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3rd IEEE International Conference on Mobile Networks and Wireless Communications, ICMNWC 2023

作者： Kavitha, V.R. Muthu, Annamalai Geetha, B. Pandi, V. Samuthira Dinesh, M. Princy, B. Anni R.M.K. Engineering College Department of Computer Science and Business Systems Tamil Nadu Chennai India University of Technology & Applied Science Department of Engineering Nizwa Oman Prince Shri Venkateshwara PadmavathyEngineering College Department of Science & Humanities Tamil Nadu Chennai India Centre for Advanced Wireless Integrated Technology Chennai Institute of Technology Tamil Nadu Chennai India Saveetha School of Engineering SIMATS Department of VLSI Microelectronics Tamil Nadu Chennai India Panimalar Engineering College Department of Computer and Communication Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350317022

The increased risk of being involved in a traffic collision is directly proportional to the rate at which the number of vehicles on the road is growing. The majority of people in the world believe that driving under the influence of alcohol is a significant factor in the number of people killed in car accidents. The fundamental purpose of this investigation is to develop a device that is able to determine the degree of drunkenness that is present in the driver of a motor vehicle. The purpose of the proposed system is to discourage users from getting behind the wheel while under the influence of alcohol or drugs in order to reduce the number of accidents that are caused by intoxicated drivers. As part of this investigation, we propose the Fuzzy Assisted Alcohol Detection Mechanism (FAADM), which is a logical fuzzy-based alcohol detection mechanism. It uses a Direct Current (DC) motor as the vehicle's engine and a push button as its ignition system. This mechanism detects the presence of alcohol using a fuzzy-logic approach. The efficiency of this system is always being evaluated to ensure that it performs as designed. If this system were put into place, there would be a reduction in the number of accidents on the roads of smart cities that were caused by drivers who were under the influence of alcohol. It is strongly suggested that this system be fitted and installed inside the vehicle. In the event of an unexpected emergency, the engine should be turned off and the alarm should be activated. If there has been no drinking or accidents, the security system can be disarmed and the vehicle's engine should be started. If alcohol is found, the car will be turned off and an alarm will ring. As the number of incidents caused by intoxicated drivers continues to rise, the implementation of a system that combines alcohol detection and vehicle immobilization has been proposed as a potential solution. Engineers have developed a gadget that can detect the amount of alcohol in a d

关键词： Alcohol Detection Mechanism Alcohol Identification Drunk and Drive FAADM Fuzzy Logic Microcontroller Road Safety Sensors

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Computational Model Based on CNN to Identify Masses from Liver Images 2

Computational Model Based on CNN to Identify Masses from Liv...

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2nd International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2024

作者： Jyothirmai, Ch. N. V. Hemalakshmi, G.R. Prakash, N.B. Upadhye, Vijay Jagdish Patil, Harshal Taqui, Syed Noeman Potti Sreeramulu Chalavadhi Mallikarjuna Rao College of Engineering and Technology Department of CSE Andhra Pradesh 521 225 India School of Computing Science and Engineering VIT Bhopal University Madhya Pradesh 466114 India National Engineering College Department of Electrical and Electronics Engineering Kovilpatti 628503 India Parul Institute of Applied Sciences Parul University Research and Development Cell Department of Microbiology Gujarat 391760 India Department of Computer Science and Engineering Maharashtra 412 115 India Saveetha Institute of Medical and Technical Sciences Department of VLSI Microelectronics Saveetha School of Engineering Chennai602105 India

ISBN: (纸本)9798350327533

Therefore, Convolutional Neural Networks (CNNs) are capable of predicting or extrapolating from identified patterns to unknown data, enabling the analysis and extraction of knowledge from large images, in order to produce consistent outputs for inputs not previously presented. On the downside, the training process takes a long time as it is computationally expensive. Aiming to reduce the computational time to perform the training of the neural network (NN), and the analysis of images during the testing process, as well as taking advantage of the natural distributed characteristic of ANN, it was decided to transfer the processing-intensive parts of the tool from CPU (Central Processing Unit) to a GPU (Graphics Processing Unit). Finally, simulator tests were carried out, with consequent verification of the effectiveness of diagnoses on ultrasound images of the liver. The accuracy and total processing time for carrying out the analyses proposed during this research were then evaluated, making a comparison between the network training and testing times obtained on the CPU and GPU. It can also be seen-in both Tr&Tt cases-that GPU had a higher gain than CPU (about 10.6 times faster), even when dealing with a small database, with 120 images of 202500 pixels each. © 2024 IEEE.

