Search results for: and processing time.

Authors: Akram M. Othman, May H. Riadh

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This research work is aimed at speech recognition using scaly neural networks. A small vocabulary of 11 words were established first, these words are “word, file, open, print, exit, edit, cut, copy, paste, doc1, doc2". These chosen words involved with executing some computer functions such as opening a file, print certain text document, cutting, copying, pasting, editing and exit. It introduced to the computer then subjected to feature extraction process using LPC (linear prediction coefficients). These features are used as input to an artificial neural network in speaker dependent mode. Half of the words are used for training the artificial neural network and the other half are used for testing the system; those are used for information retrieval. The system components are consist of three parts, speech processing and feature extraction, training and testing by using neural networks and information retrieval. The retrieve process proved to be 79.5-88% successful, which is quite acceptable, considering the variation to surrounding, state of the person, and the microphone type.

Keywords: Feature extraction, Liner prediction coefficients, neural network, Speech Recognition, Scaly ANN.

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Authors: Zaw Tun, Aung Htein Maw

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The nature of wireless ad hoc and sensor networks make them very attractive to attackers. One of the most popular and serious attacks in wireless ad hoc networks is wormhole attack and most proposed protocols to defend against this attack used positioning devices, synchronized clocks, or directional antennas. This paper analyzes the nature of wormhole attack and existing methods of defending mechanism and then proposes round trip time (RTT) and neighbor numbers based wormhole detection mechanism. The consideration of proposed mechanism is the RTT between two successive nodes and those nodes- neighbor number which is needed to compare those values of other successive nodes. The identification of wormhole attacks is based on the two faces. The first consideration is that the transmission time between two wormhole attack affected nodes is considerable higher than that between two normal neighbor nodes. The second detection mechanism is based on the fact that by introducing new links into the network, the adversary increases the number of neighbors of the nodes within its radius. This system does not require any specific hardware, has good performance and little overhead and also does not consume extra energy. The proposed system is designed in ad hoc on-demand distance vector (AODV) routing protocol and analysis and simulations of the proposed system are performed in network simulator (ns-2).

Keywords: AODV, Wormhole attacks, Wireless ad hoc andsensor networks

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Authors: Nisa Özge Önal, Kamil Karaçuha, Göksu Hazar Erdinç, Banu Bahar Karaçuha, Ertuğrul Karaçuha

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The study aims to use a mathematical approach with the fractional calculus which is developed to have the ability to continuously analyze the factors related to the children’s height development. Until now, tracking the development of the child is getting more important and meaningful. Knowing and determining the factors related to the physical development of the child any desired time would provide better, reliable and accurate results for childcare. In this frame, 7 groups for height percentile curve (3th, 10th, 25th, 50th, 75th, 90th, and 97th) of Turkey are used. By using discrete height data of 0-18 years old children and the least squares method, a continuous curve is developed valid for any time interval. By doing so, in any desired instant, it is possible to find the percentage and location of the child in Percentage Chart. Here, with the help of the fractional calculus theory, a mathematical model is developed. The outcomes of the proposed approach are quite promising compared to the linear and the polynomial method. The approach also yields to predict the expected values of children in the sense of height.

Keywords: Children growth percentile, children physical development, fractional calculus, linear and polynomial model.

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Authors: H. Abdizadeh, Y. Vahidshad

Abstract:

The present paper discusses the selection of process parameters for obtaining optimal nanocrystallites size in the CuOZrO2 catalyst. There are some parameters changing the inorganic structure which have an influence on the role of hydrolysis and condensation reaction. A statistical design test method is implemented in order to optimize the experimental conditions of CuO-ZrO2 nanoparticles preparation. This method is applied for the experiments and L16 orthogonal array standard. The crystallites size is considered as an index. This index will be used for the analysis in the condition where the parameters vary. The effect of pH, H2O/ precursor molar ratio (R), time and temperature of calcination, chelating agent and alcohol volume are particularity investigated among all other parameters. In accordance with the results of Taguchi, it is found that temperature has the greatest impact on the particle size. The pH and H2O/ precursor molar ratio have low influences as compared with temperature. The alcohol volume as well as the time has almost no effect as compared with all other parameters. Temperature also has an influence on the morphology and amorphous structure of zirconia. The optimal conditions are determined by using Taguchi method. The nanocatalyst is studied by DTA-TG, XRD, EDS, SEM and TEM. The results of this research indicate that it is possible to vary the structure, morphology and properties of the sol-gel by controlling the above-mentioned parameters.

