Search results for: Ascending Sort Index Vector

Authors: Vladyslav Povoroznyuk, Anna Musiienko, Nataliia Zaverukha, Roksolana Povoroznyuk

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Along with the global aging of population, the number of people with somatic diseases is increasing, including such interrelated pathologies as obesity, osteoarthritis (OA) and osteoporosis (OP). The objective of the study is to examine the connection between body mass index (BMI), OA and bone mineral density (BMD) of lumbar spine, femoral neck and trabecular bone score (TBS) in postmenopausal women with OA. We have observed 359 postmenopausal women (50-89 years old) and divided them into four groups by age: 50-59 yrs, 60-69 yrs, 70-79 yrs and over 80 years old. In addition, according to the American College of Rheumatology (ACR) Clinical classification criteria for knee and hip OA, we divided them into 2 groups: group I – 117 females with symptomatic OA (including 89 patients with knee OA, 28 patients with hip OA) and group II –242 women with a normal functional activity of large joints. Analysis of data was performed taking into account their BMI, classified by World Health Organization (WHO). Diagnosis of obesity was established when BMI was above 30 kg/m². In woman with obesity, a symptomatic OA was detected in 44 postmenopausal women (41.1%), a normal functional activity of large joints - in 63 women (58.9%). However, in women with normal BMI – 73 women, who account for 29.0% of cases, a symptomatic OA was detected. According to a chi-squared (χ2) test, a significantly higher level of BMI was detected in postmenopausal women with OA (χ2 = 5.05, p = 0.02). Women with a symptomatic OA had a significantly higher BMD of lumbar spine compared with women who had a normal functional activity of large joints. No significant differences of BMD of femoral necks or TBS were detected in either the group with OA or with a normal functional activity of large joints.

Keywords: Bone mineral density, BMD, body mass index, BMI, obesity, overweight, postmenopausal women, osteoarthritis.

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Authors: M. Azadbakht, E. Ghajarjazi, E. Amiri, F. Abdigaol

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In this research the effect of moisture at three levels (47, 57, and 67 w.b.%) on the physical properties of the Pofaki pea variety including, dimensions, geometric mean diameter, volume, sphericity index and the surface area was determined. The influence of different moisture levels (47, 57 and 67 w.b.%), in two loading orientation (longitudinal and transverse) and three loading speed (4,6 and 8 mm min-1) on the mechanical properties of pea such as maximum deformation, rupture force, rupture energy, toughness and the power to break the pea was investigated. It was observed in the physical properties that moisture changes were affective at 1% on, dimensions, geometric mean diameter, volume, sphericity index and the surface area. It was observed in the mechanical properties that moisture changes were effective at 1% on, maximum deformation, rupture force, rupture energy, toughness and the power to break. Loading speed was effective on maximum deformation, rupture force, rupture energy at 1% and it was effective on toughness at 5%. Loading orientation was effective on maximum deformation, rupture force, rupture energy, toughness at 1% and it was effective on power at 5%. The mutual effect of speed and orientation were effective on rupture energy at 1% and were effective on toughness at 5% probability. The mutual effect of moisture and speed were effective on rupture force and rupture energy at 1% and were effective on toughness 5% probability. The mutual effect of orientation and moisture on rupture energy and toughness were effective at 1%.

Keywords: Mechanical properties, Pea, Physical properties.

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Authors: Nilubon Kurubanjerdjit, Nattakarn Iam-On, Ka-Lok Ng

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MicroRNAs are small non-coding RNA found in many different species. They play crucial roles in cancer such as biological processes of apoptosis and proliferation. The identification of microRNA-target genes can be an essential first step towards to reveal the role of microRNA in various cancer types. In this paper, we predict miRNA-target genes for lung cancer by integrating prediction scores from miRanda and PITA algorithms used as a feature vector of miRNA-target interaction. Then, machine-learning algorithms were implemented for making a final prediction. The approach developed in this study should be of value for future studies into understanding the role of miRNAs in molecular mechanisms enabling lung cancer formation.

