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2023 Second International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)最新文献

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Solving Economic Load Dispatch Problem with Mountaineering Team-Based Optimization Technique 基于登山队优化技术解决经济负荷调度问题
Y. Reddy, M. L. Ramanaiah
The Economic load dispatch (ELD) optimally allocating available generating units based on required load demand by satisfying the constraints. Based on the input output characteristics of boiler-turbine-generator set the operating cost is a convex cost function. Under practical condition including the valve point effect (VPE), ramp rate limits (RRL), prohibited operating zones (POZs) and multiple fuels makes the cost function as non-convex and ELD is a complex problem. In order to handle complex ELD problem, a novel human intelligence-based metaheuristic optimization technique called the mountaineering team-based optimization (MTBO) algorithm is proposed in this paper. The MTBO algorithm is based on the social behaviour of people as they climb mountains. In order to solve optimization problems, the proposed MTBO algorithm captures the phases of the regular and guided movement of climbers based on the leader's experience, barriers to reaching the peak and becoming stuck in local optimality, and the coordination and social cooperation of the group to protect members from natural hazards. To evaluate the efficiency of the suggested algorithm, three different cases are considered to solve the ELD problem. The MTBO method outperforms the competition in terms of robustness, ease of implementation, effective optimization performance for optimal global solutions.
经济负荷调度(Economic load dispatch, ELD)是在满足约束条件的基础上,对发电机组进行优化配置。基于锅炉-汽轮发电机组的输入-输出特性,运行成本是一个凸成本函数。在实际工况下,包括阀点效应(VPE)、匝道限速(RRL)、禁止作业区(POZs)和多种燃料使得成本函数是非凸的,ELD是一个复杂的问题。为了解决复杂的地形优化问题,本文提出了一种基于人类智能的元启发式优化技术——登山队优化算法。MTBO算法是基于人们爬山时的社会行为。为了解决优化问题,提出的MTBO算法根据领队的经验,捕捉登山者的规则和引导运动阶段,到达顶峰的障碍和陷入局部最优状态,以及群体的协调和社会合作,以保护成员免受自然灾害。为了评估该算法的效率,我们考虑了三种不同的情况来解决ELD问题。MTBO方法在鲁棒性、易实现性、对全局最优解的有效优化性能等方面优于同类方法。
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引用次数: 0
DeepGAN: An Enhanced Approach for Detecting Brain Tumor 深度gan:一种检测脑肿瘤的增强方法
Megala G, N. Kumari
Brain Tumor is a major disease that affected in children and adults. This happens when changes occur in brain cell development and may lead the cells to partition uncontrolled and turbulently. Misclassification of these tumor cells may lead to consequences. The main objective of our examination is to distinguish the powerful and prescient calculation for the identification of bosom malignant growth, utilizing AI calculations, and figure out the best way concerning exactness and accuracy. DeepGAN is a neural network model proposed for identifying and detecting brain Tumors in the MRI images of patients. The raw MRI images are preprocessed and then passed to the generator and discriminator of the proposed model in order to extract salient features and detect a tumor. The proposed model is evaluated on computing precision, recall, specificity, sensitivity, and accuracy. From the experimental results, the DeepGAN model outperforms with 99% of accuracy on detecting tumors.
