Search results for: small baseline subset algorithm
9003 An Improved Genetic Algorithm for Traveling Salesman Problem with Precedence Constraint
Authors: M. F. F. Ab Rashid, A. N. Mohd Rose, N. M. Z. Nik Mohamed, W. S. Wan Harun, S. A. Che Ghani
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Traveling salesman problem with precedence constraint (TSPPC) is one of the most complex problems in combinatorial optimization. The existing algorithms to solve TSPPC cost large computational time to find the optimal solution. The purpose of this paper is to present an efficient genetic algorithm that guarantees optimal solution with less number of generations and iterations time. Unlike the existing algorithm that generates priority factor as chromosome, the proposed algorithm directly generates sequence of solution as chromosome. As a result, the proposed algorithm is capable of generating optimal solution with smaller number of generations and iteration time compare to existing algorithm.Keywords: traveling salesman problem, sequencing, genetic algorithm, precedence constraint
Procedia PDF Downloads 5519002 Improved FP-Growth Algorithm with Multiple Minimum Supports Using Maximum Constraints
Authors: Elsayeda M. Elgaml, Dina M. Ibrahim, Elsayed A. Sallam
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Association rule mining is one of the most important fields of data mining and knowledge discovery. In this paper, we propose an efficient multiple support frequent pattern growth algorithm which we called “MSFP-growth” that enhancing the FP-growth algorithm by making infrequent child node pruning step with multiple minimum support using maximum constrains. The algorithm is implemented, and it is compared with other common algorithms: Apriori-multiple minimum supports using maximum constraints and FP-growth. The experimental results show that the rule mining from the proposed algorithm are interesting and our algorithm achieved better performance than other algorithms without scarifying the accuracy.Keywords: association rules, FP-growth, multiple minimum supports, Weka tool
Procedia PDF Downloads 4759001 Prevalence of Rituximab Efficacy Over Immunosuppressants in Therapy of Systemic Sclerosis
Authors: Liudmila Garzanova, Lidia Ananyeva, Olga Koneva, Olga Ovsyannikova, Oxana Desinova, Mayya Starovoytova, Rushana Shayahmetova, Anna Khelkovskaya-Sergeeva
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Abstract Objectives. Rituximab (RTX) shown a positive effect in the treatment of systemic sclerosis (SSc). But there is still not enough data on comparing the effectiveness of RTX with immunosuppressants (IS). The aim of our study was to compare changes of lung function and skin score in SSc between two groups of patients (pts) - on RXT therapy (prescribed after ineffectiveness of previous therapy with IS) and on therapy with IS only. Methods. This study included 103 pts received RTX as an addition to previous therapy (group 1) and 65 pts received therapy with IS and prednisolone (group 2). The mean follow-up period was 12.6±10.7months. In group 1 the mean age was 47±12.9 years, female – 88 pts (84%), the diffuse cutaneous subset of the disease had 55 pts (53%). The mean disease duration was 6.2±5.5 years. 82% pts had interstitial lung disease (ILD) and 92% were positive for ANA, 67% of them were positive for antitopoisomerase-1. All pts received prednisolone at a dose of 11.3±4.5 mg/day, IS at inclusion received 47% of them. The cumulative mean dose of RTX was 1.7±0.6 g. In group 2 the mean age was 50.8±13.8 years, female-53 pts (82%), the diffuse cutaneous subset of the disease had 44 pts (68%). The mean disease duration was 8.8±7.7 years. 81% pts had ILD and 88% were positive for ANA, 58% of them were positive for antitopoisomerase-1. All pts received prednisolone at a dose of 8.69±4.28 mg/day, IS received 57% of them. Cyclophosphamide (CP) received 45% of pts. The cumulative mean dose of CP was 10.2±15.1g. D-penicillamine received 30% of pts. Other pts was on mycophenolate mofetil or methotrexate therapy in single cases. The pts of the compared groups did not differ in the main demographic and clinical parameters. The results are presented as delta (Δ) - difference between the baseline parameter and follow up point. Results. In group 1 there was an improvement of all outcome parameters: increased of forced vital capacity, % predicted - ΔFVC=4% (p=0.0004); Diffusing capacity for carbon monoxide, % predicted remained stable (ΔDLCO=0.1%); improvement of the Rodnan skin score-ΔmRss=3.4 (p=0.001); decrease of Activity index (EScSG-AI) - ΔActivity index=1.7 (p=0.001). In group 2 the changes was insignificant: ΔFVC=-2.3%, ΔmRss=0.87, ΔActivity index=0.3. But there was a significant decrease of DLCO: ΔDLCO=-5.1% (p=0.001). Conclusion. The results of our study confirm the data on the positive effect of RTX in complex therapy in pts with SSc (decrease of skin induration, increase of FVC, stabilization of DLCO). Meantime, pts on IS and prednisolone therapy shown the worsening of lung function and insignificant changes of other clinical parameters. RTX could be considered as a more effective option in complex treatment of SSc in comparison with IS therapyKeywords: immunosuppressants, interstitial lung disease, systemic sclerosis, rituximab
Procedia PDF Downloads 759000 An Improved Many Worlds Quantum Genetic Algorithm
Authors: Li Dan, Zhao Junsuo, Zhang Wenjun
