Search results for: Wind Turbine Type Selection

Authors: Z. Pavlík, M. Keppert, M. Pavlíková, R. Černý

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Experimental investigation of the effect of hydrophobic injection on siloxane basis on the properties of oldfashioned type of ceramic brick is presented in the paper. At the experimental testing, the matrix density, total open porosity, pore size distribution, sorptivity, water absorption coefficient, sorption and desorption isotherms are measured for the original, as well as the hydrophobic-injection treated brick. On the basis of measured data, the functionality of the hydrophobic injection for the moisture ingress prevention into the studied ceramic brick is assessed.

Keywords: Brick masonry, siloxane hydrophobic injection, moisture ingress, functionality testing.

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Authors: Sung-Hae Jun, Kyung-Whan Oh

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Statistical learning theory was developed by Vapnik. It is a learning theory based on Vapnik-Chervonenkis dimension. It also has been used in learning models as good analytical tools. In general, a learning theory has had several problems. Some of them are local optima and over-fitting problems. As well, statistical learning theory has same problems because the kernel type, kernel parameters, and regularization constant C are determined subjectively by the art of researchers. So, we propose an evolutionary statistical learning theory to settle the problems of original statistical learning theory. Combining evolutionary computing into statistical learning theory, our theory is constructed. We verify improved performances of an evolutionary statistical learning theory using data sets from KDD cup.

Keywords: Evolutionary computing, Local optima, Over-fitting, Statistical learning theory

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Authors: M. Safaei, M. Seifert, K. D. Thoben

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Supply network management adopts a systematic and integrative approach to managing the operations and relationships of various parties in a supply network. The objective of the manufactures in their supply network is to reduce inventory costs and increase customer satisfaction levels. One way of doing that is to synchronize delivery performance. A supply network can be described by nodes representing the companies and the links (relationships) between these nodes. Uncertainty in delivery time depends on type of network relationship between suppliers. The problem is to understand how the individual uncertainties influence the total uncertainty of the network and identify those parts of the network, which has the highest potential for improving the total delivery time uncertainty.

Keywords: Delivery time uncertainty, Distribution function, Statistical method, Supply Network.

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Authors: Sevil Yildiz

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Audio visual communication is a type of collective expression. Due to inform the masses, give direction to opinions, and establish public opinion, audio visual communication must be subjected to special restrictions. This has been stipulated in both the Constitution and the European Human Rights Agreement. This paper aims to review freedom of expression and its restriction in audio visual media. For this purpose, the authorization of the Radio and Television Supreme Council to impose sanctions as an independent administrative authority empowered to regulate the field of audio visual communication has been reviewed with regard to freedom of expression and its limits.

Keywords: Audio visual media, freedom of expression, its limits, Radio and Television Supreme Council.

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Authors: Vanessa Romanovicz, Beatriz A. Berns, Stephen D. Carpenter, Deyse Carpenter

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This article deals with the carbon nanotubes (CNT) synthesized from a novel precursor, sugar cane and Anodic Aluminum Oxide (AAO). The objective was to produce CNTs to be used as catalyst supports for Proton Exchange Membranes. The influence of temperature, inert gas flow rate and concentration of the precursor is presented. The CNTs prepared were characterized using TEM, XRD, Raman Spectroscopy, and the surface area determined by BET. The results show that it is possible to form CNT from sugar cane by pyrolysis and the CNTs are the type multi-walled carbon nanotubes. The MWCNTs are short and closed at the two ends with very small surface area of S_BET= 3.691m^,/g.

Keywords: Carbon nanotubes, sugar cane, fuel cell, catalyst support.

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Authors: Hsu-Hao Tsai, Jiann-Min Yang

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The analysis is mainly concentrating on the knowledge management literatures productivity trend which subjects as “knowledge management" in SSCI database. The purpose what the analysis will propose is to summarize the trend information for knowledge management researchers since core knowledge will be concentrated in core categories. The result indicated that the literature productivity which topic as “knowledge management" is still increasing extremely and will demonstrate the trend by different categories including author, country/territory, institution name, document type, language, publication year, and subject area. Focus on the right categories, you will catch the core research information. This implies that the phenomenon "success breeds success" is more common in higher quality publications.

