Search results for: special methods.

Authors: Khaled M. EL-Naggar

Abstract:

Synchronizing and damping torque coefficients of a synchronous machine can give a quite clear picture for machine behavior during transients. These coefficients are used as a power system transient stability measurement. In this paper, a crow search optimization algorithm is presented and implemented to study the power system stability during transients. The algorithm makes use of the machine responses to perform the stability study in time domain. The problem is formulated as a dynamic estimation problem. An objective function that minimizes the error square in the estimated coefficients is designed. The method is tested using practical system with different study cases. Results are reported and a thorough discussion is presented. The study illustrates that the proposed method can estimate the stability coefficients for the critical stable cases where other methods may fail. The tests proved that the proposed tool is an accurate and reliable tool for estimating the machine coefficients for assessment of power system stability.

Keywords: Optimization, estimation, synchronous, machine, crow search.

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Authors: V. Georgiev

Abstract:

Catalytic oxidation of benzene assisted by ozone, on alumina, silica, and boehmite-supported Ni/Pd catalysts was investigated at 353 K to assess the influence of the support on the reaction. Three bimetallic Ni/Pd nanosized samples with loading 4.7% of Ni and 0.17% of Pd supported on SiO₂, AlOOH and Al₂O₃ were synthesized by the extractive-pyrolytic method. The phase composition was characterized by means of XRD and the surface area and pore size were estimated using Brunauer–Emmett–Teller (BET) and Barrett–Joyner–Halenda (BJH) methods. At the beginning of the reaction, catalysts were significantly deactivated due to the accumulation of intermediates on the catalyst surface and after 60 minutes it turned stable. Ni/Pd/AlOOH catalyst showed the highest steady-state activity in comparison with the Ni/Pd/SiO₂ and Ni/Pd/Al₂O₃ catalysts. Their activity depends on the ozone decomposition potential of the catalysts because of generating oxidizing active species. The sample with the highest ozone decomposition ability which correlated to the surface area of the support oxidizes benzene to the highest extent.

Keywords: Ozone, catalysts, oxidation, Volatile organic compounds, VOCs.

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Authors: Thi T. Nguyen, Lee N. Gordon-Brown

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A new deployment of the multiple criteria decision making (MCDM) techniques: the Simple Additive Weighting (SAW), and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for portfolio allocation, is demonstrated in this paper. Rather than exclusive reference to mean and variance as in the traditional mean-variance method, the criteria used in this demonstration are the first four moments of the portfolio distribution. Each asset is evaluated based on its marginal impacts to portfolio higher moments that are characterized by trapezoidal fuzzy numbers. Then centroid-based defuzzification is applied to convert fuzzy numbers to the crisp numbers by which SAW and TOPSIS can be deployed. Experimental results suggest the similar efficiency of these MCDM approaches to selecting dominant assets for an optimal portfolio under higher moments. The proposed approaches allow investors flexibly adjust their risk preferences regarding higher moments via different schemes adapting to various (from conservative to risky) kinds of investors. The other significant advantage is that, compared to the mean-variance analysis, the portfolio weights obtained by SAW and TOPSIS are consistently well-diversified.

Keywords: Fuzzy numbers, SAW, TOPSIS, portfolio optimization, higher moments, risk management.

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Authors: S. Krustev, V. Angelova, P. Zaprjanova

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Selenium (Se) is an essential micro-nutrient for human and animals but it is highly toxic. Its organic compounds play an important role in biochemistry and nutrition of the cells. Concentration levels of this element in the different regions of the world vary considerably. This study aimed to compare the availability and levels of the Se in some rural areas of the Balkan Peninsula and relationship with the concentrations of other trace elements. For this purpose soil samples and wheat grains from different regions of Bulgaria, Serbia, Nord Macedonia, Romania, and Greece situated far from large industrial centers have been analyzed. The main methods for their determination were the atomic spectral techniques – atomic absorption and plasma atomic emission. As a result of this study, data on microelements levels from the main grain-producing regions of the Balkan Peninsula were determined and systematized. The presented results confirm the low levels of Se in this region: 0.222– 0.962 mg.kg^-1 in soils and 0.001 - 0.005 mg.kg^-1 in wheat grains and require measures to offset the effect of this deficiency.

Keywords: Agricultural soils, Balkan Peninsula, rural areas, selenium.

