2022 International Conference for Advancement in Technology (ICONAT)最新文献_第2页

Identification of Malignant and Non-malignant Skin-lesions to Minimize Biopsy Load Using Two Templates-based Saturation Counts (HSV space): Experiments on Images from ISIC Archive 使用两种基于模板的饱和计数(HSV空间)识别恶性和非恶性皮肤病变以减少活检负荷:来自ISIC存档图像的实验

2022 International Conference for Advancement in Technology (ICONAT) Pub Date : 2022-01-21 DOI: 10.1109/ICONAT53423.2022.9726128

R. S. Prasad, V. Prasad

{"title":"Identification of Malignant and Non-malignant Skin-lesions to Minimize Biopsy Load Using Two Templates-based Saturation Counts (HSV space): Experiments on Images from ISIC Archive","authors":"R. S. Prasad, V. Prasad","doi":"10.1109/ICONAT53423.2022.9726128","DOIUrl":"https://doi.org/10.1109/ICONAT53423.2022.9726128","url":null,"abstract":"Malignant skin lesion is the deadliest skin disease resulting in huge loss of lives in Europe, Australia and USA. Early detection of malignant lesions can save lives. It is highly challenging to differentiate between malignant and non-malignant skin lesions. Many non-invasive techniques have been proposed but none has been accepted in clinical practice. Consequently, biopsy remains the only gold standard for diagnosis of malignant lesions. The objective of this study which uses two master templates (MT) of dermoscopic images for identification, an improvement over the recently reported subtraction technique using only a single MT, is to propose a non- invasive technique to minimize biopsy load to an appreciable extent. This study proposes selection of two MTs, one a known 100% malignant (M) lesion, and the other a known nearly 100% benign (B) lesion. For identification of test lesions either belonging to M or B category, each test image from the publicly available ISIC archive is subtracted from each of the two MTs and the resulting pixels (RGB) data on each subtraction are converted into HSV space. Scatter plot showing Saturation (S) data counts against pixels locations below and above a trial-and-error-based threshold of 0.35, decides the B or M category of test lesions according to a rule defined for identification. The proposed method introduces, for the first time ever, use of double MTs subtraction technique, which amounts to the filter action. The proposed subtraction method has sound mathematical and logical base. On a preliminary trial over fifty images from publicly available ISIC archive, an overall high accuracy of 94% was achieved which promises clinical applications to minimize biopsy load to a great extent. The proposed method is easy to implement by non-experts and takes only fifteen minutes on average for diagnosis.","PeriodicalId":377501,"journal":{"name":"2022 International Conference for Advancement in Technology (ICONAT)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129105809","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

Smart Bot for Handwritten Digit String Recognition 手写数字字符串识别的智能机器人

2022 International Conference for Advancement in Technology (ICONAT) Pub Date : 2022-01-21 DOI: 10.1109/ICONAT53423.2022.9726081

Mallikarjuna Rao Gundavarapu, Vivek Vardhan Reddy Yannam, Akash Velagala, Snehith Reddy Lankela, Saaketh Koundinya G, Sai Chandan Regonda

{"title":"Smart Bot for Handwritten Digit String Recognition","authors":"Mallikarjuna Rao Gundavarapu, Vivek Vardhan Reddy Yannam, Akash Velagala, Snehith Reddy Lankela, Saaketh Koundinya G, Sai Chandan Regonda","doi":"10.1109/ICONAT53423.2022.9726081","DOIUrl":"https://doi.org/10.1109/ICONAT53423.2022.9726081","url":null,"abstract":"Handwritten digit string recognition is more sophisticated than determining a single digit individually. The repeated recognition of single digits is applicable for recognizing a handwritten digit string. A similar approach is exercised in this paper. The proposed approach could be advantageous in banks to recognize the digits written on the cheque and processes the cheque. Further, the banks could send the audio message of the recognized handwritten digits to the cheque issuer for confirmation before cashing the cheque. The pro-posed model is developed in the python platform and is lightweight, robust, and cross-platform. In this approach, we have trained a neural network model with MNIST handwritten digits dataset and some samples of our own for recognizing the handwritten digits. The Convolution Neural network models are widely used in the present-day technologies for object recognition, image processing, segmentation, face recognizing and also many identifications related tasks. The CNN model used in the project determines the digit in the image provided. Finally, the system plays the [pre-]recorded audio and displays the output for the recognized digits in the given digit string.","PeriodicalId":377501,"journal":{"name":"2022 International Conference for Advancement in Technology (ICONAT)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123309139","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