Keywords: MicroRNA, miRNAs, lung cancer, machine learning, Naïve Bayes, SVM.

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Authors: J. B. V. Subrahmanyam, C. Radhakrishna

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This paper presents a simple three phase power flow method for solution of three-phase unbalanced radial distribution system (RDN) with voltage dependent loads. It solves a simple algebraic recursive expression of voltage magnitude, and all the data are stored in vector form. The algorithm uses basic principles of circuit theory and can be easily understood. Mutual coupling between the phases has been included in the mathematical model. The proposed algorithm has been tested with several unbalanced radial distribution networks and the results are presented in the article. 8- bus and IEEE 13 bus unbalanced radial distribution system results are in agreements with the literature and show that the proposed model is valid and reliable.

Keywords: radial distribution networks, load flow, circuitmodel, three-phase four-wire, unbalance.

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Authors: Muhammad Umair Shahid, Abdul Rehman, Mudassir Mukhtar, Muhammad Nauman

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The smart antenna is the prominent technology that has become known in recent years to meet the growing demands of wireless communications. In an overcrowded atmosphere, its application is growing gradually. A methodical evaluation of the performance of Fixed Beamforming algorithms for smart antennas such as Multiple Sidelobe Canceller (MSC), Maximum Signal-to-interference ratio (MSIR) and minimum variance (MVDR) has been comprehensively presented in this paper. Simulation results show that beamforming is helpful in providing optimized response towards desired directions. MVDR beamformer provides the most optimal solution.

Keywords: Fixed weight beamforming, array pattern, signal to interference ratio, power efficiency, element spacing, array elements, optimum weight vector.

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Authors: A. Parizad, A. Khazali, M. Kalantar

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Voltage collapse is instability of heavily loaded electric power systems that cause to declining voltages and blackout. Power systems are predicated to become more heavily loaded in the future decade as the demand for electric power rises while economic and environmental concerns limit the construction of new transmission and generation capacity. Heavily loaded power systems are closer to their stability limits and voltage collapse blackouts will occur if suitable monitoring and control measures are not taken. To control transmission lines, it can be used from FACTS devices. In this paper Harmony search algorithm (HSA) and Genetic Algorithm (GA) have applied to determine optimal location of FACTS devices in a power system to improve power system stability. Three types of FACTS devices (TCPAT, UPFS, and SVC) have been introduced. Bus under voltage has been solved by controlling reactive power of shunt compensator. Also a combined series-shunt compensators has been also used to control transmission power flow and bus voltage simultaneously. Different scenarios have been considered. First TCPAT, UPFS, and SVC are placed solely in transmission lines and indices have been calculated. Then two types of above controller try to improve parameters randomly. The last scenario tries to make better voltage stability index and losses by implementation of three types controller simultaneously. These scenarios are executed on typical 34-bus test system and yields efficiency in improvement of voltage profile and reduction of power losses; it also may permit an increase in power transfer capacity, maximum loading, and voltage stability margin.

Keywords: FACTS Devices, Voltage Stability Index, optimal location, Heuristic methods, Harmony search, Genetic Algorithm.

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Authors: Hanan Mahmoud Ezzat Mahmoud, Alaa Abd El Fatah Hefnawy

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In this paper, we present a system for content-based retrieval of large database of classified satellite images, based on user's relevance feedback (RF).Through our proposed system, we divide each satellite image scene into small subimages, which stored in the database. The modified radial basis functions neural network has important role in clustering the subimages of database according to the Euclidean distance between the query feature vector and the other subimages feature vectors. The advantage of using RF technique in such queries is demonstrated by analyzing the database retrieval results.