脑肿瘤是影响儿童和成人的主要疾病。这种情况发生在脑细胞发育发生变化时,可能导致细胞分裂失控和动荡。这些肿瘤细胞的错误分类可能导致后果。我们研究的主要目的是利用人工智能计算,区分出识别胸部恶性生长的强大而有先见之明的计算,并找出关于准确性和准确性的最佳方法。DeepGAN是一种用于识别和检测患者MRI图像中脑肿瘤的神经网络模型。原始的MRI图像经过预处理,然后传递给该模型的生成器和鉴别器,以提取显著特征并检测肿瘤。该模型在计算精度、召回率、特异性、灵敏度和准确性等方面进行了评估。从实验结果来看,DeepGAN模型在检测肿瘤方面的准确率达到99%。
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引用次数: 0
Statistical Impact Analysis of Integration of different types of WTG on Radial Distribution System 不同类型WTG集成对径向配电系统的统计影响分析
Ankush Tandon, Pooja Jain, Abhinav Goyal, Aditya Sharma, Anoop Gupta, Anmay Kapoor
A nation's ability to obtain electrical energy determines its socio economic progress. While keeping in mind different operational and technological restrictions, planning for distribution system expansion considers the services that must be installed for the distribution networks to manage the expected load demand. When distributed generation sources (DGs) are integrated, distribution network efficiency is increased, power losses are decreased, and voltage magnitude is also enhanced. In this paper, Wind Turbine Generator (WTG) as renewable energy source of four different types are integrated under two unique control scheme in conventional radial distribution topology. A statistical analysis of WTG integration is carried out for conventional 34 bus radial distribution system using ETAP simulation package on single and multiple locations. Voltage magnitude were analyzed under critical, marginal and nominal level before and after integrating DGs in test system. In addition to this loss reduction is also noted and analyzed while incorporating different types of WTGs.
一个国家获得电能的能力决定了其社会经济的发展。在考虑不同的操作和技术限制的同时,规划配电系统扩展要考虑必须为配电网络安装的服务,以管理预期的负载需求。分布式电源集成后,配电网效率提高,功率损耗降低,电压幅值增大。本文将风力发电机组作为四种不同类型的可再生能源,在传统的径向分布拓扑中,采用两种独特的控制方案进行集成。利用ETAP仿真包对传统34总线径向配电系统的单点和多点WTG集成进行了统计分析。分析了测试系统集成dg前后在临界、边际和标称水平下的电压幅值。此外,在采用不同类型的wtg时,还注意并分析了这种损失减少。
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引用次数: 0
On Applying the BRH Curve in Digital Signature Scheme BRH曲线在数字签名方案中的应用
Batool Hatem Akar AlKfari, R. K. Ajeena
One of the most popular algorithm security solutions for ensuring the enforgeability and non-repudiation of digital data is the elliptic curve digital signature technique. The scalar multiplication process is strongly reliant on it for speed. The proposed BRH curve is used to implement the digital signature algorithm to give alternative version of elliptic curve digital signature algorithm (ECDSA). Using BRH-digital signature algorithm (BRH-DSA) reduces calculating the addition and doubling operations of points that are lying on BRH curve. On BRH-DSA, more secure communications for encryption schemes are been done in compare to the original ECDSA.
椭圆曲线数字签名技术是确保数字数据的可执行性和不可否认性的最流行的算法安全解决方案之一。标量乘法过程在速度上非常依赖于它。利用所提出的BRH曲线实现数字签名算法,给出了椭圆曲线数字签名算法(ECDSA)的替代版本。使用BRH数字签名算法(BRH- dsa)减少了BRH曲线上点的加法运算和加倍运算。与原来的ECDSA相比,在BRH-DSA上实现了更安全的加密方案通信。
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引用次数: 0
Design of a Compact and Efficient Monopole Antenna for ISM Band Applications 一种适用于ISM波段的小型高效单极天线设计
Deepali Pathak, SriHarsha Vardhan, A. Dutta
In this paper, a low cost, highly efficient and compact monopole antenna for Industrial, Scientific, and Medical (ISM) applications is presented. A new spiral coil rectangular shape structure possessing meander lines is designed to achieve a resonance at 0.915 GHz response with an Omni-directional radiation pattern. The proposed architecture makes the miniaturization by turning the conducting transmission lines as coil to both left and right part of the feedline to follow symmetry in current distribution. The ground plane has been adjusted in such a way to get proper impedance because if the area of ground plane increases input impedance shift to inductive region and resonant frequency decreases respectively. Ansys HFSS 3D High Frequency Simulation Software has been used to carry out the analysis of the presented antenna. The overall volume of the proposed antenna is 4.5 X 4.5 cm2 whereas the FR4 material is used as a substrate with a relative permittivity and loss tangent of 4.4 and 0.025, correspondingly. The peak gain of 0.88 dBi is achieved with a radiation efficiency of 80 to 98% for the desired band.
