Pub Date : 2022-10-07DOI: 10.1109/GCAT55367.2022.9972156
T. R. Delson, Iven Jose
Massive MIMO is one of the key disruptive technologies in 5G which offers significant change in the core network architecture and channel modeling compared to the previous wireless communication standards. There are many research works currently focusing on implementing Massive MIMO network in different channel propagation models. ITU, 3GPP and IMT consortium deliver timely 5G LTE releases and taken as benchmark documents by various telecom companies and universities to set up testing, trials and hardware deployments. However, without optimization on spectral efficiency parameter, the specifications proposed by 5G in terms of improvement in data rate or throughput could be difficult to achieve. This paper initially provides an in-depth study on spectral efficiency estimation and optimization in Massive MIMO by investigating different research papers. From these papers, list of parameters involved in spectral efficiency are identified, such as, fading characteristics, power or energy efficient parameters, standard deviation, angle of arrival factors in antennas installed in base stations and many others. The author however concludes with the best selection of constraint optimization parameters to improve the spectral efficiency taking into account of its simple design and major impact on the improvement in the result by taking downlink scenario of a simulation environment using 5G Massive MIMO network. SINR mapping of standard Rural Macro test scenario adopted from M 2314, LTE release 17 of 5G framework is simulated in this research paper.
{"title":"Study on 5G Massive MIMO Technology Key Parameters for Spectral Efficiency Improvement Including SINR Mapping on Rural Area Test Case","authors":"T. R. Delson, Iven Jose","doi":"10.1109/GCAT55367.2022.9972156","DOIUrl":"https://doi.org/10.1109/GCAT55367.2022.9972156","url":null,"abstract":"Massive MIMO is one of the key disruptive technologies in 5G which offers significant change in the core network architecture and channel modeling compared to the previous wireless communication standards. There are many research works currently focusing on implementing Massive MIMO network in different channel propagation models. ITU, 3GPP and IMT consortium deliver timely 5G LTE releases and taken as benchmark documents by various telecom companies and universities to set up testing, trials and hardware deployments. However, without optimization on spectral efficiency parameter, the specifications proposed by 5G in terms of improvement in data rate or throughput could be difficult to achieve. This paper initially provides an in-depth study on spectral efficiency estimation and optimization in Massive MIMO by investigating different research papers. From these papers, list of parameters involved in spectral efficiency are identified, such as, fading characteristics, power or energy efficient parameters, standard deviation, angle of arrival factors in antennas installed in base stations and many others. The author however concludes with the best selection of constraint optimization parameters to improve the spectral efficiency taking into account of its simple design and major impact on the improvement in the result by taking downlink scenario of a simulation environment using 5G Massive MIMO network. SINR mapping of standard Rural Macro test scenario adopted from M 2314, LTE release 17 of 5G framework is simulated in this research paper.","PeriodicalId":133597,"journal":{"name":"2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115062883","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 : 2022-10-07DOI: 10.1109/GCAT55367.2022.9972051
Komal, Harsh Dashora, J. Kumar, D. Kumar, D. Mamatha
Avionics hardware such as communication, power, control packages require reliable, compact, light weighted systems so as to achieve high payload to spacecraft ratio and the effort starts from selection and optimization of EEE components, mechanical housings, cables harness etc. In this article, a imported microwave device which is costly and usually realised through planar approach is targeted to be fabricated from miniaturised lumped HMC components and realised in the form of HMC, which is demonstrated to be effectively smaller with similar performance as compared to that fabricated from planar approach.
