Examining Herzberg-s Two Factor Theory in a Large Chinese Chemical Fiber Company

The validity of Herzberg-s Two-Factor Theory of Motivation was tested empirically by surveying 2372 chemical fiber employees in 2012. In the valid sample of 1875 respondents, the degree of overall job satisfaction was more than moderate. The most highly valued components of job satisfaction were: “corporate image," “collaborative working atmosphere," and “supervisor-s expertise"; whereas the lowest mean score was 34.65 for “job rotation and promotion." The top three job retention options rated by the participants were “good image of the enterprise," “good compensation," and “workplace is close to my residence." The overall evaluation of the level of thriving facilitation workplace reached almost to “mostly agree." For those participants who chose at least one motivator as their job retention options had significantly greater job satisfaction than those who chose only hygiene factors as their retention options. Therefore, Herzberg-s Two-Factor Theory of Motivation was proven valid in this study.

Verification Process of Cylindrical Contact Force Models for Internal Contact Modeling

In the numerical solution of the forward dynamics of a multibody system, the positions and velocities of the bodies in the system are obtained first. With the information of the system state variables at each time step, the internal and external forces acting on the system are obtained by appropriate contact force models if the continuous contact method is used instead of a discrete contact method. The local deformation of the bodies in contact, represented by penetration, is used to compute the contact force. The ability and suitability with current cylindrical contact force models to describe the contact between bodies with cylindrical geometries with particular focus on internal contacting geometries involving low clearances and high loads simultaneously is discussed in this paper. A comparative assessment of the performance of each model under analysis for different contact conditions, in particular for very different penetration and clearance values, is presented. It is demonstrated that some models represent a rough approximation to describe the conformal contact between cylindrical geometries because contact forces are underestimated.

Biological Data Integration using SOA

Nowadays scientific data is inevitably digital and stored in a wide variety of formats in heterogeneous systems. Scientists need to access an integrated view of remote or local heterogeneous data sources with advanced data accessing, analyzing, and visualization tools. This research suggests the use of Service Oriented Architecture (SOA) to integrate biological data from different data sources. This work shows SOA will solve the problems that facing integration process and if the biologist scientists can access the biological data in easier way. There are several methods to implement SOA but web service is the most popular method. The Microsoft .Net Framework used to implement proposed architecture.

Adaptive Network Intrusion Detection Learning: Attribute Selection and Classification

In this paper, a new learning approach for network intrusion detection using naïve Bayesian classifier and ID3 algorithm is presented, which identifies effective attributes from the training dataset, calculates the conditional probabilities for the best attribute values, and then correctly classifies all the examples of training and testing dataset. Most of the current intrusion detection datasets are dynamic, complex and contain large number of attributes. Some of the attributes may be redundant or contribute little for detection making. It has been successfully tested that significant attribute selection is important to design a real world intrusion detection systems (IDS). The purpose of this study is to identify effective attributes from the training dataset to build a classifier for network intrusion detection using data mining algorithms. The experimental results on KDD99 benchmark intrusion detection dataset demonstrate that this new approach achieves high classification rates and reduce false positives using limited computational resources.

Performance Improvement in the Bivariate Models by using Modified Marginal Variance of Noisy Observations for Image-Denoising Applications

Most simple nonlinear thresholding rules for wavelet- based denoising assume that the wavelet coefficients are independent. However, wavelet coefficients of natural images have significant dependencies. This paper attempts to give a recipe for selecting one of the popular image-denoising algorithms based on VisuShrink, SureShrink, OracleShrink, BayesShrink and BiShrink and also this paper compares different Bivariate models used for image denoising applications. The first part of the paper compares different Shrinkage functions used for image-denoising. The second part of the paper compares different bivariate models and the third part of this paper uses the Bivariate model with modified marginal variance which is based on Laplacian assumption. This paper gives an experimental comparison on six 512x512 commonly used images, Lenna, Barbara, Goldhill, Clown, Boat and Stonehenge. The following noise powers 25dB,26dB, 27dB, 28dB and 29dB are added to the six standard images and the corresponding Peak Signal to Noise Ratio (PSNR) values are calculated for each noise level.

