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检索条件"任意字段=Proceedings of the 2023 4th International Conference on Machine Learning and Computer Application"

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Wearables, Social Networking and Veracity : the Building Blocks of a Verified Exercise application 4

Wearables, Social Networking and Veracity : The Building Blo...

引用

4th IEEE international conference on Artificial Intelligence with applications in Engineering and Technology (ICAIET)

作者： Ho, Chiung Ching Sharifi, Mehdi Multimedia Univ Fac Comp & Informat Cyberjaya Malaysia

ISBN: (纸本)9781479979103

Research and development of exercise recognition applications have predominantly focused on motion related exercise, with not much emphasis on weight lifting exercise. At the same time, while such applications supports the posting of completed exercise session on social network, the veracity of the post is entirely determined by the user of the application. In this paper, we present the building blocks for a weight lifting application. It recognizes and counts the number of repetitions of a weight lifting exercise, and subsequently posts it on the user's behalf, thus ensuring the veracity of the post. Our empirical results demonstrate the potential of such an application.

关键词： wearables weight lifting exercise recognition social media integration machine learning

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application of machine learning for NonHolonomic Mobile Robot Trajectory Controlling 4

Application of Machine Learning for NonHolonomic Mobile Robo...

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4th international conference on computer and Knowledge Engineering (ICCKE)

作者： Gohari, Mohammad Tahmasebi, Mona Nozari, Amin Arak Univ Teclmol Fac Mech Engn Arak Iran Agr Minist Iran Arak Iran

ISBN: (纸本)9781479954865

Mobile robots are very interested by researchers over the last few years because of their applications and physical characteristics. the workspace of mobile robots is not always ideal, but typically filled with disturbances (known or unknown) such as uneven surface terrain, natural friction, uncertainties, and parametric changes. In this study, a new approach namely active force control (AFC) scheme integrating artificial neural network (ANN) has been suggested to cope on the disturbances and thus improve the trajectory tracking characteristic of the system therefore, a two wheeled mobile robot has been simulated, and ANN technique is explicitly employed for the estimation of the inertia matrix that is needed in the inner feedback control loop of the AFC scheme. the robustness and efficiency of the identified control scheme are studied considering various forms of loading and operating conditions. For the purpose of benchmarking, the AFC scheme performance has been compared to PID controller.

关键词： Differentially Driven Mobile Robot Machin learning Active Force Control Artificial Neural Network Nonholonomic System

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MKL-SVM-based Human Detection for Autonomous Navigation of a Robot 9

MKL-SVM-based Human Detection for Autonomous Navigation of a...

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9th IEEE international conference on computer Science and Education (ICCSE)

作者： Zhang, Yunfei Bhatt, Rajen de Silva, Clarence W. Univ British Columbia Dept Mech Engn Vancouver BC V6T 1Z4 Canada North Amer Robot Bosch LLC Res & Technol Ctr Pittsburgh PA 15203 USA

ISBN: (纸本)9781479929511

this paper presents a classifier trained by a multiple kernel-learning support vector machine (MKL-SVM) to detect a human in sequential images from a video stream. the developed method consists of two aspects: multiple features consisting of HOG features and HOF features suitable for moving objects, and combined nonlinear kernels for SVM. For the purpose of real time application in autonomous navigation, the SimpleMKL algorithm is implemented into the proposed MKL-SVM classifier. It is able to converge rapidly with comparable efficiency through a weighted 2-norm regularization formulation with an additional constraint on the weights. the classifier is compared with the state-of-the-art linear SVM using a dataset called TUD-Brussels, which is available on line. the results show that the proposed classifier outperforms the Linear SVM with respect to accuracy.

关键词： Robtic navigation support vector machine multiple kernel learning human detection

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A novel approach to model design and tuning through automatic parameter screening and optimization theory and application to a helicopter flight simulator case-study 4

A novel approach to model design and tuning through automati...

