Pub Date : 2021-06-30DOI: 10.35940/ijitee.h9261.0610821
Namratha Sampath, P. Parimala
The set of restrictions defined for a system's electrical characteristics so that the entire electrical system can function in the intended manner and without losses is known as power quality. Power quality issues such as transients, harmonics, voltage swell, sag, flicker, fluctuations, and power factor difficulties are becoming more common as power electronic devices become more widely used. The usage of a Distribution Static Compensator (D-STATCOM) to mitigate power quality issues is discussed in this study. In this case, D-STATCOM functions as a shunt active power filter to reduce harmonics caused by non-linear loads. The simulation studies on a PV-based Cascaded-H-Bridge Multi-Level Inverter i.e Solar PV and Cascaded H Bridge MLI are integrated using Selective Harmonic Elimination method with D-STATCOM injected at the load side to improve power quality are presented in this project. The Solar PV system is mathematically modelled using Boost regulator and P&O MPPT technique and to the D-STATCOM the controller is designed utilizing Synchronous Reference Frame Theory (SRFT) out of many control strategies for reactive power compensation, harmonic mitigation, and power factor enhancement as it is more accurate. A 2nd order low pass filter is employed at the load side to reduce the harmonics to some extent, and both 5-level and 7-level models are evaluated. MATLAB/SIMULINK is used for simulation.
{"title":"D-STATCOM Control using SRFT Method for PQ Improvement in a PV System","authors":"Namratha Sampath, P. Parimala","doi":"10.35940/ijitee.h9261.0610821","DOIUrl":"https://doi.org/10.35940/ijitee.h9261.0610821","url":null,"abstract":"The set of restrictions defined for a system's electrical characteristics so that the entire electrical system can function in the intended manner and without losses is known as power quality. Power quality issues such as transients, harmonics, voltage swell, sag, flicker, fluctuations, and power factor difficulties are becoming more common as power electronic devices become more widely used. The usage of a Distribution Static Compensator (D-STATCOM) to mitigate power quality issues is discussed in this study. In this case, D-STATCOM functions as a shunt active power filter to reduce harmonics caused by non-linear loads. The simulation studies on a PV-based Cascaded-H-Bridge Multi-Level Inverter i.e Solar PV and Cascaded H Bridge MLI are integrated using Selective Harmonic Elimination method with D-STATCOM injected at the load side to improve power quality are presented in this project. The Solar PV system is mathematically modelled using Boost regulator and P&O MPPT technique and to the D-STATCOM the controller is designed utilizing Synchronous Reference Frame Theory (SRFT) out of many control strategies for reactive power compensation, harmonic mitigation, and power factor enhancement as it is more accurate. A 2nd order low pass filter is employed at the load side to reduce the harmonics to some extent, and both 5-level and 7-level models are evaluated. MATLAB/SIMULINK is used for simulation.","PeriodicalId":23601,"journal":{"name":"VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88657659","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}
Pub Date : 2021-06-30DOI: 10.35940/ijitee.h9251.0610821
Shaik Gousia Begum, S. S. Nawaz, G. Anjaneyulu
This paper presents the design of a Fuzzy logic controller for a DC-DC step-down converter. Buck converters are step-down regulated converters which convert the DC voltage into a lower level standardized DC voltage. The buck converters are used in solar chargers, battery chargers, quadcopters, industrial and traction motor controllers in automobile industries etc. The major drawback in buck converter is that when input voltage and load change, the output voltage also changes which reduces the overall efficiency of the Buck converter. So here we are using a fuzzy logic controller which responds quickly for perturbations, compared to a linear controllers like P, PI, PID controllers. The Fuzzy logic controllers have become popular in designing control application like washing machine, transmission control, because of their simplicity, low cost and adaptability to complex systems without mathematical modeling So we are implementing a fuzzy logic controller for buck converter which maintains fixed output voltage even when there are fluctuations in supply voltage and load. The fuzzy logic controller for the DC-DC Buck converter is simulated using MATLAB/SIMULINK. The proposed approach is implemented on DC-DC step down converter for an input of 230V and we get the desired output for variations in load or references. This proposed system increases the overall efficiency of the buck converter.
