发布求助
文献互助 智能选刊 最新文献

Int. J. Reason. based Intell. Syst.最新文献

筛选
英文 中文
Deep learning-based detection and prediction of trending topics from streaming data 基于深度学习的流数据趋势主题检测和预测
Int. J. Reason. based Intell. Syst. Pub Date : 2021-03-30 DOI: 10.1504/IJRIS.2021.10036804
Ajeet Ram Pathak, M. Pandey, S. Rautaray
{"title":"Deep learning-based detection and prediction of trending topics from streaming data","authors":"Ajeet Ram Pathak, M. Pandey, S. Rautaray","doi":"10.1504/IJRIS.2021.10036804","DOIUrl":"https://doi.org/10.1504/IJRIS.2021.10036804","url":null,"abstract":"Detecting and predicting trending topics from steaming social data has always been the point of active research area in business and research firms to take quick decisions, change marketing strategies and set new goals. Topic modelling is one of the excellent methods to analyse the contents from large collection of documents in an unsupervised manner and it is a popular method used in natural language processing, information retrieval, text processing and many other research domains. In this paper, deep learning-based topic modelling technique has been proposed to detect and predict the trending topics from streaming data. The online version of latent semantic analysis with regularisation constraints has been designed using long short-term memory network. Specifically, a problem of detecting the topics from streaming media is handled as the minimisation of quadratic loss function constrained by l1 and l2 regularisation. The online learning mechanism supports scalable topic modelling. For topic prediction, sequence-to-sequence long short-term memory network has been designed. Experimentally, significant results have been achieved in terms of query retrieval performance and topic relevance metrics for topic detection on our published dataset. For topic prediction, the results obtained in terms of root mean squared error are also significant.","PeriodicalId":360794,"journal":{"name":"Int. J. Reason. based Intell. Syst.","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133805656","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
New type NP-CSMA of adaptive multi-priority control WSN protocol analysis 新型NP-CSMA自适应多优先级控制WSN协议分析
Int. J. Reason. based Intell. Syst. Pub Date : 2021-02-05 DOI: 10.1504/IJRIS.2021.113049
Zejun Han, H. Ding, Kun Yue, Liyong Bao, Zhijun Yang
{"title":"New type NP-CSMA of adaptive multi-priority control WSN protocol analysis","authors":"Zejun Han, H. Ding, Kun Yue, Liyong Bao, Zhijun Yang","doi":"10.1504/IJRIS.2021.113049","DOIUrl":"https://doi.org/10.1504/IJRIS.2021.113049","url":null,"abstract":"Wireless sensor networks (WSN) uses a large number of cheap micro sensor nodes, which can be used to perceive and deal with the information that the transmission network covers the object in the geographic area, so it is very popular among people. P-CSMA access to WSN can control the system and reduce energy consumption, but the overall effect is general and the practicability is common. In this paper, a three-clock non-persistent P-CSMA (NP-CSMA) based on variable collision length is proposed to improve system throughput. By dividing the successful packet transmission time (1 + a), the collision packet transmission time (b + a), the free packet sending time a, the average cycle method is used to find out the important parameters of the system, such as throughput, collision rate and idle rate, striving to minimise the system energy consumption, effectively extending the life cycle of nodes and reducing costs. Finally, simulation experiments are validated the validity of the agreement, comparing with other protocols to verify the superiority of this agreement.","PeriodicalId":360794,"journal":{"name":"Int. J. Reason. based Intell. Syst.","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130805952","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
Cryptographic algorithm for protection of communication in drones control 无人机控制中通信保护的加密算法
Int. J. Reason. based Intell. Syst. Pub Date : 2021-02-05 DOI: 10.1504/IJRIS.2021.113053
Ivan Ivanov, K. Andreev, Stella Vetova, R. Arnaudov
{"title":"Cryptographic algorithm for protection of communication in drones control","authors":"Ivan Ivanov, K. Andreev, Stella Vetova, R. Arnaudov","doi":"10.1504/IJRIS.2021.113053","DOIUrl":"https://doi.org/10.1504/IJRIS.2021.113053","url":null,"abstract":"The paper below presents an optimised cryptographic algorithm, designed to protect communication in the management of drones. In this communication the need for the data to be protected as much as possible and (in case) stored reliably rises. The use of microcontrollers requires an optimised algorithm in terms of number and type of operations, due to lower computing power and a small amount of memory. The algorithm is built on DES algorithm, according to the Feistel scheme. It is a 64-bits symmetric block cryptographic algorithm, using a 512-bits cryptographic key.","PeriodicalId":360794,"journal":{"name":"Int. J. Reason. based Intell. Syst.","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132238418","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
Estimating equations under IPW imputation of missing data 缺失数据IPW估算方程
Int. J. Reason. based Intell. Syst. Pub Date : 2021-02-05 DOI: 10.1504/IJRIS.2021.113032
Hao Wu, Cuicui Li, Chen Cheng