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Aiming at the shortcomings of the Quantum Genetic Algorithm such as the multimodal function optimization problems easily falling into the local optimum, and vulnerable to premature convergence due to no closely relationship between individuals, the paper presents an Improved Many Worlds Quantum Genetic Algorithm (IMWQGA). The paper using the concept of Many Worlds; using the derivative way of parallel worlds’ parallel evolution; putting forward the thought which updating the population according to the main body; adopting the transition methods such as parallel transition, backtracking, travel forth. In addition, the algorithm in the paper also proposes the quantum training operator and the combinatorial optimization operator as new operators of quantum genetic algorithm.Keywords: quantum genetic algorithm, many worlds, quantum training operator, combinatorial optimization operator
Procedia PDF Downloads 7318999 Radiomics: Approach to Enable Early Diagnosis of Non-Specific Breast Nodules in Contrast-Enhanced Magnetic Resonance Imaging
Authors: N. D'Amico, E. Grossi, B. Colombo, F. Rigiroli, M. Buscema, D. Fazzini, G. Cornalba, S. Papa
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Purpose: To characterize, through a radiomic approach, the nature of nodules considered non-specific by expert radiologists, recognized in magnetic resonance mammography (MRm) with T1-weighted (T1w) sequences with paramagnetic contrast. Material and Methods: 47 cases out of 1200 undergoing MRm, in which the MRm assessment gave uncertain classification (non-specific nodules), were admitted to the study. The clinical outcome of the non-specific nodules was later found through follow-up or further exams (biopsy), finding 35 benign and 12 malignant. All MR Images were acquired at 1.5T, a first basal T1w sequence and then four T1w acquisitions after the paramagnetic contrast injection. After a manual segmentation of the lesions, done by a radiologist, and the extraction of 150 radiomic features (30 features per 5 subsequent times) a machine learning (ML) approach was used. An evolutionary algorithm (TWIST system based on KNN algorithm) was used to subdivide the dataset into training and validation test and to select features yielding the maximal amount of information. After this pre-processing, different machine learning systems were applied to develop a predictive model based on a training-testing crossover procedure. 10 cases with a benign nodule (follow-up older than 5 years) and 18 with an evident malignant tumor (clear malignant histological exam) were added to the dataset in order to allow the ML system to better learn from data. Results: NaiveBayes algorithm working on 79 features selected by a TWIST system, resulted to be the best performing ML system with a sensitivity of 96% and a specificity of 78% and a global accuracy of 87% (average values of two training-testing procedures ab-ba). The results showed that in the subset of 47 non-specific nodules, the algorithm predicted the outcome of 45 nodules which an expert radiologist could not identify. Conclusion: In this pilot study we identified a radiomic approach allowing ML systems to perform well in the diagnosis of a non-specific nodule at MR mammography. This algorithm could be a great support for the early diagnosis of malignant breast tumor, in the event the radiologist is not able to identify the kind of lesion and reduces the necessity for long follow-up. Clinical Relevance: This machine learning algorithm could be essential to support the radiologist in early diagnosis of non-specific nodules, in order to avoid strenuous follow-up and painful biopsy for the patient.Keywords: breast, machine learning, MRI, radiomics
Procedia PDF Downloads 2628998 Bayesian Network and Feature Selection for Rank Deficient Inverse Problem
Authors: Kyugneun Lee, Ikjin Lee
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Parameter estimation with inverse problem often suffers from unfavorable conditions in the real world. Useless data and many input parameters make the problem complicated or insoluble. Data refinement and reformulation of the problem can solve that kind of difficulties. In this research, a method to solve the rank deficient inverse problem is suggested. A multi-physics system which has rank deficiency caused by response correlation is treated. Impeditive information is removed and the problem is reformulated to sequential estimations using Bayesian network (BN) and subset groups. At first, subset grouping of the responses is performed. Feature selection with singular value decomposition (SVD) is used for the grouping. Next, BN inference is used for sequential conditional estimation according to the group hierarchy. Directed acyclic graph (DAG) structure is organized to maximize the estimation ability. Variance ratio of response to noise is used to pairing the estimable parameters by each response.Keywords: Bayesian network, feature selection, rank deficiency, statistical inverse analysis
Procedia PDF Downloads 3088997 A Variable Neighborhood Search with Tabu Conditions for the Roaming Salesman Problem
Authors: Masoud Shahmanzari
