Search results for: linear decomposition methods

Authors: Mahtab Davari, Charles Edward Okon, Somayeh Aghanavesi

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Every institute of learning is usually interested in the performance of enrolled students. The level of these performances determines the approach an institute of study may adopt in rendering academic services. The focus of this paper is to evaluate students' academic performance in given courses of study using machine learning methods. This study evaluated various supervised machine learning classification algorithms such as Logistic Regression (LR), Support Vector Machine, Random Forest, Decision Tree, K-Nearest Neighbors, Linear Discriminant Analysis, and Quadratic Discriminant Analysis, using selected features to predict study performance. The accuracy, precision, recall, and F1 score obtained from a 5-Fold Cross-Validation were used to determine the best classification algorithm to predict students’ performances. SVM (using a linear kernel), LDA, and LR were identified as the best-performing machine learning methods. Also, using the LR model, this study identified students' educational habits such as reading and paying attention in class as strong determinants for a student to have an above-average performance. Other important features include the academic history of the student and work. Demographic factors such as age, gender, high school graduation, etc., had no significant effect on a student's performance.

Keywords: student performance, supervised machine learning, classification, cross-validation, prediction

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Authors: Pavel A. Strizhak, Geniy V. Kuznetsov, Ivan S. Voytkov, Dmitri V. Antonov

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This paper presents the results of experiments carried out at a specialized test site for establishing macroscopic patterns of heat and mass transfer processes at localizing model combustion sources of ground forest fires with the use of barrier lines in the form of a wetted lay of material in front of the zone of flame burning and thermal decomposition. The experiments were performed using needles, leaves, twigs, and mixtures thereof. The dimensions of the model combustion source and the ranges of heat release correspond well to the real conditions of ground forest fires. The main attention is paid to the complex analysis of the effect of dispersion of water aerosol (concentration and size of droplets) used to form the barrier line. It is shown that effective conditions for localization and subsequent suppression of flame combustion and thermal decomposition of forest fuel can be achieved by creating a group of barrier lines with different wetting width and depth of the material. Relative indicators of the effectiveness of one and combined barrier lines were established, taking into account all the main characteristics of the processes of suppressing burning and thermal decomposition of forest combustible materials. We performed the prediction of the necessary and sufficient parameters of barrier lines (water volume, width, and depth of the wetted lay of the material, specific irrigation density) for combustion sources with different dimensions, corresponding to the real fire extinguishing practice.

Keywords: forest fire, barrier water lines, pyrolysis front, flame front

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Authors: Vijaya K. Srivastava, Davide Spinello

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This paper presents performance of two robust gradient-based heuristic optimization procedures based on 3ⁿ enumeration and tunneling approach to seek global optimum of constrained integer problems. Both these procedures consist of two distinct phases for locating the global optimum of integer problems with a linear or non-linear objective function subject to linear or non-linear constraints. In both procedures, in the first phase, a local minimum of the function is found using the gradient approach coupled with hemstitching moves when a constraint is violated in order to return the search to the feasible region. In the second phase, in one optimization procedure, the second sub-procedure examines 3ⁿ integer combinations on the boundary and within hypercube volume encompassing the result neighboring the result from the first phase and in the second optimization procedure a tunneling function is constructed at the local minimum of the first phase so as to find another point on the other side of the barrier where the function value is approximately the same. In the next cycle, the search for the global optimum commences in both optimization procedures again using this new-found point as the starting vector. The search continues and repeated for various step sizes along the function gradient as well as that along the vector normal to the violated constraints until no improvement in optimum value is found. The results from both these proposed optimization methods are presented and compared with one provided by popular MS Excel solver that is provided within MS Office suite and other published results.

