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Dual trace gas detection using a compact two-channel multipass cell with dense and line spot patterns

HELIYON 2023年第2期9卷

作者： Kong, Rong Ma, Ningyi Liu, Peng Zhou, Xin Beijing Normal Univ Ctr Adv Quantum Studies Dept Phys Appl Opt Beijing Area Major Lab Beijing 100875 Peoples R China

A highly sensitive dual-gas sensor based on a two-channel multipass cell (MPC) was designed and developed for simultaneous detection of atmospheric methane (CH4) and carbon dioxide (CO2) by using two distributed feedback lasers emitting at 1653 nm and 2004 nm. The nondominated sorting genetic algorithm was applied to intelligently optimize the MPC configuration and accelerate the dual-gas sensor design process. A compact and novel two-channel MPC was used to achieve two optical path lengths of 27.6 m and 2.1 m in a small volume of 233 cm3. Simultaneous measurements of CH4 and CO2 in the atmosphere were performed to demonstrate the stability and robustness of the gas sensor. According to the Allan deviation analysis, the optimal detection precision for CH4 and CO2 was 4.4 ppb at an integration time of 76 s and 437.8 ppb at an integration time of 271 s, respectively. The newly developed dual-gas sensor exhibits superior characteristics of high sensitivity and stability, cost-effectiveness and simple structure, which make it well-suited for multiple trace gas sensing in various applications, including environmental monitoring, safety inspections and clinical diagnosis.

关键词： Tunable diode laser absorption spectroscopy Dual -gas sensor Multipass cell optimization algorithm

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A Hybrid optimization Method OWGWA for EEG/ERP Adaptive Noise Canceller With Controlled Search Space

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INTERNATIONAL JOURNAL OF SWARM INTELLIGENCE RESEARCH 2020年第3期11卷 30-48页

作者： Nagal, Rachana Kumar, Pradeep Bansal, Poonam Amity Univ Noida India Maharaja Surajmal Inst Technol Delhi India

In this paper, a system for filtering event-related potentials/electroencephalograph is exhibited by adaptive noise canceller through an optimization algorithm, oppositional hybrid whale-grey wolf optimization algorithm (OWGWA). The OWGWA can choose the control parameters of the grey wolf algorithm utilizing whale parameters. To balance out the randomness of optimization strategies another methodology is implemented called controlled search space. Adaptive filter's noise reduction capability has been tested through adding adaptive white Gaussian noise over contaminated EEG signals at different noise levels. The performance of the proposed OWGWA-CSS algorithm is evaluated by signal to noise ratio in dB, mean value, and the relationship between resultant and input ERP. In this work, ANCs are also implemented by utilizing other optimization techniques. In average cases of noisy environment, comparative analysis shows that the proposed OWGWA-CSS technique provides higher SNR value, significantly lower mean and higher correlation as compared to other techniques.

关键词： Adaptive Noise Canceller Controlled Search Space EEG/ERP Signal Genetic algorithm Gradient-Based algorithm Oppositional Based Learning optimization algorithm Swarm-Based algorithm

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Layout optimization Design for Manufacturing Workshop

Layout Optimization Design for Manufacturing Workshop

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第34届中国控制与决策会议

作者： Dan Liu Yan Liu Liwei Li Mouquan Shen College of Electrical Engineering and Control Science Nanjing Technology University Zhejiang Zhongde Automatic Control Science and Technology Joint Stock Co. Ltd. School of Automation Nanjing University of Information Science & Technology

This paper considers a layout optimization problem in manufacturing *** the characteristics of each work areas and logistics into consideration,a mathematical model with an objective and multiple constraints is *** model can ensure that there is no overlap between work areas,as well as between work areas and logistics *** proposed mathematical model can be solved by heuristic ***,a numerical simulation is used to verify the effectiveness of our model.

关键词： Factory layout heuristics optimization algorithm

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Risk-averse energy management of hydro/thermal/pumped storage complementarily operating with wind/solar: Balancing risk, cost and carbon emission

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SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS 2023年 60卷

作者： Li, Xudong Yang, Weijia Zhao, Zhigao Wang, Ran Yin, Xiuxing Liu, Pan Wuhan Univ State Key Lab Water Resources Engn & Management Wuhan 430072 Peoples R China

Large-scale grid integration of variable renewable energy is crucial for achieving decarbonized development. However, this integration requires frequent regulation of flexible power sources for complementary operation, which can lead to wear-and-tear and fatigue damage to key components. This poses potential risks to flexible power sources. Existing studies have primarily focused on limiting unit startups, while have neglected the risk of frequent power regulation. Thus, this work proposes a risk-averse short-term scheduling method for a Wind Solar-Cascade hydro-Thermal-Pumped storage hybrid energy system to balance frequent regulation risk, cost, and carbon emission: (1) a risk-averse short-term scheduling model is proposed, considering multilayer constraints;(2) a multi-objective hybrid African vulture optimization algorithm is proposed to effectively solve the scheduling problem including continuous and discrete variables. A case study in the Songhua River basin, China shows that: (1) compared with traditional models, the proposed model reduces the risk by 31.4% and enhances the comprehensive performance in balancing the three objectives by 22.4%;(2) the proposed algorithm performs robustness and search capability advantages, with improvements of 33.01% and 21.44% respectively, in solving the problem of challenging constraints and mixed decision variables. Overall, this work contributes to enhancing the management of large hybrid energy systems.

