2023 International Conference on Sustainable Computing and Smart Systems (ICSCSS)最新文献_第10页

Development of Decision Support System on Online Payment Failures using Ensemble Learning 基于集成学习的在线支付失败决策支持系统的开发

2023 International Conference on Sustainable Computing and Smart Systems (ICSCSS) Pub Date : 2023-06-14 DOI: 10.1109/ICSCSS57650.2023.10169602

Ch.Hemanth Kumar, S. Kishan, A. K. Ahmed

{"title":"Development of Decision Support System on Online Payment Failures using Ensemble Learning","authors":"Ch.Hemanth Kumar, S. Kishan, A. K. Ahmed","doi":"10.1109/ICSCSS57650.2023.10169602","DOIUrl":"https://doi.org/10.1109/ICSCSS57650.2023.10169602","url":null,"abstract":"Machine learning algorithms are becoming more significant in one’s daily lives, influencing a wide range of societal and industrial aspects. Machine learning is changing the living and work, from personalized recommendations to autonomous vehicles. With the increasing reliance on online transactions, the detection and prevention of payment failures in real-time has become a critical aspect of business operations. This study proposes an efficient ensemble model that employs various machine learning algorithms for accurate detection of payment failures. Multiple algorithms are compared and integrated using ensemble learning techniques to create a robust decision support system. The study identifies challenges faced in payment failure detection and prevention and presents the proposed system as a solution. Proposed experimental results demonstrate the effectiveness of the proposed system in achieving high accuracy in detecting payment failures, making it a valuable tool for businesses. The training of an efficient ensemble model that detects and prevents these problems in the present research uses a variety of machine learning algorithms. Furthermore, the use of ensemble learning techniques in the process of building a decision support system will make it more robust. This research compared various algorithms to integrate the best one and create the proposed system. Therefore, the proposed system works well for the accurate detection of payment failures, which is important for any business development.","PeriodicalId":217957,"journal":{"name":"2023 International Conference on Sustainable Computing and Smart Systems (ICSCSS)","volume":"203 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127649847","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

Comparative Analysis of FinFET and CMOS based Adiabatic ECRL Technique 基于FinFET和CMOS绝热ECRL技术的比较分析

2023 International Conference on Sustainable Computing and Smart Systems (ICSCSS) Pub Date : 2023-06-14 DOI: 10.1109/ICSCSS57650.2023.10169256

Gautam Rana, K. Sharma, Anjali Sharma

{"title":"Comparative Analysis of FinFET and CMOS based Adiabatic ECRL Technique","authors":"Gautam Rana, K. Sharma, Anjali Sharma","doi":"10.1109/ICSCSS57650.2023.10169256","DOIUrl":"https://doi.org/10.1109/ICSCSS57650.2023.10169256","url":null,"abstract":"Achieving low power consumption along with low delay for adiabatic logic circuits is challenging in CMOS technology. This study has presented an adiabatic Efficient Charge Recovery Logic (ECRL) technique based 2:1 MUX designed using FinFET 18 nm technology. A comparative analysis of the design has been performed with CMOS 2:1 MUX. Further parametric analysis of 2:1 MUX is performed in terms of average power dissipation, propagation delay, Power Delay Product (PDP), and Energy Delay Product (EDP) are presented in this work. All considered parameters have been analyzed for 0.5 V, 0.7 V, 0.9 V, and 1. 1V. The results show that the PDP of ECRL at 1.1V is $4.05times 10^{-15}$J, at 0.9 V is $0.27times 10^{-15}$J, at 0.7 V is $1.02times 10^{-15}$J, and at 0.5 V is $0.51times 10^{-15}$ J. While, the EDP at 1.1V is $0.15times 10^{-22}$ Js, at 0.9 Vis $0.01times 10^{-22}$ Js, at 0.7 Vis $0.03times 10^{-22}$ Js, at 0.5 V is $0.02times 10^{-22}$ J. The FinFET based 2:1 based ECRL is found to be energy efficient in contrast to CMOS based design. The ECRL technique base d2:1 MUX reported in this work may be used for biomedical applications in the future.","PeriodicalId":217957,"journal":{"name":"2023 International Conference on Sustainable Computing and Smart Systems (ICSCSS)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121385457","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 Novel Machine Learning Algorithm for Prostate Cancer Image Segmentation using mpMRI 一种新的mpMRI前列腺癌图像分割机器学习算法

2023 International Conference on Sustainable Computing and Smart Systems (ICSCSS) Pub Date : 2023-06-14 DOI: 10.1109/ICSCSS57650.2023.10169504

Tushar Dhar Shukla, K. Kalpana, Richa Gupta, D. Kalpanadevi, Md. Abul Ala Walid, K. Keshav Kumar

