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2023 International Conference on electronics, Information, and Communication, ICEIC 2023

作者： Jeon, Yujin Ham, Eunkyung Lim, Jaeyun Kim, Ji-Hoon Ewha Womans University Department of Electronic and Electrical Engineering Seoul Korea Republic of Ewha Womans University Smart Factory Multidisciplinary Program Seoul Korea Republic of

ISBN: (纸本)9798350320213

AES-CCM (Advanced Encryption Standard-Counter with CBC-MAC) is an encryption and decryption method that guarantees the integrity and authenticity of data, commonly used for wireless security systems. The AES Core performs the central functions for encryption and decryption of the AES-CCM, so many studies are being conducted to implement it efficiently. In this paper, to investigate the impact of the hardware-software partitioning of the AES-CCM implementation for Bluetooth LE (Low Energy), we compare the results between the software-only implementation and hardware-software co-design approach where the AES encryption into the hardware and the rest into the software. As a result, a well-balanced co-design implementation of the AES-CCM shows a reduced latency of up to 77.4% compared to the software-only implementation for the Bluetooth LE system. © 2023 IEEE.

关键词： AES AES-CCM Bluetooth LE Security Hardware-Software Co-Design

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High-Throughput Independent Component Analysis Processor for Full Duplex Systems

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IEEE Journal on Selected Areas in Communications 2023年第9期41卷 2821-2832页

作者： Cheng, Jen-Hao Chang, Tien-Min Shen, Chung-An Fouda, Mohammed E. Eltawil, Ahmed M. National Taiwan University of Science and Technology Department of Electronic and Computer Engineering Taipei10607 Taiwan University of California at Irvine Electrical Engineering and Computer Science Department IrvineCA92697 United States King Abdullah University of Science and Technology Electrical and Computer Engineering Program Thuwal23955 Saudi Arabia

This paper presents the algorithm and very-large-scale integration (VLSI) architecture of a high-throughput and highly efficient independent component analysis (ICA) processor for self-interference cancellation (SIC) in in-band full-duplex (IBFD) systems. This is the first VLSI architecture reported in the literature based on the state-of-the-art entropy bound minimization (EBM) approach. A novel ICA algorithm is presented in this paper with momentum gradient descent optimization. Simulation results show that the number of iterations for the proposed algorithm is significantly reduced compared to the conventional ICA algorithms. Furthermore, a novel early-distribution estimation scheme is proposed in the designed ICA processor to compute multiple distribution functions with low latency and low complexity. The processing flow and the efficiency for the hardware utilization are specifically designed so that the processing speed is maximized with minimum employment of hardware components. The proposed ICA processor is designed and implemented based on the application-specific-integrated circuit (ASIC) flow. The post-layout estimations show that compared with the conventional EBM-based scheme, the proposed design improves the throughput and efficiency by 30x. In addition, compared to prior designs shown in the literature, the proposed ICA processor also demonstrates a significant enhancement in terms of throughput and efficiency. © 1983-2012 IEEE.

关键词： VLSI circuits

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Adaptive Two-Stage Filter for De-snowing LiDAR Point Clouds 5

Adaptive Two-Stage Filter for De-snowing LiDAR Point Clouds

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5th International Conference on Control, Robotics and Informatics, ICCRI 2022

作者： Le, Minh-Hai Cheng, Ching-Hwa Liu, Don-Gey Nguyen, Thanh-Tuan Feng Chia University Program of Electrical and Communications Engineering Taichung Taiwan Feng Chia University Department of Electronic Engineering Taichung Taiwan

ISBN: (数字)9781665468008

ISBN: (纸本)9781665468008

The Light Detection And Ranging (LiDAR) is integrated into self-driving cars to enhance system reliability. Unfortunately, its effectiveness is severely limited under the extreme weather conditions such as rain, fog, and cloud. This paper proposes an adaptive filter that can remove snow particles (de-snowing) from raw LiDAR point clouds. The proposed method adopts the intensity threshold with a two-stage filter that provides outstanding performance on both accuracy (98%) and processing speed (1.42 frames per second) under extreme environment for the autonomous driving system. © 2022 IEEE.

