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A mixed logic dynamical modeling formulation and optimal control of intelligent robots

A mixed logic dynamical modeling formulation and optimal con...

引用

3rd International conference on optimization and Control with Applications

作者： Yin, Yingjie Hosoe, Shigeyuki Luo, Zhiwei RIKEN Biomimet Control Res Ctr Nagoya Aichi Japan Nagoya Univ Fac Engn Nagoya Aichi 464 Japan

By considering the dexterous hand manipulation problem as a hybrid system, we propose a mixed logic dynamical (MLD) modeling formulation which encapsulates phases of continuous motion, switching between types of motion, and occurrence of impacts. We first formulates the multi-contact manipulation system into a general nonlinear dynamical equation subject to (in)equality and complementarity constraints, then transform the constrained system to a MLD system model. Based on the derived MLD model, dexterous hand manipulation can be realized optimally via mixed integer quadric programming (MIQP) algorithm. This modeling formulation and an optimization approach are applied to a whole body manipulation task as an example.

关键词： multi-fingered hand hybrid system MLD model optimal control

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Ontology based approach for representing the learner profile and learning styles 3

Ontology based approach for representing the learner profile...

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3rd International conference on intelligent Computing in Data Sciences (ICDS)

作者： Bourekkache, Samir Kazar, Okba Abik, Mounia Tigane, Samir Kahloul, Laid Univ Biskra Smart Comp Sci LINFI Lab Comp Sci Dept Biskra Algeria ENSIAS Mohammed V Univ ADMIR Lab Rabat Morocco

ISBN: (纸本)9781728100036

In the era of ICT, our way of learning has known several improvements and changes. The objective of new educational systems is not delivering the learning materials through Internet or electronic devices, but they aim to use many technics and methods to enhance our learning process. Recently, increasing attention is given to these aspects such as: learning styles, learner profile, adaptive learning and their impact on learning, and how the individual characteristics and features may be supported in learning systems. These investigations are motivated by pedagogical theories that claim if we provide courses that meet the individual characteristics of learners, then it makes learning easier for them and increases the progression of their learning. Personalized learning takes into account the abilities, preferences, backgrounds, intellectual capacities, needs of learners, and learning styles, that helps the educational system to provide the appropriate activities and learning content for a particular learner. In this paper, we propose an ontological approach for the representation of learner profile and learning styles to simply use them for a personalized E-learning and to allow greater flexibility and reusability. In addition, the ontological representation of learners' profiles and learning styles gives a detailed description about them which allows the delivery of the pertinent content for each learner according to his preferences and characteristics.

关键词： Adaptive learning E-learner learner profile learning styles ontologies

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Recognizing 3D Human Motions Using Fuzzy Quantile Inference

Recognizing 3D Human Motions Using Fuzzy Quantile Inference

引用

3rd International conference on intelligent Robotics and Applications (ICIRA)

作者： Khoury, Mehdi Liu, Honghai Univ Portsmouth Inst Intelligent Syst & Robot Dept Creat Technol Portsmouth PO1 3QL Hants England

ISBN: (纸本)9783642165832

Fuzzy Quantile Inference (FQI) is a novel method that builds a simple and efficient connective between probabilistic and fuzzy paradigms and allows the classification of noisy, imprecise and complex motions while using learning samples of suboptimal size. A comparative study focusing on the recognition of multiple stances from 3d motion capture data is conducted. Results show that, when put to the test with a dataset presenting challenges such as real biologically noisy" data, cross-gait differentials from one individual to another, and relatively high dimensionality (the skeletal representation has 57 degrees of freedom), FQI outperforms sixteen other known time-invariant classifiers.

关键词： Classification (of information)

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Research on Sports Competition Result Prediction System Based on Computer Big Data Machine learning Model 3

Research on Sports Competition Result Prediction System Base...

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3rd IEEE International conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2024

作者： Lu, Xiaolong Li, Ming Ye, Chao Yunnan Vocational College of Sports Yunnan Kunming China Yunnan Youth Sports Training Center Yunnan Kunming China

ISBN: (纸本)9798350380989

Using big data theory to analyze athletes' performance data, this paper finds out the changing characteristics of athletes' performance. Using the principle of big data, we find the performance characteristics of athletes in the training process. The particle swarm optimization (PSO) method is used to predict the network parameters of support vector machine (SVM) online. The validity of this method is verified by testing on college students. This method can track athletes' performance characteristics more accurately, so as to build an excellent sports performance prediction model. The model can detect future trends from athletes' performance data in data mining and machine learning. This kind of system has a wide application prospect, and can greatly improve the efficiency and quality. The method combines machine learning theory with support vector machine network, which can effectively improve the prediction accuracy. This method has a very broad application prospect. © 2024 IEEE.

