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Symposium on Integrated Circuits and systems Design (SBCCI)

作者： Arthur M. Lima Lucas G. Nardo Erivelton Nepomuceno Janier Arias-Garcia Jones Yudi Graduate Program in Mechatronic Systems University of Brasília Brasília Brazil Graduate Program in Electrical Engineering Federal University of Minas Gerais Belo Horizonte Brazil Department of Electronic Engineering Center for Ocean Energy Research Maynooth University Maynooth reland Department of Electronic Engineering Federal University of Minas Gerais Belo Horizonte Brazil Department of Mechanical Engineering University of Brasília Brasília Brazil

With the rise of interconnected systems, security has become a crucial concern. As a result, there has been a growing interest in developing low-cost embedded cryptographic algorithms that are lightweight and can be integrated into System-on-Chip (SoC) devices. Digital chaotic systems have emerged as a promising approach for building secure communication systems, where various cryptosystems utilize chaotic dynamics to encrypt images into noise-like representations. Recent studies have demonstrated that finite-precision error can be used to derive chaos, which can be systematically applied to encrypt images. However, there is a lack of research on how SoC-based design constraints affect the overall performance of image encryption systems, especially for applications that are sensitive to latency. This study aims to address this gap by presenting an efficient architecture that explores a hardware/software co-design for image encryption based on finite-precision error, specifically designed for resource-limited devices and latency-sensitive applications. Our platform performs the capture and encryption of images with a size of 320 × 240. Using a benchmark image, results show that the developed cryptosystem architecture can encrypt images efficiently while offering low hardware occupation.

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Feature deformation network with multi-range feature enhancement for agricultural machinery operation mode identification

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International Journal of Agricultural and Biological engineering 2024年第4期17卷 265-275页

作者： Weixin Zhai Zhi Xu Jinming Liu Xiya Xiong Jiawen Pan Sun-Ok Chung Dionysis Bochtis Caicong Wu College of Information and Electrical Engineering China Agricultural UniversityBeijing 100083China Key Laboratory of Agricultural Machinery Monitoring and Big Data Application Ministry of Agriculture and Rural AffairsBeijing 100083China Department of Smart Agricultural Systems Graduate SchoolChungnam National UniversityDaejeon 34134Republic of Korea Institute for Bio-Economy and Agri-Technology(iBO) Centre for Research and Technology-Hellas(CERTH)Thessaloniki 57001Greece

Utilizing the spatiotemporal features contained in extensive trajectory data for identifying operation modes of agricultural machinery is an important basis task for subsequent agricultural machinery trajectory *** the present study,to effectively identify agricultural machinery operation mode,a feature deformation network with multi-range feature enhancement was ***,a multi-range feature enhancement module was developed to fully explore the feature distribution of agricultural machinery trajectory ***,to further enrich the representation of trajectories,a feature deformation module was proposed that can map trajectory points to high-dimensional space to form feature ***,EfficientNet-B0 was used to extract features of different scales and depths from the feature map,select features highly relevant to the results,and finally accurately predict the mode of each trajectory *** validate the effectiveness of the proposed method,experiments were conducted to compare the results with those of other methods on a dataset of real agricultural *** the corn and wheat harvester trajectory datasets,the model achieved accuracies of 96.88%and 96.68%,as well as F1 scores of 93.54%and 94.19%,exhibiting improvements of 8.35%and 9.08%in accuracy and 20.99%and 20.04%in F1 score compared with the current state-of-the-art method.

关键词： road-field trajectory classification efficientNet feature deformation network multi-range feature enhancement agricultural machinery operation mode recognition

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Optimal Deployment of an Equitable Cav Platoonable Corridor On Road Networks with Mixed Traffic Flow

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SSRN 2023年

作者： Zhu, Dan Xie, Tingting Liu, Yang Zou, Bo Rujeerapaiboon, Napat Department of Industrial Systems Engineering and Management National University of Singapore Singapore Department of Civil and Environmental Engineering National University of Singapore Singapore Department of Civil Materials and Environmental Engineering University of Illinois Chicago United States