关键词： Adaptive filters

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Unleashing Endurance Limits of Emerging Memory: Multi-Level FeRAM Recovery Array Empowered by a Coordinated Inverting Amplifier Circuit

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IEEE Transactions on Electron Devices 2024年第4期71卷 2708-2713页

作者： Hsiang, K.-Y. Chang, F.-S. Lou, Z.-F. Aich, A. Senapati, A. Lee, J.-Y. Li, Z.-X. Chen, J.-H. Liu, C.-H. Liu, C.W. Maikap, S. Su, P. Hou, T.-H. Lee, M.H. National Yang Ming Chiao Tung University Institute of Electronics Hsinchu300 Taiwan National Taiwan University Program for Semiconductor Devices Materials and Hetero-Integration Taipei10617 Taiwan National Taiwan University Graduate Institute of Electronics Engineering Taipei10617 Taiwan Chang Gung University Department of Electronic Engineering Guishan33302 Taiwan National Taiwan Normal University Institute of Electro-Optical Engineering Taipei11677 Taiwan

Asymmetric field cycling recovery (AFCR) with alternating opposite low E -field cycling is proposed to restore a fatigued ferroelectric (FE) capacitor and is experimentally demonstrated for up to 1012 switching cycles, thereby extending the endurance of FeRAM. Positive and negative asymmetric minor loops (AmLs) with AFCR exhibit nondegradation and complete restoration of Δ 2P r toward unlimited endurance operation. Furthermore, an FE random access memory (FeRAM) array circuit with an inverting amplifier is designed to simultaneously execute Write/Read and Recovery procedures via the AFCR scheme. © 1963-2012 IEEE.

关键词： Ferroelectricity

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ViT-slice: End-to-end Vision Transformer Accelerator with Bit-slice Algorithm 24

ViT-slice: End-to-end Vision Transformer Accelerator with Bi...

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61st ACM/IEEE Design Automation Conference, DAC 2024

作者： Shin, Dongjin Choi, Insu Yang, Joon-Sung Department of Electrical and Electronic Engineering Yonsei University Seoul Korea Republic of Department of Systems Semiconductor Engineering Yonsei University Seoul Korea Republic of BK21 Graduate Program in Intelligent Semiconductor Technology Yonsei University Seoul Korea Republic of

ISBN: (纸本)9798400706011

Vision Transformers have demonstrated remarkable performance in various vision tasks. However, general-purpose processors, such as CPUs and GPUs, face challenges in efficiently handling the inference of Vision Transformers. To address the issue, prior works have focused on accelerating only attention due to its high computational cost in NLP Transformers. In contrast, Vision Transformers demonstrate a higher computational cost due to linear modules such as linear transformation, linear projection and Feed-Forward Network (FFN), compared to attention. In this paper, we present ViT-slice, an algorithm-architecture co-design that enhances end-to-end performance and energy efficiency by optimizing not only attention but also linear modules. At the algorithm level, we propose bit-slice compression that avoids storing the redundant most significant bits (MSBs). Additionally, we present bit-slice dot product with early skip to efficiently compute the dot product using bit-sliced data. To enable early skip during the dot product computation, we leverage a trainable threshold. On the hardware level, we introduce a specialized bit-slice dot product unit (BSDPU) to efficiently process the bit-slice dot product with early skip algorithm. Additionally, we present a bit-slice encoder and decoder for on-chip bit-slice compression. ViT-slice achieves 244×, 35.3×, 16.8×, 10.4×, 5.0× end-to-end speedup over Xeon CPU, EdgeGPU, TITAN Xp GPU, Sanger accelerator and ViTCoD accelerator, respectively. © 2024 Copyright held by the owner/author(s).

关键词： Linear transformations

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Implementation of Multi-process Automatic Loading and Unloading Production System

Implementation of Multi-process Automatic Loading and Unload...