关键词： Athlete performance changing situation machine learning model prediction model

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3rd International conference on Data Management, Analytics and Innovation, ICDMAI 2019

3rd International Conference on Data Management, Analytics a...

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3rd International conference on Data Management, Analytics and Innovation, ICDMAI 2019

ISBN: (纸本)9789811393631

The proceedings contain 35 papers. The special focus in this conference is on Data Management, Analytics and Innovation. The topics include: Enhanced Prediction of Heart Disease Using Particle Swarm optimization and Rough Sets with Transductive Support Vector Machines Classifier;dataCan: Robust Approach for Genome Cancer Data Analysis;dataAutism: An Early Detection Framework of Autism in Infants using Data Science;anaBus: A Proposed Sampling Retrieval Model for Business and Historical Data Analytics;abrupt Scene Change Detection Using Block Based Local Directional Pattern;a Framework for Web Archiving and Guaranteed Retrieval;business Intelligence Through Big Data Analytics, Data Mining and Machine learning;the Effect of Big Data on the Quality of Decision-Making in Abu Dhabi Government Organisations;The Impact of Technology Readiness on the Big Data Adoption Among UAE Organisations;identifying Phishing Through Web Content and Addressed Bar-Based Features;sports Data Analytics: A Case Study of off-Field Behavior of Players;phrase Based Information Retrieval Analysis in Various Search Engines Using Machine learning Algorithms;The Politics of Artificial Intelligence Behaviour and Human Rights Violation Issues in the 2016 US Presidential Elections: An Appraisal;crop Prediction Using Artificial Neural Network and Support Vector Machine;a Hybrid and Adaptive Approach for Classification of Indian Stock Market-Related Tweets;generative Adversarial Networks as an Advancement in 2D to 3D Reconstruction Techniques;impact of Artificial Intelligence on Human Resources;role of Activation Functions and Order of Input Sequences in Question Answering;gestTalk—Real-Time Gesture to Speech Conversion Glove;a Unified Framework for Outfit Design and Advice.

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Estimating Dynamics of Honeybee Population Densities with Machine learning Algorithms 3rd

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3rd International conference on Machine learning, optimization, and Data Science (MOD)

作者： Salem, Ziad Radspieler, Gerald Griparic, Karlo Schmickl, Thomas Karl Franzens Univ Graz Artificial Life Lab Inst Zool Univ Pl 2 A-8010 Graz Austria Univ Zagreb LARICS Lab Fac Elect Engn & Comp Unska 3 Zagreb 10000 Croatia

ISBN: (纸本)9783319729268;9783319729251

The estimation of the density of a population of behaviourally diverse agents based on limited sensor data is a challenging task. We employed different machine learning algorithms and assessed their suitability for solving the task of finding the approximate number of honeybees in a circular arena based on data from an autonomous stationary robot's short range proximity sensors that can only detect a small proportion of a group of bees at any given time. We investigate the application of different machine learning algorithms to classify datasets of pre-processed, highly variable sensor data. We present a new method for the estimation of the density of bees in an arena based on a set of rules generated by the algorithms and demonstrate that the algorithm can classify the density with good accuracy. This enabled us to create a robot society that is able to develop communication channels (heat, vibration and airflow stimuli) to an animal society (honeybees) on its own.

关键词： Machine learning Data mining Classification algorithms Density estimation Robots Honeybees

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Deep Reinforcement learning using Cyclical learning Rates 3

Deep Reinforcement Learning using Cyclical Learning Rates

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3rd International conference on Artificial Intelligence for Industries (AI4I)

作者： Gulde, Ralf Tuscher, Marc Csiszar, Akos Riedel, Oliver Verl, Alexander Univ Stuttgart Inst Control Engn Machine Tools & Mfg Units D-70174 Stuttgart Germany

ISBN: (纸本)9781728187013

Deep Reinforcement learning (DRL) methods often rely on the meticulous tuning of hyperparameters to successfully resolve problems. One of the most influential parameters in optimization procedures based on stochastic gradient descent (SGD) is the learning rate. We investigate cyclical learning and propose a method for defining a general cyclical learning rate for various DRL problems. In this paper we present a method for cyclical learning applied to complex DRL problems. Our experiments show that, utilizing cyclical learning achieves similar or even better results than highly tuned fixed learning rates. This paper presents the first application of cyclical learning rates in DRL settings and is a step towards overcoming manual hyperparameter tuning.

