Search results for: computer mediated power point presentations

Authors: Abu Afree Andalib, Rafiur Rahman, Md Mezbah Uddin

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The main objective of this work is to anatomize on the various parameters of AGM 88 missile anatomized using FSI module in Ansys. Computational fluid dynamics is used for the study of fluid flow pattern and fluidic phenomenon such as drag, pressure force, energy dissipation and shockwave distribution in water. Using finite element analysis module of Ansys, structural parameters such as stress and stress density, localization point, deflection, force propagation is determined. Separate analysis on structural parameters is done on Abacus. State of the art coupling module is used for FSI analysis. Fine mesh is considered in every case for better result during simulation according to computational machine power. The result of the above-mentioned parameters is analyzed and compared for two phases using graphical representation. The result of Ansys and Abaqus are also showed. Computational Fluid Dynamics and Finite Element analyses and subsequently the Fluid-Structure Interaction (FSI) technique is being considered. Finite volume method and finite element method are being considered for modelling fluid flow and structural parameters analysis. Feasible boundary conditions are also utilized in the research. Significant change in the interaction and interference pattern while the impact was found. Theoretically as well as according to simulation angled condition was found with higher impact.

Keywords: FSI (Fluid Surface Interaction), impact, missile, high viscous fluid, CFD (Computational Fluid Dynamics), FEM (Finite Element Analysis), FVM (Finite Volume Method), fluid flow, fluid pattern, structural analysis, AGM-88, Ansys, Abaqus, meshing, k-omega, turbulence model

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Authors: Juan Huang, Hugo Ninanya

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Oil has been used as a source of energy and supply to make materials, such as asphalt or rubber for many years. This is the reason why new technologies have been implemented through time. However, research still needs to continue increasing due to new challenges engineers face every day, just like unconventional reservoirs. Various numerical methodologies have been applied in petroleum engineering as tools in order to optimize the production of reservoirs before drilling a wellbore, although not all of these have the same efficiency when talking about studying fracture propagation. Analytical methods like those based on linear elastic fractures mechanics fail to give a reasonable prediction when simulating fracture propagation in ductile materials whereas numerical methods based on the cohesive zone method (CZM) allow to represent the elastoplastic behavior in a reservoir based on a constitutive model; therefore, predictions in terms of displacements and pressure will be more reliable. In this work, a hydro-geomechanical coupled model of horizontal wells in fractured rock was developed using ABAQUS; both extended element method and cohesive elements were used to represent predefined fractures in a model (2-D). A power law for representing the rheological behavior of fluid (shear-thinning, power index <1) through fractures and leak-off rate permeating to the matrix was considered. Results have been showed in terms of aperture and length of the fracture, pressure within fracture and fluid loss. It was showed a high infiltration rate to the matrix as power index decreases. A sensitivity analysis is conclusively performed to identify the most influential factor of fluid loss.

Keywords: fracture, hydro-geomechanical model, non-Newtonian fluid, numerical analysis, sensitivity analysis

Procedia PDF Downloads 206

Authors: Laiba Amin, Rashna H. Sukhia, Mubassar Fida

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Introduction: This study evaluates the accuracy of responses from ChatGPT, Google Bard, and Microsoft Copilot regarding dentofacial orthopedic appliances. As artificial intelligence (AI) increasingly enhances various fields, including healthcare, understanding its reliability in specialized domains like orthodontics becomes crucial. By comparing the accuracy of different AI models, this study aims to shed light on their effectiveness and potential limitations in providing technical insights. Materials and Methods: A total of 110 questions focused on dentofacial orthopedic appliances were posed to each AI model. The responses were then evaluated by five experienced orthodontists using a modified 5-point Likert scale to ensure a thorough assessment of accuracy. This structured approach allowed for consistent and objective rating, facilitating a meaningful comparison between the AI systems. Results: The results revealed that Google Bard demonstrated the highest accuracy at 74%, followed by Microsoft Copilot, with an accuracy of 72.2%. In contrast, ChatGPT was found to be the least accurate, achieving only 52.2%. These results highlight significant differences in the performance of the AI models when addressing orthodontic queries. Conclusions: Our study highlights the need for caution in relying on AI for orthodontic insights. The overall accuracy of the three chatbots was 66%, with Google Bard performing best for removable Class II appliances. Microsoft Copilot was more accurate than ChatGPT, which, despite its popularity, was the least accurate. This variability emphasizes the importance of human expertise in interpreting AI-generated information. Further research is necessary to improve the reliability of AI models in specialized healthcare settings.

Keywords: artificial intelligence, large language models, orthodontics, dentofacial orthopaedic appliances, accuracy assessment.

