Search results for: invasive weed optimization algorithm
5071 Optimization of Fourth Order Discrete-Approximation Inclusions
Authors: Elimhan N. Mahmudov
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The paper concerns the necessary and sufficient conditions of optimality for Cauchy problem of fourth order discrete (PD) and discrete-approximate (PDA) inclusions. The main problem is formulation of the fourth order adjoint discrete and discrete-approximate inclusions and transversality conditions, which are peculiar to problems including fourth order derivatives and approximate derivatives. Thus the necessary and sufficient conditions of optimality are obtained incorporating the Euler-Lagrange and Hamiltonian forms of inclusions. Derivation of optimality conditions are based on the apparatus of locally adjoint mapping (LAM). Moreover in the application of these results we consider the fourth order linear discrete and discrete-approximate inclusions.Keywords: difference, optimization, fourth, approximation, transversality
Procedia PDF Downloads 3745070 Hydraulic Characteristics of Mine Tailings by Metaheuristics Approach
Authors: Akhila Vasudev, Himanshu Kaushik, Tadikonda Venkata Bharat
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A large number of mine tailings are produced every year as part of the extraction process of phosphates, gold, copper, and other materials. Mine tailings are high in water content and have very slow dewatering behavior. The efficient design of tailings dam and economical disposal of these slurries requires the knowledge of tailings consolidation behavior. The large-strain consolidation theory closely predicts the self-weight consolidation of these slurries as the theory considers the conservation of mass and momentum conservation and considers the hydraulic conductivity as a function of void ratio. Classical laboratory techniques, such as settling column test, seepage consolidation test, etc., are expensive and time-consuming for the estimation of hydraulic conductivity variation with void ratio. Inverse estimation of the constitutive relationships from the measured settlement versus time curves is explored. In this work, inverse analysis based on metaheuristics techniques will be explored for predicting the hydraulic conductivity parameters for mine tailings from the base excess pore water pressure dissipation curve and the initial conditions of the mine tailings. The proposed inverse model uses particle swarm optimization (PSO) algorithm, which is based on the social behavior of animals searching for food sources. The finite-difference numerical solution of the forward analytical model is integrated with the PSO algorithm to solve the inverse problem. The method is tested on synthetic data of base excess pore pressure dissipation curves generated using the finite difference method. The effectiveness of the method is verified using base excess pore pressure dissipation curve obtained from a settling column experiment and further ensured through comparison with available predicted hydraulic conductivity parameters.Keywords: base excess pore pressure, hydraulic conductivity, large strain consolidation, mine tailings
Procedia PDF Downloads 1365069 Non-Population Search Algorithms for Capacitated Material Requirement Planning in Multi-Stage Assembly Flow Shop with Alternative Machines
Authors: Watcharapan Sukkerd, Teeradej Wuttipornpun
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This paper aims to present non-population search algorithms called tabu search (TS), simulated annealing (SA) and variable neighborhood search (VNS) to minimize the total cost of capacitated MRP problem in multi-stage assembly flow shop with two alternative machines. There are three main steps for the algorithm. Firstly, an initial sequence of orders is constructed by a simple due date-based dispatching rule. Secondly, the sequence of orders is repeatedly improved to reduce the total cost by applying TS, SA and VNS separately. Finally, the total cost is further reduced by optimizing the start time of each operation using the linear programming (LP) model. Parameters of the algorithm are tuned by using real data from automotive companies. The result shows that VNS significantly outperforms TS, SA and the existing algorithm.Keywords: capacitated MRP, tabu search, simulated annealing, variable neighborhood search, linear programming, assembly flow shop, application in industry
Procedia PDF Downloads 2345068 Evaluation of Dual Polarization Rainfall Estimation Algorithm Applicability in Korea: A Case Study on Biseulsan Radar
Authors: Chulsang Yoo, Gildo Kim
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Dual polarization radar provides comprehensive information about rainfall by measuring multiple parameters. In Korea, for the rainfall estimation, JPOLE and CSU-HIDRO algorithms are generally used. This study evaluated the local applicability of JPOLE and CSU-HIDRO algorithms in Korea by using the observed rainfall data collected on August, 2014 by the Biseulsan dual polarization radar data and KMA AWS. A total of 11,372 pairs of radar-ground rain rate data were classified according to thresholds of synthetic algorithms into suitable and unsuitable data. Then, evaluation criteria were derived by comparing radar rain rate and ground rain rate, respectively, for entire, suitable, unsuitable data. The results are as follows: (1) The radar rain rate equation including KDP, was found better in the rainfall estimation than the other equations for both JPOLE and CSU-HIDRO algorithms. The thresholds were found to be adequately applied for both algorithms including specific differential phase. (2) The radar rain rate equation including horizontal reflectivity and differential reflectivity were found poor compared to the others. The result was not improved even when only the suitable data were applied. Acknowledgments: This work was supported by the Basic Science Research Program through the National Research Foundation of Korea, funded by the Ministry of Education (NRF-2013R1A1A2011012).Keywords: CSU-HIDRO algorithm, dual polarization radar, JPOLE algorithm, radar rainfall estimation algorithm
