Search results for: penalty method

Authors: M.G.A. Nassef, Linghan Li, C. Schenck, B. Kuhfuss

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Design and modeling of nonlinear systems require the knowledge of all inside acting parameters and effects. An empirical alternative is to identify the system-s transfer function from input and output data as a black box model. This paper presents a procedure using least squares algorithm for the identification of a feed drive system coefficients in time domain using a reduced model based on windowed input and output data. The command and response of the axis are first measured in the first 4 ms, and then least squares are applied to predict the transfer function coefficients for this displacement segment. From the identified coefficients, the next command response segments are estimated. The obtained results reveal a considerable potential of least squares method to identify the system-s time-based coefficients and predict accurately the command response as compared to measurements.

Keywords: feed drive systems, least squares algorithm, onlineparameter identification, short time window

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Authors: P. Srinivas, P. V. N. Prasad

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Since torque ripple is the main cause of noise and vibrations, the performance of Switched Reluctance Motor (SRM) can be improved by minimizing its torque ripple using a novel control technique called Direct Torque Control (DTC). In DTC technique, torque is controlled directly through control of magnitude of the flux and change in speed of the stator flux vector. The flux and torque are maintained within set hysteresis bands.

The DTC of SRM is analyzed by two methods. In one method, the actual torque is computed by conducting Finite Element Analysis (FEA) on the design specifications of the motor. In the other method, the torque is computed by Simplified Torque Equation. The variation of peak current, average current, torque ripple and speed settling time with Simplified Torque Equation model is compared with FEA based model.

Keywords: Direct Toque Control, Simplified Torque Equation, Finite Element Analysis, Torque Ripple.

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Authors: V. Piscopo

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In the traditional buckling analysis of rectangular plates the classical thin plate theory is generally applied, so neglecting the plating shear deformation. It seems quite clear that this method is not totally appropriate for the analysis of thick plates, so that in the following the two variable refined plate theory proposed by Shimpi (2006), that permits to take into account the transverse shear effects, is applied for the buckling analysis of simply supported isotropic rectangular plates, compressed in one and two orthogonal directions. The relevant results are compared with the classical ones and, for rectangular plates under uniaxial compression, a new direct expression, similar to the classical Bryan-s formula, is proposed for the Euler buckling stress. As the buckling analysis is a widely diffused topic for a variety of structures, such as ship ones, some applications for plates uniformly compressed in one and two orthogonal directions are presented and the relevant theoretical results are compared with those ones obtained by a FEM analysis, carried out by ANSYS, to show the feasibility of the presented method.

Keywords: Buckling analysis, Thick plates, Biaxial stresses

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Authors: Mecheri Zeid Belmecheri, Maamar Ahfir, Izzet Kale

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Automatic cardiac auscultation is still a subject of research in order to establish an objective diagnosis. Recorded heart sounds as Phonocardiogram (PCG) signals can be used for automatic segmentation into components that have clinical meanings. These are the first sound, S1, the second sound, S2, and the systolic and diastolic components, respectively. In this paper, an automatic method is proposed for the robust segmentation of heart sounds. This method is based on calculating an intermediate sawtooth-shaped signal from the length variation of the recorded PCG signal in the time domain and, using its positive derivative function that is a binary signal in training a Recurrent Neural Network (RNN). Results obtained in the context of a large database of recorded PCGs with their simultaneously recorded Electrocardiograms (ECGs) from different patients in clinical settings, including normal and abnormal subjects, show on average a segmentation testing performance average of 76% sensitivity and 94% specificity.

Keywords: Heart sounds, PCG segmentation, event detection, Recurrent Neural Networks, PCG curve length.

