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Enabling intelligent Observability Volume Management 17

Enabling Intelligent Observability Volume Management

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17th international conference on COMmunication systems and NETworkS, COMSNETS 2025

作者： Naik, Priyanka Goel, Seep Raichstein, Eran Meth, Kalman Govindarajan, Kavya Chakraborty, Aishwariya Govindarajan, Chander IBM Research Bangalore India IBM Research Haifa Israel

ISBN: (纸本)9798331531195

In the era of centralized clouds, multi-cloud, and edge computing, adaptable observability is essential to efficiently manage the growing volume of metrics data. Observability Volume Manager (OVM) addresses the complexities of dynamic observability data management by offering tailored processing capabilities that ensures efficient and effective observability across diverse infrastructures. This demo highlights OVM's ability to perform dynamic transformations for fine-grained control over observability data collection, while significantly reducing the volume of data collected, processed, and stored. These optimizations drive substantial cost savings and position OVM as an essential solution for cost-efficient observability. © 2025 ieee.

关键词： Distributed cloud

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Research on Medical Efficiency of Beijing-Tianjin-Hebei Based on SBM Model

Research on Medical Efficiency of Beijing-Tianjin-Hebei Base...

引用

2024 international conference on Mechatronics and intelligent Control, ICMIC 2024

作者： Bai, Yanxin Dong, Yaru Ding, Haozhe Zhao, Chengyu Yang, Zixi Liu, Shuo Zhang, Xinpeng Song, Weiyou School of Economics and Management Hebei University of Technology 300131 China School of Artificial Intelligence and Data Science Hebei University of Technology 300131 China School of Mathematics and Statistics Hebei University of Economics and Trade 050064 China

ISBN: (数字)9781510686847

ISBN: (纸本)9781510686830

Based on the data of Beijing-Tianjin-Hebei region from 2011 to 2019,this paper measures the medical efficiency of Beijing-Tianjin-Hebei region in recent ten years by using the super efficiency SBM model, and uses the ML index decomposition method to conduct a dynamic analysis of medical efficiency, and further discusses the calculation results through convergence analysis, The medical efficiency in Beijing-Tianjin-Hebei region was studied. The study found that the overall medical efficiency in Beijing-Tianjin-Hebei region showed an increasing trend, but the increase was not large, and there was greater room for progress;The convergence of ML index changes is also high, indicating the overall development of Beijing-Tianjin-Hebei region. © 2025 SPIE.

关键词： Medical research data modeling Analytical research data acquisition Medical equipment Diseases and disorders systems modeling Biomedical applications Education and training Energy efficiency

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Hybrid Approach for Electricity Price Forecasting using AlexNet and LSTM 3

Hybrid Approach for Electricity Price Forecasting using Alex...

引用

3rd international conference on intelligent data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Sambana, Bosubabu Devi, Kotamsetty Geethika Reddy, Bandi Rajeswara Hussain, Galeti Mohammad Siddartha, Gownivalla School of Computing Mohan Babu University Tirupati India Department of Computer Science and Systems Engineering Sree Vidyanikethan Engineering College Tirupati India

ISBN: (纸本)9798331527549

The recent development of advanced machine learning methods for hybrid models has greatly addressed the need for the correct prediction of electrical prices. This method combines AlexNet and LSTM algorithms, which are used to introduce a new model with higher accuracy in price forecasting. Despite RNN and ANN being effective, they often fail to deal with forex time sequence data. The traditional methods do not accurately forecast the prices. These traditional methods only focus on demand and price which leads to insufficient analysis of data. To address this issue, using the hybrid approach, which focuses on external variables that also effect the predicted prices. Nevertheless, due to AlexNet's excellent feature extraction and LSTM's learning sequential patterns, the prediction accuracy is vastly increased. The model is built on the past data, which has been supplied with the most significant elements like demand, temperature, sunlight, and rain. For example, the model applies methods, such as minimum-maximum scaling and a time window, to predict the electricity prices of the future. The results show that this hybrid model is good than the standalone ones in terms of accuracy. Although we got our accuracy rating of 97.08, it shows higher accompaniments than remaining models RNN and ANN with accuracies of 96.64 and 96.63 respectively. © 2025 ieee.

关键词： Prediction models

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Fuzzy Logic and Fog computing in Electronic Health Records data Privacy: A Comprehensive Review 2

Fuzzy Logic and Fog Computing in Electronic Health Records D...

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2nd international conference on Computational Intelligence, Communication Technology and Networking, CICTN 2025

作者： Mohan, Devendra Singh Bansal, Varun Kumar, Anil Shobhit University Gangoh Saharanpur India Shobhit University Gangoh Saharanpur India GCET Gautam Buddha Nagar India

ISBN: (纸本)9798331530389

The potential to improve healthcare services has drawn attention to the use of fuzzy logic and fog computing into electronic health records (EHRs). This study offers a thorough analysis of the research on Fog computing (FC) enabled Fuzzy Logic c-based EHR systems. While fog computing allows for real-time data processing and decentralized storage near end users, fuzzy logic provides a reliable method for handling ambiguities in patient data, diagnoses, and decision-making. When combined, these technologies enhance data security, scalability, and system responsiveness. This research paper includes major approaches, architectures and important applications such as in cloud computing fog-based solutions reduces bandwidth and latency related issues with the help of fuzzy logic how clinical decision support system improves. In this study we list the future research possibilities to address these type problems and also explains obstacles such as complexity of computing, interoperability and privacy of data. These type of study assists academics and practitioners to creating effective, intelligent and safe EHRs' system. In this research paper privacy preservation of EHRs addressed by integration of fuzzy logic with fog computing. © 2025 ieee.

