Search results for: academic speed and accuracy

Authors: Bassim Shaheen Bachy, Jörg Franke

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In this study, a three dimensional numerical heat transfer model has been used to simulate the laser structuring of polymer substrate material in the Three-Dimensional Molded Interconnect Device (3D MID) which is used in the advanced multi-functional applications. A finite element method (FEM) transient thermal analysis is performed using APDL (ANSYS Parametric Design Language) provided by ANSYS. In this model, the effect of surface heat source was modeled with Gaussian distribution, also the effect of the mixed boundary conditions which consist of convection and radiation heat transfers have been considered in this analysis. The model provides a full description of the temperature distribution, as well as calculates the depth and the width of the groove upon material removal at different set of laser parameters such as laser power and laser speed. This study also includes the experimental procedure to study the effect of laser parameters on the depth and width of the removal groove metal as verification to the modeled results. Good agreement between the experimental and the model results is achieved for a wide range of laser powers. It is found that the quality of the laser structure process is affected by the laser scan speed and laser power. For a high laser structured quality, it is suggested to use laser with high speed and moderate to high laser power.

Keywords: laser structuring, simulation, finite element analysis, thermal modeling

Procedia PDF Downloads 353

Authors: Dhiraj Dolai, Rupayan Bhattacharya

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In this study, a comparison of Range Of Motion (ROM) of middle and long-distance runners and swimmers has been made. The mobility of the various joints is essential for the quick movement of any sportsman. Knowledge of a ROM helps in preventing injuries, in repeating the movement, and in generating speed and power. ROM varies among individuals, and it is influenced by factors such as gender, age, and whether the motion is performed actively or passively. ROM for running and swimming, both performed with due consideration on speed, plays an important role. The time of generation of speed and mobility of the particular joints are very important for both kinds of athletes. The difficulties that happen during running and swimming in the direction of motion is changed. In this study, data were collected for a total of 102 subjects divided into three groups: control group (22), middle and long-distance runners (40), and swimmers (40), and their ages are between 12 to 18 years. The swimmers have higher ROM in shoulder joint flexion, extension, abduction, and adduction movement. Middle and long-distance runners have significantly greater ROM from Control Group in the left shoulder joint flexion with a 5.82 mean difference. Swimmers have significantly higher ROM from the Control Group in the left shoulder joint flexion with 24.84 mean difference and swimmers have significantly higher ROM from the Middle and Long distance runners in left shoulder flexion with 19.02 mean difference. The picture will be clear after a more detailed investigation.

Keywords: range of motion, runners, swimmers, significance

Procedia PDF Downloads 132

Authors: Peng Li, Luan Wang, Haifeng Fei, Renhong Xie, Yibin Rui, Shanhong Guo

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The applications of satellite-based automatic identification system (S-AIS) pave the road for wide-range maritime traffic monitoring and management. But the coverage of satellite’s view includes multiple AIS self-organizing networks, which leads to the collision of AIS signals from different cells. The contribution of this work is to propose an improved multi-channel blind source separation algorithm based on Artificial Bee Colony (ABC) and advanced stochastic optimization to perform separation of the mixed AIS signals. The proposed approach adopts modified ABC algorithm to get an optimized initial separating matrix, which can expedite the initialization bias correction, and utilizes the Adaptive Moment Estimation (Adam) to update the separating matrix by adjusting the learning rate for each parameter dynamically. Simulation results show that the algorithm can speed up convergence and lead to better performance in separation accuracy.

Keywords: satellite-based automatic identification system, blind source separation, artificial bee colony, adaptive moment estimation

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Authors: Fatemeh Sadat Sharifi

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In the present study, the capabilities of WAVEWATCH-III and MIKE21-SW for predicting the characteristics of wind waves in Hormuz Strait are evaluated. The GFS wind data (Global Forecast System) were derived. The bathymetry of gride with 2 arc-minute resolution, also were extracted from the ETOPO1. WAVEWATCH-III findings illustrate more valid prediction of wave features comparing to the MIKE-21 SW in deep water. Apparently, in shallow area, the MIKE-21 provides more uniformities with altimetry measurements. This may be due to the merits of the unstructured grid which are used in MIKE-21, leading to better representations of the coastal area. The findings on the direction of waves generated by wind in the modeling area indicate that in some regions, despite the increase in wind speed, significant wave height stays nearly unchanged. This is fundamental because of swift changes in wind track over the Strait of Hormuz. After discussing wind-induced waves in the region, the impact of instability of the surface layer on wave growth has been considered. For this purpose, the average monthly mean air temperature has been used. The results in cold months, when the surface layer is unstable, indicates an acceptable increase in the accuracy of prediction of the indicator wave height.