{"title":"Estimating equations under IPW imputation of missing data","authors":"Hao Wu, Cuicui Li, Chen Cheng","doi":"10.1504/IJRIS.2021.113032","DOIUrl":"https://doi.org/10.1504/IJRIS.2021.113032","url":null,"abstract":"The inverse probability weighted (IPW) imputation method is first applied to compensate for non-response. And then, the empirical likelihood (EL) inference is made for estimation equation parameters. It is a nice result to be obtained in this paper that the limiting distributions of the EL statistics are χ2-type distributions under the IPW imputation. Compared with the usually-used methods, the proposed method is easier to complement and performs more efficient.","PeriodicalId":360794,"journal":{"name":"Int. J. Reason. based Intell. Syst.","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129025661","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
Research on key indicators and regional comparison of green data centre 绿色数据中心关键指标及区域比较研究
Int. J. Reason. based Intell. Syst. Pub Date : 2021-02-05 DOI: 10.1504/IJRIS.2021.113038
Mei Zhang, Fei Feng, Zhilong Zhang, J. Wen
{"title":"Research on key indicators and regional comparison of green data centre","authors":"Mei Zhang, Fei Feng, Zhilong Zhang, J. Wen","doi":"10.1504/IJRIS.2021.113038","DOIUrl":"https://doi.org/10.1504/IJRIS.2021.113038","url":null,"abstract":"With the continuous growth of the amount of information, the scale of green data centre is becoming larger and larger, and it is more and more widely used, the construction of green index system of green data centre has become a key problem to be solved urgently. This paper studied on the basic index system of green data centre, with the help of PUE, CEI and TCO index analysis, it is made in depth analysis of the factors affecting the green index of the green data centre, factor analysis is used from nine aspects such as annual average temperature, annual precipitation, air quality index, earthquake belt and fixed assets of information transmission enterprises, the mathematical model of evaluating the operation advantage of green data centre is constructed, to made quantitative analysis and evaluation classification, and according to the calculation, the comparison results of green data centre development area are obtained.","PeriodicalId":360794,"journal":{"name":"Int. J. Reason. based Intell. Syst.","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131571877","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
Multimedia-aided English online translation platform based on Bayesian theorem 基于贝叶斯定理的多媒体辅助英语在线翻译平台
Int. J. Reason. based Intell. Syst. Pub Date : 2020-12-03 DOI: 10.1504/ijris.2020.10033979
Xinfei Wang
{"title":"Multimedia-aided English online translation platform based on Bayesian theorem","authors":"Xinfei Wang","doi":"10.1504/ijris.2020.10033979","DOIUrl":"https://doi.org/10.1504/ijris.2020.10033979","url":null,"abstract":"In order to overcome the problems of the traditional online English translation platform, such as low translation efficiency, poor translation accuracy and small translation database capacity, a multimedia-aided online English translation platform based on Bayesian theorem is designed. The translation platform consists of display layer, permission control layer, logic control layer and data processing layer. This paper introduces Bayes' theorem and calculates the probability of translation from English to Chinese. In the design of query module, the translation of search words and thesaurus is selected based on Bayes' theorem, and the retrieval method is optimised. SQLite management system is used to manage the vocabulary data in the vocabulary, so as to complete the design of multimedia-assisted English online translation platform. Experimental results show that the translation accuracy of the platform designed in this paper fluctuates in the range of 86-95, and the translation time is always lower than 0.4 s, indicating that the platform not only has high translation efficiency and accuracy, but also can complete the translation of large volume data.","PeriodicalId":360794,"journal":{"name":"Int. J. Reason. based Intell. Syst.","volume":"302 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123661931","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
Multistage approach for automatic spleen segmentation in MRI sequences MRI序列脾脏自动分割的多阶段方法
Int. J. Reason. based Intell. Syst. Pub Date : 2020-04-08 DOI: 10.1504/ijris.2020.10028339
Antonia Mihaylova, V. Georgieva, P. Petrov
{"title":"Multistage approach for automatic spleen segmentation in MRI sequences","authors":"Antonia Mihaylova, V. Georgieva, P. Petrov","doi":"10.1504/ijris.2020.10028339","DOIUrl":"https://doi.org/10.1504/ijris.2020.10028339","url":null,"abstract":"Most of the known methods of segmentation of the abdominal organs are not automated for the whole series of images or are semi-automatic and require additional intervention by the user. This is typical for cases where the difference in intensity of the grey level between the subject and the background is small. This paper presents a multistage approach for spleen segmentation from MRI-sequences. It is based on segmentation methods such as active contours without edges and k-mean clustering. The proposed approach consists of some basic stages. The first stage is pre-processing, based on image enhancement and morphological operation. Two atlas models are created, which are used in the initial image to define the initial contour at which the segmentation begins. The proposed approach allows extracting the spleen in the different depth images, which has a variable form and unstable position. The conducted experiments are showing the robustness of the proposed approach. The obtained results demonstrate the effectiveness of the approach for application in screening diagnostics.","PeriodicalId":360794,"journal":{"name":"Int. J. Reason. based Intell. Syst.","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130588480","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: 4
