2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME)最新文献_第2页

Augmented Reality in Childhood Education: Research and Development 儿童教育中的增强现实:研究与发展

2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME) Pub Date : 2022-11-16 DOI: 10.1109/ICECCME55909.2022.9987942

Mariyam Shaaha Shahid

引用次数: 1

MOSFET-based gas sensors for process industry IoT applications 用于过程工业物联网应用的基于mosfet的气体传感器

2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME) Pub Date : 2022-11-16 DOI: 10.1109/ICECCME55909.2022.9988741

Lida Khajavizadeh, M. Andersson

引用次数: 0

Functional Verification Measures to Challenge State Retention Strategy for Inaccessible Power-Gating of Low Power IPs 挑战低功耗ip不可访问电源门控状态保持策略的功能验证方法

2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME) Pub Date : 2022-11-16 DOI: 10.1109/ICECCME55909.2022.9987778

Surajit Bhattacherjee, D. Pal, Channabasapa M Jalagar

{"title":"Functional Verification Measures to Challenge State Retention Strategy for Inaccessible Power-Gating of Low Power IPs","authors":"Surajit Bhattacherjee, D. Pal, Channabasapa M Jalagar","doi":"10.1109/ICECCME55909.2022.9987778","DOIUrl":"https://doi.org/10.1109/ICECCME55909.2022.9987778","url":null,"abstract":"The Power Management and Control Unit (PMCU) plays a crucial role in optimizing power for both simple and complex SoCs which house for at least a few low power IPs. It requires extensive validation across the window of power transition from ungated to gated domain and vice-versa. The technologies through which the domain-based power requirement of individual IPs in an SoC is met, are mostly isolation and retention. Since physical flops are involved in these implementations, consideration is often subjected to area and gate-count budget of a IP and it is expected to be as minimum as possible for a low-power-low-speed serial-peripheral like a sensor. Moreover, when PMCU decides to turn off the supply through power-rails to perform inaccessible power gating to a IP, the retention flops are forced to lose the stored content. The issue introduces a new method, i.e. save and restore of the functional registers through an alternate access interface before and after the power shut down across the IPs respectively. The novel validation methodology proposed here, will account for an end-to-end validation of PMCU-coordinated save and restore flow and will thereby also verify the retention strategy defined for a IP Subsystem.","PeriodicalId":202568,"journal":{"name":"2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129936451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Design of FOPID Controller for Discrete System Utilizing Reduced-order Modeling 基于降阶建模的离散系统FOPID控制器设计

2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME) Pub Date : 2022-11-16 DOI: 10.1109/ICECCME55909.2022.9988005

V. Meena, Himanshu Monga, Vinay Singh

引用次数: 3

Coffee Bean Inspection Machine with Deep Learning Classification 具有深度学习分类的咖啡豆检测机

2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME) Pub Date : 2022-11-16 DOI: 10.1109/ICECCME55909.2022.9987835

Terisara Micaraseth, Khemwutta Pornpipatsakul, R. Chancharoen, G. Phanomchoeng

{"title":"Coffee Bean Inspection Machine with Deep Learning Classification","authors":"Terisara Micaraseth, Khemwutta Pornpipatsakul, R. Chancharoen, G. Phanomchoeng","doi":"10.1109/ICECCME55909.2022.9987835","DOIUrl":"https://doi.org/10.1109/ICECCME55909.2022.9987835","url":null,"abstract":"In coffee production process, after harvest often find defective coffee beans mixed with normal coffee beans. So a coffee bean inspection machine is made to classify the defects in a short time and high efficiency. The conveyor is controlled by the Raspberry Pi 4 and the camera mounting on the conveyor is for capturing images and uploading on the google drive. Then the images are analyzed by using deep learning 3 models consisting of Enhanced, ResNet-50 and AlexNet model for training image, validation image and test image. The most efficiency model is ResNet-50, which has an accuracy of 93.33%. That means it can classify the defect accurately and save working time to classify the coffee beans. From other research, coffee beans were capture image when the coffee beans place in groups. But in this research, The coffee beans are feed out of the feed machine. Run automatic shooting from a real production line through a moving on belt. and analyzed through the highest accurancy at 93.3%. Based on other literature comparisons, the accuancy was similar in the range.","PeriodicalId":202568,"journal":{"name":"2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME)","volume":"32 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128787270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Construction of Sichuan cuisine knowledge graph: methodology, annotation specification and corpus 川菜知识图谱的构建:方法论、注释规范和语料库

2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME) Pub Date : 2022-11-16 DOI: 10.1109/ICECCME55909.2022.9988746

Gaorong Yan

引用次数: 0

SentiMage: A Sentiment-Image-based COVID-19 Health Misinformation Detection using Machine Learning SentiMage:使用机器学习的基于情感图像的COVID-19健康错误信息检测

2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME) Pub Date : 2022-11-16 DOI: 10.1109/ICECCME55909.2022.9987818