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The aim of this paper is to present a Variable Neighborhood Search (VNS) with Tabu Search (TS) conditions for the Roaming Salesman Problem (RSP). The RSP is a special case of the well-known traveling salesman problem (TSP) where a set of cities with time-dependent rewards and a set of campaign days are given. Each city can be visited on any day and a subset of cities can be visited multiple times. The goal is to determine an optimal campaign schedule consist of daily open/closed tours that visit some cities and maximizes the total net benefit while respecting daily maximum tour duration constraints and the necessity to return campaign base frequently. This problem arises in several real-life applications and particularly in election logistics where depots are not fixed. We formulate the problem as a mixed integer linear programming (MILP), in which we capture as many real-world aspects of the RSP as possible. We also present a hybrid metaheuristic algorithm based on a VNS with TS conditions. The initial feasible solution is constructed via a new matheuristc approach based on the decomposition of the original problem. Next, this solution is improved in terms of the collected rewards using the proposed local search procedure. We consider a set of 81 cities in Turkey and a campaign of 30 days as our largest instance. Computational results on real-world instances show that the developed algorithm could find near-optimal solutions effectively.Keywords: optimization, routing, election logistics, heuristics
Procedia PDF Downloads 848996 Advanced Hybrid Particle Swarm Optimization for Congestion and Power Loss Reduction in Distribution Networks with High Distributed Generation Penetration through Network Reconfiguration
Authors: C. Iraklis, G. Evmiridis, A. Iraklis
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Renewable energy sources and distributed power generation units already have an important role in electrical power generation. A mixture of different technologies penetrating the electrical grid, adds complexity in the management of distribution networks. High penetration of distributed power generation units creates node over-voltages, huge power losses, unreliable power management, reverse power flow and congestion. This paper presents an optimization algorithm capable of reducing congestion and power losses, both described as a function of weighted sum. Two factors that describe congestion are being proposed. An upgraded selective particle swarm optimization algorithm (SPSO) is used as a solution tool focusing on the technique of network reconfiguration. The upgraded SPSO algorithm is achieved with the addition of a heuristic algorithm specializing in reduction of power losses, with several scenarios being tested. Results show significant improvement in minimization of losses and congestion while achieving very small calculation times.Keywords: congestion, distribution networks, loss reduction, particle swarm optimization, smart grid
Procedia PDF Downloads 4398995 Top-K Shortest Distance as a Similarity Measure
Authors: Andrey Lebedev, Ilya Dmitrenok, JooYoung Lee, Leonard Johard
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Top-k shortest path routing problem is an extension of finding the shortest path in a given network. Shortest path is one of the most essential measures as it reveals the relations between two nodes in a network. However, in many real world networks, whose diameters are small, top-k shortest path is more interesting as it contains more information about the network topology. Many variations to compute top-k shortest paths have been studied. In this paper, we apply an efficient top-k shortest distance routing algorithm to the link prediction problem and test its efficacy. We compare the results with other base line and state-of-the-art methods as well as with the shortest path. Then, we also propose a top-k distance based graph matching algorithm.Keywords: graph matching, link prediction, shortest path, similarity
Procedia PDF Downloads 3538994 Multi-Subpopulation Genetic Algorithm with Estimation of Distribution Algorithm for Textile Batch Dyeing Scheduling Problem
Authors: Nhat-To Huynh, Chen-Fu Chien
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Textile batch dyeing scheduling problem is complicated which includes batch formation, batch assignment on machines, batch sequencing with sequence-dependent setup time. Most manufacturers schedule their orders manually that are time consuming and inefficient. More power methods are needed to improve the solution. Motivated by the real needs, this study aims to propose approaches in which genetic algorithm is developed with multi-subpopulation and hybridised with estimation of distribution algorithm to solve the constructed problem for minimising the makespan. A heuristic algorithm is designed and embedded into the proposed algorithms to improve the ability to get out of the local optima. In addition, an empirical study is conducted in a textile company in Taiwan to validate the proposed approaches. The results have showed that proposed approaches are more efficient than simulated annealing algorithm.Keywords: estimation of distribution algorithm, genetic algorithm, multi-subpopulation, scheduling, textile dyeing
Procedia PDF Downloads 2938993 A Rapid Code Acquisition Scheme in OOC-Based CDMA Systems
Authors: Keunhong Chae, Seokho Yoon