Keywords: CuO-ZrO2 Nanoparticles, Sol-gel, Taguchi method.

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Authors: Ameur Abdelkader, Abed Bouarfa Hafida

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Since its inception, predictive analysis has revolutionized the IT industry through its robustness and decision-making facilities. It involves the application of a set of data processing techniques and algorithms in order to create predictive models. Its principle is based on finding relationships between explanatory variables and the predicted variables. Past occurrences are exploited to predict and to derive the unknown outcome. With the advent of big data, many studies have suggested the use of predictive analytics in order to process and analyze big data. Nevertheless, they have been curbed by the limits of classical methods of predictive analysis in case of a large amount of data. In fact, because of their volumes, their nature (semi or unstructured) and their variety, it is impossible to analyze efficiently big data via classical methods of predictive analysis. The authors attribute this weakness to the fact that predictive analysis algorithms do not allow the parallelization and distribution of calculation. In this paper, we propose to extend the predictive analysis algorithm, Classification And Regression Trees (CART), in order to adapt it for big data analysis. The major changes of this algorithm are presented and then a version of the extended algorithm is defined in order to make it applicable for a huge quantity of data.

Keywords: Predictive analysis, big data, predictive analysis algorithms. CART algorithm.

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Authors: Mehaiguene Madjid, Touhari Fadhila, Meddi Mohamed

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The Cheliff basin offers a good hydrological example for the possibility of studying the problem which elucidated in the future, because of the unclearity in several aspects and hydraulic installation. Thus, our study of the Cheliff basin is divided into two principal parts: The spatial evaluation of the precipitation: also, the understanding of the modes of the reconstitution of the resource in water supposes a good knowledge of the structuring of the precipitation fields in the studied space. In the goal of a good knowledge of revitalizes them in water and their management integrated one judged necessary to establish a precipitation card of the Cheliff basin for a good understanding of the evolution of the resource in water in the basin and that goes will serve as basis for all study of hydraulic planning in the Cheliff basin. Then, the establishment of the precipitation card of the Cheliff basin answered a direct need of setting to the disposition of the researchers for the region and a document of reference that will be completed therefore and actualized. The hydrological study, based on the statistical hydrometric data processing will lead us to specify the hydrological terms of the assessment hydrological and to clarify the fundamental aspects of the annual flow, seasonal, extreme and thus of their variability and resources surface water.

Keywords: Hydrological assessment, surface water resources, Cheliff, Algeria.

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Authors: Meltem Serhatli, Ferda N. Alpaslan

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Processing the data by computers and performing reasoning tasks is an important aim in Computer Science. Semantic Web is one step towards it. The use of ontologies to enhance the information by semantically is the current trend. Huge amount of domain specific, unstructured on-line data needs to be expressed in machine understandable and semantically searchable format. Currently users are often forced to search manually in the results returned by the keyword-based search services. They also want to use their native languages to express what they search. In this paper, an ontology-based automated question answering system on software test documents domain is presented. The system allows users to enter a question about the domain by means of natural language and returns exact answer of the questions. Conversion of the natural language question into the ontology based query is the challenging part of the system. To be able to achieve this, a new algorithm regarding free text to ontology based search engine query conversion is proposed. The algorithm is based on investigation of suitable question type and parsing the words of the question sentence.

Keywords: Description Logics, ontology, question answering, reasoning.

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Authors: Rama Bhargava, Mania Goyal

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The problem of magnetohydrodynamics boundary layer flow and heat transfer on a permeable stretching surface in a second grade nanofluid under the effect of heat generation and partial slip is studied theoretically. The Brownian motion and thermophoresis effects are also considered. The boundary layer equations governed by the PDE’s are transformed into a set of ODE’s with the help of local similarity transformations. The differential equations are solved by variational finite element method. The effects of different controlling parameters on the flow field and heat transfer characteristics are examined. The numerical results for the dimensionless velocity, temperature and nanoparticle volume fraction as well as the reduced Nusselt and Sherwood number have been presented graphically. The comparison confirmed excellent agreement. The present study is of great interest in coating and suspensions, cooling of metallic plate, oils and grease, paper production, coal water or coal-oil slurries, heat exchangers technology, materials processing exploiting.