{"title":"A Novel Machine Learning Algorithm for Prostate Cancer Image Segmentation using mpMRI","authors":"Tushar Dhar Shukla, K. Kalpana, Richa Gupta, D. Kalpanadevi, Md. Abul Ala Walid, K. Keshav Kumar","doi":"10.1109/ICSCSS57650.2023.10169504","DOIUrl":"https://doi.org/10.1109/ICSCSS57650.2023.10169504","url":null,"abstract":"Recently, the advancements in technology and the changes in lifestyle behaviors of people leads to a sedentary routine of everyday habits. For this reason, numerous cancers have been developed and causes death for millions of people every year. Although, cancer is a deadly disease, early detection can help for survival. Especially for prostate cancer (PCa), early detection helps to cure the disease. Several researches have been done in medical image processing using Artificial Intelligence (AI) algorithms, yet accuracy and computational complexities limits the performance. With the intension of introducing a novel model for PCa detection from multi-parametric Magnetic Resonance Imaging (mpMRI), this study introduces an enhanced image segmentation model using the efficiency of Machine Learning (ML) algorithm together with Moth Flame Optimization (MFO) Algorithm to eradicate the previous issues. Generally, segmentation of an image is a partition of the image into multiple regions which enhances the classification performances. The major phases in this research includes 1. Data Pre-processing, 2. Feature Extraction, and finally,3. Segmentation. In data pre-processing, noises in the input images are eliminated using Gaussian filtering. The efficiency of MFO is employed to extract the optimal features from the images, and the extracted images are further subjected for U-Net segmentation. Moreover, the performance of the proposed model is validated through a comparative analysis over state-of the-art models in terms of DSC.","PeriodicalId":217957,"journal":{"name":"2023 International Conference on Sustainable Computing and Smart Systems (ICSCSS)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121461857","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

Automated Writing System using Arduino 基于Arduino的自动书写系统

2023 International Conference on Sustainable Computing and Smart Systems (ICSCSS) Pub Date : 2023-06-14 DOI: 10.1109/ICSCSS57650.2023.10169831

A. Choudhari, Sakshi Kohad, Needhi Deshmukh, Devyani Malode, Rahul Suryawanshi, J. Gawai

{"title":"Automated Writing System using Arduino","authors":"A. Choudhari, Sakshi Kohad, Needhi Deshmukh, Devyani Malode, Rahul Suryawanshi, J. Gawai","doi":"10.1109/ICSCSS57650.2023.10169831","DOIUrl":"https://doi.org/10.1109/ICSCSS57650.2023.10169831","url":null,"abstract":"Time is a commodity that must be managed properly and efficiently to enhance production. As the process becomes more complicated and time-consuming, automation becomes a critical tool for performance and long-term growth. Automation, often known as labor-saving technology, is a technology allowing an operation to be done with minimum or almost no human incursion. Automation control refers to the use of various control systems to operate types of equipment and machinery in factories, boilers, and heat treatment furnaces, the connection of telephone networks, management and stabilization of ships, aircraft, and various other applications with or without human intervention. Higher rates of production along with enhanced productivity are typically braced by the process of automation. Efficient material usage, reduced work spans, shorter manufacturing lead times, a better quality of production and improvised safety are some other grounds favoured by automated processes. This study aims to develop an automated machine that would assist people with disabilities to write. The main aim is to be able to create a machine that would write on behalf of humans with much precision, would be error-free and save time as well as human efforts. The automatic writing machine is powered by two motors that allow the mechanical arm to move in two dimensions. A writing machine is a highly versatile piece of equipment designed to meet a broad range of requirements, specifically for graphics and writing. The automatic typewriter uses two motors to move the robotic arm, and its performance is based on this research, which is to control the movement of the x and y axes of the pen using the stepper motors, using an Arduino Nano microcontroller. After the actuation, the servo motor is used to control the vertical movement, that is, to move the pin up and down along the z-axis. Inscape and G-code are used to generate the drawings for use.","PeriodicalId":217957,"journal":{"name":"2023 International Conference on Sustainable Computing and Smart Systems (ICSCSS)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128633441","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 Adaptive Hybrid Beamforming Technique for Analysis of Throughput, Blocking Probability, Transmission Power in 5G MIMO mmWave 5G MIMO毫米波吞吐量、阻塞概率、发射功率分析的自适应混合波束形成技术

2023 International Conference on Sustainable Computing and Smart Systems (ICSCSS) Pub Date : 2023-06-14 DOI: 10.1109/ICSCSS57650.2023.10169422