Keywords: content-based image retrieval, large database of image, RBF neural net, relevance feedback

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Authors: Qiong Wang

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One of the most important problems to solve is eye location for a driver fatigue monitoring system. This paper presents an efficient method to achieve fast and accurate eye location in grey level images obtained in the real-word driving conditions. The structure of eye region is used as a robust cue to find possible eye pairs. Candidates of eye pair at different scales are selected by finding regions which roughly match with the binary eye pair template. To obtain real one, all the eye pair candidates are then verified by using support vector machines. Finally, eyes are precisely located by using binary vertical projection and eye classifier in eye pair images. The proposed method is robust to deal with illumination changes, moderate rotations, glasses wearing and different eye states. Experimental results demonstrate its effectiveness.

Keywords: eye location, structure feature, driver fatiguemonitoring

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Authors: Kamrul Hasan Talukder, Koichi Harada

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The scientific community has invested a great deal of effort in the fields of discrete wavelet transform in the last few decades. Discrete wavelet transform (DWT) associated with the vector quantization has been proved to be a very useful tool for the compression of image. However, the DWT is very computationally intensive process requiring innovative and computationally efficient method to obtain the image compression. The concurrent transformation of the image can be an important solution to this problem. This paper proposes a model of concurrent DWT for image compression. Additionally, the formal verification of the model has also been performed. Here the Symbolic Model Verifier (SMV) has been used as the formal verification tool. The system has been modeled in SMV and some properties have been verified formally.

Keywords: Computation Tree Logic, Discrete WaveletTransform, Formal Verification, Image Compression, Symbolic Model Verifier.

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Authors: Buntara Sthenly Gan

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A novel and versatile numerical technique to solve a self-stress equilibrium state is adopted herein as a form-finding procedure for an irregular tensegrity structure. The numerical form-finding scheme of a tensegrity structure uses only the connectivity matrix and prototype tension coefficient vector as the initial guess solution. Any information on the symmetrical geometry or other predefined initial structural conditions is not necessary to get the solution in the form-finding process. An eight-node initial condition example is presented to demonstrate the efficiency and robustness of the proposed method in the form-finding of an irregular tensegrity structure. Based on the conception from the form-finding of an eight-node irregular tensegrity structure, a monumental object is designed by considering the real world situation such as self-weight, wind and earthquake loadings.

Keywords: Tensegrity, Form-finding, Design, Irregular, Self-stress, Force density method.

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Authors: Yuan-Jye Tseng, Ching-Yen Chen

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In the design cycle, a main design task is to determine the external shape of the product. The external shape of a product is one of the key factors that can affect the customers’ preferences linking to the motivation to buy the product, especially in the case of a consumer electronic product such as a mobile phone. The relationship between the external shape and the customer preferences needs to be studied to enhance the customer’s purchase desire and action. In this research, a design for customer preferences model is developed for investigating the relationships between the external shape and the customer preferences of a product. In the first stage, the names of the geometric features are collected and evaluated from the data of the specified internet web pages using the developed text miner. The key geometric features can be determined if the number of occurrence on the web pages is relatively high. For each key geometric feature, the numerical values are explored using the text miner to collect the internet data from the web pages. In the second stage, a cluster analysis model is developed to evaluate the numerical values of the key geometric features to divide the external shapes into several groups. Several design suggestion cases can be proposed, for example, large model, mid-size model, and mini model, for designing a mobile phone. A customer preference index is developed by evaluating the numerical data of each of the key geometric features of the design suggestion cases. The design suggestion case with the top ranking of the customer preference index can be selected as the final design of the product. In this paper, an example product of a notebook computer is illustrated. It shows that the external shape of a product can be used to drive customer preferences. The presented design for customer preferences model is useful for determining a suitable external shape of the product to increase customer preferences.

Keywords: Cluster analysis, customer preferences, design evaluation, design for customer preferences, product design.

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Authors: M. De la Sen, O. Barambones

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This paper presents an indirect adaptive stabilization scheme for first-order continuous-time systems under saturated input which is described by a sigmoidal function. The singularities are avoided through a modification scheme for the estimated plant parameter vector so that its associated Sylvester matrix is guaranteed to be non-singular and then the estimated plant model is controllable. The modification mechanism involves the use of a hysteresis switching function. An alternative hybrid scheme, whose estimated parameters are updated at sampling instants is also given to solve a similar adaptive stabilization problem. Such a scheme also uses hysteresis switching for modification of the parameter estimates so as to ensure the controllability of the estimated plant model.

