Search results for: Quadratic objective function.

Authors: A. R. Seifi

Abstract:

This work presents a new algorithm based on a combination of fuzzy (FUZ), Dynamic Programming (DP), and Genetic Algorithm (GA) approach for capacitor allocation in distribution feeders. The problem formulation considers two distinct objectives related to total cost of power loss and total cost of capacitors including the purchase and installation costs. The novel formulation is a multi-objective and non-differentiable optimization problem. The proposed method of this article uses fuzzy reasoning for sitting of capacitors in radial distribution feeders, DP for sizing and finally GA for finding the optimum shape of membership functions which are used in fuzzy reasoning stage. The proposed method has been implemented in a software package and its effectiveness has been verified through a 9-bus radial distribution feeder for the sake of conclusions supports. A comparison has been done among the proposed method of this paper and similar methods in other research works that shows the effectiveness of the proposed method of this paper for solving optimum capacitor planning problem.

Keywords: Capacitor planning, Fuzzy logic method, Genetic Algorithm, Dynamic programming, Radial Distribution feeder

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Authors: Suraiya Jabin, Kamal K. Bharadwaj

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This research presents a system for post processing of data that takes mined flat rules as input and discovers crisp as well as fuzzy hierarchical structures using Learning Classifier System approach. Learning Classifier System (LCS) is basically a machine learning technique that combines evolutionary computing, reinforcement learning, supervised or unsupervised learning and heuristics to produce adaptive systems. A LCS learns by interacting with an environment from which it receives feedback in the form of numerical reward. Learning is achieved by trying to maximize the amount of reward received. Crisp description for a concept usually cannot represent human knowledge completely and practically. In the proposed Learning Classifier System initial population is constructed as a random collection of HPR–trees (related production rules) and crisp / fuzzy hierarchies are evolved. A fuzzy subsumption relation is suggested for the proposed system and based on Subsumption Matrix (SM), a suitable fitness function is proposed. Suitable genetic operators are proposed for the chosen chromosome representation method. For implementing reinforcement a suitable reward and punishment scheme is also proposed. Experimental results are presented to demonstrate the performance of the proposed system.

Keywords: Hierarchical Production Rule, Data Mining, Learning Classifier System, Fuzzy Subsumption Relation, Subsumption matrix, Reinforcement Learning.

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Authors: Chetan Mahawar, Sarath Chandran, Sridhar Panigrahi, V. P. Shaji

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The ever-growing advancement in space exploration has led to an alarming concern for space debris removal as it restricts further launch operations and adventurous space missions; hence various technologies and methods are explored for re-entry predictions and material selection processes for mitigating space debris. The selection of material and operating conditions is determined with the objective of lightweight structure and ability to demise faster subject to spacecraft survivability during its mission. The various evolving thermal material properties such as emissivity, specific heat capacity, thermal conductivity, radiation intensity, etc. affect demisability of spacecraft. Thus, this paper presents the analysis of evolving thermal material properties of spacecraft, which affect the demisability process and thus estimate demise time using the demisability model by incorporating evolving thermal properties for sensible heating followed by the complete or partial break-up of spacecraft. The demisability analysis thus concludes that the best suitable spacecraft material is based on the least estimated demise time, which fulfills the criteria of design-for-survivability and as well as of design-for-demisability.

Keywords: Demisability, emissivity, lightweight, re-entry, survivability.

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Authors: Kazunori Kojima, Masaaki Ishigame, Goutam Chakraborty, Hiroshi Hatsuo, Shozo Makino

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In most of the popular implementation of Parallel GAs the whole population is divided into a set of subpopulations, each subpopulation executes GA independently and some individuals are migrated at fixed intervals on a ring topology. In these studies, the migrations usually occur 'synchronously' among subpopulations. Therefore, CPUs are not used efficiently and the communication do not occur efficiently either. A few studies tried asynchronous migration but it is hard to implement and setting proper parameter values is difficult. The aim of our research is to develop a migration method which is easy to implement, which is easy to set parameter values, and which reduces communication traffic. In this paper, we propose a traffic reduction method for the Asynchronous Parallel Distributed GA by migration of elites only. This is a Server-Client model. Every client executes GA on a subpopulation and sends an elite information to the server. The server manages the elite information of each client and the migrations occur according to the evolution of sub-population in a client. This facilitates the reduction in communication traffic. To evaluate our proposed model, we apply it to many function optimization problems. We confirm that our proposed method performs as well as current methods, the communication traffic is less, and setting of the parameters are much easier.