Connected and autonomous vehicle (CAV) technology is expected to increase road capacity and reduce fuel consumption, but it may take time for all human-driven vehicles (HVs) to be replaced by CAVs. During the transition period, CAVs and HVs will continue to coexist. This paper aims to find an optimal deployment of a CAV platoonable corridor to facilitate CAV platooning and better manage traffic congestion on road networks with a mixed traffic flow of CAVs and HVs. Generally, dedicated infrastructure for CAVs, such as CAV lanes, zones, or corridors, may have distributional welfare effects on travelers. Especially, HV users may be worse off because road space is partially converted to dedicated infrastructure for CAVs. To facilitate equitable infrastructure planning, we propose a bi-level Stackelberg game that incorporates the equity concern, where the planner acts as the leader to determine the optimal deployment of an equitable CAV platoonable corridor at the upper level, while travelers are followers who make user-optimal route choices given the CAV platoonable corridor at the lower level. For the lower-level problem, we model the decision-making of travelers as a platoon-embedded network equilibrium with mixed flow (PNEMF) and derive its equivalent variational inequality (VI) problem. The existence and the uniqueness of the VI solution are proved. To solve the bi-level program efficiently, we propose a simulated-annealing-based corridor search (SACS) algorithm. Our numerical experiments on the Nguyen-Dupuis(ND) and Sioux Falls (SF) networks demonstrate the expected benefits of deploying a CAV platoonable corridor if the CAV market penetration ratio exceeds a certain threshold. In the meantime, both CAV and HV users are better off with the deployed equitable corridor. In addition, we find that the degree of the transportation planner's concern about the inequity issue has a significant impact on the corridor design when the CAV penetration ratio is low. With less c

关键词： Autonomous vehicles

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Assessing Distributed Energy Resource Hosting Capacity Under Different Grid-Tie Inverter Control Strategies

Assessing Distributed Energy Resource Hosting Capacity Under...

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Workshop on Communication Networks and Power systems (WCNPS)

作者： Brenda L. M. Santos Luciano S. Barros Daniel Barbosa Fernando A. Moreira Graduate Program in Electrical Engineering Federal University of Bahia Salvador Brazil Computer Systems Department Federal University of Paraíba João Pessoa Brazil Department of Electrical and Computer Engineering Federal University of Bahia Salvador Brazil

Despite the potential benefits that the integration of distributed energy resources (DERs) can bring to the system, it may cause problems related to power quality constraints, such $as$ reverse power flow in substation and overvoltages. An effective approach to address these problems involves the adoption of reactive and active power control in grid-tie inverters associated with DER. Therefore, this paper assesses the impacts of grid-tie inverter control modes, including both Volt-Var and Volt-Watt strategies, on the DER hosting capacity. In order to improve the overall system operation, modifications in the Volt-Var and Volt-Watt curves were proposed. It is noteworthy that these control strategies can have adverse effects on certain distribution system performance indicators, such $as$ voltage deviation and power losses; for this reason, these indicators are also evaluated in this study. A stochastic approach was adopted to deal with the uncertainties associated with DERs and loads. Finally, from tests conducted in the IEEE 33-bus test system, it was concluded that the proper adjustment of the Volt-Var and Volt-Watt control curves significantly influences DER hosting capacity, $as$ well $as$ voltage deviation and power losses.

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Combining Robust Control and Machine Learning for Uncertain Nonlinear systems Subject to Persistent Disturbances

Combining Robust Control and Machine Learning for Uncertain ...

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IEEE Conference on Decision and Control

作者： A. Banderchuk D. Coutinho E. Camponogara Post-graduate Program in Automation and Systems Engineering Universidade Federal de Santa Catarina Florianópolis SC Brazil Department of Automation and Systems Universidade Federal de Santa Catarina Florianópolis SC Brazil

This paper proposes a control strategy consisting of a robust controller and an Echo State Network (ESN) based control law for stabilizing a class of uncertain nonlinear discrete-time systems subject to persistent disturbances. Firstly, the robust controller is designed to ensure that the closed-loop system is Input-to-State Stable (ISS) with a guaranteed stability region regardless of the ESN control action and exogenous disturbances. Then, the ESN-based controller is trained in order to mitigate the effects of disturbances on the system output. A numerical example demonstrates the potential of the proposed control design method.