{"title":"Design of Indigenous Quadrature Hybrid for ISRO Missions","authors":"Komal, Harsh Dashora, J. Kumar, D. Kumar, D. Mamatha","doi":"10.1109/GCAT55367.2022.9972051","DOIUrl":"https://doi.org/10.1109/GCAT55367.2022.9972051","url":null,"abstract":"Avionics hardware such as communication, power, control packages require reliable, compact, light weighted systems so as to achieve high payload to spacecraft ratio and the effort starts from selection and optimization of EEE components, mechanical housings, cables harness etc. In this article, a imported microwave device which is costly and usually realised through planar approach is targeted to be fabricated from miniaturised lumped HMC components and realised in the form of HMC, which is demonstrated to be effectively smaller with similar performance as compared to that fabricated from planar approach.","PeriodicalId":133597,"journal":{"name":"2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117339162","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 : 2022-10-07DOI: 10.1109/GCAT55367.2022.9972172
B. Pranav, M. Dharithri, D. Venu, Mrinal. S. Setty, K. Rekha, H. D. Phaneendra
Numerous types of connectivity are now necessary for hundreds of thousands of intelligent devices, including smartphones, tablets, industrial machinery, and home appliances. The inevitable demand for better connectivity in the IoT era has increased the expectations for even the most basic smart devices to have the capability to process real-time audio and perform intelligent digital signal processing (DSP) on the network's entry point device. This has ultimately paved the way for various innovative market entrants, looking to both challenges and work in tandem with traditional solutions to provide quality data-transmission capabilities. For engineers trying to enable frictionless interactions across an ever-increasing number of connected devices, one technology is now quickly emerging as an interesting connectivity opportunity. Anyone can utilize an ultrasonic beacon nowadays thanks to cell phones with high-frequency-capable speakers and microphones. Data-over-sound allows for the transmission of data by sound waves between any devices which already have a loudspeaker or microphone, which makes it easier for anyone with basic knowledge of how to use a smartphone will be able to communicate with ease. The proposed system will have 2 peers, a receiver, and a sender, whereby converting the session data into audio tones, transmits an offer for a WebRTC connection to the other peer. who wants to connect respond with an audio answer, and the transmitted audio answer is captured by the peer who broadcasted an offer for WebRTC connection, and it is decoded and allows the other peer to connect, and then the connection is established.
{"title":"Sound Share: P2P File-Sharing System","authors":"B. Pranav, M. Dharithri, D. Venu, Mrinal. S. Setty, K. Rekha, H. D. Phaneendra","doi":"10.1109/GCAT55367.2022.9972172","DOIUrl":"https://doi.org/10.1109/GCAT55367.2022.9972172","url":null,"abstract":"Numerous types of connectivity are now necessary for hundreds of thousands of intelligent devices, including smartphones, tablets, industrial machinery, and home appliances. The inevitable demand for better connectivity in the IoT era has increased the expectations for even the most basic smart devices to have the capability to process real-time audio and perform intelligent digital signal processing (DSP) on the network's entry point device. This has ultimately paved the way for various innovative market entrants, looking to both challenges and work in tandem with traditional solutions to provide quality data-transmission capabilities. For engineers trying to enable frictionless interactions across an ever-increasing number of connected devices, one technology is now quickly emerging as an interesting connectivity opportunity. Anyone can utilize an ultrasonic beacon nowadays thanks to cell phones with high-frequency-capable speakers and microphones. Data-over-sound allows for the transmission of data by sound waves between any devices which already have a loudspeaker or microphone, which makes it easier for anyone with basic knowledge of how to use a smartphone will be able to communicate with ease. The proposed system will have 2 peers, a receiver, and a sender, whereby converting the session data into audio tones, transmits an offer for a WebRTC connection to the other peer. who wants to connect respond with an audio answer, and the transmitted audio answer is captured by the peer who broadcasted an offer for WebRTC connection, and it is decoded and allows the other peer to connect, and then the connection is established.","PeriodicalId":133597,"journal":{"name":"2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116288759","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 : 2022-10-07DOI: 10.1109/GCAT55367.2022.9971883
Km. Jyotsana, Amit Kumar
A bulk driven differential pair-based on OTAs with flipped, voltage flowers. Operational transconductance amplifiers (OTAs) for audio frequency applications are used in the signal stage. This article presents a simple and high performance conventional circuit for LP or LV efficient gates as well as a bulk-driven differential pair OTA (DPOTA) for applications of audio frequency. A composite transistor of the (FVFDP) flipped voltage follower differential pair is used to implement the summing stage, so it is capable of building the complete input as well as output dynamic range of (-VSS to VDD), which benefits the (FFV) bulk-driven OTAs of the inpu stage. Along with the design of the proposed OTAs is suitable for the operation of the CMOS transistor used to enhance the DC gain of the (FFV). OTAs, which is reduced the input referred to as noise (IRN) from $mathbf{0}.mathbf{449}boldsymbol{mu}mathbf{v}/mathbf{sqrt}$ (Hz) to 44.49nv/sqrt(Hz) at 100KHz. The transistor-level simulations performed using a 90nm CMOS process conform to the theoretical results of a cadence virtuoso environment. Simulated from a (0.7v to −0.7v) supply. These proposed conventional topology of the OTAs using an (SD) or source degenerative, resistor of 1k succeeds an open loop gain of 76.787 dB, it is seen the unity gain frequency (UGF) of 1.89 kHz and a phase margin of 78.07 companion capacitors is employed, gain bandwidth 14.04 kHz performed consumes at only 130.6nw of power.
