International Journal of Intelligent Networks最新文献_第10页

Machine-type communications in NOMA-based terahertz wireless networks 基于noma的太赫兹无线网络中的机器类型通信

International Journal of Intelligent Networks Pub Date : 2022-01-01 DOI: 10.1016/j.ijin.2022.04.002

Saifur Rahman Sabuj , Maisha Rubaiat , Mehzabien Iqbal , Monica Mobashera , Afrida Malik , Imtiaz Ahmed , Mohammad Abdul Matin

{"title":"Machine-type communications in NOMA-based terahertz wireless networks","authors":"Saifur Rahman Sabuj , Maisha Rubaiat , Mehzabien Iqbal , Monica Mobashera , Afrida Malik , Imtiaz Ahmed , Mohammad Abdul Matin","doi":"10.1016/j.ijin.2022.04.002","DOIUrl":"10.1016/j.ijin.2022.04.002","url":null,"abstract":"<div><p>Terahertz (THz) band is one of the most promising aspects of wireless communication systems because of its potential to meet the growing demands for the envisioned next-generation of cellular communications. THz band connectivity can alleviate bandwidth shortages and transmit power constraints using multiple-input multiple-output (MIMO) systems. To obtain better throughput and enhanced spectral efficiency, non-orthogonal multiple access (NOMA) configuration can be incorporated into MIMO systems, as NOMA uses non-orthogonal resource allocation by assigning the same carrier frequency to multiple devices in the power domain. In this paper, we focus on 2 × 1 MIMO-NOMA and cooperative 2 × 1 MIMO-NOMA systems for THz spectrum in the downlink transmission. In order to evaluate the effectiveness of the proposed system architecture, we derive accurate data rate, transmission latency, and reliability expressions for 2 × 1 MIMO-NOMA system consists of critical and non-critical devices by leveraging finite block length theory. Moreover, we derive the closed-form expressions for power splitting coefficients, data rate, transmission latency, and reliability for the considered cooperative 2 × 1 MIMO-NOMA system. Extensive numerical results are presented to validate the feasibility of the proposed 2 × 1 MIMO-NOMA as well as the cooperative 2 × 1 MIMO-NOMA systems in the THz band.</p></div>","PeriodicalId":100702,"journal":{"name":"International Journal of Intelligent Networks","volume":"3 ","pages":"Pages 31-47"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666603022000045/pdfft?md5=ec5bae3460f4ee4ff6560e93d34c5dc8&pid=1-s2.0-S2666603022000045-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82178354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Significance of machine learning in healthcare: Features, pillars and applications 机器学习在医疗保健中的意义:特征、支柱和应用

International Journal of Intelligent Networks Pub Date : 2022-01-01 DOI: 10.1016/j.ijin.2022.05.002

Mohd Javaid , Abid Haleem , Ravi Pratap Singh , Rajiv Suman , Shanay Rab

{"title":"Significance of machine learning in healthcare: Features, pillars and applications","authors":"Mohd Javaid , Abid Haleem , Ravi Pratap Singh , Rajiv Suman , Shanay Rab","doi":"10.1016/j.ijin.2022.05.002","DOIUrl":"10.1016/j.ijin.2022.05.002","url":null,"abstract":"<div><p>Machine Learning (ML) applications are making a considerable impact on healthcare. ML is a subtype of Artificial Intelligence (AI) technology that aims to improve the speed and accuracy of physicians' work. Countries are currently dealing with an overburdened healthcare system with a shortage of skilled physicians, where AI provides a big hope. The healthcare data can be used gainfully to identify the optimal trial sample, collect more data points, assess ongoing data from trial participants, and eliminate data-based errors. ML-based techniques assist in detecting early indicators of an epidemic or pandemic. This algorithm examines satellite data, news and social media reports, and even video sources to determine whether the sickness will become out of control. Using ML for healthcare can open up a world of possibilities in this field. It frees up healthcare providers' time to focus on patient care rather than searching or entering information. This paper studies ML and its need in healthcare, and then it discusses the associated features and appropriate pillars of ML for healthcare structure. Finally, it identified and discussed the significant applications of ML for healthcare. The applications of this technology in healthcare operations can be tremendously advantageous to the organisation. ML-based tools are used to provide various treatment alternatives and individualised treatments and improve the overall efficiency of hospitals and healthcare systems while lowering the cost of care. Shortly, ML will impact both physicians and hospitals. It will be crucial in developing clinical decision support, illness detection, and personalised treatment approaches to provide the best potential outcomes.</p></div>","PeriodicalId":100702,"journal":{"name":"International Journal of Intelligent Networks","volume":"3 ","pages":"Pages 58-73"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666603022000069/pdfft?md5=2259f97c985b93b68b9b7921ffedeba9&pid=1-s2.0-S2666603022000069-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83431241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 59

