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2021 IEEE 18th India Council International Conference (INDICON)最新文献

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Application of PID and Sliding Mode Control on Quadcopter for Autonomous Optimized Flight PID和滑模控制在四轴飞行器自主优化飞行中的应用
2021 IEEE 18th India Council International Conference (INDICON) Pub Date : 2021-12-19 DOI: 10.1109/INDICON52576.2021.9691680
M. Saad, Chinmay Rajhans, Surender Kannaiyan
{"title":"Application of PID and Sliding Mode Control on Quadcopter for Autonomous Optimized Flight","authors":"M. Saad, Chinmay Rajhans, Surender Kannaiyan","doi":"10.1109/INDICON52576.2021.9691680","DOIUrl":"https://doi.org/10.1109/INDICON52576.2021.9691680","url":null,"abstract":"Nowadays, robots are getting popular; they are being deployed everywhere, ranging from farms, homes, hospitals to industries, warehouses, and military operations. The field of autonomous robotics is becoming popular day by day. Advancement in electronics and mechanical designs can be considered the driving force for the advancement of autonomous robots. To develop an autonomous robot that can work with humans, the robot must perceive the surrounding and decide by itself the next action it should perform at each instant of time. In this paper, we present a mathematical model based autonomous quadcopter which can reach any given desired location from its initial position in an outdoor environment. Taking the desired position and orientation of the quadcopter in 3D space from the user, the system generates an optimal trajectory for the quadcopter to follow from initial position and orientation to final position and orientation. The entire pipeline with different methods of trajectory generations, the non-linear and coupled dynamic model of the quadcopter, linear and nonlinear controller development for autonomous flight is explained in this paper. Quadcopter encounters unknown air resistance and drag forces in the outdoor environment; we have discussed the problem of unknown disturbances occurring during the flight.","PeriodicalId":106004,"journal":{"name":"2021 IEEE 18th India Council International Conference (INDICON)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121788779","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
Design Of High Density Memory Cell Library For Low Voltage Operation In 65nm LSTP Technology 65nm LSTP低电压高密度存储单元库的设计
2021 IEEE 18th India Council International Conference (INDICON) Pub Date : 2021-12-19 DOI: 10.1109/INDICON52576.2021.9691642
Akshat Saxena, Swapnil Bansal, D. Sharma, Payal Kumari, Sandeep Kumar Singh, Priya Kapil, Belal Iqbal, Anuj Grover
{"title":"Design Of High Density Memory Cell Library For Low Voltage Operation In 65nm LSTP Technology","authors":"Akshat Saxena, Swapnil Bansal, D. Sharma, Payal Kumari, Sandeep Kumar Singh, Priya Kapil, Belal Iqbal, Anuj Grover","doi":"10.1109/INDICON52576.2021.9691642","DOIUrl":"https://doi.org/10.1109/INDICON52576.2021.9691642","url":null,"abstract":"In advanced high-performance digital SoCs, embedded SRAMs occupy nearly 70% of die area. Therefore, optimizing SRAMs for density, power consumption, and performance is very important. This paper presents the design of a high-density SRAM memory cell suite comprising of different configurations of IRIW 8T cell and a conventional 6T cell in 65nm low standby power (LSTP) technology node. The effect of using assist schemes to lower minimum operational voltage ($V_{min}$) of the SRAM cell is evaluated. We show that while at $V_{min}$=1.08V, a conventional 6T cell is 25% denser than a IRIW 8T cell, at $V_{min}$=0.81V, 8T cell with write assist is around 7% denser and has 33% lower leakage and better performance than a 6T cell.","PeriodicalId":106004,"journal":{"name":"2021 IEEE 18th India Council International Conference (INDICON)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124212311","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: 1
SCADA WebView: A State-of-the-Art Enterprise Transmission SCADA Engine SCADA WebView:一个最先进的企业传输SCADA引擎
2021 IEEE 18th India Council International Conference (INDICON) Pub Date : 2021-12-19 DOI: 10.1109/INDICON52576.2021.9691604
S. Saurav, P. Sudhakar, K. J. Mohan, R. Senthil Kumar, S. Bindhumadhava Bapu
