Search results for: complex nonlinear system.

Authors: P. S. Rajinikanth, Yeoh Suyu, Sanjay Garg

Abstract:

The present study is aim to prepare and evaluate the selfnanoemulsifying drug delivery (SNEDDS) system of a poorly water soluble drug valsartan in order to achieve a better dissolution rate which would further help in enhancing oral bioavailability. The present research work describes a SNEDDS of valsartan using labrafil M 1944 CS, Tween 80 and Transcutol HP. The pseudoternary phase diagrams with presence and absence of drug were plotted to check for the emulsification range and also to evaluate the effect of valsartan on the emulsification behavior of the phases. The mixtures consisting of oil (labrafil M 1944 CS) with surfactant (tween 80), co-surfactant (Transcutol HP) were found to be optimum formulations. Prepared formulations were evaluated for its particle size distribution, nanoemulsifying properties, robustness to dilution, self emulsication time, turbidity measurement, drug content and invitro dissolution. The optimized formulations are further evaluated for heating cooling cycle, centrifugation studies, freeze thaw cycling, particle size distribution and zeta potential were carried out to confirm the stability of the formed SNEDDS formulations. The prepared formulation revealed t a significant improvement in terms of the drug solubility as compared with marketed tablet and pure drug.

Keywords: Self Emulsifying Drug Delivery System, Valsartan, Bioavailability, poorly soluble drug.

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Authors: Bachir Kacimi, Fatiha Teklal, Arezki Djebbar

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Forming processes induce residual deformations on the reinforcement and sometimes lead to mesoscopic defects, which are more recurrent than macroscopic defects during the manufacture of complex structural parts. This study deals with the influence of the fabric shear and buckles defects, which appear during draping processes of composite, on the impact behavior of a glass fiber reinforced polymer. To achieve this aim, we produced several specimens with different amplitude of deformations (shear) and defects on the fabric using a specific bench. The specimens were manufactured using the contact molding and tested with several impact energies. The results and measurements made on tested specimens were compared to those of the healthy material. The results showed that the buckle defects have a negative effect on elastic parameters and revealed a larger damage with significant out-of-plane mode relatively to the healthy composite material. This effect is the consequence of a local fiber impoverishment and a disorganization of the fibrous network, with a reorientation of the fibers following the out-of-plane buckling of the yarns, in the area where the defects are located. For the material with calibrated shear of the reinforcement, the increased local fiber rate due to the shear deformations and the contribution to stiffness of the transverse yarns led to an increase in mechanical properties.

Keywords: Defects, forming, impact, induced properties, textiles.

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Authors: Chad A. Long

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The United States military is now commonly responding to complex humanitarian emergencies and natural disasters around the world. From catastrophic earthquakes in Haiti to typhoons devastating the Philippines, U.S. military assistance is requested when the event exceeds the local government's ability to assist the population. This study assesses the characteristics of catastrophes that surpass a nation’s individual ability to respond and recover from the event. The paper begins with a historical summary of military aid and then analyzes over 40 years of the United States military humanitarian response. Over 300 military operations were reviewed and coded based on the nature of the disaster. This in-depth study reviewed the U.S. military’s deployment events for cyclones and earthquakes to determine the strength of the natural disaster requiring external assistance. The climatological data for cyclone landfall and magnitude data for earthquake epicenters were identified, grouped into regions and analyzed for time-based trends. The results showed that foreign countries will likely request the U.S. military for cyclones with speeds greater or equal to 125 miles an hour and earthquakes at the magnitude of 7.4 or higher. These results of this study will assist the geographic combatant commands in determining future military response requirements.

Keywords: Cyclones, earthquakes, natural disasters, military.

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Authors: Saeed Sedighizadeh, Abbas Mansoori, Mohammad Reza Pirestani, Davoud Sedighizadeh

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The usual method of river flow diversion involves construction of tunnels and cofferdams. Given the fact that the cost of diversion works could be as high as 10-20% of the total dam construction cost, due attention should be paid to optimum design of the diversion works. The cost of diversion works depends, on factors, such as: the tunnel dimensions and the intended tunneling support measures during and after excavation; quality and characterizes of the rock through which the tunnel should be excavated; the dimensions of the upstream (and downstream) cofferdams; and the magnitude of river flood the system is designed to divert. In this paper by use of the cost of unit prices for tunnel excavation, tunnel lining, tunnel support (rock bolt + shotcrete) and cofferdam fill the cost function was determined. The function is then minimized by the aid of PSO Algorithm (particle swarm optimization). It is found that the optimum diameter and the total diversion cost are directly related to the river flood discharge (Q). It has also shown that in addition to optimum diameter design discharge (Q), river length, tunnel length, is mainly a function of the ratios (not the absolute values) of the unit prices and does not depend on the overall price levels in the respective country. The results of optimization use in some of the case study lead us to significant changes in the cost.

