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检索条件"任意字段=4th International Conference on Software and Data Technologies"

共 13474 条记录，以下是61-70 订阅

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A Study on the Green Evaluation System of Suppliers for Power Grid Enterprises Based on the Cloud Model 24

A Study on the Green Evaluation System of Suppliers for Powe...

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4th Asia-Pacific Artificial Intelligence and Big data Forum, AIBDF 2024

作者： Zhao, Zhenfeng Su, Hang Liu, Zeqi Li, Chao Li, Xiaoyi Li, Peng Mu, Qijian State Grid Jibei Electric Power Co. Ltd Beijing China Jibei Electric Power Research Institute State Grid Jibei Electric Power Co. Ltd. North China Electric Power Beijing China China International Engineering Consulting Corporation Beijing China

ISBN: (纸本)9798400710865

For the low-carbon energy transition, evaluating the supply chain system within power grid enterprises is critical to achieving national goals of sustainable development and green procurement. As a core entity within the energy industry chain, power grid companies present substantial requirements and challenges to their upstream suppliers. Taking the supply system of State Grid Jibei Electric Power Limited as a case study, this study applies a combination of MATLAB, Python, and R software to build up a cloud model for assessing the performance of materials and service providers within the power grid sector. the findings indicate that although many suppliers have made noticeable progress in implementing green management practices, significant deficiencies still persist in corporate information disclosure of carbon reduction efforts, green service capabilities, and product carbon footprints. Besides that, those companies exhibit a clear stratified pattern in evolving green and low-carbon practices, which implies uneven adoption and implementation across different suppliers. this study suggests that prioritizing investments in green technologies for suppliers can efficiently guide corporate performance into sustainable practices. Moreover, there is an urgent need for government intervention through more incentive mechanisms on grid power enterprises to accelerate the green transformation of supply chains and foster broader adoption of low-carbon practices. © 2024 Copyright held by the owner/author(s).

关键词： Cloud Model

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Next-Generation Smart Greenhouse: Integrating Universal Interaction technologies 4

Next-Generation Smart Greenhouse: Integrating Universal Inte...

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4th international conference on Robotics, Electrical and Signal Processing Techniques, ICREST 2025

作者： Hassan, Tonmoy Das, Debraj Ahmad, Shameem Murad, Sayed Hasan Hazari, Md. Rifat Rahman Zishan, Md. Saniat Hossain, Tamim American International University-Bangladesh Faculty of Engineering Department of Electrical and Electronic Engineering Dhaka1229 Bangladesh American International University-Bangladesh Dhaka1229 Bangladesh

ISBN: (纸本)9798331530938

Agriculture is the largest employment sector in Bangladesh, making up 14.2% of GDP in 2017 and employing about 42.7% of the workforce. To support the GDP and grater employment, uses of the latest technology in agricultural areas are much more needed. Farmers still using the convention way to grow crops, which leads to less production, high labor cost, more manpower needed to monitor and maintenance the yield system. this study focuses on IoT-based smart greenhouse agricultural monitoring and automation, which provides farmers with real-time data and insights into a variety of topics such as data monitoring, controlling, automation crop yield, and cost effectiveness. An ESPS266-based hardware and Adafruit platform have been designed to monitor extracted data such as soil moisture, temperature, humidity, automatic water irrigation and automatic hot air exhaust systems. the system's benefit is proved in a comprehensive manner through defined programming, hardware results, and data analysis, reducing the need for human monitoring and watering of the system, hot air will be expelled from the field, resulting in greater crop development up to 15-50% higher crop yield on the same field. © 2025 IEEE.

关键词： Soil moisture

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Prediction of Power Evolution in Second-Order Raman Systems Based on PINN 4

Prediction of Power Evolution in Second-Order Raman Systems ...