K. Srinivas, Bojja Sai Kiran, Thati Sathvika, Peram Kishore

{"title":"An Adaptive Hybrid Beamforming Technique for Analysis of Throughput, Blocking Probability, Transmission Power in 5G MIMO mmWave","authors":"K. Srinivas, Bojja Sai Kiran, Thati Sathvika, Peram Kishore","doi":"10.1109/ICSCSS57650.2023.10169422","DOIUrl":"https://doi.org/10.1109/ICSCSS57650.2023.10169422","url":null,"abstract":"The main purpose of designing broadband wireless network is to reduce the hardware complexity. This research study describes the effectiveness of an adaptable mixed analog-digital beamforming method in 5G MIMO mmWave broadband networks. The generated beams will be formed based on the traffic demands via ON-OFF operations of the antennas in vertical antenna array. This aids in offering active consumers with high data rate services. All the vertical antenna arrays consist of active radiating elements, which are arranged in a circular array configuration. The entire performance of the proposed approach is evaluated by executing the Monte Carlo simulations in MIMO configuration. The results demonstrate the downlink transmission power, blockage probability, and throughput of wireless cellular networks, which are all improved by the adaptive beamforming method. The proposed adaptive technique can decrease the total amount of actively radiated elements when compared to a fixed grid of beams. Both the transmitted energy and blockage probability can be decreased by altering the vertical antenna systems and maintaining the total number of antennas as constant.","PeriodicalId":217957,"journal":{"name":"2023 International Conference on Sustainable Computing and Smart Systems (ICSCSS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129396977","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

NCTFET Device for Low Power VLSI Application 用于低功耗VLSI的NCTFET器件

2023 International Conference on Sustainable Computing and Smart Systems (ICSCSS) Pub Date : 2023-06-14 DOI: 10.1109/ICSCSS57650.2023.10169217

Menda Lokesh Naidu, Manipatruni Vineet Patnaik, S. K. Sinha, S. Chander, Rekha Chaudhary

引用次数: 0

Assessment and Future Directions for Clustering Optimization in Cloud Computing 云计算中聚类优化的评估与未来方向

2023 International Conference on Sustainable Computing and Smart Systems (ICSCSS) Pub Date : 2023-06-14 DOI: 10.1109/ICSCSS57650.2023.10169790

Vishal Kumar, Annika Bajaj, Neha Singla, Nakul Singla, Aryan Grover

{"title":"Assessment and Future Directions for Clustering Optimization in Cloud Computing","authors":"Vishal Kumar, Annika Bajaj, Neha Singla, Nakul Singla, Aryan Grover","doi":"10.1109/ICSCSS57650.2023.10169790","DOIUrl":"https://doi.org/10.1109/ICSCSS57650.2023.10169790","url":null,"abstract":"The current cloud technology offers access to a sharable resource such as networks, storage servers, applications, and other services. The way businesses manage their data, save their files, and use their apps has been completely transformed by technology. Nonetheless, the effective and efficient use of hardware and software resources is essential to the success of cloud computing. In a cloud environment where several processes are executing simultaneously, task scheduling and virtual machine clustering become crucial to ensuring maximum performance. Efficient task scheduling methods enable the distribution of resources among various tasks in a way that maximizes overall throughput. To provide a more effective and scalable computing environment, virtual machines are grouped together in a virtual machine cluster. Metaheuristic techniques need to be introduced for effectiveness of TS optimization. By intelligently and effectively navigating the search area, these algorithms are utilized to find the best answers to challenging scheduling issues. A hybrid algorithm is one that combines the advantages of two or more different algorithms. A hybrid algorithm’s success depends on the thoughtful selection and blending of various algorithms and parameters. Several job scheduling strategies, popular cloud simulators will be presented and examine the outcomes in light of the important criteria in this study. In order to assist academics and practitioners in selecting the best algorithm for their unique needs, this study attempts to shed light on the advantages and disadvantages of various algorithms.","PeriodicalId":217957,"journal":{"name":"2023 International Conference on Sustainable Computing and Smart Systems (ICSCSS)","volume":"203 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115305350","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

Fake Review Detection using Naive Bayesian Classifier 基于朴素贝叶斯分类器的虚假评论检测

2023 International Conference on Sustainable Computing and Smart Systems (ICSCSS) Pub Date : 2023-06-14 DOI: 10.1109/ICSCSS57650.2023.10169838