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Authors: Ainul Haque, Ameeye Kumar Nayak

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Flow enhancement and species transport in a slit hydrophobic microchannel is studied for non-Newtonian fluids with the externally imposed electric field and pressure gradient. The incompressible Poisson-Nernst-Plank equations and the Navier-Stokes equations are approximated by lubrication theory to quantify the flow structure due to hydrophobic and hydrophilic surfaces. The analytical quantification of velocity and pressure of electroosmotic flow (EOF) is made with the numerical results due to the staggered grid based finite volume method for flow governing equations. The resistance force due to fluid friction and shear force along the surface are decreased by the hydrophobicity, enables the faster movement of fluid particles. The resulting flow enhancement factor Ef is increased with the low viscous fluid and provides maximum species transport. Also, the analytical comparison of EOF with pressure driven EOF justifies the flow enhancement due to hydrophobicity and shear impact on flow variation.

Keywords: electroosmotic flow, hydrophobic surface, power-law fluid, shear effect

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Authors: Adelina Vrancianu

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The problem of artificial real accession will be analyzed in this study both in terms of old and current Civil Code provisions and in terms of comparative law, European legal and Canadian systems. The current Civil Code from 2009 has brought new changes about the application and solutions regarding artificial real accession. The hypothesis in which a person is making works with his own materials on the real estate belonging to another person is developed and analyzed in detail from national and international point of view in relation with the good faith. The scope of this analysis is to point out what are the changes issued from case-law and which ones are new, inspired from other law systems in regard to the good/bad faith. The new civil code has promoted a definition for this notion. Is this definition a new one inspired from the comparative law or is it inspired from the case-law? Is it explained for every case scenario of accession or is a general notion? The study tries to respond to these questions and to present the new aspects in the area. has reserved a special place for the situation of execution of works with own materials exceeding the border with violation of another’s right of property, where the variety of solutions brings into discussion the case of expropriation for private interest. The new Civil Code is greatly influenced by the Civil Code from Quebec in comparison with the old code of French influence. The civil reform was needed and has brought into attention new solutions inspired from the Canadian system which has mitigated the permanent conflict between the constructor and the immovable owner.

Keywords: accession, good faith, new civil code, comparative law

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Authors: Rajesh Kumar, Roopali Dogra, Puneet Aggarwal

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In recent advancements in electric machine and drives, wound rotor motor is extensively used. The merit of using wound rotor induction motor is to control speed/torque characteristics by inserting external resistance. Wound rotor induction motor can be used in the cases such as (a) low inrush current, (b) load requiring high starting torque, (c) lower starting current is required, (d) loads having high inertia, and (e) gradual built up of torque. Examples include conveyers, cranes, pumps, elevators, and compressors. This paper includes speed control of wound induction motor using MATLAB/Simulink for rotor resistance and slip power recovery method. The characteristics of these speed control methods are hence analyzed.

Keywords: MATLAB/Simulink, rotor resistance method, slip power recovery method, wound rotor induction motor

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Authors: Thinh Ngo, Paul Rad, Brian Kelley

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Noise estimation is essential in today wireless systems for power control, adaptive modulation, interference suppression and quality of service. Deep learning (DL) has already been applied in the physical layer for modulation and signal classifications. Unacceptably low accuracy of less than 50% is found to undermine traditional application of DL classification for SNR prediction. In this paper, we use divide-and-conquer algorithm and classifier fusion method to simplify SNR classification and therefore enhances DL learning and prediction. Specifically, multiple CNNs are used for classification rather than a single CNN. Each CNN performs a binary classification of a single SNR with two labels: less than, greater than or equal. Together, multiple CNNs are combined to effectively classify over a range of SNR values from −20 ≤ SNR ≤ 32 dB.We use pre-trained CNNs to predict SNR over a wide range of joint channel parameters including multiple Doppler shifts (0, 60, 120 Hz), power-delay profiles, and signal-modulation types (QPSK,16QAM,64-QAM). The approach achieves individual SNR prediction accuracy of 92%, composite accuracy of 70% and prediction convergence one order of magnitude faster than that of traditional estimation.

Keywords: classification, CNN, deep learning, prediction, SNR

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Authors: Mohammed Hmimou, Khalid Amediaz, Imane Sebari, Nabil Bounajma

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Annual crop production is one of the most important macroeconomic indicators for the majority of countries around the world. This information is valuable, especially for exporting countries which need a yield estimation before harvest in order to correctly plan the supply chain. When it comes to estimating agricultural yield, especially for arboriculture, conventional methods are mostly applied. In the case of the citrus industry, the sale before harvest is largely practiced, which requires an estimation of the production when the fruit is on the tree. However, conventional method based on the sampling surveys of some trees within the field is always used to perform yield estimation, and the success of this process mainly depends on the expertise of the ‘estimator agent’. The present study aims to propose a methodology based on the combination of unmanned aerial vehicle (UAV) images and terrestrial laser scanner (TLS) point cloud to estimate citrus production. During data acquisition, a fixed wing and rotatory drones, as well as a terrestrial laser scanner, were tested. After that, a pre-processing step was performed in order to generate point cloud and digital surface model. At the processing stage, a machine vision workflow was implemented to extract points corresponding to fruits from the whole tree point cloud, cluster them into fruits, and model them geometrically in a 3D space. By linking the resulting geometric properties to the fruit weight, the yield can be estimated, and the statistical distribution of fruits size can be generated. This later property, which is information required by importing countries of citrus, cannot be estimated before harvest using the conventional method. Since terrestrial laser scanner is static, data gathering using this technology can be performed over only some trees. So, integration of drone data was thought in order to estimate the yield over a whole orchard. To achieve that, features derived from drone digital surface model were linked to yield estimation by laser scanner of some trees to build a regression model that predicts the yield of a tree given its features. Several missions were carried out to collect drone and laser scanner data within citrus orchards of different varieties by testing several data acquisition parameters (fly height, images overlap, fly mission plan). The accuracy of the obtained results by the proposed methodology in comparison to the yield estimation results by the conventional method varies from 65% to 94% depending mainly on the phenological stage of the studied citrus variety during the data acquisition mission. The proposed approach demonstrates its strong potential for early estimation of citrus production and the possibility of its extension to other fruit trees.