Procedia PDF Downloads 2155067 Riesz Mixture Model for Brain Tumor Detection
Authors: Mouna Zitouni, Mariem Tounsi
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This research introduces an application of the Riesz mixture model for medical image segmentation for accurate diagnosis and treatment of brain tumors. We propose a pixel classification technique based on the Riesz distribution, derived from an extended Bartlett decomposition. To our knowledge, this is the first study addressing this approach. The Expectation-Maximization algorithm is implemented for parameter estimation. A comparative analysis, using both synthetic and real brain images, demonstrates the superiority of the Riesz model over a recent method based on the Wishart distribution.Keywords: EM algorithm, segmentation, Riesz probability distribution, Wishart probability distribution
Procedia PDF Downloads 195066 Deterministic Random Number Generator Algorithm for Cryptosystem Keys
Authors: Adi A. Maaita, Hamza A. A. Al Sewadi
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One of the crucial parameters of digital cryptographic systems is the selection of the keys used and their distribution. The randomness of the keys has a strong impact on the system’s security strength being difficult to be predicted, guessed, reproduced or discovered by a cryptanalyst. Therefore, adequate key randomness generation is still sought for the benefit of stronger cryptosystems. This paper suggests an algorithm designed to generate and test pseudo random number sequences intended for cryptographic applications. This algorithm is based on mathematically manipulating a publically agreed upon information between sender and receiver over a public channel. This information is used as a seed for performing some mathematical functions in order to generate a sequence of pseudorandom numbers that will be used for encryption/decryption purposes. This manipulation involves permutations and substitutions that fulfills Shannon’s principle of “confusion and diffusion”. ASCII code characters wereutilized in the generation process instead of using bit strings initially, which adds more flexibility in testing different seed values. Finally, the obtained results would indicate sound difficulty of guessing keys by attackers.Keywords: cryptosystems, information security agreement, key distribution, random numbers
Procedia PDF Downloads 2685065 Design and Fabrication of Stiffness Reduced Metallic Locking Compression Plates through Topology Optimization and Additive Manufacturing
Authors: Abdulsalam A. Al-Tamimi, Chris Peach, Paulo Rui Fernandes, Paulo J. Bartolo
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Bone fixation implants currently used to treat traumatic fractured bones and to promote fracture healing are built with biocompatible metallic materials such as stainless steel, cobalt chromium and titanium and its alloys (e.g., CoCrMo and Ti6Al4V). The noticeable stiffness mismatch between current metallic implants and host bone associates with negative outcomes such as stress shielding which causes bone loss and implant loosening leading to deficient fracture treatment. This paper, part of a major research program to design the next generation of bone fixation implants, describes the combined use of three-dimensional (3D) topology optimization (TO) and additive manufacturing powder bed technology (Electron Beam Melting) to redesign and fabricate the plates based on the current standard one (i.e., locking compression plate). Topology optimization is applied with an objective function to maximize the stiffness and constraint by volume reductions (i.e., 25-75%) in order to obtain optimized implant designs with reduced stress shielding phenomenon, under different boundary conditions (i.e., tension, bending, torsion and combined loads). The stiffness of the original and optimised plates are assessed through a finite-element study. The TO results showed actual reduction in the stiffness for most of the plates due to the critical values of volume reduction. Additionally, the optimized plates fabricated using powder bed techniques proved that the integration between the TO and additive manufacturing presents the capability of producing stiff reduced plates with acceptable tolerances.Keywords: additive manufacturing, locking compression plate, finite element, topology optimization
Procedia PDF Downloads 1995064 Study of the Best Algorithm to Estimate Sunshine Duration from Global Radiation on Horizontal Surface for Tropical Region
Authors: Tovondahiniriko Fanjirindratovo, Olga Ramiarinjanahary, Paulisimone Rasoavonjy
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The sunshine duration, which is the sum of all the moments when the solar beam radiation is up to a minimal value, is an important parameter for climatology, tourism, agriculture and solar energy. Its measure is usually given by a pyrheliometer installed on a two-axis solar tracker. Due to the high cost of this device and the availability of global radiation on a horizontal surface, on the other hand, several studies have been done to make a correlation between global radiation and sunshine duration. Most of these studies are fitted for the northern hemisphere using a pyrheliometric database. The aim of the present work is to list and assess all the existing methods and apply them to Reunion Island, a tropical region in the southern hemisphere. Using a database of ten years, global, diffuse and beam radiation for a horizontal surface are employed in order to evaluate the uncertainty of existing algorithms for a tropical region. The methodology is based on indirect comparison because the solar beam radiation is not measured but calculated by the beam radiation on a horizontal surface and the sun elevation angle.Keywords: Carpentras method, data fitting, global radiation, sunshine duration, Slob and Monna algorithm, step algorithm
