2021 International Conference on Electrical, Communication, and Computer Engineering (ICECCE)最新文献_第3页

72-Hours Ahead Prediction of Ionospheric TEC using Radial Basis Function Neural Networks 基于径向基函数神经网络的电离层TEC 72小时预报

2021 International Conference on Electrical, Communication, and Computer Engineering (ICECCE) Pub Date : 2021-06-12 DOI: 10.1109/ICECCE52056.2021.9514237

B. Muslim, Charisma Juni Kumalasari, Nurrohmat Widiajanti, Asnawi

{"title":"72-Hours Ahead Prediction of Ionospheric TEC using Radial Basis Function Neural Networks","authors":"B. Muslim, Charisma Juni Kumalasari, Nurrohmat Widiajanti, Asnawi","doi":"10.1109/ICECCE52056.2021.9514237","DOIUrl":"https://doi.org/10.1109/ICECCE52056.2021.9514237","url":null,"abstract":"Prediction of Indonesia's local and regional ionosphere TEC for the next 72 hours is required for space weather services at PUSSAINSA through the Space Weather Information and Forecast Services SWIFTS website, especially during ionosphere predictions on Friday which requires predicting the ionosphere condition from Saturday to Monday according to user needs. To this date, a global modeling the form of the W index, has been used for the prediction. Therefore, we developed a local ionosphere TEC prediction model as a starting point in the development of a regional ionosphere prediction model for Indonesia. The prediction model is built using a Radial Basis Function Neural Network (RBFNN). The input of the RBFNN model is the ionospheric TEC data for the previous 72 hours and the minimum value of the geomagnetic disturbance index (Dst) for the last3 days. The output isa prediction of the TEC 72 hours ahead. In the testing phase, the RBFNN model was able to predict local TEC with a daily standard deviation of between 2.75 and 4.9 Total Electron Content Unit (TECU).","PeriodicalId":302947,"journal":{"name":"2021 International Conference on Electrical, Communication, and Computer Engineering (ICECCE)","volume":"1 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":"131148262","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

Proposed Deep Learning Classification and Ultra-Wide Band Tensors for Localization of Breast Tumor 提出了基于深度学习分类和超宽带张量的乳腺肿瘤定位方法

2021 International Conference on Electrical, Communication, and Computer Engineering (ICECCE) Pub Date : 2021-06-12 DOI: 10.1109/ICECCE52056.2021.9514173

M. Tayel, Ahmed F. Kishk

{"title":"Proposed Deep Learning Classification and Ultra-Wide Band Tensors for Localization of Breast Tumor","authors":"M. Tayel, Ahmed F. Kishk","doi":"10.1109/ICECCE52056.2021.9514173","DOIUrl":"https://doi.org/10.1109/ICECCE52056.2021.9514173","url":null,"abstract":"Due to the increase in high-performance computing facilities, deep learning techniques that implement deep neural networks have become common. Also, the ability to process a large range of features as it deals with unstructured data, deep learning achieves greater strength and versatility. Initial layers extract low-level features, and subsequent layers combine features to create a full representation. An overview of the evolution of deep learning models and a brief idea about the different learning approaches, such as supervised learning, to train the neural network, supervised learning utilizes labelled data. Different architectures Pretrained Networks, Convolution Neural Networks, used to implement deep learning. Medical screening techniques have become increasingly important in the diagnosis and treatment of diseases. Breast cancer early detection is thought to be a key factor in lowering women's death rates. To boost breast cancer diagnosis, several alternative breast screening modalities are being studied. A modern methodology for cancer diagnosis and localization uses ultra-wide band (UWB) radar for screening breast cancer and identifying the presence of tumors in the breast using artificial intelligence techniques. This work focused on experimental data set based on breast tumor detection and localization using convolution neural network (CNN) techniques (i.e., pretrained CNN). CNNs are a useful way to find solutions to real-world challenges, and neural networks with learning algorithms are an exciting emerging technology.","PeriodicalId":302947,"journal":{"name":"2021 International Conference on Electrical, Communication, and Computer Engineering (ICECCE)","volume":"1 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":"131201526","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

Revisiting some computation methods for estimating the parameters of the Weibull Distribution 重述了估计威布尔分布参数的几种计算方法

