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International Conference on Advanced Learning Technologies (ICALT)

作者： Wildemarkes de Almeida da Silva Luis Carlos Costa Fonseca Sofiane Labidi José Chrystian Lima Pacheco Post-Graduation Program in Computer and Systems Engineering State University of Maranhão - UEMA São Luís Brazil Bachelor of Science and Technology Program -BICT Federal University of Maranhão - UFMA São Luís Brazil Graduation in Computer and Systems Engineering State University of Maranhão - UEMA São Luís Brazil

ISBN: (数字)9798350362053

ISBN: (纸本)9798350362060

The rapid growing application of language models (LLMs) in education offers exciting prospects for personalized learning and interactive experiences. However, a critical challenge emerges - the risk of "hallucinations," where LLMs generate factually incorrect or misleading information. This paper proposes Comparative and Cross-Verification Prompting (CCVP), a novel technique specifically designed to mitigate hallucinations in educational LLMs. CCVP leverages the strengths of multiple LLMs, a Principal Language Model (PLM) and Auxiliary Language Models (ALMs), to verify the accuracy and educational relevance of the PLM's response to a prompt. Through a series of prompts and assessments, CCVP harnesses the diverse perspectives of various LLMs and incorporates human expertise for intricate cases. This method addresses the limitations of relying on a single model and fosters critical thinking skills in learners within the educational context. We detail the CCVP approach with examples specifically applicable to educational settings, such as geography. We also discuss its strengths and limitations, including computational cost, data reliance, and ethical considerations. We highlight its potential applications in educational disciplines, including fact-checking content, detecting bias, and promoting responsible LLM use. CCVP presents a promising avenue for ensuring the accuracy and trustworthiness of LLM-generated educational content. Further research and development will refine its scalability, address potential biases, and solidify its position as a vital tool for harnessing the power of LLMs while fostering responsible knowledge dissemination in education.

关键词： Geography Solid modeling Accuracy Scalability Prevention and mitigation Computational modeling Education

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A Shoe Shopping System based on Convolutional Neural Network Image Recognition

A Shoe Shopping System based on Convolutional Neural Network...

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IEEE Eurasia Conference on IOT, Communication and engineering (ECICE)

作者： Chin-Chih Chang Chi-Hung Wei Chen-Sheng Chen Jian-An Chen Shih-Hsien Yeh Sean Hsiao Department of Computer Science and Information Engineering Chung Hua University Hsinchu Taiwan Ph.D. Program in Engineering Science Chung Hua University Hsinchu Taiwan Department of Computer Science and Information Engineering Chang Gung University Taoyuan Taiwan Bachelor Program in Applied Foreign Language and Smart Commerce Chung Hua University Hsinchu Taiwan

In this article, we present an innovative approach to enhance the online shoe shopping experience. The convolutional neural network (CNN) image recognition technology was used to enhance shoe classification and recommendations. By training the CNN model on an extensive dataset, unique shoe features and styles were learned. Integrated into a user-friendly online platform, the system offers real-time image recognition, allowing users to snap a photo of a desired shoe for instant identification, including brand, price, and availability details. Moreover, the CNN-based recommendation engine provides personalized suggestions based on style, color, and customer preferences, enriching the shopping experience. Evaluation results confirmed the system's feasibility, and user feedback highlighted its effectiveness in simplifying the shopping process and enhancing satisfaction. This innovative system presents a significant leap in merging AI and e-commerce and shows the potential of image recognition to transform online marketplaces, benefiting consumers, offering valuable insights for retailers, and ultimately reshaping the future of online shoe shopping.

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Brain Tumor Detection and Segmentation Using Deep Learning Models 6

Brain Tumor Detection and Segmentation Using Deep Learning M...

