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21st ieee International symposium on Parallel and Distributed Processing with applications, 13th ieee International Conference on Big Data and Cloud Computing, 16th ieee International Conference on Social Computing and Networking and 13th International Conference on Sustainable Computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2023

作者： Li, Junhui Xu, Guangping Yang, Hongzhang Wu, Yulei Tianjin University of Technology School of Computer Science and Engineering Tianjin China Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin China Key Laboratory of Computer Vision and System Ministry of Education China University of Bristol Faculty of Science and Engineering Bristol United Kingdom

ISBN: (纸本)9798350329223

In various applications in Internet of Things like industrial monitoring, large amounts of floating-point time series data are generated at an unprecedented rate. Efficient compression algorithms can effectively reduce the size of data, enhance transmission performance and storage efficiency, and simultaneously lower storage costs. Therefore, there is a need for lightweight and efficient stream compression algorithms. In this paper, we propose a novel lossless floating-point data compression algorithm called Ant. The main idea is to encode double-precision floating-point numbers into integer form, calculate the delta between adjacent values, and then convert the delta into unsigned integers. This encoding method effectively reduces storage costs and improves data compression efficiency. Extensive experiments on real-world datasets demonstrate that our algorithm achieves compression speeds at least as fast as state-of-the-art streaming methods, and a 63% relative improvement in average compression rate. © 2023 ieee.

关键词： Storage efficiency

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Reliability Qualification of 1250V Lateral GaN HEMTs for High Reliability Industrial applications (Invited)

Reliability Qualification of 1250V Lateral GaN HEMTs for Hig...

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2025 ieee International Reliability Physics symposium, IRPS 2025

作者： Varadarajan, Kamal Ankoudinov, Alexei Yang, Robert Kudymov, Alexey Shankar, Bhawani Murukesan, Karthick Georgescu, Sorin Power Integrations San JoseCA United States

ISBN: (纸本)9798331504779

In this work, we present detailed high-voltage reliability qualification results for the industry's first 1250Vrated lateral GaN HEMT with significant transient overvoltage capability making it ideal for high-reliability industrial applications. Based on the PowiGaN™ technology platform of Power Integrations, the 1250V GaN cascode device shows stable off-state leakage beyond 2000V with a typical breakdown voltage of 2300 V. Results from high voltage off-state reliability stresses HTRB and H3TRB along with hard-switching DHTOL stress are discussed in detail, illustrating for the first time that lateral GaN HEMTs can be a realistic wide band-gap solution at this voltage level. Additionally, we have also demonstrated high-efficiency power supply operation at high-input voltages using a 1250V flyback switcher IC, confirming its readiness for real-world use. © 2025 ieee.

关键词： Overhead lines

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Wireless Portable Bot Car Controlled by Brain Signals 5

Wireless Portable Bot Car Controlled by Brain Signals

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5th International Conference on Electronics and Sustainable Communication Systems, ICESC 2024

作者： Kapur, Garima Semwal, Gracy Kushwaha, Pankaj Jaypee Institute of Information Technology Electronics &communication Department Noida India

ISBN: (纸本)9798350379945

This research work presents the implementation of a wireless, portable bot car controlled by brain signals. This pioneering approach integrates advanced neurotechnology with the Internet of Things (IoT) and wireless technology. The proposed prototype features effective wireless connectivity, ensuring seamless communication between the brain-computer interface (BCI) and the bot car. Efficient real-time data analysis is achieved through thresholding techniques, enabling rapid and accurate interpretation of brain signals. The incorporation of hysteresis significantly reduces the risk of accidental interruptions caused by unstable sampling, thereby improving the reliability and robustness of the portable bot car. The dynamic interplay of brain signals within this designed framework holds significant potential across multiple industries, including healthcare, assistive technologies, entertainment, and automotive sectors. The user-friendly interface ensures the prototype is accessible and easy to operate, highlighting its practicality and efficiency as an IoT/embedded system-based solution. The project underscores the transformative impact of combining brain signal processing with wireless technology, paving the way for sustainable automotive and healthcare solutions with potential future applications in the field of Brain-Computer Interfaces. © 2024 ieee.

