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Broadband Printed Dipole Antennas 宽带印刷偶极子天线
Pub Date : 2022-06-01 DOI: 10.1109/iemtronics55184.2022.9795826
R. P. Ghosh, B. Gupta
Two arms of Microstrip Dipole antenna are printed on the same side of a substrate. But two arms of the Printed Dipole Antenna (PDA) are printed on the opposite sides and hence contain no ground plane. The Return Loss (RL) Bandwidth (BW) of PDA is much higher compared to Microstrip Dipole as it does not contain ground plane like the Microstrip Dipole and therefore Q value is low which results in large RL bandwidth. The PDA is fed by printed version of two wire transmission line. The cross polar discrimination is high as width to length ratio of the arm is very small. In general the width is kept below 0.05λ0. A novel design of PDA is reported in which the antenna arms have been widened to make it a Flag shaped to achieve large RL bandwidth. The -10dB RL bandwidth as high as 76% is achieved. Due to widening of the arms the fundamental resonant frequency and its first harmonic is stagger tuned to result a high RL. Three antennas are designed and simulated in MOM based simulator IE3D. One of them has been fabricated for experimental verification. The experimental result is in good agreement with the simulated results.
微带偶极子天线的两臂被印在衬底的同一侧。但是印刷偶极子天线(PDA)的两个臂被印在相对的两侧,因此不包含接地面。与微带偶极子相比,PDA的回波损耗(RL)带宽(BW)要高得多,因为它不像微带偶极子那样包含地平面,因此Q值很低,从而导致大的RL带宽。PDA通过两线传输线的印刷版进行馈电。当臂的宽长比非常小时,交叉极性判别高。宽度一般保持在0.05λ0以下。本文报道了一种新型的PDA设计,该设计将天线臂加宽,使其成为一个旗形,以实现大的RL带宽。实现了高达76%的-10dB RL带宽。由于手臂的扩大,基本谐振频率和它的第一次谐波是交错调谐的结果一个高的RL。在基于MOM的IE3D仿真器中对三根天线进行了设计和仿真。其中一个已被制作用于实验验证。实验结果与仿真结果吻合较好。
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引用次数: 0
Efficient Simulation of Variable-Speed Diesel-Engine Generators Using Constant-Parameter Voltage-Behind-Reactance Formulation 用恒参数电抗后电压公式高效模拟变速柴油机发电机
Pub Date : 2022-06-01 DOI: 10.1109/iemtronics55184.2022.9795810
Erfan Mostajeran, Arash Safavizadeh, S. Ebrahimi, J. Jatskevich
Diesel-engine generators can operate with variable speed to enhance their efficiency over a wide range of loading conditions. Constant-parameter voltage-behind-reactance (CPVBR) models have been developed for efficient simulation of three-phase wound-field synchronous generators (WFSGs). The CPVBR models use fixed branches for interfacing (without any incompatibility, e.g., the need for snubbers, etc.) and are not required to update their interfacing circuit in every time step of the simulation. This paper presents the application of the CPVBR model of a WFSG for efficient simulation of a variable-frequency/speed diesel-engine generator-rectifier system. Simulation studies are carried out in MATLAB using PLECS toolbox to verify the computational performance of the CPVBR model. It is demonstrated that the CPVBR model achieves superior computational performance (without compromising the accuracy) compared to the built-in models of the toolbox, i.e., qd0, stator VBR, and full VBR models.