关键词： Central Processing Unit Convolutional Neural Networks Graphics Processing Unit Masses Ultrasound liver images

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Decentral load control for data centers 13

Decentral load control for data centers

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2020 IEEE Congress on Cybermatics: 13th IEEE International Conferences on Internet of Things, iThings 2020, 16th IEEE International Conference on Green Computing and Communications, GreenCom 2020, 13th IEEE International Conference on Cyber, Physical and Social Computing, CPSCom 2020 and 6th IEEE International Conference on Smart Data, SmartData 2020

作者： Uster, Felix Plocksties, Franz Timmermann, Dirk Institute of Applied Microelectronics and Computer Engineering University of Rostock Rostock Germany

ISBN: (纸本)9781728176475

The regulation and stabilization of the power grid requires various system services that have been provided so far primarily by conventional power plants. With the future shutdown of coal-fired and nuclear power plants, investigations into the provision of these services will become all the more important in order to ensure the safe operation of the grid. Currently, photovoltaic and wind can only provide limited so-called control power, so that new methods such as the regulation of large consumers will become interesting. Adapting the electricity requirements of consumers to the current grid situation has a comparable effect to the provision of additional balancing power on the generation side. Some consumers like data centers can provide primary control power at high speed. In this paper we present how data centers can autonomously support grid stabilization with minimal impact on the daily operation. Additional benefits include an higher efficiency and the ability to take advantage of any future financial bonuses by regulation authorities or electricity suppliers. © 2020 IEEE.

关键词： Power control

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The Impact of Hot Carrier Injection-Induced Device Degradation for Lower-Power FinFETs

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Journal of Electronic Materials 2023年第2期52卷 1391-1399页

作者： Chen, Yu-Lin Yeh, Wen-Kuan Hsu, Heng-Tung Chen, Ke-Horng Lien, Der-Hsien Lin, Wen-Chin Yu, Tien-Han Chiu, Yu-Sheng Godwinraj, D. Godfrey, D. Wu, Chien-Hung International College of Semiconductor Technology National Yang Ming Chiao Tung University Hsinchu Taiwan Graduate Degree Program of College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan Institute of Electronics National Yang Ming Chiao Tung University Hsinchu Taiwan Institute of Microelectronics National Cheng Kung University Tainan Taiwan Department of ECE Amal Jyothi College of Engineering Kerala Kottayam India Department of Optoelectronics and Materials Engineering Chung Hua University Hsinchu Taiwan Department of Electronics and Communication Engineering Dayananda Sagar University Bengaluru India National Applied Research Laboratories Hsinchu Taiwan

The impact of hot carrier injection (HCI) on the performance of standard and low-VT FinFETs are investigated and benchmarked with each other. For this investigation, these FinFETs were fabricated with various gate lengths (L) from 16 to 36 nm. HCI-induced transconductance degradation in standard devices for gate length variations of 36 nm down to 16 nm was 75%, while it was 35% for low-VT devices. Similarly, the degradation of threshold voltage in standard devices for gate length variations of 36 nm down to 16 nm was 39%, while it was 36% for low-VT device. In this work, as the device is subject to HCI, we found that: (1) short-channel devices cause severe degradation on the threshold voltage and transconductance (gm) compared to long-channel devices, owing to the higher electric field for short-channel devices at the gate edge, (2) standard devices exhibit a more stable threshold voltage than that of low-VT power devices, since the TiN barrier layer prevents Al atom diffusion into the HfO2 layer, and (3) the transconductance efficiency of standard devices is better than that of low-VT power devices. Further, the lower-VT devices show lower transconductance degradation than standard devices. However, the transconductance degradation of the long-channel standard and low-VT devices are the same. Compared to short-channel low-VT devices, extended-channel standard devices are more immune to the HCI effect. © 2022, The Minerals, Metals & Materials Society.

关键词： Threshold voltage

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A SystemC Model of the IEEE 802.11 EDCA Protocol for Virtual Prototyping

A SystemC Model of the IEEE 802.11 EDCA Protocol for Virtual...

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International Symposium on Networks, computers and Communications (ISNCC)

作者： Benjamin Beichler Michael Rethfeldt Hannes Raddatz Lukas Steffen Dirk Timmermann Christian Haubelt Institute of Applied Microelectronics and Computer Engineering University of Rostock Germany

