Search results for: permanent magnet machines

Authors: Khin Mar Yee, Mu Mu Than, Kyi Lint, Aye Aye Oo, Chan Mya Hmway, Khin Zar Chi Winn

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The dynamic changes of Land Use and Land Cover (LULC) changes in Yangon have generally resulted the improvement of human welfare and economic development since the last twenty years. Making map of LULC is crucially important for the sustainable development of the environment. However, the exactly data on how environmental factors influence the LULC situation at the various scales because the nature of the natural environment is naturally composed of non-homogeneous surface features, so the features in the satellite data also have the mixed pixels. The main objective of this study is to the calculation of accuracy based on change detection of LULC changes by Support Vector Machines (SVMs). For this research work, the main data was satellite images of 1996, 2006 and 2015. Computing change detection statistics use change detection statistics to compile a detailed tabulation of changes between two classification images and Support Vector Machines (SVMs) process was applied with a soft approach at allocation as well as at a testing stage and to higher accuracy. The results of this paper showed that vegetation and cultivated area were decreased (average total 29 % from 1996 to 2015) because of conversion to the replacing over double of the built up area (average total 30 % from 1996 to 2015). The error matrix and confidence limits led to the validation of the result for LULC mapping.

Keywords: land use and land cover change, change detection, image processing, support vector machines

Procedia PDF Downloads 94

Authors: Marcelo Franzkowiak Stahlschmidt

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This paper discusses the experiments carried out based on the wire drawing process analysis and later annealing on lead furnace on a galvanizing line. Using Design of Experiments methodology, the aim of this work is to understand the occurrence of lead entrainment originating from the annealed wires in order to decrease this problem. Wire samples were collected from wire drawing machines and galvanizing line and submitted to surface roughness analysis and its implications on lead drag out based on wire speed, wire diameter, lead bath temperature, thermal capacity of the lead kettle, wire surface condition, wire roughness and wire superficial cleanliness. Proposals to decrease lead drag out were made in order to increase wire drawing machines and galvanizing line performance.

Keywords: wire drawing process, galvanizing, heat treatment, lead

Procedia PDF Downloads 612

Authors: André M. Senna, Mary L. G. S. Senna, Rosa M. Machado-de-Sena

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One of the great challenges presented in educational practice is how to ensure the students not only acquire knowledge of training courses throughout their academic life, but also how to apply it in their current professional activities. Consequently, aiming to incite changes in the education system of healthcare professionals noticed the inadequacy of the training providers to solve the social problems related to health, the education related to these procedures should initiate in the earliest years of process. Following that idea, there is another question that needs an answer: If the change in the education should start sooner, in the period of basic training of healthcare professionals, what guidelines should a permanent education program incorporate to promote changes in an already established system? For this reason, the objective of this paper is to present different views of the teaching-learning process, with the purpose of better understanding the behavior adopted by healthcare professionals, through bibliographic study. The conclusion was that more than imparting knowledge to the individual, a larger approach is necessary on permanent education programs concerning the performance of professional health services in order to foment significant changes in education.

Keywords: Health Education, continuing education, training, behavior

Procedia PDF Downloads 242

Authors: V. T. Ngo, D. M. Xie

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Frequently, in the design of machines, some of parameters that directly affect the rotor dynamics of the machines are not accurately known. In particular, bearing stiffness support is one such parameter. One of the most basic principles to grasp in rotor dynamics is the influence of the bearing stiffness on the critical speeds and mode shapes associated with a rotor-bearing system. Taking a rig shafting as an example, this paper studies the lateral vibration of the rotor with multi-degree-of-freedom by using Finite Element Method (FEM). The FEM model is created and the eigenvalues and eigenvectors are calculated and analyzed to find natural frequencies, critical speeds, mode shapes. Then critical speeds and mode shapes are analyzed by set bearing stiffness changes. The model permitted to identify the critical speeds and bearings that have an important influence on the vibration behavior.

Keywords: lateral vibration, finite element method, rig shafting, critical speed

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Authors: Fadwa Chtioui

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Vital Pulp Therapy (VPT) is nowadays challenging the deep-rooted dogma of root canal treatment, being the only therapeutic option for permanent teeth diagnosed with irreversible pulpitis or carious pulp exposure. Histologic and clinical research has shown that compromised dental pulp can be treated without the full removal or excavation of all healthy pulp, and the outcome of the partial or full pulpotomy followed by a Tricalcium-Silicate-based dressing seems to show promising results in maintaining pulp vitality and preserving affected teeth in the long term. By reviewing recent advances in the techniques of VPT and their clinical effectiveness and safety in permanent teeth with irreversible Pulpitis, this work provides a new understanding of pulp pathophysiology and defense mechanisms and will reform dental practitioners' decision-making in treating irreversible pulpits from root canal therapy to vital pulp therapy by taking advantage of the biological effects of Tricalcium Silicate materials. Biography of presenting author: Fadwa Chitoui graduated from the school of Dental Medicine of Monastir, Tunisia, in 2015. After getting her DDS degree with honors, she earned her Postgraduate master's Degree in Endodontics and Restorative Dentistry from her Faculty. Since 2021, she has Started her own private and specialized practice based in the capital Tunis. She enjoys the sphere of associative life, worked with national and international associations, and got engaged in scientific dental research, whereby she tailored her passion for her field of specialty towards broadening her knowledge and ambitions, holding conferences and workshops nationally and internationally and publishing scientific articles in several journals.

