The Wijma Delivery Expectancy/Experience Questionnaire (W-DEQ) with Turkish Sample: Confirmatory and Exploratory Factor Analysis

The propose of this study is to investigate the factor structures of the W-DEQ, originally developed on UK and Swedish women, were confirmed in Turkish samples, and to obtain a new modified factor structure appropriate to Turkish culture. Statistical analyses of the data obtained were performed using SPSS© for Windows version 13.0 and the SAS statistical software Version 9.1. Both confirmatory and exploratory factor analysis of W-DEQ were performed in the study. Factor analysis yielded four factors related to hope, fear, lack of positive anticipation and riskiness. The alpha estimates of the total W-DEQ score were somewhat higher, being 0.92 for the parous and 0.90 for the nulliparous sample. These are well above the accepted limit of 0.70 and indicate excellent levels of internal reliability, thus showing that the questions were appropriate to the Turkish culture and useful scale for the evaluation of fear of childbirth in Turkish pregnants.

Fuzzy Logic Speed Controller with Reduced Rule Base for Dual PMSM Drives

Dual motor drives fed by single inverter is purposely designed to reduced size and cost with respect to single motor drives fed by single inverter. Previous researches on dual motor drives only focus on the modulation and the averaging techniques. Only a few of them, study the performance of the drives based on different speed controller other than Proportional and Integrator (PI) controller. This paper presents a detailed comparative study on fuzzy rule-base in Fuzzy Logic speed Controller (FLC) for Dual Permanent Magnet Synchronous Motor (PMSM) drives. Two fuzzy speed controllers which are standard and simplified fuzzy speed controllers are designed and the results are compared and evaluated. The standard fuzzy controller consists of 49 rules while the proposed controller consists of 9 rules determined by selecting the most dominant rules only. Both designs are compared for wide range of speed and the robustness of both controllers over load disturbance changes is tested to demonstrate the effectiveness of the simplified/reduced rulebase.

Model Order Reduction of Discrete-Time Systems Using Fuzzy C-Means Clustering

A computationally simple approach of model order reduction for single input single output (SISO) and linear timeinvariant discrete systems modeled in frequency domain is proposed in this paper. Denominator of the reduced order model is determined using fuzzy C-means clustering while the numerator parameters are found by matching time moments and Markov parameters of high order system.

Effect of Cement-kiln Dust Pollution on The Vegetation in The Western Mediterranean Desert of Egypt

This study investigated the ecological effects of particulate pollution from a cement factory on the vegetation in the western Mediterranean coastal desert of Egypt. Variations in vegetation, soil chemical characters, and some responses of Atriplex halimus, as a dominant species in the study area, were investigated in some sites located in different directions from the cement factory between Burg El-Arab in the east and El-Hammam in the west. The results showed an obvious decrease in vegetation diversity, in response to cement-kiln dust pollution, that accompanied by a high dominance attributed to the high contribution of Atriplex halimus. Annual species were found to be more sensitive to cement dust pollution as they all failed to persist in highly disturbed sites. It is remarkable that cover and phytomass of Atriplex halimus were increased greatly in response to cement dust pollution, and this was accompanied by a reduction in the mature seeds and leaf-area of the plant. The few seeds of the affected individuals seemed to be more fertile and attained higher germination percentages and exhibited hardening against drought stress.

Combining the Description Features of UMLRT and CSP+T Specifications Applied to a Complete Design of Real-Time Systems

UML is a collection of notations for capturing a software system specification. These notations have a specific syntax defined by the Object Management Group (OMG), but many of their constructs only present informal semantics. They are primarily graphical, with textual annotation. The inadequacies of standard UML as a vehicle for complete specification and implementation of real-time embedded systems has led to a variety of competing and complementary proposals. The Real-time UML profile (UML-RT), developed and standardized by OMG, defines a unified framework to express the time, scheduling and performance aspects of a system. We present in this paper a framework approach aimed at deriving a complete specification of a real-time system. Therefore, we combine two methods, a semiformal one, UML-RT, which allows the visual modeling of a realtime system and a formal one, CSP+T, which is a design language including the specification of real-time requirements. As to show the applicability of the approach, a correct design of a real-time system with hard real time constraints by applying a set of mapping rules is obtained.

A New Knapsack Public-Key Cryptosystem Based on Permutation Combination Algorithm

A new secure knapsack cryptosystem based on the Merkle-Hellman public key cryptosystem will be proposed in this paper. Although it is common sense that when the density is low, the knapsack cryptosystem turns vulnerable to the low-density attack. The density d of a secure knapsack cryptosystem must be larger than 0.9408 to avoid low-density attack. In this paper, we investigate a new Permutation Combination Algorithm. By exploiting this algorithm, we shall propose a novel knapsack public-key cryptosystem. Our proposed scheme can enjoy a high density to avoid the low-density attack. The density d can also exceed 0.9408 to avoid the low-density attack.