关键词： Electronic health record

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Proposed AES-based Obfuscation and Encryption Model for Cloud data Security 1

Proposed AES-based Obfuscation and Encryption Model for Clou...

引用

1st international conference on intelligent systems and Computational Networks, ICISCN 2025

作者： Singh, Prabhdeep Singh, Pawan Agarwal, Abhay Kumar Kumar, Anil Amity School of Engineering and Technology Department of Computer Science and Engineering Lucknow India Kamla Nehru Institute of Technology Department of Computer Science and Engineering Sultanpur India Amity University Amity School of Engineering and Technology Lucknow India

ISBN: (纸本)9798331529246

Cloud computing (CC) offers a diverse range of services along with huge data storage across a network. CC has collaborated with varied emerging technologies like IoT because of its numerous advantages. Despite CC's benefits, cloud-based servers are not always trustworthy in real-world scenarios. Users' privacy will be compromised if they send their data straight to cloud platforms since crucial information will be exposed to cloud servers. Thereby, this work develops a data security model in the cloud with two stages, proposed secured data storage and proxy re-encryption. Initially, the data is stored securely in the cloud based on improved AES-based encryption as well as obfuscation-based encryption. Based on the request from the data user, proxy re-encryption is done using Kronecker product-based encryption. The enhanced AES achieved the lowest value of 0.025 for the CCA attack with a key size of 128 bits. Thus, the final encoded key is obtained. © 2025 ieee.

关键词： Cloud platforms

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Blockchain Integration for Robust Intellectual Property Protection in New Product Development (NPD) 3

Blockchain Integration for Robust Intellectual Property Prot...

引用

3rd international conference on Electronics and Renewable systems, ICEARS 2025

作者： Chinnasamy, P. Subashini, B. Nijanthan, Nijanthan Madasamy Raja, G. Swetha, Devulapally Sreenivasulu Reddy, L. School of Computing Kalasalingam Academy of Research and Education Department of Computer Science and Engineering Tamilnadu India School of Computing Srmist Department of Data Science and Business Systems Kattankulathur India Paavai Engineering College Tamilnadu Namakkal India Paavai Engineering College Tamilnadu Namakkal India Vaagdevi Engineering College Dept. of Computer Science and Engineering Warangal Dist. Telangana Bolli Kunta506005 India School of Advanced Sciences Kalasalingam Academy of Research and Education Department of Mathematics Tamilnadu Krishnankoil India

ISBN: (纸本)9798331509675

The rapid advancement of Blockchain technology has led to its widespread application in several domains of digital activities, such as e-government concerns and monetary security. This article presents a smart contract-based Blockchain solution for protecting intellectual property rights in new product development. The proposed solution effectively tackles the challenges associated with the confidentiality of personally identifiable information, efficiency in storing transaction-related information, as well as cooperation and monitoring in IPR. Initially, we create a mathematical model based on smart contract enabled Blockchain and intelligent contracts. Subsequently, we develop algorithms for Blockchain generation, and intelligent contracts. The system is suitable for protecting IPR in a blockchain network, by implementation of distributed identity authentication and real-time extensible storage. These features enhance the security and expandability of circuit copyright protection based on blockchain technology. The experimental results demonstrate that the suggested algorithm has decreased the cost for communication and enhanced the effectiveness of storing information and administration. Furthermore, it demonstrates resilience against many common attacks such as double-spending assaults, while maintaining low cost and overhead. Additionally, it exhibits a superior level of security in comparison to three other competing algorithms. © 2025 ieee.

关键词： Smart contract

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Algorithm Implementation of Digital Protection System for Traditional Cultural Industry Based on Grey Clustering

Algorithm Implementation of Digital Protection System for Tr...

引用

2024 international conference on Mechatronics and intelligent Control, ICMIC 2024

作者： Chen, Hongxia Hou, Lanbao School of Literature and Media Jingchu University of Technology Jingmen448000 China School of Mathematics and Physics Jingchu University of Technology Jingmen448000 China

ISBN: (数字)9781510686847

ISBN: (纸本)9781510686830

The protection mode of digitalization effectively transforms various national traditional cultures into digital products, providing a way of thinking for the protection of national traditional cultures. This mode still lacks the mode of how to mine the data of national traditional culture and analyze the internal relationship structure after facing the massive data, which can guide the digital protection of national traditional culture under the complex social conditions in the future. This paper discusses the significance of digitalization for the protection of traditional national culture under the environment and ideology of big data development. The possibility of protecting traditional national culture based on big data was analyzed and discussed. This paper designs and establishes the digital perception analysis system of traditional culture. The system uses grey clustering algorithm to identify the characteristics of cultural products. The experimental results show that this method can improve the efficiency of traditional cultural product classification. This method has certain reference value for the research of digital protection system of traditional cultural industry. © 2025 SPIE.