{"title":"Implementation of Fuzzy Logic Controller for DC–DC step Down Converter","authors":"Shaik Gousia Begum, S. S. Nawaz, G. Anjaneyulu","doi":"10.35940/ijitee.h9251.0610821","DOIUrl":"https://doi.org/10.35940/ijitee.h9251.0610821","url":null,"abstract":"This paper presents the design of a Fuzzy logic controller for a DC-DC step-down converter. Buck converters are step-down regulated converters which convert the DC voltage into a lower level standardized DC voltage. The buck converters are used in solar chargers, battery chargers, quadcopters, industrial and traction motor controllers in automobile industries etc. The major drawback in buck converter is that when input voltage and load change, the output voltage also changes which reduces the overall efficiency of the Buck converter. So here we are using a fuzzy logic controller which responds quickly for perturbations, compared to a linear controllers like P, PI, PID controllers. The Fuzzy logic controllers have become popular in designing control application like washing machine, transmission control, because of their simplicity, low cost and adaptability to complex systems without mathematical modeling So we are implementing a fuzzy logic controller for buck converter which maintains fixed output voltage even when there are fluctuations in supply voltage and load. The fuzzy logic controller for the DC-DC Buck converter is simulated using MATLAB/SIMULINK. The proposed approach is implemented on DC-DC step down converter for an input of 230V and we get the desired output for variations in load or references. This proposed system increases the overall efficiency of the buck converter.","PeriodicalId":23601,"journal":{"name":"VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75606891","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}
Pub Date : 2021-06-30DOI: 10.35940/ijitee.h9204.0610821
Snehal Patil, Yash Shah, Payal Narkhede, A. Thakare, Rahul Pitale
Human communication plays a vital role; without communicating, day-to-day tasks seem difficult to complete. And the world has an almost 5% population that struggles with hearing or speaking disability, which contributes to 430 million people worldwide, and this will grow up to 900million just in the next 25 to 30 years. With the increasing noise pollution, hearing capacity degrades, leading to various hearing problems. The WHO statistics show that 32million kids are acoustically impaired. With disabilities, there are multiple issues these people face, such as lack of learning facilities, job opportunities, communication platforms, etc. These people need a cooperative environment to express, learn at their pace and level of understanding. This paper focuses on developing an application that bridges the gap between these acoustically disabled people and people unknown to their way of communication. The proposed research is an edge device application provides features like a gesture to text, speech to text, e-learning platform, and Alert mechanism. This paper majorly focuses on developing a friendly all in one platform for mute and deaf community for communication, learning and emergency alerts. The research was conducted with two approaches the traditional CNN and Tensorflow lite Efficient Net model to train the ASL (American Sign Language) dataset for the communication platform, where we obtained accuracy of 98.91% and 98.82% respectively. To overcome the computational barriers of traditional CNN approach, Tensorflow lite Efficient Net model was brought into the picture. The proposed methodology would help build a platform for the deaf and mute community to express themselves better and gain wider exposure to the world.