An Efficient Algorithm for Motion Detection Based Facial Expression Recognition using Optical Flow

One of the popular methods for recognition of facial expressions such as happiness, sadness and surprise is based on deformation of facial features. Motion vectors which show these deformations can be specified by the optical flow. In this method, for detecting emotions, the resulted set of motion vectors are compared with standard deformation template that caused by facial expressions. In this paper, a new method is introduced to compute the quantity of likeness in order to make decision based on the importance of obtained vectors from an optical flow approach. For finding the vectors, one of the efficient optical flow method developed by Gautama and VanHulle[17] is used. The suggested method has been examined over Cohn-Kanade AU-Coded Facial Expression Database, one of the most comprehensive collections of test images available. The experimental results show that our method could correctly recognize the facial expressions in 94% of case studies. The results also show that only a few number of image frames (three frames) are sufficient to detect facial expressions with rate of success of about 83.3%. This is a significant improvement over the available methods.

The Issues of Effectiveness of Advertisement Communication Process: A Case Study of Lithuania Consumers

The goal of this study was to disclose the core of the advertising research based on the psychological aspects by acquainting with the nature of advertising research and revealing the importance of psychological aspects of advertising during the advertising research. The growing interest in consumer response to advertisement served as an encouragement to make the analysis of psychological aspects of the advertising research, because the information obtained during the advertising research helps to answer the question how advertising really works. In the research analysis focuses on the nature of advertising research. The place of advertising research in advertisement planning process and the advertising research process are unfolded. Moreover, the importance of psychological aspects in the advertising research is being examined. The certain psychological aspects like the particularities of advertising communication process, psychological process that are active at advertising acceptance and awareness process as well as the advertising effects are analysed in more detail.

Steady-State Analysis and Control of Double Feed Induction Motor

This paper explores steady-state characteristics of grid-connected doubly fed induction motor (DFIM) in case of unity power factor operation. Based on the synchronized mathematical model, analytic determination of the control laws is presented and illustrated by various figures to understand the effect of the applied rotor voltage on the speed and the active power. On other hand, unlike previous works where the stator resistance was neglected, in this work, stator resistance is included such that the equations can be applied to small wind turbine generators which are becoming more popular. Finally the work is crowned by integration of the studied induction generator in a wind system where an open loop control is proposed confers a remarkable simplicity of implementation compared to the known methods.

One-DOF Precision Position Control using the Combined Piezo-VCM Actuator

This paper presents the control performance of a high-precision positioning device using the hybrid actuator composed of a piezoelectric (PZT) actuator and a voice-coil motor (VCM). The combined piezo-VCM actuator features two main characteristics: a large operation range due to long stroke of the VCM, and high precision and heavy load positioning ability due to PZT impact force. A one-degree-of-freedom (DOF) experimental setup was configured to examine the fundamental characteristics, and the control performance was effectively demonstrated by using a switching controller. In rough positioning state, an integral variable structure controller (IVSC) was used for the VCM to conduct long range of operation; in precision positioning state, an impact force controller (IFC) for the PZT actuator coupled with presliding states of the sliding table was used to obtain high-precision position control and achieve both forward and backward actuations. The experimental results showed that the sliding table having a mass of 881g and with a preload of 10 N was successfully positioned within the positioning accuracy of 10 nm in both forward and backward position controls.

Understanding and Designing Situation-Aware Mobile and Ubiquitous Computing Systems

Using spatial models as a shared common basis of information about the environment for different kinds of contextaware systems has been a heavily researched topic in the last years. Thereby the research focused on how to create, to update, and to merge spatial models so as to enable highly dynamic, consistent and coherent spatial models at large scale. In this paper however, we want to concentrate on how context-aware applications could use this information so as to adapt their behavior according to the situation they are in. The main idea is to provide the spatial model infrastructure with a situation recognition component based on generic situation templates. A situation template is – as part of a much larger situation template library – an abstract, machinereadable description of a certain basic situation type, which could be used by different applications to evaluate their situation. In this paper, different theoretical and practical issues – technical, ethical and philosophical ones – are discussed important for understanding and developing situation dependent systems based on situation templates. A basic system design is presented which allows for the reasoning with uncertain data using an improved version of a learning algorithm for the automatic adaption of situation templates. Finally, for supporting the development of adaptive applications, we present a new situation-aware adaptation concept based on workflows.

