Journal of Computational and Theoretical Nanoscience最新文献_第2页

A 4-Dimensional Service Evaluation Strategy on Web Services 基于Web服务的四维服务评估策略

Journal of Computational and Theoretical Nanoscience Pub Date : 2021-05-01 DOI: 10.1166/jctn.2021.9597

Ok-Sun Lim, Jee-Ah Shin, Jin-Hwa Kim

{"title":"A 4-Dimensional Service Evaluation Strategy on Web Services","authors":"Ok-Sun Lim, Jee-Ah Shin, Jin-Hwa Kim","doi":"10.1166/jctn.2021.9597","DOIUrl":"https://doi.org/10.1166/jctn.2021.9597","url":null,"abstract":"The purpose of this study is to suggest a multi-dimensional model that evaluates services in web stores using data mining, text mining and surveys. Unlike other service evaluation model, this study suggests a 4 dimensional approach in evaluating web services. It uses reciprocal evaluation\u0000 methods on a web service by both services providers and service users. It identifies the cognitive differences on web services between these two groups. The study also uses text mining technologies such as social mining and topic analysis to find images of the web services. The results from\u0000 the study show that there are significant differences between the evaluations on web services by service providers and service users. There are also differences between images of a service provider from news data and social media data. These differences are represented with keywords related\u0000 to the service providers. Texts from news are collected and analyzed to have more object images of a web service providers. Texts from social media are collected and analyzed to have more personal images of a web service providers. A decision tree analysis, as a data mining tool, is used to\u0000 induce and to produce a strategy to understand the cognitive differences and to improve the quality of services. A decision tree analysis is used to find the pattern and to explain the difference between service providers and service users. It can be used to better understand the quality of\u0000 their services and to improve the quality of service from service provider’s point of view. The approach this study suggests can be used to other evaluation areas such as customer satisfaction on new products or services.","PeriodicalId":15416,"journal":{"name":"Journal of Computational and Theoretical Nanoscience","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46705295","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 Analysis of Digital Assets on Exploiting Blockchain Management for Foreign Students 数字资产在留学生区块链管理中的应用分析

Journal of Computational and Theoretical Nanoscience Pub Date : 2021-05-01 DOI: 10.1166/jctn.2021.9586

Jin-Ho Lim, Kwan-Sik Na, Seungcheon Kim

{"title":"An Analysis of Digital Assets on Exploiting Blockchain Management for Foreign Students","authors":"Jin-Ho Lim, Kwan-Sik Na, Seungcheon Kim","doi":"10.1166/jctn.2021.9586","DOIUrl":"https://doi.org/10.1166/jctn.2021.9586","url":null,"abstract":"This study shows O2O (offline to online) based studying abroad platform, we called it as DRM (DoDream), that provides foreign students with various information for studying in Korea and matching platform with Korean universities (Language Institute) (Lim, J.H., et al., 2019. The architecture\u0000 design of students’ career information management system using blockchain technology. International Journal of Innovative Technology and Exploring Engineering, 8(8S2), pp.188–193). Empirical results reveal studying abroad provides a new environment for foreign students who\u0000 dream of studying in Korea by innovating structural problems of existing studying abroad market and sharing open information about Korea n universities, and to provide systematic and efficient study abroad support services to Korean universities (Language institutes) and local study abroad.\u0000 DRM (DoDream) Tokens will be otherwise intended to be generally obtainable by users of the DRM (DoDream) Platform through the methods externally from third party cryptocurrency exchanges or internally on the DRM (DoDream) platform through conversion of “step” points that are awarded\u0000 to users who have participated in events, promotions and/or who have made positive contributions to the DoDream Platform community.","PeriodicalId":15416,"journal":{"name":"Journal of Computational and Theoretical Nanoscience","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48293993","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 Improved Grey Wolf Optimization Algorithm Based Resource Management Strategy for Big Data Systems 一种新的基于改进灰太狼优化算法的大数据系统资源管理策略

