Search results for: back propagation algorithm

Authors: Pintu Modak

Abstract:

The core strength is essential not only for athletes but also for everyone to perform everyday's household chores with ease and efficiency. Core strength means to strengthen the muscles deep within the abdomen which connect to the spine and pelvis which control the position and movement of the central portion of the body. Strengthening of core muscles is important for injury prevention (lower back pain) and performance enhancement in sports. The purpose of the study was to review the literature and findings on the effects of Yoga exercise as a part of sports training method and fitness programs. Fifteen papers were found to be relevant for this review. There are five simple yoga poses: Ardha Phalakasana (Low plank), Vasisthasana (side plank), Purvottanasana (inclined plane), Sarvangasana (shoulder stand), and Virabhadrasana (Warrior) are found to be very effective for strengthening core muscles. They are the most effective poses to build core strength and flexibility to the core muscles. The study suggests that sports and fitness trainers should include these yoga exercises in their programs to strengthen core muscles.

Keywords: core strength, yoga, injuries, lower back

Procedia PDF Downloads 257

Authors: Essam Al Daoud

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This study solves a phylogeny problem by using modified wild dog pack optimization. The least squares error is considered as a cost function that needs to be minimized. Therefore, in each iteration, new distance matrices based on the constructed trees are calculated and used to select the alpha dog. To test the suggested algorithm, ten homologous genes are selected and collected from National Center for Biotechnology Information (NCBI) databanks (i.e., 16S, 18S, 28S, Cox 1, ITS1, ITS2, ETS, ATPB, Hsp90, and STN). The data are divided into three categories: 50 taxa, 100 taxa and 500 taxa. The empirical results show that the proposed algorithm is more reliable and accurate than other implemented methods.

Keywords: least square, neighbor joining, phylogenetic tree, wild dog pack

Procedia PDF Downloads 307

Authors: Mu-Yen Chen, Min-Hsuan Fan, Chia-Chen Chen, Siang-Yu Jhong

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In recent years, real estate prediction or valuation has been a topic of discussion in many developed countries. Improper hype created by investors leads to fluctuating prices of real estate, affecting many consumers to purchase their own homes. Therefore, scholars from various countries have conducted research in real estate valuation and prediction. With the back-propagation neural network that has been popular in recent years and the orthogonal array in the Taguchi method, this study aimed to find the optimal parameter combination at different levels of orthogonal array after the system presented different parameter combinations, so that the artificial neural network obtained the most accurate results. The experimental results also demonstrated that the method presented in the study had a better result than traditional machine learning. Finally, it also showed that the model proposed in this study had the optimal predictive effect, and could significantly reduce the cost of time in simulation operation. The best predictive results could be found with a fewer number of experiments more efficiently. Thus users could predict a real estate transaction price that is not far from the current actual prices.

Keywords: artificial neural network, Taguchi method, real estate valuation model, investors

Procedia PDF Downloads 465

Authors: Soumaya Sallem, Marc Olivas

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This contribution presents a method for detecting, locating, and characterizing soft faults in a complex wired network. The proposed method is based on multi-carrier reflectometry MCTDR (Multi-Carrier Time Domain Reflectometry) combined with a multi-objective genetic algorithm. In order to ensure complete network coverage and eliminate diagnosis ambiguities, the MCTDR test signal is injected at several points on the network, and the data is merged between different reflectometers (sensors) distributed on the network. An adapted multi-objective genetic algorithm is used to merge data in order to obtain more accurate faults location and characterization. The proposed method performances are evaluated from numerical and experimental results.