关键词： Augmented reality Visualization Telecommunications computing systems Cultural heritage data communications Image processing Video data storage Cameras

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Smart Servo-Operated Ball Valve with IoT Integration and PID Control for Precise Fluid Management 3

Smart Servo-Operated Ball Valve with IoT Integration and PID...

引用

3rd international conference on intelligent and Innovative Technologies in computing, Electrical and Electronics, IITCEE 2025

作者： Bhanuse, Vijaykumar Bhosale, Shreyash Nitin Bhilare, Abhishek Mahadev Bauskar, Aneesh Rajesh Vishwakarma Institute of Technology Pune411037 India

ISBN: (纸本)9798331515911

This paper presents the design and implementation of an innovative control valve system that integrates a ball valve run by a servo motor, IoT capabilities, and PID control for precise operation. The system uses a 1/4-inch ball valve mounted in a custom 3D printed housing, driven by an MG995 servo motor. An ESP32 WROOM module microcontroller enables Wi-Fi connectivity and data transmission to the cloud via the Thingspeak platform. Ultrasonic sensors are used for tank level measurement, and the valve operation is controlled using a PID algorithm implemented in C++ on the Arduino IDE. The PID parameters are fine-tuned to achieve best performance. This solution offers a cost-effective and precise method for fluid control in various industrial applications. © 2025 ieee.

关键词： Three term control systems

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Hybrid AI-Electronic systems for Real-Time Edge Processing in IoT Networks 3

Hybrid AI-Electronic Systems for Real-Time Edge Processing i...

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3rd international conference on intelligent and Innovative Technologies in computing, Electrical and Electronics, IITCEE 2025

作者： Sweety Prasanna Kiruba, G. Esakki Madura, E. Kumar, Bura Vijay Kavitha, M. Reddy, T. Srinivas Athiraja, A. Bannari Amman Institute of Technology Department of Computer Technology Tamil Nadu Sathyamangalam India Bannari Amman Institute of Technology Department of Artificial Intelligence and Data Science Tamil Nadu Sathyamangalam India School of Computer Science and Artificial Intelligence Sr University Warangal India Kathir College of Engineering Department of Artificial Intelligence and Data Science Neelambur Coimbatore India Malla Reddy Engineering College Department of Ece Main Campus Maisammaguda Telangana Medchal India Hyderabad India

ISBN: (纸本)9798331515911

Real-time data processing is facing many issues as a result of the Internet of Things' rapid expansion, especially at the network's edge where latency, bandwidth, and compute resources are limited. The creation of hybrid AI-electronic systems for real-time edge processing is investigated as a solution to these problems. To improve the effectiveness and precision of data processing in Internet of Things contexts, the research combines machine learning algorithms with sophisticated electronic circuits. The techniques include creating a brand-new hybrid framework that blends edge computing and AI models and focuses for low latency and low power consumption. When compared to conventional edge processing systems, extensive simulations and real-world research show a 25% reduction in processing latency and a 15% gain in data categorization accuracy. According to the findings, the suggested hybrid AI-electronic system can successfully handle the requirements of contemporary IoT networks and offer a scalable real-time edge processing solution. This strategy has potential for use in smart city applications, industrial automation, and other fields in the future. © 2025 ieee.

关键词： Adversarial machine learning

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data processing, analysis and Machine Learning of Electrical Atomic Force Microscopy (AFM) in data Cube mode: conduction of a nanomaterial for Lithium-ion battery electrodes 6

Data processing, analysis and Machine Learning of Electrical...

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6th ieee international conference on Image Processing, Applications and systems, IPAS 2025

作者： Germanicus, Rosine Coq De Wolf, Peter Klapetek, Petr Normandie Univ Unicaen Ensicaen CNRS CRISMAT UMR6508 Caen14000 France Bruker Nano Surfaces Santa BarbaraCA93117 United States Czech Metrology Institute Brno638 00 Czech Republic

ISBN: (纸本)9798331506520

With the increasing integration of functional systems, nanoscale characterization has become crucial not only for material investigation but also for advancing the understanding of local behavior and optimizing performances. This paper details data processing techniques and machine learning methodologies for the analysis and prediction of advanced electrical Atomic Force Microscopy datasets. The datasets are acquired using a hyperspectral data Cube approach, which combines both mapping and spectroscopy acquisitions. In the context of decarbonization and electrification, current challenges are related to energy storage and transport. A cathode material used in Lithium-ion battery electrodes is investigated for its electrical transport properties. To comprehensively characterize the electrical properties, the conductive mode of Atomic Force Microscopy is employed using the data Cube method, which enables current-voltage spectroscopy at each pixel of the acquisition. The analysis of experimental datasets reveals localized electrical behavior of the material's components as a function of applied voltage. Furthermore, machine learning algorithms are employed to predict current maps and cluster distinct regions based on their electrical characteristics. © 2025 ieee.

关键词： Network security

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