检索结果-内蒙古大学图书馆

Advancing PCB Quality Control:Harnessing YOLOv8 Deep Learning for Real-Time Fault Detection

Computers, Materials & Continua 2024年第10期81卷 345-367页

作者： Rehman Ullah Khan Fazal Shah Ahmad Ali Khan Hamza Tahir Faculty of Cognitive Sciences and Human Development Universiti Malaysia SarawakKota Samarahan94300Malaysia School of Computer Science and Engineering Anhui University of Science and TechnologyHuainan232001China Department Electronic Quaid-i-Azam UniversityIslamabad45320Pakistan

Printed Circuit Boards(PCBs)are materials used to connect components to one another to form a working *** play a crucial role in modern electronics by connecting various *** trend of integrating more components onto PCBs is becoming increasingly common,which presents significant challenges for quality control *** the potential impact that even minute defects can have on signal traces,the surface inspection of PCB remains pivotal in ensuring the overall system *** address the limitations associated with manual inspection,this research endeavors to automate the inspection process using the YOLOv8 deep learning algorithm for real-time fault detection in ***,we explore the effectiveness of two variants of the YOLOv8 architecture:YOLOv8 Small and YOLOv8 *** rigorous experimentation and evaluation of our dataset which was acquired from Peking University’s human-Robot Interaction Lab,we aim to assess the suitability of these models for improving fault detection accuracy within the PCB manufacturing *** results reveal the remarkable capabilities of YOLOv8 Small models in accurately identifying and classifying PCB *** model achieved a precision of 98.7%,a recall of 99%,an accuracy of 98.6%,and an F1 score of *** findings highlight the potential of the YOLOv8 Small model to significantly improve the quality control processes in PCB manufacturing by providing a reliable and efficient solution for fault detection.

关键词： Printed circuit boards(PCB) YOLOv8 YOLOv8 Nano YOLOv8 Small deep learning object detection

来源：评论

学校读者我要写书评

暂无评论

Benchmarking CNN Models for Black Pepper Diseases and Malnutrition Prediction 5

Benchmarking CNN Models for Black Pepper Diseases and Malnut...

引用

5th IEEE International Conference on Artificial Intelligence in Engineering and Technology, IICAIET 2023

作者： Hui Chen, Olivia Ching Bong, Chih How Lee, Nung Kion Universiti Malaysia Sarawak Faculty of Cognitive Sciences and Human Development Kota Samarahan Malaysia Universiti Malaysia Sarawak Faculty of Computer Science and Information Technology Kota Samarahan Malaysia

ISBN: (纸本)9798350304152

Black Pepper (Piper nigrum L.) is one of the most important commodities in Southeast Asia. Like other plants, black pepper plants are exposed to various diseases and growth issues. Automated recognition of plant diseases and nutrient deficiencies is important with the availability of mobile devices. This paper aims to provide a benchmark for CNN models in learning the symptoms related to black pepper disease or malnutrition indicated on the leaves. Samples of black pepper leaf for 11 diseases and nutrient deficiencies were collected from farms in Sarawak. A total of 1,043 images of the samples were taken in a controlled environment. Augmentation was performed to increase the number of samples and to generate variation. Five deep-learning neural network architectures were selected for the modelling of the classification task. The results showed that state-of-the-art CNNs EfficientNet-B0 (0.88 accuracies), MobileNet-v2 (0.88 accuracies), ResNet-V2-50(0.86 accuracies), DenseNet121 (0.85 accuracies) and a customized CNN (0.85 accuracies), can act as benchmarks for black pepper disease or malnutrition diagnosis via the leaves. The models have the potential to be used for early detection and intervention for black pepper plant management. © 2023 IEEE.

关键词： Nutrients

来源：评论

学校读者我要写书评

暂无评论

Congruency Effect During Attention Network Task for Electroencephalogram-Based Alpha Neurofeedback Training 6

Congruency Effect During Attention Network Task for Electroe...

引用

6th IEEE Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability, ECBIOS 2024

作者： Mahmood, Danyal Nisar, Humaira Ali, Siti Atiyah National University of Science and Technology Department of Biomedical Engineering and Sciences Islamabad44000 Pakistan Universiti Tunku Abdul Rahman Faculty of Engineering and Green Technology Department of Electronic Engineering Kampar31900 Malaysia Universiti Malaysia Sarawak Faculty of Cognitive Sciences and Human Development Sarawak Malaysia

ISBN: (纸本)9798350396133

A bstract-Neurofeedback Training (NFT) using Electroencephalogram (EEG) allows individuals to self-regulate the activity of their brain non-invasively. NFT improves an individual's attention levels but the effect of congruency (alternation and repetition) on brain activity is still unknown. This study aimed to investigate the congruency effect of attention on 50 healthy participants (NFT Group: 25., Control Group: 25) after long-term alpha NFT. We examined changes in functional connectivity and band power within the alpha band. During the Attention Network Task (ANT)., each participant's EEG was recorded with congruent and incongruent stimuli in a pseudorandom order. A pre to post-NFT was increased in alpha band peak power within the temporal., parietal., and occipital regions., indicating the effectiveness of NFT. Additionally., there was an increase in task-related peak functional connectivity. However., the congruency did not affect the strength of functional connections between different brain regions. Stimuli alternation had a greater effect on alpha band power and connectivity modulation than stimuli repetition. © 2024 IEEE.