Keywords: wired network, reflectometry, network distributed diagnosis, multi-objective genetic algorithm

Procedia PDF Downloads 176

Authors: Ahmed Assem Abd El Rahim

Abstract:

Background: Mechanical low back pain is serious physical and social health problem. Purpose: To examine impact of shock wave therapy versus intermittent mechanical traction on mechanical LBP, and disabilities. Subjects: 60 mechanical LBP male studied cases years old 20-35 years were assigned randomly into 3 groups, Picked up from Sohag university orthopedic hospital outpatient clinic. Methods: (Study Group) A: 20 studied cases underwent shock wave therapy plus conventional physical therapy. (Study Group) B: twenty studied cases underwent intermittent mechanical traction plus conventional physical therapy. (Control Group) C: 20 patients underwent conventional physical therapy alone. Three sessions were applied weekly for four weeks. Pain was quantified using McGill Pain Questionnaire, Roland Morris Disability Questionnaire was used for measuring disability, and the ROM was evaluated by (BROM) device pre- & post-therapy. Results: Groups (A, B & C) found a reduction in pain & disability & rise in their in flexion and extension ROM after end of 4 weeks of program. Mean values of pain scale after therapy were 15.3, 9.47, and 23.07 in groups A, B, & C. mean values of Disability scale after therapy were 8.44, 4.87, 11.8in groups A, B & C. mean values of ROM of flexion were 25.53, 29.06, & 23.9 in groups A, B & C. mean values of ROM of extension were 11.73, 15.53 & 9.85 in groups A, B & C. studied cases who received intermittent mechanical traction & conventional physical therapy (group B), found reduction in pain & disability & improvement in ROM of flexion & extension value (P<0.001) after therapy program. Conclusion: Shock wave therapy and intermittent mechanical traction, as well as conventional physical treatment, can be beneficial in studied cases with mechanical LBP.

Keywords: mechanical low back pain, shock wave, mechanical, low back pain

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Authors: ِAbdallah A. A. Shaheen

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Gaza Strip faces economic and political issues such as conflict, siege and urbanization; all these have led to an increase in the air pollution over Gaza Strip. In this study, Particulate matter 10 (PM10) concentration over Gaza Strip has been estimated by Landsat Thematic Mapper (TM) and Landsat Enhanced Thematic Mapper Plus (ETM+) data, based on a multispectral algorithm. Simultaneously, in-situ measurements for the corresponding particulate are acquired for selected time period. Landsat and ground data for eleven years are used to develop the algorithm while four years data (2002, 2006, 2010 and 2014) have been used to validate the results of algorithm. The developed algorithm gives highest regression, R coefficient value i.e. 0.86; RMSE value as 9.71 µg/m³; P values as 0. Average validation of algorithm show that calculated PM10 strongly correlates with measured PM10, indicating high efficiency of algorithm for the mapping of PM10 concentration during the years 2000 to 2014. Overall results show increase in minimum, maximum and average yearly PM10 concentrations, also presents similar trend over urban area. The rate of urbanization has been evaluated by supervised classification of the Landsat image. Urban sprawl from year 2000 to 2014 results in a high concentration of PM10 in the study area.

Keywords: PM10, landsat, atmospheric reflectance, Gaza strip, urbanization

Procedia PDF Downloads 235

Authors: Naomi Sato, Tomonori Sato, Kenji Masui, Rob Stanborough

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To date, there are few studies on the subjective experiences of patients with chronic low-back pain (CLBP). The purpose of this study was to gain a better understanding of CLBP patients’ perceptions and attitudes regarding pain. Individual, semi-constructed interviews were conducted with 7 Japanese and 10 Americans who had been diagnosed with CLBP. The interviews were transcribed verbatim and analyzed based on a content analysis approach. The study proposal was approved by the Institutional Review Board of the first author’s affiliate university. All participants provided written consent. Participants’ ages ranged from 48 to 82. Five main categories were emerged, namely, 'There are no reasons for long-term chronic pain,' 'Just will not worsen,' 'Have something to help me cope,' 'Pain restricts my life,' and 'Have something to relieve me.' Participants lived with CLBP, which could sometimes be avoided as a result of the coping strategies that they employed, and due to which they sometimes felt helpless, despite their efforts. As a result, they had mixed feelings, which included resignation, resoluteness, and optimism. However, their perceptions and attitudes toward pain seemed to differ based on their backgrounds, including biological, social, religious, and cultural status. There is a need for the development of a scale in future studies, to enable quantitative measurement of individuals’ perceptions of and attitudes toward pain. There is also a need for an investigation of factors influencing perceptions and attitudes toward pain.

