This book constitutes the refereed proceedings of the 18th internationalconference on Engineering Applications of Neural Networks, EANN 2017, held in Athens, Greece, in August 2017. The 40 revised full papers and 5 r...
ISBN:
(数字)9783319651729
ISBN:
(纸本)9783319651712
This book constitutes the refereed proceedings of the 18th internationalconference on Engineering Applications of Neural Networks, EANN 2017, held in Athens, Greece, in August 2017. The 40 revised full papers and 5 revised short papers presented were carefully reviewed and selected from 83 submissions. The papers cover the topics of deep learning, convolutional neural networks, image processing, patternrecognition, recommendation systems, machine learning, and applications of Artificial Neural Networks (ANN) applications in engineering, 5G telecommunication networks, and audio signal processing. The volume also includes papers presented at the 6th Mining Humanistic Data Workshop (MHDW 2017) and the2nd Workshop on 5G-Putting intelligence to the Network Edge (5G-PINE).
The proceedings contain 146 papers. The special focus in this conference is on Human-Computer Interaction. The topics include: Social Innovation and Design — Prototyping in the NICE2035 Future Living Labs;on the Life...
ISBN:
(纸本)9783030901752
The proceedings contain 146 papers. The special focus in this conference is on Human-Computer Interaction. The topics include: Social Innovation and Design — Prototyping in the NICE2035 Future Living Labs;on the Life Aesthetics of Packaging Design in the Context of Digital Economy;lego®-like Bricks to Go from the Real to the Virtual World;systematic Literature Review of Nuclear Safety Systems in Small Modular Reactors;bio-Spatial Study in the Urban Context: User Experience Analysis from New York, Preliminary Neurophysiological Analysis from Kuala Lumpur and Nairobi;speech Emotion recognition Using Combined Multiple Pairwise Classifiers;QFami: An Integrated Environment for Recommending Answerers on Campus;DoAR: An Augmented Reality Based Door Security Prototype Application;machine Learning-Based Font recognition and Substitution Method for Electronic Publishing;unidentified Users of Design Documentation;Collaborative Explainable AI: A Non-algorithmic Approach to Generating Explanations of AI;toothbrush Force Measurement and 3D Visualization;a Study on the Creativity of Algorithm Art Using Artificial intelligence;an Approach to Monitoring and Guiding Manual Assembly Processes;deep Learning Methods as a Detection Tools for Forest Fire Decision Making Process Fire Prevention in Indonesia;intelligent Music Lamp Design Based on Arduino;exploring Drag-and-Drop User Interfaces for Programming Drone Flights;research on the Logical Levels and Roles of Human Interaction with Intelligent Creatures Under the Trend of Human-Computer intelligence Integration;An AR-Enabled See-Through System for Vision Blind Areas;IMGDS - Intelligent Multi-dimensional Generative Design System for Industrial SCADA;common Interactive Style Guide for Designers and Developers Across Projects;Co-exploring the Design Space of Emotional AR Visualizations.
作者:
Ramkumar, G.
Saveetha University Department of Ece Chennai India
Phishing attacks pose a huge threat for online security and therefore need advanced detecting techniques in order to mitigate the damages it causes. This paper introduces a sophisticated model for the detection of phi...
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ISBN:
(纸本)9798350379945
Phishing attacks pose a huge threat for online security and therefore need advanced detecting techniques in order to mitigate the damages it causes. This paper introduces a sophisticated model for the detection of phishing websites, named the Blended ResNet-EfficientNet Model (BREM), which unifies the advantages of the ResNet and EfficientNet architectures. To address this challenge, BREM uses the rich hierarchical patternrecognition ability of ResNet-50 and the practical feature extraction capability of EfficientNet-B3 to achieve classification performance in phishing detection. On overall assessment BREM outperforms both traditional machine learning models and standalone deep learning model with an accuracy of 96%, precision at 94%, recall of 95% and FI score of 94.5%. These same authors validate the high specificity (97 %), negative predictive value (95 %) and Matthews correlation coefficient of 0.92 further underlining the robustness and reliability of BREM. This approach does not only improve the accuracy of detection, but also provides much better security against phishing campaigns. In the near future research directions such as real-time deployment, more experiments on different feature sets, adversarial robustness, transfer learning from heterogeneous datasets, model learning models and patternrecognition. They are able to draw from an immense amount of data and address minor deviances, which allows AI's better discrimination of real versus false websites, therefore increasing user cyber protections and preventable breaches [3] [4]. At the heart of securing phishing websites identification is making use of powerful AI capabilities to scan and recognize phishing convincingly. This AI utilizes different methods - natural language processing (NLP), image recognition and behavioral analysis - to keep an eye on things happening to web content and its design. Behavior analysis tracks user-interactions and web behavior to detect for abnormal operations, which co
This paper presents a novel data-adaptive anisotropic filtering technique built on top of an iterative scheme. This new technique can preserve the original significant structures while suppressing noises to the larges...