Keywords: Hybrid dynamic systems, discrete systems, saturated input, control, stabilization.

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Authors: V. Geetha, K. S. Aprameya

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Early diagnosis of dental caries is essential for maintaining dental health. In this paper, method for diagnosis of dental caries is proposed using Laplacian filter, adaptive thresholding, texture analysis and Support Vector Machine (SVM) classifier. Analysis of the proposed method is compared with Otsu thresholding, watershed segmentation and active contouring method. Adaptive thresholding has comparatively better performance with 96.9% accuracy and 96.1% precision. The results are validated using statistical method, two-way ANOVA, at significant level of 5%, that shows the interaction of proposed method on performance parameter measures are significant. Hence the proposed technique could be used for detection of dental caries in automated computer assisted diagnosis system.

Keywords: Computer assisted diagnosis, dental caries, dental radiography, image segmentation.

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Authors: Faisal Aburub, Wael Hadi

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Data mining is the process of extracting useful or hidden information from a large database. Extracted information can be used to discover relationships among features, where data objects are grouped according to logical relationships; or to predict unseen objects to one of the predefined groups. In this paper, we aim to investigate four well-known data mining algorithms in order to predict groundwater areas in Jordan. These algorithms are Support Vector Machines (SVMs), Naïve Bayes (NB), K-Nearest Neighbor (kNN) and Classification Based on Association Rule (CBA). The experimental results indicate that the SVMs algorithm outperformed other algorithms in terms of classification accuracy, precision and F1 evaluation measures using the datasets of groundwater areas that were collected from Jordanian Ministry of Water and Irrigation.

Keywords: Classification, data mining, evaluation measures, groundwater.

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Authors: Dabyltayeva R. Y., Smatova K.B., Кabekenov G., Toleshova U., Shagyrbayeva M.

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In recent years in Kazakhstan, as well as in all countries, we have been talking not only about the professional stress, but also professional Burnout Syndrome of employees. Burnout is essentially a response to chronic emotional stress – manifests itself in the form of chronic fatigue, despondency, unmotivated aggression, anger, and others. This condition is due to mental fatigue among teachers as a sort of payment for overstrain when professional commitments include the impact of “heat your soul", emotional investment. The emergence of professional Burnout among teachers is due to the system of interrelated and mutually reinforcing factors relating to the various levels of the personality: individually-psychological level is psychodynamic special subject characteristics of valuemotivational sphere and formation of skills and habits of selfregulation; the socio-psychological level includes especially the Organization and interpersonal interaction of a teacher. Signs of the Burnout were observed in 15 testees, and virtually a symptom could be observed in every teacher. As a result of the diagnosis 48% of teachers had the signs of stress (phase syndrome), resulting in a sense of anxiety, mood, heightened emotional susceptibility. The following results have also been got:-the fall of General energy potential – 14 pers. -Psychosomatic and psycho vegetative syndrome – 26 pers. -emotional deficit-34 pers. -emotional Burnout Syndrome-6 pers. The problem of professional Burnout of teachers in the current conditions should become not only meaningful, but particularly relevant. The quality of education of the younger generation depends on professional development; teachers- training level, and how “healthy" teachers are. That is why the systematic maintenance of pedagogic-professional development for teachers (including disclosure of professional Burnout Syndrome factors) takes on a special meaning.

Keywords: Professional burnout syndrome, adaptive syndrome, stage of depletion syndrome, symptoms and characteristics of burnout, prophylactic of professional destruction techniques.

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Authors: Tawiwat V., Phermsak S., Noppasit C.

