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检索条件"丛书名=Lecture Notes in Electrical Engineering"

共 22048 条记录，以下是131-140 订阅

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Resistorless Current-Mode Schmitt Trigger for Single-Event Detection in Photomultipliers Front-Ends 55th

Resistorless Current-Mode Schmitt Trigger for Single-Event D...

引用

55th Meeting of the Italian Electronics Society

作者： Colaiuda, Davide Leoni, Alfiero Barile, Gianluca Stornelli, Vincenzo Ferri, Giuseppe Univ LAquila Dept Ind & Informat Engn & Econ I-67100 Laquila Italy INFN Lab Nazionali Gran Sasso I-67100 Assergi AQ Italy

ISBN: (纸本)9783031715204;9783031715181;9783031715174

This work proposes an integrated current-mode non-inverting Schmitt Trigger in a 150nm CMOS technology, without any feedback passive element, for photomultipliers single-event detection. The proposed device is triggered by a current input signal and provides an output voltage that is suitable for interfacing with digital systems. The small currents associated with a reduced number of photoelectrons require a high transimpedance gain and a narrow hysteresis width, making conventional approaches impractical. The proposed device shows a current threshold value to trigger the system, offering a high detection capability also with small currents. In addition, it makes the trigger hysteresis width less sensitive to supply variations. The proposed circuit has great design flexibility, also allowing user to tune the threshold currents using bias voltage reference. The proposed device properly operates under a power supply voltage 1.8 V to 3.3 V. Static power consumption is 10 mu W, with a propagation delay of 25 ns and a total detection delay of 34 ns, driving a 3 pF load capacitance.

关键词： Photomultipliers Current-mode Schmitt Trigger CMOS

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Thermoelectrical Analysis of Cell Lines with a Pyroelectric Sensor 22nd

Thermoelectrical Analysis of Cell Lines with a Pyroelectric ...

引用

22nd National Conference on Sensors and Microsystems

作者： Pullano, S. A. Greco, M. Oliva, G. Lagana, F. Islam, S. K. Fiorillo, A. S. Magna Graecia Univ Catanzaro Dept Hlth Sci BATS Lab Catanzaro Italy Univ Missouri Dept Elect Engn Comp Sci Columbia MO USA

ISBN: (纸本)9783031820786;9783031820762;9783031820755

Cells are the basic units of life of animals and plants that undergo various biological/physiological processes. Most of the properties of living organisms are also exposed by individual cells. Understanding the functioning of cells is crucial to obtaining information about their function and state of health. This paper presents the design and manufacture of a pyroelectric sensor for cell line characterization. Using thermoelectric transduction in response to an external temperature stimulus, thermal impedance measurements of a sample of cells containing liquids were carried out. The outcomes of the analysis are illustrated on a Nyquist plot and are assessed at a specific frequency. The envisioned sensor is designed to enhance the information gathered from a low-volume cell sample. The thermal analysis allows to evaluate parameters such as thermal resistance and heat capacity of the cellular population. Analysis of sample at different concentration evidenced that low increase in cell volume fraction results in significant variation in the Nyquist plot and thus in the thermal components of the sample.

关键词： Biological processes Pyroelectric devices Thermal conductivity

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On-Chip Micro-incubator for Studying Cell Cultures in Space 22nd

On-Chip Micro-incubator for Studying Cell Cultures in Space

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22nd National Conference on Sensors and Microsystems

作者： Davis, N. Maipan Nardi, L. Abbasrezae, P. De Albuquerque, T. B. Caputo, D. Lovecchio, N. Costantini, F. de Cesare, G. Calabria, D. Zangheri, M. Pace, A. Lazzarini, E. Calabretta, M. M. Guardigli, M. Michelini, E. Lorenzini, F. Popova, L. Balsamo, M. Martella, C. M. Di Stefano, G. Jonker, D. Donati, A. Billi, D. Gardeniers, H. Caselle, M. Mirasoli, M. Nascetti, Augusto Univ Roma Scuola Ingn Aerospaziale Sapienza Rome Italy Univ Roma Dip Ingn Informaz Elettron Telecomun Sapienza Rome Italy Univ Bologna Dipartimento Chim Giacomo Ciamician Alma Mater Studiorum Bologna Italy Kayser Italia Srl Livorno Italy Univ Roma Tor Vergata Rome Italy Twente Univ NL Enschede Netherlands Karlsruher Inst Fuer Technol Karlsruhe Germany