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Authors: C. S. Wong, K. H. Badri, N. Ataollahi, K. P. Law, M. S. Su’ait, N. I. Hassan

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Novel bio-based polymer electrolyte was synthesized with LiClO4 as the main source of charge carrier. Initially, polyurethane-LiClO4 polymer electrolytes were synthesized via prepolymerization method with different NCO/OH ratios and labelled them as PU1, PU2, PU3 and PU4. Fourier transform infrared (FTIR) analysis indicates the co-ordination between Li+ ion and polyurethane in PU1. Differential scanning calorimetry (DSC) analysis indicates PU1 has the highest glass transition temperature (Tg) corresponds to the most abundant urethane group which is the hard segment in PU1. Scanning electron microscopy (SEM) shows the good miscibility between lithium salt and the polymer. The study found that PU1 possessed the greatest ionic conductivity and the lowest activation energy, Ea. All the polyurethanes exhibited linear Arrhenius variations indicating ion transport via simple lithium ion hopping in polyurethane. This research proves the NCO content in polyurethane plays an important role in affecting the ionic conductivity of this polymer electrolyte.

Keywords: Ionic conductivity, Palm kernel oil-based monoester polyol, polyurethane, solid polymer electrolyte.

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Authors: A. Yavar, S. Sarmani, K. S. Khoo

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The analysis of trace elements in human hair provides crucial insights into an individual's nutritional status and environmental exposure. This research aimed to examine the levels of toxic and essential elements in the scalp hair of school children aged 12-17 from three villages (Anglong Romiot (AR), Svay Romiot (SR), and Kampong Kong (KK)) in Cambodia's Kandal province, a region where residents are especially vulnerable to toxic elements, notably arsenic (As), due to their dietary habits, lifestyle, and environmental conditions. The scalp hair samples were analyzed using the k0-Instrumental Neutron Activation method (k0-INAA), with a six-hour irradiation period in the Malaysian Nuclear Agency (MNA) research reactor followed by High Purity Germanium (HPGe) detector use to identify the gamma peaks of radionuclides. The analysis identified 31 elements in the human hair from the study area, including As, Au, Br, Ca, Ce, Co, Dy, Eu-152m, Hg-197, Hg-203, Ho, Ir, K, La, Lu, Mn, Na, Pa, Pt-195m, Pt-197, Sb, Sc-46, Sc-47, Sm, Sn-117m, W-181, W-187, Yb-169, Yb-175, Zn, and Zn-69m. The accuracy of the method was verified through the analysis of ERM-DB001-human hair as a Certified Reference Material (CRM), with the results demonstrating consistency with the certified values. Given the prevalent arsenic pollution in the research area, the study also examined the relationship between the concentration of As and other elements using Pearson's correlation test. The outcomes offer a comprehensive resource for future investigations into toxic and essential element presence in the region. In the main body of the paper, a more extensive discussion on the implications of arsenic pollution and the correlations observed is provided to enhance understanding and inform future research directions.

Keywords: Human scalp hair, toxic and essential elements, Kandal Province, Cambodia, k0-Instrumental Neutron Activation Method.

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Authors: Romisaa Ali

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The Policy Gradient approach is a subset of the Deep Reinforcement Learning (DRL) combines Deep Neural Networks (DNN) with Reinforcement Learning (RL). This approach finds the optimal policy of robot movement, based on the experience it gains from interaction with its environment. Unlike previous policy gradient algorithms, which were unable to handle the two types of error variance and bias introduced by the DNN model due to over- or underestimation, this algorithm is capable of handling both types of error variance and bias. This article will discuss the state-of-the-art SOTA policy gradient technique, trust region policy optimization (TRPO), by applying this method in various environments compared to another policy gradient method, the Proximal Policy Optimization (PPO), to explain their robust optimization, using this SOTA to gather experience data during various training phases after observing the impact of hyper-parameters on neural network performance.

Keywords: Deep neural networks, deep reinforcement learning, Proximal Policy Optimization, state-of-the-art, trust region policy optimization.