Determination of Critical Source Areas for Sediment Loss: Sarrath River Basin, Tunisia

The risk of water erosion is one of the main environmental concerns in the southern Mediterranean regions. Thus, quantification of soil loss is an important issue for soil and water conservation managers. The objective of this paper is to examine the applicability of the Soil and Water Assessment Tool (SWAT) model in The Sarrath river catchment, North of Tunisia, and to identify the most vulnerable areas in order to help manager implement an effective management program. The spatial analysis of the results shows that 7 % of the catchment experiences very high erosion risk, in need for suitable conservation measures to be adopted on a priority basis. The spatial distribution of erosion risk classes estimated 3% high, 5,4% tolerable, and 84,6% low. Among the 27 delineated subcatchments only 4 sub-catchments are found to be under high and very high soil loss group, two sub-catchments fell under moderate soil loss group, whereas other sub-catchments are under low soil loss group.

Detecting Remote Protein Evolutionary Relationships via String Scoring Method

The amount of the information being churned out by the field of biology has jumped manifold and now requires the extensive use of computer techniques for the management of this information. The predominance of biological information such as protein sequence similarity in the biological information sea is key information for detecting protein evolutionary relationship. Protein sequence similarity typically implies homology, which in turn may imply structural and functional similarities. In this work, we propose, a learning method for detecting remote protein homology. The proposed method uses a transformation that converts protein sequence into fixed-dimensional representative feature vectors. Each feature vector records the sensitivity of a protein sequence to a set of amino acids substrings generated from the protein sequences of interest. These features are then used in conjunction with support vector machines for the detection of the protein remote homology. The proposed method is tested and evaluated on two different benchmark protein datasets and it-s able to deliver improvements over most of the existing homology detection methods.

New Mitigating Technique to Overcome DDOS Attack

In this paper, we explore a new scheme for filtering spoofed packets (DDOS attack) which is a combination of path fingerprint and client puzzle concepts. In this each IP packet has a unique fingerprint is embedded that represents, the route a packet has traversed. The server maintains a mapping table which contains the client IP address and its corresponding fingerprint. In ingress router, client puzzle is placed. For each request, the puzzle issuer provides a puzzle which the source has to solve. Our design has the following advantages over prior approaches, 1) Reduce the network traffic, as we place a client puzzle at the ingress router. 2) Mapping table at the server is lightweight and moderate.

Effect of Crude Extract from Bacillus Subtilis LB5 Cultivated Broth on Conidial Germination of Colletotrichum Gloeosporioides

Bacillus subtilis strain LB5 produced lipopeptide antibiotic iturin A-2 in liquid medium. Crude extract from cell-free supernatant of B. subtilis cultivated broth extracted with n-butanol showed antifungal activity to conidial germination of Colletotrichum gloeosporioides. The germination of conidia was completely inhibited by crude extract. The ultrastructure of conidia after treated with crude extract was found an accumulation of vesiclelike material between cell wall and plasma membrane while this accumulation was not observed in untreated and germinated conidia. Besides, the cell wall was not affected by crude extract.

Fuzzy T-Neighborhood Groups Acting on Sets

In this paper, The T-G-action topology on a set acted on by a fuzzy T-neighborhood (T-neighborhood, for short) group is defined as a final T-neighborhood topology with respect to a set of maps. We mainly prove that this topology is a T-regular Tneighborhood topology.

Monte Carlo Simulation of the Transport Phenomena in Degenerate Hg0.8Cd0.2Te

The present work deals with the calculation of transport properties of Hg0.8Cd0.2Te (MCT) semiconductor in degenerate case. Due to their energy-band structure, this material becomes degenerate at moderate doping densities, which are around 1015 cm-3, so that the usual Maxwell-Boltzmann approximation is inaccurate in the determination of transport parameters. This problem is faced by using Fermi-Dirac (F-D) statistics, and the non-parabolic behavior of the bands may be approximated by the Kane model. The Monte Carlo (MC) simulation is used here to determinate transport parameters: drift velocity, mean energy and drift mobility versus electric field and the doped densities. The obtained results are in good agreement with those extracted from literature.

A Bi-Objective Preventive Healthcare Facility Network Design with Incorporating Cost and Time Saving

Main goal of preventive healthcare problems are at decreasing the likelihood and severity of potentially life-threatening illnesses by protection and early detection. The levels of establishment and staffing costs along with summation of the travel and waiting time that clients spent are considered as objectives functions of the proposed nonlinear integer programming model. In this paper, we have proposed a bi-objective mathematical model for designing a network of preventive healthcare facilities so as to minimize aforementioned objectives, simultaneously. Moreover, each facility acts as M/M/1 queuing system. The number of facilities to be established, the location of each facility, and the level of technology for each facility to be chosen are provided as the main determinants of a healthcare facility network. Finally, to demonstrate performance of the proposed model, four multi-objective decision making techniques are presented to solve the model.

