Search results for: optical model parameters

Authors: Hamze Torabian, Mohammad Mehrabioun Mohammadi

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Like many other industries, the payment industry has been affected by digital transformation. The importance of digital transformation in the payment industry is very crucial. Because the payment industry is considered a leading industry in digital and emerging technologies, and the digitalization of other industries such as retail, health, and telecommunication, it also depends on the growth rate of digitalized payment systems. One of the technological innovations in service management is Field Service Management (FSM). Despite the widespread use of FSM in various industries such as petrochemical, health, maintenance, etc., this technology can also be recruited in the payment industry, transforming the payment industry into a more agile and efficient one. Accordingly, the present study pays close attention to the application of FSM in the payment industry. Given the importance of merchants' bargaining power in the payment industry, this study aims to use FSM in the digital transformation initiative with a targeted focus on providing real-time services to merchants. The research method consists of three parts. Firstly, conducting the review of past research, applications of FSM in the payment industry are considered. In the next step, merchants' benefits such as emotional, functional, economic, and social benefits in using FSM are identified using in-depth interviews and content analysis methods. The related business model in helping the payment industry transforming into a more agile and efficient industry is considered in the following step. The results revealed the 10 main pillars required to realize the digital transformation of payment systems using FSM.

Keywords: Digital transformation, field service management, merchant support systems, payment industry.

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Authors: Kyekyung Kim, Sangseung Kang, Suyoung Chi, Jaehong Kim

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In recent years, IT convergence technology has been developed to get creative solution by combining robotics or sports science technology. Object detection and recognition have mainly applied to sports science field that has processed by recognizing face and by tracking human body. But object detection and recognition using vision sensor is challenge task in real world because of illumination. In this paper, object detection and recognition using vision sensor applied to sports simulator has been introduced. Face recognition has been processed to identify user and to update automatically a person athletic recording. Human body has tracked to offer a most accurate way of riding horse simulator. Combined image processing has been processed to reduce illumination adverse affect because illumination has caused low performance in detection and recognition in real world application filed. Face has recognized using standard face graph and human body has tracked using pose model, which has composed of feature nodes generated diverse face and pose images. Face recognition using Gabor wavelet and pose recognition using pose graph is robust to real application. We have simulated using ETRI database, which has constructed on horse riding simulator.

Keywords: Horse riding simulator, Object detection, Object recognition, User identification, Pose recognition.

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Authors: Nasim Fallahi, Erasmo Carrera, Alfonso Pagani

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Variable angle tow describes the fibres which are curvilinearly steered in a composite lamina. Significantly, stiffness tailoring freedom of VAT composite laminate can be enlarged and enabled. Composite structures with curvilinear fibres have been shown to improve the buckling load carrying capability in contrast with the straight laminate composites. However, the optimal design and analysis of VAT are faced with high computational efforts due to the increasing number of variables. In this article, an efficient optimum solution has been used in combination with 1D Carrera’s Unified Formulation (CUF) to investigate the optimum fibre orientation angles for buckling analysis. The particular emphasis is on the LE-based CUF models, which provide a Lagrange Expansions to address a layerwise description of the problem unknowns. The first critical buckling load has been considered under simply supported boundary conditions. Special attention is lead to the sensitivity of buckling load corresponding to the fibre orientation angle in comparison with the results which obtain through the Genetic Algorithm (GA) optimization frame and then Artificial Neural Network (ANN) is applied to investigate the accuracy of the optimized model. As a result, numerical CUF approach with an optimal solution demonstrates the robustness and computational efficiency of proposed optimum methodology.

Keywords: Beam structures, layerwise, optimization, variable angle tow, neural network

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Authors: Amitrajit Sarkar

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The use of Electronic Commerce (EC) technologies enables Small Medium Enterprises (SMEs) to improve their efficiency and competitive position. Much of the literature proposes an extensive set of benefits for organizations that choose to adopt and implement ECommerce systems. Factors of Business –to-business (B2B) E-Commerce adoption and implementation have been extensively investigated. Despite enormous attention given to encourage Small Medium Enterprises (SMEs) to adopt and implement E-Commerce, little research has been carried out in identifying the factors of Business-to-Consumer ECommerce adoption and implementation for SMEs. To conduct the study, Tornatsky and Fleischer model was adopted and tested in four SMEs located in Christchurch, New Zealand. This paper explores the factors that impact the decision and method of adoption and implementation of ECommerce systems in automobile industry. Automobile industry was chosen because the product they deal with i.e. cars are not a common commodity to be sold online, despite this fact the eCommerce penetration in automobile industry is high. The factors that promote adoption and implementation of E-Commerce technologies are discussed, together with the barriers. This study will help SME owners to effectively handle the adoption and implementation process and will also improve the chance of successful E-Commerce implementation. The implications of the findings for managers, consultants, and government organizations engaged in promoting E-Commerce adoption and implementation in small businesses and future research are discussed.