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Authors: Mamidi Ramakrishna Rao

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Doubly-fed induction generator (DFIG) is currently the choice for many wind turbines. These generators, when connected to the grid through a converter, is subjected to varied power system conditions like voltage variation, frequency variation, short circuit fault conditions, etc. Further, many countries like Canada, Germany, UK, Scotland, etc. have distinct grid codes relating to wind turbines. Accordingly, following the network faults, wind turbines have to supply a definite reactive current. To satisfy the requirements including reactive current capability, an optimum electrical design becomes a mandate for DFIG to function. This paper intends to optimize the equivalent circuit parameters of an electrical design for satisfactory DFIG performance. Direct search method has been used for optimization of the parameters. The variables selected include electromagnetic core dimensions (diameters and stack length), slot dimensions, radial air gap between stator and rotor and winding copper cross section area. Optimization for 2 MW DFIG has been executed separately for three objective functions - maximum reactive power capability (Case I), maximum efficiency (Case II) and minimum weight (Case III). In the optimization analysis program, voltage variations (10%), power factor- leading and lagging (0.95), speeds for corresponding to slips (-0.3 to +0.3) have been considered. The optimum designs obtained for objective functions were compared. It can be concluded that direct search method of optimization helps in determining an optimum electrical design for each objective function like efficiency or reactive power capability or weight minimization.

Keywords: Direct search, DFIG, equivalent circuit parameters, optimization.

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Authors: Radim Farana, Bogdan Walek, Michal Janosek, Jaroslav Zacek

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This paper presents the advantages of fuzzy control use in technological processes control. The paper presents a real application of the Linguistic Fuzzy-Logic Control, developed at the University of Ostrava for the control of physical models in the Intelligent Systems Laboratory. The paper presents an example of a sensitive non-linear model, such as a magnetic levitation model and obtained results which show how modern information technologies can help to solve actual technical problems. A special method based on the LFLC controller with partial components is presented in this paper followed by the method of automatic context change, which is very helpful to achieve more accurate control results. The main advantage of the used system is its robustness in changing conditions demonstrated by comparing with conventional PID controller. This technology and real models are also used as a background for problem-oriented teaching, realized at the department for master students and their collaborative as well as individual final projects.

Keywords: Control, fuzzy logic, sensitive system, technological proves.

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Authors: Khaled M. EL-Naggar

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Synchronizing and damping torque coefficients of a synchronous machine can give a quite clear picture for machine behavior during transients. These coefficients are used as a power system transient stability measurement. In this paper, a crow search optimization algorithm is presented and implemented to study the power system stability during transients. The algorithm makes use of the machine responses to perform the stability study in time domain. The problem is formulated as a dynamic estimation problem. An objective function that minimizes the error square in the estimated coefficients is designed. The method is tested using practical system with different study cases. Results are reported and a thorough discussion is presented. The study illustrates that the proposed method can estimate the stability coefficients for the critical stable cases where other methods may fail. The tests proved that the proposed tool is an accurate and reliable tool for estimating the machine coefficients for assessment of power system stability.

Keywords: Optimization, estimation, synchronous, machine, crow search.

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Authors: Monika Garg, Lillie Dewan

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Three novel and significant contributions are made in this paper Firstly, non-recursive formulation of Haar connection coefficients, pioneered by the present authors is presented, which can be computed very efficiently and avoid stack and memory overflows. Secondly, the generalized approach for state analysis of singular bilinear time-invariant (TI) and time-varying (TV) systems is presented; vis-˜a-vis diversified and complex works reported by different authors. Thirdly, a generalized approach for parameter estimation of bilinear TI and TV systems is also proposed. The unified framework of the proposed method is very significant in that the digital hardware once-designed can be used to perform the complex tasks of state analysis and parameter estimation of different types of bilinear systems single-handedly. The simplicity, effectiveness and generalized nature of the proposed method is established by applying it to different types of bilinear systems for the two tasks.

Keywords: Bilinear Systems, Haar Wavelet, Haar ConnectionCoefficients, Parameter Estimation, Singular Bilinear Systems, StateAnalysis.

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Authors: Frantisek Bozek, Pavel Budinsky, Ignac Hoza, Alexandr Bozek, Magdalena Naplavova

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A cleaner production project was implemented in a bakery. The project is based on the substitution of the best available technique for an obsolete leaven production technology. The new technology enables production of durable, high-quality leavens. Moreover, 25% of flour as the original raw material can be replaced by pastry from the previous day production which has not been sold. That pastry was previously disposed in a waste incineration plant. Besides the environmental benefits resulting from less waste, lower consumption of energy, reduction of sewage waters quantity and floury dustiness there are also significant economic benefits. Payback period of investment was calculated with help of static method of financial analysis about 2.6 years, using dynamic method 3.5 years and an internal rate of return more than 29%. The supposed annual average profit after taxationin the second year of operation was incompliance with the real profit.

