Search results for: knowledge based systems

Authors: Mohammad Ebrahim Kianifar, Ehsan Ahmadi

Abstract:

Reinforced concrete structures experience local defects such as cracks over their lifetime under various environmental loadings. Consequently, they are repaired by mortars to avoid detrimental effects such as corrosion of reinforcement, which in long-term may lead to strength loss of a member or collapse of structures. However, repaired structures may need multiple repairs due to changes in load distribution, and thus, lack of compatibility between mortar and substrate concrete. On the other hand, waste tire rubber alkali-activated (WTRAA)-based materials have very high potential to be used as repair mortars because of their ductility and flexibility, which may delay failure of repair mortar, and thus, provide sufficient compatibility. Hence, this work presents a study on suitability of WTRAA-based materials as mortars for repair of concrete structures through an experimental program. To this end, WTRAA mortars with 15% aggregate replacement, alkali-activated (AA) mortars, and ordinary mortars are made to repair a number of concrete beams. The WTRAA mortars are composed of slag as base material, sodium hydroxide as alkaline activator, and different gradation of waste tire rubber (fine and coarse gradations). Flexural tests are conducted on the concrete beams repaired by the ordinary, AA, and WTRAA mortars. It is found that, despite having lower compressive strength and modulus of elasticity, the WTRAA and AA mortars increase flexural strength of the repaired beams, give compatible failures, and provide sufficient mortar-concrete interface bondings. The ordinary mortars, however, show incompatible failure modes. This study demonstrates promising application of WTRAA mortars in practical repairs of concrete structures.

Keywords: Alkali-activated mortars, concrete repair, mortar compatibility flexural strength, waste tire rubber.

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Authors: Romain Ben Taleb, Aurélie Montarnal, Matthieu Lauras, Mathieu Dahan, Romain Miclo

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To be competitive and sustainable, any company has to maximize its value. However, unlike listed companies that can assess their values based on market shares, most Small and Medium Enterprises (SMEs) which are non-listed cannot have direct and live access to this critical information. Traditional accounting reports only give limited insights to SME decision-makers about the real impact of their day-to-day decisions on the company’s performance and value. Most of the time, an SME’s financial valuation is made one time a year as the associated process is time and resource-consuming, requiring several months and external expertise to be completed. To solve this issue, we propose in this paper a value-oriented metamodel that enables real-time and dynamic assessment of the SME’s value based on the large definition of their assets. These assets cover a wider scope of resources of the company and better account for immaterial assets. The proposal, which is illustrated in a case study, discusses the benefits of incorporating assets in the SME valuation.

Keywords: SME, metamodel, decision support system, financial valuation.

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Authors: V. Churkin, M. Lopatin

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The purpose of the paper is to estimate the US small wind turbines market potential and forecast the small wind turbines sales in the US. The forecasting method is based on the application of the Bass model and the generalized Bass model of innovations diffusion under replacement purchases. In the work an exponential distribution is used for modeling of replacement purchases. Only one parameter of such distribution is determined by average lifetime of small wind turbines. The identification of the model parameters is based on nonlinear regression analysis on the basis of the annual sales statistics which has been published by the American Wind Energy Association (AWEA) since 2001 up to 2012. The estimation of the US average market potential of small wind turbines (for adoption purchases) without account of price changes is 57080 (confidence interval from 49294 to 64866 at P = 0.95) under average lifetime of wind turbines 15 years, and 62402 (confidence interval from 54154 to 70648 at P = 0.95) under average lifetime of wind turbines 20 years. In the first case the explained variance is 90,7%, while in the second - 91,8%. The effect of the wind turbines price changes on their sales was estimated using generalized Bass model. This required a price forecast. To do this, the polynomial regression function, which is based on the Berkeley Lab statistics, was used. The estimation of the US average market potential of small wind turbines (for adoption purchases) in that case is 42542 (confidence interval from 32863 to 52221 at P = 0.95) under average lifetime of wind turbines 15 years, and 47426 (confidence interval from 36092 to 58760 at P = 0.95) under average lifetime of wind turbines 20 years. In the first case the explained variance is 95,3%, while in the second – 95,3%.

Keywords: Bass model, generalized Bass model, replacement purchases, sales forecasting of innovations, statistics of sales of small wind turbines in the United States.

