Proceedings of the 4th International Conference on Information Management & Machine Intelligence最新文献_第8页

Forecasting Cryptocurrency Prices using Sequential and Time Series Models 使用顺序和时间序列模型预测加密货币价格

Proceedings of the 4th International Conference on Information Management & Machine Intelligence Pub Date : 2022-12-23 DOI: 10.1145/3590837.3590928

S. Das Gupta, Teja Kolla, R. Yadav, Mamta Arora, Mrinal Pandey

{"title":"Forecasting Cryptocurrency Prices using Sequential and Time Series Models","authors":"S. Das Gupta, Teja Kolla, R. Yadav, Mamta Arora, Mrinal Pandey","doi":"10.1145/3590837.3590928","DOIUrl":"https://doi.org/10.1145/3590837.3590928","url":null,"abstract":"The world saw a recent hype of terms, cryptocurrency, and digital assets. It was the subject of discussion. Almost everyone was fascinated by this not-so-new concept due to its numerous benefits. Those who dived deep into this area found the underlying technology that made it all possible, i.e., blockchain. This technology makes exchanges secure, recognizable, straightforward, and immutable. The most interesting aspect of blockchain is that it is decentralized, meaning it cannot be controlled by a single entity or organization which makes it more transparent. Due to these facilities, many organizations are looking for different ways to incorporate this technology into their domains. Cryptocurrency paved the way for a new form of payment system where people are no longer required to rely on third parties to ensure a secure financial transaction. Over the last decade, the field of cryptocurrency has grown at an exponential rate, with the most rapid progress coming in the last few years as a growing number of businesses worldwide have recognized the value of owning digital assets. Although having all the functionalities that work in favor of the people, the fundamental challenge to cryptographic money is its extreme volatility and implausibility. Cryptocurrency prices cannot be determined with the same degree of certainty that the stock market price can be. Therefore, this paper aims to develop a model which uses deep learning techniques that can be used to accurately predict the variations in the cryptocurrency price. Deep learning techniques such as Long Short-Term Memory, Gated Recurrent Unit, and the time series model Autoregressive Integrated Moving Average have been presented in this research. The efficacy of these models is evaluated by various losses such as Root Mean Square Error, Mean Squared Error, and Mean Absolute Error.","PeriodicalId":112926,"journal":{"name":"Proceedings of the 4th International Conference on Information Management & Machine Intelligence","volume":"27 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":"120963696","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

Nature-Inspired Load Balancing Approach in Cloud Computing Environment for Smart Healthcare 智能医疗保健云计算环境中基于自然的负载平衡方法

Proceedings of the 4th International Conference on Information Management & Machine Intelligence Pub Date : 2022-12-23 DOI: 10.1145/3590837.3590943

Navneet Kumar Rajpoot, Prabhdeep Singh, B. Pant

{"title":"Nature-Inspired Load Balancing Approach in Cloud Computing Environment for Smart Healthcare","authors":"Navneet Kumar Rajpoot, Prabhdeep Singh, B. Pant","doi":"10.1145/3590837.3590943","DOIUrl":"https://doi.org/10.1145/3590837.3590943","url":null,"abstract":"The development of a fast-response, a smart healthcare system that makes use of fog computing and the internet of things is of paramount importance at present time. Managing the ever-increasing load on fog nodes can be especially challenging in dynamic and diverse fog networks due to the high potential for overhead. As the number and variety of IoT-based devices grow, so ensure their processing requirements, and this is where fog computing comes in. The use of sensor-based technologies helps intelligent medical services operate, as well as the system's ability to automatically gather and process data can help to accelerate the entire platform's performance. The research formulated here introduces a novel framework for smart health care, in which a set of procedures are carried out with the primary goal of decreasing delay and performance issues. The Ant Colony Optimization Technique is a nature-inspired technique utilized to improve system efficiency by balancing loads, decreasing response times, and minimizing delay. In this research, we have proposed an approach for fog-assisted smart healthcare systems that is superior to the state-of-the-art in all of these important metrics: latency, response time, overall system accuracy, and system stability.","PeriodicalId":112926,"journal":{"name":"Proceedings of the 4th International Conference on Information Management & Machine Intelligence","volume":"42 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":"124899811","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

Conglomeration of fin-tech and block chain for greater financial inclusion - Systematic review analysis 金融科技与区块链融合促进普惠金融——系统回顾分析

Proceedings of the 4th International Conference on Information Management & Machine Intelligence Pub Date : 2022-12-23 DOI: 10.1145/3590837.3590932