Keywords: numerical modeling, WAVEWATCH-III, Strait of Hormuz, MIKE21-SW

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Authors: Ricardo Merlo

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The use of simulation as a digital didactic tool allowed students to reproduce the laws of Physics in order to improve their academic performance. The didactic resource of simulation also favored the motivation of most of the young people, depending on the subject of Physics to be developed in the classroom and in that sense, it was significant to know the favorable or unfavorable attitude that the students presented about the use of simulation resources to maximize the anchorage of the contents planned for the different classes developed in the classroom. The different real-time simulation applications that were offered free of charge through the Internet were not presented as a specific resource that could be used in a didactic model, and in that framework, the teachers of Physics at the university level did not apply these resources in a systematic way with the knowledge of the favorable or unfavorable attitude of the students towards these didactic resources. For this reason, this work proposed the design and application of attitude questionnaires to enhance the use of those simulation resources that allowed for improving the quality of the class and the academic performance of the students.

Keywords: physics teaching, attitude, motivation, didactic resources

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Authors: Lokeswara Rao P., Naga Venkata Rakesh N., V. Anantha Subramanian

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It is important to estimate, predict, and avoid the dynamic instability of high speed planing crafts. It is known that design parameters like relative location of center of gravity with respect to the dynamic lift centre and length to beam ratio of the craft have influence on the tendency to porpoise. This paper analyzes the hydrodynamic performance on the basis of the semi-empirical Savitsky method and also estimates the same by numerical simulations based on Reynolds Averaged Navier Stokes (RANS) equations using a commercial code namely, STAR- CCM+. The paper examines through the same numerical simulation considering dynamic equilibrium, the changing running trim, which results in porpoising. Some interesting results emerge from the study and this leads to early detection of the instability.

Keywords: CFD, planing hull, porpoising, Savitsky method

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Authors: Abe Degale D., Cheng Jian

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When creating automated video surveillance systems, violent action recognition is crucial. In recent years, hand-crafted feature detectors have been the primary method for achieving violence detection, such as the recognition of fighting activity. Researchers have also looked into learning-based representational models. On benchmark datasets created especially for the detection of violent sequences in sports and movies, these methods produced good accuracy results. The Hockey dataset's videos with surveillance camera motion present challenges for these algorithms for learning discriminating features. Image recognition and human activity detection challenges have shown success with deep representation-based methods. For the purpose of detecting violent images and identifying aggressive human behaviours, this research suggested a deep representation-based model using the transfer learning idea. The results show that the suggested approach outperforms state-of-the-art accuracy levels by learning the most discriminating features, attaining 99.34% and 99.98% accuracy levels on the Hockey and Movies datasets, respectively.

Keywords: violence detection, faster RCNN, transfer learning and, surveillance video

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Authors: Joseph Mouallem, Seyed Reza Amini Niaki, Norman Chavez-Cussy, Christian Costa Milioli, Fernando Eduardo Milioli

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Sub-grid closures for filtered two-fluid models (fTFM) useful in large scale simulations (LSS) of riser flows can be derived from highly resolved simulations (HRS) with microscopic two-fluid modeling (mTFM). Accurate sub-grid closures require accurate mTFM formulations as well as accurate correlation of relevant filtered parameters to suitable independent variables. This article deals with both of those issues. The accuracy of mTFM is touched by assessing the impact of gas sub-grid turbulence over HRS filtered predictions. A gas turbulence alike effect is artificially inserted by means of a stochastic forcing procedure implemented in the physical space over the momentum conservation equation of the gas phase. The correlation issue is touched by introducing a three-filtered variable correlation analysis (three-marker analysis) performed under a variety of different macro-scale conditions typical or risers. While the more elaborated correlation procedure clearly improved accuracy, accounting for gas sub-grid turbulence had no significant impact over predictions.