Keywords: attitude, chronic low-back pain, perception, qualitative study

Procedia PDF Downloads 233

Authors: Thang V. Kieu, Long P. Nguyen

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Kernelized Correlation Filter (KCF) based trackers have gained a lot of attention recently because of their accuracy and fast calculation speed. However, this algorithm is not robust in cases where the object is lost by a sudden change of direction, being obscured or going out of view. In order to improve KCF performance in long-term tracking, this paper proposes an anomaly detection method for target loss warning by analyzing the response map of each frame, and a classification algorithm for reliable target re-locating mechanism by using Random fern. Being tested with Visual Tracker Benchmark and Visual Object Tracking datasets, the experimental results indicated that the precision and success rate of the proposed algorithm were 2.92 and 2.61 times higher than that of the original KCF algorithm, respectively. Moreover, the proposed tracker handles occlusion better than many state-of-the-art long-term tracking methods while running at 60 frames per second.

Keywords: correlation filter, long-term tracking, random fern, real-time tracking

Procedia PDF Downloads 123

Authors: J. G. Batista, T. S. Santiago, E. A. Ribeiro, G. A. P. Thé

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This work deals with parameter identification of permanent magnet motors, a class of ac motor which is particularly important in industrial automation due to characteristics like applications high performance, are very attractive for applications with limited space and reducing the need to eliminate because they have reduced size and volume and can operate in a wide speed range, without independent ventilation. By using experimental data and genetic algorithm we have been able to extract values for both the motor inductance and the electromechanical coupling constant, which are then compared to measure and/or expected values.

Keywords: modeling, AC servomotor, permanent magnet synchronous motor-PMSM, genetic algorithm, vector control, robotic manipulator, control

Procedia PDF Downloads 502

Authors: A. Belmeguenai, K. Mansouri, R. Djemili

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This work present a new algorithm based on the nonlinear filter generator for speech encryption and decryption. The proposed algorithm consists on the use a linear feedback shift register (LFSR) whose polynomial is primitive and nonlinear Boolean function. The purpose of this system is to construct Keystream with good statistical properties, but also easily computable on a machine with limited capacity calculated. This proposed speech encryption scheme is very simple, highly efficient, and fast to implement the speech encryption and decryption. We conclude the paper by showing that this system can resist certain known attacks.

Keywords: nonlinear filter generator, stream ciphers, speech encryption, security analysis

Procedia PDF Downloads 277

Authors: Pillay J. D., D. De Wit, J. F. Ducray

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Field hockey is a popular international sport which is played in more than 100 countries across the world. Due to the nature of hockey, players repeatedly perform a combination of forward flexion and rotational movements of the spine in order to strike the ball. These movements have been shown to increase the risk of pain and injury to the lumbar spine. The aim of this study was to determine the prevalence and incidence of low back pain (LBP) in male adolescent field hockey players and the characteristics of LBP in terms of location, chronicity, disability, and treatment sought, as well as its association with selected risk factors. A survey was conducted on 112 male adolescent field hockey players in the eThekwini Municipality of KwaZulu-Natal, South Africa. The questionnaire contained sections on the demographics of participants, general characteristics of participants, health and lifestyle characteristics, low back pain patterns, treatment of low back pain, and the level of disability associated with LBP. The data were statistically analysed using IBM SPSS version 25 with statistical significance set at p-value <0.05. Descriptive statistics such as mean and standard deviation were used to summarise responses to continuous variables as appropriate. Categorical variables were described using frequency tables. Associations between risk factors and low back pain were tested using Pearson’s chi-square test and t-tests as appropriate. A total of 68 questionnaires were completed for analysis (67% participation rate); the period prevalence of LBP was 63.2% (35.0%:beginning of the season, 32.4%:mid-season, 22.1%: end of season). Incidence was 38.2%. The most common location for LBP was the middle low back region (39.5%), and the most common duration of pain was a few hours (32.6%). Most participants (79.1%) did not classify their pain as a disability, and only 44.2% of participants received medical treatment for their LBP. An interesting finding was the association between hydration and LBP (p = 0.050), i.e., those individuals who did not hydrate frequently during matches and training were significantly more likely to experience LBP. The results of this study, although limited to a select group of adolescents, showed a higher prevalence of LBP than that of previous studies. More importantly, even though most participants did not experience LBP classified as a disability, LBP still had a large impact on participants, as nearly half of the participants consulted with a medical professional for treatment. Need for the application of further strategies in the prevention and management of LBP in field hockey, such as adequate warm-up and cool-down, stretching exercises, rest between sessions, etc., are recommended as simple strategies to reduce LBP prevalence.

