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Joint Deep Learning Optical Band Selection and Classification Method for Spectral Data

Joint Deep Learning Optical Band Selection and Classificatio...

2023 Computational Optical Sensing and Imaging, COSI 2023 in Optica Imaging Congress - Part of Imaging and Applied Optics Congress 2023

作者： Fonseca, Karen Garcia, Hans da Silva, Felipe Arguello, Henry Bacca, Jorge Department of Electrical Engineering United States Department of Computer Science Universidad Industrial de Santander Bucaramanga680002 Colombia

This paper proposes a joint deep learning-based optical band selection and classification method by acquiring only the relevant data. The proposed method despite using fewer bands provides better performance than stat... 详细信息

ISBN: (纸本)9781957171289

关键词： Deep learning

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Towards Chipless RFID Based Temperature Sensing for IoT Applications

Towards Chipless RFID Based Temperature Sensing for IoT Appl...

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2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio science Meeting, AP-S/URSI 2023

作者： Rahman, Md Mirazur Mitra, Dipankar Dey, Shuvashis North Dakota State University Department of Electrical and Computer Engineering FargoND United States University of Wisconsin-La Crosse Department of Computer Science WI United States

ISBN: (纸本)9781665442282

This paper presents a novel technique to measure temperature by using a chipless RFID tag and smart material in view of loT application. The proposed technique incorporates a unique design of a chipless RFID resonator and a novel chipless technique for sensing temperature by combining ETFE fluroploymer with the resonator. The simulated material is placed on the top of the tag and dielectric parameters are varied. Initially, the original RCS response of the resonator is simulated which is then observed while varying the values of permittivity to obtain a correlation between different frequencies and dielectric constants. This correlation is further compared with the dielectric parameters of the material and the corresponding temperatures found from the literature. Finally, a calibration curve obtained where any temperature within the range can be measured by simply mapping the frequency of operation of the chipless resonator. © 2023 IEEE.

关键词： Resonators

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IoT Based Battery Monitoring System for Electric Vehicle using ESP32 2

IoT Based Battery Monitoring System for Electric Vehicle usi...

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2nd International Conference on Smart Technologies for Smart Nation, SmartTechCon 2023

作者： Usha Rani, R. Divya, G. Lakshmi Swarupa, M. Navaneetha, Kandle Department of Computer Science Engineering CVR College of Engineering Ibrahimpatnam Hyderabad India Department of Electrical and Electronics Engineering CVR College of Engineering Ibrahimpatnam Hyderabad India

ISBN: (纸本)9798350305418

Since the system is powered by the battery, it is the most vital part of any gadget. Incorrect or excessive charging or draining of the battery might damage the battery and lead to system failure, hence it is important to monitor the battery's voltage level. By far most of current electrical and electronic gear utilize a committed instrument called a battery the board framework (BMS). The battery the board framework (BMS) screens and controls the battery's fundamental capabilities such voltage, current, temperature, and auto-off. The appropriate and get treatment of lithium-particle or lithium-polymer batteries is guaranteed along these lines. More established BMS just observed the battery and notified the user when there was a problem. Thanks to IoT, however, we can now provide instantaneous alerts to far-flung targets. They may check the remaining juice from any location using their phones or computers. The goal is to demonstrate the viability of the idea's basic premise. The hardware for the battery monitoring device is developed as part of the system development. In this study, the battery status data is sent to the Arduino IoT cloud using an IoT-based battery monitoring system, node, and MCU using an ESP32 chip. Whether the battery is being charged or discharged, the Arduino IoT cloud will display the voltage and percentage of charge remaining. © 2023 IEEE.

关键词： Battery management systems (BMS) Battery Voltage Electric Vehicles Internet of Things Lithium-ion Batteries SoC measurement

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Exploring Data Workers’ Behaviours in Data Quality Discovery 34

Exploring Data Workers’ Behaviours in Data Quality Discover...