Procedia PDF Downloads 1275063 Comparative Assessment on the Impact of Sedatives on the Stress and Anxiety of Patients with a Heart Disease before and during Surgery in Iran
Authors: Farhad Fakoursevom
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Heart disease is one of the diseases which is found in abundance today. Various types of surgeries, such as bypasses, angiography, angioplasty, etc., are used to treat patients. People may receive such surgeries, some of which are invasive and some non-invasive, throughout their lives. People might cope with pre-surgery anxiety and stress, which can disrupt their normal life and even reduce the effects of the surgery, so the desired result can not be achieved in surgery. Considering this issue, the present study aimed to do a comparative assessment of people who received sedatives before surgery and people who did not receive sedatives. In terms of the purpose, this is an applied research and descriptive survey in terms of method. The statistical population included patients who underwent surgeries in the specialist heart hospitals of Mashhad, Iran; 60 people were considered as a statistical population, 30 of them received sedatives before surgery, and 30 others had not received sedatives before surgery. Valid and up-to-date articles were systematically used to collect theoretical bases, and a researcher-made questionnaire was used to examine the level of stress and anxiety of people. The questionnaire content validity was assessed by a panel of experts in psychology and medicine. The construct validity was tested using the software. Cronbach's alpha and composite reliability were used for reliability, which shows the appropriate reliability of the questionnaire. SPSS software was used to compare the research results between two groups, and the research findings showed that there is no significant association between the people who received sedatives and those who did not receive sedatives in terms of the amount of stress and anxiety. The longer the time of taking the drugs before the surgery, the more the mental peace of the patients will be. According to the results, it can be said that if we don't need to have an emergency operation and need more time, we have to use sedative drugs with different doses compared to the severity of the surgery, and also in case of a medical emergency such as heart surgery due to a stroke, we have to take advantage of psychological services during and before the operation and sedative drugs so that the patients can control their stress and anxiety and achieve better outcomes.Keywords: sedative drugs, stress, anxiety, surgery
Procedia PDF Downloads 995062 Medium Design and Optimization for High Β-Galactosidase Producing Microbial Strains from Dairy Waste through Fermentation
Authors: Ashish Shukla, K. P. Mishra, Pushplata Tripathi
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This paper investigates the production and optimization of β-galactosidase enzyme using synthetic medium by isolated wild strains (S1, S2) mutated strains (M1, M2) through SSF and SmF. Among the different cell disintegration methods used, the highest specific activity was obtained when the cells were permeabilized using isoamyl alcohol. Wet lab experiments were performed to investigate the effects of carbon and nitrogen substrates present in Vogel’s medium on β-galactosidase enzyme activity using S1, S2, and M1, M2 strains through SSF. SmF experiments were performed for effects of carbon and nitrogen sources in YLK2Mg medium on β-galactosidase enzyme activity using S1, S2 and M1, M2 strains. Effect of pH on β-galactosidase enzyme production was also done using S1, S2, and M1, M2 strains. Results were found to be very appreciable in all the cases.Keywords: β-galactosidase, cell disintegration, permeabilized, SSF, SmF
Procedia PDF Downloads 2735061 Platelet Transfusion Thresholds for Pediatrics; A Retrospective Study
Authors: Hessah Alsulami, Majedah Aldosari
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Introduction: Platelet threshold of 10x109 /L is recommended for clinically stable thrombocytopenic pediatric patients. Transfusions at a higher level (given the absence of research evidence, as determined by clinical circumstances, generally at threshold of 40x109 /L) may be required for patients with signs of bleeding, high fever, hyper-leukocytosis, rapid fall in platelet count, concomitant coagulation abnormality, critically ill patients, and those with impaired platelet function (including drug induced). Transfusions at a higher level may be also required for patients undergoing invasive procedures. Method: This study is a retrospective observational analysis of platelet transfusion thresholds in a single secondary pediatric hospital in Riyadh. From the blood bank database, the list of the patients who received platelet transfusions in the second half of 2018 was retrieved. Patients were divided into two groups; group A, those belong to the category of high platelet level for transfusion (such as those with bleeding, high fever, rapid fall in platelet count, impaired platelet function or undergoing invasive procedures) and group B, those who were not. Then we looked at the pre and post transfusion platelet levels for each group. The data was analyzed using GraphPad software and the data expressed as Mean ± SD. Result: A total of 112 of transfusion episodes in 61 patients (38% female) were analyzed. The age ranged from 24 days to 8 years. The distribution of platelet transfusion episodes was 64% (n=72) for group A and 36% (n= 40) for group B. The mean pre-transfusion platelet count was 46x103 ± (11x 103) for group A and 28x103 ± (6x103) for group B. the post-transfusion mean platelet count was 61 x 103 ± (14 x 103) and 60 x103 ± (24 x 103) for group A and B respectively. Among the groups the rise in the mean platelet count after transfusion was significant among stable patients (group B) compared to unstable patients (group A) (P < 0.001). Conclusion: The platelet count threshold for transfusion varied with the clinical condition and is higher among unstable patients’ group which is expected. For stable patients the threshold was higher than what it should be which means that the clinicians don’t follow the guidelines in this regard. The rise of platelet count after transfusion was higher among stable patients.Keywords: platelet, transfusion, threshold, pediatric