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The proceedings contain 28 papers. The special focus in this conference is on Health Care Systems Engineering. The topics include: A practical approach to machine learning for clinical decision support: Projects at lu...
ISBN:
(纸本)9783319661452
The proceedings contain 28 papers. The special focus in this conference is on Health Care Systems Engineering. The topics include: A practical approach to machine learning for clinical decision support: Projects at lucile packard children’s hospital stanford in partnership with stanford engineering;user-centered development of an information system in patient’s motor capacity evaluation;a hybrid simulation approach to analyse patient boarding in emergency departments;estimation of case numbers at pandemics and testing of hospital resource’s sufficiency with simulation modeling;empirical data driven intensive care unit drugs inventory policies;a decision-making tool for the calculation of a robust planning for home service employees;service reconfiguration in healthcare systems: The case of a new focused hospital unit;improving emergency medical services with time-region-specific cruising ambulances;a simulation model for optimizing staffing in the emergency department;patient pathways discovery and analysis using process mining techniques: An emergency department case study;analytical approaches to operating room management projects at lucile packard children’s hospital stanford;a decomposition approach for the home health care problem with time windows;discrete-event simulation of an intrahospital transportation service;appointment overbooking and scheduling: Tradeoffs between schedule efficiency and timely access to service;pattern generation policies to cope with robustness in home care;outpatient day service operations: A case study within rheumatology diseases management;can performance monitoring identify any effect of hospital for improvement/worsening: Case of heart failure patients;crowding in paediatric emergency department, a review of the literature and a simulation-based case study;patient-bed allocation in large hospitals.
The method of Target recognition and location the key technology for team-accompanied robots to realize personnel-following navigation. In this paper, the target recognition algorithm based on YOLOv3 is combined with ...
The method of Target recognition and location the key technology for team-accompanied robots to realize personnel-following navigation. In this paper, the target recognition algorithm based on YOLOv3 is combined with the target positioning algorithm based on European point cloud clustering to realize the recognition and location of following targets. The YOLOv3 algorithm using the camera as a sensor can accurately and real-time recognize the target person; the algorithm based on lidar point cloud clustering can effectively obtain the location information of the target person. By fusing the two algorithms, target location can be performed simultaneously with target recognition, and the reliability and accuracy of the algorithm are improved at the same time.
Concurrent engineering (CE) is intertwined with the field of computer-aided engineering (CAE). The author presents a vision of future for CE and CAE where computational intelligence (CI) will play an increasingly sign...
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ISBN:
(纸本)9781586036515
Concurrent engineering (CE) is intertwined with the field of computer-aided engineering (CAE). The author presents a vision of future for CE and CAE where computational intelligence (CI) will play an increasingly significant role. Various disciplines within CE such as design, manufacturing, knowledge management, collaborative computing, Web processes and services, and distributed infrastructures must rely heavily on CI to achieve the increasing sophistication demand. The author has been advocating and advancing a multi-paradigm approach for solution of complicated and noisy computational intelligence problems. In 1995 he co-authored machine Learning - Neural Networks, Genetic Algorithms, and Fuzzy Systems [1] the first authored book that presented and integrated the three principal soft computing and computational intelligence approaches. It was shown that such integration would provide a more powerful approach than any of the three approaches used individually. Since the publication of that ground-breaking book the author and his associates have demonstrated that chaos theory and wavelets can be used to further enhance computational intelligence especially for complicated and noisy patternrecognition problems. In this lecture it is shown how wavelets can be used as a powerful tool to complement and enhance other soft computing techniques such as neural networks and fuzzy logic as well as the chaos theory for solution of complicated and seemingly intractable Cl problems. Examples of research performed by the author and his research associates in the areas of intelligent transportation systems [2-4], vibrations control [5-8], and nonlinear system identification [9-10] are presented.
Folk songs take language as the carrier, and the singing tune and cultural connotation of singing are the important research contents of many music scholars, ethnologists, and linguists. In the process of folk song si...
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Fuel assemblies are very expensive parts of the nuclear reactor. Initially they were used in Hungary for 3 years, now for 4 years and soon they will stay in the core for 5 years. Each year only 1/3rd, 1/4th later 1/5t...
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ISBN:
(纸本)9780769540160
Fuel assemblies are very expensive parts of the nuclear reactor. Initially they were used in Hungary for 3 years, now for 4 years and soon they will stay in the core for 5 years. Each year only 1/3rd, 1/4th later 1/5th of them is replaced, therefore the change of the fuel type is a lengthy process, with mixed cores used. The authorities require that the staff should be trained to each particular core before they operate it. For this reason the simulator should be upgraded to simulate the exact behavior of each core foreseen for the next 5 years. The RETINA code (Reactor Thermo-hydraulics Interactive) is a 3D offline code, developed in our department. KIKO3D - Neutron Kinetics 3D - has been developed in our Institute, too, in the Reactor Analysis Department. Both of them should be integrated into our full-scope replica simulator, coupled, and stressed to operate parallel in real-time, using four hi-power processors. The simulation-specific details are discussed in the paper.
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