Mobile Manipulation-Based Path Planner for Object Clean-up Operations 基于移动操作的对象清理操作路径规划器

2022 International Conference for Advancement in Technology (ICONAT) Pub Date : 2022-01-21 DOI: 10.1109/ICONAT53423.2022.9725838

Aditya Saraiya, S.K. Das, B. K. Rout, V. Kalaichelvi

引用次数: 0

A Novel Approach for Tracking the Spread of COVID-19 Disease and Discovering the Symptom Patterns of COVID-19 Patients Using Association Rule Mining 基于关联规则挖掘的新型COVID-19疾病传播追踪与患者症状模式发现方法

2022 International Conference for Advancement in Technology (ICONAT) Pub Date : 2022-01-21 DOI: 10.1109/ICONAT53423.2022.9725935

U. N, A. Arulanandham, Keerthy G, Pranav B Nag

{"title":"A Novel Approach for Tracking the Spread of COVID-19 Disease and Discovering the Symptom Patterns of COVID-19 Patients Using Association Rule Mining","authors":"U. N, A. Arulanandham, Keerthy G, Pranav B Nag","doi":"10.1109/ICONAT53423.2022.9725935","DOIUrl":"https://doi.org/10.1109/ICONAT53423.2022.9725935","url":null,"abstract":"Coronavirus disease also known as COVID-19 is an infectious disease which is caused by the SARS-CoV-2 virus. People who get infected by the virus will experience respiratory diseases and might recover easily, but few will become seriously ill and require medical attention. Top researchers from across the world are working on cures for it. A lot of research is being conducted on the spread of the disease and cures for it. Only developing cure for this virus would not be enough. With the current technology, advanced data mining techniques can be used to track and trace the virus which is quicker and faster solution which will change the course of the pandemic. The rate at which people are getting affected, tracking becomes vital. It is necessary to alert a person when they are near the infected person. With the help of GPS and Bluetooth technologies, the users are alerted. Data mining also known as knowledge discovery of data, is the process of analyzing huge chunks of data in different ways and converting it into useful information. This process plays a significant role in various fields with vast data. Healthcare industries generate and store large amounts of data like name of the patient, disease, diagnosis method, resources, this is where data mining techniques can be applied. So the data which can be obtained from COVID datasets can be used by healthcare industries to improve the tracking and spreading of COVID-19. We propose a method to identity patterns using the factors in the dataset which can be used to predict if a person having similar symptoms is affected by the virus or not. Clustering, association rule mining, classification and other various data science concepts are used to analyze the spread of COVID in India.","PeriodicalId":377501,"journal":{"name":"2022 International Conference for Advancement in Technology (ICONAT)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116335501","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

Implementation of a Person Following Robot in ROS-gazebo platform 人跟随机器人在ros -凉亭平台上的实现

2022 International Conference for Advancement in Technology (ICONAT) Pub Date : 2022-01-21 DOI: 10.1109/ICONAT53423.2022.9726010

R. K. Megalingam, Anandu R, Dasari HemaTejaAnirudhBabu, Ghali Sriram, Venkata Sai YashwanthAvvari

引用次数: 4

Students' Assessment for Quantitative Measurement of Course Learning Outcomes in Online Class of Power Plant Instrumentation 电厂仪器在线课堂学生对课程学习成果的量化评估

2022 International Conference for Advancement in Technology (ICONAT) Pub Date : 2022-01-21 DOI: 10.1109/ICONAT53423.2022.9725978