Keywords: Bakery, best available technology, cleaner production, costs, economic benefit, efficiency, energy, environmental benefit, investment, savings.

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Authors: A. G. Sifalakis, E. P. Papadopoulou, Y. G. Saridakis

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A generalized Dirichlet to Neumann map is one of the main aspects characterizing a recently introduced method for analyzing linear elliptic PDEs, through which it became possible to couple known and unknown components of the solution on the boundary of the domain without solving on its interior. For its numerical solution, a well conditioned quadratically convergent sine-Collocation method was developed, which yielded a linear system of equations with the diagonal blocks of its associated coefficient matrix being point diagonal. This structural property, among others, initiated interest for the employment of iterative methods for its solution. In this work we present a conclusive numerical study for the behavior of classical (Jacobi and Gauss-Seidel) and Krylov subspace (GMRES and Bi-CGSTAB) iterative methods when they are applied for the solution of the Dirichlet to Neumann map associated with the Laplace-s equation on regular polygons with the same boundary conditions on all edges.

Keywords: Elliptic PDEs, Dirichlet to Neumann Map, Global Relation, Collocation, Iterative Methods, Jacobi, Gauss-Seidel, GMRES, Bi-CGSTAB.

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Authors: H. Mehdi, Kh. S. Karimov, A. A. Kavokin

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Methods of clustering which were developed in the data mining theory can be successfully applied to the investigation of different kinds of dependencies between the conditions of environment and human activities. It is known, that environmental parameters such as temperature, relative humidity, atmospheric pressure and illumination have significant effects on the human mental performance. To investigate these parameters effect, data mining technique of clustering using entropy and Information Gain Ratio (IGR) K(Y/X) = (H(X)–H(Y/X))/H(Y) is used, where H(Y)=-ΣPi ln(Pi). This technique allows adjusting the boundaries of clusters. It is shown that the information gain ratio (IGR) grows monotonically and simultaneously with degree of connectivity between two variables. This approach has some preferences if compared, for example, with correlation analysis due to relatively smaller sensitivity to shape of functional dependencies. Variant of an algorithm to implement the proposed method with some analysis of above problem of environmental effects is also presented. It was shown that proposed method converges with finite number of steps.

Keywords: Clustering, Correlation analysis, EnvironmentalParameters, Information Gain Ratio, Mental Performance.

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Authors: Yan Su, L. C. Chan

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A novel typical day prediction model have been built and validated by the measured data of a grid-connected solar photovoltaic (PV) system in Macau. Unlike conventional statistical method used by previous study on PV systems which get results by averaging nearby continuous points, the present typical day statistical method obtain the value at every minute in a typical day by averaging discontinuous points at the same minute in different days. This typical day statistical method based on discontinuous point averaging makes it possible for us to obtain the Gaussian shape dynamical distributions for solar irradiance and output power in a yearly or monthly typical day. Based on the yearly typical day statistical analysis results, the maximum possible accumulated output energy in a year with on site climate conditions and the corresponding optimal PV system running time are obtained. Periodic Gaussian shape prediction models for solar irradiance, output energy and system energy efficiency have been built and their coefficients have been determined based on the yearly, maximum and minimum monthly typical day Gaussian distribution parameters, which are obtained from iterations for minimum Root Mean Squared Deviation (RMSD). With the present model, the dynamical effects due to time difference in a day are kept and the day to day uncertainty due to weather changing are smoothed but still included. The periodic Gaussian shape correlations for solar irradiance, output power and system energy efficiency have been compared favorably with data of the PV system in Macau and proved to be an improvement than previous models.

Keywords: Grid Connected, RMSD, Solar PV System, Typical Day.