2021 International Conference on Electrical, Communication, and Computer Engineering (ICECCE) Pub Date : 2021-06-12 DOI: 10.1109/ICECCE52056.2021.9514215

B. T. Mangara

{"title":"Revisiting some computation methods for estimating the parameters of the Weibull Distribution","authors":"B. T. Mangara","doi":"10.1109/ICECCE52056.2021.9514215","DOIUrl":"https://doi.org/10.1109/ICECCE52056.2021.9514215","url":null,"abstract":"To employ the wind speed measurements to determine the wind power potential of sites by way of computation methods to: 1) appraise the wind data to detect outliers (that is, spurious or distrustful values) that have the potential to degrade the quality of the data; and 2) obtain generic data information utilizing statistical procedures, such as the wind rose and Weibull distribution parameters of the wind in a specific time period. The study revisits some computation methods for estimating the parameters of the Weibull distribution of the wind and thereby assess the potential for generating electricity from wind for a site. Computation methods for estimating the parameters of the Weibull Distribution namely: 1) the graphical method; 2) the linear least square method; 3) the maximum likelihood estimation; and 4) the methods of moments: are presented and discussed. A meaningful example on applying the preceding computation methods on how to compute the Weibull distribution parameters from a wind speed time series data for a specific time period is presented. The statistical computations and analysis for estimating the parameters of the Weibull Distribution were conducted using MATLAB. The boxplot was used to examine the example data for outliers (that is, unusual observations that are far removed from the mass of data).","PeriodicalId":302947,"journal":{"name":"2021 International Conference on Electrical, Communication, and Computer Engineering (ICECCE)","volume":"198 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":"132766832","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

FA-GAN: High Resolution Face-Aging FA-GAN:高分辨率面部老化

2021 International Conference on Electrical, Communication, and Computer Engineering (ICECCE) Pub Date : 2021-06-12 DOI: 10.1109/ICECCE52056.2021.9514090

Arsh Agarwal, Aryan Singhal, Anmol Srivastava, P. Tewari

引用次数: 1

A Ka-band Vector-Sum Phase Shifter in 65nm CMOS for Phased Array Receivers 一种用于相控阵接收器的65nm CMOS ka波段矢量和移相器

2021 International Conference on Electrical, Communication, and Computer Engineering (ICECCE) Pub Date : 2021-06-12 DOI: 10.1109/ICECCE52056.2021.9514160

Haifeng Liu, Benqing Guo, Huifen Wang, Jingwei Wu

{"title":"A Ka-band Vector-Sum Phase Shifter in 65nm CMOS for Phased Array Receivers","authors":"Haifeng Liu, Benqing Guo, Huifen Wang, Jingwei Wu","doi":"10.1109/ICECCE52056.2021.9514160","DOIUrl":"https://doi.org/10.1109/ICECCE52056.2021.9514160","url":null,"abstract":"In this paper, a Ka-band vector-sum phase shifter with high quadrature precision I/Q signal generator and a new type of digitally controlled variable gain amplifier is presented. Specifically, the parasitic capacitance of the input common source stage of the I/Q signal generator is absorbed by an additional inductor in parallel resonance. In effect, the quadrature precision between the I/Q branch has been improved across the entire Ka-band. A variable gain amplifier based on digital control of transconductance was also proposed, which is equivalent to a cascode structure. The equivalent cascode transistor is composed of a 3x4 transistor array, and the transconductance of the overall circuit is adjustable by turning some of them on or off through programmable digital control signals. The proposed Ka-band vector-sum phase shifter is simulated with the TSMC 65nm CMOS process. It achieves an RMS phase error of 1.7°-2.2° and an RMS magnitude error of 0.9-2.1dB over 27-40GHz while covering a 360° phase range in steps less than 5.625°. The maximum DC power consumption is 8.9mW under 1.2V supply voltage, and the chip area is 0.399mm2.","PeriodicalId":302947,"journal":{"name":"2021 International Conference on Electrical, Communication, and Computer Engineering (ICECCE)","volume":"211 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":"115933249","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

