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).

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.

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.

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.

A Remote Sensing Approach for Vulnerability and Environmental Change in Apodi Valley Region, Northeast Brazil

The objective of this study was to improve our understanding of vulnerability and environmental change; it's causes basically show the intensity, its distribution and human-environment effect on the ecosystem in the Apodi Valley Region, This paper is identify, assess and classify vulnerability and environmental change in the Apodi valley region using a combined approach of landscape pattern and ecosystem sensitivity. Models were developed using the following five thematic layers: Geology, geomorphology, soil, vegetation and land use/cover, by means of a Geographical Information Systems (GIS)-based on hydro-geophysical parameters. In spite of the data problems and shortcomings, using ESRI-s ArcGIS 9.3 program, the vulnerability score, to classify, weight and combine a number of 15 separate land cover classes to create a single indicator provides a reliable measure of differences (6 classes) among regions and communities that are exposed to similar ranges of hazards. Indeed, the ongoing and active development of vulnerability concepts and methods have already produced some tools to help overcome common issues, such as acting in a context of high uncertainties, taking into account the dynamics and spatial scale of asocial-ecological system, or gathering viewpoints from different sciences to combine human and impact-based approaches. Based on this assessment, this paper proposes concrete perspectives and possibilities to benefit from existing commonalities in the construction and application of assessment tools.

Selective Encryption using ISMA Cryp in Real Time Video Streaming of H.264/AVC for DVB-H Application

Multimedia information availability has increased dramatically with the advent of video broadcasting on handheld devices. But with this availability comes problems of maintaining the security of information that is displayed in public. ISMA Encryption and Authentication (ISMACryp) is one of the chosen technologies for service protection in DVB-H (Digital Video Broadcasting- Handheld), the TV system for portable handheld devices. The ISMACryp is encoded with H.264/AVC (advanced video coding), while leaving all structural data as it is. Two modes of ISMACryp are available; the CTR mode (Counter type) and CBC mode (Cipher Block Chaining) mode. Both modes of ISMACryp are based on 128- bit AES algorithm. AES algorithms are more complex and require larger time for execution which is not suitable for real time application like live TV. The proposed system aims to gain a deep understanding of video data security on multimedia technologies and to provide security for real time video applications using selective encryption for H.264/AVC. Five level of security proposed in this paper based on the content of NAL unit in Baseline Constrain profile of H.264/AVC. The selective encryption in different levels provides encryption of intra-prediction mode, residue data, inter-prediction mode or motion vectors only. Experimental results shown in this paper described that fifth level which is ISMACryp provide higher level of security with more encryption time and the one level provide lower level of security by encrypting only motion vectors with lower execution time without compromise on compression and quality of visual content. This encryption scheme with compression process with low cost, and keeps the file format unchanged with some direct operations supported. Simulation was being carried out in Matlab.

Security Analysis on Anonymous Mutual Authentication Protocol for RFID Tag without Back-End Database and its Improvement

RFID (Radio Frequency IDentification) system has been widely used in our life, such as transport systems, passports, automotive, animal tracking, human implants, library, and so on. However, the RFID authentication protocols between RF (Radio Frequency) tags and the RF readers have been bring about various privacy problems that anonymity of the tags, tracking, eavesdropping, and so on. Many researchers have proposed the solution of the problems. However, they still have the problem, such as location privacy, mutual authentication. In this paper, we show the problems of the previous protocols, and then we propose a more secure and efficient RFID authentication protocol.

Application of Pattern Search Method to Power System Security Constrained Economic Dispatch

Direct search methods are evolutionary algorithms used to solve optimization problems. (DS) methods do not require any information about the gradient of the objective function at hand while searching for an optimum solution. One of such methods is Pattern Search (PS) algorithm. This paper presents a new approach based on a constrained pattern search algorithm to solve a security constrained power system economic dispatch problem (SCED). Operation of power systems demands a high degree of security to keep the system satisfactorily operating when subjected to disturbances, while and at the same time it is required to pay attention to the economic aspects. Pattern recognition technique is used first to assess dynamic security. Linear classifiers that determine the stability of electric power system are presented and added to other system stability and operational constraints. The problem is formulated as a constrained optimization problem in a way that insures a secure-economic system operation. Pattern search method is then applied to solve the constrained optimization formulation. In particular, the method is tested using one system. Simulation results of the proposed approach are compared with those reported in literature. The outcome is very encouraging and proves that pattern search (PS) is very applicable for solving security constrained power system economic dispatch problem (SCED).

On Reversal and Transposition Medians

During the last years, the genomes of more and more species have been sequenced, providing data for phylogenetic recon- struction based on genome rearrangement measures. A main task in all phylogenetic reconstruction algorithms is to solve the median of three problem. Although this problem is NP-hard even for the sim- plest distance measures, there are exact algorithms for the breakpoint median and the reversal median that are fast enough for practical use. In this paper, this approach is extended to the transposition median as well as to the weighted reversal and transposition median. Although there is no exact polynomial algorithm known even for the pairwise distances, we will show that it is in most cases possible to solve these problems exactly within reasonable time by using a branch and bound algorithm.

