Search results for: Generalized linear mixed model (GLMM)

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: M. Farahnakian, M.R. Razfar, S. Elhami-Joosheghan

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This paper presents an approach for the determination of the optimal cutting parameters (spindle speed, feed rate, depth of cut and engagement) leading to minimum surface roughness in face milling of high silicon stainless steel by coupling neural network (NN) and Electromagnetism-like Algorithm (EM). In this regard, the advantages of statistical experimental design technique, experimental measurements, artificial neural network, and Electromagnetism-like optimization method are exploited in an integrated manner. To this end, numerous experiments on this stainless steel were conducted to obtain surface roughness values. A predictive model for surface roughness is created by using a back propogation neural network, then the optimization problem was solved by using EM optimization. Additional experiments were performed to validate optimum surface roughness value predicted by EM algorithm. It is clearly seen that a good agreement is observed between the predicted values by EM coupled with feed forward neural network and experimental measurements. The obtained results show that the EM algorithm coupled with back propogation neural network is an efficient and accurate method in approaching the global minimum of surface roughness in face milling.

Keywords: cutting parameters, face milling, surface roughness, artificial neural network, Electromagnetism-like algorithm,

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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: Reza Dinarvand, Mahdi Sadeghian, Somaye Sadeghian

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Prediction of the ultimate bearing capacity of piles (Qu) is one of the basic issues in geotechnical engineering. So far, several methods have been used to estimate Qu, including the recently developed artificial intelligence methods. In recent years, optimization algorithms have been used to minimize artificial network errors, such as colony algorithms, genetic algorithms, imperialist competitive algorithms, and so on. In the present research, artificial neural networks based on colonial competition algorithm (ANN-ICA) were used, and their results were compared with other methods. The results of laboratory tests of short piles in clayey soils with parameters such as pile diameter, pile buried length, eccentricity of load and undrained shear resistance of soil were used for modeling and evaluation. The results showed that ICA-based artificial neural networks predicted lateral bearing capacity of short piles with a correlation coefficient of 0.9865 for training data and 0.975 for test data. Furthermore, the results of the model indicated the superiority of ICA-based artificial neural networks compared to back-propagation artificial neural networks as well as the Broms and Hansen methods.

Keywords: Lateral bearing capacity, short pile, clayey soil, artificial neural network, Imperialist competition algorithm.

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Authors: C. Lodato, S. Lopes

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The image segmentation method described in this paper has been developed as a pre-processing stage to be used in methodologies and tools for video/image indexing and retrieval by content. This method solves the problem of whole objects extraction from background and it produces images of single complete objects from videos or photos. The extracted images are used for calculating the object visual features necessary for both indexing and retrieval processes. The segmentation algorithm is based on the cooperation among an optical flow evaluation method, edge detection and region growing procedures. The optical flow estimator belongs to the class of differential methods. It permits to detect motions ranging from a fraction of a pixel to a few pixels per frame, achieving good results in presence of noise without the need of a filtering pre-processing stage and includes a specialised model for moving object detection. The first task of the presented method exploits the cues from motion analysis for moving areas detection. Objects and background are then refined using respectively edge detection and seeded region growing procedures. All the tasks are iteratively performed until objects and background are completely resolved. The method has been applied to a variety of indoor and outdoor scenes where objects of different type and shape are represented on variously textured background.

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

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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: Raja Das, M. K. Pradhan

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This paper presents a comparative study between two neural network models namely General Regression Neural Network (GRNN) and Back Propagation Neural Network (BPNN) are used to estimate radial overcut produced during Electrical Discharge Machining (EDM). Four input parameters have been employed: discharge current (Ip), pulse on time (Ton), Duty fraction (Tau) and discharge voltage (V). Recently, artificial intelligence techniques, as it is emerged as an effective tool that could be used to replace time consuming procedures in various scientific or engineering applications, explicitly in prediction and estimation of the complex and nonlinear process. The both networks are trained, and the prediction results are tested with the unseen validation set of the experiment and analysed. It is found that the performance of both the networks are found to be in good agreement with average percentage error less than 11% and the correlation coefficient obtained for the validation data set for GRNN and BPNN is more than 91%. However, it is much faster to train GRNN network than a BPNN and GRNN is often more accurate than BPNN. GRNN requires more memory space to store the model, GRNN features fast learning that does not require an iterative procedure, and highly parallel structure. GRNN networks are slower than multilayer perceptron networks at classifying new cases.

Keywords: Electrical-discharge machining, General Regression Neural Network, Back-propagation Neural Network, Radial Overcut.

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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: 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: S. Hossainpour, A. R. Binesh

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High-velocity oxygen fuel (HVOF) thermal spraying uses a combustion process to heat the gas flow and coating material. A computational fluid dynamics (CFD) model has been developed to predict gas dynamic behavior in a HVOF thermal spray gun in which premixed oxygen and propane are burnt in a combustion chamber linked to a parallel-sided nozzle. The CFD analysis is applied to investigate axisymmetric, steady-state, turbulent, compressible, chemically reacting, subsonic and supersonic flow inside and outside the gun. The gas velocity, temperature, pressure and Mach number distributions are presented for various locations inside and outside the gun. The calculated results show that the most sensitive parameters affecting the process are fuel-to-oxygen gas ratio and total gas flow rate. Gas dynamic behavior along the centerline of the gun depends on both total gas flow rate and fuel-to-oxygen gas ratio. The numerical simulations show that the axial gas velocity and Mach number distribution depend on both flow rate and ratio; the highest velocity is achieved at the higher flow rate and most fuel-rich ratio. 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 HVOF system design, optimization and performance analysis.

