Search results for: Technology Acceptance Model (TAM)

Authors: Selma R. Oliveira, E. W. Cazarini

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Recently, studies have referenced innovation as a key factor affecting the performance of firms. Companies make use of its innovative capacities to achieve sustainable competitive advantage. In this perspective, the objective of this paper is to contribute to innovation planning policies in industry 4.0. Thus, this paper examines the disruptive innovation capacity on firm performance in Europe. This procedure was prepared according to the following phases: Phase 1: Determination of the conceptual model; and Phase 2: Verification of the conceptual model. The research was initially conducted based on the specialized literature, which extracted the data regarding the constructs/structure and content in order to build the model. The research involved the intervention of experts knowledgeable on the object studied, selected by technical-scientific criteria. The data were extracted using an assessment matrix. To reduce subjectivity in the results achieved the following methods were used complementarily and in combination: multicriteria analysis, multivariate analysis, psychometric scaling and neurofuzzy technology. The data were extracted using an assessment matrix and the results were satisfactory, validating the modeling approach.

Keywords: disruptive innovation, capacity, performance, Industry 4.0

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Authors: Mohamed Ghorab

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Local generated and distributed system for thermal and electrical energy is sighted in the near future to reduce transmission losses instead of the centralized system. Distributed Energy Resources (DER) is designed at different sizes (small and medium) and it is incorporated in energy distribution between the hubs. The energy generated from each technology at each hub should meet the local energy demands. Economic and environmental enhancement can be achieved when there are interaction and energy exchange between the hubs. Network energy system and CO₂ optimization between different six hubs presented Canadian community level are investigated in this study. Three different scenarios of technology systems are studied to meet both thermal and electrical demand loads for the six hubs. The conventional system is used as the first technology system and a reference case study. The conventional system includes boiler to provide the thermal energy, but the electrical energy is imported from the utility grid. The second technology system includes combined heat and power (CHP) system to meet the thermal demand loads and part of the electrical demand load. The third scenario has integration systems of CHP and Organic Rankine Cycle (ORC) where the thermal waste energy from the CHP system is used by ORC to generate electricity. General Algebraic Modeling System (GAMS) is used to model DER system optimization based on energy economics and CO₂ emission analyses. The results are compared with the conventional energy system. The results show that scenarios 2 and 3 provide an annual total cost saving of 21.3% and 32.3 %, respectively compared to the conventional system (scenario 1). Additionally, Scenario 3 (CHP & ORC systems) provides 32.5% saving in CO₂ emission compared to conventional system subsequent case 2 (CHP system) with a value of 9.3%.  

Keywords: distributed energy resources, network energy system, optimization, microgeneration system

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Authors: Fujio Akagi, Hiroaki Ito, Shin-Ichi Inage

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The aim of this study is to develop a combustion model that can be applied uniformly to laminar and turbulent premixed flames while considering the effect of the Lewis number (Le). The model considers the effect of Le on the transport equations of the reaction progress, which varies with the chemical species and temperature. The distribution of the reaction progress variable is approximated by a hyperbolic tangent function, while the other distribution of the reaction progress variable is estimated using the approximated distribution and transport equation of the reaction progress variable considering the Le. The validity of the model was evaluated under the conditions of propane with Le > 1 and methane with Le = 1 (equivalence ratios of 0.5 and 1). The estimated results were found to be in good agreement with those of previous studies under all conditions. A method of introducing a turbulence model into this model is also described. It was confirmed that conventional turbulence models can be expressed as an approximate theory of this model in a unified manner.

Keywords: combustion model, laminar flame, Lewis number, turbulent flame

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Authors: Yang Zhuo

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This study explores the integration of MIDI technology as one of the important digital technologies in music teaching, from the perspective of teaching practice, into the process of cultivating students' teaching skills. At the same time, the framework elements of the learning environment for music education students are divided into four aspects: digital technology supported learning space, new knowledge learning, teaching methods, and teaching evaluation. In teaching activities, more attention should be paid to students' subjectivity and interaction between them so as to enhance their emotional experience in teaching practice simulation. In the process of independent exploration and cooperative interaction, problems should be discovered and solved, and basic knowledge of music and teaching methods should be exercised in practice.