ISBN: (纸本)9783031820786;9783031820762;9783031820755

This paper presents the design and manufacturing of initial lab-on-chip micro-incubator prototypes within the ALCYONE project, to study different types of cell cultures in space. ALCYONE is a project funded by the EU under the Horizon Europe program, jointly developed by the School of Aerospace engineering of Sapienza University of Rome (SIA), Bologna University, Kayser Italia Srl, Tor Vergata University, Twente University, and the Karlsruher Institut fuer Technologie. Envisioned as a key component for understanding the effects of prolonged space exposure on biological systems, the project focuses on creating an on-chip micro-incubator featuring integrated thin-film sensors and actuators to study the effect of space radiation environment on four different types of cell cultures. Genetically modified cells designed to express bioluminescence under given metabolic conditions enable real-time monitoring of cells status. This is achieved through specifically designed photosensors able to collect the emitted light, while on-chip actuators maintain a controlled environment within the chip incubator for precise experimentation and providing the required nutrients. The electronic system integrated into the platform characterizes the radiation environment, correlating biological responses with radiation exposure. This technology, with attributes such as low power consumption, compactness, high data efficiency, and full automation, aligns perfectly with CubeSat missions, culminating in the design of a comprehensive payload. This paper presents a pivotal aspect of the ALCYONE project, focusing on the design and manufacturing processes involved in creating the first micro-incubator prototypes. Different geometries and configurations have been evaluated and a first bench of incubator has been produced to make the first chemical experiments to define the protocol with engineered cell cultures. In addition, the design and manufacturing of the on-chip sensors is described.

关键词： lab-on-chip micro-incubator hydrogenated amorphous silicon photosensors bioluminescence

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A Wearable Multi-sensor Node for Detecting Anomalies on Worker Safety in Complex Scenarios 22nd

A Wearable Multi-sensor Node for Detecting Anomalies on Work...

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22nd National Conference on Sensors and Microsystems

作者： Formisano, Fabrizio Del Giudice, Antonio Dellutri, Michele Di Francia, Girolamo ENEA Portici Italy STMicroelect Analog & MEMS Grp R&D & Strategy Catania Italy

ISBN: (纸本)9783031820786;9783031820762;9783031820755

Smart Personal Protective Equipment (PPE) enhances workplace safety by continuously monitoring workers and environmental parameters, enabling real-time interventions in the event of accidents. This paper presents advancements in such devices, utilizing Internet of Things (IoT) technology for monitoring purposes. Specifically, it outlines improvements in a battery-powered sensor node over similar devices documented in scientific literature [1-3] and earlier prototypes [4, 5]. The IoT node can monitor chemical and physical parameters, including particulate matter, VOCs, O2, CO2, CO, as well as incorporating audio and inertial sensors, and a connectivity module for the LORAWAN (TM) network to transmit reports to a dashboard. It also features real-time location capabilities for both indoor and outdoor scenarios, which can localize a worker's location in the event of an accident, aiding in reducing response times for first aid. This version of the system can identify complex hazardous conditions by detecting simultaneous breaches of both minimum or maximum thresholds for relevant chemical parameters. For physical parameters, the system uses AI-driven processing to identify potentially dangerous worker activities. In audio detection, it recognizes not only threshold violations but also specific audio patterns indicative of hazardous situations. The progress includes the development of a compact sensor node with enhanced low-power features and an updated prototype sensor shield with latest sensors available in the market. Preliminary trials in simplified operational settings have assessed initial performance metrics, such as battery life, data delivery time to the dashboard, and location detection accuracy.

关键词： Wearable personal protective equipment (PPE) sensor IoT node safety particulate matter (PM) gas exposure inertial sensor indoor and outdoor localization

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InternEase: Creating Pathways to Professional Success for Students and Companies 5th

InternEase: Creating Pathways to Professional Success for St...