Keywords: E-Commerce in SMEs, E-Commerce in automobile industry, B2C E-Commerce, E-Commerce adoption and Implementation, E-Commerce Website Implementation, E-Commerce Models.

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Authors: Guorong Yan, Subhash Rakheja

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The liquid cargo contained in a partly-filled road tank vehicle is prone to dynamic slosh movement when subjected to external disturbances. The slosh behavior has been identified as a significant factor impairing the safety of liquid cargo transportation. The laboratory experiments have been conducted for analyzing fluid slosh in partly filled tanks. The experiment results measured under forced harmonic excitations reveal the three-dimensional nature of the fluid motion and coupling between the lateral and longitudinal fluid slosh at resonance. Several spectral components are observed for the transient slosh forces, which can be associated with the excitation, resonance, and beat frequencies. The peak slosh forces and moments in the vicinity of resonance are significantly larger than those of the equivalent rigid mass. Due to the nature of coupling between sloshing fluid and vehicle body, the issue of the dynamic fluid-structure interaction is essential in the analysis of tank-vehicle dynamics. A dynamic pitch plane model of a Tridem truck incorporated the fluid slosh dynamics is developed to analyze the fluid-vehicle interaction under the straight-line braking maneuvers. The results show that the vehicle responses are highly associated with the characteristics of fluid slosh force and moment.

Keywords: Braking performance, fluid induced vibration, fluidslosh, fluid structure interaction, tank trucks, vehicle dynamics.

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Authors: Dennis L. Owuor, Okuthe P. Kogeda, Johnson I. Agbinya

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Mobile localization has attracted a great deal of attention recently due to the introduction of wireless networks. Although several localization algorithms and systems have been implemented and discussed in the literature, very few researchers have exploited the gap that exists between indoor localization, tracking, external storage of location information and outdoor localization for the purpose of digital forensics during and after a disaster. The contribution of this paper lies in the implementation of a robust system that is capable of locating, tracking mobile device users and store location information for both indoor and partially outdoor the cloud. The system can be used during disaster to track and locate mobile phone users. The developed system is a mobile application built based on Android, Hypertext Preprocessor (PHP), Cascading Style Sheets (CSS), JavaScript and MATLAB for the Android mobile users. Using Waterfall model of software development, we have implemented a three level system that is able to track, locate and store mobile device information in secure database (cloud) on almost a real time basis. The outcome of the study showed that the developed system is efficient with regard to the tracking and locating mobile devices. The system is also flexible, i.e. can be used in any building with fewer adjustments. Finally, the system is accurate for both indoor and outdoor in terms of locating and tracking mobile devices.

Keywords: Indoor localization, waterfall, digital forensics, tracking and cloud.

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Authors: T. Wuttipornpun, U. Wangrakdiskul, W. Songserm

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This paper aims to develop an algorithm of finite capacity material requirement planning (FCMRP) system for a multistage assembly flow shop. The developed FCMRP system has two main stages. The first stage is to allocate operations to the first and second priority work centers and also determine the sequence of the operations on each work center. The second stage is to determine the optimal start time of each operation by using a linear programming model. Real data from a factory is used to analyze and evaluate the effectiveness of the proposed FCMRP system and also to guarantee a practical solution to the user. There are five performance measures, namely, the total tardiness, the number of tardy orders, the total earliness, the number of early orders, and the average flow-time. The proposed FCMRP system offers an adjustable solution which is a compromised solution among the conflicting performance measures. The user can adjust the weight of each performance measure to obtain the desired performance. The result shows that the combination of FCMRP NP3 and EDD outperforms other combinations in term of overall performance index. The calculation time for the proposed FCMRP system is about 10 minutes which is practical for the planners of the factory.

Keywords: Material requirement planning, Finite capacity, Linear programming, Permutation, Application in industry.

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Authors: Kazuhisa Koda, Tsutomu Kobayashi

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Laura Island, which is located about 50 km away from downtown, is a source of water supply in Majuro atoll, which is the capital of the Republic of the Marshall Islands. Low and flat Majuro atoll has neither river nor lake. It is very important for Majuro atoll to ensure the conservation of its water resources. However, upconing, which is the process of partial rising of the freshwater-saltwater boundary near the water-supply well, was caused by the excess pumping from it during the severe drought in 1998. Upconing will make the water usage of the freshwater lens difficult. Thus, appropriate water usage is required to prevent up coning in the freshwater lens because there is no other water source during drought. Numerical simulation of water usage applying SEAWAT model was conducted at the central part of Laura Island, including the water supply well, which was affected by upconing. The freshwater lens was created as a result of infiltration of consistent average rainfall. The lens shape was almost the same as the one in 1985. 0 of monthly rainfall and variable daily pump discharge were used to calculate the sustainable pump discharge from the water supply well. Consequently, the total amount of pump discharge was increased as the daily pump discharge was increased, indicating that it needs more time to recover from upconing. Thus, a pump standard to reduce the pump intensity is being proposed, which is based on numerical simulation concerning the occurrence of the up-coning phenomenon in Laura Island during the drought.