Testing Database of Information System using Conceptual Modeling

This paper focuses on testing database of existing information system. At the beginning we describe the basic problems of implemented databases, such as data redundancy, poor design of database logical structure or inappropriate data types in columns of database tables. These problems are often the result of incorrect understanding of the primary requirements for a database of an information system. Then we propose an algorithm to compare the conceptual model created from vague requirements for a database with a conceptual model reconstructed from implemented database. An algorithm also suggests steps leading to optimization of implemented database. The proposed algorithm is verified by an implemented prototype. The paper also describes a fuzzy system which works with the vague requirements for a database of an information system, procedure for creating conceptual from vague requirements and an algorithm for reconstructing a conceptual model from implemented database.

Dynamic Capitalization and Visualization Strategy in Collaborative Knowledge Management System for EI Process

Knowledge is attributed to human whose problemsolving behavior is subjective and complex. In today-s knowledge economy, the need to manage knowledge produced by a community of actors cannot be overemphasized. This is due to the fact that actors possess some level of tacit knowledge which is generally difficult to articulate. Problem-solving requires searching and sharing of knowledge among a group of actors in a particular context. Knowledge expressed within the context of a problem resolution must be capitalized for future reuse. In this paper, an approach that permits dynamic capitalization of relevant and reliable actors- knowledge in solving decision problem following Economic Intelligence process is proposed. Knowledge annotation method and temporal attributes are used for handling the complexity in the communication among actors and in contextualizing expressed knowledge. A prototype is built to demonstrate the functionalities of a collaborative Knowledge Management system based on this approach. It is tested with sample cases and the result showed that dynamic capitalization leads to knowledge validation hence increasing reliability of captured knowledge for reuse. The system can be adapted to various domains.

A Study of DSRC Radio Testbed under Heavy Channel Load

Dedicated Short Range Communication (DSRC) is a key enabling technology for the next generation of communication-based safety applications. One of the important problems for DSRC deployment is maintaining high performance under heavy channel load. Many studies focus on congestion control mechanisms for simulating hundreds of physical radios deployed on vehicles. The U.S. department of transportation-s (DOT) Intelligent Transportation Systems (ITS) division has a plan to chosen prototype on-board devices capable of transmitting basic “Here I am" safety messages to other vehicles. The devices will be used in an IntelliDrive safety pilot deployment of up to 3,000 vehicles. It is hard to log the information of 3,000 vehicles. In this paper we present the designs and issues related to the DSRC Radio Testbed under heavy channel load. The details not only include the architecture of DSRC Radio Testbed, but also describe how the Radio Interfere System is used to help for emulating the congestion radio environment.

Using Radial Basis Function Neural Networks to Calibrate Water Quality Model

Modern managements of water distribution system (WDS) need water quality models that are able to accurately predict the dynamics of water quality variations within the distribution system environment. Before water quality models can be applied to solve system problems, they should be calibrated. Although former researchers use GA solver to calibrate relative parameters, it is difficult to apply on the large-scale or medium-scale real system for long computational time. In this paper a new method is designed which combines both macro and detailed model to optimize the water quality parameters. This new combinational algorithm uses radial basis function (RBF) metamodeling as a surrogate to be optimized for the purpose of decreasing the times of time-consuming water quality simulation and can realize rapidly the calibration of pipe wall reaction coefficients of chlorine model of large-scaled WDS. After two cases study this method is testified to be more efficient and promising, and deserve to generalize in the future.

Quality of Service in Multioperator GPON Access Networks with Triple-Play Services

Recently, in some places, optical-fibre access networks have been used with GPON technology belonging to organizations (in most cases public bodies) that act as neutral operators. These operators simultaneously provide network services to various telecommunications operators that offer integrated voice, data and television services. This situation creates new problems related to quality of service, since the interests of the users are intermingled with the interests of the operators. In this paper, we analyse this problem and consider solutions that make it possible to provide guaranteed quality of service for voice over IP, data services and interactive digital television.

Combining Ant Colony Optimization and Dynamic Programming for Solving a Dynamic Facility Layout Problem

This paper presents an algorithm which combining ant colony optimization in the dynamic programming for solving a dynamic facility layout problem. The problem is separated into 2 phases, static and dynamic phase. In static phase, ant colony optimization is used to find the best ranked of layouts for each period. Then the dynamic programming (DP) procedure is performed in the dynamic phase to evaluate the layout set during multi-period planning horizon. The proposed algorithm is tested over many problems with size ranging from 9 to 49 departments, 2 and 4 periods. The experimental results show that the proposed method is an alternative way for the plant layout designer to determine the layouts during multi-period planning horizon.