本文提出了一种低成本、高效率、紧凑的单极天线,用于工业、科学和医疗(ISM)应用。设计了一种具有弯曲线的新型螺旋线圈矩形结构,以实现0.915 GHz的全向辐射响应。所提出的结构通过将导电传输线作为线圈旋转到馈线的左右两端以遵循电流分布的对称性来实现小型化。由于地平面面积增大,输入阻抗向感应区偏移,谐振频率减小,因此对地平面进行了调整,得到了合适的阻抗。利用Ansys HFSS三维高频仿真软件对所设计的天线进行了分析。所提出天线的总体体积为4.5 X 4.5 cm2,而FR4材料用作衬底,相应的相对介电常数和损耗正切为4.4和0.025。峰值增益为0.88 dBi,期望波段的辐射效率为80%至98%。
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引用次数: 0
Performance Analysis on Induction Motor Integrated Wide Band Gap Bidirectional Converter for Low Power Traction Applications 低功率牵引用感应电机集成宽带隙双向变换器性能分析
M. Deepak, G. Janaki, C. Bharatiraja
The wide band gap devices Gallium Nitride (GaN) and Silicon Carbide (SiC) solutions are becoming more popular in high-voltage power electronic applications. Also, they provide lower switching losses and the ability to increase switching frequencies. On the other hand, magnet less induction motor (IM) drive offers superior performance compared to other electrical machines. This paper proposed a hybrid combination of IM and bidirectional DC-DC power converters in Electric Vehicles (EVs) that helps to improve the overall performance. Therefore, improving IM and DC-DC converter topologies is essential in the future development of EV infrastructure. The integrated module reduces the cost, volume, weight, and compact size to increase the performance and consistency of the vehicle. As a solution, an IM-based DC-DC dual active bridge bidirectional converter analyzes the dynamic behavior of the machine. The implementation of this work is executed using MATLAB software. The simulation results show that the suggested design of the IM and power converter module has greater efficiency.
宽带隙器件氮化镓(GaN)和碳化硅(SiC)解决方案在高压电力电子应用中越来越受欢迎。此外,它们提供更低的开关损耗和提高开关频率的能力。另一方面,与其他电机相比,无磁铁感应电机(IM)驱动提供了卓越的性能。本文提出了一种混合组合的IM和双向DC-DC功率转换器在电动汽车(ev)有助于提高整体性能。因此,改进IM和DC-DC转换器拓扑结构对未来电动汽车基础设施的发展至关重要。集成模块降低了成本、体积、重量和紧凑的尺寸,从而提高了车辆的性能和一致性。作为解决方案,基于im的DC-DC双有源桥双向变换器分析了机器的动态行为。本工作的实现是利用MATLAB软件进行的。仿真结果表明,所提出的IM和功率转换器模块设计具有较高的效率。
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引用次数: 0
Ensemble deep learning prediction of STEMI using ECG signals 基于心电信号的STEMI集成深度学习预测
Kanimozhi J, Hemalatha Karnan, UmaMaheshwari Durairaj
Myocardial infarction or heart attack is caused due to atherosclerotic plaque deposition in the coronary arteries thereby occluding the artery, which leads to decrease in blood flow and oxygen supply to the specific regions of the heart muscles. For diagnostic purpose, ECG is used which shows the ST elevation, negative T wave and pathologic Q wave. Classification of myocardial infarction from the normal ECG is handled in this work using the ensemble model of CNN, LSTM and BiLSTM algorithm. The myocardial infarction dataset [10506X188] and normal ECG dataset [4046X188] are retrieved from the PTB Diagnostic ECG Database. The tabular datasets in the size of [14553X191] consisting of abnormal and normal signals and the labels are generated prior to classification. Preprocessing steps involve the signal extraction and signal denoising of both the signal types. The tabular datasets are k-fold cross- validated for training, validation and testing. The split data are trained using CNN, LSTM and BiLSTM network layers individually. The ensemble model, thenceforth, combining all these three networks consecutively is evaluated for the performance in terms of training accuracy 100% and confusion chart for all the four models is also compared.