An Approach for Reducing the Computational Complexity of LAMSTAR Intrusion Detection System using Principal Component Analysis

The security of computer networks plays a strategic role in modern computer systems. Intrusion Detection Systems (IDS) act as the 'second line of defense' placed inside a protected network, looking for known or potential threats in network traffic and/or audit data recorded by hosts. We developed an Intrusion Detection System using LAMSTAR neural network to learn patterns of normal and intrusive activities, to classify observed system activities and compared the performance of LAMSTAR IDS with other classification techniques using 5 classes of KDDCup99 data. LAMSAR IDS gives better performance at the cost of high Computational complexity, Training time and Testing time, when compared to other classification techniques (Binary Tree classifier, RBF classifier, Gaussian Mixture classifier). we further reduced the Computational Complexity of LAMSTAR IDS by reducing the dimension of the data using principal component analysis which in turn reduces the training and testing time with almost the same performance.

Variable Step-Size Affine Projection Algorithm With a Weighted and Regularized Projection Matrix

This paper presents a forgetting factor scheme for variable step-size affine projection algorithms (APA). The proposed scheme uses a forgetting processed input matrix as the projection matrix of pseudo-inverse to estimate system deviation. This method introduces temporal weights into the projection matrix, which is typically a better model of the real error's behavior than homogeneous temporal weights. The regularization overcomes the ill-conditioning introduced by both the forgetting process and the increasing size of the input matrix. This algorithm is tested by independent trials with coloured input signals and various parameter combinations. Results show that the proposed algorithm is superior in terms of convergence rate and misadjustment compared to existing algorithms. As a special case, a variable step size NLMS with forgetting factor is also presented in this paper.

Performance Analysis of the Subgroup Method for Collective I/O

As many scientific applications require large data processing, the importance of parallel I/O has been increasingly recognized. Collective I/O is one of the considerable features of parallel I/O and enables application programmers to easily handle their large data volume. In this paper we measured and analyzed the performance of original collective I/O and the subgroup method, the way of using collective I/O of MPI effectively. From the experimental results, we found that the subgroup method showed good performance with small data size.

Multilevel Classifiers in Recognition of Handwritten Kannada Numerals

The recognition of handwritten numeral is an important area of research for its applications in post office, banks and other organizations. This paper presents automatic recognition of handwritten Kannada numerals based on structural features. Five different types of features, namely, profile based 10-segment string, water reservoir; vertical and horizontal strokes, end points and average boundary length from the minimal bounding box are used in the recognition of numeral. The effect of each feature and their combination in the numeral classification is analyzed using nearest neighbor classifiers. It is common to combine multiple categories of features into a single feature vector for the classification. Instead, separate classifiers can be used to classify based on each visual feature individually and the final classification can be obtained based on the combination of separate base classification results. One popular approach is to combine the classifier results into a feature vector and leaving the decision to next level classifier. This method is extended to extract a better information, possibility distribution, from the base classifiers in resolving the conflicts among the classification results. Here, we use fuzzy k Nearest Neighbor (fuzzy k-NN) as base classifier for individual feature sets, the results of which together forms the feature vector for the final k Nearest Neighbor (k-NN) classifier. Testing is done, using different features, individually and in combination, on a database containing 1600 samples of different numerals and the results are compared with the results of different existing methods.

An Expansion Method for Schrödinger Equation of Quantum Billiards with Arbitrary Shapes

A numerical method for solving the time-independent Schrödinger equation of a particle moving freely in a three-dimensional axisymmetric region is developed. The boundary of the region is defined by an arbitrary analytic function. The method uses a coordinate transformation and an expansion in eigenfunctions. The effectiveness is checked and confirmed by applying the method to a particular example, which is a prolate spheroid.

Accessible Business Process Modelling

This article concerns with the accessibility of Business process modelling tools (BPMo tools) and business process modelling languages (BPMo languages). Therefore the reader will be introduced to business process management and the authors' motivation behind this inquiry. Afterwards, the paper will reflect problems when applying inaccessible BPMo tools. To illustrate these problems the authors distinguish between two different categories of issues and provide practical examples. Finally the article will present three approaches to improve the accessibility of BPMo tools and BPMo languages.

Using Teager Energy Cepstrum and HMM distancesin Automatic Speech Recognition and Analysis of Unvoiced Speech

In this study, the use of silicon NAM (Non-Audible Murmur) microphone in automatic speech recognition is presented. NAM microphones are special acoustic sensors, which are attached behind the talker-s ear and can capture not only normal (audible) speech, but also very quietly uttered speech (non-audible murmur). As a result, NAM microphones can be applied in automatic speech recognition systems when privacy is desired in human-machine communication. Moreover, NAM microphones show robustness against noise and they might be used in special systems (speech recognition, speech conversion etc.) for sound-impaired people. Using a small amount of training data and adaptation approaches, 93.9% word accuracy was achieved for a 20k Japanese vocabulary dictation task. Non-audible murmur recognition in noisy environments is also investigated. In this study, further analysis of the NAM speech has been made using distance measures between hidden Markov model (HMM) pairs. It has been shown the reduced spectral space of NAM speech using a metric distance, however the location of the different phonemes of NAM are similar to the location of the phonemes of normal speech, and the NAM sounds are well discriminated. Promising results in using nonlinear features are also introduced, especially under noisy conditions.