Keywords: constrained integer problems, enumerative search algorithm, Heuristic algorithm, Tunneling algorithm

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Authors: Fawwaz Eniola Fajingbesi, Nur Shahida Midia, Elsheikh M. A. Elsheikh, Siti Hajar Yusoff

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Empirical analysis of lightning related phenomena in real time is extremely dangerous due to the relatively high electric discharge involved. Hence, design and optimization of efficient grounding systems depending on real time empirical methods are impeded. Using numerical methods, the dynamics of complex systems could be modeled hence solved as sets of linear and non-linear systems . In this work, the induced current distribution as lightning strike traverses the soil have been numerically modeled in a 2D axial-symmetry and solved using finite element method (FEM) in COMSOL Multiphysics 5.2 AC/DC module. Stratified and non- stratified electrode system were considered in the solved model and soil conductivity (σ) varied between 10 – 58 mS/m. The result discussed therein were the electric field distribution, current distribution and soil ionization phenomena. It can be concluded that the electric field and current distribution is influenced by the injected electric potential and the non-linearity in soil conductivity. The result from numerical calculation also agrees with previously laboratory scale empirical results.

Keywords: current distribution, grounding systems, lightning discharge, numerical model, soil conductivity, soil ionization

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Authors: Fehmi Bouguezzi

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This paper studies optimal licensing regimes in a linear Hotelling model where firms are located at the end points of the city and where the transportation cost is not linear but quadratic. We study for that a more general cost function and we try to compare the findings with the results of the linear cost. We find the same optimal licensing regimes. A per unit royalty is optimal when innovation is not drastic and no licensing is better when innovation is drastic. We also find that no licensing is always better than fixed fee licensing.

Keywords: Hotelling model, technology transfer, patent licensing, quadratic transportation cost

Procedia PDF Downloads 328

Authors: Tunjo Perič, Marin Fatović

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In this paper a new methodology for vendor selection and supply quotas determination (VSSQD) is proposed. The problem of VSSQD is solved by the model that combines revised weighting method for determining the objective function coefficients, and a multiple objective linear programming (MOLP) method based on the cooperative game theory for VSSQD. The criteria used for VSSQD are: (1) purchase costs and (2) product quality supplied by individual vendors. The proposed methodology is tested on the example of flour purchase for a bakery with two decision makers.

Keywords: cooperative game theory, multiple objective linear programming, revised weighting method, vendor selection

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Authors: Mohammedi Ferhate

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This paper deals with the generalized the notion of the function of wave a micro particle moving free, the concept of the linear operator in the representation function delta of Dirac which is a generalization of the symbol of Kronecker to the case of a continuous variation of the sizes concerned with the condition of orthonormation of the Eigen functions the use of linear operators and their Eigen functions in connection with the solution of given differential equations, it is of interest to study the properties of the operators themselves and determine which of them follow purely from the nature of the operators, without reference to specific forms of Eigen functions. The models simulation examples are also presented.

Keywords: function, operator, simulation, wave

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Authors: M. Najafi, F. Rahimi Dehgolan

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In this paper, the dynamic modeling of a single-link flexible beam with a tip mass is given by using Hamilton's principle. The link has been rotational and translational motion and it was assumed that the beam is moving with a harmonic velocity about a constant mean velocity. Non-linearity has been introduced by including the non-linear strain to the analysis. Dynamic model is obtained by Euler-Bernoulli beam assumption and modal expansion method. Also, the effects of rotary inertia, axial force, and associated boundary conditions of the dynamic model were analyzed. Since the complex boundary value problem cannot be solved analytically, the multiple scale method is utilized to obtain an approximate solution. Finally, the effects of several conditions on the differences among the behavior of the non-linear term, mean velocity on natural frequencies and the system stability are discussed.

Keywords: non-linear vibration, stability, axially moving beam, bifurcation, multiple scales method

Procedia PDF Downloads 339

Authors: Débora V. Busman, Venerando E. Amaro, Mattheus da C. Prudêncio

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Prognostic studies of the shoreline are of utmost importance for Ponta Negra Beach, located in Natal, Northeastern Brazil, where the infrastructure recently built along the shoreline is severely affected by flooding and erosion. This study compares shoreline predictions using three linear regression methods (LMS, LRR and WLR) and tries to discern the best method for different shoreline position scenarios. The methods have shown erosion on the beach in each of the scenarios tested, even in less intense dynamic conditions. The WLA_A with confidence interval of 95% was the well-adjusted model and calculated a retreat of -1.25 m/yr to -2.0 m/yr in hot spot areas. The change of the shoreline on Ponta Negra Beach can be measured as a negative exponential curve. Analysis of these methods has shown a correlation with the morphodynamic stage of the beach.

