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International Journal of Advanced Intelligence Paradigms最新文献

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A novel map matching algorithm for real-time location using low frequency floating trajectory data 一种基于低频浮动轨迹数据的实时定位匹配算法
International Journal of Advanced Intelligence Paradigms Pub Date : 2023-01-01 DOI: 10.1504/ijaip.2023.129188
Kanta Prasad Sharma, Ramesh Chandra Poonia, Surendra Sunda
{"title":"A novel map matching algorithm for real-time location using low frequency floating trajectory data","authors":"Kanta Prasad Sharma, Ramesh Chandra Poonia, Surendra Sunda","doi":"10.1504/ijaip.2023.129188","DOIUrl":"https://doi.org/10.1504/ijaip.2023.129188","url":null,"abstract":"The continuous enhancement of technologies and modern well-equipped infrastructures are necessary for easy life. Road accident and missing vehicle ratio are very challenging in preventing misshapenness because these are continually increasing due to traffic hazards. The single way to protect human life from such type of conditions that is more reliable navigation services such as correct location tracking of vehicles on the road network. The real-time location tracking methods fully depends on the map matching algorithms, which also compute a reliable path on the road network. A smart vehicle can provide more reliable tracking services during or before any misshaping using proposed map matching algorithm. This work contributes to ensure correct location for necessary action during misshaping, alert accident zone and communicate messages without wasting valuable time. The proposed approach is validated on the real tracking data and is compared against poor GPS service.","PeriodicalId":38797,"journal":{"name":"International Journal of Advanced Intelligence Paradigms","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135535114","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
Efficient video transmission technique using clustering and optimisation algorithms in MANETs 基于聚类和优化算法的manet高效视频传输技术
International Journal of Advanced Intelligence Paradigms Pub Date : 2023-01-01 DOI: 10.1504/ijaip.2023.132371
G.N. Vivekananda, P. Chenna Reddy
{"title":"Efficient video transmission technique using clustering and optimisation algorithms in MANETs","authors":"G.N. Vivekananda, P. Chenna Reddy","doi":"10.1504/ijaip.2023.132371","DOIUrl":"https://doi.org/10.1504/ijaip.2023.132371","url":null,"abstract":"","PeriodicalId":38797,"journal":{"name":"International Journal of Advanced Intelligence Paradigms","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135733736","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
Impact of multimedia in learning profiles 多媒体对学习概况的影响
International Journal of Advanced Intelligence Paradigms Pub Date : 2023-01-01 DOI: 10.1504/ijaip.2023.128072
Ariel Zambrano, Daniela López De Luise
{"title":"Impact of multimedia in learning profiles","authors":"Ariel Zambrano, Daniela López De Luise","doi":"10.1504/ijaip.2023.128072","DOIUrl":"https://doi.org/10.1504/ijaip.2023.128072","url":null,"abstract":"The present paper has as original contribution the definition of an automated model of the behaviour of a user against a certain type of images in a context of playful learning. Therefore, the entropy is used to classify profiles, starting from temporary information, which is mixed with certain characteristics previously extracted from the images. The aim of all this is to determine to what extent visual images trigger functions of comprehension and abstraction on topics of high degree complexity. Part of the obtained model is intended to generate learning profiles, which will enrich in the future with other non-invasive device, and to observe the behaviour of the user. For example: cameras, monitory keyboard, mouse and among others. The profiles are discovered and described with the minimum information needed. The collected information is processed with bio inspired techniques, which are essentially bases on 'deep learning' concept.","PeriodicalId":38797,"journal":{"name":"International Journal of Advanced Intelligence Paradigms","volume":"130 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134996605","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
Email spam detection using bagging and boosting of machine learning classifiers 垃圾邮件检测使用装袋和提升机器学习分类器
International Journal of Advanced Intelligence Paradigms Pub Date : 2023-01-01 DOI: 10.1504/ijaip.2023.128084
Uma Bhardwaj, Priti Sharma
{"title":"Email spam detection using bagging and boosting of machine learning classifiers","authors":"Uma Bhardwaj, Priti Sharma","doi":"10.1504/ijaip.2023.128084","DOIUrl":"https://doi.org/10.1504/ijaip.2023.128084","url":null,"abstract":"The increase in the popularity, utility, and significance of electronic mails has also raised the exposure of spam emails. This paper endeavours to detect email spam by constructing an ensemble system using bagging and boosting of machine learning techniques. The dataset used for the experimentation is Ling-Spam Corpus. The system detects spam email by bagging the machine learning-based multinomial Naïve Bayes (MNB) and J48 decision tree classifiers followed by the boosting technique of converting weak classifiers into strong by implementing the Adaboost algorithm. The experimentation includes three different experiments and the results attained are compared with each other. Experiment 1 employs the individual classifiers, experiment 2 ensembles the classifiers with bagging approach, and experiment 3 ensembles the classifiers by implementing the boosting approach for the email spam detection. The effectiveness of the ensemble methods is manifested by comparing the evaluated results with individual classifiers in terms of evaluation metrics.","PeriodicalId":38797,"journal":{"name":"International Journal of Advanced Intelligence Paradigms","volume":"313 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134996606","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
