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2021 3rd International Conference on Electrical & Electronic Engineering (ICEEE)最新文献

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Design and Implementation of Bandwidth Based Time Varying Online Exam 基于带宽的时变在线考试的设计与实现
Pub Date : 2021-12-22 DOI: 10.1109/ICEEE54059.2021.9718990
Md. Nazmul Islam, Abdullah Mohammad Tanvirul Hoque, Md. Ahasan Habib
A lots of online courses are other remote education programs are continuing throughout the whole universe as a result of globalization and advancement of modern technology and internet. Examination is a part and parcel of both online and offline education system to evaluate the students took part in the program. In case of online exam numerous techniques were proposed to limit probability of cheating in the examination but no algorithm is available to consider the bandwidth problem for students in low internet speeds. In this paper, a completely new algorithm is designed where the total exam time of the students is dependent on data speed of his device. Moreover, a mock test is arranged with ten students locating different locations to validate the proposed method. The integration of this method with any one high security algorithm will enrich the acceptability of the software to the users.
由于全球化和现代技术和互联网的进步,许多在线课程和其他远程教育项目正在全球范围内继续发展。考试是在线和离线教育系统的重要组成部分,用于评估参加课程的学生。对于在线考试,人们提出了许多技术来限制考试作弊的概率,但没有一种算法可以考虑网速较低的学生的带宽问题。本文设计了一种全新的算法,其中学生的总考试时间取决于其设备的数据速度。此外,还安排了10名学生在不同地点进行模拟测试,以验证所提出的方法。将该方法与任何一种高安全算法相结合,都将丰富软件对用户的可接受性。
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引用次数: 0
Offline Bangla Handwritten Text Recognition: A Comprehensive Study of Various Deep Learning Approaches 离线孟加拉语手写文本识别:各种深度学习方法的综合研究
Pub Date : 2021-12-22 DOI: 10.1109/ICEEE54059.2021.9718890
Farhan Sadaf, S. M. Taslim Uddin Raju, Abdul Muntakim
Offline Handwritten Text Recognition (HTR) is a technique for translating handwritten images into digitally editable text format. Due to the presence of cursive letters, punctuation marks, and compound characters, it is more complex to recognize Bangla handwritten text. Over the years, several approaches to the optical model of the HTR system have been developed, including Hidden Markov Model (HMM) or deep learning techniques such as Convolutional Recurrent Neural Networks (CRNN), and current state-of-the-art Gated-CNN based architectures. Despite this, there are relatively limited works available for Bangla word recognition. In this paper, we introduce an end-to-end system for Bangla word recognition. We used a variety of popular pre-trained CNN architectures, including Xception, MobileNet, and DenseNet, followed by recurrent units such as LSTM or GRU. Furthermore, we experimented with Puigcerver’s CRNN based and Flor’s Gated-CNN based optical model architectulimited works available in Bangla.res. Flor architecture provided the highest recognition rate in our experiment, with a CER of 12.83% and a WER of 36.01%.
脱机手写文本识别(HTR)是一种将手写图像转换为数字可编辑文本格式的技术。由于草书字母、标点符号和复合字符的存在,识别孟加拉语手写文本更加复杂。多年来,HTR系统光学模型的几种方法已经开发出来,包括隐马尔可夫模型(HMM)或深度学习技术,如卷积循环神经网络(CRNN),以及当前最先进的基于门特cnn的架构。尽管如此,可用于孟加拉语单词识别的工作相对有限。本文介绍了一个端到端的孟加拉语词识别系统。我们使用了各种流行的预训练CNN架构,包括excepeption、MobileNet和DenseNet,其次是循环单元,如LSTM或GRU。此外,我们实验了Puigcerver的基于CRNN和Flor的基于gate - cnn的光学模型架构,这些作品在孟加拉可用。floor architecture在我们的实验中提供了最高的识别率,CER为12.83%,WER为36.01%。
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引用次数: 3
Double Plasmonic Layered Electro-Absorption Modulator on Silicon Waveguide 硅波导双等离子体层状电吸收调制器
Pub Date : 2021-12-22 DOI: 10.1109/ICEEE54059.2021.9718801
Riziya Akter Keya, Abdul Khaleque, K. Shaha, Sumaya Akter, Md. Sarwar Hosen
The electro-absorption modulator is the future of photonic integrated circuits technology. In this paper, a double-layered indium tin oxide based electro-absorption modulator is proposed and analyzed through the finite element method. Double plasmonic layers play an effective role to obtain a compact modulator having 3 dB length of 0.2118 μm with higher figure of merit around 797.60 and high extinction ratio of 14.15 dB/μm at 1550 nm. The device can also show a lower insertion loss of around 0.01774 dB/μm at the same wavelength. Therefore, the proposed plasmonic based modulator could be a better candidate for the optical communication.
