2022 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)最新文献

Enhancing Mental Illness Prediction using Tree based Machine Learning Approach 利用基于树的机器学习方法增强精神疾病预测

2022 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT) Pub Date : 2022-07-08 DOI: 10.1109/CONECCT55679.2022.9865689

Srinath K S, K. K, Gagan A G, Jyothi D K, P. D. Shenoy, V. K. R.

引用次数: 0

Real-Time Implementation and Analysis of Age of Information for Cognitive Radio Internet-of-Things 认知无线电物联网信息时代的实时实现与分析

2022 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT) Pub Date : 2022-07-08 DOI: 10.1109/CONECCT55679.2022.9865850

M. Ruchitha, S. Suzain, Rajalekshmi Kishore, Sanjeev Gurugopinath

引用次数: 0

Teaching Aerospace Software Quality at an Undergrad Level in the Pandemic – Experiences 航空航天软件质量教学在大流行的本科水平-经验

2022 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT) Pub Date : 2022-07-08 DOI: 10.1109/CONECCT55679.2022.9865779

Gauri V. Nair, S. Sai Girish, Vasudev Bm, Y. Jeppu

{"title":"Teaching Aerospace Software Quality at an Undergrad Level in the Pandemic – Experiences","authors":"Gauri V. Nair, S. Sai Girish, Vasudev Bm, Y. Jeppu","doi":"10.1109/CONECCT55679.2022.9865779","DOIUrl":"https://doi.org/10.1109/CONECCT55679.2022.9865779","url":null,"abstract":"This paper describes the experiences of teaching software quality as an undergraduate course. The subject was offered at National Institute of Technology Karnataka, Surathkal and the course covered the aerospace standards, safety, software requirements, design, reviews, and testing. Teaching the ARP 4761, ARP 4754, DO 178C and DO 331 to the students was enlightening. The course was completely conducted online on Teams and Moodle and this itself brings out many insights of teaching an industry level training as an undergraduate course. The course covered the basic of these standards and went through a safety analysis process using the System Theoretic Process Analysis. The problem statement was an onboard scanner. This mimicked a radar system but was called a scanner and had a set of functionalities that was simple enough to understand at an undergrad level. A detailed set of requirements was developed during the course. The process of requirement review was done on the requirements to merge the workflow and process defined in the standards with a practical example. The design model and code were developed for the problem statement. This also went through a review process. A formal method approach was used to test the modes of the scanner. Finally, a set of random tests were developed with a set of Orthogonal Array tests to test the system. The use of a problem helped the students to better interact and understand the complexity. The paper describes the curriculum and presents the work done by the students and their experiences during the course.","PeriodicalId":380005,"journal":{"name":"2022 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120947237","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

Deep Learning based Semantic Segmentation to Detect Ripened Strawberry Guava Fruits 基于深度学习语义分割的草莓番石榴果实成熟检测

2022 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT) Pub Date : 2022-07-08 DOI: 10.1109/CONECCT55679.2022.9865808

Nagaraju Y, Venkatesh, V. K. R.

{"title":"Deep Learning based Semantic Segmentation to Detect Ripened Strawberry Guava Fruits","authors":"Nagaraju Y, Venkatesh, V. K. R.","doi":"10.1109/CONECCT55679.2022.9865808","DOIUrl":"https://doi.org/10.1109/CONECCT55679.2022.9865808","url":null,"abstract":"Strawberry Guava is a fruit that is high in nutrients. Manually harvesting this fruit is a time-consuming and labor-intensive task. The characteristics of ripened strawberry fruit need automated harvesting, as matured strawberries are unfit for consumption within two days. Deep learning-based approaches have arisen as answers to many issues in recent years. They offer a lot of hope in tricky sectors like agriculture, where they can manage distortion in data more successfully than the typical computer vision approaches. This paper describes a strawberry guava identification algorithm based on semantic segmentation. The modified UNet model was trained to segment ripened strawberry guava fruit with the help of human-annotated images appropriately. To analyze our experimental results on the segmentation of ripened strawberry guava the Dice score measure was used. The validation and test dataset dice scores were 91.04% and 89.72%. The proposed methodology demonstrated that matured strawberry guava could be accurately detected using the modified UNet semantic segmentation model with a few input images.","PeriodicalId":380005,"journal":{"name":"2022 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124792586","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 & Validation of LQG Controller for IDSN32 Antenna Control Servo System IDSN32天线控制伺服系统LQG控制器的设计与验证

2022 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT) Pub Date : 2022-07-08 DOI: 10.1109/CONECCT55679.2022.9865734

N. Gupta

引用次数: 0

A versatile cubic-curved triangle mesh generator using subparametric transformation for FEM and image processing applications 基于子参数变换的通用三曲面三角形网格生成器，适用于有限元和图像处理

2022 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT) Pub Date : 2022-07-08 DOI: 10.1109/CONECCT55679.2022.9865775

