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Software and Hardware Processing Method for Blockchain Light Node SPV Verification 21

Software and Hardware Processing Method for Blockchain Light...

引用

21st ieee international Symposium on Parallel and Distributed Processing with Applications, 13th ieee international conference on Big data and Cloud computing, 16th ieee international conference on Social computing and Networking and 13th international conference on Sustainable computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2023

作者： Ma, Zhan'Gang Yan, Jiandong Zou, Feng Cao, Xixin Peking University School of Software and Microelectronics Dept. Integrated Circuits and Intelligent Systems Beijing China Ruiyuan Venture Capital Co. Ltd. Changzhou Zhonglou Jinlong Holding Group Dept. Development Planning and Strategic Inverstment Changzhou China

ISBN: (纸本)9798350329223

With the application of blockchain light nodes in embedded devices, how to alleviate computing pressure brought by complex operations such as transaction's SPV Verification for CPU of embedded devices and improve the performance of devices in these aspects has gradually become a research topic in industry and academia. This paper proposes a series of methods to improve the performance of blockchain SPV Verification from the perspectives of system architecture and hash computing unit: (1) According to the computational characteristics of SPV Verification, this paper customizes macro instructions and microinstructions for the coprocessor to meet the requirements of flexibility;The built-in dedicated cache holds transaction data fetched from external memory and intermediate data generated by internal Hash computing Unit, which not only prepares transaction data for hash computation, but also avoids frequent access to the bus and external memory. (2) Techniques like two-round unfolded computing, timing-balanced pipeline architecture and optimized adders are adopted to improve the performance of SHA256 computation. (3) When double hash computing is required for transactions, Hash computing Unit can directly perform the second hash computation based on the first hash computation, reducing the frequency of accessing to external memory, thereby improving the performance to a certain extent. Through these methods, the performance of the hardware coprocessor for SVP verification of transactions is more than double that of traditional solutions. © 2023 ieee.

关键词： Blockchain

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Optimizing Microgrid Energy Management: intelligent Techniques 28

Optimizing Microgrid Energy Management: Intelligent Techniqu...

引用

28th international Electrical Power Distribution conference, EPDC 2024

作者： Meydani, Amir Shahinzadeh, Hossein Nafisi, Hamed Gharehpetian, Gevork B. Department of Electrical Engineering Tehran Iran

ISBN: (纸本)9798350385502

advanced methodologies like Artificial Intelligence (AI), Consensus Algorithms (CA), and Model Predictive Control (MPC) significantly enhance Microgrid Energy Management (MG EMS). This study highlights how these technologies boost the effectiveness, durability, and eco-friendliness of decentralized energy systems. AI is used for predictive maintenance, demand forecasting, and anomaly detection. CAs facilitate decentralized decision-making among distributed energy resources, as shown through case studies. MPC optimizes energy generation, storage, and consumption using real-time data and predictive models, improving grid stability and economic efficiency. These intelligent methods help MG operators manage modern energy systems, promoting sustainable energy integration and cost optimization. The evolving global energy landscape is expected to benefit greatly from these advancements in MG technology. © 2024 ieee.

关键词： Model predictive control

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Centering on Humans - Intersectionality in Vision systems for Human Order Picking 43rd

Centering on Humans - Intersectionality in Vision Systems fo...

引用

43rd IFIP WG 5.7 international conference on Advances in Production Management systems (APMS)

作者： Flores-Garcia, Erik Jeong, Yongkuk Zuniga, Enrique Ruiz Wiktorsson, Magnus KTH Royal Inst Technol Dept Prod Engn S-15136 Sodertalje Sweden Univ Skovde Sch Engn Sci Dept Intelligent Automat S-54136 Skovde Sweden

ISBN: (纸本)9783031716355;9783031716331;9783031716324

This study applies an intersectional approach to address concerns about diversity of data acquisition when applying computer vision systems in human order picking. The study draws empirical data from a single case study conducted at an automotive manufacturer. It identifies critical factors of intersectionality for the use of vision systems to enrich data collection in human order picking at four levels including form and function, experience and services, systems and infrastructure, and paradigm and purpose. These findings are helpful for mitigating bias and ensuring accurate representation of the target population in training datasets. The results of our study are indispensable for enhancing human-centricity when applying computer vision systems, and facilitating the acquisition of unstructured data in human order picking. The study contributes to enhancing diversity in human order picking, a situation that is highly relevant because of the variations in age, gender, cultural background, and language of staff. The study discusses theoretical and managerial implications of findings, alongside suggestions for future research.

关键词： vision systems diversity human-centricity

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The data Structure of an intelligent System for Developing Educational Programs 10

The Data Structure of an Intelligent System for Developing E...

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10th international conference on systems and Informatics, ICSAI 2024

作者： Kaibassova, Dinara Seipisheva, Elmira Mukhametzhanova, Bigul Assanova, Baktygul Sagatbekova, Dinara Astana IT University Department of Computing Engeneering Astana Kazakhstan Abylkas Saginov Karaganda Technical University Department of Information Computing System Karaganda Kazakhstan Kh. Dosmukhamedov Atyrau University Faculty of Physics Mathematics and Information Technology Atyrau Kazakhstan

ISBN: (纸本)9798331510138

The results of the research on supporting the process of formation of educational programs by processing large volumes of poorly structured texts without re-processing and adapting professional content are presented. In connection with this, the design of educational programs involves the procedure of creating a database of professional competencies based on professional standards, which, in turn, will serve as the foundation for the process of developing and updating educational programs. The subject of the study is the content of professional standards, defined as a set of data characterizing learning outcomes and qualification skills. As a result of the work, the authors have created a formal-structural model of representing elements of professional content in the form of entities connected by structural relations. The obtained base of professional competencies based on professional standards will be the basis for the process of formation and updating of educational programs. © 2024 ieee.

