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Deep Statistical Comparison Applied on Quality Indicators to Compare Multi-objective Stochastic optimization Algorithms 3rd

引用

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

作者： Eftimov, Tome Korosec, Peter Seljak, Barbara Korousic Jozef Stefan Inst Comp Syst Dept Jamova Cesta 39 Ljubljana 1000 Slovenia Jozef Stefan Int Postgrad Sch Jamova Cesta 39 Ljubljana 1000 Slovenia Fac Math Nat Sci & Informat Technol Glagoljaska Ulica 8 Koper 6000 Slovenia

ISBN: (纸本)9783319729268;9783319729251

In this paper, a study of how to compare the performance of multi-objective stochastic optimization algorithms using quality indicators and Deep Statistical Comparison (DSC) approach is presented. DSC is a recently proposed approach for statistical comparison of meta-heuristic stochastic optimization algorithms over single-objective problems. The main contribution of DSC is the ranking scheme that is based on the whole distribution, instead of using only one statistic such as average or median. Experimental results performed by using 6 multi-objective stochastic optimization algorithms on 16 test problems show that the DSC gives more robust results compared to some standard statistical approaches that are recommended for a comparison of multi-objective stochastic optimization algorithms according to some quality indicator.

关键词： Multi-objective optimization Quality indicators Deep statistical comparison Single problem analysis Multiple problem analysis

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An Enhanced Delay Time Model to Support Evidence Based Maintenance in Healthcare Domain 3rd

An Enhanced Delay Time Model to Support Evidence Based Maint...

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3rd International Afro-European conference for Industrial Advancement (AECIA)

作者： Mahfoud, Hassana Elbarkany, Abdellah El Biyaali, Ahmed Sidi Mohammed Ben Abdellah Univ Fac Sci & Tech Mech Engn Lab Fes 2202 Morocco

ISBN: (纸本)9783319608341;9783319608334

The concern for patient safety and regulatory requirements classically based on manufacturers' recommendations discouraged evidence based maintenance, and thus limited the possibility of maintenance optimization within healthcare organization. Although, the need for preventive maintenance and its appropriate frequency have been debated extensively for decades, very few studies have been conducted to revise healthcare maintenance strategy and improve the effectiveness of clinical engineers work, as well as focus on tasks that could provide the highest return for their limited resources. In this paper, the shift from a compliance-based to a goal-based approach is well established in an improved proportional delay time framework taking into account hidden nature of failures, the influence of the utilization rate and maintenance effectiveness on medical devices degradation. To illustrate the model capabilities, a real case study from the healthcare domain is presented, the model parameters are estimated entirely using the collected maintenance data. Then, the optimal maintenance policy is determined by a multi-objective optimization to achieve the desired cost effectiveness.

关键词： Healthcare maintenance Dependability Proportional delay time model Utilization rate Imperfect maintenance Hidden failure Safety Multi-objective optimization

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An adaptive Medical Cyber-Physical System for post diagnosis patient care using cloud computing and machine learning approach 3

An adaptive Medical Cyber-Physical System for post diagnosis...

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3rd International conference for Emerging Technology, INCET 2022

作者： Miah, M. Saef Ullah Sarwar, Talha Bin Islam, Saima Sharleen Haque, Md. Samiul Masuduzzaman, Md. Bhowmik, Abhijit Universiti Malaysia Pahang Faculty of Computing Pekan Malaysia Department of Computer Science Dhaka Bangladesh University of Dhaka Institute of Information Technology Dhaka Bangladesh Kumoh National Institute of Technology Department of It Convergence Engineering Gumi Korea Republic of

ISBN: (纸本)9781665494991

Medical care is one of the most basic human needs. Due to the global shortage of doctors, nurses, and other healthcare personnel, medical cyber-physical systems are quickly becoming a viable option. Post-diagnosis surveillance is an essential application of these systems, which can be performed more successfully using various monitoring devices rather than active observation by nurses in their physical presence. However, most existing solutions for this application are rigid and do not consider current difficulties. intelligent and adaptive systems can overcome the challenges because of the advances in relevant technology, especially healthcare 4.0. Therefore, this work presents an adaptive system based on cloud and edge computing architecture and machine learning approaches to perform post-diagnosis medical tasks on patients, thus reducing the need for nurses, especially in the post-diagnosis phase. © 2022 IEEE.