K. Ramakrishnan, Vimala Balakrishnan

{"title":"SentiMage: A Sentiment-Image-based COVID-19 Health Misinformation Detection using Machine Learning","authors":"K. Ramakrishnan, Vimala Balakrishnan","doi":"10.1109/ICECCME55909.2022.9987818","DOIUrl":"https://doi.org/10.1109/ICECCME55909.2022.9987818","url":null,"abstract":"The rapid dissemination of misinformation (generally known as fake news) has become worrisome, especially during the on-going COVID-19 pandemic both globally, and locally. In fact, the proliferation of health-related misinformation intensified on social media, which many experts believe is contributing to the threats of the pandemic. Sentiment has been shown to improve detection mechanisms in various social media related studies, however this aspect is under-researched in the context of health misinformation. Further, metadata such as location or image that constitute part of real and fake news were not fully explored as well. This study develops a health misinformation detection model using machine learning algorithms, and further assesses the impact of sentiment and image on the model performance. Local data gathered from a fact-checking portal were pre-processed, translated, and used to train the detection model. Evaluation results show Support Vector Machine to yield the best performance with 99.4% for F-measure and accuracy of 99.1%, followed closely by Random Forest when sentiment was included, however, the presence of image was not found to significantly improve health misinformation detection.","PeriodicalId":202568,"journal":{"name":"2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129319032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Wideband Low-Frequency Piezoelectric Energy Harvester with Two Concentrated Proof Masses 具有两个集中证明质量的宽带低频压电能量采集器

2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME) Pub Date : 2022-11-16 DOI: 10.1109/ICECCME55909.2022.9987891

M. Bani-Hani, Wael A. Altabey, Mohamed Abdelnaeem, Mohamed Hassan, S. A. Kouritem

{"title":"Wideband Low-Frequency Piezoelectric Energy Harvester with Two Concentrated Proof Masses","authors":"M. Bani-Hani, Wael A. Altabey, Mohamed Abdelnaeem, Mohamed Hassan, S. A. Kouritem","doi":"10.1109/ICECCME55909.2022.9987891","DOIUrl":"https://doi.org/10.1109/ICECCME55909.2022.9987891","url":null,"abstract":"Harvesting the wasted vibrations in the surroundings and converting these vibrations to voltage difference through the piezoelectric (PZT) effect, is a promising approach to power many industrial and medical sensor networks. Ambient vibrations often exist in a wideband frequency form, so it is recommended to propose a simple design that can operate in broadband natural frequency of ambient vibration. This paper presents a two-degree-of-freedom (2-DOF) of a piezoelectric cantilever with two concentrated masses. The proposed design provides a broadband natural frequency (1–41 Hz) with high performance. The investigation is conducted using the Finite Element Method (FEM) using COMSOL Multiphysics. 2DOF Lumped mass system of the proposed harvester is derived for verification purposes. The effect of two concentrated masses on the natural frequency range is investigated. The resistance and piezoelectric thickness effects on output power are presented. It is found that the optimum power density at the optimal electric resistance is 0.037 $({mu}mathbf{W}/mathbf{mm}^{mathbf{3}})$.","PeriodicalId":202568,"journal":{"name":"2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124619500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

ProperBERT - Proactive Recognition of Offensive Phrasing for Effective Regulation property -主动识别攻击性措辞以促进有效监管

2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME) Pub Date : 2022-11-16 DOI: 10.1109/ICECCME55909.2022.9987933

Clara Diesenreiter, O. Krauss, Simone Sandler, Andreas Stöckl

{"title":"ProperBERT - Proactive Recognition of Offensive Phrasing for Effective Regulation","authors":"Clara Diesenreiter, O. Krauss, Simone Sandler, Andreas Stöckl","doi":"10.1109/ICECCME55909.2022.9987933","DOIUrl":"https://doi.org/10.1109/ICECCME55909.2022.9987933","url":null,"abstract":"This work discusses and contains content that may be offensive or unsettling. Hateful communication has always been part of human interaction, even before the advent of social media. Nowadays, offensive content is spreading faster and wider through digital communication channels. To help improve regulation of hate speech, we introduce ProperBERT, a fine-tuned BERT model for hate speech and offensive language detection specific to English. To ensure the portability of our model, five data sets from literature were combined to train ProperBERT. The pooled dataset contains racist, homophobic, misogynistic and generally offensive statements. Due to the variety of statements, which differ mainly in the target the hate is aimed at and the obviousness of the hate, a sufficiently robust model was trained. ProperBERT shows stability on data sets that have not been used for training, while remaining efficiently usable due to its compact size. By performing portability tests on data sets not used for fine-tuning, it is shown that fine-tuning on large scale and varied data leads to increased model portability.","PeriodicalId":202568,"journal":{"name":"2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124762318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Mixed Signal Simulation Marathon for Education and Employment 混合信号模拟马拉松教育和就业

2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME) Pub Date : 2022-11-16 DOI: 10.1109/ICECCME55909.2022.9988191

Sumanto Kar, Rahul Paknikar, Digvijay Singh, K. Moudgalya, Steve Hoover, S. Nalinkumar, S. Charaan, R. Ram, M. Kadam, Kunal P. Ghosh

引用次数: 0