Due to the increasing complexity of distributed embedded systems, the development process demands early substantiation of design decisions for the targeted system. Virtual prototypes enable an early validation of hardware/software systems and they have proven to be very beneficial for target software development. However, these prototypes often do not include models for inter-device communication aspects of distributed systems. Especially the use of wireless communication has a significant impact on the overall system behavior and performance. This paper introduces a SystemC model of an essential part of IEEE 802.11 Wireless LAN communication, the Enhanced Distributed Channel Access (EDCA) protocol. In comparison to widely used network simulations, the modeling with SystemC promises an easier integration into existing virtual prototypes. EDCA is the main part of the lower medium access layer (MAC) of IEEE 802.11 and interfaces to the physical-layer communication as well as to non-time-critical higher MAC-layer functions. We conducted experiments with an additional simple physical communication channel model to compare our solution in terms of precision and performance to the well-established network simulator ns-3. We show that our model differs by $\approx 0.3 \%$ of retransmitted frames and an accompanied difference of the overall simulated transmission time of $\approx 0.45 \%$. It meets the overall expectations for the stochastic EDCA protocol. Moreover, the presented model has a significantly better simulation performance with $3 \cdot 10^{-5}$ s wall-clock time per frame, which is at least two orders of magnitude better than with the compared ns-3 simulation.

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Towards virtual prototyping of electrically active implants using systemc-AMS

Towards virtual prototyping of electrically active implants ...

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GMM/ITG/GI-Workshop Methoden und Beschreibungssprachen zur Modellierung und Verifikation von Schaltungen und Systemen, MBMV 2020 - GMM/ITG/GI Workshop Methods and Description Languages for Modeling and Verification of Circuits and Systems, MBMV 2020

作者： Heller, Jakob Niemann, Christoph Plocksties, Franz Haubelt, Christian Timmermann, Dirk Institute of Applied Microelectronics and Computer Engineering University of Rostock Rostock18051 Germany

ISBN: (纸本)9783800752218

Deep Brain Stimulation is an indispensable therapy option for severe neurodegenerative diseases like parkinson. However, the lack of understanding of the functional principle hinders an optimal clinical application. Therefore, basic research in animal models is crucial. For the development of neurostimulators in rodents, physical prototyping alone is not feasible anymore due to the growing complexity and necessary optimization of the overall implants. However, there is no scientific approach for virtual prototyping of neurostimulators. This work proposes a power model for a developed neurostimulator, based on a time continuous battery model and power-state-machines. The model was implemented in SystemC and SystemC-AMS and validated against measurements. The model helped us understand and find power optimal working points of the implant and thus achieve a runtime gain of 44% with a given battery. Consequently, this work shows that we can use virtual prototyping in SystemC-AMS to aid design decisions for future implant versions. © 2020 MBMV 2020: Methoden und Beschreibungssprachen zur Modellierung und Verifikation von Schaltungen und Systemen - GMM/ITG/GI-Workshop. All rights reserved.

关键词： Virtual prototyping

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Approximate Multipliers for Optimal Utilization of FPGA Resources

Approximate Multipliers for Optimal Utilization of FPGA Reso...

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IEEE Design and Diagnostics of Electronic Circuits and Systems (DDECS)

作者： Christoph Niemann Michael Rethfeldt Dirk Timmermann Institute of Applied Microelectronics and Computer Engineering University of Rostock Germany

Approximate or inexact arithmetic is a promising approach towards lower power consumption for applications that can tolerate a certain amount of imprecision. As human perception is limited in its precision, this applies to image and audio processing. Beyond, other applications like neuronal networks or AI processing can benefit from such arithmetic as well, as they are inherently tolerant to a certain amount of inaccuracy. One of the most critical components of arithmetic circuits regarding power, delay, and area are multipliers. Various sophisticated approaches towards approximate multipliers are already published for ASICs. However, such ASIC approaches are under-performing in conjunction with the specific Lookup-Table (LUT)-based design of FPGAs. As FPGAs gain in importance for applications like signal processing, there is a substantial lack of approximate design methodology for FPGAs. We propose an approach towards approximate signal processing that is specifically tailored towards the LUT-based hardware of FPGAs. It allows for significant performance improvements while lowering the energy demands. While introducing an insignificant average relative error of just 0.14%, we achieve a 45.9% area reduction in terms of LUTs while decreasing the delay by 30.6% compared to the Xilinx Vivado multiplier IP core. Our proposed design is open source and available at https://***/niemann-c/approx-mult-for-fpga.

关键词： Power demand Design methodology Signal processing Hardware Delays Table lookup IP networks

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AI-based Object Detection for Assisting the Visually Impaired People 5

AI-based Object Detection for Assisting the Visually Impaire...

