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A 4.5 μW Miniaturized 3-Channel Wireless Intra-Cardiac Acquisition System

IEEE Transactions on Biomedical Circuits and systems 2023年第5期17卷 1097-1110页

作者： Rezaeiyan, Yasser Koolivand, Yarallah Zamani, Milad Shoaei, Omid Akbari, Meysam Moradi, Farshad Tang, Kea-Tiong Integrated Circuits and Electronics Laboratory Department of Engineering Aarhus University Aarhus8200 Denmark Electrical Engineering KN Toosi University of Technology Tehran15418-49611 Iran Bio-Integrated Systems Lab School of Electrical and Computer Engineering University of Tehran Tehran*** Iran Department of Electrical Engineering University of Kurdistan Sanandaj*** Iran Department of Electrical Engineering National TsingHua University Hsinchu30013 Taiwan

This article presents a chip designed for wireless intra-cardiac monitoring systems. The design consists of a three-channel analog front-end, a pulse-width modulator featuring output-frequency offset and temperature calibration, and inductive data telemetry. By employing a resistance boosting technique in the instrumentation amplifier feedback, the pseudo-resistor exhibits lower non-linearity, leading to a total harmonic distortion of below 0.1%. Furthermore, the boosting technique enhances the feedback resistance, leading to a reduction in the size of the feedback capacitor and, consequently, the overall size. To make the modulator's output frequency resilient to temperature and process changes, coarse and fine-tuning algorithms are used. The front-end channel is capable of extracting the intra-cardiac signal with an effective number of bits of 8.9, while exhibiting an input-referred noise of less than 2.7 μ Vrms, and consuming 200 nW per channel. The front-end output is encoded by an ASK-PWM modulator, which drives an on-chip transmitter at 13.56 MHz. The proposed System-on-Chip (SoC) is fabricated in a 0.18 μ m standard CMOS technology and consumes 4.5 μW while occupying 1.125 mm2. © 2023 IEEE.

关键词： Transmitters

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Automating CPPSs Analyses with SysML v2 and Lingua Franca in the Context of Industry 4.0 50

Automating CPPSs Analyses with SysML v2 and Lingua Franca in...

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50th Annual Conference of the IEEE industrial Electronics Society, IECON 2024

作者： Gaiardelli, Sebastiano Wilch, Jan Fummi, Franco Vogel-Heuser, Birgit Industrial Computer Engineering Laboratory Department of Engineering for Innovation Medicine University of Verona Italy Institute of Automation and Information Systems Technical University of Munich Germany

ISBN: (纸本)9781665464543

The design of manufacturing systems requires exploring diverse component configurations for one that best satisfies the requirements of the target system. At the same time, manufacturing systems evolve continuously, increasing their complexity and that of the production line in which they are installed. Model-based System engineering (MBSE) methodologies and modeling languages like System Modeling Language (SysML) are used to assist system engineers during the entire design process. Yet, MBSE methodologies mainly rely on manually composed models for requirements verification, incurring enormous cost and effort especially in larger, more complex systems. This paper proposes a methodology exploiting the knowledge enclosed in a SysML model to automate the execution of a set of analyses defined over the represented manufacturing system. The proposed approach relies on Lingua Franca (LF) to simulate the specified analysis and analyze the results. Moreover, the methodology supports chains of analyses to represent dependent requirements and tradeoffs imposed upon a manufacturing system. The proposed methodology has been evaluated on a manufacturing system demonstrator. Results show the proposed methodology’s applicability and scalability on diverse configurations of the manufacturing system. © 2024 IEEE.

关键词： Smart manufacturing

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Machine Learning for Smart Agriculture: A Comprehensive Survey

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第6期5卷 2568-2588页

作者： Mahmood, M. Rezwanul Matin, Mohammad Abdul Goudos, Sotirios K. Karagiannidis, George North South University Department of Electrical and Computer Engineering Dhaka1229 Bangladesh Aristotle University of Thessaloniki ELEDIA@AUTH Department of Physics Thessaloniki54124 Greece Aristotle University of Thessaloniki Department of Electrical and Computer Engineering Thessaloniki54124 Greece Cyber Security Systems and Applied AI Research Center Beirut1102 2801 Lebanon

As communication technologies and equipment evolve, smart assets become smarter. The agricultural industry is also evolving in line with the implementation of modern communication protocols, intelligent sensors, and equipment. This evolution is enabling large-scale agricultural production processes to operate independently, thus, securing the food supply chain for an ever-growing population. Data processing for such a system with multiple heterogeneous sources requires proper management for effective agricultural operations. Recognizing the advantages of machine learning (ML) in performing large-scale data processing, researchers are investigating the implementation of ML to design an effective intelligent agricultural architecture. The aim of this article is to provide a thorough analysis of the state-of-the-art in smart agriculture, open challenges, and guidelines for the development of further enhanced smart agriculture systems. Specifically, we describe how ML is used to create intelligent agricultural systems supported by state-of-the-art technology. © 2020 IEEE.