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We propose a code acquisition scheme called improved multiple-shift (IMS) for optical code division multiple access systems, where the optical orthogonal code is used instead of the pseudo noise code. Although the IMS algorithm has a similar process to that of the conventional MS algorithm, it has a better code acquisition performance than the conventional MS algorithm. We analyze the code acquisition performance of the IMS algorithm and compare the code acquisition performances of the MS and the IMS algorithms in single-user and multi-user environments.Keywords: code acquisition, optical CDMA, optical orthogonal code, serial algorithm
Procedia PDF Downloads 5328992 Poliovirus Vaccine Immunity among Chronically Malnourished Pakistani Infants: A Randomized Controlled Trial from Developing Country
Authors: Ali Faisal Saleem, Farheen Quadri, Mach Ondrej, Anita Zaidi
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Purpose: Pakistan is the final frontier for a polio-free world. Chronic malnutrition is associated with lack of effective gut immunity, and possibly associated with poliomyelitis in children received multiple OPV. We evaluate IPV dose administered together with OPV results in higher immunogenicity and mucosal immunity compared to OPV alone in chronically malnourished infants. Methods AND Materials: A community-based, unblinded-randomized-trial, conducted in 5 peri-urban, low-middle-income households of Karachi, in infants 9-12 months. Two study groups were non-malnourished (HAZ= -2 or more) and chronic malnourished (HAZ <-2SD), with 2-arms each i) OPV and ii) OPV and IPV. Two blood specimens (2ml) at baseline and at day 28 and two stool specimens (6 gm.) at day 29 and after 7 days. All infants received a bOPV challenge dose after first stool specimen. Calculates sample size was 210 in each arm. Serological (baseline compared to 28 days post-vaccine) and mucosal immunity after one week of bOPV challenge dose were study outcomes. Results: Baseline seroprevalence in malnourished infants were low compared to non-malnourished (P1, P2 and P3 (p=<0.001). There is significant rise in antibody titer and P1 seroprevalence in Mal A and B after receiving study vaccine; much higher in Mal B. Infants randomized to bOPV + IPV study vaccine showed incremental immune response against P1 (Mal B, 92.2%; Nor B, 98.4%), P2 (Mal B, 90.4%; Nor B, 94.7%), and P3 (Mal B, 85.6% and Nor B, 93.5%) was observed. A significant proportion of infants in malnourished (P1, 13%; P2, 24%; P3, 26%) and normally nourished group (P1, 5%; P2, 11%; P3, 14%) were found to be seronegative at baseline. Infants who received BOPV + IPV as their study vaccine showed a very high seroconversion response after vaccine (p=<0.001 for P1, P2 and P3). Majority of the specimens were negative at baseline (Mal A, 2%, Mal B, 1%; Nor A, 2%; Nor B, 1%), and remains negative after bOPV challenge dose (Mal A, 8%, Mal B, 6%; Nor A, 11%; Nor B, 10%). Conclusion: Malnourished-infants have low poliovirus-seroprevalence that increased remarkably after IPV. There is less viral shedding after IPV in infants.Keywords: chronic malnutrition, infants, IPV, OPV
Procedia PDF Downloads 3958991 Literature Review on the Barriers to Access Credit for Small Agricultural Producers and Policies to Mitigate Them in Developing Countries
Authors: Margarita Gáfaro, Karelys Guzmán, Paola Poveda
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This paper establishes the theoretical aspects that explain the barriers to accessing credit for small agricultural producers in developing countries and identifies successful policy experiences to mitigate them. We will test two hypotheses. The first one is that information asymmetries, high transaction costs and high-risk exposure limit the supply of credit to small agricultural producers in developing countries. The second hypothesis is that low levels of financial education and productivity and high uncertainty about the returns of agricultural activity limit the demand for credit. To test these hypotheses, a review of the theoretical and empirical literature on access to rural credit in developing countries will be carried out. The first part of this review focuses on theoretical models that incorporate information asymmetries in the credit market and analyzes the interaction between these asymmetries and the characteristics of the agricultural sector in developing countries. Some of the characteristics we will focus on are the absence of collateral, the underdevelopment of the judicial systems and insurance markets, and the high dependence on climatic factors of production technologies. The second part of this review focuses on the determinants of credit demand by small agricultural producers, including the profitability of productive projects, security conditions, risk aversion or loss, financial education, and cognitive biases, among others. There are policies that focus on resolving these supply and demand constraints and managing to improve credit access. Therefore, another objective of this paper is to present a review of effective policies that have promoted access to credit for smallholders in the world. For this, information available in policy documents will be collected. This information will be complemented by interviews with officials in charge of the design and execution of these policies in a subset of selected countries. The information collected will be analyzed in light of the conceptual framework proposed in the first two parts of this section. The barriers to access to credit that each policy attempts to resolve and the factors that could explain its effectiveness will be identified.Keywords: agricultural economics, credit access, smallholder, developing countries
