Cognitive Computation and Systems最新文献_第9页

Ensemble learning-based classification of microarray cancer data on tree-based features 基于树状特征的集成学习微阵列癌症数据分类

Cognitive Computation and Systems Pub Date : 2021-02-25 DOI: 10.1049/ccs2.12003

Guesh Dagnew, B.H. Shekar

{"title":"Ensemble learning-based classification of microarray cancer data on tree-based features","authors":"Guesh Dagnew, B.H. Shekar","doi":"10.1049/ccs2.12003","DOIUrl":"https://doi.org/10.1049/ccs2.12003","url":null,"abstract":"<p>Cancer is a group of related diseases with high mortality rate characterized by abnormal cell growth which attacks the body tissues. Microarray cancer data is a prominent research topic across many disciplines focused to address problems related to the higher curse of dimensionality, a small number of samples, noisy data and imbalance class. A random forest (RF) tree-based feature selection and ensemble learning based on hard voting and soft voting is proposed to classify microarray cancer data using six different base classifiers. The selected features due to RF tree are submitted to the base classifiers as the training set. Then, an ensemble learning method is applied to the base classifiers in which case each base classifier predicts class label individually. The final prediction is carried out hard and soft voting techniques that use majority voting and weighted probability on the test set. The proposed ensemble learning method is validated on eight different standard microarray cancer datasets, of which three of the datasets are binary class and the remaining five datasets are multi-class datasets. Experimental results of the proposed method show 1.00 classification accuracy on six of the datasets and 0.96 on two of the datasets.</p>","PeriodicalId":33652,"journal":{"name":"Cognitive Computation and Systems","volume":"3 1","pages":"48-60"},"PeriodicalIF":0.0,"publicationDate":"2021-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/ccs2.12003","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91870066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 12

Human motion intention recognition based on EMG signal and angle signal 基于肌电信号和角度信号的人体运动意图识别

Cognitive Computation and Systems Pub Date : 2021-02-22 DOI: 10.1049/ccs2.12002

Baixin Sun, Guang Cheng, Quanmin Dai, Tianlin Chen, Weifeng Liu, Xiaorong Xu

引用次数: 2

A review on manipulation skill acquisition through teleoperation-based learning from demonstration 远程操作示范学习中操作技能习得的研究进展

Cognitive Computation and Systems Pub Date : 2021-02-22 DOI: 10.1049/ccs2.12005

Weiyong Si, Ning Wang, Chenguang Yang

{"title":"A review on manipulation skill acquisition through teleoperation-based learning from demonstration","authors":"Weiyong Si, Ning Wang, Chenguang Yang","doi":"10.1049/ccs2.12005","DOIUrl":"https://doi.org/10.1049/ccs2.12005","url":null,"abstract":"<p>Manipulation skill learning and generalisation have gained increasing attention due to the wide applications of robot manipulators and the spurt of robot learning techniques. Especially, the learning from demonstration method has been exploited widely and successfully in the robotic community, and it is regarded as a promising direction to realise the manipulation skill learning and generalisation. In addition to the learning techniques, the immersive teleoperation enables the human to operate a remote robot with an intuitive interface and achieve the telepresence. Thus, it is a promising way to transfer manipulation skills from humans to robots by combining the learning methods and teleoperation, and adapting the learned skills to different tasks in new situations. This review, therefore, aims to provide an overview of immersive teleoperation for skill learning and generalisation to deal with complex manipulation tasks. To this end, the key technologies, for example, manipulation skill learning, multimodal interfacing for teleoperation and telerobotic control, are introduced. Then, an overview is given in terms of the most important applications of immersive teleoperation platform for robot skill learning. Finally, this survey discusses the remaining open challenges and promising research topics.</p>","PeriodicalId":33652,"journal":{"name":"Cognitive Computation and Systems","volume":"3 1","pages":"1-16"},"PeriodicalIF":0.0,"publicationDate":"2021-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/ccs2.12005","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91860353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 34

Personal-specific gait recognition based on latent orthogonal feature space 基于潜在正交特征空间的个性化步态识别