A Distributed Cognition Framework to Compare E-Commerce Websites Using Data Envelopment Analysis

This paper presents an approach based on the adoption of a distributed cognition framework and a non parametric multicriteria evaluation methodology (DEA) designed specifically to compare e-commerce websites from the consumer/user viewpoint. In particular, the framework considers a website relative efficiency as a measure of its quality and usability. A website is modelled as a black box capable to provide the consumer/user with a set of functionalities. When the consumer/user interacts with the website to perform a task, he/she is involved in a cognitive activity, sustaining a cognitive cost to search, interpret and process information, and experiencing a sense of satisfaction. The degree of ambiguity and uncertainty he/she perceives and the needed search time determine the effort size – and, henceforth, the cognitive cost amount – he/she has to sustain to perform his/her task. On the contrary, task performing and result achievement induce a sense of gratification, satisfaction and usefulness. In total, 9 variables are measured, classified in a set of 3 website macro-dimensions (user experience, site navigability and structure). The framework is implemented to compare 40 websites of businesses performing electronic commerce in the information technology market. A questionnaire to collect subjective judgements for the websites in the sample was purposely designed and administered to 85 university students enrolled in computer science and information systems engineering undergraduate courses.

A Self Adaptive Genetic Based Algorithm for the Identification and Elimination of Bad Data

The identification and elimination of bad measurements is one of the basic functions of a robust state estimator as bad data have the effect of corrupting the results of state estimation according to the popular weighted least squares method. However this is a difficult problem to handle especially when dealing with multiple errors from the interactive conforming type. In this paper, a self adaptive genetic based algorithm is proposed. The algorithm utilizes the results of the classical linearized normal residuals approach to tune the genetic operators thus instead of making a randomized search throughout the whole search space it is more likely to be a directed search thus the optimum solution is obtained at very early stages(maximum of 5 generations). The algorithm utilizes the accumulating databases of already computed cases to reduce the computational burden to minimum. Tests are conducted with reference to the standard IEEE test systems. Test results are very promising.

Toward a New Simple Analytical Formulation of Navier-Stokes Equations

Incompressible Navier-Stokes equations are reviewed in this work. Three-dimensional Navier-Stokes equations are solved analytically. The Mathematical derivation shows that the solutions for the zero and constant pressure gradients are similar. Descriptions of the proposed formulation and validation against two laminar experiments and three different turbulent flow cases are reported in this paper. Even though, the analytical solution is derived for nonreacting flows, it could reproduce trends for cases including combustion.

Preliminary Assessment of Feasibility of a Wind Energy Conversion System for a Martian Probe or Surface Rover

Nuclear energy sources have been widely used in the past decades in order to power spacecraft subsystems. Nevertheless, their use has attracted controversy because of the risk of harmful material released into the atmosphere if an accident were to occur during the launch phase of the mission, leading to the general adoption of photovoltaic systems. As compared to solar cells, wind turbines have a great advantage on Mars, as they can continuously produce power both during dust storms and at night-time: this paper focuses on the potential of a wind energy conversion system (WECS) considering the atmospheric conditions on Mars. Wind potential on Martian surface has been estimated, as well as the average energy requirements of a Martian probe or surface rover. Finally, the expected daily energy output of the WECS has been computed on the basis of both the swept area of the rotor and the equivalent wind speed at the landing site.

Computational Aspects of Regression Analysis of Interval Data

We consider linear regression models where both input data (the values of independent variables) and output data (the observations of the dependent variable) are interval-censored. We introduce a possibilistic generalization of the least squares estimator, so called OLS-set for the interval model. This set captures the impact of the loss of information on the OLS estimator caused by interval censoring and provides a tool for quantification of this effect. We study complexity-theoretic properties of the OLS-set. We also deal with restricted versions of the general interval linear regression model, in particular the crisp input – interval output model. We give an argument that natural descriptions of the OLS-set in the crisp input – interval output cannot be computed in polynomial time. Then we derive easily computable approximations for the OLS-set which can be used instead of the exact description. We illustrate the approach by an example.

