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Articles 5911 - 5940 of 11192

Full-Text Articles in Artificial Intelligence and Robotics

Research And Application On Space-Launching Mission Simulated Rehearsal Technology, Xiuluo Liu, Wang Jia, Wu Feng, Liu Yang, Ailiang Zhang, Wang Min Sep 2021

Research And Application On Space-Launching Mission Simulated Rehearsal Technology, Xiuluo Liu, Wang Jia, Wu Feng, Liu Yang, Ailiang Zhang, Wang Min

Journal of System Simulation

Abstract: High-density space launching tasks need the new requirements for space-launching mission rehearsal. The new concept of space-launching mission simulated rehearsal is proposed, the definition and content are presented in detail,and the technology research objective and key works are analyzed. The technology implementation architecture is established on five dimensions of the domain resources, developing tools, simulation modeling, fundamental function design and domain application. On the basis of simulation, the working process is given, the simulation software architecture is designed, and the simulation application tool is developed. The simulation results are also given, which validate the method and technology.

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Mechanism Design For Entities' Passive Dimensional Sensing Interaction In Discrete Event Simulations, Yan Fei, Bin Gan, Zhaodi Chen, Wenjuan Ma, Luyao Li, Zhang Ke Sep 2021

Mechanism Design For Entities' Passive Dimensional Sensing Interaction In Discrete Event Simulations, Yan Fei, Bin Gan, Zhaodi Chen, Wenjuan Ma, Luyao Li, Zhang Ke

Journal of System Simulation

Abstract: Dimensional sensing interaction mechanism is a method of computing the entities' visibility on the basis of the position and visible range, and informing when and where the entities can perceive each other. Entities' active computing on the relative position needs a lot of computation and is low efficiency, and slow down the simulation execution at last. The mechanism and framework of the passive dimensional sensing interaction, including the spatial grid models, discrete movement models, and passive sense models are researched. Dimensional sensing interaction manager is designed to realize the computation of entities' dimensional sensing interaction in discrete event-based battle …

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Research On The Issues Of Next Generation Wargame System Model Engine, Yubo Tang, Bilong Shen, Shi Lei, Yi Xing Sep 2021

Research On The Issues Of Next Generation Wargame System Model Engine, Yubo Tang, Bilong Shen, Shi Lei, Yi Xing

Journal of System Simulation

Abstract: Aiming at the more and more complex war systems, widely used artificial intelligence technology is needed to make up the human deficiencies in future wargame deduction, which is necessary for the next generation wargame system model engine. To address these challenges, a framework prototype of the next generation wargame model engine based on the experience of the long-term development and application is proposed. The decoupling method for the complexity of structure and computation is researched. The human-computer integration architecture on digital twinning technology is studied. Some new modeling techniques which the threshold of model development is reduced and the …

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Abroad Wargaming Deduction And System Research, Zhanguang Cao, Tao Shuai, Xiaofeng Hu, Lülong He Sep 2021

Abroad Wargaming Deduction And System Research, Zhanguang Cao, Tao Shuai, Xiaofeng Hu, Lülong He

Journal of System Simulation

Abstract: Wargaming is an important auxiliary means of war deduction, scheme evaluation and operational analysis. Wargaming deduction system can support the research of operational problems, innovation of tactics and development of operational concepts. The development status of foreign computer wargaming system from the deduction method and system research is reviewed, and the online deduction the multi-level joint deduction, as well as the research status of multi-level wargaming fusion design, the multi system combination and auxiliary tool development are mainly introduced, which can providereference to the development and application of computer wargame system.

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Fault Diagnosis Of Industrial Process Based On Lle And K-Means Clustering Algorithm, Li Yuan, Zewei Geng Sep 2021

Fault Diagnosis Of Industrial Process Based On Lle And K-Means Clustering Algorithm, Li Yuan, Zewei Geng

Journal of System Simulation

Abstract: Because of the similarity of various types of data in the industrial process. The fault diagnosis using the K-means algorithm has a large error rate. A K-means clustering algorithm based on Locally Linear Embedding (LLE) is proposed. the normal data is reduced by the LLE algorithm and the projection matrix is obtained. The projection matrix is used to map the original fault data to the low-dimensional space and the K-means algorithm clusters is used to carry out the data to establish a detection and diagnosis model. The method is applied to the fault detection and diagnosis in the TE …