Design and implementation of a Social Distance Vest for Covid19 prevention (SODIV-COP) covid - 19预防社交距离背心(SODIV-COP)的设计与实现

International Journal of Intelligent Networks Pub Date : 2022-01-01 DOI: 10.1016/j.ijin.2022.08.003

Henry Eric Kapalamula, Justice Stanley Mlatho, Paul Stone Macheso

{"title":"Design and implementation of a Social Distance Vest for Covid19 prevention (SODIV-COP)","authors":"Henry Eric Kapalamula, Justice Stanley Mlatho, Paul Stone Macheso","doi":"10.1016/j.ijin.2022.08.003","DOIUrl":"10.1016/j.ijin.2022.08.003","url":null,"abstract":"<div><p>According to research, it is discovered that amongst the Covid19 preventive measures, social distance is easily neglected especially in a public setting such as markets, trading centers, social and political gatherings. Furthermore, according to World Health Organization (WHO), not observing social distance is one the major ways that the corona virus is being transmitted. Hence, working on a vest that can help to remind individuals and alert them in cases where they are not observing social distance. The Social Distance Vest for Covid19 Prevention, is based on Arduino Uno microcontroller board, D6T-44L-06 thermal sensor which detects the presence of a person, HC-SR04 Ultrasonic sensor that calculates the distance from where the person is standing and an alert/warning system that is composed of a Light Emitting Diode and a buzzer. Finally, the whole system is mounted on a reflective vest. The prototype vest works perfectly, in that it is able to detect a person which was not possible in the previous covid 19 distance vests which had only messages, and it is able to calculate the distance from where humans are standing and finally, triggers an alarm in a case where the person is standing at a distance of less than 1 m. The varying temperature ranges were in an array form and from 35 to 38° Celsius it detected the obstacle to be a human and had some ranges of distance 0.334 m measured by the ultrasonic sensor. Key applications of the prototypes are in crowded places like stadiums hospitals and schools.</p></div>","PeriodicalId":100702,"journal":{"name":"International Journal of Intelligent Networks","volume":"3 ","pages":"Pages 113-118"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666603022000112/pdfft?md5=7019b8e6ab6f3e3ee2b600b892d72157&pid=1-s2.0-S2666603022000112-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80030328","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Improved constrained social network rating-based neural network technique for recommending products in E-commerce environment 基于约束社会网络评级的改进电子商务环境下产品推荐神经网络技术

International Journal of Intelligent Networks Pub Date : 2022-01-01 DOI: 10.1016/j.ijin.2022.07.001

Lohith Ottikunta

{"title":"Improved constrained social network rating-based neural network technique for recommending products in E-commerce environment","authors":"Lohith Ottikunta","doi":"10.1016/j.ijin.2022.07.001","DOIUrl":"10.1016/j.ijin.2022.07.001","url":null,"abstract":"<div><p>In the modern world, the essentiality in the utilization of the e-commerce contents like movies, music and electronic goods becomes indispensable with diversified items searched over the internet. The relevant results of the items search are made feasible through the enforcement of filtering techniques since it determines relevant data for recommendation of an item. A diversified number of filtering schemes are available of filtering the data instead of accessing each data available on the internet for deriving associated results. The data access and efficiency, the process of identifying relevant results based on users’ preferences is challenging task. In this paper, the proposed Constrained Social Network Rating-based Neural Network Technique (CSNR-NNT) is presented with the key significances and implementation processes. This proposed CSNR-NNT significantly concentrates on the exploration of trustee information that aids in social content persuading selection process for facilitating superior recommendation. The proposed CSNR-NNT scheme utilized the benefits of neural learning for ensuring recommendation through the incorporation of distrust and trustee relation. This proposed CSNR-NNT scheme also aids in categorizing the positive and negative recommendation of the trustee based on the process of the prediction.</p></div>","PeriodicalId":100702,"journal":{"name":"International Journal of Intelligent Networks","volume":"3 ","pages":"Pages 80-86"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666603022000070/pdfft?md5=87ad3ea9e9bff958fd0a38bc82a5cf98&pid=1-s2.0-S2666603022000070-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73240523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Application of machine learning techniques for identifying productive zones in unconventional reservoir 机器学习技术在非常规油藏产层识别中的应用