Keywords: Viscoelastic nanofluid, partial slip, stretching sheet, heat generation/absorption, MHD flow, FEM.

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Authors: Akash Rathee, Harish Parthasarathy

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In this paper, a frequency-variation based method has been proposed for transistor parameter estimation in a commonemitter transistor amplifier circuit. We design an algorithm to estimate the transistor parameters, based on noisy measurements of the output voltage when the input voltage is a sine wave of variable frequency and constant amplitude. The common emitter amplifier circuit has been modelled using the transistor Ebers-Moll equations and the perturbation technique has been used for separating the linear and nonlinear parts of the Ebers-Moll equations. This model of the amplifier has been used to determine the amplitude of the output sinusoid as a function of the frequency and the parameter vector. Then, applying the proposed method to the frequency components, the transistor parameters have been estimated. As compared to the conventional time-domain least squares method, the proposed method requires much less data storage and it results in more accurate parameter estimation, as it exploits the information in the time and frequency domain, simultaneously. The proposed method can be utilized for parameter estimation of an analog device in its operating range of frequencies, as it uses data collected from different frequencies output signals for parameter estimation.

Keywords: Perturbation Technique, Parameter estimation, frequency-variation based method.

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Authors: Emel Kızılkaya Aydogan, Mihrimah Ozmen, Yılmaz Delice

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In recent days, there is a change and the ongoing development of the telecommunications sector in the global market. In this sector, churn analysis techniques are commonly used for analysing why some customers terminate their service subscriptions prematurely. In addition, customer churn is utmost significant in this sector since it causes to important business loss. Many companies make various researches in order to prevent losses while increasing customer loyalty. Although a large quantity of accumulated data is available in this sector, their usefulness is limited by data quality and relevance. In this paper, a cost-sensitive feature selection framework is developed aiming to obtain the feature reducts to predict customer churn. The framework is a cost based optional pre-processing stage to remove redundant features for churn management. In addition, this cost-based feature selection algorithm is applied in a telecommunication company in Turkey and the results obtained with this algorithm.

Keywords: Churn prediction, data mining, decision-theoretic rough set, feature selection.

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Authors: Maris Klavins, Valery Rodinov

Abstract:

The aim of this study was to analyze long term changes of surface water quality in Latvia, spatial variability of water chemical composition, possible impacts of different pollution sources as well as to analyze the measures to protect national water resources - river basin management. Within this study, the concentrations of major water ingredients and microelements in major rivers and lakes of Latvia have been determined. Metal concentrations in river and lake waters were compared with water chemical composition. The mean concentrations of trace metals in inland waters of Latvia are appreciably lower than the estimated world averages for river waters and close to or lower than background values, unless regional impacts determined by local geochemistry. This may be explained by a comparatively lower level of anthropogenic load. In the same time in several places, direct anthropogenic impacts are evident, regarding influences of point sources both transboundary transport impacts. Also, different processes related to pollution of surface waters in Latvia have been analyzed. At first the analysis of changes and composition of pollutant emissions in Latvia has been realized, and the obtained results were compared with actual composition of atmospheric precipitation and their changes in time.

Keywords: Water quality, trend analysis, pollution, human impact.

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Authors: K. A. Sumitra Devi, N. P. Banashree, Annamma Abraham

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Partitioning is a critical area of VLSI CAD. In order to build complex digital logic circuits its often essential to sub-divide multi -million transistor design into manageable Pieces. This paper looks at the various partitioning techniques aspects of VLSI CAD, targeted at various applications. We proposed an evolutionary time-series model and a statistical glitch prediction system using a neural network with selection of global feature by making use of clustering method model, for partitioning a circuit. For evolutionary time-series model, we made use of genetic, memetic & neuro-memetic techniques. Our work focused in use of clustering methods - K-means & EM methodology. A comparative study is provided for all techniques to solve the problem of circuit partitioning pertaining to VLSI design. The performance of all approaches is compared using benchmark data provided by MCNC standard cell placement benchmark net lists. Analysis of the investigational results proved that the Neuro-memetic model achieves greater performance then other model in recognizing sub-circuits with minimum amount of interconnections between them.