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Authors: S. N. Hosseini, S. M. H. Karimian

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A new conserving approach in the context of Immersed Boundary Method (IBM) is presented to simulate one dimensional, incompressible flow in a moving boundary problem. The method employs control volume scheme to simulate the flow field. The concept of ghost node is used at the boundaries to conserve the mass and momentum equations. The Present method implements the conservation laws in all cells including boundary control volumes. Application of the method is studied in a test case with moving boundary. Comparison between the results of this new method and a sharp interface (Image Point Method) IBM algorithm shows a well distinguished improvement in both pressure and velocity fields of the present method. Fluctuations in pressure field are fully resolved in this proposed method. This approach expands the IBM capability to simulate flow field for variety of problems by implementing conservation laws in a fully Cartesian grid compared to other conserving methods.

Keywords: Immersed Boundary Method, conservation of mass and momentum laws, moving boundary, boundary condition.

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Authors: Mahmoud Saeidi, Khadijeh Saeidi, Mahmoud Khaleghi

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In this paper, we propose a novel spatiotemporal fuzzy based algorithm for noise filtering of image sequences. Our proposed algorithm uses adaptive weights based on a triangular membership functions. In this algorithm median filter is used to suppress noise. Experimental results show when the images are corrupted by highdensity Salt and Pepper noise, our fuzzy based algorithm for noise filtering of image sequences, are much more effective in suppressing noise and preserving edges than the previously reported algorithms such as [1-7]. Indeed, assigned weights to noisy pixels are very adaptive so that they well make use of correlation of pixels. On the other hand, the motion estimation methods are erroneous and in highdensity noise they may degrade the filter performance. Therefore, our proposed fuzzy algorithm doesn-t need any estimation of motion trajectory. The proposed algorithm admissibly removes noise without having any knowledge of Salt and Pepper noise density.

Keywords: Image Sequences, Noise Reduction, fuzzy algorithm, triangular membership function

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Authors: M.V Rajesh, Archana R, A Unnikrishnan, R Gopikakumari, Jeevamma Jacob

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The System Identification problem looks for a suitably parameterized model, representing a given process. The parameters of the model are adjusted to optimize a performance function based on error between the given process output and identified process output. The linear system identification field is well established with many classical approaches whereas most of those methods cannot be applied for nonlinear systems. The problem becomes tougher if the system is completely unknown with only the output time series is available. It has been reported that the capability of Artificial Neural Network to approximate all linear and nonlinear input-output maps makes it predominantly suitable for the identification of nonlinear systems, where only the output time series is available. [1][2][4][5]. The work reported here is an attempt to implement few of the well known algorithms in the context of modeling of nonlinear systems, and to make a performance comparison to establish the relative merits and demerits.

Keywords: Multilayer neural networks, Radial Basis Functions, Clustering algorithm, Back Propagation training, Extended Kalmanfiltering, Mean Square Error, Nonlinear Modeling, Cramer RaoLower Bound.

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Authors: R. Samsudin, Yogendra, Hairil Satar, Y.Zaidey

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Power transformer consists of components which are under consistent thermal and electrical stresses. The major component which degrades under these stresses is the paper insulation of the power transformer. At site, lightning impulses and cable faults may cause the winding deformation. In addition, the winding may deform due to impact during transportation. A deformed winding will excite more stress to its insulating paper thus will degrade it. Insulation degradation will shorten the life-span of the transformer. Currently there are two methods of detecting the winding deformation which are Sweep Frequency Response Analysis (SFRA) and Low Voltage Impulse Test (LVI). The latter injects current pulses to the winding and capture the admittance plot. In this paper, a transformer which experienced overheating and arcing was identified, and both SFRA and LVI were performed. Next, the transformer was brought to the factory for untanking. The untanking results revealed that the LVI is more accurate than the SFRA method for this case study.

Keywords: Winding Deformation, Arcing, Dissolved GasAnalysis, Sweep Frequency Response Analysis, Low VoltageImpulse Method

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Authors: Abdullah Gokhan Yilmaz, Monzur Alam Imteaz, Shirley Gato-Trinidad, Iqbal Hossain

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Climate change leading to global warming affects the earth through many different ways such as weather (temperature, precipitation, humidity and the other parameters of weather), snow coverage and ice melting, sea level rise, hydrological cycles, quality of water, agriculture, forests, ecosystems and health. One of the most affected areas by climate change is hydrology and water resources. Regions where majority of runoff consists of snow melt are more sensitive to climate change. The first step of climate change studies is to establish trends of significant climate variables including precipitation, temperature and flow data to detect any potential climate change impacts already happened. Two popular non-parametric trend analysis methods, Mann-Kendal and Spearman-s Rho were applied to Upper Euphrates Basin (Turkey) to detect trends of precipitation, temperatures (maximum, minimum and average) and streamflow.