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Authors: Milad Eghtedari Naeini, Gholamreza Heravi

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In this paper, based on the past project cost and time performance, a model for forecasting project cost performance is developed. This study presents a probabilistic project control concept to assure an acceptable forecast of project cost performance. In this concept project activities are classified into sub-groups entitled control accounts. Then obtain the Stochastic S-Curve (SS-Curve), for each sub-group and the project SS-Curve is obtained by summing sub-groups- SS-Curves. In this model, project cost uncertainties are considered through Beta distribution functions of the project activities costs required to complete the project at every selected time sections through project accomplishment, which are extracted from a variety of sources. Based on this model, after a percentage of the project progress, the project performance is measured via Earned Value Management to adjust the primary cost probability distribution functions. Then, accordingly the future project cost performance is predicted by using the Monte-Carlo simulation method.

Keywords: Monte Carlo method, Probabilistic model, Project forecasting, Stochastic S-curve

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Authors: Wennan Long, Yuhao Nie, Yunan Li, Adam Brandt

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To fight against climate change, California government issued the Senate Bill No. 100 (SB-100) in 2018 September, which aims at achieving a target of 100% renewable electricity by the end of 2045. A capacity expansion problem is solved in this case study using a binary quadratic programming model. The optimal locations and capacities of the potential renewable power plants (i.e., solar, wind, biomass, geothermal and hydropower), the phase-out schedule of existing fossil-based (nature gas) power plants and the transmission of electricity across the entire network are determined with the minimal total annualized cost measured by net present value (NPV). The results show that the renewable electricity contribution could increase to 85.9% by 2030 and reach 100% by 2035. Fossil-based power plants will be totally phased out around 2035 and solar and wind will finally become the most dominant renewable energy resource in California electricity mix.

Keywords: 100% renewable electricity, California, capacity expansion, binary quadratic programming.

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Authors: Ming-Hui Cheng, Jyh-Horng Jeng

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In this study, a classification-based video super-resolution method using artificial neural network (ANN) is proposed to enhance low-resolution (LR) to high-resolution (HR) frames. The proposed method consists of four main steps: classification, motion-trace volume collection, temporal adjustment, and ANN prediction. A classifier is designed based on the edge properties of a pixel in the LR frame to identify the spatial information. To exploit the spatio-temporal information, a motion-trace volume is collected using motion estimation, which can eliminate unfathomable object motion in the LR frames. In addition, temporal lateral process is employed for volume adjustment to reduce unnecessary temporal features. Finally, ANN is applied to each class to learn the complicated spatio-temporal relationship between LR and HR frames. Simulation results show that the proposed method successfully improves both peak signal-to-noise ratio and perceptual quality.

Keywords: Super-resolution, classification, spatio-temporal information, artificial neural network.

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Authors: Sanjeeb Kumar Kar

Abstract:

The optimal control problem of a linear distributed parameter system is studied via shifted Legendre polynomials (SLPs) in this paper. The partial differential equation, representing the linear distributed parameter system, is decomposed into an n - set of ordinary differential equations, the optimal control problem is transformed into a two-point boundary value problem, and the twopoint boundary value problem is reduced to an initial value problem by using SLPs. A recursive algorithm for evaluating optimal control input and output trajectory is developed. The proposed algorithm is computationally simple. An illustrative example is given to show the simplicity of the proposed approach.

Keywords: Optimal control, linear systems, distributed parametersystems, Legendre polynomials.

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Authors: M. Rahou, A. Cheikh, F. Sebaa

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Manufacturing tolerancing is intended to determine the intermediate geometrical and dimensional states of the part during its manufacturing process. These manufacturing dimensions also serve to satisfy not only the functional requirements given in the definition drawing, but also the manufacturing constraints, for example geometrical defects of the machine, vibration and the wear of the cutting tool. In this paper, an experimental study on the influence of the wear of the cutting tool (systematic dispersions) is explored. This study was carried out on three stages .The first stage allows machining without elimination of dispersions (random, systematic) so the tolerances of manufacture according to total dispersions. In the second stage, the results of the first stage are filtered in such way to obtain the tolerances according to random dispersions. Finally, from the two previous stages, the systematic dispersions are generated. The objective of this study is to model by the least squares method the error of manufacture based on systematic dispersion. Finally, an approach of optimization of the manufacturing tolerances was developed for machining on a CNC machine tool

Keywords: Dispersions, Compensation, modeling, manufacturing Tolerance, machine tool.