Keywords: Freshwater lens, islands, numerical simulation, sustainable water use.

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Authors: A. Doaa M. Atia, Faten H. Fahmy, Ninet M. Ahmed, Hassen T. Dorrah

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Temperature is one of the most principle factors affects aquaculture system. It can cause stress and mortality or superior environment for growth and reproduction. This paper presents the control of pond water temperature using artificial intelligence technique. The water temperature is very important parameter for shrimp growth. The required temperature for optimal growth is 34oC, if temperature increase up to 38oC it cause death of the shrimp, so it is important to control water temperature. Solar thermal water heating system is designed to supply an aquaculture pond with the required hot water in Mersa Matruh in Egypt. Neural networks are massively parallel processors that have the ability to learn patterns through a training experience. Because of this feature, they are often well suited for modeling complex and non-linear processes such as those commonly found in the heating system. Artificial neural network is proposed to control water temperature due to Artificial intelligence (AI) techniques are becoming useful as alternate approaches to conventional techniques. They have been used to solve complicated practical problems. Moreover this paper introduces a complete mathematical modeling and MATLAB SIMULINK model for the aquaculture system. The simulation results indicate that, the control unit success in keeping water temperature constant at the desired temperature by controlling the hot water flow rate.

Keywords: artificial neural networks, aquaculture, forced circulation hot water system,

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Authors: Arunesh Chandra, Pankaj Chandna, Surinder Deswal, Rajesh Kumar Mishra, Rajender Kumar

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The arm length, hand length, hand breadth and middle finger length of 1540 right-handed industrial workers of Haryana state was used to assess the relationship between the upper limb dimensions and stature. Initially, the data were analyzed using basic univariate analysis and independent t-tests; then simple and multiple linear regression models were used to estimate stature using SPSS (version 17). There was a positive correlation between upper limb measurements (hand length, hand breadth, arm length and middle finger length) and stature (p < 0.01), which was highest for hand length. The accuracy of stature prediction ranged from ± 54.897 mm to ± 58.307 mm. The use of multiple regression equations gave better results than simple regression equations. This study provides new forensic standards for stature estimation from the upper limb measurements of male industrial workers of Haryana (India). The results of this research indicate that stature can be determined using hand dimensions with accuracy, when only upper limb is available due to any reasons likewise explosions, train/plane crashes, mutilated bodies, etc. The regression formula derived in this study will be useful for anatomists, archaeologists, anthropologists, design engineers and forensic scientists for fairly prediction of stature using regression equations.

Keywords: Anthropometric dimensions, Forensic identification, Industrial workers, Stature prediction.

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Authors: R. Gary Black, Abolhassan Astaneh-Asl

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The International Building Code (IBC) and the  California Building Code (CBC) both recognize four basic types of  steel seismic resistant frames; moment frames, concentrically braced  frames, shear walls and eccentrically braced frames. Based on  specified geometries and detailing, the seismic performance of these  steel frames is well understood. In 2011, the authors designed an  innovative steel braced frame system with tapering members in the  general shape of a branching tree as a seismic retrofit solution to an  existing four story “lift-slab” building. Located in the seismically  active San Francisco Bay Area of California, a frame of this  configuration, not covered by the governing codes, would typically  require model or full scale testing to obtain jurisdiction approval.  This paper describes how the theories, protocols, and code  requirements of eccentrically braced frames (EBFs) were employed  to satisfy the 2009 International Building Code (IBC) and the 2010  California Building Code (CBC) for seismically resistant steel frames  and permit construction of these nonconforming geometries.

 

Keywords: Eccentrically Braced Frame, Lift Slab Construction, Seismic Retrofit, Shear Link, Steel Design.

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Authors: Ons Sassi, Wahiba Ramdane Cherif-Khettaf, Ammar Oulamara

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In this paper, we consider the vehicle routing problem with mixed fleet of conventional and heterogenous electric vehicles and time dependent charging costs, denoted VRP-HFCC, in which a set of geographically scattered customers have to be served by a mixed fleet of vehicles composed of a heterogenous fleet of Electric Vehicles (EVs), having different battery capacities and operating costs, and Conventional Vehicles (CVs). We include the possibility of charging EVs in the available charging stations during the routes in order to serve all customers. Each charging station offers charging service with a known technology of chargers and time dependent charging costs. Charging stations are also subject to operating time windows constraints. EVs are not necessarily compatible with all available charging technologies and a partial charging is allowed. Intermittent charging at the depot is also allowed provided that constraints related to the electricity grid are satisfied. The objective is to minimize the number of employed vehicles and then minimize the total travel and charging costs. In this study, we present a Mixed Integer Programming Model and develop a Charging Routing Heuristic and a Local Search Heuristic based on the Inject-Eject routine with different insertion methods. All heuristics are tested on real data instances.

