A Method for Modeling Multiple Antenna Channels

In this paper we propose a method for modeling the correlation between the received signals by two or more antennas operating in a multipath environment. Considering the maximum excess delay in the channel being modeled, an elliptical region surrounding both transmitter and receiver antennas is produced. A number of scatterers are randomly distributed in this region and scatter the incoming waves. The amplitude and phase of incoming waves are computed and used to obtain statistical properties of the received signals. This model has the distinguishable advantage of being applicable for any configuration of antennas. Furthermore the common PDF (Probability Distribution Function) of received wave amplitudes for any pair of antennas can be calculated and used to produce statistical parameters of received signals.

Stability of New Macromycetes Phytases under Room, Cooling and Freezing Temperatures of Storage

Phytases are enzymes used as an important component in monogastric animals feeds in order to improve phosphorous availability, since it is not readily assimilated by these animals in the form of the phytate presented in plants and grains. As these enzymes are used in industrial activities, they must retain its catalytic activities during a certain storage period. This study presents information about the stability of 4 different phytases, produced by four macromycetes fungi through solid-state fermentation (SSF). There is a lack of data in literature concerning phytase from macromycetes shelf-life in storage conditions at room, cooling and freezing temperatures. The 4 phytases from macromycetes still had enzymatic activities around 100 days of storage at room temperature. At cooling temperature in 146 days of studies, the phytase from G. stipitatum was the most stable with 44% of the initial activity, in U.gds (units per gram of dried fermented substrate). The freezing temperature was the best condition storage for phytases from G. stipitatum and T. versicolor. Each condition provided a study for each mushroom phytase, totalizing 12 studies. The phytases showed to be stable for a long period without the addition of additives.

The Impact of Product Package Information on Consumer Behavior toward Genetically Modified Foods

Genetically modified (GM) technology in food production continued to generate controversies. Consumers were concerned with the GM foods about the healthy and environmental risks. While consumers- acceptance was a critical factor affecting how widely this technology be used. According to the research review, consumers- lack of information was one of the reasons to explain consumers- low acceptance toward GM foods. The objective for this study wanted to find out would informative product package affect consumers- behavior toward GM foods. An experiment was designed to investigate consumer behavior toward different product package information. The results indicated that the product package information influenced consumer product trust toward GM foods. Compared with the traceability production system information, the information about the GM rice was approved by authorized organizations could increase consumers product trust in GM foods. Consumers in Taiwan saw the information provided by authorized organizations more credible than other information.

An Overview of Issues to Consider Before Introducing Performance-Based Road Maintenance Contracting

Road authorities have confronted problems to maintaining the serviceability of road infrastructure systems by using various traditional methods of contracting. As a solution to these problems, many road authorities have started contracting out road maintenance works to the private sector based on performance measures. This contracting method is named Performance-Based Maintenance Contracting (PBMC). It is considered more costeffective than other traditional methods of contracting. It has a substantial success records in many developed and developing countries over the last two decades. This paper discusses and analyses the potential issues to be considered before the introduction of PBMC in a country.

Anomaly Detection and Characterization to Classify Traffic Anomalies Case Study: TOT Public Company Limited Network

This paper represents four unsupervised clustering algorithms namely sIB, RandomFlatClustering, FarthestFirst, and FilteredClusterer that previously works have not been used for network traffic classification. The methodology, the result, the products of the cluster and evaluation of these algorithms with efficiency of each algorithm from accuracy are shown. Otherwise, the efficiency of these algorithms considering form the time that it use to generate the cluster quickly and correctly. Our work study and test the best algorithm by using classify traffic anomaly in network traffic with different attribute that have not been used before. We analyses the algorithm that have the best efficiency or the best learning and compare it to the previously used (K-Means). Our research will be use to develop anomaly detection system to more efficiency and more require in the future.

Improving Cache Memory Utilization

In this paper, an efficient technique is proposed to manage the cache memory. The proposed technique introduces some modifications on the well-known set associative mapping technique. This modification requires a little alteration in the structure of the cache memory and on the way by which it can be referenced. The proposed alteration leads to increase the set size virtually and consequently to improve the performance and the utilization of the cache memory. The current mapping techniques have accomplished good results. In fact, there are still different cases in which cache memory lines are left empty and not used, whereas two or more processes overwrite the lines of each other, instead of using those empty lines. The proposed algorithm aims at finding an efficient way to deal with such problem.

Finite Volume Model to Study The Effect of Voltage Gated Ca2+ Channel on Cytosolic Calcium Advection Diffusion

Mathematical and computational modeling of calcium signalling in nerve cells has produced considerable insights into how the cells contracts with other cells under the variation of biophysical and physiological parameters. The modeling of calcium signaling in astrocytes has become more sophisticated. The modeling effort has provided insight to understand the cell contraction. Main objective of this work is to study the effect of voltage gated (Operated) calcium channel (VOC) on calcium profile in the form of advection diffusion equation. A mathematical model is developed in the form of advection diffusion equation for the calcium profile. The model incorporates the important physiological parameter like diffusion coefficient etc. Appropriate boundary conditions have been framed. Finite volume method is employed to solve the problem. A program has been developed using in MATLAB 7.5 for the entire problem and simulated on an AMD-Turion 32-bite machine to compute the numerical results.