引用

4th international Computational Imaging conference, CITA 2024

作者： Feng, Zhongshuai Li, Wei Mei, Muyang Hu, Kaijing Su, Xingrui Mei, Liang Luo, Ming Huang, Liyan Wuhan National Laboratory for Optoelectronics Huazhong University of Science and Technology Wuhan430074 China Fiberhome Telecommunication Technologies Co. Ltd. Wuhan430074 China State Key Laboratory of Optical Communication Technologies and Networks 430074 China Accelink Technologies Co. Ltd. Wuhan430074 China

ISBN: (纸本)9781510688834

the application of second-order Raman amplifiers is growing due to their superior performance, but modeling these systems is complex and computationally demanding. Traditional numerical methods for simulating Raman power evolution require extensive resources and are highly sensitive to initial conditions, leading to potential inaccuracies. data-driven machine learning models have been explored as alternatives, but they often require large datasets and are prone to underfitting or overfitting. Physics-Informed Neural Networks (PINNs) offer a promising solution, integrating physics-based constraints directly into the model. While previously applied only to first-order Raman systems, this paper extends PINNs to second-order Raman systems. By combining neural network capabilities with boundary conditions from Raman coupling equations, PINNs can simulate signal evolution accurately. Experiments with a 200 km bidirectional Raman system show that PINN achieves less than 1 dB error, improved efficiency, and higher tolerance for boundary conditions compared to traditional methods. these findings highlight PINN's potential for accurate and practical applications in Raman system modeling. © 2025 SPIE.

关键词： Photons

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A Machine Learning-Based Approach for Soil Chemical Property Estimation Using Multispectral data in Hungary 4th

A Machine Learning-Based Approach for Soil Chemical Propert...

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4th international conference on Emerging Trends and technologies on Intelligent Systems, ETTIS 2024

作者： Seal, Sourav Sethia, Divyashikha Department of Software Engineering Delhi Technological University Delhi India

ISBN: (纸本)9789819757022

Soil is essential to the environmental process and growing crops. An accurate assessment of soil chemical characteristics is essential for agricultural and land management decisions to be well-informed. Precision agriculture has advanced significantly because of machine learning. It uses automation and data-driven insights to improve several facets of agricultural methods, fostering effectiveness, sustainability, and productivity. the "Land Use/Cover Area Frame Statistical Survey Soil" (LUCAS) is a comprehensive and frequent topsoil survey conducted throughout the European Union to get data pertinent to policy about how land management affects soil properties. the data covers 28 European Union States. this paper analyzes and predicts the chemical properties of the soil of Hungary based on the LUCAS 2015 dataset that includes calcium carbonates (CaCO3), nitrogen (N), phosphorus (P), potassium (K), electrical conductivity (EC), pH. It estimates them using LUCAS and Landsat 8 satellite images by using different regression-based algorithms like partial least square regression (PLSR), Gaussian process regression (GPR), support vector regression (SVR), multilayer perceptron (MLP), AdaBoost, ridge and compares them. the Lucas survey data points and Landsat 8 satellite images (multispectral) are integrated for forecasting different soil nutrients, expanding the model’s relevance to diverse agricultural and environmental applications. the algorithms undergo evaluation, producing acceptable Root Mean Squared Error (RMSE) and Ratio of Performance to Prediction (RPD) values. the proposed approach can estimate the chemical properties of the soil samples in Hungary replacing the orthodox method of laboratory analysis with the soil samples’ spectral image. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Soil surveys

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Blockchain Based Access Control: A Review and Future Perspectives 4th

Blockchain Based Access Control: A Review and Future Perspec...

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4th international conference on data and Information in Online Environments

作者： Xu, Riqing Shan, Liang Wang, Xinlong Lei, Gang Jiangxi Normal Univ Sch Software Nanchang 330022 Jiangxi Peoples R China Jiangxi Prov Engn Res Ctr Blockchain Data Secur & Nanchang Jiangxi Peoples R China

ISBN: (纸本)9783031807121;9783031807138

this paper reviews the state of the art in blockchain-based access control research. In the digital era, data security and access management are increasingly important. Traditional access control (e.g. RBAC, ABAC, CapBAC) faces various challenges in IoT, such as the risk of centralization and the threat of data leakage. To address these issues blockchain technology (with its properties such as distributed and tamper-proof) provides innovative solutions. this paper first introduces the three main-stream access control in IoT, then discusses the basic concepts of blockchain (including consensus mechanism, smart contract and cryptography), and analyzes the blockchain in access control applications (including authentication, privilege management and audit trail). It then discusses the advantages and challenges of block-chain access control and future research directions. Finally, the potential of block-chain in access control is summarized, emphasizing its importance for data security and privacy protection. through this overview paper, readers can better understand the application of blockchain technology in access control and provide valuable insights for future research and practice.