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34th Australasian Conference on Information Systems, ACIS 2023

作者： Chen, Tianwa Demartini, Gianluca Indulska, Marta Sadiq, Shazia School of Electrical Engineering and Computer Science The University of Queensland Brisbane Australia Business School The University of Queensland Brisbane Australia

The rise of data re-purposing has resulted in an unprecedented opportunity to create new value from existing data assets. Unlike previous approaches that relied on well-understood data quality requirements, this open-ended setting demands a discovery-oriented approach. Despite a growing market of tools that assist with data exploration and profiling, data quality discovery continues to drain the time of data workers due to its cognitively demanding and contextual nature. Accordingly, we study data quality discovery through purpose-built experimental platforms that mimic typical data exploration platforms, and explore implicit sensemaking behaviours of data workers when required to write code or use available functions, by exploiting eye-tracking and log data. Our analysis of visual scanning and attention patterns reveals various sensemaking loops amongst data workers with different performance levels in different settings. Our findings provide insights for researchers and tool designers to consider how to support different data workers in data quality discovery. Copyright © 2023 Tianwa Chen, Gianluca Demartini, Marta Indulska, Shazia Sadiq.

关键词： Eye tracking

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IoT-Based remote monitoring and control system for controlled enviornment precision farming of saffron

IoT-Based remote monitoring and control system for controlle...

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2024 International Conference on Smart Devices, ICSD 2024

作者： Malik, Sarthak Singh, Amanjot Sethi, Gaurav Pal, Ravishankar Kumar, Bura Vijay Alzubaidi, Laith H. Lovely Professional University School of Computer Science and Engineering Punjab Phagwara India Lovely Professional University School of Electronics and Electrical Engineering Punjab Phagwara India UP Ghaziabad India SR University School of Computer Science and Artificial Intelligence Warangal India The Islamic University Najaf Iraq

ISBN: (纸本)9798350394412

Farming is an essential industry that feeds the world's population. However, in recent years, there has been an increase in the demand for high-quality products, resulting in the adoption of precision agriculture. Controlled environment agriculture (CEA) has been gaining popularity. Precision agriculture refers to the agriculture practice where modern technology like IoT, WSNs are used to monitor the key metrics and therefore processes like irrigation, pesticide spray, etc. are initiated as and when required only, also at the required area only instead of traditional farming methods where the whole field was being sprayed although not all crops were in need. Apart from this, controlled environment farming is another method currently being used in farming of various crops, mainly for expensive and low yield crops where the environment of farming is artificially controlled to provide the best possible environment for the crop to grow and produce maximum yields. For the same, the Internet of Things (IoT) is a game-changer. IoT-based remote monitoring and control systems can provide real-time data on numerous key metrics such as temperature, humidity, and soil moisture. These data help farmers and other users to automate their farming, monitor growth and other aspects allowing them to improve their farming yield, reduce waste and costs from various sectors. In this study we are going to use the IoT tech stack to discuss and build a IoT based remote monitoring and control system for controlled environment precision farming of saffron which will be really beneficial for the saffron farmers to produce maximum yields while having all the metrics and controls within the reach of their fingerprints. © 2024 IEEE.

关键词： Soil moisture

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RIS-Assisted ISAC: Precoding and Phase-Shift Optimization for Mono-Static Target Detection

RIS-Assisted ISAC: Precoding and Phase-Shift Optimization fo...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Demir, Özlem Tuǧfe Björnson, Emil Tobb University of Economics and Technology Department of Electrical-Electronics Engineering Ankara Turkey Kth Royal Institute of Technology Department of Computer Science Stockholm Sweden

