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Towards Virtual Prototyping of Electrically Active Implants Using SystemC-AMS

Towards Virtual Prototyping of Electrically Active Implants ...

MBMV 2020 - Methods and Description Languages for Modelling and Verification of Circuits and Systems;GMM/ITG/GI-Workshop

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

ISBN: (纸本)9783800752201

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.

关键词： Virtual prototyping Neurostimulator Implants and Prostheses powered models Deep Brain Stimulation Prosthesis Laboratory animal Electricity

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Ability to control the temperature profile of soldering using local heat screens 11

Ability to control the temperature profile of soldering usin...

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11th National Conference with International Participation, ELECTRONICA 2020

作者： Videkov, Valentin Tsenev, Valentin Faculty of Electronic Engineering and Technologies Department of Microelectronics College of Energy and Electronics Technical University of Sofia Department Applied Electronic and Computer Technology Sofia1000 Bulgaria

ISBN: (纸本)9781728175317

This paper presents the results of the study of a method of soldering using heat shields. The essence of the method involves placing additional metal screens on the soldered SMD elements, which change the effective heat mass. Changing the effective mass allows for slower heating of sensitive elements. In the present study, attention is paid to the effect of the thickness of the printed circuit board on the change of the temperature profile under the screen. The impact of the additional heat mass in the screen at the moment of change of the heat profile is also considered. In addition to the amount of material added to the screen, the temperature of its phase conversion also has an effect. The results of using a reflow process with infrared heating are presented. © 2020 IEEE.

关键词： Temperature control

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Combined footprint with jet printing and soldering in the vapor phase 11

Combined footprint with jet printing and soldering in the va...

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11th National Conference with International Participation, ELECTRONICA 2020

作者： Tsenev, Valentin Videkov, Valentin College of Energy and Electronics Department Applied Electronic and Computer Technology Faculty of Electronic Engineering and Technologies Technical University of Sofia Department of Microelectronics Sofia1000 Bulgaria

ISBN: (纸本)9781728175317

The paper presents how a combined footprint of two or more solder pastes is obtained using a jet printer. When using the Pin in Paste (PiP) technology with over printing, two problems arise - obtaining solder balls outside the solder pads and not everywhere melting of the solder paste. To avoid these problems, a combined footprint of two solder pastes could be used, which can reduce the melting temperature and collect the solder material in the pad. Combined footprints were realized by means of a Jet printer on different pads with different content of the two solder pastes. Using the reflow process in the vapor phase, the soldering was performed. The research also was studied and evaluated how the solder material melted in different sized pads and with different contents of the two solder pastes. The soldering of SMD and TH elements was also observed and evaluated using a combined fingerprint. © 2020 IEEE.

关键词： Soldering

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An Improved Fuzzy Logic Based Alcohol Detection System to Preserve Road Safety using Smart Sensors Association

An Improved Fuzzy Logic Based Alcohol Detection System to Pr...

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Mobile Networks and Wireless Communications (ICMNWC), IEEE International Conference on

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

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

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Computational Model Based on CNN to Identify Masses from Liver Images

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

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Intelligent Data Communication Technologies and Internet of Things (IDCIoT), International Conference on

作者： CH. N. V. Jyothirmai G.R. Hemalakshmi N.B. Prakash Vijay Jagdish Upadhye Harshal Patil Syed Noeman Taqui Department of CSE Potti Sreeramulu Chalavadhi Mallikarjuna Rao College of Engineering & Technology Andhra Pradesh India School of Computing Science and Engineering VIT Bhopal University Madhya Pradesh India Department of Electrical and Electronics Engineering National Engineering College Kovilpatti India Department of Microbiology Research and Development Cell Parul Institute of Applied Sciences Parul University Gujarat India Department of Computer Science and Engineering Symbiosis Institute of Technology Symbiosis International (Deemed University) Maharashtra India Department of VLSI Microelectronics. Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India

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.

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Research on Credit Risk Early Warning Model of Commercial Banks Based on Neural Network Algorithm

arXiv

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arXiv 2024年

作者： Cheng, Yu Yang, Qin Wang, Liyang Xiang, Ao Zhang, Jingyu Columbia University The Fu Foundation School of Engineering and Applied Science Operations Research New YorkNY United States Microelectronics Science and Engineering Sichuan Chengdu China Washington University in St. Louis Olin Business School Finance St. LouisMO United States University of Electronic Science and Technology of China School of Computer Science & Engineering School of Cybersecurity Digital Media Technology Sichuan Chengdu China The University of Chicago The Division of the Physical Sciences Analytics ChicagoIL United States

In the realm of globalized financial markets, commercial banks are confronted with an escalating magnitude of credit risk, thereby imposing heightened requisites upon the security of bank assets and financial stability. This study harnesses advanced neural network techniques, notably the Backpropagation (BP) neural network, to pioneer a novel model for preempting credit risk in commercial banks. The discourse initially scrutinizes conventional financial risk preemptive models, such as ARMA, ARCH, and Logistic regression models, critically analyzing their real-world applications. Subsequently, the exposition elaborates on the construction process of the BP neural network model, encompassing network architecture design, activation function selection, parameter initialization, and objective function construction. Through comparative analysis, the superiority of neural network models in preempting credit risk in commercial banks is elucidated. The experimental segment selects specific bank data, validating the model's predictive accuracy and practicality. Research findings evince that this model efficaciously enhances the foresight and precision of credit risk management. Copyright © 2024, The Authors. All rights reserved.