Keywords: Diversion Tunnel, Optimization, PSO Algorithm

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Authors: Y. Harold Robinson, M. Rajaram, E. Golden Julie, S. Balaji

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In wireless sensor networks, locality and positioning information can be captured using Global Positioning System (GPS). This message can be congregated initially from spot to identify the system. Users can retrieve information of interest from a wireless sensor network (WSN) by injecting queries and gathering results from the mobile sink nodes. Routing is the progression of choosing optimal path in a mobile network. Intermediate node employs permutation of device nodes into teams and generating cluster heads that gather the data from entity cluster’s node and encourage the collective data to base station. WSNs are widely used for gathering data. Since sensors are power-constrained devices, it is quite vital for them to reduce the power utilization. A tree-based data fusion clustering routing algorithm (TBDFC) is used to reduce energy consumption in wireless device networks. Here, the nodes in a tree use the cluster formation, whereas the elevation of the tree is decided based on the distance of the member nodes to the cluster-head. Network simulation shows that this scheme improves the power utilization by the nodes, and thus considerably improves the lifetime.

Keywords: WSN, TBDFC, LEACH, PEGASIS, TREEPSI.

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Authors: Rudolf Egger

Abstract:

This paper explores the relationships between the basic learning processes of leading trade union workers and their methods for coping with the changes in the life-courses of societies today. It will discuss the fragile discourse on lifelong learning in trade unions and the “production of self-techniques” to get in touch with the new economic forms. On the basis of an empirical project, different processes of the socialization of leading trade union workers will be analysed to discover the consequences of the lifelong learning discourse. The results show what competences they need to develop for the “wider benefits of negotiations”. The main challenge remains to make visible how deeply intertwined trade union learning and education are with development in an ongoing dynamic economic process, rather than a quick-fix injection of skills and information. There is a complex relationship existing between the three ‘partners’, work, learning and society forming. The author suggests that contemporary trade unions could be trendsetters who make their own learning agendas by drawing less on formal education and more on informal and non-formal learning contexts. This is in parallel with growing political and scientific consciousness of the need to arrive at new educational/vocational policies and practices.

Keywords: Lifelong learning, Trade unions, Non-formal learning, Educational/vocational policies.

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Authors: A. Tellaeche, X. P. Burgos-Artizzu, G. Pajares, A. Ribeiro

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One important objective in Precision Agriculture is to minimize the volume of herbicides that are applied to the fields through the use of site-specific weed management systems. In order to reach this goal, two major factors need to be considered: 1) the similar spectral signature, shape and texture between weeds and crops; 2) the irregular distribution of the weeds within the crop's field. This paper outlines an automatic computer vision system for the detection and differential spraying of Avena sterilis, a noxious weed growing in cereal crops. The proposed system involves two processes: image segmentation and decision making. Image segmentation combines basic suitable image processing techniques in order to extract cells from the image as the low level units. Each cell is described by two area-based attributes measuring the relations among the crops and the weeds. From these attributes, a hybrid decision making approach determines if a cell must be or not sprayed. The hybrid approach uses the Support Vector Machines and the Fuzzy k-Means methods, combined through the fuzzy aggregation theory. This makes the main finding of this paper. The method performance is compared against other available strategies.

Keywords: Fuzzy k-Means, Precision agriculture, SupportVectors Machines, Weed detection.

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Authors: E. Bruno, F. Lacarbonara, M. C. Placentino, D. Gramegna

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Environmental decision making, particularly about hazardous waste management, is inherently exposed to a high potential conflict, principally because of the trade-off between sociopolitical, environmental, health and economic factors. The need to plan complex contexts has led to an increasing request for decision analytic techniques as support for the decision process. In this work, alternative systems of asbestos-containing waste management (ACW) in Puglia (Southern Italy) were explored by a multi-criteria decision analysis. In particular, through Analytic Hierarchy Process five alternatives management have been compared and ranked according to their performance and efficiency, taking into account environmental, health and socio-economic aspects. A separated valuation has been performed for different temporal scale. For short period results showed a narrow deviation between the disposal alternatives “mono-material landfill in public quarry" and “dedicate cells in existing landfill", with the best performance of the first one. While for long period “treatment plant to eliminate hazard from asbestos-containing waste" was prevalent, although high energy demand required to achieve the change of crystalline structure. A comparison with results from a participative approach in valuation process might be considered as future development of method application to ACW management.

Keywords: Multi-criteria decision analysis, Hazardous wastemanagement, Asbestos.