{"title":"SCADA WebView: A State-of-the-Art Enterprise Transmission SCADA Engine","authors":"S. Saurav, P. Sudhakar, K. J. Mohan, R. Senthil Kumar, S. Bindhumadhava Bapu","doi":"10.1109/INDICON52576.2021.9691604","DOIUrl":"https://doi.org/10.1109/INDICON52576.2021.9691604","url":null,"abstract":"The Industrial Control System is experiencing a massive redesign because of the digital transition and the promises of Industry 4.0 and Industry 5.0. The convergence of Information Technology and Operational Technology has reinforced the Process Industry as a cyber-physical ecosystem. In today’s industrial automation environment, the Internet of Things and Industrial Internet of Things have become intrinsically tied. SCADA systems are crucial for monitoring and managing control parameters and notifying system failures to reduce downtime in the process industry. The SCADA operations, such as data collection, control operations, and visualization, have undergone substantial changes because of technological advancements. These transformations have motivated us to design and implement a novel SCADA engine using the latest technologies. The SCADA WebView is an innovative Enterprise Transmission SCADA engine developed under the COPS framework for the power sector. It can also be tailored to different process industries. This product has been extensively deployed across the Indian Power Grid. In the future, an AI-based cognitive decision-making system will be incorporated for optimal control.","PeriodicalId":106004,"journal":{"name":"2021 IEEE 18th India Council International Conference (INDICON)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125301235","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
Pitch Channel Tracking Control of an Autonomous Underwater Vehicle with Delayed Output 具有延迟输出的自主水下航行器俯仰通道跟踪控制
2021 IEEE 18th India Council International Conference (INDICON) Pub Date : 2021-12-19 DOI: 10.1109/INDICON52576.2021.9691723
Ravishankar P. Desai, N. Manjarekar
{"title":"Pitch Channel Tracking Control of an Autonomous Underwater Vehicle with Delayed Output","authors":"Ravishankar P. Desai, N. Manjarekar","doi":"10.1109/INDICON52576.2021.9691723","DOIUrl":"https://doi.org/10.1109/INDICON52576.2021.9691723","url":null,"abstract":"A linearized and reduced-order pitch channel model of an experimental autonomous underwater vehicle AUV-150 is considered. A sliding mode controller (SMC) is designed by considering the parametric variations in the state of the pitch channel. A delayed output estimator is designed by considering a delay in the measurement signal of pitch channel dynamics. The proposed SMC based delayed output estimator tracks the vehicle position under parametric variations and time-varying disturbances. The closed-loop stability is analysed. The observer error and tracking error asymptotic convergence is realized. Furthermore, controller performance is demonstrated through simulation results using MATLAB Simulink R2019b (9.7.0.1471314).","PeriodicalId":106004,"journal":{"name":"2021 IEEE 18th India Council International Conference (INDICON)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122669971","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: 2
Quality Assessment of Deep Learning Based Super Resolution Techniques on Thermal Images 基于深度学习的热图像超分辨率技术质量评估
2021 IEEE 18th India Council International Conference (INDICON) Pub Date : 2021-12-19 DOI: 10.1109/INDICON52576.2021.9691653
Shashwat Pandey, Darshika Sharma, B. Kumar, Himanshu Singh
{"title":"Quality Assessment of Deep Learning Based Super Resolution Techniques on Thermal Images","authors":"Shashwat Pandey, Darshika Sharma, B. Kumar, Himanshu Singh","doi":"10.1109/INDICON52576.2021.9691653","DOIUrl":"https://doi.org/10.1109/INDICON52576.2021.9691653","url":null,"abstract":"This paper presents a new quality assessment parameter for the evaluation of deep learning based super resolution techniques applied on thermal images. Three widely used deep learning-based models namely Super-Resolution Convolutional Neural Network (SRCNN), Thermal Enhancement Network (TEN) and Very Deep Super Resolution (VDSR) have been implemented for achieving super resolution of thermal images. Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index (SSIM) have been the most widely used conventional evaluation metrics for performance measurement of super resolution algorithms. Since these parameters require a reference image for the evaluation of the resultant images, we propose a new quality assessment parameter based on strength of the edges. Edge detection of the super resoluted image is performed utilizing Canny Edge Detection method and the entropy of the edge detection image is computed to provide a new parameter, Edge Detection Entropy Score (EDES). For the comparison and validation of the proposed image quality assessment techniques, Mean Opinion Score (MOS) of the target images have been obtained to be used as a benchmark. The obtained results indicate that the proposed EDES of the super resoluted images has high degree of correlation with the MOS as well as PSNR and SSIM.","PeriodicalId":106004,"journal":{"name":"2021 IEEE 18th India Council International Conference (INDICON)","volume":"1992 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128609839","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: 1
