2021 International Conference on Computing Sciences (ICCS)最新文献_第3页

An Efficient IoT Based Electricity Theft Detecting Framework For Electricity Consumption 一种高效的基于物联网的电力盗窃检测框架

2021 International Conference on Computing Sciences (ICCS) Pub Date : 2021-12-01 DOI: 10.1109/ICCS54944.2021.00055

Kuldeep Sharma, A. Malik, I. Isha

{"title":"An Efficient IoT Based Electricity Theft Detecting Framework For Electricity Consumption","authors":"Kuldeep Sharma, A. Malik, I. Isha","doi":"10.1109/ICCS54944.2021.00055","DOIUrl":"https://doi.org/10.1109/ICCS54944.2021.00055","url":null,"abstract":"The framework is designed for the electricity power trading companies for detecting any electricity theft by unauthorized means. The framework is based on the (Internet of Things) IoT techniques. The Data for all consumers tagged to specific geographical area is required to be analyzed by the framework. The framework in first part is analyzing the data of the past consumption of the specific area, this area may be Distribution Transformer level or Feeder Level or any portion of the electricity supply which is suspected of such electricity theft. In the second part, the IoT devices are added to the metering units of the specific sources. From this source, all the electricity supplied to the specific region will be accumulated on real-time basis. Rest IoT devices will be added to different parts of the Electricity Supply Line. Based on the analysis of real-time data accumulated via these IoT devices through Global System for Mobile (GSM) technology at the server located at either Data Center or Cloud Storage as the case may be. The framework will pinpoint the specific area where the theft of electricity is affected. Another vigilance IoT device is used to capture the images of the scenes for monitoring the naked wire for prevention from the electricity theft. The Real-Time reporting of this devices is generating alert to the power distribution company representatives to take necessary steps to reduce the losses occurred due to energy theft. The advanced infrastructure, now a days, is more prone to electricity theft, the Advanced Metering Infrastructure (AMI), is fully machine to machine (M2M) functioning, if such system is compromised, the theft may occur, to stop such electricity theft, since last two decades, various researchers are proposing their expert algorithms to minimize the same. The current paper proposes the additions in the existing literature of electricity theft detection and prevention.","PeriodicalId":340594,"journal":{"name":"2021 International Conference on Computing Sciences (ICCS)","volume":"5 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123804926","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

Vehicle Detection And Accident Prediction In Sand/Dust Storms 沙尘暴中的车辆检测与事故预测

2021 International Conference on Computing Sciences (ICCS) Pub Date : 2021-12-01 DOI: 10.1109/ICCS54944.2021.00029

Aruni Singh, D. P. Kumar, Kelothu Shivaprasad, M. Mohit, Ankita Wadhawan

{"title":"Vehicle Detection And Accident Prediction In Sand/Dust Storms","authors":"Aruni Singh, D. P. Kumar, Kelothu Shivaprasad, M. Mohit, Ankita Wadhawan","doi":"10.1109/ICCS54944.2021.00029","DOIUrl":"https://doi.org/10.1109/ICCS54944.2021.00029","url":null,"abstract":"In this era of a smart and modern world that is designed by progressing technology, automated vehicles would become a precious part of it. The first thing that strikes in our minds talking about vehicles is traffic and accidents. Accidents could take place because of several reasons: dense traffic, unfavorable weather conditions, sudden braking, change in speed, etc, and the solution to this is machine learning, computer vision, and deep learning. Our focus is to improve the vision in areas of low visibility and predict the future by analyzing the present. Here we introduce a model which would help in dehazing and improving the visibility for a better driving experience in adverse weather especially targeting sandstorms and dust storms which would be quite common in the future because of the afforestation, the procedure is divided into two categories the dehazing and second is vehicle detection, situation analysis, and prediction. We have also incorporated things like estimating traffic density(dense/sparse), and the fire's in the worst situation using python, tensor flow, deep learning, and counting vehicles entering and departing from the frame.","PeriodicalId":340594,"journal":{"name":"2021 International Conference on Computing Sciences (ICCS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130297813","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: 18

Diagnosis of Pulmonary Tuberculosis through Intelligent Techniques: A Review 智能技术诊断肺结核的研究进展

2021 International Conference on Computing Sciences (ICCS) Pub Date : 2021-12-01 DOI: 10.1109/ICCS54944.2021.00045

Abdul Karim Siddiqui, V. Garg

引用次数: 0

A Study of Software Clone Detection Techniques for Better Software Maintenance and Reliability 提高软件维护和可靠性的软件克隆检测技术研究