Keywords: irreversible pulpitis, permanenet teeth, vital pulp therapy, pulpotomy

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Authors: Nadia el Atlas, Mohammed el Aroussi, Mohammed Wahbi

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In this paper a novel technique of mass characterization based on robust features-fusion is presented. The proposed method consists of mainly four stages: (a) the first phase involves segmenting the masses using edge information’s. (b) The second phase is to calculate and fuse the most relevant morphological features. (c) The last phase is the classification step which allows us to classify the images into benign and malignant masses. In this step we have implemented Support Vectors Machines (SVM) and Artificial Neural Networks (ANN), which were evaluated with the following performance criteria: confusion matrix, accuracy, sensitivity, specificity, receiver operating characteristic ROC, and error histogram. The effectiveness of this new approach was evaluated by a recently developed database: INBREAST database. The fusion of the most appropriate morphological features provided very good results. The SVM gives accuracy to within 64.3%. Whereas the ANN classifier gives better results with an accuracy of 97.5%.

Keywords: breast cancer, mammography, CAD system, features, fusion

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Authors: Ezio Bassi, Francesco Vercesi, Francesco Benzi

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The aim of this study is to evaluate the potentiality of synchronous reluctance motors for lift systems by also evaluating the vibroacoustic behaviour of the motor. Two types of synchronous machines are designed, analysed, and compared with an equivalent induction motor, which is the more common solution in such gearbox applications. The machines' performance are further improved with optimization procedures based on multiobjective optimization genetic algorithm (MOGA). The difference between the two synchronous motors consists in the rotor geometry; a symmetric and an asymmetric rotor design were investigated. The evaluation of the vibroacoustic performance has been conducted with a multi-variable model and finite element software taking into account electromagnetic, mechanical, and thermal features of the motor, therefore carrying out a multi-physics analysis of the electrical machine.

Keywords: synchronous reluctance motor, vibro-acoustic, lift systems, genetic algorithm

Procedia PDF Downloads 140

Authors: Xiaogang Li, Jieqiong Miao

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As for the problem of the grey forecasting model prediction accuracy is low, an improved grey prediction model is put forward. Firstly, use trigonometric function transform the original data sequence in order to improve the smoothness of data , this model called SGM( smoothness of grey prediction model), then combine the improved grey model with support vector machine , and put forward the grey support vector machine model (SGM - SVM).Before the establishment of the model, we use trigonometric functions and accumulation generation operation preprocessing data in order to enhance the smoothness of the data and weaken the randomness of the data, then use support vector machine (SVM) to establish a prediction model for pre-processed data and select model parameters using genetic algorithms to obtain the optimum value of the global search. Finally, restore data through the "regressive generate" operation to get forecasting data. In order to prove that the SGM-SVM model is superior to other models, we select the battery life data from calce. The presented model is used to predict life of battery and the predicted result was compared with that of grey model and support vector machines．For a more intuitive comparison of the three models, this paper presents root mean square error of this three different models .The results show that the effect of grey support vector machine (SGM-SVM) to predict life is optimal, and the root mean square error is only 3.18%. Keywords: grey forecasting model, trigonometric function, support vector machine, genetic algorithms, root mean square error

Keywords: Grey prediction model, trigonometric functions, support vector machines, genetic algorithms, root mean square error

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Authors: Z. Q. Zhang, Y. Zhang, D. L. Li

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To overcome the some shortcomings associated with traditional flotation machines and columns in collophanite flotation, a flotation device was designed and fabricated in the laboratory. A multi-impeller pump with same function as a mechanical cell was used instead of the injection sparger and circulation pump in column flotation unit. The influence of main operational parameters of the device like feed flow rate, air flow rate and impellers’ speed on collophanite flotation was analyzed. Experiment results indicate that the influence of the operational parameters were significant on flotation recovery and grade of phosphate concentrate. The best operating conditions of the device were: feed flow rate 0.62 L/min, air flow rate 6.67 L/min and impellers speed 900 rpm. At these conditions, a phosphate concentrate assaying about 30.5% P₂O₅ and 1% MgO with a P₂O₅ recovery of about 81% was obtained from a Yuan'an phosphate ore sample containing about 22.30% P₂O₅ and 3.2% MgO.