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Authors: Suhadiyana Hanapi, Alhassan Salami Tijani, W. A. N Wan Mohamed

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In this paper, a prototype PEM fuel cell vehicle integrated with a 1 kW air-blowing proton exchange membrane fuel cell (PEMFC) stack as a main power sources has been developed for a lightweight cruising vehicle. The test vehicle is equipped with a PEM fuel cell system that provides electric power to a brushed DC motor. This vehicle was designed to compete with industrial lightweight vehicle with the target of consuming least amount of energy and high performance. Individual variations in driving style have a significant impact on vehicle energy efficiency and it is well established from the literature. The primary aim of this study was to assesses the power and fuel consumption of a hydrogen fuel cell vehicle operating at three difference driving technique (i.e. 25 km/h constant speed, 22-28 km/h speed range, 20-30 km/h speed range). The goal is to develop the best driving strategy to maximize performance and minimize fuel consumption for the vehicle system. The relationship between power demand and hydrogen consumption has also been discussed. All the techniques can be evaluated and compared on broadly similar terms. Automatic intelligent controller for driving prototype fuel cell vehicle on different obstacle while maintaining all systems at maximum efficiency was used. The result showed that 25 km/h constant speed was identified for optimal driving with less fuel consumption.

Keywords: Prototype fuel cell electric vehicles, energy efficient, control/driving technique, fuel economy.

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Authors: V.S.Kale, S.R.Bhide, P.P.Bedekar, G.V.K.Mohan

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The protection of parallel transmission lines has been a challenging task due to mutual coupling between the adjacent circuits of the line. This paper presents a novel scheme for detection and classification of faults on parallel transmission lines. The proposed approach uses combination of wavelet transform and neural network, to solve the problem. While wavelet transform is a powerful mathematical tool which can be employed as a fast and very effective means of analyzing power system transient signals, artificial neural network has a ability to classify non-linear relationship between measured signals by identifying different patterns of the associated signals. The proposed algorithm consists of time-frequency analysis of fault generated transients using wavelet transform, followed by pattern recognition using artificial neural network to identify the type of the fault. MATLAB/Simulink is used to generate fault signals and verify the correctness of the algorithm. The adaptive discrimination scheme is tested by simulating different types of fault and varying fault resistance, fault location and fault inception time, on a given power system model. The simulation results show that the proposed scheme for fault diagnosis is able to classify all the faults on the parallel transmission line rapidly and correctly.

Keywords: Artificial neural network, fault detection and classification, parallel transmission lines, wavelet transform.

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Authors: Jaydip M. Desai, Antonio Valdevit, Arthur Ritter

Abstract:

Robotic surgery is used to enhance minimally invasive surgical procedure. It provides greater degree of freedom for surgical tools but lacks of haptic feedback system to provide sense of touch to the surgeon. Surgical robots work on master-slave operation, where user is a master and robotic arms are the slaves. Current, surgical robots provide precise control of the surgical tools, but heavily rely on visual feedback, which sometimes cause damage to the inner organs. The goal of this research was to design and develop a realtime Simulink based robotic system to study force feedback mechanism during instrument-object interaction. Setup includes three VelmexXSlide assembly (XYZ Stage) for three dimensional movement, an end effector assembly for forceps, electronic circuit for four strain gages, two Novint Falcon 3D gaming controllers, microcontroller board with linear actuators, MATLAB and Simulink toolboxes. Strain gages were calibrated using Imada Digital Force Gauge device and tested with a hard-core wire to measure instrument-object interaction in the range of 0-35N. Designed Simulink model successfully acquires 3D coordinates from two Novint Falcon controllers and transfer coordinates to the XYZ stage and forceps. Simulink model also reads strain gages signal through 10-bit analog to digital converter resolution of a microcontroller assembly in real time, converts voltage into force and feedback the output signals to the Novint Falcon controller for force feedback mechanism. Experimental setup allows user to change forward kinematics algorithms to achieve the best-desired movement of the XYZ stage and forceps. This project combines haptic technology with surgical robot to provide sense of touch to the user controlling forceps through machine-computer interface.

Keywords: Haptic feedback, MATLAB, Simulink, Strain Gage, Surgical Robot.

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Authors: Anukriti Kumar, Tanmay Singh, Dinesh Kumar Vishwakarma

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Traffic control has been one of the most common and irritating problems since the time automobiles have hit the roads. Problems like traffic congestion have led to a significant time burden around the world and one significant solution to these problems can be the proper implementation of the Intelligent Transport System (ITS). It involves the integration of various tools like smart sensors, artificial intelligence, position technologies and mobile data services to manage traffic flow, reduce congestion and enhance driver's ability to avoid accidents during adverse weather. Road and traffic signs’ recognition is an emerging field of research in ITS. Classification problem of traffic signs needs to be solved as it is a major step in our journey towards building semi-autonomous/autonomous driving systems. The purpose of this work focuses on implementing an approach to solve the problem of traffic sign classification by developing a Convolutional Neural Network (CNN) classifier using the GTSRB (German Traffic Sign Recognition Benchmark) dataset. Rather than using hand-crafted features, our model addresses the concern of exploding huge parameters and data method augmentations. Our model achieved an accuracy of around 97.6% which is comparable to various state-of-the-art architectures.