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Authors: Mario R. Acevedo Amaya, Fernanda M. Martinez Reyes

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Through the time, the higher education has changed the learning system since mother tongue to bilingual, and in this new century has been coming develop a multilingual education. All as part of globalization process of the countries and the education. Nevertheless, this change only has been effectively in countries of the first world, the rest have been lagging. Therefore, these countries require strengthen their higher education systems through models that give way to multilingual and bilingual education. In this way, shows a new model adapted from a systemic form to allow a higher bilingual and multilingual education in Latin America. This systematization aims to increase the skills and competencies student’s, decrease the time learning of a second tongue, add to multilingualism in the American Latin Universities, also, contribute to position the region´s countries in a better global status, and stimulate the development of new research in this area.

Keywords: Bilingual Education, Higher Education, Multilingual Education, Multilingual Education Model

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Authors: MooSeop Kim, Juhan Kim, Yongje Choi

Abstract:

Recently, much research has been conducted for security for wireless sensor networks and ubiquitous computing. Security issues such as authentication and data integrity are major requirements to construct sensor network systems. Advanced Encryption Standard (AES) is considered as one of candidate algorithms for data encryption in wireless sensor networks. In this paper, we will present the hardware architecture to implement low power AES crypto module. Our low power AES crypto module has optimized architecture of data encryption unit and key schedule unit which could be applicable to wireless sensor networks. We also details low power design methods used to design our low power AES crypto module.

Keywords: Algorithm, Low Power Crypto Circuit, AES, Security.

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Authors: Lydia Chan, Islam Shyha, Dale Dreyer, John Hamilton, Phil Hackney

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Nickel-based superalloys are generally known to be difficult to cut due to their strength, low thermal conductivity, and high work hardening tendency. Superalloy such as alloy 625 is often used in the oil and gas industry as a surfacing material to provide wear and corrosion resistance to components. The material is typically applied onto a metallic substrate through weld overlay cladding, an arc welding technique. Cladded surfaces are always rugged and carry a tough skin; this creates further difficulties to the machining process. The present work utilised design of experiment to optimise the internal cylindrical rough turning for weld overlay surfaces. An L27 orthogonal array was used to assess effects of the four selected key process variables: cutting insert, depth of cut, feed rate, and cutting speed. The optimal cutting conditions were determined based on productivity and the level of tool wear.

Keywords: Cylindrical turning, nickel superalloy, turning of overlay, weld overlay.

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Authors: Panagiotis Kosmas, Panayiotis Zaphiris

Abstract:

Embodied Cognition (EC) as a learning paradigm is based on the idea of an inseparable link between body, mind, and environment. In recent years, the advent of theoretical learning approaches around EC theory has resulted in a number of empirical studies exploring the implementation of the theory in education. This systematic literature overview identifies the mainstream of EC research and emphasizes on the implementation of the theory across learning environments. Based on a corpus of 43 manuscripts, published between 2013 and 2017, it sets out to describe the range of topics covered under the umbrella of EC and provides a holistic view of the field. The aim of the present review is to investigate the main issues in EC research related to the various learning contexts. Particularly, the study addresses the research methods and technologies that are utilized, and it also explores the integration of body into the learning context. An important finding from the overview is the potential of the theory in different educational environments and disciplines. However, there is a lack of an explicit pedagogical framework from an educational perspective for a successful implementation in various learning contexts.

Keywords: Embodied cognition, embodied learning, education, technology, schools.

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Authors: Yasmin Mohd Yacob, Harsa A. Mat Sakim, Nor Ashidi Mat Isa

Abstract:

Feature selection study is gaining importance due to its contribution to save classification cost in terms of time and computation load. In search of essential features, one of the methods to search the features is via the decision tree. Decision tree act as an intermediate feature space inducer in order to choose essential features. In decision tree-based feature selection, some studies used decision tree as a feature ranker with a direct threshold measure, while others remain the decision tree but utilized pruning condition that act as a threshold mechanism to choose features. This paper proposed threshold measure using Manhattan Hierarchical Cluster distance to be utilized in feature ranking in order to choose relevant features as part of the feature selection process. The result is promising, and this method can be improved in the future by including test cases of a higher number of attributes.