Keywords: music education, educational technology, MIDI, teacher training

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Authors: Kalaashini Ramachandran, Maznah Dahlui, Nik Daliana Nik Farid

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WHO recommends all babies to be exclusively breastfed and donor milk is the next best alternative in the absence of mother’s own milk. The establishment of a human milk bank (HMB) is still being debated due to religious concerns in Malaysia leading to informal milk sharing practices, but little is known on the knowledge, attitude and perception of women towards HMB and its benefits. This study hypothesizes that there is no association between knowledge and attitude and the acceptance towards the establishment of human milk bank among Malaysian women and healthcare providers. The aim of this study is to determine the drivers and barriers among Malaysian towards the acceptance of an HMB. A cross-sectional study with 367 participants was enrolled within a period of 3 months to answer an online self-administered questionnaire. Data on sociodemographic, knowledge on breastfeeding benefits, knowledge and attitude on HMB and its specific issues were analyzed in terms of frequency and then proceed to multiple logistic regression. Majority of the respondents are of Islamis religion (73.3%), have succeesfully completed their tertiary education (82.8%), and are employed (70.8%). Only 55.9% of respondents have heard of an HMB stating internet as their main source of information but a higher prevalence is agreeable to the establishment of a human milk bank (67.8%). Most respondents have a good score on knowledge of breastfeeding benefits and on HMB specific issues (70% and 54.2% respectively) while 63.8% of them have a positive attitude towards HMB. In the multivariate analysis, mothers with a good score on general knowledge of breastfeeding (AOR: 1.715) were more likely to accept the establishment of an HMB while Islamic religion was negatively associated with its establishment (AOR:0.113). This study has found a high prevalence rate of mothers who are willing to accept the establishment of an HMB. This action can be potentially shaped by educating mothers on the benefits of breastfeeding as well as addressing their religious concerns so the establishment of a religiously abiding HMB in Malaysia may be accepted without compromising their belief or the health benefit of donor milk.

Keywords: acceptability, attitude, human milk bank, knowledge

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Authors: S. W. Chen, W. K. Lin, J. R. Wang, C. Shih, H. T. Lin, H. C. Chang, W. Y. Li

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Kuosheng nuclear power plant (NPP) is a BWR/6 type NPP and located on the northern coast of Taiwan. First, Kuosheng NPP TRACE model were developed in this research. In order to assess the system response of Kuosheng NPP TRACE model, startup tests data were used to evaluate Kuosheng NPP TRACE model. Second, the over pressurization transient analysis of Kuosheng NPP TRACE model was performed. Besides, in order to confirm the mechanical property and integrity of fuel rods, FRAPTRAN analysis was also performed in this study.

Keywords: TRACE, safety analysis, BWR/6, FRAPTRA

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Authors: Tatsanawalai Utarasakul, Ch. Hirannukhrao

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The purpose of this research was to investigate the appropriate guidelines for promoting manuscript publication of the academic staff in Faculty of Science and Technology, Suan Sunandha Rajabhat University (SciSSRU). Data were collected from 88 academic staff of SciSSRU. The qualitative approach and knowledge management were used to determine the guidelines for promoting manuscript publication. In addition, TUNA Model was applied in order to follow the process of knowledge management. Simplified techniques were presented and shared with academic staff in the Knowledge Management exhibition, brochure, and websites. The result of this study revealed that, the comparison of number of manuscript publication of academic staff between academic year 2012 and 2013 is rapidly increasing for 60 percentages.

Keywords: knowledge management, articles, publication, academic staff

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Authors: Mohammadali Abedini Sanigy, Jiangang Fei

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In this paper, a mathematical optimization model was developed to maximize the profit in a vegetable production planning problem. It serves as a decision support system that assists farmers in land allocation to crops and harvest scheduling decisions. The developed model can handle different rotation rules in two consecutive cycles of production, which is a common practice in organic production system. Moreover, different production methods of the same crop were considered in the model formulation. The main strength of the model is that it is not restricted to predetermined production periods, which makes the planning more flexible. The model is classified as a mixed integer programming (MIP) model and formulated in PYOMO -a Python package to formulate optimization models- and solved via Gurobi and CPLEX optimizer packages. The model was tested with secondary data from 'Australian vegetable growing farms', and the results were obtained and discussed with the computational test runs. The results show that the model can successfully provide reliable solutions for real size problems.

Keywords: crop rotation, harvesting, mathematical model formulation, vegetable production

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Authors: Shahzad Hassan, Kamran Saeed

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People are always in search of Wi-Fi hotspots because Internet is a major demand nowadays. But like all other technologies, there is still room for improvement in the Wi-Fi technology with regards to the speed and quality of connectivity. In order to address these aspects, Harald Haas, a professor at the University of Edinburgh, proposed what we know as the Li-Fi (Light Fidelity). Li-Fi is a new technology in the field of wireless communication to provide connectivity within a network environment. It is a two-way mode of wireless communication using light. Basically, the data is transmitted through Light Emitting Diodes which can vary the intensity of light very fast, even faster than the blink of an eye. From the research and experiments conducted so far, it can be said that Li-Fi can increase the speed and reliability of the transfer of data. This paper pays particular attention on the assessment of the performance of this technology. In other words, it is a 5G technology which uses LED as the medium of data transfer. For coverage within the buildings, Wi-Fi is good but Li-Fi can be considered favorable in situations where large amounts of data are to be transferred in areas with electromagnetic interferences. It brings a lot of data related qualities such as efficiency, security as well as large throughputs to the table of wireless communication. All in all, it can be said that Li-Fi is going to be a future phenomenon where the presence of light will mean access to the Internet as well as speedy data transfer.