Keywords: charging problem, electric vehicle, heuristics, local search, optimization, routing problem.

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Authors: Mohsen A. Bakouri, Andrey V. Savkin, Abdul-Hakeem H. Alomari, Robert F. Salamonsen, Einly Lim, Nigel H. Lovell

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Physiological control of a left ventricle assist device (LVAD) is generally a complicated task due to diverse operating environments and patient variability. In this work, a tracking control algorithm based on sliding mode and feed forward control for a class of discrete-time single input single output (SISO) nonlinear uncertain systems is presented. The controller was developed to track the reference trajectory to a set operating point without inducing suction in the ventricle. The controller regulates the estimated mean pulsatile flow Qp and mean pulsatility index of pump rotational speed PIω that was generated from a model of the assist device. We recall the principle of the sliding mode control theory then we combine the feed-forward control design with the sliding mode control technique to follow the reference trajectory. The uncertainty is replaced by its upper and lower boundary. The controller was tested in a computer simulation covering two scenarios (preload and ventricular contractility). The simulation results prove the effectiveness and the robustness of the proposed controller

Keywords: robust control system, discrete-sliding mode, left ventricularle assist devicse, pulsatility index.

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Authors: Md. Zahangir Alom, Mei-Lan Piao, Md. Shariful Islam, Nam Kim, Jae-Hyeung Park

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The evaluation and measurement of human body dimensions are achieved by physical anthropometry. This research was conducted in view of the importance of anthropometric indices of the face in forensic medicine, surgery, and medical imaging. The main goal of this research is to optimization of facial feature point by establishing a mathematical relationship among facial features and used optimize feature points for age classification. Since selected facial feature points are located to the area of mouth, nose, eyes and eyebrow on facial images, all desire facial feature points are extracted accurately. According this proposes method; sixteen Euclidean distances are calculated from the eighteen selected facial feature points vertically as well as horizontally. The mathematical relationships among horizontal and vertical distances are established. Moreover, it is also discovered that distances of the facial feature follows a constant ratio due to age progression. The distances between the specified features points increase with respect the age progression of a human from his or her childhood but the ratio of the distances does not change (d = 1 .618 ) . Finally, according to the proposed mathematical relationship four independent feature distances related to eight feature points are selected from sixteen distances and eighteen feature point-s respectively. These four feature distances are used for classification of age using Support Vector Machine (SVM)-Sequential Minimal Optimization (SMO) algorithm and shown around 96 % accuracy. Experiment result shows the proposed system is effective and accurate for age classification.

Keywords: 3D Face Model, Face Anthropometrics, Facial Features Extraction, Feature distances, SVM-SMO

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Authors: Seongcheol Kwon, Jeongmin Kim, Kwang Ryel Ryu

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We assume an IoT-based smart-home environment where the on-off status of each of the electrical appliances including the room lights can be recognized in a real time by monitoring and analyzing the smart meter data. At any moment in such an environment, we can recognize what the household or the user is doing by referring to the status data of the appliances. In this paper, we focus on a smart-home service that is to activate a robot vacuum cleaner at right time by recognizing the user situation, which requires a situation-aware model that can distinguish the situations that allow vacuum cleaning (Yes) from those that do not (No). We learn as our candidate models a few classifiers such as naïve Bayes, decision tree, and logistic regression that can map the appliance-status data into Yes and No situations. Our training and test data are obtained from simulations of user behaviors, in which a sequence of user situations such as cooking, eating, dish washing, and so on is generated with the status of the relevant appliances changed in accordance with the situation changes. During the simulation, both the situation transition and the resulting appliance status are determined stochastically. To compare the performances of the aforementioned classifiers we obtain their learning curves for different types of users through simulations. The result of our empirical study reveals that naïve Bayes achieves a slightly better classification accuracy than the other compared classifiers.

Keywords: Situation-awareness, Smart home, IoT, Machine learning, Classifier.