Keywords: collophanite flotation, flotation columns, flotation machines, multi-impeller pump

Procedia PDF Downloads 235

Authors: Ali Ulvi Uzer

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Data reduction is an important topic in the field of pattern recognition applications. The basic concept is the reduction of multitudinous amounts of data down to the meaningful parts. The Principal Component Analysis (PCA) method is frequently used for data reduction. The Support Vector Machine (SVM) method is a discriminative classifier formally defined by a separating hyperplane. In other words, given labeled training data, the algorithm outputs an optimal hyperplane which categorizes new examples. This study offers a hybrid approach that uses the PCA for data reduction and Support Vector Machines (SVM) for classification. In order to detect the accuracy of the suggested system, two boreholes taken from the soil sample was used. The classification accuracies for this dataset were obtained through using ten-fold cross-validation method. As the results suggest, this system, which is performed through size reduction, is a feasible system for faster recognition of dataset so our study result appears to be very promising.

Keywords: feature selection, sequential forward selection, support vector machines, soil sample

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Authors: Renu Gautam, S. M. S. Chauhan

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The magnetic Fe3O4 nanoparticles has been used as an efficient and facile acid catalyst for the synthesis of calix[4]pyrrole in moderate to excellent yields by the one pot condensation of different ketones and pyrrole. The catalyst was easily recovered using external magnet and reused over several cycles without losing its catalytic activity.

Keywords: calix[4]pyrrole, magnetic, Fe3O4 nanoparticles, catalysis

Procedia PDF Downloads 404

Authors: Akella Amarendra Babu, Rama Devi Yellasiri, Natukula Sainath

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Where human beings can easily learn and adopt pronunciation variations, machines need training before put into use. Also humans keep minimum vocabulary and their pronunciation variations are stored in front-end of their memory for ready reference, while machines keep the entire pronunciation dictionary for ready reference. Supervised methods are used for preparation of pronunciation dictionaries which take large amounts of manual effort, cost, time and are not suitable for real time use. This paper presents an unsupervised adaptation model for building agile and dynamic pronunciation dictionaries online. These methods mimic human approach in learning the new pronunciations in real time. A new algorithm for measuring sound distances called Dynamic Phone Warping is presented and tested. Performance of the system is measured using an adaptation model and the precision metrics is found to be better than 86 percent.

Keywords: pronunciation variations, dynamic programming, machine learning, natural language processing

Procedia PDF Downloads 146

Authors: Elmo Thiago Lins Cöuras Ford, Valentina Alessandra Carvalho do Vale

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With the evolution of the productive processes, demonstrated mainly by the presence every time larger of the irrigation and to crescent it disputes for water, accompanied by your shortage (distances every time larger), there is need to project facilities that can provide supply of water with larger speed and efficiency. Being like this, the presence of hydraulic pumps in an irrigation project or water supply for small communities, is of highest importance, and the knowledge of the fundamental parts to your good operation it deserves the due attention and care. Hydraulic pumps are machines of flow, whose function is to supply energy for the water, in order to press down her, through the conversion of mechanical energy of your originating from rotor a motor the combustion or of an electric motor. This way, the hydraulic pumps are had as generating hydraulic machines. The objective of this work was to project and to build a radial centrifugal pump for agricultural application in small communities.

Keywords: centrifuge pump, hydraulic energy, agricultural applications, irrigation

Procedia PDF Downloads 347

Authors: J. BalaRaju, M. Govinda Raj, C. S. N. Murthy

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Every organization in the competitive world tends to improve its economy by increasing their production and productivity rates. Unequivocally, the production in Indian underground mines over the years is not satisfactory, due to a variety of reasons. There are manifold of avenues for the betterment of production, and one such approach is through enhanced utilization of mechanized equipment such as Load Haul Dumper (LHD). This is used as loading and hauling purpose in underground mines. In view of the aforementioned facts, this paper delves into identification of the key influencing factors such as LHDs maintenance effectiveness, vehicle condition, operator skill and utilization of the machines on performance of LHDs. An attempt has been made for improvement of performance of the equipment through evaluation of Overall Equipment Effectiveness (OEE). Two different approaches for evaluation of OEE have been adopted and compared under various operating conditions. The use of OEE calculation in terms of percentage availability, performance and quality and the hitherto existing situation of the underground mine production is evaluated. Necessary recommendations are suggested to mining industry on the basis of OEE.

Keywords: utilization, maintenance, availability, performance and quality

Procedia PDF Downloads 192

Authors: Fabio L. Vieira, Micaelle F. C. Lemos, Luciano C. Lemos, Rafaela S. Oliveira, Ian A. Cunha