Keywords: citrus, digital surface model, point cloud, terrestrial laser scanner, UAV, yield estimation, 3D modeling

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Authors: Asma Qudrat, Abid Ullah, Rafi Ullah, Ali Raza, Shah Zeb, Syed Ali Shan Ul-Haq, Shahkar Ahmed Shah, Attiya Hameed Khan, Saad Zaheer, Umama Qasim, Kiran Jamal, Zahoor khan

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Objectives: Coronary artery disease (CAD) is the major public health issue associated with high mortality and morbidity rate worldwide. Young patients with ACS have unique characteristics with different demographic profiles and risk factors. The precise diagnosis and early risk stratification is important in guiding treatment and predicting the prognosis of young patients with ACS. To evaluate the associated demographics, risk factors, and outcomes profile of ACS in young age patients. Methods: The research follow a retrospective design, the single centre study of patients diagnosis with the first event of ACS in young age (>18 and <40) were included. Data collection included demographic profiles, risk factors, and in-hospital outcomes of young ACS patients. The patient’s data was retrieved through Electronic Medical Records (EMR) of Peshawar Institute of Cardiology (PIC), and all characteristic were assessed. Results: In this study, 77% were male, and 23% were female patients. The risk factors were assessed with CAD and shown significant results (P < 0.01). The most common presentation was STEMI, with (45%) most in ACS young patients. The angiographic pattern showed single vessel disease (SVD) in 49%, double vessel disease (DVD) in 17% and triple vessel disease (TVD) was found in 10%, and Left Artery Disease (LAD) (54%) was present to be the most common involved artery. Conclusion: It is concluded that the male sex was predominant in ACS young age patients. SVD was the common coronary angiographic finding. Risk factors showed significant results towards CAD and common presentations.

Keywords: coronary artery disease, Non-ST elevation myocardial infarction, ST elevation myocardial infarction, unstable angina, acute coronary syndrome

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Authors: Kathleen Joy Hingan, Jessiraye Luienne Catubigan, Carlo Mercado, Janisse RañEses

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In this research, the researchers wanted to explore how specialists and resident doctors in the fields of surgery, and obstetrics and gynecology handle their medical errors. They are interested in understanding the factors that contributed to the disclosure of medical error, the feelings after the occurrence of an error, and the way they coped with it given the power relations in place. The researchers conducted semi-structured interviews, transcribed the recordings, and analyzed the transcripts using thematic analysis. They found that doctors disclosed to their superiors and co-residents to cope with and to learn from the errors. In terms of disclosure to patients, the participants told them about the adverse event, but not about the error because of fear for themselves, their colleagues, their institution, and their patient. Doctors also performed compensatory actions to make up for the error and the nondisclosure of its occurrence. These actions functioned as a form of damage control too. Resident doctors and specialists receive different sanctions because of the power structures in the system.

Keywords: coping, disclosure, doctors, interviews, medical errors, thematic analysis

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Authors: Javier E. García-Gallo, Nelson J. Fonseca-Ruiz, John F. Duitama-Munoz

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Sepsis is a syndrome that occurs with physiological and biochemical abnormalities induced by severe infection and carries a high mortality and morbidity, therefore the severity of its condition must be interpreted quickly. After patient admission in an intensive care unit (ICU), it is necessary to synthesize the large volume of information that is collected from patients in a value that represents the severity of their condition. Traditional severity of illness scores seeks to be applicable to all patient populations, and usually assess in-hospital mortality. However, the use of machine learning techniques and the data of a population that shares a common characteristic could lead to the development of customized mortality prediction scores with better performance. This study presents the development of a score for the one-year mortality prediction of the patients that are admitted to an ICU with a sepsis diagnosis. 5650 ICU admissions extracted from the MIMICIII database were evaluated, divided into two groups: 70% to develop the score and 30% to validate it. Comorbidities, demographics and clinical information of the first 24 hours after the ICU admission were used to develop a mortality prediction score. LASSO (least absolute shrinkage and selection operator) and SGB (Stochastic Gradient Boosting) variable importance methodologies were used to select the set of variables that make up the developed score; each of this variables was dichotomized and a cut-off point that divides the population into two groups with different mean mortalities was found; if the patient is in the group that presents a higher mortality a one is assigned to the particular variable, otherwise a zero is assigned. These binary variables are used in a logistic regression (LR) model, and its coefficients were rounded to the nearest integer. The resulting integers are the point values that make up the score when multiplied with each binary variables and summed. The one-year mortality probability was estimated using the score as the only variable in a LR model. Predictive power of the score, was evaluated using the 1695 admissions of the validation subset obtaining an area under the receiver operating characteristic curve of 0.7528, which outperforms the results obtained with Sequential Organ Failure Assessment (SOFA), Oxford Acute Severity of Illness Score (OASIS) and Simplified Acute Physiology Score II (SAPSII) scores on the same validation subset. Observed and predicted mortality rates within estimated probabilities deciles were compared graphically and found to be similar, indicating that the risk estimate obtained with the score is close to the observed mortality, it is also observed that the number of events (deaths) is indeed increasing as the outcome go from the decile with the lowest probabilities to the decile with the highest probabilities. Sepsis is a syndrome that carries a high mortality, 43.3% for the patients included in this study; therefore, tools that help clinicians to quickly and accurately predict a worse prognosis are needed. This work demonstrates the importance of customization of mortality prediction scores since the developed score provides better performance than traditional scoring systems.