关键词： Cyber Physical System

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Modeling and optimization of Proactive Management of the Production Pollutions in the Conditions of Information Asymmetry 3rd

Modeling and Optimization of Proactive Management of the Pro...

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3rd conference on Creativity in intelligent Technologies and Data Science (CIT&DS)

作者： Rogachev, Aleksey F. Lukashin, Maksim S. Volgograd State Agrarian Univ Volgograd Russia Volgograd State Tech Univ Volgograd Russia

ISBN: (纸本)9783030297435;9783030297428

On the basis of the constructed mathematical model, an analysis is made of which of the instruments for regulating industrial emissions of enterprises - environmental standards or quotas sold for industrial emissions of pollutants - allows minimizing the total costs of the strategy of environmental regulation. The necessity of taking into account the asymmetry of information support of the optimization process is shown. It has been proved that the environmental policy regulator, aiming to limit the aggregate level of emissions of a given pollutant by several enterprises, can minimize total costs by applying enterprise-specific environmental standards. The system of quotas sold for production emissions allows minimizing the total costs of the strategy of environmental and economic regulation only if the costs of the environmental audit are the same for all enterprises. It is established that in the event that the cost of implementing penalties varies between enterprises, the competitive market for emission allowances will not minimize the total costs of providing the total amount of emissions for a certain level, allowing a certain degree of non-compliance with environmental requirements.

关键词： Mathematical modeling Industrial pollution optimization Proactive control Asymmetry

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3rd International conference on Smart Electronics and Communication, ICOSEC 2022 - Proceedings

3rd International Conference on Smart Electronics and Commun...

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3rd International conference on Smart Electronics and Communication, ICOSEC 2022

ISBN: (纸本)9781665497640

The proceedings contain 294 papers. The topics discussed include: cooperative spectrum sensing with hard decision fusion based on modified correlation detection scheme in additive Laplacian noise;Archimedes spiral antenna for the microwave hyperthermia application;research on inter-symbol interference suppression technology and fusion algorithm of optical communication system;marketing data collection and chaotic clustering based on the computer network era;PHP implementation of a comprehensive evaluation platform for innovative talent training quality based on internet data clustering and integration;multi-bit collection and hierarchical classification algorithm of computer application fundamentals based teaching data under the background of hybrid clustering algorithm;centralized analysis algorithm of multi-dimensional traditional data for smart new computer network course platform;pomegranate leaf disease classification using feature extraction and machine learning;a study of cloud-based VPN establishment using network function virtualization technique;and analysis of the application of user experience and interactive intelligent data protocol in industrial design under the Internet + mode.

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The CHREST Architecture of Cognition The Role of Perception in General Intelligence

The CHREST Architecture of Cognition The Role of Perception ...

引用

3rd conference on Artificial General Ingelligence, AGI 2010

作者： Gobet, Fernand Lane, Peter C. R. Brunel Univ Ctr Study Expertise Uxbridge UB8 3PH Middx England Univ Hertfordshire Sch Comp Sci Hatfield AL10 9AB Herts England

ISBN: (纸本)9789078677369

This paper argues that the CHREST architecture of cognition can shed important light on developing artificial general intelligence. The key theme is that "cognition is perception." The description of the main components and mechanisms of the architecture is followed by a discussion of several domains where CHREST has already been successfully applied, such as the psychology of expert behaviour, the acquisition of language by children, and the learning of multiple representations in physics. The characteristics of CHREST that enable it to account for empirical data include: self-organisation, an emphasis on cognitive limitations, the presence of a perception-learning cycle, and the use of naturalistic data as input for learning. We argue that some of these characteristics can help shed light on the hard questions facing theorists developing artificial general intelligence, such as intuition, the acquisition and use of concepts, and the role of embodiment.