Keywords: Feature ranking, decision tree, hierarchical cluster, Manhattan distance.

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Authors: Petar Sarajcev, Josip Vasilj, Damir Jakus

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This paper presents a novel statistical description of the counterpoise effective length due to lightning surges, where the (impulse) effective length had been obtained by means of regressive formulas applied to the transient simulation results. The effective length is described in terms of a statistical distribution function, from which median, mean, variance, and other parameters of interest could be readily obtained. The influence of lightning current amplitude, lightning front duration, and soil resistivity on the effective length has been accounted for, assuming statistical nature of these parameters. A method for determining the optimal counterpoise length, in terms of the statistical impulse effective length, is also presented. It is based on estimating the number of dangerous events associated with lightning strikes. Proposed statistical description and the associated method provide valuable information which could aid the design engineer in optimising physical lengths of counterpoises in different grounding arrangements and soil resistivity situations.

Keywords: Counterpoise, Grounding conductor, Effective length, Lightning, Monte Carlo method, Statistical distribution.

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Authors: M. Ayazi, R. Karami, B. Kamkari

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Solid oxide fuel cells have been considered in the last years as one of the most promising technologies for very highefficiency electric energy generation from hydrogen or other hydrocarbons, both with simple fuel cell plants and with integrated gas turbine-fuel cell systems. In the present study, a detailed thermodynamic analysis has been carried out. Mass and exergy balances are performed not only for the whole plant but also for each component in order to evaluate the thermal efficiency of combined cycle. Moreover, different sources of irreversibilities within the SOFC stack have been discussed and a parametric study conducted to evaluate the effect of temperature as well as pressure on SOFC irreversibilities and its performance. In this investigation methane and hydrogen have been used for fueling the SOFC stack and combustion chamber.

Keywords: SOFC, Energy, Power turbine, Irreversibility.

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Authors: Emma R. Arakelova, Stepan G. Grigoryan, Ashot M. Khachatryan, Karapet E. Avjyan, Lilia M. Savchenko, Flora G. Arsenyan

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The paper presents a new drugs delivery system, based on the thin film technology. As a model antitumor drug, highly toxic doxorubicin is chosen. The system is based on the technology of obtaining zinc oxide composite of doxorubicin by deposition of nanosize ZnO films on the surface of doxorubicin coating on glass substrate using DC magnetron sputtering of zinc targets in Ar:O₂ medium at room temperature. For doxorubicin zinc oxide compositions in the form of coatings and gels with 180-200nm thick ZnO films, higher (by a factor 2) in vivo (ascitic Ehrlich's carcinoma) antitumor activity is observed at low doses of doxorubicin in comparison with that of the initial preparation at therapeutic doses. The vector character of the doxorubicin zinc oxide composite transport to tumor tissues ensures the increase in antitumor activity as well as decrease of toxicity in comparison with the initial drug.

Keywords: Antitumor activity, doxorubicin, DC magnetron sputtering, zinc oxide.

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Authors: A. Ouanane, A. Serir

Abstract:

In this paper, a novel algorithm based on Ridgelet Transform and support vector machine is proposed for human action recognition. The Ridgelet transform is a directional multi-resolution transform and it is more suitable for describing the human action by performing its directional information to form spatial features vectors. The dynamic transition between the spatial features is carried out using both the Principal Component Analysis and clustering algorithm K-means. First, the Principal Component Analysis is used to reduce the dimensionality of the obtained vectors. Then, the kmeans algorithm is then used to perform the obtained vectors to form the spatio-temporal pattern, called set-of-labels, according to given periodicity of human action. Finally, a Support Machine classifier is used to discriminate between the different human actions. Different tests are conducted on popular Datasets, such as Weizmann and KTH. The obtained results show that the proposed method provides more significant accuracy rate and it drives more robustness in very challenging situations such as lighting changes, scaling and dynamic environment

Keywords: Human action, Ridgelet Transform, PCA, K-means, SVM.

