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Cognitive Shadow: A Policy Capturing Tool to Support Naturalistic Decision Making

Cognitive Shadow: A Policy Capturing Tool to Support Natural...

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3rd IEEE international Multi-Disciplinary conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA)

作者： Lafond, Daniel Tremblay, Sebastien Banbury, Simon Thales Res & Technol Canada Quebec City PQ G1P 4P5 Canada Univ Laval Ecole Psychol Quebec City PQ G1V 0A6 Canada C3 Human Factors Consulting Quebec City PQ G1P 4P5 Canada

ISBN: (纸本)9781467324373;9781467324366

Policy capturing is an approach to decision analysis using statistical models such as multiple linear regression or machine learning algorithms to approximate the mental models of decision makers. The present work seeks to apply a robust policy capturing technique to functionally mirror expert mental models and create individually-tailored cognitive assistants. The "cognitive shadow" method aims to improve decision quality by recognizing probable errors in cases where the decision maker is diverging from his usual judgmental patterns. The tool actually shadows the decision maker by un-intrusively monitoring the situation and comparing its own decisions to those of the human decision maker, and then provides advisory warnings in case of a mismatch. The support methodology is designed to be minimally intrusive to avoid an increase in cognitive load, either in real-time or off-line dynamic decision making situations. Importantly, user trust is likely to be a key asset since the cognitive shadow is derived from one's own judgments. A use case of the cognitive shadow is described within the context of a maritime threat classification task, using the classic CART decision tree induction algorithm for policy capturing. This approach is deemed applicable to a large variety of domains such as supervisory control, intelligence analysis and surveillance in defence and security, and of particular relevance in high-reliability organizations with low tolerance for error.

关键词： Adaptive decision support systems situation assessment policy capturing online monitoring naturalistic decision making

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Comparison between Waveform and Bug Path Planning Algorithm for Mobile Robot

Comparison between Waveform and Bug Path Planning Algorithm ...

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3rd international conference on machine Design and Manufacturing Engineering (ICMDME)

作者： Tang, Swee Ho Yeong, Che Fai Su, Eileen Lee Ming Univ Teknol Malaysia Malaysia Japan Int Inst Technol Terengganu Malaysia Univ Teknol Malaysia Ctr Artificial Intelligence & Robot Terengganu Malaysia Univ Teknol Malaysia Fac Elect Engn Terengganu Malaysia

ISBN: (纸本)9783038351801

Mobile robots frequently find themselves in a circumstance where they need to find a trajectory to another position in their environment, subject to constraints postured by obstacles and the capabilities of the robot itself. This study compared path planning algorithms for mobile robots to move efficiently in a collision free grid based static environment. Two algorithms have been selected to do the comparison namely wavefront algorithm and bug algorithm. The wavefront algorithm involves a breadth-first search of the graph beginning at the goal position until it reaches the start position. The bug algorithm uses obstacles borders as guidance toward a goal with restricted details about the environment. The algorithms are compared in terms of parameters such as execution time of the algorithm and planned path length by using Player/Stage simulation software. Results shown that wavefront algorithm is a better path planning algorithm compared to bug algorithm in static environment.

关键词： Path Planning Wave front Algorithm Bug Algorithm Player/Stage Mobile Robot

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FEATURE AND COMPUTATIONAL TIME REDUCTION ON HAND BIOMETRIC SYSTEM

FEATURE AND COMPUTATIONAL TIME REDUCTION ON HAND BIOMETRIC S...

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3rd international conference on Bio-Inspired Systems and Signal Processing (BIOSIGNALS 2010)

作者： Travieso, Carlos M. Sole-Casals, Jordi Ferrer, Miguel A. Alonso, Jesus B. Univ Las Palmas Gran Canaria Technol Ctr Innovat Communnicat Signals & Commun Dept Campus Tafira SnEd TelecomuncacPabellon B E-35017 Las Palmas Gran Canaria Spain Univ Vic Digital Technol Grp Digital & Informat Technol Dept E-08500 Barcelona Spain

ISBN: (纸本)9789896740184

In real-time biometric systems, computational time is a critical and important parameter. In order to improve it, simpler systems are necessary but without loosing classification rates. In this present work, we explore how to improve the characteristics of a hand biometric system by reducing the computational time. For this task, neural network-multi layer Perceptron (NN-MLP) are used instead of original Hidden Markov Model (HMM) system and classical Principal Component Analysis (PCA) procedure is combined with MLP in order to obtain better results. As showed in the experiments, the new proposed PCA+MLP system achieves same success rate while computational time is reduced from 247 seconds (HMM case) to 7.3 seconds.

关键词： Principal Component Analysis pattern recognition Hand Biometric System Parameterization Feature reduction Classification system

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Improvement of Automated Guided Vehicle Design Using Finite Element Analysis

Improvement of Automated Guided Vehicle Design Using Finite ...