关键词： Bot (Internet)

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Method of Moment Analysis of Carbon Nanotubes embedded in a Lossy Dielectric Slab Using a Multilayer Dyadic Green's Function

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ieee TRANSACTIONS ON ANTENNAS AND PROPAGATION 2022年第8期70卷 6918-6933页

作者： Dey, Sumitra Chatterjee, Deb Garboczi, Edward J. Hassan, Ahmed M. Univ Missouri Dept Comp Sci & Elect Engn Kansas City MO 64110 USA Cadence Design Syst San Jose CA 95134 USA NIST Mat Measurement Lab Appl Chem & Mat Div Boulder CO 80305 USA

Modeling the electromagnetic response of carbon nanotube (CNT) reinforced composites is inherently a 3-D multiscale problem that is challenging to solve in real time for nondestructive evaluation (NDE) applications. This article presents a fast and accurate full-wave electromagnetic solver based on a multilayer dyadic Green's function approach. In this approach, we account for the effects of the dielectric slab, where the CNTs are embedded, without explicitly discretizing its interfaces. Due to their large aspect ratios, the CNTs are modeled as arbitrary thin wires (ATWs), and the method-of-moment (MoM) formulation with distributed line impedance is used to solve for their coupled currents. The accuracy of the in-house solver is validated against the commercial MoM and the finite element method (FEM) solvers over a broad range of frequencies (from 1 GHz to 10 THz) and for a wide range of dielectric slab properties. Examples of 100 nm-long vertical and horizontal CNTs embedded in a 1 mu m-thick lossy dielectric substrate are presented. The in-house solver provides more than 50x speed up while solving the vertical CNT and more than 570x speed up while solving the horizontal CNT than a commercial MoM solver over the GHz-to-THz frequency range.

关键词： Arbitrary thin wire (ATW) carbon nanotubes (CNTs) electric field integral equation (EFIE) method of moment (MoM) multilayer dyadic Green's function Sommerfeld integrals (SI)

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A Human Activity Recognition System Using Temporal Convolutional Network with Multi-Scale Temporal Attention Mechanism 4

A Human Activity Recognition System Using Temporal Convoluti...

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4th ieee International Conference on Mobile Networks and Wireless Communications, ICMNWC 2024

作者： Sundari, V Soma Hossain, Ramy Read Sindhu, Monika Jansirani, D. Saranya, N. Naga Saveetha College of Liberal Arts and Sciences Simats Department of Computer Science Chennai India College of Technical Engineering The Islamic University of Al Diwaniyah Department of Computers Techniques Engineering Al Diwaniyah Iraq University Centre for Research & Development Chandigarh University Mohali India New Prince Shri Bhavani College of Engineering and Technology Department of Information Technology Chennai India Saveetha Liberal Arts and Sciences Simats Department of Computer Applications Chennai India

ISBN: (纸本)9798350352931

In recent years, the common adoption of smart glasses has created new opportunities for human and computer interaction mainly in Human Activity Recognition (HAR) domain. The smart glasses can capture a collection of wearer's activities data with the help of built-in sensors and cameras. However, the development of HAR systems for smart glasses led to significant challenges such as the requirement of real-time processing and effective computation on resource-constrained devices. Therefore, this research aims to develop an embedded Artificial Intelligence (AI) powered HAR system for smart glasses using Temporal Convolutional Network (TCN) with Multi-Scale Temporal Attention Mechanism (MSTAM). Initially, the data is gathered from HAR dataset, a complete source of human activities. Then, the collected data is further preprocessed with the help of Dynamic time Warping (DTW), as it aligns time-series signals of verifying lengths. After that, Haar Wavelet and Symlet Wavelet Coefficient Scattering (HW-SWCS) is employed to extract the features from preprocessed signals. Finally, TCN-MSTAM is introduced to recognize and classify the human activities. From the results, the proposed TCN-MSTAM model offered outstanding results in accuracy of 93.4% when compared with existing Sensors based on a Capsule Network (SensCapsNet). © 2024 ieee.

关键词： Metadata

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Survey and Compare of Some embedded Operation Systems for the Internet of Things 7

Survey and Compare of Some Embedded Operation Systems for th...