{"title":"Design and Implementation of Low Power Flipped Voltage Follower Differential Pair-based Summing Stage OTA","authors":"Km. Jyotsana, Amit Kumar","doi":"10.1109/GCAT55367.2022.9971883","DOIUrl":"https://doi.org/10.1109/GCAT55367.2022.9971883","url":null,"abstract":"A bulk driven differential pair-based on OTAs with flipped, voltage flowers. Operational transconductance amplifiers (OTAs) for audio frequency applications are used in the signal stage. This article presents a simple and high performance conventional circuit for LP or LV efficient gates as well as a bulk-driven differential pair OTA (DPOTA) for applications of audio frequency. A composite transistor of the (FVFDP) flipped voltage follower differential pair is used to implement the summing stage, so it is capable of building the complete input as well as output dynamic range of (-VSS to VDD), which benefits the (FFV) bulk-driven OTAs of the inpu stage. Along with the design of the proposed OTAs is suitable for the operation of the CMOS transistor used to enhance the DC gain of the (FFV). OTAs, which is reduced the input referred to as noise (IRN) from $mathbf{0}.mathbf{449}boldsymbol{mu}mathbf{v}/mathbf{sqrt}$ (Hz) to 44.49nv/sqrt(Hz) at 100KHz. The transistor-level simulations performed using a 90nm CMOS process conform to the theoretical results of a cadence virtuoso environment. Simulated from a (0.7v to −0.7v) supply. These proposed conventional topology of the OTAs using an (SD) or source degenerative, resistor of 1k succeeds an open loop gain of 76.787 dB, it is seen the unity gain frequency (UGF) of 1.89 kHz and a phase margin of 78.07 companion capacitors is employed, gain bandwidth 14.04 kHz performed consumes at only 130.6nw of power.","PeriodicalId":133597,"journal":{"name":"2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123512513","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 : 2022-10-07DOI: 10.1109/GCAT55367.2022.9972219
Srikumar Manghat
Determination of critical clearing time (CCT) for a power system is an important component of transient stability analysis. The methods proposed so far suffer from the drawback that either they do not determine the CCTs reliably or are too complex to implement or both. Also, none of the methods easily determine the generator most vulnerable to de-synchronization for a particular fault. The present paper proposes a new method to determine CCTs and the most vulnerable generator. It first reduces the multi-machine power system to a two-machine system with one of the machines being one of the generators of the power system. It then determines the CCT for this generator from this system using known formulae. This procedure is repeated for each generator of the power system and CCTs determined for each. The least value of the CCTs obtained is declared the CCT of the power system and the corresponding generator is declared the most vulnerable one. The method uses minimum computational effort and is easy to implement. Also, it is shown that the values of CCTs obtained are always less than actual values, making the method extremely reliable. These facts are confirmed by testing the method on various test systems.