Keywords: communication, LED, Li-Fi, Wi-Fi

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Authors: Shashi Sharma, V. K. Katiyar, Uaday Singh

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The ability to manipulate magnetic particles in fluid flows by means of inhomogeneous magnetic fields is used in a wide range of biomedical applications including magnetic drug targeting (MDT). In MDT, magnetic carrier particles bounded with drug molecules are injected into the vascular system up-stream from the malignant tissue and attracted or retained at the specific region in the body with the help of an external magnetic field. Although the concept of MDT has been around for many years, however, wide spread acceptance of the technique is still looming despite the fact that it has shown some promise in both in vivo and clinical studies. This is because traditional MDT has some inherent limitations. Typically, the magnetic force is not very strong and it is also very short ranged. Since the magnetic force must overcome rather large hydrodynamic forces in the body, MDT applications have been limited to sites located close to the surface of the skin. Even in this most favorable situation, studies have shown that it is difficult to collect appreciable amounts of the MDCPs at the target site. To overcome these limitations of the traditional MDT approach, Ritter and co-workers reported the implant assisted magnetic drug targeting (IA-MDT). In IA-MDT, the magnetic implants are placed strategically at the target site to greatly and locally increase the magnetic force on MDCPs and help to attract and retain the MDCPs at the targeted region. In the present work, we develop a mathematical model to study the capturing of magnetic nanoparticles flowing in a fluid in an implant assisted cylindrical channel under the magnetic field. A coil of ferromagnetic SS 430 has been implanted inside the cylindrical channel to enhance the capturing of magnetic nanoparticles under the magnetic field. The dominant magnetic and drag forces, which significantly affect the capturing of nanoparticles, are incorporated in the model. It is observed through model results that capture efficiency increases from 23 to 51 % as we increase the magnetic field from 0.1 to 0.5 T, respectively. The increase in capture efficiency by increase in magnetic field is because as the magnetic field increases, the magnetization force, which is attractive in nature and responsible to attract or capture the magnetic particles, increases and results the capturing of large number of magnetic particles due to high strength of attractive magnetic force.

Keywords: capture efficiency, implant assisted-magnetic drug targeting (IA-MDT), magnetic nanoparticles, modelling

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Authors: Mario Gianni, Manuel A. Ruiz Garcia, Fiora Pirri

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In this work, we present a Bayesian non-parametric approach to model the motion control of ATVs. The motion control model is based on a Dirichlet Process-Gaussian Process (DP-GP) mixture model. The DP-GP mixture model provides a flexible representation of patterns of control manoeuvres along trajectories of different lengths and discretizations. The model also estimates the number of patterns, sufficient for modeling the dynamics of the ATV.

Keywords: Dirichlet processes, gaussian mixture models, learning motion patterns, tracked robots for urban search and rescue

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Authors: Farhad Salek, Shahaboddin Resalati

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The production of electric vehicles (EVs) featuring lithium-ion battery technology has substantially escalated over the past decade, demonstrating a steady and persistent upward trajectory. The imminent retirement of electric vehicle (EV) batteries after approximately eight years underscores the critical need for their redirection towards recycling, a task complicated by the current inadequacy of recycling infrastructures globally. A potential solution for such concerns involves extending the operational lifespan of electric vehicle (EV) batteries through their utilization in stationary energy storage systems during secondary applications. Such adoptions, however, require addressing the safety concerns associated with batteries’ knee points and thermal runaways. This paper develops an accurate mathematical model representative of the second-life battery packs from a cell-to-pack scale using an equivalent circuit model (ECM) methodology. Neural network algorithms are employed to forecast the degradation parameters based on the EV batteries' aging history to develop a degradation model. The degradation model is integrated with the ECM to reflect the impacts of the cycle aging mechanism on battery parameters during operation. The developed model is tested under real-life load profiles to evaluate the life span of the batteries in various operating conditions. The methodology and the algorithms introduced in this paper can be considered the basis for Battery Management System (BMS) design and techno-economic analysis of such technologies.