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5th International Conference on Data Science, Machine Learning and Applications

作者： Jeny, J. R. V. Babu, G. Bharath Reddy, S. Jaganmohan Abhiram, K. Vignan Inst Technol & Sci Dept Comp Sci & Engn AI&ML Bhuvanagiri India

ISBN: (纸本)9789819780334;9789819780310;9789819780303

InternEase is an innovative platform designed to revolutionize the way students and companies engage in the internship recruitment process. The InternEase platform provides a centralized hub where students can create comprehensive profiles, showcasing their educational background, skills, achievements, and availability status for internships. Companies, on the other hand, are granted access to a user-friendly dashboard where they can effortlessly browse through student profiles, filter candidates based on specific criteria, and identify potential internswho alignwith their organization's needs. By collecting feedback and monitoring successful internship offers, InternEase ensures that the platform remains up-to-date and relevant, further enhancing its utility. Students can also interact with the bots virtually for any issues and internship opportunities.

关键词： Recruitment Internship Profiles

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Application of Unsupervised Learning in Detecting Behavioral Patterns in E-commerce Customers 5th

Application of Unsupervised Learning in Detecting Behavioral...

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5th International Conference on Data Science, Machine Learning and Applications

作者： Udayan, J. Divya Moneesh, N. Vemulapalli, Nehith Sai Pruthvi, Paladugula Sakhamuri, Rakshith Amrita Vishwa Vidyapeetham Deptartment Comp Sci & Engn Chennai Tamil Nadu India Indian Inst Informat Technol Dept Comp Sci & Engn Tiruchirappalli India

ISBN: (纸本)9789819780334;9789819780310;9789819780303

In the rapidly growing e-commerce world, effectively discerning customer behavior is indispensable for fine-tuning services and bolstering sales. Our research centers around the Online Retail dataset, utilizing unsupervised machine learning to unveil distinct behavioral patterns. Initial data examination was pivotal, ensuring anomalies were addressed, paving the way for reliable results. The novelty of our approach lies in leveraging the Recency, Frequency, and Monetary (RFM) methodology, revealing multifaceted behavior of customer interactions. This method demystified customer activity into recent engagements, purchasing frequency, and spending magnitude. Utilizing silhouette scores, an optimal clustering number was identified, followed by the application of the KMeans algorithm, which correctly segements customers into discernible behavioral groups. The visualization of these clusters uncovers clear purchase patterns, providing businesses with a lens to refine their marketing endeavors. Conclusively, this method offers businesses an edge, extracting deeper insights into customer behavior and steering optimal growth trajectories.

关键词： e-commerce unsupervised machine learning RFM methodology silhouette scores KMeans clustering

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Analysis of SQNR Degradation in Noise-Shaped SAR Analog-to-Digital Converters at High Input Signal Amplitudes 27th

Analysis of SQNR Degradation in Noise-Shaped SAR Analog-to-D...

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27th International Symposium on VLSI Design and Test

作者： Godavarthi, Sekhar Manivannan, Saravana Indian Inst Technol Roorkee 247667 Uttarakhand India

ISBN: (纸本)9789819783830;9789819752690;9789819752683

This paper discusses the architectural choices to design noise-shaped successive approximation register (NS-SAR) analog-to-digital converters (ADCs) with high signal-to-quantization noise ratio (SQNR). It also covers the operating principle, limitations, and improvements achieved using the noise shaping technique. The NS-SAR suffers from quantizer saturation at high input amplitudes, where filtered quantization noise gets added to the input signal thereby saturating the SAR quantizer. We have analyzed this effect in a first-order NS-SAR ADC. We have also derived an expression for the peak loop filter output when the NS-SAR ADC is saturated. Macromodel simulation results are also provided to validate our analysis.

关键词： Analog-to-digital converters Noise-shaping SAR Quantizer Saturation

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A Comparative Study of Inertial Response Improvement Methods in Isolated Power Systems with Increased Penetration of Variable Renewable Energy

A Comparative Study of Inertial Response Improvement Methods...