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Optimization Algorithm Of Mine Ventilation Based On Sa-Ipso, Liangshan Shao, Wang Zhen, Changming Li Sep 2021

Optimization Algorithm Of Mine Ventilation Based On Sa-Ipso, Liangshan Shao, Wang Zhen, Changming Li

Journal of System Simulation

Abstract: A non-linear optimization mathematical model aiming at the minimum total power of the mine ventilation network is established, in which SA-IPSO algorithm is applied for the optimization. The mutation operation is introduced in the PSO algorithm, in which a new inertia weight is proposed and a new particle selection method is constructed to control the number of particles violating the constraints, and the ability of the PSO algorithm to find boundaries is improved. The constraint conditions of the mine ventilation law are transformed into the penalty term of the objective function. IPSO optimizes the objective function and uses SA …

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An Improved Srgan Infrared Image Super-Resolution Reconstruction Algorithm, Hu Lei, Zugen Wang, Chen Tian, Yongmei Zhang Sep 2021

An Improved Srgan Infrared Image Super-Resolution Reconstruction Algorithm, Hu Lei, Zugen Wang, Chen Tian, Yongmei Zhang

Journal of System Simulation

Abstract: Aiming at the low resolution of infrared images, an improved SRGAN super-resolution reconstruction algorithm is designed. In the generative network, the method of applying the residual dense network to obtain the image features extracted from each network layer so as to retain more high-frequency information of the image, and adopting a progressive upsampling method to improve the super-resolution reconstruction effect under a large scaling factor. In terms of the loss function, the perceptual loss that is more in line with human senses is adopted to make the generated image being closer to the real high-resolution image of senses and …

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Trajectory Planning Of 6-Dof Manipulator Based On Inverse Multi-Objective Optimization, Xianyin Duan, Can Zhang, Zerun Zhu, Zhaoyang Sun, Guozhang Jiang, Xiang Feng Sep 2021

Trajectory Planning Of 6-Dof Manipulator Based On Inverse Multi-Objective Optimization, Xianyin Duan, Can Zhang, Zerun Zhu, Zhaoyang Sun, Guozhang Jiang, Xiang Feng

Journal of System Simulation

Abstract: In order to optimize the machining quality and production efficiency of manipulator, an inverse multi-objective determination method based on the optimization of manipulator stiffness and global travel is proposed. Establishing the forward kinematics model of manipulator, the inverse kinematics is solved by using behaviour tree. The stiffness performance evaluation index and the mathematical model of total stroke of joint angle are constructed to carry out the inverse solution multi-objective optimization. The 7-5-7 order polynomial joint space interpolation algorithm is designed for the trajectory planning. Compared with the commonly used cubic polynomial programming method, the manipulator trajectory obtained by …

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Chaotic Gravitational Search Iterative Identification For Wiener Systems, Shanling Xu, Junhong Li, Mengru Liu, Hua Liang Sep 2021

Chaotic Gravitational Search Iterative Identification For Wiener Systems, Shanling Xu, Junhong Li, Mengru Liu, Hua Liang

Journal of System Simulation

Abstract: The Wiener nonlinear system is composed of a dynamic linear subsystem and a series of nonlinear static subsystems, which is widely used in the fields of automatic control, chemical engineering, electrical and other fields. Considering the identification of the Wiener Output Error Autoregressive (Wiener OEAR) system, a chaotic gravitational search iterative identification algorithm is proposed, in which the chaotic optimization mechanism is introduced into the gravitational search algorithm to estimate the unknown parameters of the Wiener OEAR system and the convergence is proved. In order to show the effectiveness of the proposed identification algorithm, the gravitational search algorithm and …

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Multi-Uav Trajectory Planning Simulation Based On Adaptive Extended Potential Field, Wang Ning, Jiyang Dai, Ying Jin, Yeding Li, Liangliang Lu Sep 2021

Multi-Uav Trajectory Planning Simulation Based On Adaptive Extended Potential Field, Wang Ning, Jiyang Dai, Ying Jin, Yeding Li, Liangliang Lu