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An integrated transient model in TRNSYS for thermal management of the tomato growth process in a greenhouse with a PV-aided heat pump-assisted HVAC system

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International Journal of Thermofluids 2024年 22卷

作者： Çam, Nezir Yağız Ezan, Mehmet Akif Biçer, Yusuf Dokuz Eylül University The Graduate School of Natural and Applied Sciences Izmir Buca Turkey Yaşar University Faculty of Engineering Department of Energy Systems Engineering Izmir Bornova Turkey Dokuz Eylül University Faculty of Engineering Department of Mechanical Engineering Izmir Buca Turkey Buca Izmir Turkey Division of Sustainable Development College of Science and Engineering Hamad Bin Khalifa University Qatar Foundation Doha Qatar

Greenhouses are the most common agricultural structures for controlled environment agriculture, and it is not easy to control the indoor climate due to the complexity of the heat and mass transfer mechanisms. Therefore, numerical models help to simulate the greenhouse indoor environment under various design alternatives, obtain the heating and cooling rates, and determine the appropriate control strategy. In this study, a novel transient thermal model of a greenhouse is developed in MATLAB and implemented in TRNSYS software to simulate the thermal management procedure for the tomato growth process. A PV-aided HVAC system with a heat pump is integrated into the greenhouse to meet the heating/cooling load and maintain the temperature and relative humidity of the indoor ambient within the desired ranges. It is assumed that the greenhouse has three tomato growth seasons annually. The temperature and relative humidity of the indoor air and the heating and cooling rates of the HVAC system are determined, and the temperature and relative humidity variations are compared against a greenhouse without an HVAC unit. The simulations are conducted with TRNSYS for four climatically different cities: Izmir, Valencia, Casablanca, and Tunis. The results reveal that the electricity consumption of the heat pump-assisted HVAC system is highest in Izmir, with 742,230 kWh/year. Besides, the highest photovoltaic electricity production is determined in Tunis, with 417,960 kWh/year. The highest reduction in carbon emissions is determined in Casablanca, with 112,541.4 kg CO2 eq./year. © 2024

关键词： Temperature control

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Sustainable management of wastewater supply chain: A literature review

Sustainable management of wastewater supply chain: A literat...

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Electrical, Computer, Communications and Mechatronics engineering (ICECCME), International Conference on

作者： Matías Ponce Andrea Espinoza Óscar C. Vásquez Industrial Engineering Department University of Santiago of Chile (USACH) Santiago Chile Program for the Development of Sustainable Production Systems Industrial Engineering Department University of Santiago of Chile Santiago Chile

Water scarcity has led to the search for sustainable methods of wastewater management in recent years. This article presents a comprehensive analysis of wastewater management through a systematic literature review, examining thirty articles published between 2012 and 2022. The main contribution lies in the in-depth analysis conducted on the management wastewater supply chain, focusing on the dimensions of sustainability studied, how they are addressed in models, the types of decisions made, and the methodologies employed. This provides insight into how sustainability has been approached in wastewater management while highlighting areas for improvement and future research.A positive trend is observed in related research, indicating a growing interest in the topic of sustainable management of wastewater supply chains up to the year 2020. To assess sustainability, optimization, and case studies were predominantly utilized, with evolutionary algorithms commonly employed in optimizations, complemented by uncertainty *** suggestions for future research, it is recommended to include political and technological aspects in the analysis of sustainability. Additionally, integrating methodologies with a greater capacity to incorporate multiple objective functions, along with a case study to illustrate their applicability, would be valuable. Addressing these outstanding issues could contribute to a better understanding of sustainable wastewater management and provide more effective solutions.

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FISS GAN:A Generative Adversarial Network for Foggy Image Semantic Segmentation

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IEEE/CAA Journal of Automatica Sinica 2021年第8期8卷 1428-1439页

作者： Kunhua Liu Zihao Ye Hongyan Guo Dongpu Cao Long Chen Fei-Yue Wang School of Computer Science and Engineering Sun Yat-sen UniversityGuangzhou 510006China State Key Laboratory of Automotive Simulation and Control and the Department of Control Science and Engineering Jilin University(Campus Nanling)Changchun 130025China Mechanical and Mechatronics Engineering Department at the University of Waterloo 200 University Avenue West WaterlooON N2L 3G1Canada State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078China

Because pixel values of foggy images are irregularly higher than those of images captured in normal weather(clear images),it is difficult to extract and express their *** method has previously been developed to directly explore the relationship between foggy images and semantic segmentation *** investigated this relationship and propose a generative adversarial network(GAN)for foggy image semantic segmentation(FISS GAN),which contains two parts:an edge GAN and a semantic segmentation *** edge GAN is designed to generate edge information from foggy images to provide auxiliary information to the semantic segmentation *** semantic segmentation GAN is designed to extract and express the texture of foggy images and generate semantic segmentation *** on foggy cityscapes datasets and foggy driving datasets indicated that FISS GAN achieved state-of-the-art performance.

