2021 8th International Conference on Electrical and Electronics Engineering (ICEEE)最新文献_第4页

Free Space Doppler Analysis and RCS of a Moving PEC Plate Under Physical Optics Approximation 物理光学近似下运动PEC板的自由空间多普勒分析和RCS

2021 8th International Conference on Electrical and Electronics Engineering (ICEEE) Pub Date : 2021-04-09 DOI: 10.1109/ICEEE52452.2021.9415919

B. Polat, Ramazan Daşbaşı

引用次数: 3

Needle Detection in Ultrasound Images using Ultrasound Beamformed RF Signals 利用超声波束形成的射频信号在超声图像中检测针头

2021 8th International Conference on Electrical and Electronics Engineering (ICEEE) Pub Date : 2021-04-09 DOI: 10.1109/ICEEE52452.2021.9415947

M. Daoud, Ayah Abuhani, A. Zayadeen, R. Alazrai

{"title":"Needle Detection in Ultrasound Images using Ultrasound Beamformed RF Signals","authors":"M. Daoud, Ayah Abuhani, A. Zayadeen, R. Alazrai","doi":"10.1109/ICEEE52452.2021.9415947","DOIUrl":"https://doi.org/10.1109/ICEEE52452.2021.9415947","url":null,"abstract":"Medical ultrasound imaging is used in many image-guided needle interventions to visualize the patient anatomy and the advancing needle. Despite the improved capability of ultrasound to visualize the patient anatomy, detecting the needle in ultrasound images is often a difficult task. Many methods were introduced to detect the needle in ultrasound images. However, most of these methods employed ultrasound B-mode image analysis to detect the needle. Hence, the accuracy of these methods might be degraded by the limited visibility of the needle in ultrasound B-mode images, particularly at steep insertion angles. This study introduces an effective method to accurately detect the needle in ultrasound images based on the beamformed radio frequency (RF) signals that are recorded during conventional ultrasound imaging procedures. In particular, the beamformed RF signals are processed to identify the needle echoes using two signature-based features. The identified n e edle e c hoes are analyzed using the Robust Model Fitting Random Sample Consensus (RANSAC) algorithm to detect the needle trajectory. Moreover, the needle tip is detected using a moving window procedure that quantifies t h e v a riations o f t h e b e amformed R F signals around the needle trajectory. The performance of the proposed method is evaluated by detecting the trajectories and tips of biopsy needles inserted in bovine liver tissue specimens at different insertion angles. The results show that the proposed method was able to detect the needles with needle angular deviations between 0.2° and 0.6° and needle tip deviations between 0.3 to 0.5 mm. Furthermore, the results indicate that the proposed method was able to outperform a recently introduced needle detection method. These results suggest the feasibility of employing the proposed method to achieve accurate needle detection during ultrasound-guided needle interventions.","PeriodicalId":429645,"journal":{"name":"2021 8th International Conference on Electrical and Electronics Engineering (ICEEE)","volume":"17 8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115726389","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

Annular Ring Microstrip Patch Antennas with Slots in Patch and Ground Plane for GSM-1800 and Radio Navigation 用于GSM-1800和无线电导航的贴片和接地平面带槽的环形微带贴片天线

2021 8th International Conference on Electrical and Electronics Engineering (ICEEE) Pub Date : 2021-04-09 DOI: 10.1109/ICEEE52452.2021.9415946

C. Erbas

引用次数: 0

A Novel 5G Wideband Metamaterial Based Absorber for Microwave Energy Harvesting Applications 基于新型5G宽带超材料的微波能量收集吸收体

2021 8th International Conference on Electrical and Electronics Engineering (ICEEE) Pub Date : 2021-04-09 DOI: 10.1109/ICEEE52452.2021.9415941

Gökberk Akarsu, Mohammed Farouk Nakmouche, D. Fawzy, A. Allam, Kadir Başköy, Mehmet Faruk Cengiz

{"title":"A Novel 5G Wideband Metamaterial Based Absorber for Microwave Energy Harvesting Applications","authors":"Gökberk Akarsu, Mohammed Farouk Nakmouche, D. Fawzy, A. Allam, Kadir Başköy, Mehmet Faruk Cengiz","doi":"10.1109/ICEEE52452.2021.9415941","DOIUrl":"https://doi.org/10.1109/ICEEE52452.2021.9415941","url":null,"abstract":"This paper proposes a novel design of a compact and thin metamaterials (MMs) based wideband absorber aiming at specific microwave energy harvesting for 5G applications. The developed unit cell is obtained by combining two letters-like patches printed on a grounded dielectric substrate. The developed operating band is achieved based on the superposition of the two-resonances generated by the two letters. The simulations are based on Rogers RT5880 (thickness of 1.575 mm, dielectric constant of εr=2.2, loss tangent of tanδ=0.009) and FR-4 substrates (thickness of 1.2 mm dielectric constant of εr=4.3, loss tangent of tanδ=0.02). The obtained results show a wide 10 dB absorption bandwidth in the frequency range between 18 GHz and 30 GHz with absorptivity close to 99% for normal and oblique incident up top to 30° in the case of Rogers RT5880. An absorptivity rate of 96% is obtained for the cased of FR-4 because of high dielectric losses. The obtained results are reasonable compared to other studies in the literatures.","PeriodicalId":429645,"journal":{"name":"2021 8th International Conference on Electrical and Electronics Engineering (ICEEE)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127952190","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: 4