柴油发电机可以以变速运行,以提高其在各种负载条件下的效率。为了有效地模拟三相绕组场同步发电机(WFSGs),建立了恒参数电抗模型。CPVBR模型使用固定支路进行接口(没有任何不兼容性,例如,需要缓冲器等),并且不需要在仿真的每个时间步长更新其接口电路。本文介绍了WFSG的CPVBR模型在变频调速柴油机发电机-整流系统仿真中的应用。利用PLECS工具箱在MATLAB中进行仿真研究,验证CPVBR模型的计算性能。结果表明,与工具箱的内置模型(即qd0、定子VBR和全VBR模型)相比,CPVBR模型在不影响精度的情况下实现了卓越的计算性能。
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引用次数: 0
Convolutional Neural Network Structure to Detect and Localize CTC Using Image Processing 基于图像处理的卷积神经网络结构检测和定位CTC
Pub Date : 2022-06-01 DOI: 10.1109/iemtronics55184.2022.9795734
Shorouq Al-Eidi, Omar A. Darwish, G. Husari, Y. Chen, M. Elkhodr
Many cybersecurity attacks utilize Covert Timing Channels as a method to secretly transmit (steal) sensitive information from target networks such as untrusted Internet of Things (IoT) and 5G/6G networks. Such attacks aim to violate the confidentiality and privacy of the data that resides in the targeted networks by transmitting the stolen information in a stealth manner over a prolonged period of time to avoid detection by cyber defenses and anti-exfiltration tools.In this work, we proposed a novel approach that utilize novel Artificial Intelligence (AI) algorithms, in particular, deep learning to detect and localize covert channels over cyber networks. Taking advantage of the rapidly improving deep learning algorithms in image processing, we convert the malicious and normal network traffic (or packets) inter-arrival times to colored images. Then, we implement an AI-based approach using the popular deep learning algorithm Convolutional Neural Network (CNN) to process images and detect the ones that contain malicious CTC activities. Finally, we design and conduct a set of experiments to evaluate the ability of our proposed system to detect and localize CTC-based privacy attacks. The conducted experiments show that our approach yielded a high accuracy of 96.75% in detecting stealth covert channels.
许多网络安全攻击利用隐蔽定时通道作为从目标网络(如不受信任的物联网(IoT)和5G/6G网络)秘密传输(窃取)敏感信息的方法。这类攻击的目的是侵犯目标网络中数据的机密性和隐私性,将窃取的信息在很长一段时间内以隐形的方式传输,以避免被网络防御和反渗透工具发现。在这项工作中,我们提出了一种新的方法,利用新的人工智能(AI)算法,特别是深度学习来检测和定位网络上的隐蔽通道。利用图像处理中快速改进的深度学习算法,我们将恶意和正常网络流量(或数据包)的间隔到达时间转换为彩色图像。然后,我们实现了一种基于人工智能的方法,使用流行的深度学习算法卷积神经网络(CNN)来处理图像并检测包含恶意CTC活动的图像。最后,我们设计并进行了一组实验来评估我们提出的系统检测和定位基于ctc的隐私攻击的能力。实验结果表明,该方法检测隐身隐蔽信道的准确率高达96.75%。
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引用次数: 1
Intelligent Feature Selection on Multivariate Dataset using Advanced Data Profiling 基于高级数据分析的多元数据集智能特征选择
Pub Date : 2022-06-01 DOI: 10.1109/iemtronics55184.2022.9795745
Ritu Chaturvedi, Vandana V. Patnaik
The differential diagnosis of diseases which share similar clinical features is a real and difficult problem in medicine. This paper demonstrates the use of data mining (DM) techniques to augment standard data profiling methods and establishes an efficient approach for an intelligent feature selection method for disease that share similar features. The results from experiments returned show that by using DM techniques to select features as an additional layer on top of data profiling, there is considerable improvement in the performance of the prediction model built to predict a disease such as "Psoriasis". A brief comparison between features selected by existing mining tools such as Weka and the proposed approach with respect to predictive accuracy is recorded in this paper. The proposed algorithm works as a promising tool for assisting diagnosis of disease like erythemato-squamous diseases, where the symptoms are overlapping. By combining data cleansing and knowledge discovery techniques, the algorithm aims to be "agnostic" and can be used on a wide variety of data standards with variable data quality. 1