International Journal of Intelligent Networks Pub Date : 2022-01-01 DOI: 10.1016/j.ijin.2022.08.001

Amir Gharavi, Mohamed Hassan, Jebraeel Gholinezhad, Hesam Ghoochaninejad, Hossein Barati, James Buick, Karrar A. Abbas

{"title":"Application of machine learning techniques for identifying productive zones in unconventional reservoir","authors":"Amir Gharavi, Mohamed Hassan, Jebraeel Gholinezhad, Hesam Ghoochaninejad, Hossein Barati, James Buick, Karrar A. Abbas","doi":"10.1016/j.ijin.2022.08.001","DOIUrl":"10.1016/j.ijin.2022.08.001","url":null,"abstract":"<div><p>Unconventional reservoirs are the productive zones in other words the rock quality and the mechanical properties of the rocks this process is devastating if humans or people try to search for the best reservoirs. So we can use machine learning (ML) algorithms to help us find and search easily and fast for the best reservoirs with less human interaction as possible. The objectives of this paper is to use machine learning (ML) techniques to predict and classify the reservoirs based on the properties of each reservoirs and choose the best reservoir. In this paper we have made a comparison between the different types of machine learning algorithm and described how we get the best and worst result for each one, the comparison we made gave us that the AdaBoost algorithm gave the worst performance measured in the accuracy while the random forest (RF) algorithm gave the best performance, this paper aim to make improvement of the process of searching for productive zones using ML algorithms.</p></div>","PeriodicalId":100702,"journal":{"name":"International Journal of Intelligent Networks","volume":"3 ","pages":"Pages 87-101"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666603022000094/pdfft?md5=2cb2f4012b28bfa5958a29ceb674a4ea&pid=1-s2.0-S2666603022000094-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76529156","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Improved Henon Chaotic Map-based Progressive Block-based visual cryptography strategy for securing sensitive data in a cloud EHR system 基于Henon混沌映射的改进渐进式块视觉加密策略在云EHR系统中保护敏感数据

International Journal of Intelligent Networks Pub Date : 2022-01-01 DOI: 10.1016/j.ijin.2022.08.004

Aneruth Mohanasundaram , Aruna S.K.

{"title":"Improved Henon Chaotic Map-based Progressive Block-based visual cryptography strategy for securing sensitive data in a cloud EHR system","authors":"Aneruth Mohanasundaram , Aruna S.K.","doi":"10.1016/j.ijin.2022.08.004","DOIUrl":"10.1016/j.ijin.2022.08.004","url":null,"abstract":"<div><p>The core objective of secret sharing concentrates on developing a novel technique that prevents the destruction and leakage of original data during the distribution and encoding processes. Progressive Visual Cryptography (VC) is considered for the potential over the traditional VC schemes since the former does not require and does not suffer from the limitations of requiring a minimum number of participants during the process of encryption and sharing. The chaotic map-based Progressive VC is superior in facilitating predominant secrecy under sharing and encryption. In this paper, an Improved Henon Chaotic Map-based Progressive Block-based VC (IHCMPBVC) scheme is proposed to prevent the leakage and destruction of sensitive information during an exchange and encryption. This proposed IHCMPBVC technique uses the merits of Henon and Lorentz maps for effective encryption since it introduces the option of deriving non-linear behavior that results in sequence generation that covers the complete range with proper distribution in order to minimize the degree of leaks in sharing. The simulation results of the proposed IHCMPBVC technique investigated using entropy, PSNR, and Mean Square Error were improved at an average rate of 27%, 23%, and 31%, predominant to the baseline VC approaches considered in the comparison.</p></div>","PeriodicalId":100702,"journal":{"name":"International Journal of Intelligent Networks","volume":"3 ","pages":"Pages 109-112"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666603022000124/pdfft?md5=48557b11a8189befa9c9b7805edba93e&pid=1-s2.0-S2666603022000124-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82398781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Multi-Objective Genetic Algorithm and CNN-Based Deep Learning Architectural Scheme for effective spam detection 多目标遗传算法和基于cnn的深度学习体系结构方案的有效垃圾邮件检测