Keywords: adolescents, field hockey players, incidence, low back pain, prevalence, risk factors

Procedia PDF Downloads 44

Authors: Qing Lyu, Hang Zhu

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Various flows in the network require to go through different types of middlebox. The improper placement of network middlebox and path assignment for flows could greatly increase the network latency and also decrease the performance of network. Minimizing the total end to end latency of all the ows requires to assign path for the incoming flows. In this paper, the flow path assignment problem in regard to the placement of various kinds of middlebox is studied. The flow path assignment problem is formulated to a linear programming problem, which is very time consuming. On the other hand, a naive greedy algorithm is studied. Which is very fast but causes much more latency than the linear programming algorithm. At last, the paper presents a heuristic algorithm named FPA, which takes bottleneck link information and estimated bandwidth occupancy into consideration, and achieves near optimal latency in much less time. Evaluation results validate the effectiveness of the proposed algorithm.

Keywords: flow path, latency, middlebox, network

Procedia PDF Downloads 190

Authors: Vesna Karapetkovska Hristova, M. Ayaz Ahmad, Julijana Tomovska, Biljana Bogdanova Popov, Blagojce Najdovski

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The average total concentrations of heavy metals; (cadmium [Cd], copper [Cu], nickel [Ni], lead [Pb], and zinc [Zn]) were analyzed in soil and vegetables samples collected from the different region of Macedonia during the years 2010-2012. Basic soil properties such as pH, organic matter and clay content were also included in the study. The average concentrations of Cd, Cu, Ni, Pb, Zn in the A horizon (0-30 cm) of agricultural soils were as follows, respectively: 0.25, 5.3, 6.9, 15.2, 26.3 mg kg-1 of soil. We have found that neural networking model can be considered as a tool for prediction and spatial analysis of the processes controlling the metal transfer within the soil-and vegetables. The predictive ability of such models is well over 80% as compared to 20% for typical regression models. A radial basic function network reflects good predicting accuracy and correlation coefficients between soil properties and metal content in vegetables much better than the back-propagation method. Neural Networking / soft computing can support the decision-making processes at different levels, including agro ecology, to improve crop management based on monitoring data and risk assessment of metal transfer from soils to vegetables.

Keywords: soft computing approach, total concentrations, heavy metals, agricultural soils

Procedia PDF Downloads 349

Authors: Jorge A. Ruiz-Vanoye, Ocotlán Díaz-Parra, Alejandro Fuentes-Penna, Daniel Vélez-Díaz, Edith Olaco García

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In this paper, we present the use of the discriminant analysis to select evolutionary algorithms that better solve instances of the vehicle routing problem with time windows. We use indicators as independent variables to obtain the classification criteria, and the best algorithm from the generic genetic algorithm (GA), random search (RS), steady-state genetic algorithm (SSGA), and sexual genetic algorithm (SXGA) as the dependent variable for the classification. The discriminant classification was trained with classic instances of the vehicle routing problem with time windows obtained from the Solomon benchmark. We obtained a classification of the discriminant analysis of 66.7%.