心肌梗死或心脏病发作是由于冠状动脉粥样硬化斑块沉积,阻塞动脉,导致心肌特定区域的血流量和供氧减少。心电图显示ST段抬高、负T波和病理性Q波,用于诊断。本工作采用CNN、LSTM和BiLSTM算法的集成模型对心肌梗死与正常心电图进行分类。心肌梗死数据集[10506X188]和正常心电图数据集[4046X188]从PTB诊断心电图数据库中检索。分类前生成大小为[14553X191]的表格数据集,由异常信号和正常信号以及标签组成。预处理步骤包括两种信号的信号提取和信号去噪。表格数据集经过k折交叉验证,用于训练、验证和测试。分割后的数据分别使用CNN、LSTM和BiLSTM网络层进行训练。然后,对这三种网络连续组合的集成模型的训练准确率进行了100%的评价,并对四种模型的混淆图进行了比较。
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引用次数: 0
Design of Microstrip Patch Antenna At 3.5 GHz Frequency Using FEKO Simulation 基于FEKO仿真的3.5 GHz微带贴片天线设计
Ramakrishna Ch, Krishna Chaitnaya Varma A, Rangarao Orugu, V. V. S. S. Ch, K. M, Venkateswara Rao Ch
A fundamental microstrip patch antenna is made up of a ground and a metallic patch separated by a dielectric layer known as the substrate. These antennas are commonly used in communications, especially in military and civil applications. This study uses FEKO simulation software to design and simulate a microstrip patch antenna that operates at 3.5 GHz. The design process involves selecting an appropriate substrate material and its thickness, determining the patch dimensions, selecting the ground plane dimensions, creating a simulation model in FEKO, and analysing the performance in terms of directivity, radiation pattern, and gain. Several challenges involved in the design process are discussed, including substrate material selection, patch dimensions, ground plane dimensions, simulation accuracy, optimization, and fabrication tolerance. These challenges are addressed through careful consideration of the antenna design parameters and the use of FEKO simulation software to accurately model and simulate the antenna's performance. The simulation results demonstrate that the designed microstrip patch antenna at 3.5 GHz frequency meets the desired performance specifications. The antenna has a return loss of −20 dB, a radiation pattern that is nearly omnidirectional, and a gain of 2.5 dBi. The simulation results demonstrate the effectiveness of the proposed design process and the utility of FEKO simulation software for designing microstrip patch antennas at 3.5 GHz frequency.
基本微带贴片天线由一个地被称为衬底的介电层隔开的地和金属贴片组成。这些天线通常用于通信,特别是在军事和民用应用中。本研究利用FEKO仿真软件设计并仿真了工作频率为3.5 GHz的微带贴片天线。设计过程包括选择合适的衬底材料及其厚度,确定贴片尺寸,选择接地面尺寸,在FEKO中创建仿真模型,并分析指向性,辐射方向图和增益方面的性能。讨论了设计过程中涉及的几个挑战,包括衬底材料选择、贴片尺寸、接地面尺寸、仿真精度、优化和制造公差。通过仔细考虑天线设计参数和使用FEKO仿真软件精确建模和模拟天线的性能,解决了这些挑战。仿真结果表明,所设计的3.5 GHz频率微带贴片天线达到了预期的性能指标。天线的回波损耗为- 20 dB,辐射方向图几乎是全向的,增益为2.5 dBi。仿真结果验证了所提设计过程的有效性,以及FEKO仿真软件在3.5 GHz频段微带贴片天线设计中的实用性。
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引用次数: 0
Center Fitting Shadowing Property for Partial Hyperbolic Diffeomorphisms 部分双曲微分同态的中心拟合阴影性质
D. M. Al-Ftlawy, Iftichar M. T. Al-Shara’a
The idea of shadowing in dynamical systems theory (DS) is to approximate the pseudo-orbit (PO) of certain dynamical systems (DS) by real orbits of course, depending on the type of approximation. The aim of this work to explain the stable fitting shadowing property for partially hyperbolic diffeomorphism, to clarification that if partially hyperbolic diffeomorphism contain $w_{i}$, where $i=1,2$ saddle points with indices not equal, then $mathcal{L}:Mrightarrow M$ does not satisfy the fitting shadowing property FSP. On other hand can be achieved fitting shadowing property of a closed $C^{infty}$ of M(i.e., boundary less and compact) if the center is uniformly compact center foliation $(W^{c})$, to proof the main Theorem K.