Keywords: intensive care, logistic regression model, mortality prediction, sepsis, severity of illness, stochastic gradient boosting

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Authors: Fatemeh Nokhodchi Bonab

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Bioinformatics, in its broad sense, involves application of computer processes to solve biological problems. A wide range of computational tools are needed to effectively and efficiently process large amounts of data being generated as a result of recent technological innovations in biology and medicine. A number of computational tools have been developed or adapted to deal with the experimental riches of complex and multivariate data and transition from data collection to information or knowledge. These bioinformatics tools are being evaluated and applied in various medical areas including early detection, risk assessment, classification, and prognosis of cancer. The goal of these efforts is to develop and identify bioinformatics methods with optimal sensitivity, specificity, and predictive capabilities. The recent flood of data from genome sequences and functional genomics has given rise to new field, bioinformatics, which combines elements of biology and computer science. Bioinformatics is conceptualizing biology in terms of macromolecules (in the sense of physical-chemistry) and then applying "informatics" techniques (derived from disciplines such as applied maths, computer science, and statistics) to understand and organize the information associated with these molecules, on a large-scale. Here we propose a definition for this new field and review some of the research that is being pursued, particularly in relation to transcriptional regulatory systems.

Keywords: methods, applications, transcriptional regulatory systems, techniques

Procedia PDF Downloads 127

Authors: G. S. Ayyappan, Srinivas Kota, Jaffer R. C. Sheriff, C. Prakash Chandra Joshua

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In the present scenario of energy crises, energy conservation in the electrical machines is very important in the industries. In order to conserve energy, one needs to monitor the performance of an induction motor on-site and in-situ. The instruments available for this purpose are very meager and very expensive. This paper deals with the design and development of induction motor performance analyser on-line, on-site, and in-situ. The system measures only few electrical input parameters like input voltage, line current, power factor, frequency, powers, and motor shaft speed. These measured data are coupled to name plate details and compute the operating efficiency of induction motor. This system employs the method of computing motor losses with the help of equivalent circuit parameters. The equivalent circuit parameters of the concerned motor are estimated using the developed algorithm at any load conditions and stored in the system memory. The developed instrument is a reliable, accurate, compact, rugged, and cost-effective one. This portable instrument could be used as a handy tool to study the performance of both slip ring and cage induction motors. During the analysis, the data can be stored in SD Memory card and one can perform various analyses like load vs. efficiency, torque vs. speed characteristics, etc. With the help of the developed instrument, one can operate the motor around its Best Operating Point (BOP). Continuous monitoring of the motor efficiency could lead to Life Cycle Assessment (LCA) of motors. LCA helps in taking decisions on motor replacement or retaining or refurbishment.

Keywords: energy conservation, equivalent circuit parameters, induction motor efficiency, life cycle assessment, motor performance analysis

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Authors: Ahmet Emre Yonder

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The concept of present time is inevitably and rapidly changing. That provokes unbalanced, uncertain and elusive platform in the world order. Keeping up with this fluctuation requires a willingness to step beyond the comfort zones and to take a step through unknown. That is the perspectives of organizations in which the shareholders persistently create and then they share their creation. Moreover they are adapted to the unpredictable shifts and they establish vision. These are the meaning of innovation which is a process that converts new ideas to invaluable outcomes and that process can be ensured via innovative leaders. Leaders’ creativity is needed when challenging against countless complicated and unsteady situations in the battlefield. However, little attention has been paid to the importance of being innovative leader apart from innovating new technologies so far. Additionally, in most situation militarist organizations are hesitant to welcome different attitudes and that may discourage new ideas. Furthermore military leaders may complain about the lack of sources in today's world where the sources are very rare. In that point military leaders should change the strategies they apply from conventional views to the innovation of different point of views. But the constant occupation in Air Forces can be counted as a huge obstacle for innovative thinking. An organizational structure is needed to be developed for solutions of the problems which the creative leaders will encounter.This article focuses on how to raise innovative military leaders with innovative thinking skills and the need for a change from conventional to the innovative leadership in Air Forces. It also gives important suggestions to encourage raising innovative military leaders.