关键词： Hybrid energy system Hydropower Risk optimization algorithm Decarbonization

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A New Approach for Educational Data Analytics with Wearable Devices 21

A New Approach for Educational Data Analytics with Wearable ...

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21st IEEE International Conference on Advanced Learning Technologies (ICALT)

作者： Zhou, Zhenxing Tam, Vincent W. L. Lui, King-Shan Lam, Edmund Y. Kong, Runzhi Hu, Xiao Law, Nancy Univ Hong Kong Dept Elect & Elect Engn Hong Kong Peoples R China Univ Hong Kong Fac Educ Hong Kong Peoples R China

ISBN: (纸本)9781665441063

The rapid development of wearable technologies has dramatically promoted the potential usages of wearable devices in educational data analytics. However, the large amount of input data and the various types of educational output labels also increase the difficulties in selecting the useful information and discovering the implicit relations between different input data. To address this issue, this paper proposed a new two-layer approach for conducting educational data analytics automatically. In this approach, there are three key components: input layer, output layer and recognition model. For the input layer, we adopted the newly proposed optimization algorithm: Adaptive Multi-Population optimization (AMPO) to select the most related input features and suitable model structures. For the output layer, we inserted domain-specific constraints during the searching for all combinations of different output labels to discover a meaningful output strategy with a relatively higher accuracy. Based on the input elements and output strategy provided by the input layer and the output layer, the recognition model will produce the corresponding recognition accuracy. With these three components, our proposed method can find out some connotative information to provide guidance for conducting educational data analytics and drawing meaningful conclusions.

关键词： educational data analytics wearable device optimization algorithm

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Integrating Fuzzy Systems with optimization algorithm

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INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS & STATISTICS 2013年第13期43卷 23-29页

作者： Ren, Huilin Gou, Jin Huaqiao Univ Sch Informat Comp Sci & Technol Xiamen 361021 Fujian Peoples R China

In this paper, a fuzzy system fusion structure that can integrate multiple fuzzy systems is proposed. The novel approach is made up of three phases: fuzzy knowledge encoding, the initial fuzzy rule bases acquisition and fuzzy system integration. In the fuzzy knowledge encoding stage, the data set is coded as positive integer according to encoding strategy. The initial fuzzy rule bases are derived from expert groups, evolutionary algorithms or other methods. In the fuzzy system integration phrase, an optimal fuzzy system or an almost optimal fuzzy system is derived from the initial population by using the multi-mutation particle swarm optimization algorithm. Experimental evaluation on different kinds of methods shows that our proposed algorithm can improve the performance of the fusion fuzzy system.

关键词： fuzzy system optimization algorithm pso

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Study of a New Global optimization algorithm Based on the Standard PSO

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JOURNAL OF optimization THEORY AND APPLICATIONS 2013年第3期158卷 935-944页

作者： Yang, B. Cheng, L. Shanghai Jiao Tong Univ Sch Mech Engn Shanghai Peoples R China

In this paper, a new global optimization algorithm is developed, which is named Particle Swarm optimization combined with Particle Generator (PSO-PG). Based on a series of comparable numerical experiments, we show that the calculation accuracy of the new algorithm is greatly improved and optimization efficiency is increased as well, in comparison with those of the standard PSO. It is also found that the optimization results obtained from PSO-PG are almost independent of the coefficients adopted in the algorithm.

关键词： Particle swarm optimization (PSO) Particle generator optimization algorithm Global optimization

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Equitable Top-k Results for Long Tail Data

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Proceedings of the ACM on Management of Data 2023年第4期1卷 1-24页

作者： Md Mouinul Islam Mahsa Asadi Senjuti Basu Roy New Jersey Institute of Technology Newark NJ USA