Procedia PDF Downloads 608990 Efficient Heuristic Algorithm to Speed Up Graphcut in Gpu for Image Stitching
Authors: Tai Nguyen, Minh Bui, Huong Ninh, Tu Nguyen, Hai Tran
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GraphCut algorithm has been widely utilized to solve various types of computer vision problems. Its expensive computational cost encouraged many researchers to improve the speed of the algorithm. Recent works proposed schemes that work on parallel computing platforms such as CUDA. However, the problem of low convergence speed prevents the usage of GraphCut for real time applications. In this paper, we propose global suppression heuristic to boost the conver-gence process of the algorithm. A parallel implementation of GraphCut algorithm on CUDA designed for the image stitching problem is introduced. Our method achieves up to 3× time boost on the graph of size 80 × 480 compared to the best sequential GraphCut algorithm while achieving satisfactory stitched images, suitable for panorama applications. Our source code will be soon available for further research.Keywords: CUDA, graph cut, image stitching, texture synthesis, maxflow/mincut algorithm
Procedia PDF Downloads 1208989 Crater Detection Using PCA from Captured CMOS Camera Data
Authors: Tatsuya Takino, Izuru Nomura, Yuji Kageyama, Shin Nagata, Hiroyuki Kamata
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We propose a method of detecting the craters from the image of the lunar surface. This proposal assumes that it is applied to SLIM (Smart Lander for Investigating Moon) working group aiming at the pinpoint landing on the lunar surface and investigating scientific research. It is difficult to equip and use high-performance computers for the small space probe. So, it is necessary to use a small computer with an exclusive hardware such as FPGA. We have studied the crater detection using principal component analysis (PCA), In this paper, We implement detection algorithm into the FPGA, and the detection is performed on the data that was captured from the CMOS camera.Keywords: crater detection, PCA, FPGA, image processing
Procedia PDF Downloads 5428988 A Hybrid Heuristic for the Team Orienteering Problem
Authors: Adel Bouchakhchoukha, Hakim Akeb
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In this work, we propose a hybrid heuristic in order to solve the Team Orienteering Problem (TOP). Given a set of points (or customers), each with associated score (profit or benefit), and a team that has a fixed number of members, the problem to solve is to visit a subset of points in order to maximize the total collected score. Each member performs a tour starting at the start point, visiting distinct customers and the tour terminates at the arrival point. In addition, each point is visited at most once, and the total time in each tour cannot be greater than a given value. The proposed heuristic combines beam search and a local optimization strategy. The algorithm was tested on several sets of instances and encouraging results were obtained.Keywords: team orienteering problem, vehicle routing, beam search, local search
Procedia PDF Downloads 4148987 A Discovery of the Dual Sequential Pattern of Prime Numbers in P x P: Applications in a Formal Proof of the Twin-Prime Conjecture
Authors: Yingxu Wang
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This work presents basic research on the recursive structures and dual sequential patterns of primes for the formal proof of the Twin-Prime Conjecture (TPC). A rigorous methodology of Twin-Prime Decomposition (TPD) is developed in MATLAB to inductively verify potential twins in the dual sequences of primes. The key finding of this basic study confirms that the dual sequences of twin primes are not only symmetric but also infinitive in the unique base 6 cycle, except a limited subset of potential pairs is eliminated by the lack of dual primality. Both theory and experiments have formally proven that the infinity of twin primes stated in TPC holds in the P x P space.Keywords: number theory, primes, twin-prime conjecture, dual primes (P x P), twin prime decomposition, formal proof, algorithm
Procedia PDF Downloads 598986 A Novel NRIS Index to Evaluate Brain Activity in Prefrontal Regions While Listening to First and Second Languages for Long Time Periods
Authors: Kensho Takahashi, Ko Watanabe, Takashi Kaburagi, Hiroshi Tanaka, Kajiro Watanabe, Yosuke Kurihara
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Near-infrared spectroscopy (NIRS) has been widely used as a non-invasive method to measure brain activity, but it is corrupted by baseline drift noise. Here we present a method to measure regional cerebral blood flow as a derivative of NIRS output. We investigate whether, when listening to languages, blood flow can reasonably localize and represent regional brain activity or not. The prefrontal blood flow distribution pattern when advanced second-language listeners listened to a second language (L2) was most similar to that when listening to their first language (L1) among the patterns of mean and standard deviation. In experiments with 25 healthy subjects, the maximum blood flow was localized to the left BA46 of advanced listeners. The blood flow presented is robust to baseline drift and stably localizes regional brain activity.Keywords: NIRS, oxy-hemoglobin, baseline drift, blood flow, working memory, BA46, first language, second language