引用

4th international conference on Simulation and Modeling Methodologies, Technologies and applications, SIMULTECH 2014

作者： Hessel, Matteo Borgatelli, Francesco Ortalli, Fabio Engineering of Computing Systems Politecnico di Milano Piazza Leonardo Da Vinci 32 Milano Italy TXT Next TXT e-Solutions Via Frigia 27 Milano Italy

ISBN: (纸本)9789897580383

the aim of this paper is to describe a novel methodology for model-design and tuning in computer simulations, based on automatic parameter screening and optimization. Simulation requires three steps: mathematical modelling, numerical solution, and tuning of the model’s parameters. We address Tuning because, at the state-of-the-art, the development of life-critical simulations requires months to appropriately tune the model. Our methodology can be split in Screening (identification of the relevant parameters to simulate a system) and Optimization (search of optimal values for those parameters). All techniques are fully general, because they leverage ideas from machine-learning and Optimization theory to achieve their goals without directly analysing the simulator’s mathematical model. Concerning screening, we show how machine-learning algorithms, based on Neural Networks and Logistic Regression, can be used for ranking the parameters according to their relevance. Concerning optimization, we describe two algorithms: an adaptive hill-climbing procedure and a novel strategy, specific for model tuning, called sequential masking. Eventually, we show the performances achieved and the impact on the time and effort required for tuning a helicopter flight-simulator, proving that the proposed techniques can significantly speed-up the process. © 2014 SciTePress. All rights reserved.

关键词： Optimization

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machine learning approach for forecasting crop yield based on climatic parameters 4

Machine learning approach for forecasting crop yield based o...

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4th international conference on computer Communication and Informatics (ICCCI)

作者： Veenadhari, S. Misra, Bharat Singh, C. D. MGCGV Chitrakoot Madhya Pradesh India CIAE Bhopal Madhya Pradesh India

ISBN: (纸本)9781479923526

With the impact of climate change in India, majority of the agricultural crops are being badly affected interms of their performance over a period of last two decades. Predicting the crop yield well ahead of its harvest would help the policy makers and farmers for taking appropriate measures for marketing and storage. Such predictions will also help the associated industries for planning the logistics of their business. Several methods of predicting and modeling crop yields have been developed in the past with varying rateof success, as these don't take into account characteristicsoftheweather, and aremostly empirical. In the present study a software tool named 'Crop Advisor' has been developed as an user friendly web page for predicting the influence of climatic parameters on the crop yields. C4.5 algorithm is used to find out the most influencing climatic parameter on the crop yields of selected crops in selected districts of Madhya Pradesh. this software provides an indication of relative influence of different climatic parameters on the crop yield, other agro-input parameters responsible for crop yield are not considered in this tool, since, application of these input parameters varies with individual fields in space and time.

关键词： Climate agricultural productivity C4.5 alogarithm prediction

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Predicting arousal with machine learning of EEG signals 5

Predicting arousal with machine learning of EEG signals

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5th IEEE international conference on Cognitive Infocommunications, CogInfoCom 2014

作者： Nagya, Tamás Telleza, David Divák, Ádam Lógób, Emma Kólesb, Máté Hámornikb, Bálazs Synetiq Ltd. Krisztina krt. 99. BudapestH-1016 Hungary Budapesti Muszaki És Gazdaságtudományi Egyetem Ergónómia És Pszichológia Tanszék Magyar Tudósok körútja 2 BudapestH-1117 Hungary

ISBN: (纸本)9781479972807

the usage of brain-computer interface (BCI) is becoming more and more popular in real life settings. As BCI equipment increases in ubiquity, the potential for application areas also rises. Present utilization of BCI includes - among others - prosthesis control [1], neurofeedback training [2], and neuromarketing [3]. A now popular field of BCI is the automatic identification of emotions using different physiological devices [4], [5]. the following study represents our effort to identify the arousal component of emotion [6] using EEG. Contrary to previous studies - that have mostly used questionnaire responses to assess arousal [4], [7] - our approach involved the use of objective physiological markers to gauge arousal. © 2014 IEEE.

关键词： Brain computer interface

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application and research of data mining technology in communication network environment

Application and research of data mining technology in commun...

