2023 11th International Symposium on Electronic Systems Devices and Computing (ESDC)最新文献

Design of Improved Content Addressable Memory Using QCA Technology 基于QCA技术的改进型内容可寻址存储器设计

2023 11th International Symposium on Electronic Systems Devices and Computing (ESDC) Pub Date : 2023-05-04 DOI: 10.1109/ESDC56251.2023.10149853

Sujatha Kotte, Ganapavarapu Kanaka Durga

引用次数: 0

Design and FPGA Implementation of an Efficient Architecture for Noise Removal in ECG Signals Using Lifting-Based Wavelet Denoising 基于提升小波去噪的心电信号高效去噪架构设计与FPGA实现

2023 11th International Symposium on Electronic Systems Devices and Computing (ESDC) Pub Date : 2023-05-04 DOI: 10.1109/ESDC56251.2023.10149865

Anusaka Gon, Atin Mukherjee

{"title":"Design and FPGA Implementation of an Efficient Architecture for Noise Removal in ECG Signals Using Lifting-Based Wavelet Denoising","authors":"Anusaka Gon, Atin Mukherjee","doi":"10.1109/ESDC56251.2023.10149865","DOIUrl":"https://doi.org/10.1109/ESDC56251.2023.10149865","url":null,"abstract":"Noise removal is the most crucial pre-processing step for present-generation biomedical wearable electrocardiogram (ECG) patches and devices to provide efficient detection and monitoring of cardiac arrhythmias. This paper proposes a hardware-efficient and multiplier-less FPGA-based ECG noise removal architecture based on lifting-based wavelet denoising that employs a universal threshold level-dependent function in combination with soft thresholding to produce a noise-free ECG signal. The paper also proposes a modified lifting-based discrete wavelet transform (DWT) algorithm that is multiplier-less and provides a one-step equation for the calculation of the forward output coefficients and the inverse output coefficients. Since a comparator circuit is a very complicated circuitry in VLSI implementation, an optimized median calculation and soft thresholding block with no compare operations for wavelet-based thresholding is proposed. The ECG data is collected from the MIT-BIH arrhythmia database and the ECG noises from the MIT-BIH noise stress database. The proposed denoising technique for the ECG signal is tested on MATLAB which achieves an average improvement in SNR of 7.4 dB and an MSE of 0.0206. The FPGA implementation is performed on the Nexys 4 DDR board, and the proposed wavelet-based denoising architecture results in lower hardware utilization and a relatively high operating frequency of 166 MHz when compared to existing ECG denoising architectures.","PeriodicalId":354855,"journal":{"name":"2023 11th International Symposium on Electronic Systems Devices and Computing (ESDC)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126623216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Substrate Noise Evaluation and Reduction of N-MOSFET Using Optimized Silicone-On-Insulator based on Seagull optimization algorithm 基于海鸥优化算法的N-MOSFET衬底噪声评价与降低

2023 11th International Symposium on Electronic Systems Devices and Computing (ESDC) Pub Date : 2023-05-04 DOI: 10.1109/ESDC56251.2023.10149882

Sanjay Sharma, R. P. Yadav, V. Janyani

{"title":"Substrate Noise Evaluation and Reduction of N-MOSFET Using Optimized Silicone-On-Insulator based on Seagull optimization algorithm","authors":"Sanjay Sharma, R. P. Yadav, V. Janyani","doi":"10.1109/ESDC56251.2023.10149882","DOIUrl":"https://doi.org/10.1109/ESDC56251.2023.10149882","url":null,"abstract":"Silicone-on-Insulator (SOI) chips contains numerous single-transistor islands that are dielectrically isolated on the silicon substrate. Leakage currents, radiation-induced photocurrents, latch-up effects and other parasitic effects caused by the huge substrate are initially protected from the thin active silicon layer by the vertical isolation. Correspondingly, the SOI eliminates the need for intricate trench or well creation techniques providing inter device separation. VLSI chips are more compact that results extreme simplification and circuit design. Although the SOI-MOSFET is developed to overcome these restrictions, additional problems are also generated such as kink effect in the I-V characteristics. To address the kink effect issue, the ideally selective buried oxide (SELBOX) MOSFET is developed. In this model, the fully depleted SOI-MOSFET is designed based on the n-MOSFET silicone substrate with optimally selected Buried Oxide (BOX) layer using the seagull optimization algorithm based on the capacitance of the material for reducing the substrate leakage current. Then, the gate oxide insulator, the bi-layer high k-dielectric materials such as Al203 and Si3N4 are used. For evaluating the designed model, the noise is manually injected into the MOSFET based on the noise models in TCAD. The drain current characteristic and transfer characteristics of the SOI-MOSFET are experimentally analysed. In this analysis, the noise affected MOSFET produces drain current of 1.4μA for 3v (Vds) and the noise reduced SOI-MOSFET produces 1.78μA for 3v (Vds). Thus, the designed fully depleted SOI-MOSFET model performs better by reducing the substrate noise.","PeriodicalId":354855,"journal":{"name":"2023 11th International Symposium on Electronic Systems Devices and Computing (ESDC)","volume":"179 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116395437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Detection of Multi-varieties of On-tree Mangoes using MangoYOLO5 利用MangoYOLO5检测多品种树上芒果