Keywords: HVOF, CFD, gas dynamics, thermal spray, combustion.

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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: A. Rifa’i, Y. Takeshita, M. Komatsu

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The post-rain puddles problem that occurs in the first yard of Prambanan Temple are often disturbing visitor activity. A poodle layer and a drainage system had ever built to avoid such a problem, but puddles still did not stop appearing after rain. Permeability parameter needs to be determined by using a simpler procedure to find exact method of solution. The instrument modelling was proposed according to the development of field permeability testing instrument. This experiment used a proposed Constant Discharge method. Constant Discharge method used a tube poured with constant water flow from unsaturated until saturated soil condition. Volumetric water content (θ) were monitored by soil moisture measurement device. The results were correlations between k and θ which were drawn by numerical approach from Van Genutchen model. Parameters θr optimum value obtained from the test was at very dry soil. Coefficient of permeability with a density of 19.8 kN/m3 for unsaturated conditions was in range of 3 x 10-6 cm/sec (Sr=68%) until 9.98 x 10-4 cm/sec (Sr=82%). The equipment and testing procedure developed in this research was quite effective, simple and easy to be implemented on determining field soil permeability coefficient value of sandy soil. Using constant discharge method in proposed permeability test, value of permeability coefficient under unsaturated condition can be obtained without establish soil water characteristic curve.

Keywords: Constant discharge method, in situ permeability test, sandy soil, unsaturated conditions.

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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: Oseni Taiwo Amoo, Bloodless Dzwairo

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In this paper, we extend the versatility and usefulness of GIS as a methodology for any river basin hydrologic characteristics analysis (HCA). The Gurara River basin located in North-Central Nigeria is presented in this study. It is an on-going research using spatial Digital Elevation Model (DEM) and Arc-Hydro tools to take inventory of the basin characteristics in order to predict water abstraction quantification on streamflow regime. One of the main concerns of hydrological modelling is the quantification of runoff from rainstorm events. In practice, the soil conservation service curve (SCS) method and the Conventional procedure called rational technique are still generally used these traditional hydrological lumped models convert statistical properties of rainfall in river basin to observed runoff and hydrograph. However, the models give little or no information about spatially dispersed information on rainfall and basin physical characteristics. Therefore, this paper synthesizes morphometric parameters in generating runoff. The expected results of the basin characteristics such as size, area, shape, slope of the watershed and stream distribution network analysis could be useful in estimating streamflow discharge. Water resources managers and irrigation farmers could utilize the tool for determining net return from available scarce water resources, where past data records are sparse for the aspect of land and climate.

Keywords: Hydrological characteristic, land and climate, runoff discharge, streamflow.

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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: Rashid S. Mohammad, Shicheng Zhang, Sun Lu, Syed Jamal-Ud-Din, Xinzhe Zhao

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A compositional reservoir simulation model (CMG-GEM) was used for cyclic CO₂ injection process in unconventional tight reservoir. Cyclic CO₂ injection is an enhanced oil recovery process consisting of injection, shut-in, and production. The study of cyclic CO₂ injection and hydrocarbon recovery in ultra-low permeability reservoirs is mainly a function of rock, fluid, and operational parameters. CMG-GEM was used to study several design parameters of cyclic CO₂ injection process to distinguish the parameters with maximum effect on the oil recovery and to comprehend the behavior of cyclic CO₂ injection in tight reservoir. On the other hand, permeability reduction induced by asphaltene precipitation is one of the major issues in the oil industry due to its plugging onto the porous media which reduces the oil productivity. In addition to asphaltene deposition, solubility of CO₂ in the aquifer is one of the safest and permanent trapping techniques when considering CO₂ storage mechanisms in geological formations. However, the effects of the above uncertain parameters on the process of CO₂ enhanced oil recovery have not been understood systematically. Hence, it is absolutely necessary to study the most significant parameters which dominate the process. The main objective of this study is to improve techniques for designing cyclic CO₂ injection process while considering the effects of asphaltene deposition and solubility of CO₂ in the brine in order to prevent asphaltene precipitation, minimize CO₂ emission, optimize cyclic CO₂ injection, and maximize oil production.

Keywords: Tight reservoirs, cyclic O2 injection, asphaltene, solubility, reservoir simulation.

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Authors: Aleš Florian, Lenka Ševelová

Abstract:

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: 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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Authors: Miguel Angel Garcia-Ruiz, Pedro Cesar Santana-Mancilla, Laura Sanely Gaytan-Lugo

Abstract:

This paper describes the design and application of a short in-class project conducted in Algoma University’s Human-Computer Interaction (HCI) course taught at the Bachelor of Computer Science. The project was based on the Maker Movement (people using and reusing electronic components and everyday materials to tinker with technology and make interactive applications), where students applied low-cost and easy-to-use electronic components, the Arduino Uno microcontroller board, software tools, and everyday objects. Students collaborated in small teams by completing hands-on activities with them, making an interactive walking cane for blind people. At the end of the course, students filled out a Technology Acceptance Model version 2 (TAM2) questionnaire where they evaluated microcontroller boards’ applications in HCI classes. We also asked them about applying the Maker Movement in HCI classes. Results showed overall students’ positive opinions and response about using microcontroller boards in HCI classes. We strongly suggest that every HCI course should include practical activities related to tinkering with technology such as applying microcontroller boards, where students actively and constructively participate in teams for achieving learning objectives.

Keywords: Maker movement, microcontrollers, learning, projects, course, technology acceptance.

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