For datasets exhibiting long tail phenomenon, we identify a fairness concern in existing top-k algorithms, that return a "fixed" set of k results for a given query. This causes a handful of popular records (products, items, etc) getting overexposed and always be returned to the user query, whereas, there exists a long tail of niche records that may be equally desirable (have similar utility). To alleviate this, we propose θ-Equiv-top-k-MMSP inside existing top-k algorithms - instead of returning a fixed top-k set, it generates all (or many) top-k sets that are equivalent in utility and creates a probability distribution over those sets. The end user will be returned one of these sets during the query time proportional to its associated probability, such that, after many draws from many end users, each record will have as equal exposure as possible (governed by uniform selection probability). θ-Equiv-top-k-MMSP is formalized with two sub-problems. (a) θ-Equiv-top-k-Sets to produce a set S of sets, each set has k records, where the sets are equivalent in utility with the top-k set; (b) MaxMinFair to produce a probability distribution over S, that is, PDF(S), such that the records in S have uniform selection probability. We formally study the hardness of θ-Equiv-top-k-MMSP. We present multiple algorithmic results - (a) An exact solution for θ-Equiv-top-k-Sets, and MaxMinFair. (b) We design highly scalable algorithms that solve θ-Equiv-top-k-Sets through a random walk and is backed by probability theory, as well as a greedy solution designed for MaxMinFair. (c) We finally present an adaptive random walk based algorithm that solves θ-Equiv-top-k-Sets and MaxMinFair at the same time. We empirically study how θ-Equiv-top-k-MMSP can alleviate a equitable exposure concerns that group fairness suffers from. We run extensive experiments using 6 datasets and design intuitive baseline algorithms that corroborate our theoretical analysis.

关键词： equal exposure fairness long tail data optimization algorithm top-k retrieval

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Intelligent Resource Scheduling Method for Surface Observation of Satellites based on Segmented Coding

Intelligent Resource Scheduling Method for Surface Observati...

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第六届体系工程学术会议—体系工程与高质量发展

作者：俞棋睿尹明娄矫媛媛王笑潘晓刚 College of Science National University of Defense Technology College of Systems Engineering National University of Defense Technology

With the development of modern military strategy, satellite observation has become a key asset for obtaining global security and operational environment dynamics. This article proposes an intelligent scheduling method for ground observation of satellite based on segmented coding, aiming to optimize observation plans, improve the quality and efficiency of data collection. The article first analyzes the current research status of satellite observation duration allocation and points out the shortcomings of current research on ground observation task duration allocation. In response to this issue, this article establishes an observation duration allocation model, which maximizes the observation benefits of satellites in different orbits(high, medium, and low) by adjusting the observation duration decision variables of each satellite. The model introduces an encoding system to represent different observation time allocation schemes and establishes a relationship function between observation duration and benefit value. Furthermore, this article proposes an improved genetic algorithm based on allele replacement to solve the allocation problem of observation time. The experimental results show that the method tends to stabilize after 10000 iterations, and the total allocatable time resource utilization rate of the proposed scheduling scheme reaches 99.9999%, which is much higher than the benefit value of the uniform allocation scheme, proving the feasibility and effectiveness of the proposed method in this paper.

关键词： satellite observation Resource scheduling Observation duration allocation Genetic algorithm optimization algorithm

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LCU-level Rate-Distortion optimization for Versatile Video Coding

LCU-level Rate-Distortion Optimization for Versatile Video C...

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IEEE International Symposium on Circuits and Systems

作者： Gencheng Xu Shiyu Jin KaichenTang Zijing Zhang Yimin Zhou Schoo of Couer Science nd Engineering Universiy of Eecronic Science nd Technoogy of Chin ChengduSchoo of Couer Science nd Engineering Universiy of Eecronic Science nd Technoogy of Chin ChengduSchoo of Couer Science nd Engineering Universiy of Eecronic Science nd Technoogy of Chin ChengduSchoo of Couer Science nd Engineering Universiy of Eecronic Science nd Technoogy of Chin ChengduSchoo of Cybersecuriy Chengdu Universiy of Inforion Technoogy Chengdu

ISBN: (数字)9781665484855

ISBN: (纸本)9781665484862

Rate-distortion curve is greatly influenced by the texture and motion compensation. Therefore, using a uniform Lagrangian multiplier (lambda, to all the LCUs in a picture may not achieve the optimal coding performance. To address the challenging problem on how to formulate the appropriate to an individual LCU, this paper proposes a LCU-level Lagrangian multiplier adaption (LLMA) algorithm. Firstly, a motion compensation information entropy (MCIE) of 16 16 block is calculated by obtaining a simple binary information entropy from the source. Secondly, MCIE is normalized to a standard normal distribution, on the basis of the strong assumption that the video sources obey the Gaussian distribution. Thirdly, an adaption factor is assigned to a LCU, which multiples on the picture-level from the system calculation. Experiments show that the proposed LLMA algorithm achieves remarkable performance in low-delay and random-access configurations, with the resulting achievements of 1.81% BD-Rate gains, compared with VTM 13.0 at low-delay common test condition.

关键词： information entropy motion compensation Lagrangian multiplier optimization algorithm

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