Keywords: Intelligent Transportation Systems, data-mining techniques, evolutionary algorithms, discriminant analysis, machine learning

Procedia PDF Downloads 449

Authors: Adilah Abdul Ghapor, Yong Zulina Zubairi, A. H. M. R. Imon

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Missing value problem is common in statistics and has been of interest for years. This article considers two modern techniques in handling missing data for linear functional relationship model (LFRM) namely the Expectation-Maximization (EM) algorithm and Expectation-Maximization with Bootstrapping (EMB) algorithm using three performance indicators; namely the mean absolute error (MAE), root mean square error (RMSE) and estimated biased (EB). In this study, we applied the methods of imputing missing values in two types of LFRM namely the full model of LFRM and in LFRM when the slope is estimated using a nonparametric method. Results of the simulation study suggest that EMB algorithm performs much better than EM algorithm in both models. We also illustrate the applicability of the approach in a real data set.

Keywords: expectation-maximization, expectation-maximization with bootstrapping, linear functional relationship model, performance indicators

Procedia PDF Downloads 439

Authors: Jamileh Darsareh, Mohammad Nikafrooz

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Some teachers and e-content producers, based on their experiences, try to produce educational videos using screen recording software. There are many challenges that they may encounter while producing screen-recorded videos. These are in the domains of technical and pedagogical challenges like designing the roadmap, preparing the screen, setting the recording software and recording the screen, editing, etc. This study is a descriptive study and tries to present some procedures for producing acceptable and well-made videos. These procedures are presented in the form of an algorithm for producing screen-recorded video. This algorithm presents the main producing phases, including design, pre-production, production, post-production, and distribution. These phases consist of some steps which are supported by several technical and pedagogical considerations. Following these phases and steps according to the suggested order helps the producers to produce their intended and desired video by saving time and also facing fewer technical problems. It is expected that by using this algorithm, e-content producers and teachers gain better performance in producing educational videos.

Keywords: e-content producing algorithm, screen-recorded videos, screen recording software, technical and pedagogical considerations

Procedia PDF Downloads 183

Authors: Rimmy Yadav, Avtar Singh

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—Ant Colony Optimization (ACO) is a promising modern approach to the unused combinatorial optimization. Here ACO is applied to finding the shortest during communication link failure. In this paper, the performances of the prim’s and ACO algorithm are made. By comparing the time complexity and program execution time as set of parameters, we demonstrate the pleasant performance of ACO in finding excellent solution to finding shortest path during communication link failure.

Keywords: ant colony optimization, link failure, prim’s algorithm, shortest path

Procedia PDF Downloads 380

Authors: R. Chakib, A. Essadki, M. Cherkaoui

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This paper proposes the study of a robust control of the doubly fed induction generator (DFIG) used in a wind energy production. The proposed control is based on the linear active disturbance rejection control (ADRC) and it is applied to the control currents rotor of the DFIG, the DC bus voltage and active and reactive power exchanged between the DFIG and the network. The system under study and the proposed control are simulated using MATLAB/SIMULINK.

Keywords: doubly fed induction generator (DFIG), active disturbance rejection control (ADRC), vector control, MPPT, extended state observer, back-to-back converter, wind turbine

Procedia PDF Downloads 466

Authors: Jiahe Liu, Hongyang Yu, Feng Qian, Miao Luo

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SMPL-X was a powerful parametric human body model that included male, neutral, and female models, with significant gender differences between these three models. During the process of 3D human body reconstruction, the correct selection of standard templates was crucial for obtaining accurate results. To address this issue, we developed an efficient gender classification algorithm to automatically select the appropriate template for 3D human body reconstruction. The key to this gender classification algorithm was the precise analysis of human body features. By using the SMPL-X model, the algorithm could detect and identify gender features of the human body, thereby determining which standard template should be used. The accuracy of this algorithm made the 3D reconstruction process more accurate and reliable, as it could adjust model parameters based on individual gender differences. SMPL-X and the related gender classification algorithm have brought important advancements to the field of 3D human body reconstruction. By accurately selecting standard templates, they have improved the accuracy of reconstruction and have broad potential in various application fields. These technologies continue to drive the development of the 3D reconstruction field, providing us with more realistic and accurate human body models.

