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The Influence of Applying Digital Toolkits to Assist 3D Software Development on Individual Work Performance and Perceived Stress 10

The Influence of Applying Digital Toolkits to Assist 3D Soft...

引用

10th International Conference on Applied System Innovation, ICASI 2024

作者： Wu, Wen-Chuan Lee, Ming-Han National Ilan University Dep. of Computer Science and Information Engineering Yilan City Taiwan National Ilan University Master Program of E-Learning for Multimedia and Network Communications Yilan City Taiwan

ISBN: (纸本)9798350394924

Digital content industry, encompassing areas such as digital games, computer animation, digital audio-visual applications, and digital art, plays a pivotal role in today's and future developmental trends. Maya 3D software stands out as a crucial development tool in these domains. However, the multitude of built-in tools in Maya 3D can lead to overly complex interfaces, impacting development efficiency for software developers. To address this issue, this paper designs a digital toolkit for Maya 3D software, presented in a Menu Bar format. This toolkit offers features like naming, sorting, categorization, and automatic saving to JSON files for future use. Through a crossover experimental design, this paper investigates the impact of this proposed toolkit on 3D software developers' individual work performance, work engagement, and stress perception. Results shows a significant positive influence of that toolkit on software developers, particularly in enhancing work performance. It means that the proposed digital toolkit effectively improves the performance of software developers' work and reduces their stress during the software development process. © 2024 IEEE.

关键词： Digital devices

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Revolutionizing Neurological Diagnostics: Integrating 6G Technology with Deep Learning for Enhanced Detection of Multiple Sclerosis and Myelitis

Revolutionizing Neurological Diagnostics: Integrating 6G Tec...

引用

2024 International Telecommunications Conference, ITC-Egypt 2024

作者： Noureldeen, Rana M. Elshshtawy, Rahma A. Elgohary, Omnia A. Wahba, Fatma Alzahraa A. Attia, Marco K. Abo Elazm, Zeinab B. Khattap, Mohamed G. Galal Eldeen Mohamed Ali Hassan, Hend Mostafa, Mariam Ibrahim, Nayra Ramadan, Reem Refaat, Yomna Khaled, Mennatallah Maher, Ali Abd Elaziz, Mohamed Gamal Abdellatif Ibrahim, Ahmed Faculty of Applied Health Sciences Galala University Suez435611 Egypt Faculty of Computer Science and Engineering Galala University Suez435611 Egypt Artificial Intelligence Science Program Faculty of Computer Science and Engineering Galala University Suez435611 Egypt Air Defense College Department of Electronics and Electrical Communications Engineering Alexandria Egypt

ISBN: (纸本)9798350351408

This paper proposes an alternative detection frame-work for multiple sclerosis (MS) and idiopathic acute transverse myelitis (ATM) within the 6G-enabled Internet of Medical Things (IoMT) environment. The developed framework relies on the implementation of a deep learning technique known as Dense Convolutional Networks (DenseNets) in the 6G-enabled IoMT to enhance prediction performance. To validate the performance of DenseNets, we compared it with other deep learning techniques, including Convolutional Neural Networks (CNN) and MobileNet, using real-world datasets. The experimental results show the high performance of DenseNets in predicting MS and ATM compared to other methods, achieving an accuracy of nearly 90 %. © 2024 IEEE.

关键词： Convolutional neural networks

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Comparative Assessment of Off-shore Wind Converters and Wave Energy Converters in the Philippines 15

Comparative Assessment of Off-shore Wind Converters and Wave...

