2022 2nd International Conference on Innovative Practices in Technology and Management (ICIPTM)最新文献

{"title":"An Exploratory analysis of Machine Learning adaptability in Big Data Analytics Environments: A Data Aggregation in the age of Big Data and the Internet of Things","authors":"Ratchana Rajendran, Priyanka Sharma, Nitin Kumar Saran, Samrat Ray, Joel Alanya-Beltran, Korakod Tongkachok","doi":"10.1109/iciptm54933.2022.9753921","DOIUrl":"https://doi.org/10.1109/iciptm54933.2022.9753921","url":null,"abstract":"The paper discusses a new concept combining the potentialities of Big Data processing as well as machine learning developed for security monitoring of mobile Internet of Things. The structure of the security monitoring system is considered as a most effective and useful element to create a new viewpoint of mobile IoT. This article focuses implementation of machine learning in online education. Thus mobile IoT has found successful application in few areas such as security monitoring in public places, transport management, medicine, smart houses, industrial production, electrical consumption, and robotics. All the mathematical foundations along with issues related to this have been considered in this study. In order to solve the classification task, several machine learning mechanisms have been mentioned in this paper. Large organizations are incorporating data-driven actions, and decision making in organizational function. The role of data aggregation is effective here achieving the business objectives. Vast amount of raw data can be processed linearly through data aggregation. This article describes the interaction of data aggregation through wireless networking assuming its effectiveness in online education. Data aggregation in machine learning is highlighted based on evidence based data. The purpose of this research article is to investigate the machine learning adaptability in big data analytics environments with the approach of IoT. In order to collect accurate data, the researcher has taken the help of a secondary data collection method. It has helped the researcher to find out the valid information about mobile IoT. In addition, qualitative methods have been adapted to malaise the collected data within a systematic way. Moreover, this study will help the readers to understand the value of mobile IoT helping in machine learning adaptability in big data analytics.","PeriodicalId":6810,"journal":{"name":"2022 2nd International Conference on Innovative Practices in Technology and Management (ICIPTM)","volume":"8 1","pages":"32-36"},"PeriodicalIF":0.0,"publicationDate":"2022-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85388904","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}

{"title":"A Decentralized Digital Voting System Based on Block chain Architecture","authors":"Shambhavi Bhardwaj, T. Poongodi, Ashutosh Dixit, S. Sharma","doi":"10.1109/iciptm54933.2022.9754194","DOIUrl":"https://doi.org/10.1109/iciptm54933.2022.9754194","url":null,"abstract":"Voting is the backbone of democracy and the fundamental right of every citizen. BlockChain based Election is like a boon for every nation through which the election can be conducted digitally, Unlike those old (paper based) and traditional (EVM) voting systems it makes the whole process of election safe, smooth and easy. In this era of Covid-19 this Block chain enabled election is the need of the hour, People can cast votes from their own space just with the help of a mobile phone or a computer, Security would get enhanced and threats like EVM hacking, Chaos at election booth would reduce drastically just by the implementation of this advanced voting system. Personal ID's and unique keys would be provided to each and every eligible voter which can't be tampered at any cost. It has two modules to make the entire project look consolidated and unified. First module is the Election Commission who could be liable for undertaking it, appending concerned everyone competing for the voting attached under blockchain. User end will be the resident's component where every eligible voter can choose a leader according to their separate Constituent sitting and the votes would get registered on the blockchain to make it tamper protected.","PeriodicalId":6810,"journal":{"name":"2022 2nd International Conference on Innovative Practices in Technology and Management (ICIPTM)","volume":"484 1","pages":"756-760"},"PeriodicalIF":0.0,"publicationDate":"2022-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85576207","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}