{"title":"A Simple Method to Find the Most Vulnerable Generator and a Safe Value of Critical Clearing Time for a Fault in a Power System","authors":"Srikumar Manghat","doi":"10.1109/GCAT55367.2022.9972219","DOIUrl":"https://doi.org/10.1109/GCAT55367.2022.9972219","url":null,"abstract":"Determination of critical clearing time (CCT) for a power system is an important component of transient stability analysis. The methods proposed so far suffer from the drawback that either they do not determine the CCTs reliably or are too complex to implement or both. Also, none of the methods easily determine the generator most vulnerable to de-synchronization for a particular fault. The present paper proposes a new method to determine CCTs and the most vulnerable generator. It first reduces the multi-machine power system to a two-machine system with one of the machines being one of the generators of the power system. It then determines the CCT for this generator from this system using known formulae. This procedure is repeated for each generator of the power system and CCTs determined for each. The least value of the CCTs obtained is declared the CCT of the power system and the corresponding generator is declared the most vulnerable one. The method uses minimum computational effort and is easy to implement. Also, it is shown that the values of CCTs obtained are always less than actual values, making the method extremely reliable. These facts are confirmed by testing the method on various test systems.","PeriodicalId":133597,"journal":{"name":"2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT)","volume":"280 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123619535","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 : 2022-10-07DOI: 10.1109/GCAT55367.2022.9972154
Shiv Charan Banerjee, Shobhan Banerjee, Pratik Rai
In order to tackle the Corona Virus Disease, it took a considerable amount of time for the governments to come up with effective and efficient vaccines. After the vaccines were developed, the next challenge was to supply the vaccines to various designated centers based on demographics, population distribution, and other factors. The whole system for vaccine supply played a vital role during the COVID-19 pandemic. We also saw a lot of haphazard and mismanagement in some places especially when the cases per day surged high, as people weren't prepared for such a situation. Now that we have got enough data, we can use it to optimize the vaccine supply across various Covid Vaccination Centers and be prepared for any such circumstances in the future. In this paper, we have proposed a two-step approach where considering the past supply and wastage data we performed a classification task that indicates whether doses are to get wasted at a given center. If yes, we then perform demand forecasting based on the number of administered doses so that the wastage can be reduced, and supply can be optimized.
{"title":"Vaccine Supply Optimization and Forecasting using Random Forest and ARIMA Models","authors":"Shiv Charan Banerjee, Shobhan Banerjee, Pratik Rai","doi":"10.1109/GCAT55367.2022.9972154","DOIUrl":"https://doi.org/10.1109/GCAT55367.2022.9972154","url":null,"abstract":"In order to tackle the Corona Virus Disease, it took a considerable amount of time for the governments to come up with effective and efficient vaccines. After the vaccines were developed, the next challenge was to supply the vaccines to various designated centers based on demographics, population distribution, and other factors. The whole system for vaccine supply played a vital role during the COVID-19 pandemic. We also saw a lot of haphazard and mismanagement in some places especially when the cases per day surged high, as people weren't prepared for such a situation. Now that we have got enough data, we can use it to optimize the vaccine supply across various Covid Vaccination Centers and be prepared for any such circumstances in the future. In this paper, we have proposed a two-step approach where considering the past supply and wastage data we performed a classification task that indicates whether doses are to get wasted at a given center. If yes, we then perform demand forecasting based on the number of administered doses so that the wastage can be reduced, and supply can be optimized.","PeriodicalId":133597,"journal":{"name":"2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121923507","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 : 2022-10-07DOI: 10.1109/GCAT55367.2022.9972035
Swetha Sivakumar, T. C. Pramod
cardiovascular disease remains the major cause of fatality for both men and women worldwide. Heart disease is on the rise in both old and the young of males and females in today's society. As a result, developing and implementing comprehensive health-tracking rules should be spotlight in order to tackle the epidemic of heart-associated illnesses. As a result, early detection and treatment, using both traditional and novel techniques, must be prioritized. The primary goal of this study is to determine the best classifying approach for heart disease-related health data and the factors that impact it. This comprehensive work is based on the performance of systems that have been evaluated and described using various models presented in various research papers, and it provides a complete review of those research papers in order to set up the heart disease prognostication model and its performance.