Keywords: Knowledge Management, SSCI, Bibliometric, Lotka's Law

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Authors: K. Okubo, Y. Kurihara, T. Kaburagi, K. Watanabe

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Many of the ever-growing elderly population require exercise, such as running, for health management. One important element of a runner’s training is the choice of shoes for exercise; shoes are important because they provide the interface between the feet and road. When we purchase shoes, we may instinctively choose a pair after trying on many different pairs of shoes. Selecting the shoes instinctively may work, but it does not guarantee a suitable fit for running activities. Therefore, if we could select suitable shoes for each runner from the viewpoint of brain activities, it would be helpful for validating shoe selection. In this paper, we describe how brain activities show different characteristics during particular task, corresponding to different properties of shoes. Using five subjects, we performed a verification experiment, applying weight, softness, and flexibility as shoe properties. In order to affect the shoe property’s differences to the brain, subjects run for 10 min. Before and after running, subjects conducted a paced auditory serial addition task (PASAT) as the particular task; and the subjects’ brain activities during the PASAT are evaluated based on oxyhemoglobin and deoxyhemoglobin relative concentration changes, measured by near-infrared spectroscopy (NIRS). When the brain works actively, oxihemoglobin and deoxyhemoglobin concentration drastically changes; therefore, we calculate the maximum values of concentration changes. In order to normalize relative concentration changes after running, the maximum value are divided by before running maximum value as evaluation parameters. The classification of the groups of shoes is expressed on a self-organizing map (SOM). As a result, deoxyhemoglobin can make clusters for two of the three types of shoes.

Keywords: Brain activities, NIRS, PASAT, running shoes.

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Authors: Milan Rippel, Pert Teplý

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Operational risk has become one of the most discussed topics in the financial industry in the recent years. The reasons for this attention can be attributed to higher investments in information systems and technology, the increasing wave of mergers and acquisitions and emergence of new financial instruments. In addition, the New Basel Capital Accord (known as Basel II) demands a capital requirement for operational risk and further motivates financial institutions to more precisely measure and manage this type of risk. The aim of this paper is to shed light on main characteristics of operational risk management and common applied methods: scenario analysis, key risk indicators, risk control self assessment and loss distribution approach.

Keywords: Operational risk, economic capital, key risk indicators, loss distribution approach.

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Authors: Nassib Abdallah, Pierre Chauvet, Abd El Salam Hajjar, Bassam Daya

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In this paper, we propose an optimized brain computer interface (BCI) system for unspoken speech recognition, based on the fact that the constructions of unspoken words rely strongly on the Wernicke area, situated in the temporal lobe. Our BCI system has four modules: (i) the EEG Acquisition module based on a non-invasive headset with 14 electrodes; (ii) the Preprocessing module to remove noise and artifacts, using the Common Average Reference method; (iii) the Features Extraction module, using Wavelet Packet Transform (WPT); (iv) the Classification module based on a one-hidden layer artificial neural network. The present study consists of comparing the recognition accuracy of 5 Arabic words, when using all the headset electrodes or only the 4 electrodes situated near the Wernicke area, as well as the selection effect of the subbands produced by the WPT module. After applying the articial neural network on the produced database, we obtain, on the test dataset, an accuracy of 83.4% with all the electrodes and all the subbands of 8 levels of the WPT decomposition. However, by using only the 4 electrodes near Wernicke Area and the 6 middle subbands of the WPT, we obtain a high reduction of the dataset size, equal to approximately 19% of the total dataset, with 67.5% of accuracy rate. This reduction appears particularly important to improve the design of a low cost and simple to use BCI, trained for several words.

Keywords: Brain-computer interface, speech recognition, electroencephalography EEG, Wernicke area, artificial neural network.

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Authors: Fadi Awawdeh, O. Alsayyed

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New exact three-wave solutions including periodic two-solitary solutions and doubly periodic solitary solutions for the (2+1)-dimensional asymmetric Nizhnik-Novikov- Veselov (ANNV) system are obtained using Hirota's bilinear form and generalized three-wave type of ansatz approach. It is shown that the generalized three-wave method, with the help of symbolic computation, provides an e¤ective and powerful mathematical tool for solving high dimensional nonlinear evolution equations in mathematical physics.

