Isomorphism on Fuzzy Graphs

In this paper, the order, size and degree of the nodes of the isomorphic fuzzy graphs are discussed. Isomorphism between fuzzy graphs is proved to be an equivalence relation. Some properties of self complementary and self weak complementary fuzzy graphs are discussed.

Dynamic Model of a Buck Converter with a Sliding Mode Control

This paper presents the averaging model of a buck converter derived from the generalized state-space averaging method. The sliding mode control is used to regulate the output voltage of the converter and taken into account in the model. The proposed model requires the fast computational time compared with those of the full topology model. The intensive time-domain simulations via the exact topology model are used as the comparable model. The results show that a good agreement between the proposed model and the switching model is achieved in both transient and steady-state responses. The reported model is suitable for the optimal controller design by using the artificial intelligence techniques.

On Bounds For The Zeros of Univariate Polynomial

Problems on algebraical polynomials appear in many fields of mathematics and computer science. Especially the task of determining the roots of polynomials has been frequently investigated.Nonetheless, the task of locating the zeros of complex polynomials is still challenging. In this paper we deal with the location of zeros of univariate complex polynomials. We prove some novel upper bounds for the moduli of the zeros of complex polynomials. That means, we provide disks in the complex plane where all zeros of a complex polynomial are situated. Such bounds are extremely useful for obtaining a priori assertations regarding the location of zeros of polynomials. Based on the proven bounds and a test set of polynomials, we present an experimental study to examine which bound is optimal.

Utilization of 3-N-trimethylamino-1-propanol by Rhodococcus sp. strain A4 isolated from Natural Soil

The aim of this study was to screen for microorganism that able to utilize 3-N-trimethylamino-1-propanol (homocholine) as a sole source of carbon and nitrogen. The aerobic degradation of homocholine has been found by a gram-positive Rhodococcus sp. bacterium isolated from soil. The isolate was identified as Rhodococcus sp. strain A4 based on the phenotypic features, physiologic and biochemical characteristics, and phylogenetic analysis. The cells of the isolated strain grown on both basal-TMAP and nutrient agar medium displayed elementary branching mycelia fragmented into irregular rod and coccoid elements. Comparative 16S rDNA sequencing studies indicated that the strain A4 falls into the Rhodococcus erythropolis subclade and forms a monophyletic group with the type-strains of R. opacus, and R. wratislaviensis. Metabolites analysis by capillary electrophoresis, fast atom bombardment-mass spectrometry, and gas chromatography- mass spectrometry, showed trimethylamine (TMA) as the major metabolite beside β-alanine betaine and trimethylaminopropionaldehyde. Therefore, the possible degradation pathway of trimethylamino propanol in the isolated strain is through consequence oxidation of alcohol group (-OH) to aldehyde (-CHO) and acid (-COOH), and thereafter the cleavage of β-alanine betaine C-N bonds yielded trimethylamine and alkyl chain.

Meta-Search in Human Resource Management

In the area of Human Resource Management, the trend is towards online exchange of information about human resources. For example, online applications for employment become standard and job offerings are posted in many job portals. However, there are too many job portals to monitor all of them if someone is interested in a new job. We developed a prototype for integrating information of different job portals into one meta-search engine. First, existing job portals were investigated and XML schema documents were derived automated from these portals. Second, translation rules for transforming each schema to a central HR-XML-conform schema were determined. The HR-XML-schema is used to build a form for searching jobs. The data supplied by a user in this form is now translated into queries for the different job portals. Each result obtained by a job portal is sent to the meta-search engine that ranks the result of all received job offers according to user's preferences.