Classification of radar non-homogenous clutter based on statistical features using neural network 基于统计特征的神经网络雷达非均匀杂波分类
Int. J. Reason. based Intell. Syst. Pub Date : 2020-04-08 DOI: 10.1504/ijris.2020.10028340
Thamir R. Saeed, Ghufran M. Hatem, J. W. A. Sadah
{"title":"Classification of radar non-homogenous clutter based on statistical features using neural network","authors":"Thamir R. Saeed, Ghufran M. Hatem, J. W. A. Sadah","doi":"10.1504/ijris.2020.10028340","DOIUrl":"https://doi.org/10.1504/ijris.2020.10028340","url":null,"abstract":"This paper presents a robust clutter classifier based on the neural network to assist the radar receiver by choosing optimal constant false alarm rate where this classifier has been trained for 16 classes, four radar return distribution with different situations. The return radar signal distributions are Rayleigh, Weibull, lognormal and K-distribution, while the situations are, signal, multi-target, closed multi-target, and clutter edge. Multilayer perceptron with back-propagation as a neural network with seven features, mean, variance, mode, kurtosis, skewness, median, and entropy, have been used to classify the return signal. A least mean square error is used to evaluate the classifier performance. The simulation is evaluated for the signal to clutter ration from +35 dB to −35 dB, with 5-20 neurons of the hidden layer, and 60-360 samples. By performing, the optimisation has been gained by using 240 samples and 20 neurons then lead to 98.1% return signal classification.","PeriodicalId":360794,"journal":{"name":"Int. J. Reason. based Intell. Syst.","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114625037","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
Multi-criteria clustering-based recommendation using Mahalanobis distance 基于马氏距离的多准则聚类推荐
Int. J. Reason. based Intell. Syst. Pub Date : 2020-04-08 DOI: 10.1504/ijris.2020.10028336
Mohammed Wasid, R. Ali
{"title":"Multi-criteria clustering-based recommendation using Mahalanobis distance","authors":"Mohammed Wasid, R. Ali","doi":"10.1504/ijris.2020.10028336","DOIUrl":"https://doi.org/10.1504/ijris.2020.10028336","url":null,"abstract":"There have been significant advances made in the research of recommender systems over the past decades and have been implemented in both industry and academia. Recently, multi-criteria ratings are being incorporated into traditional recommender systems to further improve their quality, especially to handle the data sparsity and cold start issues. However, incorporation of multi-criteria ratings have improved the performance of the recommendation, but at the same time, multi-dimensionality issue also arises. This paper presents a clustering-based recommendation approach which is used for dealing with the multi-dimensionality issue in multi-criteria recommender systems. Here, we cluster the users based on their individual criteria ratings using K-means clustering and the intra-cluster similarity is computed using Mahalanobis distance measure for neighbourhood set generation. This improves the recommendations quality and predictive accuracy of both traditional and clusteringbased collaborative recommendations. The Yahoo! Movies dataset was used for testing the approach and the experiment conducted shows promising results.","PeriodicalId":360794,"journal":{"name":"Int. J. Reason. based Intell. Syst.","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116587143","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: 9
Exchanging deep knowledge for fault diagnosis using ontologies 使用本体交换深度知识以进行故障诊断
Int. J. Reason. based Intell. Syst. Pub Date : 2020-04-08 DOI: 10.1504/ijris.2020.10028338
X. Tang, M. Xiao, Bin Hu, Dongqing Pan
{"title":"Exchanging deep knowledge for fault diagnosis using ontologies","authors":"X. Tang, M. Xiao, Bin Hu, Dongqing Pan","doi":"10.1504/ijris.2020.10028338","DOIUrl":"https://doi.org/10.1504/ijris.2020.10028338","url":null,"abstract":"To improve the development efficiency of automatical diagnosis equipment (ADE) and ensure the generality of ADE software, this paper proposes a novel method to exchange deep knowledge of systems under diagnosis (SUD) using ontologies. A general framework of knowledge base combining test information model and diagnosis information model is proposed. The diagnosis information model is decomposed into structure model and function model. The structure model describes the connectivity of adjacent components as well as the structural hierarchy, and the function model describes behaviour of modules by mapping input signals into output signals. Moreover, the method to locate the fault based on the proposed knowledge base is introduced. Finally, a case study for guiding system of passive-radar guidance missile is carried out to illustrate our proposed method. The practice shows that our method can achieve the object well.","PeriodicalId":360794,"journal":{"name":"Int. J. Reason. based Intell. Syst.","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134440067","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
下一页 尾页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：604180095
Book学术官方微信