关键词： Cyclic Cyclic learning Rates Deep Reinforcement learning Gym learning OpenAI

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T3: A classification algorithm for data mining 3rd

引用

3rd International conference on intelligent Data Engineering and Automated learning

作者： Tjortjis, C Keane, J UMIST Dept Computat Manchester M60 1QD Lancs England

ISBN: (纸本)3540440259

This paper describes and evaluates T3, an algorithm that builds trees of depth at most three, and results in high accuracy whilst keeping the size of the tree reasonably small. T3 is an improvement over T2 in that it builds larger trees and adopts a less greedy approach. T3 gave better results than both T2 and C4.5 when run against publicly available data sets: T3 decreased classification error on average by 47% and generalisation error by 29%, compared to T2;and T3 resulted in 46% smaller trees and 32% less classification error compared to C4.5. Due to its way of handling unknown values, T3 outperforms C4.5 in generalisation by 99% to 66%, on a specific medical dataset.

关键词： Data mining

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Client-server architecture for collaborative remote experimentation

Client-server architecture for collaborative remote experime...

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3rd International conference on Information Technology and Applications

作者： Callaghan, MJ Harkin, J El Gueddari, M McGinnity, TM Maguire, LP Univ Ulster Fac Engn Intelligent Syst Engn Lab Derry BT48 7JL North Ireland

ISBN: (纸本)0769523161

Experience in leaching engineering related subjects has Shown that a complementary approach combining theoretical and practical exercises is vital for effective learning. Increasingly, leaching institutions are offering remote access to distant laboratories as part of an overall e-learning strategy. However, the majority of remote laboratories developed to date have suffered from a major deficiency, namely the provision of a web based environment that accurately recreates the group working and tutor driven experience of traditional on-campus based laboratories. This paper addresses one of these issues and presents an architecture for a collaborative learning environment for remote experimentation.

关键词： Client server computer systems

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Optimisation of the optical fibre infrastructure in Mali for distance learning: An approach based on VxLAN and SDN 3

Optimisation of the optical fibre infrastructure in Mali for...

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3rd International conference on intelligent Computing and Next Generation Networks, ICNGN 2024

作者： Coulibaly, Souhahébou Ba, Mamadou Gbetie, Erick Gauthier Kora, Ahmed Dooguy Ouya, Samuel Multinational School of Telecommunications University Cheikh Anta Diop of Dakar Senegal Higher Polytechnic School - LITA University Cheikh Anta Diop of Dakar Senegal

ISBN: (纸本)9798331529222

The Malian education system, and higher education in particular, is facing problems of various kinds: lack of infrastructure, materials and equipment, poor governance, and a shortage of sufficiently qualified human resources, both in terms of teaching staff and management teams. The combination of these factors has led to a serious deterioration in teaching and learning conditions and in the quality of the training courses, the products of which are more or less unfit to meet the country’s socio-economic development needs. This study proposes a solution for optimising the existing fibre optic infrastructure to support distance learning, particularly in STEM fields. Our approach uses VxLAN (Virtual Extensible LAN) and SDN (Software-Defined Networking) technologies to create a unified and flexible virtual learning environment. We are presenting a network architecture that enables students, regardless of their geographical location, to access educational resources as if they were on a local network. This solution exploits the national fibre optic infrastructure, reducing costs while maximising accessibility. Our experiments, based on practical scenarios in automation, web development and networks, demonstrate the effectiveness of this approach in enriching the STEM learning experience. The results show a significant improvement in the accessibility of advanced educational resources and a facilitation of remote collaboration. This study paves the way for a digital transformation of higher education in Mali, offering a potential model for other developing countries facing similar challenges. It thus contributes to the overall objective of more accessible and equitable quality education. ©2024 IEEE.

关键词： Distance education

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