Pallavi Asthana, S. Tanwar, Anil Kumar, Sumita Mishra

{"title":"Students' Assessment for Quantitative Measurement of Course Learning Outcomes in Online Class of Power Plant Instrumentation","authors":"Pallavi Asthana, S. Tanwar, Anil Kumar, Sumita Mishra","doi":"10.1109/ICONAT53423.2022.9725978","DOIUrl":"https://doi.org/10.1109/ICONAT53423.2022.9725978","url":null,"abstract":"Due to COVID-19, engineering education has moved to an exclusive online mode, imposing various challenges for students and teachers. Many activities and methods have been introduced to improve teaching and increase students' engagement in online education. In this work, a trajectory-based pedagogy was used to enhance the associative learning and it was integrated with a trajectory based adaptive assessment to evaluate the students learning in the Power Plant Instrumentation Course of seventh semester. Evaluation was done in two modes; as a regular IRT mode, where students scored on their performance against individual question, and in trajectory-based assessment, students scored on the performance of previous question. For both assessments, scores were calculated as ‘Learning coefficients.’ Analysis of these learning coefficients demonstrated that in absence of innovative teaching pedagogy and assessment techniques, students may score good grades, but these are insufficient to measure the Course Learning outcomes. It is important to integrate new teaching pedagogies with complimenting assessments tools as a summative assessment to measure the Course Learning outcomes quantitatively during continuous evaluation conducted throughout the semester. This provides a robust method of assessment of students' knowledge in exclusive online education.","PeriodicalId":377501,"journal":{"name":"2022 International Conference for Advancement in Technology (ICONAT)","volume":"179 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124449991","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

Optimal Tuning Based Linear Active Disturbance Rejection Control Applied to a Quadcopter 基于最优整定的线性自抗扰控制在四轴飞行器中的应用

2022 International Conference for Advancement in Technology (ICONAT) Pub Date : 2022-01-21 DOI: 10.1109/ICONAT53423.2022.9725873

S. A. Suhail, M. A. Bazaz, Shoeb Hussain

引用次数: 0

Artificial Intelligence Based Solar Powered Electric Bi-hybrid Vehicle Compared with IC Engine Vehicles Using Graph Analytics 基于人工智能的太阳能电动双动力汽车与集成电路发动机汽车的图分析比较

2022 International Conference for Advancement in Technology (ICONAT) Pub Date : 2022-01-21 DOI: 10.1109/ICONAT53423.2022.9725853

K. C. Reddy, V. K, Nischal Dinesh, Sarthak Das, Prajwal, Ashu Anand

引用次数: 0

A Ku-Band Microstrip Patch Antenna With Suspended Ground for Wireless Applications 一种用于无线应用的ku波段悬地微带贴片天线

2022 International Conference for Advancement in Technology (ICONAT) Pub Date : 2022-01-21 DOI: 10.1109/ICONAT53423.2022.9725972

Aakarsh Mekap, Pranjal Wadhwa, D. Yadav, Madhuri Sahal

引用次数: 0

Adaptation of Machine Learning in Fog Computing: An Analytical Approach 机器学习在雾计算中的适应性:一种分析方法

2022 International Conference for Advancement in Technology (ICONAT) Pub Date : 2022-01-21 DOI: 10.1109/ICONAT53423.2022.9726114

Soumili Das, Payel Guria

{"title":"Adaptation of Machine Learning in Fog Computing: An Analytical Approach","authors":"Soumili Das, Payel Guria","doi":"10.1109/ICONAT53423.2022.9726114","DOIUrl":"https://doi.org/10.1109/ICONAT53423.2022.9726114","url":null,"abstract":"With the growth of the world, IoT and Cloud computing is becoming very highly sophisticated technological application widely used in various fields, like medical science, transportation, industry, monitoring environment, smart city, gaming, home automation, security, etc. Whenever we are talking about IoT and cloud computing there is an extension of this paradigm to the edge of the network namely Fog computing. Fog computing plays a crucial role in providing faster response time and improving network traffic by reducing latency time while executing any kind of task. The main purpose of fog computing is to reduce the burden of the cloud with low latency in a distributed manner. However, sometimes due to some issues, Fog computing has failed to provide adequate and accurate results that reduce effectiveness and quality in performance operations. For this reason, Machine learning (ML) can be used to increase the speed and transmission processes of data through Fog nodes. It helps in improving the architectural series of Fog nodes through real-time processing and communication processes that can be developed according to the user's expectations. This paper tried to present a comprehensive review of the role of Machine Learning in Fog computing by exploring the latest adaptation of ML techniques in some key aspects of Fog (Resource management, security, and Computational enhancement).","PeriodicalId":377501,"journal":{"name":"2022 International Conference for Advancement in Technology (ICONAT)","volume":"2009 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125588872","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