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5th International conference on Machine Learning and Computer Application, ICMLCA 2024

作者： Gui, Gaihua Liang, Yuyan Zhang, Qiqi Wang, Zhongchao Yuan, Zhanjiang Guangdong Polytechnic Of Science and Technology Guangdong Zhuhai China

ISBN: (纸本)9798331530334

This study combines the methods of data analysis and mathematical modeling to explore an effective solution about traffic flow control in well-known scenic towns. Firstly, the missing and abnormal data of license plate number are eliminated through the open source dataset. Then, through hierarchical clustering analysis to divide the peak traffic flow hours, statistical traffic flow hour data, and using NSGA-ii algorithm to optimize the signal timing, and establish a service level model to analyze the results, and it is found that it can effectively improve the traffic efficiency and alleviate traffic congestion. The case used in this paper is the 2024 National Student Mathematical modeling Competition E question - traffic flow control of the topic for research and analysis, the results obtained and the actual review of the results of the information very much in line with the results. © 2024 IEEE.

关键词： Traffic congestion

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Production of sweet potato distilled beverage: Economic evaluation via enzymatic and acid hydrolysis

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BIOFUELS BIOPRODUCTS & BIOREFINING-BIOFPR 2024年第6期18卷 1880-1891页

作者： Carvalho, Debora Goncalves Trierweiler, Luciane Ferreira Trierweiler, Jorge Otavio Fed Univ Rio Grande do Sul UFRGS Dept Chem Engn Grp Intensificat Modeling Simulat Control & Optimi Rua Engenheiro Luiz Englert s-n BR-90040040 Porto Alegre RS Brazil

This study aimed to assess the feasibility of utilizing sweet potato waste for distilled beverage production in two process scenarios: (i) acid hydrolysis and (ii) enzymatic hydrolysis. Laboratory experiments were conducted using in natura sweet potato waste and the data obtained were used to design a production system capable of producing 1000 L of distillate per day. Net present value (NPV), internal rate of return (IRR), and discounted payback indicators were used for economic analysis, with a minimum attractiveness rate (MARR) of 15%. The initial investment for the projects was BRL 1 139 610.86 (USD 223 146.80) for enzymatic hydrolysis and BRL 1 314 824.54 (USD 257 455.36) for acid hydrolysis. Packaging costs were identified as the greatest expenses in the process. Assuming a selling price of BRL 14.50 (USD 2.84), the enzymatic hydrolysis process demonstrated an NPV of BRL 4 792 520.77 (USD 938 421.92) and IRR of 83.39%, and the acid hydrolysis process showed an NPV of BRL 2 191 636.78 (USD 429 143.68) and IRR of 42.49%. Consequently, establishing a production plant for distilled beverages proved to be more economically attractive when employing the enzymatic hydrolysis process and fermentation simultaneously, resulting in a return on investment within 1.46 years of operation. Upon scrutinizing the gain matrix, it became apparent that critical factors with the potential to affect the project's feasibility detrimentally, if increased, included the cost of acquiring packaging, the final volumetric fraction of the distilled beverage, and the tax rate. Nevertheless, an upturn in the selling price of the beverage and a process improvement yield both have the potential to underpin the project effectively.

关键词： sweet potato waste distilled beverage acid hydrolysis enzymatic hydrolysis economic evaluation food waste

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Optimizing Privacy-Utility Trade-Off in Healthcare processes: Simulation, Anonymization, and Evaluation (Using process Mining) of Event Logs 19

Optimizing Privacy-Utility Trade-Off in Healthcare Processes...

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19th International conference on Software Technologies, ICSOFT 2024

作者： Kamal, Omar Samy Sohail, Syeda Amna Bukhsh, Faiza Allah University of Twente Enschede7500 AE Netherlands

ISBN: (纸本)9789897587061

In healthcare, big data analytics involve balancing patients’ privacy and data utility. Optimizing healthcare data utility often includes limited access to sensitive data by trusted onsite entities. This potentially hinders broader-scale data utilization by third-party data analysts. As a solution, this research simulates a healthcare process-based event log, inspired by a local hospital’s radiology department. The simulated event log is anonymized using k-anonymity. The anonymized and un-anonymized event logs are evaluated, through process discovery techniques, using the process mining tool, ProM 6.11, for Privacy-utility trade-off assessment. Results indicate successful privacy preservation with a distinct loss in utility in the anonymized healthcare process model, which was not visible otherwise. Therefore, to ensure the efficacy of healthcare process analysis on anonymized sensitive event logs, the utilization of process mining techniques is beneficial for process utility and privacy protection evaluation. © 2024 by SCITEPRESS – Science and Technology Publications, Lda.