Keywords: air force, creativity, leadership, military, innovation

Procedia PDF Downloads 313

Authors: Arvind Kumar, Manoj Kumar, Dattatraya H. Nagaraj, Amanpreet Singh, Jayanthi Prattapati

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In recent years, the use of renewable energy resources instead of pollutant fossil fuels and other forms has increased. Photovoltaic generation is becoming increasingly important as a renewable resource since it does not cause in fuel costs, pollution, maintenance, and emitting noise compared with other alternatives used in power applications. In this paper, Perturb and Observe and Incremental Conductance methods are used to improve energy conversion efficiency under different environmental conditions. PI controllers are used to control easily DC-link voltage, active and reactive currents. The whole system is simulated under standard climatic conditions (1000 W/m2, 250C) in MATLAB and the irradiance is varied from 1000 W/m2 to 300 W/m2. The use of PI controller makes it easy to directly control the power of the grid connected PV system. Finally the validity of the system will be verified through the simulations in MATLAB/Simulink environment.

Keywords: incremental conductance algorithm, modeling of PV panel, perturb and observe algorithm, photovoltaic system and simulation results

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Authors: Khalil Ibrahim, Ahmed Ramadan, Mohamed Fanni, Yo Kobayashi, Ahmed Abo-Ismail, Masakatus G. Fujie

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This paper deals with the design process and the dynamic control simulation of a new type of 4-DOFs parallel mechanism that can be used as an endoscopic surgical manipulator. The proposed mechanism, 2-PUU_2-PUS, is designed based on the screw theory and the parallel virtual chain type synthesis method. Based on the structure analysis of the 4-DOF parallel mechanism, the inverse position equation is studied using the inverse analysis theory of kinematics. The design and the stress analysis of the mechanism are investigated using SolidWorks software. The virtual prototype of the parallel mechanism is constructed, and the dynamic simulation is performed using ADAMS TM software. The system model utilizing PID and PI controllers has been built using MATLAB software. A more realistic simulation in accordance with a given bending angle and point to point control is implemented by the use of both ADAMS/MATLAB software. The simulation results showed that this control method has solved the coordinate control for the 4-DOF parallel manipulator so that each output is feedback to the four driving rods. From the results, the tracking performance is achieved. Other control techniques, such as intelligent ones, are recommended to improve the tracking performance and reduce the numerical truncation error.

Keywords: parallel mechanisms, medical robotics, tracjectory control, virtual chain type synthesis method

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Authors: Mohamed Mokhtar, Mostafa F. Shaaban

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Among the challenges facing solar photovoltaic (PV) systems in the United Arab Emirates (UAE), dust accumulation on solar panels is considered the most severe problem that faces the growth of solar power plants. The accumulation of dust on the solar panels significantly degrades output from these panels. Hence, solar PV panels have to be cleaned manually or using costly automated cleaning methods. This paper focuses on initiating cleaning actions when required to reduce maintenance costs. The cleaning actions are triggered only when the dust level exceeds a threshold value. The amount of dust accumulated on the PV panels is estimated using an artificial neural network (ANN). Experiments are conducted to collect the required data, which are used in the training of the ANN model. Then, this ANN model will be fed by the output power from solar panels, ambient temperature, and solar irradiance, and thus, it will be able to estimate the amount of dust accumulated on solar panels at these conditions. The model was tested on different case studies to confirm the accuracy of the developed model.

Keywords: machine learning, dust, PV panels, renewable energy

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Authors: P. C. Ihenacho, M. Burby, G. G. Nasr, G. C. Enyi

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Formulation of a low oil-water ratio drilling mud with vegetable oil continuous phase without adversely affecting the mud rheology and stability has been a major challenge. A low oil-water ratio is beneficial in producing low fluid loss which is essential for wellbore stability. This study examined the possibility of 50/50 oil-water ratio invert emulsion drilling mud using a vegetable oil continuous phase. Jatropha oil was used as continuous phase. 12 ml of egg yolk which was separated from the albumen was added as the primary emulsifier additive. The rheological, stability and filtration properties were examined. The plastic viscosity and yield point were found to be 36cp and 17 Ib/100 ft2 respectively. The electrical stability at 48.9ºC was 353v and the 30 minutes fluid loss was 6ml. The results compared favourably with a similar formulation using 70/30 oil - water ratio giving plastic viscosity of 31cp, yield point of 17 Ib/100 ft2, electrical stability value of 480v and 12ml for the 30 minutes fluid loss. This study indicates that with a good mud composition using guided empiricism, 50/50 oil-water ratio invert emulsion drilling mud is feasible with a vegetable oil continuous phase. The choice of egg yolk as emulsifier additive is for compatibility with the vegetable oil and environmental concern. The high water content with no fluid loss additive will also minimise the cost of mud formulation.