Yield Prediction Using Support Vectors Based Under-Sampling in Semiconductor Process

It is important to predict yield in semiconductor test process in order to increase yield. In this study, yield prediction means finding out defective die, wafer or lot effectively. Semiconductor test process consists of some test steps and each test includes various test items. In other world, test data has a big and complicated characteristic. It also is disproportionably distributed as the number of data belonging to FAIL class is extremely low. For yield prediction, general data mining techniques have a limitation without any data preprocessing due to eigen properties of test data. Therefore, this study proposes an under-sampling method using support vector machine (SVM) to eliminate an imbalanced characteristic. For evaluating a performance, randomly under-sampling method is compared with the proposed method using actual semiconductor test data. As a result, sampling method using SVM is effective in generating robust model for yield prediction.

The Efficacy of Danger Ideation Reduction Therapy for an 86-Year Old Man with a 63-Year History of Obsessive-Compulsive Disorder: A Case Study

While OCD is one of the most commonly occurring psychiatric conditions experienced by older adults, there is a paucity of research conducted into the treatment of older adults with OCD. This case study represents the first published investigation of a cognitive treatment for geriatric OCD. It describes the successful treatment of an 86-year old man with a 63-year history of OCD using Danger Ideation Reduction Therapy (DIRT). The client received 14 individual, 50-minute treatment sessions of DIRT over 13 weeks. Clinician-based Y-BOCS scores reduced 84% from 25 (severe) at pre-treatment, to 4 (subclinical) at 6-month post-treatment follow-up interview, demonstrating the efficacy of DIRT for this client. DIRT may have particular advantages over ERP and pharmacological approaches, however further research is required in older adults with OCD.

Experimental Studies on the Combustion and Emission Characteristics of a Diesel Engine Fuelled with Used Cooking Oil Methyl Esterand its Diesel Blends

Transesterified vegetable oils (biodiesel) are promising alternative fuel for diesel engines. Used vegetable oils are disposed from restaurants in large quantities. But higher viscosity restricts their direct use in diesel engines. In this study, used cooking oil was dehydrated and then transesterified using an alkaline catalyst. The combustion, performance and emission characteristics of Used Cooking oil Methyl Ester (UCME) and its blends with diesel oil are analysed in a direct injection C.I. engine. The fuel properties and the combustion characteristics of UCME are found to be similar to those of diesel. A minor decrease in thermal efficiency with significant improvement in reduction of particulates, carbon monoxide and unburnt hydrocarbons is observed compared to diesel. The use of transesterified used cooking oil and its blends as fuel for diesel engines will reduce dependence on fossil fuels and also decrease considerably the environmental pollution.

Optimal Straight Line Trajectory Generation in 3D Space using Deviation Algorithm

This paper presents an efficient method of obtaining a straight-line motion in the tool configuration space using an articulated robot between two specified points. The simulation results & the implementation results show the effectiveness of the method.

Application of Multi-Dimensional Principal Component Analysis to Medical Data

Multi-dimensional principal component analysis (PCA) is the extension of the PCA, which is used widely as the dimensionality reduction technique in multivariate data analysis, to handle multi-dimensional data. To calculate the PCA the singular value decomposition (SVD) is commonly employed by the reason of its numerical stability. The multi-dimensional PCA can be calculated by using the higher-order SVD (HOSVD), which is proposed by Lathauwer et al., similarly with the case of ordinary PCA. In this paper, we apply the multi-dimensional PCA to the multi-dimensional medical data including the functional independence measure (FIM) score, and describe the results of experimental analysis.

Holistic Face Recognition using Multivariate Approximation, Genetic Algorithms and AdaBoost Classifier: Preliminary Results