电吸收调制器是光子集成电路技术的发展方向。本文提出了一种双层氧化铟锡基电吸收调制器,并对其进行了有限元分析。双等离子体层有效地实现了3db长度为0.2118 μm的紧凑调制器,在1550 nm处具有797.60左右的高品质系数和14.15 dB/μm的高消光比。该器件在相同波长下的插入损耗也较低,约为0.01774 dB/μm。因此,所提出的基于等离子体的调制器可能是光通信的一个较好的候选。
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引用次数: 0
FPGA based Histogram Equalization for Image Processing 基于FPGA的直方图均衡化图像处理
Pub Date : 2021-12-22 DOI: 10.1109/ICEEE54059.2021.9718837
Nahin Ul Sadad, Afsana Afrin, Md. Nazrul Islam Mondal
Histogram Equalization is one of the most common algorithms used in image processing applications. Traditional software based histogram equalization using CPU is no longer sufficient for high-computation based real-time image processing applications. To meet high computation demand, image processing operations can be hardware accelerated using Field Programmable Gate Array (FPGA). In this paper, we implemented histogram equalization using Verilog Hardware Description Language (HDL) on Xilinx FPGA for hardware acceleration. The result shows that our FPGA-based histogram equalization is on average 1.5 thousand times faster than traditional software based histogram equalization on CPU.
直方图均衡化是图像处理应用中最常用的算法之一。传统的基于软件的基于CPU的直方图均衡已经不能满足高计算量的实时图像处理应用。为了满足高计算需求,可以使用现场可编程门阵列(FPGA)对图像处理操作进行硬件加速。在本文中,我们使用Verilog硬件描述语言(HDL)在Xilinx FPGA上实现了直方图均衡,以实现硬件加速。结果表明,基于fpga的直方图均衡化比传统的基于软件的CPU直方图均衡化平均快1500倍。
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引用次数: 3
A Backstepping Sliding Mode Controller Design for Synchronous Machine Excitation Systems for Enhancing the Transient Stability 提高同步电机励磁系统暂态稳定性的反步滑模控制器设计
Pub Date : 2021-12-22 DOI: 10.1109/ICEEE54059.2021.9718838
T. S. Joyeeta, T. K. Roy, M. Sheikh
This research proposes a nonlinear composite excitation controller for synchronous generators (SGs) to improve power system stability. First, the nonlinear model is transformed into a reduced-order model using the nonlinear partial feedback linearization approach. Second, the control signal is produced by applying the reduced-order model to the suggested fast reaching law based-backstepping sliding mode controller (BSMC). Following that, the whole system’s stability is maintained by employing the Lyapunov function theory. Finally, a simulation study with a big disturbance is performed to validate the suggested controller’s theoretical notion. In addition, an existing controller is used to demonstrate the superiority of the proposed controller.
为了提高电力系统的稳定性,提出了一种用于同步发电机的非线性复合励磁控制器。首先,利用非线性部分反馈线性化方法将非线性模型转化为降阶模型。其次,将降阶模型应用于所提出的基于快速逼近律的反步滑模控制器(BSMC)产生控制信号。然后,利用李雅普诺夫函数理论来保持整个系统的稳定性。最后,通过大扰动的仿真研究验证了所提控制器的理论概念。另外,用一个已有的控制器验证了所提控制器的优越性。
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引用次数: 0
Deep Transfer Learning Based Multi-Class Brain Tumors Classification Using MRI Images 基于深度迁移学习的MRI多类脑肿瘤分类
Pub Date : 2021-12-22 DOI: 10.1109/ICEEE54059.2021.9719003
Mrinmoy Mondal, Md. Farukuzzaman Faruk, Nasif Raihan, Protiva Ahammed
A brain tumor is a severe disease that can be fatal and significantly impacts one’s quality of life. The traditional method of identifying tumors relies on physicians, which is time-consuming and prone to errors, putting the patient’s life in jeopardy. Identifying the classes of brain tumors is difficult due to the high anatomical and spatial diversity of the brain tumor’s surrounding region. An automated and precise diagnosis approach is required to treat this severe disease effectively. Deep learning technology, such as CNN, can be used to diagnose various tumor types in the early stages of their development using brain MRI. In this study, a deep transfer learning framework based on VGG-19 is introduced to accurately detect three common kinds of tumors from brain MRI. There are primarily two phases to the suggested framework. The VGG-19 frozen part is the first phase, while the modified neural style classification part is the second phase. With certain modified techniques, the class imbalance impact within the MRI dataset and the generalization error issue during the training process were also resolved. The proposed model has a 94% classification accuracy and a 94% F1-score.