Keywords: Parallel Distributed Genetic Algorithm (PDGA), asynchronousPDGA, Server-Client configuration, Elite Migration

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Authors: Abimbola M. Enitan, John O. Odiyo, Feroz M. Swalaha

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The study of microbial ecology and their function in anaerobic digestion processes are essential to control the biological processes. This is to know the symbiotic relationship between the microorganisms that are involved in the conversion of complex organic matter in the industrial wastewater to simple molecules. In this study, diversity and quantity of bacterial community in the granular sludge taken from the different compartments of a full-scale upflow anaerobic sludge blanket (UASB) reactor treating brewery wastewater was investigated using polymerase chain reaction (PCR) and real-time quantitative PCR (qPCR). The phylogenetic analysis showed three major eubacteria phyla that belong to Proteobacteria, Firmicutes and Chloroflexi in the full-scale UASB reactor, with different groups populating different compartment. The result of qPCR assay showed high amount of eubacteria with increase in concentration along the reactor’s compartment. This study extends our understanding on the diverse, topological distribution and shifts in concentration of microbial communities in the different compartments of a full-scale UASB reactor treating brewery wastewater. The colonization and the trophic interactions among these microbial populations in reducing and transforming complex organic matter within the UASB reactors were established.

Keywords: Bacteria, brewery wastewater, real-time quantitative PCR, UASB reactor.

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Authors: Mojtaba Valinejadshoubi, Ashutosh Bagchi, Osama Moselhi

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Structures such as buildings, bridges, dams, wind turbines etc. need to be maintained against various factors such as deterioration, excessive loads, environment, temperature, etc. Choosing an appropriate monitoring system is important for determining any critical damage to a structure and address that to avoid any adverse consequence. Structural Health Monitoring (SHM) has emerged as an effective technique to monitor the health of the structures. SHM refers to an ongoing structural performance assessment using different kinds of sensors attached to or embedded in the structures to evaluate their integrity and safety to help engineers decide on rehabilitation measures. Ability of SHM in identifying the location and severity of structural damages by considering any changes in characteristics of the structures such as their frequency, stiffness and mode shapes helps engineers to monitor the structures and take the most effective corrective actions to maintain their safety and extend their service life. The main objective of this study is to review the overall SHM process specifically determining the natural frequency of an instrumented simply-supported concrete beam using modal testing and finite element model updating.

Keywords: Structural Health Monitoring, Natural Frequency, FFT analysis, Finite element model updating.

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Authors: Insung Jung, Gi-Nam Wang

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The objective of this paper is to a design of pattern classification model based on the back-propagation (BP) algorithm for decision support system. Standard BP model has done full connection of each node in the layers from input to output layers. Therefore, it takes a lot of computing time and iteration computing for good performance and less accepted error rate when we are doing some pattern generation or training the network. However, this model is using exclusive connection in between hidden layer nodes and output nodes. The advantage of this model is less number of iteration and better performance compare with standard back-propagation model. We simulated some cases of classification data and different setting of network factors (e.g. hidden layer number and nodes, number of classification and iteration). During our simulation, we found that most of simulations cases were satisfied by BP based using exclusive connection network model compared to standard BP. We expect that this algorithm can be available to identification of user face, analysis of data, mapping data in between environment data and information.

Keywords: Neural network, Back-propagation, classification.

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Authors: Ch. Antonopoulos, Th. Kapourniotis, V. Triantafillou

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Optimum communication and performance in Wireless Sensor Networks, constitute multi-facet challenges due to the specific networking characteristics as well as the scarce resource availability. Furthermore, it is becoming increasingly apparent that isolated layer based approaches often do not meet the demands posed by WSNs applications due to omission of critical inter-layer interactions and dependencies. As a counterpart, cross-layer is receiving high interest aiming to exploit these interactions and increase network performance. However, in order to clearly identify existing dependencies, comprehensive performance studies are required evaluating the effect of different critical network parameters on system level performance and behavior.This paper-s main objective is to address the need for multi-parametric performance evaluations considering critical network parameters using a well known network simulator, offering useful and practical conclusions and guidelines. The results reveal strong dependencies among considered parameters which can be utilized by and drive future research efforts, towards designing and implementing highly efficient protocols and architectures.