Weather Conditions Impact on Electricity Consumption in Smart Homes: Machine Learning Based Prediction Model 天气状况对智能家居用电量的影响:基于机器学习的预测模型

2021 8th International Conference on Electrical and Electronics Engineering (ICEEE) Pub Date : 2021-04-09 DOI: 10.1109/ICEEE52452.2021.9415917

G. B. Brahim

{"title":"Weather Conditions Impact on Electricity Consumption in Smart Homes: Machine Learning Based Prediction Model","authors":"G. B. Brahim","doi":"10.1109/ICEEE52452.2021.9415917","DOIUrl":"https://doi.org/10.1109/ICEEE52452.2021.9415917","url":null,"abstract":"With the fluctuations of energy pricing, the electricity bills for many households is becoming an increasing burden in the monthly bills to be paid. Many households in many countries would appreciate Smart Electricity Monitors and Smart Electricity controllers that can be used both in Smart Cities and regular households. Weather conditions play a vital role in electricity consumption, for example, in a hot desert climate, the electricity bill is tripled or quadrupled due to the use of air conditioning in summer. In this paper, we propose a machine learning based technique to anticipate the electricity consumption using weather data. Using a dataset consisting of reading over 350 days of household appliances with weather condition, the proposed method is able to predict the electricity consumption with a correlation coefficient of 75.7% using Random Tree. The results obtained provide an excellent basis for the ultimate goal of setting up an accurate smart electricity consumption monitor to be used both in Smart Cities and even in regular households which could ultimately help households to reduce electricity by regulating the use of the most electricity consuming appliances according to weather conditions.","PeriodicalId":429645,"journal":{"name":"2021 8th International Conference on Electrical and Electronics Engineering (ICEEE)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128318028","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

Calculating the Single-Link Performance for Space Division Multiplexing Elastic Optical Network 空间复用弹性光网络单链路性能计算

2021 8th International Conference on Electrical and Electronics Engineering (ICEEE) Pub Date : 2021-04-09 DOI: 10.1109/ICEEE52452.2021.9415928

Anwar Alyatama

引用次数: 0

An Alternative Approach for the Detection of Broken Rotor Bars and Bearing Faults of Induction Motor Based on Vibration Signals 基于振动信号的感应电机转子断条和轴承故障检测方法

2021 8th International Conference on Electrical and Electronics Engineering (ICEEE) Pub Date : 2021-04-09 DOI: 10.1109/ICEEE52452.2021.9415920

A. Kabul, A. Ünsal

{"title":"An Alternative Approach for the Detection of Broken Rotor Bars and Bearing Faults of Induction Motor Based on Vibration Signals","authors":"A. Kabul, A. Ünsal","doi":"10.1109/ICEEE52452.2021.9415920","DOIUrl":"https://doi.org/10.1109/ICEEE52452.2021.9415920","url":null,"abstract":"Induction motors are widely used in industrial facilities for the conversion of electrical energy to mechanical energy due to their simplicity, easy maintenance and robustness. The smooth operation of these motors may be interrupted due to broken rotor bars and/or bearing faults. In single fault detection, the fault characteristic harmonics can be successfully detected by applying conventional Motor Vibration Signal Analysis (MVSA) methods. The characteristic harmonics may appear hiding or overlapping with closely-located spectral components in the presence of multiple faults. This paper proposes an effective solution to overcome this difficulty. Hilbert envelope analysis is applied to the vibration signals of an induction motor with multiple faults (broken rotor bars and bearing faults). Two different fault cases were implemented. At the first case, the induction motor was tested with three broken rotor bars and outer-race bearing faults. At the second case, the induction motor was tested three broken rotor bars and inner-race bearing faults. The results indicate/show that the proposed method is capable of detecting all characteristic harmonics in both cases under four different loading levels (25%, 50%, 75% and 100%) of induction motor.","PeriodicalId":429645,"journal":{"name":"2021 8th International Conference on Electrical and Electronics Engineering (ICEEE)","volume":"382 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121771330","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: 5