Keywords: coastal erosion, prognostic model, DSAS, environmental safety

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Authors: Sunil Mittal, Sukhpreet Singh, Hardeep Kaur

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A simple voltammetric technique for on-line analysis of arsenite [As (III)] is reported. Owing to the affinity of As (III) with thiol group of proteins and enzymes, cysteine has been employed as reducing agent. The reduction study of As(III)-cysteine complex on indium tin oxide (ITO) electrode has been explored. The experimental parameters such as scan rate, cysteine concentration, pH etc. were optimized to achieve As (III) determination. The developed method provided dynamic linear range of detection from 0.1 to 1 mM with a detection limit of 0.1 mM. The method is applicable to environmental monitoring of As (III) from highly contaminated sources such as industrial effluents, wastewater sludge etc.

Keywords: arsenite, cysteine, linear sweep voltammetry, reduction

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Authors: Hung-Shuo Wu, Huan-Chieh Chiu, Xiang-Yao Zheng, Yu-Cheng Yang, Chien-Hao Wang, Jen-Cheng Wang, Chwan-Lu Tseng, Joe-Air Jiang

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Dynamic Thermal Rating (DTR) provides crucial information by estimating the ampacity of transmission lines to improve power dispatching efficiency. To perform the DTR, it is necessary to install on-line thermal sensors to monitor conductor temperature and weather variables. A simple and intuitive strategy is to allocate a thermal sensor to every span of transmission lines, but the cost of sensors might be too high to bear. To deal with the cost issue, a thermal sensor placement problem must be solved. This research proposes and implements a hybrid algorithm which combines proper orthogonal decomposition (POD) with particle swarm optimization (PSO) methods. The proposed hybrid algorithm solves a multi-objective optimization problem that concludes the minimum number of sensors and the minimum error on conductor temperature, and the optimal sensor placement is determined simultaneously. The data of 345 kV transmission lines and the hourly weather data from the Taiwan Power Company and Central Weather Bureau (CWB), respectively, are used by the proposed method. The simulated results indicate that the number of sensors could be reduced using the optimal placement method proposed by the study and an acceptable error on conductor temperature could be achieved. This study provides power companies with a reliable reference for efficiently monitoring and managing their power grids.

Keywords: dynamic thermal rating, proper orthogonal decomposition, particle swarm optimization, sensor placement, smart grid

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Authors: J. Dharmaraj, C. Gunasekaran

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Invertebrates are the reliable ecological indicators of disturbance of the forest ecosystems and they respond to environment changes more quickly than other fauna. Among these the terrestrial invertebrates are vital to functioning ecosystems, contributing to processes such as decomposition, nutrient cycling and soil fertility. The natural ecosystems of the forests have been subject to various types of disturbances, which lead to decline of flora and fauna. The comparative diversity of micro-arthropods in natural forest, wattle plantation and eucalyptus plantations were studied in Nilgiris. The study area was divided in to five major sites (Emerald (Site-I), Thalaikundha (Site-II), Kodapmund (Site-III), Aravankad (Site-IV), Kattabettu (Site-V). The research was conducted during period from March 2014 to August 2014. The leaf and soil samples were collected and isolated by using Berlese funnel extraction methods. Specimens were isolated and identified according to their morphology (Balogh 1972). In the present study results clearly showed the variation in soil pH, NPK (Major Nutrients) and organic carbon among the study sites. The chemical components of the leaf litters of the plantation decreased the diversity of micro-arthropods and decomposition rate leads to low amount of carbon and other nutrients present in the soil. Moreover eucalyptus and wattle plantations decreases the availability of the ground water source to other plantations and micro-arthropods and hences affects the soil fertility. Hence, the present study suggests to minimize the growth of wattle and eucalyptus tree plantations in the natural areas which may help to reduce the decline of forests.

Keywords: micro-arthropods, assemblage, berlese funnel, morphology, NPK, nilgiris

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Authors: Mohammed F. Almograbi

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For reinforced concrete panels the risk of failure due to compression -tension state of stresses, results from pure shear or torsion, can be a major problem. The present calculation methods for such stresses from multiple influences are without taking into account the softening of cracked concrete remains conservative. The non-linear finite element method has become an important and increasingly used tool for the analysis and assessment of the structures by including cracking softening and tension-stiffening. The aim of this paper is to test a computer program refined recently and to simulate the compression response of cracked concrete element and to compare with the available experimental results.

