Search results for: flexible thermoelectric module

Authors: Nagore Guerra Bilbao, Clemente Lobato Fraile

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Mentoring is provided by professionals with a higher level of experience and competence as part of the professional development of a university faculty. This paper explores the characteristics of the mentoring provided by those teachers participating in the development of an active methodology program run at the University of the Basque Country: to examine and to analyze mentors’ performance with the aim of providing empirical evidence regarding its value as a lifelong learning strategy for teaching staff. A total of 183 teachers were trained during the first three programs. The analysis method uses a coding technique and is based on flexible, systematic guidelines for gathering and analyzing qualitative data. The results have confirmed the conception of mentoring as a methodological innovation in higher education. In short, university teachers in general assessed the mentoring they received positively, considering it to be a valid, useful strategy in their professional development. They highlighted the methodological expertise of their mentor and underscored how they monitored the learning process of the active method and provided guidance and advice when necessary. Finally, they also drew attention to traits such as availability, personal commitment and flexibility in. However, a minority critique is pointed to some aspects of the performance of some mentors.

Keywords: higher education, mentoring, professional development, university teachers

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Authors: Lorena Caires Moreira, Marcos Kauffman

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This paper outlines the results of experimental research on deploying an emerging augmented reality (AR) system for real-time task assistance of highly customized and high-risk manual operations. The focus is on operators’ training capabilities and the aim is to test if such technologies can support achieving higher levels of knowledge retention and accuracy of task execution to improve health and safety (H and S) levels. The proposed solution is tested and validated using a real-world case study of electric vehicles’ battery module assembly. The experimental results revealed that the proposed AR method improved the training practices by increasing the knowledge retention levels from 40% to 84% and improved the accuracy of task execution from 20% to 71%, compared to the traditional paper-based method. The results of this research can be used as a demonstration of how emerging technologies are advancing the choice of manual, hybrid, or fully automated processes by promoting the connected worker (Industry 5.0) and supporting manufacturing in becoming more resilient in times of constant market changes.

Keywords: augmented reality, extended reality, connected worker, XR-assisted operator, manual assembly, industry 5.0, smart training, battery assembly

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Authors: Mona Elhelbawy, Mac Gray

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Traditional wired endoscopy is an intrusive process that requires a long flexible tube to be inserted through the patient’s mouth while intravenously sedated. Only images of the upper 4 feet of stomach, colon, and rectum can be captured, leaving the remaining 20 feet of small intestines. Wireless capsule endoscopy offers a painless, non-intrusive, efficient and effective alternative to traditional endoscopy. In wireless capsule endoscopy (WCE), ingestible vitamin-pill-shaped capsules with imaging capabilities, sensors, batteries, and antennas are designed to send images of the gastrointestinal (GI) tract in real time. In this paper, we investigate the radiation performance and specific absorption rate (SAR) of a miniature conformal capsule antenna operating at the Medical Implant Communication Service (MICS) frequency band in the human body. We perform numerical simulations using the finite element method based commercial software, high-frequency structure simulator (HFSS) and the ANSYS human body model (HBM). We also investigate the in-body channel characteristics between the implantable capsule and an external antenna placed on the surface of the human body.

Keywords: IEEE 802.15.6, MICS, SAR, WCE

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Authors: Ya Lv

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This article presents the application of the semi-analytic method (SAM) in the thermal management solution (TMS) of the energy storage system (ESS). The TMS studied in this work is fluid cooling. In fluid cooling, both effective heat conduction and heat convection are indispensable due to the heat transfer from solid to fluid. Correspondingly, an efficient TMS requires a design investigation of the following parameters: fluid inlet temperature, ESS initial temperature, fluid flow rate, working c rate, continuous working time, and materials properties. Their variation induces a change of thermal performance in the battery module, which is usually evaluated by numerical simulation. Compared to complicated computation resources and long computation time in simulation, the SAM is developed in this article to predict the thermal influence within a few seconds. In SAM, a fast prediction model is reckoned by combining numerical simulation with theoretical/empirical equations. The SAM can explore the thermal effect of boundary parameters in both steady-state and transient heat transfer scenarios within a short time. Therefore, the SAM developed in this work can simplify the design cycle of TMS and inspire more possibilities in TMS design.