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3rd international conference on machine Design and Manufacturing Engineering (ICMDME)

作者： Ahmad, Shafeek Yeong, Che Fai Su, Eileen Lee Ming Tang, Swee Ho Univ Teknol Malaysia Malaysia Japan Int Inst Technol Kuala Lumpur Malaysia Univ Teknol Malaysia Ctr Artificial Intelligence & Robot Kuala Lumpur Malaysia Univ Teknol Malaysia Fac Elect Engn Kuala Lumpur Malaysia

ISBN: (纸本)9783038351801

Automated Guided Vehicle is a mobile robot used in various industries to transfer goods and materials from one place to another in the industrial compound such as production line and warehouses. Due to the payload it carries, the design should be able to handle certain level of mechanical stress. The optimization study is important to assure the material and design are safe and optimum under the specified conditions before the AGV is manufactured. In this study, a conventional AGV designed previously by an AGV manufacturer to bring a payload of 70 kg is analyzed using the Finite Element Method (FEM) and SolidWorks software is used to perform the FEA simulation. This paper also explain on how the factor of safety for the AGV is derived. The parameter change in this study was the thickness of the sheet metal used to build the AGV while the study output is the stress level, factor of safety and weight of the AGV.

关键词： Design Improvement Stress Analysis Finite Element Method AGV Finite Element Analysis

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Enhancing the Detection of Botnet Attacks in the Internet of Things Networks Through the Utilization of Hybrid Feature Selection 3

Enhancing the Detection of Botnet Attacks in the Internet of...

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3rd FORTEI-international conference on Electrical Engineering, FORTEI-ICEE 2024

作者： Kurniawan, Hartanto Samsudiat Nugroho, Cahyono Saputra, Andri Nursyahbani, Aditya Research Center for Artificial Intelligence and Cybersecurity National Research and Innovation Agency Jakarta Indonesia Center of Data and Information National Research and Innovation Agency Jakarta Indonesia

ISBN: (纸本)9798331542207

The proliferation of Internet of Things (IoT) technology is leading to an escalation in cyber risks. The Intrusion Detection System (IDS) is crucial in countering cyber threats, with botnets being the most commonly detected attack in IoT networks. Anomaly-based IDS is necessary to enhance their capability in identifying cyber threat attributes through the use of supervised machine learning. This work investigates an enhanced supervised machine learning algorithm technique that combines filter-based feature selection methods, specifically Low Variance and Pearson Correlation Coefficient, to detect a new type of botnet attack. The CICIoT2023 dataset, an updated benchmark intrusion dataset specifically designed for IoT networks, is employed to assess the model’s performance using several algorithms including Decision Tree, Random Forest, Logistic Regression, and Naive Bayes. The results demonstrate that the model effectively enhances the identification of botnet attacks by reducing the number of features from 46 to 14. This optimization leads to improved performance, including increased accuracy level and reduced computation time. © 2024 IEEE.

关键词： Bot (Internet)

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Human Pose Estimation Based on GAN and DCGAN Models

Human Pose Estimation Based on GAN and DCGAN Models

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international conference on machine Learning, Big Data and Business intelligence (MLBDBI)

作者： Jiaming Ma Jiaqi Li Shenglu Feng School of Computer Science and Technology Donghua University Shanghai China School of Artificial Intelligence and Data Science Hebei University of Technology Tianjin China School of Electrical Engineering Wuhan University Wuhan China

ISBN: (纸本)9781665417914

As an important application based on the field of computer vision, the various human movements and gestures can be reconstructed by detecting the key articulation points of the human body. It is mainly used in human behavior recognition, human-computer interaction, and attitude tracking. However, the current human pose estimation models have many challenges, such as difficulty detecting the non-typical articulation points of the human body and inaccurate locating of the extremities. They are prone to error or lack of information in complex situations. This paper proposed GAN and DCGAN models to tackle this issue, which can improve the accuracy of human posture prediction. This paper mainly focuses on the contribution of Generative Adversarial Network to the detection of human key articulation points, revising the original model posture and obtaining a model that is closer to the real posture of the human body. The experimental results demonstrated that the model's accuracy is improved to a certain extent after using the DCGAN model. Furthermore, we note that in most cases, the performance of the proposed model is superior to others.

关键词： Training Analytical models Convolution Tracking Biological system modeling Pose estimation Neural networks

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Mobility pattern based routing algorithm for delay/disruption tolerant networks

Mobility pattern based routing algorithm for delay/disruptio...