在动力系统理论(DS)中,阴影的思想是用实际轨道来近似某些动力系统(DS)的伪轨道(PO),当然,这取决于近似的类型。本文的目的是解释部分双曲微分同态的稳定拟合阴影性质,说明如果部分双曲微分同态包含$w_{i}$,其中$i=1,2$鞍点的指标不相等,则$mathcal{L}:Mrightarrow M$不满足拟合阴影性质FSP。另一方面可以实现M(即)的封闭$C^{infty}$的拟合遮蔽性。,无边界紧)如果中心是一致紧中心叶理$(W^{c})$,证明主要定理K。
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引用次数: 0
Deep learning based mobile application for varietal identification and ripeness grading of traditional Indian banana varieties 基于深度学习的印度传统香蕉品种鉴定和成熟度分级移动应用
Shuprajhaa T, Mathav Raj J, S. P., Sheeba K N, Dhayalini K
India is the largest producer of bananas, con-tributing to 1/5th of the world production. Traditional Indian banana varieties have their own health benefits and consumer preferences. Grading of ripening stages is essential for quality check during handling and export as well as domestic market consumer acceptance. The proposed work is aimed to develop a smart phone based mobile application capable of identification of various traditional Indian banana varieties along with the grading of its ripening stages. Image processing is the better choice for identification of banana varieties and the determination of colour dependent ripening stages. Combining multiple aspects of deep learning inclusive of Convolution neural network (CNN) and eXtreme Gradient Boosting (XGboost) algorithm (CNN-XGBoost), a varietal identification and ripeness grading model is developed. Images of the banana fruits are fed to the network, where the CNN acts as the trainable feature extractor of the images and XGboost in the last layer of the CNN acts as the identifier of variety and ripening stage. The identification accuracy of the proposed model is 95 % which is higher than other techniques such as Gaussian Naive Bayes classifier (66 %), support vector classifier (83.5 %) and k-nearest neighbourhood algorithm (90 %). The developed model is deployed into smart phone based mobile application to facilitate non-invasive varietal identification of banana fruits. The developed app is capable to identify various unique Indian traditional banana varieties and could provide detailed insights on the ripening stages. The computational complexity of the developed model is also lesser which reduces the computational burden of the mobile application. The developed mobile application could be of great help to the consumers to decide upon the right variety and the optimal stage of ripening to be consumed for their dietary requirement.
印度是最大的香蕉生产国,占世界香蕉产量的五分之一。传统的印度香蕉品种有其自身的健康益处和消费者偏好。成熟阶段的分级对于处理和出口过程中的质量检查以及国内市场消费者的接受程度至关重要。拟议的工作旨在开发一种基于智能手机的移动应用程序,能够识别各种传统的印度香蕉品种,并对其成熟阶段进行分级。图像处理是香蕉品种识别和颜色依赖成熟阶段确定的较好选择。结合卷积神经网络(CNN)和极限梯度提升(XGboost)算法(CNN- XGboost)等深度学习的多个方面,建立了一个品种识别和成熟度分级模型。将香蕉果实的图像输入网络,其中CNN作为图像的可训练特征提取器,CNN最后一层的XGboost作为品种和成熟阶段的标识符。该模型的识别准确率为95%,高于高斯朴素贝叶斯分类器(66%)、支持向量分类器(83.5%)和k近邻算法(90%)等其他技术。将开发的模型部署到基于智能手机的移动应用程序中,方便香蕉果实的无创品种鉴定。开发的应用程序能够识别各种独特的印度传统香蕉品种,并可以提供成熟阶段的详细见解。所开发模型的计算复杂度也较低,从而减少了移动应用程序的计算负担。开发的移动应用程序可以极大地帮助消费者决定正确的品种和最佳成熟阶段,以满足他们的饮食需求。
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引用次数: 0
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2023 Second International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)
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