Journal of Computational and Theoretical Nanoscience Pub Date : 2021-04-01 DOI: 10.1166/JCTN.2021.9383

L. Babu, J. Kumar

{"title":"A Novel Improved Grey Wolf Optimization Algorithm Based Resource Management Strategy for Big Data Systems","authors":"L. Babu, J. Kumar","doi":"10.1166/JCTN.2021.9383","DOIUrl":"https://doi.org/10.1166/JCTN.2021.9383","url":null,"abstract":"Presently, big data is very popular, since it finds helpful in diverse domains like social media, E-commerce transactions, etc. Cloud computing offers services on demand, broader networking access, source collection, quick flexibility and calculated services. The cloud sources are usually\u0000 different and the application necessities of the end user are rapidly changing from time to time. So, the resource management is the tedious process. At the same time, resource management and scheduling plays a vital part in cloud computing (CC) results, particularly while the environment\u0000 is employed in the analysis of big data, and minimum predictable workload dynamically enters into the cloud. The identification of the optimal scheduling solutions with diverse variables in varying platform still remains a crucial problem. Under cloud platform, the scheduling techniques should\u0000 be able to adapt the changes quickly and according to the input workload. In this paper, an improved grey wolf optimization (IGWO) algorithm with oppositional learning principle has been important to carry out the scheduling task in an effective way. The presented IGWO based scheduling algorithm\u0000 achieves optimal cloud resource usage and offers effective solution over the compared methods in a significant way.","PeriodicalId":15416,"journal":{"name":"Journal of Computational and Theoretical Nanoscience","volume":"18 1","pages":"1227-1232"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48039206","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

Breakdown Voltage Analysis in Quaternary InAlGaN High Electron Mobility Transistor of High-K Passivation Layer for High Power Applications 用于高功率应用的高K钝化层四元InAlGaN高电子迁移率晶体管的击穿电压分析

Journal of Computational and Theoretical Nanoscience Pub Date : 2021-04-01 DOI: 10.1166/JCTN.2021.9386

N. Anbuselvan, P. Anandan

{"title":"Breakdown Voltage Analysis in Quaternary InAlGaN High Electron Mobility Transistor of High-K Passivation Layer for High Power Applications","authors":"N. Anbuselvan, P. Anandan","doi":"10.1166/JCTN.2021.9386","DOIUrl":"https://doi.org/10.1166/JCTN.2021.9386","url":null,"abstract":"The 2-Dimensional breakdown characteristics analysis in InAlGaN/GaN high electron mobility transistors (HEMTs) is implemented through including of donor and acceptor atoms inside the barrier layer. Thereby dependences of the relative permittivity εr and the thickness\u0000 d of passivation layer on the breakdown voltage are related for the parametric analysis. When the relative permittivity εr increases duly affects the breakdown voltage by order of increases, owing to its electric field existence at the drain, there on resulting in εr\u0000 upsurges. This occurs due to the properties of insulator with the applied voltage evenly drops uniformly. The inducing voltage drop alongside the heterostructure of materials InAlGaN/GaN develops flatter response on the drain terminal of the gate owing to its permittivity εr\u0000 of higher order. The aforementioned breakdown voltage surges, since of the electric field nearby the drain has weakened as a owing to it thickness of passivating layer d, this resolute InAlGaN/GaN HEMTs of a high-k along with the thicker passivation layer has higher breakdown voltage.","PeriodicalId":15416,"journal":{"name":"Journal of Computational and Theoretical Nanoscience","volume":"18 1","pages":"1282-1286"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46165287","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

Enhanced Load Balancing Approach for Cloud Data Center Load Optimization 云数据中心负载优化的增强型负载均衡方法

Journal of Computational and Theoretical Nanoscience Pub Date : 2021-04-01 DOI: 10.1166/JCTN.2021.9399