Keywords: Climate change, precipitation, snow hydrology, trend analysis and Upper Euphrates Basin

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Authors: XianYu Zhao, JinXu Guo

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Recently, low-dose computed tomography (CT) has become highly desirable due to increasing attention to the potential risks of excessive radiation. For low-dose CT imaging, ensuring image quality while reducing radiation dose is a major challenge. To facilitate low-dose CT imaging, we propose an improved statistical iterative reconstruction scheme based on the Penalized Weighted Least Squares (PWLS) standard combined with total variation (TV) minimization and sparse dictionary learning (DL) to improve reconstruction performance. We call this method "PWLS-TV-DL". In order to evaluate the PWLS-TV-DL method, we performed experiments on digital phantoms and physical phantoms, respectively. The experimental results show that our method is in image quality and calculation. The efficiency is superior to other methods, which confirms the potential of its low-dose CT imaging.

Keywords: Low dose computed tomography, penalized weighted least squares, total variation, dictionary learning.

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Authors: Danijela Tuljak-Suban, Valter Suban

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Food as perishable goods represents a specific and sensitive part in the supply chain theory, since changing physical or chemical characteristics considerably influence the approach to stock management. The most delicate phase of this process is transportation, where it becomes difficult to ensure the stable conditions which limit deterioration, since the value of the deterioration rate could be easily influenced by the mode of transportation. The fuzzy definition of variables allows one to take these variations into account. Furthermore, an appropriate choice of the defuzzification method permits one to adapt results to real conditions as far as possible. In this article those methods which take into account the relationship between the deterioration rate of perishable goods and transportation by ship will be applied with the aim of (a) minimizing the total cost function, defined as the sum of the ordering cost, holding cost, disposing cost and transportation costs, and (b) improving the supply chain sustainability by reducing environmental impact and waste disposal costs.

Keywords: Perishable goods, fuzzy reasoning, transport by ship, supply chain sustainability.

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Authors: H. Mehdi, Kh. S. Karimov, A. A. Kavokin

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Methods of clustering which were developed in the data mining theory can be successfully applied to the investigation of different kinds of dependencies between the conditions of environment and human activities. It is known, that environmental parameters such as temperature, relative humidity, atmospheric pressure and illumination have significant effects on the human mental performance. To investigate these parameters effect, data mining technique of clustering using entropy and Information Gain Ratio (IGR) K(Y/X) = (H(X)–H(Y/X))/H(Y) is used, where H(Y)=-ΣPi ln(Pi). This technique allows adjusting the boundaries of clusters. It is shown that the information gain ratio (IGR) grows monotonically and simultaneously with degree of connectivity between two variables. This approach has some preferences if compared, for example, with correlation analysis due to relatively smaller sensitivity to shape of functional dependencies. Variant of an algorithm to implement the proposed method with some analysis of above problem of environmental effects is also presented. It was shown that proposed method converges with finite number of steps.

Keywords: Clustering, Correlation analysis, EnvironmentalParameters, Information Gain Ratio, Mental Performance.

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Authors: Atheel Hassan Alwash, Ahmad Zuhairi Abdullah, Norli Ismail

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Characteristics and sonocatalytic activity of zeolite Y catalysts loaded with TiO2 using impregnation and ion exchange methods for the degradation of amaranth dye were investigated. The Ion-exchange method was used to encapsulate the TiO2 into the internal pores of the zeolite while the incorporation of TiO2 mostly on the external surface of zeolite was carried out using the impregnation method. Different characterization techniques were used to elucidate the physicochemical properties of the produced catalysts. The framework of zeolite Y remained virtually unchanged after the encapsulation of TiO2 while the crystallinity of zeolite decreased significantly after the incorporation of 15 wt% of TiO2. The sonocatalytic activity was enhanced by TiO2 incorporation with maximum degradation efficiencies of 50% and 68% for the encapsulated titanium and titanium loaded onto the zeolite, respectively after 120min of reaction. Catalysts characteristics and sonocatalytic behaviors were significantly affected by the preparation method and the location of TiO2 introduced with zeolite structure. Behaviors in the sonocatalytic process were successfully correlated with the characteristics of the catalysts used.