Keywords: Wireless sensor network, Communication Systems, cross-layer architectures, simulation based performance evaluation

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Authors: Nuray Gökçek Karaca, Berrin Gökçek

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Employers occupational safety and health training obligations are regulated in 89/391/EEC Framework Directive and also in 6331 numbered Occupational Health and Safety Law in Turkey. The main objective of this research is to determine and evaluate the employers’ occupational health and safety training obligations in Framework Directive in comparison with the 6331 numbered Occupational Health and Safety Law and to examine training principles in Turkey. For this purpose, employers’ occupational health and safety training obligations examined in Framework Directive and Occupational Health and Safety Law. This study carried out through comparative scanning model and literature model. The research data were collected through European Agency and ministry legislations. As a result, employers’ occupational health and safety training obligations in the 6331 numbered Occupational Health and Safety Law are compatible with the 89/391/EEC numbered Framework Directive and training principles are determined by in different ways like the trained workers, training issues, training period, training time and trainers. In this study, employers’ training obligations are evaluated in detail.

Keywords: Directive, occupational health and safety, training.

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Authors: S. H. Iranmanesh, L. Aliabadi, A. Mollajan

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Integrated resilience engineering (IRE) is capable of returning banking systems to the normal state in extensive economic circumstances. In this study, information system of a large bank (with several branches) is assessed and optimized under severe economic conditions. Data envelopment analysis (DEA) models are employed to achieve the objective of this study. Nine IRE factors are considered to be the outputs, and a dummy variable is defined as the input of the DEA models. A standard questionnaire is designed and distributed among executive managers to be considered as the decision-making units (DMUs). Reliability and validity of the questionnaire is examined based on Cronbach's alpha and t-test. The most appropriate DEA model is determined based on average efficiency and normality test. It is shown that the proposed integrated design provides higher efficiency than the conventional RE design. Results of sensitivity and perturbation analysis indicate that self-organization, fault tolerance, and reporting culture respectively compose about 50 percent of total weight.

Keywords: Banking system, data envelopment analysis, DEA, integrated resilience engineering, IRE, performance evaluation, perturbation analysis.

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Authors: Shih-Wen Hsiao, Rong-Qi Chen, Chien-Yu Lin

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The topic of surface flattening plays a vital role in the field of computer aided design and manufacture. Surface flattening enables the production of 2D patterns and it can be used in design and manufacturing for developing a 3D surface to a 2D platform, especially in fashion design. This study describes surface flattening based on minimum energy methods according to the property of different fabrics. Firstly, through the geometric feature of a 3D surface, the less transformed area can be flattened on a 2D platform by geodesic. Then, strain energy that has accumulated in mesh can be stably released by an approximate implicit method and revised error function. In some cases, cutting mesh to further release the energy is a common way to fix the situation and enhance the accuracy of the surface flattening, and this makes the obtained 2D pattern naturally generate significant cracks. When this methodology is applied to a 3D mannequin constructed with feature lines, it enhances the level of computer-aided fashion design. Besides, when different fabrics are applied to fashion design, it is necessary to revise the shape of a 2D pattern according to the properties of the fabric. With this model, the outline of 2D patterns can be revised by distributing the strain energy with different results according to different fabric properties. Finally, this research uses some common design cases to illustrate and verify the feasibility of this methodology.

Keywords: Surface flattening, Strain energy, Minimum energy, approximate implicit method, Fashion design.