人际沟通起着至关重要的作用;没有沟通，日常任务似乎很难完成。世界上有近5%的人口患有听力或语言障碍，全世界有4.3亿人患有听力或语言障碍，在未来25到30年内，这一数字将增长到9亿。随着噪声污染的日益严重，听觉能力下降，导致各种听力问题。世界卫生组织的统计数据显示，3200万儿童有听觉障碍。残疾人士面临着许多问题，比如缺乏学习设施、工作机会、交流平台等。这些人需要一个合作的环境来表达，以他们的速度和理解水平学习。本文的重点是开发一个应用程序，以弥合这些听障人士和不知道他们的沟通方式的人之间的差距。提出的研究是一个边缘设备应用程序，提供手势到文本、语音到文本、电子学习平台和警报机制等功能。本文主要致力于为聋哑人社区开发一个友好的all in one平台，用于交流、学习和紧急报警。本研究采用传统CNN和Tensorflow lite Efficient Net两种方法对交流平台的ASL (American Sign Language)数据集进行训练，准确率分别达到98.91%和98.82%。为了克服传统CNN方法的计算障碍，引入了Tensorflow lite Efficient Net模型。拟议的方法将有助于为聋哑人社区建立一个更好地表达自己和更广泛地接触世界的平台。
{"title":"Gesture Detection using Tensor flow lite Efficient Net Model for Communication and\u0000E-learning Module for Mute and Deaf","authors":"Snehal Patil, Yash Shah, Payal Narkhede, A. Thakare, Rahul Pitale","doi":"10.35940/ijitee.h9204.0610821","DOIUrl":"https://doi.org/10.35940/ijitee.h9204.0610821","url":null,"abstract":"Human communication plays a vital role; without communicating, day-to-day tasks seem difficult to complete. And the world has an almost 5% population that struggles with hearing or speaking disability, which contributes to 430 million people worldwide, and this will grow up to 900million just in the next 25 to 30 years. With the increasing noise pollution, hearing capacity degrades, leading to various hearing problems. The WHO statistics show that 32million kids are acoustically impaired. With disabilities, there are multiple issues these people face, such as lack of learning facilities, job opportunities, communication platforms, etc. These people need a cooperative environment to express, learn at their pace and level of understanding. This paper focuses on developing an application that bridges the gap between these acoustically disabled people and people unknown to their way of communication. The proposed research is an edge device application provides features like a gesture to text, speech to text, e-learning platform, and Alert mechanism. This paper majorly focuses on developing a friendly all in one platform for mute and deaf community for communication, learning and emergency alerts. The research was conducted with two approaches the traditional CNN and Tensorflow lite Efficient Net model to train the ASL (American Sign Language) dataset for the communication platform, where we obtained accuracy of 98.91% and 98.82% respectively. To overcome the computational barriers of traditional CNN approach, Tensorflow lite Efficient Net model was brought into the picture. The proposed methodology would help build a platform for the deaf and mute community to express themselves better and gain wider exposure to the world.","PeriodicalId":23601,"journal":{"name":"VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE","volume":"181 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89815317","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}
Pub Date : 2021-06-30DOI: 10.35940/ijeat.d2436.0610521
R. Subalakshmi, G. Baskar
Danger characterization of tumors from radiology image container to be much precise and quicker with computer aided diagnosis (CAD) implements. Tumor portrayal via such devices can likewise empower non-intrusive prognosis, and foster personalized, and treatment arranging as a piece of accuracy medication. In this study , in cooperation machine learning algorithm strategies to better tumor characterization. Our methodological analysis depends on directed erudition for which we exhibit critical increases with machine learning algorithm, particularly by exploitation a 3D Convolutional Neural Network and Transfer Learning. Disturbed by the radiologists' understandings of the outputs, we at that point tell the best way to fuse task subordinate feature representations into a CAD framework by means of a diagram regularized inadequate MultiTask Learning (MTL) system with the help of feature fusion.
{"title":"Lung and Tumor Characterization in the Machine Learning Era","authors":"R. Subalakshmi, G. Baskar","doi":"10.35940/ijeat.d2436.0610521","DOIUrl":"https://doi.org/10.35940/ijeat.d2436.0610521","url":null,"abstract":"Danger characterization of tumors from radiology\u0000image container to be much precise and quicker with computer\u0000aided diagnosis (CAD) implements. Tumor portrayal via such\u0000devices can likewise empower non-intrusive prognosis, and foster\u0000personalized, and treatment arranging as a piece of accuracy\u0000medication. In this study , in cooperation machine learning\u0000algorithm strategies to better tumor characterization. Our\u0000methodological analysis depends on directed erudition for which we\u0000exhibit critical increases with machine learning algorithm,\u0000particularly by exploitation a 3D Convolutional Neural Network\u0000and Transfer Learning. Disturbed by the radiologists'\u0000understandings of the outputs, we at that point tell the best way to\u0000fuse task subordinate feature representations into a CAD\u0000framework by means of a diagram regularized inadequate MultiTask Learning (MTL) system with the help of feature fusion.","PeriodicalId":23601,"journal":{"name":"VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE","volume":"23 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73439415","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}
Security on the Internet of Things (IoT) accentuates safeguarding the Internet-empowered devices that connect to remote networks. IoT Safety endeavors to shield IoT gadgets and frameworks against cybercrime, and it is considered a vital security element linked to the IoT. Conversely, banking applications are dynamically being regulated for their inability to give an adequate level of client assistance and insure themselves against and react to digital assaults. One of the primary components for this is the weakness of Fintech systems and organizations to breaking down. Therefore, wireless organizations covering these IoT items are incredibly unprotected. IoT is a lightweight framework, and it is ideal when utilizing lightweight and energy-effective cryptography for assurance. Deep learning is a proficient technique to examine dangers and react to assaults and security occurrences. So this business locales both security and energy productivity in IoT utilizing two novel strategies helped out through the deep learning. This work adds to the most inventive method of saving energy in IoT gadgets through diminishing the utilization of energy-costly '1' values in the interface of Dynamic RAM. This should be possible by utilizing Base + XOR encoding of information during information transmission. Utilizing Conditional Generative Adversarial Network (CGAN) based deep learning strategy, the Base + XOR encoding technique and C.X.E. are prepared or trained quite well in the banking/financial application. The information age in CGAN is done dependent on rules delivered utilizing the generator model. This work is ended up being burning-through less energy, less information transmission time, and gives greater security when thought about the existing frameworks.