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6th World Symposium on Artificial Intelligence, WSAI 2024

作者： Abiodun, Moses Kazeem Adeniyi, Abidemi Emmanuel Awotunde, Joseph Bamidele Aworinde, Halleluyah Tinuoye, George Imoize, Agbotiname Lucky Li, Chun-Ta Lee, Cheng-Chi Landmark University Department of Computer Science Kwara State Omu-Aran Nigeria Bowen University Department of Computer Science Osun State Iwo Nigeria University of Ilorin Department of Computer Science Kwara State Ilorin Nigeria University of Lagos Faculty of Engineering Department of Electrical and Electronics Engineering Akoka Nigeria Fu Jen Catholic University Bachelor's Program of Artificial Intelligence and Information Security New Taipei City Taiwan Fu Jen Catholic University Department of Library and Information Science New Taipei City Taiwan

ISBN: (纸本)9798350374162

This study focuses on brain tumor detection and segmentation using Convolutional Neural Networks (CNN) with architectures of Fully Convolutional Net-work (FCN) and VGG16. The dataset imported for this study consists of brain MRI images, which were preprocessed to improve the overall image resolution. Data augmentation techniques were applied to heighten the variability and volume of the training data. For feature extraction, CNN models were utilized, specifically the VGG16 architectures. This model was trained on a preprocessed dataset to learn the important features associated with the presence of brain tumor. Image segmentation was performed to precisely outline and identify the tumor region within the brain images. FCN architecture was employed for this task, which allowed pixel-level classification of tumor regions. Finally, image classification was carried out to group brain images based on the absence or presence of a tumor. The trained models were evaluated using accuracy, precision, recall and F1score as the performance metrics. The results of the study demonstrated promising outcomes, achieving an accuracy score of 93% and a precision, recall and f1score ranging from 75% to 100% based on the specific type of tumor enlisted. This indicates that the developed CNN models, with the FCN and VGG16 architectures, effectively detect and segment brain tumors from MRI images. The findings of this study contribute to the field of medical image analysis and gives a foundation for further research and development in brain tumor diagnosis and treatment. The study recommends the use of more deep learning algorithms for the process of detecting brain tumors. © 2024 IEEE.

关键词： Convolutional neural networks

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Wave power extraction by a dual OWC chambers over an undulated bottom

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Renewable Energy 2023年第1期216卷

作者： Naik, Nikita Gayathri, R. Behera, H. Tsai, Chia-Cheng Department of Mathematics SRM Institute of Science and Technology Tamil Nadu Kattankulathur603203 India Center of Excellence for Ocean Engineering National Taiwan Ocean University Keelung202301 Taiwan Bachelor Degree Program in Ocean Engineering and Technology National Taiwan Ocean University Keelung202301 Taiwan

The impacts of sloping bottom and slanted impenetrable wall on dual oscillating water columns (OWCs) with a slanted front wall are examined. To tackle the physical model, a coupled eigenfunction expansion — boundary element system is employed. The concept is based on employing the anticipated amplification of scattered and reflected wave fields generated by the existence of sloping walls to enhance the absorption of wave power driven by the walls’ wave reflections. The study concludes that 100% efficiency occurs for smaller incident wave angles. It is also observed that compared with short waves, the efficiency of the device is more in the long-wave region. OWCs are observed to be more effective over the undulating bottom and sloping impermeable wall with an increased spacing between the water columns and the second OWC to the impermeable wall. Additionally, the chambers’ width and the sloping bottom angle are vital parameters for higher power extraction from the OWCs. Furthermore, the optimal values of slope bottom and wall inclination may be employed to build and implement an efficient OWC device. Moreover, the proposed model can also be used as a breakwater to protect the coastline. © 2023 Elsevier Ltd

关键词： Boundary element method

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AI-based Computer-aided System on Long Term Care

AI-based Computer-aided System on Long Term Care

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IEEE International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)

作者： Yi-Jui Huang Hong-Yao Ciou Yuan-Hsun Yang Chin-Yin Lin Chia-Wei Lee Yu-Hsien Chen Computer Science and Information Engineering National Taitung University Taitung Taiwan Computer Science University of Taipei Taitung Taiwan Bachelor’s Degree Program for Indigenous Peoples in Senior Health and Care Management National Taitung University Taitung Taiwan

ISBN: (数字)9798350389210

ISBN: (纸本)9798350389227

According to data from Taiwan’s National Development Council in 2024, Taiwan is expected to enter a super-aged society by 2025, indicating a great acceleration in population aging. With the aging population and the increasing prevalence of chronic diseases, the importance of rehabilitation for the elderly has become crucial. Rehabilitation aims not only to aid in recovering from illness or surgery but also to maintain health in daily life. For the elderly, appropriate rehabilitation exercises can improve physical strength, cardiopulmonary function, and overall quality of life. This not only helps restore physical function but also reduces the occurrence and progression of chronic diseases. The system includes contextual rehabilitation games, general rehabilitation training, accessible remote instruction, and physical fitness assessment. The contextual rehabilitation games utilize gamified interactive designs to enhance engagement and motivation. General rehabilitation training provides standardized guidance on rehabilitation movements. Accessible remote instruction allows patients who are unable to move due to various factors to receive professional guidance in hospitals or care centers, reducing the inconvenience of movement. Finally, physical fitness assessment provides accurate data support for medical personnel, while also reducing manual calculation errors and labor costs. Through this comprehensive assistive system, smart healthcare can not only improve the effectiveness and efficiency of rehabilitation but also provide a new approach for health management and rehabilitation of the elderly, helping to address the challenges brought by an aging society in the future.