Procedia PDF Downloads 5548985 Thermal Property Improvement of Silica Reinforced Epoxy Composite Specimens
Authors: Hyu Sang Jo, Gyo Woo Lee
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In this study, the mechanical and thermal properties of epoxy composites that are reinforced with micrometer-sized silica particles were investigated by using the specimen experiments. For all specimens used in this study (from the baseline to specimen containing 70 wt% silica filler), the tensile strengths were gradually increased by 8-10%, but the ductility of the specimen was decreased by 34%, compared with those of the baseline samples. Similarly, for the samples containing 70 wt% silica filler, the coefficient of thermal expansion was reduced by 25%, but the thermal conductivity was increased by 100%, compared with those of the baseline samples. The improvement of thermal stability of the silica-reinforced specimen was confirmed to be within the experimented range, and the smaller silica particle was found to be more effective in delaying the thermal expansion of the specimens. When the smaller particle was used as filler, due to the increased specific interface area between filler and matrix, the thermal conductivities of the composite specimens were measured to be slightly lower than those of the specimens reinforced with the larger particle.Keywords: carbon nanotube filler, epoxy composite, mechanical property, thermal property
Procedia PDF Downloads 2318984 Travel Planning in Public Transport Networks Applying the Algorithm A* for Metropolitan District of Quito
Authors: M. Fernanda Salgado, Alfonso Tierra, Wilbert Aguilar
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The present project consists in applying the informed search algorithm A star (A*) to solve traveler problems, applying it by urban public transportation routes. The digitization of the information allowed to identify 26% of the total of routes that are registered within the Metropolitan District of Quito. For the validation of this information, data were taken in field on the travel times and the difference with respect to the times estimated by the program, resulting in that the difference between them was not greater than 2:20 minutes. We validate A* algorithm with the Dijkstra algorithm, comparing nodes vectors based on the public transport stops, the validation was established through the student t-test hypothesis. Then we verified that the times estimated by the program using the A* algorithm are similar to those registered on field. Furthermore, we review the performance of the algorithm generating iterations in both algorithms. Finally, with these iterations, a hypothesis test was carried out again with student t-test where it was concluded that the iterations of the base algorithm Dijsktra are greater than those generated by the algorithm A*.Keywords: algorithm A*, graph, mobility, public transport, travel planning, routes
Procedia PDF Downloads 2308983 Design of H-Shape X-band Application Electrically Small Antenna
Authors: Riki H. Patel, Arpan H. Desai, Trushit Upadhyaya
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This paper presents a new small electrically antenna rectangular X- band micro-strip patch antenna loaded with material Rogers RT/duroid 5870 (tm). The present discussion focuses on small Electrically antenna which are electrically small compared to wave length the performance of electrically small antenna are closely related to their electrical size, the gain can be increased to maintain the efficiency of the radiator. Basically micro-strip Patch antennas have been used in satellite communications and for their good characteristics such as lightness, low cost, and so on. Here in the design H- shape folded dipole, which increase the band width of the antenna.Keywords: electrically small antennas, X-band application, antenna, micro-strip patch, frequency antenna, feed, gain
Procedia PDF Downloads 4598982 Experimental and CFD of Desgined Small Wind Turbine
Authors: Tarek A. Mekail, Walid M. A. Elmagid
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Many researches have concentrated on improving the aerodynamic performance of wind turbine blade through testing and theoretical studies. A small wind turbine blade is designed, fabricated and tested. The power performance of small horizontal axis wind turbines is simulated in details using Computational Fluid Dynamic (CFD). The three-dimensional CFD models are presented using ANSYS-CFX v13 software for predicting the performance of a small horizontal axis wind turbine. The simulation results are compared with the experimental data measured from a small wind turbine model, which designed according to a vehicle-based test system. The analysis of wake effect and aerodynamic of the blade can be carried out when the rotational effect was simulated. Finally, comparison between experimental, numerical and analytical performance has been done. The comparison is fairly good.Keywords: small wind turbine, CFD of wind turbine, CFD, performance of wind turbine, test of small wind turbine, wind turbine aerodynamic, 3D model
Procedia PDF Downloads 5348981 Features Reduction Using Bat Algorithm for Identification and Recognition of Parkinson Disease
Authors: P. Shrivastava, A. Shukla, K. Verma, S. Rungta
