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Design of wide field of view and broad spectrum objective system for Terahertz imaging 13

Design of wide field of view and broad spectrum objective sy...

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13th International conference on information Optics and Photonics, CIOP 2022

作者： Chen, Xiaogang Huang, Youping Huang, Shuyan Zhang, Hao Laboratory for Advanced Sensing Technology Fujian Jiangxia University Fuzhou350108 China The Smart Home Information Collection and Processing on Internet of Things Laboratory of Digital Fujian Fuzhou350108 China

ISBN: (纸本)9781510660632

Terahertz (THz) wave has great potential applications in the fields of security, material, biomedicine and nondestructive testing, due to its low energy, high penetrability, nondestructive property and fingerprint characteristics. In this paper, a high-performance objective system was presented and designed for THz camera. The THz objective system has an effective focal length of 39.5 mm, a F-number of 0.9, a full field angle of 24°, and a working band covering 70 - 200 μm (frequency range from 1.5 to 4.28 THz). In the system, a coaxial structure consisted of three spherical lens and a piece of aspherical lens was used. The design result shown that the root mean square radius (RMS Radius) of the sport diagrams were basically within the airy disk radius. At a cut-off frequency of 5 lp/mm, the modulation transfer function (MTF) values in the full field of view were above 0.22, which was close to the diffraction limited curve. In summary, the designed objective system has good imaging quality and high resolution, which can meet the performance requirements of large-field THz imaging systems, and has good application prospects in THz microscopic imaging. © 2022 SPIE.

关键词： Terahertz waves

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A Portable Remote Optoelectronic Tweezer System for Microobjects Manipulation

A Portable Remote Optoelectronic Tweezer System for Microobj...

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IEEE/RSJ International conference on Intelligent Robots and systems (IROS)

作者： Cao, Yuqing Liang, Shuzhang Chen, Hanlong Gan, Chunyuan Song, Li Zhang, Chaonan Arai, Fumihito Feng, Lin Beihang Univ Sch Mech Engn & Automat Beijing Peoples R China Univ Tokyo Dept Mech Engn Tokyo 1138656 Japan Beihang Univ Beijing Adv Innovat Ctr Biomed Engn Beijing 100083 Peoples R China

ISBN: (纸本)9781665417143

Non-contact manipulation technology has extensive application in the manipulation and fabrication of micro/nanomaterials. However, the manipulation devices are often precise and complex, operated only by professionals and subject to site constraints. We propose a simple optoelectronic tweezer platform, which can be controlled remotely and simply for the manipulation of microparticles at different scales, based on the novel manipulation technique called optically-induced dielectrophoresis. In this work, we design and set up the optoelectronic tweezer manipulation platform and develop the full-function human-computer interactive control interface and graphics rendering system to simplify the micro-operation process. Using Qt5.0 development environment, an experimental image processing system with multi-thread characteristics is developed, and the information interaction requirements needed in the experimental operation of optoelectronic tweezers are integrated into a control system to achieve unified information management and data analysis. Combined with cloud computing technology, the system realizes local/remote synchronous linkage operation, with cross-platform operation capability of various portable operating terminals like laptop and iPad.

关键词： Cloud computing Protocols Portable computers optical feedback systems architecture Process control Tablet computers

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Advanced AI Techniques for Grid-Connected Renewable Energy systems

Advanced AI Techniques for Grid-Connected Renewable Energy S...

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International conference on information Science and Communications Technologies (ICISCT)

作者： Laith H. Fezaa Ahmed Alkhayyat J.S. Chohan Raj Kumar Jatinder Kumar Nilesh Bhosle Department of Optical Techniques Al-Zahrawi University College Karbala Iraq College of Technical Engineering The Islamic University Najaf Iraq School of Mechanical Engineering Rayat Bahra University Mohali India Dept. of CSE Chandigarh University Mohali Punjab India Department of Computer Science Engineering Chandigarh Engineering College Chandigarh Group of Colleges Mohali Punjab India NIMS School of Computing Science and Artificial Intelligence NIMS University Jaipur Rajasthan India