2023 11th International Symposium on Electronic Systems Devices and Computing (ESDC) Pub Date : 2023-05-04 DOI: 10.1109/ESDC56251.2023.10149849

Hari Chandana Pichhika, P. Subudhi

{"title":"Detection of Multi-varieties of On-tree Mangoes using MangoYOLO5","authors":"Hari Chandana Pichhika, P. Subudhi","doi":"10.1109/ESDC56251.2023.10149849","DOIUrl":"https://doi.org/10.1109/ESDC56251.2023.10149849","url":null,"abstract":"Automated harvesting and detection of fruits are crucial for agronomic applications like estimation and mapping of yield. Earlier, fruit detection methods were mostly dependent on hand-crafted features and were prone to changes in the actual orchard environment. However, recently deep learning-based methods especially one-stage object detection techniques like YOLO has achieved a higher detection accuracy to detect different fruits including mango in on-tree orchard images. In our previous work, we proposed a lightweight YOLOv5 model named \"MangoYOLO5\" for the detection of mangoes, and we have achieved an accuracy of 94.4% on one variety. Now, we have created a dataset of seven varieties of on-tree mangoes, with four varieties being publicly available, and the other three varieties from a local mango orchard using a UAV. We have tried detecting these seven varieties using the MangoYOLO5 model and achieved an average accuracy of 92%. It shows that the mango detection performance is 3.4% better than the YOLOv5s, taking into several characteristics like occlusion, distance, and lighting conditions. Additionally, compared to the original YOLOv5s, the achieved lighter model requires 55.55% less training time, which can significantly affect on real-time implementations.","PeriodicalId":354855,"journal":{"name":"2023 11th International Symposium on Electronic Systems Devices and Computing (ESDC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123910599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Ground Robots for Disaster Response: A Review 地面机器人灾害响应:综述

2023 11th International Symposium on Electronic Systems Devices and Computing (ESDC) Pub Date : 2023-05-04 DOI: 10.1109/ESDC56251.2023.10149862

R. Mathew, Pratik Jagtap, Kingshuk Mitra

{"title":"Ground Robots for Disaster Response: A Review","authors":"R. Mathew, Pratik Jagtap, Kingshuk Mitra","doi":"10.1109/ESDC56251.2023.10149862","DOIUrl":"https://doi.org/10.1109/ESDC56251.2023.10149862","url":null,"abstract":"Because of human activity, the number of disasters in the world is rising daily. and other environmental factors. A total of 327 disaster events were recorded in 2016 out of these 136 were man-made and 191 were natural disasters, the former accounted for $8 billion in losses and the latter$46 billion. As of July 2020, the number of natural disasters has gone up to 207 and 118 man-made disasters. These numbers are proof that there is a need to find better ways to combat disaster incidents, the limitations to the extent of rescue tasks that can be performed by humans calls for the use of robotic technologies in this field. While several robots such as The BigDog, Thermite 3.0 and Parosha Cheetah GOSAFER are being used presently, there is still some uncertainty about completely relying on them. Furthermore, the paper talks about issues faced while using these robots and how advancements in newer robots such as the Centauro Robot, RoboSimian, Octopus Robot and ATLAS Robot have helped overcome these problems, making use of robots and robotic technologies more effective and efficient and in turn integrating robots with disaster response tasks even better. Based on the mechanism and methods used for their functioning and operation, the mentioned robots have been discussed.","PeriodicalId":354855,"journal":{"name":"2023 11th International Symposium on Electronic Systems Devices and Computing (ESDC)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124863558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Underwater Object Detection Using Synthetic Data 基于合成数据的水下目标检测