Keywords: second life battery, electric vehicles, degradation, neural network

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Authors: Thammanoon Charmjuree, Yuosre F. Badir, Umar Safdar

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There is a consensus among innovation scholars that knowledge is a vital antecedent for firm’s innovation; e.g., process innovation. Recently, there has been an increasing amount of attention to more open approaches to innovation. This open model emphasizes the use of purposive flows of knowledge across the organization boundaries. Firms adopt open innovation strategy to improve their innovation performance by bringing knowledge into the organization (inbound open innovation) to accelerate internal innovation or transferring knowledge outside (outbound open innovation) to expand the markets for external use of innovation. Reviewing open innovation research reveals the following. First, the majority of existing studies have focused on inbound open innovation and less on outbound open innovation. Second, limited research has considered the possible interaction between both and how this interaction may impact the firm’s innovation performance. Third, scholars have focused mainly on the impact of open innovation strategy on product innovation and less on process innovation. Therefore, our knowledge of the relationship between firms’ inbound and outbound open innovation and how these two impact process innovation is still limited. This study focuses on the firm’s external technology acquisition (ETA) and external technology exploitation (ETE) and the firm’s process innovation performance. The ETA represents inbound openness in which firms rely on the acquisition and absorption of external technologies to complement their technology portfolios. The ETE, on the other hand, refers to commercializing technology assets exclusively or in addition to their internal application. This study hypothesized that both ETA and ETE have a positive relationship with process innovation performance and that ETE fully mediates the relationship between ETA and process innovation performance, i.e., ETA has a positive impact on ETE, and turn, ETE has a positive impact on process innovation performance. This study empirically explored these hypotheses in software development firms in Thailand. These firms were randomly selected from a list of Software firms registered with the Department of Business Development, Ministry of Commerce of Thailand. The questionnaires were sent to 1689 firms. After follow-ups and periodic reminders, we obtained 329 (19.48%) completed usable questionnaires. The structure question modeling (SEM) has been used to analyze the data. An analysis of the outcome of 329 firms provides support for our three hypotheses: First, the firm’s ETA has a positive impact on its process innovation performance. Second, the firm’s ETA has a positive impact its ETE. Third, the firm’s ETE fully mediates the relationship between the firm’s ETA and its process innovation performance. This study fills up the gap in open innovation literature by examining the relationship between inbound (ETA) and outbound (ETE) open innovation and suggest that in order to benefits from the promises of openness, firms must engage in both. The study went one step further by explaining the mechanism through which ETA influence process innovation performance.

Keywords: process innovation performance, external technology acquisition, external technology exploitation, open innovation

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Authors: Rohini Hariharan, Yazhini R., Blessy Maria Mathew

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The task of detecting email spam is a very important one in the era of digital technology that needs effective ways of curbing unwanted messages. This paper presents an approach aimed at making email spam categorization algorithms transparent, reliable and more trustworthy by incorporating Local Interpretable Model-agnostic Explanations (LIME). Our technique assists in providing interpretable explanations for specific classifications of emails to help users understand the decision-making process by the model. In this study, we developed a complete pipeline that incorporates LIME into the spam classification framework and allows creating simplified, interpretable models tailored to individual emails. LIME identifies influential terms, pointing out key elements that drive classification results, thus reducing opacity inherent in conventional machine learning models. Additionally, we suggest a visualization scheme for displaying keywords that will improve understanding of categorization decisions by users. We test our method on a diverse email dataset and compare its performance with various baseline models, such as Gaussian Naive Bayes, Multinomial Naive Bayes, Bernoulli Naive Bayes, Support Vector Classifier, K-Nearest Neighbors, Decision Tree, and Logistic Regression. Our testing results show that our model surpasses all other models, achieving an accuracy of 96.59% and a precision of 99.12%.

Keywords: text classification, LIME (local interpretable model-agnostic explanations), stemming, tokenization, logistic regression.

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Authors: H. Al-Hajeri

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The computation of the effectiveness of turbulence enhancement surface features, such as ribs as means of promoting mixing and hence heat transfer, has attracted the continued attention of the engineering community. In this study, the simulation of a three-dimensional cooling passage is carried out employing a number of turbulence models including Durbin model. The cooling passage consists of a square section duct whose upper and lower surfaces feature staggered cuboid ribs. The main objective of this paper is to provide comparisons of the performance of the v2-f model against other established turbulence models as implemented in the commercial CFD code Ansys Fluent. The present study demonstrates that the v2-f model can successfully capture the isothermal air flow phenomena in flow over obstacles.

Keywords: CFD, cooling passage, Durbin model, turbulence model

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Authors: Fahd Sabry Esmail, M. Badr Senousy, Mohamed Ragaie

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In recent years, there has been an explosion in the rate of using technology that help discovering the diseases. For example, DNA microarrays allow us for the first time to obtain a "global" view of the cell. It has great potential to provide accurate medical diagnosis, to help in finding the right treatment and cure for many diseases. Various classification algorithms can be applied on such micro-array datasets to devise methods that can predict the occurrence of Leukemia disease. In this study, we compared the classification accuracy and response time among eleven decision tree methods and six rule classifier methods using five performance criteria. The experiment results show that the performance of Random Tree is producing better result. Also it takes lowest time to build model in tree classifier. The classification rules algorithms such as nearest- neighbor-like algorithm (NNge) is the best algorithm due to the high accuracy and it takes lowest time to build model in classification.

