Proceedings of the 4th International Conference on Information Management & Machine Intelligence最新文献_第2页

Offer and Deal-Quality Prediction using Machine learning and Fuzzy approach: A Shark Tank India Case Study 使用机器学习和模糊方法的报价和交易质量预测:一个鲨鱼坦克印度案例研究

Proceedings of the 4th International Conference on Information Management & Machine Intelligence Pub Date : 2022-12-23 DOI: 10.1145/3590837.3590891

Atharva Parikh, Shreya Jain, P. Mahalle, G. Shinde

{"title":"Offer and Deal-Quality Prediction using Machine learning and Fuzzy approach: A Shark Tank India Case Study","authors":"Atharva Parikh, Shreya Jain, P. Mahalle, G. Shinde","doi":"10.1145/3590837.3590891","DOIUrl":"https://doi.org/10.1145/3590837.3590891","url":null,"abstract":"The Hindi-language television program Shark Tank India, which airs on Sony LIV, has changed the conversation in many Indian homes and raised awareness of entrepreneurship and start-ups. Shark Tank India depicts the background of each start-up and the business owners pitching their wholesome ideas to a panel of Sharks (Investors) who are entrepreneurs in various industries. Sharks then opt to invest in exchange for equity in the company (some percentage of ownership). Two of the major problems faced by startups before coming on the show is an understanding of what role each business factor plays in determining the proposition of offer by the sharks and the quality of deal done with or without negotiation with the sharks. To address this issue, we created a new dataset for Shark Tank India that contains essential features representing information about participating startups. Then we used this data to propose two ambient systems. The first one uses machine learning to predict whether investors will make an offer to the pitching team, with the Artificial Neural Network (ANN) model performing best with an F1 score of 87.09%, and the second one uses a fuzzy system consisting of 22 rules to categorize the quality of a deal after an investment is made.","PeriodicalId":112926,"journal":{"name":"Proceedings of the 4th International Conference on Information Management & Machine Intelligence","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134164883","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

Recent Advancement in Education System Using AR Tools: A New Perspective AR工具在教育系统中的最新进展:一个新的视角

Proceedings of the 4th International Conference on Information Management & Machine Intelligence Pub Date : 2022-12-23 DOI: 10.1145/3590837.3590869

Ratnesh Kashyap, Juhi Singh, Shweta Sinha

引用次数: 0

Bioinspired Model for Edge-based Task Scheduling Applications 基于边缘的任务调度应用程序的仿生模型

Proceedings of the 4th International Conference on Information Management & Machine Intelligence Pub Date : 2022-12-23 DOI: 10.1145/3590837.3590889

S. Nimkar, M. Khanapurkar

{"title":"Bioinspired Model for Edge-based Task Scheduling Applications","authors":"S. Nimkar, M. Khanapurkar","doi":"10.1145/3590837.3590889","DOIUrl":"https://doi.org/10.1145/3590837.3590889","url":null,"abstract":"Optimization of task scheduling for edge devices requires extensive analysis of task computational requirements & capacities of edge VirtOptimizingual Machines (VMs). Scheduling models are responsible for mapping edge tasks with these VMs for minimization of make-span, with higher deadline-hit-ratio, and lower computational complexity. To perform this task, a wide variety of bioinspired models are proposed by researchers, and most of them use static learning rates, which limits their task-to-edge mapping performance. Moreover, adaptive learning rate models are highly complex, which increases their convergence delays, thereby reducing scheduling efficiency under heterogeneous task types. To overcome these limitations, this text proposes design of an Improved & Adaptive Bioinspired Model for Edge-based Task Scheduling Applications, which uses League Championship Model (LCM). It optimizes its learning performance via an adaptive stochastic process. The model sets-up an initial learning rate for scheduling tasks to edge VMs, and then uses a Grey Wolf Optimizer (GWO) to continuously update learning rate for better mapping performance. The GWO Model uses low-complexity wolf behavioral functions in order to determine optimum learning rates for different VM & task types. This allows for faster convergence, and lower service delays when evaluated on standard scheduling datasets. The model was compared in terms of scheduling efficiency, make-span, computational complexity, and delay needed for scheduling, with various state-of-the-art models. It was observed that the proposed model outperformed them w.r.t. these evaluation metrics under most use cases, wherein it showcases 8.5% lower make-span, 1.5% higher efficiency, 5.9% lower computational complexity, and 8.3% lower computational delay, thereby making it useful for a wide variety of real-time use casesthey had developed.","PeriodicalId":112926,"journal":{"name":"Proceedings of the 4th International Conference on Information Management & Machine Intelligence","volume":"148 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115542884","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 Review on Path Planning Technique for Bio-Inspired Robot 仿生机器人路径规划技术综述