Pseudo-Homogeneous Kinetic of Dilute-Acid Hydrolysis of Rice Husk for Ethanol Production: Effect of Sugar Degradation

Rice husk is a lignocellulosic source that can be converted to ethanol. Three hundreds grams of rice husk was mixed with 1 L of 0.18 N sulfuric acid solutions then was heated in an autoclave. The reaction was expected to be at constant temperature (isothermal), but before that temperature was achieved, reaction has occurred. The first liquid sample was taken at temperature of 140 0C and repeated every 5 minute interval. So the data obtained are in the regions of non-isothermal and isothermal. It was observed that the degradation has significant effects on the ethanol production. The kinetic constants can be expressed by Arrhenius equation with the frequency factors for hydrolysis and sugar degradation of 1.58 x 105 1/min and 2.29 x 108 L/mole/min, respectively, while the activation energies are 64,350 J/mole and 76,571 J/mole. The highest ethanol concentration from fermentation is 1.13% v/v, attained at 220 0C.

On the Use of Correlated Binary Model in Social Network Analysis

In social network analysis the mean nodal degree and density of the graph can be considered as a measure of the activity of all actors in the network and this is an important property of a graph and for making comparisons among networks. Since subjects in a family or organization are subject to common environment factors, it is prime interest to study the association between responses. Therefore, we study the distribution of the mean nodal degree and density of the graph under correlated binary units. The cross product ratio is used to capture the intra-units association among subjects. Computer program and an application are given to show the benefits of the method.

Local Algorithm for Establishing a Virtual Backbone in 3D Ad Hoc Network

Due to the limited lifetime of the nodes in ad hoc and sensor networks, energy efficiency needs to be an important design consideration in any routing algorithm. It is known that by employing a virtual backbone in a wireless network, the efficiency of any routing scheme for the network can be improved. One common design for routing protocols in mobile ad hoc networks is to use positioning information; we use the node-s geometric locations to introduce an algorithm that can construct the virtual backbone structure locally in 3D environment. The algorithm construction has a constant time.

A Statistical Approach for Predicting and Optimizing Depth of Cut in AWJ Machining for 6063-T6 Al Alloy

In this paper, a set of experimental data has been used to assess the influence of abrasive water jet (AWJ) process parameters in cutting 6063-T6 aluminum alloy. The process variables considered here include nozzle diameter, jet traverse rate, jet pressure and abrasive flow rate. The effects of these input parameters are studied on depth of cut (h); one of most important characteristics of AWJ. The Taguchi method and regression modeling are used in order to establish the relationships between input and output parameters. The adequacy of the model is evaluated using analysis of variance (ANOVA) technique. In the next stage, the proposed model is embedded into a Simulated Annealing (SA) algorithm to optimize the AWJ process parameters. The objective is to determine a suitable set of process parameters that can produce a desired depth of cut, considering the ranges of the process parameters. Computational results prove the effectiveness of the proposed model and optimization procedure.

The Effect of Granule Size on the Digestibility of Wheat Starch Using an in vitro Model

Wheat has a bimodal starch granule population and the dependency of the rate of enzymatic hydrolysis on particle size has been investigated. Ungelatinised wheaten starch granules were separated into two populations by sedimentation and decantation. Particle size was analysed by laser diffraction and morphological characteristics were viewed using SEM. The sedimentation technique though lengthy, gave satisfactory separation of the granules. Samples (10μm and original) were digested with a-amylase using a dialysis model. Granules of 10μm (p10μm. Moreover, the digestion rate was dependent on particle size whereby smaller granules produced higher rate of release. The methodology and results reported here can be used as a basis for further evaluations designed to delay the release of glucose during the digestion of native starches.

Synthesis of Monoacylglycerol from Glycerolysis of Crude Glycerol with Coconut Oil Catalyzed by Carica papaya Lipase

This paper studied the synthesis of monoacylglycerol (monolaurin) by glycerolysis of coconut oil and crude glycerol, catalyzed by Carica papaya lipase. Coconut oil obtained from cold pressed extraction method and crude glycerol obtained from the biodiesel plant in Department of Chemistry, Uttaradit Rajabhat University, Thailand which used oils were used as raw materials for biodiesel production through transesterification process catalyzed by sodium hydroxide. The influences of the following variables were studied: (i) type of organic solvent, (ii) molar ratio of substrate, (iii) reaction temperature, (iv) reaction time, (v) lipase dosage, and (vi) initial water activity of enzyme. High yields in monoacylglycerol (58.35%) were obtained with molar ratio of glycerol to oil at 8:1 in ethanol, temperature was controlled at 45oC for 36 hours, the amount of enzyme used was 20 wt% of oil and initial water activity of enzyme at 0.53.