关键词： Weed control

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A Multi-Criteria Decision Support Tool for the Evaluation of Energy Storage systems: A Case Study in Battery Technology 15

A Multi-Criteria Decision Support Tool for the Evaluation of...

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15th International Conference on Information, Intelligence, systems and Applications, IISA 2024

作者： Trachanas, Georgios P. Arsenopoulos, Apostolos Tsalidis, Theodoros Serepas, Filippos Markaki, Ourania Askounis, Dimitrios School of Electrical and Computer Engineering National Technical University of Athens Decision Support Systems Laboratory Greece

ISBN: (纸本)9798350368833

The increasing integration of renewable energy sources necessitates the deployment of efficient energy storage systems to ensure grid resilience, stability, and efficient operation. Selecting the optimal energy storage technology involves the evaluation across multiple criteria, reflecting technical, economic, and environmental dimensions, among others. This paper presents a decision support tool, based on an ensemble of Multi-Criteria Decision-Making methods, to rank energy storage technologies. These methods are renowned for their ability to handle conflicting criteria and provide clear, actionable insights for decision-makers. A detailed case study concerning battery systems is also included, evaluating the alternatives against seven technology and economic type criteria. The results demonstrate the efficacy of the employed tool in identifying the most suitable energy storage technologies, providing valuable guidance for stakeholders in the selection and development of energy storage solutions. © 2024 IEEE.

关键词： Battery storage

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IoT-Based Smart Farmland Using Deep Learning 2

IoT-Based Smart Farmland Using Deep Learning

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2nd International Conference on Artificial Intelligence and Machine Learning Applications, AIMLA 2024

作者： Uma, J. Shobana, M. Abhiniti, G. Rahul, R. Kavinkumar, S.P. Hirithik Roshan, S. M. Kumarasamy College of Engineering Electrical and Electronics Engineering Karur India M. Kumarasamy College of Engineering Department of Computer Science and Business Systems Karur India M. Kumarasamy College of Engineering Computer Science and Business Systems Karur India

ISBN: (纸本)9798350349221

The IoT based Smart farmland using deep learning is a system for tracking animals on agricultural land combines surveillance cameras, drones, an Arduino controller, IR sensors, and an LCD display to detect and tally the animal's presence. Upon detection, the system utilizes AI methods to categorize the animal type and send immediate SMS notifications to farmers through a GSM module. It incorporates an animal-repellant buzzer and a gate control mechanism. Through the use of transfer learning with CNN models, it accurately identifies four specific animal species: elephants, cows, goats, and pigs. Continuous updates and training with new data maintain its precision, serving the agricultural and wildlife protection domains. This technology significantly aids farmers in safeguarding their crops, offering crucial insights into intrusions and amplifying crop yield. Its primary purpose revolves around simplifying the identification of animals on agricultural land. © 2024 IEEE.

关键词： Crops

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Near-Optimal Scheduling for IC Packaging Operations Considering Processing-Time Variations and Factory Practices

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IEEE Robotics and Automation Letters 2024年第4期9卷 3878-3885页

作者： Tsai, Tsung-Han Yan, Bing Luh, Peter B. Yang, Haw-Ching Bragin, Mikhail A. Cheng, Fan-Tien National Cheng Kung University Institute of Manufacturing Information and Systems Tainan701401 Taiwan Rochester Institute of Technology Department of Electrical and Microelectronic Engineering RochesterNY14623 United States University of Connecticut Department of Electrical and Computer Engineering StorrsCT06269 United States National Taiwan University Department of Electrical Engineering Taipei106329 Taiwan National Kaohsiung University of Science and Technology Department of Electrical Engineering Kaohsiung824005 Taiwan University of California Department of Electrical and Computer Engineering RiversideCA92507 United States

Due to the short life cycles of electronic products, trial run lots of new products are crucial in IC packaging for production verification and engineering adjustments. The processing time of trial run lots may differ significantly from production lots due to engineering adjustments and is difficult to predict without sufficient historical data. The purpose of this letter is to develop a framework for near-optimal scheduling of IC packaging considering processing time variations and factory practices. Using an orthogonal greedy algorithm and recurrent neural network, this framework extracts key features and predicts the processing times of trial run lots and production lots for each operation using these algorithms. After formulating the scheduling problem in an integer linear programming form, an ordinal optimization method is embedded within the decomposition and coordination framework to obtain dynamic and near-optimal schedules in a computationally efficient manner. This approach can improve the efficiency of IC packaging and potentially other operations by optimizing lot scheduling, reducing production tardiness, and increasing productivity in the factory, paving the way for self-optimizing factories in the future. © 2016 IEEE.

关键词： Integer programming

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Optimizing Maximum Profit for Electric Vehicle Users in a Bipolar DC Distribution Grid with Probabilistic EV Load Demand and V2G Integration 12

Optimizing Maximum Profit for Electric Vehicle Users in a Bi...