引用

15th IEEE International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management, HNICEM 2023

作者： Alquiza, Laurence Keith P. Recto, King Harold A. Loresco, Pocholo James M. Villalobos, Jesus Ateneo de Manila University Department of Electronics Computer and Communications Engineering Quezon City Philippines Feu Institute of Technology Department of Electronics Engineering Manila Philippines Institut Catholique d'Arts et Métiers International Program in General Engineering Toulouse France

ISBN: (纸本)9798350381177

The Republic of the Philippines is confronted with rebuilding its energy landscape, which now depends heavily on imported fossil fuels for a substantial supply. The Department of Energy (DOE) has established lofty objectives to enhance the nation's renewable energy (RE) capability;nevertheless, these objectives are still to be achieved. This research supports DOE's goals by studying other possible renewable energy sources. In particular, the primary aim of this research is to examine the viability of Offshore Wind Converters (OWCs) and Wave Energy Converters (WECs) as viable sustainable energy options for the Philippines. Ocean wave converters (OWCs) provide inherent benefits in terms of dependability and have widespread societal acceptance. Conversely, wave energy converters (WECs) harness the vast energy potential contained within ocean waves. A comparative evaluation was undertaken to analyze the differences between these two potential renewable energy sources. The assessment concludes that OWCs possess a minor advantage over WECs regarding their economic viability and higher societal acceptability. It recommended that the government adopts a diversified energy portfolio, which may include the incorporation of WECs to effectively navigate the changing dynamics of the energy sector, enhance sustainability, and ensure the long-term security of the nation's energy supply. © 2023 IEEE.

关键词： Water waves

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SoC-Oriented Implementation of Machine Learning Based Breast Cancer Classification Algorithm 12

SoC-Oriented Implementation of Machine Learning Based Breast...

引用

12th Mediterranean Conference on Embedded Computing, MECO 2023

作者： Saeed, Abdelrahman Tawfik, Ayman Mostafa, Hassan Khalil, Ahmed Hussein Cairo University Electronics and Communications Engineering Department Giza12613 Egypt Ajman University Department of Electrical and Computer Engineering United Arab Emirates University of Science and Technology Nanotechnology and Nanoelectronics Program Zewail City of Science and Technology Giza Egypt

ISBN: (纸本)9798350322910

Convolutional Neural Networks (CNN) have drawn the attention of researchers in the medical imaging field. Many researchers have exploited CNN for breast cancer detection. This study provides an Internet of Things (IoT) friendly implementation of CNN for breast cancer detection. To achieve faster time to Market, Deep-learning Processing Unit (DPU) on Field programmable Gate Array (FPGA) is adopted for the CNN hardware implementation. CNN inference on the proposed system achieves a 1.6x speed-up factor and 91.5% reduction in energy consumption compared to the conventional general-purpose multi-core Central Processing Unit (CPU). © 2023 IEEE.

关键词： Convolutional neural networks

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Analysis of Negative Capacitance MOSFETs Characteristic with Spacer

Analysis of Negative Capacitance MOSFETs Characteristic with...

引用

2020 International Symposium on VLSI Technology, Systems and Applications, VLSI-TSA 2020

作者： Lee, Yu-Chun Kola, Sekhar Reddy Chen, Chieh-Yang Chuang, Min-Hui Li, Yiming Parallel and Scientific Computing Laboratory Institute of Biomedical Engineering Institute of Communications Engineering Eecs International Graduate Program Department of Electrical and Computer Engineering Center for MmWave Smart Radar System and Technologies National Chiao Tung University 1001 Ta-Hsueh Rd Hsinchu300 Taiwan

ISBN: (纸本)9781728142326

In this work, our study comprises of design and investigation on negative capacitance (NC), metal-oxide-semiconductor (MOS) field effects transistors (MOSFETs) with spacer and source/drain (S/D) overlap engineering. The scope of the work is to boost the performance and high-energy efficiency of the studied NC-MOSFETs by using the ferro electric material (FE). The NC-MOSFETs with the spacer technology can achieve the admirable Ion/Ioff ratio and subthreshold swing (SS), compared with planar MOSFETs. It makes device scaling possible by eliminating the short channel effect (SCE). We further estimated the effect of FE thickness and spacer, which are another critical parameter of obtaining better electrical characteristics and reducing SS. © 2020 IEEE.