Proceedings of the 4th International Conference on Information Management & Machine Intelligence Pub Date : 2022-12-23 DOI: 10.1145/3590837.3590858

R. M, Ashok Kumar, Shah Fahad Saboon, Shreay Kumar, Yashwin Gowda Bp, Shivam Deo Prasad

引用次数: 0

Mental Health Classification on Social-Media: Systematic Review 社交媒体上的心理健康分类:系统回顾

Proceedings of the 4th International Conference on Information Management & Machine Intelligence Pub Date : 2022-12-23 DOI: 10.1145/3590837.3590946

Priya Mathur, Amit Kumar Gupta, A. Dadhich

引用次数: 0

Enhanced Edges Detection from Different Color Space 基于不同颜色空间的增强边缘检测

Proceedings of the 4th International Conference on Information Management & Machine Intelligence Pub Date : 2022-12-23 DOI: 10.1145/3590837.3590853

S. Sharma, Adarsh Kumar, U. Singh

引用次数: 0

Artificial intelligence-based indicators for ALGO trading strategy on the NSE derivatives 基于人工智能指标的NSE衍生品ALGO交易策略

Proceedings of the 4th International Conference on Information Management & Machine Intelligence Pub Date : 2022-12-23 DOI: 10.1145/3590837.3590875

Joyjit Patra, Mimo Patra, Subir Gupta

引用次数: 0

Text and Audio Framework for an Effective Mathematical Symbols’ Visualization for Blind Students 盲文学生有效数学符号可视化的文本与音频框架

Proceedings of the 4th International Conference on Information Management & Machine Intelligence Pub Date : 2022-12-23 DOI: 10.1145/3590837.3590933

Anshu Singla, Vandana Pushe

{"title":"Text and Audio Framework for an Effective Mathematical Symbols’ Visualization for Blind Students","authors":"Anshu Singla, Vandana Pushe","doi":"10.1145/3590837.3590933","DOIUrl":"https://doi.org/10.1145/3590837.3590933","url":null,"abstract":"There is no denying with the fact that the vision impaired candidates/blind candidates were allocated to explicit instructive settings depending on their impairment. India's schooling framework rebuilt in 2020 brought some major and crucial changes in the curriculum, including the absorption of a language of comprehensive training in approach drives. The instructive encounters of visually impaired/vision-weakened individuals, the elements that impacted these encounters and how these aided or blocked their future odds were the critical focal point of the review and execution of new methods on which this research is based. The blind students or the visually impaired are dependent on two senses, the touch sense and the auditory sense, for their academics and their daily activities. During Pandemic-2019, the importance of auditory sense becomes much more important than the touch sense for the visually impaired people. Online studies for blind students especially subjects like mathematics and science emerged as a big challenge for the society. The researchers need to find effective solution to teach blind students through audio and visual aids. This paper focus on the framework for the effective mathematical symbols visualisation and has been designed to assist students and the teaching staff in text as well as audio format.","PeriodicalId":112926,"journal":{"name":"Proceedings of the 4th International Conference on Information Management & Machine Intelligence","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130988206","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