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2023 International Conference on Consumer electronics - Taiwan, ICCE-Taiwan 2023

作者： Tung, Li-Chiuan Chen, Shu-Hung Ye, Yu-Cheng Liu, Guan-Zhi Chen, Lin-Yin Tu, Yu-Rou Lai, Yen-Wen Lee, Jeng-Dao National Formosa University Department of Automation Engineering Yunlin Taiwan Ming Chuan University Department of Electronic Engineering Taoyuan City Taiwan National Yunlin University of Science and Technology Doctoral Program in Industrial Engineering and Management Yunlin Taiwan

ISBN: (纸本)9798350324174

This research develops an intelligent automatic production loading and unloading solution for a multi-process part. According to the posture required for each processing operation of each part, a novel gripper and carrier that can implement multi-position clamping are designed. The Beckhoff controller is adopted as the host controller in the control system to integrate the robotic arm (including the vision system), the automated guided vehicle (AGV), and the computer numerical control (CNC) machine. The main topic of this research is to meet the requirements of automatic loading and unloading in the processing of the entire production line. It will significantly reduce the workforce consumption of the processing production line and avoid human error, thereby improving processing reproducibility and product production stability. © 2023 IEEE.

关键词： Controllers

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Banana Plants Soil Health Analysis Using Wireless Sensor Networks 10

Banana Plants Soil Health Analysis Using Wireless Sensor Net...

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10th International Conference on Computing and Pattern Recognition, ICCPR 2021

作者： Vilvestre, Diane Michael L. Lawas, Joshua James P. Becerra, Carl Rafael A. Angelia, Hanna Leah Pacure Electronic Engineering Program University of Mindanao Philippines Computer Engineering Program University of Mindanao Philippines

ISBN: (纸本)9781450390439

The tedious process of acquiring sample from a hundred-hectare wide or more of banana plantation to determine soil moisture, soil pH, Nitrogen, Phosphorus and Potassium nutrient levels through a laboratory test is time-consuming and inefficient. In this technical research, the objective is to automate the soil health analysis by introducing RGB sensors, motors, submersible pumps, microcontrollers and algorithm that measures Nitrogen, Phosphorus, potassium, pH level and moisture content. The data gathered is transmitted wirelessly. The interpretation of the assessed data is displayed through an android application. Using confusion matrix, the accuracy is found to be 93.33% for both Nitrogen and Phosphorus, and 90% for potassium. Also, the results arrived at 0.97706 and 0.098957 as the coefficient of determination for soil moisture and pH respectively. Considering the high accuracy rate, it is therefore concluded that the system is effective in soil health analysis and minimizes human interaction. © 2021 ACM.

关键词： Potassium

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Application of Chaotic Encryption and Decryption in Wireless Transmission From Sensory Toolholders on Machine Tools

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IEEE Sensors Journal 2023年第11期23卷 11453-11468页

作者： Lin, Chi-Yuan Wu, Shu-Cing Kuo, Ping-Huan Huang, Meng-Jun Hong, Song-Wei Yau, Her-Terng National Chin-Yi University of Technology Department of Electronic Engineering Taichung411030 Taiwan National Chin-Yi University of Technology Prospective Technology of Electrical Engineering and Computer Science Program Taichung411030 Taiwan Chiayi62102 Taiwan National Chung Cheng University Department of Mechanical Engineering Chiayi62102 Taiwan

In recent years, several industries have increased their demand for processing precision, automatic detection, and visualization interfaces. Therefore, to keep pace with the fourth industrial revolution, machine tool operators install a large number of sensors on machine tools to obtain more precise physical quantities during processing and use a variety of sensors to obtain measurements in various situations. However, these additional sensors on machine tools result in complicated wire layouts, which exhibit negative effects on processing. Such problems lead to the birth of wireless data transmission, which is expected to become the new standard in the future. At present, there is more and more interactive integration between relevant embedded system and the machine tool, which allows information communication between each other in the wireless domain. However, generally, the majority of machine tool operators focus on optimizing the sensing conditions during processing, but they disregard the importance of information security. In the current era of the Internet of Things (IoT), information security is regarded as a crucial factor. For the wireless communication between the IoT equipment for each machine in the machining field, the transmitted data are almost exposed within public space directly due to the loss in constraint and protection of physical wiring. Therefore, such a process can easily be intercepted by other devices that capture information on relevant status of the machine or command messages received by the controller, where intentional individual may possibly control the operating mechanism and progress of entire plant. This leads to theft of relevant secrets in manufacturing technology for the subject company, or intentional shutdown, machine damage, and vicious blackmailing attacks. Therefore, introducing the mechanism of safety protection during wireless signal transmission is an inevitable technology to maintain the company interests and also the