Keywords: Multiclass classification, convolution neural network, OpenCV, Data Augmentation.

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Authors: Ching-Feng Chen, Shih-Kai Chen

Abstract:

The Floating Photovoltaic (FPV) system highlights economic benefits and energy performance to carbon dioxide (CO2) discharges. Due to land resource scarcity and many negligent water territories, such as reservoirs, dams, and lakes in Japan and Taiwan, both countries are actively developing FPV and responding to the pricing of the emissions trading systems (ETS). This paper performs a case study through a synthesis approach to compare the economic indicators between the FPVs of Taiwan’s Agongdian Reservoir and Japan’s Yamakura Dam. The research results show that the metrics of the system capacity, installation costs, bank interest rates, and ETS and Electricity Bills affect FPV operating gains. In the post-Feed-In-Tariff (FIT) phase, investing in FPV in Japan is more profitable than in Taiwan. The former’s positive net present value (NPV), eminent internal rate of return (IRR) (11.6%), and benefit-cost ratio (BCR) above 1 (2.0) at the discount rate of 10% indicate that investing the FPV in Japan is more favorable than in Taiwan. In addition, the breakeven point is modest (about 61.3%). The presented methodology in the study helps investors evaluate schemes’ pros and cons and determine whether a decision is beneficial while funding PV or FPV projects.

Keywords: Carbon Border Adjustment Mechanism, Floating Photovoltaic, Emissions Trading Systems, Net Present Value, NPV, Internal Rate of Return, IRR, Benefit-Cost Ratio.

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Authors: Gökçen A. Çiftçioğlu, M. A. Neşet Kadırgan, Figen Kadırgan

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Solar energy, since it is available every day, is seen as one of the most valuable renewable energy resources. Thus, the energy of sun should be efficiently used in various applications. The most known applications that use solar energy are heating water and spaces. High efficiency solar collectors need appropriate selective surfaces to absorb the heat. Selective surfaces (Selektif-Sera) used in this study are applied to flat collectors, which are produced by a roll to roll cost effective coating of nano nickel layers, developed in Selektif Teknoloji Co. Inc. Efficiency of flat collectors using Selektif-Sera absorbers are calculated in collaboration with Institute for Solar Technik Rapperswil, Switzerland. The main cause of high energy consumption in industry is mostly caused from low temperature level processes. There is considerable effort in research to minimize the energy use by renewable energy sources such as solar energy. A feasibility study will be presented to obtain the potential of solar thermal energy utilization in the textile industry using these solar collectors. For the feasibility calculations presented in this study, textile dyeing and finishing factory located at Kahramanmaras is selected since the geographic location was an important factor. Kahramanmaras is located in the south east part of Turkey thus has a great potential to have solar illumination much longer. It was observed that, the collector area is limited by the available area in the factory, thus a hybrid heating generating system (lignite/solar thermal) was preferred in the calculations of this study to be more realistic. During the feasibility work, the calculations took into account the preheating process, where well waters heated from 15 °C to 30-40 °C by using the hot waters in heat exchangers. Then the preheated water was heated again by high efficiency solar collectors. Economic comparison between the lignite use and solar thermal collector use was provided to determine the optimal system that can be used efficiently. The optimum design of solar thermal systems was studied depending on the optimum collector area. It was found that the solar thermal system is more economic and efficient than the merely lignite use. Return on investment time is calculated as 5.15 years.

Keywords: Solar energy, heating, solar heating.

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Authors: Rabab M. Ramadan, Elaraby A. Elgallad

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With extensive application, the performance of unimodal biometrics systems has to face a diversity of problems such as signal and background noise, distortion, and environment differences. Therefore, multimodal biometric systems are proposed to solve the above stated problems. This paper introduces a bimodal biometric recognition system based on the extracted features of the human palm print and iris. Palm print biometric is fairly a new evolving technology that is used to identify people by their palm features. The iris is a strong competitor together with face and fingerprints for presence in multimodal recognition systems. In this research, we introduced an algorithm to the combination of the palm and iris-extracted features using a texture-based descriptor, the Scale Invariant Feature Transform (SIFT). Since the feature sets are non-homogeneous as features of different biometric modalities are used, these features will be concatenated to form a single feature vector. Particle swarm optimization (PSO) is used as a feature selection technique to reduce the dimensionality of the feature. The proposed algorithm will be applied to the Institute of Technology of Delhi (IITD) database and its performance will be compared with various iris recognition algorithms found in the literature.

Keywords: Iris recognition, particle swarm optimization, feature extraction, feature selection, palm print, scale invariant feature transform.