Keywords: VLSI, circuit partitioning, memetic algorithm, genetic algorithm.

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Authors: Ibrahim Gomaa, Hoda M. O. Mokhtar

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Although most of the existing skyline queries algorithms focused basically on querying static points through static databases; with the expanding number of sensors, wireless communications and mobile applications, the demand for continuous skyline queries has increased. Unlike traditional skyline queries which only consider static attributes, continuous skyline queries include dynamic attributes, as well as the static ones. However, as skyline queries computation is based on checking the domination of skyline points over all dimensions, considering both the static and dynamic attributes without separation is required. In this paper, we present an efficient algorithm for computing continuous skyline queries without discriminating between static and dynamic attributes. Our algorithm in brief proceeds as follows: First, it excludes the points which will not be in the initial skyline result; this pruning phase reduces the required number of comparisons. Second, the association between the spatial positions of data points is examined; this phase gives an idea of where changes in the result might occur and consequently enables us to efficiently update the skyline result (continuous update) rather than computing the skyline from scratch. Finally, experimental evaluation is provided which demonstrates the accuracy, performance and efficiency of our algorithm over other existing approaches.

Keywords: Continuous query processing, dynamic database, moving object, skyline queries.

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Authors: E. Binaeian, SH. Soroushnia

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Acute toxicity of nano SiO2, ZnO, MCM-41 (Meso pore silica), Cu, Multi Wall Carbon Nano Tube (MWCNT), Single Wall Carbon Nano Tube (SWCNT) , Fe (Coated) to bacteria Vibrio fischeri using a homemade luminometer , was evaluated. The values of the nominal effective concentrations (EC), causing 20% and 50% inhibition of biouminescence, using two mathematical models at two times of 5 and 30 minutes were calculated. Luminometer was designed with Photomultiplier (PMT) detector. Luminol chemiluminescence reaction was carried out for the calibration graph. In the linear calibration range, the correlation coefficients and coefficient of Variation (CV) were 0.988 and 3.21% respectively which demonstrate the accuracy and reproducibility of the instrument that are suitable. The important part of this research depends on how to optimize the best condition for maximum bioluminescence. The culture of Vibrio fischeri with optimal conditions in liquid media, were stirring at 120 rpm at a temperature of 150C to 180C and were incubated for 24 to 72 hours while solid medium was held at 180C and for 48 hours. Suspension of nanoparticles ZnO, after 30 min contact time to bacteria Vibrio fischeri, showed the highest toxicity while SiO2 nanoparticles showed the lowest toxicity. After 5 min exposure time, the toxicity of ZnO was the strongest and MCM-41 was the weakest toxicant component.

Keywords: Bioluminescence, effective concentration, nanomaterials, toxicity, Vibrio fischeri.

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Authors: Abbas Ali Mahmood Karwi

Abstract:

Accurate timing alignment and stability is important to maximize the true counts and minimize the random counts in positron emission tomography So signals output from detectors must be centering with the two isotopes to pre-operation and fed signals into four units of pulse-processing units, each unit can accept up to eight inputs. The dual source computed tomography consist two units on the left for 15 detector signals of Cs-137 isotope and two units on the right are for 15 detectors signals of Co-60 isotope. The gamma spectrum consisting of either single or multiple photo peaks. This allows for the use of energy discrimination electronic hardware associated with the data acquisition system to acquire photon counts data with a specific energy, even if poor energy resolution detectors are used. This also helps to avoid counting of the Compton scatter counts especially if a single discrete gamma photo peak is emitted by the source as in the case of Cs-137. In this study the polyenergetic version of the alternating minimization algorithm is applied to the dual energy gamma computed tomography problem.