Travel Time Evaluation of an Innovative U-Turn Facility on Urban Arterial Roadways

Signalized intersections on high-volume arterials are often congested during peak hours, causing a decrease in through movement efficiency on the arterial. Much of the vehicle delay incurred at conventional intersections is caused by high left-turn demand. Unconventional intersection designs attempt to reduce intersection delay and travel time by rerouting left-turns away from the main intersection and replacing it with right-turn followed by Uturn. The proposed new type of U-turn intersection is geometrically designed with a raised island which provides a protected U-turn movement. In this study several scenarios based on different distances between U-turn and main intersection, traffic volume of major/minor approaches and percentage of left-turn volumes were simulated by use of AIMSUN, a type of traffic microsimulation software. Subsequently some models are proposed in order to compute travel time of each movement. Eventually by correlating these equations to some in-field collected data of some implemented U-turn facilities, the reliability of the proposed models are approved. With these models it would be possible to calculate travel time of each movement under any kind of geometric and traffic condition. By comparing travel time of a conventional signalized intersection with U-turn intersection travel time, it would be possible to decide on converting signalized intersections into this new kind of U-turn facility or not. However comparison of travel time is not part of the scope of this research. In this paper only travel time of this innovative U-turn facility would be predicted. According to some before and after study about the traffic performance of some executed U-turn facilities, it is found that commonly, this new type of U-turn facility produces lower travel time. Thus, evaluation of using this type of unconventional intersection should be seriously considered.

Corporate Social Responsibility in China Apparel Industry

China apparel industry, which is deeply embedded in the global production network (GPN), faces the dual pressures of social upgrading and economic upgrading. Based on the survey in Ningbo apparel cluster, the paper shows the state of corporate social responsibility (CSR) in China apparel industry is better than before. And the investigation indicates that the firms who practice CSR actively perform better both socially and economically than those who inactively. The research demonstrates that CSR can be an initial capital rather than cost, and “doing well by doing good" is also existed in labor intensive industry.

Traffic Flow on Road Junctions

The paper deals with a mathematical model for fluid dynamic flows on road networks which is based on conservation laws. This nonlinear framework is based on the conservation of cars. We focus on traffic circle, which is a finite number of roads that meet at some junctions. The traffic circle with junctions having either one incoming and two outgoing or two incoming and one outgoing roads. We describe the numerical schemes with the particular boundary conditions used to produce approximated solutions of the problem.

Impact of Viscous and Heat Relaxation Loss on the Critical Temperature Gradients of Thermoacoustic Stacks

A stack with a small critical temperature gradient is desirable for a standing wave thermoacoustic engine to obtain a low onset temperature difference (the minimum temperature difference to start engine-s self-oscillation). The viscous and heat relaxation loss in the stack determines the critical temperature gradient. In this work, a dimensionless critical temperature gradient factor is obtained based on the linear thermoacoustic theory. It is indicated that the impedance determines the proportion between the viscous loss, heat relaxation losses and the power production from the heat energy. It reveals the effects of the channel dimensions, geometrical configuration and the local acoustic impedance on the critical temperature gradient in stacks. The numerical analysis shows that there exists a possible optimum combination of these parameters which leads to the lowest critical temperature gradient. Furthermore, several different geometries have been tested and compared numerically.

Project Risk Management Techniques in Resource Allocation, Scheduling and Planning

Normally business changes are made in order to change a level of activity in some way, whether it is sales, cash flow, productivity, or product portfolio. When attempts are made to make such changes, too often the business reverts to the old levels of activity as soon as management attention is diverted. Risk management is a field of growing interest to project managers as well as in general business and organizational management. There are several approaches used to manage risk in projects and this paper is a brief outline of some that you might encounter, with an indication of their strengths and weaknesses.

Soft Connected Spaces and Soft Paracompact Spaces

Soft topological spaces are considered as mathematical tools for dealing with uncertainties, and a fuzzy topological space is a special case of the soft topological space. The purpose of this paper is to study soft topological spaces. We introduce some new concepts in soft topological spaces such as soft closed mapping, soft open mappings, soft connected spaces and soft paracompact spaces. We also redefine the concept of soft points such that it is reasonable in soft topological spaces. Moreover, some basic properties of these concepts are explored.

Class Outliers Mining: Distance-Based Approach

In large datasets, identifying exceptional or rare cases with respect to a group of similar cases is considered very significant problem. The traditional problem (Outlier Mining) is to find exception or rare cases in a dataset irrespective of the class label of these cases, they are considered rare events with respect to the whole dataset. In this research, we pose the problem that is Class Outliers Mining and a method to find out those outliers. The general definition of this problem is “given a set of observations with class labels, find those that arouse suspicions, taking into account the class labels". We introduce a novel definition of Outlier that is Class Outlier, and propose the Class Outlier Factor (COF) which measures the degree of being a Class Outlier for a data object. Our work includes a proposal of a new algorithm towards mining of the Class Outliers, presenting experimental results applied on various domains of real world datasets and finally a comparison study with other related methods is performed.