2021 2nd Global Conference for Advancement in Technology (GCAT)最新文献_第10页

Impairment Impact on the Wireless Communication System 对无线通信系统的影响

2021 2nd Global Conference for Advancement in Technology (GCAT) Pub Date : 2021-10-01 DOI: 10.1109/GCAT52182.2021.9587620

Souparnika Jadhav, K. N. Nagesh

{"title":"Impairment Impact on the Wireless Communication System","authors":"Souparnika Jadhav, K. N. Nagesh","doi":"10.1109/GCAT52182.2021.9587620","DOIUrl":"https://doi.org/10.1109/GCAT52182.2021.9587620","url":null,"abstract":"In communication systems, distortion and noise are the main reason to decrease the reliability of the system, these distortions occurs because of the hardware deficiencies. In Wireless ad hoc network, connectivity and coverage area the two biggest issues. Therefore, this paper gives the practical analysis of the hardware deficiencies on hoping transmission, which amplifies and sends the better signal for the static and dynamic gain of the nodes and determine the localization of isolation nodes, improve connectivity and coverage area by reducing Nakagami-m fading. The outage possibility obtained in practical is by the signal to noise with the distortion noise, where these achieve the hardware deficiencies in the initial node and the relay node. In the same way, we consider the ergodic capability, in which hops are not dependent but it also assigns the ‘Nakagami-m’fading effect in the communication system. In this, the SNR and the signal to noise with distortion is more, which are continuous, where these are inversely proportional for the amount of hardware deficiencies. Theoretical transceivers will not satisfy the requirements in practically therefore in this paper, we provide some of the basic rules which is very helpful for the better communication in practical manner while focusing on ‘Nakagami-m’ fading effect in improving connectivity and coverage are in wireless ad-hoc networks.","PeriodicalId":436231,"journal":{"name":"2021 2nd Global Conference for Advancement in Technology (GCAT)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114896632","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

Comparative Study on Influence of Moon's Phases in Rainfall Prediction 月相对降雨预报影响的比较研究

2021 2nd Global Conference for Advancement in Technology (GCAT) Pub Date : 2021-10-01 DOI: 10.1109/GCAT52182.2021.9587582

D. Vishwakarma, Amandeep Singh, A. Kushwaha, Ayush K. Sharma

{"title":"Comparative Study on Influence of Moon's Phases in Rainfall Prediction","authors":"D. Vishwakarma, Amandeep Singh, A. Kushwaha, Ayush K. Sharma","doi":"10.1109/GCAT52182.2021.9587582","DOIUrl":"https://doi.org/10.1109/GCAT52182.2021.9587582","url":null,"abstract":"Rainfall prediction is a routine part of meteorological observations. An essential work of this department includes keeping daily record of rainfall characteristics, variations, intensity, etc. for a particular region. Although, in our general life, we may not pay much attention to our day-to-day weather conditions, for instance, sunrise, humidity, rainfall, air pressure and others, but in terms of climatology, such weather events or their fluctuation can leave a great impact on the habitat, if they remain consistent in long run. For this reason, advance methods are being implemented to develop accurate weather prediction tools. Also, several researches are done in the area of climatology to confirm a presumed connection between our Earth's weather and unconventional, new unusual phenomenon that is noticed within the climate influencing atmospheric range. Our research is planned to analyze such a phenomenon. In our study, we constructed a Machine Learning Based Rainfall prediction Model with Moon's phases included as a feature to observe the its importance level in rainfall prediction as well as compare its value with other influencing factors. We have chosen Machine Learning approach to achieve desired accuracy, speed and efficiency than any contemporary manual engineering processes done for data analysis. We have incorporated two predictive algorithms, namely, Logistic Regression and Random Forest to enhance our Model's predictive potentiality. Since, lowering of computational speed, making erroneous calculations, increasing system processing risk are some of the difficulties of Machine Learning implementation with large dataset, we have utilized Feature Selection Technique to overcome them.","PeriodicalId":436231,"journal":{"name":"2021 2nd Global Conference for Advancement in Technology (GCAT)","volume":"222 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114634335","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 Classification of Foreign Language Accent 外语口音自动分类

2021 2nd Global Conference for Advancement in Technology (GCAT) Pub Date : 2021-10-01 DOI: 10.1109/GCAT52182.2021.9587650

Radha Krishna Guntur, Kr Ramakrishnan, V. K. Mittal

引用次数: 0

A Reinforcement Learning based Eye-Gaze Behavior Tracking 基于强化学习的眼注视行为跟踪

2021 2nd Global Conference for Advancement in Technology (GCAT) Pub Date : 2021-10-01 DOI: 10.1109/GCAT52182.2021.9587480