Keywords: Sonocatalytic degradation, TiO2 loaded, ionexchange, impregnation, amaranth dye, process behavior.

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Authors: Kasthurirangan Gopalakrishnan, Naga Shashidhar, Xiaoxiong Zhong

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During the process of compaction in Hot-Mix Asphalt (HMA) mixtures, the distance between aggregate particles decreases as they come together and eliminate air-voids. By measuring the inter-particle distances in a cut-section of a HMA sample the degree of compaction can be estimated. For this, a calibration curve is generated by computer simulation technique when the gradation and asphalt content of the HMA mixture are known. A two-dimensional cross section of HMA specimen was simulated using the mixture design information (gradation, asphalt content and air-void content). Nearest neighbor distance methods such as Delaunay triangulation were used to study the changes in inter-particle distance and area distribution during the process of compaction in HMA. Such computer simulations would enable making several hundreds of repetitions in a short period of time without the necessity to compact and analyze laboratory specimens in order to obtain good statistics on the parameters defined. The distributions for the statistical parameters based on computer simulations showed similar trends as those of laboratory specimens.

Keywords: Computer simulations, Hot-Mix Asphalt (HMA), inter-particle distance, image analysis, nearest neighbor

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Authors: S. Sudhakar, Geetha Manjunath, Siva Teja Kakileti, Himanshu Madhu

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Diagnosis of breast cancer at early stages has seen better clinical and survival outcomes. Survival rates in developing countries like India are very low due to accessibility and affordability issues of screening tests such as Mammography. In addition, Mammography is not much effective in younger women with dense breasts. This leaves a gap in current screening methods. Thermalytix is a new technique for detecting breast abnormality in a non-contact, non-invasive way. It is an AI-enabled computer-aided diagnosis solution that automates interpretation of high resolution thermal images and identifies potential malignant lesions. The solution is low cost, easy to use, portable and is effective in all age groups.  This paper presents the results of a retrospective comparative analysis of Thermalytix over Mammography and Clinical Breast Examination for breast cancer screening. Thermalytix was found to have better sensitivity than both the tests, with good specificity as well. In addition, Thermalytix identified all malignant patients without palpable lumps.

Keywords: Breast Cancer Screening, Radiology, Thermalytix, Artificial Intelligence, Thermography.

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Authors: Alexander A. Karabutov, Natalia B. Podymova, Elena B. Cherepetskaya, Vladimir A. Makarov, Yulia G. Sokolovskaya

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The laser-ultrasonic method is realized for quantifying the influence of porosity on the local Young’s modulus of isotropic composite materials. The method is based on a laser thermooptical method of ultrasound generation combined with measurement of the phase velocity of longitudinal and shear acoustic waves in samples. The main advantage of this method compared with traditional ultrasonic research methods is the efficient generation of short and powerful probing acoustic pulses required for reliable testing of ultrasound absorbing and scattering heterogeneous materials. Using as an example samples of a metal matrix composite with reinforcing microparticles of silicon carbide in various concentrations, it is shown that to provide an effective increase in Young’s modulus with increasing concentration of microparticles, the porosity of the final sample should not exceed 2%.

Keywords: Laser ultrasonic, longitudinal and shear ultrasonic waves, porosity, composite, local elastic moduli.

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Authors: Inas S. Khayal, Weiping Zhou, Jonathan Skinner

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Healthcare delivery systems around the world are in crisis. The need to improve health outcomes while decreasing healthcare costs have led to an imminent call to action to transform the healthcare delivery system. While Bioinformatics and Biomedical Engineering have primarily focused on biological level data and biomedical technology, there is clear evidence of the importance of the delivery of care on patient outcomes. Classic singular decomposition approaches from reductionist science are not capable of explaining complex systems. Approaches and methods from systems science and systems engineering are utilized to structure healthcare delivery system data. Specifically, systems architecture is used to develop a multi-scale and multi-dimensional characterization of the healthcare delivery system, defined here as the Healthcare Delivery System Knowledge Base. This paper is the first to contribute a new method of structuring and visualizing a multi-dimensional and multi-scale healthcare delivery system using systems architecture in order to better understand healthcare delivery.