关键词： Neural network models

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Research on Splicing Image Detection Algorithms Based on Natural Image Statistical Characteristics

arXiv

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arXiv 2024年

作者： Xiang, Ao Zhang, Jingyu Yang, Qin Wang, Liyang Cheng, Yu University of Electronic Science and Technology of China School of Computer Science & Engineering School of Cybersecurity Digital Media Technology Sichuan Chengdu China The University of Chicago The Division of the Physical Sciences Analytics ChicagoIL United States Microelectronics Science and Engineering Sichuan Chengdu China Washington University in St. Louis Olin Business School Finance St. LouisMO United States Columbia University The Fu Foundation School of Engineering and Applied Science Operations Research New YorkNY United States

With the development and widespread application of digital image processing technology, image splicing has become a common method of image manipulation, raising numerous security and legal issues. This paper introduces a new splicing image detection algorithm based on the statistical characteristics of natural images, aimed at improving the accuracy and efficiency of splicing image detection. By analyzing the limitations of traditional methods, we have developed a detection framework that integrates advanced statistical analysis techniques and machine learning methods. The algorithm has been validated using multiple public datasets, showing high accuracy in detecting spliced edges and locating tampered areas, as well as good robustness. Additionally, we explore the potential applications and challenges faced by the algorithm in real-world scenarios. This research not only provides an effective technological means for the field of image tampering detection but also offers new ideas and methods for future related research. Copyright © 2024, The Authors. All rights reserved.

关键词： Machine learning

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Strategies on Deep Brain Stimulation Devices for Effective Behavioral Studies in Rodents

Strategies on Deep Brain Stimulation Devices for Effective B...

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IEEE EMBS Conference on Biomedical engineering and Sciences (IECBES)

作者： Franz Plocksties Anika Lüttig Christoph Niemann Felix Uster Denise Franz Maria Kober Maximilian Koschay Stefanie Perl Angelika Richter Rüdiger Köhling Alexander Storch Dirk Timmermann Institute of Applied Microelectronics and Computer Engineering University of Rostock Germany Institute of Pharmacology Pharmacy and Toxicology University of Leipzig Leipzig Germany Institute of Physiology University of Rostock Rostock Rostock Germany Germany Department of Neurology University of Rostock Rostock Germany

Deep brain stimulation (DBS) is an essential therapeutic resource for treating movement disorders like dystonia. In order to gain further insight into the underlying disease mechanisms, animal models are used. However, the most critical obstacle for further research is the lack of subcutaneous implantable, miniaturized neurostimulators that can deliver reliable and replicable results. Extracorporeal mounting of neurostimulators on the head or back places a high burden on the animal. Furthermore, the animals frequently tamper with these stimulation setups, leading to high failure rates. In the absence of suitable diagnostic tests, such defects generally escape detection. Therefore, this article presents strategies for a DBS stimulator design intending to increase the scientific merit of behavioral experiments in rodents. In this context, we demonstrate an easy-to-implement, waterproof, biocompatible, and compact encapsulation method suited for full implantation in small rodents. Using this method, we implanted DBS devices subcutaneously in dystonic hamsters that have been successfully tested for up to 17 days.

关键词： Encapsulation Instruments Satellite broadcasting Deep brain stimulation Wires Rodents Epoxy resins

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Low-Cost, Self-Calibrating Light Barriers in Sports

Low-Cost, Self-Calibrating Light Barriers in Sports

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Mediterranean Conference on Embedded Computing (MECO)

作者： Theo Gabloffsky Ralf Salomon Institute of Applied Microelectronics and Computer Engineering University of Rostock Germany

ISBN: (数字)9781728169491

ISBN: (纸本)9781728169507

Light barriers are well-known and widely used tools in numerous application areas, as diverse as engineering, sports sciences, social sciences, and nuclear physics. Besides their success and distribution, light barriers have to be calibrated by hand, which is at least cumbersome and error-prone in the field. This paper proposes a new light barrier architecture, which solves this problems by providing a self-calibration mechanism. The first prototypical implementation was successfully tested in two different environments. The system costs are as low as 30 USD, since the proposed system can be realized by off-the-shelf components.

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Hot Carrier Injection Reliability of Fabricated N- and P-Type Multi FinFETs with Different TiN Stacks

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ECS Journal of Solid State Science and Technology 2023年第3期12卷 035007-035007页

作者： Chen, Yu-Lin Yeh, Wen-Kuan Hsu, Heng-Tung Chen, Ke-Horng Lin, Wen-Chin Yu, Tien-Han Chou, Hung-Ting Godwin Raj, D. Godfrey, D. International College of Semiconductor Technology National Yang Ming Chiao Tung University Taiwan Graduate Degree Program of College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Taiwan National Applied Research Laboratories Taiwan Institute of Microelectronics National Cheng Kung University Taiwan National Chung-Shan Institute of Science and Technology Taoyuan Taiwan Dept of ECE Amal Jyothi College of Engineering Kerala India Dept of Electronics and Communication Engineering Dayananda Sagar University Bengaluru India

Device degradation due to hot carrier injection (HCI) in multi-fin 20 nm and 10 nm N- and P-type FinFET devices are thoroughly analyzed. To further understand the HCI reliability of the four FinFET devices, the device is fabricated with a standard Vt base and low Vt base gate stacks with different work functions. It is evident that: (i) The standard Vt device sustains lower effective stress bias due to the difference in threshold voltage, resulting in a more stable threshold voltage than the low Vt base device, and (ii) the transconductance of the single N- and P-type FinFET is more severely degraded than the multi-fin N- and P-type FinFET, mainly because multi N- and P-type Finfet has coupe effect, which effectively reduces the impact of HCI. © 2023 The Electrochemical Society ("ECS"). Published on behalf of ECS by IOP Publishing Limited

关键词： FinFET

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