关键词： Anonymity

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modeling Agent Behavior in Interacting Microgrids 10

Modeling Agent Behavior in Interacting Microgrids

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10th International conference on Information Technology and Nanotechnology, ITNT 2024

作者： Bychkov, Igor Feoktistov, Alexander Chekan, Mikhail Matrosov Institute For System Dynamics And Control Theory Of Sb Ras Irkutsk Russia

ISBN: (纸本)9798350372939

We propose the agent-based approach to intellectualize data processing and analysis in modeling the operations of interconnected microgrids. Microgrids are modern energy systems with a large share of environmentally friendly and resource-saving equipment. The modeling of different aspects for the organization and operation of microgrids is relevant for their structural and parametric optimization. The study of these aspects in the interaction of microgrids deserves special attention. In this case, it becomes possible to take into account the synergistic effect in the distribution and consumption of electric power. We implement the modeling process using a multi-agent system. In this regard, we describe the structure of this system, methods of its construction, and goals and processes of agent operations. In addition, we provide a model of agent behavior developed based on the basis of a finite-state control machine. The advantages of the proposed approach are demonstrated on a model example of balancing generation and consumption of electric power. © 2024 IEEE.

关键词： Balancing

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Fe³⁺ and Mn²⁺ Removal from Water Solutions by Clinoptilolite Zeolites as a Potential Treatment for Groundwater Wells

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processES 2025年第4期13卷 1060-1060页

作者： Arenhardt, William D. Ketzer, Felipe Wancura, Joao H. C. Seraglio, Janaina Carasek, Fabio L. Zin, Guilherme Calisto, Jean F. F. Rodrigues, Clovis A. de Meneses, Alessandra C. Oliveira, Jose Vladimir Dal Magro, Jacir Community Univ Chapeco Reg Environm Sci Area BR-89809900 Chapeco SC Brazil Farroupilha Fed Inst Ind Proc Grp Technol & Control IPG TC BR-98280000 Panambi RS Brazil Univ Fed Santa Maria Lab Biomass & Biofuels L2B BR-97105900 Santa Maria RS Brazil Univ Vale Itajai Chem Pharmaceut Res Ctr NIQFAR BR-88302901 Itajai SC Brazil Univ Fed Santa Catarina Dept Chem Engn & Food Engn BR-88040 900 Florianopolis SC Brazil

This study presents data on the water quality of the Guarani Aquifer based on samples collected from distinct groundwater wells in the western region of Santa Catarina State, Brazil. Among the analyses performed, the results indicated the need for treatment to ensure suitability for human consumption, particularly concerning Fe3+ and Mn2+ ions. Accordingly, natural (NCLIN) and activated clinoptilolite (ACLIN) zeolites were evaluated for ion removal from synthetic aqueous solutions through adsorption. NCLIN demonstrated excellent performance in adsorbing Fe3+ and Mn2+ ions, achieving removal efficiencies of over 98% and 95%, respectively, at a controlled pH of 6.0 (NCLIN) or 4.0 (ACLIN). A non-linear approach to modeling adsorption kinetics indicated that the pseudo-second-order model best represented the experimental data. This finding suggests that the interaction between the adsorbent and Fe3+ and Mn2+ ions occur through electron sharing and chemisorption. Equilibrium modeling analysis revealed that adsorption on NCLIN occurred in a monolayer, whereas adsorption on ACLIN followed a multilayer pattern. This behavior is attributed to the activation process with H2SO4, which led to dealumination and the formation of HSO3- groups on the adsorbent surface.

关键词： heavy metals ion adsorption iron (iiI) manganese (ii) potable water natural zeolite

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Sparse Gaussian process Regression for Residual Dynamics Learning in Multi-rotor Aerial Vehicles control 20

Sparse Gaussian Process Regression for Residual Dynamics Lea...

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IEEE 20th International conference on Automation Science and Engineering (CASE)

作者： Kulathunga, Geesara Hanheide, Marc Klintchik, Alexandr Univ Lincoln Lincoln Inst Agrifood Technol Lincoln LN1 England Univ Lincoln Sch Comp Sci Lincoln LN6 England

ISBN: (纸本)9798350358513;9798350358520

This paper introduces a method for modeling residual dynamics between a high-level planner and a low-level controller, using reference trajectory tracking in a cluttered environment as a case study. We aim to mitigate residual dynamics resulting solely from the kinematical modeling employed in high-level planning. Our high-level planner utilizes a simplified motion model for quadrotor motion. We propose a Sparse Gaussian process Regression-based technique to model residual dynamics. In contrast, data-Driven MPC, a recent technique, targets aggressive maneuvers without obstacle constraints. Our proposed method is compared with data-Driven MPC in estimating residual dynamics error, including obstacle constraints. Comparative analysis indicates that our technique reduces nominal model error by an average factor of 2. Furthermore, we evaluate our complete framework against four other trajectorytracking approaches in terms of tracking reference trajectory while avoiding collisions. Our approach demonstrates superior performance, achieving shorter flight times without sacrificing computational efficiency.

关键词： Gaussian distribution

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Towards Aleatoric and Epistemic Uncertainty in Medical Image Classification 22nd

Towards Aleatoric and Epistemic Uncertainty in Medical Image...