Keywords: data mining, classification techniques, decision tree, classification rule, leukemia diseases, microarray data

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Authors: Vani Singhal, Jitendra Parmar, Satyendra Singh Chouhan

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Unseen class discovery has now become an important part of a machine-learning algorithm to judge new classes. Unseen classes are the classes on which the machine learning model is not trained on. With the advancement in technology and AI replacing humans, the amount of data has increased to the next level. So while implementing a model on real-world examples, we come across unseen new classes. Our aim is to find the number of unseen classes by using a hierarchical-based active learning algorithm. The algorithm is based on hierarchical clustering as well as active sampling. The number of clusters that we will get in the end will give the number of unseen classes. The total clusters will also contain some clusters that have unseen classes. Instead of first discovering unseen classes and then finding their number, we directly calculated the number by applying the algorithm. The dataset used is for intent classification. The target data is the intent of the corresponding query. We conclude that when the machine learning model will encounter real-world data, it will automatically find the number of unseen classes. In the future, our next work would be to label these unseen classes correctly.

Keywords: active sampling, hierarchical clustering, open world learning, unseen class discovery

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Authors: Tero Huhtala, Minna Pikkarainen, Saila Saraniemi

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Information technology has long been used as an enabler of exchange for goods and services. Services are evolving from generic to personalized, and the reverse use of customer data has been discussed in both academia and industry for the past few years. This article presents the results of an empirical case study in the area of preventive health care services. The primary data were gathered in workshops, in which future personal data-based services were conceptualized by analyzing future scenarios from a business perspective. The aim of this study is to understand business model transformation in emerging personal data ecosystems. The work was done as a case study in the context of occupational healthcare. The results have implications to theory and practice, indicating that adopting personal data management principles requires transformation of the business model, which, if successfully managed, may provide access to more resources, potential to offer better value, and additional customer channels. These advantages correlate with the broadening of the business ecosystem. Expanding the scope of this study to include more actors would improve the validity of the research. The results draw from existing literature and are based on findings from a case study and the economic properties of the healthcare industry in Finland.

Keywords: ecosystem, business model, personal data, preventive healthcare

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Authors: Keyi Wang

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Similar to the touchscreen, hand gesture based human-computer interaction (HCI) is a technology that could allow people to perform a variety of tasks faster and more conveniently. This paper proposes a training method of an image-based hand gesture image and video clip recognition system using a CNN (Convolutional Neural Network) with a dataset. A dataset containing 6 hand gesture images is used to train a 2D CNN model. ~98% accuracy is achieved. Furthermore, a 3D CNN model is trained on a dataset containing 4 hand gesture video clips resulting in ~83% accuracy. It is demonstrated that a Cozmo robot loaded with pre-trained models is able to recognize static and dynamic hand gestures.

Keywords: deep learning, hand gesture recognition, computer vision, image processing

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Authors: Maba Boniface Matadi

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This paper analyses the model of Malaria endemic from the point of view of the group theoretic approach. The study identified new independent variables that lead to the transformation of the nonlinear model. Furthermore, corresponding determining equations were constructed, and new symmetries were found. As a result, the findings of the study demonstrate of the integrability of the model to present an invariant solution for the Malaria model.

Keywords: group theory, lie symmetry, invariant solutions, malaria

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Authors: Javier López

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This Paper presents the evaluation model designed for the virtual education branch of The “Universidad Manuela Beltrán, Bogotá-Colombia”. This was the result of a research, developed as a case study, which had three stages: Document review, observation, and a perception survey for teachers. In the present model, the evaluation is a cross-cutting issue to the educational process. Therefore, it consists in a group of actions and guidelines which lead to analyze the student’s learning process from the admission, during the academic training, and to the graduation. This model contributes to the evaluation components which might interest other educational institutions or might offer methodological guidance to consolidate an own model

Keywords: model, evaluation, virtual education, learning process

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Authors: Shuo Tian, Xuepiao Bai, Jianqin Shang, Pengtao Gai, Yuansong Zeng

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Shot peen forming is an essential forming process for aircraft metal wing panel. With the development of computer simulation technology, scholars have proposed a numerical simulation method of shot peen forming based on stress field. Three shot peen forming indexes of crater diameter, shot speed and surface coverage are required as simulation parameters in the stress field method. It is necessary to establish the relationship between simulation and experimental process parameters in order to simulate the deformation under different shot peen forming parameters. The shot peen forming tests of the 2024-T351 aluminum alloy workpieces were carried out using uniform test design method, and three factors of air pressure, feed rate and shot flow were selected. The second-order response surface model between simulation parameters and uniform test factors was established by stepwise regression method using MATLAB software according to the results. The response surface model was combined with the stress field method to simulate the shot peen forming deformation of the workpiece. Compared with the experimental results, the simulated values were smaller than the corresponding test values, the maximum and average errors were 14.8% and 9%, respectively.

