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Low Routing Complexity Multiframe Pipelined LDPC Decoder Based on a Novel Pseudo Marginalized Min-Sum Algorithm for High Throughput Applications

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IEEE Transactions on Very Large Scale Integration (VLSI) Systems 2023年第1期31卷 29-42页

作者： Davila, HenryLopez Wu, Tsung-Han Jou, Shyh-Jye Jerry Chen, Sau-Gee Tsai, Pei-Yun National Chiao Tung University Eecs International Graduate Program Hsinchu30010 Taiwan National Yang Ming Chiao Tung University Institute of Electronics Hsinchu30010 Taiwan National Central University Electrical Engineering Department Taoyuan32001 Taiwan

This article presents a high throughput and low routing complexity multiframe pipelined low-density parity check (LDPC) decoder design based on a novel pseudo marginalized min-sum (PMMS) message passing approach. The proposed PMMS approach reduces the required number of interconnections in the routing network allowing the design to be implemented with reduced hardware complexity, low power consumption and high throughput capability while supporting multiple coding rates with short and long codewords as defined in many application standards. Implementation results for IEEE802.11ad/ay standards show that the proposed design satisfies a target bit error rate (BER) requirement of 3× 10-7 with 64 quadrature amp mod (QAM) targeting high throughput applications. Furthermore, the proposed design is able to achieve a throughput of 62 and 101.8 Gb/s with two pipelining stages under 28-nm CMOS and 16-nm FinFET CMOS process, respectively. As compared to the existing NMS algorithm, the proposed design based on the PMMS approach reduces the number of wires in the routing network by 45.5%, and the wirelength of the overall decoder by 17%. The area and power consumption are also reduced by 9.4% and 12%, respectively, as compared to the conventional normalized min-sum (NMS) algorithm. © 1993-2012 IEEE.

关键词： Message passing

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Goral Detection System using YOLOv4 Object Detection Algorithm

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Transactions of the Korean Institute of Electrical Engineers 2022年第9期71卷 1308-1314页

作者： Lee, Han-Sung Oh, Yu-Jeong Park, Yung-Chul Lim, Sang Jin Cho, Hyun-Chong Dept. of Electronics Engineering and Interdisciplinary Graduate Program for BIT Medical Convergence Kangwon National University Korea Republic of Dept. of Interdisciplinary Graduate Program for BIT Medical Convergence Kangwon National University Korea Republic of Dept. of Electronics Engineering Kangwon National University Korea Republic of Dept. of Forest Science Kangwon National University Korea Republic of Dept. of Forest Science and Institute of Forest Science Kangwon National University Korea Republic of

Global industrialization has made human life comfortable, while causing environmental pollution. Environmental pollution has destroyed wildlife habitats, and as a result, several animals are endangered. In particular, long-tailed goral (Naemorhaedus caudatus) is an international endangered species that must be restored. A huge amount of photographic data has been accumulated through camera trap research for the restoration of endangered species. Until now, analysis of such photo data has only relied on experts, so it took a lot of time to analyze camera trap data. The goral detection system developed in this study, based on goral camera trap data, can enable goral data analysis at a faster than conventional methods. YOLOv4 was used as an object detection algorithm for goral detection. YOLOv4 is a network based on CSPDarknet53 and has improved performance through Bos (Bag of Specials) and BoF (Bag of Freebies). As a result, goral detection was possible with high accuracy and high speed. The performance of the goral detection system can be decreased by luminance at night. In this work, we propose a light invariant goral detection system by appropriately distributing day and night datasets for training YOLOv4. Test results on the night dataset showed an mAP of 0.907 and test results on the day dataset showed an mAP of 0.927. As a result, the goral detection system showed robust detection performance at night. © 2022 Korean Institute of Electrical Engineers. All rights reserved.

关键词： Cameras

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Comparison of Bioinspired MLP Controllers for Mobile Robots Obstacle Following/Avoidance

Comparison of Bioinspired MLP Controllers for Mobile Robots ...

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Latin America Congress on Computational Intelligence (LA-CCI)

作者： Matheus de S. Luiz M. A. Pastrana Lukas. A. Da Silva Pamela. R. A. N. Campagnucci Jose Mendoza-Peñaloza Rafael R.L. Benevides Daniel M. Muñoz Faculty of Gama Electronics Engineering Undergraduate Program University of Brasilia Brasilia DF Brazil Department of Mechanical Engineering Mechatronics Graduate Program University of Brasilia Brasilia DF Brazil

ISBN: (数字)9798350374575

ISBN: (纸本)9798350374582

Proportional, integral, and derivative (PID) controllers have been widely adopted for industrial applications. However, these controllers are not very efficient for non-linear systems. Artificial neural networks (ANN) based on the Multilayer Perceptron (MLP) have great potential to replace PID controllers due to their polynomial structure, allowing complex non-linear systems to be controlled. This article introduces the integration of four MLPs as alternatives to a traditional PID controller. These MLPs were trained through four bioinspired algorithms tailored for following tasks in mobile robots. The bioinspired algorithms employed for MLP network training include Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), Month-Flame Optimization (MFO), and Artificial Hummingbird Algorithm (AHA). A comparative analysis was conducted between these MLPs and a classic PID controller, focusing on parameters such as overshoot (OS), settling time (ST), and steady-state error for different simulated scenarios.