Several works regarding facial recognition have dealt with methods which identify isolated characteristics of the face or with templates which encompass several regions of it. In this paper a new technique which approaches the problem holistically dispensing with the need to identify geometrical characteristics or regions of the face is introduced. The characterization of a face is achieved by randomly sampling selected attributes of the pixels of its image. From this information we construct a set of data, which correspond to the values of low frequencies, gradient, entropy and another several characteristics of pixel of the image. Generating a set of “p" variables. The multivariate data set with different polynomials minimizing the data fitness error in the minimax sense (L∞ - Norm) is approximated. With the use of a Genetic Algorithm (GA) it is able to circumvent the problem of dimensionality inherent to higher degree polynomial approximations. The GA yields the degree and values of a set of coefficients of the polynomials approximating of the image of a face. By finding a family of characteristic polynomials from several variables (pixel characteristics) for each face (say Fi ) in the data base through a resampling process the system in use, is trained. A face (say F ) is recognized by finding its characteristic polynomials and using an AdaBoost Classifier from F -s polynomials to each of the Fi -s polynomials. The winner is the polynomial family closer to F -s corresponding to target face in data base.

Analyzing and Comparing the Architectural Specifications and the Urban Role of Scientific– Technological Parks in Iran and the World

The issue of scientific – technological parks has been proposed in several countries of the world especially in western countries since a few decades ago and its efficiency is under examination. In our county Iran, some scientific – technological parks have been established or are being established. This design would evaluate the urban role and method of architecture of these parks in order to criticize its efficiency and offer some suggestions, as much as possible to improve its building methods in Iran. The main problem of this design is that how much these parks in Iran do meet the international measurements. So for this reason, one scientific park in Iran and one from western countries would be studied and compared with each other.

Borderline Personality Organization and the Interpersonal Components of Perfectionism: A Review of Two Overlapping Personality Pathologies

This work represents the first review paper to explore the relationship between perfectionistic personality and borderline personality organization. The developmental origins, identity diffusion, interpersonal difficulties, and defense mechanisms that are common to both borderline personality and the interpersonal components of perfectionism are explored, and existing research on perfectionism and borderline personality is reviewed. The importance of the link between perfectionism and borderline features is discussed in terms of its contribution to the conceptual understanding of personality pathology as well as to applied clinical practices.

A Comparative Study of Main Memory Databases and Disk-Resident Databases

Main Memory Database systems (MMDB) store their data in main physical memory and provide very high-speed access. Conventional database systems are optimized for the particular characteristics of disk storage mechanisms. Memory resident systems, on the other hand, use different optimizations to structure and organize data, as well as to make it reliable. This paper provides a brief overview on MMDBs and one of the memory resident systems named FastDB and compares the processing time of this system with a typical disc resident database based on the results of the implementation of TPC benchmarks environment on both.

Biokinetics of Coping Mechanism of Freshwater tilapia following Exposure to Waterborne and Dietary Copper

The purpose of this study was to understand the main sources of copper (Cu) accumulation in target organs of tilapia (Oreochromis mossambicus) and to investigate how the organism mediate the process of Cu accumulation under prolonged conditions. By measuring both dietary and waterborne Cu accumulation and total concentrations in tilapia with biokinetic modeling approach, we were able to clarify the biokinetic coping mechanisms for the long term Cu accumulation. This study showed that water and food are both the major source of Cu for the muscle and liver of tilapia. This implied that control the Cu concentration in these two routes will be correlated to the Cu bioavailability for tilapia. We found that exposure duration and level of waterborne Cu drove the Cu accumulation in tilapia. The ability for Cu biouptake and depuration in organs of tilapia were actively mediated under prolonged exposure conditions. Generally, the uptake rate, depuration rate and net bioaccumulation ability in all selected organs decreased with the increasing level of waterborne Cu and extension of exposure duration.Muscle tissues accounted for over 50%of the total accumulated Cu and played a key role in buffering the Cu burden in the initial period of exposure, alternatively, the liver acted a more important role in the storage of Cu with the extension of exposures. We concluded that assumption of the constant biokinetic rates could lead to incorrect predictions with overestimating the long-term Cu accumulation in ecotoxicological risk assessments.