Procedia PDF Downloads 715060 Inverse Scattering of Two-Dimensional Objects Using an Enhancement Method
Authors: A.R. Eskandari, M.R. Eskandari
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A 2D complete identification algorithm for dielectric and multiple objects immersed in air is presented. The employed technique consists of initially retrieving the shape and position of the scattering object using a linear sampling method and then determining the electric permittivity and conductivity of the scatterer using adjoint sensitivity analysis. This inversion algorithm results in high computational speed and efficiency, and it can be generalized for any scatterer structure. Also, this method is robust with respect to noise. The numerical results clearly show that this hybrid approach provides accurate reconstructions of various objects.Keywords: inverse scattering, microwave imaging, two-dimensional objects, Linear Sampling Method (LSM)
Procedia PDF Downloads 3875059 Optimization of Multiplier Extraction Digital Filter On FPGA
Authors: Shiksha Jain, Ramesh Mishra
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One of the most widely used complex signals processing operation is filtering. The most important FIR digital filter are widely used in DSP for filtering to alter the spectrum according to some given specifications. Power consumption and Area complexity in the algorithm of Finite Impulse Response (FIR) filter is mainly caused by multipliers. So we present a multiplier less technique (DA technique). In this technique, precomputed value of inner product is stored in LUT. Which are further added and shifted with number of iterations equal to the precision of input sample. But the exponential growth of LUT with the order of FIR filter, in this basic structure, makes it prohibitive for many applications. The significant area and power reduction over traditional Distributed Arithmetic (DA) structure is presented in this paper, by the use of slicing of LUT to the desired length. An architecture of 16 tap FIR filter is presented, with different length of slice of LUT. The result of FIR Filter implementation on Xilinx ISE synthesis tool (XST) vertex-4 FPGA Tool by using proposed method shows the increase of the maximum frequency, the decrease of the resources as usage saving in area with more number of slices and the reduction dynamic power.Keywords: multiplier less technique, linear phase symmetric FIR filter, FPGA tool, look up table
Procedia PDF Downloads 3905058 Optimization of a Method of Total RNA Extraction from Mentha piperita
Authors: Soheila Afkar
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Mentha piperita is a medicinal plant that contains a large amount of secondary metabolite that has adverse effect on RNA extraction. Since high quality of RNA is the first step to real time-PCR, in this study optimization of total RNA isolation from leaf tissues of Mentha piperita was evaluated. From this point of view, we researched two different total RNA extraction methods on leaves of Mentha piperita to find the best one that contributes the high quality. The methods tested are RNX-plus, modified RNX-plus (1-5 numbers). RNA quality was analyzed by agarose gel 1.5%. The RNA integrity was also assessed by visualization of ribosomal RNA bands on 1.5% agarose gels. In the modified RNX-plus method (number 2), the integrity of 28S and 18S rRNA was highly satisfactory when analyzed in agarose denaturing gel, so this method is suitable for RNA isolation from Mentha piperita.Keywords: Mentha piperita, polyphenol, polysaccharide, RNA extraction
Procedia PDF Downloads 1905057 A Versatile Algorithm to Propose Optimized Solutions to the Dengue Disease Problem
Authors: Fernando L. P. Santos, Luiz G. Lyra, Helenice O. Florentino, Daniela R. Cantane
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Dengue is a febrile infectious disease caused by a virus of the family Flaviridae. It is transmitted by the bite of mosquitoes, usually of the genus Aedes aegypti. It occurs in tropical and subtropical areas of the world. This disease has been a major public health problem worldwide, especially in tropical countries such as Brazil, and its incidence has increased in recent years. Dengue is a subject of intense research. Efficient forms of mosquito control must be considered. In this work, the mono-objective optimal control problem was solved for analysing the dengue disease problem. Chemical and biological controls were considered in the mathematical aspect. This model describes the dynamics of mosquitoes in water and winged phases. We applied the genetic algorithms (GA) to obtain optimal strategies for the control of dengue. Numerical simulations have been performed to verify the versatility and the applicability of this algorithm. On the basis of the present results we may recommend the GA to solve optimal control problem with a large region of feasibility.Keywords: genetic algorithm, dengue, Aedes aegypti, biological control, chemical control
Procedia PDF Downloads 3495056 A Genetic Algorithm Based Ensemble Method with Pairwise Consensus Score on Malware Cacophonous Labels
Authors: Shih-Yu Wang, Shun-Wen Hsiao