Keywords: Alignment, Spectrum, Laser, Detectors, Image

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Authors: R. V. Kurahatti, D. G. Mallapur, K. Rajendra Udupa

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In the present work, a comparative study on the microstructure and mechanical properties of as cast, cast aged and forged aged A356 alloy has been investigated. The study reveals that mechanical properties of A356 alloy are highly influenced by melt treatment and solid state processing. Cast aged alloys achieve highest strength and hardness compared to as cast and forge aged ones. Ones treated with combined addition of grain refiners and modifiers achieve maximum strength and hardness. Cast aged A356 alloy possesses higher wear resistance compared to as cast and forge aged ones. Forging improves both strength and ductility of alloys over as cast ones. However, the improvement in ductility is perceptible only for properly grain refined and modified alloys. Ones refined with 0.65% Al-3Ti shows highest improvement in ductility while ones treated with 0.20% Al-10Sr exhibits less improvement in ductility.

Keywords: Forged A356 alloy, Grain refinement, Modification, Wear

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Authors: Shonak Bansal, Prince Jain, Arun Kumar Singh, Neena Gupta

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Recently nature–inspired algorithms have widespread use throughout the tough and time consuming multi–objective scientific and engineering design optimization problems. In this paper, we present extended forms of firefly algorithm to find optimal Golomb ruler (OGR) sequences. The OGRs have their one of the major application as unequally spaced channel–allocation algorithm in optical wavelength division multiplexing (WDM) systems in order to minimize the adverse four–wave mixing (FWM) crosstalk effect. The simulation results conclude that the proposed optimization algorithm has superior performance compared to the existing conventional computing and nature–inspired optimization algorithms to find OGRs in terms of ruler length, total optical channel bandwidth and computation time.

Keywords: Channel allocation, conventional computing, four–wave mixing, nature–inspired algorithm, optimal Golomb ruler, Lévy flight distribution, optimization, improved multi–objective Firefly algorithms, Pareto optimal.

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Authors: G. Aloisio, L. T. De Paolis, A. De Mauro, A. Mongelli

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One of the essential requirements of a realistic surgical simulator is to reproduce haptic sensations due to the interactions in the virtual environment. However, the interaction need to be performed in real-time, since a delay between the user action and the system reaction reduces the immersion sensation. In this paper, a prototype of a coronary stent implant simulator is present; this system allows real-time interactions with an artery by means of a specific haptic device. To improve the realism of the simulation, the building of the virtual environment is based on real patients- images and a Web Portal is used to search in the geographically remote medical centres a virtual environment with specific features in terms of pathology or anatomy. The functional architecture of the system defines several Medical Centres in which virtual environments built from the real patients- images and related metadata with specific features in terms of pathology or anatomy are stored. The searched data are downloaded from the Medical Centre to the Training Centre provided with a specific haptic device and with the software necessary both to manage the interaction in the virtual environment. After the integration of the virtual environment in the simulation system it is possible to perform training on the specific surgical procedure.

Keywords: Medical Simulation, Web Portal, Virtual Reality.

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Authors: Mohamed Watfa, William Daher, Hisham Al Azar

Abstract:

The main idea behind in network aggregation is that, rather than sending individual data items from sensors to sinks, multiple data items are aggregated as they are forwarded by the sensor network. Existing sensor network data aggregation techniques assume that the nodes are preprogrammed and send data to a central sink for offline querying and analysis. This approach faces two major drawbacks. First, the system behavior is preprogrammed and cannot be modified on the fly. Second, the increased energy wastage due to the communication overhead will result in decreasing the overall system lifetime. Thus, energy conservation is of prime consideration in sensor network protocols in order to maximize the network-s operational lifetime. In this paper, we give an energy efficient approach to query processing by implementing new optimization techniques applied to in-network aggregation. We first discuss earlier approaches in sensors data management and highlight their disadvantages. We then present our approach “Energy Efficient Indexed Aggregation" (EEIA) and evaluate it through several simulations to prove its efficiency, competence and effectiveness.