Keywords: semi-analytic method, fast prediction model, thermal influence of boundary parameters, energy storage system

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Authors: G. Levacic, A. Zupan

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Application of new technological solutions and installation of new elements into the network requires special attention when investigating its interaction with the existing power system. Special attention needs to be devoted to the occurrence of harmonic resonance. Sources of increasing harmonic penetration could be wind power plants, Flexible Alternating Current Transmission System (FACTS) devices, underground and submarine cable installations etc. Calculation in frequency domain with various software, for example, the software for power systems transients EMTP-RV presents one of the most common ways to obtain the harmonic impedance of the system. Along calculations in frequency domain, such software allows performing of different type of calculations as well as steady-state domain. This paper describes a power system modeling with software EMTP-RV based on data from SCADA/EMS system. The power flow results on 220 kV and 400 kV voltage levels retrieved from EMTP-RV are verified by comparing with power flow results from power transmissions system planning software PSS/E. The determination of the harmonic impedance for the case of remote power plant connection with cable up to 2500 Hz is presented as an example of calculations in frequency domain.

Keywords: power system modeling, frequency domain, steady state, EMTP-RV, PSS/E

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Authors: A. Oukaira, A. Lakhssassi, O. Ettahri

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To make a good thermal management in an ABDM (Adapter Board Detector Module) card, we must first control temperature and its gradient from the first step in the design of integrated circuits ASIC of our complex system. In this paper, our main goal is to develop and validate the thermal stability in order to get an idea of the flow of heat around the ASIC in transient and thus address the thermal issues for integrated circuits at the ABDM card. However, we need heat sources simulations for ABDM card to establish its thermal mapping. This led us to perform simulations at each ASIC that will allow us to understand the thermal ABDM map and find real solutions for each one of our complex system that contains 36 ABDM map, taking into account the different layers around ASIC. To do a transient simulation under NISA, we had to build a function of power modulation in time TIMEAMP. The maximum power generated in the ASIC is 0.6 W. We divided the power uniformly in the volume of the ASIC. This power was applied for 5 seconds to visualize the evolution and distribution of heat around the ASIC. The DBC (Dirichlet Boundary conditions) method was applied around the ABDM at 25°C and just after these simulations in NISA tool we will validate them by COMSOL tool, wich is a numerical calculation software for a modular finite element for modeling a wide variety of physical phenomena characterizing a real problem. It will also be a design tool with its ability to handle 3D geometries for complex systems.

Keywords: ABDM, APD, thermal mapping, complex system

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Authors: Anika Zafiah M. Rus, Nik Normunira Mat Hassan

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Biopolymer made from renewable material are one of the most important group of polymer because of their versatility and they can be manufactured in a wide range of densities and stiffness. In this project, biopolymer based on waste vegetable oil were synthesized and crosslink with commercial polymethane polyphenyl isocyanate (known as BF).The BF was compressed by using hot compression moulding technique at 90 oC based on the evaporation of volatile matter and known as compress biopolymer (CB). The density, vibration and damping characteristic of CB were determined after UV irradiation. Treatment with titanium dioxide (TiO2) was found to affect the physical property of compress biopolymer composite (CBC). The density of CBC samples was steadily increased with an increase of UV irradiation time and TiO2 loading. The highest density of CBC samples is at 10 % of TiO2 loading of 1.1088 g/cm3 due to the amount of filler loading. The vibration and damping characteristic of CBC samples was generated at displacements of 1 mm and 1.5 mm and acceleration of 0.1 G and 0.15 G base excitation according to ASTM D3580-9. It was revealed that, the vibration and damping characteristic of CBC samples is significantly increased with the increasing of UV irradiation time, lowest thickness and percentages of TiO2 loading at the frequency range of 15 - 25 Hz. Therefore, this study indicated that the damping property of CBC could be improved upon prolonged exposure to UV irradiation.

Keywords: biopolymer flexible foam, TGA, UV irradiation, vibration and damping

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Authors: Yu-Lin Chen, Kimberly Koester, Marissa Raymond-Flesh, Anika Thapar, Jay Thapar

