2021 International Conference on Electrical, Communication, and Computer Engineering (ICECCE)最新文献_第6页

Comparative study of conventional PID and fuzzy logic controllers applied to an electric oven 传统PID与模糊控制器在电烤箱中的应用比较研究

2021 International Conference on Electrical, Communication, and Computer Engineering (ICECCE) Pub Date : 2021-06-12 DOI: 10.1109/ICECCE52056.2021.9514104

Serigne Diouf, I. Gueye, A. Kebe, Moustapha Diop

引用次数: 3

Evaluating Cross- feature Trained Machine Learning Models for Estimating QoT of Unestablished Lightpaths 评估用于估计未建立光路QoT的交叉特征训练机器学习模型

2021 International Conference on Electrical, Communication, and Computer Engineering (ICECCE) Pub Date : 2021-06-12 DOI: 10.1109/ICECCE52056.2021.9514154

Fehmida Usmani, I. Khan, M. Siddiqui, Mahnoor Khan, Muhamamd Bilal, M. U. Masood, Arsalan Ahmad, M. Shahzad, V. Curri

{"title":"Evaluating Cross- feature Trained Machine Learning Models for Estimating QoT of Unestablished Lightpaths","authors":"Fehmida Usmani, I. Khan, M. Siddiqui, Mahnoor Khan, Muhamamd Bilal, M. U. Masood, Arsalan Ahmad, M. Shahzad, V. Curri","doi":"10.1109/ICECCE52056.2021.9514154","DOIUrl":"https://doi.org/10.1109/ICECCE52056.2021.9514154","url":null,"abstract":"The rapid increase in bandwidth-driven applications has resulted in exponential internet traffic growth, especially in the backbone networks. To address this growth of internet traffic, operators always demand the total capacity utilization of underlying infrastructure. In this perspective, precise estimation of the quality of transmission (QoT) of the lightpaths (LPs) is vital for reducing the margins provisioned by uncertainty in network equipment's working point. This article proposes and compares several data-driven Machine learning (ML) based models to estimate QoT of unestablished LP before its deployment in the future deploying network. The proposed models are cross-trained on the data acquired from an already established LP of an entirely different in-service network. The metric considered to evaluate the QoT of LP is the Generalized Signal-to-Noise Ratio (GSNR). The dataset is generated synthetically using well tested GNPy simulation tool. Promising results are achieved to reduce the GSNR uncertainty and, consequently, the provisioning margin.","PeriodicalId":302947,"journal":{"name":"2021 International Conference on Electrical, Communication, and Computer Engineering (ICECCE)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121891723","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

Optimal Accommodation of DERs in Practical Radial Distribution Feeder for Techno-Economic with Artificial Bee Colony Algorithm 应用人工蜂群算法优化技术经济实用径向分配给料机中der的调节

2021 International Conference on Electrical, Communication, and Computer Engineering (ICECCE) Pub Date : 2021-06-12 DOI: 10.1109/ICECCE52056.2021.9514122

Abdulbari Ali Mohamed Frei, M. Güneser

引用次数: 0

Robustness analysis of PCA-SVM model used for fault detection in supermarket refrigeration systems * 超市制冷系统故障检测的PCA-SVM模型鲁棒性分析*

2021 International Conference on Electrical, Communication, and Computer Engineering (ICECCE) Pub Date : 2021-06-12 DOI: 10.1109/ICECCE52056.2021.9514086

Z. Soltani, Kresten Kjaer Soerensen, J. Leth, Jan Dimon Bendtsen

{"title":"Robustness analysis of PCA-SVM model used for fault detection in supermarket refrigeration systems *","authors":"Z. Soltani, Kresten Kjaer Soerensen, J. Leth, Jan Dimon Bendtsen","doi":"10.1109/ICECCE52056.2021.9514086","DOIUrl":"https://doi.org/10.1109/ICECCE52056.2021.9514086","url":null,"abstract":"Supermarket refrigeration systems represent an important type of energy demanding appliances, which is in such widespread use that any development in the associated technology can have a huge impact on general health and global warming. Using automatic fault detection and diagnosis may for instance improve energy efficiency and reduce food waste as well as reduce expenses for the supermarket owners. In this paper, three model-free classification algorithms are tested on faulty/non-faulty data obtained from an actual refrigeration system. It is found that support vector machines (SVM) are able to classify fan faults in a real refrigeration system with near-100% classification accuracy, independent of the number of input variables. The classification performance and robustness against an unseen operation mode, low-resolution data, noisy data, and data of different operating points is tested for three different classifier configurations. The results show Principle Component Analysis (PCA)-SVM is highly robust to different operating points, disturbances, and gives the best computational efficiency, as it is able to reduce the feature space to only two dimensions. It is concluded that while all of the examined methods are insensitive to noise, and effective in terms of detecting faults from relatively small amounts of data, overall, PCA -SVM is slightly more computationally efficient.","PeriodicalId":302947,"journal":{"name":"2021 International Conference on Electrical, Communication, and Computer Engineering (ICECCE)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124266883","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: 2