2021 International Conference on Computing Sciences (ICCS) Pub Date : 2021-12-01 DOI: 10.1109/ICCS54944.2021.00056

Chavi Ralhan, Navneet Malik

{"title":"A Study of Software Clone Detection Techniques for Better Software Maintenance and Reliability","authors":"Chavi Ralhan, Navneet Malik","doi":"10.1109/ICCS54944.2021.00056","DOIUrl":"https://doi.org/10.1109/ICCS54944.2021.00056","url":null,"abstract":"Major problem in the development of software development is the presence of duplicate code that has a great impact on the overall affect the maintainability of the software. Clone detection technique applied with the core objective to identify the software codes which are identical. Various approached had been proposed in past by various researchers based which are based on text based, and token-based techniques. However, the proposed approaches were not considered very reliable methods due to the inability to find out syntactic differences between programs. Highly effective way to identify syntactic difference is through usage of abstract syntax tree. There are numerous ways to find similarity between two programs. In the proposed work, proposed software clone detection technique software code would be represented in the form of metrics affecting maintenance and reliability of opensource software. Afterwards, features extraction would be done in the form of flexible vectors of different forms to detect different types of clones. Proposed technique would be based upon adaptive prefix filtering on sets of vectors to detect similarity among the vectors. Similarity index detected among the vectors would be used to define given codes as code clones.","PeriodicalId":340594,"journal":{"name":"2021 International Conference on Computing Sciences (ICCS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130257295","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 Scheme for Data Deduplication Using Advance Machine Learning Architecture in Distributed Systems 分布式系统中基于高级机器学习架构的重复数据删除方案

2021 International Conference on Computing Sciences (ICCS) Pub Date : 2021-12-01 DOI: 10.1109/ICCS54944.2021.00019

S. Tarun, Ranbir Singh Batth, Sukhpreet Kaur

{"title":"A Scheme for Data Deduplication Using Advance Machine Learning Architecture in Distributed Systems","authors":"S. Tarun, Ranbir Singh Batth, Sukhpreet Kaur","doi":"10.1109/ICCS54944.2021.00019","DOIUrl":"https://doi.org/10.1109/ICCS54944.2021.00019","url":null,"abstract":"In a distributed architecture, data as a resource has its own value, but continuous integration of large amounts of data across several locations without cross-verification to preserve a single instance data pattern appears impossible. As a result, systems have encountered hurdles that have a direct influence on the efficiency and performance of distributed workforces. Users need high-quality data or information in order to continue working as improved data services in order to find future trends. However, duplicate data entries in storage repositories are considered a major flaw or stumbling block in the data analysis and query operations processes. As a result, businesses have invested significant resources in detecting duplicate data throughout the duplicate entry detection process. We've introduced a cutting-edge machine learning framework for detecting duplicate data on both current and new data entries. Textual data inputs or queries are imported into memory, preprocessed, and transformed to a vector space model using this technique. To arrange data in groups with equal capacity, a clustering K-means approach is used. To save time and money during the detection phase, similarity computations were done cluster-by-cluster rather than on a huge dataset. The suggested technique performs better than existing deduplication algorithms, with an optimal accuracy of 99.7%. If the result-test and gt-test outcomes are determined to be same during comparison, the accuracy performance parameter of the deduplication process is greater.","PeriodicalId":340594,"journal":{"name":"2021 International Conference on Computing Sciences (ICCS)","volume":"129 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116572561","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

A Comprehensive Study of Internet of Things and Digital Business on the Economic Growth and its Impact on Human Resource Management 物联网与数字商业对经济增长的综合研究及其对人力资源管理的影响

2021 International Conference on Computing Sciences (ICCS) Pub Date : 2021-12-01 DOI: 10.1109/ICCS54944.2021.00026

S. Prabu, A. Tripathi, Kamaljeet Kaur, M. Krishna, Ashim Bora, Mohammed Faez Hasan

{"title":"A Comprehensive Study of Internet of Things and Digital Business on the Economic Growth and its Impact on Human Resource Management","authors":"S. Prabu, A. Tripathi, Kamaljeet Kaur, M. Krishna, Ashim Bora, Mohammed Faez Hasan","doi":"10.1109/ICCS54944.2021.00026","DOIUrl":"https://doi.org/10.1109/ICCS54944.2021.00026","url":null,"abstract":"The research paper aims to examine the impact of digitalization and IoT technologies on the business world and the ways in which it also impacts the global economy. The paper examines that digital Human Resource Management can increase the productivity and the efficiency of both the HR professionals and the employees of the organisation. The findings of the research also reveals that through digitalisation the HR managers can build better relationships between the employee and the company, can think about the wellbeing of the employees better, and make them feel more valued and appreciated. It can also help in creating a competitive atmosphere in the workplace which can motivate the employees. The research further reveals that the active IoT technologies are increasing in the business world. The articles also analyses the advantages and disadvantages of implementing digitalisation and IoT in the workplace and there exists some requirements that need to be met for the successful implementation of the IoT technology. The research also estimates that in future companies can develop their business by adopting digitalisation. In the paper it is also mentioned that during the pandemic the global economy has decreased and to balance the condition it is important to implement digitalisation in the business world.","PeriodicalId":340594,"journal":{"name":"2021 International Conference on Computing Sciences (ICCS)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126159147","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: 5