Keywords: fluidization, gas-particle flow, two-fluid model, sub-grid models, filtered closures

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Authors: Teja Sai Puligadda

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Satellite images in detail can serve an important role in the geographic study. Quantitative and qualitative information provided by the satellite and remote sensing images minimizes the complexity of work and time. Data/images are captured at regular intervals by satellite remote sensing systems, and the amount of data collected is often enormous, and it expands rapidly as technology develops. Interpreting remote sensing images, geographic data mining, and researching distinct vegetation types such as agricultural and forests are all part of satellite image categorization. One of the biggest challenge data scientists faces while classifying satellite images is finding the best suitable classification algorithms based on the available that could able to classify images with utmost accuracy. In order to categorize satellite images, which is difficult due to the sheer volume of data, many academics are turning to deep learning machine algorithms. As, the CNN algorithm gives high accuracy in image recognition problems and automatically detects the important features without any human supervision and the ANN algorithm stores information on the entire network (Abhishek Gupta., 2020), these two deep learning algorithms have been used for satellite image classification. This project focuses on remote sensing through Deep Neural Networks i.e., ANN and CNN with Deep Sat (SAT-4) Airborne dataset for classifying images. Thus, in this project of classifying satellite images, the algorithms ANN and CNN are implemented, evaluated & compared and the performance is analyzed through evaluation metrics such as Accuracy and Loss. Additionally, the Neural Network algorithm which gives the lowest bias and lowest variance in solving multi-class satellite image classification is analyzed.

Keywords: artificial neural network, convolutional neural network, remote sensing, accuracy, loss

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Authors: Mohammad Hadi Khorashadi Zadeh, Amin Karkon, Hamid Golnari

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This study aimed to investigate the impact of information technology on the quality of accounting information was made in 2014. A survey of 425 executives of listed companies in Tehran Stock Exchange, using the Cochran formula simple random sampling method, 84 managers of these companies as the sample size was considered. Methods of data collection based on questionnaire information technology some of the questions of the impact of information technology was standardized questionnaires and the questions were designed according to existing components. After the distribution and collection of questionnaires, data analysis and hypothesis testing using structural equation modeling Smart PLS2 and software measurement model and the structure was conducted in two parts. In the first part of the questionnaire technical characteristics including reliability, validity, convergent and divergent validity for PLS has been checked and in the second part, application no significant coefficients were used to examine the research hypotheses. The results showed that IT and its dimensions (timeliness, relevance, accuracy, adequacy, and the actual transfer rate) affect the quality of accounting information of listed companies in Tehran Stock Exchange influence.

Keywords: information technology, information quality, accounting, transfer speed

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Authors: Hao Mi, Ming Yang, Tian-yue Yang

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Ultrasonic infrared nondestructive testing is a kind of testing method with high speed, accuracy and localization. However, there are still some problems, such as the detection requires manual real-time field judgment, the methods of result storage and viewing are still primitive. An intelligent non-destructive detection system based on embedded linux is put forward in this paper. The hardware part of the detection system is based on the ARM (Advanced Reduced Instruction Set Computer Machine) core and an embedded linux system is built to realize image processing and defect detection of thermal images. The CLAHE algorithm and the Butterworth filter are used to process the thermal image, and then the boa server and CGI (Common Gateway Interface) technology are used to transmit the test results to the display terminal through the network for real-time monitoring and remote monitoring. The system also liberates labor and eliminates the obstacle of manual judgment. According to the experiment result, the system provides a convenient and quick solution for industrial non-destructive testing.

Keywords: remote monitoring, non-destructive testing, embedded Linux system, image processing

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Authors: Seun Mayowa Sunday

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Loan prediction is one of the most significant and recognised fields of research in the banking, insurance, and the financial security industries. Some prediction systems on the market include the construction of static software. However, due to the fact that static software only operates with strictly regulated rules, they cannot aid customers beyond these limitations. Application of many machine learning (ML) techniques are required for loan prediction. Four separate machine learning models, random forest (RF), decision tree (DT), k-nearest neighbour (KNN), and logistic regression, are used to create the loan prediction model. Using the anaconda navigator and the required machine learning (ML) libraries, models are created and evaluated using the appropriate measuring metrics. From the finding, the random forest performs with the highest accuracy of 80.17% which was later implemented into the Django framework. For real-time testing, the web application is deployed on the Alibabacloud which is among the top 4 biggest cloud computing provider. Hence, to the best of our knowledge, this research will serve as the first academic paper which combines the model development and the Django framework, with the deployment into the Alibaba cloud computing application.