脑肿瘤是一种严重的疾病,可能是致命的,并严重影响一个人的生活质量。传统的肿瘤识别方法依赖于医生,这既耗时又容易出错,危及患者的生命。由于脑肿瘤周围区域的高度解剖和空间多样性,确定脑肿瘤的类别是困难的。为了有效地治疗这种严重疾病,需要一种自动化和精确的诊断方法。CNN等深度学习技术可以通过大脑MRI在肿瘤发展的早期阶段诊断出各种类型的肿瘤。本研究引入基于VGG-19的深度迁移学习框架,从脑MRI中准确检测三种常见肿瘤。建议的框架主要分为两个阶段。VGG-19冻结部分为第一阶段,修正神经风格分类部分为第二阶段。通过一定的改进技术,解决了MRI数据集中的类不平衡影响和训练过程中的泛化误差问题。所提出的模型具有94%的分类精度和94%的f1得分。
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引用次数: 5
Performance Analysis of Textile Antennas for Body Worn Application 用于人体磨损的纺织天线性能分析
Pub Date : 2021-12-22 DOI: 10.1109/ICEEE54059.2021.9718796
Sadia Enam, M. Rana
This paper presents conventional shaped (rectangular elliptical, and circular) textile antennas performance and SAR analysis with and without human body tissue model (HBTM) at 2.45 GHz. The antenna design involved a coaxial probe feeding technique and fabric substrates (wash cotton, curtain cotton, and polycot) of 3 mm thickness. At 2.45 GHz WLAN band, both for OFF body and ON body, circular antenna with curtain cotton presents an overall superior performance in terms of return loss (−60.9995 dB and −52.423 dB), VSWR (1.0018 and 1.0048), peak directivity (8.969 dBi and 8.825 dBi), gain (7.391 dBi and 7.109 dBi), and radiation efficiency (69.81% and 68.07%) maintaining a bandwidth (BW) of 108.2 MHz and 107.4 MHz at −10dB. The antennas are also analyzed in close proximity (2 mm away) to a three-layered (skin, fat, and muscle) flat body phantom to determine the Specific Absorption Rate (SAR). The SAR recorded for circular MPA (curtain cotton) is 0.0293 W/kg< 2 W/kg averaged over 10g tissue. The overall simulation is done using CST Microwave Studio software. The proposed antenna is considered to be an effective antenna for on body wireless communication.
本文介绍了传统形状(矩形椭圆和圆形)纺织天线在2.45 GHz下的性能和在使用和不使用人体组织模型(HBTM)时的SAR分析。天线设计包括同轴探针馈送技术和3毫米厚的织物基板(水洗棉、窗帘棉和聚棉)。在2.45 GHz频段,无论是OFF体还是ON体,幕布圆形天线在回波损耗(- 60.9995 dB和- 52.423 dB)、VSWR(1.0018和1.0048)、峰值方向性(8.969 dBi和8.825 dBi)、增益(7.391 dBi和7.109 dBi)和辐射效率(69.81%和68.07%)方面均表现出总体优势,在- 10dB时保持108.2 MHz和107.4 MHz的带宽(BW)。天线也在近距离(2毫米外)分析三层(皮肤、脂肪和肌肉)平面体模体,以确定比吸收率(SAR)。圆形MPA(窗帘棉)的SAR记录为0.0293 W/kg< 2 W/kg,平均超过10g组织。采用CST Microwave Studio软件进行整体仿真。该天线被认为是一种有效的体上无线通信天线。
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引用次数: 0
Optimization-based Energy Management System to Minimize Electricity Bill for Residential Customer 基于优化的能源管理系统,实现住宅用户电费最小化
Pub Date : 2021-12-22 DOI: 10.1109/ICEEE54059.2021.9718575
Sancoy Barua, N. Mohammad
In order to meet the increasing growth of energy demand, incorporation of renewable resources appears to be a viable solution. With the increase of renewable integration, a big challenge is to handle these intermittent resources in a smart way. An effective approach can be the optimal management of energy of Solar PV panels and energy storage besides the main utility. In this research, an optimization method is employed to manage variable load demand to minimize the overall electricity bill of residential house over a period of 24 hours. Optimization approach schedules the energy resources and decides, when to use grid or cut it off, depending on the availability of solar power, state-of-charge (SOC) of ESS and dynamic electricity tariffs. The impact of using smart energy management system (EMS), is tested by executing three different plausible cases. To verify and validate the real time behaviors of the model, optimization results are compared with the static electricity tariffs and a substantial cost reduction is observed.