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Purpose: Effectively communicating adolescent health topics to teens and their parents is crucial. This study emphasizes critically evaluating the optimal use of artificial intelligence tools (AI), which are increasingly prevalent in disseminating health information. By fostering a deeper understanding of AI voice preference in the context of health, the research aspires to have a ripple effect, enhancing the collective health literacy and decision-making capabilities of both teenagers and their parents. This study explores AI voices' potential within health learning modules for annual well-child visits. We aim to identify preferred voice characteristics and understand factors influencing perceived trustworthiness, ultimately aiming to improve health literacy and decision-making in both demographics. Methods: A cross-sectional study assessed preferences and trust perceptions of AI voices in learning modules among teens (11-18) and their parents/guardians in Northern California. The study involved the development of four distinct learning modules covering various adolescent health-related topics, including general communication, sexual and reproductive health communication, parental monitoring, and well-child check-ups. Participants were asked to evaluate eight AI voices across the modules, considering a set of six factors such as intelligibility, naturalness, prosody, social impression, trustworthiness, and overall appeal, using Likert scales ranging from 1 to 10 (the higher, the better). They were also asked to select their preferred choice of voice for each module. Descriptive statistics summarized participant demographics. Chi-square/t-tests explored differences in voice preferences between groups. Regression models identified factors impacting the perceived trustworthiness of the top-selected voice per module. Results: Data from 104 participants (teen=63; adult guardian = 41) were included in the analysis. The mean age is 14.9 for teens (54% male) and 41.9 for the parent/guardian (12% male). At the same time, similar voice quality ratings were observed across groups, and preferences varied by topic. For instance, in general communication, teens leaned towards young female voices, while parents preferred mature female tones. Interestingly, this trend reversed for parental monitoring, with teens favoring mature male voices and parents opting for mature female ones. Both groups, however, converged on mature female voices for sexual and reproductive health topics. Beyond preferences, the study delved into factors influencing perceived trustworthiness. Interestingly, social impression and sound appeal emerged as the most significant contributors across all modules, jointly explaining 71-75% of the variance in trustworthiness ratings. Conclusion: The study emphasizes the importance of catering AI voices to specific audiences and topics. Social impression and sound appeal emerged as critical factors influencing perceived trustworthiness across all modules. These findings highlight the need to tailor AI voices by age and the specific health information being delivered. Ensuring AI voices resonate with both teens and their parents can foster their engagement and trust, ultimately leading to improved health literacy and decision-making for both groups. Limitations and future research: This study lays the groundwork for understanding AI voice preferences for teenagers and their parents in healthcare settings. However, limitations exist. The sample represents a specific geographic location, and cultural variations might influence preferences. Additionally, the modules focused on topics related to well-child visits, and preferences might differ for more sensitive health topics. Future research should explore these limitations and investigate the long-term impact of AI voice on user engagement, health outcomes, and health behaviors.

Keywords: artificial intelligence, trustworthiness, voice, adolescent

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Authors: Jaisridhar P.

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The present study aimed to investigate preferred teaching styles of young faculties in agricultural education among 23 constituent colleges of Tamil Nadu Agricultural University (TNAU) using Staffordshire Evaluation of Teaching Styles (SETS). An onlinesurvey was conducted among 156 young faculties of 2014 Batch working in different constituent colleges of TNAU and 73 faculties respondent to the survey. The results showed that 62.53 percent preferred “The one-off teacher” stylefollowed by62.26 percent preferring “The student centered, sensitive teacher” style.“The all-round flexible and adaptable teaching style” was preferred by 61.64 percent. The Official Curriculum Teacher” with 61.23 per cent preferring this style.58.97 per cent preferred “The Big Conference Teacher” followed by 58.08 percent of the faculties preferring “The Straight Fact no Non-sense Teacher” type of teaching style. From the results, it wasconcluded that blended teaching approach can balance a teacher’s personal strengths and interest with student’s needs, and curricular requirements enables a teacher to tailor their teaching according to the student’s needs and as per subject matter.

Keywords: teaching styles, assistant professors, agriculture, tamil nadu

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Authors: Wen Li, Zhengyu Bai, Qi Zhang

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The demand for smart scheduling platform in agriculture, particularly in the scheduling process of machinery equipment, is high. With the continuous development of agricultural machinery equipment technology, a large number of agricultural machinery equipment and agricultural machinery cooperative service organizations continue to appear in China. The large area of cultivated land and a large number of agricultural activities in the central and western regions of China have made the demand for smart and efficient agricultural machinery equipment scheduling platforms more intense. In this study, we design and implement a platform for agricultural machinery equipment scheduling to allocate agricultural machinery equipment resources reasonably. With agricultural machinery equipment scheduling platform taken as the research object, we discuss its research significance and value, use the service blueprint technology to analyze and characterize the agricultural machinery equipment schedule workflow, the network analytic method to obtain the demand platform function requirements, and divide the platform functions through the platform function division diagram. Simultaneously, based on the case-based reasoning (CBR) algorithm, the equipment scheduling module of the agricultural machinery equipment scheduling platform is realized; finally, a design scheme of the agricultural machinery equipment scheduling platform architecture is provided, and the visualization interface of the platform is established via VB programming language. It provides design ideas and theoretical support for the construction of a modern agricultural equipment information scheduling platform.