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This paper deals with under actuator dynamic systems such as spring-mass-damper system when the number of control variable is less than the number of state variable. In order to apply optimal control, the controllability must be checked. There are many objective functions to be selected as the goal of the optimal control such as minimum energy, maximum energy and minimum jerk. As the objective function is the first priority, if one like to have the second goal to be applied; however, it could not fit in the objective function format and also avoiding the vector cost for the objective, this paper will illustrate the problem of under actuator dynamic systems with the easiest to deal with comparing between minimum energy and minimum jerk.

Keywords: Under actuator, Dynamic optimal control, Minimumjerk, Minimum energy.

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Authors: J. Umamaheswari, G. Radhamani

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This paper describes about the process of recognition and classification of brain images such as normal and abnormal based on PSO-SVM. Image Classification is becoming more important for medical diagnosis process. In medical area especially for diagnosis the abnormality of the patient is classified, which plays a great role for the doctors to diagnosis the patient according to the severeness of the diseases. In case of DICOM images it is very tough for optimal recognition and early detection of diseases. Our work focuses on recognition and classification of DICOM image based on collective approach of digital image processing. For optimal recognition and classification Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Support Vector Machine (SVM) are used. The collective approach by using PSO-SVM gives high approximation capability and much faster convergence.

Keywords: Recognition, classification, Relaxed Median Filter, Adaptive thresholding, clustering and Neural Networks

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Authors: Suresh S. Salankar, Balasaheb M. Patre

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Research into the problem of classification of sonar signals has been taken up as a challenging task for the neural networks. This paper investigates the design of an optimal classifier using a Multi layer Perceptron Neural Network (MLP NN) and Support Vector Machines (SVM). Results obtained using sonar data sets suggest that SVM classifier perform well in comparison with well-known MLP NN classifier. An average classification accuracy of 91.974% is achieved with SVM classifier and 90.3609% with MLP NN classifier, on the test instances. The area under the Receiver Operating Characteristics (ROC) curve for the proposed SVM classifier on test data set is found as 0.981183, which is very close to unity and this clearly confirms the excellent quality of the proposed classifier. The SVM classifier employed in this paper is implemented using kernel Adatron algorithm is seen to be robust and relatively insensitive to the parameter initialization in comparison to MLP NN.

Keywords: Classification, MLP NN, backpropagation algorithm, SVM, Receiver Operating Characteristics.

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Authors: Moustafa A. Bani-Hasan, Yasser M. Kadah, Fatma M. El-Hefnawi

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An electrocardiogram (ECG) feature extraction system based on the calculation of the complex resonance frequency employing Prony-s method is developed. Prony-s method is applied on five different classes of ECG signals- arrhythmia as a finite sum of exponentials depending on the signal-s poles and the resonant complex frequencies. Those poles and resonance frequencies of the ECG signals- arrhythmia are evaluated for a large number of each arrhythmia. The ECG signals of lead II (ML II) were taken from MIT-BIH database for five different types. These are the ventricular couplet (VC), ventricular tachycardia (VT), ventricular bigeminy (VB), and ventricular fibrillation (VF) and the normal (NR). This novel method can be extended to any number of arrhythmias. Different classification techniques were tried using neural networks (NN), K nearest neighbor (KNN), linear discriminant analysis (LDA) and multi-class support vector machine (MC-SVM).

Keywords: Arrhythmias analysis, electrocardiogram, featureextraction, statistical classifiers.

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Authors: P. Nammalvar, P. Meganathan, A. Balamuguran

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Among various active filters, shunt active filter is a viable solution for reactive power and harmonics compensation. In this paper, the SRF plan is used to generate current reference for compensation and conventional PI controllers were used as the controller to compensate the reactive power. The design of the closed loop controllers is reserved simple by modeling them as first order systems. Computationally uncomplicated and efficient SVM system is used in the present work for better utilization of dc bus voltage. The rating of shunt active filter has been finalized based on the reactive power demand of the selected reactive load. The proposed control and SVM technique are validated by simulating in MATLAB software.

