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International Journal of Cognitive Informatics and Natural Intelligence最新文献

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Balancing Exploration and Exploitation With Decomposition-Based Dynamic Multi-Objective Evolutionary Algorithm 基于分解的动态多目标进化算法平衡探索与开发
IF 0.9
International Journal of Cognitive Informatics and Natural Intelligence Pub Date : 2021-10-01 DOI: 10.4018/IJCINI.20211001.OA25
Qing Zhang, Ruwang Jiao, Sanyou Zeng, Z. Zeng
{"title":"Balancing Exploration and Exploitation With Decomposition-Based Dynamic Multi-Objective Evolutionary Algorithm","authors":"Qing Zhang, Ruwang Jiao, Sanyou Zeng, Z. Zeng","doi":"10.4018/IJCINI.20211001.OA25","DOIUrl":"https://doi.org/10.4018/IJCINI.20211001.OA25","url":null,"abstract":"","PeriodicalId":43637,"journal":{"name":"International Journal of Cognitive Informatics and Natural Intelligence","volume":"16 1","pages":"1-23"},"PeriodicalIF":0.9,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79319035","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
Cognitive Support Tools for a Pre-Performance Routine in a Darts Game 认知支持工具在一个飞镖游戏的表演前例行程序
IF 0.9
International Journal of Cognitive Informatics and Natural Intelligence Pub Date : 2021-10-01 DOI: 10.4018/IJCINI.20211001.OA45
H. Hiraishi
{"title":"Cognitive Support Tools for a Pre-Performance Routine in a Darts Game","authors":"H. Hiraishi","doi":"10.4018/IJCINI.20211001.OA45","DOIUrl":"https://doi.org/10.4018/IJCINI.20211001.OA45","url":null,"abstract":"This paper describes two types of a cognitive support tools for a pre-performance routine (PPR) in a darts game. PPRs entail the performance of determined motions before an action and are often executed in sports for the purpose of removing stress or raising concentration. The concentration-stabilizing phenomenon was discovered by the previous research, and it determined that the phenomenon appears more conspicuous in the case of experts and PPRs. A tool using a simple brainwaves sensor has been designed and shows us the current status of concentration and notifies us of the concentration-stabilizing phenomenon on a tablet computer. Another tool has been developed on a smart watch with a heart rate sensor. The smart watch indicated heartbeat as a “beep” sound to a user. It was designed based on a result that indicated that darts game scores tend to improve by throwing immediately after a heartbeat. The effectiveness of the tools were verified in several experiments.","PeriodicalId":43637,"journal":{"name":"International Journal of Cognitive Informatics and Natural Intelligence","volume":"133 8 1","pages":"1-15"},"PeriodicalIF":0.9,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79624070","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
Analysis of Traffic Accident Features and Crash Severity Prediction 交通事故特征分析与碰撞严重程度预测
IF 0.9
International Journal of Cognitive Informatics and Natural Intelligence Pub Date : 2021-10-01 DOI: 10.4018/ijcini.20211001.oa1
Sindhu Sumukha, C. GeorgePhilip
{"title":"Analysis of Traffic Accident Features and Crash Severity Prediction","authors":"Sindhu Sumukha, C. GeorgePhilip","doi":"10.4018/ijcini.20211001.oa1","DOIUrl":"https://doi.org/10.4018/ijcini.20211001.oa1","url":null,"abstract":"Vehicle crashes occur because of numerous factors. It leads to loss of lives and permanent incapacity. The budgetary expenses of both individuals as well as for the nation are influenced by vehicle crashes. According to Road accident statistics, a total of 464910 road accidents were reported in India, claiming 1,47,913 lives and causing injuries to 4,70,975 persons every year. In this work, the UK data set sourced from Kaggle is used. For the study, 17 attributes and 35k records of the year 2015 are considered. The data set is imbalanced, so to balance out the data, the over-sampling technique is used. Random Forest, Decision tree, Logistic Regression, and Gradient Naïve Bayes algorithms are used to predict the severity of Accidents. To evaluate the model, performance measures like Accuracy, Precision, Recall, F1-Score are used. When Accuracy, Precision, F1-Score performance measure is considered Random Forest yielded the best result. When Recall performance measure is used, Random forest for Fatal, Decision Trees for Serious, Logistic regression for Slight yielded the best result.","PeriodicalId":43637,"journal":{"name":"International Journal of Cognitive Informatics and Natural Intelligence","volume":"31 1","pages":"1-18"},"PeriodicalIF":0.9,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80947414","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