关键词： Electroencephalography

来源：评论

学校读者我要写书评

暂无评论

Social Versus Physical Distancing: Analysis of Public Health Messages at the Start of COVID-19 Outbreak in Malaysia Using Natural Language Processing 8th

Social Versus Physical Distancing: Analysis of Public Health...

引用

8th International Conference on Computational science and Technology, ICCST 2021

作者： Juan, Sarah Samson Saee, Suhaila Mohamad, Fitri Faculty of Computer Science and Information Technology Universiti Malaysia Sarawak Kota Samarahan Malaysia Faculty of Cognitive Sciences and Human Resource Development Universiti Malaysia Sarawak Kota Samarahan Malaysia

ISBN: (纸本)9789811685149

The study presents an attempt to analyse how social media netizens in Malaysia responded to the calls for "Social Distancing" and "Physical Distancing" as the newly recommended social norm was introduced to the world as a response to the COVID-19 global pandemic. The pandemic drove a sharp increase in social media platforms’ use as a public health communication platform since the first wave of the COVID-19 outbreak in Malaysia in April 2020. We analysed thousands of tweets posted by Malaysians daily between January 2020 and August 2021 to determine public perceptions and interactions patterns. The analysis focused on positive and negative reactions and the interchanges of uses of the recommended terminologies "social distancing" and "physical distancing". Using linguistic analysis and natural language processing, findings dominantly indicate influences from the multilingual and multicultural values held by Malaysian netizens, as they embrace the concept of distancing as a measure of global public health safety. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： COVID-19

来源：评论

学校读者我要写书评

暂无评论

Shaping the Digital Future of Civil Service: An Assessment of Digital Transformation and Data science Competencies 8

Shaping the Digital Future of Civil Service: An Assessment o...

引用

8th IEEE International Conference on Software Engineering and Computer Systems, ICSECS 2023

作者： Junaini, Syahrul Nizam Bujang, Sopian Basmawi, Nadri Aetis Fauzaman, Jusmawati Universiti Malaysia Sarawak Faculty of Computer Science and Information Technology Kota Samarahan Sarawak94300 Malaysia Universiti Malaysia Sarawak Faculty of Cognitive Science and Human Development Kota Samarahan Sarawak94300 Malaysia Leadership Institute of Sarawak Civil Service Kuching Sarawak93250 Malaysia Abdulhamid Abusulayman Kulliyyah of IRKHS International Islamic University Malaysia Kuala Lumpur50728 Malaysia

ISBN: (纸本)9798350310931

In the era of digital transformation and data proliferation, the need for effective digital competency assessment is increasingly critical. However, existing frameworks often lack comprehensive integration of key digital transformation and data science competencies necessary for roles within the civil service sector. This study introduces a robust instrument to profile competency domains critical to digital transformation and data science roles in the civil service. Leveraging a four-phase mixed-method methodology, including brainstorming, external validation, and a pilot study, the instrument was developed, validated, and tested among 30 state government servants. The reliability of the domains-Data Analytics, Data science Management, Data and Digital Architecture, and Digital Transformation-was confirmed by excellent Cronbach's Alpha values ( 0.9). Content validity was evaluated using Lawshe's Content Validity Ratio (CVR) and Index (CVI), indicating strong validity for Digital Transformation and Data and Digital Architecture domains, while suggesting refinement for Data Analytics and Data science Management. The proposed instrument, validated through self-evaluation scores, illustrates potential for career and organizational development within the civil service, emphasizing its practical value and feasibility. © 2023 IEEE.

关键词： Data Analytics

来源：评论

学校读者我要写书评

暂无评论

Benchmarking CNN Models for Black Pepper Diseases and Malnutrition Prediction

Benchmarking CNN Models for Black Pepper Diseases and Malnut...

引用

IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)

作者： Olivia Ching Hui Chen Chih How Bong Nung Kion Lee Faculty of Cognitive Sciences and Human Development Universiti Malaysia Sarawak Kota Samarahan Malaysia Faculty of Computer Science and Information Technology Universiti Malaysia Sarawak Kota Samarahan Malaysia

关键词：

来源：评论

学校读者我要写书评

暂无评论

Congruency Effect During Attention Network Task for Electroencephalogram-Based Alpha Neurofeedback Training

Congruency Effect During Attention Network Task for Electroe...

引用

IEEE Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability (ECBIOS)

作者： Danyal Mahmood Humaira Nisar Siti Atiyah Ali Department of Biomedical Engineering and Sciences National University of Science and Technology Islamabad Pakistan Department of Electronic Engineering Faculty of Engineering and Green Technology Universiti Tunku Abdul Rahman Kampar Malaysia Faculty of Cognitive Sciences and Human Development Universiti Malaysia Sarawak Sarawak Malaysia

ISBN: (数字)9798350396133

ISBN: (纸本)9798350396140

关键词： Training Frequency modulation Protocols Frontal lobe Medical services Electroencephalography Sustainable development Neurofeedback Biomedical engineering

来源：评论

学校读者我要写书评

暂无评论

Evaluation of Deep Learning for Image-based Black Pepper Disease and Nutrient Deficiency Classification 2

Evaluation of Deep Learning for Image-based Black Pepper Dis...