关键词： Edge GAN foggy images foggy image semantic segmentation GAN semantic segmentation

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A GIS Based Approach Towards a Change Detection Framework for Assessing Land Cover in Coastal Lands

A GIS Based Approach Towards a Change Detection Framework fo...

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IISE Annual Conference and Expo 2023

作者： Madkour, Nader Eren-Tokgoz, Berna Amer, Reda Cankaya, Burak Department of Industrial and Systems Engineering Lamar University BeaumontTX77705 United States Department of Earth and Space Sciences Lamar University BeaumontTX77705 United States Department of Management and Technology Embry-Riddle Aeronautical University Daytona BeachFL32114 United States

ISBN: (纸本)9781713877851

In recent years, there has been an increase in interest in using Geographic Information systems (GIS) to study soil erosion. Soil erosion is one of the most significant environmental challenges, making it imperative to study its prevention, assessment, and monitoring. Not only is fertile land being lost, but sediments in water are increasing, causing pollution, killing marine life, and obstructing the water supply. GIS and remote sensing are accurate methods for mapping and analyzing land use and cover changes. A framework was developed for this study to classify, verify, and detect changes in land cover using multitemporal high-resolution images. Using ArcMap software, a change detection model was developed to detect the land loss and gain between multitemporal images. To implement the framework, high-resolution aerial images of Port Arthur in Southeast Texas were obtained from the National Agriculture Imagery program (NAIP). The resolution of these images, taken between 2004 and 2020, ranged from 60 centimeters to 1 meter. The results revealed that the total land loss in the port was more than 770,000 m2, and the total land gain was more than 391,000 m2 over the 16-year period. This framework can be used to quantify and classify the type of change, as well as to assess the accuracy using change detection statistics. © IISE and Expo *** rights reserved.

关键词： Erosion

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Dynamics of Electricity Price Volatility and its Impacts on Energy Investments

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SSRN 2025年

作者： Muğaloğlu, Erhan Kılıç, Edanur Keskin, Hazar Selçuklu, Saltuk Buğra Erciyes University Faculty of Economics and Administrative Sciences Kayseri Turkey Erciyes University Graduate School of Social Sciences Kayseri Turkey Hatay Turkey Erciyes University Faculty of Engineering Department of Energy Systems Engineering Kayseri Turkey

Electricity price fluctuations affect economic growth, social welfare, and investor behavior. This study examines the price volatility dynamics of Türkiye’s day-ahead electricity market from 2018 to 2024, analyzing price variations across three regimes: moderate, high, and extreme. The Markov Regime-Switching GJR-GARCH (MS-GJR-GARCH) model captures sudden regime shifts, proving that the three-regime model outperforms the single-regime model based on Value-at-Risk (VaR) calculations. Regime 1 accounts for 42% of observations in Türkiye’s electricity market, while Regimes 2 and 3 comprise 45% and 13%, respectively. Transition probabilities indicate that electricity prices tend to stay in more volatile regimes, especially during crucial shocks like the Russia-Ukraine conflict and the COVID-19 pandemic. A linear model is also constructed to assess the impact of different energy sources—solar, wind, hydropower, and natural gas—on price volatility. Results show that these effects vary by regime: solar power reduces volatility in extreme conditions, wind and hydropower can either stabilize or amplify volatility, and natural gas is a key driver of volatility in all regimes. Investors and policymakers must adjust strategies based on each volatility regime. Renewable energy investments increase short-term price volatility due to the Merit Order Effect, but in the long run, they enhance energy security by reducing fossil fuel dependence. This study suggests strategies ranging from risk management techniques to energy policies to strengthen Türkiye’s electricity market resilience against sudden price shifts. © 2025, The Authors. All rights reserved.

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