Keywords: Shunt Active Filter, Space vector pulse width modulation, Voltage Source Converter, Reactive Power, Synchronous Reference Frame, Point of common coupling.

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Authors: N. Valderrama, W. Albarracín, N. Algecira

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The effect of the inclusion of thyme and rosemary essential oils into chitosan films, as well as the microbiological and physical properties when storing chitosan film with and without the mentioned inclusion was studied. The film forming solution was prepared by dissolving chitosan (2%, w/v), polysorbate 80 (4% w/w CH) and glycerol (16% w/w CH) in aqueous lactic acid solutions (control). The thyme (TEO) and rosemary (REO) essential oils (EOs) were included 1:1 w/w (EOs:CH) on their combination 50/50 (TEO:REO). The films were stored at temperatures of 5, 20, 33°C and a relative humidity of 75% during four weeks. The films with essential oil inclusion did not show an antimicrobial activity against strains. This behavior could be explained because the chitosan only inhibits the growth of microorganisms in direct contact with the active sites. However, the inhibition capacity of TEO was higher than the REO and a synergic effect between TEO:REO was found for S. enteritidis strains in the chitosan solution. Some physical properties were modified by the inclusion of essential oils. The addition of essential oils does not affect the mechanical properties (tensile strength, elongation at break, puncture deformation), the water solubility, the swelling index nor the DSC behavior. However, the essential oil inclusion can significantly decrease the thickness, the moisture content, and the L* value of films whereas the b* value increased due to molecular interactions between the polymeric matrix, the loosing of the structure, and the chemical modifications. On the other hand, the temperature and time of storage changed some physical properties on the chitosan films. This could have occurred because of chemical changes, such as swelling in the presence of high humidity air and the reacetylation of amino groups. In the majority of cases, properties such as moisture content, tensile strength, elongation at break, puncture deformation, a*, b*, chrome, 7E increased whereas water resistance, swelling index, L*, and hue angle decreased.

Keywords: Chitosan, food additives, modified films, polymers.

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Authors: M. Behbahani-Nejad, Y. Shekari

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A reduced order modeling approach for natural gas transient flow in pipelines is presented. The Euler equations are considered as the governing equations and solved numerically using the implicit Steger-Warming flux vector splitting method. Next, the linearized form of the equations is derived and the corresponding eigensystem is obtained. Then, a few dominant flow eigenmodes are used to construct an efficient reduced-order model. A well-known test case is presented to demonstrate the accuracy and the computational efficiency of the proposed method. The results obtained are in good agreement with those of the direct numerical method and field data. Moreover, it is shown that the present reduced-order model is more efficient than the conventional numerical techniques for transient flow analysis of natural gas in pipelines.

Keywords: Eigenmode, Natural Gas, Reduced Order Modeling, Transient Flow.

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Authors: L. Parisi

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Kinematic data wisely correlate vector quantities in space to scalar parameters in time to assess the degree of symmetry between the intact limb and the amputated limb with respect to a normal model derived from the gait of control group participants. Furthermore, these particular data allow a doctor to preliminarily evaluate the usefulness of a certain rehabilitation therapy. Kinetic curves allow the analysis of ground reaction forces (GRFs) to assess the appropriateness of human motion. Electromyography (EMG) allows the analysis of the fundamental lower limb force contributions to quantify the level of gait asymmetry. However, the use of this technological tool is expensive and requires patient’s hospitalization. This research work suggests overcoming the above limitations by applying artificial neural networks.

Keywords: Kinetics, kinematics, cyclograms, neural networks.