引用

2nd International Conference on Artificial Intelligence and Data sciences, AiDAS 2021

作者： Khew, Choy Yuen Teow, Yi Qin Lau, Ee Tiing Hwang, Siaw San Bong, Chih How Lee, Nung Kion Malaysian Pepper Board Dept of Research and Quality Development Kuching Malaysia Universiti Malaysia Sarawak Faculty of Cognitive Sciences and Human Development Kota Samarahan Malaysia Kuching Malaysia Universiti Malaysia Sarawak Faculty of Computer Science and Information Technology Kota Samarahan Malaysia

ISBN: (纸本)9781665417266

Black pepper (Piper nigrum) diseases and nutrient deficiency can often be observed based on the symptoms exerted on its leaves. This paper aimed to investigate the effectiveness of employing a deep learning approach to classify black pepper disease and nutrient deficiency based on leaf images. We constructed a customized convolutionary neural network to determine how its training parameters would affect the prediction performances. Another two deep learning neural networks VGG16 and Inception V3, are also employed for comparisons. We have sampled 947 images from farms in Sarawak consisted of 8 classes in total. Image augmentation is performed on the images to produce a total of 9532 images. The result shows that the customized CNN performed slightly better than the other two deep learning approaches at a 0.98 sensitivity rate. Furthermore, image augmentation contributed to improving prediction performance for all the deep learning models. This study has demonstrated that deep learning is a feasible approach for classifying black pepper diseases and nutrient deficiency based on leaf images. © 2021 IEEE.

关键词： Nutrients

来源：评论

学校读者我要写书评

暂无评论

Personalized Recommendation System of Innovation and Entrepreneurship Course Based on Collaborative Filtering

Personalized Recommendation System of Innovation and Entrepr...

引用

2021 International Conference on Networking Systems of AI, INSAI 2021

作者： Wang, Dongliang Zheng, Yaming Liu, Zhixin Zheng, Wenfeng Tian, Jiawei Fan, Xinxin Shaoxing University School of Civil Engineering Shaoxing China Malaysia Sarawak Faculty of Cognitive Sciences and Human Development University Sarawak Malaysia Shaoxing University School of Life Science Shaoxing China University of Electronic Science and Technology of China School of Automation Chengdu China

ISBN: (纸本)9781665408592

This article will use the process and structure of personalized recommendation to design a recommendation system suitable for innovation and entrepreneurship course platform. It also conducts a comparative analysis of the existing innovation and entrepreneurship platforms to clarify the characteristics and attributes of the innovation and entrepreneurship platforms. Through comparative research on the use process, application scenarios, advantages and disadvantages of traditional personalized recommendation algorithms. On the basis of making full use of the characteristics of the innovation and entrepreneurship platform, a collaborative filtering algorithm was selected to complete the recommendation system design. © 2021 IEEE.

关键词： Collaborative filtering

来源：评论

学校读者我要写书评

暂无评论

Shaping the Digital Future of Civil Service: An Assessment of Digital Transformation and Data science Competencies

Shaping the Digital Future of Civil Service: An Assessment o...

引用

International Conference on Software Engineering and Computer Systems (ICSECS)

作者： Syahrul Nizam Junaini Sopian Bujang Nadri Aetis Basmawi Jusmawati Fauzaman Faculty of Computer Science and Information Technology Universiti Malaysia Sarawak Kota Samarahan Sarawak Malaysia Faculty of Cognitive Science and Human Development Universiti Malaysia Sarawak Kota Samarahan Sarawak Malaysia Leadership Institute of Sarawak Civil Service Kuching Sarawak Malaysia Abdulhamid Abusulayman Kulliyyah of IRKHS International Islamic University Malaysia Kuala Lumpur

In the era of digital transformation and data proliferation, the need for effective digital competency assessment is increasingly critical. However, existing frameworks often lack comprehensive integration of key digital transformation and data science competencies necessary for roles within the civil service sector. This study introduces a robust instrument to profile competency domains critical to digital transformation and data science roles in the civil service. Leveraging a four-phase mixed-method methodology, including brainstorming, external validation, and a pilot study, the instrument was developed, validated, and tested among 30 state government servants. The reliability of the domains-Data Analytics, Data science Management, Data & Digital Architecture, and Digital Transformation-was confirmed by excellent Cronbach's Alpha values ( 0.9). Content validity was evaluated using Lawshe's Content Validity Ratio (CVR) and Index (CVI), indicating strong validity for Digital Transformation and Data & Digital Architecture domains, while suggesting refinement for Data Analytics and Data science Management. The proposed instrument, validated through self-evaluation scores, illustrates potential for career and organizational development within the civil service, emphasizing its practical value and feasibility.

关键词：

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：