Keywords: Soliton Solution, Hirota Bilinear Method, ANNV System.

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Authors: Saleh Dabil

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the research was conducted using the self report of shoplifters who apprehended in the supermarket while stealing. 943 shoplifters in three years were interviewed right after the stealing act and before calling the police. The aim of the study is to know the shoplifting characteristics in Saudi Arabia, including the trait of shoplifters and the situation of the supermarkets where the stealing takes place. The analysis based on the written information about each thief as the documentary research method. Descriptive statistics as well as some inferential statistics were employed. The result shows that there are differences between genders, age groups, occupations, time of the day, days of the week, months, way of stealing, individual or group of thieves and other supermarket situations in the type of items stolen, total price and the count of items. The result and the recommendation will serve as a guide for retailers where, when and who to look at to prevent shoplifting.

Keywords: Shoplifting, stealing, theft, supermarket.

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Authors: H. Bouadi, M. Bouchoucha, M. Tadjine

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In this paper; we are interested principally in dynamic modelling of quadrotor while taking into account the high-order nonholonomic constraints in order to develop a new control scheme as well as the various physical phenomena, which can influence the dynamics of a flying structure. These permit us to introduce a new state-space representation. After, the use of Backstepping approach for the synthesis of tracking errors and Lyapunov functions, a sliding mode controller is developed in order to ensure Lyapunov stability, the handling of all system nonlinearities and desired tracking trajectories. Finally simulation results are also provided in order to illustrate the performances of the proposed controller.

Keywords: Dynamic modeling, nonholonomic constraints, Backstepping, sliding mode.

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Authors: Xiaoqing Wang, Junfeng Wang, Xiaolan Zhu

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Android operating system has been recognized by most application developers because of its good open-source and compatibility, which enriches the categories of applications greatly. However, it has become the target of malware attackers due to the lack of strict security supervision mechanisms, which leads to the rapid growth of malware, thus bringing serious safety hazards to users. Therefore, it is critical to detect Android malware effectively. Generally, the permissions declared in the AndroidManifest.xml can reflect the function and behavior of the application to a large extent. Since current Android system has not any restrictions to the number of permissions that an application can request, developers tend to apply more than actually needed permissions in order to ensure the successful running of the application, which results in the abuse of permissions. However, some traditional detection methods only consider the requested permissions and ignore whether it is actually used, which leads to incorrect identification of some malwares. Therefore, a machine learning detection method based on the actually used permissions combination and API calls was put forward in this paper. Meanwhile, several experiments are conducted to evaluate our methodology. The result shows that it can detect unknown malware effectively with higher true positive rate and accuracy while maintaining a low false positive rate. Consequently, the AdaboostM1 (J48) classification algorithm based on information gain feature selection algorithm has the best detection result, which can achieve an accuracy of 99.8%, a true positive rate of 99.6% and a lowest false positive rate of 0.

Keywords: Android, permissions combination, API calls, machine learning.

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Authors: Warunpun Kongsom, Chaiwat Kongsom

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The objective of this study was to investigate the awareness, knowledge and consumer behavior towards organic products in Thailand. For this study, a purposive sampling technique was used to identify a sample group of 2,575 consumers over the age of 20 years who intended or made purchases from 1) green shops; 2) supermarkets with branches; and, 3) green markets. A questionnaire was used for data collection across the country. Descriptive statistics were used for data analysis. The results showed that more than 92% of consumers were aware of organic agriculture, but had less knowledge about it. More than 60% of consumers knew that organic agriculture production and processing did not allow the use of chemicals. And about 40% of consumers were confused between the food safety logo and the certified organic logo, and whether GMO was allowed in organic agriculture practice or not. In addition, most consumers perceived that organic agricultural products, good agricultural practice (GAP) products, agricultural chemicals free products, and hydroponic vegetable products had the same standard. In the view of organic consumers, the organic Thailand label was the most seen and reliable among various organic labels. Less than 3% of consumers thought that the International Federation of Organic Agriculture Movements (IFOAM) Global Organic Mark (GOM) was the most seen and reliable. For the behaviors of organic consumers, they purchased organic products mainly at the supermarket and green shop (55.4%), one to two times per month, and with a total expenditure of about 200 to 400 baht each time. The main reason for buying organic products was safety and free from agricultural chemicals. The considered factors in organic product selection were price (29.5%), convenience (22.4%), and a reliable certification system (21.3%). The demands for organic products were mainly rice, vegetables and fruits. Processed organic products were relatively small in quantity.