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Authors: A. Zaidi, F. Khelifi, R. Masmoudi, M. Bouhicha

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5

In order to eradicate the degradation of reinforced concrete structures due to the steel corrosion, professionals in constructions suggest using fiber reinforced polymers (FRP) for their excellent properties. Nevertheless, high temperatures may affect the bond between FRP bar and concrete, and consequently the serviceability of FRP-reinforced concrete structures. This paper presents a nonlinear numerical investigation using ADINA software to investigate the effect of the spacing between glass FRP (GFRP) bars embedded in concrete on circumferential thermal deformations and the distribution of radial thermal cracks in reinforced concrete beams submitted to high temperature variations up to 60 °C for asymmetrical problems. The thermal deformations predicted from nonlinear finite elements model, at the FRP bar/concrete interface and at the external surface of concrete cover, were established as a function of the ratio of concrete cover thickness to FRP bar diameter (c/d_b) and the ratio of spacing between FRP bars in concrete to FRP bar diameter (e/d_b). Numerical results show that the circumferential thermal deformations at the external surface of concrete cover are linear until cracking thermal load varied from 32 to 55 °C corresponding to the ratio of e/d_b varied from 1.3 to 2.3, respectively. However, for ratios e/d_b >2.3 and c/d_b >1.6, the thermal deformations at the external surface of concrete cover exhibit linear behavior without any cracks observed on the specified surface. The numerical results are compared to those obtained from analytical models validated by experimental tests.

Keywords: Concrete beam, FRP bars, spacing effect, thermal deformation.

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Authors: Hoang Van Ngoc, Nguyen Vu Nhan, Nguyen Quang Bau

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The light-effect in cylindrical quantum wire with an infinite potential for the case of electrons, optical phonon scattering, is studied based on the quantum kinetic equation. The density of the direct current in a cylindrical quantum wire by a linearly polarized electromagnetic wave, a DC electric field, and an intense laser field is calculated. Analytic expressions for the density of the direct current are studied as a function of the frequency of the laser radiation field, the frequency of the linearly polarized electromagnetic wave, the temperature of system, and the size of quantum wire. The density of the direct current in cylindrical quantum wire with an infinite potential for the case of electrons – optical phonon scattering is nonlinearly dependent on the frequency of the linearly polarized electromagnetic wave. The analytic expressions are numerically evaluated and plotted for a specific quantum wire, GaAs/GaAsAl.

Keywords: The light-effect, cylindrical quantum wire with an infinite potential, the density of the direct current, electrons - optical phonon scattering.

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Authors: Luen Chow Chan

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With the advocacy of green transportation and green traveling, cycling has become increasingly popular nowadays. Physiology and bike design are key factors for the influence of cycling efficiency. Therefore, this study aimed to investigate the significance of bike-frame geometric factors on cycling efficiency and muscle activation for different body sizes of non-professional Asian male cyclists. Participants who represented various body sizes, as measured by leg and back lengths, carried out cycling tests using a tailor-assembled road bike with different ergonomic design configurations including seat-height adjustments (i.e., 96%, 100%, and 104% of trochanteric height) and bike frame sizes (i.e., small and medium frames) for an assessable distance of 1 km. A specific power meter and self-developed adaptable surface electromyography (sEMG) were used to measure average pedaling power and cadence generated and muscle activation, respectively. The results showed that changing the seat height was far more significant than the body and bike frame sizes. The sEMG data evidently provided a better understanding of muscle activation as a function of different seat heights. Therefore, the interpretation of this study is that the major bike ergonomic design factor dominating the cycling efficiency of Asian participants with different body sizes was the seat height.

Keywords: Bike frame sizes, cadence rate, pedaling power, seat height.

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Authors: Shadrack Mambo, Karim Djouani, Yskandar Hamam, Barend van Wyk, Patrick Siarry

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This paper discusses the current trends in medical image registration techniques and addresses the need to provide a solid theoretical foundation for research endeavours. Methodological analysis and synthesis of quality literature was done, providing a platform for developing a good foundation for research study in this field which is crucial in understanding the existing levels of knowledge. Research on medical image registration techniques assists clinical and medical practitioners in diagnosis of tumours and lesion in anatomical organs, thereby enhancing fast and accurate curative treatment of patients. Literature review aims to provide a solid theoretical foundation for research endeavours in image registration techniques. Developing a solid foundation for a research study is possible through a methodological analysis and synthesis of existing contributions. Out of these considerations, the aim of this paper is to enhance the scientific community’s understanding of the current status of research in medical image registration techniques and also communicate to them, the contribution of this research in the field of image processing. The gaps identified in current techniques can be closed by use of artificial neural networks that form learning systems designed to minimise error function. The paper also suggests several areas of future research in the image registration.