R. Deepalakshmi, J. Amudha

{"title":"A Reinforcement Learning based Eye-Gaze Behavior Tracking","authors":"R. Deepalakshmi, J. Amudha","doi":"10.1109/GCAT52182.2021.9587480","DOIUrl":"https://doi.org/10.1109/GCAT52182.2021.9587480","url":null,"abstract":"In video established eye tracking methods, there are both mechanical and electrical based approaches existing. With the emerging spread of gaze tracking technology in the recent years and its significance in daily life routine, the data content acquired from the eye behavior tracing turn into important. Several research works were proposed to track the behavior of gaze while playing videos. Tracking an eye gaze while playing a dynamic videos consisting of numerous frames is a complex problem which needs excessive computational efforts. To handle such a complex task, this research proposes Reinforcement Learning (RL) based gaze behavior prediction model. These techniques are found to be invasive in nature and for visual attention behavior analysis applications, these invasive eye tracking system is not applicable. Hence the non-invasive eye tracking could be developed by determining the point of gaze based on observed image processing techniques. Some of the prevailing techniques include artificial intelligence, deep learning, and reinforcement learning and so on. Though quite a few research works has been admitted in this research area, there are several challenges existing so far. The suggested learning techniques are found to be computationally complex and time consuming. This current research work intends to propose a deep convolutional reinforcement learning (DC-RL) model for predicting the visual attention behavior of a person over dynamic scenes.","PeriodicalId":436231,"journal":{"name":"2021 2nd Global Conference for Advancement in Technology (GCAT)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124874073","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

Analysis of Volatile Organic Compounds in Exhaled Breath for Detection of Diabetes Mellitus 呼气中挥发性有机物分析对糖尿病的检测

2021 2nd Global Conference for Advancement in Technology (GCAT) Pub Date : 2021-10-01 DOI: 10.1109/GCAT52182.2021.9587790

Rajesh Sudi, Vibha Biligere, Tejaswini R, T. P, T. M

{"title":"Analysis of Volatile Organic Compounds in Exhaled Breath for Detection of Diabetes Mellitus","authors":"Rajesh Sudi, Vibha Biligere, Tejaswini R, T. P, T. M","doi":"10.1109/GCAT52182.2021.9587790","DOIUrl":"https://doi.org/10.1109/GCAT52182.2021.9587790","url":null,"abstract":"In recent years, lifestyle related illness has become more pronounced and demand for technology that enables easy and quick checking of diseases is increasing. Breath analysis is a very promising field of research work having great potential for diagnosis of diseases in non-invasive way for analyzing the volatile organic compounds (VOC’s) and its concentrations in exhaled human breath and also has potential for the early detection and progress monitoring of several diseases. As far as detection of Diabetes Mellitus is concerned, glucose level is calculated by invasive methods which is quite painful, time consuming and tormenting to some people, hence there has been a constant demand for the development of non-invasive, sensitive sensor system that offers fast and real-time electronic readout of blood glucose level. Responding to this we have prototyped a design of handy and non-invasive instrument which investigates the potential of breath signal analysis as a way for blood glucose monitoring with the help of an acetone gas sensor through which results can be actualized. Acetone is not only an effective biomarker of Diabetes Mellitus but also proved to be a rapid, patient compliant viable alternative to the conventional methods of blood glucose determination.","PeriodicalId":436231,"journal":{"name":"2021 2nd Global Conference for Advancement in Technology (GCAT)","volume":"335 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122135764","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

Performance of Network Intrusion Detection Systems in Cloud Computing: A Review 云计算环境下网络入侵检测系统性能研究综述

2021 2nd Global Conference for Advancement in Technology (GCAT) Pub Date : 2021-10-01 DOI: 10.1109/GCAT52182.2021.9587481

Sanjay Razdan, Himanshu Gupta, A. Seth

引用次数: 0

Anchored versus Anchorless Detector for Car Detection in Aerial Imagery 航空图像中汽车检测的锚定与无锚定检测器

2021 2nd Global Conference for Advancement in Technology (GCAT) Pub Date : 2021-10-01 DOI: 10.1109/GCAT52182.2021.9587621

K. Akshatha, Subhrajyoti Biswas, A. K. Karunakar, B. Satish Shenoy

引用次数: 0

Artificial Intelligence Based Predictive Threat Hunting In The Field of Cyber Security 基于人工智能的网络安全领域预测威胁搜索

2021 2nd Global Conference for Advancement in Technology (GCAT) Pub Date : 2021-10-01 DOI: 10.1109/GCAT52182.2021.9587507