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Authors: Norziana Aminudin, Titik Khawa Abdul Rahman, Ismail Musirin

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One of the factors to maintain system survivability is the adequate reactive power support to the system. Lack of reactive power support may cause undesirable voltage decay leading to total system instability. Thus, appropriate reactive power support scheme should be arranged in order to maintain system stability. The strength of a system capacity is normally denoted as system loadability. This paper presents the enhancement of system loadability through optimal reactive power planning technique using a newly developed optimization technique, termed as Multiagent Immune Evolutionary Programming (MAIEP). The concept of MAIEP is developed based on the combination of Multiagent System (MAS), Artificial Immune System (AIS) and Evolutionary Programming (EP). In realizing the effectiveness of the proposed technique, validation is conducted on the IEEE-26-Bus Reliability Test System. The results obtained from pre-optimization and post-optimization process were compared which eventually revealed the merit of MAIEP.

Keywords: Load margin, MAIEP, Maximum loading point, ORPP.

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Authors: Mais Nijim, Rama Devi Chennuboyina, Waseem Al Aqqad

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Advances in spatial and spectral resolution of satellite images have led to tremendous growth in large image databases. The data we acquire through satellites, radars, and sensors consists of important geographical information that can be used for remote sensing applications such as region planning, disaster management. Spatial data classification and object recognition are important tasks for many applications. However, classifying objects and identifying them manually from images is a difficult task. Object recognition is often considered as a classification problem, this task can be performed using machine-learning techniques. Despite of many machine-learning algorithms, the classification is done using supervised classifiers such as Support Vector Machines (SVM) as the area of interest is known. We proposed a classification method, which considers neighboring pixels in a region for feature extraction and it evaluates classifications precisely according to neighboring classes for semantic interpretation of region of interest (ROI). A dataset has been created for training and testing purpose; we generated the attributes by considering pixel intensity values and mean values of reflectance. We demonstrated the benefits of using knowledge discovery and data-mining techniques, which can be on image data for accurate information extraction and classification from high spatial resolution remote sensing imagery.

Keywords: Remote sensing, object recognition, classification, data mining, waterbody identification, feature extraction.

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Authors: Choeng-Ryul Choi, Chang-Nyung Kim, Tae-Hyub Hong

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A numerical method is developed for simulating the motion of particles with arbitrary shapes in an effectively infinite or bounded viscous flow. The particle translational and angular motions are numerically investigated using a fluid-structure interaction (FSI) method based on the Arbitrary-Lagrangian-Eulerian (ALE) approach and the dynamic mesh method (smoothing and remeshing) in FLUENT ( ANSYS Inc., USA). Also, the effects of arbitrary shapes on the dynamics are studied using the FSI method which could be applied to the motions and deformations of a single blood cell and multiple blood cells, and the primary thrombogenesis caused by platelet aggregation. It is expected that, combined with a sophisticated large-scale computational technique, the simulation method will be useful for understanding the overall properties of blood flow from blood cellular level (microscopic) to the resulting rheological properties of blood as a mass (macroscopic).

Keywords: Blood Flow, Fluid-Structure Interaction (FSI), Micro-Channels, Arbitrary Shapes, Red Blood Cells (RBCs)

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Authors: C. Lodato, S. Lopes

Abstract:

This paper describes a segmentation algorithm based on the cooperation of an optical flow estimation method with edge detection and region growing procedures. The proposed method has been developed as a pre-processing stage to be used in methodologies and tools for video/image indexing and retrieval by content. The addressed problem consists in extracting whole objects from background for producing images of single complete objects from videos or photos. The extracted images are used for calculating the object visual features necessary for both indexing and retrieval processes. The first task of the algorithm exploits the cues from motion analysis for moving area detection. Objects and background are then refined using respectively edge detection and region growing procedures. These tasks are iteratively performed until objects and background are completely resolved. The developed method has been applied to a variety of indoor and outdoor scenes where objects of different type and shape are represented on variously textured background.

Keywords: Motion Detection, Object Extraction, Optical Flow, Segmentation.

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Authors: Sergey N. Sayapin, Anatoly P. Karpenko, Suan H. Dang

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Comparative analysis of robotic vehicles for pipe inspection is presented in this paper. The promising concept of self-propelled intelligent robotic vehicle (SPIRV) based on octahedral dodekapod for inspection and operation in active branched pipelines with variable cross-sections is reasoned. SPIRV is able to move in pipeline, regardless of its spatial orientation. SPIRV can also be used to move along the outside of the pipelines as well as in space between surfaces of annular tubes. Every one of faces of the octahedral dodekapod can clamp/unclamp a thing with a closed loop surface of various forms as well as put pressure on environmental surface of contact. These properties open new possibilities for its applications in SPIRV. We examine design principles of octahedral dodekapod as future intelligent building blocks for various robotic vehicles that can self-move and self-reconfigure.