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Authors: Isaac Kofi Mensah

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Governments around the world are adopting Information and Communication Technologies (ICTs) because of the important opportunities it provides through E-government (EG) to modernize government public administration processes and delivery of quality and efficient public services. Almost every country in the world is adopting ICT in its public sector administration (EG) to modernize and change the traditional process of government, increase citizen engagement and participation in governance, as well as the provision of timely information to citizens. This paper, therefore, seeks to present the adoption, development and implementation of EG in regions globally, as well as the ICT indicators around the world, which are making EG initiatives successful. Europe leads the world in its EG adoption and development index, followed by the Americas, Asia, Oceania and Africa. There is a gradual growth in ICT indicators in terms of the increase in Internet access and usage, increase in broadband penetration, an increase of individuals using the Internet at home and a decline in fixed telephone use, while the mobile cellular phone has been on the increase year-on-year. Though the lack of ICT infrastructure is a major challenge to EG adoption and implementation around the world, in Africa it is very pervasive, hampering the expansion of Internet access and provision of broadband, and hence is a barrier to the successful adoption, development, and implementation of EG initiatives in countries on the continent. But with the general improvement and increase in ICT indicators around the world, it provides countries in Europe, Americas, Asia, Arab States, Oceania and Africa with the huge opportunity to enhance public service delivery through the adoption of EG. Countries within these regions cannot fail their citizens who desire to enjoy an enhanced and efficient public service delivery from government and its many state institutions.

Keywords: E-government development index, e-government, indicators, information and communication technologies.

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Authors: Elif Alaybeyoğlu, Y. Esra Albayrak

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Marketing establishes a communication network between producers and consumers. Nowadays, marketing approach is customer-focused and products are directly oriented to meet customer needs. Marketing, which is a long process, needs organization and management. Therefore strategic marketing planning becomes more and more important in today’s competitive conditions. Main focus of this paper is to evaluate pricing strategies and select the best pricing strategy solution while considering internal and external factors influencing the company’s pricing decisions associated with new product development. To reflect the decision maker’s subjective preference information and to determine the weight vector of factors (attributes), the fuzzy linear programming technique for multidimensional analysis of preference (LINMAP) under intuitionistic fuzzy (IF) environments is used.

Keywords: IF Sets, LINMAP, MAGDM, Marketing.

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Authors: Raimund Leitner, Susanne Rosskopf

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Near-infrared (NIR) spectroscopy is a widely used method for material identification for laboratory and industrial applications. While standard spectrometers only allow measurements at one sampling point at a time, NIR Spectral Imaging techniques can measure, in real-time, both the size and shape of an object as well as identify the material the object is made of. The online classification and sorting of recovered paper with NIR Spectral Imaging (SI) is used with success in the paper recycling industry throughout Europe. Recently, the globalisation of the recycling material streams caused that water-based flexographic-printed newspapers mainly from UK and Italy appear also in central Europe. These flexo-printed newspapers are not sufficiently de-inkable with the standard de-inking process originally developed for offset-printed paper. This de-inking process removes the ink from recovered paper and is the fundamental processing step to produce high-quality paper from recovered paper. Thus, the flexo-printed newspapers are a growing problem for the recycling industry as they reduce the quality of the produced paper if their amount exceeds a certain limit within the recovered paper material. This paper presents the results of a research project for the development of an automated entry inspection system for recovered paper that was jointly conducted by CTR AG (Austria) and PTS Papiertechnische Stiftung (Germany). Within the project an NIR SI prototype for the identification of flexo-printed newspaper has been developed. The prototype can identify and sort out flexoprinted newspapers in real-time and achieves a detection accuracy for flexo-printed newspaper of over 95%. NIR SI, the technology the prototype is based on, allows the development of inspection systems for incoming goods in a paper production facility as well as industrial sorting systems for recovered paper in the recycling industry in the near future.

Keywords: spectral imaging, imaging spectroscopy, NIR, waterbasedflexographic, flexo-printed, recovered paper, real-time classification.

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Authors: Do Phuc, Nguyen Thi Kim Phung

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In this paper, we represent protein structure by using graph. A protein structure database will become a graph database. Each graph is represented by a spectral vector. We use Jacobi rotation algorithm to calculate the eigenvalues of the normalized Laplacian representation of adjacency matrix of graph. To measure the similarity between two graphs, we calculate the Euclidean distance between two graph spectral vectors. To cluster the graphs, we use M-tree with the Euclidean distance to cluster spectral vectors. Besides, M-tree can be used for graph searching in graph database. Our proposal method was tested with graph database of 100 graphs representing 100 protein structures downloaded from Protein Data Bank (PDB) and we compare the result with the SCOP hierarchical structure.