Keywords: Health informatics, systems thinking, systems architecture, healthcare delivery system, data analytics.

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Authors: C. G. Jinimole, A. Harsha

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One of the key problems facing in the analysis of Computed Tomography (CT) images is the poor contrast of the images. Image enhancement can be used to improve the visual clarity and quality of the images or to provide a better transformation representation for further processing. Contrast enhancement of images is one of the acceptable methods used for image enhancement in various applications in the medical field. This will be helpful to visualize and extract details of brain infarctions, tumors, and cancers from the CT image. This paper presents a comparison study of five contrast enhancement techniques suitable for the contrast enhancement of CT images. The types of techniques include Power Law Transformation, Logarithmic Transformation, Histogram Equalization, Contrast Stretching, and Laplacian Transformation. All these techniques are compared with each other to find out which enhancement provides better contrast of CT image. For the comparison of the techniques, the parameters Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE) are used. Logarithmic Transformation provided the clearer and best quality image compared to all other techniques studied and has got the highest value of PSNR. Comparison concludes with better approach for its future research especially for mapping abnormalities from CT images resulting from Brain Injuries.

Keywords: Computed tomography, enhancement techniques, increasing contrast, PSNR and MSE.

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Authors: Melissa C. LaDuke

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The use of new literacies within science classrooms needs to be balanced by teachers to both teach different forms of communication while assessing content area proficiency. Using new literacies such as Twitter and Facebook needs to be incorporated into science content area literacy studies in addition to continuing to use generally-accepted forms of scientific content area presentation which include scientific papers and textbooks. The research question this literature review seeks to answer is “What are some ways in which new forms of literacy are better suited to teach scientific content area literacy to 21st century learners?” The research question is addressed through a literature review that highlights methods currently being used to educate the next wave of learners in the world of science content area literacy. Both temporal discourse analysis (TDA) and critical discourse analysis (CDA) were used to determine the need to use new literacies to teach science content area literacy. Increased use of digital technologies and a change in science content area pedagogy were explored.

Keywords: Science content area literacy, new literacies, critical discourse analysis, temporal discourse analysis.

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Authors: Chin-Pin Chen, David W.S. Tai, Wen-Jong Chen, Hui-Min Lai

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This study aims to analyze the effect of e-learning on photonics technology and daily livings among college students. The course contents of photonics technology and daily livings are first drafted based on research discussions and expert interviews. Having expert questionnaires with Delphi Technique for three times, the knowledge units and items for the course of photonics technology and daily livings are established. The e-learning materials and the drafts of instructional strategies, academic achievement, and learning attitude scales are then developed. With expert inspection, reliability and validity test, and experimental instructions, the scales and the material are further revised. Finally, the formal instructions are implemented to test the effect of different instructional methods on the academic achievement of photonics technology and daily livings among students in universities of technology. The research results show that e-learning could effectively promote academic achievement and learning attitude, and the students with e-learning obviously outperform the ones with trandition instructions.

Keywords: E-learning, Photonics Technology and Daily Livings, Academic Achievement

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Authors: D. Zabala, Y. Cárdenas, G. Núñez

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In this work the numerical simulation of transient heat transfer in a cylindrical probe is done. An experiment was conducted introducing a steel cylinder in a heating chamber and registering its surface temperature along the time during one hour. In parallel, a mathematical model was solved for one dimension transient heat transfer in cylindrical coordinates, considering the boundary conditions of the test. The model was solved using finite difference method, because the thermal conductivity in the cylindrical steel bar and the convection heat transfer coefficient used in the model are considered temperature dependant functions, and both conditions prevent the use of the analytical solution. The comparison between theoretical and experimental results showed the average deviation is below 2%. It was concluded that numerical methods are useful in order to solve engineering complex problems. For constant k and h, the experimental methodology used here can be used as a tool for teaching heat transfer in mechanical engineering, using mathematical simplified models with analytical solutions.

Keywords: Heat transfer experiment, thermal conductivity, finite difference, engineering education.