Analysis of Program PRIME at Brazil

Policies that support entrepreneurship are keys to the generation of new business. In Brazil, seed capital, installation of technology parks, programs and zero interest financing, economic subsidy as Program First Innovative Company (PRIME) are examples of incentive policies. For the implementation of PRIME, in particular the Brazilian Innovation Agency (FINEP) decentralized operationalization so that business incubators could select innovative projects. This paper analyzes the program PRIME Business Incubator Center of the State of Sergipe (CISE) after calculating the mean and standard deviation of the grades obtained by companies in the factors of innovation, market potential, financial return economic, market strategy and staff and application of the Mann-Whitney test.

Review of Surface Electromyogram Signals: Its Analysis and Applications

Electromyography (EMG) is the study of muscles function through analysis of electrical activity produced from muscles. This electrical activity which is displayed in the form of signal is the result of neuromuscular activation associated with muscle contraction. The most common techniques of EMG signal recording are by using surface and needle/wire electrode where the latter is usually used for interest in deep muscle. This paper will focus on surface electromyogram (SEMG) signal. During SEMG recording, several problems had to been countered such as noise, motion artifact and signal instability. Thus, various signal processing techniques had been implemented to produce a reliable signal for analysis. SEMG signal finds broad application particularly in biomedical field. It had been analyzed and studied for various interests such as neuromuscular disease, enhancement of muscular function and human-computer interface.

Topological Properties of an Exponential Random Geometric Graph Process

In this paper we consider a one-dimensional random geometric graph process with the inter-nodal gaps evolving according to an exponential AR(1) process. The transition probability matrix and stationary distribution are derived for the Markov chains concerning connectivity and the number of components. We analyze the algorithm for hitting time regarding disconnectivity. In addition to dynamical properties, we also study topological properties for static snapshots. We obtain the degree distributions as well as asymptotic precise bounds and strong law of large numbers for connectivity threshold distance and the largest nearest neighbor distance amongst others. Both exact results and limit theorems are provided in this paper.

Minaret of Medieval City Aktobe

In the article the remains of the base of the minaret, found in 2009 at the medieval fortress shakhristan Aktobe, which is located along the courses of the rivers Balta and Aksu. The minaret, which consists of two parts: the stylobate in the pit and base part refers to the XI-XII centuries. The preserved height of the building is 3.6 meters. Volume stylobat quadrangular minaret, the corners of which are aimed at the four corners of the world amounts to 8,65 x8, 5 m, height – 2.6 m. Diameter octagonal upper cap of 7.85 m and a height of preserved – 1 m. This minaret is of particular importance among the historical and architectural monuments of Kazakhstan, as it is so far the only minaret belonging to Karakhanid epoch in which Islam was the state religion.

Dynamic Analysis of Porous Media Using Finite Element Method

The mechanical behavior of porous media is governed by the interaction between its solid skeleton and the fluid existing inside its pores. The interaction occurs through the interface of gains and fluid. The traditional analysis methods of porous media, based on the effective stress and Darcy's law, are unable to account for these interactions. For an accurate analysis, the porous media is represented in a fluid-filled porous solid on the basis of the Biot theory of wave propagation in poroelastic media. In Biot formulation, the equations of motion of the soil mixture are coupled with the global mass balance equations to describe the realistic behavior of porous media. Because of irregular geometry, the domain is generally treated as an assemblage of fmite elements. In this investigation, the numerical formulation for the field equations governing the dynamic response of fluid-saturated porous media is analyzed and employed for the study of transient wave motion. A finite element model is developed and implemented into a computer code called DYNAPM for dynamic analysis of porous media. The weighted residual method with 8-node elements is used for developing of a finite element model and the analysis is carried out in the time domain considering the dynamic excitation and gravity loading. Newmark time integration scheme is developed to solve the time-discretized equations which are an unconditionally stable implicit method Finally, some numerical examples are presented to show the accuracy and capability of developed model for a wide variety of behaviors of porous media.