Keywords: reinforced concrete panels, compression-tension, shear, torsion, compression softening, tension stiffening, non-linear finite element analysis

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Authors: Redvan Ghasemlounia, Elham Ansari, Hikmet Kerem Cigizoglu

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Hydrological modeling in arid and semi-arid regions is very important. Iran has many regions with these climate conditions such as Chaharmahal and Bakhtiari province that needs lots of attention with an appropriate management. Forecasting of hydrological parameters and estimation of hydrological events of catchments, provide important information that used for design, management and operation of water resources such as river systems, and dams, widely. Discharge in rivers is one of these parameters. This study presents the application and comparison of some estimation methods such as Feed-Forward Back Propagation Neural Network (FFBPNN), Multi Linear Regression (MLR), Gene Expression Programming (GEP) and Bayesian Network (BN) to predict the daily flow discharge of the Soolegan River, located at Chaharmahal and Bakhtiari province, in Iran. In this study, Soolegan, station was considered. This Station is located in Soolegan River at 51° 14՜ Latitude 31° 38՜ longitude at North Karoon basin. The Soolegan station is 2086 meters higher than sea level. The data used in this study are daily discharge and daily precipitation of Soolegan station. Feed Forward Back Propagation Neural Network(FFBPNN), Multi Linear Regression (MLR), Gene Expression Programming (GEP) and Bayesian Network (BN) models were developed using the same input parameters for Soolegan's daily discharge estimation. The results of estimation models were compared with observed discharge values to evaluate performance of the developed models. Results of all methods were compared and shown in tables and charts.

Keywords: ANN, multi linear regression, Bayesian network, forecasting, discharge, gene expression programming

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Authors: Levan Nadareishvili, Roland Bakuradze, Barbara Kilosanidze, Nona Topuridze, Liana Sharashidze, Ineza Pavlenishvili

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Some regularities of formation of a new structural state of the thermoplastic polymers-gradually oriented (stretched) state (GOS) are discussed. Transition into GOS is realized by the graded oriented stretching-by action of inhomogeneous mechanical field on the isotropic linear polymers or by zonal stretching that is implemented on a standard tensile-testing machine with using a specially designed zone stretching device (ZSD). Both technical approaches (especially zonal stretching method) allows to manage the such quantitative parameters of gradually oriented polymers as a range of change in relative elongation/orientation degree, length of this change and profile (linear, hyperbolic, parabolic, logarithmic, etc.). Uniaxial graded stretching method should be considered as an effective technological solution to create polymer materials with a predetermined gradient of physical properties.

Keywords: controlled graded stretching, gradually oriented state, linear polymers, zone stretching device

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Authors: Kumaran Narayanan, Pei-Sheng Liew

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This paper adapts the bacteriophage N15 protelomerase enzyme to assemble linear chromosomes as vectors for gene expression in human cells. Phage N15 has the unique ability to replicate as a linear plasmid with telomeres in E. coli during its prophage stage of life-cycle. The virus-encoded protelomerase enzyme cuts its circular genome and caps its ends to form hairpin telomeres, resulting in a linear human-chromosome-like structure in E. coli. In mammalian cells, however, no enzyme with TelN-like activities has been found. In this work, we show for the first-time transfer of the protelomerase from phage into human and mouse cells and demonstrate recapitulation of its activity in these hosts. The function of this enzyme is assayed by demonstrating cleavage of its target DNA, followed by detecting telomere formation based on its resistance to recBCD enzyme digestion. We show protelomerase expression persists for at least 60 days, which indicates limited silencing of its expression. Next, we show that an intact human β-globin gene delivered on this linear chromosome accurately retains its expression in the human cellular environment for at least 60 hours, demonstrating its stability and potential as a vector. These results demonstrate that the N15 protelomerse is able to function in mammalian cells to cut and heal DNA to create telomeres, which provides a new tool for creating novel structures by DNA resolution in these hosts.