Keywords: Image registration techniques, medical images, neural networks, optimisation, transformation.

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Authors: Farshad Zeinali, Sajedeh Norouzi, Nader Mokari, Eduard A. Jorswieck

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The capacity of fifth-generation (5G)vehicle-to-everything (V2X) networks poses significant challenges.To address this challenge, this paper utilizes New Radio (NR) and New Radio Unlicensed (NR-U) networks to develop a vehicular heterogeneous network (HetNet). We propose a framework, named joint BS assignment and resource allocation (JBSRA) for mobile V2X users and also consider coexistence schemes based on flexible duty cycle (DC) mechanism for unlicensed bands. Our objective is to maximize the average throughput of vehicles, while guarantying the WiFi users throughput. In simulations based on deep reinforcement learning (DRL) algorithms such as deep deterministic policy gradient (DDPG) and deep Q network (DQN), our proposed framework outperforms existing solutions that rely on fixed DC or schemes without consideration of unlicensed bands.

Keywords: Vehicle-to-everything, resource allocation, BS assignment, new radio, new radio unlicensed, coexistence NR-U and WiFi, deep deterministic policy gradient, Deep Q-network, Duty cycle mechanism.

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Authors: Ashwin Bala, K. Panthalaraja Kumaran, S. Prithviraj, R. Pradeep, J. Udhayakumar, S. Ajith

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In this paper comprehensive studies have been carried out for the design optimization of a waste heat recovery system for effectively utilizing the domestic air conditioner heat energy for producing hot water. Numerical studies have been carried for the geometry optimization of a waste heat recovery system for domestic air conditioners. Numerical computations have been carried out using a validated 2d pressure based, unsteady, 2nd-order implicit, SST k-ω turbulence model. In the numerical study, a fully implicit finite volume scheme of the compressible, Reynolds-Averaged, Navier- Stokes equations is employed. At identical inflow and boundary conditions various geometries were tried and effort has been taken for proposing the best design criteria. Several combinations of pipe line shapes viz., straight and spiral with different number of coils for the radiator have been attempted and accordingly the design criteria has been proposed for the waste heat recovery system design. We have concluded that, within the given envelope, the geometry optimization is a meaningful objective for getting better performance of waste heat recovery system for air conditioners.

Keywords: Air-conditioning system, Energy conversion system, Hot water production from waste heat, Waste heat recovery system.

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Authors: Florin Gorunescu

Abstract:

Diagnosis can be achieved by building a model of a certain organ under surveillance and comparing it with the real time physiological measurements taken from the patient. This paper deals with the presentation of the benefits of using Data Mining techniques in the computer-aided diagnosis (CAD), focusing on the cancer detection, in order to help doctors to make optimal decisions quickly and accurately. In the field of the noninvasive diagnosis techniques, the endoscopic ultrasound elastography (EUSE) is a recent elasticity imaging technique, allowing characterizing the difference between malignant and benign tumors. Digitalizing and summarizing the main EUSE sample movies features in a vector form concern with the use of the exploratory data analysis (EDA). Neural networks are then trained on the corresponding EUSE sample movies vector input in such a way that these intelligent systems are able to offer a very precise and objective diagnosis, discriminating between benign and malignant tumors. A concrete application of these Data Mining techniques illustrates the suitability and the reliability of this methodology in CAD.

Keywords: Endoscopic ultrasound elastography, exploratorydata analysis, neural networks, non-invasive cancer detection.

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Authors: M. Sreedhar Babu, Vishal Garg, S. B. Akella, Shibu Clement, N. K. S Rajan

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Producer gas is a biomass derived gaseous fuel which is extensively used in internal combustion engines for power generation application. Unlike the conventional hydrocarbon fuels (Gasoline and Natural gas), the combustion properties of producer gas fuel are much different. Therefore, setting of optimal spark time for efficient engine operation is required. Owing to the fluctuating tendency of producer gas composition during gasification process, the heat release patterns (dictating the power output and emissions) obtained are quite different from conventional fuels. It was found that, valve lift timing is yet another factor which influences the burn rate of producer gas fuel, and thus, the heat release rate of the engine. Therefore, the present study was motivated to estimate the influence of valve lift timing analytically (Wiebe model) on the burn rate of producer gas through curve fitting against experimentally obtained mass fraction burn curves of several producer gas compositions. Furthermore, Wiebe models are widely used in zero-dimensional codes for engine parametric studies and are quite popular. This study also addresses the influence of hydrogen and methane concentration of producer gas on combustion trends, which are known to cause dynamics in engine combustion.