{"title":"Performance Evaluation of Apache Kafka – A Modern Platform for Real Time Data Streaming","authors":"Shubham Vyas, R. Tyagi, Charu Jain, Shashank Sahu","doi":"10.1109/iciptm54933.2022.9754154","DOIUrl":"https://doi.org/10.1109/iciptm54933.2022.9754154","url":null,"abstract":"Current generation businesses become more demanding on timely availability of data. Many real-time data streaming tools and technologies are capable to meet business expectations. Apache Kafka is one of the capable open-source distributed scalable technology that enables real-time data streaming with good throughput and latency. In traditional batch processing, data is getting processed in groups or batches but in streaming services, data records are handled separately and there is a flow of data processing that is continuous and real-time. Once Data is available at the source, Kafka can detect and stream it in real-time to the target application. After doing the literature survey it was observed that there are insufficient experiments have been done till now with a variety of volumes and with different values of the number of partitions and polling intervals. The purpose of this study is to elaborate on Apache Kafka implementation and evaluate its performance. This study will analyse key performance indicators for the streaming platform and will provide useful insights from it. These insights will help to design optimized applications in Apache Kafka. Based on gaps identified after the literature survey, multiple experiments have been conducted for the producer and consumer API (Application Programming interface). Configuration of Kafka with Apache Zookeeper helped to drive the results which are captured in tabular form for different values of polling intervals, volumes, and partitions. Data for all test runs have been analysed further to drive the conclusions as mentioned in the results section. This study provides valuable insights about the utilization of CPU (Central Processing Unit) and memory for Apache Kafka streaming on changing volumes, also elaborates the impacts on streaming performance when key configurations are getting changed.","PeriodicalId":6810,"journal":{"name":"2022 2nd International Conference on Innovative Practices in Technology and Management (ICIPTM)","volume":"46 1","pages":"465-470"},"PeriodicalIF":0.0,"publicationDate":"2022-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87697126","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}

{"title":"Fraud App Detection of Google Play Store Apps Using Decision Tree","authors":"K. Joshi, S. Kumar, Jyoti Rawat, Ansita Kumari, Aayush Gupta, Nikhil Sharma","doi":"10.1109/iciptm54933.2022.9754207","DOIUrl":"https://doi.org/10.1109/iciptm54933.2022.9754207","url":null,"abstract":"Along the rise in the various mobile applications which are used in daily life, it's more necessary than ever to stay on top of things to decide which are safe and which don't. It is impossible to pass judgment. Our system is based on four parameter that include ratings, reviews, in app purchases and Contains ad to predict. Our system compares three models Decision Tree classifier, Logistic Regression and Naïve Bayes. These models were further analyzed on four parameters of F1 score, Recall, Precision and Accuracy. A good F1 score should be greater than 0.7 and a recall score greater than 0.5 is considered to be good with higher precision and accuracy. On analysis we found Decision tree model as a good model with accuracy of 85%, F1score of 0.815, Recall value of 0.85 and precision of 0.87","PeriodicalId":6810,"journal":{"name":"2022 2nd International Conference on Innovative Practices in Technology and Management (ICIPTM)","volume":"93 1","pages":"243-246"},"PeriodicalIF":0.0,"publicationDate":"2022-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80462056","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}

{"title":"A novel Genetic Algorithm based Encryption Technique for Securing Data on Fog Network Using DNA Cryptography","authors":"D. Garg, K. Bhatia, Sonali Gupta","doi":"10.1109/iciptm54933.2022.9754031","DOIUrl":"https://doi.org/10.1109/iciptm54933.2022.9754031","url":null,"abstract":"The data generated by the intelligent systems is enormous, hence storing and analyzing it over the cloud environment is a wise decision. However, most state of the art applications demands minimal network latency in the network so that the response can reach the user within fraction of seconds. To meet this requirement, fog computing came into existence, where computing and analysis of data is carried out at the fog nodes instead at the cloud. In such a scenario, security is of utmost concern since each fog node and each IoT device generating the data is vulnerable to attack. Industries such as healthcare in particular, need to practice security measures because it contains Patient's Identifiable Information (PII). Encryption is one of the most effective techniques to provide security to data. Various encryption techniques are available but they all suffer from some limitations. In this paper, a new encryption technique is proposed, which is based on genetic science and works in two phases. In the first phase, the plaintext is converted to a complex cipher text by making use of a complicated key. The key is randomly selected from the DNA population and is made further complex by using logical operators. The cipher text obtained in the first phase is made more impenetrable in the second phase, by using genetic science principles of crossover and mutation. The simulation and results of the proposed technique indicate that it provides more security to the data as compared to the existing encryption techniques.","PeriodicalId":6810,"journal":{"name":"2022 2nd International Conference on Innovative Practices in Technology and Management (ICIPTM)","volume":"1 1","pages":"362-368"},"PeriodicalIF":0.0,"publicationDate":"2022-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82904141","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}