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Authors: L. Grinis

Abstract:

Turbulent flow in complex geometries receives considerable attention due to its importance in many engineering applications. It has been the subject of interest for many researchers. Some of these interests include the design of storm water channels. The design of these channels requires testing through physical models. The main practical limitation of physical models is the so called “scale effect”, that is, the fact that in many cases only primary physical mechanisms can be correctly represented, while secondary mechanisms are often distorted. These observations form the basis of our study, which centered on problems associated with the design of storm water channels near the Dead Sea, in Israel. To help reach a final design decision we used different physical models. Our research showed good coincidence with the results of laboratory tests and theoretical calculations, and allowed us to study different effects of fluid flow in an open channel. We determined that problems of this nature cannot be solved only by means of theoretical calculation and computer simulation. This study demonstrates the use of physical models to help resolve very complicated problems of fluid flow through baffles and similar structures. The study applies these models and observations to different construction and multiphase water flows, among them, those that include sand and stone particles, a significant attempt to bring to the testing laboratory a closer association with reality.

Keywords: Baffles, open channel, physical modeling.

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Authors: Dasom Kim, Chen Liu, Myungsu Lim, Soo-Hyeon Jeon, Byeoung Kug Jeon, Kee-Young Kwahk, Namgyu Kim

Abstract:

Recently, numerous documents including large volumes of unstructured data and text have been created because of the rapid increase in the use of social media and the Internet. Usually, these documents are categorized for the convenience of users. Because the accuracy of manual categorization is not guaranteed, and such categorization requires a large amount of time and incurs huge costs. Many studies on automatic categorization have been conducted to help mitigate the limitations of manual categorization. Unfortunately, most of these methods cannot be applied to categorize complex documents with multiple topics because they work on the assumption that individual documents can be categorized into single categories only. Therefore, to overcome this limitation, some studies have attempted to categorize each document into multiple categories. However, the learning process employed in these studies involves training using a multi-categorized document set. These methods therefore cannot be applied to the multi-categorization of most documents unless multi-categorized training sets using traditional multi-categorization algorithms are provided. To overcome this limitation, in this study, we review our novel methodology for extending the category of a single-categorized document to multiple categorizes, and then introduce a survey-based verification scenario for estimating the accuracy of our automatic categorization methodology.

Keywords: Big Data Analysis, Document Classification, Text Mining, Topic Analysis.

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Authors: Vikas Tewari, Shivendra Tewari, K. R. Pardasani

Abstract:

Calcium is a vital second messenger used in signal transduction. Calcium controls secretion, cell movement, muscular contraction, cell differentiation, ciliary beating and so on. Two theories have been used to simplify the system of reaction-diffusion equations of calcium into a single equation. One is excess buffer approximation (EBA) which assumes that mobile buffer is present in excess and cannot be saturated. The other is rapid buffer approximation (RBA), which assumes that calcium binding to buffer is rapid compared to calcium diffusion rate. In the present work, attempt has been made to develop a model for calcium diffusion under excess buffer approximation in neuron cells. This model incorporates the effect of [Na+] influx on [Ca2+] diffusion,variable calcium and sodium sources, sodium-calcium exchange protein, Sarcolemmal Calcium ATPase pump, sodium and calcium channels. The proposed mathematical model leads to a system of partial differential equations which have been solved numerically using Forward Time Centered Space (FTCS) approach. The numerical results have been used to study the relationships among different types of parameters such as buffer concentration, association rate, calcium permeability.

Keywords: Excess buffer approximation, Na+ influx, sodium calcium exchange protein, sarcolemmal calcium atpase pump, forward time centred space.

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Authors: H. Al-Jabli

Abstract:

Using the freeze-melting process for the disposing of high saline brines was the aim of the paper by confirming the performance estimation of the treatment system. A laboratory bench scale freezing technique test unit was designed, constructed, and tested at Doha Research Plant (DRP) in Kuwait. The principal unit operations that have been considered for the laboratory study are: ice crystallization, separation, washing, and melting. The applied process is characterized as “the secondary-refrigerant indirect freezing”, which is utilizing normal freezing concept. The high saline brine was used as definite feed water, i.e. average TDS of 250,000 ppm. Kuwait desalination plants were carried out in the experimental study to measure the performance of the proposed treatment system. Experimental analysis shows that the freeze-melting process is capable of dropping the TDS of the feed water from 249,482 ppm to 56,880 ppm of the freeze-melting process in the two-phase’s course, whereas overall recovery results of the salt passage and salt rejection are 31.11%, 19.05%, and 80.95%, correspondingly. Therefore, the freeze-melting process is encouraging for the proposed application, as it shows on the results, which approves the process capability of reducing a major amount of the dissolved salts of the high saline brine with reasonable sensible recovery. This process might be reasonable with other brine disposal processes.