J. Prassanna, V. Neelanarayanan

{"title":"Enhanced Load Balancing Approach for Cloud Data Center Load Optimization","authors":"J. Prassanna, V. Neelanarayanan","doi":"10.1166/JCTN.2021.9399","DOIUrl":"https://doi.org/10.1166/JCTN.2021.9399","url":null,"abstract":"Cloud computing is a most popular technology that has huge response in markets. Cloud computing has the potential to access applications and their related data via the Internet anywhere. Most companies already pay for the use of cloud resources for storage purposes and ultimately reduce\u0000 the costs of infrastructure spending. They can make use of this technology for accessing to company applications like pay-as-you-go approach. One of the major obstacles associated with cloud computing technology is to better optimization of resource allocation. Assigning of workloads to the\u0000 servers using load balancing techniques is used to achieve less response time and better resource optimization across the server. Resource control and balance of load are the major conflicts in the cloud environment, which is why there are different load balancing algorithms, each with its\u0000 own advantages and disadvantage. In order to achieve a better economy and mutual benefit, efficient algorithms can be derived simultaneously by optimizing servers, green computing and better utilization of resources. The objective of this paper is to analyze and enhance existing load balancing\u0000 algorithms.","PeriodicalId":15416,"journal":{"name":"Journal of Computational and Theoretical Nanoscience","volume":"18 1","pages":"1270-1274"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46099422","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

Fuzzy C-Means (FCM) Clustering with Probabilistic Neural Network (PNN) Model for Detection and Classification of Rice Plant Diseases in Internet of Things-Cloud Centric Precision Agriculture 基于概率神经网络(PNN)模型的模糊c均值聚类在物联网云中心精准农业中的水稻病害检测与分类

Journal of Computational and Theoretical Nanoscience Pub Date : 2021-04-01 DOI: 10.1166/JCTN.2021.9400

P. Sindhu, G. Indirani, P. Dinadayalan

{"title":"Fuzzy C-Means (FCM) Clustering with Probabilistic Neural Network (PNN) Model for Detection and Classification of Rice Plant Diseases in Internet of Things-Cloud Centric Precision Agriculture","authors":"P. Sindhu, G. Indirani, P. Dinadayalan","doi":"10.1166/JCTN.2021.9400","DOIUrl":"https://doi.org/10.1166/JCTN.2021.9400","url":null,"abstract":"Presently, the field of Internet of Things (loT) has been employed in diverse applications like Smart Grid, Surveillance, Smart homes, and so on. Precision Agriculture is a concept of farm management which makes use of IoT and networking concepts to improve the crop health. Recognition\u0000 of diseases from the plant images is an active research topic which makes use of machine learning (ML) approaches. This paper introduces an effective rice plant disease identification and classification model to identify the type of disease from infected rice plants. The proposed method aims\u0000 to detect three rice plant diseases such as Bacterial leaf blight, Brown spot, and Leaf smut. The proposed method involves a set of different processes namely image acquisition, preprocessing, segmentation, feature extraction and classification. At the earlier stage, IoT devices will be used\u0000 to capture the image and stores it with a cloud server, which executes the classification process. In the cloud, the rice plant images under preprocessing to improvise the quality of the image. Then, fuzzy c-means (FCM) clustering method is utilized for the segmentation of disease portion\u0000 from a leaf image. Afterwards, feature extraction takes place under three kinds namely color, shape, and texture. Finally, probabilistic neural network (PNN) is applied for multi-class classification. A detailed experimental analysis ensured the effective classification performance of the\u0000 proposed method under all the test images applied.","PeriodicalId":15416,"journal":{"name":"Journal of Computational and Theoretical Nanoscience","volume":"18 1","pages":"1194-1200"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41742667","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

An Advanced Image Processing Prototype for Corrosion Finding Using Image Processing 利用图像处理技术进行腐蚀检测的先进图像处理原型

Journal of Computational and Theoretical Nanoscience Pub Date : 2021-04-01 DOI: 10.1166/JCTN.2021.9388

M. Malathi, P. Sinthia

引用次数: 0

Subtractive Gradient Boost Clustering for Mobile Node Authentication in Internet of Things Aware 5G Networks 物联网感知5G网络中移动节点认证的减梯度增强聚类