Spatial-Temporal Prediction of Electric Vehicle Charging Demand in Realistic Urban Transportation System of a Mid-sized City in Brazil 巴西某中型城市现实城市交通系统中电动汽车充电需求时空预测

2021 8th International Conference on Electrical and Electronics Engineering (ICEEE) Pub Date : 2021-04-09 DOI: 10.1109/ICEEE52452.2021.9415942

Eslam Mahmoudi, E. R. Filho

{"title":"Spatial-Temporal Prediction of Electric Vehicle Charging Demand in Realistic Urban Transportation System of a Mid-sized City in Brazil","authors":"Eslam Mahmoudi, E. R. Filho","doi":"10.1109/ICEEE52452.2021.9415942","DOIUrl":"https://doi.org/10.1109/ICEEE52452.2021.9415942","url":null,"abstract":"Increasing the number of Electric Vehicles (EVs) in the urban transportation system will bring a large amount of energy demand, making urban planners construct a large number of charging piles. However, the blind construction of charging infrastructure brings problems such as excessive or insufficient charging facilities in different urban zones and irregular fluctuations in the power grid. These problems can be easily prevented with an accurate forecast of spatial-temporal charging demand in the urban area. The proposed methods in the literature are rarely applicable for charging demand prediction in the urban area because of ignoring the detailed spatial-temporal travel patterns of EVs in actual urban street networks. To obtain accurate spatial-temporal EV charging demand, the detailed travel pattern is modeled in this paper by integrating the actual street network and functional zones of the urban area. The urban street networks are modeled as a detailed graph based on OpenStreetMap data. A novel stochastic trip chain including the destination choice, route choice, speed-flow, and traffic allocation models is developed to simulate the spatial-temporal travel patterns of EVs in the urban street network. The travel patterns are incorporated by charging patterns and preferences of EV users to predict the EV charging demand in different locations of the urban area. The main results of the current research are 1) providing a detailed spatial-temporal model for EV travel patterns in the urban transportation system, 2) obtaining spatial-temporal slow and fast charging demand distributions of EVs in different functional zones, and 3) analyzing the slow and fast charging load demand distributions in different locations to suggest the charging infrastructure construction.","PeriodicalId":429645,"journal":{"name":"2021 8th International Conference on Electrical and Electronics Engineering (ICEEE)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115748707","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: 3

Implementation and Realization of Power Amplifier in Two Types of Matching Network Style for LTE Application LTE应用中两种匹配网络方式下功率放大器的实现

2021 8th International Conference on Electrical and Electronics Engineering (ICEEE) Pub Date : 2021-04-09 DOI: 10.1109/ICEEE52452.2021.9415926

Ahmed S. Al-Jawadi, K. H. Hamid, F. Aldabbagh

引用次数: 0

Voice Command Recognition for Drone Control by Deep Neural Networks on Embedded System 基于嵌入式系统的深度神经网络无人机控制语音命令识别

2021 8th International Conference on Electrical and Electronics Engineering (ICEEE) Pub Date : 2021-04-09 DOI: 10.1109/ICEEE52452.2021.9415964

Cengizhan Yapıcıoğlu, Z. Dokur, T. Ölmez

{"title":"Voice Command Recognition for Drone Control by Deep Neural Networks on Embedded System","authors":"Cengizhan Yapıcıoğlu, Z. Dokur, T. Ölmez","doi":"10.1109/ICEEE52452.2021.9415964","DOIUrl":"https://doi.org/10.1109/ICEEE52452.2021.9415964","url":null,"abstract":"Speech recognition and its applications for controlling a system has been an important and attractive issue over the last few decades. Controlling electronic devices by speech commands allows us to manage systems quickly and easily since users would not need any additional information or remote controller. Being able to communicate a system by using speech commands also brings with the requirements of fast and accurate response. So, at the present, speech recognition algorithms are extensively performing on high performance computers. However, the improvements of system on a chip (SoC) board and deep neural network based algorithms, make it possible to execute such kind of programs on them. The proposed study defines a model for controlling a drone system by using Turkish speech directional commands in real time which is based on deep learning approaches using spectrogram images. At first, speech commands are detected in real time with the help of signal energy and zero crossing rate and these are converted to log spectrogram images. A CNN (three convolutional layers and a fully connected layer) structure is created and trained by feeding those images. Then, the trained model is moved to embedded board to achieve real time, low-cost performance. Speech commands are provided by the user instantaneously and transferred to the model as an input for decision. Then, algorithm decides which directional command is given by the user and desired operation is performed on the drone system. It is observed that, by using the proposed model, accuracies of 95.72% for offline dataset and 92,88% for real time classification are obtained.","PeriodicalId":429645,"journal":{"name":"2021 8th International Conference on Electrical and Electronics Engineering (ICEEE)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123309967","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