Cognitive Computation and Systems Pub Date : 2021-02-22 DOI: 10.1049/ccs2.12007

Quan Zhou, Jianhua Shan, Bin Fang, Shixin Zhang, Fuchun Sun, Wenlong Ding, Chengyin Wang, Qin Zhang

引用次数: 3

An adaptive frame slotted ALOHA anti-collision algorithm based on tag grouping 一种基于标签分组的自适应帧槽ALOHA防碰撞算法

Cognitive Computation and Systems Pub Date : 2021-02-14 DOI: 10.1049/ccs2.12001

Junsuo Qu, Ting Wang

{"title":"An adaptive frame slotted ALOHA anti-collision algorithm based on tag grouping","authors":"Junsuo Qu, Ting Wang","doi":"10.1049/ccs2.12001","DOIUrl":"https://doi.org/10.1049/ccs2.12001","url":null,"abstract":"<p>Multi-tag anti-collision is an important problem in radio frequency identification (RFID) application. Solving the problem is of great significance to the RFID technology application and the future internet of things; therefore, an adaptive frame slotted ALOHA anti-collision algorithm based on tag grouping (IGA) is proposed. First, a novel method for estimating the number of tags accurately is proposed. Through theoretical research and the experimental verification, a relationship is obtained between the ratio of the collision time slot in the frame and the average number of tags in each collision slot, which helps us to calculate the number of tags. Second, the method of estimating the number of tags is applied to the IGA algorithm. The reader randomly groups the tags after the number of tags are estimated, and recognises the tags by grouping. In the identification process, the idle time slot is skipped automatically, and the collided tags can be identified with an additional frame until all tags are identified. The simulation results show that the total time slot of the IGA algorithm is relatively small, and the identification efficiency is about 71%, which is 30% better than the the improved RFID anti-collision algorithm and 90% higher than the traditional ALOHA algorithm.</p>","PeriodicalId":33652,"journal":{"name":"Cognitive Computation and Systems","volume":"3 1","pages":"17-27"},"PeriodicalIF":0.0,"publicationDate":"2021-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/ccs2.12001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91884788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fault recognition method of smart grid data acquisition system based on FNN and sequential DS fusion 基于FNN和序列DS融合的智能电网数据采集系统故障识别方法

Cognitive Computation and Systems Pub Date : 2021-02-14 DOI: 10.1049/ccs2.12006

Hanzhe Qiao, Quanbo Ge, Haoyu Jiang, Ziyi Li, Zilong You, Jianmin Zhang, Fengjuan Bi, Chunlei Yu

{"title":"Fault recognition method of smart grid data acquisition system based on FNN and sequential DS fusion","authors":"Hanzhe Qiao, Quanbo Ge, Haoyu Jiang, Ziyi Li, Zilong You, Jianmin Zhang, Fengjuan Bi, Chunlei Yu","doi":"10.1049/ccs2.12006","DOIUrl":"https://doi.org/10.1049/ccs2.12006","url":null,"abstract":"<p>It is of significant practical importance to ensure the operational safety of the smart grid, which requires real-time fault diagnosis and identifying what causes it based on an enormous amount of data. This article further studies the intelligent fault-identification method based on the combination of multi-machine learning methods on the bases of researching on Fault Diagnosis of Smart Grid Data Acquisition System. Firstly, we should apply statistical analysis and feature extraction for fault data. Then, we can use fuzzy neural network (FNN) to calculate the probability of fault prediction of power distribution stations, manufacturers and operation businesses, and use the membership function to calculate the corresponding fault membership and uncertainty. Secondly, it makes use of Dempster/Shafer (DS) evidence sequential fusion method to realize fault membership fusion, and gives the corresponding decision criteria for failure causes. Thirdly, a fault-identification method of smart grid data-acquisition system is established based on FNN and DS Evidence Fusion. Finally, the experimental results based on the actual operation data of smart grid show that the new method has a very good application effect at fault cause identification.</p>","PeriodicalId":33652,"journal":{"name":"Cognitive Computation and Systems","volume":"3 1","pages":"28-36"},"PeriodicalIF":0.0,"publicationDate":"2021-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/ccs2.12006","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91884789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Fully in tensor computation manner: one-shot dense 3D structured light and beyond 全张量计算方式:一次密集三维结构光及以上