关键词： Training Process control Artificial neural networks Vectors Stability analysis Steady-state Mobile robots Optimization Videos Testing

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Microcontrolled System to Map and Monitor Normalized Difference Vegetation Index (NDVI) in Pasture Areas

Microcontrolled System to Map and Monitor Normalized Differe...

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International Symposium on Instrumentation Systems, Circuits and Transducers (INSCIT)

作者： Victório Mariani Roque Tiago Oliveira Weber Altamiro Amadeu Susin Electrical Engineering Graduate Program University Federal of Rio Grande do Sul Porto Alegre Brazil

ISBN: (数字)9798350350869

ISBN: (纸本)9798350350876

The vast territorial extension of Brazil is also a positive factor, but there is room for improvement through technological implementations. This work proposes monitoring the vegetation index (NDVI) by mapping the state of the pasture during the cattle's stay in the field. Measurements obtained with a commercial Greenseeker device are compared and integrated with values extracted from satellite images from the Satveg tool, which has a periodicity of 16 days and a resolution of 250 meters. A function is created to predict the NDVI in the total area based on points collected locally and from the satellite, using the KNN and Kriging algorithms for data fusion and interpolation. The article foresees contributions to the efficiency of agricultural production, allowing correct livestock management based on NDVI mapping. Additionally, results from previous simulations of analog circuits are presented for developing the NDVI measuring instrument. Future work aims to use the embedded system to automatically collect NDVI data and generate the Map presented here.

关键词： Meters Normalized difference vegetation index Vegetation mapping Data visualization Data integration Production Cows Analog circuits Satellite images Monitoring

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A Hybrid Inference Engine to Predict Uncertain Sugar Content for Sugar Industry

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Procedia Computer Science 2024年 245卷 480-489页

作者： Muhammad Asrol Napthaleni Ditdit Nugeraha Utama Suharjito Christian Harito Muhammad Syafrudin Industrial Engineering Department BINUS Graduate Program – Master of Industrial Engineering Bina Nusantara University Jakarta 11480 Indonesia Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta 11480 Indonesia Department of Artificial Intelligence and Data Science Sejong University Seoul 05006 South Korea

The sugar industry is facing challenges in increasing productivity to meet consumer demand. One opportunity for productivity improvement lies in ensuring sugar content. This study proposes a hybrid model to predict sugar content by considering uncertainty factors. A hybrid model combining fuzzy subtractive clustering, and a fuzzy inference system is proposed to predict sugar content. The clustering results using silhouette and fuzzy subtractive clustering successfully identified 6 cluster centres from 2225 datasets collected in a sugar industry in East Java Province. The hybrid inference engine model is designed with fuzzy rules derived from the clustered data. Two inference models are developed: triangular and Gaussian fuzzy numbers. The testing results indicate that the hybrid model with triangular fuzzy numbers shows the smallest error with an R2 value of 0.95. This model is possible to applied in the sugar industry for decision makers in improving productivity with taking attention into uncertain factors influencing sugar content.

关键词： Clustering Fuzzy Hybrid model Inference System Prediction Sugarcane

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Automation of User Pace-Adjusted Treadmill: Comparison of Control Methods based on LRF Sensors

Automation of User Pace-Adjusted Treadmill: Comparison of Co...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Brayan S. Moreno Ricardo C. Mello Anselmo Frizera Graduate Program in Electrical Engineering Federal University of Espírito Santo Vitória ES Brazil

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

Neurological disorders affect gait and posture, leading to significant difficulties in daily life. Traditional gait assessment lacks objective and quantifiable data, hindering comprehensive evaluation. To address these limitations, interactive and objective systems, such as smart walkers and specialized treadmills, have been developed utilizing advanced technologies to gather detailed gait data. This study focuses on evaluating two control strategies (A controller based on adaptive estimation of gait parameters and a PI controller-based systems) to automate a conventional treadmill, utilizing LRF sensors and the user’s walking speed for personalized system control. The results demonstrate high adaptability of the control models to gait variations, surpassing reported walking speeds in the literature using these algorithms. These findings are relevant for enhancing user interaction and experience in rehabilitation applications and serious games, which can enable improvements in rehabilitation and human-machine interaction. Our results show that the strategy employing adaptive filters exhibits superior responsiveness, enabling adaptation to different treadmill speeds with greater ease.

关键词： Legged locomotion Neurological diseases Human computer interaction Automation Games Control systems Sensor systems Biosensors engineering in medicine and biology Intelligent sensors

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An Ultra-high Concentration of Colloidal Quantum Dots for Efficient Light Generation in A Packaged LED

An Ultra-high Concentration of Colloidal Quantum Dots for Ef...