Keywords: chromosome, beta-globin, DNA, gene expression, linear vector

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Authors: Kang Sungjae

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This research proposes a gait stability evaluation technique based on the linear inverted pendulum model and moving support foot Zero Moment Point. With this, an improvement towards the gait analysis of the orthosis walk is validated. The application of Lagrangian mechanics approximation to the solutions of the dynamics equations for the linear inverted pendulum does not only simplify the solution, but it provides a smooth Zero Moment Point for the double feet support phase. The Zero Moment Point gait analysis techniques mentioned above validates reference trajectories for the center of mass of the gait orthosis, the timing of the steps and landing position references for the swing feet. The stability evaluation technique are tested with a 6 DOF powered gait orthosis. The results obtained are promising for implementations.

Keywords: locomotion, center of mass, gait stability, linear inverted pendulum model

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Authors: T. Zitoun, M. Bouhadef

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When a partially or completely immersed solid moves in a liquid such as water, it undergoes a force called hydrodynamic drag. Reducing this force has always been the objective of hydrodynamic engineers to make water slide better on submerged bodies. This paper deals with the examination of the different terms composing the analytical solution of the flow over an obstacle embedded at the bottom of a hydraulic channel. We have chosen to use a linear method to study a two-dimensional flow over an obstacle, in order to understand the evolution of the drag. We set the following assumptions: incompressible inviscid fluid, irrotational flow, low obstacle height compared to the water height. Those assumptions allow overcoming the difficulties associated with modelling these waves. We will mathematically formulate the equations that allow the determination of the stream function, and then the free surface equation. A similar method is used to determine the exact analytical solution for an obstacle in the shape of a sinusoidal arch.

Keywords: analytical solution, free-surface wave, hydraulic channel, inviscid fluid

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Authors: P. Priyanka, S. Shruthi, N. Guruprasad

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Health is a common theme in most cultures. In fact all communities have their concepts of health, as part of their culture. Health continues to be a neglected entity. Planning of Human diet should be done very careful by selecting the food items or groups of food items also the composition involved. Low price and good taste of foods are regarded as two major factors for optimal human nutrition. Linear programming techniques have been extensively used for human diet formulation for quiet good number of years. Through the process, we mainly apply “The Simplex Method” which is a very useful statistical tool based on the theorem of Elementary Row Operation from Linear Algebra and also incorporate some other necessary rules set by the Simplex Method to help solve the problem. The study done by us is an attempt to develop a programming model for optimal planning and best use of nutrient ingredients.

Keywords: diet formulation, linear programming, nutrient ingredients, optimization, simplex method

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Authors: Vikrant Gupta, Amrit Goswami

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The fixed income market forms the basis of the modern financial market. All other assets in financial markets derive their value from the bond market. Owing to its over-the-counter nature, corporate bonds have relatively less data publicly available and thus is researched upon far less compared to Equities. Bond price prediction is a complex financial time series forecasting problem and is considered very crucial in the domain of finance. The bond prices are highly volatile and full of noise which makes it very difficult for traditional statistical time-series models to capture the complexity in series patterns which leads to inefficient forecasts. To overcome the inefficiencies of statistical models, various machine learning techniques were initially used in the literature for more accurate forecasting of time-series. However, simple machine learning methods such as linear regression, support vectors, random forests fail to provide efficient results when tested on highly complex sequences such as stock prices and bond prices. hence to capture these intricate sequence patterns, various deep learning-based methodologies have been discussed in the literature. In this study, a recurrent neural network-based deep learning model using long short term networks for prediction of corporate bond prices has been discussed. Long Short Term networks (LSTM) have been widely used in the literature for various sequence learning tasks in various domains such as machine translation, speech recognition, etc. In recent years, various studies have discussed the effectiveness of LSTMs in forecasting complex time-series sequences and have shown promising results when compared to other methodologies. LSTMs are a special kind of recurrent neural networks which are capable of learning long term dependencies due to its memory function which traditional neural networks fail to capture. In this study, a simple LSTM, Stacked LSTM and a Masked LSTM based model has been discussed with respect to varying input sequences (three days, seven days and 14 days). In order to facilitate faster learning and to gradually decompose the complexity of bond price sequence, an Empirical Mode Decomposition (EMD) has been used, which has resulted in accuracy improvement of the standalone LSTM model. With a variety of Technical Indicators and EMD decomposed time series, Masked LSTM outperformed the other two counterparts in terms of prediction accuracy. To benchmark the proposed model, the results have been compared with traditional time series models (ARIMA), shallow neural networks and above discussed three different LSTM models. In summary, our results show that the use of LSTM models provide more accurate results and should be explored more within the asset management industry.