Face recognition using local binary pattern and Gabor-Kernel Fisher analysis 基于局部二值模式和Gabor-Kernel Fisher分析的人脸识别
International Journal of Advanced Intelligence Paradigms Pub Date : 2023-01-01 DOI: 10.1504/ijaip.2023.10058844
Hemantha Kumar Kalluri, Tulasi Krishna Sajja
{"title":"Face recognition using local binary pattern and Gabor-Kernel Fisher analysis","authors":"Hemantha Kumar Kalluri, Tulasi Krishna Sajja","doi":"10.1504/ijaip.2023.10058844","DOIUrl":"https://doi.org/10.1504/ijaip.2023.10058844","url":null,"abstract":"","PeriodicalId":38797,"journal":{"name":"International Journal of Advanced Intelligence Paradigms","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134889030","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
Elephant herd optimisation algorithm for solving optimal reactive power problem 求解最优无功功率问题的象群优化算法
International Journal of Advanced Intelligence Paradigms Pub Date : 2020-05-08 DOI: 10.1504/ijaip.2020.10029406
K. Lenin
{"title":"Elephant herd optimisation algorithm for solving optimal reactive power problem","authors":"K. Lenin","doi":"10.1504/ijaip.2020.10029406","DOIUrl":"https://doi.org/10.1504/ijaip.2020.10029406","url":null,"abstract":"Multifaceted deeds of elephants are considered for a bio-inspired algorithm model. In this work reactive power optimisation problem is solved by elephant herd optimisation (EHO) algorithm. Normally elephants lead the life as clan under the single leadership of matriarch and during mathematical modelling population of elephants are alienated to have a mixture of relations. In each cycle of generation, male elephants leave their clan at matured stage and move far away from the clan. In first step of the algorithm elephant population are segregated as 'k' clans. Exploration and exploitation has been balanced throughout the process. Proposed EHO algorithm is evaluated in IEEE-30, 57,118,300 systems without considering voltage stability index. Then in IEEE 30 bus system with considering voltage stability index criterion, evaluation has been done. Voltage stability index value increased and power loss reduced considerably.","PeriodicalId":38797,"journal":{"name":"International Journal of Advanced Intelligence Paradigms","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47535744","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
Multi-objective Multi-Join Query Optimization using Modified Grey Wolf Optimization 基于改进灰狼优化的多目标多连接查询优化
International Journal of Advanced Intelligence Paradigms Pub Date : 2020-04-16 DOI: 10.1504/IJAIP.2020.10019251
Deepak Kumar, Sushil Kumar, Rohit Bansal
{"title":"Multi-objective Multi-Join Query Optimization using Modified Grey Wolf Optimization","authors":"Deepak Kumar, Sushil Kumar, Rohit Bansal","doi":"10.1504/IJAIP.2020.10019251","DOIUrl":"https://doi.org/10.1504/IJAIP.2020.10019251","url":null,"abstract":"Nowadays information retrieved by a query is based upon extracting data across the world, which are located in different data sites. In distributed database management systems (DDBMS), due to partitioning or replication of data among several sites the relations required for an answer of a query may be stored at several data sites (DS). Many experimental results have showed that combination of optimal join order (OJO) and optimal selection of relations in query plan (QP) gives out better results compare to the several existing query optimising methodologies like teacher-learner based optimisation (TLBO), genetic algorithm (GA), etc. In this paper an approach has been proposed to compute a best optimal QP that could answer the user query with minimal cost values and minimum time using modified grey wolf optimisation algorithm (MGWO) which is multi-objective constrained. Proposed approach also aims for producing OJO in order to reduce the dimensionality complexity of the QP.","PeriodicalId":38797,"journal":{"name":"International Journal of Advanced Intelligence Paradigms","volume":"17 1","pages":"67-79"},"PeriodicalIF":0.0,"publicationDate":"2020-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44858036","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
SCALABLE INFORMATION RETRIEVAL SYSTEM IN SEMANTIC WEB BY QUERY EXPANSION AND ONTOLOGICAL BASED LSA RANKING SIMILARITY MEASUREMENT 基于查询扩展和本体的lsa排序相似度度量的语义网可扩展信息检索系统
International Journal of Advanced Intelligence Paradigms Pub Date : 2020-04-16 DOI: 10.1504/IJAIP.2020.10013899
M. Devi, G. Gandhi
