Fuzzy Types Clustering for Microarray Data

The main goal of microarray experiments is to quantify the expression of every object on a slide as precisely as possible, with a further goal of clustering the objects. Recently, many studies have discussed clustering issues involving similar patterns of gene expression. This paper presents an application of fuzzy-type methods for clustering DNA microarray data that can be applied to typical comparisons. Clustering and analyses were performed on microarray and simulated data. The results show that fuzzy-possibility c-means clustering substantially improves the findings obtained by others.

A “Greedy“ Czech Manufacturing Case

The article describes a case study on one of Czech Republic-s manufacturing middle size enterprises (ME), where due to the European financial crisis, production lines had to be redesigned and optimized in order to minimize the total costs of the production of goods. It is considered an optimization problem of minimizing the total cost of the work load, according to the costs of the possible locations of the workplaces, with an application of the Greedy algorithm and a partial analogy to a Set Packing Problem. The displacement of working tables in a company should be as a one-toone monotone increasing function in order for the total costs of production of the goods to be at minimum. We use a heuristic approach with greedy algorithm for solving this linear optimization problem, regardless the possible greediness which may appear and we apply it in a Czech ME.

3D CFD Simulation of Thermal Hydraulic Performances on Louvered Fin Automotive Heat Exchangers

This study deals with Computational Fluid Dynamics (CFD) studies of the interactions between the air flow and louvered fins which equipped the automotive heat exchangers. 3D numerical simulation results are obtained by using the ANSYS Fluent 13.0 code and compared to experimental data. The paper studies the effect of louver angle and louver pitch geometrical parameters, on overall thermal hydraulic performances of louvered fins. The comparison between CFD simulations and experimental data show that established 3-D CFD model gives a good agreement. The validation agrees, with about 7% of deviation respectively of friction and Colburn factors to experimental results. As first, it is found that the louver angle has a strong influence on the heat transfer rate. Then, louver angle and louver pitch variation of the louvers and their effects on thermal hydraulic performances are studied. In addition to this study, it is shown that the second half of the fin takes has a significant contribution on pressure drop increase without any increase in heat transfer.

Creating Maintenance Cost Model for University Buildings

Maintenance costs incurred on building differs. The difference can be as results of the types, functions, age, building health index, size, form height, location and complexity of the building. These are contributing to the difficulty in maintenance development of deterministic maintenance cost model. This paper is concerns with reporting the preliminary findings on the creation of building maintenance cost distributions for universities in Malaysia. This study is triggered by the need to provide guides on maintenance costs distributions for decision making. For this purpose, a survey questionnaire was conducted to investigate the distribution of maintenance costs in the universities. Altogether, responses were received from twenty universities comprising both private and publicly owned. The research found that engineering services, roofing and finishes were the elements contributing the larger segment of the maintenance costs. Furthermore, the study indicates the significance of maintenance cost distribution as decision making tool towards maintenance management.

Self-Organization of Clusters having Locally Distributed Patterns for Synchronized Inputs

Many experimental results suggest that more precise spike timing is significant in neural information processing. We construct a self-organization model using the spatiotemporal patterns, where Spike-Timing Dependent Plasticity (STDP) tunes the conduction delays between neurons. We show that the fluctuation of conduction delays causes globally continuous and locally distributed firing patterns through the self-organization.

Game Skill Measure for Mixed Games

Games can be classified as games of skill, games of chance or otherwise be classified as mixed. This paper deals with the topic of scientifically classifying mixed games as more reliant on elements of chance or elements of skill and ways to scientifically measure the amount of skill involved. This is predominantly useful for classification of games as legal or illegal in deferent jurisdictions based on the local gaming laws. We propose a novel measure of skill to chance ratio called the Game Skill Measure (GSM) and utilize it to calculate the skill component of a popular variant of Poker.

The Design and Analysis of Learning Effects for a Game-based Learning System

The major purpose of this study is to use network and multimedia technologies to build a game-based learning system for junior high school students to apply in learning “World Geography" through the “role-playing" game approaches. This study first investigated the motivation and habits of junior high school students to use the Internet and online games, and then designed a game-based learning system according to situated and game-based learning theories. A teaching experiment was conducted to analyze the learning effectiveness of students on the game-based learning system and the major factors affecting their learning. A questionnaire survey was used to understand the students- attitudes towards game-based learning. The results showed that the game-based learning system can enhance students- learning, but the gender of students and their habits in using the Internet have no significant impact on learning. Game experience has a significant impact on students- learning, and the higher the experience value the better the effectiveness of their learning. The results of questionnaire survey also revealed that the system can increase students- motivation and interest in learning "World Geography".