ISBN: (纸本)9798350351255

The reconfigurable intelligent surface (RIS) technology emerges as a highly useful component of the rapidly evolving integrated sensing and communications paradigm, primarily owing to its remarkable signal-to-noise ratio enhancement capabilities. In this paper, our focus is on mono-static target detection while considering the communication requirement of a user equipment. Both sensing and communication benefit from the presence of an RIS, which makes the channels richer and stronger. Diverging from prior research, we comprehensively examine three target echo paths: the direct (static) channel path, the path via the RIS, and a combination of these, each characterized by distinct radar cross sections (RCSs). We take both the line-of-sight (LOS) and the non-line-of-sight (NLOS) paths into account under a clutter for which the distribution is not known, but the low-rank subspace it resides. We derive the generalized likelihood ratio test (GLRT) detector and introduce a novel approach for jointly optimizing the configuration of RIS phase-shifts and precoding. Our simulation results underscore the paramount importance of this combined design in terms of enhancing detection probability. Moreover, it becomes evident that the derived clutter-aware target detection significantly enhances detection performance, especially when the clutter is strong. © 2024 IEEE.

关键词： Radar clutter

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Vertical Interconnect Technology in Silicon, Package, and Printed Circuit Board (PCB) with Coaxial Structure

Vertical Interconnect Technology in Silicon, Package, and Pr...

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2024 IEEE International Symposium on Electromagnetic Compatibility, Signal and Power Integrity, EMC+SIPI 2024

作者： Park, Junyong Li, Chaofeng Mok, Eddie Dickson, Joe Tourne, Joan Kim, Donghyun Missouri University of Science and Technology Electrical and Computer Engineering RollaMO United States Co. Ltd Kunshan China NextGin Technology Netherlands

ISBN: (纸本)9798350360394

This paper introduces vertical interconnect technology in silicon, package, and printed circuit board (PCB) levels with a coaxial structure, respectively. The coaxial structure has been known to be advantageous in terms of signal integrity (SI) compared to the non-coaxial structure. The coaxial structure is easy to control the characteristic impedance Z0 and robust to crosstalk. The silicon-level interconnect includes the wire bonding (WB) and through-silicon via (TSV) technology, the package-level interconnect includes an elastomer package test socket. The PCB-level interconnect includes the vias, and vertical conductive structure (VeCS). For each level, the non-coaxial and coaxial interconnects are compared with the measurement results in the frequency domain. In conclusion, this paper successfully shows the improvement of the coaxial structure at silicon, package, and PCB levels. © 2024 IEEE.

关键词： Three dimensional integrated circuits

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A Comprehensive Study of Artificial Intelligence and Cybersecurity on Bitcoin, Crypto Currency and Banking System

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Annals of Data science 2024年第1期11卷 103-135页

作者： Choithani, Tamanna Chowdhury, Asmita Patel, Shriya Patel, Poojan Patel, Daxal Shah, Manan Department of Computer Science and Engineering Indus University Gujarat Ahmedabad India Department of Electrical Engineering Nirma University Gujarat Ahmedabad India Department of Electronics and Communication Engineering Nirma University Gujarat Ahmedabad India Department of Chemical Engineering School of Technology Pandit Deendayal Energy University Gujarat Gandhinagar382426 India

In recent years cryptocurrencies are emerging as a prime digital currency as an important asset and financial system is also emerging as an important aspect. To reduce the risk of investment and to predict price, trend, portfolio construction, and fraud detection some Artificial Intelligence techniques are required. The Paper discusses recent research in the field of AI techniques for cryptocurrency and Bitcoin which is the most popular cryptocurrency. AI and ML techniques such as SVM, ANN, LSTM, GRU, and much other related research work with cryptocurrency and Bitcoin have been reviewed and most relevant studies are discussed in the paper. Also highlighted some possible research opportunities and areas for better efficiency of the results. Recently in the past few years, artificial intelligence (AI) and cybersecurity have advanced expeditiously. Its implementation has been extensively useful in finance as well as has a crucial impact on markets, institutions, and legislation. It is making the world a better place. AI is responsible for the simulation of machines that are replicas of human beings and are intelligent enough. AI in finance is changing the way we communicate with money. It helps the financial industry streamline and optimize processes from credit judgments to quantitative analysis marketing and economic risk management. The main goal of this research has been investigating certain impacts of artificial intelligence in this contemporary world. It's centered on the appeal of artificial intelligence, confrontation, chances, and its influence on professions and careers. The research paper uses AI to enable banks to generate financial resources and to provide valuable customer services. The application of the growing Indian banking sector is part of everyday life made up of several banks like RBI, SBI, HDFC, etc. and these banks have digitally implemented using chat-bots that have brought benefits to the customers. © The Author(s), under exclusive licence t