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In the field of cybersecurity, there exists many vendors giving malware samples classified results, namely naming after the label that contains some important information which is also called AV label. Lots of researchers relay on AV labels for research. Unfortunately, AV labels are too cluttered. They do not have a fixed format and fixed naming rules because the naming results were based on each classifiers' viewpoints. A way to fix the problem is taking a majority vote. However, voting can sometimes create problems of bias. Thus, we create a novel ensemble approach which does not rely on the cacophonous naming result but depend on group identification to aggregate everyone's opinion. To achieve this purpose, we develop an scoring system called Pairwise Consensus Score (PCS) to calculate result similarity. The entire method architecture combine Genetic Algorithm and PCS to find maximum consensus in the group. Experimental results revealed that our method outperformed the majority voting by 10% in term of the score.Keywords: genetic algorithm, ensemble learning, malware family, malware labeling, AV labels
Procedia PDF Downloads 865055 Performance Analysis of Bluetooth Low Energy Mesh Routing Algorithm in Case of Disaster Prediction
Authors: Asmir Gogic, Aljo Mujcic, Sandra Ibric, Nermin Suljanovic
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Ubiquity of natural disasters during last few decades have risen serious questions towards the prediction of such events and human safety. Every disaster regardless its proportion has a precursor which is manifested as a disruption of some environmental parameter such as temperature, humidity, pressure, vibrations and etc. In order to anticipate and monitor those changes, in this paper we propose an overall system for disaster prediction and monitoring, based on wireless sensor network (WSN). Furthermore, we introduce a modified and simplified WSN routing protocol built on the top of the trickle routing algorithm. Routing algorithm was deployed using the bluetooth low energy protocol in order to achieve low power consumption. Performance of the WSN network was analyzed using a real life system implementation. Estimates of the WSN parameters such as battery life time, network size and packet delay are determined. Based on the performance of the WSN network, proposed system can be utilized for disaster monitoring and prediction due to its low power profile and mesh routing feature.Keywords: bluetooth low energy, disaster prediction, mesh routing protocols, wireless sensor networks
Procedia PDF Downloads 3855054 An Improved Tracking Approach Using Particle Filter and Background Subtraction
Authors: Amir Mukhtar, Dr. Likun Xia
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An improved, robust and efficient visual target tracking algorithm using particle filtering is proposed. Particle filtering has been proven very successful in estimating non-Gaussian and non-linear problems. In this paper, the particle filter is used with color feature to estimate the target state with time. Color distributions are applied as this feature is scale and rotational invariant, shows robustness to partial occlusion and computationally efficient. The performance is made more robust by choosing the different (YIQ) color scheme. Tracking is performed by comparison of chrominance histograms of target and candidate positions (particles). Color based particle filter tracking often leads to inaccurate results when light intensity changes during a video stream. Furthermore, background subtraction technique is used for size estimation of the target. The qualitative evaluation of proposed algorithm is performed on several real-world videos. The experimental results demonstrate that the improved algorithm can track the moving objects very well under illumination changes, occlusion and moving background.Keywords: tracking, particle filter, histogram, corner points, occlusion, illumination
Procedia PDF Downloads 3815053 Characteization and Optimization of S-Parameters of Microwave Circuits
Authors: N. Ourabia, M. Boubaker Ourabia
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An approach for modeling and numerical simulation of passive planar structures using the edge line concept is developed. With this method, we develop an efficient modeling technique for microstrip discontinuities. The technique obtains closed form expressions for the equivalent circuits which are used to model these discontinuities. Then, it would be easy to handle and to characterize complicated structures like T and Y junctions, truncated junctions, arbitrarily shaped junctions, cascading junctions and more generally planar multiport junctions. Another advantage of this method is that the edge line concept for arbitrary shape junctions operates with real parameters circuits. The validity of the method was further confirmed by comparing our results for various discontinuities (bend, filters) with those from HFSS as well as from other published sources.Keywords: optimization, CAD analysis, microwave circuits, S-parameters
Procedia PDF Downloads 4545052 Battery Control with Moving Average Algorithm to Smoothen the Intermittent Output Power of Photovoltaic Solar Power Plants in Off-Grid Configuration
Authors: Muhammad Gillfran Samual, Rinaldy Dalimi, Fauzan Hanif Jufri, Budi Sudiarto, Ismi Rosyiana Fitri
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Solar energy is increasingly recognized as an important future energy source due to its abundant availability and renewable nature. However, the intermittent nature of solar energy can cause fluctuations in the electricity produced, making it difficult to guarantee a stable and reliable electricity supply. One solution that can be implemented is to use batteries in a photovoltaic solar power plant system with a Moving Average control algorithm, which can help smooth and reduce fluctuations in solar power output power. The parameter that can be adjusted in the Moving Average algorithm is the window size or the arithmetic average width of the photovoltaic output power over time. This research evaluates the effect of a change of window size parameter in the Moving Average algorithm on the resulting smoothed photovoltaic output power and the technical effects on batteries, i.e., power and energy usage. Based on the evaluation, it is found that the increase of window size parameter will slow down the response of photovoltaic output power to changes in irradiation and increase the smoothing quality of the intermittent photovoltaic output power. In addition, increasing the window size will reduce the maximum power received on the load side, and the amount of energy used by the battery during the power smoothing process will increase, which, in turn, increases the required battery capacity.Keywords: battery, intermittent, moving average, photovoltaic, power smoothing