关键词： Training Hospitals Surgery Games Manuals Signal processing Health and safety Personnel Older adults Diseases

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Effects of topographical disturbances on flexural wave motion in a viscous fluid

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Physics of Fluids 2024年第3期36卷 037103-037103页

作者： Prasad, Indra Mani Behera, Harekrushna Tsai, Chia-Cheng Hsu, Tai-Wen Department of Mathematics SRM Institute of Science and Technology Tamil Nadu Kattankulathur603203 India Center of Excellence for Ocean Engineering National Taiwan Ocean University Keelung202301 Taiwan Bachelor Degree Program in Ocean Engineering and Technology National Taiwan Ocean University Keelung202301 Taiwan Department of Harbor and River Engineering National Taiwan Ocean University Keelung202301 Taiwan

Main causes of ground disturbances are geological events such as earthquakes, underwater gravity mass flows, volcanic eruptions, and bottom explosions. This paper investigates the effects of transitory ground disturbance on the generation of flexural waves in the presence of a thin floating elastic plate. The problem is formulated using the Stokes stream function and wave potential boundary value problems in a viscous fluid. The expression of the plate deflection is obtained as multiple infinite integrals using the Fourier and Laplace transforms, which is further solved by the steepest descent method. Three types of ground disturbances such as H 0 ( x ) = e ( − x 2 / 2 ) , H 0 ( x ) = e − | x | , and H 0 ( x ) = δ ( x ) are considered. The deflection of the floating elastic plate is investigated in connection to ground disturbances, fluid viscosity, and structural parameters such as mass per unit length of the plate and flexural rigidity. The study reveals that with higher viscosity and flexural rigidity, the amplitude of the plate deflection is reduced. Moreover, these two parameters play a great role in the reduction of plate deflection. © 2024 Author(s).

关键词： Viscous flow

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RF Front-end with Antenna for Bluetooh Wireless of Medical Biosensing 15

RF Front-end with Antenna for Bluetooh Wireless of Medical B...

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15th IEEE International Conference on Anti-Counterfeiting, Security, and Identification, ASID 2021

作者： Lai, Wen-Cheng Wu, Yi National Yunlin University of Science and Technology Bachelor Program in Industrial Projects Taiwan Dept. Electronic Engineering National Yunlm University of Science and Technology Taiwan Fujian Normal Univ. College of Photonic and Electronic Engineering China

ISBN: (纸本)9781665440080

The proposed article introduces RF wireless integrated transceiver for Bluetooth wireless of medical biosensing applications. The proposed wireless integrated transceiver consists of two-stage power amplifier (PA) with predistorter, band-pass Gm-C filter, distributed single-pole double-throw (SPDT) radio frequency (RF) switching, low noise amplifier (LNA) and chip antenna. The presented PA design presents conversion gain of 13 dB, the output 1-dB compression point (OP1dB) of 2.7 dBm and power added efficiency (PAE) more than 20%, respectively. The presented LNA exhibits return loss of input more than 10.32 dB, return loss of output more than 10.77 dB, the produce gain between 8.16 dB and 13.1 dB, isolation more than 42 dB, the produce noise figure between 4.48 dB and 7.66 dB, the produce input 1-dB compression point (IP1dB) between -13.43 dB and -5.43 dB, respectively. The implemented integrated RF frontend using 0.18um CMOS technology has experimental outdoor/ indoor throughput base on channels, distance and concurrently complies with the Bluetooth wireless requirement. © 2021 IEEE.