ISBN: (数字)9798331527921

ISBN: (纸本)9798331527938

This research paper explores the ability to integrate innovative AI methods to optimise grid-integrated renewable energy systems. Consequently, this study assesses the benefits of energy demand forecasting, fault detection, and real-time energy management using Long Short Term Memory LSTM networks, SVM and RL models focusing on three broad areas. The LSTM model performed well in the energy demand forecast with low MAE and RMSE than other models while the SVM model performed well in fault detection with a 92% accuracy. LBC revealed that the RL-based system contributed to the reduction of energy cost while regulating the grid stability through optimizing energy in different demand situations. This paper also presents several key issues associated with data quality, model generalization, computational overhead, and interfaces to extant systems. This emphasizes the gaps on the effectiveness of data acquisition techniques, flexibility of AI mod- els and robustness of the algorithms to perform within resource constraints. There are some issues arise while integrating new AI technologies with existing traditional systems which must be considered and standardized. Possible future works are provided to overcome these issues, which include the refinement of pre processing techniques, flexi- bility of models, and solution extensibility. The studies highlight multiple possibilities of using AI in the enhancement of energy systems and their managing factor, decrease of operation costs, as well as increase of the robustness of grids, opening the way to further development of the more effective and stable energy managing solutions.

关键词： Support vector machines Renewable energy sources Energy consumption Accuracy Costs Computational modeling Predictive models Data models Artificial intelligence Long short term memory

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Experimental Testing of the Phased Array Antenna Beamsteering for the V2X Applications

Experimental Testing of the Phased Array Antenna Beamsteerin...

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Annual Siberian Russian Workshop on Electron devices and Materials (EDM)

作者： Talgat E. Saifullin Elizaveta P. Grakhova Arsen A. Ishmiyarov Ekaterina N. Katerinkina Denis A. Letavin Ruslan V. Kutluyarov Research Lab. “Sensor Systems Based on the Integrated Photonics Devices” Ufa University of Science and Technology Ufa Russian Federation Telecommunication systems dept Ufa University of Science and Technology Ufa Russian Federation Information Technologies dept. Ural Federal University Institute of Radio Electronics Ekatirenburg Russian Federation

ISBN: (数字)9798350389234

ISBN: (纸本)9798350353051

The paper showcases experimental testing of a phased array antenna for connecting and tracking vehicles in Vehicle-to-Everything technology applications. The study involved measuring the performance of a microstrip halfoctagon shaped emitter and a 14 -element linear antenna array with a main lobe width of no more than 8 degrees. Both the emitter and antenna array were designed and manufactured using WL-CT350 laminate material. The antenna system operates within the frequency range of 5614 to 5943 MHz. To control the main lobe position of the antenna array, a beamforming circuit was developed, which consisted of a splitter and a phase control unit utilizing planar phase shifters. These phase shifters were controlled by Arduino Mega 2560 microcontrollers, which implemented machine-learning algorithms to determine the optimal service sector based on the location of the vehicle. Experimental tests were conducted in an anechoic chamber to demonstrate the antenna’s ability to steer a focused radio beam across ten different sectors within a scanning range of 90 degrees.

关键词： Phased arrays Antenna measurements Microstrip antenna arrays Array signal processing Phase shifters Adaptive arrays Microstrip antennas

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License Plate Recognition Using Federated Learning

License Plate Recognition Using Federated Learning

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Multimedia processing, Communication & information Technology (MPCIT), International conference on

作者： Prajwal B S Suraj B Madagaonkar Krishnamoorthi Makkithaya CSE Department Manipal Institute of Technology Manipal Manipal Academy of Higher Education Manipal Karnataka India

ISBN: (数字)9798350375466

ISBN: (纸本)9798350375473

Federated learning is a decentralized approach in machine learning where models are trained locally on distributed data across various devices or servers. Only model updates, not the raw data, are sent to a central server for aggregation, ensuring privacy and security. This method supports collaborative learning without centralizing sensitive information. Vehicle plate images are gathered, and a Federated Learning algorithm processes them. The primary aim of this study is to improve the privacy of License Plate Recognition systems. The rationale for using License Plate Recognition technology lies in its potential to enhance security through access control and prevent unauthorized entries. Additionally, License Plate Recognition helps in the quick identification of stolen vehicles, leading to prompt response actions, and enhances traffic flow, reducing congestion and optimizing efficiency. Federated Learning ensures secure data transmission, strengthening system reliability. The methodology includes collecting standardized image data from cameras, enhancing image quality, and extracting alphanumeric characters from license plates. The Federated Learning algorithm maintains data decentralization, boosting privacy. A thorough evaluation, adherence to data protection regulations, and comprehensive documentation ensure system accuracy and transparency. Expected results suggest this integrated system offers a comprehensive solution to urban traffic issues. By utilizing image-based technology, it gathers essential data, improving traffic management efficiency and cost-effectiveness. The License Plate Recognition algorithm effectively detects license plates. Overall, this project presents a holistic approach to enhancing road safety and traffic management. By focusing on license plate detection, it addresses key urban traffic challenges. The integration of segmentation and advanced algorithms aims to create safer roadways and improve the well-being of urban communities.

