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.

An Energy-Efficient Distributed Unequal Clustering Protocol for Wireless Sensor Networks

The wireless sensor networks have been extensively deployed and researched. One of the major issues in wireless sensor networks is a developing energy-efficient clustering protocol. Clustering algorithm provides an effective way to prolong the lifetime of a wireless sensor networks. In the paper, we compare several clustering protocols which significantly affect a balancing of energy consumption. And we propose an Energy-Efficient Distributed Unequal Clustering (EEDUC) algorithm which provides a new way of creating distributed clusters. In EEDUC, each sensor node sets the waiting time. This waiting time is considered as a function of residual energy, number of neighborhood nodes. EEDUC uses waiting time to distribute cluster heads. We also propose an unequal clustering mechanism to solve the hot-spot problem. Simulation results show that EEDUC distributes the cluster heads, balances the energy consumption well among the cluster heads and increases the network lifetime.

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.

Agreement Options in Multi-person Decision on Optimizing High-Rise Building Columns

This paper presents a conceptual model of agreement options for negotiation support in multi-person decision on optimizing high-rise building columns. The decision is complicated since many parties involved in choosing a single alternative from a set of solutions. There are different concern caused by differing preferences, experiences, and background. Such building columns as alternatives are referred to as agreement options which are determined by identifying the possible decision maker group, followed by determining the optimal solution for each group. The group in this paper is based on three-decision makers preferences that are designer, programmer, and construction manager. Decision techniques applied to determine the relative value of the alternative solutions for performing the function. Analytical Hierarchy Process (AHP) was applied for decision process and game theory based agent system for coalition formation. An n-person cooperative game is represented by the set of all players. The proposed coalition formation model enables each agent to select individually its allies or coalition. It further emphasizes the importance of performance evaluation in the design process and value-based decision.

Ethics in the Technology Driven Enterprise

Innovations in technology have created new ethical challenges. Essential use of electronic communication in the workplace has escalated at an astronomical rate over the past decade. As such, legal and ethical dilemmas confronted by both the employer and the employee concerning managerial control and ownership of einformation have increased dramatically in the USA. From the employer-s perspective, ownership and control of all information created for the workplace is an undeniable source of economic advantage and must be monitored zealously. From the perspective of the employee, individual rights, such as privacy, freedom of speech, and freedom from unreasonable search and seizure, continue to be stalwart legal guarantees that employers are not legally or ethically entitled to abridge in the workplace. These issues have been the source of great debate and the catalyst for legal reform. The fine line between ethical and legal has been complicated by emerging technologies. This manuscript will identify and discuss a number of specific legal and ethical issues raised by the dynamic electronic workplace and conclude with suggestions that employers should follow to respect the delicate balance between employees- legal rights to privacy and the employer's right to protect its knowledge systems and infrastructure.

Feature Reduction of Nearest Neighbor Classifiers using Genetic Algorithm

The design of a pattern classifier includes an attempt to select, among a set of possible features, a minimum subset of weakly correlated features that better discriminate the pattern classes. This is usually a difficult task in practice, normally requiring the application of heuristic knowledge about the specific problem domain. The selection and quality of the features representing each pattern have a considerable bearing on the success of subsequent pattern classification. Feature extraction is the process of deriving new features from the original features in order to reduce the cost of feature measurement, increase classifier efficiency, and allow higher classification accuracy. Many current feature extraction techniques involve linear transformations of the original pattern vectors to new vectors of lower dimensionality. While this is useful for data visualization and increasing classification efficiency, it does not necessarily reduce the number of features that must be measured since each new feature may be a linear combination of all of the features in the original pattern vector. In this paper a new approach is presented to feature extraction in which feature selection, feature extraction, and classifier training are performed simultaneously using a genetic algorithm. In this approach each feature value is first normalized by a linear equation, then scaled by the associated weight prior to training, testing, and classification. A knn classifier is used to evaluate each set of feature weights. The genetic algorithm optimizes a vector of feature weights, which are used to scale the individual features in the original pattern vectors in either a linear or a nonlinear fashion. By this approach, the number of features used in classifying can be finely reduced.