Keywords: Consumer behavior, consumer knowledge, organic products, Thailand.

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Authors: Varun Gupta, Ankit Pandey

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Crude oil market is an immensely complex and dynamic environment and thus the task of predicting changes in such an environment becomes challenging with regards to its accuracy. A number of approaches have been adopted to take on that challenge and machine learning has been at the core in many of them. There are plenty of examples of algorithms based on machine learning yielding satisfactory results for such type of prediction. In this paper, we have tried to predict crude oil prices using Long Short-Term Memory (LSTM) based recurrent neural networks. We have tried to experiment with different types of models using different epochs, lookbacks and other tuning methods. The results obtained are promising and presented a reasonably accurate prediction for the price of crude oil in near future.

Keywords: Crude oil price prediction, deep learning, LSTM, recurrent neural networks.

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Authors: N.Karpagam, D.Devaraj

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Static Var Compensator (SVC) is a shunt type FACTS device which is used in power system primarily for the purpose of voltage and reactive power control. In this paper, a fuzzy logic based supplementary controller for Static Var Compensator (SVC) is developed which is used for damping the rotor angle oscillations and to improve the transient stability of the power system. Generator speed and the electrical power are chosen as input signals for the Fuzzy Logic Controller (FLC). The effectiveness and feasibility of the proposed control is demonstrated with Single Machine Infinite Bus (SMIB) system and multimachine system (WSCC System) which show improvement over the use of a fixed parameter controller.

Keywords: FLC, SVC, Transient stability, SMIB, PIDcontroller.

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Authors: Brandon Foggo, Nanpeng Yu

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Power distribution circuits undergo frequent network topology changes that are often left undocumented. As a result, the documentation of a circuit’s connectivity becomes inaccurate with time. The lack of reliable circuit connectivity information is one of the biggest obstacles to model, monitor, and control modern distribution systems. To enhance the reliability and efficiency of electric power distribution systems, the circuit’s connectivity information must be updated periodically. This paper focuses on one critical component of a distribution circuit’s topology - the secondary transformer to phase association. This topology component describes the set of phase lines that feed power to a given secondary transformer (and therefore a given group of power consumers). Finding the documentation of this component is call Phase Identification, and is typically performed with physical measurements. These measurements can take time lengths on the order of several months, but with supervised learning, the time length can be reduced significantly. This paper compares several such methods applied to Phase Identification for a large range of real distribution circuits, describes a method of training data selection, describes preprocessing steps unique to the Phase Identification problem, and ultimately describes a method which obtains high accuracy (> 96% in most cases, > 92% in the worst case) using only 5% of the measurements typically used for Phase Identification.

Keywords: Distribution network, machine learning, network topology, phase identification, smart grid.

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Authors: Mohd Hasmadi Ismail, Kamaruzaman Jusoff

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In order to develop forest management strategies in tropical forest in Malaysia, surveying the forest resources and monitoring the forest area affected by logging activities is essential. There are tremendous effort has been done in classification of land cover related to forest resource management in this country as it is a priority in all aspects of forest mapping using remote sensing and related technology such as GIS. In fact classification process is a compulsory step in any remote sensing research. Therefore, the main objective of this paper is to assess classification accuracy of classified forest map on Landsat TM data from difference number of reference data (200 and 388 reference data). This comparison was made through observation (200 reference data), and interpretation and observation approaches (388 reference data). Five land cover classes namely primary forest, logged over forest, water bodies, bare land and agricultural crop/mixed horticultural can be identified by the differences in spectral wavelength. Result showed that an overall accuracy from 200 reference data was 83.5 % (kappa value 0.7502459; kappa variance 0.002871), which was considered acceptable or good for optical data. However, when 200 reference data was increased to 388 in the confusion matrix, the accuracy slightly improved from 83.5% to 89.17%, with Kappa statistic increased from 0.7502459 to 0.8026135, respectively. The accuracy in this classification suggested that this strategy for the selection of training area, interpretation approaches and number of reference data used were importance to perform better classification result.