Keywords: bond prices, long short-term memory, time series forecasting, empirical mode decomposition

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Authors: Yogesh Kumar, Adarsh Kumar

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A body farm is a research facility where research is done on forensic investigation and medico-legal disciplines like forensic entomology, forensic pathology, forensic anthropology, forensic archaeology, and related areas of forensic veterinary. All the research is done to collect data on the rate of decomposition (animal and human) and forensically important insects to assist in crime detection. The data collected is used by forensic pathologists, forensic experts, and other experts for the investigation of crime cases and further research. The research work includes different conditions of a dead body like fresh, bloating, decay, dry, and skeleton, and data on local insects which depends on the climatic conditions of the local areas of that country. Therefore, it is the need of time to collect appropriate data in managed conditions with a proper set-up in every country. Hence, it is the duty of the scientific community of every country to establish/propose such facilities for justice and social management. The body farms are also used for training of police, military, investigative dogs, and other agencies. At present, only four countries viz. U.S., Australia, Canada, and Netherlands have body farms and related facilities in organised manner. There is no body farm in Asia also. In India, we have been trying to establish a body farm in A&N Islands that is near Singapore, Malaysia, and some other Asian countries. In view of the above, it becomes imperative to discuss the matter with Asian countries to collect the data on decomposition in a proper manner by establishing a body farm. We can also share the data, knowledge, and expertise to collaborate with one another to make such facilities better and have good scientific relations to promote science and explore ways of investigation at the world level.

Keywords: body farm, rate of decomposition, forensically important flies, time since death

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Authors: Sofiane Bououden, Ilyes Boulkaibet

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In this paper, a robust model predictive controller (RMPC) for uncertain nonlinear system under actuator saturation is designed to control a DC-DC buck converter in PV pumping application, where this system is subject to actuator saturation and parameter uncertainties. The considered nonlinear system contains a linear constant part perturbed by an additive state-dependent nonlinear term. Based on the saturating actuator property, an appropriate linear feedback control law is constructed and used to minimize an infinite horizon cost function within the framework of linear matrix inequalities. The proposed approach has successfully provided a solution to the optimization problem that can stabilize the nonlinear plants. Furthermore, sufficient conditions for the existence of the proposed controller guarantee the robust stability of the system in the presence of polytypic uncertainties. In addition, the simulation results have demonstrated the efficiency of the proposed control scheme.

Keywords: PV pumping system, DC-DC buck converter, robust model predictive controller, nonlinear system, actuator saturation, linear matrix inequality

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Authors: Jingling Li, Yi Zhang, Wei Liang, Tao Cui, Jun Li

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Compared with terrestrial network, the traffic of spatial information network has both self-similarity and short correlation characteristics. By studying its traffic prediction method, the resource utilization of spatial information network can be improved, and the method can provide an important basis for traffic planning of a spatial information network. In this paper, considering the accuracy and complexity of the algorithm, the spatial information network traffic is decomposed into approximate component with long correlation and detail component with short correlation, and a time series hybrid prediction model based on wavelet decomposition is proposed to predict the spatial network traffic. Firstly, the original traffic data are decomposed to approximate components and detail components by using wavelet decomposition algorithm. According to the autocorrelation and partial correlation smearing and truncation characteristics of each component, the corresponding model (AR/MA/ARMA) of each detail component can be directly established, while the type of approximate component modeling can be established by ARIMA model after smoothing. Finally, the prediction results of the multiple models are fitted to obtain the prediction results of the original data. The method not only considers the self-similarity of a spatial information network, but also takes into account the short correlation caused by network burst information, which is verified by using the measured data of a certain back bone network released by the MAWI working group in 2018. Compared with the typical time series model, the predicted data of hybrid model is closer to the real traffic data and has a smaller relative root means square error, which is more suitable for a spatial information network.