{"title":"Comprehensive Analysis of Heart Disease Prediction: Machine Learning Approach","authors":"Swetha Sivakumar, T. C. Pramod","doi":"10.1109/GCAT55367.2022.9972035","DOIUrl":"https://doi.org/10.1109/GCAT55367.2022.9972035","url":null,"abstract":"cardiovascular disease remains the major cause of fatality for both men and women worldwide. Heart disease is on the rise in both old and the young of males and females in today's society. As a result, developing and implementing comprehensive health-tracking rules should be spotlight in order to tackle the epidemic of heart-associated illnesses. As a result, early detection and treatment, using both traditional and novel techniques, must be prioritized. The primary goal of this study is to determine the best classifying approach for heart disease-related health data and the factors that impact it. This comprehensive work is based on the performance of systems that have been evaluated and described using various models presented in various research papers, and it provides a complete review of those research papers in order to set up the heart disease prognostication model and its performance.","PeriodicalId":133597,"journal":{"name":"2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122031008","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 : 2022-10-07DOI: 10.1109/GCAT55367.2022.9971859
Shalini K B Devi, Sanjay Kumar, Jambi Ratna Raja Kumar
Internet of Things (IoT) connects billions of devices that can communicate with each other with little human input. IoT is the rapid-growth segment of computing, but it is also one of the most susceptible to cyber-attacks. Practical countermeasures to safeguard IoT networks, for instance network anomaly monitoring, must be devised. While attacks cannot be completely prevented, early identification is critical for effective protection. Because IoT devices have limited storage and processing power, typical most sophisticated security solutions are ineffective. Also, IoT devices now connect automatically for longer durations. This necessitates clever network-based security solutions like machine learning. Although numerous studies have recently examined the use of Machine Learning (ML) techniques in attacks detection, a small attention is to be paid for detecting the attacks in IoT networks. We want to add to the field by testing several machine learning techniques for detecting IoT network attacks. The Bot-IoT dataset is used to test detection methods. For implementing the system, various machine learning algorithms are deployed, most of which performed well. During deployment, additional characteristics were collected from the Bot-IoT dataset and compared to existing research, with superior results.
{"title":"Machine Learning Methods for Secure Internet of Things Against Cyber Threats","authors":"Shalini K B Devi, Sanjay Kumar, Jambi Ratna Raja Kumar","doi":"10.1109/GCAT55367.2022.9971859","DOIUrl":"https://doi.org/10.1109/GCAT55367.2022.9971859","url":null,"abstract":"Internet of Things (IoT) connects billions of devices that can communicate with each other with little human input. IoT is the rapid-growth segment of computing, but it is also one of the most susceptible to cyber-attacks. Practical countermeasures to safeguard IoT networks, for instance network anomaly monitoring, must be devised. While attacks cannot be completely prevented, early identification is critical for effective protection. Because IoT devices have limited storage and processing power, typical most sophisticated security solutions are ineffective. Also, IoT devices now connect automatically for longer durations. This necessitates clever network-based security solutions like machine learning. Although numerous studies have recently examined the use of Machine Learning (ML) techniques in attacks detection, a small attention is to be paid for detecting the attacks in IoT networks. We want to add to the field by testing several machine learning techniques for detecting IoT network attacks. The Bot-IoT dataset is used to test detection methods. For implementing the system, various machine learning algorithms are deployed, most of which performed well. During deployment, additional characteristics were collected from the Bot-IoT dataset and compared to existing research, with superior results.","PeriodicalId":133597,"journal":{"name":"2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT)","volume":"37 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120823309","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 : 2022-10-07DOI: 10.1109/GCAT55367.2022.9972008
S. Hossain, Md. Sohel Rana, Md. Mostafizur Rahman
Microstrip slotted patch antennas are drawing antenna designers' attention due to appealing features such as less weight and low profile, but they also have certain downsides such as low gain, narrow bandwidth and higher VSWR (Voltage Standing Wave Ratio). These disadvantages can be mitigated to some extent by careful antenna design. This research offers a novel design for microstrip patch antenna bandwidth augmentation, efficiency and reduction of VSWR using a slotted patch adjacent to the radiating patch. A microstrip slotted patch antenna is also proposed for 5G communication in this study. The designed structure operates at 29.416 GHz. The proposed design is simulated using the CST studio suite (Computer Simulation Technology) software. The return loss is -44.78 dB, the bandwidth is 900 MHz and the VSWR is 1.0115. The findings demonstrate that the proposed design has favorable properties for Ka-band applications.