Journal of Computational and Theoretical Nanoscience Pub Date : 2021-04-01 DOI: 10.1166/JCTN.2021.9394

M. Haripriya, P. Venkadesh

{"title":"Subtractive Gradient Boost Clustering for Mobile Node Authentication in Internet of Things Aware 5G Networks","authors":"M. Haripriya, P. Venkadesh","doi":"10.1166/JCTN.2021.9394","DOIUrl":"https://doi.org/10.1166/JCTN.2021.9394","url":null,"abstract":"The 5G mobile wireless network systems faces a lot of security issues due to the opening of network and its insecurity. The insecure network prone to various attacks and it disrupts secure data communications between legitimate users. Many works have addressed the security problems\u0000 in 3G and 4G networks in efficient way through authentication and cryptographic techniques. But, the security in 5G networks during data communication was not improved. Subtractive Gradient Boost Clustered Node Authentication (SGBCNA) Method is introduced to perform secure data communication.\u0000 The subtractive gradient boost clustering technique is applied to authenticate the mobile node as normal nodes and malicious nodes based on the selected features. The designed ensemble clustering model combines the weak learners to make final strong clustering results with minimum loss. Finally,\u0000 the malicious nodes are eliminated and normal mobile nodes are taken for performing the secured communication in 5G networks. Simulation is carried out on factors such as authentication accuracy, computation overhead and security level with respect to a number of mobile nodes and data packets.\u0000 The observed outcomes clearly illustrate that the SGBCNA Method efficiently improves node authentication accuracy, security level with minimum overhead than the state-of-the-art-methods.","PeriodicalId":15416,"journal":{"name":"Journal of Computational and Theoretical Nanoscience","volume":"18 1","pages":"1287-1293"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46052184","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

Contemporary Human Activity Recognition Based Predictions by Sensors Using Random Forest Classifier 基于现代人类活动识别的随机森林分类器传感器预测

Journal of Computational and Theoretical Nanoscience Pub Date : 2021-04-01 DOI: 10.1166/JCTN.2021.9404

S. Anand, S. Magesh, I. Arockiamary

{"title":"Contemporary Human Activity Recognition Based Predictions by Sensors Using Random Forest Classifier","authors":"S. Anand, S. Magesh, I. Arockiamary","doi":"10.1166/JCTN.2021.9404","DOIUrl":"https://doi.org/10.1166/JCTN.2021.9404","url":null,"abstract":"The task of recognizing human activities directs extensive divergence of various functions and applications. Despite analysing the intricate activity it endures demanding requirements in contemporary field of research. A subject performs a definite task at a particular time by determining\u0000 the activity by using sensor data. In this research task we appraise a unique way by using data with supervised learning techniques by placing sensors on the human body by contingent upon classification process at different stages. The State-of-art machine learning approach random forests\u0000 are widely discussed in terms of covering practical and theoretical aspects of body sensing. The eventual target is the superior rate of accurate predictions effecting Human Activity Recognition further effective for behavioural monitoring, medical and healthcare sectors. Classification processes\u0000 are deployed for pairs of activities that are distracted often and this work attempts to analyse the essential sensors for the improved prediction. The results shows the best accuracy scores and the remaining of our findings we expose the outline, exhibiting the degree of distraction between\u0000 features of ranking and human activities which renders back to sensor ranking.","PeriodicalId":15416,"journal":{"name":"Journal of Computational and Theoretical Nanoscience","volume":"18 1","pages":"1243-1250"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41956662","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

Optimized Design of Low Power Complementary Metal Oxide Semiconductor Low Noise Amplifier for Zigbee Application Zigbee低功耗互补金属氧化物半导体低噪声放大器的优化设计

Journal of Computational and Theoretical Nanoscience Pub Date : 2021-04-01 DOI: 10.1166/JCTN.2021.9387

S. Manjula, R. Karthikeyan, S. Karthick, N. Logesh, M. Logeshkumar

引用次数: 0