Keywords: spatial information network, traffic prediction, wavelet decomposition, time series model

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Authors: István Fekete, Imre Berki, Áron Béni, Katalin Juhos, Marianna Makádi, Zsolt Kotroczó

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The average annual precipitation significantly influences the moisture content of the soils and, through this, the decomposition of the organic substances in the soils, the leaching of nutrients from the soils, and the pH of the soils. Climate change, together with the lengthening of the vegetation period and the increasing CO₂ level, can increase the amount of biomass that is formed. Degradation processes, which accelerate as the temperature increases and slow down due to the drying climate, and the change in the degree of leaching can cancel out or strengthen each other's effects. In the course of our research, we looked for oak forests with climate-zonal soils where the geological, geographical and ecological background conditions are as similar as possible, apart from the different annual precipitation averages and the differences that can arise from them. We examined 5 dry and 5 humid Hungarian oak soils. Climate change affects the soils of drier and wetter forests differently. The aim of our research was to compare the content of carbon, nitrogen and some other nutrients, as well as the pH of the soils of humid and dry forests. Showing the effects of the drier climate on the tested soil parameters. In the case of the examined forest soils, we found a significant difference between the soils of dry and humid forests: in the case of the annual average precipitation values (p≥ 0.0001, for dry forest soils: 564±5.2 mm; for humid forest soils: 716±3.8 mm) for pH (p= 0.0004, for dry forest soils: 5.49±0.16; for wet forest soils: 5.36±0.21); for C content (p= 0.0054, for dry forest soils: 6.92%±0.59; for humid forest soils 3.09%±0.24), for N content (p= 0.0022, dry forest in the case of soils: 0.44%±0.047; in the case of humid forest soils: 0.23%±0.013), for the K content (p=0.0017, in the case of dry forest soils: 5684±732 (mg/kg); in the case of humid forest soils 2169±196 (mg/kg)), for the Ca content (p= 0.0096, for dry forest soils: 8207±2118 (mg/kg); for wet forest soils 957±320 (mg/kg)). No significant difference was found in the case of Mg. In a wetter environment, especially if the moisture content of the soil is also optimal for the decomposing organisms during the growing season, the decomposition of organic residues accelerates, and the processes of leaching from the soil are also intensified. The different intensity of the leaching processes is also well reflected in the quantitative differences of Ca and K, and in connection with these, it is also reflected in the difference in pH values. The differences in the C and N content can be explained by differences in the intensity of the decomposition processes. In addition to warming, drying is expected in a significant part of Hungary due to climate change. Thus, the comparison of the soils of dry and humid forests allows us to predict the subsequent changes in the case of the examined parameters.

Keywords: soil nutrients, precipitation difference, climate change, organic matter decomposition, leaching

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Authors: Anjanna Matta, P. A. L. Narayana

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An investigation has been presented to analyze the effect of internal heat source on the onset of Hadley-Prats flow in a horizontal fluid saturated porous medium. We examine a better understanding of the combined influence of the heat source and mass flow effect by using linear stability analysis. The resultant eigenvalue problem is solved by using shooting and Runga-Kutta methods for evaluate critical thermal Rayleight number with respect to various flow governing parameters. It is identified that the flow is switch from stabilizing to destabilizing as the horizontal thermal Rayleigh number is enhanced. The heat source and mass flow increases resulting a stronger destabilizing effect.

Keywords: linear stability analysis, heat source, porous medium, mass flow

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Authors: Chang-Ho Lee, Seung-Hoon Lee, Myeong-Jin Park, Oh-Min Kwon

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This paper investigates improved stability criteria for sampled-data control of linear systems with disturbances and time-varying delays. Based on Lyapunov-Krasovskii stability theory, delay-dependent conditions sufficient to ensure H∞ stability for the system are derived in the form of linear matrix inequalities(LMI). The effectiveness of the proposed method will be shown in numerical examples.