{"title":"A Review on Secure Data Transmission for Banking Application using Machine Learning","authors":"Gurram Bhaskar, Motati Dinesh Reddy, Thatikonda , Mounika","doi":"10.35940/ijeat.e2746.0610521","DOIUrl":"https://doi.org/10.35940/ijeat.e2746.0610521","url":null,"abstract":"Security on the Internet of Things (IoT) accentuates\u0000safeguarding the Internet-empowered devices that connect to\u0000remote networks. IoT Safety endeavors to shield IoT gadgets and\u0000frameworks against cybercrime, and it is considered a vital\u0000security element linked to the IoT. Conversely, banking\u0000applications are dynamically being regulated for their inability to\u0000give an adequate level of client assistance and insure themselves\u0000against and react to digital assaults. One of the primary\u0000components for this is the weakness of Fintech systems and\u0000organizations to breaking down. Therefore, wireless organizations\u0000covering these IoT items are incredibly unprotected. IoT is a\u0000lightweight framework, and it is ideal when utilizing lightweight\u0000and energy-effective cryptography for assurance. Deep learning is\u0000a proficient technique to examine dangers and react to assaults\u0000and security occurrences. So this business locales both security\u0000and energy productivity in IoT utilizing two novel strategies\u0000helped out through the deep learning. This work adds to the most\u0000inventive method of saving energy in IoT gadgets through\u0000diminishing the utilization of energy-costly '1' values in the\u0000interface of Dynamic RAM. This should be possible by utilizing\u0000Base + XOR encoding of information during information\u0000transmission. Utilizing Conditional Generative Adversarial\u0000Network (CGAN) based deep learning strategy, the Base + XOR\u0000encoding technique and C.X.E. are prepared or trained quite well\u0000in the banking/financial application. The information age in\u0000CGAN is done dependent on rules delivered utilizing the generator\u0000model. This work is ended up being burning-through less energy,\u0000less information transmission time, and gives greater security\u0000when thought about the existing frameworks.","PeriodicalId":23601,"journal":{"name":"VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE","volume":"36 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77351175","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}
Pub Date : 2021-06-30DOI: 10.35940/ijeat.e2688.0610521
N. Mhetre, A. V. Deshpande, P. Mahalle
Ubiquitous computing comprises scenarios where networks, devices within the network, and software components change frequently. Market demand and cost-effectiveness are forcing device manufacturers to introduce new-age devices. Also, the Internet of Things (IoT) is transitioning rapidly from the IoT to the Internet of Everything (IoE). Due to this enormous scale, effective management of these devices becomes vital to support trustworthy and high-quality applications. One of the key challenges of IoT device management is proactive device classification with the logically semantic type and using that as a parameter for device context management. This would enable smart security solutions. In this paper, a device classification approach is proposed for the context management of ubiquitous devices based on unsupervised machine learning. To classify unknown devices and to label them logically, a proactive device classification model is framed using a k-Means clustering algorithm. To group devices, it uses the information of network parameters such as Received Signal Strength Indicator (rssi), packet_size, number_of_nodes in the network, throughput, etc. Experimental analysis suggests that the well-formedness of clusters can be used to derive cluster labels as a logically semantic device type which would be a context for resource management and authorization of resources.