Keywords: case-based reasoning, service blueprint, system design, ANP, VB programming language

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Authors: Madhurima S. Waghmare, Shaleen Singhal

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The concept of smartness, inclusion, sustainability is multidisciplinary and fuzzy, rooted in economic and social development theories and policies which get reflected in the spatial development of the cities. It is a challenge to convert these concepts from aspirations to transforming actions. There is a dearth of assessment and planning tools to support the city planners and administrators in developing smart, inclusive, and sustainable cities. To address this gap, this study develops an inclusive cities decision matrix based on an exploratory approach and using mixed methods. The matrix is soundly based on a review of multidisciplinary urban sector literature and refined and finalized based on inputs from experts and insights from case studies. The application of the decision matric on the case study cities in India suggests that the contemporary planning tools for cities need to be multidisciplinary and flexible to respond to the unique needs of the diverse contexts. The paper suggests that a multidimensional and inclusive approach to city planning can play an important role in building sustainable smart cities.

Keywords: inclusive-cities decision matrix, smart cities in India, city planning tools, sustainable cities

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Authors: Georg Brunnthaller, Sandra Stein, Wilfried Sihn

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Logistics service providers are facing increasing volatility concerning future transport demand. Short-term planning horizons and planning uncertainties lead to reduced capacity utilisation and increasing empty mileage. To overcome these challenges, a model is proposed to continuously pre-plan future transport capacity in order to redesign and adjust the intermodal fleet accordingly. It is expected that the model will enable logistics service providers to organise more economically and ecologically sustainable transport chains in a more flexible way. To further describe such planning aspects, this paper gives a structured literature review on transport planning problems. The focus is on strategic and tactical planning levels, comprising relevant fleet-sizing-, network-design- and choice-of-carriers-problems. Models and their developed solution techniques are presented and the literature review is concluded with an outlook to our future research objectives

Keywords: choice of transport mode, fleet-sizing, freight transport planning, multimodal, review, service network design

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Authors: Zhiwu Zheng, Prakhar Kumar, Sigurd Wagner, Naveen Verma, James C. Sturm

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Soft robots have drawn great interest recently due to a rich range of possible shapes and motions they can take on to address new applications, compared to traditional rigid robots. Large-area electronics (LAE) provides a unique platform for creating soft robots by leveraging thin-film technology to enable the integration of a large number of actuators, sensors, and control circuits on flexible sheets. However, the rich shapes and motions possible, especially when interacting with complex environments, pose significant challenges to forming well-generalized and robust models necessary for robot design and control. In this work, we describe an analytical model for predicting the shape and locomotion of a flexible (steel-foil-based) piezoelectric-actuated 2D robot based on Euler-Bernoulli beam theory. It is nominally (unpowered) lying flat on the ground, and when powered, its shape is controlled by an array of piezoelectric thin-film actuators. Key features of the models are its ability to incorporate the significant effects of gravity on the shape and to precisely predict the spatial distribution of friction against the contacting surfaces, necessary for determining inchworm-type motion. We verified the model by developing a distributed discrete element representation of a continuous piezoelectric actuator and by comparing its analytical predictions to discrete-element robot simulations using PyBullet. Without gravity, predicting the shape of a sheet with a linear array of piezoelectric actuators at arbitrary voltages is straightforward. However, gravity significantly distorts the shape of the sheet, causing some segments to flatten against the ground. Our work includes the following contributions: (i) A self-consistent approach was developed to exactly determine which parts of the soft robot are lifted off the ground, and the exact shape of these sections, for an arbitrary array of piezoelectric voltages and configurations. (ii) Inchworm-type motion relies on controlling the relative friction with the ground surface in different sections of the robot. By adding torque-balance to our model and analyzing shear forces, the model can then determine the exact spatial distribution of the vertical force that the ground is exerting on the soft robot. Through this, the spatial distribution of friction forces between ground and robot can be determined. (iii) By combining this spatial friction distribution with the shape of the soft robot, in the function of time as piezoelectric actuator voltages are changed, the inchworm-type locomotion of the robot can be determined. As a practical example, we calculated the performance of a 5-actuator system on a 50-µm thick steel foil. Piezoelectric properties of commercially available thin-film piezoelectric actuators were assumed. The model predicted inchworm motion of up to 200 µm per step. For independent verification, we also modelled the system using PyBullet, a discrete-element robot simulator. To model a continuous thin-film piezoelectric actuator, we broke each actuator into multiple segments, each of which consisted of two rigid arms with appropriate mass connected with a 'motor' whose torque was set by the applied actuator voltage. Excellent agreement between our analytical model and the discrete-element simulator was shown for both for the full deformation shape and motion of the robot.