Procedia PDF Downloads 635051 Spatial Object-Oriented Template Matching Algorithm Using Normalized Cross-Correlation Criterion for Tracking Aerial Image Scene
Authors: Jigg Pelayo, Ricardo Villar
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Leaning on the development of aerial laser scanning in the Philippine geospatial industry, researches about remote sensing and machine vision technology became a trend. Object detection via template matching is one of its application which characterized to be fast and in real time. The paper purposely attempts to provide application for robust pattern matching algorithm based on the normalized cross correlation (NCC) criterion function subjected in Object-based image analysis (OBIA) utilizing high-resolution aerial imagery and low density LiDAR data. The height information from laser scanning provides effective partitioning order, thus improving the hierarchal class feature pattern which allows to skip unnecessary calculation. Since detection is executed in the object-oriented platform, mathematical morphology and multi-level filter algorithms were established to effectively avoid the influence of noise, small distortion and fluctuating image saturation that affect the rate of recognition of features. Furthermore, the scheme is evaluated to recognized the performance in different situations and inspect the computational complexities of the algorithms. Its effectiveness is demonstrated in areas of Misamis Oriental province, achieving an overall accuracy of 91% above. Also, the garnered results portray the potential and efficiency of the implemented algorithm under different lighting conditions.Keywords: algorithm, LiDAR, object recognition, OBIA
Procedia PDF Downloads 2455050 Multiclass Support Vector Machines with Simultaneous Multi-Factors Optimization for Corporate Credit Ratings
Authors: Hyunchul Ahn, William X. S. Wong
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Corporate credit rating prediction is one of the most important topics, which has been studied by researchers in the last decade. Over the last decade, researchers are pushing the limit to enhance the exactness of the corporate credit rating prediction model by applying several data-driven tools including statistical and artificial intelligence methods. Among them, multiclass support vector machine (MSVM) has been widely applied due to its good predictability. However, heuristics, for example, parameters of a kernel function, appropriate feature and instance subset, has become the main reason for the critics on MSVM, as they have dictate the MSVM architectural variables. This study presents a hybrid MSVM model that is intended to optimize all the parameter such as feature selection, instance selection, and kernel parameter. Our model adopts genetic algorithm (GA) to simultaneously optimize multiple heterogeneous design factors of MSVM.Keywords: corporate credit rating prediction, Feature selection, genetic algorithms, instance selection, multiclass support vector machines
Procedia PDF Downloads 2945049 Conversion of HVAC Lines into HVDC in Transmission Expansion Planning
Authors: Juan P. Novoa, Mario A. Rios
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This paper presents a transmission planning methodology that considers the conversion of HVAC transmission lines to HVDC as an alternative of expansion of power systems, as a consequence of restrictions for the construction of new lines. The transmission expansion planning problem formulates an optimization problem that minimizes the total cost that includes the investment cost to convert lines from HVAC to HVDC and possible required reinforcements of the power system prior to the conversion. The costs analysis assesses the impact of the conversion on the reliability because transmission lines are out of service during the conversion work. The presented methodology is applied to a test system considering a planning a horizon of 10 years.Keywords: transmission expansion planning, HVDC, cost optimization, energy non-supplied
Procedia PDF Downloads 3885048 An Invasive Lessepsian Species, Golden-Banded Goatfish, Upeneus Moluccensis Population from Iskenderun Bay, the Eastern Mediterranean Sea, Türkiye, With Some Biological Notes: The Effects of Climate Differences and Opening of Suez Canal
Authors: Hatice Torcu Koc, Zeliha Erdogan