Keywords: environmental compatibility, low cost of mud formulation, low fluid loss, wellbore stability

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Authors: Shih-Wen Hsiao, Rong-Qi Chen

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In the field of fashion design, 3D Mannequin is a kind of assisting tool which could rapidly realize the design concepts. While the concept of 3D Mannequin is applied to the computer added fashion design, it will connect with the development and the application of design platform and system. Thus, the situation mentioned above revealed a truth that it is very critical to develop a module of 3D Mannequin which would correspond with the necessity of fashion design. This research proposes a concrete plan that developing and constructing a system of 3D Mannequin with Kinect. In the content, ergonomic measurements of objective human features could be attained real-time through the implement with depth camera of Kinect, and then the mesh morphing can be implemented through transformed the locations of the control-points on the model by inputting those ergonomic data to get an exclusive 3D mannequin model. In the proposed methodology, after the scanned points from the Kinect are revised for accuracy and smoothening, a complete human feature would be reconstructed by the ICP algorithm with the method of image processing. Also, the objective human feature could be recognized to analyze and get real measurements. Furthermore, the data of ergonomic measurements could be applied to shape morphing for the division of 3D Mannequin reconstructed by feature curves. Due to a standardized and customer-oriented 3D Mannequin would be generated by the implement of subdivision, the research could be applied to the fashion design or the presentation and display of 3D virtual clothes. In order to examine the practicality of research structure, a system of 3D Mannequin would be constructed with JAVA program in this study. Through the revision of experiments the practicability-contained research result would come out.

Keywords: 3D mannequin, kinect scanner, interactive closest point, shape morphing, subdivision

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Authors: Azzeddine Atibi, Khadija El Kababi, Salim Ahmed, Mohamed Radid

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Teaching and learning occupy a significant position globally, as the sustainable development of all sectors is intrinsically linked to the improvement of the educational system. The COVID-19 pandemic demonstrated that the integration of Information and Communication Technology (ICT) in the learning process is not optional but essential, and that proficiency in computer tools is an asset that will enhance pedagogy and ensure the continuity of learning under any circumstances. The objective of our study is to evaluate the impact of introducing computer tools on the quality of learning and the realization of conceptual change in learners. To this end, a learning situation was meticulously prepared, targeting first-year baccalaureate students in experimental sciences at a public high school, "Khadija Oum Almouminin," focusing on the chapter on glycemia regulation in the Moroccan Life and Earth Sciences (LES) curriculum. The learning situation was implemented with a pilot group that utilized computer tools and a control group that studied the same chapter without using ICT. The analysis and comparison of the results allowed us to verify the research question posed and to propose perspectives to ensure conceptual change in learners.

Keywords: information and communication technology, conceptual change, continuity of learning, life and earth sciences, glycemia regulation

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Authors: Ibrahim Sadek Sedik Ibrahim, Mohamed M. Elgohary

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Sea ports are considered one of the factors affecting the progress of economic globalization and the international trade; consequently, they are considered one of the sources involved in the deterioration of the maritime environment due to the excessive amount of exhaust gases emitted from their activities. The majority of sea ports depend on the national electric grid as a source of power for the domestic and ships’ electric demands. This paper discusses the possibility of shifting ports from relying on the national grid electricity to green power-based ports. Offshore wind turbines and hydrogenic PEM fuel cell units appear as two typical promising clean energy sources for ports. As a case study, the paper investigates the prospect of converting Alexandria Port in Egypt to be an eco-friendly port with the study of technical, logistic, and financial requirements. The results show that the fuel cell, followed by a combined system of wind turbines and fuel cells, is the best choice regarding electricity production unit cost by 0.101 and 0.107 $/kWh, respectively. Furthermore, using of fuel cells and offshore wind turbine as green power concept will achieving emissions reduction quantity of CO₂, NOx, and CO emissions by 80,441, 20.814, and 133.025 ton per year, respectively. Finally, the paper highlights the role that renewable energy can play when supplying Alexandria Port with green energy to lift the burden on the government in supporting the electricity, with a possibility of achieving a profit of 3.85% to 22.31% of the annual electricity cost compared with the international prices.

Keywords: fuel cells, green ports, IMO, national electric grid, offshore wind turbines, port emissions, renewable energy

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Authors: Intissar Benrhouma, Marta Victoria, Ignacio Anton, Bechir Chaouachi

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Concentrating photovoltaic systems CPV use optical elements, such as Fresnel lenses, to concentrate solar intensity. The concentrated solar energy is delivered to the solar cell from 20 to 100 W/cm². Some of this energy is converted to electricity, while the rest must be disposed of as a residual heat. Solar cells cooling should be a necessary part of CPV modeling because these systems allowed increasing the power received by the cell. This high power can rise the electrons’ potential causing the heating of the cell, which reduces the global module’s efficiency. This work consists of modeling a concentrating photovoltaic module with and without a cooling system. We have established a theoretical model based on energy balances carried out on a photovoltaic module using solar radiation concentration cells. Subsequently, we developed a calculation program on Matlab which allowed us to simulate the functioning of this module. The obtained results show that the addition of a cooling system to the module improves greatly the performance of our CPV system.