{"title":"SCALABLE INFORMATION RETRIEVAL SYSTEM IN SEMANTIC WEB BY QUERY EXPANSION AND ONTOLOGICAL BASED LSA RANKING SIMILARITY MEASUREMENT","authors":"M. Devi, G. Gandhi","doi":"10.1504/IJAIP.2020.10013899","DOIUrl":"https://doi.org/10.1504/IJAIP.2020.10013899","url":null,"abstract":"In recent days, semantic web presents a key role in intelligent retrieval of information system that resolves vocabulary mismatch problem by query expansion process. However, achieving the scalable information retrieval (IR) in semantic web is a challenging issue in a large dataset. The semantic IR problem is addressed by an ontological-based semantic similarity measurement using natural language processing. The two novel algorithms namely syntactic correlation coefficient (SCC) and mapping-based K-nearest neighbour (M-KNN) for semantic similarity measurement is proposed which improves the accuracy of relevant result. The ontological constructs with word sense disambiguation (WSD) algorithm for document repository improves the conceptual relationships, reduces the ambiguities in ontology and improves scalability by intensely analysing the semantic relationship as well as dynamically reconstructing the ontology when numbers of documents are updated. Ranking is done with latent semantic analysis (LSA) after semantic similarity analysis, which improves the retrieved result and reduces the complexity in relevancy. The performance of the system is analysed with respect to different metrics such as processing time, F-measure (0.97), time complexity, precision (0.95), recall (0.98) and space complexity.","PeriodicalId":38797,"journal":{"name":"International Journal of Advanced Intelligence Paradigms","volume":"17 1","pages":"44-66"},"PeriodicalIF":0.0,"publicationDate":"2020-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45936030","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
Speech-based automatic personality trait prediction analysis 基于语音的人格特征自动预测分析
International Journal of Advanced Intelligence Paradigms Pub Date : 2020-04-16 DOI: 10.1504/ijaip.2020.10028512
J. Sangeetha, R. Brindha, S. Jothilakshmi
{"title":"Speech-based automatic personality trait prediction analysis","authors":"J. Sangeetha, R. Brindha, S. Jothilakshmi","doi":"10.1504/ijaip.2020.10028512","DOIUrl":"https://doi.org/10.1504/ijaip.2020.10028512","url":null,"abstract":"Automatic personality perception is the prediction of personality that others attribute to a person in a given situation. The aim of automatic personality perception is to predict the personality of the speaker perceived by the listener from nonverbal behaviour. Extroversion, conscientiousness, agreeableness, neuroticism, and openness are the speaker traits used for personality assessment. In this work, a speaker trait prediction approach for automatic personality assessment has been proposed. This approach is based on modelling the relationship between speech signal and personality traits. The experiments are performed over the SSPNet speaker personality corpus. For speaker trait prediction, support vector machines (SVM), multilayer perceptron (MLP), and instance-based k-nearest neighbour were analysed with multiple features. Various features have been analysed to find suitable feature for various speaker traits. The analyses have been conducted using pitch, formant, and mel frequency cepstral coefficients (MFCC) and the analysis results are presented. The accuracy of 100% has been obtained for MFCC features with 19 coefficients.","PeriodicalId":38797,"journal":{"name":"International Journal of Advanced Intelligence Paradigms","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43839740","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
Support Vector Machine based proactive fault-tolerant scheduling for Grid Computing Environment 网格计算环境下基于支持向量机的主动容错调度
International Journal of Advanced Intelligence Paradigms Pub Date : 2020-04-13 DOI: 10.1504/IJAIP.2020.10017213
A. Ebenezer, E. Rajsingh, B. Kaliaperumal
{"title":"Support Vector Machine based proactive fault-tolerant scheduling for Grid Computing Environment","authors":"A. Ebenezer, E. Rajsingh, B. Kaliaperumal","doi":"10.1504/IJAIP.2020.10017213","DOIUrl":"https://doi.org/10.1504/IJAIP.2020.10017213","url":null,"abstract":"To classify the reliable resources accurately and perform a proactive fault tolerant scheduling in grid computing environment, a combination of support vector machine (SVM) with the quantum-behaved particle swarm optimization using Gaussian distributed local attractor point (GAQPSO) is proposed in this paper. When tuned with appropriate kernel parameters, the SVM classifier provides high accuracy in reliable resource prediction. The higher diversity of GAQPSO compared to other variants of QPSO, reduces the makespan of the schedule significantly. The performance of the SVM-GAQPSO scheduler is analysed in terms of the makespan, reliability, and accuracy. The empirical result shows that the reliability of the SVM-GAQPSO scheduler is 14% higher than the average reliability of the compared algorithms. Also, the accuracy of prediction using the SVM classifier is 92.55% and it is 37.2% high compared to classification and regression trees (CART), linear discriminant analysis (LDA), K-nearest neighbourhood (K-NN), and random forest (RF) algorithm.","PeriodicalId":38797,"journal":{"name":"International Journal of Advanced Intelligence Paradigms","volume":"16 1","pages":"381-403"},"PeriodicalIF":0.0,"publicationDate":"2020-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43574944","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
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