{"title":"Device Classification-Based Context Management for Ubiquitous Computing using\u0000Machine Learning","authors":"N. Mhetre, A. V. Deshpande, P. Mahalle","doi":"10.35940/ijeat.e2688.0610521","DOIUrl":"https://doi.org/10.35940/ijeat.e2688.0610521","url":null,"abstract":"Ubiquitous computing comprises scenarios where\u0000networks, devices within the network, and software components\u0000change frequently. Market demand and cost-effectiveness are\u0000forcing device manufacturers to introduce new-age devices. Also,\u0000the Internet of Things (IoT) is transitioning rapidly from the IoT\u0000to the Internet of Everything (IoE). Due to this enormous scale,\u0000effective management of these devices becomes vital to support\u0000trustworthy and high-quality applications. One of the key\u0000challenges of IoT device management is proactive device\u0000classification with the logically semantic type and using that as a\u0000parameter for device context management. This would enable\u0000smart security solutions. In this paper, a device classification\u0000approach is proposed for the context management of ubiquitous\u0000devices based on unsupervised machine learning. To classify\u0000unknown devices and to label them logically, a proactive device\u0000classification model is framed using a k-Means clustering\u0000algorithm. To group devices, it uses the information of network\u0000parameters such as Received Signal Strength Indicator (rssi),\u0000packet_size, number_of_nodes in the network, throughput, etc.\u0000Experimental analysis suggests that the well-formedness of\u0000clusters can be used to derive cluster labels as a logically semantic\u0000device type which would be a context for resource management\u0000and authorization of resources.","PeriodicalId":23601,"journal":{"name":"VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84445240","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}
Pub Date : 2021-06-30DOI: 10.35940/ijeat.e2824.0610521
Salma Shofia Rosyda, E. Maulina, M. Purnomo
Enterprise resource planning needs to be maximized in line with technological developments and circumstances that can change unexpectedly. The goal is to integrate business processes to enhance collaboration. Organizational performance and critical success factors have become important in enterprise resource planning from 2011 to 2020. This article aims to classify, identify scientific publications, and thematic analysis of the latest literature to create a broad and detailed understanding of enterprise resource planning. The research method used is a systematic mapping study (SMS) to examine scientific publications produced from time to time, types of research, and methods. The SMS procedure follows established empirical guidelines and the mapping data relies on the IEEE, ScienceDirect, and Scopus electronic databases. Based on the results of SMS, it is known that 89 studies met the inclusion criteria. 89 articles were classified by type of paper, method, focus, locus, and year of publication. Then, categorization and quantification of current studies are generated on various dimensions, topic summaries, and current research trends.
{"title":"Systematic Mapping Study of Enterprise Resource Planning","authors":"Salma Shofia Rosyda, E. Maulina, M. Purnomo","doi":"10.35940/ijeat.e2824.0610521","DOIUrl":"https://doi.org/10.35940/ijeat.e2824.0610521","url":null,"abstract":"Enterprise resource planning needs to be maximized\u0000in line with technological developments and circumstances that\u0000can change unexpectedly. The goal is to integrate business\u0000processes to enhance collaboration. Organizational performance\u0000and critical success factors have become important in enterprise\u0000resource planning from 2011 to 2020. This article aims to classify,\u0000identify scientific publications, and thematic analysis of the latest\u0000literature to create a broad and detailed understanding of\u0000enterprise resource planning. The research method used is a\u0000systematic mapping study (SMS) to examine scientific\u0000publications produced from time to time, types of research, and\u0000methods. The SMS procedure follows established empirical\u0000guidelines and the mapping data relies on the IEEE,\u0000ScienceDirect, and Scopus electronic databases. Based on the\u0000results of SMS, it is known that 89 studies met the inclusion\u0000criteria. 89 articles were classified by type of paper, method, focus,\u0000locus, and year of publication. Then, categorization and\u0000quantification of current studies are generated on various\u0000dimensions, topic summaries, and current research trends.","PeriodicalId":23601,"journal":{"name":"VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE","volume":"2015 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87171775","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}
Pub Date : 2021-06-30DOI: 10.35940/ijeat.e2808.0610521
A. HyilsSharonMagdalene., D. Punithavathani