Keywords: sampled-data control system, Lyapunov-Krasovskii functional, time delay-dependent, LMI, H∞ control

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Authors: Cherief Houria, Fouka Mourad

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In this work, the simulation of the radiation attenuation is carried out in a photon detector consisting of different common shielding material using a Monte Carlo program called PTM. The aim of the study is to investigate the effect of atomic weight and the thickness of shielding materials on the gamma radiation attenuation ability. The linear attenuation coefficients of Aluminum (Al), Iron (Fe), and lead (Pb) elements were evaluated at photons energy of 661:7KeV that are considered to be emitted from a standard radioactive point source Cs 137. The experimental measurements have been performed for three materials to obtain these linear attenuation coefficients, using a Gamma NaI(Tl) scintillation detector. Our results have been compared with the simulation results of the linear attenuation coefficient using the XCOM database and Geant4 codes and reveal that they are well agreed with both simulation data.

Keywords: gamma photon, Monte Carlo program, radiation attenuation, shielding material, the linear attenuation coefficient

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Authors: Takhchi Jamal, Ouisse Morvan, Sadoulet-Reboul Emeline, Bouhaddi Noureddine, Gagliardini Laurent, Bornet Frederic, Lakrad Faouzi

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Structural intensity is a technique that can be used to indicate both the magnitude and direction of power flow through a structure from the excitation source to the dissipation sink. However, current analysis is limited to the low frequency range. At medium and high frequencies, a rotational component appear in the field, masking the energy flow and make its understanding difficult or impossible. The objective of this work is to implement a methodology to filter out the rotational components of the structural intensity field in order to fully understand the energy flow in complex structures. The approach is based on the Helmholtz decomposition. It allows to decompose the structural intensity field into rotational, irrotational, and harmonic components. Only the irrotational component is needed to describe the net power flow from a source to a dissipative zone in the structure. The methodology has been applied on academic structures, and it allows a good analysis of the energy transfer paths.

Keywords: structural intensity, power flow, helmholt decomposition, irrotational intensity

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Authors: Markus Pajones, Theresa Steiner, Matthias Neubauer

Abstract:

Selecting a logistics location is vital for logistics providers, food retailing and other trading companies since the selection poses an essential factor for economic success. Therefore various location search methods like cost-benefit analysis and others are well known and under usage. The development of a logistics location can be related to considerable negative effects for the eco system such as sealing the surface, wrecking of biodiversity or CO2 and noise emissions generated by freight and commuting traffic. The increasing importance of sustainability demands for taking an informed decision when selecting a logistics location for the future. Sustainability considers economic, ecologic and social aspects which should be equally integrated in the process of location search. Objectives of this paper are to define various methods which support the selection of sustainable logistics locations and to generate knowledge about the suitability, assets and limitations of the methods within the selection process. This paper investigates the role of economical, ecological and social aspects when searching for new logistics locations. Thereby, related work targeted towards location search is analyzed with respect to encoded sustainability aspects. In addition, this research aims to gain knowledge on how to include aspects of sustainability and take an informed decision when searching for a logistics location. As a result, a decomposition of the various location search methods in there components leads to a comparative analysis in form of a matrix. The comparison within a matrix enables a transparent overview about the mentioned assets and limitations of the methods and their suitability for selecting sustainable logistics locations. A further result is to generate knowledge on how to combine the separate methods to a new method for a more efficient selection of logistics locations in the context of sustainability. Future work will especially investigate the above mentioned combination of various location search methods. The objective is to develop an innovative instrument, which supports the search for logistics locations with a focus on a balanced sustainability (economy, ecology, social). Because of an ideal selection of logistics locations, induced traffic should be reduced and a mode shift to rail and public transport should be facilitated.

Keywords: commuting traffic, freight traffic, logistics location search, location search method

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Authors: Mahnaz Hosseinzadeh, Aliyeh Kazemi

Abstract:

In this paper, a method is proposed for solving Fuzzy Multi-Objective Linear Programming problems (FMOLPP) with fuzzy right hand side and fuzzy decision variables. To illustrate the proposed method, it is applied to the problem of selecting suppliers for an automotive parts producer company in Iran in order to find the number of optimal orders allocated to each supplier considering the conflicting objectives. Finally, the obtained results are discussed.

Keywords: fuzzy multi-objective linear programming problems, triangular fuzzy numbers, fuzzy ranking, supplier selection problem

Procedia PDF Downloads 358