Keywords: Image Classification, Reference Data, Accuracy Assessment, Kappa Statistic, Forest Land Cover

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Authors: Shima Fasahat

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This research is an experimental research which was done about microbial fuel cells in order to study them for electricity generating and wastewater treatment. These days, it is very important to find new, clean and sustainable ways for energy supplying. Because of this reason there are many researchers around the world who are studying about new and sustainable energies. There are different ways to produce these kind of energies like: solar cells, wind turbines, geothermal energy, fuel cells and many other ways. Fuel cells have different types one of these types is microbial fuel cell. In this research, an MFC was built in order to study how it can be used for electricity generating and wastewater treatment. The microbial fuel cell which was used in this research is a reactor that has two tanks with a catalyst solution. The chemical reaction in microbial fuel cells is a redox reaction. The microbial fuel cell in this research is a two chamber MFC. Anode chamber is an anaerobic one (ABR reactor) and the other chamber is a cathode chamber. Anode chamber consists of stabilized sludge which is the source of microorganisms that do redox reaction. The main microorganisms here are: Propionibacterium and Clostridium. The electrodes of anode chamber are graphite pages. Cathode chamber consists of graphite page electrodes and catalysts like: O₂, KMnO₄ and C₆N₆FeK₄. The membrane which separates the chambers is Nafion117. The reason of choosing this membrane is explained in the complete paper. The main goal of this research is to generate electricity and treating wastewater. It was found that when you use electron receptor compounds like: O_2, MnO₄, C₆N₆FeK₄ the velocity of electron receiving speeds up and in a less time more current will be achieved. It was found that the best compounds for this purpose are compounds which have iron in their chemical formula. It is also important to pay attention to the amount of nutrients which enters to bacteria chamber. By adding extra nutrients in some cases the result will be reverse.  By using ABR the amount of chemical oxidation demand reduces per day till it arrives to a stable amount.

Keywords: Anaerobic baffled reactor, bioenergy, electrode, energy efficient, microbial fuel cell, renewable chemicals, sustainable.

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Authors: D. Almazo, M. Toledo, C. Rodríguez

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This work presents a methodology for the design and manufacture of propellers oriented to the experimental verification of theoretical results based on the combined model. The design process begins by using algorithms in Matlab which output data contain the coordinates of the points that define the blade airfoils, in this case the NACA 6512 airfoil was used. The modeling for the propeller blade was made in NX7, through the imported files in Matlab and with the help of surfaces. Later, the hub and the clamps were also modeled. Finally, NX 7 also made possible to create post-processed files to the required machine. It is possible to find the block of numbers with G & M codes about the type of driver on the machine. The file extension is .ptp. These files made possible to manufacture the blade, and the hub of the propeller.

Keywords: Airfoil, CAM, manufacturing, mathematical algorithm, numeric control, propeller design, simulation.

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Authors: Milan Paudel, Fook Fah Yap, Anil K. Bastola

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The difficulties in riding small wheel bicycles and their lesser stability have been perceived for a long time. Although small wheel bicycles are designed using the similar approach and guidelines that have worked well for big wheel bicycles, the performance of the big wheelers and the smaller wheelers are markedly different. Since both the big wheelers and small wheelers have same fundamental geometry, most blame the small wheel for this discrepancy in the performance. This paper reviews existing guidelines for bicycle design, especially the front steering geometry for the bicycle, and provides a systematic and quantitative analysis of different wheel sized bicycles. A validated mathematical model has been used as a tool to assess the dynamic performance of the bicycles in term of their self-stability. The results obtained were found to corroborate the subjective perception of cyclists for small wheel bicycles. The current approach for small wheel bicycle design requires higher speed to be self-stable. However, it was found that increasing the headtube angle and selecting a proper trail could improve the dynamic performance of small wheel bicycles. A range of parameters for front steering geometry has been identified for small wheel bicycles that have comparable stability as big wheel bicycles. Interestingly, most of the identified geometries are found to be beyond the ISO recommended range and seem to counter the current approach of small wheel bicycle design. Therefore, it was successfully shown that the guidelines for big wheelers do not translate directly to small wheelers, but careful selection of the front geometry could make small wheel bicycles as stable as big wheel bicycles.