Keywords: analytical modeling, piezoelectric actuators, soft robot locomotion, thin-film technology

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Authors: Konstantinos G. Dassios, Guillaume Bonnefont, Gilbert Fantozzi, Theodore E. Matikas, Costas Galiotis

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We report herein the development and preliminary mechanical characterization of fully-dense multi-wall carbon nanotube (MWCNT)-reinforced ceramics and glasses based on a completely new methodology termed High Shear Compaction (HSC). The tubes are introduced and bound to the matrix grains by aid of polymeric binders to form flexible green bodies which are sintered and densified by spark plasma sintering to unprecedentedly high densities of 100% of the pure-matrix value. The strategy was validated across a PyrexTM glass / MWCNT composite while no identifiable factors limit application to other types of matrices. Non-destructive evaluation, based on ultrasonics, of the dynamic mechanical properties of the materials including elastic, shear and bulk modulus as well as Poisson’s ratio showed optimum property improvement at 0.5 %wt tube loading while evidence of nanoscale-specific energy dissipative characteristics acting complementary to nanotube bridging and pull-out indicate a high potential in a wide range of reinforcing and multifunctional applications.

Keywords: ceramic matrix composites, carbon nanotubes, toughening, ultrasonics

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Authors: Angel Daniel Muñoz Guzmán

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E-learning is becoming more and more common every day. For online, hybrid or traditional face-to-face programs, there are some e-teaching platforms like Google classroom, Blackboard, Moodle and Canvas, and there are platforms for full e-learning like Coursera, edX or Udemy. These tools are changing the way students acquire knowledge at schools; however, in today’s changing world that is not enough. As students’ needs and skills change and become more complex, new tools will need to be added to keep them engaged and potentialize their learning. This is especially important in the current global situation that is changing everything: the Covid-19 pandemic. Due to Covid-19, education had to make an unexpected switch from face-to-face courses to digital courses. In this study, the students’ learning experience is analyzed by applying different e-tools and following the Tec21 Model and a flexible and digital model, both developed by the Tecnologico de Monterrey University. The evaluation of the students’ learning experience has been made by the quantitative PrEmo method of emotions. Findings suggest that the quantity of e-tools used during a course does not affect the students’ learning experience as much as how a teacher links every available tool and makes them work as one in order to keep the student engaged and motivated.

Keywords: student, experience, e-learning, e-teaching, e-tools, technology, education

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Authors: Anette Hay, Zama Simamane

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Capacity-building and integration of practical activities is one of the key SDGs of the 2030 Agenda for Sustainable Development. This paper will focus on SDG# 17 – “the means of implementation” - and the role of systems thinking in practice (STiP) in supporting both competence and SDG implementation capability in teacher education curricula at North-West University, South Africa. The “Environmental Management for Sustainability” module (EDTM 312), which is compulsory for all students enrolled in the education program at North-West University, will be used as a case study. There is a need for higher education to implement and practically integrate SDG goals into their curricula, and one way to achieve this is through the development of competencies. Education for Sustainable Development (ESD) has the potential to offer approaches that can be useful in the development of capacity-building activities to foster sustainability. The methodological approach adopted is based on a participatory paradigm followed by two cycles and reflection. This paper focuses on systems thinking in practice demonstrating how students apply and reflect on competencies to situations and how praxis captures the actual experiences. The results of this research indicated how to re-orientate the EDTM 312 curriculum to include an environmental justice focus. This research shares practical knowledge of systems thinking as a sustainability competency.

Keywords: education for sustainable development, environmental justice competencies, sustainable development goals, systems thinking in practice

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Authors: Amol M. Jadhav, Sharad S. Chudhari, S. S. Khedkar

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This review presents a through survey of research paper work on the experimental analysis, FEM Analysis & simulation of the metal spinning process. In this literature survey all the papers being taken from Elsevier publication and most of the from journal of material processing technology. In a last two decade or so, metal spinning process gradually used as chip less formation for the production of engineering component in a small to medium batch quantities. The review aims to provide include into the experimentation, FEM analysis of various components, simulation of metal spinning process and act as guide for research working on metal spinning processes. The review of existing work has several gaps in current knowledge of metal spinning processes. The evaluation of experiment is thickness strain, the spinning force, the twisting angle, the surface roughness of the conventional & shear metal spinning process; the evaluation of FEM of metal spinning to path definition with sufficient fine mesh to capture behavior of work piece; The evaluation of feed rate of roller, direction of roller,& type of roller stimulated. The metal spinning process has the more flexible to produce a wider range of product shape & to form more challenge material.