Cognitive Computation and Systems Pub Date : 2020-12-03 DOI: 10.1049/ccs.2019.0027

Xuan-Li Chen, Luc Van Gool

{"title":"Fully in tensor computation manner: one-shot dense 3D structured light and beyond","authors":"Xuan-Li Chen, Luc Van Gool","doi":"10.1049/ccs.2019.0027","DOIUrl":"10.1049/ccs.2019.0027","url":null,"abstract":"<div>\u0000 <p>Tensor computation evolves fast towards a prosperous existence in recent years, e.g. PyTorch. An immediate advantage of using tensor computation is that one does not need to implement low-level parallelism to attain efficient computation, which is of simplicity for both research and application development. The authors began with discovering that a simple manoeuvre ‘tensor shift’ could perform neighbourhood manipulation in very efficient parallel manner. Based on ‘tensor shift’, they derive the tensor version of a renowned correspondence search algorithm: semi-global matching (SGM), which they prefix the name as tensor-SGM. To evaluate their idea, they build-up a novel and practical one-shot structured light 3D acquisition system, which yields state-of-art reconstruction results using off-the-shelf hardware. This is the first fully tensorised 3D reconstruction system published to the authors’ best knowledge, and it opens new possibilities. A major one is, in the same tensorised framework, they solved the pattern interfering problem which hinders multi-structured light systems from working together. This part is marked as ‘beyond’ in this study to avoid confusing the readers the spotlight: the fully tensorised 3D structured light framework.</p>\u0000 </div>","PeriodicalId":33652,"journal":{"name":"Cognitive Computation and Systems","volume":"2 4","pages":"262-272"},"PeriodicalIF":0.0,"publicationDate":"2020-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/ccs.2019.0027","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127264662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Retrieval and management system for layer sound effect library 图层音效库检索与管理系统

Cognitive Computation and Systems Pub Date : 2020-11-16 DOI: 10.1049/ccs.2020.0027

Jiale Yang, Ying Zhang, Yang Hai

引用次数: 1

Robust control of vehicle multi-target adaptive cruise based on model prediction 基于模型预测的车辆多目标自适应巡航鲁棒控制

Cognitive Computation and Systems Pub Date : 2020-11-16 DOI: 10.1049/ccs.2020.0030

Zibao Zhou, Juping Zhu, Yuansheng Li

{"title":"Robust control of vehicle multi-target adaptive cruise based on model prediction","authors":"Zibao Zhou, Juping Zhu, Yuansheng Li","doi":"10.1049/ccs.2020.0030","DOIUrl":"10.1049/ccs.2020.0030","url":null,"abstract":"<div>\u0000 <p>On the issue of low utilisation and acceptance of current adaptive cruise control (ACC), a multi-objective adaptive cruise control (MO-ACC) algorithm is developed in this study. Based on model predictive control theory, comprehensively considering the coordination among various conflicting objectives, the decision of desired longitudinal acceleration is transformed into online quadratic programming (QP) problem. In order to compensate for prediction error caused by modelling mismatch, the robustness of control system is improved by introducing an error feedback correction mechanism. Meanwhile, vector management method is adopted to deal with the non-feasible solution owing to hard constraints during the process of optimisation. Further, under different work conditions, the focusing performance index along with constraint space varies, and therefore different ACC modes are established to meet the demand of skilled driving groups by means of slightly adjusting performance index, constraint space as well as slack relaxation. The simulations show that under the combined work conditions of the preceding vehicle, the following vehicle can realise seamless switching among various working modes, and also is able to achieve the good expectation during vehicle following, which will help to enhance the adaptability of the ACC system to the complex road traffic environment.</p>\u0000 </div>","PeriodicalId":33652,"journal":{"name":"Cognitive Computation and Systems","volume":"2 4","pages":"254-261"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/ccs.2020.0030","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130400828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Randomised fast no-loss expert system to play tic-tac-toe like a human 随机快速无损失专家系统，像人类一样玩井字游戏

Cognitive Computation and Systems Pub Date : 2020-11-09 DOI: 10.1049/ccs.2020.0018

Aditya Jyoti Paul

引用次数: 2