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Brazil has some challenges ahead related to population oral health, most of them associated with the need of expanding into the local level its promotion and prevention activities, offer equal access to services and promote changes in the lifestyle of the population. The program implemented an oral health initiative in public schools in the city of Salvador, Bahia. The mission was to improve oral health among students on primary and secondary education, from 2 to 15 years old, using the school as a pathway to increase access to healthcare. The main actions consisted of a team's visit to the schools with educational sessions for dental cavity prevention and individual assessment. The program incorporated a clinical surveillance component through a dental evaluation of every student searching for dental disease and caries, standardization of the dentists’ team to reach uniform classification on the assessments, and the use of an online platform to register data directly from the schools. Sequentially, the students with caries were referred for free clinical treatment on the program’s Health Centre. The primary purpose of this study was to analyze the effects and outcomes of this school-based oral health program. The study sample was composed by data of a period of 3 years - 2015 to 2017 - from 13 public schools on the suburb of the city of Salvador with a total number of assessments of 9,278 on this period. From the data collected the prevalence of children with decay on permanent teeth was chosen as the most reliable indicator. The prevalence was calculated for each one of the 13 schools using the number of children with 1 or more dental caries on permanent teeth divided by the total number of students assessed for school each year. Then the percentage change per year was calculated for each school. Some schools presented a higher variation on the total number of assessments in one of the three years, so for these, the percentage change calculation was done using the two years with less variation. The results show that 10 of the 13 schools presented significative improvements for the indicator of caries in permanent teeth. The mean for the number of students with caries percentage reduction on the 13 schools was 26.8%, and the median was 32.2% caries in permanent teeth institution. The highest percentage of improvement reached a decrease of 65.6% on the indicator. Three schools presented a rise in caries prevalence (8.9, 18.9 and 37.2% increase) that, on an initial analysis, seems to be explained with the students’ cohort rotation among other schools, as well as absenteeism on the treatment. In conclusion, the program shows a relevant impact on the reduction of caries in permanent teeth among students and the need for the continuity and expansion of this integrated healthcare approach. It has also been evident the significative of the articulation between health and educational systems representing a fundamental approach to improve healthcare access for children especially in scenarios such as presented in Brazil.

Keywords: primary care, public health, oral health, school-based oral health, data management

Procedia PDF Downloads 108

Authors: Shamsulhaq Amin

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Unbound granular materials (UGMs) are pivotal in ensuring long-term quality, especially in the layers under the surface of flexible pavements and other constructions. This study seeks to better understand the behavior of the UGMs by looking at popular models for predicting lasting deformation under various levels of stresses and load cycles. These models focus on variables such as the number of load cycles, stress levels, and features specific to materials and were evaluated on the basis of their ability to accurately predict outcomes. The study showed that these factors play a crucial role in how well the models work. Therefore, the research highlights the need to look at a wide range of stress situations to more accurately predict how much the UGMs bend or shift. The research looked at important factors, like how permanent deformation relates to the number of times a load is applied, how quickly this phenomenon happens, and the shakedown effect, in two different types of UGMs: granite and limestone. A detailed study was done over 100,000 load cycles, which provided deep insights into how these materials behave. In this study, a number of factors, such as the level of stress applied, the number of load cycles, the density of the material, and the moisture present were seen as the main factors affecting permanent deformation. It is vital to fully understand these elements for better designing pavements that last long and handle wear and tear. A series of laboratory tests were performed to evaluate the mechanical properties of materials and acquire model parameters. The testing included gradation tests, CBR tests, and Repeated load triaxial tests. The repeated load triaxial tests were crucial for studying the significant components that affect deformation. This test involved applying various stress levels to estimate model parameters. In addition, certain model parameters were established by regression analysis, and optimization was conducted to improve outcomes. Afterward, the material parameters that were acquired were used to construct graphs for each model. The graphs were subsequently compared to the outcomes obtained from the repeated load triaxial testing. Additionally, the models were evaluated to determine if they demonstrated the two inherent deformation behaviors of materials when subjected to repetitive load: the initial phase, post-compaction, and the second phase volumetric changes. In this study, using log-log graphs was key to making the complex data easier to understand. This method made the analysis clearer and helped make the findings easier to interpret, adding both precision and depth to the research. This research provides important insight into picking the right models for predicting how these materials will act under expected stress and load conditions. Moreover, it offers crucial information regarding the effect of load cycle and permanent deformation as well as the shakedown effect on granite and limestone UGMs.

Keywords: permanent deformation, unbound granular materials, load cycles, stress level

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Authors: Galu Papy Yuma

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This paper presents a new dynamic simulation of a power system consisting of four machines equipped with the Generalized Unified Power Flow Controller (GUPFC) to improve power system stability. The dynamic simulation of the GUPFC consists of one shunt converter and two series converters based on voltage source converter, and DC link capacitor installed in the power system. MATLAB/Simulink is used to arrange the dynamic simulation of the GUPFC, where the power system is simulated in order to investigate the impact of the controller on power system oscillation damping and to show the simulation program reliability. The Improved Chaotic- Harmony Search (IC-HS) Algorithm is used to provide the parameter controller in order to lead-lag compensation design. The results obtained by simulation show that the power system with four machines is suitable for stability analysis. The use of GUPFC and IC-HS Algorithm provides the excellent capability in fast damping of power system oscillations and improve greatly the dynamic stability of the power system.