2023 11th International Symposium on Electronic Systems Devices and Computing (ESDC) Pub Date : 2023-05-04 DOI: 10.1109/ESDC56251.2023.10149870

Nitish Reddy Nandyala, Rakesh Kumar Sanodiya

{"title":"Underwater Object Detection Using Synthetic Data","authors":"Nitish Reddy Nandyala, Rakesh Kumar Sanodiya","doi":"10.1109/ESDC56251.2023.10149870","DOIUrl":"https://doi.org/10.1109/ESDC56251.2023.10149870","url":null,"abstract":"The ability to detect life in challenging underwater environments holds the potential to preserve many aquatic species and coral reefs. Recent object detection research has witnessed a remarkable upsurge in natural images but not in Underwater, due to the imbalanced lighting, inadequate contrast, frequent occlusions, and the mimicry displayed by aquatic life forms. The assessment of object recognition models utilized in various contexts has augmented the need for annotated datasets. Due to the labor-intensive nature of generating these datasets, we have opted to undertake training using synthetic images as an alternative. In this study, we train the cutting-edge YOLO object detection system on a synthetic underwater dataset, with the aim of achieving category-agnostic object detection and then evaluated through practical assessments conducted on real underwater images. In addition, we provide benchmarking results for different YOLO versions in this work, assessing their performance on both real-world and synthetic datasets. Our investigation reveal that YOLOv5 shines in its ability to perform on synthetic data, whereas the latest YOLOv8, excels in real data domains, outpacing other two models tested. These findings have far reaching implications for the design and development of object detection in underwater environments.","PeriodicalId":354855,"journal":{"name":"2023 11th International Symposium on Electronic Systems Devices and Computing (ESDC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127927047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Investigation of RF-based networking for underwater wireless sensor networks using dynamic cluster head selection strategy 基于动态簇头选择策略的水下无线传感器网络射频组网研究

2023 11th International Symposium on Electronic Systems Devices and Computing (ESDC) Pub Date : 2023-05-04 DOI: 10.1109/ESDC56251.2023.10149879

Pavan Ganesh Pss, Nujeti Lavanya

{"title":"Investigation of RF-based networking for underwater wireless sensor networks using dynamic cluster head selection strategy","authors":"Pavan Ganesh Pss, Nujeti Lavanya","doi":"10.1109/ESDC56251.2023.10149879","DOIUrl":"https://doi.org/10.1109/ESDC56251.2023.10149879","url":null,"abstract":"Communication between two underwater wireless nodes or two underwater vehicles is possible with RF communication, provided the aspects of low transmission distance and high attenuation are taken care of in the communication system design. Notably, a cluster-based communication architecture is better suited than direct communication architecture when an RF signal is considered. This paper presents a cluster-based two-hop communication mechanism between two underwater nodes or two underwater vehicles. Particularly, a novel dynamic cluster head selection mechanism based on the unused energy and distance from cluster head to buoy has been proposed. This mechanism ensures uniform power consumption among all the underwater nodes or vehicles in a cluster. Moreover, it eliminates the necessity for a dedicated cluster head. The network performance using the proposed model has been analyzed in terms of the total network’s life and the time after which a node dies first in the network. The results have been compared with the existing communication mechanisms like communication via a fixed cluster head and direct communication.","PeriodicalId":354855,"journal":{"name":"2023 11th International Symposium on Electronic Systems Devices and Computing (ESDC)","volume":"400 5-6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114016266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A novel Optimization technique in 5G based IoVs using hybrid Fuzzy Weight-NSGA Scheme 基于混合模糊权重- nsga方案的5G车联网优化新技术

2023 11th International Symposium on Electronic Systems Devices and Computing (ESDC) Pub Date : 2023-05-04 DOI: 10.1109/ESDC56251.2023.10149880