Object-Based Image Indexing and Retrieval in DCT Domain using Clustering Techniques

In this paper, we present a new and effective image indexing technique that extracts features directly from DCT domain. Our proposed approach is an object-based image indexing. For each block of size 8*8 in DCT domain a feature vector is extracted. Then, feature vectors of all blocks of image using a k-means algorithm is clustered into groups. Each cluster represents a special object of the image. Then we select some clusters that have largest members after clustering. The centroids of the selected clusters are taken as image feature vectors and indexed into the database. Also, we propose an approach for using of proposed image indexing method in automatic image classification. Experimental results on a database of 800 images from 8 semantic groups in automatic image classification are reported.

Value of Sharing: Viral Advertisement

Sharing motivations of viral advertisements by consumers and the impacts of these advertisements on the perceptions for brand will be questioned in this study. Three fundamental questions are answered in the study. These are advertisement watching and sharing motivations of individuals, criteria of liking viral advertisement and the impact of individual attitudes for viral advertisement on brand perception respectively. This study will be carried out via a viral advertisement which was practiced in Turkey. The data will be collected by survey method and the sample of the study consists of individuals who experienced the practice of sample advertisement. Data will be collected by online survey method and will be analyzed by using SPSS statistical package program. Recently traditional advertisement mind have been changing. New advertising approaches which have significant impacts on consumers have been argued. Viral advertising is a modernist advertisement mind which offers significant advantages to brands apart from traditional advertising channels such as television, radio and magazines. Viral advertising also known as Electronic Word-of- Mouth (eWOM) consists of free spread of convincing messages sent by brands among interpersonal communication. When compared to the traditional advertising, a more provocative thematic approach is argued. The foundation of this approach is to create advertisements that are worth sharing with others by consumers. When that fact is taken into consideration, in a manner of speaking it can also be stated that viral advertising is media engineering. The content worth sharing makes people being a volunteer spokesman of a brand and strengthens the emotional bonds among brand and consumer. Especially for some sectors in countries which are having traditional advertising channel limitations, viral advertising creates vital advantages.

Comparative Approach of Measuring Price Risk on Romanian and International Wheat Market

This paper aims to present the main instruments used in the economic literature for measuring the price risk, pointing out on the advantages brought by the conditional variance in this respect. The theoretical approach will be exemplified by elaborating an EGARCH model for the price returns of wheat, both on Romanian and on international market. To our knowledge, no previous empirical research, either on price risk measurement for the Romanian markets or studies that use the ARIMA-EGARCH methodology, have been conducted. After estimating the corresponding models, the paper will compare the estimated conditional variance on the two markets.

Operation Assay of an Industrial Single-Source – Single-Detector Gamma CT Using MCNP4C Code Simulation and Experimental Test Comparisons

A 3D industrial computed tomography (CT) manufactured based on a first generation CT systems, single-source – single-detector, was evaluated. Operation accuracy assessment of the manufactured system was achieved using simulation in comparison with experimental tests. 137Cs and 60Co were used as a gamma source. Simulations were achieved using MCNP4C code. Experimental tests of 137Cs were in good agreement with the simulations

Process Simulation of Ethyl tert-Butyl Ether (ETBE) Production from Naphtha Cracking Wastes

The production of ethyl tert-butyl ether (ETBE) was simulated through Aspen Plus. The objective of this work was to use the simulation results to be an alternative platform for ETBE production from naphtha cracking wastes for the industry to develop. ETBE is produced from isobutylene which is one of the wastes in naphtha cracking process. The content of isobutylene in the waste is less than 30% weight. The main part of this work was to propose a process to save the environment and to increase the product value by converting a great majority of the wastes into ETBE. Various processes were considered to determine the optimal production of ETBE. The proposed process increased ETBE production yield by 100% from conventional process with the purity of 96% weight. The results showed a great promise for developing this proposed process in an industrial scale.

New Wavelet-Based Superresolution Algorithm for Speckle Reduction in SAR Images

This paper describes a novel projection algorithm, the Projection Onto Span Algorithm (POSA) for wavelet-based superresolution and removing speckle (in wavelet domain) of unknown variance from Synthetic Aperture Radar (SAR) images. Although the POSA is good as a new superresolution algorithm for image enhancement, image metrology and biometric identification, here one will use it like a tool of despeckling, being the first time that an algorithm of super-resolution is used for despeckling of SAR images. Specifically, the speckled SAR image is decomposed into wavelet subbands; POSA is applied to the high subbands, and reconstruct a SAR image from the modified detail coefficients. Experimental results demonstrate that the new method compares favorably to several other despeckling methods on test SAR images.

Health Effects of Trihalomethanes as Chlorinated Disinfection by Products: A Review Article

Trihalomethanes (THMs) were among the first disinfection byproducts to be discovered in chlorinated water. The substances form during a reaction between chlorine and organic matter in the water. Trihalomethanes are suspected to have negative effects on birth such as, low birth weight, intrauterine growth retardation in term births, as well as gestational age and preterm delivery. There are also some evidences showing these by-products to be mutagenic and carcinogenic, the greatest amount of evidence being related to the bladder cancer. However, there exist inconsistencies regarding such effects of THMs as different studies have provided different results in this regard. The aim of the present study is to provide a review of the related researches about the above mentioned health effects of THMs.