Keywords: metal spinning, FEM analysis, simulation of metal spinning, mechanical engineering

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Authors: Zhihao Zheng, Zhilin Wang, Linxin Liu

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In the research of automated knowledge question-answering systems, accuracy and efficiency are critical challenges. This paper proposes a knowledge graph-enhanced Retrieval-Augmented Generation (RAG) method, combined with a Graph Neural Network (GNN) structure, to automatically determine the correctness of knowledge competition questions. First, a domain-specific knowledge graph was constructed from a large corpus of academic journal literature, with key entities and relationships extracted using Natural Language Processing (NLP) techniques. Then, the RAG method's retrieval module was expanded to simultaneously query both text databases and the knowledge graph, leveraging the GNN to further extract structured information from the knowledge graph. During answer generation, contextual information provided by the knowledge graph and GNN is incorporated to improve the accuracy and consistency of the answers. Experimental results demonstrate that the knowledge graph and GNN-enhanced RAG method perform excellently in determining the correctness of questions, achieving an accuracy rate of 95%. Particularly in cases involving ambiguity or requiring contextual information, the structured knowledge provided by the knowledge graph and GNN significantly enhances the RAG method's performance. This approach not only demonstrates significant advantages in improving the accuracy and efficiency of automated knowledge question-answering systems but also offers new directions and ideas for future research and practical applications.

Keywords: knowledge graph, graph neural network, retrieval-augmented generation, NLP

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Authors: Nader Ghareeb, Rüdiger Schmidt

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Minimizing the weight in flexible structures means reducing material and costs as well. However, these structures could become prone to vibrations. Attenuating these vibrations has become a pivotal engineering problem that shifted the focus of many research endeavors. One technique to do that is to design and implement an active control system. This system is mainly composed of a vibrating structure, a sensor to perceive the vibrations, an actuator to counteract the influence of disturbances, and finally a controller to generate the appropriate control signals. In this work, two different techniques are explored to create two different mathematical models of an active control system. The first model is a finite element model with a reduced number of nodes and it is called a super-element. The second model is in the form of state-space representation, i.e. a set of partial differential equations. The damping coefficients are calculated and incorporated into both models. The effectiveness of these models is demonstrated when the system is excited by its first natural frequency and an active control strategy is developed and implemented to attenuate the resulting vibrations. Results from both modeling techniques are presented and compared.

Keywords: damping coefficients, finite element analysis, super-element, state-space model

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Authors: Mehdi Rostamzadeh

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Genetic Algorithms (GAs) are an adaptive heuristic search algorithm premised on the evolutionary ideas of natural selection and genetic. In this study, we apply GAs for fundamental and technical models of exchange rate determination in exchange rate market. In this framework, we estimated absolute and relative purchasing power parity, Mundell-Fleming, sticky and flexible prices (monetary models), equilibrium exchange rate and portfolio balance model as fundamental models and Auto Regressive (AR), Moving Average (MA), Auto-Regressive with Moving Average (ARMA) and Mean Reversion (MR) as technical models for Iranian Rial against European Union’s Euro using monthly data from January 1992 to December 2014. Then, we put these models into the genetic algorithm system for measuring their optimal weight for each model. These optimal weights have been measured according to four criteria i.e. R-Squared (R2), mean square error (MSE), mean absolute percentage error (MAPE) and root mean square error (RMSE).Based on obtained Results, it seems that for explaining of Iranian Rial against EU Euro exchange rate behavior, fundamental models are better than technical models.

Keywords: exchange rate, genetic algorithm, fundamental models, technical models

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Authors: Georg Brunnthaller, Sandra Stein, Wilfried Sihn

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Transportation service providers are facing increasing volatility concerning future transport demand. Short-term planning horizons and planning uncertainties lead to reduced capacity utilization and increasing empty mileage. To overcome these challenges, a model is proposed to continuously pre-plan future transportation capacity in order to redesign and adjust the intermodal fleet accordingly. It is expected that the model will enable logistics service providers to organize more economically and ecologically sustainable transport chains in a more flexible way. To further describe these planning aspects, this paper gives an overview on transportation planning problems in a structured way. The focus is on strategic and tactical planning levels, comprising relevant fleet-sizing, service-network-design and choice-of-carriers-problems. Models and their developed solution techniques are presented, and the literature review is concluded with an outlook to our future research directions.

Keywords: freight transportation planning, multimodal, fleet-sizing, service network design, choice of transportation mode, review

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Authors: Shaghayegh Shajari, Mehdi Mahmoodi, Mahmood Rajabian, Uttandaraman Sundararaj, Les J. Sudak

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Although several strain sensors based on carbon nanotubes (CNTs) have been reported, the stretchability and sensitivity of these sensors have remained as a challenge. Highly stretchable and sensitive strain sensors are in great demand for human motion monitoring and human-machine interface. This paper reports the fabrication and characterization of a new type of strain sensors based on a stretchable fluoropolymer / CNT nanocomposite system made via melt-mixing technique. Electrical and mechanical characterizations were obtained. The results showed that this nanocomposite sensor has high stretchability up to 280% of strain at an optimum level of filler concentration. The piezoresistive properties and the strain sensing mechanism of the strain sensor were investigated using Electrochemical Impedance Spectroscopy (EIS). High sensitivity was obtained (gauge factor as large as 12000 under 120% applied strain) in particular at the concentrations above the percolation threshold. Due to the tunneling effect, a non- linear piezoresistivity was observed at high concentrations of CNT loading. The nanocomposites with good conductivity and lightweight could be a promising candidate for strain sensing applications.