{"title":"ARIA The Bot","authors":"Shubham Singh, Dilpreet Kaur Arora, Iram Nabi Dar, Abdul Moghni, Satyam Kumar, Ajit Kumar","doi":"10.1109/iciptm54933.2022.9753961","DOIUrl":"https://doi.org/10.1109/iciptm54933.2022.9753961","url":null,"abstract":"Aria The bot is a windows personal voice assistant software which performed various task which is given by the user in the form of the voice command this concept is taken by the movie named “IRON MAN” character Jarvis which perform all the task assigned by Tony Stark. In this project we are going to make a windows voice assistant which is going perform all the task such as opening of file, perform searching on the web, getting result from the Wikipedia, reading pdf, opening of application and suggesting some jokes to you. By taking input by voice we are going to convert voice into text and according to dictionary which is present in the database we are going to perform task which is assign to the keyword, we are importing so much of library such as “os” for performing operating system tasks. “speech recognition” for to analyzing voice command, “pyttsx3” for converting voice command in to the text string, “Time” for fetching the current time and date, “web browser” for performing web based task on default web browser, we also add activation command to run the aria the bot which is used as state for this project.","PeriodicalId":6810,"journal":{"name":"2022 2nd International Conference on Innovative Practices in Technology and Management (ICIPTM)","volume":"114 1","pages":"167-174"},"PeriodicalIF":0.0,"publicationDate":"2022-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90091344","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}

{"title":"Novel lung cancer detection using ANN classifier in comparison with Decision Tree to measure the Accuracy, Sensitivity, Specificity and Precision","authors":"D. Preethi, K. Ganapathy","doi":"10.1109/iciptm54933.2022.9754184","DOIUrl":"https://doi.org/10.1109/iciptm54933.2022.9754184","url":null,"abstract":"The aim of this work is to predict the performance of the Artificial Neural Network algorithm for novel lung cancer detection. A total of 1339 samples are collected from two lung cancer datasets found in Kaggle. The G power for samples is calculated from clincalc which contains two different groups from which group 1 is taken as ($mathrm{n}1=670$) and for group 2 ($mathrm{n}2= 670$), alpha (0.05), power (80%) and enrollment ratio. The collected samples are divided into training dataset $(mathrm{n}=937 [75%])$ and test dataset $(mathrm{n}=402 [25%])$. Accuracy, sensitivity, specificity and precision score values are calculated for evaluating the performance of the Artificial Neural Network algorithm. By comparing these two algorithms Artificial Neural Network had given better accuracy, specificity, sensitivity and precision of 97.95%, 96.55%, 98.55% and 98.55% than Decision Tree of 61.22%, 40.90%, 67.10% and 71.68%. By using the SPSS tool, the Significance value is calculated as 0.02. From this proposed work it is observed that the Artificial Neural Network (ANN) had given better accuracy than the Decision Tree algorithm.","PeriodicalId":6810,"journal":{"name":"2022 2nd International Conference on Innovative Practices in Technology and Management (ICIPTM)","volume":"14 1","pages":"528-534"},"PeriodicalIF":0.0,"publicationDate":"2022-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90765881","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}