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10th international conference on Next Generation Teletraffic and Wired/Wireless Advanced Networking, NEW2AN 2010 and 3rd conference on Smart Spaces (Are You Smart), ruSMART 2010

作者： Park, ManKyu Min, SeokHong So, SangHo Oh, DeockGil Kim, ByungChul Lee, JaeYong Satellite Broadcasting and Telecommunication Convergence Research Team ETRI 138 Gajeongno Yuseong-gu Daejeon 305-700 Korea Republic of Department of Information Communications Engineering Chungnam National University 79 Daehangno Yuseong-gu Daejeon 305-764 Korea Republic of

ISBN: (纸本)3642148905

Delay/Disruption Tolerant Networks (DTN) can support data transmission under the challenging network conditions. And one of the most important protocol components for DTN is a routing protocol to improve the performance of transmission delay and delivery success ratio. In this paper, we propose the "Mobility pattern based Routing (MPR)" algorithm that controls the total number of transferred message copies based on mobility patterns of mobile nodes. We consider a realistic "Levy walk" mobility pattern that has a super-diffusive property which well represents human mobility pattern. We implemented a DTN simulator using ONE simulator [9] for the proposed MPR algorithm and Levy walk mobility pattern. Simulation results show that Levy walk mobility pattern provides more accurate evaluation environment for DTN, and the proposed MPR enhances the routing performance of delivery delay and success delivery ratio under realistic mobility pattern. © 2010 Springer-Verlag.

关键词： Delay tolerant networks

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Islanding Detection Using pattern recognition by HOG Features with Ensemble Classifier 3

Islanding Detection Using Pattern Recognition by HOG Feature...

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3rd IEEE international conference on Electrical Power and Energy Systems, ICEPES 2024

作者： Pal, Kumaresh Goswami, Subhadip Bhuyan, Anshuman Koley, Santanu Roy, Soumya Bhakat, Rishika National Institute of Technology Department of Electrical Engineering Jamshedpur India Gandhi Institute for Education & Technology Department of Electrical Engineering Bhubaneswar India Haldia Institute of Technology Department of Computer Science Engineering Haldia India Brainware University Department of Computational Sciences West Bengal India Cambridge Institute of Technology Department of Management Ranchi India

ISBN: (纸本)9798350390728

This study presents a novel approach for detecting islanding based upon image categorisation using Ensemble Classifier is proposed. Images are used to derive the histogram of oriented gradient (HOG) characteristics so as to identify non-islanding as well as islanding events. The ever-increasing need for power encourages the growth of Distributed Generation (DG). Islanding is one of the key challenges associated with excessive penetration of DG sources and can cause harm to the clients and their equipment. The islanding needs to be detected in two seconds, according to the IEEE 1547 DG interconnection rules, and the DG must be turned off. In the suggestive technique, spectrogram images are acquired through the time-series signals that are derived from the point of common coupling (PCC). The features are extracted from these images using the histogram of oriented gradient (HOG). The resulting feature vector is then utilised as an input for both the training and testing processes of the ensemble classifier. For deriving the spectrogram image, the rate of change of voltage is utilised as a parameter. In order to evaluate the performance of the ensemble classifier, 5, 10, 20, and 25-fold cross-validations are performed. The findings from the classification analysis indicate that the utilisation of an ensemble classifier in conjunction with the histogram of oriented gradient feature for image classification yielded remarkable outcomes, including an accuracy of 97.45% and a validation error of 0.188. © 2024 IEEE.

关键词： Graphic methods

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Extraction of peripheral shape features in Chinese character recognition

Extraction of peripheral shape features in Chinese character...

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international conference on pattern recognition

作者： Y.Y. Tang C.Y. Suen Centre for Pattern Recognition and Machine Intelligence Concordia University Montreal QUE Canada

Extraction of a stable and representative set of features is the heart of the design of a pattern recognition system. Knowing the distribution of information on the pixels of a character will be of great assistance to the study of feature extraction. In this paper, an analysis of the distribution of information on the pixels of binarized Chinese characters is presented. From the analysis, it is obvious that the information of a Chinese character tends to concentrate around the peripheries of the character. Several methods to extract peripheral shape features are presented. Some experiments are conducted on Chinese character recognition and the results show the advantages of the peripheral shape features.

关键词： Shape Character recognition Feature extraction Data mining Information analysis pattern recognition Heart Dictionaries Entropy machine intelligence

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Low-error star pattern recognition based on point cloud matching algorithm 3

Low-error star pattern recognition based on point cloud matc...

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2020 3rd international Symposium on Power Electronics and Control Engineering, ISPECE 2020

作者： Liang, Luo Jing Bo, Yu Cheng Min, Luo Chongqing University of Technology Chongqing China

Aiming at the problem that the matching rate of traditional star map recognition methods is not high enough, this paper proposes a star map recognition method based on the ICP point cloud matching algorithm based on feature point extraction. Feature points are selected through the change of the local normal vector of the point cloud, and then used Common (ICP) algorithm to realize more accurate registration of point clouds. In order to further reduce the error rate of star map matching, an improved ICP algorithm based on feature points is used to accurately register the point cloud. Finally, the matching conditions of several star maps are obtained through MATLAB tool simulation and the matching rate error rate is calculated. Common ICP algorithm The minimum matching error of is 14.224, and the minimum matching error of the improved ICP algorithm based on feature points is 14.0715. Obviously, the star map matching error rate of the ICP algorithm based on feature points is lower, which also verifies the superiority of the improved ICP algorithm. © Published under licence by IOP Publishing Ltd.

关键词： Stars

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