2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT)最新文献_第5页

Deep Learning based Simultaneous Wireless Information and Power Transfer Enabled Massive MIMO NOMA for Beyond 5G 基于深度学习的同步无线信息和电力传输支持5G以上的大规模MIMO NOMA

2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT) Pub Date : 2023-05-25 DOI: 10.1109/IConSCEPT57958.2023.10170536

Sundaresan Sabapathy, Aswini Krishnan, Nishanth Nedoumarane, Surendar Maruthu, D. Jayakody

{"title":"Deep Learning based Simultaneous Wireless Information and Power Transfer Enabled Massive MIMO NOMA for Beyond 5G","authors":"Sundaresan Sabapathy, Aswini Krishnan, Nishanth Nedoumarane, Surendar Maruthu, D. Jayakody","doi":"10.1109/IConSCEPT57958.2023.10170536","DOIUrl":"https://doi.org/10.1109/IConSCEPT57958.2023.10170536","url":null,"abstract":"The exponential growth of wireless data services driven by mobile internet and connected devices has triggered the thriving of beyond fifth-generation (B5G) cellular networks. The integration of simultaneous wireless information and power transfer (SWIPT), non-orthogonal multiple access (NOMA), with multiple antenna system is a potential solution to improve spectral efficiency (SE) and energy efficiency (EE). Moreover, it paves the way for ultra-reliable and low-latency communication (URLLC) and massive machine-type communication (mMTC) scenarios. This paper explores an optimal solution for power allocation (PA) and power splitting (PS) control for EE maximization in SWIPT-based multiple input multiple outputs (MIMO) NOMA system. The significant aim is to maximize the EE of the system, maintaining equal fairness among the users in the cluster while satisfying the quality-of-service (QoS) requirements. The optimal solution to fulfill the trade-off between data decoded and energy harvested (EH) at the receiver is achieved through a deep learning (DL) model, viz., deep belief network (DBN). The dataset consisting of 3500 samples is created by varying the power levels from 20 dBm to 40 dBm, and also varying the distance of the users from the base station (BS). The PA and PS efficiency of 94.09 and 91.36 percent respectively, is achieved with DBN which aids for energy and SE in SWIPT MIMO NOMA system for 5GB.","PeriodicalId":240167,"journal":{"name":"2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114910364","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

An Automatic Fake News Identification System using Machine Learning Techniques 基于机器学习技术的假新闻自动识别系统

2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT) Pub Date : 2023-05-25 DOI: 10.1109/IConSCEPT57958.2023.10170307

Archana Saini, Kalpna Guleria, Shagun Sharma

{"title":"An Automatic Fake News Identification System using Machine Learning Techniques","authors":"Archana Saini, Kalpna Guleria, Shagun Sharma","doi":"10.1109/IConSCEPT57958.2023.10170307","DOIUrl":"https://doi.org/10.1109/IConSCEPT57958.2023.10170307","url":null,"abstract":"With the evolvement in technology and social media, the prevalence of fake news is rapidly increasing. It has become a new research field that is gaining popularity and requires attention. However, due to a scarcity of resources such as insufficient and invalid datasets along with analysis techniques, there are various challenges such as the flourishment of fake news, that are faced. It has a considerable influence on everyday lives, as well as in almost every single field, especially politics, and education. Hence, this condition requires attention to detect fake news for reducing distrust in the government systems. This article introduces a solution to fake news detection by implementing a model using various classification techniques. This work has been implemented with Decision Tree, Random Forest, Logistic Regression, and Passive Aggressive Classifier for identifying fake news. However, the outcome of the passive-aggressive classifier has resulted in the highest accuracy of 93.05%. Furthermore, this work can help in the real-time identification of fake news leading to maintaining people’s trust on social media and government systems.","PeriodicalId":240167,"journal":{"name":"2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT)","volume":"126 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128197275","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

Sovereign Critique Network (SCN) Based Super-Resolution for chest X-rays images 基于主权批判网络(SCN)的胸部x射线图像超分辨率

2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT) Pub Date : 2023-05-25 DOI: 10.1109/IConSCEPT57958.2023.10170157

P. V. Yeswanth, Raavi Raviteja, S. Deivalakshmi

{"title":"Sovereign Critique Network (SCN) Based Super-Resolution for chest X-rays images","authors":"P. V. Yeswanth, Raavi Raviteja, S. Deivalakshmi","doi":"10.1109/IConSCEPT57958.2023.10170157","DOIUrl":"https://doi.org/10.1109/IConSCEPT57958.2023.10170157","url":null,"abstract":"A prevalent and serious illness that affects people all over the globe is tuberculosis. A successful diagnosis of tuberculosis is essential for better survival rates and a successful course of treatment. Different techniques for detecting tuberculosis have been developed recently as a result of advancements in medical technology. These techniques have greatly increased the reliability and precision of tuberculosis detection. Finding tuberculosis at an early state, in which it is most treatable, is still a challenge. In order to improve the resolution of X-ray chest images for the early detection of tuberculosis, study is currently being done in this area. The Sovereign Critique Network (SCN) model is suggested in this article as a means of generating super resolution images from low-resolution X-ray images. The suggested SCN model is evaluated on the Tuberculosis (TB) Chest X-ray database for super resolution factors of 2, 4, and 6 separately with PSNR values of 31.85, 33.79, and 35.93 and SSIM values of 0.84, 0.91, and 0.96 for super resolution factors 2, 4, and 6, respectively. The proposed model shows promising results than any of the existing models.","PeriodicalId":240167,"journal":{"name":"2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT)","volume":"297 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123464237","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