P. Kalaivani, V.Dinesh Raj, R. Madhavan, A. P. Naveen Kumar

{"title":"Fake Review Detection using Naive Bayesian Classifier","authors":"P. Kalaivani, V.Dinesh Raj, R. Madhavan, A. P. Naveen Kumar","doi":"10.1109/ICSCSS57650.2023.10169838","DOIUrl":"https://doi.org/10.1109/ICSCSS57650.2023.10169838","url":null,"abstract":"The issue of fake reviews is becoming an increasingly prevalent one on the internet. The purpose of these reviews is to deliberately deceive potential customers and influence their purchasing decisions. Businesses and customers alike are looking for ways to spot and filter out these fake reviews as a result. The Naive Bayes algorithm is one effective method for identifying fake reviews. A well-known machine learning algorithm for classification tasks is Naive Bayes. It is based on the probability theorem of Bayes, which enables us to determine the probability of an event with some evidence. The Naive Bayes algorithm can be trained on a dataset of reviews that are known to be real or fake in the context of fake reviews. The characteristics of genuine and fake reviews are then learned with the algorithm by utilizing this training data. After the algorithm has been trained, it can use the characteristics of new reviews to determine whether they are genuine or fake. The fact that Naive Bayes is a relatively straightforward algorithm that can be trained quickly and easily is one advantage of using it to detect fake reviews. Additionally, it works well with text data, which is the format used by the majority of reviews. Having said that, it’s critical to keep in mind that Naive Bayes isn’t perfect and may not be able to spot all fake reviews. Cleaning and normalizing data, dealing with missing data, and dealing with outliers are all potential obstacles in data pre-processing.","PeriodicalId":217957,"journal":{"name":"2023 International Conference on Sustainable Computing and Smart Systems (ICSCSS)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114440130","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

Data Mining in Healthcare using Machine Learning Techniques 使用机器学习技术的医疗保健数据挖掘

2023 International Conference on Sustainable Computing and Smart Systems (ICSCSS) Pub Date : 2023-06-14 DOI: 10.1109/ICSCSS57650.2023.10169802

Honey Goel, Deepak Kumar

{"title":"Data Mining in Healthcare using Machine Learning Techniques","authors":"Honey Goel, Deepak Kumar","doi":"10.1109/ICSCSS57650.2023.10169802","DOIUrl":"https://doi.org/10.1109/ICSCSS57650.2023.10169802","url":null,"abstract":"Classification techniques have become increasingly important in healthcare due to the need for accurate and efficient disease diagnosis, treatment planning, and patient care. Supervised learning algorithms, such as decision trees, logistic regression, and support vector machines, are used for disease diagnosis, predicting patient outcomes, and identifying potential risk factors. Classification techniques are also used in image recognition and analysis, such as in radiology and pathology. Classification is a supervised learning technique used to predict the class or category of an instance based on the given set of attributes. This research study explores the use of classification techniques in data mining for healthcare applications. The goal of this study is to apply classification algorithms such as Naive Bayes, Logistic Regression and Random Forest to healthcare datasets and evaluate their performance. The datasets used in this study include patient information such as demographics, medical history, and diagnosis. The findings suggest that the classification techniques can be effective in data mining for healthcare applications, enabling healthcare professionals to make more informed decisions based on patient data.","PeriodicalId":217957,"journal":{"name":"2023 International Conference on Sustainable Computing and Smart Systems (ICSCSS)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114447884","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

CNTFET-based Multiplexer Unit using INDEP Method 使用INDEP方法的基于cntfet的多路复用器单元

2023 International Conference on Sustainable Computing and Smart Systems (ICSCSS) Pub Date : 2023-06-14 DOI: 10.1109/ICSCSS57650.2023.10169240

M. Maqbool, S. Haq, V.K. Sharma

{"title":"CNTFET-based Multiplexer Unit using INDEP Method","authors":"M. Maqbool, S. Haq, V.K. Sharma","doi":"10.1109/ICSCSS57650.2023.10169240","DOIUrl":"https://doi.org/10.1109/ICSCSS57650.2023.10169240","url":null,"abstract":"The integration of digital circuits and the scaling down of complementary metal oxide semiconductor (CMOS) technology are closely related. As CMOS feature size continues to shrink, it eventually reaches the nanoscale region, which has raised the effects like Short Channel Effect (SCE), leakage power, and interconnects delay. Therefore, to overcome these limits and improve the efficiency of digital circuits, researchers are looking into other nanoscale technologies that can be used in upcoming technological advancements. Due to the excellent properties, Carbon Nanotube Field Effect Transistor (CNTFET) is going to use in the replacement of CMOS technology. In the current study, a CNTFET-based multiplexer using input dependent (INDEP) leakage reduction technique is proposed for a 32nm technology node. In this work, a comparative study of conventional and proposed INDEP-based multiplexers is carried out for power consumption, delay, and power delay product (PDP). It is observed that the proposed CNTFET-based multiplexer using the INDEP method is energy efficient and leads to significant improvement in leakage power and PDP compared to the conventional architecture.","PeriodicalId":217957,"journal":{"name":"2023 International Conference on Sustainable Computing and Smart Systems (ICSCSS)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125641467","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