A Multi-Objective Differential Evolutionary Optimization Method for Performance Optimization of Cloud Application 云应用性能优化的多目标差分进化优化方法
IF 0.9
International Journal of Cognitive Informatics and Natural Intelligence Pub Date : 2021-10-01 DOI: 10.4018/ijcini.295808
Xin Du, Youcong Ni, Peng Ye, Ruliang Xiao
{"title":"A Multi-Objective Differential Evolutionary Optimization Method for Performance Optimization of Cloud Application","authors":"Xin Du, Youcong Ni, Peng Ye, Ruliang Xiao","doi":"10.4018/ijcini.295808","DOIUrl":"https://doi.org/10.4018/ijcini.295808","url":null,"abstract":"Due to the limited search space in the existing performance optimization ap-proaches at software architectures of cloud applications (SAoCA) level, it is difficult for these methods to obtain the cloud resource usage scheme with optimal cost-performance ratio. Aiming at this problem, this paper firstly de-fines a performance optimization model called CAPOM that can enlarge the search space effectively. Secondly, an efficient differential evolutionary op-timization algorithm named MODE4CA is proposed to solve the CAPOM model by defining evolutionary operators with strategy pool and repair mechanism. Further, a method for optimizing performance at SAoCA level, called POM4CA is derived. Finally, two problem instances with different sizes are taken to conduct the experiments for comparing POM4CA with the current representative method under the light and heavy workload. The ex-perimental results show that POM4CA method can obtain better response time and spend less cost of cloud resources.","PeriodicalId":43637,"journal":{"name":"International Journal of Cognitive Informatics and Natural Intelligence","volume":"13 1","pages":"1-15"},"PeriodicalIF":0.9,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84966503","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
Eye Movement Feature Set and Predictive Model for Dyslexia: Feature Set and Predictive Model for Dyslexia 阅读障碍的眼动特征集和预测模型:阅读障碍的特征集和预测模型
IF 0.9
International Journal of Cognitive Informatics and Natural Intelligence Pub Date : 2021-10-01 DOI: 10.4018/IJCINI.20211001.OA28
Jothi Prabha Appadurai, R. Bhargavi
{"title":"Eye Movement Feature Set and Predictive Model for Dyslexia: Feature Set and Predictive Model for Dyslexia","authors":"Jothi Prabha Appadurai, R. Bhargavi","doi":"10.4018/IJCINI.20211001.OA28","DOIUrl":"https://doi.org/10.4018/IJCINI.20211001.OA28","url":null,"abstract":"Dyslexia is a learning disorder that can cause difficulties in reading or writing. Dyslexia is not a visual problem, but many dyslexics have impaired magnocellular system, which causes poor eye control. Eye-trackers are used to track eye movements. This research work proposes a set of significant eye movement features that are used to build a predictive model for dyslexia. Fixation and saccade eye events are detected using the dispersion-threshold and velocity-threshold algorithms. Various machine learning models are experimented. Validation is done on 185 subjects using 10-fold cross-validation. Velocity-based features gave high accuracy compared to statistical and dispersion features. Highest accuracy of 96% was achieved using the hybrid kernel support vector machine-particle swarm optimization model followed by the xtreme gradient boosting model with an accuracy of 95%. The best set of features are the first fixation start time, average fixation saccade duration, the total number of fixations, total number of saccades, and ratio between saccades and fixations.","PeriodicalId":43637,"journal":{"name":"International Journal of Cognitive Informatics and Natural Intelligence","volume":"26 1","pages":"1-22"},"PeriodicalIF":0.9,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86085001","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: 7
Elliptical Slot Microstrip Patch Antenna Design Based on a Dynamic Constrained Multiobjective Optimization Evolutionary Algorithm 基于动态约束多目标优化进化算法的椭圆槽微带贴片天线设计
IF 0.9
International Journal of Cognitive Informatics and Natural Intelligence Pub Date : 2021-10-01 DOI: 10.4018/ijcini.20211001.oa30
Rangzhong Wu, Caie Hu, Z. Zeng, Sanyou Zeng, Jawdat S. Alkasassbeh