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Authors: Jinyong Yao, Hongzhi Li, Chao Du, Jiao Li

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Reliability of long-term storage products is related to the availability of the whole system, and the evaluation of storage life is of great necessity. These products are usually highly reliable and little failure information can be collected. In this paper, an analytical method based on data from accelerated storage life test is proposed to evaluate the reliability index of the long-term storage products. Firstly, singularities are eliminated by data normalization and residual analysis. Secondly, with the preprocessed data, the degradation path model is built to obtain the pseudo life values. Then by life distribution hypothesis, we can get the estimator of parameters in high stress levels and verify failure mechanism consistency. Finally, the life distribution under the normal stress level is extrapolated via the acceleration model and evaluation of the actual average life is available. An application example with the camera stabilization device is provided to illustrate the methodology we proposed.

Keywords: Accelerated storage life test, failure mechanism consistency, life distribution, reliability.

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Authors: Saowaluck Ukrisdawithid

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The thermal conductivity of thermal insulation materials are measured by Heat Flow Meter (HFM) apparatus. The components of uncertainty are complex and difficult on routine measurement by modelling approach. In this study, uncertainty of thermal conductivity measurement was estimated by single laboratory validation approach. The within-laboratory reproducibility was 1.1%. The standard uncertainty of method and laboratory bias by using SRM1453 expanded polystyrene board was dominant at 1.4%. However, it was assessed that there was no significant bias. For sample measurement, the sources of uncertainty were repeatability, density of sample and thermal conductivity resolution of HFM. From this approach to sample measurements, the combined uncertainty was calculated. In summary, the thermal conductivity of sample, polystyrene foam, was reported as 0.03367 W/m·K ± 3.5% (k = 2) at mean temperature 23.5 °C. The single laboratory validation approach is simple key of routine testing laboratory for estimation uncertainty of thermal conductivity measurement by using HFM, according to ISO/IEC 17025-2017 requirements. These are meaningful for laboratory competent improvement, quality control on products, and conformity assessment.

Keywords: Single laboratory validation approach, within-laboratory reproducibility, method and laboratory bias, certified reference material.

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Authors: Salam Alzubaidi, G. Fantoni, F. Failli, M. Frosolini

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The dynamic facility layout problem is a really critical issue in the competitive industrial market; thus, solving this problem requires robust design and effective simulation systems. The sustainable simulation requires inputting reliable and accurate data into the system. So this paper describes an automated system integrated into the real environment to measure the duration of the material handling operations, collect the data in real-time, and determine the variances between the actual and estimated time schedule of the operations in order to update the simulation software and redesign the facility layout periodically. The automated method- time measurement system collects the real data through using Radio Frequency-Identification (RFID) and Internet of Things (IoT) technologies. Hence, attaching RFID- antenna reader and RFID tags enables the system to identify the location of the objects and gathering the time data. The real duration gathered will be manipulated by calculating the moving average duration of the material handling operations, choosing the shortest material handling path, and then updating the simulation software to redesign the facility layout accommodating with the shortest/real operation schedule. The periodic simulation in real-time is more sustainable and reliable than the simulation system relying on an analysis of historical data. The case study of this methodology is in cooperation with a workshop team for producing mechanical parts. Although there are some technical limitations, this methodology is promising, and it can be significantly useful in the redesigning of the manufacturing layout.

Keywords: Dynamic facility layout problem, internet of things, method time measurement, radio frequency identification, simulation.

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Authors: Aisha Tarek Noour, Nick Hubbard

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Learner motivation is considered to be an important component for the Blended e-Learning (BL) Method. BL is an effective learning method in multiple domains, which opens several opportunities for its participants to engage in the learning environment. This research explores the learners’ perspective of BL according to the Self-Determination Theory (SDT). It identifies the opportunities and challenges for using the BL in Logistics Education (LE) in Egyptian Higher Education (HE). SDT is approached from different perspectives within the relationship between Intrinsic Motivation (IM), Extrinsic Motivation (EM) and Amotivation (AM). A self-administered face-to-face questionnaire was used to collect data from learners who were geographically widely spread around three colleges of International Transport and Logistics (CILTs) at the Arab Academy for Science, Technology and Maritime Transport (AAST&MT) in Egypt. Six hundred and sixteen undergraduates responded to a questionnaire survey. Respondents were drawn from three branches in Greater Cairo, Alexandria, and Port Said. The data analysis used was SPSS 22 and AMOS 18.