关键词： Access control Blockchain data security Privacy IoT

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IAAD: Integrated Anti-Anti-Drone mechanics with cryptography utilized in power grid inspection 4

IAAD: Integrated Anti-Anti-Drone mechanics with cryptography...

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4th international conference on Network Communication and Information Security, ICNCIS 2024

作者： Wang, Qinghan Liu, Liang Zou, Hui Wang, Xingzhao Li, Yang Wang, Xinkai State Grid Intelligent Technologies Co. Ltd. Jinan250101 China

ISBN: (数字)9781510688261

ISBN: (纸本)9781510688254

the application of drone inspection with airports and an online system has been significantly expanded to encompass smart power grid inspection. the communication infrastructure for this application is based on serial, 4G/5G cellular, wireless remote and Ethernet, with a deep fusion into the industrial network of the power grid. the intricacy of the protocol stack and topology necessitates the implementation of robust mechanisms for data integrity verification, cyber threats monitoring and defense. Furthermore, drones are susceptible to damage during automated inspection, and the deployment of anti-drone measures may result in the destruction of aircraft and the impairment of power facilities. the Integrated Anti-Anti-Drone (IAAD) mechanics on the drone system are implemented by a combination of three cryptographic elements: (1) a cryptographic mechanism set working with the security protocol, (2) physical anti-disassembly and auto key destruction, (3) code/data encryption mechanics. Finally, an analysis of the experimental system is presented to further validate the applicability of the technology to power grid inspection. © 2025 SPIE.

关键词： Drones

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Smart Savior: A Life Jacket Integrated IoT Emergency Response System Utilizing TTGO T-Call ESP32 and Advanced Sensor technologies 4

Smart Savior: A Life Jacket Integrated IoT Emergency Respons...

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4th international conference on Robotics, Electrical and Signal Processing Techniques, ICREST 2025

作者： Jakarea, Md. Sutradhar, Debopom Talukder, Ariful Islam Sourov, S.M. Azizul Hoque Debnath, Ripon Kumar Karim, Md Shifat Nion, Md. Tamzidul Islam Akter, Tania Bulbul, Helena United International University Department of Eee Dhaka1212 Bangladesh United International University Department of Cse Dhaka1212 Bangladesh United International University Department of Bba Dhaka1212 Bangladesh

ISBN: (纸本)9798331530938

Life jackets are crucial for aquatic safety, preventing drowning and aiding in rescue. However, locating survivors can be challenging. the Smart Savior life jacket, enhanced with IoT technology, integrates advanced sensors into a wristband and jacket to monitor environmental and physiological data. Key components include the NEO-6M GPS module, heart rate and body temperature sensors, and the ESP32 microprocessor. data is transmitted via ESP-NOW for real-time monitoring and analysis. Rescue teams access a dynamic dashboard to prioritize rescue efforts based on geolocation and critical health indicators. the system's performance, evaluated against industry standards, shows faster GPS connectivity, real-time data synchronization, and improved accuracy in heart rate monitoring (98%) and water temperature sensing (±0.5°C). this integration offers a robust and effective approach to enhancing safety and responsiveness during aquatic disasters, making it a vital tool in saving lives. © 2025 IEEE.

关键词： Heart

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Multi-agent digital twin of broccoli: Development and test evaluation 4

Multi-agent digital twin of broccoli: Development and test e...