Keywords: Combustion Duration, crank angle, mass fraction burnt, producer gas, wiebe combustion model, wide open throttle.

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Authors: U. Yerlikaya, R. T. Balkan

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In this research, a method is developed to obtain high-dimensional configuration space for path planning problems. In typical cases, the path planning problems are solved directly in the 3-dimensional (D) workspace. However, this method is inefficient in handling the robots with various geometrical and mechanical restrictions. To overcome these difficulties, path planning may be formalized and solved in a new space which is called configuration space. The number of dimensions of the configuration space comes from the degree of freedoms of the system of interest. The method can be applied in two ways. In the first way, the point clouds of all the bodies of the system and interaction of them are used. The second way is performed via using the clearance function of simulation software where the minimum distances between surfaces of bodies are simultaneously measured. A double-turret system is held in the scope of this study. The 4-D configuration space of a double-turret system is obtained in these two ways. As a result, the difference between these two methods is around 1%, depending on the density of the point cloud. The disparity between the two forms steadily decreases as the point cloud density increases. At the end of the study, in order to verify 4-D configuration space obtained, 4-D path planning problem was realized as 2-D + 2-D and a sample path planning is carried out with using A* algorithm. Then, the accuracy of the configuration space is proved using the obtained paths on the simulation model of the double-turret system.

Keywords: A* Algorithm, autonomous turrets, high-dimensional C-Space, manifold C-Space, point clouds.

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Authors: Grace Rachid, Mutasem El-Fadel, Mahmoud Al-Hindi, Ibrahim Jamali, Daniel Abdel Nour

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This study examines the feasibility of indirect solar desalination in oil producing countries in the Middle East and North Africa (MENA) region. It relies on value engineering (VE) and costbenefit with sensitivity analyses to identify optimal coupling configurations of desalination and solar energy technologies. A comparative return on investment was assessed as a function of water costs for varied plant capacities (25,000 to 75,000 m3/day), project lifetimes (15 to 25 years), and discount rates (5 to 15%) taking into consideration water and energy subsidies, land cost as well as environmental externalities in the form of carbon credit related to greenhouse gas (GHG) emissions reduction. The results showed reverse osmosis (RO) coupled with photovoltaic technologies (PVs) as the most promising configuration, robust across different prices for Brent oil, discount rates, as well as different project lifetimes. Environmental externalities and subsidies analysis revealed that a 16% reduction in existing subsidy on water tariffs would ensure economic viability. Additionally, while land costs affect investment attractiveness, the viability of RO coupled with PV remains possible for a land purchase cost <$ 80/m2 or a lease rate <$1/m2/yr. Beyond those rates, further subsidy lifting is required.

Keywords: Solar energy, desalination, value engineering, CBA, carbon credit, subsidies.

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Authors: Imran Ahmed, Muhammad Islam, Syed Inayat Ali Shah, Awais Adnan

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The identification and classification of weeds are of major technical and economical importance in the agricultural industry. To automate these activities, like in shape, color and texture, weed control system is feasible. The goal of this paper is to build a real-time, machine vision weed control system that can detect weed locations. In order to accomplish this objective, a real-time robotic system is developed to identify and locate outdoor plants using machine vision technology and pattern recognition. The algorithm is developed to classify images into broad and narrow class for real-time selective herbicide application. The developed algorithm has been tested on weeds at various locations, which have shown that the algorithm to be very effectiveness in weed identification. Further the results show a very reliable performance on weeds under varying field conditions. The analysis of the results shows over 90 percent classification accuracy over 140 sample images (broad and narrow) with 70 samples from each category of weeds.

Keywords: Weed detection, Image Processing, real-timerecognition, Standard Deviation.