关键词： Risk assessment

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Signature Analysis of SRAM-PUF for IoT Decentralized Identifier in Large-Scale Networks 14

Signature Analysis of SRAM-PUF for IoT Decentralized Identif...

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14th International Conference on Ubiquitous and Future Networks, ICUFN 2023

作者： Han, Seungnam Kim, Jeein Lee, Haewon Hwang, Euiseok School of Electrical Engineering and Computer Science Gwangju Korea Republic of Artificial Intelligence Graduate School Gwangju Korea Republic of

ISBN: (纸本)9798350335385

In this paper, we extract hardware signatures from numerous static random access memory (SRAM) and analyze the feasibility as a signature for Internet of Things (IoT) decentralized identifier (DID). Due to uncontrollable variations in the manufacturing process, SRAM contains inherent randomness that can serve as a physical unclonable function (PUF) to identify the device uniquely. In particular, with the massive deployment of IoT devices, research on SRAM-PUF based distributed device identification is being actively investigated. However, conventional SRAM-PUF research has mainly focused on application to a small-scale IoT environment, so a limited number of SRAM have been analyzed. To generalize the signature utilization, we investigate uniqueness of the PUF from a number of SRAMs. We employed commercial SRAMs and off-the-shelf development boards to extract SRAM-PUFs. Evaluation results demonstrate that SRAM-PUFs are suitable for DIDs even in large-scale IoT networks, considering both chip-by-chip and block-by-block uniqueness. © 2023 IEEE.

关键词： Internet of things

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RETHINKING SYMBOLIC REGRESSION: MORPHOLOGY AND ADAPTABILITY FOR EVOLUTIONARY ALGORITHMS 11

RETHINKING SYMBOLIC REGRESSION: MORPHOLOGY AND ADAPTABILITY ...

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11th International Conference on Learning Representations, ICLR 2023

作者： Fong, Kei Sen Wongso, Shelvia Motani, Mehul Department of Electrical and Computer Engineering National University of Singapore Singapore Institute of Data Science National University of Singapore Singapore

Symbolic Regression (SR) is the well-studied problem of finding closed-form analytical expressions that describe the relationship between variables in a measurement *** this paper, we rethink SR from two perspectives: morphology and ***: Current SR algorithms typically use several man-made heuristics to influence the morphology (or structure) of the expressions in the search *** man-made heuristics may introduce unintentional bias and data leakage, especially with the relatively few equation-recovery benchmark problems available for evaluating SR *** address this, we formulate a novel minimalistic approach, based on constructing a depth-aware mathematical language model trained on terminal walks of expression trees, as a replacement to these ***: Current SR algorithms tend to select expressions based on only a single fitness function (e.g., MSE on the training set).We promote the use of an adaptability framework in evolutionary SR which uses fitness functions that alternate across *** leads to robust expressions that perform well on the training set and are close to the true functional *** demonstrate this by alternating fitness functions that quantify faithfulness to values (via MSE) and empirical derivatives (via a novel theoretically justified fitness metric coined MSEDI).Proof-of-concept: We combine these ideas into a minimalistic evolutionary SR algorithm that outperforms a suite of benchmark and state of-the-art SR algorithms in problems with unknown constants added, which we claim are more reflective of SR performance for real-world *** claim is then strengthened by reproducing the superior performance on real-world regression datasets from *** researchers interested in equation-recovery problems, we also propose a set of conventions that can be used to promote fairness in comparison across SR methods and to reduce unintentional bias. © 2023 11th Internation

关键词： Morphology

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