Early Alzheimer’s Detection Using Random Forest Algorithm 基于随机森林算法的早期阿尔茨海默病检测

2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT) Pub Date : 2023-05-25 DOI: 10.1109/IConSCEPT57958.2023.10170234

Pranjlee Kolte, Nandani Rabra, Aditya Shrivastava, Anushka Khadatkar, Himanshu Choudhary, Divya Shrivastava

{"title":"Early Alzheimer’s Detection Using Random Forest Algorithm","authors":"Pranjlee Kolte, Nandani Rabra, Aditya Shrivastava, Anushka Khadatkar, Himanshu Choudhary, Divya Shrivastava","doi":"10.1109/IConSCEPT57958.2023.10170234","DOIUrl":"https://doi.org/10.1109/IConSCEPT57958.2023.10170234","url":null,"abstract":"Alzheimer’s disease (AD) is a progressive neurological ailment causing damage to brain cells. Beginning with mild symptoms that usually goes unnoticed, the disorder gets worse as it progresses hindering the general abilities of person. Early AD symptoms being ordinarily simple, detection occurs only on disease progression to an advance irreversible stage. Early detection of AD is thus critical to reduce the adverse effects of the disease. Earlier detection can prove promising for the development of specific treatment strategies that improve or slow AD progression. Machine Learning (ML) approach has become increasingly useful in the detection of Alzheimer’s disease in recent years. In this paper, early detection of Alzheimer’s disease using different machine learning algorithms for predictive categorization of patients is presented. The study suggests that random forest algorithm offers best performance for early prediction of Alzheimer’s disease with an accuracy of 93.69%. A GUI for users to enter parameters for early detection and display the categorized result for random forest algorithm is also designed.","PeriodicalId":240167,"journal":{"name":"2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT)","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131475119","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

The Role of IOT & AI in Battery Management of Electric Vehicles 物联网和人工智能在电动汽车电池管理中的作用

2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT) Pub Date : 2023-05-25 DOI: 10.1109/IConSCEPT57958.2023.10170275

Kavitha Kumari.K.S, L. Chitra, Jibin M Abraham, Noyal Joseph, Yedu Krishnan T.K

{"title":"The Role of IOT & AI in Battery Management of Electric Vehicles","authors":"Kavitha Kumari.K.S, L. Chitra, Jibin M Abraham, Noyal Joseph, Yedu Krishnan T.K","doi":"10.1109/IConSCEPT57958.2023.10170275","DOIUrl":"https://doi.org/10.1109/IConSCEPT57958.2023.10170275","url":null,"abstract":"Electric vehicle (EV) performance is influenced by a variety of parameters like battery life, cell voltage and health, safety and charging-discharging speeds. In EVs, the battery management is a crucial task which facilitates the effective functioning of battery. This paper suggests an improved monitoring of battery State-Of-Charge (SOC) using Internet of Things (IOT) and Artificial Intelligence (AI). This paper focus on a problem for researchers in order to ensure the safety of cars and users by exactly estimating SOC, monitoring and spotting in-time breakdowns of the rechargeable batteries of electric vehicles respectively. The voltage obtained from the Photovoltaic (PV) system is improved by the Boost integrated fly back rectifier energy DC-DC (BIFRED) converter which is controlled by an cascaded ANFIS controller. The SOC of the battery is monitored by Recurrent Neural Networks (RNN) and the data is stored in IOT. The IOT allows for the continuous monitoring and transmission of all battery-related data to the cloud, enabling for the capture of real-time battery information. Thus this paper clearly focus on monitoring and estimating time breakdown of the rechargeable batteries of vehicles.","PeriodicalId":240167,"journal":{"name":"2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122331888","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 FinFET pass transistor based XOR and XNOR circuit designed for 18nm technology 一种基于18nm技术的XOR和XNOR电路的FinFET通管

2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT) Pub Date : 2023-05-25 DOI: 10.1109/IConSCEPT57958.2023.10169937

Pavan Adulapuram, C. Kumar, Tejaswini Tula, Farasha Mehroz Mohammed Abdul, Sritha Katrapally, Lavan Kumar Pakala

引用次数: 0

Design and Implementation of Vedic Multiplier using Carry Increment Adder 采用进位增量加法器的吠陀乘法器的设计与实现

2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT) Pub Date : 2023-05-25 DOI: 10.1109/IConSCEPT57958.2023.10170489