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Authors: Zukisa Nante, Wang Zenghui

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Face recognition is the problem of identifying or recognizing individuals in an image. This paper investigates a possible method to bring a solution to this problem. The method proposes an amalgamation of Principal Component Analysis (PCA), K-Means clustering, and Convolutional Neural Network (CNN) for a face recognition system. It is trained and evaluated using the ORL dataset. This dataset consists of 400 different faces with 40 classes of 10 face images per class. Firstly, PCA enabled the usage of a smaller network. This reduces the training time of the CNN. Thus, we get rid of the redundancy and preserve the variance with a smaller number of coefficients. Secondly, the K-Means clustering model is trained using the compressed PCA obtained data which select the K-Means clustering centers with better characteristics. Lastly, the K-Means characteristics or features are an initial value of the CNN and act as input data. The accuracy and the performance of the proposed method were tested in comparison to other Face Recognition (FR) techniques namely PCA, Support Vector Machine (SVM), as well as K-Nearest Neighbour (kNN). During experimentation, the accuracy and the performance of our suggested method after 90 epochs achieved the highest performance: 99% accuracy F1-Score, 99% precision, and 99% recall in 463.934 seconds. It outperformed the PCA that obtained 97% and KNN with 84% during the conducted experiments. Therefore, this method proved to be efficient in identifying faces in the images.

Keywords: Face recognition, Principal Component Analysis, PCA, Convolutional Neural Network, CNN, Rectified Linear Unit, ReLU, feature extraction.

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Authors: Andrea Tundis, Carlos García Cordero, Rolf Egert, Alfredo Garro, Max Mühlhäuser

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Resilience is an important system property that relies on the ability of a system to automatically recover from a degraded state so as to continue providing its services. Resilient systems have the means of detecting faults and failures with the added capability of automatically restoring their normal operations. Mastering resilience in the domain of Cyber-Physical Systems is challenging due to the interdependence of hybrid hardware and software components, along with physical limitations, laws, regulations and standards, among others. In order to overcome these challenges, this paper presents a modeling approach, based on the concept of Dynamic Cells, tailored to the management of Smart Grids. Additionally, a heuristic algorithm that works on top of the proposed modeling approach, to find resilient configurations, has been defined and implemented. More specifically, the model supports a flexible representation of Smart Grids and the algorithm is able to manage, at different abstraction levels, the resource consumption of individual grid elements on the presence of failures and faults. Finally, the proposal is evaluated in a test scenario where the effectiveness of such approach, when dealing with complex scenarios where adequate solutions are difficult to find, is shown.

Keywords: Cyber-physical systems, energy management, optimization, smart grids, self-healing, resilience, security.

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Authors: H. M. Mohammad, A. Martin, N. Brown, N. Hodson, P. Hill, E. Roberts

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Graphite intercalation compound (GIC) has been demonstrated to be a useful, low capacity and rapid adsorbent for the removal of organic micropollutants from water. The high electrical conductivity and low capacity of the material lends itself to electrochemical regeneration. Following electrochemical regeneration, equilibrium loading under similar conditions is reported to exceed that achieved by the fresh adsorbent. This behavior is reported in terms of the regeneration efficiency being greater than 100%. In this work, surface analysis techniques are employed to investigate the material in three states: ‘Fresh’, ‘Loaded’ and ‘Regenerated’. ‘Fresh’ GIC is shown to exhibit a hydrogen and oxygen rich surface layer approximately 150 nm thick. ‘Loaded’ GIC shows a similar but slightly thicker surface layer (approximately 370 nm thick) and significant enhancement in the hydrogen and oxygen abundance extending beyond 600 nm from the surface. 'Regenerated’ GIC shows an oxygen rich layer, slightly thicker than the fresh case at approximately 220 nm while showing a very much lower hydrogen enrichment at the surface. Results demonstrate that while the electrochemical regeneration effectively removes the phenol model pollutant, it also oxidizes the exposed carbon surface. These results may have a significant impact on the estimation of adsorbent life.

Keywords: Graphite, adsorbent, electrochemical, regeneration, phenol.

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Authors: Fooad Karimi Ghaleh Jough, Mohsen Soori

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Today, the occurrence of progressive failure in structures has become a challenging issue, requiring the presentation of suitable solutions for structural resistance to this phenomenon. It is also necessary to evaluate the vulnerability of existing and under-construction buildings to progressive failure. The kind of lateral load-resisting system the building and its connections have is one of the most significant and influential variables in structural resistance to the risk of progressing failure. Using the "Alternative Path" approach suggested by the GSA2003 and UFC2013 recommendations, different configurations of semi-rigid connections against progressive failure are offered in this study. In order to do this, the Opensees program was used to model nine distinct semi-rigid connection configurations on a three-story Special Area of Conservation (SAC) structure, accounting for the impact of connection stiffness. Then, using nonlinear dynamic analysis, the effects of column removal were explored in two scenarios: corner column removal and middle column removal on the first level. Nonlinear static analysis results showed that when a column is removed, structures with semi-rigid connections experience larger displacements, which result in the construction of a plastic hinge. Furthermore, it was clear from the findings of the nonlinear static analysis that the possibility of progressive failure increased with the number of semi-rigid connections in the structure.

Keywords: Semi-rigid, nonlinear static analysis, progressive collapse, alternative path.