Radiation Safety of Population in the Region of NPP-2006/MIR-1200 Site

The main features of NPP-2006/MIR-1200 design are described. Estimation of individual doses for population under normal operation and accident conditions is performed for Leningradskaya NPP – 2 as an example. The radiation effect on population and environment doesn-t exceed the established normative limit and is as low as reasonably achievable. NPP- 2006/MIR-1200 design meets all Russian and international requirements for power units under construction.

Multi-Stakeholder Road Pricing Game: Solution Concepts

A road pricing game is a game where various stakeholders and/or regions with different (and usually conflicting) objectives compete for toll setting in a given transportation network to satisfy their individual objectives. We investigate some classical game theoretical solution concepts for the road pricing game. We establish results for the road pricing game so that stakeholders and/or regions playing such a game will beforehand know what is obtainable. This will save time and argument, and above all, get rid of the feelings of unfairness among the competing actors and road users. Among the classical solution concepts we investigate is Nash equilibrium. In particular, we show that no pure Nash equilibrium exists among the actors, and further illustrate that even “mixed Nash equilibrium" may not be achievable in the road pricing game. The paper also demonstrates the type of coalitions that are not only reachable, but also stable and profitable for the actors involved.

Speckle Reducing Contourlet Transform for Medical Ultrasound Images

Speckle noise affects all coherent imaging systems including medical ultrasound. In medical images, noise suppression is a particularly delicate and difficult task. A tradeoff between noise reduction and the preservation of actual image features has to be made in a way that enhances the diagnostically relevant image content. Even though wavelets have been extensively used for denoising speckle images, we have found that denoising using contourlets gives much better performance in terms of SNR, PSNR, MSE, variance and correlation coefficient. The objective of the paper is to determine the number of levels of Laplacian pyramidal decomposition, the number of directional decompositions to perform on each pyramidal level and thresholding schemes which yields optimal despeckling of medical ultrasound images, in particular. The proposed method consists of the log transformed original ultrasound image being subjected to contourlet transform, to obtain contourlet coefficients. The transformed image is denoised by applying thresholding techniques on individual band pass sub bands using a Bayes shrinkage rule. We quantify the achieved performance improvement.

Improved IDR(s) Method for Gaining Very Accurate Solutions

The IDR(s) method based on an extended IDR theorem was proposed by Sonneveld and van Gijzen. The original IDR(s) method has excellent property compared with the conventional iterative methods in terms of efficiency and small amount of memory. IDR(s) method, however, has unexpected property that relative residual 2-norm stagnates at the level of less than 10-12. In this paper, an effective strategy for stagnation detection, stagnation avoidance using adaptively information of parameter s and improvement of convergence rate itself of IDR(s) method are proposed in order to gain high accuracy of the approximated solution of IDR(s) method. Through numerical experiments, effectiveness of adaptive tuning IDR(s) method is verified and demonstrated.

Scrum as the Method Supporting the Implementation of Knowledge Management in an Organization

Many companies have switched their processes to project-oriented in the last years. This brings new possibilities and effectiveness not only in the field of external processes connected with the product delivery but also the internal processes as well. However centralized project organization which is based on the role of project manager in the team has proved insufficient in some cases. Agile methods of project organization are trying to solve this problem by bringing new view on the project organization, roles, processes and competences. Scrum is one of these methods which builds on the principles of knowledge management to drive the project to effectiveness from all view angles. Using this method to organize internal and delivery projects helps the organization to create and share knowledge throughout the company. It also supports forming unique competences of individuals and project teams and drives innovations in the company.