Industrial Development, Environment And Occupational Problems: The Case Of Iran

There are three distinct stages in the evolution of economic thought, namely: 1. in the first stage, the major concern was to accelerate economic growth with increased availability of material goods, especially in developing economies with very low living standards, because poverty eradication meant faster economic growth. 2. in the second stage, economists made distinction between growth and development. Development was seen as going beyond economic growth, and bringing certain changes in the structure of the economy with more equitable distribution of the benefits of growth, with the growth coming automatic and sustained. 3. the third stage is now reached. Our concern is now with “sustainable development", that is, development not only for the present but also of the future. Thus the focus changed from “sustained growth" to “sustained development". Sustained development brings to the fore the long term relationship between the ecology and economic development. Since the creation of UNEP in 1972 it has worked for development without destruction for environmentally sound and sustained development. It was realised that the environment cannot be viewed in a vaccum, it is not separate from development, nor is it competing. It suggested for the integration of the environment with development whereby ecological factors enter development planning, socio-economic policies, cost-benefit analysis, trade, technology transfer, waste management, educational and other specific areas. Industrialisation has contributed to the growth of economy of several countries. It has improved the standards of living of its people and provided benefits to the society. It has also created in the process great environmental problems like climate change, forest destruction and denudation, soil erosion and desertification etc. On the other hand, industry has provided jobs and improved the prospects of wealth for the industrialists. The working class communities had to simply put up with the high levels of pollution in order to keep up their jobs and also to save their income. There are many roots of the environmental problem. They may be political, economic, cultural and technological conditions of the modern society. The experts concede that industrial growth lies somewhere close to the heart of the matter. Therefore, the objective of this paper is not to document all roots of an environmental crisis but rather to discuss the effects of industrial growth and development. We have come to the conclusion that although public intervention is often unnecessary to ensure that perfectly competitive markets will function in society-s best interests, such intervention is necessary when firms or consumers pollute.

Dynamic Slope Scaling Procedure for Stochastic Integer Programming Problem

Mathematical programming has been applied to various problems. For many actual problems, the assumption that the parameters involved are deterministic known data is often unjustified. In such cases, these data contain uncertainty and are thus represented as random variables, since they represent information about the future. Decision-making under uncertainty involves potential risk. Stochastic programming is a commonly used method for optimization under uncertainty. A stochastic programming problem with recourse is referred to as a two-stage stochastic problem. In this study, we consider a stochastic programming problem with simple integer recourse in which the value of the recourse variable is restricted to a multiple of a nonnegative integer. The algorithm of a dynamic slope scaling procedure for solving this problem is developed by using a property of the expected recourse function. Numerical experiments demonstrate that the proposed algorithm is quite efficient. The stochastic programming model defined in this paper is quite useful for a variety of design and operational problems.

Automatic Clustering of Gene Ontology by Genetic Algorithm

Nowadays, Gene Ontology has been used widely by many researchers for biological data mining and information retrieval, integration of biological databases, finding genes, and incorporating knowledge in the Gene Ontology for gene clustering. However, the increase in size of the Gene Ontology has caused problems in maintaining and processing them. One way to obtain their accessibility is by clustering them into fragmented groups. Clustering the Gene Ontology is a difficult combinatorial problem and can be modeled as a graph partitioning problem. Additionally, deciding the number k of clusters to use is not easily perceived and is a hard algorithmic problem. Therefore, an approach for solving the automatic clustering of the Gene Ontology is proposed by incorporating cohesion-and-coupling metric into a hybrid algorithm consisting of a genetic algorithm and a split-and-merge algorithm. Experimental results and an example of modularized Gene Ontology in RDF/XML format are given to illustrate the effectiveness of the algorithm.

Comparative Study of Decision Trees and Rough Sets Theory as Knowledge ExtractionTools for Design and Control of Industrial Processes

General requirements for knowledge representation in the form of logic rules, applicable to design and control of industrial processes, are formulated. Characteristic behavior of decision trees (DTs) and rough sets theory (RST) in rules extraction from recorded data is discussed and illustrated with simple examples. The significance of the models- drawbacks was evaluated, using simulated and industrial data sets. It is concluded that performance of DTs may be considerably poorer in several important aspects, compared to RST, particularly when not only a characterization of a problem is required, but also detailed and precise rules are needed, according to actual, specific problems to be solved.

Cross-Industry Innovations – Systematic Identification and Adaption

Due to today-s fierce competition, companies have to be proactive creators of the future by effectively developing innovations. Especially radical innovations allow high profit margins – but they also entail high risks. One possibility to realize radical innovations and reduce the risk of failure is cross-industry innovation (CII). CII brings together problems and solution ideas from different industries. However, there is a lack of systematic ways towards CII. Bridging this gap, the present paper provides a systematic approach towards planned CII. Starting with the analysis of potentials, the definition of promising search strategies is crucial. Subsequently, identified solution ideas need to be assessed. For the most promising ones, the adaption process has to be systematically planned – regarding the risk affinity of a company. The introduced method is explained on a project from the furniture industry.