Journal of System Simulation

Abstract: To address the defects of the traditional artificial potential field method, such as unreachable targets, easy to fall into local minimums, inability to avoid obstacles, and lack of trajectory optimization strategies, and to solve the problem of slow planning rate due to more layers in the layered potential field algorithm, the model of the UAV is established, in which the influence factor of the attractive and repulsive force is introduced into the layered potential field function to solve the problem of unreachable targets, and the " auxiliary force" is introduced to solve the problem of easily falling into local …

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Simulation On Aviation Maintenance Support System Based On Goal-Driven, Jiping Cong, Lijie Cui, Ding Gang, Ren Bo Sep 2021

Simulation On Aviation Maintenance Support System Based On Goal-Driven, Jiping Cong, Lijie Cui, Ding Gang, Ren Bo

Journal of System Simulation

Abstract: Aiming at the large investment and long time for optimization in aviation maintenance support model practice, for the first time, based on Netlogo platform, the multi-agent aviation maintenance support simulation system is constructed, which provides a reference to adapt the current support tasks and improve the evaluation efficiency. Selecting the annual mission flight time, echelon status, aircraft intact rate, and mission completion rate as the goal drivers, the simulation on different aviation maintenance support process is carried out, which displays the changes in flight arrangements, aircraft status, personnel, support equipment, etc. The simulation experiment shows that the multi-agent …

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Modeling And Simulation On Optimum Maneuver Control Surface Configuration Of Aircraft In Low Altitude Penetration Mode, Huzi Wu, Wang Jin, Wantao Qi, Kaibao Jin Sep 2021

Modeling And Simulation On Optimum Maneuver Control Surface Configuration Of Aircraft In Low Altitude Penetration Mode, Huzi Wu, Wang Jin, Wantao Qi, Kaibao Jin

Journal of System Simulation

Abstract: Optimum maneuver control surface can ensure the safety flight cability of aircraft in low altitude penetration mode, and it is of great siginifcance to establish the valid and effective numerical simulation model. The numerical differential equations with muti-constraints is adopted for the first time, to construct the simulaton model for the aircraft with small wing load and mutifunctional and combined CS in low altitude manuever, the schemes of different maneuver CS considering the obstacle, the limit of angle of bank, the graident of climb are built. The simulation results show that the model is effective for solving the …

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Research On Simulation Object Interfaces Oriented To Plug-In-Play Pattern, Zhongwei Lin, Xiuhe Li, Yiping Yao, Shen Yang, Shaoqi Dai, Qianqian Shi Sep 2021

Research On Simulation Object Interfaces Oriented To Plug-In-Play Pattern, Zhongwei Lin, Xiuhe Li, Yiping Yao, Shen Yang, Shaoqi Dai, Qianqian Shi

Journal of System Simulation

Abstract: Models and simulation engines provide services mainly in the format of executable files in cloud environment, thus plug-in-play pattern becomes the first choice of simulation, which needs necessitating interfaces to connect the model processing logics and the simulation engine control logics. A set of simulation object interfaces that covers the simulation full life cycle of initialization, event scheduling, processing and cancel, publish and processing of subscription, roll-back and termination is proposed, and then defined in C++ language. Two examples show the process of the interfaces and the effectiveness of constructing the simulation objects. With the instantiation and disposal …

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Research And Implementation Of A High Performance Distributed Object-Oriented Simulation Engine, Xiaodong Huang, Kongshu Xie Sep 2021

Research And Implementation Of A High Performance Distributed Object-Oriented Simulation Engine, Xiaodong Huang, Kongshu Xie

Journal of System Simulation

Abstract: Simulation engine is the core of simulation platform and the operating system of simulation field. On the basis of the reflection-based object-oriented simulation modeling framework and programing specification, aiming at the developing integration and operation requirements for the large-scale multi-granularity computation intensive simulation system, a High-performance Distributed Object-oriented Simulation Engine (HDOSE) is developed. Combined with the brief review of HDOSE development, on the basis of expounding the HDOSE function services and architecture, the key technology, large-scale multi-granularity parallel computation, programming model and interface, parameterized componentized modeling and so on are mainly introduced. The HDOSE typical application cases …

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Whole Ship Simulation Training Platform Based On Virtual Reality, Jiawen Sun, Hongxiang Ren, Fangbing Xiao, Xiaobin Jiang Sep 2021

Whole Ship Simulation Training Platform Based On Virtual Reality, Jiawen Sun, Hongxiang Ren, Fangbing Xiao, Xiaobin Jiang