为了满足日益增长的能源需求,结合可再生资源似乎是一个可行的解决办法。随着可再生能源整合的增加,一个巨大的挑战是以一种智能的方式处理这些间歇性资源。除了主要的公用事业外,太阳能光伏板的能量优化管理和储能是一种有效的方法。本研究采用一种优化方法对变负荷需求进行管理,使住宅24小时内的总电费达到最小。优化方法根据太阳能的可用性、ESS的充电状态(SOC)和动态电价,调度能源资源并决定何时使用电网或切断电网。使用智能能源管理系统(EMS)的影响,通过执行三个不同的貌似合理的案例进行测试。为了验证模型的实时行为,将优化结果与静电电价进行比较,观察到成本大幅降低。
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引用次数: 6
Predicting Autism Spectrum Disorder Based On Gender Using Machine Learning Techniques 使用机器学习技术基于性别预测自闭症谱系障碍
Pub Date : 2021-12-22 DOI: 10.1109/ICEEE54059.2021.9718798
Tania Akter, M. Ali
Autism is a set of complicated developmental disorders marked by social skills impairments, communication difficulties (verbal and nonverbal), and recurring behavior. Autistic children are frequently alienated as a result of these impairments. Rapid recognition of autism can help to establish a treatment strategy and lessen the burden on sufferers. As a result, effective methods to early diagnosis and treatment for ASD are necessary. The toddler, child, adolescent, and adult screening datasets are collected in this study and separated according to gender (male and female). By using random oversampling (ROS), these datasets are balanced. Next, different classifiers are applied to both the primary and balanced datasets. The MLP classifier produced the best results, and the hyperparameter for it was tuned to improve autism identification rate. However, the experimental outcome for the female dataset is better than the male dataset. The shapely adaptive explanation (SHAP) method is also employed to assess the significant features of male and female.
自闭症是一组复杂的发育障碍,其特征是社交技能障碍、沟通困难(语言和非语言)和反复出现的行为。由于这些缺陷,自闭症儿童经常被疏远。快速识别自闭症有助于制定治疗策略,减轻患者的负担。因此,有必要采取有效的方法对ASD进行早期诊断和治疗。本研究收集了幼儿、儿童、青少年和成人筛查数据集,并根据性别(男性和女性)进行了分类。通过使用随机过采样(ROS)来平衡这些数据集。接下来,对主数据集和平衡数据集应用不同的分类器。MLP分类器产生了最好的结果,并对其超参数进行了调整,以提高自闭症识别率。然而,女性数据集的实验结果优于男性数据集。采用形状适应解释(SHAP)方法对男女显著性特征进行评价。
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引用次数: 0
Unreal Engine Blueprint: Developing Hack and Slash Using Spawn Projectile Method 虚幻引擎蓝图:开发Hack和Slash使用刷出射弹方法
Pub Date : 2021-12-22 DOI: 10.1109/ICEEE54059.2021.9718774
Shadib Mahmud, S. S. Ghosh
Spawn projectile method is an algorithm where projectiles are created and it generates output on the basis of the collision of those projectiles. Spawn projectile methods are widely used in any shooting game in the Unreal engine blueprint framework with a ray-tracing feature or other features. Hack and Slash games are mainly close combat action games where Socket collider methods are used for core features and projectile-based weapons may be used as secondary options or other unique methods which are not widely used in a game. Firing system of first and third-person shooting games, selected assets with a skeletal mesh, secondary attack, or special abilities of a player were successfully implemented by using the spawn projectile method as a central algorithm. This research found that Hack and Slash games also can be designed based on the basic algorithm of spawn projectile method, which is mainly an enhanced domain of the current features of Unreal Engine 4.
Spawn抛射方法是一种算法,其中抛射被创建,它产生的输出的基础上碰撞这些抛射。刷出弹丸方法被广泛应用于任何射击游戏在虚幻引擎蓝图框架与光线追踪功能或其他功能。《Hack and Slash》主要是近距离战斗动作游戏,其中Socket对撞机方法被用于核心功能,基于弹射的武器可能被用作次要选择或其他在游戏中并未广泛使用的独特方法。第一人称和第三人称射击游戏的射击系统、带有骨骼网格的选定资产、二次攻击或玩家的特殊能力通过使用刷出射弹方法作为中心算法成功实现。本研究发现砍杀类游戏也可以基于刷出抛射法的基本算法进行设计,刷出抛射法主要是虚幻引擎4当前特性的增强领域。
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引用次数: 0
期刊
2021 3rd International Conference on Electrical & Electronic Engineering (ICEEE)
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