Keywords: carbon nanotubes, fluoropolymer, piezoresistive, strain sensor

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Authors: Mohamed Al-Badrashiny, Abdelghani Bellaachia

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This paper presents a classifier ensemble approach for predicting the survivability of the breast cancer patients using the latest database version of the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute. The system consists of two main components; features selection and classifier ensemble components. The features selection component divides the features in SEER database into four groups. After that it tries to find the most important features among the four groups that maximizes the weighted average F-score of a certain classification algorithm. The ensemble component uses three different classifiers, each of which models different set of features from SEER through the features selection module. On top of them, another classifier is used to give the final decision based on the output decisions and confidence scores from each of the underlying classifiers. Different classification algorithms have been examined; the best setup found is by using the decision tree, Bayesian network, and Na¨ıve Bayes algorithms for the underlying classifiers and Na¨ıve Bayes for the classifier ensemble step. The system outperforms all published systems to date when evaluated against the exact same data of SEER (period of 1973-2002). It gives 87.39% weighted average F-score compared to 85.82% and 81.34% of the other published systems. By increasing the data size to cover the whole database (period of 1973-2014), the overall weighted average F-score jumps to 92.4% on the held out unseen test set.

Keywords: classifier ensemble, breast cancer survivability, data mining, SEER

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Authors: Pratham Madnur, Prathamkumar Shetty, Sneha Varur, Gouri Parashetti

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In order to overcome conventional obstacles, this research paper investigates novel approaches for cricket pitch and ball detection that make use of cutting-edge technologies. The research integrates OpenCV for pitch inspection and modifies the YOLOv8 model for cricket ball detection in order to overcome the shortcomings of manual pitch assessment and traditional ball detection techniques. To ensure flexibility in a range of pitch environments, the pitch detection method leverages OpenCV’s color space transformation, contour extraction, and accurate color range defining features. Regarding ball detection, the YOLOv8 model emphasizes the preservation of minor object details to improve accuracy and is specifically trained to the unique properties of cricket balls. The methods are more reliable because of the careful preparation of the datasets, which include novel ball and pitch information. These cutting-edge methods not only improve cricket analytics but also set the stage for flexible methods in more general sports technology applications.

Keywords: OpenCV, YOLOv8, cricket, custom dataset, computer vision, sports

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Authors: Benedict Okundaye, Patricia Tzortzopoulos, Yun Gao

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Scholars and international organisations have contended that developing nations lack the technical expertise, infrastructure, and ability to cope with or prepare for the neighbourhood’s sustainable development as Sustainable Development Goals, mainly targeting goal 11 unimpressive accomplishments. Both wealthy and impoverished communities are facing increasing issues due to rapid urbanisation and pandemics, particularly in Africa. The global neighbourhood challenges, especially in developing countries such as South Africa, include pollution poverty, energy poverty, digital poverty, environmental degradation, social exclusion, and socioeconomic inequalities. With the problematic international sustainability assessment tools lingering, few researchers have produced frameworks to engage the local contexts, but improvements are still required. This research anchors on developing a people-centred, flexible, and adaptable neighbourhood sustainability assessment framework that becomes a tool to assess the characteristics of neighbourhood sustainability in South Africa. The conceptual framework employs a variety of approaches, including broader dimensional factors, a closed-ended questionnaire, and statistical analysis to improve on and complement other existing frameworks.

Keywords: participation, development, inclusion, urbanism, cities, resilience

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Authors: Neha Bhushan

Abstract:

For the purpose of this study a village of district Azamgarh has been selected which is a part of the most populous and backward state of the country, Uttar Pradesh. In the age of information, everyone has the right to acquire information and it becomes important to assess the acceptance and non-acceptance of social media among rural population. Rural women of the state are showing positive trends in the form of increased social media and mobile usage. This study is an effort to know the purpose of rural women for using social media. The study design is exploratory and qualitative in nature. Data collection primarily consisted of 25 semi-structured individual interviews having 10 open-ended specific questions in one of the villages of Azamgarh district of Eastern Uttar Pradesh. Sampling approach is flexible and situational. Data reveals that rural women have become active on social media since last six months to one year. Most of them are using Facebook, Whatsapp, and YouTube for the purpose of interaction, learning new skills, checking out recipes and latest fashion. This pilot study gives a bird eye view of the problem and opens door for exploring this least explored area.