Garbage Detection and Classification using Faster-RCNN with Inception-V2 基于Inception-V2的Faster-RCNN垃圾检测与分类
2021 IEEE 18th India Council International Conference (INDICON) Pub Date : 2021-12-19 DOI: 10.1109/INDICON52576.2021.9691547
Asif Iqbal Middya, Debjani Chattopadhyay, Sarbani Roy
{"title":"Garbage Detection and Classification using Faster-RCNN with Inception-V2","authors":"Asif Iqbal Middya, Debjani Chattopadhyay, Sarbani Roy","doi":"10.1109/INDICON52576.2021.9691547","DOIUrl":"https://doi.org/10.1109/INDICON52576.2021.9691547","url":null,"abstract":"Street garbage monitoring is important for ensuring a clean and healthy civic environment. In this context, automatic detection and classification of waste/litter objects on the streets is necessary for proper garbage disposal. Specifically, such detection and classification of waste objects could be utilized in developing automated waste sorting applications. This paper attempts to build a Faster R-CNN based predictive model for automatic classification of ten different types of waste/litter objects. Two pre-trained networks namely Inception-V2 and ResNet-101 are investigated as backbone networks for feature extraction. The performance of the proposed model is also compared with two baselines namely RFCN (region-based fully convolutional network) and SSD (single shot multibox detector). It is observed that the Faster R-CNN configured with InceptionV2 achieves the highest mAP (mean average precision) of 92%.","PeriodicalId":106004,"journal":{"name":"2021 IEEE 18th India Council International Conference (INDICON)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130233706","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: 3
Machine Comprehension Comparison using Latest Advancements in Deep Learning 使用深度学习最新进展的机器理解比较
2021 IEEE 18th India Council International Conference (INDICON) Pub Date : 2021-12-19 DOI: 10.1109/INDICON52576.2021.9691737
Aryan Kumar Singh, Kapil Gyanchandani, Pramod Kumar Singh, J. Prakash
{"title":"Machine Comprehension Comparison using Latest Advancements in Deep Learning","authors":"Aryan Kumar Singh, Kapil Gyanchandani, Pramod Kumar Singh, J. Prakash","doi":"10.1109/INDICON52576.2021.9691737","DOIUrl":"https://doi.org/10.1109/INDICON52576.2021.9691737","url":null,"abstract":"Machine Comprehension or Question Answering (QA) is one of the most challenging natural language processing tasks due to the language’s dynamic nature and understanding the context of the question. In this paper, we propose a similarity attention layer with an aim to reduce human labor by automating tedious QA tasks using the attention mechanism in deep learning model; it uses attention scores and obtains good results even without pre-training. The QA using attention has immense scope in search engine optimization, page ranking, and chatbots. The traditional rule-based models and statistical methods underperform due to variations in the language. This dynamic nature of the language is well captured by the nonlinear learning of the neural networks. The conventional encoder-decoder architecture of neural networks for QA works well in the case of short sentences. However, the performance comes down for paragraphs and very long sentences as it is difficult for the network to memorize the super-long sentences. In contrast, the attention model helps the network focus on smaller attention areas in the complex input paragraph, part by part, until the entire text is processed. The results are very promising; our (single) model outperforms the existing ensemble method too.","PeriodicalId":106004,"journal":{"name":"2021 IEEE 18th India Council International Conference (INDICON)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126663914","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
Multi-object Foreground Extraction in Streaming Video using Low Rank Sparse Decomposition 基于低秩稀疏分解的流视频多目标前景提取
2021 IEEE 18th India Council International Conference (INDICON) Pub Date : 2021-12-19 DOI: 10.1109/INDICON52576.2021.9691672
Yogesh Sanku, Soumyo Bhattacharjee, Saumik Bhattacharya