Keywords: Modular robot, octahedral dodekapod, pipe inspection robot, spatial parallel structure.

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Authors: Fereidoun Nowshiravan Rahatabad, Mohammad Ali Nekoui, Mohammad Reza Hashemi Golpaygani, AliFallah, Mehdi Kazemzadeh Narbat

Abstract:

The people are differed by their capabilities, skills and mental agilities. The evolution of human from childhood when they are completely dependent up to adultness the time they gradually set the dependency free is too complicated, by considering they have all started from almost one point but some become cleverer and some less. The main control command of a cybernetic hand should be posted by remaining healthy organs of disabled Person. These commands can be from several channels, which their recording and detecting are different and need complicated study. In this research, we suppose that, this stage has been done or in the other words, the command has been already sent and detected. So the main goal is to control a long hand, upper elbow hand missing, by an interest angle define by disabled. It means that, the system input is the position desired by disables and the output is the elbow-joint angle variation. Therefore the goal is a suitable control design based on neural network theory in order to meet the given mapping.

Keywords: Control - system design, Upper limb prosthesis, neuralnetwork.

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Authors: Mouataz Zreika, Maria Estela Varua

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Stock investment decisions are often made based on current events of the global economy and the analysis of historical data. Conversely, visual representation could assist investors’ gain deeper understanding and better insight on stock market trends more efficiently. The trend analysis is based on long-term data collection. The study adopts a hybrid method that combines the Clustering algorithm and Force-directed algorithm to overcome the scalability problem when visualizing large data. This method exemplifies the potential relationships between each stock, as well as determining the degree of strength and connectivity, which will provide investors another understanding of the stock relationship for reference. Information derived from visualization will also help them make an informed decision. The results of the experiments show that the proposed method is able to produced visualized data aesthetically by providing clearer views for connectivity and edge weights.

Keywords: Clustering, force-directed, graph drawing, stock investment analysis.

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Authors: P. H. Mukti, I. Kurniawati, F. Oktaviansyah, A. D. Adhitya, N. Rachmadani, R. Corputty, G. Hendrantoro, T. Fukusako

Abstract:

HF Communication system is one of the attractive fields among many researchers since it can be reached long-distance areas with low-cost. This long-distance communication can be achieved by exploiting the ionosphere as a transmission medium for the HF radio wave. However, due to the dynamic nature of ionosphere, the channel characteristic of HF communication has to be investigated in order to gives better performances. Many techniques to characterize HF channel are available in the literature. However, none of those techniques describe the HF channel characteristic in low-latitude regions, especially equatorial areas. Since the ionosphere around equatorial region has an ESF phenomenon, it becomes an important investigation to characterize the wideband HF Channel in low-latitude region. On the other sides, the appearance of software-defined radio attracts the interest of many researchers. Accordingly, in this paper a SDR-based channel measurement system is proposed to be used for characterizing the HF channel in low-latitude region.

Keywords: Channel Characteristic, HF Communication System, LabVIEW, Software-Defined Radio, Universal Software Radio Pheripheral.

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Authors: B. Sathyanandhi, P. M. Balasubramaniam

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This paper presents Buck-Boost converter topology to maintain the input power factor by using the power factor stage control and regulation stage control. Suppose, if we are using the RL load the power factor will be reduced due to the presence of total harmonic distortion in the current wave. To improve the power factor the current waveform should follow the fundamental component of the voltage waveform. These can be achieved by using the high -frequency power converter. Based on the resonant circuit the converter is able to perform the function of Buck, Boost, and buck-boost converter. Here ,we have used Buck-Boost converter, because, the buck-boost converter has more advantages than the boost converter. Here the switching action of the power converter can  take place by using the external zero comparator PFC stage control. The power converter consisting of the resonant  circuit which is used to control the output voltage gain of the converter. The power converter is operated at a very high switching frequency in the range of 400KHz in order to overcome the switching losses of the power converter. Due to  presence of high switching frequency, the power factor will improve. Therefore, the total harmonics distortion present in the current waveform has also reduced. These results has generated in the form of simulation by using MATLAB/SIMULINK software.  Similar to the Buck and Boost converters, the operation of the Buck-Boost has best understood, in terms of the inductor's "reluctance" for allowing rapid change in current, which also reduces the Total Harmonic Distortion (THD) in the input current waveform, which can improve the input Power factor, based on the type of load used.