Keywords: Big wheel bicycle, design approach, ISO requirements, small wheel bicycle, stability and performance.

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Authors: F. Castillo, J. Arellano, S. Sánchez

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In this paper an alternative analysis in the time domain is described and the results of the interpolation process are presented by means of functions that are based on the rule of conditional mathematical expectation and the covariance function. A comparison between the interpolation error caused by low order filters and the classic sinc(t) truncated function is also presented. When fewer samples are used, low-order filters have less error. If the number of samples increases, the sinc(t) type functions are a better alternative. Generally speaking there is an optimal filter for each input signal which depends on the filter length and covariance function of the signal. A novel scheme of work for adaptive interpolation filters is also presented.

Keywords: Interpolation, basis function, over-sampling.

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Authors: L. Yu, W. K. Li, S. K. Ong, A. Y. C. Nee

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In this paper, a scalable augmented reality framework for handheld devices is presented. The presented framework is enabled by using a server-client data communication structure, in which the search for tracking targets among a database of images is performed on the server-side while pixel-wise 3D tracking is performed on the client-side, which, in this case, is a handheld mobile device. Image search on the server-side adopts a residual-enhanced image descriptors representation that gives the framework a scalability property. The tracking algorithm on the client-side is based on a gravity-aligned feature descriptor which takes the advantage of a sensor-equipped mobile device and an optimized intensity-based image alignment approach that ensures the accuracy of 3D tracking. Automatic content streaming is achieved by using a key-frame selection algorithm, client working phase monitoring and standardized rules for content communication between the server and client. The recognition accuracy test performed on a standard dataset shows that the method adopted in the presented framework outperforms the Bag-of-Words (BoW) method that has been used in some of the previous systems. Experimental test conducted on a set of video sequences indicated the real-time performance of the tracking system with a frame rate at 15-30 frames per second. The presented framework is exposed to be functional in practical situations with a demonstration application on a campus walk-around.

Keywords: Augmented reality framework, server-client model, vision-based tracking, image search.

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Authors: D. H. Lee, Nur Irmawati

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This paper aims to study the heat transfer and fluid flow characteristics of nanofluids used in spray cooling systems. The effect of spray height, type of nanofluids and concentration of nanofluids are numerically investigated. Five different nanofluids such as AgH2O, Al2O3, CuO, SiO2 and TiO2 with volume fraction range of 0.5% to 2.5% are used. The results revealed that the heat transfer performance decreases as spray height increases. It is found that TiO2 has the highest transfer coefficient among other nanofluids. In dilute spray conditions, low concentration of nanofluids is observed to be more effective in heat removal in a spray cooling system.

Keywords: Numerical simulation, Spray cooling, Heat transfer, Nanofluids.

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Authors: Ahmed Sakr Ashour, Hoda Saad AboRemila

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An attempt was made to fill the gap in the macro analysis of corruption by suggesting a conceptual framework that differentiates four types of macro corruption: state capture, political, bureaucratic and financial/corporate. The economic consequences or forward linkages (growth, inclusiveness and sustainability of development) and macro institutional determinants constituting the backward linkages of each type were delineated. The research implications of the macro perspective and proposed framework were discussed. Implications of the findings for theory, research and reform policies addressing macro corruption issues were discussed.

Keywords: Economic growth, Inclusive growth, macro corruption, sustainable development.

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Authors: N. Kekelidze, B. Kvirkvelia, E. Khutsishvili, T. Qamushadze, D. Kekelidze, R. Kobaidze, Z. Chubinishvili, N. Qobulashvili, G. Kekelidze

Abstract:

On the basis of InAs, InP and their InP_xAs_1-x solid solutions, the technologies were developed and materials were created where the electron concentration and optical and thermoelectric properties do not change under the irradiation with Ф = 2∙10¹⁸ n/cm² fluences of fast neutrons high-energy electrons (50 MeV, Ф = 6·10¹⁷ e/cm²) and 3 MeV electrons with fluence Ф = 3∙10¹⁸ e/cm². The problem of obtaining such material has been solved, in which under hard irradiation the mobility of the electrons does not decrease, but increases. This material is characterized by high thermal stability up to T = 700 °C. The complex process of defects formation has been analyzed and shown that, despite of hard irradiation, the essential properties of investigated materials are mainly determined by point type defects.

