Int. J. Knowl. Based Intell. Eng. Syst.最新文献_第4页

Models for MADM with hesitant interval-valued fuzzy information under uncertain environment 不确定环境下具有犹豫区间模糊信息的MADM模型

Int. J. Knowl. Based Intell. Eng. Syst. Pub Date : 2021-11-10 DOI: 10.3233/kes-210074

Hongjun Wang

引用次数: 0

Personalized privacy assistant for digital voice assistants: Case study on Amazon Alexa 数字语音助手的个性化隐私助手:以亚马逊Alexa为例

Int. J. Knowl. Based Intell. Eng. Syst. Pub Date : 2021-11-10 DOI: 10.3233/kes-210071

J. Hyma, M. Murty, A. Naveen

引用次数: 1

An approach for bibliographic citation sentiment analysis using deep learning 基于深度学习的书目引文情感分析方法

Int. J. Knowl. Based Intell. Eng. Syst. Pub Date : 2021-01-18 DOI: 10.3233/kes-200087

S. Muppidi, Satya Keerthi Gorripati, B. Kishore

{"title":"An approach for bibliographic citation sentiment analysis using deep learning","authors":"S. Muppidi, Satya Keerthi Gorripati, B. Kishore","doi":"10.3233/kes-200087","DOIUrl":"https://doi.org/10.3233/kes-200087","url":null,"abstract":"Sentiment analysis of scientific citations is a novel and remarkable research area. Most of the work on opinion or sentiment analysis has been suggested on social platforms such as Blogs, Twitter, and Facebook. Nevertheless, when it comes to recognizing sentiments from scientific citation papers, investigators used to face difficulties due to the implied and unseen natures of sentiments or opinions. As the citation references are reflected implicitly positive in opinion, famous ranking and indexing prototypes frequently disregard the sentiment existence while citing. Hence, in the proposed framework the paper emphasizes the issue of classifying positive and negative polarity of reference sentiments in scientific research papers. First, the paper scraps the PDF articles from arxiv.org under the computer science group consisting of articles that are comprised of ‘autism’ in their title, then the paper extracted cited references and assigns polarity scores to each cited reference. The paper uses a supervised classifier with a combination of significant feature sets and compared the performance of the models. Experimental results show that a combined CNN-LSTM deep neural network model results in 85% of accuracy while traditional models result in less accuracy.","PeriodicalId":210048,"journal":{"name":"Int. J. Knowl. Based Intell. Eng. Syst.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114868737","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: 5

Identification of myocardial infarction from analysis of ECG signal 从心电信号分析判断心肌梗死

Int. J. Knowl. Based Intell. Eng. Syst. Pub Date : 2020-09-28 DOI: 10.3233/KES-200043

D. Jagannadham, D. V. S. Narayana, P. Ganesh, D. Koteswar

引用次数: 0

A robust intrusion detection system using machine learning techniques for MANET 基于机器学习技术的入侵检测系统

Int. J. Knowl. Based Intell. Eng. Syst. Pub Date : 2020-09-28 DOI: 10.3233/KES-200047

N. Ravi, G. Ramachandran

{"title":"A robust intrusion detection system using machine learning techniques for MANET","authors":"N. Ravi, G. Ramachandran","doi":"10.3233/KES-200047","DOIUrl":"https://doi.org/10.3233/KES-200047","url":null,"abstract":"Recent advancement in technologies such as Cloud, Internet of Things etc., leads to the increase usage of mobile computing. Present day mobile computing are too sophisticated and advancement are reaching great heights. Moreover, the present day mobile network suffers due to external and internal intrusions within and outside networks. The existing security systems to protect the mobile networks are incapable to detect the recent attacks. Further, the existing security system completely depends on the traditional signature and rule based approaches. Recent attacks have the property of not fluctuating its behaviour during attack. Hence, a robust Intrusion Detection System (IDS) is desirable. In order to address the above mentioned issue, this paper proposed a robust IDS using Machine Learning Techniques (MLT). The key of using MLT is to utilize the power of ensembles. The ensembles of classifier used in this paper are Random Forest (RF), KNN, Naïve Bayes (NB), etc. The proposed IDS is experimentally tested and validated using a secure test bed. The experimental results also confirms that the proposed IDS is robust enough to withstand and detect any form of intrusions and it is also noted that the proposed IDS outperforms the state of the art IDS with more than 95% accuracy.","PeriodicalId":210048,"journal":{"name":"Int. J. Knowl. Based Intell. Eng. Syst.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128067823","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