微带开槽贴片天线因其重量轻、外形低等优点而备受天线设计者的关注，但也存在增益低、带宽窄、驻波比高等缺点。通过仔细的天线设计，这些缺点可以在一定程度上得到缓解。本研究提供了一种新的微带贴片天线设计，利用与辐射贴片相邻的开槽贴片来增加带宽、提高效率和降低驻波比。本研究还提出了一种用于5G通信的微带开槽贴片天线。设计的结构工作在29.416 GHz。本设计采用CST studio suite (Computer Simulation Technology)软件进行仿真。回波损耗为-44.78 dB，带宽为900 MHz，驻波比为1.0115。结果表明，所提出的设计具有良好的性能，适用于ka波段。
{"title":"Design and Analysis of A Ka Band Microstrip Slotted Patch Antenna with 5G Communication Technology Using CST","authors":"S. Hossain, Md. Sohel Rana, Md. Mostafizur Rahman","doi":"10.1109/GCAT55367.2022.9972008","DOIUrl":"https://doi.org/10.1109/GCAT55367.2022.9972008","url":null,"abstract":"Microstrip slotted patch antennas are drawing antenna designers' attention due to appealing features such as less weight and low profile, but they also have certain downsides such as low gain, narrow bandwidth and higher VSWR (Voltage Standing Wave Ratio). These disadvantages can be mitigated to some extent by careful antenna design. This research offers a novel design for microstrip patch antenna bandwidth augmentation, efficiency and reduction of VSWR using a slotted patch adjacent to the radiating patch. A microstrip slotted patch antenna is also proposed for 5G communication in this study. The designed structure operates at 29.416 GHz. The proposed design is simulated using the CST studio suite (Computer Simulation Technology) software. The return loss is -44.78 dB, the bandwidth is 900 MHz and the VSWR is 1.0115. The findings demonstrate that the proposed design has favorable properties for Ka-band applications.","PeriodicalId":133597,"journal":{"name":"2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124473162","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 : 2022-10-07DOI: 10.1109/GCAT55367.2022.9972062
Sanai Divadkar, Akshat Sahu, Shalini Puri
In this modern world, fake and ambiguous news identification and detection is a critical issue in the life of digital and social media. Fake news manipulates the public and gains readership in the wrong sense. Its fast spread and misuse are very harmful to an individual, society, organization, government, and nation. Presently, many automated learning-based detection systems and models have been developed to date. This paper aims to review those existing ambiguous-fake news identification models using deep learning, machine learning, and ensemble learning paradigms. This review compares a large number of such contributions using some key parameters and explores their challenges. Their analytical observations state that most of the works used the Kaggle dataset for the implementation. The accuracy results of DL learning-based systems outperformed the results of both ML-based and ensemble learning-based learning systems.
{"title":"A Review of Ambiguous News Detection Approaches with Deep Learning, Machine Learning, and Ensemble Paradigms","authors":"Sanai Divadkar, Akshat Sahu, Shalini Puri","doi":"10.1109/GCAT55367.2022.9972062","DOIUrl":"https://doi.org/10.1109/GCAT55367.2022.9972062","url":null,"abstract":"In this modern world, fake and ambiguous news identification and detection is a critical issue in the life of digital and social media. Fake news manipulates the public and gains readership in the wrong sense. Its fast spread and misuse are very harmful to an individual, society, organization, government, and nation. Presently, many automated learning-based detection systems and models have been developed to date. This paper aims to review those existing ambiguous-fake news identification models using deep learning, machine learning, and ensemble learning paradigms. This review compares a large number of such contributions using some key parameters and explores their challenges. Their analytical observations state that most of the works used the Kaggle dataset for the implementation. The accuracy results of DL learning-based systems outperformed the results of both ML-based and ensemble learning-based learning systems.","PeriodicalId":133597,"journal":{"name":"2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128446106","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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