Keywords: shot peen forming, process parameter, response surface model, numerical simulation

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Authors: Seyedeh Fatemeh Nabavi, Hamid Dalir, Anooshiravan Farshidianfar

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Laser welding is pivotal in modern manufacturing, offering unmatched precision, speed, and efficiency. Its versatility in minimizing heat-affected zones, seamlessly joining dissimilar materials, and working with various metals makes it indispensable for crafting intricate automotive components. Integration into automated systems ensures consistent delivery of high-quality welds, thereby enhancing overall production efficiency. Noteworthy are the safety benefits of laser welding, including reduced fumes and consumable materials, which align with industry standards and environmental sustainability goals. As the automotive sector increasingly demands advanced materials and stringent safety and quality standards, laser welding emerges as a cornerstone technology. A comprehensive model encompassing thermal dynamic and characteristics models accurately predicts geometrical, metallurgical, and mechanical aspects of the laser beam welding process. Notably, Model 2 showcases exceptional accuracy, achieving remarkably low error rates in predicting primary and secondary dendrite arm spacing (PDAS and SDAS). These findings underscore the model's reliability and effectiveness, providing invaluable insights and predictive capabilities crucial for optimizing welding processes and ensuring superior productivity, efficiency, and quality in the automotive industry.

Keywords: laser welding process, geometrical characteristics, mechanical characteristics, metallurgical characteristics, comprehensive model, thermal dynamic

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Authors: Mian Huang, Chi Ma, Junyu Lin, William Lu

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Introduction: Bone health attracts more attention recently and an intelligent question and answer (QA) chatbot for osteoporosis is helpful for science popularization. With Generative Pretrained Transformer (GPT) technology developing, we build an osteoporosis corpus dataset and then fine-tune LLaMA, a famous open-source GPT foundation large language model(LLM), on our self-constructed osteoporosis corpus. Evaluated by clinical orthopedic experts, our fine-tuned model outperforms vanilla LLaMA on osteoporosis QA task in Chinese. Three-dimensional quantitative computed tomography (QCT) measured bone mineral density (BMD) is considered as more accurate than DXA for BMD measurement in recent years. We develop an automatic Phantom-less QCT(PL-QCT) that is more efficient for BMD measurement since no need of an external phantom for calibration. Combined with LLM on osteoporosis, our PL-QCT provides efficient and accurate BMD measurement for our chatbot users. Material and Methods: We build an osteoporosis corpus containing about 30,000 Chinese literatures whose titles are related to osteoporosis. The whole process is done automatically, including crawling literatures in .pdf format, localizing text/figure/table region by layout segmentation algorithm and recognizing text by OCR algorithm. We train our model by continuous pre-training with Low-rank Adaptation (LoRA, rank=10) technology to adapt LLaMA-7B model to osteoporosis domain, whose basic principle is to mask the next word in the text and make the model predict that word. The loss function is defined as cross-entropy between the predicted and ground-truth word. Experiment is implemented on single NVIDIA A800 GPU for 15 days. Our automatic PL-QCT BMD measurement adopt AI-associated region-of-interest (ROI) generation algorithm for localizing vertebrae-parallel cylinder in cancellous bone. Due to no phantom for BMD calibration, we calculate ROI BMD by CT-BMD of personal muscle and fat. Results & Discussion: Clinical orthopaedic experts are invited to design 5 osteoporosis questions in Chinese, evaluating performance of vanilla LLaMA and our fine-tuned model. Our model outperforms LLaMA on over 80% of these questions, understanding ‘Expert Consensus on Osteoporosis’, ‘QCT for osteoporosis diagnosis’ and ‘Effect of age on osteoporosis’. Detailed results are shown in appendix. Future work may be done by training a larger LLM on the whole orthopaedics with more high-quality domain data, or a multi-modal GPT combining and understanding X-ray and medical text for orthopaedic computer-aided-diagnosis. However, GPT model gives unexpected outputs sometimes, such as repetitive text or seemingly normal but wrong answer (called ‘hallucination’). Even though GPT give correct answers, it cannot be considered as valid clinical diagnoses instead of clinical doctors. The PL-QCT BMD system provided by Bone’s QCT(Bone’s Technology(Shenzhen) Limited) achieves 0.1448mg/cm2(spine) and 0.0002 mg/cm2(hip) mean absolute error(MAE) and linear correlation coefficient R2=0.9970(spine) and R2=0.9991(hip)(compared to QCT-Pro(Mindways)) on 155 patients in three-center clinical trial in Guangzhou, China. Conclusion: This study builds a Chinese osteoporosis corpus and develops a fine-tuned and domain-adapted LLM as well as a PL-QCT BMD measurement system. Our fine-tuned GPT model shows better capability than LLaMA model on most testing questions on osteoporosis. Combined with our PL-QCT BMD system, we are looking forward to providing science popularization and early morning screening for potential osteoporotic patients.