Deep Sequence Models for Text Classification Tasks 文本分类任务的深度序列模型

2021 International Conference on Electrical, Communication, and Computer Engineering (ICECCE) Pub Date : 2021-06-12 DOI: 10.1109/ICECCE52056.2021.9514261

S. Abdullahi, Su Yiming, Shamsuddeen Hassan Muhammad, A. Mustapha, Ahmad Muhammad Aminu, Abdulkadir Abdullahi, Musa Bello, Saminu Mohammad Aliyu

{"title":"Deep Sequence Models for Text Classification Tasks","authors":"S. Abdullahi, Su Yiming, Shamsuddeen Hassan Muhammad, A. Mustapha, Ahmad Muhammad Aminu, Abdulkadir Abdullahi, Musa Bello, Saminu Mohammad Aliyu","doi":"10.1109/ICECCE52056.2021.9514261","DOIUrl":"https://doi.org/10.1109/ICECCE52056.2021.9514261","url":null,"abstract":"The exponential growth of data generated on the Internet in the current information age is a driving force for the digital economy. Extraction of information is the major value in an accumulated big data. Big data dependency on statistical analysis and hand-engineered rules machine learning algorithms are overwhelmed with vast complexities inherent in human languages. Natural Language Processing (NLP) is equipping machines to understand these human diverse and complicated languages. Text Classification is an NLP task which automatically identifies patterns based on predefined or undefined labeled sets. Common text classification application includes information retrieval, modeling news topic, theme extraction, sentiment analysis, and spam detection. In texts, some sequences of words depend on the previous or next word sequences to make full meaning; this is a challenging dependency task that requires the machine to be able to store some previous important information to impact future meaning. Sequence models such as RNN, GRU, and LSTM is a breakthrough for tasks with long-range dependencies. As such, we applied these models to Binary and Multi-class classification. Results generated were excellent with most of the models performing within the range of 80% and 94%. However, this result is not exhaustive as we believe there is room for improvement if machines are to compete with humans.","PeriodicalId":302947,"journal":{"name":"2021 International Conference on Electrical, Communication, and Computer Engineering (ICECCE)","volume":"9 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":"117215507","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

Efficient Private Cloud Resources Platform 高效私有云资源平台

2021 International Conference on Electrical, Communication, and Computer Engineering (ICECCE) Pub Date : 2021-06-12 DOI: 10.1109/ICECCE52056.2021.9514093

T. Ali, A. Morad, M. A. Abdala

{"title":"Efficient Private Cloud Resources Platform","authors":"T. Ali, A. Morad, M. A. Abdala","doi":"10.1109/ICECCE52056.2021.9514093","DOIUrl":"https://doi.org/10.1109/ICECCE52056.2021.9514093","url":null,"abstract":"Cloud-computing is becoming an increasingly popular model for accessing computing resources. The demand for advanced computing capabilities is increasing; however, conventional resource management systems have many drawbacks such as being costly, limited resources, and inefficiency. Therefore, an advanced management is needed. In this paper, we propose an innovative private cloud platform structure designed to secure sensitive company information, which other cloud offerings may not always protect effectively. The aim of this platform is to boost the efficiency in determining an enterprise's ability, custom priorities, and security threats. As a result, the proposed private cloud system provides account login with a username and password for each client. Then after login, each client can access to a proposed private cloud system and using different services privately such as file sharing, word document, slideshows, spreadsheets, local emails, photo sharing and display, online video playing, and also there is a specific storage area for each user after he login to his account. This storage area will enable the user for storing his files and documents on the cloud and using, retrieve or even editing them from any end device connecting to this private cloud inside organization, universities, Enterprise Company etc. without required to an internet connection for any reason with take in consideration the high privacy and security.","PeriodicalId":302947,"journal":{"name":"2021 International Conference on Electrical, Communication, and Computer Engineering (ICECCE)","volume":"39 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":"116489382","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

Model of Two-Mass Electric Drive of DC Electric Locomotive with the Full Order Observer 具有全阶观测器的直流电力机车双质量电传动模型

2021 International Conference on Electrical, Communication, and Computer Engineering (ICECCE) Pub Date : 2021-06-12 DOI: 10.1109/ICECCE52056.2021.9514247

Vasyl Stopkin, V. Kuznetsov, Vitaliy Kuznetsov, A. Nikolenko, Mvkola Babyak, Petro Hubskvi