Keywords: High saline brine, freeze-melting process, ice crystallization, brine disposal process.

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Authors: Wilayat Ali, Li Sheng, Waleed Ahmed

Abstract:

The ability of the robot to make simultaneously map of the environment and localize itself with respect to that environment is the most important element of mobile robots. To solve SLAM many algorithms could be utilized to build up the SLAM process and SLAM is a developing area in Robotics research. Robot Operating System (ROS) is one of the frameworks which provide multiple algorithm nodes to work with and provide a transmission layer to robots. Manyof these algorithms extensively in use are Hector SLAM, Gmapping and Cartographer SLAM. This paper describes a ROS-based Simultaneous localization and mapping (SLAM) library Google Cartographer mapping, which is open-source algorithm. The algorithm was applied to create a map using laser and pose data from 2d Lidar that was placed on a mobile robot. The model robot uses the gazebo package and simulated in Rviz. Our research work's primary goal is to obtain mapping through Cartographer SLAM algorithm in a static indoor environment. From our research, it is shown that for indoor environments cartographer is an applicable algorithm to generate 2d maps with LIDAR placed on mobile robot because it uses both odometry and poses estimation. The algorithm has been evaluated and maps are constructed against the SLAM algorithms presented by Turtlebot2 in the static indoor environment.

Keywords: SLAM, ROS, navigation, localization and mapping, Gazebo, Rviz, Turtlebot2, SLAM algorithms, 2d Indoor environment, Cartographer.

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Authors: S. Z. Moussavi, A. Badri, F. Rastegar Kashkooli

Abstract:

Wind farms (WFs) with high level of penetration are being established in power systems worldwide more rapidly than other renewable resources. The Independent System Operator (ISO), as a policy maker, should propose appropriate places for WF installation in order to maximize the benefits for the investors. There is also a possibility of congestion relief using the new installation of WFs which should be taken into account by the ISO when proposing the locations for WF installation. In this context, efficient wind farm (WF) placement method is proposed in order to reduce burdens on congested lines. Since the wind speed is a random variable and load forecasts also contain uncertainties, probabilistic approaches are used for this type of study. AC probabilistic optimal power flow (P-OPF) is formulated and solved using Monte Carlo Simulations (MCS). In order to reduce computation time, point estimate methods (PEM) are introduced as efficient alternative for time-demanding MCS. Subsequently, WF optimal placement is determined using generation shift distribution factors (GSDF) considering a new parameter entitled, wind availability factor (WAF). In order to obtain more realistic results, N-1 contingency analysis is employed to find the optimal size of WF, by means of line outage distribution factors (LODF). The IEEE 30-bus test system is used to show and compare the accuracy of proposed methodology.

Keywords: Probabilistic optimal power flow, Wind power, Pointestimate methods, Congestion management

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Authors: T Rusu, P I Moraru, I Bogdan, A I Pop, M L Sopterean

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The paper presents the influence of the conventional ploughing tillage technology in comparison with the minimum tillage, upon the soil properties, weed control and yield in the case of maize (Zea mays L.), soya-bean (Glycine hispida L.) and winter wheat (Triticum aestivum L.) in a three years crop rotation. A research has been conducted at the University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca, Romania. The use of minimum soil tillage systems within a three years rotation: maize, soya-bean, wheat favorites the rise of the aggregates hydro stability with 5.6-7.5% on a 0-20 cm depth and 5-11% on 20-30 cm depth. The minimum soil tillage systems – paraplow, chisel or rotary grape – are polyvalent alternatives for basic preparation, germination bed preparation and sowing, for fields and crops with moderate loose requirements being optimized technologies for: soil natural fertility activation and rationalization, reduction of erosion, increasing the accumulation capacity for water and realization of sowing in the optimal period. The soil tillage system influences the productivity elements of cultivated species and finally the productions thus obtained. Thus, related to conventional working system, the productions registered in minimum tillage working represented 89- 97% in maize, 103-112% in soya-bean, 93-99% in winter-wheat. The results of investigations showed that the yield is a conclusion soil tillage systems influence on soil properties, plant density assurance and on weed control. Under minimum tillage systems in the case of winter weat as an option for replacing classic ploughing, the best results in terms of quality indices were obtained from version worked with paraplow, followed by rotary harrow and chisel. At variants worked with paraplow were obtained quality indices close to those of the variant worked with plow, and protein and gluten content was even higher. At Ariesan variety, highest protein content, 12.50% and gluten, 28.6% was obtained for the variant paraplow.

Keywords: Minimum tillage, soil properties, yields quality.