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Authors: Chungkuk Jin, Moohyun Kim, Woo Chul Chung

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This paper presents global performance and dynamic behaviors of a discrete-pontoon-type floating bridge with mooring lines in time domain under wind and wave excitations. The structure is designed for long-distance and deep-water crossing and consists of the girder, columns, pontoons, and mooring lines. Their functionality and behaviors are investigated by using elastic-floater/mooring fully-coupled dynamic simulation computer program. Dynamic wind, first- and second-order wave forces, and current loads are considered as environmental loads. Girder’s dynamic responses and mooring tensions are analyzed under different analysis methods and environmental conditions. Girder’s lateral responses are highly influenced by the second-order wave and wind loads while the first-order wave load mainly influences its vertical responses.

Keywords: Floating bridge, elastic dynamic response, coupled dynamics, mooring line, pontoon, wave/wind excitation, resonance, second-order effect.

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Authors: Kristina Maiksteniene

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Various formal and informal brand alliances are being formed in professional service firms. Professional service corporate brand is heavily dependent on brands of professional employees who comprise them, and professional employee brands are in turn dependent on the corporate brand. Prior work provides limited scientific evidence of brand alliance effects in professional service area – i.e., how professional service corporate-employee brand allies are affected by an alliance, what are brand attitude effects after alliance formation and how these effects vary with different strengths of an ally. Scientific literature analysis and theoretical modeling are the main methods of the current study. As a result, a theoretical model is constructed for estimating spillover effects of professional service corporate-employee brand alliances and for comparison among different professional service firm expertise practice models – from “brains" to “procedure" model. The resulting theoretical model lays basis for future experimental studies.

Keywords: Brand alliances, professional services, corporatebrand, employee brand.

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Authors: T. Motsima, K. Zuma, E Rapoo

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Childhood mortality is a key sign of the coverage of child survival interventions, social and economic progressions. Although the level of under-five mortality has been declining, it is still unacceptably high. The primary aim of this paper is to establish and analyse the levels and trends of under-five mortality for the periods 1998, 2003 and 2012 in South Africa. Methods: The data used for analysis came from the 1998 SADHS, the 2003 SADHS and the 2012 SABSSM which collected information on the survival status of children. The Kaplan-Meier estimate of the survival function method was used to determine the probabilities of failure (death) from birth up to 59 months. Results and Conclusion: The overall U5MR declined by 28.2% from 53.1 in 1998 to 38.1 in 2012. The U5MR of male children declined from 59.2 in 1998 to 46.2 in 2003 and dropped further to 41.4 in 2012. The U5MR of children of mothers aged 40 years and older increased from 64.0 in 1998 to 89.0 in 2003 and rose further to 129.9 in 2012. The U5MR of children of mothers with education level of 12 years or more increased from 32.2 in 1998 to 35.2 in 2003 and declined substantially to 17.5 in 2012.

Keywords: Demographic and health survey, Kaplan-Meier, levels and trends, under-five mortality.

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Authors: Shin Je Lee, Go Bong Choi, Jeong Cheol Seo, Jong Min Lee, Gibaek Lee

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Water pipe network is installed underground and once equipped, it is difficult to recognize the state of pipes when the leak or burst happens. Accordingly, post management is often delayed after the fault occurs. Therefore, the systematic fault management system of water pipe network is required to prevent the accident and minimize the loss. In this work, we develop online fault detection system of water pipe network using data of pipes such as flow rate or pressure. The transient model describing water flow in pipelines is presented and simulated using MATLAB. The fault situations such as the leak or burst can be also simulated and flow rate or pressure data when the fault happens are collected. Faults are detected using statistical methods of fast Fourier transform and discrete wavelet transform, and they are compared to find which method shows the better fault detection performance.

Keywords: fault detection, water pipeline model, fast Fourier transform, discrete wavelet transform.

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Authors: Tatyana Alexandrova, Alexandr Alexandrov, Nadezhda Nikolaeva

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A problem of complex mineral resources development is urgent and priority, it is aimed at realization of the processes of their ecologically safe development, one of its components is revealing the influence of the forms of element compounds in raw materials and in the processing products. In view of depletion of the precious metal reserves at the traditional deposits in the XXI century the large-size open cast deposits, localized in black shale strata begin to play the leading role. Carbonaceous (black) shales carry a heightened metallogenic potential. Black shales with high content of carbon are widely distributed within the scope of Bureinsky massif. According to academician Hanchuk`s data black shales of Sutirskaya series contain generally PGEs native form. The presence of high absorptive towards carbonaceous matter gold and PGEs compounds in crude ore results in decrease of valuable components extraction because of their sorption into dissipated carbonaceous matter.