Keywords: InAs, InP, solid solutions, irradiation.

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Authors: Zsolt János Viharos, Krisztián Balázs Kis, Imre Paniti, Gábor Belső, Péter Németh, János Farkas

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The paper presents the results and industrial applications in the production setup period estimation based on industrial data inherited from the field of polymer cutting. The literature of polymer cutting is very limited considering the number of publications. The first polymer cutting machine is known since the second half of the 20th century; however, the production of polymer parts with this kind of technology is still a challenging research topic. The products of the applying industrial partner must met high technical requirements, as they are used in medical, measurement instrumentation and painting industry branches. Typically, 20% of these parts are new work, which means every five years almost the entire product portfolio is replaced in their low series manufacturing environment. Consequently, it requires a flexible production system, where the estimation of the frequent setup periods' lengths is one of the key success factors. In the investigation, several (input) parameters have been studied and grouped to create an adequate training information set for an artificial neural network as a base for the estimation of the individual setup periods. In the first group, product information is collected such as the product name and number of items. The second group contains material data like material type and colour. In the third group, surface quality and tolerance information are collected including the finest surface and tightest (or narrowest) tolerance. The fourth group contains the setup data like machine type and work shift. One source of these parameters is the Manufacturing Execution System (MES) but some data were also collected from Computer Aided Design (CAD) drawings. The number of the applied tools is one of the key factors on which the industrial partners’ estimations were based previously. The artificial neural network model was trained on several thousands of real industrial data. The mean estimation accuracy of the setup periods' lengths was improved by 30%, and in the same time the deviation of the prognosis was also improved by 50%. Furthermore, an investigation on the mentioned parameter groups considering the manufacturing order was also researched. The paper also highlights the manufacturing introduction experiences and further improvements of the proposed methods, both on the shop floor and on the quotation preparation fields. Every week more than 100 real industrial setup events are given and the related data are collected.

Keywords: Artificial neural network, low series manufacturing, polymer cutting, setup period estimation.

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Authors: Sarma Cakula, Maija Sedleniece

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Simulation and modeling computer programs are concerned with construction of models for analyzing different perspectives and possibilities in changing conditions environment. The paper presents theoretical justification and evaluation of qualitative e-learning development model in perspective of advancing modern technologies. There have been analyzed principles of qualitative e-learning in higher education, productivity of studying process using modern technologies, different kind of methods and future perspectives of e-learning in formal education. Theoretically grounded and practically tested model of developing e-learning methods using different technologies for different type of classroom, which can be used in professor-s decision making process to choose the most effective e-learning methods has been worked out.

Keywords: E-learning, modeling, E-learning methods development, personal knowledge management

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Authors: Pradip Kundu, Samarjit Kar, Manoranjan Maiti

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In this paper, some practical solid transportation models are formulated considering per trip capacity of each type of conveyances with crisp and rough unit transportation costs. This is applicable for the system in which full vehicles, e.g. trucks, rail coaches are to be booked for transportation of products so that transportation cost is determined on the full of the conveyances. The models with unit transportation costs as rough variables are transformed into deterministic forms using rough chance constrained programming with the help of trust measure. Numerical examples are provided to illustrate the proposed models in crisp environment as well as with unit transportation costs as rough variables.

Keywords: Solid transportation problem, Rough set, Rough variable, Trust measure.

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Authors: M. Jalali Azizpour, S.Norouzi H. Mohammadi Majd

Abstract:

In this paper, the babbitting of a bearing in boiler feed pump of an electromotor has been studied. These bearings have an important role in reducing the shut down times in the pumps, compressors and turbines. The most conventional method in babbitting is casting as a melting method. The comparison between thermal spray and casting methods in babbitting shows that the thermal spraying babbitt layer has better performance and tribological behavior. The metallurgical and tribological analysis such as SEM, EDS and wet chemical analysis has been made in the Babbitt alloys and worn surfaces. Two type of babbitt materials: tinbase and lead-base babbitt was used. The benefits of thermally sprayed babbitt layers are completely clear especially in large bearings.

Keywords: Thermal spray, Babbitting, Bonding, Bearing, BFP, CWP

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