Keywords: gender classification, joint detection, SMPL-X, 3D reconstruction

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Authors: Arslan Ellahi, Syed Amjad Hussain

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Software Testing is a vital process in software development life cycle. We can attain the quality of software after passing it through software testing phase. We have tried to find out automatic test data generation techniques that are a key research area of software testing to achieve test automation that can eventually decrease testing time. In this paper, we review some of the approaches presented in the literature which use evolutionary search based algorithms like Genetic Algorithm, Particle Swarm Optimization (PSO), etc. to validate the test data generation process. We also look into the quality of test data generation which increases or decreases the efficiency of testing. We have proposed test data generation techniques for model-based testing. We have worked on tuning and fitness function of PSO algorithm.

Keywords: search based, evolutionary algorithm, particle swarm optimization, genetic algorithm, test data generation

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Authors: P. K. Singhal, R. Naresh, V. Sharma

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This paper presents the three optimization models, namely New Binary Artificial Bee Colony (NBABC) algorithm, NBABC with Local Search (NBABC-LS), and NBABC with Genetic Crossover (NBABC-GC) for solving the Wind-Thermal Unit Commitment (WTUC) problem. The uncertain nature of the wind power is incorporated using the Weibull probability density function, which is used to calculate the overestimation and underestimation costs associated with the wind power fluctuation. The NBABC algorithm utilizes a mechanism based on the dissimilarity measure between binary strings for generating the binary solutions in WTUC problem. In NBABC algorithm, an intelligent scout bee phase is proposed that replaces the abandoned solution with the global best solution. The local search operator exploits the neighboring region of the current solutions, whereas the integration of genetic crossover with the NBABC algorithm increases the diversity in the search space and thus avoids the problem of local trappings encountered with the NBABC algorithm. These models are then used to decide the units on/off status, whereas the lambda iteration method is used to dispatch the hourly load demand among the committed units. The effectiveness of the proposed models is validated on an IEEE 10-unit thermal system combined with a wind farm over the planning period of 24 hours.

Keywords: artificial bee colony algorithm, economic dispatch, unit commitment, wind power

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Authors: Deepa Das, Susmita Das

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Cognitive Radio (CR) is an emerging technology to combat the spectrum scarcity issues. This is achieved by consistently sensing the spectrum, and detecting the under-utilized frequency bands without causing undue interference to the primary user (PU). In soft decision fusion (SDF) based cooperative spectrum sensing, various evolutionary algorithms have been discussed, which optimize the weight coefficient vector for maximizing the detection performance. In this paper, we propose the hybrid invasive weed optimization and particle swarm optimization (IWO/PSO) algorithm as a fast and global optimization method, which improves the detection probability with a lesser sensing time. Then, the efficiency of this algorithm is compared with the standard invasive weed optimization (IWO), particle swarm optimization (PSO), genetic algorithm (GA) and other conventional SDF based methods on the basis of convergence and detection probability.

Keywords: cognitive radio, spectrum sensing, soft decision fusion, GA, PSO, IWO, hybrid IWO/PSO