Economic victimisation of convict's family: Statistical analysis through SPSS 罪犯家庭经济受害:SPSS统计分析

Int. J. Knowl. Based Intell. Eng. Syst. Pub Date : 2020-09-28 DOI: 10.3233/KES-200048

Snigdha Sarkar, S. Samanta, A. Mitra

{"title":"Economic victimisation of convict's family: Statistical analysis through SPSS","authors":"Snigdha Sarkar, S. Samanta, A. Mitra","doi":"10.3233/KES-200048","DOIUrl":"https://doi.org/10.3233/KES-200048","url":null,"abstract":"In new age scenario Prisons are meant not only to punish the convict but also correct the situation and habits of the convicts, who is responsible for inflicting harm on the victim. But family members of the convict are also the victim in the process and situation. Convicts family face the horrific situation during this process. Prisoner’s families are maltreated directly and indirectly by the society. They live in destitution. Imprisonment of family member not only diminishes the earnings of adult men but also reduces familial resources for the basic necessities of life. The family members have to sacrifice their children’s education, ancestor’s property, past savings, in some cases even necessary wants of their life. We always think about the victim on whom the harm has been directly inflicted and completely ignore the harm inflicted on the kin of the convict. The present study is an endeavour to bring to light the economic vulnerability of families of convicts in a prison in Bhubaneswar. After interviewing the family members of prisoners, statistical analysis is done through SPSS. The findings are elaborated in narrative manner so that the findings will be helpful for policy makers in future.","PeriodicalId":210048,"journal":{"name":"Int. J. Knowl. Based Intell. Eng. Syst.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133186607","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

Literature review and analysis on big data stream classification techniques 大数据流分类技术的文献综述与分析

Int. J. Knowl. Based Intell. Eng. Syst. Pub Date : 2020-09-28 DOI: 10.3233/KES-200042

B. Srivani, N. Sandhya, B. Rani

{"title":"Literature review and analysis on big data stream classification techniques","authors":"B. Srivani, N. Sandhya, B. Rani","doi":"10.3233/KES-200042","DOIUrl":"https://doi.org/10.3233/KES-200042","url":null,"abstract":"Rapid growth in technology and information lead the human to witness the improved growth in velocity, volume of data, and variety. The data in the business organizations demonstrate the development of big data applications. Because of the improving demand of applications, analysis of sophisticated streaming big data tends to become a significant area in data mining. One of the significant aspects of the research is employing deep learning approaches for effective extraction of complex data representations. Accordingly, this survey provides the detailed review of big data classification methodologies, like deep learning based techniques, Convolutional Neural Network (CNN) based techniques, K-Nearest Neighbor (KNN) based techniques, Neural Network (NN) based techniques, fuzzy based techniques, and Support vector based techniques, and so on. Moreover, a detailed study is made by concerning the parameters, like evaluation metrics, implementation tool, employed framework, datasets utilized, adopted classification methods, and accuracy range obtained by various techniques. Eventually, the research gaps and issues of various big data classification schemes are presented.","PeriodicalId":210048,"journal":{"name":"Int. J. Knowl. Based Intell. Eng. Syst.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129057025","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

Minimum square distance thresholding method applying gray-gradient co-occurrence matrix 应用灰度梯度共现矩阵的最小二乘距离阈值法

Int. J. Knowl. Based Intell. Eng. Syst. Pub Date : 2020-09-28 DOI: 10.3233/KES-200040

Hong Zhang, Qiang Zhi, Fan Yang

引用次数: 0

Automatic segmentation algorithm for breast cell image based on multi-scale CNN and CSS corner detection 基于多尺度CNN和CSS角点检测的乳腺细胞图像自动分割算法

Int. J. Knowl. Based Intell. Eng. Syst. Pub Date : 2020-09-28 DOI: 10.3233/KES-200041

Hao-yang Tang, Cong Song, Meng Qian

引用次数: 2

Recognition of human emotion with spectral features using multi layer-perceptron 基于多层感知器的人类情感谱特征识别

Int. J. Knowl. Based Intell. Eng. Syst. Pub Date : 2020-09-28 DOI: 10.3233/KES-200044

A. Reddy, V. Vijayarajan

引用次数: 3