International Journal of Intelligent Networks Pub Date : 2022-01-01 DOI: 10.1016/j.ijin.2022.01.001

Jenifer Darling Rosita P , W. Stalin Jacob

{"title":"Multi-Objective Genetic Algorithm and CNN-Based Deep Learning Architectural Scheme for effective spam detection","authors":"Jenifer Darling Rosita P , W. Stalin Jacob","doi":"10.1016/j.ijin.2022.01.001","DOIUrl":"10.1016/j.ijin.2022.01.001","url":null,"abstract":"<div><p>E-mail has traditionally been regarded as the most powerful medium in online social networks, where users can discuss, connect, and share links with other online social media users. In particular, Twitter, in particular, has been determined to be the most popular social network that serves as the best communication channel for its users to share current news, ideas, thoughts, comments, and beliefs with other online social media users. Despite the efforts put in to combat spam operations on the online social network, Twitter spam has a new type of functionality that is limited to 140 characters. It is not only the major cause of annoyance for day-to-day users, but also responsible for the majority of computer security issues that cost billions of dollars in terms of productivity losses. In this paper, we propose a Multi-Objective Genetic Algorithm and a CNN-based Deep Learning Architectural Scheme (MOGA–CNN–DLAS) for the predominant Twitter spam detection process. The experimental details and results discussions of the proposed MOGA-CNN-DLAS are evaluated in terms of accuracy, precision, recall, F-Score, RMSE, and MAE by varying the ratio of training data under the utilization of three real datasets, such as the Twitter 100k dataset and the ASU dataset.</p></div>","PeriodicalId":100702,"journal":{"name":"International Journal of Intelligent Networks","volume":"3 ","pages":"Pages 9-15"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S266660302200001X/pdfft?md5=3d4fbd3faaf7f91a77e4a6f57ae61ae1&pid=1-s2.0-S266660302200001X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89844072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 13

Enhancing smart farming through the applications of Agriculture 4.0 technologies 通过应用农业4.0技术提升智慧农业

International Journal of Intelligent Networks Pub Date : 2022-01-01 DOI: 10.1016/j.ijin.2022.09.004

Mohd Javaid , Abid Haleem , Ravi Pratap Singh , Rajiv Suman

{"title":"Enhancing smart farming through the applications of Agriculture 4.0 technologies","authors":"Mohd Javaid , Abid Haleem , Ravi Pratap Singh , Rajiv Suman","doi":"10.1016/j.ijin.2022.09.004","DOIUrl":"10.1016/j.ijin.2022.09.004","url":null,"abstract":"<div><p>Agriculture 4.0 represents the fourth agriculture revolution that uses digital technologies and moves toward a smarter, more efficient, environmentally responsible agriculture sector. Agricultural technologies have emerged to enhance sustainability and discover more effective farm methods. This encompasses all digitalisation and automation processes in business and our daily lives, including Big Data, Artificial Intelligence (AI), robots, the Internet of Things (IoT), and virtual and augmented reality. These technological advancements are having a profound impact on our lives. From a technical standpoint, it brings us to precision agriculture. This provides a data-driven strategy for efficiently growing and maintaining crops on cultivable land, enabling farmers to use most of the resources at their disposal. Throughout the supply chain, daily operations create massive volumes of data. Most of this information was previously untouched, but with the help of big data technologies, such information can be used to improve the performance and production of any crop. Depending on the crop type and its growth needs, digitised harvesters can help handle huge areas in various situations, particularly agriculture. This paper is brief about Agriculture 4.0 and its condition. Smart farming, Various key technologies and specific domains for the Exploring Agriculture 4.0 Domain are discussed in detail and, finally, identified and discussed significant applications of Agriculture 4.0 technologies. These technologies are essential to our lives since they simplify our daily duties without recognising them. In Agriculture 4.0 systems, fleets of digitised equipment employ current infrastructures like cloud computing to connect, identify the processing condition of different regions and the requirement for input materials and coordinate the machinery.</p></div>","PeriodicalId":100702,"journal":{"name":"International Journal of Intelligent Networks","volume":"3 ","pages":"Pages 150-164"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666603022000173/pdfft?md5=aa240b204485568f541ce45a0e89e7be&pid=1-s2.0-S2666603022000173-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78724300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 61