{"title":"Elliptical Slot Microstrip Patch Antenna Design Based on a Dynamic Constrained Multiobjective Optimization Evolutionary Algorithm","authors":"Rangzhong Wu, Caie Hu, Z. Zeng, Sanyou Zeng, Jawdat S. Alkasassbeh","doi":"10.4018/ijcini.20211001.oa30","DOIUrl":"https://doi.org/10.4018/ijcini.20211001.oa30","url":null,"abstract":"Most evolutionary optimization algorithms have already been used for antenna design and shown promising results on improving the performance of the antenna. However, for many real-world antenna optimization problems, they are difficult to solve in that there are highly constrained and multimodal difficulty. These difficulties impede the development of antenna design. In this paper, an elliptical slot microstrip patch antenna design with these difficulties is modeled as a constrained optimization problem (COP). To address the problem, a Dynamic Constrained Multiobjective Optimization Evolutionary Algorithm(DCMOEA) is used. The experimental results show that the optimum antenna with satisfying the design requirement is obtained, and as well as we find the radiation patch should be a whole ellipse instead of subtracting with two ellipses.","PeriodicalId":43637,"journal":{"name":"International Journal of Cognitive Informatics and Natural Intelligence","volume":"131 1","pages":"1-15"},"PeriodicalIF":0.9,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86350324","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
Object-Based Scene Classification Modeled by Hidden Markov Models Architecture 基于隐马尔可夫模型的场景分类
IF 0.9
International Journal of Cognitive Informatics and Natural Intelligence Pub Date : 2021-10-01 DOI: 10.4018/ijcini.20211001.oa6
Benrais Lamine, N. Baha
{"title":"Object-Based Scene Classification Modeled by Hidden Markov Models Architecture","authors":"Benrais Lamine, N. Baha","doi":"10.4018/ijcini.20211001.oa6","DOIUrl":"https://doi.org/10.4018/ijcini.20211001.oa6","url":null,"abstract":"Multiclass classification problems such as document classification, medical diagnosis or scene classification are very challenging to address due to similarities between mutual classes. The use of reliable tools is necessary to get good classification results. This paper addresses the scene classification problem using objects as attributes. The process of classification is modeled by a famous mathematical tool: The Hidden Markov Models. We introduce suitable relations that scale the parameters of the Hidden Markov Model into variables of scene classification. The construction of Hidden Markov Chains is supported with weight measures and sorting functions. Lastly, inference algorithms extract most suitable scene categories from the Discrete Markov Chain. A parallelism approach constructs several Discrete Markov Chains in order to improve the accuracy of the classification process. We provide numerous tests on different datasets and compare classification accuracies with some state of the art methods. The proposed approach distinguishes itself by outperforming the other.","PeriodicalId":43637,"journal":{"name":"International Journal of Cognitive Informatics and Natural Intelligence","volume":"44 1","pages":"1-30"},"PeriodicalIF":0.9,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83670238","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
Feasibility of Hybrid PSO-ANN Model for Identifying Soybean Diseases 混合PSO-ANN模型识别大豆病害的可行性
IF 0.9
International Journal of Cognitive Informatics and Natural Intelligence Pub Date : 2021-10-01 DOI: 10.4018/ijcini.290328
Miaomiao Ji, Peng Liu, Qiufeng Wu
{"title":"Feasibility of Hybrid PSO-ANN Model for Identifying Soybean Diseases","authors":"Miaomiao Ji, Peng Liu, Qiufeng Wu","doi":"10.4018/ijcini.290328","DOIUrl":"https://doi.org/10.4018/ijcini.290328","url":null,"abstract":"Soybean disease has become one of vital factors restricting the sustainable development of high-yield and high-quality soybean industry. A hybrid artificial neural network (ANN) model optimized via particle swarm optimization (PSO) algorithm, which is denoted as PSO-ANN, is proposed in this paper for soybean diseases identification based on categorical feature inputs. Augmentation dataset is created via Synthetic minority over-sampling technique (SMOTE) to deal with quantitative insufficiency and categorical unbalance of the dataset. PSO algorithm is used to optimize the parameters in ANN, including the activation function, the number of hidden layers, the number of neurons in each hidden layer and the optimizer. In the end, ANN model with 2 hidden layers, 63 and 61 neurons in hidden layers respectively, Relu activation function and Adam optimizer yields the best overall test accuracy of 92.00%, compared with traditional machine learning methods. PSO-ANN shows superiority on various evaluation metrics, which may have great potential in crop diseases control for modern agriculture.","PeriodicalId":43637,"journal":{"name":"International Journal of Cognitive Informatics and Natural Intelligence","volume":"13 1","pages":"1-16"},"PeriodicalIF":0.9,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84011933","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