Keywords: GUPFC, IC-HS algorithm, Matlab/Simulink, damping oscillation

Procedia PDF Downloads 422

Authors: Sneha Leslie

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The current situation in the cyber world is that crimes performed by Botnets are increasing and the masterminds (botmaster) are not detectable easily. The botmaster in the botnet compromises the legitimate host machines in the network and make them bots or zombies to initiate the cyber-attacks. This paper will focus on the live detection of the botmaster in the network by using the strong framework 'metasploit', when distributed denial of service (DDOS) attack is performed by the botnet. The affected victim machine will be continuously monitoring its incoming packets. Once the victim machine gets to know about the excessive count of packets from any IP, that particular IP is noted and details of the noted systems are gathered. Using the vulnerabilities present in the zombie machines (already compromised by botmaster), the victim machine will compromise them. By gaining access to the compromised systems, applications are run remotely. By analyzing the incoming packets of the zombies, the victim comes to know the address of the botmaster. This is an effective and a simple system where no specific features of communication protocol are considered.

Keywords: bonet, DDoS attack, network security, detection system, metasploit framework

Procedia PDF Downloads 224

Authors: Payman Davoodi-Nasab, Ahmad Rahbar-Kelishami, Jaber Safdari, Hossein Abolghasemi

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The high purity rare earth elements (REEs) have been vastly used in the field of chemical engineering, metallurgy, nuclear energy, optical, magnetic, luminescence and laser materials, superconductors, ceramics, alloys, catalysts, and etc. Neodymium is one of the most abundant rare earths. By development of a neodymium–iron–boron (Nd–Fe–B) permanent magnet, the importance of neodymium has dramatically increased. Solvent extraction processes have many operational limitations such as large inventory of extractants, loss of solvent due to the organic solubility in aqueous solutions, volatilization of diluents, etc. One of the promising methods of liquid membrane processes is emulsion liquid membrane (ELM) which offers an alternative method to the solvent extraction processes. In this work, a study on Nd extraction through multi-walled carbon nanotubes (MWCNTs) assisted ELM using response surface methodology (RSM) has been performed. The ELM composed of diisooctylphosphinic acid (CYANEX 272) as carrier, MWCNTs as nanoparticles, Span-85 (sorbitan triooleate) as surfactant, kerosene as organic diluent and nitric acid as internal phase. The effects of important operating variables namely, surfactant concentration, MWCNTs concentration, and treatment ratio were investigated. Results were optimized using a central composite design (CCD) and a regression model for extraction percentage was developed. The 3D response surfaces of Nd(III) extraction efficiency were achieved and significance of three important variables and their interactions on the Nd extraction efficiency were found out. Results indicated that introducing the MWCNTs to the ELM process led to increasing the Nd extraction due to higher stability of membrane and mass transfer enhancement. MWCNTs concentration of 407 ppm, Span-85 concentration of 2.1 (%v/v) and treatment ratio of 10 were achieved as the optimum conditions. At the optimum condition, the extraction of Nd(III) reached the maximum of 99.03%.

Keywords: emulsion liquid membrane, extraction of neodymium, multi-walled carbon nanotubes, response surface method

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Authors: Aniruddha Joshi

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This paper discusses a simulation study of automated sand casting production system. Therefore, the first aims of this study is development of automated sand casting process model and analyze this model with a simulation software Witness. Production methodology aims to improve overall productivity through elimination of wastes and that leads to improve quality. Integration of automation with Simulation is beneficial to identify the obstacles in implementation and to take appropriate options to implement successfully. For this integration, there are different Simulation Software’s. To study this integration, with the help of “WITNESS” Simulation Software the model is created. This model is based on literature review. The input parameters are Setup Time, Number of machines, cycle time and output parameter is number of castings, avg, and time and percentage usage of machines. Obtained results are used for Statistical Analysis. This analysis concludes the optimal solution to get maximum output.

Keywords: automated sand casting production system, simulation, WITNESS software, performance evaluation

Procedia PDF Downloads 765

Authors: Carla Pérez-Chirinos Buxadé, Bruno Fernández-Valdés, Mónica Morral-Yepes, Sílvia Tuyà Viñas, Josep Maria Padullés Riu, Gerard Moras Feliu

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There is a long way to explore all the possible applications inertial measurement units (IMUs) have in the sports field. The aim of this study was to evaluate the validity of a new application on the use of these wearable sensors, specifically it was to evaluate a magnet-based timing system (M-BTS) for timing gate-to-gate in an alpine ski slalom using the magnetometer embedded in an IMU. This was a validation study. The criterion validity of time measured by the M-BTS was assessed using the 95% error range against actual time obtained from photocells. The experiment was carried out with first-and second-year junior skiers performing a ski slalom on a ski training slope. Eight alpine skiers (17.4 ± 0.8 years, 176.4 ± 4.9 cm, 67.7 ± 2.0 kg, 128.8 ± 26.6 slalom FIS-Points) participated in the study. An IMU device was attached to the skier’s lower back. Skiers performed a 40-gate slalom from which four gates were assessed. The M-BTS consisted of placing four bar magnets buried into the snow surface on the inner side of each gate’s turning pole; the magnetometer built into the IMU detected the peak-shaped magnetic field when passing near the magnets at a certain speed. Four magnetic peaks were detected. The time compressed between peaks was calculated. Three inter-gate times were obtained for each system: photocells and M-BTS. The total time was defined as the time sum of the inter-gate times. The 95% error interval for the total time was 0.050 s for the ski slalom. The M-BTS is valid for timing gate-to-gate in an alpine ski slalom. Inter-gate times can provide additional data for analyzing a skier’s performance, such as asymmetries between left and right foot.