关键词： Bandpass filters

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Thermal Management of Electric Bike Battery Module Based on Heat Pipe Cooling System

SSRN

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SSRN 2022年

作者： Septiadi, Wayan Nata Alif Ramadhan Lazuardi, Sulthan Apriliani, Hepy Erza Alim, Muhamad Nara Pradipta Adi, Made Pierce, Rolland Department of Mechanical Engineering Udayana University Bukit Jimbaran Bali 80361 Indonesia Bachelor Program of Mechanical Engineering Udayana University Bukit Jimbaran Bali 80361 Indonesia

This research represents the battery thermal management system on the electric bike using heat pipes as a passive cooling system. The experiment was conducted using rollers positioned on a rear wheel, which provided rolling resistance to influence the power consumption of the module battery. The batteries thermal performance experiment was conducted under 30 minutes of data sampling using 3 different loads, which were 1 C, 1.5 C, and 2 C. The purpose of the experiment was to design the battery thermal management system and analyze the thermal performance of the battery module on an electric bike. The results indicate that compared to battery modules without a cooling system, a battery thermal management system based on heat pipes could reduce the temperature battery at 1 C, 1.5 C, and 2 C loads which were 4.5 oC, 6.3 oC, and 8.1 oC, respectively. Furthermore, combining the heat pipe and air cooling system could reduce the battery temperature to 11.3 oC, 12.2 oC, and 12.9 oC at a 2 C load. © 2022, The Authors. All rights reserved.

关键词： Heat pipes

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Feature Extraction of Internal Fault Types for the Solar PV System using the Novel NIFM Techniques

Feature Extraction of Internal Fault Types for the Solar PV ...

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Power and Electrical engineering (ACPEE), 5th Asia Conference on

作者： Hsueh-Hsien Chang Ren-Rong Guo Ching-Lung Lin Bachelor Program of Wind Power Minghsin University of Science and Technology Hsinchu Taiwan R.O. C. Dept. Electrical Engineering Program B Yuan Ze University Taoyuan Taiwan R.O. C. Dept. Electrical Engineering Minghsin University of Science and Technology Hsinchu Taiwan R.O. C.

ISBN: (数字)9798350309638

ISBN: (纸本)9798350309645

In low-voltage solar grids, traditional fault analysis and monitoring systems are used to detect power faults. These include wide-area protection technology with GPS and phasor measurement units (PMUs) and protective relays at each transmission line end. However, these designs increase data complexity and system cost. This paper uses the non-intrusive load identification technology, which involves installing a measuring device at the entrance of the extra high-voltage (EHV) transmission network. The measurement signal is processed by a proposed feature extraction method to form power energy features of various fault types in the frequency domain of the internal line of the low-voltage solar photovoltaic power grid. This approach is not only easier to install, but it is also more cost-effective. The results of the proposed method show the apparent differences for the different fault types.

关键词： Photovoltaic systems Low voltage Protective relaying Feature extraction Transmission line measurements Power grids Phasor measurement units

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Thermal Management of Electric Vehicle Battery Module Based on Heat Pipe Cooling System

SSRN

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SSRN 2022年

作者： Septiadi, Wayan Nata Lazuardi, Sulthan Alif Ramadhan Apriliani, Hepy Erza Alim, Muhamad Adi, Made Nara Pradipta Pierce, Rolland Department of Mechanical Engineering Udayana University Bukit Jimbaran Bali 80361 Indonesia Bachelor Program of Mechanical Engineering Udayana University Bukit Jimbaran Bali 80361 Indonesia

Conventional fuel vehicles emit significant amounts of lead, nitrogen, and carbon monoxide into the atmosphere. To overcome this issue, the use of electric vehicles is becoming more popular because the electricity needed can be produced from non-fossil fuel sources, thus reducing the pollution generated by conventional vehicles. The development of energy storage technology, such as new battery technology, fuel cells, ultracapacitors, etc, has been developed for electric and hybrid vehicles. Li-ion batteries are widely used because of their high energy density, longer life service, and eco-friendliness. Nevertheless, the charge and discharge time of the battery will generate heat and raise the battery temperature. The heat pipe is a two-phase passive heat exchanger technology with high thermal conductivity to maintain a uniform temperature difference along with the evaporator and condenser and could be used as a battery thermal management system. In this study, a heat pipe was designed for battery thermal management systems for cylindrical lithium battery modules. The experimental results showed that the use of heat pipes can effectively reduce the battery temperature by 12.9 o C when compared to conditions without cooling. © 2022, The Authors. All rights reserved.

关键词： Lithium-ion batteries

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