Road Steering system with several metrics (RSSSM): A novel technique for a Smart Vehicular Network to control congestion 多指标道路转向系统(RSSSM):智能车辆网络控制拥塞的一种新技术

2021 International Conference on Computing Sciences (ICCS) Pub Date : 2021-12-01 DOI: 10.1109/ICCS54944.2021.00030

Gaganpreet Kaur Marwah, Anuj.S Jain

引用次数: 0

A Comparative Study of NLP based Semantic Web Standard model using SPARQL database 基于SPARQL数据库的NLP语义Web标准模型的比较研究

2021 International Conference on Computing Sciences (ICCS) Pub Date : 2021-12-01 DOI: 10.1109/ICCS54944.2021.00010

C. Raghavendra Rao, J. Babu, S. J. Pimo, Asmita Dixit, Sushma Jaiswal, Aatif Jamshed

引用次数: 1

Real time data evaluation with wearable devices: An Impact of Artifact Calibration Method on Emotion Recognition 基于可穿戴设备的实时数据评估:伪影校准方法对情绪识别的影响

2021 International Conference on Computing Sciences (ICCS) Pub Date : 2021-12-01 DOI: 10.1109/ICCS54944.2021.00038

F. Fayaz, Arun Malik

{"title":"Real time data evaluation with wearable devices: An Impact of Artifact Calibration Method on Emotion Recognition","authors":"F. Fayaz, Arun Malik","doi":"10.1109/ICCS54944.2021.00038","DOIUrl":"https://doi.org/10.1109/ICCS54944.2021.00038","url":null,"abstract":"Smartwatch technology is transforming the environment of transmission and monitoring for stakeholders and research participants who want to provide real-time data for evaluation. A range of sensors are available in smartwatches for gathering physical activity and location data. Here, combining all of these elements allows the collected data to be sent to a remote computer, allowing for real-time monitoring of physical and perhaps emotional development. Photoplethysmography is an easy and economical optical sensing technology that is commonly used to assess heartbeats. PPG is a non-invasive device that measures the volumetric fluctuations of blood flow using a light source and a sensor at the top layer of skin. Models concerning HRV (Heart Rate Variability) analysis are being studied in various domains, including human emotion recognition (HER). Smartwatches as sensor-based devices play an essential role as photoplethysmographic (PPG) data are frequently evaluated for this assessment. However, the nature of these waves (in terms of additional interruptions) may not always be flawless, even though they are susceptible to many factors, such as motion artifacts, light sources, stress distribution, ethnic background, or circumstances. Here techniques for antique rectification play a significant role &, as a response, impact the outcome. This research proposes a novel data distortions mitigation strategy for improving emotion detection classification efficiency using photoplethysmography waves throughout auditory invitation & a Support Vector Machine (SVM) model. Compared to previously undertaken data using a conventional toolset, i.e.,48.81, the presented scheme provides an improved categorization in trigger sensing, i.e., 68.75 percent. An alternative indicator, such as electroencephalographic activity, could be used in conjunction with PPG for further improvement.","PeriodicalId":340594,"journal":{"name":"2021 International Conference on Computing Sciences (ICCS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132479084","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

Empirical Analysis of Security Enabled Cloud Computing Strategy Using Artificial Intelligence 基于人工智能的安全云计算策略实证分析

2021 International Conference on Computing Sciences (ICCS) Pub Date : 2021-12-01 DOI: 10.1109/ICCS54944.2021.00024

Diego Antonio García Tadeo, S.Franklin John, Ankan Bhaumik, Rahul Neware, Nagendar Yamsani, Dhiraj Kapila

{"title":"Empirical Analysis of Security Enabled Cloud Computing Strategy Using Artificial Intelligence","authors":"Diego Antonio García Tadeo, S.Franklin John, Ankan Bhaumik, Rahul Neware, Nagendar Yamsani, Dhiraj Kapila","doi":"10.1109/ICCS54944.2021.00024","DOIUrl":"https://doi.org/10.1109/ICCS54944.2021.00024","url":null,"abstract":"Cloud Computing (CC) has emerged as an on-demand accessible tool in different practical applications such as digital industry, academics, manufacturing, health sector and others. In this paper different security threats faced by CC are discussed with suitable examples. Moreover, an artificial intelligence based security enabled CC is also discussed based on suitable empirical data. It is found that an artificial neural network (ANN) is an effective system to detect the level of risk factors associated with CC along with mitigating those risk issues with appropriate algorithms. Hence, it provides a desired level of protection against cyber attacks, internal confidential threats and external threat of data theft from a cloud computing system. Levenberg–Marquardt (LMBP) algorithms are also found as a significant tool to estimate the level of security performance around a cloud computing system. ANN is used to improve the performance level of data security across a cloud computing network and make it security enabled to ensure a protected data transmission to clients associated with the system.","PeriodicalId":340594,"journal":{"name":"2021 International Conference on Computing Sciences (ICCS)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114845422","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