关键词： Capacitance

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A web-based active learning conceptual framework for innovative business plan creation : ddeveloping new tools for entrepreneurship education 22

A web-based active learning conceptual framework for innovat...

引用

22nd International computer Science and engineering Conference, ICSEC 2018

作者： Phuengpunum, Saravanee Piromsopa, Krerk Songkram, Noawanit Technopreneurship and Innovation Management Program Graduate School Chulalongkorn University Bangkok10330 Thailand Department of Computer Engineering Faculty of Engineering Chulalongkorn University Bangkok10330 Thailand Department of Educational Technology and Communications Faculty of Education Chulalongkorn University Bangkok10330 Thailand

ISBN: (纸本)9781538681640

This research aims to develop a framework for writing a business plan that support innovation for undergraduate students. The scope of this research is circumscribed to undergraduate students in Thailand. In respect of internet technology advancement and the popularity of internet access of teenagers, the researcher employs e-learning instruction media, which is considered a keystone to reduce educational inequalities. The study particularly introduces an established Nanoka's knowledge creation concept, which consists of Socialisation, Externalisation, Combination and Internalisation. In earlier times, this concept has been verified to create the domain of innovation in business organisation. Remarkably, it has been employed in the process of teaching innovative business plans and creativity management. This process specifically incorporates active learning, which turns the passive role of merely listening to active learners. The framework offers three principal contributions: first, to develop a new educational platform that implements active learning into E-Learning styles;second, to develop of an uncommon conceptual framework that adheres to theory reflecting good practices for innovation creation;third, taking this concept into practice, to help the universities build upon core strengths and students' innovation skills. It is the confluence of all contributions that make for a full-fledged entrepreneurial university. © 2018 IEEE.

关键词： E-learning

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Bagging-based active learning model for named entity recognition with distant supervision

Bagging-based active learning model for named entity recogni...

引用

International Conference on Big Data and Smart Computing (BIGCOMP)

作者： Sunghee Lee Yeongkil Song Maengsik Choi Harksoo Kim Program of Computer and Communications Engineering Kangwon National University Chuncheon-si Gangwon-do Korea

Named entity recognition (NER) is a preliminary step to performing information extraction and question answering. Most previous studies on NER have been based on supervised machine learning methods that need a large amount of human-annotated training corpus. In this paper, we propose a semi-supervised NER model to minimize the time-consuming and labor-intensive task for constructing the training corpus. The proposed model generates weakly labeled training corpus using a distant supervision method. Then, it improves NER accuracy by refining the weakly labeled training corpus using a bagging-based active learning method. In the experiments, the proposed model outperformed the previous semi-supervised model. It showed F1-measure of 0.764 after 15 times of bagging-based active learning.

关键词： Training Dictionaries Data models Bagging Biological system modeling Refining Data mining

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Scaling Limitations of Line TFETs at Sub-8-nm Technology Node

Scaling Limitations of Line TFETs at Sub-8-nm Technology Nod...

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2020 International Symposium on VLSI Technology, Systems and Applications, VLSI-TSA 2020

作者： Thoti, Narasimhulu Li, Yiming Kola, Sekhar Reddy Parallel and Scientific Computing Laboratory Eecs International Graduate Program Institute of Communications Engineering Department of Electrical and Computer Engineering Center for MmWave Smart Radar System and Technologies National Chiao Tung University 1001 Ta-Hsueh Rd Hsinchu300 Taiwan

ISBN: (纸本)9781728142326

The scope of the work is to investigate limitations in device scaling by identifying various parameters of short channel effects (SCEs) in current challenging geometries of the line tunnel field effect transistors (TFETs). Key factors of the considered device, such as the doping and the thickness (tn) of n-epitaxial region, and source-to-drain length (LSDeff) scaling cannot be tuned anymore to boost the device characteristics for the sub-8-nm technology node. The main results of this study indicates that the engineering acceptable performance are achieved at a low doping of 5 1018 cm-3, an optimal tn as low (about 0.5 nm), and a LSDeff greater than 12.5 nm. Hence, the line TFETs below sub-8-nm faces serious bottleneck of scaling and cannot be further scaled with the conventional scaling rule at all. © 2020 IEEE.