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7th International Conference on Computer and Communication Systems, ICCCS 2022

作者： Yuan, Benchi Chen, Xiangning Cao, Shuai Nanjing University School of Electronic Science and Engineering Nanjing China

ISBN: (数字)9781665450607

ISBN: (纸本)9781665450607

The Internet of Things has a very wide range of applications, and embedded devices are widely used in new fields such as smart home, smart transportation, medical care, and smart cars. The embedded operating system for the Internet of Things should have good real-time performance and reliability, can make more reasonable and effective use of CPU resources, simplify the design of application software, and improve the efficiency of system development. With the rapid development of the Internet of Things and the gradual maturity of Internet of Things applications, the Internet of Things OS developed on the basis of embedded real-time operating systems is emerging. The embedded operating system running in the Internet of Things environment is different from the ordinary RTOS and has new technical characteristics and requirements. Through the study of the development history of the Internet of Things operating system and a brief analysis of the technical architecture of several emerging and powerful Internet of Things operating systems such as Huawei LiteOS, AliOS Things, and RT-Thread, this article summarizes the characteristic requirements of the kernel and peripheral modules of the embedded operating system oriented to the Internet of Things. © 2022 ieee.

关键词： Internet of things

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Compact embedded Detection Electronics for Accurate Dose Measurements of MV Pulsed X-rays and Electrons 17

Compact Embedded Detection Electronics for Accurate Dose Mea...

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17th ieee International symposium on Medical Measurements and applications (ieee MeMeA)

作者： Pettinato, Sara Girolami, Marco Olivieri, Riccardo Stravato, Antonella Barettin, Daniele Salvatori, Stefano Univ Niccolo Cusano Rome Italy ISM CNR Rome Italy CNR Ist Struttura Mat Rome Italy San Giovanni Addolorata Hosp Uosd Clin Risk Management Rome Italy San Giovanni Addolorata Hosp UOC Radiotherapy Dept Rome Italy

ISBN: (数字)9781665482998

ISBN: (纸本)9781665482998

Modern radiation therapies in which ultra-narrow, collimated radiation beams are used to treat even irregular tumor geometries are leading to new challenges in dosimetry. In this context, FLASH technique, involving the use of high dose-rates as well as ultra-high dose-per-pulse beams, is receiving more and more attention. On this basis, the development of detection systems capable of meeting the stringent requirements of dose-per-pulse monitoring, such as real-time acquisition and processing of dosimeter signals, is becoming crucial. In this work, the main features of a synthetic single-crystal diamond dosimeter coupled to a specifically designed compact and versatile front-end electronics are illustrated. Proposed system is able to monitor the generated charge by the detector at every pulse on the impinging beam. Tests were performed for synchronous measurements under either X-ray photons or electrons generated by a medical linear accelerator, with an accelerating voltage of 6 MV. Experimental results highlight that diamond dosimeter displays a response only dependent on the impinging dose regardless of the beam nature (X-rays or electrons), therefore confirming that diamond is the elective material for accurate dosimetry in radiotherapy. The system acquires, processes and transfers the data within 0.5 ms, thus allowing for a real time monitoring for pulse repetition rates up to more than 2 kHz. Exploiting the high quality of the implemented components, the proposed front-end and read-out electronics represents an effective solution for accurate dose-per-pulse measurements in modern radiotherapy techniques.

关键词： CVD-diamond LINAC X-ray pulses electron detection dose-per-pulse

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Deep Neural Network Based Multi-Object Detection for real-time Aerial Surveillance 11

Deep Neural Network Based Multi-Object Detection for Real-ti...