Keywords: Intrinsic Motivation, Extrinsic Motivation, Amotivation, Blended e-Learning, Self Determination Theory.

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Authors: Weifeng Wang, Xianwei Zeng, Jianping Ding

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Nanomaterials have attracted considerable attention during the last two decades, due to their unusual electrical, mechanical and other physical properties as compared with their bulky counterparts. The mechanical properties of nanostructured materials show strong size dependency, which has been explained within the framework of continuum mechanics by including the effects of surface stress. The size-dependent deformations of two-dimensional nanosized structures with surface effects are investigated in the paper by the finite element method. Truss element is used to evaluate the contribution of surface stress to the total potential energy and the Gurtin and Murdoch surface stress model is implemented with ANSYS through its user programmable features. The proposed approach is used to investigate size-dependent stress concentration around a nanosized circular hole and the size-dependent effective moduli of nanoporous materials. Numerical results are compared with available analytical results to validate the proposed modeling approach.

Keywords: Nanomaterials, finite element method, sizedependency, surface stress

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Authors: Achmad Nizar Hidayanto, Elisabeth Martha Koeanan

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Image clustering is a process of grouping images based on their similarity. The image clustering usually uses the color component, texture, edge, shape, or mixture of two components, etc. This research aims to explore image clustering using color composition. In order to complete this image clustering, three main components should be considered, which are color space, image representation (feature extraction), and clustering method itself. We aim to explore which composition of these factors will produce the best clustering results by combining various techniques from the three components. The color spaces use RGB, HSV, and L*a*b* method. The image representations use Histogram and Gaussian Mixture Model (GMM), whereas the clustering methods use KMeans and Agglomerative Hierarchical Clustering algorithm. The results of the experiment show that GMM representation is better combined with RGB and L*a*b* color space, whereas Histogram is better combined with HSV. The experiments also show that K-Means is better than Agglomerative Hierarchical for images clustering.

Keywords: Image clustering, feature extraction, RGB, HSV, L*a*b*, Gaussian Mixture Model (GMM), histogram, Agglomerative Hierarchical Clustering (AHC), K-Means, Expectation-Maximization (EM).

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Authors: C. Ardil

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Neutrosophic logic decision analysis is proposed as a method of stealth fighter aircraft selection for Turkish Air Force. The opinion of experts is employed to rank the alternatives across a set of criteria. The analyst uses neutrosophic logic numbers to describe the experts' preferences. This approach can handle the situation in the case of unavailability of precise data, which is most commonly the case in stealth fighter aircraft selection. Neutrosophic logic numbers can consider the imprecision of the factors affecting decision making such as stealth analysis, survivability analysis, and performance analysis. Neutrosophic logic ranking is achieved using weighted arithmetic operator and weighted geometric operator and the alternatives are ranked from best to worst. An example is also presented to illustrate the applicability and effectiveness of the proposed method. 

Keywords: Neutrosophic set theory, stealth fighter aircraft selection, multiple criteria decision-making, neutrosophic logic decision making, Turkish Air Force, MCDM

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Authors: Eric Sitorus, Septian Prahastudhi, Turgod Nainggolan, Erwin Riyanto

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Mining by block or panel caving is a mining method that takes advantage of fractures within an ore body, coupled with gravity, to extract material from a predetermined column of ore. The caving column is weakened from beneath through the use of undercutting, after which the ore breaks up and is extracted from below in a continuous cycle. The nature of this method induces cyclical stresses on the pillars of excavations as stress is built up and released over time, which has a detrimental effect on both the installed ground support and the rock mass itself. Ground support capacity, especially on the production where excavation void ratio is highest, is subjected to heavy loading. Strain above threshold of the elongation of support capacity can yield resulting in damage to excavations. Geotechnical engineers must evaluate not only the remnant capacity of ground support systems but also investigate depth of rock mass yield within pillars, backs and floors. Ground Penetrating Radar (GPR) is a geophysical method that has the ability to evaluate rock mass damage using electromagnetic waves. This paper illustrates a case study from the Grasberg mining complex where non-invasive information on the depth of damage and condition of the remaining rock mass was required. GPR with 100 MHz antenna resolution was used to obtain images of the subsurface to determine rehabilitation requirements prior to recommencing production activities. The GPR surveys were used to calibrate the reflection coefficient response of varying rock mass conditions to known Rock Quality Designation (RQD) parameters observed at the mine. The calibrated GPR survey allowed site engineers to map subsurface conditions and plan rehabilitation accordingly.