Keywords: Buck-boost converter, High switching frequency, Power factor correction, power factor correction stage Regulation stage, Total harmonic distortion (THD).

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Authors: Seung-Jun Yu, Jang-Kyun Ahn, Eui-Young Lee, Hyoung-Kyu Song

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Space-time block codes (STBC) and spatial multiplexing (SM) are promising techniques that effectively exploit multipleinput multiple-output (MIMO) transmission to achieve more reliable communication and a higher multiplexing rate, respectively. In this paper, we study a practical design for hybrid scheme with multi-input multi-output orthogonal frequency division multiplexing (MIMOOFDM) systems to flexibly maximize the tradeoff between diversity and multiplexing gains. Unlike the existing STBC and SM designs which are suitable for the integer multiplexing rate, the proposed design can achieve arbitrary number of multiplexing rate.

Keywords: Space-Time Block Codes, Spatial Multiplexing, MIMO-OFDM.

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Authors: Alexandros Lioulemes, Michail Theofanidis, Varun Kanal, Konstantinos Tsiakas, Maher Abujelala, Chris Collander, William B. Townsend, Angie Boisselle, Fillia Makedon

Abstract:

This paper presents a home-based robot-rehabilitation instrument, called ”MAGNI Dynamics”, that utilized a vision-based kinematic/dynamic module and an adaptive haptic feedback controller. The system is expected to provide personalized rehabilitation by adjusting its resistive and supportive behavior according to a fuzzy intelligence controller that acts as an inference system, which correlates the user’s performance to different stiffness factors. The vision module uses the Kinect’s skeletal tracking to monitor the user’s effort in an unobtrusive and safe way, by estimating the torque that affects the user’s arm. The system’s torque estimations are justified by capturing electromyographic data from primitive hand motions (Shoulder Abduction and Shoulder Forward Flexion). Moreover, we present and analyze how the Barrett WAM generates a force-field with a haptic controller to support or challenge the users. Experiments show that by shifting the proportional value, that corresponds to different stiffness factors of the haptic path, can potentially help the user to improve his/her motor skills. Finally, potential areas for future research are discussed, that address how a rehabilitation robotic framework may include multisensing data, to improve the user’s recovery process.

Keywords: Human-robot interaction, kinect, kinematics, dynamics, haptic control, rehabilitation robotics, artificial intelligence.

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Authors: Li Feng

Abstract:

In this paper, center conditions and bifurcation of limit cycles at the nilpotent critical point in a class of quintic polynomial differential system are investigated.With the help of computer algebra system MATHEMATICA, the first 10 quasi Lyapunov constants are deduced. As a result, sufficient and necessary conditions in order to have a center are obtained. The fact that there exist 10 small amplitude limit cycles created from the three order nilpotent critical point is also proved. Henceforth we give a lower bound of cyclicity of three-order nilpotent critical point for quintic Lyapunov systems. At last, we give an system which could bifurcate 10 limit circles.

Keywords: Three-order nilpotent critical point, center-focus problem, bifurcation of limit cycles, Quasi-Lyapunov constant.

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Authors: Mona M. Salem, Khaled S. Al-Hagla, Hany M. Ayad

Abstract:

The concept of urban metabolism has increasingly been employed in a diverse range of disciplines as a mean to analyze and theorize the city. Urban ecology has a particular focus on the implications of applying the metabolism concept to the urban realm. This approach has been developed by a few researchers, though it has rarely if ever been used in policy development for city planning. The aim of this research is to use ecologically informed urban planning interventions to increase the sustainability of urban metabolism; with special focus on land stock as a most important city resource by developing a system dynamic based DSS. This model identifies two critical management strategy variables for the Strategic Urban Plan Alexandria SUP 2032. As a result, this comprehensive and precise quantitative approach is needed to monitor, measure, evaluate and observe dynamic urban changes working as a decision support system (DSS) for policy making.

Keywords: Alexandria SUP 2032, DSS, ecology, land resource, LULCC, management, metabolism, model, scenarios, System dynamics, urban development.

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