Keywords: Eigenvalues, m-tree, graph database, protein structure, spectra graph theory.

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Authors: Ashutosh Kumar Singh, Anand Mohan

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This paper deals with efficient computation of probability coefficients which offers computational simplicity as compared to spectral coefficients. It eliminates the need of inner product evaluations in determination of signature of a combinational circuit realizing given Boolean function. The method for computation of probability coefficients using transform matrix, fast transform method and using BDD is given. Theoretical relations for achievable computational advantage in terms of required additions in computing all 2n probability coefficients of n variable function have been developed. It is shown that for n ≥ 5, only 50% additions are needed to compute all probability coefficients as compared to spectral coefficients. The fault detection techniques based on spectral signature can be used with probability signature also to offer computational advantage.

Keywords: Binary Decision Diagrams, Spectral Coefficients, Fault detection

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Authors: Hajji Lobna, Chattaoui Mayssa, Regaieg Hajer, M'Hamdi-Boughalleb Naima, Rhouma Ali, Horrigue-Raouani Najet

Abstract:

In this study, three local isolates of Trichoderma (Tr1: T. viride, Tr2: T. harzianum and Tr3: T. asperellum) were isolated and evaluated for their biocontrol effectiveness under in vitro conditions and in greenhouse. In vitro bioassay revealed a biopotential control against Fusarium oxysporum f. sp. radicis lycopersici and Meloidogyne javanica (RKN) separately. All species of Trichoderma exhibited biocontrol performance and (Tr1) Trichoderma viride was the most efficient. In fact, growth rate inhibition of Fusarium oxysporum f. sp. radicis lycopersici (FORL) was reached 75.5% with Tr1. Parasitism rate of root-knot nematode was 60% for juveniles and 75% for eggs with the same one. Pots experiment results showed that Tr1 and Tr2, compared to chemical treatment, enhanced the plant growth and exhibited better antagonism against root-knot nematode and root-rot fungi separated or combined. All Trichoderma isolates revealed a bioprotection potential against Fusarium oxysporum f. sp. radicis lycopersici. When pathogen fungi inoculated alone, Fusarium wilt index and browning vascular rate were reduced significantly with Tr1 (0.91, 2.38%) and Tr2 (1.5, 5.5%), respectively. In the case of combined infection with Fusarium and nematode, the same isolate of Trichoderma Tr1 and Tr2 decreased Fusarium wilt index at 1.1 and 0.83 and reduced the browning vascular rate at 6.5% and 6%, respectively. Similarly, the isolate Tr1 and Tr2 caused maximum inhibition of nematode multiplication. Multiplication rate was declined at 4% with both isolates either tomato infected by nematode separately or concomitantly with Fusarium. The chemical treatment was moderate in activity against Meloidogyne javanica and Fusarium oxysporum f. sp. radicis lycopersici alone and combined.

Keywords: Trichoderma spp., Meloidogyne javanica, Fusarium oxysporum f.sp. radicis lycopersici, biocontrol.

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Authors: Hazem M. El-Bakry, Qiangfu Zhao

Abstract:

Here, a new idea to speed up the operation of complex valued time delay neural networks is presented. The whole data are collected together in a long vector and then tested as a one input pattern. The proposed fast complex valued time delay neural networks uses cross correlation in the frequency domain between the tested data and the input weights of neural networks. It is proved mathematically that the number of computation steps required for the presented fast complex valued time delay neural networks is less than that needed by classical time delay neural networks. Simulation results using MATLAB confirm the theoretical computations.

Keywords: Fast Complex Valued Time Delay Neural Networks, Cross Correlation, Frequency Domain

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