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This study presented the investigation of the population structure of Upeneus moluccensis in order to provide further knowledge and to compare the data with the studies before and thus help in the management of the population in the İskenderun Bay. For this purpose, a total of 370 golden-banded goatfish were caught by a commercial vessel monthly at a depth of 50-60 m. from İskenderun Bay in the years 2016-2018. Von Bertalanffy growth equation,length-weight relationships, sex ratio, age, condition, and gonado and hepato-somatic index values of U.peneus moluccensis specimens were determined. For this, the lengths and weights were measured using a dial caliper of 0.05 mm and a sensitive balance. Total lengths were 7.2–17.5 cm in females and 7.0–17.9 cm in males, while total weight ranges for females and males were 3.91-64.26 g and 3.69-60.95 g., respectively. Length-weight relationship for all individuals was calculated as W=0.004*L³ ³⁸, R²=0.85. Growth parameter was determined as L∞= 20.75 cm, k=0.33, t₀= - 0.56. The age readings were done by using the Bhattacharya method. The population was composed of 3 ages (1-3). The sex ratio was found as 1:1.42, corresponding to 41.4% males and 58.6% females, in favor of females (p<0.05). Values of the average condition and hepatosomatic index were found to be shown a similar pattern for males (1.088, 1.104) and females (1.124, 1.177), respectively. According to GSI values, the spawning period started in March and increased to April, May, and September. It was estimated that total (Z) mortality, natural (M) mortality, and fishing (F) mortality rates were estimated as Z=0.94 year-¹, M=0.033 year-¹, and F=0.63 year-¹, respectively. As the exploitation rate was estimated to be E=0.67, it can be shown that the golden-banded goatfish stock was influenced by overfishing. The findings of this study are very important to point out the population of U. moluccensis, which penetrated into the eastern Mediterranean Sea of Türkiye due to global heating and the construction of the Suez Canal and to be basic data for the next fisheries investigations.Keywords: biology, U. moluccensis, invasive, lessepsian, İskenderun Bay
Procedia PDF Downloads 745047 Light-Weight Network for Real-Time Pose Estimation
Authors: Jianghao Hu, Hongyu Wang
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The effective and efficient human pose estimation algorithm is an important task for real-time human pose estimation on mobile devices. This paper proposes a light-weight human key points detection algorithm, Light-Weight Network for Real-Time Pose Estimation (LWPE). LWPE uses light-weight backbone network and depthwise separable convolutions to reduce parameters and lower latency. LWPE uses the feature pyramid network (FPN) to fuse the high-resolution, semantically weak features with the low-resolution, semantically strong features. In the meantime, with multi-scale prediction, the predicted result by the low-resolution feature map is stacked to the adjacent higher-resolution feature map to intermediately monitor the network and continuously refine the results. At the last step, the key point coordinates predicted in the highest-resolution are used as the final output of the network. For the key-points that are difficult to predict, LWPE adopts the online hard key points mining strategy to focus on the key points that hard predicting. The proposed algorithm achieves excellent performance in the single-person dataset selected in the AI (artificial intelligence) challenge dataset. The algorithm maintains high-precision performance even though the model only contains 3.9M parameters, and it can run at 225 frames per second (FPS) on the generic graphics processing unit (GPU).Keywords: depthwise separable convolutions, feature pyramid network, human pose estimation, light-weight backbone
Procedia PDF Downloads 1545046 Space Time Adaptive Algorithm in Bi-Static Passive Radar Systems for Clutter Mitigation
Authors: D. Venu, N. V. Koteswara Rao
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Space – time adaptive processing (STAP) is an effective tool for detecting a moving target in spaceborne or airborne radar systems. Since airborne passive radar systems utilize broadcast, navigation and excellent communication signals to perform various surveillance tasks and also has attracted significant interest from the distinct past, therefore the need of the hour is to have cost effective systems as compared to conventional active radar systems. Moreover, requirements of small number of secondary samples for effective clutter suppression in bi-static passive radar offer abundant illuminator resources for passive surveillance radar systems. This paper presents a framework for incorporating knowledge sources directly in the space-time beam former of airborne adaptive radars. STAP algorithm for clutter mitigation for passive bi-static radar has better quantitation of the reduction in sample size thereby amalgamating the earlier data bank with existing radar data sets. Also, we proposed a novel method to estimate the clutter matrix and perform STAP for efficient clutter suppression based on small sample size. Furthermore, the effectiveness of the proposed algorithm is verified using MATLAB simulations in order to validate STAP algorithm for passive bi-static radar. In conclusion, this study highlights the importance for various applications which augments traditional active radars using cost-effective measures.Keywords: bistatic radar, clutter, covariance matrix passive radar, STAP
Procedia PDF Downloads 2965045 Wireless Transmission of Big Data Using Novel Secure Algorithm
Authors: K. Thiagarajan, K. Saranya, A. Veeraiah, B. Sudha
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This paper presents a novel algorithm for secure, reliable and flexible transmission of big data in two hop wireless networks using cooperative jamming scheme. Two hop wireless networks consist of source, relay and destination nodes. Big data has to transmit from source to relay and from relay to destination by deploying security in physical layer. Cooperative jamming scheme determines transmission of big data in more secure manner by protecting it from eavesdroppers and malicious nodes of unknown location. The novel algorithm that ensures secure and energy balance transmission of big data, includes selection of data transmitting region, segmenting the selected region, determining probability ratio for each node (capture node, non-capture and eavesdropper node) in every segment, evaluating the probability using binary based evaluation. If it is secure transmission resume with the two- hop transmission of big data, otherwise prevent the attackers by cooperative jamming scheme and transmit the data in two-hop transmission.Keywords: big data, two-hop transmission, physical layer wireless security, cooperative jamming, energy balance