New Triangle-Ring UWB Bandpass Filter with Sharp Roll-Off and Dual Notched Bands

This paper presents a new ultra-wideband (UWB) bandpass filter (BPF) with sharp roll-off and dual-notched bands. The filter consists of a triangle ring multi-mode resonator (MMR) with the stub-loaded resonator (SLR) for controlling the two transmission zeros at 2.8 / 11 GHz, the embedded open-circuited stub and the asymmetric tight coupled input/output (I/O) lines for introducing the dual notched bands at 5.2 / 6.8 GHz. The attenuation slope in the lower and higher passband edges of the proposed filter show 160- and 153-dB/GHz, respectively. This study mainly provides a simple method to design a UWB bandpass filter with high passband selectivity and dual-notched bands for satisfying the Federal Communications Commission (FCC-defined) indoor UWB specification

On the Effectivity of Different Pseudo-Noise and Orthogonal Sequences for Speech Encryption from Correlation Properties

We analyze the effectivity of different pseudo noise (PN) and orthogonal sequences for encrypting speech signals in terms of perceptual intelligence. Speech signal can be viewed as sequence of correlated samples and each sample as sequence of bits. The residual intelligibility of the speech signal can be reduced by removing the correlation among the speech samples. PN sequences have random like properties that help in reducing the correlation among speech samples. The mean square aperiodic auto-correlation (MSAAC) and the mean square aperiodic cross-correlation (MSACC) measures are used to test the randomness of the PN sequences. Results of the investigation show the effectivity of large Kasami sequences for this purpose among many PN sequences.

Current Controlled Current Conveyor (CCCII)and Application using 65nm CMOS Technology

Current mode circuits like current conveyors are getting significant attention in current analog ICs design due to their higher band-width, greater linearity, larger dynamic range, simpler circuitry, lower power consumption and less chip area. The second generation current controlled conveyor (CCCII) has the advantage of electronic adjustability over the CCII i.e. in CCCII; adjustment of the X-terminal intrinsic resistance via a bias current is possible. The presented approach is based on the CMOS implementation of second generation positive (CCCII+), negative (CCCII-) and dual Output Current Controlled Conveyor (DOCCCII) and its application as Universal filter. All the circuits have been designed and simulated using 65nm CMOS technology model parameters on Cadence Virtuoso / Spectre using 1V supply voltage. Various simulations have been carried out to verify the linearity between output and input ports, range of operation frequency, etc. The outcomes show good agreement between expected and experimental results.

Synthesis of Silver Nanoparticles by Chemical Reduction Method and Their Antibacterial Activity

Silver nanoparticles were prepared by chemical reduction method. Silver nitrate was taken as the metal precursor and hydrazine hydrate as a reducing agent. The formation of the silver nanoparticles was monitored using UV-Vis absorption spectroscopy. The UV-Vis spectroscopy revealed the formation of silver nanopart├¡cles by exhibing the typical surface plasmon absorption maxima at 418-420 nm from the UV–Vis spectrum. Comparison of theoretical (Mie light scattering theory) and experimental results showed that diameter of silver nanoparticles in colloidal solution is about 60 nm. We have used energy-dispersive spectroscopy (EDX), X-ray diffraction (XRD), transmission electron microscopy (TEM) and, UV–Vis spectroscopy to characterize the nanoparticles obtained. The energy-dispersive spectroscopy (EDX) of the nanoparticles dispersion confirmed the presence of elemental silver signal no peaks of other impurity were detected. The average size and morphology of silver nanoparticles were determined by transmission electron microscopy (TEM). TEM photographs indicate that the nanopowders consist of well dispersed agglomerates of grains with a narrow size distribution (40 and 60 nm), whereas the radius of the individual particles are between 10 and 20 nm. The synthesized nanoparticles have been structurally characterized by X-ray diffraction and transmission high-energy electron diffraction (HEED). The peaks in the XRD pattern are in good agreement with the standard values of the face-centered-cubic form of metallic silver (ICCD-JCPDS card no. 4-0787) and no peaks of other impurity crystalline phases were detected. Additionally, the antibacterial activity of the nanopart├¡culas dispersion was measured by Kirby-Bauer method. The nanoparticles of silver showed high antimicrobial and bactericidal activity against gram positive bacteria such as Escherichia Coli, Pseudimonas aureginosa and staphylococcus aureus which is a highly methicillin resistant strain.