Journal of System Simulation

Abstract: Under the current navigation education mode, it is common that trainees lack the overall navigation knowledge and the operation practice on onboard equipment and instruments. It is necessary to develop a whole ship simulation training platform that is not limited by time and sites. The six-degree freedom mathematical model of ship motion is established by using the separation modeling theory of ship maneuverability. The flexible object simulation technology, the modeling and rendering of ocean wave technology, and the reverse dynamics technology are adopted to realize the ship scene roaming and equipment interaction. The simulation results show that …

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Evolutionary Simulation Of Medical Products Export Safety Supervision Considering Regulation Of Importing Country, Xiaoli Li, Cejun Cao, Fanshun Zhang Sep 2021

Evolutionary Simulation Of Medical Products Export Safety Supervision Considering Regulation Of Importing Country, Xiaoli Li, Cejun Cao, Fanshun Zhang

Journal of System Simulation

Abstract: In order to investigate the impacts of the regulation of importing country on export safety supervision regarding medical products in the COVID-19 epidemic situation, an evolutionary game model considering the relation between export enterprise and supervision of government is constructed. Based on MATLAB simulation, the influences of different factors including regulation level of importing country, punishment mechanism on export safety supervision of medical products are analyzed. Results show that the illegal behaviors of the export enterprises of medical products can be restrained when the regulation level of importing country reaches a certain threshold. But that would fuel the passively …

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Classification Of Flight Delay Based On Nonlinear Weighted Xgboost, Tang Hong, Wang Dong, Song Bo, Wenkui Chu, Linyuan He Sep 2021

Classification Of Flight Delay Based On Nonlinear Weighted Xgboost, Tang Hong, Wang Dong, Song Bo, Wenkui Chu, Linyuan He

Journal of System Simulation

Abstract: Aiming at the classification of flight delay under imbalance data, a novel method based on nonlinear weighted XGBoost (extreme gradient boosting) is proposed. The imbalance of flight delay data and the influence for classification performance caused by the data imbalance are analyzed. A heuristic nonlinear weighting method based on sample proportion is proposed, and the negative log likelihood loss function is optimized. The real flight delay dataset is used to validate the performance of the classification algorithm. The experiment results show that the proposed nonlinear weighted XGBoost algorithm can improve the classification accuracy of flight delay, while ensuing a …

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Research On Benefits Of Mixed Traffic Flow Of Intelligent Connected Vehicles, Mingwei Hu, Zhiming Zhang, Xiangsheng Chen Sep 2021

Research On Benefits Of Mixed Traffic Flow Of Intelligent Connected Vehicles, Mingwei Hu, Zhiming Zhang, Xiangsheng Chen

Journal of System Simulation

Abstract: In order to study the benefits of the mixed traffic flow Intelligent Connected Vehicles (ICV) and non-connected vehicles, aiming at the intelligent and connected characteristics of ICV. Through the microscopic traffic simulation software Vissim redevelopment, ICV having the function of intelligent connected vehicles traffic flow modeling is realized. The mixed traffic flow composed of intelligent connected vehicles and non-connected vehicles under different market penetration rates is simulated. By comparing the traffic benefits at different time periods and different penetration rates, it is found that with the increase of the market penetration rate of intelligent connected vehicles, the average speed …

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Visual Analysis Method Of Tobacco Quality Data Based On Dimension Reduction, Tian Dong, Guihua Shan, Xuebin Chi, Yanling Zhang, Weihua Feng, Jianwei Wang, Aiguo Wang, Wang Rui Sep 2021

Visual Analysis Method Of Tobacco Quality Data Based On Dimension Reduction, Tian Dong, Guihua Shan, Xuebin Chi, Yanling Zhang, Weihua Feng, Jianwei Wang, Aiguo Wang, Wang Rui

Journal of System Simulation

Abstract: In order to meet the requirements of tobacco leaf matching across regions in tobacco material selection, a visual analysis method of tobacco leaf quality data that incorporating dimension reduction and correlation analysis methods is developed. Through the dimension reduction algorithm, the comparison algorithm and the visual interaction method based on the classification of aroma area for tobacco leaf quality data, a visual analysis method for exploring space division and correlation analysis of tobacco leaf quality data is provided. National tobacco leaf quality data analysis cases and expert demonstrations show that the method can carry out the tobacco leaf quality …