Keywords: Block caving, ground penetrating radar, reflectivity, RQD.

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Authors: Rekha P. Labade, Shankar B. Deosarkar, Narayan Pisharoty

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In this article design and optimization of square printed monopole antenna for wireless application is proposed. Theory of characteristics mode (TCM) is used for analysis of current modes on the antenna. TCM analysis shows that beveled ground plane improves the impedance bandwidth. The antenna operates over the frequency range from 1.860 GHz to 5 GHz for a VSWR ≤ 2, covering the GSM (1900-1990MHz), IMT-2000(1920-2170MHz), Bluetooth (2.400-2484 MHz) and lower band of ultrawideband (UWB). Stable radiation pattern shows minimal pulse distortion. The radiation pattern is omni-directional along the H-plane and figure of eight along the E-plane. Size of proposed antenna is 39 mm x 29 mm x 1.6mm. Antenna is simulated using CAD FEKO suite (6.2) using method of moment. A prototype antenna is fabricated using FR4 dielectric substrate with a dielectric constant of 4.4 and loss tangent of 0.02 to validate the simulated and measured results of the proposed antenna. Measured results are in good agreement with simulated results.

Keywords: Destructive Ground Surface (DGS), Method of moment, Theory of characteristics mode, UWB, VSWR.

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Authors: Boonyisa Wanitwattanarumlug, Apanee Luengnaruemitchai, Sujitra Wongkasemjit

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The complexity of lignocellulosic biomass requires a pretreatment step to improve the yield of fermentable sugars. The efficient pretreatment of corn cobs using microwave and potassium hydroxide and enzymatic hydrolysis was investigated. The objective of this work was to characterize the optimal condition of pretreatment of corn cobs using microwave and potassium hydroxide enhance enzymatic hydrolysis. Corn cobs were submerged in different potassium hydroxide concentration at varies temperature and resident time. The pretreated corn cobs were hydrolyzed to produce the reducing sugar for analysis. The morphology and microstructure of samples were investigated by Thermal gravimetric analysis (TGA, scanning electron microscope (SEM), X-ray diffraction (XRD). The results showed that lignin and hemicellulose were removed by microwave/potassium hydroxide pretreatment. The crystallinity of the pretreated corn cobs was higher than the untreated. This method was compared with autoclave and conventional heating method. The results indicated that microwave-alkali treatment was an efficient way to improve the enzymatic hydrolysis rate by increasing its accessibility hydrolysis enzymes.

Keywords: Corn cobs, Enzymatic hydrolysis, Microwave, Potassium hydroxide, Pretreatment.

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Authors: M.T. Shervani-Tabar, M. Rezaee, E. Madadi Kandjani

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Dynamics of a vapour bubble generated due to a high local energy input near a circular thin bronze plate in the absence of the buoyancy forces is numerically investigated in this paper. The bubble is generated near a thin bronze plate and during the growth and collapse of the bubble, it deforms the nearby plate. The Boundary Integral Equation Method is employed for numerical simulation of the problem. The fluid is assumed to be incompressible, irrotational and inviscid and the surface tension on the bubble boundary is neglected. Therefore the fluid flow around the vapour bubble can be assumed as a potential flow. Furthermore, the thin bronze plate is assumed to have perfectly plastic behaviour. Results show that the displacement of the circular thin bronze plate has considerable effect on the dynamics of its nearby vapour bubble. It is found that by decreasing the thickness of the thin bronze plate, the growth and collapse rate of the bubble becomes higher and consequently the lifetime of the bubble becomes shorter.