A. Lavanya, S. Nagaraj, Lekhya M

{"title":"Design and Implementation of Vedic Multiplier using Carry Increment Adder","authors":"A. Lavanya, S. Nagaraj, Lekhya M","doi":"10.1109/IConSCEPT57958.2023.10170489","DOIUrl":"https://doi.org/10.1109/IConSCEPT57958.2023.10170489","url":null,"abstract":"Vedic multiplier uses adders as its fundamental building block. One of the crucial performance criteria for many digital circuits is the circuit’s operating speed, which ultimately depends on the basic adder unit’s delay. This project is devoted to the construction and analysis of a speed Vedic multiplier that uses various adders to analyse speed, area, and power. Using the carry increment adder and Halfadders in Verilog HDL, a 16-bit Vedic multiplier is created. Modelsim is used to simulate the modules, while Xilinx ISE 14.7 is used to synthesise them. In this project, a carry increment adder-based Vedic multiplier will be implemented using the CLA, and its performance will be compared to Vedic multiplier implemented using the ripple carry adder.. In this project an implementation of Vedic Multiplier using carry increment adder and comparing it with the Vedic multiplier using Ripple Carry Adder will be performed. The synthesis report shows that CIA-CLA has 1% lesser area than Vedic Multiplier using Ripple Carry Adder and CIA-RCA. and CIA-CLA has 10% greater delay than Vedic Multiplier using Ripple Carry Adder and CIA-RCA.","PeriodicalId":240167,"journal":{"name":"2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130084699","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

Noise Reduction Algorithm for Speech Enhancement 语音增强的降噪算法

2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT) Pub Date : 2023-05-25 DOI: 10.1109/IConSCEPT57958.2023.10170204

S. Pradeep Kumar, Anusha Daripelly, Sai Meghana Rampelli, Surya Kiran Reddy Nagireddy, Akhila Badishe, Amulya Attanthi

{"title":"Noise Reduction Algorithm for Speech Enhancement","authors":"S. Pradeep Kumar, Anusha Daripelly, Sai Meghana Rampelli, Surya Kiran Reddy Nagireddy, Akhila Badishe, Amulya Attanthi","doi":"10.1109/IConSCEPT57958.2023.10170204","DOIUrl":"https://doi.org/10.1109/IConSCEPT57958.2023.10170204","url":null,"abstract":"Speech communication involves transmitting information through speech between individuals or between individuals and machines in different areas such as speaker identification and automatic speech recognition. However, background noise can hinder effective communication by interfering with speech signals. Therefore, it is necessary to improve speech signals to minimize external disturbances. The process used to generate a more precise voice synthesis from an unclear audio source is called speech enhancement, which employs different algorithms to enhance speech quality. Wavelet transform is used to remove background noise from the messy audio while retaining essential speech information. To eliminate noise from the signal and achieve a clear signal, a semi-soft thresholding approach is employed, which removes chaotic coefficients from the wavelet. The primary objective of this paper is to use semi-soft thresholding to eliminate noise from signal and produce a clear signal. Noise reduction is a critical aspect of speech enhancement that has various applications, including speaker identification, prosthetic devices, VoIP, telepresence, and mobile devices.","PeriodicalId":240167,"journal":{"name":"2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115108577","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

Resume Classification Using ML Techniques 使用ML技术进行简历分类

2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT) Pub Date : 2023-05-25 DOI: 10.1109/IConSCEPT57958.2023.10169907

B Surendiran, Tejus Paturu, Harsha Vardhan Chirumamilla, Maruprolu Naga Raju Reddy

引用次数: 1

An approach to Generation of sentences using Sign Language Detection 一种基于手语检测的句子生成方法

2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT) Pub Date : 2023-05-25 DOI: 10.1109/IConSCEPT57958.2023.10170218

K. S. Vikash, Kaavya Jayakrishnan, Siddharth Ramanathan, G. Rohith, Vijayendra Hanumara

{"title":"An approach to Generation of sentences using Sign Language Detection","authors":"K. S. Vikash, Kaavya Jayakrishnan, Siddharth Ramanathan, G. Rohith, Vijayendra Hanumara","doi":"10.1109/IConSCEPT57958.2023.10170218","DOIUrl":"https://doi.org/10.1109/IConSCEPT57958.2023.10170218","url":null,"abstract":"Deaf and mute people use sign language naturally. This article provides an application that addresses the problem of sign language detection by using computer vision and machine learning. The proposed system is a sign language interpreter that recognizes and understands the sign language words. These detected words and phrases are placed together as a sentence, enabling the user to get a complete translation. The system will collect video of a signer using a camera, and computer vision algorithms to recognize hand motions and movements. The user’s dominant hand (left or right) will conduct most of this activity. Single Shot MultiBox Detector (SSD) MobileNet V2 Deep learning technique is used to recognize the hand motions and movements and convert the identified signs into text output. The system will be trained on a dataset of sign language phrases, and its accuracy will be assessed using a range of performance indicators. The suggested technique is 96% accurate in identifying the type of sign language and 100% accurate in translating it to interpretation.","PeriodicalId":240167,"journal":{"name":"2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132196047","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