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2024 Conference on Lasers and Electro-Optics, CLEO 2024

作者： Huang, Tzu Chia Chang, Ching Huang, Chung-Ping Kuo, Hao-Chung Lin, Chien-Chung Graduate Institute of Photonics and Optoelectronics National Taiwan University Taipei City106 Taiwan Graduate Program of College of Photonics College of Photonics National Yang Ming Chiao Tung University Tainan City Taiwan Department of Photonics Institute of Electro-Optical Engineering National Yang Ming Chiao Tung University Hsinchu300 Taiwan

ISBN: (纸本)9781957171395

In this study, we propose various methods to increase the colloidal quantum dot (CQD) efficiency in a packaged LED. The amount of CQD is much higher than the regular concentration with some of them over 40% of weight percentage. The microcarriers were applied to hold the CQDs and an 63.5% improvement of color conversion efficiency can be observed. © Optica Publishing Group 2024 © 2024 The Author(s)

关键词： Nanocrystals

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Objective Sleep Quality Measurement based on Fuzzy Logic and Wearable Device 8

Objective Sleep Quality Measurement based on Fuzzy Logic and...

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8th International Conference on Computer Science and Computational Intelligence, ICCSCI 2023

作者： Wijaya, Jason A. Andersen, Pauw D. Surantha, Nico Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia Department of Electrical Electronic and Communication Engineering Tokyo City University Japan

Sleep is the natural state of relaxation for human being. Sleep quality is an essential yet frequently neglected aspect of sleep in general. Sleep quality is essential because it allows the body to restore itself and prepare for the next day. The standard method for evaluating sleep quality was subjective evaluation. Actigraphy devices, which can measure the sleep cycle, are now widely available. This study developed a method using Fuzzy Logic and an actigraphy device to measure and classify sleep quality. The fuzzy logic method was developed in several stages, which are determining the sleep quality measurement parameters, constructing the fuzzy set for each input variable, and developing the fuzzy rules. To evaluate the proposed fuzzy model, five individuals were invited to participate in the experiment and required to complete the PSQI subjective sleep questionnaire. The evaluation result shows that our proposed Fuzzy model achieves lower error compared to the existing method. © 2023 The Authors. Published by Elsevier B.V.

关键词： actigraphy artificial intelligences fuzzy logic sleep sleep quality

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Mobile Based Brand and Car Type Detection Using Convolutional Neural Network 8

Mobile Based Brand and Car Type Detection Using Convolutiona...

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8th International Conference on Computer Science and Computational Intelligence, ICCSCI 2023

作者： Ramadhan, Cahaya Saputra, Hasta Ragil Dewi, Ratna Sari Suharjito Computer Science Department BINUS Online Learning Bina Nusantara University Jakarta11480 Indonesia Industrial Engineering Department BINUS Graduate Program Bina Nusantara University Jakarta11480 Indonesia

Although the parking lot is equipped with CCTV surveillance, car theft incidents still occur occasionally. These thieves exploit a loophole in the system that prevents the identification of the car's brand and model upon entering and exiting the parking lot using the same ticket. Therefore, the aim of this research is to develop a system capable of detecting the brand and model of cars. The study utilizes convolutional neural network technology and specifically focuses on the EfficientNet, MobileNet, and MobileNetV2 architectures due to their low resource requirements. Training images for the study are sourced from an online marketplace for used cars, with each of the 20 car brand and model variations consisting of 100 photographs. creates a model after being processed. For the prototype, the approach is put into practice through a mobile application. This study compares EfficientNet, MobileNetV1, and MobileNetV2 as the end result. EfficientNet scored 74%, MobileNetV1 74%, and MobileNetV2 66% on the test of accuracy. The accuracy increases to 80% after the EfficientNet has been tuned. © 2023 The Authors. Published by Elsevier B.V.

关键词： Convolutional Neural Network EfficientNet MobileNet V2 MobileNetV1 Parking system Transfer Learning

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Single-Phase Transformerless UPS with Interleaved Boost Converters for Battery Discharging

Single-Phase Transformerless UPS with Interleaved Boost Conv...

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2023 IEEE Energy Conversion Congress and Exposition, ECCE 2023

作者： Pinto, Alan R. A. Bahia, Filipe A. C. Souza, Reuben P. R. Pinheiro, José R. Costa, Fabiano F. Federal University of Bahia Post-Graduate Program in Electrical Engineering - Ppgee Salvador Brazil Federal University of Bahia Dept. of Electrical and Computer Engineering - Deec Salvador Brazil Federal University of Campina Grande Dept. of Electrical Engineering - Dee Campina Grande Brazil

ISBN: (纸本)9798350316445

This paper proposes a reconfiguration for a single-phase, double conversion uninterruptible power supply (UPS). With the addition of two static switches to the original circuit, the UPS mitigates the ripple in the current, through battery discharge performed by two legs. Other than these switches, the circuit topology is preserved. The preliminary results show a satisfactory level of ripples for the inductor current and suitable power quality for the output voltage. © 2023 IEEE.

关键词： battery mode discharger interleaved boost normal mode

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