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4th international conference on Evolutionary Computing and Mobile Sustainable Networks, ICECMSN 2024

作者： Skobelev, Petr Tabachinskiy, Aleksey Simonova, Elena Zhuravel, Yulia Galitskaya, Anastasiya Samara Federal Research Scientific Center RAS 3a Studencheskiy lane Samara443001 Russia Samara State Technical University 244 Molodogvardeyskaya Str. Samara443100 Russia Samara National Research University 34 Moskovskoye Shosse Samara443086 Russia

Crop production is a complex multi-domain field of knowledge dealing with living objects. Ongoing global climate change has been destroying this long-established sustainable knowledge system. Precise farming needs digital integration of several domain fields: technologies, machinery and equipment, knowledge about plant growth, predicting the impact of activities on crop yield online. Digital twin of plant, mirroring and predicting plant's state and growth in real-time should be the central element of precision farming system. In the paper, a Smart Plant Digital Twin (SPDT) is proposed as a smart software system with a knowledge base and methods of reasoning. SPDT is developed for online management and simulation of plant behaviour in sync with development of the real plant. A multi-agent implementation of multi-level plant structure is discussed in the paper, which considers crop physiology and resource demand, describing internal processes inside a plant, and a method for calculating the crop parameters and duration of plant development stages based on expert knowledge. Ontological model of SDTP for crop cultivation domain reflects the production process of each field or greenhouse crop and allows the scale up of the number of simulated cultures, specifying the differences between the varieties and cultivars, and widening the effects of agricultural measures. the plant model is illustrated in broccoli growth process. the model was validated in real experiment compared to the growth of real broccoli crops, planted in the Taiwan region, and real data from the field sensors and agronomists from the farms acquired data from their sensors and worked with digital twins of their crops. © 2025 the Authors. Published by Elsevier B.V.

关键词： Decision-making Digital twin Knowledge base Multi-agent technologies Precise farming Production process

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E-Healthcare Record System Using Blockchain 4th

E-Healthcare Record System Using Blockchain

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4th international conference on Smart IoT Systems: Innovations and Computing, SSIC 2023

作者： Pattnayak, Parthasarathi Mohanty, Arpeeta Das, Tulip Patnaik, Sanghamitra School of Computer Applications KIIT Deemed to Be University Odisha Bhubaneswar India Faculty of Emerging Technologies SRI SRI University Odisha Cuttack India School of Law KIIT Deemed to Be University Odisha Bhubaneswar India

ISBN: (纸本)9789819751990

the term "Electronic Healthcare Record" (EHR) refers to an electronic recording of the medical record of a patient that is maintained by the system over time and can include all relevant, authoritative clinical information important to the user’s care. All of the patient’s medical data (also called PHI) about the diagnosis of disease along with diagnostic reports is saved and communicated across the system’s users within a contemporary, stored in the cloud E-healthcare system. But a significant concern is the protection of these private documents from misuse and unauthorized access. In this situation, the blockchain-based record-sharing solution might be crucial for safe medical data exchange. In this paper we discussed the session data will be encrypted using intelligent deals with between planetary file solution (IPFS)-based secured healthcare picture security solution. For improved accountability, it also logs each health care interaction in the blockchain. For healthcare services, this cutting-edge paradigm offers significant adaptability and EHR accessibility. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Electronic health record

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Electronic consumption vouchers fraud detection of city Y based on improved LSTM-AE structure 4

Electronic consumption vouchers fraud detection of city Y ba...

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2024 4th international conference on Intelligent Traffic Systems and Smart City, ITSSC 2024

作者： He, Mozhou Guo, Yi Zeng, Kewei Xia, Shishun School of Electrical Engineering and Electronic Information Xihua University Sichuan Chengdu610039 China International Department of Chengdu Shude High School Sichuan Chengdu610031 China

ISBN: (纸本)9781510686304

In response to the post-COVID-19 economic recession, City Y, as part of its smart city initiatives, issued electronic consumption vouchers (ECVs) to boost the market economy. However, some individuals exploited these vouchers, affecting their fairness and effectiveness. thus, this paper presents an unsupervised deep learning framework to detect fraudulent merchants and anomalies in voucher redemptions. We use Long Short-Term Memory (LSTM) units combined with an autoencoder (AE) to learn long-term dependencies in time series data. A smoothing unit is also used to reduce prediction bias. the fraud scoring module assesses merchants based on the ratio of anomalous redemptions to total redemptions. Our experimental results show that this approach significantly improves fraud detection accuracy and efficiency, making it a promising tool for maintaining the fairness and effectiveness of ECVs within the smart city ecosystem. © 2025 SPIE.

关键词： Computer security databases Security technologies Standards development Autonomous driving Roads Transportation Intelligence systems Compliance Navigation systems

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