关键词： Architecture

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Competitive-Driven learning for Image Ordinal Classification 3

Competitive-Driven Learning for Image Ordinal Classification

引用

3rd International conference on Electronic Information Engineering and Computer Communication, EIECC 2023

作者： Zhang, Chao Feng, Chao Cheng, Jianmei Fu, Keren Intelligent Policing Key Laboratory of Sichuan Province Luzhou China Sichuan Police College Luzhou China University of Michigan Dept. Electrical Engineering and Computer Science Ann Arbor United States Sichuan University Dept. Computer Science Chengdu China

ISBN: (纸本)9798350359961

Image ordinal classification (IOC) assigns a discrete yet ordinal scalar label to an input image, such as age estimation. For IOC, it is non-trivial to effectively incorporate the ordinal information of inputs into the classification task. In this work, we adopt the concept of CutMix, a data augmentation technique that mixes two samples and their labels proportionally during the training, to help the task of ordinal classification. In particular, we study the CutMix from the perspective of metric learning instead of data augmentation, which naturally and simply implements classification learning and difference regression learning. Firstly, we embed two ordinal images into the training procedure by a virtual combination of image and label, and explain why CutMix fits IOC well. Secondly, the ordinal difference between two images is utilized to learn the fine difference in category classification, which is integrated with CutMix properly. Finally, for further improvement, dual pairing and random augmentation are proposed to enlarge the disparity of two objects, so as to exploit more discriminative feature. Comprehensive experiments demonstrate the effectiveness of our newly proposed approach, which outperforms previous methods with a relatively large margin (>2%). © 2023 IEEE.

关键词： Competitive learning Image ordinal classification Image recognition

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Implementation and optimization of the eye gaze tracking system based on DM642

Implementation and optimization of the eye gaze tracking sys...

引用

International conference on intelligent Network and intelligent Systems

作者： Liu, Ruian Ma, Shengtao Zhang, Mimi Wang, Lei College of Physics and Electronic Information Science Tianjin Normal University Tianjin China

ISBN: (纸本)9780769542492

Real-time eye detection is important for many HCI applications;including eye gaze tracking, auto stereoscopic displays, video conferencing, face detection, and recognition. Currently, the eye gaze tracking systems are usually implemented on general purpose processors. As eye gaze tracking algorithms move from research labs to the real world, power consumption and cost become critical issues. This motivates searching for implementations using a digital signal processor (DSP). Our goal in this paper is to explore the feasibility of implementing DSP-based eye gaze tracking systems. To achieve this goal, we implement a fully automatic eye gaze tracking system on Texas Instruments' TMS320DM642 DSP, profile performance, and analyze opportunities for optimization. Our experiments demonstrate that well-optimized eye gaze tracking implementations on DSP can be an effective choice for embedded eye gaze tracking products. © 2010 IEEE.

关键词： Face recognition

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SIDES: SCALABLE intelligent DISTRIBUTED EMERGENCY SYSTEM

SIDES: SCALABLE INTELLIGENT DISTRIBUTED EMERGENCY SYSTEM

引用

3rd IEEE International conference on Network Infrastructure and Digital Content. (IC-NIDC)

作者： Guan, Junjie Wu, Yanyi Ma, Jinming Li, Tao Xie, Chunlei Mo, Yuli Beijing Univ Posts & Telecommun Beijing 100876 Peoples R China

ISBN: (纸本)9781467322010

Nowadays, evacuation is mostly based on individual decisions, which is unreliable. This paper introduces a practical solution towards emergency evacuation by guiding people out of building efficiently. Built on wireless sensor network (WSN), our system is capable of learning and dynamically generating evacuation strategy. Distributed mechanism and backup mechanism feature the scalability and invulnerability. Simulations prove the efficiency and reliability of the system.

关键词： Wireless sensor network Evacuation model Emergency navigation Distributed computing

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Dynamic Portfolio Management Based on Pair Trading and Deep Reinforcement learning 3

Dynamic Portfolio Management Based on Pair Trading and Deep ...

引用

3rd International conference on Computational Intelligence and intelligent Systems, CIIS 2020

作者： Xu, Fucui Tan, Shan School of Artificial Intelligence and Automation Huazhong University of Science and Technology China

ISBN: (纸本)9781450388085

Existing portfolio management methods have made great progress in diversifying non-systematic risks, but they have ignored systemic risks. In response to this issue, we proposed a dynamic, market-neutral, risk-diversified portfolio management model by combining the ideas of pair trading strategy, deep reinforcement learning with traditional portfolio management model. We conduct an experiment on the Chinese A-share market by selecting 32 pairs of stocks. The experiment results showed that the proposed pair-based deep portfolio model has superiority for dynamic portfolio management problem in trade-off investment returns and risks. © 2020 ACM.

关键词： Reinforcement learning

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