Inferring Hierarchical Pronunciation Rules from a Phonetic Dictionary

This work presents a new phonetic transcription system based on a tree of hierarchical pronunciation rules expressed as context-specific grapheme-phoneme correspondences. The tree is automatically inferred from a phonetic dictionary by incrementally analyzing deeper context levels, eventually representing a minimum set of exhaustive rules that pronounce without errors all the words in the training dictionary and that can be applied to out-of-vocabulary words. The proposed approach improves upon existing rule-tree-based techniques in that it makes use of graphemes, rather than letters, as elementary orthographic units. A new linear algorithm for the segmentation of a word in graphemes is introduced to enable outof- vocabulary grapheme-based phonetic transcription. Exhaustive rule trees provide a canonical representation of the pronunciation rules of a language that can be used not only to pronounce out-of-vocabulary words, but also to analyze and compare the pronunciation rules inferred from different dictionaries. The proposed approach has been implemented in C and tested on Oxford British English and Basic English. Experimental results show that grapheme-based rule trees represent phonetically sound rules and provide better performance than letter-based rule trees.

Effect of Helium-Argon Mixtures on the Heat Transfer and Fluid Flow in Gas Tungsten Arc Welding

A transient finite element model has been developed to study the heat transfer and fluid flow during spot Gas Tungsten Arc Welding (GTAW) on stainless steel. Temperature field, fluid velocity and electromagnetic fields are computed inside the cathode, arc-plasma and anode using a unified MHD formulation. The developed model is then used to study the influence of different helium-argon gas mixtures on both the energy transferred to the workpiece and the time evolution of the weld pool dimensions. It is found that the addition of helium to argon increases the heat flux density on the weld axis by a factor that can reach 6.5. This induces an increase in the weld pool depth by a factor of 3. It is also found that the addition of only 10% of argon to helium decreases considerably the weld pool depth, which is due to the electrical conductivity of the mixture that increases significantly when argon is added to helium.

Sensor Fusion Based Discrete Kalman Filter for Outdoor Robot Navigation

The objective of the presented work is to implement the Kalman Filter into an application that reduces the influence of the environmental changes over the robot expected to navigate over a terrain of varying friction properties. The Discrete Kalman Filter is used to estimate the robot position, project the estimated current state ahead at time through time update and adjust the projected estimated state by an actual measurement at that time via the measurement update using the data coming from the infrared sensors, ultrasonic sensors and the visual sensor respectively. The navigation test has been performed in a real world environment and has been found to be robust.

Hybridizing Genetic Algorithm with Biased Chance Local Search

This paper explores university course timetabling problem. There are several characteristics that make scheduling and timetabling problems particularly difficult to solve: they have huge search spaces, they are often highly constrained, they require sophisticated solution representation schemes, and they usually require very time-consuming fitness evaluation routines. Thus standard evolutionary algorithms lack of efficiency to deal with them. In this paper we have proposed a memetic algorithm that incorporates the problem specific knowledge such that most of chromosomes generated are decoded into feasible solutions. Generating vast amount of feasible chromosomes makes the progress of search process possible in a time efficient manner. Experimental results exhibit the advantages of the developed Hybrid Genetic Algorithm than the standard Genetic Algorithm.

Design of Thermal Control Subsystem for TUSAT Telecommunication Satellite

TUSAT is a prospective Turkish Communication Satellite designed for providing mainly data communication and broadcasting services through Ku-Band and C-Band channels. Thermal control is a vital issue in satellite design process. Therefore, all satellite subsystems and equipments should be maintained in the desired temperature range from launch to end of maneuvering life. The main function of the thermal control is to keep the equipments and the satellite structures in a given temperature range for various phases and operating modes of spacecraft during its lifetime. This paper describes the thermal control design which uses passive and active thermal control concepts. The active thermal control is based on heaters regulated by software via thermistors. Alternatively passive thermal control composes of heat pipes, multilayer insulation (MLI) blankets, radiators, paints and surface finishes maintaining temperature level of the overall carrier components within an acceptable value. Thermal control design is supported by thermal analysis using thermal mathematical models (TMM).

Cloud Computing Initiative using Modified Ant Colony Framework

Scheduling of diversified service requests in distributed computing is a critical design issue. Cloud is a type of parallel and distributed system consisting of a collection of interconnected and virtual computers. It is not only the clusters and grid but also it comprises of next generation data centers. The paper proposes an initial heuristic algorithm to apply modified ant colony optimization approach for the diversified service allocation and scheduling mechanism in cloud paradigm. The proposed optimization method is aimed to minimize the scheduling throughput to service all the diversified requests according to the different resource allocator available under cloud computing environment.