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Authors: Shahabeddin Sotudian, M. H. Fazel Zarandi, I. B. Turksen

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Hepatitis is one of the most common and dangerous diseases that affects humankind, and exposes millions of people to serious health risks every year. Diagnosis of Hepatitis has always been a challenge for physicians. This paper presents an effective method for diagnosis of hepatitis based on interval Type-II fuzzy. This proposed system includes three steps: pre-processing (feature selection), Type-I and Type-II fuzzy classification, and system evaluation. KNN-FD feature selection is used as the preprocessing step in order to exclude irrelevant features and to improve classification performance and efficiency in generating the classification model. In the fuzzy classification step, an “indirect approach” is used for fuzzy system modeling by implementing the exponential compactness and separation index for determining the number of rules in the fuzzy clustering approach. Therefore, we first proposed a Type-I fuzzy system that had an accuracy of approximately 90.9%. In the proposed system, the process of diagnosis faces vagueness and uncertainty in the final decision. Thus, the imprecise knowledge was managed by using interval Type-II fuzzy logic. The results that were obtained show that interval Type-II fuzzy has the ability to diagnose hepatitis with an average accuracy of 93.94%. The classification accuracy obtained is the highest one reached thus far. The aforementioned rate of accuracy demonstrates that the Type-II fuzzy system has a better performance in comparison to Type-I and indicates a higher capability of Type-II fuzzy system for modeling uncertainty.

Keywords: Hepatitis disease, medical diagnosis, type-I fuzzy logic, type-II fuzzy logic, feature selection.

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Authors: Mohamed A. Shanan, Ashraf H. El-Zanaty, Kamal G. Metwally

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This paper presents the effect of concrete compressive strength and rectangularity ratio on strength and ductility of normal and high strength reinforced concrete columns confined with transverse steel under axial compressive loading. Nineteen normal strength concrete rectangular columns with different variables tested in this research were used to study the effect of concrete compressive strength and rectangularity ratio on strength and ductility of columns. The paper also presents a nonlinear finite element analysis for these specimens and another twenty high strength concrete square columns tested by other researchers using ANSYS 15 finite element software. The results indicate that the axial force – axial strain relationship obtained from the analytical model using ANSYS are in good agreement with the experimental data. The comparison shows that the ANSYS is capable of modeling and predicting the actual nonlinear behavior of confined normal and high-strength concrete columns under concentric loading. The maximum applied load and the maximum strain have also been confirmed to be satisfactory. Depending on this agreement between the experimental and analytical results, a parametric numerical study was conducted by ANSYS 15 to clarify and evaluate the effect of each variable on strength and ductility of the columns.

Keywords: ANSYS, concrete compressive strength effect, ductility, rectangularity ratio, strength.

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Authors: Achim Kampker, Kai Kreiskoether, Johannes Wagner, Sarah Fluchs

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The growing speed of innovation in related industries requires the automotive industry to adapt and increase release frequencies of new vehicle derivatives which implies a significant reduction of investments per vehicle and ramp-up times. Emerging markets in various parts of the world augment the currently dominating established main automotive markets. Local content requirements such as import tariffs on final products impede the accessibility of these micro markets, which is why in the future market exploitation will not be driven by pure sales activities anymore but rather by setting up local assembly units. The aim of this paper is to provide an overview of the concept of decentralized assembly and to discuss and critically assess some currently researched and crucial approaches in production technology. In order to determine the scope in which complementary mobile assembly can be profitable for manufacturers, a general cost model is set up and each cost driver is assessed with respect to varying levels of decentralization. One main result of the paper is that the presented approaches offer huge cost-saving potentials and are thus critical for future production strategies. Nevertheless, they still need to be further exploited in order for decentralized assembly to be profitable for companies. The optimal level of decentralization must, however, be specifically determined in each case and cannot be defined in general.

Keywords: Automotive assembly, e-mobility, production technology, small series assembly.

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Authors: Maziar Ahmad Sharbafi, Caro Lucas, Abolfazel Toroghi Haghighat, Omid AmirGhiasvand, Omid Aghazade

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RoboCup Rescue simulation as a large-scale Multi agent system (MAS) is one of the challenging environments for keeping coordination between agents to achieve the objectives despite sensing and communication limitations. The dynamicity of the environment and intensive dependency between actions of different kinds of agents make the problem more complex. This point encouraged us to use learning-based methods to adapt our decision making to different situations. Our approach is utilizing reinforcement leaning. Using learning in rescue simulation is one of the current ways which has been the subject of several researches in recent years. In this paper we present an innovative learning method implemented for Police Force (PF) Agent. This method can cope with the main difficulties that exist in other learning approaches. Different methods used in the literature have been examined. Their drawbacks and possible improvements have led us to the method proposed in this paper which is fast and accurate. The Brain Emotional Learning Based Intelligent Controller (BELBIC) is our solution for learning in this environment. BELBIC is a physiologically motivated approach based on a computational model of amygdale and limbic system. The paper presents the results obtained by the proposed approach, showing the power of BELBIC as a decision making tool in complex and dynamic situation.