具有相似临床特征的疾病的鉴别诊断是医学上一个现实而困难的问题。本文演示了使用数据挖掘(DM)技术来增强标准数据分析方法,并为具有相似特征的疾病的智能特征选择方法建立了一种有效的方法。返回的实验结果表明,通过使用DM技术选择特征作为数据分析的附加层,用于预测“牛皮癣”等疾病的预测模型的性能有相当大的提高。本文记录了现有挖掘工具(如Weka)选择的特征与提出的方法在预测精度方面的简要比较。该算法是一种很有前途的工具,可以帮助诊断症状重叠的疾病,如红斑-鳞状疾病。通过结合数据清理和知识发现技术,该算法旨在实现“不可知论”,并可用于具有可变数据质量的各种数据标准。1
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引用次数: 0
Mechanical and Electronic Design of a Prototype of a Modular Exoskeleton for Lower-Limbs 一种模块化下肢外骨骼原型的机械与电子设计
Pub Date : 2022-06-01 DOI: 10.1109/iemtronics55184.2022.9795712
Yerson Taza-Aquino, Deyby Huamanchahua
In many countries, the rehabilitation of partial disability of the lower limbs performs the process traditionally due to the high cost of implementing physiotherapy and rehabilitation centers with robotic devices. Therefore, the primary motivation of this work is to propose the first design of an exoskeleton with adjustable links that can be adapted depending on the height of the user, muscle sensors (EMG) and position are used to achieve a better response of the patient's intention of movement and thus achieve rehabilitation of the legs. The exoskeleton in question was designed using the VDI 2206 methodology, and this work presents a proposal for mechanical and electronic design with the ability to withstand the user's weight. A study of stress analysis and simulation of the electronic circuit was carried out. The electronic circuit was simulated in the Proteus software, where the correct interaction of the sensors with the motors is achieved. The results obtained show that the design of the proposed exoskeleton manages to support the weight of a person of 75 Kg with a maximum height of 170 cm. These results were obtained after being subjected to the design of the exoskeleton to the stress analysis in the SolidWorks software. Another feature of the exoskeleton design is its low weight because the material chosen is aluminum alloy 6061 T-6, which can withstand all stress tests.
在许多国家,由于使用机器人设备进行物理治疗和康复中心的高成本,下肢部分残疾的康复传统上执行这一过程。因此,这项工作的主要动机是提出一种外骨骼的设计,这种外骨骼具有可调节的链接,可以根据用户的高度进行调整,肌肉传感器(EMG)和位置被用来更好地响应患者的运动意图,从而实现腿部康复。所讨论的外骨骼是使用VDI 2206方法设计的,这项工作提出了能够承受用户体重的机械和电子设计的建议。对电子电路进行了应力分析和仿真研究。在Proteus软件中对电子电路进行了仿真,实现了传感器与电机的正确交互。结果表明,所提出的外骨骼设计能够支撑一个75公斤的人的重量,最大高度为170厘米。这些结果是在SolidWorks软件中对外骨骼设计进行应力分析后得到的。外骨骼设计的另一个特点是重量轻,因为选择的材料是6061 T-6铝合金,可以承受所有的压力测试。
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引用次数: 1
An Optimum Sizing for a Hybrid Storage System in Solar Water Pumping Using ICA 基于ICA的太阳能抽水混合蓄能系统的最优规模
Pub Date : 2022-06-01 DOI: 10.1109/iemtronics55184.2022.9795848
Amirhossein Jahanfar, M. Iqbal
Solar water pumps must be the most optimum size to work efficiently and be at a reasonable price. The storage system can play a main role in both system reliability and the total cost of a solar water pumping project; thus, it should be designed carefully. Traditionally, only batteries or water tanks are used as primary storage system; each of them has its benefits and drawbacks. In this research, a new approach to a storage system is proposed, consisting of both batteries and water tanks at the same time. Such hybrid storage can decrease project cost and increase system reliability. To find the most optimum size for such a hybrid system an optimization algorithm named "Imperialist Competitive Algorithm (ICA)" is used to minimize the Life-Cycle Cost Analysis (LCCA) of the storage system. In this paper, a hybrid storage configuration for solar water pumping for a site in Iran is proposed, and results of the optimum size for that system using ICA are expressed. It is shown that the configuration is more feasible compared with many other configurations.