Keywords: Sensor Networks, Data Base, Data Fusion, Aggregation, Indexing, Energy Efficiency

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Authors: Reza Ghasemi, Negin Amiri Hazaveh

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In this paper, control methodology based on the selection of the type of traffic light and the period of the green phase to accomplish an optimum balance at intersections is proposed. This balance should be flexible to the static behavior of time, and randomness in a traffic situation; the goal of the proposed method is to reduce traffic volume in transportation, the average delay for each vehicle, and control over the crash of cars. The proposed method was specifically investigated at the intersection through an appropriate timing of traffic lights by sampling a multi-agent system. It consists of a large number of intersections, each of which is considered as an independent agent that exchanges information with each other, and the stability of each agent is provided separately. The robustness against uncertainties, scalability, and stability of the closed-loop overall system are the main merits of the proposed methodology. The simulation results show that the fuzzy intelligent controller in this multi-factor system which is a Takagi-Sugeno (TS) fuzzy is more useful than scheduling in the fixed-time method and it reduces the lengths of vehicles queuing.

Keywords: Fuzzy intelligent controller, traffic-light control, multi-agent systems, state space equations, stability.

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Authors: Li Long, Thomas Ortlepp

Abstract:

A theoretical model for the optimization of thermopile sensor performance is developed for thermoelectric-based infrared radiation detection. It is shown that the performance of polycrystalline silicon film thermopile sensor can be optimized according to the thermoelectric quality factor, sensor layer structure factor and sensor layout shape factor. Based on the properties of electrons, phonons, grain boundaries and their interactions, the thermoelectric quality factor of polycrystalline silicon is analyzed with the relaxation time approximation of Boltzmann transport equation. The model includes the effects of grain structure, grain boundary trap properties and doping concentration. The layer structure factor of sensor is analyzed with respect to infrared absorption coefficient. The effect of layout design is characterized with the shape factor, which is calculated for different sensor designs. Double layer polycrystalline silicon thermopile infrared sensors on suspended support membrane have been designed and fabricated with a CMOS-compatible process. The theoretical approach is confirmed with measurement results.

Keywords: Polycrystalline silicon film, relaxation time approximation, specific detectivity, thermal conductivity, thermopile infrared sensor.

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Authors: Tofigh Hamidavi, Sepehr Abrishami, Pasquale Ponterosso, David Begg

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Structural design and analysis is an important and time-consuming process, particularly at the conceptual design stage. Decisions made at this stage can have an enormous effect on the entire project, as it becomes ever costlier and more difficult to alter the choices made early on in the construction process. Hence, optimisation of the early stages of structural design can provide important efficiencies in terms of cost and time. This paper suggests a structural design optimisation (SDO) framework in which Genetic Algorithms (GAs) may be used to semi-automate the production and optimisation of early structural design alternatives. This framework has the potential to leverage conceptual structural design innovation in Architecture, Engineering and Construction (AEC) projects. Moreover, this framework improves the collaboration between the architectural stage and the structural stage. It will be shown that this SDO framework can make this achievable by generating the structural model based on the extracted data from the architectural model. At the moment, the proposed SDO framework is in the process of validation, involving the distribution of an online questionnaire among structural engineers in the UK.

Keywords: Building Information Modelling, BIM, Genetic Algorithm, GA, architecture-engineering-construction, AEC, Optimisation, structure, design, population, generation, selection, mutation, crossover, offspring.

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Authors: Mustafa Kisa, Fatih Mehmet Botsali

Abstract:

Recent developments in automotive technology are focused on economy, comfort and safety. Vehicle tracking and collision detection systems are attracting attention of many investigators focused on safety of driving in the field of automotive mechatronics. In this paper, a vision-based vehicle detection system is presented. Developed system is intended to be used in collision detection and driver alert. The system uses RGB images captured by a camera in a car driven in the highway. Images captured by the moving camera are used to detect the moving vehicles in the image. A vehicle ahead of the camera is detected in daylight conditions. The proposed method detects moving vehicles by subtracting successive images. Plate height of the vehicle is determined by using a plate recognition algorithm. Distance of the moving object is calculated by using the plate height. After determination of the distance of the moving vehicle relative speed of the vehicle and Time-to-Collision are calculated by using distances measured in successive images. Results obtained in road tests are discussed in order to validate the use of the proposed method.

Keywords: Image possessing, vehicle tracking, license plate detection, computer vision.