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Authors: Pinki Sharma, Himanshu Joshi

Abstract:

Distillery spentwash contains high chemical oxygen demand (COD), biological oxygen demand (BOD), color, total dissolved solids (TDS) and other contaminants even after biological treatment. The effluent can’t be discharged as such in the surface water bodies or land without further treatment. Reverse osmosis (RO) treatment plants have been installed in many of the distilleries at tertiary level in many of the distilleries in India, but are not properly working due to fouling problem which is caused by the presence of high concentration of organic matter and other contaminants in biologically treated spentwash. In order to make the membrane treatment a proven and reliable technology, proper pre-treatment is mandatory. In the present study, ultra-filtration (UF) for pretreatment of RO at tertiary stage has been performed. Operating parameters namely initial pH (pHo: 2–10), trans-membrane pressure (TMP: 4-20 bars) and temperature (T: 15-43°C) were used for conducting experiments with UF system. Experiments were optimized at different operating parameters in terms of COD, color, TDS and TOC removal by using response surface methodology (RSM) with central composite design. The results showed that removal of COD, color and TDS was 62%, 93.5% and 75.5% respectively, with UF, at optimized conditions with increased permeate flux from 17.5 l/m2/h (RO) to 38 l/m2/h (UF-RO). The performance of the RO system was greatly improved both in term of pollutant removal as well as water recovery.

Keywords: Bio-digested distillery spentwash, reverse osmosis, Response surface methodology, ultra-filtration.

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Authors: G. R. Nouri, H. Imani Kalesar, Zahra Ameli

Abstract:

Chevron frames (Inverted-V-braced frames or Vbraced frames) have seismic disadvantages, such as not good exhibit force redistribution capability and compression brace buckles immediately. Researchers developed new design provisions on increasing both the ductility and lateral resistance of these structures in seismic areas. One of these new methods is adding zipper columns, as proposed by Khatib et al. (1988) [2]. Zipper columns are vertical members connecting the intersection points of the braces above the first floor. In this paper applicability of the suspended zipper system to Seismic Rehabilitation of Steel Structures is investigated. The models are 3-, 6-, 9-, and 12-story Inverted-V-braced frames. In this case, it is assumed that the structures must be rehabilitated. For rehabilitation of structures, zipper column is used. The result of researches showed that the suspended zipper system is effective in case of 3-, 6-, and 9-story Inverted-V-braced frames and it would increase lateral resistance of structure up to life safety level. But in case of high-rise buildings (such as 12 story frame), it doesn-t show good performance. For solving this problem, the braced bay can consist of small “units" over the height of the entire structure, which each of them is a zipper-braced bay with a few stories. By using this method the lateral resistance of 12 story Inverted-V-braced frames is increased up to safety life level.

Keywords: chevron-braced frames, suspended zipper frames, zipper frames, zipper columns

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Authors: Helia Barzegar Sedigh, Farzaneh Hamedi, Payam Ashtari

Abstract:

There are some limitations in common structural systems, such as providing appropriate lateral stiffness, adequate ductility, and architectural openings at the same time. Consequently, the concept of T-Resisting Frame (TRF) has been introduced to overcome all these deficiencies. The configuration of TRF in this study is a Vertical Plate Girder (VPG) which is placed within the span and two Horizontal Plate Girders (HPGs) connect VPG to side columns at each story level by the use of rigid connections. System performance is improved by utilizing rigid connections in side columns base joint. Shear yield of HPGs causes energy dissipation in TRF; therefore, high plastic deformation in web of HPGs and VPG affects the ductility of system. Moreover, in order to prevent shear buckling in web of TRF’s members and appropriate criteria for placement of web stiffeners are applied. In this paper, an experimental study is conducted by applying cyclic loading and using finite element models and numerical studies such as push over method are assessed on shear and flexural yielding of HPGs. As a result, seismic parameters indicate adequate lateral stiffness, and high ductility factor of 6.73, and HPGs’ shear yielding achieved as a proof of TRF’s better performance.

Keywords: Experimental study, finite element model, flexural and shear yielding, T-resisting frame.

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Authors: Mona Soliman Habib

Abstract:

This paper explores the scalability issues associated with solving the Named Entity Recognition (NER) problem using Support Vector Machines (SVM) and high-dimensional features. The performance results of a set of experiments conducted using binary and multi-class SVM with increasing training data sizes are examined. The NER domain chosen for these experiments is the biomedical publications domain, especially selected due to its importance and inherent challenges. A simple machine learning approach is used that eliminates prior language knowledge such as part-of-speech or noun phrase tagging thereby allowing for its applicability across languages. No domain-specific knowledge is included. The accuracy measures achieved are comparable to those obtained using more complex approaches, which constitutes a motivation to investigate ways to improve the scalability of multiclass SVM in order to make the solution more practical and useable. Improving training time of multi-class SVM would make support vector machines a more viable and practical machine learning solution for real-world problems with large datasets. An initial prototype results in great improvement of the training time at the expense of memory requirements.