Keywords: k-nearest neighbor, random forest, logistic regression, decision tree, django, cloud computing, alibaba cloud

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Authors: Carrie Prendergast, Lisa Bortman

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The focus of this presentation will be on non-traditional (adult) students as they seek their Bachelors’ degrees online. This presentation will specifically examine nontraditional online student perceptions of Tinto’s success conditions: expectations, support, assessment, and engagement. Expectations include those of the student, the faculty and the institution. Support includes academic, social, and financial support. Feedback and assessment encompasses feedback in the classroom, upon entry, and on an institutional level. The fourth success condition is involvement or engagement of students with their peers and faculty in both academic and social contexts. This program will review and discuss a rich, detailed description of the lived experience of the nontraditional online student to add to the paucity of research on this understudied population and guide higher education professionals in supporting this growing population of students.

Keywords: adult students, online education, student success, vincent tinto

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Authors: Lívia B. Meirelles, Erika C. A. N. Chrisman, Flávia B. de Andrade, Lilian C. M. de Oliveira

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True Boiling Point distillation (TBP) is one of the most common experimental techniques for the determination of petroleum properties. This curve provides information about the performance of petroleum in terms of its cuts. The experiment is performed in a few days. Techniques are used to determine the properties faster with a software that calculates the distillation curve when a little information about crude oil is known. In order to evaluate the accuracy of distillation curve prediction, eight points of the TBP curve and specific gravity curve (348 K and 523 K) were inserted into the HYSYS Oil Manager, and the extended curve was evaluated up to 748 K. The methods were able to predict the curve with the accuracy of 0.6%-9.2% error (Software X ASTM), 0.2%-5.1% error (Software X Spaltrohr).

Keywords: distillation curve, petroleum distillation, simulation, true boiling point curve

Procedia PDF Downloads 445

Authors: Adar Pelah, Avraham Adelman, Amanda Balash, Jake Mitchell, Mattan J. Pelah, Viswadeep Sarangi, Xin Chen Cai, Zadok Storkey, Gregg B. Fields, Ximena Levy, Ali A. Danesh

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Introduction: Post-Acute Sequelae of Severe Acute Respiratory Syndrome Coronavirus 2 infection (PASC), or Long COVID, while primarily a respiratory disorder, can also include dizziness, lasting weeks to months in individuals who had previously tested positive for COVID-19. This study utilized gait analysis to assess the potential vestibular effects of PASC on the presentation of gait anomalies. Materials and Methods: The study included 11 participants who tested positive for COVID-19, a mean of 2.8 months prior to gait testing (PP=11), and 8 control participants who did not test positive for COVID-19 (NP=8). Participants walked 7.5m at three self-selected speeds: ‘slow,’ ‘normal,’ and ‘fast.’ Mean walking speeds were determined for each speed and overall range from four laps on an instrumented walkway using video capture. Results: A Z-test at 0.05 significance was used for speed range, ‘normal’ and ‘fast’ at the lower tail, and for ‘slow’ at the higher tail. Average speeds (m/s) were: ‘slow’ (PP=0.709, NP=0.678), ‘normal’ (PP=1.141, NP=1.170), ‘fast’ (PP=1.529, NP=1.821), average range (PP=0.846, NP=1.143). Significant speed decreases between PP and NP were observed in ‘fast’ (-17.43%) and average range (-29.86%), while changes in ‘slow’ (+2.44%) and ‘normal’ (-4.39%) speeds were not significant. Conclusions: Long COVID is a recognized disability (Americans with Disabilities Act), and although it presents variably, dizziness, vertigo, and tinnitus are not uncommon in COVID-19 infection. These results suggest that potential inner-ear damage may persist and manifest in gait changes even after recovery from acute illness. Further research with a larger sample size may indicate the need for providers to consider PASC when diagnosing patients with vestibular dysfunction.

Keywords: gait analysis, long-COVID, vestibular dysfunction, walking speed

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Authors: Sayor Ajfar Aaron, Sajjat Hossain Abir, Ashif Newaz, Mushfiqur Rahman

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Investigating the convergence of blockchain technology and artificial intelligence, this paper examines their synergistic effects on data integrity and decision-making within smart contracts. By implementing AI-driven analytics on blockchain-based platforms, the research identifies improvements in automated contract enforcement and decision accuracy. The paper presents a framework that leverages AI to enhance transparency and trust while blockchain ensures immutable record-keeping, culminating in significantly optimized operational efficiencies in various industries.