Keywords: Vapour Bubble, Thin Bronze Plate, Boundary Integral Equation Method.

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Authors: Jawad Makki, Anne-Marie Alquier, Violaine Prince

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In this paper we propose an NLP-based method for Ontology Population from texts and apply it to semi automatic instantiate a Generic Knowledge Base (Generic Domain Ontology) in the risk management domain. The approach is semi-automatic and uses a domain expert intervention for validation. The proposed approach relies on a set of Instances Recognition Rules based on syntactic structures, and on the predicative power of verbs in the instantiation process. It is not domain dependent since it heavily relies on linguistic knowledge. A description of an experiment performed on a part of the ontology of the PRIMA1 project (supported by the European community) is given. A first validation of the method is done by populating this ontology with Chemical Fact Sheets from Environmental Protection Agency2. The results of this experiment complete the paper and support the hypothesis that relying on the predicative power of verbs in the instantiation process improves the performance.

Keywords: Information Extraction, Instance Recognition Rules, Ontology Population, Risk Management, Semantic analysis.

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Authors: Liu Ying-jie, Lu Wen-bo, Peng Cheng-jian

Abstract:

With the development of the automotive technology and electric vehicle, the contribution of the wind noise on the interior noise becomes the main source of noise. The main transfer path which the exterior excitation is transmitted through is the greenhouse panels and side windows. Simulating the wind noise transmitted into the vehicle accurately in the early development stage can be very challenging. The basic methodologies of this study were based on the Lighthill analogy; the exterior flow field around a passenger car was computed using unsteady Computational Fluid Dynamics (CFD) firstly and then a Finite Element Method (FEM) was used to compute the interior acoustic response. The major findings of this study include: 1) The Sound Pressure Level (SPL) response at driver’s ear locations is mainly induced by the turbulence pressure fluctuation; 2) Peaks were found over the full frequency range. It is found that the methodology used in this study could predict the interior wind noise induced by the exterior aerodynamic excitation in industry.

Keywords: Wind noise, computational fluid dynamics, finite element method, passenger car.

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Authors: Truong Nguyen Luan Vu, Moonyong Lee

Abstract:

The interactions between input/output variables are a very common phenomenon encountered in the design of multi-loop controllers for interacting multivariable processes, which can be a serious obstacle for achieving a good overall performance of multiloop control system. To overcome this impediment, the decomposed dynamic interaction analysis is proposed by decomposing the multiloop control system into a set of n independent SISO systems with the corresponding effective open-loop transfer function (EOTF) within the dynamic interactions embedded explicitly. For each EOTF, the reduced model is independently formulated by using the proposed reduction design strategy, and then the paired multi-loop proportional-integral-derivative (PID) controller is derived quite simply and straightforwardly by using internal model control (IMC) theory. This design method can easily be implemented for various industrial processes because of its effectiveness. Several case studies are considered to demonstrate the superior of the proposed method.

Keywords: Multi-loop PID controller, internal model control(IMC), effective open-loop transfer function (EOTF)

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Authors: Kavita H. Dhanawade, Hanamant S. Dhanawade

Abstract:

Heat transfer enhancement objects like extended surfaces, fins etc. are chosen for their thermal performance as well as for other design parameters depending on various applications. The present paper is on experimental study to investigate the heat transfer enhancement through wire mesh fin arrays equipped with horizontal base plate. The data used in performance analysis were obtained experimentally for the material (mild steel) for different heat inputs such as 40, 60, 80, 100 and 120 watt, by varying wire mesh diameter, fin height and spacing between two fin arrays. Using the Taguchi experimental design method, optimum design parameters and their levels were investigated. Average heat transfer coefficient was considered as a performance characteristic parameter. An L₉ (3³) orthogonal array was selected as an experimental plan. Optimum results were found by experimenting. It is observed that the wire mesh diameter and fin height have a higher impact on heat transfer coefficient as compared to spacing between two fin arrays.

Keywords: Heat transfer enhancement, finned surface, wire mesh diameter, natural convection.

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