Vaddi Sowmya Sree, Chaitna Sri Koganti, Srinivas K Kalyana, P. Anudeep

{"title":"Artificial Intelligence Based Predictive Threat Hunting In The Field of Cyber Security","authors":"Vaddi Sowmya Sree, Chaitna Sri Koganti, Srinivas K Kalyana, P. Anudeep","doi":"10.1109/GCAT52182.2021.9587507","DOIUrl":"https://doi.org/10.1109/GCAT52182.2021.9587507","url":null,"abstract":"Artificial intelligence (AI) is a broad field of computer science that focuses on designing smart machines capable of performing tasks typically requiring human intelligence. Despite the fact that security solutions are growing progressively modern and stable, cyberattacks are still evolving and are at their extreme. The main reason is that conventional methods of malware detection fail. Cyber attackers are actively developing new ways to prevent defence programmes from infecting malware networks and servers. Most anti-malware and antivirus applications currently use signature-based detection to identify attacks, which is unsuccessful in detecting new threats. This is where Artificial Intelligence is most handy. The standardised models for threatened hunting and performance quantification from the start of hazard hunting to the end still allow methodological rigour and completeness to be studied remain undefined. The organised practise of hazard hunts seeks to disclose the presence of TTP in the field of detection that has not already been detected. In this study, a realistic and comprehensive model is outlined to detect attackers in six stages: aim, scale, equipment, planning, execution and input. This study describes Threat Hunting in an ecosystem as the constructive, analyst-driven scanning mechanism for attackers TTP. The model has been checked for real-world data sets using a variety of threats. The effectiveness and practicality of this research have been shown with and without a blueprint through danger hunts. In addition, the article presents an analysis of the concept of threat hunting based on data from Ukrainian electricity grid attacks in an online environment to highlight the effects of this model on threat hunting in a simulated environment. The findings of this analysis include an effective and repetitive way to search for and quantify honesty, coverage and rigour.","PeriodicalId":436231,"journal":{"name":"2021 2nd Global Conference for Advancement in Technology (GCAT)","volume":"382 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131762319","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

Novel Process for Miniature Low Dropout Voltage Regulator Hybrid for Aerospace Applications 用于航空航天的微型低压差混合式稳压器新工艺

2021 2nd Global Conference for Advancement in Technology (GCAT) Pub Date : 2021-10-01 DOI: 10.1109/GCAT52182.2021.9587887

Anju Singh, S. Vaishnavi, Ajay Andhiwal, A. V. Nirmal

{"title":"Novel Process for Miniature Low Dropout Voltage Regulator Hybrid for Aerospace Applications","authors":"Anju Singh, S. Vaishnavi, Ajay Andhiwal, A. V. Nirmal","doi":"10.1109/GCAT52182.2021.9587887","DOIUrl":"https://doi.org/10.1109/GCAT52182.2021.9587887","url":null,"abstract":"Low Dropout Regulators (LDO) are extensively used in power conditioning and distribution systems that need a low noise & stable voltage supplies independent of load, input voltage variations, temperature, and time. This article details the development of thick film technology-based miniature LDO hybrid providing excellent electrical performance with required thermal management attained by implementing high thermal conductive GlidCop base metal package & Copper cored pin materials for applications in space power systems. Advance attachment materials used at various segments of hybrid i.e., silicon die component to substrate, substrate to package and heat sink interface material for isometric heat transfer, are also highlighted. Hybrid realization of LDO faced various challenges as traditional packaging approach results in instable performance with extremely unmanageable thermal deals. Fabrication challenges and issues faced while designing functional & Burn-in test jigs are also addressed. Glidcop package qualification and hybrid realization process qualification details have also been presented in this article.","PeriodicalId":436231,"journal":{"name":"2021 2nd Global Conference for Advancement in Technology (GCAT)","volume":"178 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120899833","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

Employee Burnout Prediction: A Supervised Learning Approach 员工倦怠预测:一种监督学习方法

2021 2nd Global Conference for Advancement in Technology (GCAT) Pub Date : 2021-10-01 DOI: 10.1109/GCAT52182.2021.9587830

Anupriya Jain, Muskan Agarwal, V. Shubha Rao

{"title":"Employee Burnout Prediction: A Supervised Learning Approach","authors":"Anupriya Jain, Muskan Agarwal, V. Shubha Rao","doi":"10.1109/GCAT52182.2021.9587830","DOIUrl":"https://doi.org/10.1109/GCAT52182.2021.9587830","url":null,"abstract":"Burnout is a mental state caused by excessive stress that results in emotional instability and a reduction in an individual’s performance capacity. Burnout is defined as, among other things, a fear of failure, a sense of powerlessness, and a sense of performance pressure. It has more to do with dealing with one’s conscience than with dealing with society. Tiredness, a lack of sleep, a lack of inspiration and productivity, concentration issues, frequent headaches, and other factors all contribute to burnout. Burnout isn’t just a problem for people in the business world; it can affect anyone, including students, stay-at-home moms, teachers, and others. Many people are affected by this, and they are unaware that they are “burned out,” therefore the symptoms go untreated, which can be problematic in the long term. It is possible to create a model that allows people to assess themselves using a curated set of criteria (factors) and estimate the rate of burnout. This paper gives an overview of various regression models offered in the existing literature for predicting employee burnout, and the best performing model is selected through a comparison based on different evaluation techniques.","PeriodicalId":436231,"journal":{"name":"2021 2nd Global Conference for Advancement in Technology (GCAT)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120952090","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