Keywords: artificial intelligence, blockchain, data integrity, smart contracts

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Authors: Lianzhong Zhang, Chao Huang

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Sea-land segmentation is a basic step in many tasks such as sea surface monitoring and ship detection. The existing sea-land segmentation algorithms have poor segmentation accuracy, and the parameter adjustments are cumbersome and difficult to meet actual needs. Also, the current sea-land segmentation adopts traditional deep learning models that use Convolutional Neural Networks (CNN). At present, the transformer architecture has achieved great success in the field of natural images, but its application in the field of radar images is less studied. Therefore, this paper proposes a sea-land segmentation method based on the transformer architecture to strengthen edge supervision. It uses a self-attention mechanism with a gating strategy to better learn relative position bias. Meanwhile, an additional edge supervision branch is introduced. The decoder stage allows the feature information of the two branches to interact, thereby improving the edge precision of the sea-land segmentation. Based on the Gaofen-3 satellite image dataset, the experimental results show that the method proposed in this paper can effectively improve the accuracy of sea-land segmentation, especially the accuracy of sea-land edges. The mean IoU (Intersection over Union), edge precision, overall precision, and F1 scores respectively reach 96.36%, 84.54%, 99.74%, and 98.05%, which are superior to those of the mainstream segmentation models and have high practical application values.

Keywords: SAR, sea-land segmentation, deep learning, transformer

Procedia PDF Downloads 189

Authors: Siti Noor Suzila Maqsood-Ul-Haque, Ummi Kalthum Ibrahim, Norekanadirah Abdul Rahman

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Banana are rich in vitamins, potassium and carbohydrate.The objective for this research work is to produce banana milk powder that can help children that suffers from constipation. Two types of the most common dryers used for this purpose are the spray and freeze dryer. The effects of the type of dryers, pump feed speed in the spray dryer and the ratio proportion of the banana milk powder were investigated in the study. The result indicate that increasing proportion ratio of the banana milk powder produce lower yield of the powder.From the result it is also concluded that speed 2 is more suitable in the production of the banana milk powder since the value of the moisture content is lower.

Keywords: freeze dryer, spray dryer, moisture content, dissolution, banana, milk

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Authors: Priyadarsini Samal, Rajesh Singla

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Many mobile games come with the benefits of entertainment by introducing stress to the human brain. In recognizing this mental stress, the brain-computer interface (BCI) plays an important role. It has various neuroimaging approaches which help in analyzing the brain signals. Electroencephalogram (EEG) is the most commonly used method among them as it is non-invasive, portable, and economical. Here, this paper investigates the pattern in brain signals when introduced with mental stress. Two healthy volunteers played a game whose aim was to search hidden words from the grid, and the levels were chosen randomly. The EEG signals during gameplay were recorded to investigate the impacts of stress with the changing levels from easy to medium to hard. A total of 16 features of EEG were analyzed for this experiment which includes power band features with relative powers, event-related desynchronization, along statistical features. Support vector machine was used as the classifier, which resulted in an accuracy of 93.9% for three-level stress analysis; for two levels, the accuracy of 92% and 98% are achieved. In addition to that, another game that was similar in nature was played by the volunteers. A suitable regression model was designed for prediction where the feature sets of the first and second game were used for testing and training purposes, respectively, and an accuracy of 73% was found.

Keywords: brain computer interface, electroencephalogram, regression model, stress, word search

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Authors: S. S. Patil, Sachidanand Kini

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Classification of land use patterns is compelling in complexity and variability of remote sensing imageries data. An imperative research in remote sensing application exploited to mine some of the significant spatially variable factors as land cover and land use from satellite images for remote arid areas in Karnataka State, India. The diverse classification techniques, unsupervised and supervised consisting of maximum likelihood, Mahalanobis distance, and minimum distance are applied in Bellary District in Karnataka State, India for the classification of the raw satellite images. The accuracy evaluations of results are compared visually with the standard maps with ground-truths. We initiated with the maximum likelihood technique that gave the finest results and both minimum distance and Mahalanobis distance methods over valued agriculture land areas. In meanness of mislaid few irrelevant features due to the low resolution of the satellite images, high-quality accord between parameters extracted automatically from the developed maps and field observations was found.