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5th International Conference on Mobile Computing and Sustainable Informatics, ICMCSI 2024

作者： Sameer, Syed Madan, Parul Kannan, Sathish Upadhye, Vijay Jagdish Patil, Harshal Rajkumar, S. Campus Department of Science and Technology Karnataka Bengaluru560012 India Graphic Era Deemed to be University Department of Computer Science & Engineering Uttarakhand Dehradun248002 India Saveetha Institute of Medical and Technical Sciences Department of VLSI Microelectronics Saveetha School of Engineering Tamil Nadu Chennai602105 India Parul Institute of Applied Sciences Parul University Research and Development Cell Department of Microbiology Gujarat Waghodia India Symbiosis Institute of Technology Maharashtra Pune412 115 India Hawassa University Faculty of Manufacturing Institute of Technology Department of Mechanical Engineering Ethiopia

ISBN: (纸本)9798350395235

In recent decades, vision problems have become more common. One significant barrier is that people who are visually impaired generally require assistance performing their daily tasks. As a result, developing a technological solution to this challenge is critical. Implementing an automatic object identification system can enable visually impaired people to roam independently. The study employs two Artificial Intelligence (AI) models, a Region-based Fully Convolutional Network (RFCN) and a Mask Region-based Convolutional Neural Network (Mask RCNN), to detect objects and assess their performance. The evaluation demonstrates RFCN's outstanding performance with an impressive Mean Average Precision (mAP) score of 0.825. The Raspberry Pi processor is used as a vital component in the process of hardware development. The RFCN model is integrated into the processor to aid in the identification of objects collected by the system's picamera. The detected objects are communicated to users via auditory feedback. The hardware system also includes an ultrasonic sensor, which provides distance information for the detected objects. This full hardware solution is specifically developed to help visually impaired people overcome mobility issues in both indoor and outdoor settings. The suggested system seeks to improve the autonomy and safety of visually impaired individuals in their day-to-day activities by seamlessly mixing advanced technologies such as AI and embedded systems. © 2024 IEEE.

关键词： Object detection

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An FPGA-based 7-ENOB 600 msample/s adc without any external components 21

An FPGA-based 7-ENOB 600 msample/s adc without any external ...

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2021 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, FPGA 2021

作者： Leuenberger, Lukas Amiet, Dorian Wei, Tao Zbinden, Paul OST-Eastern Switzerland University of Applied Sciences Imes Institute for Microelectronics and Embedded Systems Rapperswil Switzerland University of Rhode Island Department of Electrical Computer and Biomedical Engineering Kingston United States

ISBN: (纸本)9781450382182

Analog to digital converters (ADCs) are indispensable nowadays. Analog signals are digitized earlier and earlier in the processing chain to reduce the need for complex analog signal processing. For this reason, ADCs are often integrated directly into field-programmable gate arrays (FPGA) or microprocessors. However, such ADCs are designed for a specific set of requirements with limited flexibility. In this paper, a new structure of an FPGA-based ADC is proposed. The ADC is based on the slope ADC, where a time-to-digital converter (TDC) measures the time from the beginning of a reference slope until the slope reaches the voltage-to-be-measured. Only FPGA-internal elements are used to build the ADC. It is fully reconfigurable and does not require any external components. This innovation offers the flexibility to convert almost any digital input/output (I/O) into an ADC. Considering the very high number of digital I/O ports available in today's FPGA systems, this enables the construction of a massive and powerful ADC array directly on a standard FPGA. The proposed ADC has a resolution of 9.3 bit and achieves an effective number of bits (ENOB) of 7 at a sample rate of 600 MSample/s. The differential nonlinearity (DNL) ranges from-0.9 to 0.9 bit, and the integral nonlinearity (INL) is in the range between-1.1 and 0.9 bit. An alternative version of the ADC operates at 1.2 GSample/s and achieves an ENOB of 5.3. © 2021 ACM.

关键词： Signal processing

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An Attention-Based Parallel Algorithm for Hyperspectral Skin Cancer Classification on Low-Power GPUs

An Attention-Based Parallel Algorithm for Hyperspectral Skin...

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Euromicro Symposium on Digital System Design

作者： Emanuele Torti Marco Gazzoni Elisa Marenzi Raquel Leon Gustavo Marrero Callicò Giovanni Danese Francesco Leporati Dept. of Electrical Computer and Biomedical Engineering University of Pavia Pavia Italy Institute for Applied Microelectronics (IUMA) Universidad de Las Palmas de Gran Canaria Las Palmas de Gran Canaria Spain

Recently, several medical applications have relied on hyperspectral imaging. This technology enables both automated diagnosis and surgeon guidance. The employed algorithms adopt machine and deep learning methods to classify the images. In particular, Vision Transformers are a recent deep architecture that have been used to classify hyperspectral images of skin cancers achieving interesting results. However, deep architectures are computationally intensive and parallel architectures are mandatory to ensure a fast classification (depending on the application type even in real time). In this paper, we propose a parallel Vision Transformer architecture exploiting a low power GPU targeting the development of a portable diagnostic device. The classification time and power consumption of the low power board are compared with the performance of a desktop GPU. The results clearly highlight the suitability of the low power GPU to develop a portable diagnostic system based on hyperspectral imaging.

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