Keywords: Сarbonaceous rocks, bitumens, precious metals, concentration, extraction.

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Authors: Achmad Nizar Hidayanto, Elisabeth Martha Koeanan

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Image clustering is a process of grouping images based on their similarity. The image clustering usually uses the color component, texture, edge, shape, or mixture of two components, etc. This research aims to explore image clustering using color composition. In order to complete this image clustering, three main components should be considered, which are color space, image representation (feature extraction), and clustering method itself. We aim to explore which composition of these factors will produce the best clustering results by combining various techniques from the three components. The color spaces use RGB, HSV, and L*a*b* method. The image representations use Histogram and Gaussian Mixture Model (GMM), whereas the clustering methods use KMeans and Agglomerative Hierarchical Clustering algorithm. The results of the experiment show that GMM representation is better combined with RGB and L*a*b* color space, whereas Histogram is better combined with HSV. The experiments also show that K-Means is better than Agglomerative Hierarchical for images clustering.

Keywords: Image clustering, feature extraction, RGB, HSV, L*a*b*, Gaussian Mixture Model (GMM), histogram, Agglomerative Hierarchical Clustering (AHC), K-Means, Expectation-Maximization (EM).

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Authors: K. M. Ravikumar, Balakrishna Reddy, R. Rajagopal, H. C. Nagaraj

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Automatic detection of syllable repetition is one of the important parameter in assessing the stuttered speech objectively. The existing method which uses artificial neural network (ANN) requires high levels of agreement as prerequisite before attempting to train and test ANNs to separate fluent and nonfluent. We propose automatic detection method for syllable repetition in read speech for objective assessment of stuttered disfluencies which uses a novel approach and has four stages comprising of segmentation, feature extraction, score matching and decision logic. Feature extraction is implemented using well know Mel frequency Cepstra coefficient (MFCC). Score matching is done using Dynamic Time Warping (DTW) between the syllables. The Decision logic is implemented by Perceptron based on the score given by score matching. Although many methods are available for segmentation, in this paper it is done manually. Here the assessment by human judges on the read speech of 10 adults who stutter are described using corresponding method and the result was 83%.

Keywords: Assessment, DTW, MFCC, Objective, Perceptron, Stuttering.

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Authors: P. Chihomvu, P. Stegmann, M. Pillay

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Pollution of the Klip River has caused microorganisms inhabiting it to develop protective survival mechanisms. This study isolated and characterized the heavy metal resistant bacteria in the Klip River. Water and sediment samples were collected from six sites along the course of the river. The pH, turbidity, salinity, temperature and dissolved oxygen were measured in-situ. The concentrations of six heavy metals (Cd, Cu, Fe, Ni, Pb and Zn) of the water samples were determined by atomic absorption spectroscopy. Biochemical and antibiotic profiles of the isolates were assessed using the API 20E® and Kirby Bauer Method. Growth studies were carried out using spectrophotometric methods. The isolates were identified using 16SrDNA sequencing. The uppermost part of the Klip River with the lowest pH had the highest levels of heavy metals. Turbidity, salinity and specific conductivity increased measurably at Site 4 (Henley on Klip Weir). MIC tests showed that 16 isolates exhibited high iron and lead resistance. Antibiotic susceptibility tests revealed that the isolates exhibited multitolerances to drugs such as Tetracycline, Ampicillin, and Amoxicillin.

Keywords: Klip River, heavy metals, resistance.

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Authors: Samson Henry Dogo, Allan Clark, Elena Kulinskaya

Abstract:

The objective of meta-analysis is to combine results from several independent studies in order to create generalization and provide evidence base for decision making. But recent studies show that the magnitude of effect size estimates reported in many areas of research significantly changed over time and this can impair the results and conclusions of meta-analysis. A number of sequential methods have been proposed for monitoring the effect size estimates in meta-analysis. However they are based on statistical theory applicable only to fixed effect model (FEM) of meta-analysis. For random-effects model (REM), the analysis incorporates the heterogeneity variance, τ 2 and its estimation create complications. In this paper we study the use of a truncated CUSUM-type test with asymptotically valid critical values for sequential monitoring in REM. Simulation results show that the test does not control the Type I error well, and is not recommended. Further work required to derive an appropriate test in this important area of applications.

Keywords: Meta-analysis, random-effects model, sequential testing, temporal changes in effect sizes.

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