Knowledge Sharing Behavior in E-Communities: from the Perspective of Transaction Cost Theory

This study aims to examine the factors affecting knowledge sharing behavior in knowledge-based electronic communities (e-communities) because quantity and quality of knowledge shared among the members play a critical role in the community-s sustainability. Past research has suggested three perspectives that may affect the quantity and quality of knowledge shared: economics, social psychology, and social ecology. In this study, we strongly believe that an economic perspective may be suitable to validate factors influencing newly registered members- knowledge contribution at the beginning of relationship development. Accordingly, this study proposes a model to validate the factors influencing members- knowledge sharing based on Transaction Cost Theory. By doing so, we may empirically test our hypotheses in various types of e-communities to determine the generalizability of our research models.

Hazard Identification and Sensitivity of Potential Resource of Emergency Water Supply

The paper presents the case study of hazard identification and sensitivity of potential resource of emergency water supply as part of the application of methodology classifying the resources of drinking water for emergency supply of population. The case study has been carried out on a selected resource of emergency water supply in one region of the Czech Republic. The hazard identification and sensitivity of potential resource of emergency water supply is based on a unique procedure and developed general registers of selected types of hazards and sensitivities. The registers have been developed with the help of the “Fault Tree Analysis” method in combination with the “What if method”. The identified hazards for the assessed resource include hailstorms and torrential rains, drought, soil erosion, accidents of farm machinery, and agricultural production. The developed registers of hazards and vulnerabilities and a semi-quantitative assessment of hazards for individual parts of hydrological structure and technological elements of presented drilled wells are the basis for a semi-quantitative risk assessment of potential resource of emergency supply of population and the subsequent classification of such resource within the system of crisis planning.

Study of the Effect of Over-expansion Factor on the Flow Transition in Dual Bell Nozzles

Dual bell nozzle is a promising one among the altitude adaptation nozzle concepts, which offer increased nozzle performance in rocket engines. Its advantage is the simplicity it offers due to the absence of any additional mechanical device or movable parts. Hence it offers reliability along with improved nozzle performance as demanded by future launch vehicles. Among other issues, the flow transition to the extension nozzle of a dual bell nozzle is one of the major issues being studied in the development of dual bell nozzle. A parameter named over-expansion factor, which controls the value of the wall inflection angle, has been reported to have substantial influence in this transition process. This paper studies, through CFD and cold flow experiments, the effect of overexpansion factor on flow transition in dual bell nozzles.

A Strategy for a Robust Design of Cracked Stiffened Panels

This work is focused on the numerical prediction of the fracture resistance of a flat stiffened panel made of the aluminium alloy 2024 T3 under a monotonic traction condition. The performed numerical simulations have been based on the micromechanical Gurson-Tvergaard (GT) model for ductile damage. The applicability of the GT model to this kind of structural problems has been studied and assessed by comparing numerical results, obtained by using the WARP 3D finite element code, with experimental data available in literature. In the sequel a home-made procedure is presented, which aims to increase the residual strength of a cracked stiffened aluminum panel and which is based on the stochastic design improvement (SDI) technique; a whole application example is then given to illustrate the said technique.

A Study of Computational Organizational Narrative Generation for Decision Support

Narratives are invaluable assets of human lives. Due to the distinct features of narratives, they are useful for supporting human reasoning processes. However, many useful narratives become residuals in organizations or human minds nowadays. Researchers have contributed effort to investigate and improve narrative generation processes. This paper attempts to contemplate essential components in narratives and explore a computational approach to acquire and extract knowledge to generate narratives. The methodology and significant benefit for decision support are presented.