The Radio Frequency (RF) Spectrum decision in Cognitive Radio (CR) allows unlicensed users of wireless communication schemes to conquer the unoccupied spectrum slots as a resolution for barely spectrum. The Internet of Things (IoT) is a broad-arriving network and its object is linked by wireless communication technologies, donating cost- efficiency and generously opens to remote users. When IoT is applied, it is injured by challenges of susceptibility in the forceful surrounding situations, allotment and use of bandwidth, ease of approach and expense to buy RF spectrum. The object is permeated with cognitive capacity and is capable to model RF spectrum decisions to attain interference-release and wireless connectivity due to their Quality of Service (QoS) demands. Therefore the spectrum decision through an unlicensed user on CR influences an importance in CR-based IoT in 5G system and further network. This article depicts a systematic sustainment of the spectrum decision structure to CR Network. So, this can be mainly achieved by applying a favorable spectrum sensing technique and a novel spectrum decision framework. Presently, the wireless connectivity is intended to greater capacity, immense machine connectivity, and greater data range, low end-to-end latency, low cost and coherent Quality of Experience (QoE) condition. Hence, 4G is being substituted by 5G. Being in this 5G, the vast connectivity can be properly inspired by using the novel techniques, which is applied under the Energy detection spectrum sensing system. Also, a novel spectrum decision framework is designed for the optimum application of applying the IoT in 5G system ie., the effective use of an allocated RF spectrum is differently underutilized because of the standard handling with the licensed users are called as Primary Users (PUs).
{"title":"A Novel Spectrum Decision Pattern for The Favorable Cognitive Radio Based Internet of Things in 5G System","authors":"A. HyilsSharonMagdalene., D. Punithavathani","doi":"10.35940/ijeat.e2808.0610521","DOIUrl":"https://doi.org/10.35940/ijeat.e2808.0610521","url":null,"abstract":"The Radio Frequency (RF) Spectrum decision in\u0000Cognitive Radio (CR) allows unlicensed users of wireless\u0000communication schemes to conquer the unoccupied spectrum\u0000slots as a resolution for barely spectrum. The Internet of Things\u0000(IoT) is a broad-arriving network and its object is linked by\u0000wireless communication technologies, donating cost- efficiency\u0000and generously opens to remote users. When IoT is applied, it is\u0000injured by challenges of susceptibility in the forceful surrounding\u0000situations, allotment and use of bandwidth, ease of approach and\u0000expense to buy RF spectrum. The object is permeated with\u0000cognitive capacity and is capable to model RF spectrum decisions\u0000to attain interference-release and wireless connectivity due to their\u0000Quality of Service (QoS) demands. Therefore the spectrum\u0000decision through an unlicensed user on CR influences an\u0000importance in CR-based IoT in 5G system and further network.\u0000This article depicts a systematic sustainment of the spectrum\u0000decision structure to CR Network. So, this can be mainly achieved\u0000by applying a favorable spectrum sensing technique and a novel\u0000spectrum decision framework. Presently, the wireless connectivity\u0000is intended to greater capacity, immense machine connectivity,\u0000and greater data range, low end-to-end latency, low cost and\u0000coherent Quality of Experience (QoE) condition. Hence, 4G is\u0000being substituted by 5G. Being in this 5G, the vast connectivity can\u0000be properly inspired by using the novel techniques, which is\u0000applied under the Energy detection spectrum sensing system. Also,\u0000a novel spectrum decision framework is designed for the optimum\u0000application of applying the IoT in 5G system ie., the effective use\u0000of an allocated RF spectrum is differently underutilized because\u0000of the standard handling with the licensed users are called as\u0000Primary Users (PUs).","PeriodicalId":23601,"journal":{"name":"VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81690402","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}
Pub Date : 2021-06-30DOI: 10.35940/ijeat.e2800.0610521
V. N. Aher, G. Sable, M. R. Rajput
Development of Mathematical model has significant role in many applications such as estimation of relations between input and output variables. The relations can be deterministic or behavioral. From the point of view of control actions to be estimated for a particular application, behavioral model is considered to be of utmost importance. This also amounts the prediction of process behavior in time, frequency and complex domains. Here in this paper, attempts have been made to develop behavioral model of milk evaporation used in dairy industry which is of prominent importance in India because of its agriculture based economy. Besides India, there are also many milk producing countries in the world and their economy is dependent on milk producing animals. It is also imperative that excess milk production to be converted in its preservable form and evaporated milk has special significance in this context. The Milk evaporation is a complex process and its output control variables depend on many of its input manipulation variables. Because of its complex nature and many variables involved in it poses a challenge real life MIMO problem. In this paper, MIMO model of Milk evaporation model is estimated and described.