{"title":"Multi-object Foreground Extraction in Streaming Video using Low Rank Sparse Decomposition","authors":"Yogesh Sanku, Soumyo Bhattacharjee, Saumik Bhattacharya","doi":"10.1109/INDICON52576.2021.9691672","DOIUrl":"https://doi.org/10.1109/INDICON52576.2021.9691672","url":null,"abstract":"Low rank sparse decomposition (LRSD) algorithm is a popular technique to split an input video in to a low rank form and a complementary sparse form. The decomposed low rank matrix signifies the background information while the sparse matrix captures the foreground information. The real power of the algorithm proposed is in the use of stationary camera systems, particularly in surveillance systems to extract moving objects efficiently for analyses. However, the existing LRSD algorithms are designed such that it can only work on the entire video cube, but not on streaming videos. This severely affects the usability of LRSD-based algorithms in real-world surveillance tasks. In this paper, we propose a novel LRSD decomposition algorithm that can deal with streaming video data. To the best of our knowledge, this is the first attempt to design an LRSD-based system to work on streaming videos with varying background conditions. Exhaustive experimental analyses have shown that the proposed framework can process the videos almost in real-time.","PeriodicalId":106004,"journal":{"name":"2021 IEEE 18th India Council International Conference (INDICON)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126867363","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: 1
Circularly Polarized Graphene Antenna for THz Applications 太赫兹应用的圆极化石墨烯天线
2021 IEEE 18th India Council International Conference (INDICON) Pub Date : 2021-12-19 DOI: 10.1109/INDICON52576.2021.9691640
Amit Sharma, Dinesh Kr. Vishwakarma
{"title":"Circularly Polarized Graphene Antenna for THz Applications","authors":"Amit Sharma, Dinesh Kr. Vishwakarma","doi":"10.1109/INDICON52576.2021.9691640","DOIUrl":"https://doi.org/10.1109/INDICON52576.2021.9691640","url":null,"abstract":"This manuscript reports a single substrate (silica) terahertz graphene plasmonic antenna having slotted circular patch for circular polarization, resonant at frequency of 1THz. The variation of graphene’s complex conductivity & propagation of transverse magnetic surface plasmon polariton are verified. To improve the performance of the proposed antenna a dual substrate structure is presented (by adding silicon below silica), and analyzed. By parametric variation appropriate height of substrate is calculated. Graphene’s tunability is verified using variation in its chemical potential $(mu_{c}$). Using proper values of $mu_{c}$ & relaxation time, the dual substrate, circularly polarized, graphene plasmonic THz antenna is designed, providing gain of 4. 318dBi, radiation efficiency of 85% with total efficiency of 62% & 3-dB axial ratio bandwidth of 100GHz.","PeriodicalId":106004,"journal":{"name":"2021 IEEE 18th India Council International Conference (INDICON)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121957685","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
Cognitive State Classification using Optimized Feature Selection Approach 基于优化特征选择方法的认知状态分类
2021 IEEE 18th India Council International Conference (INDICON) Pub Date : 2021-12-19 DOI: 10.1109/INDICON52576.2021.9691622
J. S. Ramakrishna
{"title":"Cognitive State Classification using Optimized Feature Selection Approach","authors":"J. S. Ramakrishna","doi":"10.1109/INDICON52576.2021.9691622","DOIUrl":"https://doi.org/10.1109/INDICON52576.2021.9691622","url":null,"abstract":"Functional Magnetic Resonance Imaging (fMRI) is the most widely used technique where it is possible to capture neural activity in human brain regions when subjected to different stimuli. However, due to the fMRI dataset’s high dimensional and sparse nature, the selection of appropriate features plays a crucial role in achieving the best classification accuracy. In this work, the stable features are selected from the fMRI dataset by combining Fast Fourier Transform (FFT) with Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). Then, the machine learning classifiers such as Support Vector Machine (SVM), Gaussian NB, and XGboost have been trained using these features. StarPlus fMRI dataset is used to examine the performance of the proposed feature selection framework. The experimental results reveal that the proposed feature selection algorithm resulted in optimum features with better classification accuracy. Comparison of the proposed scheme with state of the art models show that it performs better, and as a result, can be used for the pattern recognition of brain responses in multisubject fMRI data.","PeriodicalId":106004,"journal":{"name":"2021 IEEE 18th India Council International Conference (INDICON)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122252684","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
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