Satyabrata Sahoo, S. Sahoo, R. C. Barik, M. R. Kabat

引用次数: 0

High Resolution DOA Estimation of Narrowband Signal for MUSIC, MVDR and Beamscan Algorithm 基于MUSIC、MVDR和波束扫描算法的窄带信号高分辨率DOA估计

2023 11th International Symposium on Electronic Systems Devices and Computing (ESDC) Pub Date : 2023-05-04 DOI: 10.1109/ESDC56251.2023.10149863

Meenal Job, Ram Suchit Yadav

{"title":"High Resolution DOA Estimation of Narrowband Signal for MUSIC, MVDR and Beamscan Algorithm","authors":"Meenal Job, Ram Suchit Yadav","doi":"10.1109/ESDC56251.2023.10149863","DOIUrl":"https://doi.org/10.1109/ESDC56251.2023.10149863","url":null,"abstract":"This paper presents the in-depth understanding for the direction of arrival (DOA) estimate technique. Here, we have considered three DOA algorithm, i.e., Beamscan, Minimum Variance Distortionless Response (MVDR), Multiple Signal Classification (MUSIC), which are used to estimate broadside angle with Uniform Linear Array (ULA) (10 isotropic antennas) and azimuth and elevation angles with Uniform Rectangular Array (URA) (16x16). Simulation is carried out by considering narrowband signal impinge on the array. Operating frequency of the system is 300MHz. DOA is estimated from the peaks of output signal. For different arriving signal, Beamscan technique forms a conventional beam and scan it over direction of interest to get the spatial spectrum. When signals come from directions that are closer than the beamwidth, then beam scanning is unable to resolve the signals. MVDR beam is examine over the specified region. It has smaller band-widths so has higher resolution. MVDR correctly estimates the DOAs of the signal. It is sensitive to position error so under such situation MUSIC provides accurate DOA estimation and better spatial resolution. Study is carried out in 2-D for the estimation of azimuth and elevation angle of URA. It uses the same algorithm as in 1-D. Simulation is carried out in Matrix laboratory (MATLAB) R2020 Version.","PeriodicalId":354855,"journal":{"name":"2023 11th International Symposium on Electronic Systems Devices and Computing (ESDC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128224975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Scalp EEG-based Classification of Disorder of Consciousness States using Machine Learning Techniques 基于头皮脑电图的意识状态障碍的机器学习分类

2023 11th International Symposium on Electronic Systems Devices and Computing (ESDC) Pub Date : 2023-05-04 DOI: 10.1109/ESDC56251.2023.10149867

Sreelakshmi Raveendran, Santhos A. Kumar, Raghavendra Kenchiah, Farsana M K, Ravindranath Choudary, S. Bansal, B. S, A. G. Ramakrishnan, S. R, Kala S

{"title":"Scalp EEG-based Classification of Disorder of Consciousness States using Machine Learning Techniques","authors":"Sreelakshmi Raveendran, Santhos A. Kumar, Raghavendra Kenchiah, Farsana M K, Ravindranath Choudary, S. Bansal, B. S, A. G. Ramakrishnan, S. R, Kala S","doi":"10.1109/ESDC56251.2023.10149867","DOIUrl":"https://doi.org/10.1109/ESDC56251.2023.10149867","url":null,"abstract":"Disorders of consciousness (DOC) described by impaired wakefulness and awareness, can be categorized into Coma, Unresponsive Wakefulness Syndrome (UWS), and Minimally Conscious State (MCS). Resting-state EEG-based differentiation of these classes acts as a helping hand or even more to the conventional behavioral assessment methods in the diagnosis and prognosis of DOC patients. In this paper, multi-class classification of DOC patients using different machine learning models was performed and the results were analyzed using features like sample entropy, permutation entropy, and absolute and relative power extracted from resting state EEG data. The one-way ANOVA method determined the discriminative ability of the features with a post hoc Least Significant Difference (LSD) test. All four features showed significant differences (p < 0.05) in delta, alpha, and beta bands between the groups. The feature significance was also measured across the different brain regions as well. The classification results showed that the Random Forest classifier best classified the group with an accuracy of 78% and a precision of 88%.","PeriodicalId":354855,"journal":{"name":"2023 11th International Symposium on Electronic Systems Devices and Computing (ESDC)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114161501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0