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Authors: A. Kasmi, N. E. Abriak, M. Benzerzour, I. Shahrour

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Large volumes of river sediments are dredged each year in Europe in order to maintain harbour activities and prevent floods. The management of this sediment has become increasingly complex. Several European projects were implemented to find environmentally sound solutions for these materials. The main objective of this study is to show the ability of river sediment to be used in road. Since sediments contain a high amount of water, then a dehydrating treatment by addition of the flocculation aid has been used. Firstly, a lot of physical characteristics are measured and discussed for a better identification of the raw sediment and this dehydrated sediment by addition the flocculation aid. The identified parameters are, for example, the initial water content, the density, the organic matter content, the grain size distribution, the liquid limit and plastic limit and geotechnical parameters. The environmental impacts of the used material were evaluated. The results obtained show that there is a slight change on the physical-chemical and geotechnical characteristics of sediment after dehydration by the addition of polymer. However, these sediments cannot be used in road construction.

Keywords: River sediment, dehydration, flocculation aid, characteristics, environmental impacts, road construction.

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Authors: Manisha Rathi, Thierry Chaussalet

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Hospital staff and managers are under pressure and concerned for effective use and management of scarce resources. The hospital admissions require many decisions that have complex and uncertain consequences for hospital resource utilization and patient flow. It is challenging to predict risk of admissions and length of stay of a patient due to their vague nature. There is no method to capture the vague definition of admission of a patient. Also, current methods and tools used to predict patients at risk of admission fail to deal with uncertainty in unplanned admission, LOS, patients- characteristics. The main objective of this paper is to deal with uncertainty in health system variables, and handles uncertain relationship among variables. An introduction of machine learning techniques along with statistical methods like Regression methods can be a proposed solution approach to handle uncertainty in health system variables. A model that adapts fuzzy methods to handle uncertain data and uncertain relationships can be an efficient solution to capture the vague definition of admission of a patient.

Keywords: Admission, Fuzzy, Regression, Uncertainty

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Authors: Isabela Romanha de Alcantara, José Eustáquio Ribeiro Vieira Filho, José Garcia Gasques

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Innovation and technology can be determinant factors to ensure agricultural and sustainable growth, as well as productivity gains. Technical change has contributed considerably to supply agricultural expansion in Brazil. This agricultural growth could be achieved by incorporating more land or capital. If capital is the main source of agricultural growth, it is possible to increase production per unit of land. The objective of this paper is to estimate: 1) total factor productivity (TFP), which is measured in terms of the rate of output per unit of input; and 2) the land-saving effect (LSE) that is the amount of land required in the case that yield rate is constant over time. According to this study, from 1990 to 2019, it appears that 87% of Brazilian agriculture product growth comes from the gains of productivity; the remaining 13% comes from input growth. In the same period, the total LSE was roughly 400 Mha, which corresponds to 47% of the national territory. These effects reflect the greater efficiency of using productive factors, whose technical change has allowed an increase in the agricultural production based on productivity gains.

Keywords: agriculture, land-saving effect, livestock, productivity

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Authors: B. A. A. Paixão, J. V. B. Gomide

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This work aims to analyze the locative structure used by the locative games of the company Niantic. To fulfill this objective, a literature review on the representation and simulation of cities was developed; interviews with Ingress players and playing Ingress. Relating these data, it was possible to deepen the relationship between the virtual and the real to create the simulation of cities and their cultural objects in locative games. Cities representation associates geo-location provided by the Global Positioning System (GPS), with augmented reality and digital image, and provides a new paradigm in the city interaction with its parts and real and virtual world elements, homeomorphic to real world. Bibliographic review of papers related to the representation and simulation study and their application in locative games was carried out and is presented in the present paper. The cities representation and simulation concepts in locative games, and how this setting enables the flow and immersion in urban space, are analyzed. Some examples of games are discussed for this new setting development, which is a mix of real and virtual world. Finally, it was proposed a Locative Structure for electronic games using the concepts of heterotrophic representations and isotropic representations conjoined with immediacy and hypermediacy.

Keywords: Cities representation, city simulation, games simulation, locative games.