Sakthirama Vadivelu

{"title":"Conglomeration of fin-tech and block chain for greater financial inclusion - Systematic review analysis","authors":"Sakthirama Vadivelu","doi":"10.1145/3590837.3590932","DOIUrl":"https://doi.org/10.1145/3590837.3590932","url":null,"abstract":"To create a more equitable society, financial services should be available and accessible to most of the nation's population. Extensive research on the existing literature shows that Fintech and Blockchain are the prime sectors that could bridge the gap and improve financial inclusion in the nation. The primary objective of the study is to understand the prospects of financial inclusion and how blockchain and fintech can help achieve that. The specific objectives include to understand the architecture and benefits of Blockchain and Fintech through the study on literature, to establish a framework to bring the blockchain infrastructure to financial inclusion and determine the factors that need to be improved for greater financial inclusion in rural areas. The study found the architecture and benefits based on existing research and establish a framework to bring the blockchain infrastructure's use of financial inclusion. The gap in the research is that the study is perceptive and no definite conclusion has been reached from the past studies. Based on the research analysis, common factors that were related to financial inclusion has been determined and considered for review analysis. The result findings of the study such as major challenges of the technology interventions of blockchain and fintech technologies could be used and offer recommendation for greater financial inclusion.","PeriodicalId":112926,"journal":{"name":"Proceedings of the 4th International Conference on Information Management & Machine Intelligence","volume":"11 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":"124740044","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

Monuments Identification using Satellite Images: A CNN based approach 使用卫星图像识别古迹:基于CNN的方法

Proceedings of the 4th International Conference on Information Management & Machine Intelligence Pub Date : 2022-12-23 DOI: 10.1145/3590837.3590865

Preet Jadhav, K. Wanjale, A. Chitre, Vedmani Vaidya

{"title":"Monuments Identification using Satellite Images: A CNN based approach","authors":"Preet Jadhav, K. Wanjale, A. Chitre, Vedmani Vaidya","doi":"10.1145/3590837.3590865","DOIUrl":"https://doi.org/10.1145/3590837.3590865","url":null,"abstract":"The significant rise in the amount of satellite images that have become available in recent years makes large-scale analysis of this data difficult. To make meaningful inferences from such images, one must have a thorough comprehension of the information they convey. Deep learning advances recently make it possible to train powerful machine learning models that can recognise several objects in a shot regardless of their attributes or distinct points of view. In this study, it is investigated if it's possible to identify monuments in satellite pictures using deep learning models. More specifically, the TensorFlow and Keras packages are used to build a model based on Indian monuments. Using Google Colab, the VGG16 model is trained on a variety of offline and online images. In order to enhance the performance of the model, the data augmentation technique is also used. Overall accuracy for VGG16 is 100 percent, which is extremely good. With the help of data augmentation on the model, a marginal improvement in accuracy is achieved. Lastly, this study's findings show that deep learning can be used to train a model, resulting in quite good outcomes even when trained on small and low-quality data sets.","PeriodicalId":112926,"journal":{"name":"Proceedings of the 4th International Conference on Information Management & Machine Intelligence","volume":"43 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":"128543887","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

Making a long video short: A Systematic Review 制作长视频短片:系统性回顾

Proceedings of the 4th International Conference on Information Management & Machine Intelligence Pub Date : 2022-12-23 DOI: 10.1145/3590837.3590863

Shikha Sharma, Dinesh Goyal

引用次数: 1

Fusion Techniques in Neural Network Model for Image Captioning 图像标注神经网络模型的融合技术

Proceedings of the 4th International Conference on Information Management & Machine Intelligence Pub Date : 2022-12-23 DOI: 10.1145/3590837.3590929

V. P. Saxena, Christabell Fredrick

引用次数: 0

Performance Analysis of Various on Demand Multipath Routing Protocols 各种随需应变多路径路由协议的性能分析

Proceedings of the 4th International Conference on Information Management & Machine Intelligence Pub Date : 2022-12-23 DOI: 10.1145/3590837.3590854

Dinesh Goyal, Kalu Ram Yadav

{"title":"Performance Analysis of Various on Demand Multipath Routing Protocols","authors":"Dinesh Goyal, Kalu Ram Yadav","doi":"10.1145/3590837.3590854","DOIUrl":"https://doi.org/10.1145/3590837.3590854","url":null,"abstract":"MANET is a network of self-organized mobile nodes whose topology changes dynamically. There is no pre existing infrastructure is available for network setup. Nodes in MANET are mobile in nature which acts as a router as well as host. For transmitting the data and forwarding it to the desire destination MANET use multi-hop communication to transmitting the data if nodes are not in direct communication range. MANET is self configuring in nature and nodes are also work in cooperative manner to meet the performance requirements. Many on-demand multipath routing protocols have been developed in recent years, with the designers claiming that their protocol has the greatest performance. We have been done on comparison and evaluation of existing three multipath routing (SMR, ROAM and MP-DSR) algorithms using NS2 (Network Simulator 2). This paper presents performance evaluations of SMR,ROAM and MP-DSR multipath routing protocols using NS2.Performance is analyzed on the average delay and packet delivery ratio metrics . For performance comparison we consider the network of 25, 50 and 100 nodes that are dispersed at random around the region of 800mX800m. Other than MP-DSR and SMR, simulation findings indicate that the ROAM protocol performs better in terms of average end-to-end delay. Result analysis also demonstrates that ROAM is also performing better in terms of PDR.","PeriodicalId":112926,"journal":{"name":"Proceedings of the 4th International Conference on Information Management & Machine Intelligence","volume":"36 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":"129047410","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 Machine Learning Model for Disease Prediction and Remote Patient Monitoring 疾病预测和远程病人监测的机器学习模型

