2021 International Conference on Computational Performance Evaluation (ComPE)最新文献_第4页

Simulation of Household Appliances with Energy Disaggrigation using Deep Learning Technique 基于深度学习技术的家用电器能量分解仿真

2021 International Conference on Computational Performance Evaluation (ComPE) Pub Date : 2021-12-01 DOI: 10.1109/ComPE53109.2021.9752375

B. Nandish, V. Pushparajesh

引用次数: 2

An Intrinsic Review on Securitization using Blockchain b区块链资产证券化的内在回顾

2021 International Conference on Computational Performance Evaluation (ComPE) Pub Date : 2021-12-01 DOI: 10.1109/ComPE53109.2021.9752154

Varun Gupta, Saheb Gabadia, Menita Agarwal, Krishna Samdani

{"title":"An Intrinsic Review on Securitization using Blockchain","authors":"Varun Gupta, Saheb Gabadia, Menita Agarwal, Krishna Samdani","doi":"10.1109/ComPE53109.2021.9752154","DOIUrl":"https://doi.org/10.1109/ComPE53109.2021.9752154","url":null,"abstract":"This paper presents a blockchain-based Securitization Model, which simplifies the transactional methods. This paper elaborates upon integrating the components of Securitization with Distributed Ledger Technology (DTL) and provides a process flow of transactions occurring. The process which once led to the 2008 Financial Crisis has been improved in terms of security and reliability. Using this revolutionizing model, securities, which were once considered opaque & risky, will now be informative and gauged accordingly, thereby smoothening the process of transforming non-tradable assets into tradable securities. This paper highlights how blockchain features, i.e., smart contracts, decentralization, authentication & immutability, will increase efficiency. Furthermore, the paper explores boons of the amalgamation, i.e., reduced risk, enhanced transparency, lower costs, proficient processes and robust authentication without compromising information asymmetry, high transactional costs and nebulous portfolio rating. The goal of this paper is to portray how the integration will augment the cardinal Securitization process.","PeriodicalId":211704,"journal":{"name":"2021 International Conference on Computational Performance Evaluation (ComPE)","volume":"121 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129407880","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

Analyzing Security Approaches for Threats, Vulnerabilities, and attacks in an IoT Environment 分析物联网环境中威胁、漏洞和攻击的安全方法

2021 International Conference on Computational Performance Evaluation (ComPE) Pub Date : 2021-12-01 DOI: 10.1109/ComPE53109.2021.9752151

Himani Tyagi, Rajendra Kumar

引用次数: 0

A Novel Transfer Learning Ensemble based Deep Neural Network for Plant Disease Detection 基于迁移学习集成的植物病害检测深度神经网络

2021 International Conference on Computational Performance Evaluation (ComPE) Pub Date : 2021-12-01 DOI: 10.1109/ComPE53109.2021.9751910

R. Lakshmi, N. Savarimuthu

引用次数: 0

Artificial Intelligence (AI) Prediction of Atari Game Strategy by using Reinforcement Learning Algorithms 基于强化学习算法的人工智能(AI) Atari游戏策略预测

2021 International Conference on Computational Performance Evaluation (ComPE) Pub Date : 2021-12-01 DOI: 10.1109/ComPE53109.2021.9752304

S. U, Punitha S, Girish Perakam, Vishnu Priya Palukuru, Jaswanth Varma Raghavaraju, Praveena R

{"title":"Artificial Intelligence (AI) Prediction of Atari Game Strategy by using Reinforcement Learning Algorithms","authors":"S. U, Punitha S, Girish Perakam, Vishnu Priya Palukuru, Jaswanth Varma Raghavaraju, Praveena R","doi":"10.1109/ComPE53109.2021.9752304","DOIUrl":"https://doi.org/10.1109/ComPE53109.2021.9752304","url":null,"abstract":"Video games produce reactionary, resilient, or clever behavior, mostly on non-player characters (NPCs), who resemble Artificial Intelligence (AI). Since the launch of video games in the 1950s AI has become an important component. AI is a separate subfield in computer games that varies from AI. Instead of learning the machine or determining it is used to enhance the player experience. The concept of an AI opponent was popularized during the golden age of arcade videogames in the form of graded levels of difficulty, distinct action styles and events based on the player’s involvement. Modern games also apply current strategies such as path-finding and decision-making bodies to control NPCs’ actions. AI is used often in mechanisms, such as data mining and process content creation, which is not immediately accessible to the user. We were creating an AI Organization to use the same hyper parameter to learn how to play a variety of Atari games. Over time it became a more theory-oriented project, in which we discussed numerous ways to use our methods for deep learning, and Put them on a game, Pong, rather than a game package.","PeriodicalId":211704,"journal":{"name":"2021 International Conference on Computational Performance Evaluation (ComPE)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126782799","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

Performance Analysis of Dual Axis Solar Tracker 双轴太阳能跟踪器性能分析

2021 International Conference on Computational Performance Evaluation (ComPE) Pub Date : 2021-12-01 DOI: 10.1109/ComPE53109.2021.9751972

Sapam Rhison Singh, Piyali Das

引用次数: 0

Examining the Role of Social Media in Higher Education through SWOT Analysis 运用SWOT分析法考察社交媒体在高等教育中的作用

2021 International Conference on Computational Performance Evaluation (ComPE) Pub Date : 2021-12-01 DOI: 10.1109/ComPE53109.2021.9752150