{"title":"Optimization and Estimation of Transfer Function Model of Milk Evaporation Process","authors":"V. N. Aher, G. Sable, M. R. Rajput","doi":"10.35940/ijeat.e2800.0610521","DOIUrl":"https://doi.org/10.35940/ijeat.e2800.0610521","url":null,"abstract":"Development of Mathematical model has significant\u0000role in many applications such as estimation of relations between\u0000input and output variables. The relations can be deterministic or\u0000behavioral. From the point of view of control actions to be\u0000estimated for a particular application, behavioral model is\u0000considered to be of utmost importance. This also amounts the\u0000prediction of process behavior in time, frequency and complex\u0000domains. Here in this paper, attempts have been made to develop\u0000behavioral model of milk evaporation used in dairy industry which\u0000is of prominent importance in India because of its agriculture\u0000based economy. Besides India, there are also many milk\u0000producing countries in the world and their economy is dependent\u0000on milk producing animals. It is also imperative that excess milk\u0000production to be converted in its preservable form and evaporated\u0000milk has special significance in this context. The Milk evaporation\u0000is a complex process and its output control variables depend on\u0000many of its input manipulation variables. Because of its complex\u0000nature and many variables involved in it poses a challenge real life\u0000MIMO problem. In this paper, MIMO model of Milk evaporation\u0000model is estimated and described.","PeriodicalId":23601,"journal":{"name":"VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE","volume":"13 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89598882","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}
Pub Date : 2021-06-30DOI: 10.35940/ijeat.e2587.0610521
K. Mhatre, Nikita Jha, Sonali Dhurway, Jugnum Parimal
Considering the current scenario of warfare between India and China, we got inspired by the thought of various ways technology can help our hardworking soldiers by reducing the human loss by using an application that can spy on the enemy, and also for security purpose. This project’s main purpose is to deal with difficult situations like where humans cannot go through scenarios like darkness, entering narrow areas and detecting hidden bombs etc. The robot serves as a perfect machine for the defense sector in order to reduce the human life loss and will also help in prevention of illegal activities. The robot is self-powered, with a backtracking facility, in case a situation arises where there is connection loss from the base station. Wireless cameras sends back real-time video and audio inputs that can be seen on a monitor in the base station and action can be taken accordingly.
{"title":"War Field Robot with Night Vision Camera","authors":"K. Mhatre, Nikita Jha, Sonali Dhurway, Jugnum Parimal","doi":"10.35940/ijeat.e2587.0610521","DOIUrl":"https://doi.org/10.35940/ijeat.e2587.0610521","url":null,"abstract":"Considering the current scenario of warfare between\u0000India and China, we got inspired by the thought of various ways\u0000technology can help our hardworking soldiers by reducing the\u0000human loss by using an application that can spy on the enemy, and\u0000also for security purpose. This project’s main purpose is to deal\u0000with difficult situations like where humans cannot go through\u0000scenarios like darkness, entering narrow areas and detecting\u0000hidden bombs etc. The robot serves as a perfect machine for the\u0000defense sector in order to reduce the human life loss and will also\u0000help in prevention of illegal activities. The robot is self-powered,\u0000with a backtracking facility, in case a situation arises where there is\u0000connection loss from the base station. Wireless cameras sends back\u0000real-time video and audio inputs that can be seen on a monitor in\u0000the base station and action can be taken accordingly.","PeriodicalId":23601,"journal":{"name":"VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79611211","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}
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