Predicting “Maintenance Priority” with AI 用人工智能预测“维护优先级”

2021 International Conference on Electrical, Communication, and Computer Engineering (ICECCE) Pub Date : 2021-06-12 DOI: 10.1109/ICECCE52056.2021.9514218

Ömer Yiğit Astepe, Ali Seymen Alkara

{"title":"Predicting “Maintenance Priority” with AI","authors":"Ömer Yiğit Astepe, Ali Seymen Alkara","doi":"10.1109/ICECCE52056.2021.9514218","DOIUrl":"https://doi.org/10.1109/ICECCE52056.2021.9514218","url":null,"abstract":"In Tiipras oil refineries, an average of 100 thousand maintenance requests are created annually for more than 140 thousand pieces of equipment. These requests are prioritized manually by chief experts with over 25 years of experience and classified as urgent or planned. If maintenance requests that need to be solved urgently in the refining industry are mislabeled and delayed, they may cause process upsets leading to health & safety hazards, environment problems or big asset damage. To minimize this risk, we think that supporting the decision mechanism with algorithms and cross checking/replacing human decisions by using today's AI technologies is the right approach that reduces the possibility of human error. In this study, our main goal is to automate maintenance prioritization process with supervised and unsupervised ML algorithms, deploy an AI system and achieve high accuracy. Our study was carried out basically in 4 main steps: • Exploratory Data Analysis • Clustering - Feature Addition - Feature Selection • Model Selection and Results • Additional Studies With this study, we aim to explain our AI study, share our experience with other partners that have similar needs and provide them an effective tool and systematic approach about management of transition from human to machine with a real industry case. We believe that the transfer of priority selection process from human to algorithms ensure consistent decisions, reduce costs and tolerate experience losses.","PeriodicalId":302947,"journal":{"name":"2021 International Conference on Electrical, Communication, and Computer Engineering (ICECCE)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125546847","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

High Bandwidth Hybrid Supply Modulation Using Totem Pole Configuration for Envelope Tracking Applications 用于包络跟踪应用的图腾柱配置的高带宽混合电源调制

2021 International Conference on Electrical, Communication, and Computer Engineering (ICECCE) Pub Date : 2021-06-12 DOI: 10.1109/ICECCE52056.2021.9514243

Mohd Zainal Bin Nurdin, Z. Yusoff, M. Roslee, S. Hashim, Azah Syafiah Mohd Marzuki

引用次数: 0

Rain Attenuation Prediction for 2.4-72GHz using LTSM, an artificial recurrent neural network technology 利用人工递归神经网络LTSM技术预测2.4-72GHz频段的降雨衰减

2021 International Conference on Electrical, Communication, and Computer Engineering (ICECCE) Pub Date : 2021-06-12 DOI: 10.1109/ICECCE52056.2021.9514095

M. Domb, G. Leshem

{"title":"Rain Attenuation Prediction for 2.4-72GHz using LTSM, an artificial recurrent neural network technology","authors":"M. Domb, G. Leshem","doi":"10.1109/ICECCE52056.2021.9514095","DOIUrl":"https://doi.org/10.1109/ICECCE52056.2021.9514095","url":null,"abstract":"Free-space communication is a leading component in global communications. Its advantages relate to a broader signal spread, no wiring, and ease of engagement. However, satellite communication links suffer from arbitrary weather phenomena such as clouds, rain, snow, fog, and dust. Therefore, satellites commonly use redundant signal strength to ensure constant and continuous signal transmission, resulting in excess energy consumption, challenging the limited power capacity generated by solar energy or the fixed amount of fuel. This research proposes a Machine Learning [ML]-based model that provides a time-dependent prediction of the expected attenuation level due to rain and fog. Based on the predicted attenuation level, we calibrate the communication signal strength to save energy. We used collected data from the Genesis LEO satellite and corresponding simulated data in the range of 2.4GHz to 72GHz. We then executed the ML system, and after several adjustments for the frequencies up to 48GHz, we reached a very narrow gap between the predicted and actual attenuation levels. However, in the 72GHz frequency, we got a partial correlation.","PeriodicalId":302947,"journal":{"name":"2021 International Conference on Electrical, Communication, and Computer Engineering (ICECCE)","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126273020","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