太阳能水泵必须是最理想的尺寸,以有效地工作,并在一个合理的价格。储能系统可以在系统可靠性和太阳能抽水工程总成本中发挥主要作用;因此,它应该仔细设计。传统上,只有电池或水箱作为主存储系统;每种方法都有其优点和缺点。在这项研究中,提出了一种新的存储系统的方法,同时由电池和水箱组成。这种混合存储方式可以降低工程成本,提高系统可靠性。为了找到这种混合系统的最优规模,使用了“帝国主义竞争算法(ICA)”的优化算法来最小化存储系统的生命周期成本分析(LCCA)。本文针对伊朗某电站的太阳能抽水系统,提出了一种混合蓄能结构,并给出了该系统最优规模的ICA计算结果。结果表明,与许多其他构型相比,该构型更为可行。
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引用次数: 3
Machine learning Models to Predict COVID-19 Cases 预测COVID-19病例的机器学习模型
Pub Date : 2022-06-01 DOI: 10.1109/iemtronics55184.2022.9795797
Ghadah Alshabana, Thao Tran, Marjan Saadati, Michael Thompson George, Ashritha Chitimalla
Coronavirus can be transmitted through the air by close proximity to infected persons. Commercial aircraft are a likely way to both transmit the virus among passengers and move the virus between locations. The importance of learning about where and how coronavirus has entered the United States will help further our understanding of the disease. Air travelers can come from countries or areas with a high rate of infection and may very well be at risk of being exposed to the virus. Therefore, as they reach the United States, the virus could easily spread. On our analysis, we utilized machine learning to determine if the number of flights into the Washington DC Metro Area had an effect on the number of cases and deaths reported in the city and surrounding area.
冠状病毒可通过与感染者的近距离接触通过空气传播。商用飞机可能是在乘客之间传播病毒和在地点之间传播病毒的一种方式。了解冠状病毒在哪里以及如何进入美国的重要性将有助于我们进一步了解这种疾病。航空旅客可能来自高感染率的国家或地区,很可能有接触病毒的风险。因此,当它们到达美国时,病毒很容易传播。在我们的分析中,我们利用机器学习来确定进入华盛顿特区都市区的航班数量是否对该市及周边地区报告的病例和死亡人数有影响。
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引用次数: 0
A Machine Learning Approach for the Early Detection of Dementia 一种用于早期检测痴呆症的机器学习方法
Pub Date : 2022-06-01 DOI: 10.1109/iemtronics55184.2022.9795717
S. Broman, E. O'Hara, M. Ali
Longer life spans in today's society have contributed to the growth of degenerative disease prevalence, especially dementia. Dementia causes a deterioration in thought process and a decline in cognitive function, specifically thinking, reasoning, and remembering. While dementia cannot be completely prevented, its early detection can delay the onset of the disease. With the help of a machine learning algorithm, relevant attributes to detect the disease in its early stages can be refined and successful predictions can be made. To conduct this analysis, the Alzheimer Features and Exploratory Data Analysis for Predicting Dementia datasets were utilized. The following machine learning models were applied to the dataset: Naïve Bayes, Decision Trees, K-Nearest Neighbors, and Fully Connected Neural Networks. After evaluation of accuracy scores, confusion matrices for both Naïve Bayes and Decision Trees were determined to provide the best results among the models. While further investigation with a larger dataset is necessary, such models suggest that machine learning algorithms are a promising tool to detect and mitigate the growth of dementia in older populations.