Keywords: GPT, phantom-less QCT, large language model, osteoporosis

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Authors: L. R. Valencia Pérez, A. Morita Alexander, Peña A. Juan Manuel, A. Lamadrid Álvarez

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This research shows the reflection and identification of explanatory variables and their relationships between different variables that are involved with educational technology, all of them encompassed in macro-concepts which are: cognitive inequality, economy, food and language; These will give the guideline to have a more detailed knowledge of educational systems, the communication and equipment, the physical space and the teachers; All of them interacting with each other give rise to what is called educational technology management. These elements contribute to have a very specific knowledge of the equipment of communications, networks and computer equipment, systems and content repositories. This is intended to establish the importance of knowing a global environment in the transfer of knowledge in poor countries, so that it does not diminish the capacity to be authentic and preserve their cultures, their languages or dialects, their hierarchies and real needs; In short, to respect the customs of different towns, villages or cities that are intended to be reached through the use of internationally agreed professional educational technologies. The methodology used in this research is the analytical - descriptive, which allows to explain each of the variables, which in our opinion must be taken into account, in order to achieve an optimal incorporation of the educational technology in a model that gives results in a medium term. The idea is that in an encompassing way the concepts will be integrated to others with greater coverage until reaching macro concepts that are of national coverage in the countries and that are elements of conciliation in the different federal and international reforms. At the center of the model is the educational technology which is directly related to the concepts that are contained in factors such as the educational system, communication and equipment, spaces and teachers, which are globally immersed in macro concepts Cognitive inequality, economics, food and language. One of the major contributions of this article is to leave this idea under an algorithm that allows to be as unbiased as possible when evaluating this indicator, since other indicators that are to be taken from international preference entities like the OECD in the area of education systems studied, so that they are not influenced by particular political or interest pressures. This work opens the way for a relationship between involved entities, both conceptual, procedural and human activity, to clearly identify the convergence of their impact on the problem of education and how the relationship can contribute to an improvement, but also shows possibilities of being able to reach a comprehensive education reform for all.

Keywords: relationships macro-concepts, cognitive inequality, economics, alimentation and language

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Authors: Mingook Lee, Sungjoo Lee

Abstract:

As technology-based service industries grow drastically worldwide; companies are recognizing the importance of market preoccupancy and have made an effort to capture a large market to gain the upper hand. To this end, a focus on patents can be used to determine the properties of a technology, as well as to capture advantages in technical skills, in comparison with the firm’s competitors. However, technology-based services largely depend not only on their technological value but also their economic value, due to the recognized worth that is passed to a plurality of users. Thus, it is important to determine whether there are any competitors in the target areas and what services they provide in any field. Despite this importance, little effort has been made to systematically benchmark competitors in order to identify business opportunities. Thus, this study aims to not only identify each position of technology-centered service companies in complex market dynamics, but also to discover new business opportunities. For this, we try to consider both technology and market environments simultaneously by utilizing patent data as a representative proxy for technology and trademark dates as an index for a firm’s target goods and services. Theoretically, this is one of the earliest attempts to combine patent data and trademark data to analyze corporate strategies. In practice, the research results are expected to be used as a decision criterion to diagnose the economic value that companies can obtain by entering the market, as well as the technological value to be passed onto their customers. Thus, the proposed approach can be useful to support effective technology and business strategies in a firm.

Keywords: business opportunity, patent, Portfolio analysis, trademark

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Authors: Peter Winzer, Erik Massarczyk

Abstract:

Experts, enterprises and operators expect that the bandwidth request will increase up to rates of 100 to 1,000 Mbps within several years. Therefore the most important question is, which technology shall satisfy the future consumer broadband demands. Currently the consensus is, that the fiber technology has the best technical characteristics to achieve such the high bandwidth rates. But fiber technology is so far very cost-intensive and resource consuming. To avoid these investments, operators are concentrating to upgrade the existing copper and hybrid fiber coax infrastructures. This work presents a comparison of the copper and fiber technologies including an overview about the current German broadband market. Both technologies are reviewed in the terms of demand, willingness to pay and economic efficiency in connection with the technical characteristics.