Cycle Embedding in Folded Hypercubes with More Faulty Elements

Faults in a network may take various forms such as hardware/software errors, vertex/edge faults, etc. Folded hypercube is a well-known variation of the hypercube structure and can be constructed from a hypercube by adding a link to every pair of nodes with complementary addresses. Let FFv (respectively, FFe) be the set of faulty nodes (respectively, faulty links) in an n-dimensional folded hypercube FQn. Hsieh et al. have shown that FQn - FFv - FFe for n ≥ 3 contains a fault-free cycle of length at least 2n -2|FFv|, under the constraints that (1) |FFv| + |FFe| ≤ 2n - 4 and (2) every node in FQn is incident to at least two fault-free links. In this paper, we further consider the constraints |FFv| + |FFe| ≤ 2n - 3. We prove that FQn - FFv - FFe for n ≥ 5 still has a fault-free cycle of length at least 2n - 2|FFv|, under the constraints : (1) |FFv| + |FFe| ≤ 2n - 3, (2) |FFe| ≥ n + 2, and (3) every vertex is still incident with at least two links.

Dust Storm Prediction Using ANNs Technique (A Case Study: Zabol City)

Dust storms are one of the most costly and destructive events in many desert regions. They can cause massive damages both in natural environments and human lives. This paper is aimed at presenting a preliminary study on dust storms, as a major natural hazard in arid and semi-arid regions. As a case study, dust storm events occurred in Zabol city located in Sistan Region of Iran was analyzed to diagnose and predict dust storms. The identification and prediction of dust storm events could have significant impacts on damages reduction. Present models for this purpose are complicated and not appropriate for many areas with poor-data environments. The present study explores Gamma test for identifying inputs of ANNs model, for dust storm prediction. Results indicate that more attempts must be carried out concerning dust storms identification and segregate between various dust storm types.

EGCL: An Extended G-Code Language with Flow Control, Functions and Mnemonic Variables

In the context of computer numerical control (CNC) and computer aided manufacturing (CAM), the capabilities of programming languages such as symbolic and intuitive programming, program portability and geometrical portfolio have special importance. They allow to save time and to avoid errors during part programming and permit code re-usage. Our updated literature review indicates that the current state of art presents voids in parametric programming, program portability and programming flexibility. In response to this situation, this article presents a compiler implementation for EGCL (Extended G-code Language), a new, enriched CNC programming language which allows the use of descriptive variable names, geometrical functions and flow-control statements (if-then-else, while). Our compiler produces low-level generic, elementary ISO-compliant Gcode, thus allowing for flexibility in the choice of the executing CNC machine and in portability. Our results show that readable variable names and flow control statements allow a simplified and intuitive part programming and permit re-usage of the programs. Future work includes allowing the programmer to define own functions in terms of EGCL, in contrast to the current status of having them as library built-in functions.

Direct Democracy and Social Contract in Ancient Athens

In the present essay, a model of choice by actors is analysedby utilizing the theory of chaos to explain how change comes about. Then, by using ancient and modern sources of literature, the theory of the social contract is analysed as a historical phenomenon that first appeared during the period of Classical Greece. Then, based on the findings of this analysis, the practice of direct democracy and public choice in ancient Athens is analysed, through two historical cases: Eubulus and Lycurgus political program in the second half of the 4th century. The main finding of this research is that these policies can be interpreted as an implementation of a social contract, through which citizens were taking decisions based on rational choice according to economic considerations.

High Energy Dual-Wavelength Mid-Infrared Extracavity KTA Optical Parametric Oscillator

A high energy dual-wavelength extracavity KTA optical parametric oscillator (OPO) with excellent stability and beam quality, which is pumped by a Q-switched single-longitudinal-mode Nd:YAG laser, has been demonstrated based on a type II noncritical phase matching (NCPM) KTA crystal. The maximum pulse energy of 10.2 mJ with the output stability of better than 4.1% rms at 3.467 μm is obtained at the repetition rate of 10 Hz and pulse width of 2 ns, and the 11.9 mJ of 1.535 μm radiation is obtained simultaneously. This extracavity NCPM KTA OPO is very useful when high energy, high beam quality and smooth time domain are needed.