Copper Loss Reduction of Torque Sharing Function in Switched Reluctance Motor by Division of Commutation Region 通过划分换相区降低开关磁阻电机转矩共享功能的铜损耗

2021 International Conference on Electrical, Communication, and Computer Engineering (ICECCE) Pub Date : 2021-06-12 DOI: 10.1109/ICECCE52056.2021.9514205

Jiayi Fan, Yongkeun Lee

{"title":"Copper Loss Reduction of Torque Sharing Function in Switched Reluctance Motor by Division of Commutation Region","authors":"Jiayi Fan, Yongkeun Lee","doi":"10.1109/ICECCE52056.2021.9514205","DOIUrl":"https://doi.org/10.1109/ICECCE52056.2021.9514205","url":null,"abstract":"Torque sharing function (TSF) method is widely used in switched reluctance motor (SRM) drive to reduce the torque ripple. Besides maintaining the torque control performance, the copper loss reduction should also be considered while determining the TSF profiles. In this paper, an improved TSF method modified from the previous method recently done by the other research group is proposed focusing on the optimal allocation of torque component in the commutation phases and reduction of copper loss. Based on the torque generating nature of SRM, the commutation region is suggested to be divided into two regions where the incoming phase and outgoing phase have different torque generating capacity. The commutation phase with higher rate of change of inductance with respect to the rotor position is preferred to mainly contribute to the torque production while the other phase is penalized to have reduced current. Thus, the total copper loss can be reduced. Simulation is carried out in MATLAB/Simulink environment and the simulation results show that the modified TSF with region division has a lower copper loss compared to the previous method done by the other research group.","PeriodicalId":302947,"journal":{"name":"2021 International Conference on Electrical, Communication, and Computer Engineering (ICECCE)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130277048","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

Mechanical stresses of electromagnetic origin. Effects produced by three-phase short-circuit currents on a rigid busbar system 电磁源的机械应力。三相短路电流对刚性母线系统的影响

2021 International Conference on Electrical, Communication, and Computer Engineering (ICECCE) Pub Date : 2021-06-12 DOI: 10.1109/ICECCE52056.2021.9514162

Horacio M. Frene, C. D. Arrojo, R. Dias, J. C. Scaramutti

引用次数: 0

Multi-Scale Safety Hardhat Wearing Detection using Deep Learning: A Top-Down and Bottom-Up Module 基于深度学习的多尺度安全安全帽佩戴检测:一个自上而下和自下而上的模块

2021 International Conference on Electrical, Communication, and Computer Engineering (ICECCE) Pub Date : 2021-06-12 DOI: 10.1109/ICECCE52056.2021.9514144

M. Ferdous, Sk. Md. Masudul Ahsan

{"title":"Multi-Scale Safety Hardhat Wearing Detection using Deep Learning: A Top-Down and Bottom-Up Module","authors":"M. Ferdous, Sk. Md. Masudul Ahsan","doi":"10.1109/ICECCE52056.2021.9514144","DOIUrl":"https://doi.org/10.1109/ICECCE52056.2021.9514144","url":null,"abstract":"Construction sites are the most unsafe and risky places where thousands of workers are injured and die every year throughout the world. Some protective gear like hardhat can protect personnel from unexpected accidents. Administrators need to confirm all personnel put on hardhat on their heads during working time. However, it is inefficient and time-consuming to monitor this task manually. Hence, an automatic system may give convenience to detect personnel whether they wearing hardhat or not when they are on duty. RatinaNet is used to detect and localize the hardhat/head of personnel into the construction site. ResNet50+Feature Pyramid Network (FPN) is used as the backbone of the architecture, a classification and a regression sun-module are used to classifying objects and localizing bounding box around the object. A robust semantical description is achieved using both top-down pathways and lateral connections. Hardhats or heads are detected on a multiscale using the bottom-up and top-down modules. Experimental analysis on a dataset using RatinaNet produces a prominent result that may be usable in real-time applications.","PeriodicalId":302947,"journal":{"name":"2021 International Conference on Electrical, Communication, and Computer Engineering (ICECCE)","volume":"141 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121251389","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: 2