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22nd International conference on Artificial Intelligence in Medicine (AIME)

作者： Loehr, Timo Ingrisch, Michael Huellermeier, Eyke Ludwig Maximilians Univ Munchen Dept Informat Munich Germany Munich Ctr Machine Learning MCML Munich Germany Ludwig Maximilians Univ Munchen Dept Radiol Univ Hosp Munich Germany

ISBN: (纸本)9783031665349;9783031665356

Medical domain applications require a detailed understanding of the decision making process, in particular when data-driven modeling via machine learning is involved, and quantifying uncertainty in the process adds trust and interpretability to predictive models. However, current uncertainty measures in medical imaging are mostly monolithic and do not distinguish between different sources and types of uncertainty. In this paper, we advocate the distinction between so-called aleatoric and epistemic uncertainty in the medical domain and illustrate its potential in clinical decision making for the case of PET/CT image classification.

关键词： Medical Image analysis Machine Learning Uncertainty Quantification PET/CT data

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Using control Charts with Variable control Limits in Statistical process control 5

Using Control Charts with Variable Control Limits in Statist...

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5th International conference on control Systems, Mathematical modeling, Automation and Energy Efficiency, SUMMA 2023

作者： Zhuravlyova, Marina Financial University under the Government of the Russian Federation Department of Data Analysis and Machine Learning Moscow Russia

ISBN: (纸本)9798350309126

The procedure of building control charts with variable control limits based on nonparametric bootstrap percentile method is proposed. It makes possible to construct control chart of any statistic with unknown continuous distribution and involves a large number of calculations. The order of building one of the scalar statistics to be monitored for the group of mutually dependent quality characteristics is considered. Formulas for obtaining variable control limits based on percentile method are shown. The issue of identifying the structure of relationships between quality characteristics is raised. Proposed control chart, Hotelling T2 and Shewhart usual control charts and their modifications for variable control limits have been constructed using actual data of two characteristics of the rolled steel manufacturing process. It is concluded that the development of the proposed approach can be useful in statistical process control. © 2023 IEEE.

关键词： control charts

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ThreMA: Ontology-Based Automated Threat modeling for ICT Infrastructures

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IEEE ACCESS 2022年 10卷 116514-116526页

作者： De Rosa, Fabio Maunero, Nicolo Prinetto, Paolo Talentino, Federico Trussoni, Martina Natl Interuniv Consortium Informat I-00185 Rome Italy Politecn Torino Dept Control & Comp Engn I-10129 Turin Italy IMT Sch Adv Studies Syst Secur Modelling & Anal Grp I-55100 Lucca Italy

Threat Modelling allows defenders to identify threats to which the target system is exposed. Such a process requires a detailed infrastructure analysis to map threats to assets and to identify possible flaws. Unfortunately, the process is still mostly done manually and without the support of formally sound approaches. Moreover, Threat Modelling often involves teams with different levels of security knowledge, leading to different possible interpretation in the system under analysis representation. Threat modelling automation comes with two main challenges: (i) the need for a standard representation of models and data used in various stages of the process, establishing a formal vocabulary for all involved parties, and (ii) the requirement for a well-defined inference rule set enabling reasoning process automation for threat identification. The paper presents the ThreMA approach to automating threat modelling for ICT infrastructures, aiming at addressing the key automation issues through the use of ontologies. Specifically, a formal vocabulary for modelling an ICT infrastructure, a threat catalog and a set of inference rules needed to support the reasoning process for threat identification are provided. The proposed approach has been validated against actual significant case studies provided by different Stakeholders of the Italian Public Sector.

关键词： Ontologies data models Automation Vocabulary Analytical models Risk management Computer security Threat modeling Automation cybersecurity ontology threat modeling

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A data-Mechanism Joint Driven Based Multi-Energy Flow Calculation Method for Electricity-Heat Interconnected System 19

A Data-Mechanism Joint Driven Based Multi-Energy Flow Calcul...

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IEEE 19th conference on Industrial Electronics and Applications (ICIEA)

作者： Zhang, Shi Li, Ke Chen, Jianfei Wang, Haiyang Mu, Yuchen Zhang, Chenghui Shandong Univ Sch Control Sci & Engn Jinan Peoples R China

ISBN: (纸本)9798350360875;9798350360868

With the rapid development of integrated energy system (IES), the combine operation of heterogeneous energy networks becomes richer and richer, and the nonlinear characteristics of the multi-energy flow (MEF) model become more and more significant, which poses a challenge to the analysis and optimization of system operation. In this paper, a joint driven MEF modeling method based on electricity-heat interconnected system is proposed, which utilizes a deep learning method to mine the internal relationship of MEF historical data and effectively avoids the stability problem caused by iterative. On this basis, the fusion mechanism-driven module is used as a buffer zone for the nonlinear regression process of MEF to reduce the error stacking. This model can achieve the organic unification of calculation accuracy and timeliness to a certain extent. Finally, different scales of electricity-heat interconnection systems are selected for example analysis to verify the accuracy and implementation of the proposed method.

关键词： integrated energy system multi-energy flow deep learning long-short term memory joint driven modeling

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