在当今社会,寿命的延长导致了退行性疾病患病率的增长,尤其是痴呆症。痴呆症会导致思维过程的恶化和认知功能的下降,特别是思考、推理和记忆。虽然痴呆症不能完全预防,但它的早期发现可以延缓疾病的发作。在机器学习算法的帮助下,可以提炼出早期发现疾病的相关属性,并做出成功的预测。为了进行这项分析,使用了阿尔茨海默病特征和预测痴呆症的探索性数据分析数据集。以下机器学习模型应用于数据集:Naïve贝叶斯,决策树,k近邻和全连接神经网络。在评估准确率得分后,确定Naïve贝叶斯和决策树的混淆矩阵,以在模型中提供最佳结果。虽然需要使用更大的数据集进行进一步的研究,但这些模型表明,机器学习算法是一种很有前途的工具,可以检测和减轻老年人群中痴呆症的增长。
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引用次数: 1
Multilayer Aperture Coupled Single Band Second Order Bandpass Patch Resonator 多层孔径耦合单波段二阶带通贴片谐振器
Pub Date : 2022-06-01 DOI: 10.1109/iemtronics55184.2022.9795731
K. Mohan, Yogesh Kumar Choukiker
Multilayer aperture coupled patch resonator antenna (M-ACRA) introduced to achieve single band second order frequency response. L shaped truncated patch at 12GHz designed to achieve circular polarization and minimize cross polarization at the receiver section. A theoretical approach for demonstrating floquet excitation are explained, furthermore, current distribution of proposed design are demonstrated. Based on analysis mode, the operation principle for equivalent circuit model about proposed designed also discussed. The simulated results and antenna parameters are to be consider for aperture coupled based frequency selective surfaces, reconfigurable frequency selective surfaces, reconfigurable intelligent surface, etc.
采用多层孔径耦合贴片谐振器天线(M-ACRA)实现单频段二阶频率响应。12GHz的L形截尾贴片设计,实现圆极化,最小化接收部分的交叉极化。阐述了floquet激励的一种理论方法,并对所提设计的电流分布进行了论证。在分析模型的基础上,讨论了所设计的等效电路模型的工作原理。考虑了基于孔径耦合的频率选择曲面、可重构频率选择曲面、可重构智能曲面等的仿真结果和天线参数。
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引用次数: 0
Envisioning A Light-Based Quantum-Computational Nano-Cyborg 设想一种基于光的量子计算纳米机器人
Pub Date : 2022-06-01 DOI: 10.1109/iemtronics55184.2022.9795762
Pravir Malik
By viewing light as a symmetrical, multi-layered construct, it is possible to envision a new genre of nano-cyborgs. In general cyborgs can be considered as a portmanteau of cybernetic and organic, and therefore as an entity consisting of both organic and mechatronic parts. However, in the multi-layered model of light subtle information existing in antecedent layers of light can be thought of as materializing through a process of quantization, that subsequently would require a nano-cyborg to interface with it, make sense of it, and act on it. Further quantum-level dynamics would necessitate nano-cyborgs of a tunneling type, annealing type, superposition type, and entanglement type, amongst others, that would have practical applications at nano-levels of different granularity. Such nano-cyborgs are envisioned to be built leveraging computational stratum at different levels of granularity ranging from the electromagnetic level, to the quantum particle level, to the level of atoms, to the level of molecular plans in cells. Immediate application areas of such light-based quantum-computational nano-cyborgs are envisioned to be in medical technology, material sciences, and alteration of genetic-type information, amongst others.
通过将光视为对称的多层结构,我们可以设想一种新型的纳米半机械人。一般来说,赛博格可以被认为是控制论和有机的合成词,因此作为一个由有机和机电部分组成的实体。然而,在光的多层模型中,存在于前一层光中的细微信息可以被认为是通过量子化过程实现的,随后需要纳米机器人与之交互,理解它,并对其采取行动。进一步的量子级动力学将需要隧道型、退火型、叠加型和纠缠型等纳米赛博格,它们将在不同粒度的纳米级上有实际应用。这种纳米机器人被设想在不同粒度的计算层上建立,从电磁水平到量子粒子水平,到原子水平,再到细胞中的分子计划水平。这种基于光的量子计算纳米机器人的直接应用领域被设想为医疗技术、材料科学和基因类型信息的改变等。
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引用次数: 1
期刊
2022 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS)
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