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Parkinson's disease is a chronic neurological disorder that directly affects human gait. It leads to slowness of movement, causes muscle rigidity and tremors. Gait serve as a primary outcome measure for studies aiming at early recognition of disease. Using gait techniques, this paper implements efficient binary bat algorithm for an early detection of Parkinson's disease by selecting optimal features required for classification of affected patients from others. The data of 166 people, both fit and affected is collected and optimal feature selection is done using PSO and Bat algorithm. The reduced dataset is then classified using neural network. The experiments indicate that binary bat algorithm outperforms traditional PSO and genetic algorithm and gives a fairly good recognition rate even with the reduced dataset.Keywords: parkinson, gait, feature selection, bat algorithm
Procedia PDF Downloads 5358980 FlexPoints: Efficient Algorithm for Detection of Electrocardiogram Characteristic Points
Authors: Daniel Bulanda, Janusz A. Starzyk, Adrian Horzyk
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The electrocardiogram (ECG) is one of the most commonly used medical tests, essential for correct diagnosis and treatment of the patient. While ECG devices generate a huge amount of data, only a small part of them carries valuable medical information. To deal with this problem, many compression algorithms and filters have been developed over the past years. However, the rapid development of new machine learning techniques poses new challenges. To address this class of problems, we created the FlexPoints algorithm that searches for characteristic points on the ECG signal and ignores all other points that do not carry relevant medical information. The conducted experiments proved that the presented algorithm can significantly reduce the number of data points which represents ECG signal without losing valuable medical information. These sparse but essential characteristic points (flex points) can be a perfect input for some modern machine learning models, which works much better using flex points as an input instead of raw data or data compressed by many popular algorithms.Keywords: characteristic points, electrocardiogram, ECG, machine learning, signal compression
Procedia PDF Downloads 1578979 Selecting the Best RBF Neural Network Using PSO Algorithm for ECG Signal Prediction
Authors: Najmeh Mohsenifar, Narjes Mohsenifar, Abbas Kargar
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In this paper, has been presented a stable method for predicting the ECG signals through the RBF neural networks, by the PSO algorithm. In spite of quasi-periodic ECG signal from a healthy person, there are distortions in electro cardiographic data for a patient. Therefore, there is no precise mathematical model for prediction. Here, we have exploited neural networks that are capable of complicated nonlinear mapping. Although the architecture and spread of RBF networks are usually selected through trial and error, the PSO algorithm has been used for choosing the best neural network. In this way, 2 second of a recorded ECG signal is employed to predict duration of 20 second in advance. Our simulations show that PSO algorithm can find the RBF neural network with minimum MSE and the accuracy of the predicted ECG signal is 97 %.Keywords: electrocardiogram, RBF artificial neural network, PSO algorithm, predict, accuracy
Procedia PDF Downloads 6188978 Small Traditional Retailers in Emerging Markets
Authors: Y. Boulaksil, J. C. Fransoo, E.E. Blanco, S. Koubida
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In this paper, we study the small traditional retailers that are located in the neighborhoods of big cities in emerging markets. Although modern retailing has grown in the last two decades in these markets, the number of small retailers is still increasing and serving a substantial part of the daily demand for many basic products, such as bread, milk, and cooking oil. We conduct an empirical study to understand the business environment of these small traditional retailers in emerging markets by collecting data from 333 small retailers, spread over 8 large cities in Morocco. We analyze the data and describe their business environment with a focus on the informal credits they offer to their customers. We find that smaller small retailers that are funded from personal savings and managed by the owner himself offer relatively the most credits. Our study also provides interesting insights about these small retailers that will help FMCG manufacturers that are (planning to be) active in Morocco and other emerging markets. We also discuss a number opportunities to improve the efficiency of the supply chains that serve them.Keywords: small retailers, big cities, emerging markets, empirical study, supply chain management, Morocco
Procedia PDF Downloads 5698977 Improvement of the Aerodynamic Behaviour of a Land Rover Discovery 4 in Turbulent Flow Using Computational Fluid Dynamics (CFD)
Authors: Ahmed Al-Saadi, Ali Hassanpour, Tariq Mahmud