Keywords: exploratory research, mobile usage, rural women, social media

Procedia PDF Downloads 145

Authors: Fatma Al-Maadheed

Abstract:

Following an ethnographic approach this study explored bilingual programmes offered by two types of primary schools in Qatar: international and Independent schools. Qatar with its unique linguistic and socio-economic situation launched a new initiative for educatiobnal development in 2001 but with hardly any research linked to theses changes. The study reveals that the Qatari bilingual schools context was one of heteroglossia, with three codes in operation: Modern Standard Arabic, Colloquial Arabic dialects and English. The two schools adopted different models of bilingualism. The international school adopted a strict separation policy between the two languages following a monoglossic belief. The independent school was found to apply a flexible language policy. The study also highlighted the daily challnges produced from the diglossia situation in Qatar, the difference between students and teacher dialect as well as acquiring literacy in the formal language. In addition to an abscence of a clear language policy in Schools, the study brought attention to the instructional methods utilised in language teaching which are mostly associated with successful bilingual education.

Keywords: diglossia, instructional methods, language policy, qatari primary schools

Procedia PDF Downloads 473

Authors: K. Asanimoghadam, M. Salahi, A. Jamalian

Abstract:

Data envelopment analysis is an approach to measure the efficiency of decision making units with multiple inputs and outputs. The structure of many decision making units also has decision-making subunits that are not considered in most data envelopment analysis models. Also, the inputs and outputs of the decision-making units usually are considered desirable, while in some real-world problems, the nature of some inputs or outputs are undesirable. In this thesis, we study the evaluation of the efficiency of two stage decision-making units, where some outputs are undesirable using two non-radial models, the SBM and the ASBM models. We formulate the nonlinear ASBM model as a second order cone optimization problem. Finally, we compare two models for both external and internal evaluation approaches for two real world example in the presence of undesirable outputs. The results show that, in both external and internal evaluations, the overall efficiency of ASBM model is greater than or equal to the overall efficiency value of the SBM model, and in internal evaluation, the ASBM model is more flexible than the SBM model.

Keywords: network DEA, conic optimization, undesirable output, SBM

Procedia PDF Downloads 194

Authors: Adel M. Belal, Sameh Abu El-Soud, Mariam Farid

Abstract:

This study presents the effect of reinforcement inclusions (fibers-geogrids) on fine sand bearing capacity under strip footings. Experimental model tests were carried out using a rectangular plates [(10cm x 38 cm), (7.5 cm x 38 cm), and (12.5 cm x 38 cm)] with a geogrids and randomly reinforced fibers. The width and depth of the geogrid were varied to determine their effects on the engineering properties of treated poorly graded fine sand. Laboratory model test results for the ultimate stresses and the settlement of a rigid strip foundation supported by single and multi-layered fiber-geogrid-reinforced sand are presented. The number of layers of geogrid was varied between 1 to 4. The effect of the first geogrid reinforcement depth, the spacing between the reinforcement and its length on the bearing capacity is investigated by experimental program. Results show that the use of flexible random fibers with a content of 0.125% by weight of the treated sand dunes, with 3 geogrid reinforcement layers, u/B= 0.25 and L/B=7.5, has a significant increase in the bearing capacity of the proposed system.

Keywords: earth reinforcement, geogrid, random fiber, reinforced soil

Procedia PDF Downloads 312

Authors: C. Manjula, Lilly Florence

Abstract:

Software technology is developing rapidly which leads to the growth of various industries. Now-a-days, software-based applications have been adopted widely for business purposes. For any software industry, development of reliable software is becoming a challenging task because a faulty software module may be harmful for the growth of industry and business. Hence there is a need to develop techniques which can be used for early prediction of software defects. Due to complexities in manual prediction, automated software defect prediction techniques have been introduced. These techniques are based on the pattern learning from the previous software versions and finding the defects in the current version. These techniques have attracted researchers due to their significant impact on industrial growth by identifying the bugs in software. Based on this, several researches have been carried out but achieving desirable defect prediction performance is still a challenging task. To address this issue, here we present a machine learning based hybrid technique for software defect prediction. First of all, Genetic Algorithm (GA) is presented where an improved fitness function is used for better optimization of features in data sets. Later, these features are processed through Decision Tree (DT) classification model. Finally, an experimental study is presented where results from the proposed GA-DT based hybrid approach is compared with those from the DT classification technique. The results show that the proposed hybrid approach achieves better classification accuracy.

Keywords: decision tree, genetic algorithm, machine learning, software defect prediction

Procedia PDF Downloads 329