Procedia PDF Downloads 446

Authors: Selen Unaldi, Emmanuel Richaud, Matthieu Gervais, Laurent Berthe

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Aircrafts are painted with several layers to guarantee their protection from external attacks. For aluminum AA 2024-T3 (metallic structural part of the plane), a protective primer is applied to ensure its corrosion protection. On top of this layer, the top coat is applied for aesthetic aspects. During the lifetime of an aircraft, top coat stripping has an essential role which should be operated as an average of every four years. However, since conventional stripping processes create hazardous disposals and need long hours of labor work, alternative methods have been investigated. Amongst them, laser stripping appears as one of the most promising techniques not only because of the reasons mentioned above but also its controllable and monitorable aspects. The application of a laser beam from the coated side provides stripping, but the depth of the process should be well controlled in order to prevent damage to a substrate and the anticorrosion primer. Apart from that, thermal effects should be taken into account on the painted layers. As an alternative, we worked on developing a process that includes the usage of shock wave propagation to create the stripping via mechanical effects with the application of the beam from the substrate side (back face) of the samples. Laser stripping was applied on thickness-specified samples with a thickness deviation of 10-20%. First, the stripping threshold is determined as a function of power density which is the first flight off of the top coats. After obtaining threshold values, the same power densities were applied to specimens to create large stripping zones with a spot overlap of 10-40%. Layer characteristics were determined on specimens in terms of physicochemical properties and thickness range both before and after laser stripping in order to validate the substrate material health and coating properties. The substrate health is monitored by measuring the roughness of the laser-impacted zones and free surface energy tests (both before and after laser stripping). Also, Hugoniot Elastic Limit (HEL) is determined from VISAR diagnostic on AA 2024-T3 substrates (for the back face surface deformations). In addition, the coating properties are investigated as a function of adhesion levels and anticorrosion properties (neutral salt spray test). The influence of polyurethane top-coat thickness is studied in order to verify the laser stripping process window for industrial aircraft applications.

Keywords: aircraft coatings, laser stripping, laser adhesion tests, epoxy, polyurethane

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Authors: Jiahe Liu, HongyangYu, Feng Qian, Miao Luo

Abstract:

The aim of this study was to improve the effects of human body 3D reconstruction. The MvP algorithm was adopted to obtain key point information from multiple perspectives. This algorithm allowed the capture of human posture and joint positions from multiple angles, providing more comprehensive and accurate data. The study also incorporated the SMPL-X model, which has been widely used for human body modeling, to achieve more accurate 3D reconstruction results. The use of the MvP algorithm made it possible to observe the reconstructed object from multiple angles, thus reducing the problems of blind spots and missing information. This algorithm was able to effectively capture key point information, including the position and rotation angle of limbs, providing key data for subsequent 3D reconstruction. Compared with traditional single-view methods, the method of multi-view fusion significantly improved the accuracy and stability of reconstruction. By combining the MvP algorithm with the SMPL-X model, we successfully achieved better human body 3D reconstruction effects. The SMPL-X model is highly scalable and can generate highly realistic 3D human body models, thus providing more detail and shape information.

Keywords: 3D human reconstruction, multi-view, joint point, SMPL-X

Procedia PDF Downloads 50

Authors: Mafarja Majdi, Salwani Abdullah, Najmeh S. Jaddi

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One of the global combinatorial optimization problems in machine learning is feature selection. It concerned with removing the irrelevant, noisy, and redundant data, along with keeping the original meaning of the original data. Attribute reduction in rough set theory is an important feature selection method. Since attribute reduction is an NP-hard problem, it is necessary to investigate fast and effective approximate algorithms. In this paper, we proposed two feature selection mechanisms based on memetic algorithms (MAs) which combine the genetic algorithm with a fuzzy record to record travel algorithm and a fuzzy controlled great deluge algorithm to identify a good balance between local search and genetic search. In order to verify the proposed approaches, numerical experiments are carried out on thirteen datasets. The results show that the MAs approaches are efficient in solving attribute reduction problems when compared with other meta-heuristic approaches.

Keywords: rough set theory, attribute reduction, fuzzy logic, memetic algorithms, record to record algorithm, great deluge algorithm

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Authors: Qazi Salman Khalid, Muhammad Khalid, Shahid Maqsood

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This paper presents a solution for optimizing the cycle time in an assembly line with human-robot collaboration and diverse operators. A genetic algorithm with tailored parameters is used to address the assembly line balancing problem in the automobile sector. A mathematical model is developed, depicting the problem. Currently, the firm runs on the largest candidate rule; however, it causes a lag in orders, which ultimately gets penalized. The results of the study show that the proposed GA is effective in providing efficient solutions and that the cycle time has significantly impacted productivity.