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11th International symposium on Electronic Systems Devices and Computing, ESDC 2023

作者： Dey, Rebanta Pandit, Binit Kumar Ganguly, Anirban Chakraborty, Anirban Banerjee, Ayan Indian Institute of Engineering Science and Technology Electronics and Telecommunication Engineering Howrah Shibpur India University of Engineering and Management Computer Science and Technology Kolkata India

ISBN: (纸本)9781665455725

Aerial surveillance is one of the widely used modern days surveillance methodologies, finding applications in many important fields including military and civilian. This article presents a comprehensive study of Deep Neural Network (DNN) based solutions for real-time object tracking from Unmanned Aerial Vehicle (UAV) using a modified version of the state-of-the-art object detection algorithm YOLOv5 model. The modified YOLOv5 architecture is achieved by changing the activation function to Rectified Linear Unit (ReLU) and fine-tuning the network's hyperparameter. A comparative analysis was then done on a subset of the AU-AIR dataset by comparing the different YOLOv5 models based on the network depth to determine the improvements in training speed and accuracy. The modified network was also compared in terms of mean average precision (mAP) to the original paper, a performance gain of almost 2.9 times was achieved in the best-case scenario. © 2023 ieee.

关键词： Object detection

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AI/ML Model Training in O-RAN: Assessing Datasets for Hoarding and Choosing Strategies 17

AI/ML Model Training in O-RAN: Assessing Datasets for Hoardi...

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17th ieee International Conference on Advanced Networks and Telecommunications Systems, ANTS 2023

作者： Gudepu, Venkateswarlu Chirumamilla, Bhargav Chintapalli, Venkatarami Reddy Castoldi, Piero Valcarenghi, Luca Kondepu, Koteswararao Indian Institute of Technology Dharwad India National Institute of Technology Calicut Calicut India Scuola Superiore Sant'Anna Pisa Italy

ISBN: (纸本)9798350307672

The advent of Open Radio Access Network (O-RAN) is transforming the traditional cellular networks into flexible, interoperable, and innovative through open standard interfaces (i.e., O1, A1, E2) and RAN Intelligent Controllers (RICs) - Near-real time and Non-real time (Near- and Non-RT RIC). These RICs leverage AI/ML models for intelligent decisions, interacting with RAN components - centralized units (CUs), distributed units (DUs), and radio units (RUs). Choosing the appropriate data for AI/ML model training in O-RAN is critical, as training based on the nature of the data, whether homogeneous or heterogeneous, can significantly improve model accuracy and efficient resource utilization. This paper introduces an approach that determines the dataset homogeneity by employing the Kolmogorov-Smirnov test (KS Test) and also considers evaluating both real-time and synthetic datasets. © 2023 ieee.

关键词： Radio access networks

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Efficient Drone-Based Mobile Wireless Sensor Network for Spatio-Temporal Environmental Monitoring 18

Efficient Drone-Based Mobile Wireless Sensor Network for Spa...

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18th ieee International Conference on Advanced Networks and Telecommunications Systems, ANTS 2024

作者： Kapoor, Ayshika Kumar, Dheeraj Indian Institute of Technology Department of Electronics and Communication Engineering Uttarakhand Roorkee India

ISBN: (纸本)9798350391725

The technological advancements in wireless sensor networks (WSNs) and unmanned aerial vehicles (UAVs) or drones have made significant contributions in various fields, benefiting human society. Although WSNs have been widely used for environmental monitoring, their utility is constrained by inherent limitations, which make them suitable only for small-scale sensing tasks. On the other hand, UAVs provide quick access to large areas, including challenging terrains, allowing faster data collection that is both less labor-intensive and more cost-effective. In this paper, we present an efficient method to collect data for environmental monitoring using a drone-based mobile WSN system. The framework discretizes the region to be monitored into a 3D spatial-temporal field, where the field is further divided into sub-grids for the deployment of drones in each sub-grid. The drones utilize their built-in sensors to move around the designated region in a pre-defined trajectory to collect spatio-temporal data. In order to obtain parameter values at intermediate points within the surveyed region, interpolation techniques such as inverse distance weighting (IDW) and nearest neighbors (NN) are applied, ensuring comprehensive data coverage. To validate the feasibility of our proposed system, experiments are performed for temperature modeling applications using a simulated dataset, a real-world NYC weather dataset, and a real-time REST API dataset. The obtained results demonstrate that the proposed model is well-suited for large-scale sensing, even in remote areas, exhibiting cost-effectiveness and substantial reductions in labor and resource requirements, providing a robust and efficient solution for real-time environmental data collection and analysis. © 2024 ieee.

关键词： Environmental monitoring

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