Keywords: gate crossing time, inertial measurement unit, timing system, wearable sensor

Procedia PDF Downloads 157

Authors: Márcia Afonso, Marisa Dinis-Almeida, Cristina Fael

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Climate change, namely precipitation patterns alteration, has led to extreme conditions such as floods and droughts. In turn, excessive construction has led to the waterproofing of the soil, increasing the surface runoff and decreasing the groundwater recharge capacity. The permeable pavements used in areas with low traffic lead to a decrease in the probability of floods peaks occurrence and the sediments reduction and pollutants transport, ensuring rainwater quality improvement. This study aims to evaluate the porous asphalt performance, developed in the laboratory, with addition of cellulosic fibres. One of the main objectives of cellulosic fibres use is to stop binder drainage, preventing its loss during storage and transport. Comparing to the conventional porous asphalt the cellulosic fibres addition improved the porous asphalt performance. The cellulosic fibres allowed the bitumen content increase, enabling retention and better aggregates coating and, consequently, a greater mixture durability. With this solution, it is intended to develop better practices of resilience and adaptation to the extreme climate changes and respond to the sustainability current demands, through the eco-friendly materials use. The mix design was performed for different size aggregates (with fine aggregates – PA1 and with coarse aggregates – PA2). The percentage influence of the fibres to be used was studied. It was observed that overall, the binder drainage decreases as the cellulose fibres percentage increases. It was found that the PA2 mixture obtained most binder drainage relative to PA1 mixture, irrespective of the fibres percentage used. Subsequently, the performance was evaluated through laboratory tests of indirect tensile stiffness modulus, water sensitivity, permeability and permanent deformation. The stiffness modulus for the two mixtures groups (with and without cellulosic fibres) presented very similar values between them. For the water sensitivity test it was observed that porous asphalt containing more fine aggregates are more susceptible to the water presence than mixtures with coarse aggregates. The porous asphalt with coarse aggregates have more air voids which allow water to pass easily leading to ITSR higher values. In the permeability test was observed that asphalt porous without cellulosic fibres presented had lower permeability than asphalt porous with cellulosic fibres. The resistance to permanent deformation results indicates better behaviour of porous asphalt with cellulosic fibres, verifying a bigger rut depth in porous asphalt without cellulosic fibres. In this study, it was observed that porous asphalt with bitumen higher percentages improve the performance to permanent deformation. This fact was only possible due to the bitumen retention by the cellulosic fibres.

Keywords: binder drainage, cellulosic fibres, permanent deformation, porous asphalt

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Authors: Fahad Y. Al-dawish

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The current trend by a large number of organizations and individuals to use cloud computing. Many consider it a significant shift in the field of computing. Cloud computing are distributed and parallel systems consisting of a collection of interconnected physical and virtual machines. With increasing request and profit of cloud computing infrastructure, diverse computing processes can be executed on cloud environment. Many organizations and individuals around the world depend on the cloud computing environments infrastructure to carry their applications, platform, and infrastructure. One of the major and essential issues in this environment related to allocating incoming tasks to suitable virtual machine (cloud task scheduling). Cloud task scheduling is classified as optimization problem, and there are several meta-heuristic algorithms have been anticipated to solve and optimize this problem. Good task scheduler should execute its scheduling technique on altering environment and the types of incoming task set. In this research project a cloud task scheduling methodology based on ant colony optimization ACO algorithm, we call it ACO-TS Ant Colony Optimization for Task Scheduling has been proposed and compared with different scheduling algorithms (Random, First Come First Serve FCFS, and Fastest Processor to the Largest Task First FPLTF). Ant Colony Optimization (ACO) is random optimization search method that will be used for assigning incoming tasks to available virtual machines VMs. The main role of proposed algorithm is to minimizing the makespan of certain tasks set and maximizing resource utilization by balance the load among virtual machines. The proposed scheduling algorithm was evaluated by using Cloudsim toolkit framework. Finally after analyzing and evaluating the performance of experimental results we find that the proposed algorithm ACO-TS perform better than Random, FCFS, and FPLTF algorithms in each of the makespaan and resource utilization.