Keywords: solar energy, photovoltaic, concentration, cooling, performance improvement

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Authors: Dong-Woo Kang

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This paper presents an optimal magnet shape of a spoke-shaped interior permanent magnet synchronous motor by using ferrite magnets. Generally, the permanent magnet motor used the ferrite magnets has lower output power and efficiency than a rare-earth magnet motor, because the ferrite magnet has lower magnetic energy than the rare-earth magnet. Nevertheless, the ferrite magnet motor is used to many industrial products owing to cost effectiveness. In this paper, the authors propose a high power density design of the ferrite permanent magnet synchronous motor. Furthermore, because the motor design has to be taken a manufacturing process into account, the design is simulated by using the finite element method for analyzing the demagnetization, the magnetizing, and the structure stiffness. Especially, the magnet shape and dimensions are decided for satisfying these properties. Finally, the authors design an optimal motor for applying our system. That final design is manufactured and evaluated from experimentations.

Keywords: demagnetization, design optimization, magnetic analysis, permanent magnet motors

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Authors: Dudam Bharath Kumar, Harsh Kumar, Naveed Ahmed

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Vehicular traffic on the road-side plays a significant role in affecting the noise pollution in most of the cities over the world. To assess the correlation of the road-traffic on noise pollution in the city environment, continuous measurements were carried out in an entire daytime starting from 8:00 AM IST to 6:00 PM IST at a single point for each 5 minutes (8:00-8:05, 9:00-9:05, 10:00-10:05 AM, ...) near the KIIT University campus road. Noise levels were observed using a mobile operated app of android cell phone and a handheld noise meter. Calibration analysis shows high correlation about 0.89 for the study location for the day time period. Results show diurnal variability of atmospheric noise pollution levels go hand-in and with the vehicular number which pass through a point of observation. The range of noise pollution levels in the daytime period is observed as 55 to 75 dB(A). As a day starts, sudden upsurge of noise levels is observed from 65 to 71 dB(A) in the early morning, 64 dB(A) in late morning, regains the same quantity 68-71 dB(A) in the afternoon, and rises 70 dB(A) in the early evening. Vehicular number of the corresponding noise levels exhibits 115-120, 150-160, and 140-160, respectively. However, this preliminary study suggests the importance of vehicular traffic on noise pollution levels in the urban environment and further to study population exposed to noise levels. Innovative approaches help curb the noise pollution through modelling the traffic noise pollution spatially and temporally over the city environments.

Keywords: noise pollution, vehicular traffic, urban environment, noise meter

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Authors: Chungkuk Jin, Moo-Hyun Kim, HeonYong Kang

Abstract:

A surface riding (SR) wave energy converter (WEC) is designed and its feasibility and performance are numerically simulated by the author-developed floater-mooring-magnet-electromagnetics fully-coupled dynamic analysis computer program. The biggest advantage of the SR-WEC is that the performance is equally effective even in low sea states and its structural robustness is greatly improved by simply riding along the wave surface compared to other existing WECs. By the numerical simulations and actuator testing, it is clearly demonstrated that the concept works and through the optimization process, its efficiency can be improved.

Keywords: computer simulation, electromagnetics fully-coupled dynamics, floater-mooring-magnet, optimization, performance evaluation, surface riding, WEC

Procedia PDF Downloads 145

Authors: Wang Shuai, Su Rong, K. J.Tseng, V. Viswanathan, S. Ramakrishna

Abstract:

The More-Electric-Aircraft concept in aircraft industry levies an increasing demand on the embedded starter/generators (ESG). The high-speed and high-temperature environment within an engine poses great challenges to the operation of such machines. In view of such challenges, squirrel cage induction machines (SCIM) have shown advantages due to its simple rotor structure, absence of temperature-sensitive components as well as low torque ripples etc. The tight operation constraints arising from typical ESG applications together with the detailed operation principles of SCIMs have been exploited to derive the mathematical interpretation of the ESG-SCIM design process. The resultant non-linear mathematical treatment yielded unique solution to the SCIM design problem for each configuration of pole pair number p, slots/pole/phase q and conductors/slot zq, easily implemented via loop patterns. It was also found that not all configurations led to feasible solutions and corresponding observations have been elaborated. The developed mathematical procedures also proved an effective framework for optimization among electromagnetic, thermal and mechanical aspects by allocating corresponding degree-of-freedom variables. Detailed 3D FEM analysis has been conducted to validate the resultant machine performance against design specifications. To obtain higher power ratings, electrical machines often have to increase the slot areas for accommodating more windings. Since the available space for embedding such machines inside an engine is usually short in length, axial air gap arrangement appears more appealing compared to its radial gap counterpart. The aforementioned approach has been adopted in case studies of designing series of AFIMs and RFIMs respectively with increasing power ratings. Following observations have been obtained. Under the strict rotor diameter limitation AFIM extended axially for the increased slot areas while RFIM expanded radially with the same axial length. Beyond certain power ratings AFIM led to long cylinder geometry while RFIM topology resulted in the desired short disk shape. Besides the different dimension growth patterns, AFIMs and RFIMs also exhibited dissimilar performance degradations regarding power factor, torque ripples as well as rated slip along with increased power ratings. Parametric response curves were plotted to better illustrate the above influences from increased power ratings. The case studies may provide a basic guideline that could assist potential users in making decisions between AFIM and RFIM for relevant applications.