Keywords: Mahalanobis distance, minimum distance, supervised, unsupervised, user classification accuracy, producer's classification accuracy, maximum likelihood, kappa coefficient

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Authors: Ahmed. A. Hossam Eldin, Karim H. Youssef, Kareem M. AboRas

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Recent current rapid industrial development and energy shortage are essential problems, which face most of the developing countries. Moreover, increased prices of fossil fuel and advanced energy conversion technology lead to the need for renewable energy resources. A study, modelling and simulation of an outdoor micro scale stand alone wind turbine was carried out. For model validation an experimental study was applied. In this research the aim was to clarify effects of real outdoor operating conditions and the instantaneous fluctuations of both wind direction and wind speed on the actual produced power. The results were compared with manufacturer’s data. The experiments were carried out in Borg Al-Arab, Alexandria. This location is on the north Western Coast of Alexandria. The results showed a real max output power for outdoor micro scale wind turbine, which is different from manufacturer’s value. This is due to the fact that the direction of wind speed is not the same as that of the manufacturer’s data. The measured wind speed and direction by the portable metrological weather station anemometer varied with time. The blade tail response could not change the blade direction at the same instant of the wind direction variation. Therefore, designers and users of micro scale wind turbine stand alone system cannot rely on the maker’s name plate data to reach the required power.

Keywords: micro-turbine, wind turbine, inverters, renewable energy, hybrid system

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Authors: Eric Shannon, Mark J. McGuire, John P. Parmigiani

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A hazard associated with the use of timber harvesters is chain shot. Harvester saw chain is subjected to large dynamic mechanical stresses which can cause it to fracture. The resulting open loop of saw chain can fracture a second time and create a projectile consisting of several saw-chain links referred to as a chain shot. Its high kinetic energy enables it to penetrate operator enclosures and be a significant hazard. Accurate data on projectile composition, mass, and speed are needed for the design of both operator enclosures resistant to projectile penetration and for saw chain resistant to fracture. The work presented here contributes to providing this data through the use of a test machine designed and built at Oregon State University. The machine’s enclosure is a standard shipping container. To safely contain any anticipated chain shot, the container was lined with both 9.5 mm AR500 steel plates and 50 mm high-density polyethylene (HDPE). During normal operation, projectiles are captured virtually undamaged in the HDPE enabling subsequent analysis. Standard harvester components are used for bar mounting and chain tensioning. Standard guide bars and saw chains are used. An electric motor with flywheel drives the system. Testing procedures follow ISO Standard 11837. Chain speed at break was approximately 45.5 m/s. Data was collected using both a 75 cm solid bar (Oregon 752HSFB149) and 90 cm solid bar (Oregon 902HSFB149). Saw chains used were 89 Drive Link .404”-18HX loops made from factory spools. Standard 16-tooth sprockets were used. Projectile speed was measured using both a high-speed camera and a chronograph. Both rotational and translational kinetic energy are calculated. For this study 50 chain shot events were executed. Results showed that projectiles consisted of a variety combinations of drive links, tie straps, and cutter links. Most common (occurring in 60% of the events) was a drive-link / tie-strap / drive-link combination having a mass of approximately 10.33 g. Projectile mass varied from a minimum of 2.99 g corresponding to a drive link only to a maximum of 18.91 g corresponding to a drive-link / tie-strap / drive-link / cutter-link / drive-link combination. Projectile translational speed was measured to be approximately 270 m/s and rotational speed of approximately 14000 r/s. The calculated translational and rotational kinetic energy magnitudes each average over 600 J. This study provides useful information for both timber harvester manufacturers and saw chain manufacturers to design products that reduce the hazards associated with timber harvesting.

Keywords: chain shot, timber harvesters, safety, testing

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Authors: Ch. Sridevi, A. Chalapathi Rao, P. Srinivasulu