Keywords: Named entity recognition, support vector machines, language independence, bioinformatics.

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Authors: A. Faro, D. Giordano, F. Maiorana

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Data mining uses a variety of techniques each of which is useful for some particular task. It is important to have a deep understanding of each technique and be able to perform sophisticated analysis. In this article we describe a tool built to simulate a variation of the Kohonen network to perform unsupervised clustering and support the entire data mining process up to results visualization. A graphical representation helps the user to find out a strategy to optimize classification by adding, moving or delete a neuron in order to change the number of classes. The tool is able to automatically suggest a strategy to optimize the number of classes optimization, but also support both tree classifications and semi-lattice organizations of the classes to give to the users the possibility of passing from one class to the ones with which it has some aspects in common. Examples of using tree and semi-lattice classifications are given to illustrate advantages and problems. The tool is applied to classify macroeconomic data that report the most developed countries- import and export. It is possible to classify the countries based on their economic behaviour and use the tool to characterize the commercial behaviour of a country in a selected class from the analysis of positive and negative features that contribute to classes formation. Possible interrelationships between the classes and their meaning are also discussed.

Keywords: Unsupervised classification, Kohonen networks, macroeconomics, Visual data mining, Cluster interpretation.

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Authors: Mohammad Koushafar, Amir Hossein Khoshgoftarmanesh

Abstract:

Due to water shortage, application of saline water for irrigation is an urgent in agriculture. In this study the effect of calcium and potassium application as additive in saline root media for reduce salinity adverse effects was investigated on tomato growth in a hydroponic system with unequal distribution of salts in the root media, which was divided in to two equal parts containing full Johnson nutrient solution and 40 mMNaCl solution, alone or in combination with KCl (6 mM), CaCl2 (4 mM), K+Ca (3+2 mM) or half-strength Johnson nutrient solution. The root splits were exchanged every 7 days. Results showed that addition of calcium, calcium-potassium and nutrition elements equivalent to half the concentration of Johnson formula to the saline-half of culture media minimized the reduction in plant growth caused by NaCl, although addition of potassium to culture media wasn’t effective. The greatest concentration of sodium was observed at the shoot of treatments which had smallest growth. According to the results of this study, in case of dynamic and non-uniform distribution of salts in the root media, by addition of additive to the saline solution, it would be possible to use of saline water with no significant growth reduction.

Keywords: Calcium, Hydroponic, Local salinity, Potassium, Saline water, Tomato.

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Authors: S. Panda, J. S. Yadav, N. P. Patidar, C. Ardil

Abstract:

Recently, genetic algorithms (GA) and particle swarm optimization (PSO) technique have attracted considerable attention among various modern heuristic optimization techniques. The GA has been popular in academia and the industry mainly because of its intuitiveness, ease of implementation, and the ability to effectively solve highly non-linear, mixed integer optimization problems that are typical of complex engineering systems. PSO technique is a relatively recent heuristic search method whose mechanics are inspired by the swarming or collaborative behavior of biological populations. In this paper both PSO and GA optimization are employed for finding stable reduced order models of single-input- single-output large-scale linear systems. Both the techniques guarantee stability of reduced order model if the original high order model is stable. PSO method is based on the minimization of the Integral Squared Error (ISE) between the transient responses of original higher order model and the reduced order model pertaining to a unit step input. Both the methods are illustrated through numerical example from literature and the results are compared with recently published conventional model reduction technique.

Keywords: Genetic Algorithm, Particle Swarm Optimization, Order Reduction, Stability, Transfer Function, Integral Squared Error.

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Authors: Nino Abesadze, Marine Mindorashvili, Nino Paresashvili

Abstract:

At present actual tourism indicators cannot be calculated in Georgia, making it impossible to perform their quantitative analysis. Therefore, the study conducted by us is highly important from a theoretical as well as practical standpoint. The main purpose of the article is to make complex statistical analysis of tourist expenses of foreign visitors and to calculate statistical attractiveness indices of the tourism potential of Georgia. During the research, the method involving random and proportional selection has been applied. Computer software SPSS was used to compute statistical data for corresponding analysis. Corresponding methodology of tourism statistics was implemented according to international standards. Important information was collected and grouped from major Georgian airports, and a representative population of foreign visitors and a rule of selection of respondents were determined. The results show a trend of growth in tourist numbers and the share of tourists from post-soviet countries are constantly increasing. The level of satisfaction with tourist facilities and quality of service has improved, but still we have a problem of disparity between the service quality and the prices. The design of tourist expenses of foreign visitors is diverse; competitiveness of tourist products of Georgian tourist companies is higher. Attractiveness of popular cities of Georgia has increased by 43%.

Keywords: Tourist, expenses, indexes, statistics, analysis.

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