关键词： Tunnel field effect transistors

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Efficient Automatic External Defibrillator Using the Slope of Hilbert Transformed ECG Signals 11

Efficient Automatic External Defibrillator Using the Slope o...

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11th International Japan-Africa Conference on Electronics, communications, and Computations, JAC-ECC 2023

作者： Elsagheer, Samir A. Sayed, Mohammed S. Hassan, Mohsen A. Egypt-Japan University of Science and Technology Computer Science and Information Technology Alexandria21934 Egypt Aswan Universty Facurlty of Engineering Aswan Egypt Egypt-Japan University of Science and Technology Department of Electronics and Communications Engineering Alexandria21934 Egypt Zagazig University Department of Electronics and Communications Engineering Zagazig Egypt Egypt-Japan University of Science and Technology Materials science and engineering program IDE Alexandria21934 Egypt

ISBN: (纸本)9798350369328

Sudden cardiac arrest (SCA) is a life-threatening condition that demands immediate intervention. The key to survival often lies in the timely and precise analysis of electrocardiogram (ECG) signals to determine the necessity of a shock from an Automatic External Defibrillator (AED). In this paper, we address the critical need for improved accuracy in AED decision-making by presenting a novel approach that leverages the Hilbert Transform to calculate the slope of ECG signals by harnessing the analytical power of Hilbert Transformed ECG signals. By scrutinizing the heart's electrical activity through this method, we aim to enhance the AED's ability to differentiate between cases of ventricular fibrillation and other non-shockable rhythms, ultimately leading to more efficient and effective treatment. Our research explores two distinct approaches for signal analysis and correlates their findings to achieve higher precision in defibrillation decisions. To validate the effectiveness of our approach, we employ a diverse and publicly available dataset containing various heart conditions, allowing us to demonstrate the robustness of our method across a wide spectrum of cases. This study represents a significant advancement in the field of automatic external defibrillation, with the potential to save countless lives through more accurate and timely interventions. © 2023 IEEE.

关键词： Defibrillators

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Enhancing Acute Ischemic Stroke Diagnosis Using IoMT and Deep Learning Technologies

Enhancing Acute Ischemic Stroke Diagnosis Using IoMT and Dee...

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2024 International Telecommunications Conference, ITC-Egypt 2024

作者： El-Sheikh, Mohamed M. Bayoumy, Aya Ahmed, Nada M. Mohamed Eldeeb, Amany Rabea, Fatma I. Nawar, Amira A. Khattap, Mohamed G. Galal Eldeen Mohamed Ali Hassan, Hend Mostafa, Mariam Ibrahim, Nayra Ramadan, Reem Refaat, Yomna Khaled, Mennatallah Maher, Ali Abd Elaziz, Mohamed Gamal Abdellatif Ibrahim, Ahmed Radiology and Medical Imaging Faculty of Applied Health Sciences Galala University Suez435611 Egypt Faculty of Computer Science and Engineering Galala University Suez435611 Egypt Artificial Intelligence Science Program Faculty of Computer Science and Engineering Galala University Suez435611 Egypt Air Defense College Department of Electronics and Electrical Communications Engineering Alexandria Egypt

ISBN: (纸本)9798350351408

This paper introduces an alternative technique for diagnosing Acute Ischemic Stroke within the IoMT environment. In the proposed approach, the collected data is transmitted to a cloud-based center where the technique utilizes EfficientNet, a deep learning model, designed to extract features from MRI images thereby enhancing the detection of acute ischemic infarctions. The performance of EfficientNet is compared against two other models, CNN and MobileNet, demonstrating its superior efficacy through metrics such as accuracy, precision, recall, and F1-score, which stand at 92.31%, 92.28%, 92.33%, and 92.30%, respectively. © 2024 IEEE.

关键词： Contrastive Learning

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