关键词： Privacy Image segmentation Federated learning Data models Road safety Regulation Servers Reliability information technology License plate recognition

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Algorithm for optimizing the mode of electric power systems by active power

Algorithm for optimizing the mode of electric power systems ...

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International conference on information Science and Communications Technologies (ICISCT)

作者： Oksana Porubay Isamiddin Siddikov Khasanova Madina Department of Information Technologies Fergana branch of the Tashkent University of Information Technologies named after Muhammad al-Khwarizmi Fergana Uzbekistan Department of Information Processing and Management Tashkent State Technical University named after Islam Karimov Tashkent Uzbekistan

The paper considers the issues of optimizing the modes of electric power systems based on the methods of intelligent technologies: evolutionary and ant algorithms, taking into account the features of the object under consideration. An optimization criterion has been formulated, which includes minimizing the total cost of fuel in electric power facilities. The main restrictions imposed by the dynamics of the functioning of technological units and their mode of operation are determined. These restrictions are presented in the form of a system of linear equations that characterize the steady state of the units, as well as in the form of inequalities, which are the limiting restrictions on the parameters of the generated electricity. To solve this problem, evolutionary modeling algorithms and an ant colony algorithm have been developed. A comparative analysis of these algorithms was carried out in order to determine their capabilities and scope. The use of evolutionary algorithms in problems with discrete values of variables does not require any assumptions and simplifications of the problem. When solving the problem of optimal placement and determination of the parameters of compensating devices and linear regulators, it was possible to reduce losses in the system by 3.5%.

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LI-RV: A Fast and Efficient RISC-V based Coprocessor for Lightweight Cryptography

LI-RV: A Fast and Efficient RISC-V based Coprocessor for Lig...

引用

International SoC Design conference, ISOCC

作者： Ngoc Hung Nguyen Duc Hong An Le Vu Trung Duong Le Van Tinh Nguyen Tuan Hai Vu Hoai Luan Pham Yasuhiko Nakashima University of Information Technology VNUHCM Vietnam Nara Institute of Science and Technology Nara Japan Le Quy Don Technical University Viet Nam

ISBN: (数字)9798350377088

ISBN: (纸本)9798350377095

Hardware development for modern lightweight cryptography is essential to achieve high speed and low power consumption for IoT devices, where the RISC-V architecture with low-power, scalable, and configurable characteristics has been considered the most effective solution. Unfortunately, existing RISC-V designs for lightweight cryptography still suffer from low performance and hardware efficiency. To address this issue, we propose a RISC-V architecture, referred to as LI-RV, to handle various lightweight algorithms with enhanced performance and hardware efficiency. Particularly, LI-RV applies two key optimal ideas to achieve these goals, including dual ALUs and multi-level custom function units. Notably, LI-RV is the first RISC-V architecture utilizing dual concatenable 32-bit ALUs to perform two 32-bit parallel calculations or combine them to perform one 64bit calculation. Real-time performance evaluation on the ZCU102 FPGA shows that LI-RV provides a 1.7-3.0 times improvement in processing speed and a 1.6-2.5 times improvement in the power-delay product compared to the software implementation. Compared with related RISC-V designs, LI-RV outperforms them by 1.2-7.9 times in throughput.

关键词： Performance evaluation Power demand Software algorithms Computer architecture Throughput Hardware Software Real-time systems Cryptography Internet of Things

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Age-minimal CPU Scheduling

Age-minimal CPU Scheduling

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IEEE Annual Joint conference: INFOCOM, IEEE Computer and Communications Societies

作者： Mengqiu Zhou Meng Zhang Howard H. Yang Roy D. Yates ZJU-UIUC Institute Zhejiang University Department of Electrical and Computer Engineering WINLAB Rutgers University