Shikha Gupta, Harikishni Nain

引用次数: 5

Data Science: Relationship with big data, data driven predictions and machine learning 数据科学:与大数据、数据驱动预测和机器学习的关系

2021 International Conference on Computational Performance Evaluation (ComPE) Pub Date : 2021-12-01 DOI: 10.1109/ComPE53109.2021.9752435

Akansha Singh, Nidhi Saxena

{"title":"Data Science: Relationship with big data, data driven predictions and machine learning","authors":"Akansha Singh, Nidhi Saxena","doi":"10.1109/ComPE53109.2021.9752435","DOIUrl":"https://doi.org/10.1109/ComPE53109.2021.9752435","url":null,"abstract":"We are living in the age of big data, advanced analytics, and data science. Companies these days have realized the importance of data management and therefore are recruiting staff as data scientists and academics institutions and publications have accepted data science as one the trending career options. The current era of IT industry is evolving very rapidly. With the growing requirement of IT sector the demand of each sub-unit is also developing with huge pace. Introduction of distributed computing had resolved the issues of the industry but now analyzing the growth pace the requirements will be drastically challenging for the industry, organisations as well as society. If we want this science to serve and promote business effectively, it is important for us (i) to recognize its associations to other important technologies and concepts, and (ii) to initiate the classify the fundamental ideologies underlying data science. This paper has a systematic overview on data science, its application and its interactions to other important related perceptions. The combination of data science and distributed computing can resolve many issues of the industry.","PeriodicalId":211704,"journal":{"name":"2021 International Conference on Computational Performance Evaluation (ComPE)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125240501","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 Efficient Model for Detection and Classification of Internal Eye Diseases using Deep Learning 一种基于深度学习的内眼疾病检测与分类的高效模型

2021 International Conference on Computational Performance Evaluation (ComPE) Pub Date : 2021-12-01 DOI: 10.1109/ComPE53109.2021.9752188

Richa Gupta, V. Tripathi, A. Gupta

{"title":"An Efficient Model for Detection and Classification of Internal Eye Diseases using Deep Learning","authors":"Richa Gupta, V. Tripathi, A. Gupta","doi":"10.1109/ComPE53109.2021.9752188","DOIUrl":"https://doi.org/10.1109/ComPE53109.2021.9752188","url":null,"abstract":"Natural eye is influenced by the distinctive eye illnesses some of them are great cause of vision loss. Many Artificial Intelligence (AI) approaches have been proposed for the identification of such diseases. The proposed method intends to plan an AI based automated network for eye illness identification and grouping to help the ophthalmologists all the more viably distinguishing and ordering of internal eye diseases like Choroid Neovascularisation (CNV), Diabetic Macular Edema (DME) and Drusen by utilizing the Optical Coherence Tomography (OCT) pictures portraying various tissues. The procedure utilized for planning this framework includes diverse deep learning convolutional neural organization (CNN) models. The proposed methodology is called efficient because it is performed on a large scale data-set which has four classes and improves the performance to a great level. The best picture subtitling model is chosen after execution investigation by looking at different picture inscribing frameworks for helping ophthalmologists to identify and order eye illnesses. The proposed methodology achieves the performance to a great level, 83.66% of accuracy for the test images when the data-set is divide in the format of 70-30 ratio.","PeriodicalId":211704,"journal":{"name":"2021 International Conference on Computational Performance Evaluation (ComPE)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122538070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Performance Evaluation of Speed Behaviour of Fuzzy-PI Operated BLDC Motor Drive 模糊pi操作无刷直流电机驱动速度特性的性能评价

2021 International Conference on Computational Performance Evaluation (ComPE) Pub Date : 2021-12-01 DOI: 10.1109/ComPE53109.2021.9752453

Samiksha Chintawar, Snehal Ghodke, V. Khatavkar, Utkarsh Alset, Hrishikesh Mehta

{"title":"Performance Evaluation of Speed Behaviour of Fuzzy-PI Operated BLDC Motor Drive","authors":"Samiksha Chintawar, Snehal Ghodke, V. Khatavkar, Utkarsh Alset, Hrishikesh Mehta","doi":"10.1109/ComPE53109.2021.9752453","DOIUrl":"https://doi.org/10.1109/ComPE53109.2021.9752453","url":null,"abstract":"In many applications, brushless direct current (BLDC) motor drives use fuzzy logic controllers for speed control owing to their advantages like auto-tuning of parameters, wide operational range, low computational requirements and low cost. However, the effect of different rulesets on the transient and steady-state speed Behaviour of BLDC motors has not been widely covered in the literature. The contribution of this paper includes speed characteristics of the triangular membership function (trimf) based fuzzy proportional-integral (FPI) controller is evaluated. Rulesets of 3 × 3, 5 × 5 and 7 × 7 formed using 3, 5 and 7 trimfs are compared for their Behaviour and time required for performing computations for speed benchmark of the BLDC motor used in comprehensive electric vehicle (EV) applications. The fuzzy logic control algorithm is implemented by means of Mathworks’ Fuzzy Logic Tool-set. The results are substantiated using MATLAB/Simulink. It is thereby concluded that increasing the number of membership functions improves the dynamic and steady-state behaviour of the BLDC motor.","PeriodicalId":211704,"journal":{"name":"2021 International Conference on Computational Performance Evaluation (ComPE)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131481353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2