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4th international conference on Materials Science and Information Technology, MSIT 2014

作者： Zhi, Zhang Jiangxi Science and Technology Normal University Technique Center of Modern Education Jiangx i Nanchang 330013 China

ISBN: (纸本)9783038351733

the abnormal data of communication networks are complex and diverse, it is difficult to recognize and mine the abnormal data accurately and effectively with traditional methods. In order to improve the recognition accuracy of communication network, a data mining algorithms based on the method of communication network abnormal data recognition is presented. Firstly, the communication network data samples are analyzed for fuzzy c-means clustering in order to obtain the degree of membership matrix. Secondly, the training samples of communication network abnormal data mining are selected according to the membership. At last, the training samples are put into the least square support vector machine learning, which establish the model of abnormal data identification in communication network. the performance of the algorithm was tested by simulation tests, and the results show that, the abnormal data recognition efficiency and accuracy in this paper was improved much more than the traditional identification methods. © (2014) Trans Tech Publications, Switzerland.

关键词： Data mining

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A novel approach to model design and tuning through automatic parameter screening and optimization theory and application to a helicopter flight simulator case-study

A novel approach to model design and tuning through automati...

引用

international conference on Simulation and Modeling Methodologies, Technologies and applications (SIMULTECH)

作者： Matteo Hessel Francesco Borgatelli Fabio Ortalli Engineering of Computing Systems Politecnico di Milano Piazza Leonardo Da Vinci 32 Italy TXT Next TXT e-solutions Milano Italy

the aim of this paper is to describe a novel methodology for model-design and tuning in computer simulations, based on automatic parameter screening and optimization. Simulation requires three steps: mathematical modelling, numerical solution, and tuning of the model's parameters. We address Tuning because, at the state-of-the-art, the development of life-critical simulations requires months to appropriately tune the model. Our methodology can be split in Screening (identification of the relevant parameters to simulate a system) and Optimization (search of optimal values for those parameters). All techniques are fully general, because they leverage ideas from machine-learning and Optimization theory to achieve their goals without directly analysing the simulator's mathematical model. Concerning screening, we show how machine-learning algorithms, based on Neural Networks and Logistic Regression, can be used for ranking the parameters according to their relevance. Concerning optimization, we describe two algorithms: an adaptive hill-climbing procedure and a novel strategy, specific for model tuning, called sequential masking. Eventually, we show the performances achieved and the impact on the time and effort required for tuning a helicopter flight-simulator, proving that the proposed techniques can significantly speed-up the process.

关键词： Mathematical model Computational modeling Tuning Numerical models Optimization Logistics Databases

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application of Multivariable Sequential Patterns Mining in Teaching Effect Evaluation

Application of Multivariable Sequential Patterns Mining in T...

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2013 IEEE 4th international conference on Software Engineering and Service Science

作者： Yan Liu Xiaowei Qin Yan Zou Computer and Information Engineering College Chifeng University

ISBN: (纸本)9781467349994

Build the multivariable model for teaching effect evaluation in tutoring system,and discuss the algorithm and application of multivariable sequential patterns mining in tutoring *** mining results can find the learning habits and advantages of students,and help students to correct learning method and increase learning interest,so that we can realize the intervention and guidance of learning activities through tutoring system.

关键词： teaching effect evaluation multivariable sequences sequential patterns

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Evaluation of a language learning application in Facebook

Evaluation of a language learning application in Facebook

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4th international conference on Information, Intelligence, Systems and applications, IISA 2013

作者： Troussas, Christos Virvou, Maria Caro, Jaime Espinosa, Kurt Junshean Department of Informatics University of Piraeus Piraeus Greece Department of Computer Science University of the Philippines Quezon City Philippines

ISBN: (纸本)9781479907717

Facebook applications are more convenient and flexible to use, since students tend to invest a good deal of time in the use of such technologies, given that Facebook retains the educational quality, as it is widely used in instructional contexts. To this direction, our Facebook application promotes language learning. Furthermore, it incorporates machine learning techniques in order to offer user classification based on multiple user characteristics. Our resulting Facebook language learning application has been evaluated by both instructors and Facebook users. the results of the evaluation showed that Facebook provides opportunities within curriculum education and learning and user classification in such applications promotes the cognitive procedure. © 2013 IEEE.

关键词： computer aided instruction

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