{"title":"Model of Two-Mass Electric Drive of DC Electric Locomotive with the Full Order Observer","authors":"Vasyl Stopkin, V. Kuznetsov, Vitaliy Kuznetsov, A. Nikolenko, Mvkola Babyak, Petro Hubskvi","doi":"10.1109/ICECCE52056.2021.9514247","DOIUrl":"https://doi.org/10.1109/ICECCE52056.2021.9514247","url":null,"abstract":"The paper deals with development of the mathematical model of the two-mass electric drive of a direct current of the electric locomotive with the observer of a full order. The model provides an opportunity to study the change in the ratio of the moments of inertia of the two masses of the electric drive in order to reduce speed fluctuations and inconsistencies in the speeds of these masses. The observer estimates the speed on the basis of information about the supply voltage and motor current. Instead of directly measuring the speed, an observer is used, who uses the measured armature current and supply voltage to change the task to speed. As a comparison, the classical model of subordinate coordinate control for a two-mass electric drive is considered. The disadvantages of the latter are the complexity of calculating the parameters of the links during debugging. Identification and description of the load moment is carried out by a system of differential equations. Reproduction of the vector of coordinates of the system and the vector of perturbations (load moment) is carried out by the observer with an error in the steady state. To compensate for it, the load torque signal in the static is fed to the input of the speed circuit through the debugging link. The results of research on the mathematical model, with its appropriate adjustment under the conditions of a particular electric drive, can significantly reduce the impact loads on the electric drive by accurately matching the speeds of two masses and from a practical point of view provide information on calculations of the kinematic circuit and selection of optimal gear ratio.","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":"124751468","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

Comparison of Transceiver and C+L Band Upgrades: Network Traffic and Energy Assessment 收发器和C+L波段升级的比较:网络流量和能量评估

2021 International Conference on Electrical, Communication, and Computer Engineering (ICECCE) Pub Date : 2021-06-12 DOI: 10.1109/ICECCE52056.2021.9514166

R. Sadeghi, B. Correia, E. Virgillito, A. Napoli, N. Costa, J. Pedro, V. Curri

{"title":"Comparison of Transceiver and C+L Band Upgrades: Network Traffic and Energy Assessment","authors":"R. Sadeghi, B. Correia, E. Virgillito, A. Napoli, N. Costa, J. Pedro, V. Curri","doi":"10.1109/ICECCE52056.2021.9514166","DOIUrl":"https://doi.org/10.1109/ICECCE52056.2021.9514166","url":null,"abstract":"Being as power-efficient as possible is becoming an issue of increasing importance in optical networks due to the continuous increase of requested capacity resulting from the exponential growth of IP traffic. In this work, we investigate the trade-off between network capacity and energy consumption in optical transport networks when considering (i) three coherent transceiver implementations; (ii) two capacity upgrade strategies, and (iii) uniform and nonuniform traffic distributions. We show that, in Deutsche Telekom (DT) reference network, a nonuniform traffic distribution leads to an increase in network capacity of about 100 Tbps with respect to the uniform case. Interestingly, the nonuniform traffic distribution showed that, in the DT reference network, more traffic could be transmitted with less energy consumption than when considering the uniform traffic distribution. Additionally, it is also shown that C+L systems lead to an only negligible increase in energy consumption while attaining comparable network capacity as adding a second optical fiber and using C-band only for the three considered coherent transceiver implementations. Newer transceivers are found to be very power efficient when compared with older ones. This is a consequence of technological advances enabling to increase capacity via using higher-order modulation formats and baud rates. In the case of the ZR implementation, a compromise between lower power consumption and capacity was reached to address shorter links.","PeriodicalId":302947,"journal":{"name":"2021 International Conference on Electrical, Communication, and Computer Engineering (ICECCE)","volume":"1 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":"129461758","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

A New Protection Scheme for Low Voltage DC Microgrids 一种新的低压直流微电网保护方案

2021 International Conference on Electrical, Communication, and Computer Engineering (ICECCE) Pub Date : 2021-06-12 DOI: 10.1109/ICECCE52056.2021.9514143

M. Alshareef

引用次数: 2