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Cognition-Enhanced Machine Learning For Better Predictions With Limited Data, Florian Sense, Ryan Wood, Michael G. Collins, Joshua Fiechter, Aihua W. Wood, Michael Krusmark, Tiffany Jastrzembski, Christopher W. Myers Sep 2021

Cognition-Enhanced Machine Learning For Better Predictions With Limited Data, Florian Sense, Ryan Wood, Michael G. Collins, Joshua Fiechter, Aihua W. Wood, Michael Krusmark, Tiffany Jastrzembski, Christopher W. Myers

Faculty Publications

The fields of machine learning (ML) and cognitive science have developed complementary approaches to computationally modeling human behavior. ML's primary concern is maximizing prediction accuracy; cognitive science's primary concern is explaining the underlying mechanisms. Cross-talk between these disciplines is limited, likely because the tasks and goals usually differ. The domain of e-learning and knowledge acquisition constitutes a fruitful intersection for the two fields’ methodologies to be integrated because accurately tracking learning and forgetting over time and predicting future performance based on learning histories are central to developing effective, personalized learning tools. Here, we show how a state-of-the-art ML model can …

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Teachers’ Engagement And Self-Efficacy In A Pk–12 Computer Science Teacher Virtual Community Of Practice, Robert Schwarzhaupt, Feng Liu, Joseph Wilson, Fanny Lee, Melissa Rasberry Sep 2021

Teachers’ Engagement And Self-Efficacy In A Pk–12 Computer Science Teacher Virtual Community Of Practice, Robert Schwarzhaupt, Feng Liu, Joseph Wilson, Fanny Lee, Melissa Rasberry

Journal of Computer Science Integration

Prekindergarten to 12th-grade teachers of computer science (CS) face many challenges, including isolation, limited CS professional development resources, and low levels of CS teaching self-efficacy that could be mitigated through communities of practice (CoPs). This study used survey data from 420 PK–12 CS teacher members of a virtual CoP, CS for All Teachers, to examine the needs of these teachers and how CS teaching self-efficacy, community engagement, and sharing behaviors vary by teachers’ instructional experiences and school levels taught. Results show that CS teachers primarily join the CoP to gain high-quality pedagogical, assessment, and instructional resources. The study also found …

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How ‘Human’ Should Robots Be?, Singapore Management University Sep 2021

How ‘Human’ Should Robots Be?, Singapore Management University

Perspectives@SMU

Hotel guests like interaction with devices that look and sound like them, but they can spark displeasure after service failures, new CUHK study shows

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Reinforcement Learning Algorithms: An Overview And Classification, Fadi Almahamid, Katarina Grolinger Sep 2021

Reinforcement Learning Algorithms: An Overview And Classification, Fadi Almahamid, Katarina Grolinger

Electrical and Computer Engineering Publications

The desire to make applications and machines more intelligent and the aspiration to enable their operation without human interaction have been driving innovations in neural networks, deep learning, and other machine learning techniques. Although reinforcement learning has been primarily used in video games, recent advancements and the development of diverse and powerful reinforcement algorithms have enabled the reinforcement learning community to move from playing video games to solving complex real-life problems in autonomous systems such as self-driving cars, delivery drones, and automated robotics. Understanding the environment of an application and the algorithms’ limitations plays a vital role in selecting the …

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Advancing Proper Dataset Partitioning And Classification Of Visual Search And The Vigilance Decrement Using Eeg Deep Learning Algorithms, Alexander J. Kamrud Sep 2021

Advancing Proper Dataset Partitioning And Classification Of Visual Search And The Vigilance Decrement Using Eeg Deep Learning Algorithms, Alexander J. Kamrud

Theses and Dissertations

Electroencephalography (EEG) classification of visual search and vigilance tasks has vast potential in its benefits. In future human-machine teaming systems, EEG could act as the tool for operator state assessment, enabling AI teammates to know when to assist the operator in these tasks, with the potential to lead to increased safety of operations, better training systems for our operators, and improved operational effectiveness. This research investigates deep learning methods which utilize EEG signals to classify the efficiency of an operator's search and to classify whether an operator is in a decrement during a vigilance type task, and investigates performing these …

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Solving Multiple Inference In Graphical Models, Cong Chen Sep 2021