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The location accuracy of data products is a critical parameter in assessing the geometric performance of satellite sensors. This study focuses on reliability analysis of onboard sensors to evaluate their performance in terms of location accuracy performance over time. The analysis utilizes field failure data and employs the weibull distribution to determine the reliability and in turn to understand the improvements or degradations over a period of time. The analysis begins by scrutinizing the location accuracy error which is the root mean square (RMS) error of differences between ground control point coordinates observed on the product and the map and identifying the failure data with reference to time. A significant challenge in this study is to thoroughly analyze the possibility of an infant mortality phase in the data. To address this, the Weibull distribution is utilized to determine if the data exhibits an infant stage or if it has transitioned into the operational phase. The shape parameter beta plays a crucial role in identifying this stage. Additionally, determining the exact start of the operational phase and the end of the infant stage poses another challenge as it is crucial to eliminate residual infant mortality or wear-out from the model, as it can significantly increase the total failure rate. To address this, an approach utilizing the well-established statistical Laplace test is applied to infer the behavior of sensors and to accurately ascertain the duration of different phases in the lifetime and the time required for stabilization. This approach also helps in understanding if the bathtub curve model, which accounts for the different phases in the lifetime of a product, is appropriate for the data and whether the thresholds for the infant period and wear-out phase are accurately estimated by validating the data in individual phases with Weibull distribution curve fitting analysis. Once the operational phase is determined, reliability is assessed using Weibull analysis. This analysis not only provides insights into the reliability of individual sensors with regards to location accuracy over the required period of time, but also establishes a model that can be applied to automate similar analyses for various sensors and parameters using field failure data. Furthermore, the identification of the best-performing sensor through this analysis serves as a benchmark for future missions and designs, ensuring continuous improvement in sensor performance and reliability. Overall, this study provides a methodology to accurately determine the duration of different phases in the life data of individual sensors. It enables an assessment of the time required for stabilization and provides insights into the reliability during the operational phase and the commencement of the wear-out phase. By employing this methodology, designers can make informed decisions regarding sensor performance with regards to location accuracy, contributing to enhanced accuracy in satellite-based applications.

Keywords: bathtub curve, geometric performance, Laplace test, location accuracy, reliability analysis, Weibull analysis

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Authors: Taiyo Matsumura, Kuninori Takahashi, Takashi Ono

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The purpose of this research is to improve the convenience of waiting for trains at level crossings and stations and to prevent accidents resulting from forcible entry into level crossings, by providing level crossing users and passengers with information that tells them when the next train will pass through or arrive. For this paper, we proposed methods for estimating operation by means of an average value method, variable response smoothing method, and exponential smoothing method, on the basis of open data, which has low accuracy, but for which performance schedules are distributed in real time. We then examined the accuracy of the estimations. The results showed that the application of an exponential smoothing method is valid.

Keywords: exponential smoothing method, open data, operation estimation, train schedule

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Authors: Yilin Liao, Hewen Li, Paula McConvey

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Speed skaters often face a risk of concussion when they fall on the ice floor and impact crash mats during practices and competitive races. Several variables, including those related to the skater, the crash mat, and the impact position (body side/head/feet impact), are believed to influence the severity of the skater's concussion. While computer simulation modeling can be employed to analyze these accidents, the simulation process is time-consuming and does not provide rapid information for coaches and teams to assess the skater's injury risk in competitive events. This research paper promotes the exploration of the feasibility of using AI techniques for evaluating skater’s potential concussion severity, and to develop a fast concussion prediction tool using artificial neural networks to reduce the risk of treatment delays for injured skaters. The primary data is collected through virtual tests and physical experiments designed to simulate skater-mat impact. It is then analyzed to identify patterns and correlations; finally, it is used to train and fine-tune the artificial neural networks for accurate prediction. The development of the prediction tool by employing machine learning strategies contributes to the application of AI methods in sports science and has theoretical involvements for using AI techniques in predicting and preventing sports-related injuries.

Keywords: artificial neural networks, concussion, machine learning, impact, speed skater

Procedia PDF Downloads 116

Authors: Belkheir Noura, Rabah Kerfah, Boumehani Abdellah

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The influence of solidity variations on the aerodynamic performance of H type vertical axis wind turbine is studied in this paper. The wind turbine model used in this paper is the three-blade wind turbine with the symmetrical airfoil, NACA0021. The length of the chord is 0.265m. Numerical investigations were implemented for the different solidity by changing the radius and blade number. A two-dimensional model of the wind turbine is employed. The approach a Reynolds-Averaged Navier–Stokes equations, completed by the K- ώ SST turbulence model, is used. Motion mesh model capability of a computational fluid dynamics (CFD) solver is used. For each value of the solidity, the aerodynamics performances and the characteristics of the flow field are studied at several values of the tip speed ratio, λ = 0.5 to λ = 3, with an incoming wind speed of 8 m/s. The results show that increasing the number of blades will reduce the maximum value of the power coefficient of the wind turbine. Also, for the VAWT with a lower solidity can obtain the maximum Cp at a high tip speed ratio. The effects of changing the radius and blade number on aerodynamic performance are almost the same. Finally, for the validation, experimental data from the literature and computational results were compared. In conclusion, to study the influence of the solidity in the performances of the wind turbine is to provide the reference for the design of H type vertical axis wind turbines.

