Considering two possible diagonal forms of Dirac neutrino mass matrix as either charged lepton or up-quark mass matrix, the heavy right-handed mass matrices are constructed from the light neutrino mass matrix. Only the normal hierarchical model leads to the best predictions of baryon asymmetry of the universe, consistent with observations in non-thermal leptogenesis scenario.

Graphical Approach for Targeting Work Exchange Networks

Depressurization and pressurization streams in industrial systems constitute a work exchange network (WEN). In this paper, a novel graphical approach for targeting energy conservation potential of a WEN is proposed. Through constructing the composite work curves in the pressure-work diagram and assuming all of the mechanical energy of the depressurization streams is recovered by expanders, the maximum work target of a WEN can be determined via the proposed targeting steps. A WEN in an ammonia production process is used as a case study to illustrate the applicability of the proposed graphical approach.

Computer Simulations of an Augmented Automatic Choosing Control Using Automatic Choosing Functions of Gradient Optimization Type

In this paper we consider a nonlinear feedback control called augmented automatic choosing control (AACC) using the automatic choosing functions of gradient optimization type for nonlinear systems. Constant terms which arise from sectionwise linearization of a given nonlinear system are treated as coefficients of a stable zero dynamics. Parameters included in the control are suboptimally selected by minimizing the Hamiltonian with the aid of the genetic algorithm. This approach is applied to a field excitation control problem of power system to demonstrate the splendidness of the AACC. Simulation results show that the new controller can improve performance remarkably well.

Analytical Solutions of Kortweg-de Vries(KdV) Equation

The objective of this paper is to present a comparative study of Homotopy Perturbation Method (HPM), Variational Iteration Method (VIM) and Homotopy Analysis Method (HAM) for the semi analytical solution of Kortweg-de Vries (KdV) type equation called KdV. The study have been highlighted the efficiency and capability of aforementioned methods in solving these nonlinear problems which has been arisen from a number of important physical phenomenon.

Experimental Measurements of the Mean Flow Field in Wide-Angled Diffusers: A Data Bank Contribution

Due to adverse pressure gradient along the diverging walls of wide-angled diffusers, the attached flow separates from one wall and remains attached permanently to the other wall in a process called stalling. Stalled diffusers render the whole fluid flow system, in which they are part of, very inefficient. There is then an engineering need to try to understand the whole process of diffuser stall if any meaningful attempts to improve on diffuser efficiency are to be made. In this regard, this paper provides a data bank contribution for the mean flow-field in wide-angled diffusers where the complete velocity and static pressure fields, and pressure recovery data for diffusers in the fully stalled flow regime are experimentally measured. The measurements were carried out at Reynolds numbers between 1.07×105 and 2.14×105 based on inlet hydraulic diameter and centreline velocity for diffusers whose divergence angles were between 30Ôùª and 50Ôùª. Variation of Reynolds number did not significantly affect the velocity and static pressure profiles. The wall static pressure recovery was found to be more sensitive to changes in the Reynolds number. By increasing the velocity from 10 m/s to 20 m/s, the wall static pressure recovery increased by 8.31%. However, as the divergence angle was increased, a similar increase in the Reynolds number resulted in a higher percentage increase in pressure recovery. Experimental results showed that regardless of the wall to which the flow was attached, both the velocity and pressure fields were replicated with discrepancies below 2%.

Hybrid MAC Protocols Characteristics in Multi-hops Wireless Sensor Networks

In the current decade, wireless sensor networks are emerging as a peculiar multi-disciplinary research area. By this way, energy efficiency is one of the fundamental research themes in the design of Medium Access Control (MAC) protocols for wireless sensor networks. Thus, in order to optimize the energy consumption in these networks, a variety of MAC protocols are available in the literature. These schemes were commonly evaluated under simple network density and a few results are published on their robustness in realistic network-s size. We, in this paper, provide an analytical study aiming to highlight the energy waste sources in wireless sensor networks. Then, we experiment three energy efficient hybrid CSMA/CA based MAC protocols optimized for wireless sensor networks: Sensor-MAC (SMAC), Time-out MAC (TMAC) and Traffic aware Energy Efficient MAC (TEEM). We investigate these protocols with different network densities in order to discuss the end-to-end performances of these schemes (i.e. in terms of energy efficiency, delay and throughput). Through Network Simulator (NS- 2) implementations, we explore the behaviors of these protocols with respect to the network density. In fact, this study may help the multihops sensor networks designers to design or select the MAC layer which matches better their applications aims.

Neutronic Study of Two Reactor Cores Cooled with Light and Heavy Water Using Computation Method

Most HWRs currently use natural uranium fuel. Using enriched uranium fuel results in a significant improvement in fuel cycle costs and uranium utilization. On the other hand, reactivity changes of HWRs over the full range of operating conditions from cold shutdown to full power are small. This reduces the required reactivity worth of control devices and minimizes local flux distribution perturbations, minimizing potential problems due to transient local overheating of fuel. Analyzing heavy water effectiveness on neutronic parameters such as enrichment requirements, peaking factor and reactivity is important and should pay attention as primary concepts of a HWR core designing. Two nuclear nuclear reactors of CANDU-type and hexagonal-type reactor cores of 33 fuel assemblies and 19 assemblies in 1.04 P/D have been respectively simulated using MCNP-4C code. Using heavy water and light water as moderator have been compared for achieving less reactivity insertion and enrichment requirements. Two fuel matrixes of (232Th/235U)O2 and (238/235U)O2 have been compared to achieve more economical and safe design. Heavy water not only decreased enrichment needs, but it concluded in negative reactivity insertions during moderator density variations. Thorium oxide fuel assemblies of 2.3% enrichment loaded into the core of heavy water moderator resulted in 0.751 fission to absorption ratio and peaking factor of 1.7 using. Heavy water not only provides negative reactivity insertion during temperature raises which changes moderator density but concluded in 2 to 10 kg reduction of enrichment requirements, depend on geometry type.

High Speed Bitwise Search for Digital Forensic System

The most common forensic activity is searching a hard disk for string of data. Nowadays, investigators and analysts are increasingly experiencing large, even terabyte sized data sets when conducting digital investigations. Therefore consecutive searching can take weeks to complete successfully. There are two primary search methods: index-based search and bitwise search. Index-based searching is very fast after the initial indexing but initial indexing takes a long time. In this paper, we discuss a high speed bitwise search model for large-scale digital forensic investigations. We used pattern matching board, which is generally used for network security, to search for string and complex regular expressions. Our results indicate that in many cases, the use of pattern matching board can substantially increase the performance of digital forensic search tools.