Keywords: Emotional learning, rescue, simulation environment, RoboCup, multi-agent system.

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Authors: Verónica Arredondo, Miguel Martínez-Panero, Teresa Peña, Victoriano Ramírez

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The Mexican Chamber of Deputies is composed of 500 representatives: 300 of them elected by relative majority and another 200 ones elected through proportional representation in five electoral clusters (constituencies) with 40 representatives each. In this mixed-member electoral system, the seats distribution of proportional representation is not independent of the election by relative majority, as it attempts to correct representation imbalances produced in single-member districts. This two-fold structure has been maintained in the successive electoral reforms carried out along the last three decades (eight from 1986 to 2014). In all of them, the election process of 200 seats becomes complex: Formulas in the Law are difficult to understand and to be interpreted. This paper analyzes the Mexican electoral system after the electoral reform of 2014, which was applied for the first time in 2015. The research focuses on contradictions and issues of applicability, in particular situations where seats allocation is affected by ambiguity in the law and where asymmetrical treatment of political parties arises. Due to these facts, a proposal of electoral reform will be presented. It is intended to be simpler, clearer, and more enduring than the current system. Furthermore, this model is more suitable for producing electoral outcomes free of contradictions and paradoxes. This approach would allow a fair treatment of political parties and as a result an improved opportunity to exercise democracy.

Keywords: Apportionment paradoxes, biproportional representation, electoral mathematics, electoral reform, Mexican electoral system, proportional representation, political asymmetry.

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Authors: Aleš Florian, Lenka Ševelová

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Low volume roads are widely used all over the world. To improve their quality the computer simulation of their behavior is proposed. The FEM model enables to determine stress and displacement conditions in the pavement and/or also in the particular material layers. Different variants of pavement layers, material used, humidity as well as loading conditions can be studied. Among others, the input information about material properties of individual layers made from recycled materials is crucial for obtaining results as exact as possible. For this purpose the cyclic-load triaxial test machine testing of cyclic-load performance of materials is a promising test method. The test is able to simulate the real traffic loading on particular materials taking into account the changes in the horizontal stress conditions produced in particular layers by crossings of vehicles. Also the test specimen can be prepared with different amount of water. Thus modulus of elasticity (Young modulus) of different materials including recycled ones can be measured under the different conditions of horizontal and vertical stresses as well as under the different humidity conditions. Using the proposed testing procedure the modulus of elasticity of recycled materials used in the newly built low volume road is obtained under different stress and humidity conditions set to standard, dry and fully saturated level. Obtained values of modulus of elasticity are used in FEA.

Keywords: FEA, FEM, geotechnical materials, low volume roads, pavement, triaxial test, Young modulus.

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Authors: Khalid S. Hashim, Andy Shaw, Rafid Alkhaddar, Montserrat Ortoneda Pedrola

Abstract:

A flow column has been innovatively used in the design of a new electrocoagulation reactor (ECR1) that will reduce the temperature of water being treated; where the flow columns work as a radiator for the water being treated. In order to investigate the performance of ECR1 and compare it to that of traditional reactors; 600 mL water samples with an initial temperature of 350C were pumped continuously through these reactors for 30 min at current density of 1 mA/cm2. The temperature of water being treated was measured at 5 minutes intervals over a 30 minutes period using a thermometer. Additional experiments were commenced to investigate the effects of initial temperature (15-350C), water conductivity (0.15 – 1.2 S) and current density (0.5 -3 mA/cm2) on the performance of ECR1. The results obtained demonstrated that the ECR1, at a current density of 1 mA/cm2 and continuous flow model, reduced water temperature from 350C to the vicinity of 280C during the first 15 minutes and kept the same level till the end of the treatment time. While, the temperature increased from 28.1 to 29.80C and from 29.8 to 31.90C in the batch and the traditional continuous flow models respectively. In term of initial temperature, ECR1 maintained the temperature of water being treated within the range of 22 to 280C without the need for external cooling system even when the initial temperatures varied over a wide range (15 to 350C). The influent water conductivity was found to be a significant variable that affect the temperature. The desirable value of water conductivity is 0.6 S. However, it was found that the water temperature increased rapidly with a higher current density.

Keywords: Water temperature, flow column, electrocoagulation.