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2024 Electric Power and Renewable Energy Conference

作者： Mahtani, Kumar Univ Politecn Madrid Madrid 28006 Spain

ISBN: (纸本)9789819779239;9789819779215;9789819779208

Historically, with the lead of conventional generation, the inertia of power systems has been taken for granted, but as these evolve with increased penetration of inverter-based resources, new questions arise, particularly on which are the adequate solutions to maintain or improve the system reliability in this modern scenario. Various technologies are available to overcome the lack of inertia, avoiding high frequency changes and deviations in the power system. Among these technologies, synchronous condensers engendered from the conversion of alternators in decommissioned power plants, fast frequency response services, and virtual inertia systems are the most widespread. In this work, a comparative study between these technologies is carried out, based on an isolated system with low inertia and high penetration of variable generation, in which sudden load variations have been considered. The objective of this study is to deliver some useful conclusions, particularly for transmission system operators, about the differences, interchangeability, and the combinability of these compensatory technologies.

关键词： Battery energy storage system Fast frequency response Isolated power systems Power system inertia Synchronous condensers Virtual inertia

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Multi-model Collaborative Prediction of Photovoltaic Power Generation of Stormwater Detention Tank Based on Meteorological and Temporal Characteristics 13th

Multi-model Collaborative Prediction of Photovoltaic Power G...

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13th International Conference on Clean and Green Energy

作者： Yuan Zheng Li Yijun Liu Yahui Liu Qian Shanghai Municipal Engn Design Inst Grp Co Ltd Shanghai Peoples R China

ISBN: (纸本)9789819618149;9789819618125;9789819618118

As the construction of urban stormwater detention tanks advances, the problem of their energy consumption is becoming more prominent. At present, some of stormwater detention tanks try to add distributed photovoltaic power generation and energy storage systems to realize zero-carbon operation. However, the power generation of distributed photovoltaic is small and random, and the existing prediction methods are difficult to meet the long-term accuracy requirements. Therefore, in response to China's strategy of Carbon peaking and Carbon neutrality, and with the goal of green and low-carbon operation of stormwater detention tanks, this paper proposes a multi-model collaborative prediction of photovoltaic power generation of stormwater detention tank based on meteorological and temporal characteristics. The algorithm can realize the accurate prediction of photovoltaic power generation of stormwater detention tanks, so as to reasonably and effectively formulate a flexible control strategy for the load of stormwater detention tank, and create conditions for building the infrastructure of "zero-carbon" cities. This method first detects outliers in the original data through DBSCAN. Then, the random forest algorithm is used for reverse feature selection, and the EEMD algorithm is used to decompose the photovoltaic power data into several intrinsic mode functions and residuals. The meteorological characteristics that affect photovoltaic output are effectively combined with their own time series characteristics. A CNN-BiGRU hybrid neural network prediction model is established to predict the decomposed components separately and obtain the prediction of each component. Finally, all the predictions are superimposed to obtain the final prediction of photovoltaic power generation. This paper takes the real power generation data of stormwater detention tank as an example, the experimental results show that the proposed algorithm has higher prediction accuracy than other neural netw

关键词： Stormwater detention tank Photovoltaic power Energy storage DBSCAN EEMD CNN-BiGRU

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Exploring the Potential of GANs, LSTM, and VAEs in Advancing Music Generation 5th

Exploring the Potential of GANs, LSTM, and VAEs in Advancing...

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5th International Conference on Data Science, Machine Learning and Applications

作者： Pavan, G. Sai Ram Kucharlapati, Akash Varma Moneesh, N. Abhishek, S. Anjali, T. Amrita Vishwa Vidyapeetham Amrita Sch Comp Dept Comp Sci & Engn Amritapuri India

ISBN: (纸本)9789819780334;9789819780310;9789819780303

In this paper, we explore three popular approaches: GANs, LSTMs, and VAEs, to explore the fascinating world of computer-generated music. To envision GANs, imagine two creative friends working together to create a musical composition;one works diligently on the composition while the other serves as the discerning judge, ensuring its aesthetic appeal. As a memory reservoir, LSTMs, on the other hand, preserve the essence of previous melodies to serve as an inspiration for and guide in the creation of new harmonious compositions. Like a musical blender, VAEs expertly blend song fragments to produce completely new and melodic musical compositions. Our main goal is to determine which of these techniques produces the most enjoyable musical result while also pointing out any potential drawbacks. We can learn a lot about the future of computer-generated music, and its transformative potential in reshaping our listening experiences and perspectives on music composition, by carefully examining these methodologies.

关键词： Computers and music GANs LSTMs VAEs tunes melodies

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