T. V. Smitha, A. T, Asha S. Manek, Nataraj V

{"title":"A versatile cubic-curved triangle mesh generator using subparametric transformation for FEM and image processing applications","authors":"T. V. Smitha, A. T, Asha S. Manek, Nataraj V","doi":"10.1109/CONECCT55679.2022.9865775","DOIUrl":"https://doi.org/10.1109/CONECCT55679.2022.9865775","url":null,"abstract":"Image processing applications are often affected by noise during the segmentation of curved edges. In this article, a versatile curved triangle mesh development method is proposed for finite element-based image processing applications using MATLAB. This approach first creates meshes using an open-source finite element mesh generator. The proposed technique then generates and visualizes cubic-order curved triangular elements using subparametric transformation. The resulting meshes can be used to solve a variety of problems using finite element analysis for image and video processing applications. The results of the presented work include a cubic-order curved triangular mesh using subparametric transformation, node coordinates, connectivity matrix, and border nodes for finite element implementations. The results obtained by the proposed mesh generator are verified to obtain the most accurate numerical results for an eigenvalue problem by FEM. It can be utilized to improve numerical results very well for various finite element analysis applications. This technology can be utilized in areas such as medical simulation, image processing, material engineering, video processing, computational materials science, optical flow estimation, computational electromagnetics, and so on.","PeriodicalId":380005,"journal":{"name":"2022 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126606397","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

Automatic Building Footprint Extraction using Random Forest Algorithm from High Resolution Google Earth Images: A Feature-Based Approach 利用随机森林算法从高分辨率谷歌地球图像中自动提取建筑物足迹:一种基于特征的方法

2022 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT) Pub Date : 2022-07-08 DOI: 10.1109/CONECCT55679.2022.9865829

Rahisha Thottolil, U. Kumar

{"title":"Automatic Building Footprint Extraction using Random Forest Algorithm from High Resolution Google Earth Images: A Feature-Based Approach","authors":"Rahisha Thottolil, U. Kumar","doi":"10.1109/CONECCT55679.2022.9865829","DOIUrl":"https://doi.org/10.1109/CONECCT55679.2022.9865829","url":null,"abstract":"Mapping building structures in urban areas are fundamental for many urban studies. High-resolution satellite images and machine learning algorithms are often used for semi-automatic and automatic building detection. This study explores the utility of classification algorithm and high-resolution Google Earth images to detect buildings from a complex urban area having heterogeneous building structures of various shapes, sizes and construction materials. The proposed model converts the RGB images to grayscale followed by derivation of several filtered profiles to capture spatial and spectral feature vectors. Differential morphological profiles (DMPs) were constructed from consecutive morphological profiles to identify the structural information of probable buildings present in the image. Consequently, morphological building index was computed by averaging the DMPs that included mislabeled rooftops due to the presence of shadows. Global Otsu thresholding was used to reduce the number of mislabeled buildings. Finally, Random Forest algorithm was used for the classification of buildings based on the computed feature vectors. After noise removal, the quality of final building maps were assessed using evaluation metrics with reference to the ground truth which showed 4.4% improvement (from 81.2 to 85.62 %) over RF model while also revealing the detailed structural information of buildings.","PeriodicalId":380005,"journal":{"name":"2022 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115056245","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

Classification and Analysis of Dementia using Machine Learning Algorithms 使用机器学习算法对痴呆症进行分类和分析

2022 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT) Pub Date : 2022-07-08 DOI: 10.1109/CONECCT55679.2022.9865789

Aakarsh Arora, Mahendra Kumar Gourisaria, Rajdeep Chatterjee

{"title":"Classification and Analysis of Dementia using Machine Learning Algorithms","authors":"Aakarsh Arora, Mahendra Kumar Gourisaria, Rajdeep Chatterjee","doi":"10.1109/CONECCT55679.2022.9865789","DOIUrl":"https://doi.org/10.1109/CONECCT55679.2022.9865789","url":null,"abstract":"Dementia is associated to one of the early phases of fatal diseases such as Huntington's disease or, in more severe situations, death. It is a chronic and degenerative disease that affects millions of people throughout the world. Memory loss, difficulty in concentration, mood changes, and being confused are some of the symptoms of dementia. Early detection can prevent or postpone the course of dementia, which is the most common degenerative illness among the elderly. This paper's principal objective is to deploy a variety of machine learning algorithms like Logistic Regression, ExtraTreesClassifier, Random Forest, ExtremeBoost Classifier (XGBoost), Light Gradient Boost (LGBM), Decision Tree, Gradient Boosting, Gaussian Nave Bayes, and Classifier Support Vector Machine (SVM) on selected features from the dataset for multi-class classification of dementia patients as 'demented,' 'non-demented,' and 'converted'. The model evaluation was based on the F1-score, precision and accuracy and it was found that Gradient Boost performed well with an accuracy of 0.96.","PeriodicalId":380005,"journal":{"name":"2022 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115517222","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

Design and Implementation of FPGA based DDS-ADPLL for Resonant Frequency Tracking in Sensors 基于FPGA的DDS-ADPLL传感器谐振频率跟踪的设计与实现

2022 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT) Pub Date : 2022-07-08 DOI: 10.1109/CONECCT55679.2022.9865678

Mohd Ziauddin Jahangir, P. Chandra Sekhar, M. Sikander, J. V. Krishna

引用次数: 0

A Spurious free VHF front end SAW Filter for Satellite AIS 一种用于卫星AIS的无杂散VHF前端SAW滤波器

2022 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT) Pub Date : 2022-07-08 DOI: 10.1109/CONECCT55679.2022.9865693

Urvi Popat, Santanu Sinha

引用次数: 0