Keywords: broadband customer demand, fiber development, g.fast, vectoring, willingness to pay for broadband services

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Authors: Sofia N. Gonçalves, Duarte M. S. Albuquerque, José C. F. Pereira

Abstract:

The energy transition is spurred by structural changes in energy demand, supply, and prices. Microwave technology was first proposed as a faster alternative for cooking food. It was found that food heated instantly when interacting with high-frequency electromagnetic waves. The dielectric properties account for a material’s ability to absorb electromagnetic energy and dissipate this energy in the form of heat. Many energy-intense industries could benefit from electromagnetic heating since many of the raw materials are dielectric at high temperatures. Limestone sedimentary rock is a dielectric material intensively used in the cement industry to produce unslaked lime. A numerical 3D model was implemented in COMSOL Multiphysics to study the limestone continuous processing under microwave heating. The model solves the two-way coupling between the Energy equation and Maxwell’s equations as well as the coupling between heat transfer and chemical interfaces. Complementary, a controller was implemented to optimize the overall heating efficiency and control the numerical model stability. This was done by continuously matching the cavity impedance and predicting the required energy for the system, avoiding energy inefficiencies. This controller was developed in MATLAB and successfully fulfilled all these goals. The limestone load influence on thermal decomposition and overall process efficiency was the main object of this study. The procedure considered the Verification and Validation of the chemical kinetics model separately from the coupled model. The chemical model was found to correctly describe the chosen kinetic equation, and the coupled model successfully solved the equations describing the numerical model. The interaction between flow of material and electric field Poynting vector revealed to influence limestone decomposition, as a result from the low dielectric properties of limestone. The numerical model considered this effect and took advantage from this interaction. The model was demonstrated to be highly unstable when solving non-linear temperature distributions. Limestone has a dielectric loss response that increases with temperature and has low thermal conductivity. For this reason, limestone is prone to produce thermal runaway under electromagnetic heating, as well as numerical model instabilities. Five different scenarios were tested by considering a material fill ratio of 30%, 50%, 65%, 80%, and 100%. Simulating the tube rotation for mixing enhancement was proven to be beneficial and crucial for all loads considered. When uniform temperature distribution is accomplished, the electromagnetic field and material interaction is facilitated. The results pointed out the inefficient development of the electric field within the bed for 30% fill ratio. The thermal efficiency showed the propensity to stabilize around 90%for loads higher than 50%. The process accomplished a maximum microwave efficiency of 75% for the 80% fill ratio, sustaining that the tube has an optimal fill of material. Electric field peak detachment was observed for the case with 100% fill ratio, justifying the lower efficiencies compared to 80%. Microwave technology has been demonstrated to be an important ally for the decarbonization of the cement industry.

Keywords: CFD numerical simulations, efficiency optimization, electromagnetic heating, impedance matching, limestone continuous processing

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Authors: Elaheh Ezami, Behzad Mohammadian, Elham Aznab

Abstract:

Health service design will need to change due to bringing in new digital health tools. This highlights the importance of innovation in adopting Health Information Technology (HIT). It can be argued that innovation in the health sector correlates with entrepreneurship. Various reasons exist for health entrepreneurs to advocate increased investment in HIT to compensate for shortcomings in the health sector and improve the quality of healthcare. Furthermore, every innovative program presents challenges and motivations for entrepreneurs that may distract or encourage the adoption of technology. Our study used a systematic literature review to identify relevant articles that defined the frustrations and promotions of using health information technology in organizations or enterprises. A meta-analysis of the articles was conducted to identify the factors driving or pulling entrepreneurs to use HIT.

Keywords: health information technology, health entrepreneurship, health enterprise, health entrepreneurs' innovation

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Authors: Jamie Sundvall, Lisa Jennings

Abstract:

Site based field internship learning (SBL) is an educational approach within a Master’s of Social Work (MSW) university field placement department that promotes a more streamlined approach to the integration of theory and evidence based practices for social work students. The SBL model is founded on research in the field, consideration of current work force needs, United States national trends of MSW graduate skill and knowledge deficits, educational trends in students pursing a master’s degree in social work, and current social problems that require unique problem solving skills. This study explores the use of site-based learning in a hybrid social work program. In this setting, site based learning pairs online education courses and social work field education to create training opportunities for social work students within their own community and cultural context. Students engage in coursework in an online setting with both synchronous and asynchronous features that facilitate development of core competencies for MSW students. Through the SBL model, students are then partnered with faculty in a virtual course room and a university vetted site within their community. The study explores how this model of learning creates community partnerships, through which students engage in a learning loop to develop social work skills, while preparing students to address current community, social, and global issues with the engagement of technology. The goal of SBL is to more effectively equip social work students for practice according to current workforce demands, provide access to education and care to populations who have limited access, and create self-sustainable partnerships. Further, the model helps students learn integration of evidence based practices and helps instructors more effectively teach integration of ethics into practice. The study found that the SBL model increases the influence and professional relevance of the social work profession, and ultimately facilitates stronger approaches to integrating theory into practice. Current implementation of the practice in the United States will be presented in the study. dditionally, future research conceptualization of SBL models will be presented, in order to collaborate on advancing best approaches of translating theory into practice, according to the current needs of the profession and needs of social work students.

Keywords: collaboration, fieldwork, research, site-based learning, technology

Procedia PDF Downloads 122