Colour Image Cryptography using Chaotic Pixel Shuffling and 3D Logistic Diffusion 使用混沌像素变换和三维逻辑扩散的彩色图像密码

Proceedings of the 4th International Conference on Information Management & Machine Intelligence Pub Date : 2022-12-23 DOI: 10.1145/3590837.3590871

Renjith V. Ravi, S. Goyal, Sanjay Singla

{"title":"Colour Image Cryptography using Chaotic Pixel Shuffling and 3D Logistic Diffusion","authors":"Renjith V. Ravi, S. Goyal, Sanjay Singla","doi":"10.1145/3590837.3590871","DOIUrl":"https://doi.org/10.1145/3590837.3590871","url":null,"abstract":"All types of multimedia data, including digital images, audio, text, and video, are now easily accessible on the internet due to the phenomenal growth of internet services and wireless telecommunication systems, including mobile and computer systems, in order to achieve a specific degree of security, integrity, and secrecy as well as to prevent malicious access to the information. In contrast, for data storage and transmission, cryptographic procedures are necessary. This study presents brand-new, very effective colour image encryption and decryption algorithms that use diffusion and pixel scrambling. At first Zig-Zag permutation was used to scramble the data. Then, by concealing the statistical makeup of the pixels, the two-dimensional Lozi map is used to distort further the connection between neighbouring pixels in the original image. Furthermore, the diffusion in three colour channels is accomplished using a 3D logistic map. During the decryption process, the image pixels are again moved back to their original positions. The chaotic mapping technique encrypts images to reduce the correlation between encrypted and unencrypted versions. As described in this study, the tested and examined encryption algorithm on certain colour photos showed substantial security and authenticity to resist statistical and differential cyber attacks.","PeriodicalId":112926,"journal":{"name":"Proceedings of the 4th International Conference on Information Management & Machine Intelligence","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130504250","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

Classification and Localization of COVID-19 based on a Pneumonia Radiograph using a Deep Learning Approach 基于肺炎x线片的COVID-19分类和定位的深度学习方法

Proceedings of the 4th International Conference on Information Management & Machine Intelligence Pub Date : 2022-12-23 DOI: 10.1145/3590837.3590857

M. Bennet, S. Saranya, Dinesh Goyal, P. Dadheech, S. Balu, Sudhakar Sengan

{"title":"Classification and Localization of COVID-19 based on a Pneumonia Radiograph using a Deep Learning Approach","authors":"M. Bennet, S. Saranya, Dinesh Goyal, P. Dadheech, S. Balu, Sudhakar Sengan","doi":"10.1145/3590837.3590857","DOIUrl":"https://doi.org/10.1145/3590837.3590857","url":null,"abstract":"The world is battling the pandemic corona virus disease (COVID-19) now, and even after 2 years of the COVID-19 pandemic, this technology is still not reasonably advanced to tackle the battle against this virus most efficiently. The total number of COVID-19 cases worldwide surpassed 420 million, with 5.8 million deaths. COVID-19 infects a person with various symptoms, and one of the symptoms is pneumonia. A person suffering from pneumonia may or may not be carrying COVID-19. This research article aims to describe an X-radiation (X-ray) of patients with pneumonia and proposes other subjects who also have the corona virus. This system is based on Deep Learning (DL), and the Convolutional Neural Networks (CNN) method is applied. The work is done with additional help from the frameworks Tensorflow and Keras. Firstly, the images are loaded into the compiler, cleaned, and preprocessed accordingly. The next thing to come up with is setting up the Neural Network (NN) layer. The CNN layer is formed, and a particular Activation Function (AF), Rectified Linear Unit (ReLu), is applied. Finally, the model is trained, and a classification is done to determine whether the patient's X-ray is only for pneumonia or pneumonia + COVID-19. The paper's outcome has an accuracy of 96% to 98%.","PeriodicalId":112926,"journal":{"name":"Proceedings of the 4th International Conference on Information Management & Machine Intelligence","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125441563","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