Keywords: line balancing, cycle time, genetic algorithm, productivity

Procedia PDF Downloads 120

Authors: Zhang Xiaodong, Tang Zixin, Liu Xin

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In order to avoid self-collision of space manipulators during operation process, a real-time detection method is proposed in this paper. The manipulator is fitted into a cylinder enveloping surface, and then the detection algorithm of collision between cylinders is analyzed. The collision model of space manipulator self-links can be detected by using this algorithm in real-time detection during the operation process. To ensure security of the operation, a safety threshold is designed. The simulation and experiment results verify the effectiveness of the proposed algorithm for a 7-DOF space manipulator.

Keywords: space manipulator, collision detection, self-collision, the real-time collision detection

Procedia PDF Downloads 445

Authors: Ahmed R. Z. Baghdadi, Ibrahim M. I. Hamoda,  Mona H. Gamal Eldein, Ibrahim Magdy Elnaggar

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Background: High-velocity low amplitude thrust (HVLAT) manipulation and low-velocity low amplitude (LVLA) mobilization are an effective treatment for low back pain (LBP). Purpose: This study compared the effects of HVLAT versus LVLA on pain, functional deficits and segmental mobility in treatment of chronic mechanical LBP. Methods: Ninety patients suffering from chronic mechanical LBP are classified to three groups; Thirty patients treated by HVLAT (group I), thirty patients treated by LVLA (group II) and thirty patients as control group (group III) participated in the study. The mean age was 28.00±2.92, 27.83±2.28 and 28.07±3.05 years and BMI 27.98±2.60, 28.80±2.40 and 28.70±2.53 kg/m2 for group I, II and III respectively. The Visual Analogue Scale (VAS), the Oswestry low back pain disability questionnaire and modified schoper test were used for assessment. Assessments were conducted two weeks before and after treatment with the control group being assessed at the same time intervals. The treatment program group one was two weeks single session per week, and for group II two sessions per week for two weeks. Results: The One-way ANOVA revealed that group I had significantly lower pain scores and Oswestry score compared with group II two weeks after treatment. Moreover, the mobility in modified schoper increased significantly and the pain scores and Oswestry scores decreased significantly after treatment in group I and II compared with control group. Interpretation/Conclusion: HVLAT is preferable to LVLA mobilization, possibly due to a beneficial neurophysiological effect by Stimulating mechanically sensitive neurons in the lumbar facet joint capsule.

Keywords: low back pain, manipulation, mobilization, low velocity

Procedia PDF Downloads 578

Authors: Konstantinos Metaxiotis, Konstantinos Liagkouras

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The objective of this study is to examine the performance of three well-known multiobjective evolutionary algorithms for solving optimization problems. The first algorithm is the Non-dominated Sorting Genetic Algorithm-II (NSGA-II), the second one is the Strength Pareto Evolutionary Algorithm 2 (SPEA-2), and the third one is the Multiobjective Evolutionary Algorithms based on decomposition (MOEA/D). The examined multiobjective algorithms are analyzed and tested on the ZDT set of test functions by three performance metrics. The results indicate that the NSGA-II performs better than the other two algorithms based on three performance metrics.

Keywords: MOEAs, multiobjective optimization, ZDT test functions, evolutionary algorithms

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Authors: Rosa L. Figueroa, Christopher A. Flores, Qing Zeng-Treitler

Abstract:

A regular expression consists of sequence characters which allow describing a text path. Usually, in clinical research, regular expressions are manually created by programmers together with domain experts. Lately, there have been several efforts to investigate how to generate them automatically. This article presents a text classification algorithm based on regexes. The algorithm named REX was designed, and then, implemented as a simplified method to create regexes to classify Spanish text automatically. In order to classify ambiguous cases, such as, when multiple labels are assigned to a testing example, REX includes an information gain method Two sets of data were used to evaluate the algorithm’s effectiveness in clinical text classification tasks. The results indicate that the regular expression based classifier proposed in this work performs statically better regarding accuracy and F-measure than Support Vector Machine and Naïve Bayes for both datasets.

Keywords: information gain, regular expressions, smith-waterman algorithm, text classification

Procedia PDF Downloads 301