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12th International electrical engineering Congress, iEECON 2024

作者： Sakulphaisan, Guntinan Son-In, Sirirat Junhuathon, Nitikorn Pathumwan Institute Of Technology Industrial Technology And Innovation Management Faculty Of Science And Technology Bangkok Thailand Bansomdejchaopraya Rajabhat University Electrical Engineering And Automation Control Systems Faculty Of Engineering And Industrial Technology Bangkok Thailand Rajamangala University Of Technology Thanyaburi Faculty Of Engineering Department Of Electrical Engineering Pathumthani Thailand

ISBN: (纸本)9798350383591

This article delves into the synergistic potential of integrating Bipolar DC distribution grids, Probabilistic EV load demand forecasting, and Vehicle-to-Grid (V2G) technology. It offers a blueprint for electric vehicle (EV) users to smartly improve their financial results. Through the amalgamation of these components, individuals who possess electric vehicles have the potential to mitigate their energy expenditures while concurrently generating additional income. The study reveals that the integration of EV into the distribution system can lead to a substantial increase in daily energy loss, reaching up to 25.91%. However, when V2G technology is employed within the distribution grid, it has the remarkable capability to mitigate this increase in daily energy loss significantly, achieving a reduction of up to 64.12%. © 2024 IEEE.

关键词： Integration

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Three-Dimensional Autonomous Guidance for Enclosing a Stationary Target Within Arbitrary Smooth Geometrical Shapes

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IEEE Transactions on Aerospace and Electronic systems 2023年第6期59卷 9247-9256页

作者： Sinha, Abhinav Cao, Yongcan The University of Texas at San Antonio Unmanned Systems Lab Department of Electrical and Computer Engineering San AntonioTX78249 United States

This article presents a target-enclosing guidance law for an autonomous vehicle to enclose a stationary target within arbitrary smooth geometrical shapes or patterns in 3-D, thereby presenting a generic guidance strategy for target-enclosing behavior. We particularly focus on designing a target-enclosing strategy wherein the vehicle does not have radial acceleration capabilities and is steered by its lateral acceleration only. Such consideration makes the design appealing for aerial vehicles with turning constraints. The proposed design accounts for the coupled 3-D engagement, thereby preventing performance degradation when the pitch and the yaw channels are decoupled into two separate and mutually orthogonal planar engagements. We further evaluate the lateral acceleration components of the vehicle in the orthogonal (pitch and yaw) channels by minimizing the instantaneous total control effort subject to an affine constraint. We demonstrate the effectiveness and advantages of the proposed controller through simulations. © 1965-2011 IEEE.

关键词： Three dimensional displays

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Inverse-Designed 16-Channel Time-of-Flight Receiver in 45nm Silicon Photonic Process

Inverse-Designed 16-Channel Time-of-Flight Receiver in 45nm ...

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2024 Integrated Photonics Research, Silicon and Nanophotonics, IPR 2024

作者： Rollinson, John Karlicek, Robert Hella, Mona Dept. of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute TroyNY United States

A 16-channel monolithic electronic-photonic receiver for flash time-of-flight LIDAR is demonstrated in 45nm silicon photonic process. Enverse-designed grating array antennas are utilized for efficient, low-noise coupling of free-space light, thus improving signal-to-noise ratio and extending sensing range of the free-space optical receiver. © 2024 The Author (s).© Optica Publishing Group 2024

关键词： Silicon photonics

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Combining Automatic Annotation with Human Validation for the Semantic Enrichment of Cultural Heritage Metadata

Combining Automatic Annotation with Human Validation for the...

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2024 Computational Humanities Research Conference, CHR 2024

作者： Kaldeli, Eirini Chortaras, Alexandros Lyberatos, Vassilis Liartis, Jason Kantarelis, Spyridon Stamou, Giorgos AI and Learning Systems Lab School of Electrical and Computer Engineering National Technical University of Athens Greece

The addition of controlled terms from linked open datasets and vocabularies to metadata can increase the discoverability and accessibility of digital collections. However, the task of semantic enrichment requires a lot of effort and resources that cultural heritage organizations often lack. State-of-the-art AI technologies can be employed to analyse textual metadata and match it with external semantic resources. Depending on the data characteristics and the objective of the enrichment, different approaches may need to be combined to achieve high-quality results. What is more, human inspection and validation of the automatic annotations should be an integral part of the overall enrichment methodology. In the current paper, we present a methodology and supporting digital platform, which combines a suite of automatic annotation tools with human validation for the enrichment of cultural heritage metadata within the European data space for cultural heritage. The methodology and platform have been applied and evaluated on a set of datasets on crafts heritage, leading to the publication of more than 133K enriched records to the Europeana platform. A statistical analysis of the achieved results is performed, which allows us to draw some interesting insights as to the appropriateness of annotation approaches in different contexts. The process also led to the creation of an openly available annotated dataset, which can be useful for the in-domain adaptation of ML-based enrichment tools. © 2024 Copyright for this paper by its authors.

关键词： Semantics

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