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Authors: Shafiq Alam, Mirza Hossain, Hesam Hassan Nejad

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Impurity metals such as manganese and cadmium from high-tenor cobalt electrolyte solution were selectively removed by solvent extraction method using Co-D2EHPA after converting the functional group of D2EHPA with Co2+ ions. The process parameters such as pH, organic concentration, O/A ratio, kinetics etc. were investigated and the experiments were conducted by batch tests in the laboratory bench scale. Results showed that a significant amount of manganese and cadmium can be extracted using Co-D2EHPA for the optimum processing of cobalt electrolyte solution at equilibrium pH about 3.5. The McCabe-Thiele diagram, constructed from the extraction studies showed that 100% impurities can be extracted through four stages for manganese and three stages for cadmium using O/A ratio of 0.65 and 1.0, respectively. From the stripping study, it was found that 100% manganese and cadmium can be stripped from the loaded organic using 0.4 M H2SO4 in a single contact. The loading capacity of Co-D2EHPA by manganese and cadmium were also investigated with different O/A ratio as well as with number of stages of contact of aqueous and organic phases. Valuable information was obtained for the designing of an impurities removal process for the production of pure cobalt with less trouble in the electrowinning circuit.

Keywords: Manganese, Cadmium, Cobalt, D2EHPA, Solvent extraction.

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Authors: Hiroshi Abe, Minoru Nakayama

Abstract:

The frontal area in the brain is known to be involved in behavioral judgement. Because a Kanji character can be discriminated visually and linguistically from other characters, in Kanji character discrimination, we hypothesized that frontal event-related potential (ERP) waveforms reflect two discrimination processes in separate time periods: one based on visual analysis and the other based on lexcical access. To examine this hypothesis, we recorded ERPs while performing a Kanji lexical decision task. In this task, either a known Kanji character, an unknown Kanji character or a symbol was presented and the subject had to report if the presented character was a known Kanji character for the subject or not. The same response was required for unknown Kanji trials and symbol trials. As a preprocessing of signals, we examined the performance of a method using independent component analysis for artifact rejection and found it was effective. Therefore we used it. In the ERP results, there were two time periods in which the frontal ERP wavefoms were significantly different betweeen the unknown Kanji trials and the symbol trials: around 170ms and around 300ms after stimulus onset. This result supported our hypothesis. In addition, the result suggests that Kanji character lexical access may be fully completed by around 260ms after stimulus onset.

Keywords: Character discrimination, Event-related Potential, IndependentComponent Analysis, Kanji, Lexical access.

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Authors: Hadeer R. M. Tawfik, Rania A. K. Birry, Amani A. Saad

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Eyes are considered to be the most sensitive and important organ for human being. Thus, any eye disorder will affect the patient in all aspects of life. Cataract is one of those eye disorders that lead to blindness if not treated correctly and quickly. This paper demonstrates a model for automatic detection, classification, and grading of cataracts based on image processing techniques and artificial intelligence. The proposed system is developed to ease the cataract diagnosis process for both ophthalmologists and patients. The wavelet transform combined with 2D Log Gabor Wavelet transform was used as feature extraction techniques for a dataset of 120 eye images followed by a classification process that classified the image set into three classes; normal, early, and advanced stage. A comparison between the two used classifiers, the support vector machine SVM and the artificial neural network ANN were done for the same dataset of 120 eye images. It was concluded that SVM gave better results than ANN. SVM success rate result was 96.8% accuracy where ANN success rate result was 92.3% accuracy.

Keywords: Cataract, classification, detection, feature extraction, grading, log-gabor, neural networks, support vector machines, wavelet.

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Authors: Sašo Pečnik, Borut Žalik

Abstract:

Cloud Computing is an approach that provides computation and storage services on-demand to clients over the network, independent of device and location. In the last few years, cloud computing became a trend in information technology with many companies that transfer their business processes and applications in the cloud. Cloud computing with service oriented architecture has contributed to rapid development of Geographic Information Systems. Open Geospatial Consortium with its standards provides the interfaces for hosted spatial data and GIS functionality to integrated GIS applications. Furthermore, with the enormous processing power, clouds provide efficient environment for data intensive applications that can be performed efficiently, with higher precision, and greater reliability. This paper presents our work on the geospatial data services within the cloud computing environment and its technology. A cloud computing environment with the strengths and weaknesses of the geographic information system will be introduced. The OGC standards that solve our application interoperability are highlighted. Finally, we outline our system architecture with utilities for requesting and invoking our developed data intensive applications as a web service.