Keywords: wind energy, darrieus h type vertical axis wind turbine, computational fluid dynamic, solidity

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Authors: Z. Y. Jiang, H. B. Tibar, A. Aljabri

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Optimisation of the physical and mechanical properties of cold rolled thin strips is achieved by controlling the rolling parameters. In this paper, the factors affecting the asymmetrical cold rolling of thin low carbon steel strip have been studied at a speed ratio of 1.1 without lubricant applied. The effect of rolling parameters on the resulting microstructure was also investigated. It was found that under dry condition, work roll shifting and work roll cross angle can improve the strip profile, and the result is more significant with an increase of work roll cross angle rather than that of work roll shifting. However, there was no obvious change in microstructure. In addition, effects of rolling parameters on strip profile and microstructure have also been discussed.

Keywords: rolling speed ratio, microstructure, work roll cross angle, work roll shifting

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Authors: Alexander P. Smirnov, Sergey A. Matveev, Dmitry A. Zheltkov, Eugene E. Tyrtyshnikov

Abstract:

We propose a new computational technique for multidimensional (multicomponent) Smoluchowski coagulation equation. Using low-rank approximations in Tensor Train format of both the solution and the coagulation kernel, we accelerate the classical finite-difference Runge-Kutta scheme keeping its level of accuracy. The complexity of the taken finite-difference scheme is reduced from O(N^2d) to O(d^2 N log N ), where N is the number of grid nodes and d is a dimensionality of the problem. The efficiency and the accuracy of the new method are demonstrated on concrete problem with known analytical solution.

Keywords: tensor train decomposition, multicomponent Smoluchowski equation, runge-kutta scheme, convolution

Procedia PDF Downloads 436

Authors: Gubiani Rino, Nicola Zucchiatti, Da Broi Ugo, Bietresato Marco

Abstract:

The problem of vibrations in agriculture is very important due to the different types of machinery used for the different types of soil in which work is carried out. One of the most commonly used machines is the tractor, where the phenomenon has been studied for a long time by measuring the whole body and placing the sensor on the seat. However, this measurement system does not take into account the characteristics of the drivers, such as their body index (BMI), their gender (male, female) or the muscle fatigue they are subjected to, which is highly dependent on their age for example. The aim of the research was therefore to place sensors not only on the seat but along the spinal column to check the transmission of vibration on drivers with different BMI on different tractors and at different travel speeds and of different genders. The test was also done using wearable sensors such as a dynamometer applied to the muscles, the data of which was correlated with the vibrations produced by the tractor. Initial data show that even on new tractors with pneumatic seats, the vibrations attenuate little and are still correlated with the roughness of the track travelled and the forward speed. Another important piece of data are the root-mean square values referred to 8 hours (A(8)x,y,z) and the maximum transient vibration values (MTVVx,y,z) and, the latter, the MTVVz values were problematic (limiting factor in most cases) and always aggravated by the speed. The MTVVx values can be lowered by having a tyre-pressure adjustment system, able to properly adjust the tire pressure according to the specific situation (ground, speed) in which a tractor is operating.

Keywords: fatigue, effect vibration on health, tractor driver vibrations, vibration, muscle skeleton disorders

Procedia PDF Downloads 76

Authors: Min Wei

Abstract:

The traditional prediction methods of the forecast for tourism market are paid more attention to the accuracy of the forecasts, ignoring the results of the feasibility of forecasting and predicting operability, which had made it difficult to predict the results of scientific testing. With the application of Linear Regression Model, this paper attempts to construct a scientific evaluation system for predictive value, both to ensure the accuracy, stability of the predicted value, and to ensure the feasibility of forecasting and predicting the results of operation. The findings show is that a scientific evaluation system can implement the scientific concept of development, the harmonious development of man and nature co-ordinate.

Keywords: linear regression model, tourism market, forecast, tourism economics

Procedia PDF Downloads 335