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Authors: Manop Vorasri, Komson Jirapattarasilp, Sittichai Kaewkuekool

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The objective of this research was to study factors, which were affected on surface roughness in high speed milling of hardened tool steel. Material used in the experiment was tool steel JIS SKD 61 that hardened on 60 ±2 HRC. Full factorial experimental design was conducted on 3 factors and 3 levels (3 3 designs) with 2 replications. Factors were consisted of cutting speed, feed rate, and depth of cut. The results showed that influenced factor affected to surface roughness was cutting speed, feed rate and depth of cut which showed statistical significant. Higher cutting speed would cause on better surface quality. On the other hand, higher feed rate would cause on poorer surface quality. Interaction of factor was found that cutting speed and depth of cut were significantly to surface quality. The interaction of high cutting speed associated with low depth of cut affected to better surface quality than low cutting speed and high depth of cut.

Keywords: High-speed milling, Tool steel, SKD 61 Steel, Surface roughness, Cutting speed, Feed rate, Depth of cut

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Authors: Carlos David Carrillo Trujillo, Rebelín Echeverría Echeverría, Nancy Evia Alamilla, Rocío Quintal López

Abstract:

Gender as a social construct is a term now widely studied. Within the social sciences it has become very important. In this sense, psychology tries to make some contributions from your area. The intention is to promote equal opportunities for men and women. Social, employment and educational inequities perpetuate sexism, violence and other important social problems in Mexico. The gender perspective is conceptualized as a tool to promote laws, policies, plans, programs and procedures where women are made ​​visible and empowered. The aim of this is the pursuit of equality. Thus, gender mainstreaming is one of the main challenges of education in Mexico. Only a few universities have programs, research or subjects related to the topic. Human resources, and time allocated to teachers are identified as obstacles to the institutionalization of gender. The objective was to make a diagnosis on course offerings and policies on gender. A documentary study and interviews with managers of at least 20 higher education institutions (IES's) were performed. The results indicate the need for greater gender courses, research projects and intervention. The need to promote policies that seek equal opportunities between men and women is also noted.

Keywords: Gender mainstreaming, institutionalization, universities.

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Authors: M.H. Ahmad Fadzil, Hurriyatul Fitriyah, Esa Prakasa, Hermawan Nugroho, S.H. Hussein, Azura Mohd. Affandi

Abstract:

Psoriasis is a chronic inflammatory skin condition which affects 2-3% of population around the world. Psoriasis Area and Severity Index (PASI) is a gold standard to assess psoriasis severity as well as the treatment efficacy. Although a gold standard, PASI is rarely used because it is tedious and complex. In practice, PASI score is determined subjectively by dermatologists, therefore inter and intra variations of assessment are possible to happen even among expert dermatologists. This research develops an algorithm to assess psoriasis lesion for PASI scoring objectively. Focus of this research is thickness assessment as one of PASI four parameters beside area, erythema and scaliness. Psoriasis lesion thickness is measured by averaging the total elevation from lesion base to lesion surface. Thickness values of 122 3D images taken from 39 patients are grouped into 4 PASI thickness score using K-means clustering. Validation on lesion base construction is performed using twelve body curvature models and show good result with coefficient of determinant (R2) is equal to 1.

Keywords: 3D digital imaging, base construction, PASI, psoriasis lesion thickness.

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Authors: Zhou Luchen, Wu Yubing, Burra Venkata Durga Kumar

Abstract:

As the scale of the network becomes larger and more complex than before, the density of user devices is also increasing. The development of Unmanned Aerial Vehicle (UAV) networks is able to collect and transform data in an efficient way by using software-defined networks (SDN) technology. This paper proposed a three-layer distributed and dynamic cluster architecture to manage UAVs by using an AI-based resource allocation calculation algorithm to address the overloading network problem. Through separating services of each UAV, the UAV hierarchical cluster system performs the main function of reducing the network load and transferring user requests, with three sub-tasks including data collection, communication channel organization, and data relaying. In this cluster, a head node and a vice head node UAV are selected considering the CPU, RAM, and ROM memory of devices, battery charge, and capacity. The vice head node acts as a backup that stores all the data in the head node. The k-means clustering algorithm is used in order to detect high load regions and form the UAV layered clusters. The whole process of detecting high load areas, forming and selecting UAV clusters, and moving the selected UAV cluster to that area is proposed as offloading traffic algorithm.

Keywords: k-means, resource allocation, SDN, UAV network, unmanned aerial vehicles.

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