Keywords: Cloud Computing, Geographic Information System, Open Geospatial Consortium, Interoperability, Spatial data, Web- Services.

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Authors: A. S. Jambhale, B. V. Barbadekar

Abstract:

Microwave energy can be used for drying purpose. It is unique process. It is distinctly different from conventional drying process. It is advantageous over conventional drying / heating processes. When microwave energy is used for drying purpose, the process can be accelerated with a better control to achieve uniform heating, more conversion efficiency, selective drying and ultimately improved product quality of the output. Also, less floor space and compact system are the added advantages. Existing low power microwave drying system is to be modified with suitable applicator. Appropriate sensors are to be used to measure parameters like moisture, temperature, weight of sample. Suitable high tech controller is to be used to control microwave power continuously from minimum to maximum. Phase - controller, cycle - controller and PWM - controller are some of the advanced power control techniques. It has been proposed to work on turmeric using high-tech phase controller to control the microwave power conveniently. The drying of turmeric with microwave energy employing phase controller gives better results as formulated in this paper and hence new approach of processing turmeric will open future doors of profit making to allied industries and the farmers.

Keywords: Applicator, microwave drying, phase controller.

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Authors: Karim Hamidi Machekposhti, Hossein Sedghi

Abstract:

This study was designed to find the best stochastic model (using of time series analysis) for annual extreme streamflow (peak and maximum streamflow) of Karkheh River at Iran. The Auto-regressive Integrated Moving Average (ARIMA) model used to simulate these series and forecast those in future. For the analysis, annual extreme streamflow data of Jelogir Majin station (above of Karkheh dam reservoir) for the years 1958–2005 were used. A visual inspection of the time plot gives a little increasing trend; therefore, series is not stationary. The stationarity observed in Auto-Correlation Function (ACF) and Partial Auto-Correlation Function (PACF) plots of annual extreme streamflow was removed using first order differencing (d=1) in order to the development of the ARIMA model. Interestingly, the ARIMA(4,1,1) model developed was found to be most suitable for simulating annual extreme streamflow for Karkheh River. The model was found to be appropriate to forecast ten years of annual extreme streamflow and assist decision makers to establish priorities for water demand. The Statistical Analysis System (SAS) and Statistical Package for the Social Sciences (SPSS) codes were used to determinate of the best model for this series.

Keywords: Stochastic models, ARIMA, extreme streamflow, Karkheh River.

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Authors: D. Lepe-Cervantes, E. Leon-Becerril, J. Gomez-Romero, O. Garcia-Depraect, A. Lopez-Lopez

Abstract:

In this study, raw coffee wastewater (CWW) was used as a complex substrate for anaerobic digestion. The inoculum adaptation stage, microbial diversity analysis and biomethane potential (BMP) tests were performed. A fast inoculum adaptation stage was used by the replacement of vinasse to CWW in an anaerobic sequential batch reactor (AnSBR) operated at mesophilic conditions. Illumina MiSeq sequencing was used to analyze the microbial diversity. While, BMP tests using inoculum adapted to CWW were carried out at different inoculum to substrate (I/S) ratios (2:1, 3:1 and 4:1, on a VS basis). Results show that the adaptability percentage was increased gradually until it reaches the highest theoretical value in a short time of 10 d; with a methane yield of 359.10 NmL CH₄/g COD-removed; Methanobacterium beijingense was the most abundant microbial (75%) and the greatest specific methane production was achieved at I/S ratio 4:1, whereas the lowest was obtained at 2:1, with BMP values of 320 NmL CH₄/g VS and 151 NmL CH₄/g VS, respectively. In conclusion, gradual replacement of substrate was a feasible method to adapt the inoculum in a short time even using complex raw substrates, whereas in the BMP tests, the specific methane production was proportional to the initial amount of inoculum.

Keywords: Fast inoculum adaptation, coffee wastewater, biomethane potential test, anaerobic digestion.

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