Keywords: cloud Task scheduling, ant colony optimization (ACO), cloudsim, cloud computing

Procedia PDF Downloads 393

Authors: Chin Pang Lei

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Colonized by the UK, handed over to China, and now as a global financial city, Hong Kong’s history is never easy to write under the dominant discourses of colonialism, nationalism and globalization. In this plight, cinema, regarded as Hong Kong’s most representative cultural form, is used for writing, exploring and questioning the local history of the city. In their writing of the past, Hong Kong directors such as Wong Kar-wai, Stanley Kwan and Tsui Hark have demonstrated alternative ways of historicizing Hong Kong. Despite their interests in different periods of time (Wong is obsessed with the 1960s; Kwan is attracted to the 1930s; Tsui often goes back to the early 20th century), all these directors use genres as their time machines to revisit the past. As a popular cultural form, genres always come with a series of ideologies which define our lives and explain the society. Hence, in a changing society, genres change and complicate themselves with different packages of meanings. Genres function as open-ended and corrigible schemata which can contain multiple themes and various meanings. In Hong Kong, genres, often seen as highly commercial and overly market-oriented, are opportunities for alternative history writing and the exploration of local identities. This paper examines how these Hong Kong directors use the popular forms of genres, such as melodrama, martial art and gangster films, to present the past, and how the stories of the fictional characters, such as prostitutes, martial artists and jobless hooligans mobilize imagination of history. These texts show that genre is a crucial platform for Hong Kong’s post-colonial self-writing. Via genres, history in these films is against official and canonical history as well as grand narrative. Genres as time machines articulate a voice for Hong Kong.

Keywords: Hong Kong cinema, genre, historicizing, local history, Wong Kar-Wai

Procedia PDF Downloads 336

Authors: Bin Liu

Abstract:

As one of the most important tasks in protein sequence analysis, protein remote homology detection has been studied for decades. Currently, the profile-based methods show state-of-the-art performance. Position-Specific Frequency Matrix (PSFM) is widely used profile. However, there exists noise information in the profiles introduced by the amino acids with low frequencies. In this study, we propose a method to remove the noise information in the PSFM by removing the amino acids with low frequencies called Top frequency profile (TFP). Three new matrix transformation methods, including Autocross covariance (ACC) transformation, Tri-gram, and K-separated bigram (KSB), are performed on these profiles to convert them into fixed length feature vectors. Combined with Support Vector Machines (SVMs), the predictors are constructed. Evaluated on two benchmark datasets, and experimental results show that these proposed methods outperform other state-of-the-art predictors.

Keywords: protein remote homology detection, protein fold recognition, top frequency profile, support vector machines

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Authors: J. F. Gonzalez-Rojo, Federico Lluesma-Rodriguez, Temoatzin Gonzalez

Abstract:

Hyperloop, a new mode of transport, is gaining significance. It consists of the use of a ground-based transport system which includes a levitation system, that avoids rolling friction forces, and which has been covered with a tube, controlling the inner atmosphere lowering the aerodynamic drag forces. Thus, hyperloop is proposed as a solution to the current limitation on ground transportation. Rolling and aerodynamic problems, that limit large speeds for traditional high-speed rail or even maglev systems, are overcome using a hyperloop solution. Zeleros is one of the companies developing technology for hyperloop application worldwide. It is working on a concept that reduces the infrastructure cost and minimizes the power consumption as well as the losses associated with magnetic drag forces. For this purpose, Zeleros proposes a Hybrid ElectroMagnetic Suspension (EMS) for its prototype. In the present manuscript an active and optimal electromagnetic suspension levitation method based on nearly zero power consumption individual modules is presented. This system consists of several hybrid permanent magnet-coil levitation units that can be arranged along the vehicle. The proposed unit manages to redirect the magnetic field along a defined direction forming a magnetic circuit and minimizing the loses due to field dispersion. This is achieved using an electrical steel core. Each module can stabilize the gap distance using the coil current and either linear or non-linear control methods. The ratio between weight and levitation force for each unit is 1/10. In addition, the quotient between the lifted weight and power consumption at the target gap distance is 1/3 [kg/W]. One degree of freedom (DoF) (along the gap direction) is controlled by a single unit. However, when several units are present, a 5 DoF control (2 translational and 3 rotational) can be achieved, leading to the full attitude control of the vehicle. The proposed system has been successfully tested reaching TRL-4 in a laboratory test bench and is currently in TRL-5 state development if the module association in order to control 5 DoF is considered.

Keywords: active optimal control, electromagnetic levitation, HEMS, high-speed transport, hyperloop

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Authors: Cytha Nilam Chairani, Ditha Noviantika, Hidayati Amir, Nurul Khairiyah, Siti Rahmadita, Fadila Khairani

Abstract:

Background: Dental caries is one of the most common diseases with high prevalence in children. The first permanent molar (FPM) has an essential role in establishing the occlusion. Nevertheless, FPM is very prone to caries because of various factors, such as their anatomical structure and early emergence in oral cavity. It is due to the little knowledge from parents and children regarding the timing of emergence of FPM in oral cavity which is still considered as primary teeth. Furthermore, the lack of knowledge from parents and children may affect their oral hygiene practice resulting to carious process. Objective: The aim of this study was to assess the status of FPM caries and its association with children’s oral hygiene practice in 9-12-year-old school children in Lubuk Kilangan Community Health Centre, Padang City. Methods: A cross-sectional study was performed in 50 school children (9-12 years old) using random sampling technique from two randomly selected schools in Lubuk Kilangan Community Health Centre, Padang City. A questionnaire was developed from other studies consisting of four closed ended questions regarding oral health practice. The data obtained were analyzed statistically using Mann-Whitney Test to assess the status of FPM caries and its association with children’s oral hygiene practice. Results: The results showed that 32% of children had FPMs sound and the remaining 68% had FPMs carious which were grouped into 1-2 FPMs carious (60%) and 3-4 FPMs carious (8%). The caries status of mandibular FPM (64%) was higher compared to maxillary FPM (10%). Conclusion: There was significant association in subject who did not visit dentist in the last 6 months which had more carious FPMs compared to subject who visited dentist (p < 0.05). There was no significant association between the status of FPM caries and knowledge of the timing eruption of FPM, oral hygiene instruction from parents and tooth brushing (p > 0.05).

Keywords: dental caries, children, first permanent molar, oral hygiene practice

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Authors: S. K. Kakraliya, R. D. Jat, H. S. Jat, P. C. Sharma, M. L. Jat

Abstract:

The traditional rice-wheat (RW) system in the IGP of South Asia is tillage, water, energy, and capital intensive. Coupled with more pumping of groundwater over the years to meet the high irrigation water requirement of the RW system has resulted in over-exploitation of groundwater. Replacement of traditional rice with less water crops such as maize under climate-smart agriculture (CSA) based management (tillage, crop establishment and residue management) practices are required to promote sustainable intensification. Furthermore, inefficient nutrient management practices are responsible for low crop yields and nutrient use efficiencies in maize-wheat (MW) system. A 7-year field experiment was conducted in farmer’s participatory strategic research mode at Taraori, Karnal, India to evaluate the effects of tillage and crop establishment (TCE) methods, residue management, mungbean integration, and nutrient management practices on crop yields, water productivity and profitability of MW system. The main plot treatments included four combinations of TCE, residue and mungbean integration [conventional tillage (CT), conventional tillage with mungbean (CT + MB), permanent bed (PB) and permanent bed with MB (PB + MB] with three nutrient management practices [farmer’s fertilizer practice (FFP), recommended dose of fertilizer (RDF) and site-specific nutrient management (SSNM)] using Nutrient Expert® as subplot treatments. System productivity, water use efficiency (WUE) and net returns under PB + MB were significantly increased by 25–30%, 28–31% and 35–40% compared to CT respectively, during seven years of experimentation. The integration of MB in MW system contributed ~25and ~ 28% increases in system productivity and net returns compared with no MB, respectively. SSNM based nutrient management increased the mean (averaged across 7 yrs) system productivity by 12- 15% compared with FFP. The study revealed that CSA based sustainable intensification (PB + MB) and SSNM approach provided opportunities for enhancing crop productivity, WUE and profitability of the MW system in India.

Keywords: Conservation Agriculture, Precision water and nutrient management, Permanent beds, Crop yields

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Authors: Hyunchul Ahn, William X. S. Wong

Abstract:

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

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Authors: Jamerson Felipe Pereira Lima, Jeane Cecília Bezerra de Melo

Abstract:

The difficulty and cost related to obtaining of protein tertiary structure information through experimental methods, such as X-ray crystallography or NMR spectroscopy, helped raising the development of computational methods to do so. An approach used in these last is prediction of tridimensional structure based in the residue chain, however, this has been proved an NP-hard problem, due to the complexity of this process, explained by the Levinthal paradox. An alternative solution is the prediction of intermediary structures, such as the secondary structure of the protein. Artificial Intelligence methods, such as Bayesian statistics, artificial neural networks (ANN), support vector machines (SVM), among others, were used to predict protein secondary structure. Due to its good results, artificial neural networks have been used as a standard method to predict protein secondary structure. Recent published methods that use this technique, in general, achieved a Q3 accuracy between 75% and 83%, whereas the theoretical accuracy limit for protein prediction is 88%. Alternatively, to achieve better results, support vector machines prediction methods have been developed. The statistical evaluation of methods that use different AI techniques, such as ANNs and SVMs, for example, is not a trivial problem, since different training sets, validation techniques, as well as other variables can influence the behavior of a prediction method. In this study, we propose a prediction method based on artificial neural networks, which is then compared with a selected SVM method. The chosen SVM protein secondary structure prediction method is the one proposed by Huang in his work Extracting Physico chemical Features to Predict Protein Secondary Structure (2013). The developed ANN method has the same training and testing process that was used by Huang to validate his method, which comprises the use of the CB513 protein data set and three-fold cross-validation, so that the comparative analysis of the results can be made comparing directly the statistical results of each method.

Keywords: artificial neural networks, protein secondary structure, protein structure prediction, support vector machines

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