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Authors: Joseph E. Estevez, Mahdi Ghazizadeh, James G. Ryan, Ajit D. Kelkar

Abstract:

Radiation shielding is an obstacle in long duration space exploration. Boron Nitride Nanotubes (BNNTs) have attracted attention as an additive to radiation shielding material due to B¹⁰’s large neutron capture cross section. The B¹⁰ has an effective neutron capture cross section suitable for low energy neutrons ranging from 10^-5 to 10⁴ eV and hydrogen is effective at slowing down high energy neutrons. Hydrogenated BNNTs are potentially an ideal nanofiller for radiation shielding composites. We use Molecular Dynamics (MD) Simulation via Material Studios Accelrys 6.0 to model the Young’s Modulus of Hydrogenated BNNTs. An extrapolation technique was employed to determine the Young’s Modulus due to the deformation of the nanostructure at its theoretical density. A linear regression was used to extrapolate the data to the theoretical density of 2.62g/cm³. Simulation data shows that the hydrogenated BNNTs will experience a 11% decrease in the Young’s Modulus for (6,6) BNNTs and 8.5% decrease for (8,8) BNNTs compared to non-hydrogenated BNNT’s. Hydrogenated BNNTs are a viable option as a nanofiller for radiation shielding nanocomposite materials for long range and long duration space exploration.

Keywords: Boron Nitride Nanotube, Radiation Shielding, Young Modulus, Atomistic Modeling.

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Authors: A. R. Binesh, S. Hossainpour

Abstract:

Due to the stringent legislation for emission of diesel engines and also increasing demand on fuel consumption, the importance of detailed 3D simulation of fuel injection, mixing and combustion have been increased in the recent years. In the present work, FIRE code has been used to study the detailed modeling of spray and mixture formation in a Caterpillar heavy-duty diesel engine. The paper provides an overview of the submodels implemented, which account for liquid spray atomization, droplet secondary break-up, droplet collision, impingement, turbulent dispersion and evaporation. The simulation was performed from intake valve closing (IVC) to exhaust valve opening (EVO). The predicted in-cylinder pressure is validated by comparing with existing experimental data. A good agreement between the predicted and experimental values ensures the accuracy of the numerical predictions collected with the present work. Predictions of engine emissions were also performed and a good quantitative agreement between measured and predicted NOx and soot emission data were obtained with the use of the present Zeldowich mechanism and Hiroyasu model. In addition, the results reported in this paper illustrate that the numerical simulation can be one of the most powerful and beneficial tools for the internal combustion engine design, optimization and performance analysis.

Keywords: Diesel engine, Combustion, Pollution, CFD.

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Authors: Oliver Haala, Bernhard Wagner, Maximilian Hofmann, Martin Marz

Abstract:

The excellent suitability of the externally excited synchronous machine (EESM) in automotive traction drive applications is justified by its high efficiency over the whole operation range and the high availability of materials. Usually, maximum efficiency is obtained by modelling each single loss and minimizing the sum of all losses. As a result, the quality of the optimization highly depends on the precision of the model. Moreover, it requires accurate knowledge of the saturation dependent machine inductances. Therefore, the present contribution proposes a method to minimize the overall losses of a salient pole EESM and its inverter in steady state operation based on measurement data only. Since this method does not require any manufacturer data, it is well suited for an automated measurement data evaluation and inverter parametrization. The field oriented control (FOC) of an EESM provides three current components resp. three degrees of freedom (DOF). An analytic minimization of the copper losses in the stator and the rotor (assuming constant inductances) is performed and serves as a first approximation of how to choose the optimal current reference values. After a numeric offline minimization of the overall losses based on measurement data the results are compared to a control strategy that satisfies cos (ϕ) = 1.

Keywords: Current control, efficiency, externally excited synchronous machine, optimization.

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Authors: Morten Stigaard Laursen, Rasmus Nyholm Jørgensen, Henrik Skov Midtiby, Anders Krogh Mortensen, Sanmohan Baby

Abstract:

This work contributes a statistical model and simulation framework yielding the best estimate possible for the potential herbicide reduction when using the MoDiCoVi algorithm all the while requiring a efficacy comparable to conventional spraying. In June 2013 a maize field located in Denmark were seeded. The field was divided into parcels which was assigned to one of two main groups: 1) Control, consisting of subgroups of no spray and full dose spraty; 2) MoDiCoVi algorithm subdivided into five different leaf cover thresholds for spray activation. In addition approximately 25% of the parcels were seeded with additional weeds perpendicular to the maize rows. In total 299 parcels were randomly assigned with the 28 different treatment combinations. In the statistical analysis, bootstrapping was used for balancing the number of replicates. The achieved potential herbicide savings was found to be 70% to 95% depending on the initial weed coverage. However additional field trials covering more seasons and locations are needed to verify the generalisation of these results. There is a potential for further herbicide savings as the time interval between the first and second spraying session was not long enough for the weeds to turn yellow, instead they only stagnated in growth.

Keywords: Weed crop discrimination, macrosprayer, herbicide reduction, site-specific, sprayer-boom.

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