Proceedings of the 4th International Conference on Information Management & Machine Intelligence Pub Date : 2022-12-23 DOI: 10.1145/3590837.3590844

K. Naik, B. Garg

{"title":"A Machine Learning Model for Disease Prediction and Remote Patient Monitoring","authors":"K. Naik, B. Garg","doi":"10.1145/3590837.3590844","DOIUrl":"https://doi.org/10.1145/3590837.3590844","url":null,"abstract":"People's health reports, including diagnostic information and medical prescriptions, are delivered in the form of test-based case notes, making it impossible to determine a person's prior health issues or medications taken until he or she returns to the hospital later on. Storing all of a person's health information in the cloud as a soft copy, on the other hand, alleviates this issue. To accomplish this, each and every hospital, dispensary, and laboratory must have an internet connection for the registration of patient data. A unique Health Id will identify each patient, and all of the patient's data will be stored in the cloud, where the specific patient can only access it. In order to prevent and treat illness, it is critical to perform an accurate and timely analysis on any health-related problem. The ability to diagnose disease by obtaining all information from a linked Health ID combined with Machine Learning techniques will improve the system's ability to detect diseases. We believe that our diagnostic model can operate like a doctor in the earlier diagnosis of this disease, allowing for timely treatment and the preservation of life.","PeriodicalId":112926,"journal":{"name":"Proceedings of the 4th International Conference on Information Management & Machine Intelligence","volume":"64 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":"126552466","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 Effect of Stacked CNN for Network Intrusion Detection System 堆叠CNN对网络入侵检测系统的影响

Proceedings of the 4th International Conference on Information Management & Machine Intelligence Pub Date : 2022-12-23 DOI: 10.1145/3590837.3590901

Pankaj Rahi, Monika Dandotiya, A. Anushya, A. Khunteta, Pankaj Agarwal

{"title":"An Effect of Stacked CNN for Network Intrusion Detection System","authors":"Pankaj Rahi, Monika Dandotiya, A. Anushya, A. Khunteta, Pankaj Agarwal","doi":"10.1145/3590837.3590901","DOIUrl":"https://doi.org/10.1145/3590837.3590901","url":null,"abstract":"The Intrusion Detection System (IDS) is a vital component of network security since it recognizes & inhibits hostile behavior. Because of the dynamic and time-varying nature of the network environment, network intrusion data are drowned out by a big number of normal samples, resulting in inadequate samples for model training & detection outcomes with a high percentage of false positives. An ID (Intrusion Detection) approach based on stacked Convolutional Neural Networks is discussed in this work to solve the issue of data imbalance. Modern network security requires more than conventional firewalls & data encryption technologies, which are no longer capable of meeting the demands of modern network security. It has as a consequence been advocated to use IDSs to cope with network threats. Recent mainstream ID methods are helped by Machine Learning and Deep Learning; however, they suffer from poor detection rates and the requirement for considerable feature engineering, which makes them less effective. This research presents DLNID (Deep Learning Model for Network Intrusion Detection) utilizing stacked CNN to improve detection accuracy. The experimental results demonstrate that this model's accuracy & F1- score by CNN on NSL-KDD and UNS are better than CNN.","PeriodicalId":112926,"journal":{"name":"Proceedings of the 4th International Conference on Information Management & Machine Intelligence","volume":"15 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":"117227965","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

Intrusion Detection System Based Ameliorated Technique of Pattern Matching 基于改进模式匹配技术的入侵检测系统

Proceedings of the 4th International Conference on Information Management & Machine Intelligence Pub Date : 2022-12-23 DOI: 10.1145/3590837.3590947

Akshat Tanwar, Priyank Sharma, Anjali Pandey, Sumit Kumar

{"title":"Intrusion Detection System Based Ameliorated Technique of Pattern Matching","authors":"Akshat Tanwar, Priyank Sharma, Anjali Pandey, Sumit Kumar","doi":"10.1145/3590837.3590947","DOIUrl":"https://doi.org/10.1145/3590837.3590947","url":null,"abstract":"Intrusion Detection System is a set of programs that overlook both internal & external network operations. These IDS disinter skeptic patterns that expose a system attack from external variables (Hackers, Organizations, Government etc). The main function of IDS is to monitor a system and uncover malicious activity by generating alerts. These alerts or warnings get reported to a security operations center (SOC) analyst or incident responder who then takes appropriate action to rectify the threats. It enhances stability, surveillance, integrity, etc. of the user's system by protecting the user from network infiltrations. The more intrusions IDS detects, the better the detection rate is. IDS works on the multi-pattern matching method which can compete with the line–speed of pocket transfer. This method efficiently handles a range of patterns with variable pattern lengths. This article presents an approach that ventures to exceed efficacy in comparison to earlier reports. It also indicates that the algorithm developed is inferior as the number of comparisons is less which leads to better time complexity. In particular, this algorithm attains a refined and uniform graph for all alphabet sizes.","PeriodicalId":112926,"journal":{"name":"Proceedings of the 4th International Conference on Information Management & Machine Intelligence","volume":"29 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":"134470392","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