Keywords: axial flux induction machine, electrical starter/generator, finite element analysis, squirrel cage induction machine

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Authors: Aleksandra Aleksandrovna Filimonova, Lev Sergeevich Kazarinov, Tatyana Aleksandrovna Barbasova

Abstract:

A method of effective planning and control of industrial facility energy consumption is offered. The method allows to optimally arrange the management and full control of complex production facilities in accordance with the criteria of minimal technical and economic losses at the forecasting control. The method is based on the optimal construction of the power efficiency characteristics with the prescribed accuracy. The problem of optimal designing of the forecasting model is solved on the basis of three criteria: maximizing the weighted sum of the points of forecasting with the prescribed accuracy; the solving of the problem by the standard principles at the incomplete statistic data on the basis of minimization of the regularized function; minimizing the technical and economic losses due to the forecasting errors.

Keywords: energy consumption, energy efficiency, energy management system, forecasting model, power efficiency characteristics

Procedia PDF Downloads 393

Authors: M. Çevik, S. Sabancı, D. Tezcan, C. Çelebi, F. İçier

Abstract:

Ultrasound technology is the one of the non-thermal food processing method in recent years which has been used widely in the food industry. Ultrasound application in the food industry is divided into two groups: low and high intensity ultrasound application. While low intensity ultrasound is used to obtain information about physicochemical properties of foods, high intensity ultrasound is used to extract bioactive components and to inactivate microorganisms and enzymes. In this study, the ultrasound pre-treatment at a constant power (1500 W) and fixed frequency (20 kHz) was applied to the red beetroot slices having the dimension of 25×25×50 mm at the constant temperature (25°C) for different application times (0, 5, 10, 15 and 20 min). The red beet root slices pretreated with ultrasonication was squeezed immediately. The changes on rheological properties of red beet root juice depending on ultrasonication duration applied to slices were investigated. Rheological measurements were conducted by using Brookfield viscometer (LVDV-II Pro, USA). Shear stress-shear rate data was obtained from experimental measurements for 0-200 rpm range by using spindle 18. Rheological properties of juice were determined by fitting this data to some rheological models (Newtonian, Bingham, Power Law, Herschel Bulkley). It was investigated that the best model was Power Law model for both untreated red beet root juice (R2=0.991, χ2=0.0007, RMSE=0.0247) and red beetroot juice produced from ultrasonicated slices (R2=0.993, χ2=0.0006, RMSE=0.0216 for 20 min pre-treatment). k (consistency coefficient) and n (flow behavior index) values of red beetroot juices were not affected from the duration of ultrasonication applied to the slices. Ultrasound treatment does not result in any changes on the rheological properties of red beetroot juice. This can be explained by lack of ability to homogenize of the intensity of applied ultrasound.

Keywords: ultrasonication, rheology, red beet root slice, juice

Procedia PDF Downloads 407

Authors: Junkyeong Kim, Seunghee Park, Ju-Won Kim, Myung-Sug Cho

Abstract:

Recently, demands for the construction of Nuclear Power Plants (NPP) using high strength concrete (HSC) has been increased. However, HSC might be susceptible to brittle fracture if the curing process is inadequate. To prevent unexpected collapse during and after the construction of HSC structures, it is essential to confirm the strength development of HSC during the curing process. However, several traditional strength-measuring methods are not effective and practical. In this study, a novel method to estimate the strength development of HSC based on electromechanical impedance (EMI) measurements using an embedded piezoelectric sensor is proposed. The EMI of NPP concrete specimen was tracked to monitor the strength development. In addition, cross-correlation coefficient was applied in sequence to examine the trend of the impedance variations more quantitatively. The results confirmed that the proposed technique can be applied successfully monitoring of the strength development during the curing process of HSC structures.

Keywords: concrete curing, embedded piezoelectric sensor, high strength concrete, nuclear power plant, self-sensing impedance

Procedia PDF Downloads 516

Authors: Ronit Chakraborty, Sugata Banerji

Abstract:

There has been a marked increase in the reported prevalence of Autism Spectrum Disorder (ASD) among children in the US over the past two decades. This research has analyzed the growth in state-level ASD prevalence against 45 different potentially explanatory factors, including socio-economic, demographic, healthcare, public policy, and political factors. The goal was to understand if these factors have adequate predictive power in modeling the differential growth in ASD prevalence across various states and if they do, which factors are the most influential. The key findings of this study include (1) the confirmation that the chosen feature set has considerable power in predicting the growth in ASD prevalence, (2) the identification of the most influential predictive factors, (3) given the nature of the most influential predictive variables, an indication that a considerable portion of the reported ASD prevalence differentials across states could be attributable to over and under diagnosis, and (4) identification of Florida as a key outlier state pointing to a potential under-diagnosis of ASD there.

Keywords: autism spectrum disorder, clustering, machine learning, predictive modeling

Procedia PDF Downloads 103