ISBN: (数字)9798350383508

ISBN: (纸本)9798350383515

The proliferation of real-time status updating applications and ubiquitous mobile devices have motivated the analysis and optimization of data freshness in the context of age of information. At the same time, increasing requirements on computer performance have inspired research on CPU scheduling, with a focus on reducing energy consumption. However, since prior CPU scheduling strategies have ignored data freshness, we formulate the first CPU scheduling problem that aims to minimize the long-term average age of information, subject to an average power constraint. In particular, we optimize CPU scheduling strategies that specify when the CPU sleeps and adapt the CPU speed (clock frequency) during the execution of update-processing tasks. We formulate the age-minimal CPU scheduling problem as a constrained semi-Markov decision process (SMDP) problem with uncountable space. We develop a value-iteration-based algorithm and further prove its convergence in infinite space to obtain the optimal policy. Compared with existing benchmarks in terms of long-term average AoI, numerical results show that our proposed scheme can reduce the AoI by up to 53%, and obtains greater benefits when faced with a tighter power constraint. In addition, for a given AoI target, the age-minimal CPU scheduling policy can save more than 50% on energy consumption.

关键词： Energy consumption Scheduling algorithms Data integrity Transforms information age Real-time systems Servers

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Vehicle Registration Plate Recognition Using YoloV8 and IOT

Vehicle Registration Plate Recognition Using YoloV8 and IOT

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AIML-Applications for Engineering & Technology (ICAET), International conference on

作者： Juber Nadaf Amol Kadam Pramod Jadhav Prasad Kadam Vinod Patil Milind Gaikwad Department of Computer Bharati Vidyapeeth (Deemed to be University) College of Engineering Pune India Department of CSBS Bharati Vidyapeeth (Deemed to be University) College of Engineering Pune India Department of E & TC Bharati Vidyapeeth (Deemed to be University) College of Engineering Pune India Department of Information Technology Bharati Vidyapeeth (Deemed to be University) College of Engineering Pune India

ISBN: (数字)9798350355611

ISBN: (纸本)9798350355628

Number Plate recognition or the vehicle License Plate recognition is an interesting topic of research in smart cities which utilizes Image processing techniques. Since the number of cars is rising at an exponential rate, automated systems are supposed to store vehicle data for a variety of applications. In this intended algorithm, an efficient technique has been identified for recognition of different vehicle number registration plates. Through this technique, we can easily deal with problems like low light, irregular font number plates, wrong angles. We use the method of optical Character Recognition to identify characters that are extracted from the registration plate. Even though this project works efficiently for common use cases, it has its own drawbacks and limitations even though we are not using deep learning or any other machine learning algorithms. One of the important steps in vehicle plate recognition is the character recognition which is a technique to obtain individual text characters. YOLOv8 (You Only Look Once), and Darknet- 53 are the methods that is used to extract the features of the data. In this model, the input data is the image of the vehicle that is captured from the camera sensors or cell phones and later cropped to display only the registration plate. We undergo data-pre-processing to improve the quality or the pixels of image on the number plate. Testing is done using two different models one is the model which is obtained with more pre-processing data and the other obtained without any pre-processing data. We evaluate two datasets of number plate images: one with no interference and one where the colour intensity of the image has been decreased to test, the accuracy of the model

关键词： Deep learning YOLO Training Image recognition Accuracy Feature extraction Data models Internet of Things Character recognition License plate recognition

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Flow-based situation-aware approach for eHealth data processing 22

Flow-based situation-aware approach for eHealth data process...

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22nd IEEE International conference on E-Health Networking, Application and Services, HEALTHCOM 2020

作者： Celestrini, Jordano R. Baldi, Alessandro M. Andreao, Rodrigo V. Filho, Jose G. P. Santos, Celso A. S. Federal University of Espírito Santo Vitória-ES Brazil Federal Institute of Espirito Santo Vitória-ES Brazil

ISBN: (纸本)9781728162676

A major challenge for remote patient monitoring (RPM) systems is processing data collected from a large number of healthcare devices and developing suitable algorithms and approaches to react accordingly to a wide spectrum of situations of interest, which must be properly detected. Flow-based programming, whose operation is based on state changes, is a promising approach to overcome this challenge, facilitating the personalization of data processing according to patients' health conditions. However, this approach is not suited to the detection of complex contextual situations, thereby hindering its adoption in RPM systems for data processing. In this regard, we propose an approach that combines situation awareness and flow-based programming to widen the capability of RPM systems to handle many-sided scenarios, which requires the monitoring of complex patient healthcare conditions. An evaluation of the proposed approach was conducted to demonstrate the flexibility of the solution for processing heterogeneous health information. © 2021 IEEE.

关键词： Internet of things

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