Laplacian Likelihood-Based Generalized Additive Model for RNA-Seq Analysis of Oral Squamous Cell Carcinoma 基于拉普拉斯似然的口腔鳞癌RNA-Seq分析的广义加性模型
IF 0.9
International Journal of Cognitive Informatics and Natural Intelligence Pub Date : 2021-10-01 DOI: 10.4018/ijcini.20211001.oa18
V. Biju, C. Prashanth
{"title":"Laplacian Likelihood-Based Generalized Additive Model for RNA-Seq Analysis of Oral Squamous Cell Carcinoma","authors":"V. Biju, C. Prashanth","doi":"10.4018/ijcini.20211001.oa18","DOIUrl":"https://doi.org/10.4018/ijcini.20211001.oa18","url":null,"abstract":"The study's objective is to identify the non-linear relationship of differentially expressed genes that vary in terms of the tumour and normal tissue and correct for any variations among the RNA-Seq experiment focused on Oral squamous cell carcinoma samples from patients. A Laplacian Likelihood version of the Generalized Additive Model is proposed and compared with the regular GAM models in terms of the non-linear fitting. The Non-Linear machine learning approach of Laplacian Likelihood-based GAM could complement RNA-Seq Analysis mainly to interpret, validate, and prioritize the patient samples data of differentially expressed genes. The analysis eases the standard parametric presumption and helps discover complexity in the association between the dependent and the independent variable and parameter smoothing that might otherwise be neglected. Concurvity, standard error, deviance, and other statistical verification have been carried out to confirm Laplacian Likelihood-based GAM efficiency.","PeriodicalId":43637,"journal":{"name":"International Journal of Cognitive Informatics and Natural Intelligence","volume":"46 1","pages":"1-19"},"PeriodicalIF":0.9,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80480235","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
Optical Flow-Based Weighted Magnitude and Direction Histograms for the Detection of Abnormal Visual Events Using Combined Classifier 基于光流加权幅度和方向直方图的组合分类器异常视觉事件检测
IF 0.9
International Journal of Cognitive Informatics and Natural Intelligence Pub Date : 2021-07-01 DOI: 10.4018/IJCINI.20210701.OA2
Gajendra Singh, Rajiv Kapoor, A. Khosla
{"title":"Optical Flow-Based Weighted Magnitude and Direction Histograms for the Detection of Abnormal Visual Events Using Combined Classifier","authors":"Gajendra Singh, Rajiv Kapoor, A. Khosla","doi":"10.4018/IJCINI.20210701.OA2","DOIUrl":"https://doi.org/10.4018/IJCINI.20210701.OA2","url":null,"abstract":"Movement information of persons is a very vital feature for abnormality detection in crowded scenes. In this paper, a new method for detection of crowd escape event in video surveillance system is proposed. The proposed method detects abnormalities based on crowd motion pattern, considering both crowd motion magnitude and direction. Motion features are described by weighted-oriented histogram of optical flow magnitude (WOHOFM) and weighted-oriented histogram of optical flow direction (WOHOFD), which describes local motion pattern. The proposed method uses semi-supervised learning approach using combined classifier (KNN and K-Means) framework to detect abnormalities in motion pattern. The authors validate the effectiveness of the proposed approach on publicly available UMN, PETS2009, and Avanue datasets consisting of events like gathering, splitting, and running. The technique reported here has been found to outperform the recent findings reported in the literature.","PeriodicalId":43637,"journal":{"name":"International Journal of Cognitive Informatics and Natural Intelligence","volume":"22 1","pages":"12-30"},"PeriodicalIF":0.9,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89469982","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
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