关键词： Synchronization

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Computer-Aided Diagnosis for Tuberculosis Classification with Water Strider Optimization Algorithm

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Computer Systems Science & engineering 2023年第8期46卷 1337-1353页

作者： José Escorcia-Gutierrez Roosvel Soto-Diaz Natasha Madera Carlos Soto Francisco Burgos-Florez Alexander Rodríguez Romany F.Mansour Department of Computational Science and Electronic Universidad de la CostaCUCBarranquilla080002Colombia Biomedical Engineering Program Universidad Simón BolívarBarranquilla080002Colombia Mechatronics Engineering Program Universidad Simón BolívarBarranquilla080002Colombia Department of Medicine Universidad del NorteBarranquilla081007Colombia Department of Mathematics Faculty of ScienceNew Valley UniversityEl-Kharga72511Egypt

Computer-aided diagnosis(CAD)models exploit artificial intelligence(AI)for chest X-ray(CXR)examination to identify the presence of tuberculosis(TB)and can improve the feasibility and performance of CXR for TB screening and *** the same time,CXR interpretation is a time-consuming and subjective ***,high resemblance among the radiological patterns of TB and other lung diseases can result in ***,computer-aided diagnosis(CAD)models using machine learning(ML)and deep learning(DL)can be designed for screening TB *** this motivation,this article develops a Water Strider Optimization with Deep Transfer Learning Enabled Tuberculosis Classification(WSODTL-TBC)model on Chest X-rays(CXR).The presented WSODTL-TBC model aims to detect and classify TB on CXR ***,the WSODTL-TBC model undergoes image filtering techniques to discard the noise content and U-Net-based image ***,a pre-trained residual network with a two-dimensional convolutional neural network(2D-CNN)model is applied to extract feature *** addition,the WSO algorithm with long short-term memory(LSTM)model was employed for identifying and classifying TB,where the WSO algorithm is applied as a hyperparameter optimizer of the LSTM methodology,showing the novelty of the *** performance validation of the presented WSODTL-TBC model is carried out on the benchmark dataset,and the outcomes were investigated in many *** experimental development pointed out the betterment of the WSODTL-TBC model over existing algorithms.

关键词： Computer-aided diagnosis water strider optimization deep learning chest x-rays transfer learning

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Edge Artificial Intelligence Used to Activate Indicator Lights on Bicycle Helmets

Edge Artificial Intelligence Used to Activate Indicator Ligh...

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Latin America Congress on Computational Intelligence (LA-CCI)

作者： Ahyza Yined Prieto Rodríguez Julián David Núñez Casilimas Javier Alberto Chaparro Electronic Engineering Program Escuela Colombiana de Ingeniería Julio Garavito Bogota Colombia

ISBN: (数字)9798350374575

ISBN: (纸本)9798350374582

The city of Bogota is characterized by the different problems it has related to traffic, especially with the traffic jams that occur within the capital. For this reason, people have opted for the use of alternative means of transportation such as bicycles, however, the number of accidents involving these road actors has increased over time. For this reason, we proposed the use of a learning algorithm, which is able to identify certain movements made by the cyclist with his head and depending on these, the directional signals of the bicycle will be activated, in order to provide information to the other entities of the actions performed by the cyclist. Classifiers refer to the process of training on a labeled data set (dataframe) to assign data points to classes for classification. In order to achieve this, classification models require a large amount of data to be able to predict more accurately. For this reason, the first thing that was done was the creation of the dataset, which was created from the data collection by means of the IMU of the microcontroller of the movements to be classified. After that, the windows of each movement were created, which for this project were 12 samples. The variance was calculated for each window and this was used to test the different classical classifiers (k-near neighbors, logistic regresión, decision trees, random forest, Naive Bayes, support vector machines and support vector machines). The best model were select using the accuracy meusurement and was easier to implement to predict the movement, which would be the logistic regression classifier. From this, the equation of this algorithm was implemented in the Arduino BLE sense 33 and this microcontroller would be placed in the cyclist’s helmet to identify the movements.

关键词： Support vector machines Head Microcontrollers Urban areas Transportation Bicycles Predictive models Mathematical models Safety Classification algorithms

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