{"title":"SAFA-E (The E-Waste Management System)","authors":"Vishwash Chaturvedi, Ritika Babbar, Ishita Arora, Divakar Varshney, Hariharan U","doi":"10.1109/iciptm54933.2022.9753821","DOIUrl":"https://doi.org/10.1109/iciptm54933.2022.9753821","url":null,"abstract":"The term “e-waste” describes electronics/electrical items that have been discarded. Computers, servers, monitors, and other appliances like these are included. (E-waste) is composed of electronics or electrical items contains toxisubstances, such as lead and cadmium in circuit boards, The monitor contains lead oxide and cadmium, and the switch contains mercury, which is highly toxic. E-waste is the main cause of air, soil pollution caused due to improper disposal of e-waste which decomposed into soil and make it infertile and goes into the food chain. We propose a software system in this article publication paper - Safa-e (the E-waste management). Efforts are being made to address the wide scope of E-waste. We use an android application and website for these which take user data of e-waste in there house and give them the way to dispose and recycle it properly by taking help of us.","PeriodicalId":6810,"journal":{"name":"2022 2nd International Conference on Innovative Practices in Technology and Management (ICIPTM)","volume":"43 1","pages":"401-405"},"PeriodicalIF":0.0,"publicationDate":"2022-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91134911","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}

{"title":"Recursive CNN Model to Detect Anomaly Detection in X-Ray Security Image","authors":"R. S. Kumar, S. A, A. Balaji, G. Singh, Ashok Kumar, Manikandaprabu P","doi":"10.1109/iciptm54933.2022.9754033","DOIUrl":"https://doi.org/10.1109/iciptm54933.2022.9754033","url":null,"abstract":"To address the issue of contraband scale difference in the identification of X-ray pictures during security inspection, we upgrade the Faster RCNN network and propose a multi-channel region proposal network (MCRPN). Multi-layer feature extraction is achieved using the complementarily of distinct levels of convolution features in visual semantics, and the richer semantic components of VGG16 high-level layers and the shallower edge features of low-level layers are fused; To construct a multi-scale contraband detection network, the multi-scale candidate target regions are mapped to the corresponding feature maps; dilated convolutions are introduced into the multi-channel, and a multi-branch dilated convolutions module (DCM) is designed to increase the Receptive field and thus enhance features at different scales. On the self-created data set SIXray OD, the enhanced algorithm achieves an average detection accuracy of 84.69 percent and a test performance improvement of 6.28 percent over the original network. Additionally, the testing findings indicate that the enhanced algorithm's recognition accuracy has been increased to a considerable level.","PeriodicalId":6810,"journal":{"name":"2022 2nd International Conference on Innovative Practices in Technology and Management (ICIPTM)","volume":"1 1","pages":"742-747"},"PeriodicalIF":0.0,"publicationDate":"2022-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91317748","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}

{"title":"Cancer Prediction using Machine Learning","authors":"G. Sruthi, Chokkakula Likitha Ram, Malegam Koushik Sai, Bhanu Pratap Singh, Nikhil Majhotra, Neha Sharma","doi":"10.1109/iciptm54933.2022.9754059","DOIUrl":"https://doi.org/10.1109/iciptm54933.2022.9754059","url":null,"abstract":"Machine learning is increasingly being employed in cancer detection and diagnosis. Cancer prediction will become quite easy in the future and we can predict it without the need of going to the hospitals. As we can see many technologies are being used and tested in the medical field. So, by this we can say that this will make us easier in the future to detect cancer. We are testing which algorithm will give us good result among CART, SVM AND KNN. We are making a cancer prediction using machine learning, in which we are including three types of cancer they are breast cancer, lungs cancer and prostate cancer. In breast cancer, we are using SVM algorithm and for lung and prostate we are using Random forest algorithm. We are going to give different attributes for three cancer system where the user has to enter data to get result. For breast cancer we are considering attributes like clump thickness, uniform cell size, uniform cell shape etc. and the prediction result will be whether the cancer is malignant or benign. For lung cancer, we are considering smoking, yellow fingers, anxiety, peer pressure etc. In prostate cancer, we are considering are radius, texture, perimeter, area etc. and the result for both cancer is likelihood of being affected by the cancer.","PeriodicalId":6810,"journal":{"name":"2022 2nd International Conference on Innovative Practices in Technology and Management (ICIPTM)","volume":"7 1","pages":"217-221"},"PeriodicalIF":0.0,"publicationDate":"2022-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78849073","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}