Procedia PDF Downloads 4905044 Functional Traits and Agroecosystem Multifunctionality in Summer Cover Crop Mixtures and Monocultures
Authors: Etienne Herrick
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As an economically and ecologically feasible method for farmers to introduce greater diversity into their crop rotations, cover cropping presents a valuable opportunity for improving the sustainability of food production. Planted in-between cash crop growing seasons, cover crops serve to enhance agroecosystem functioning, rather than being destined for sale or consumption. In fact, cover crops may hold the capacity to deliver multiple ecosystem functions or services simultaneously (multifunctionality). Building upon this line of research will not only benefit society at present, but also support its continued survival through its potential for restoring depleted soils and reducing the need for energy-intensive and harmful external inputs like fertilizers and pesticides. This study utilizes a trait-based approach to explore the influence of inter- and intra-specific interactions in summer cover crop mixtures and monocultures on functional trait expression and ecosystem services. Functional traits that enhance ecosystem services related to agricultural production include height, specific leaf area (SLA), root, shoot ratio, leaf C and N concentrations, and flowering phenology. Ecosystem services include biomass production, weed suppression, reduced N leaching, N recycling, and support of pollinators. Employing a trait-based approach may allow for the elucidation of mechanistic links between plant structure and resulting ecosystem service delivery. While relationships between some functional traits and the delivery of particular ecosystem services may be readily apparent through existing ecological knowledge (e.g. height positively correlating with weed suppression), this study will begin to quantify those relationships so as to gain further understanding of whether and how measurable variation in functional trait expression across cover crop mixtures and monocultures can serve as a reliable predictor of variation in the types and abundances of ecosystem services delivered. Six cover crop species, including legume, grass, and broadleaf functional types, were selected for growth in six mixtures and their component monocultures based upon the principle of trait complementarity. The tricultures (three-way mixtures) are comprised of a legume, grass, and broadleaf species, and include cowpea/sudex/buckwheat, sunnhemp/sudex/buckwheat, and chickling vetch/oat/buckwheat combinations; the dicultures contain the same legume and grass combinations as above, without the buckwheat broadleaf. By combining species with expectedly complimentary traits (for example, legumes are N suppliers and grasses are N acquirers, creating a nutrient cycling loop) the cover crop mixtures may elicit a broader range of ecosystem services than that provided by a monoculture, though trade-offs could exist. Collecting functional trait data will enable the investigation of the types of interactions driving these ecosystem service outcomes. It also allows for generalizability across a broader range of species than just those selected for this study, which may aid in informing further research efforts exploring species and ecosystem functioning, as well as on-farm management decisions.Keywords: agroecology, cover crops, functional traits, multifunctionality, trait complementarity
Procedia PDF Downloads 2565043 A Novel RLS Based Adaptive Filtering Method for Speech Enhancement
Authors: Pogula Rakesh, T. Kishore Kumar
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Speech enhancement is a long standing problem with numerous applications like teleconferencing, VoIP, hearing aids, and speech recognition. The motivation behind this research work is to obtain a clean speech signal of higher quality by applying the optimal noise cancellation technique. Real-time adaptive filtering algorithms seem to be the best candidate among all categories of the speech enhancement methods. In this paper, we propose a speech enhancement method based on Recursive Least Squares (RLS) adaptive filter of speech signals. Experiments were performed on noisy data which was prepared by adding AWGN, Babble and Pink noise to clean speech samples at -5dB, 0dB, 5dB, and 10dB SNR levels. We then compare the noise cancellation performance of proposed RLS algorithm with existing NLMS algorithm in terms of Mean Squared Error (MSE), Signal to Noise ratio (SNR), and SNR loss. Based on the performance evaluation, the proposed RLS algorithm was found to be a better optimal noise cancellation technique for speech signals.Keywords: adaptive filter, adaptive noise canceller, mean squared error, noise reduction, NLMS, RLS, SNR, SNR loss
Procedia PDF Downloads 4815042 The Optimization Design of Sound Absorbing for Automotive Interior Material
Authors: Un-Hwan Park, Jun-Hyeok Heo, In-Sung Lee, Tae-Hyeon Oh, Dae-Gyu Park
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Nonwoven fabric such as an automobile interior material becomes consists of several material layers required for the sound-absorbing function. Because several material layers, many experimental tuning is required to achieve the target of sound absorption. Therefore, a lot of time and money is spent in the development of the car interior materials. In this study, we present the method to predict the sound-absorbing performance of the various layers with physical properties of each material. and we will verify it with the measured value of a prototype. If the sound absorption can be estimated, it can be optimized without a number of tuning tests of the interiors. So, it can reduce the development cost and time during developmentKeywords: automotive interior material, sound absorbing, optimization design, nonwoven fabric
Procedia PDF Downloads 837