Solving Multiple Inference In Graphical Models, Cong Chen

Dissertations, Theses, and Capstone Projects

For inference problems in graphical models, much effort has been directed at algorithms for obtaining one single optimal prediction. In practice, the data is often noisy or incomplete, which makes one single optimal solution unreliable. To address this problem, multiple Inference is proposed to find several best solutions, M-Best, where multiple hypotheses are preferred for advanced reasoning. People use oracle accuracy as an evaluation criterion expecting one of the solutions has high accuracy with the ground truth. It has been shown that it is beneficial for the top solutions to be diverse. Approaches for solving diverse multiple inference are proposed …

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Adversarial Training For Skill Learning In A Mobile Robot, Todd W. Flyr Sep 2021

Adversarial Training For Skill Learning In A Mobile Robot, Todd W. Flyr

Dissertations, Theses, and Capstone Projects

Machine Learning in mobile robotics is sometimes hampered by the difficulties associated with the creation of a large corpus of labeled data that most neural network based learning algorithms demand. In recent years, advances in the field of machine learning have been facilitated via the creation of large collaboratively-created labeled training datasets that researchers can use as the basis for experiments to validate and improve their candidate neural network architectures. For the field of robotics, however, tasks are so disparate and the physical devices so varied that in most cases the creation of collaborative benchmark datasets are impractical. Obtaining data …

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Piecewise Linear Manifold Clustering, Artyom Diky Sep 2021

Piecewise Linear Manifold Clustering, Artyom Diky

Dissertations, Theses, and Capstone Projects

This work studies the application of topological analysis to non-linear manifold clustering. A novel method, that exploits the data clustering structure, allows to generate a topological representation of the point dataset. An analysis of topological construction under different simulated conditions is performed to explore the capabilities and limitations of the method, and demonstrated statistically significant improvements in performance. Furthermore, we introduce a new information-theoretical validation measure for clustering, that exploits geometrical properties of clusters to estimate clustering compressibility, for evaluation of the clustering goodness-of-fit without any prior information about true class assignments. We show how the new validation measure, when …

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Exploring The Personality Of Virtual Tutors In Conversational Foreign Language Practice, Johanna Dobbriner, Cathy Ennis, Robert J. Ross Sep 2021

Exploring The Personality Of Virtual Tutors In Conversational Foreign Language Practice, Johanna Dobbriner, Cathy Ennis, Robert J. Ross

Conference papers

Fluid interaction between virtual agents and humans requires the understanding of many issues of conversational pragmatics. One such issue is the interaction between communication strategy and personality. As a step towards developing models of personality driven pragmatics policies, in this paper, we present our initial experiment to explore differences in user interaction with two contrasting avatar personalities. Each user saw a single personality in a video-call setting and gave feedback on the interaction. Our expectations, that a more extroverted outgoing positive personality would be a more successful tutor, were only partially confirmed. While this personality did induce longer conversations in …

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Exploiting Group Structures To Infer Social Interactions From Videos, Maksim Bolonkin Sep 2021

Exploiting Group Structures To Infer Social Interactions From Videos, Maksim Bolonkin

Dartmouth College Ph.D Dissertations

In this thesis, we consider the task of inferring the social interactions between humans by analyzing multi-modal data. Specifically, we attempt to solve some of the problems in interaction analysis, such as long-term deception detection, political deception detection, and impression prediction. In this work, we emphasize the importance of using knowledge about the group structure of the analyzed interactions. Previous works on the matter mostly neglected this aspect and analyzed a single subject at a time. Using the new Resistance dataset, collected by our collaborators, we approach the problem of long-term deception detection by designing a class of histogram-based features …

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Artificial Intelligence And Work: Two Perspectives, Steven Miller, Thomas H. Davenport Sep 2021

Artificial Intelligence And Work: Two Perspectives, Steven Miller, Thomas H. Davenport

Research Collection School Of Computing and Information Systems

One of the most important issues in contemporary societies is the impact of intelligent technologies on human work. For an empirical perspective on the issue, we recently completed 30 case studies of people collaborating with AI-enabled smart machines. Twenty-four were from North America, mostly in the US. Six were from Southeast Asia, mostly in Singapore. We compare some of our observations to one of the broadest academic examinations of the issue. In particular, we focus on our case study observations with regard to key findings from the MIT Task Force on the Work of the Future report.

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