Hybrid TABU search with SDS based feature selection for lung cancer prediction 混合禁忌搜索与基于SDS的特征选择用于肺癌预测

International Journal of Intelligent Networks Pub Date : 2022-01-01 DOI: 10.1016/j.ijin.2022.09.002

S. Shanthi , V.S. Akshaya , J.A. Smitha , M. Bommy

{"title":"Hybrid TABU search with SDS based feature selection for lung cancer prediction","authors":"S. Shanthi , V.S. Akshaya , J.A. Smitha , M. Bommy","doi":"10.1016/j.ijin.2022.09.002","DOIUrl":"10.1016/j.ijin.2022.09.002","url":null,"abstract":"<div><p>Cancer falls under a group of diseases where abnormal growths of the cells are observed. Generally, lung cancer does not result in any type of obvious symptoms in its early stages. Among the people diagnosed with lung cancer, about 40% are found to be in an advanced stage. Thus, the motivation of the work is to present an automatic screening of lung images for early diagnosis. For this, Machine Learning (ML) methods are popularly employed as a tool among medical researchers for classifying their medical images. To improve the performance of Lung cancer detection with ML techniques, feature selection is employed. As the feature selection is a Nondeterministic Polynomial (NP) hard problem, metaheuristic algorithms are widely used for finding the optimal feature set. The Tabu Search (TS) is semi-deterministic and also tends to act as a method of local, as well as global search. The techniques are capable of discovering and further identifying the relationships and patterns among them obtained from complex datasets and are also capable of effective prediction. In this work, a new hybrid TS with Stochastic Diffusion Search (SDS) based feature selection that was employed using the Naïve Bayes, Decision tree and Neural Network (NN) classifiers to improve classification. The results demonstrate the effectiveness of the proposed TABU-SDS- NN which achieves an accuracy of 94.07%.</p></div>","PeriodicalId":100702,"journal":{"name":"International Journal of Intelligent Networks","volume":"3 ","pages":"Pages 143-149"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S266660302200015X/pdfft?md5=3d8c04a0a86f1693ec11770fe0ff73b0&pid=1-s2.0-S266660302200015X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82326440","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Rough set based on least dissimilarity normalized index for handling uncertainty during E-learners learning pattern recognition 基于最小不相似度归一化指标的粗糙集处理网络学习者学习模式识别中的不确定性

International Journal of Intelligent Networks Pub Date : 2022-01-01 DOI: 10.1016/j.ijin.2022.09.001

Vijayan Sugumaran , S. Jafar Ali Ibrahim

{"title":"Rough set based on least dissimilarity normalized index for handling uncertainty during E-learners learning pattern recognition","authors":"Vijayan Sugumaran , S. Jafar Ali Ibrahim","doi":"10.1016/j.ijin.2022.09.001","DOIUrl":"10.1016/j.ijin.2022.09.001","url":null,"abstract":"<div><p>The determination of e-learners' learning style in an online environment has raised the potential scope of interest as its exact estimation prompts a sensational improvement in the contents of the learning framework and student performance. It requires a deep investigation of the learning habits of the learner. Grouping e-learners together provides a more quantifiable way to analyze the learner's feedback and log files to discriminate them based on their learning style. This is accomplished with the help of clustering algorithms in data mining that aids in determining their learning styles well. The target clusters are analyzed by generating functional patterns or rules using the rule induction algorithms. Most of the existing works in the literature attributed to the elucidation of learning styles fail to address the uncertainty and inconsistency in the learner's characteristics. The RST is an optimal method for analyzing the learner's behavior in this context. Thus, a Rough set based least dissimilarity normalized index (RS-LDNI) is proposed for resolving uncertainty while estimating e-learners' learning patterns. This RS-LNDI used the merits of Maximum Dependency Attributes (MDA) for categorical clustering such that the maximal dependency between attributes can be determined by splitting attributes instead of Roughness. It also adopted categorical data clustering to attain the correlation between attributes that cannot be used for learning style prediction. The experimental results of the RS-LNDI algorithm outperform the demerits of these existing clustering algorithms by utilizing the reduct and equivalence class property of rough set theory.</p></div>","PeriodicalId":100702,"journal":{"name":"International Journal of Intelligent Networks","volume":"3 ","pages":"Pages 133-137"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666603022000148/pdfft?md5=de01da26b8655021f70e550c06fc56c9&pid=1-s2.0-S2666603022000148-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88087285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1