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The main objective of this study is to investigate ways to reduce the aerodynamic drag coefficient and to increase the stability of the full-size Sport Utility Vehicle using three-dimensional Computational Fluid Dynamics (CFD) simulation. The baseline model in the simulation was the Land Rover Discovery 4. Many aerodynamic devices and external design modifications were used in this study. These reduction aerodynamic techniques were tested individually or in combination to get the best design. All new models have the same capacity and comfort of the baseline model. Uniform freestream velocity of the air at inlet ranging from 28 m/s to 40 m/s was used. ANSYS Fluent software (version 16.0) was used to simulate all models. The drag coefficient obtained from the ANSYS Fluent for the baseline model was validated with experimental data. It is found that the use of modern aerodynamic add-on devices and modifications has a significant effect in reducing the aerodynamic drag coefficient.Keywords: aerodynamics, RANS, sport utility vehicle, turbulent flow
Procedia PDF Downloads 3108976 Effect of Kinesio Taping on Anaerobic Power and Maximum Oxygen Consumption after Eccentric Exercise
Authors: Disaphon Boobpachat, Nuttaset Manimmanakorn, Apiwan Manimmanakorn, Worrawut Thuwakum, Michael J. Hamlin
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Objectives: To evaluate effect of kinesio tape compared to placebo tape and static stretching on recovery of anaerobic power and maximal oxygen uptake (Vo₂max) after intensive exercise. Methods: Thirty nine untrained healthy volunteers were randomized to 3 groups for each intervention: elastic tape, placebo tape and stretching. The participants performed intensive exercise on the dominant quadriceps by using isokinetic dynamometry machine. The recovery process was evaluated by creatine kinase (CK), pressure pain threshold (PPT), muscle soreness scale (MSS), maximum voluntary contraction (MVC), jump height, anaerobic power and Vo₂max at baseline, immediately post-exercise and post-exercise day 1, 2, 3 and 7. Results: The kinesio tape, placebo tape and stretching groups had significant changes of PPT, MVC, jump height at immediately post-exercise compared to baseline (p < 0.05), and changes of MSS, CK, anaerobic power and Vo₂max at day 1 post-exercise compared to baseline (p < 0.05). There was no significant difference of those outcomes among three groups. Additionally, all experimental groups had little effects on anaerobic power and Vo₂max compared to baseline and compared among three groups (p > 0.05). Conclusion: Kinesio tape and stretching did not improve recovery of anaerobic power and Vo₂max after eccentric exercise compared to placebo tape.Keywords: stretching, eccentric exercise, Wingate test, muscle soreness
Procedia PDF Downloads 1278975 Optimal Emergency Shipment Policy for a Single-Echelon Periodic Review Inventory System
Authors: Saeed Poormoaied, Zumbul Atan
Abstract:
Emergency shipments provide a powerful mechanism to alleviate the risk of imminent stock-outs and can result in substantial benefits in an inventory system. Customer satisfaction and high service level are immediate consequences of utilizing emergency shipments. In this paper, we consider a single-echelon periodic review inventory system consisting of a single local warehouse, being replenished from a central warehouse with ample capacity in an infinite horizon setting. Since the structure of the optimal policy appears to be complicated, we analyze this problem under an order-up-to-S inventory control policy framework, the (S, T) policy, with the emergency shipment consideration. In each period of the periodic review policy, there is a single opportunity at any point of time for the emergency shipment so that in case of stock-outs, an emergency shipment is requested. The goal is to determine the timing and amount of the emergency shipment during a period (emergency shipment policy) as well as the base stock periodic review policy parameters (replenishment policy). We show that how taking advantage of having an emergency shipment during periods improves the performance of the classical (S, T) policy, especially when fixed and unit emergency shipment costs are small. Investigating the structure of the objective function, we develop an exact algorithm for finding the optimal solution. We also provide a heuristic and an approximation algorithm for the periodic review inventory system problem. The experimental analyses indicate that the heuristic algorithm is computationally more efficient than the approximation algorithm, but in terms of the solution efficiency, the approximation algorithm performs very well. We achieve up to 13% cost savings in the (S, T) policy if we apply the proposed emergency shipment policy. Moreover, our computational results reveal that the approximated solution is often within 0.21% of the globally optimal solution.Keywords: emergency shipment, inventory, periodic review policy, approximation algorithm.
Procedia PDF Downloads 1348974 Application of a New Efficient Normal Parameter Reduction Algorithm of Soft Sets in Online Shopping
Authors: Xiuqin Ma, Hongwu Qin
Abstract:
A new efficient normal parameter reduction algorithm of soft set in decision making was proposed. However, up to the present, few documents have focused on real-life applications of this algorithm. Accordingly, we apply a New Efficient Normal Parameter Reduction algorithm into real-life datasets of online shopping, such as Blackberry Mobile Phone Dataset. Experimental results show that this algorithm is not only suitable but feasible for dealing with the online shopping.Keywords: soft sets, parameter reduction, normal parameter reduction, online shopping
Procedia PDF Downloads 505