关键词： data assimilation

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A Review of Deep Learning based Intrusion Detection systems 4

A Review of Deep Learning based Intrusion Detection Systems

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4th ieee international conference on computing, Communication, and intelligent systems, ICCCIS 2023

作者： Jangra, Rekha Kajal, Abhishek Guru Jambheshwar University of Science and Technology Department of Computer Science and Engineering Haryana Hisar India

ISBN: (纸本)9798350306118

In recent years, proliferation of network attacks and cyber threats has underscored the critical need for robust and efficient Intrusion Detection systems (IDS) to safeguard digital assets and sensitive information. Deep Learning (DL) has emerged as a promising technology for enhancing accuracy and effectiveness of IDS due to its ability to automatically extract intricate patterns and anomalies from large-scale network data. This review paper provides a comprehensive survey of DL-based IDS, offering insights into their strengths, limitations, and recent advancements. Due to the necessity of cyber security, numerous researches have been undertaken to categorize the data moving through the network. Intrusion detection is the prominent method of cyber security to identify the intruders and lessen the network hazard. The present study work has concentrated on the necessity and procedure of IDS using DL mechanisms. Reliability and feasibility of IDS depend on performance and accuracy of deep learning. Present research has conducted a review study of conventional research work and focused on the methodology used during IDS detection and classification using ML and DL. The limitation of conventional research work is also presented in problem statement to propose a better deep learning approach in the future. © 2023 ieee.

关键词： Intrusion detection

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A Novel AI Framework for Assuring data Sustainability in Health Care dataset 3

A Novel AI Framework for Assuring Data Sustainability in Hea...

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3rd international conference on Ubiquitous computing and intelligent Information systems, ICUIS 2023

作者： Sudharson, D. Divya, P. Saranya, K. Dubey, Aman Kumar Vijay, Shreya Mayuri, G. Kumaraguru College of Technology Coimbatore India Bannari Amman Institute of Tech Erode India

ISBN: (纸本)9798350306989

data is acquired from various sources which helps in reaching the Enterprise data Warehouses (EDW) and Enterprise data Hubs (EDH). Therefore, a high quality of sensitive data must be maintained in these EDW and EDH. This quality in data has become crucial for any health care sector since all the analysis and solutions were framed with respect to it. In this article, a well-defined framework is curated for ensuring the data quality by segregating them accordingly. data performance being the Key Performance Indicator (KPI) ultimately impacts the success or failure of any application in cloud or remote environment. These frameworks also monitor the data performance and enable performance analysis on data quality. The F-Status ensures the diversity among heterogenous dataset and scale them accordingly such that they can be classified as per instance or per batch in healthcare datahubs or data warehouses. © 2023 ieee.

关键词： Health care

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Validation of the Global Human Settlement Layer and NASA Population data for Ukraine 11

Validation of the Global Human Settlement Layer and NASA Pop...

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11th ieee international conference on intelligent data acquisition and advanced computing systems - Technology and Applications (IDAACS)

作者： Kussul, Nataliia Yailymova, Hanna Drozd, Sophia Shelestov, Andrii Natl Tech Univ Ukraine Igor Sikorsky Kyiv Polytech Inst UA-03056 Kiev Ukraine Space Res Inst NASU SSAU Glushkov Ave 404-1 UA-03187 Kiev 187 Ukraine

ISBN: (纸本)9781665426053

In Ukraine, due to financial difficulties, the planned census is often postponed from year to year. The country is forced to rely on static data, which is sometimes completely untrue. In addition, it is not possible to count the number of inhabitants everywhere. In particular, Ukraine has not known for several years exactly how many people live in the occupied territories. As a result - the wrong distribution of the budget, which entails another financial crisis and a number of other troubles. At the same time there several satellite based products allowing to estimate the population. This study provide validation of satellite based population products delivered by JRC and NASA for the territory of Ukraine. To verify the correctness of the satellite based products, such as Global Human Settlement Layer (GHSL) and NASA population GPWv4 data collection have been compared to official statistics on the number of the largest cities of Ukraine.

关键词： population satellite products GHSL corellation NASA

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Pediatric Vascular Anomalies Recognition with a Swin Transformer Framework 9

Pediatric Vascular Anomalies Recognition with a Swin Transfo...

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9th international conference on Image, Vision and computing, ICIVC 2024

作者： Zhang, Xieyang Zhang, Zhao Chen, Siyu Lang, Xun He, Bingbing Zhang, Yufeng School of Information Science and Engineering Yunnan University Kunming China Department of Dermatology Kunming Children’s Hospital Kunming Children’s Hospital Kunming China Yunnan Key Laboratory of Intelligent Systems and Computing Yunnan University Kunming China

ISBN: (纸本)9798350385991

Vascular anomalies primarily manifest in the head and neck area, impacting roughly one in every 22 children. Early and accurate diagnosis of these anomalies holds the potential to significantly improve physical functioning impairments in children. While computer-aided diagnosis (CAD) system can enhance diagnostic accuracy and address the scarcity of medical resources, existing systems for vascular anomalies identification are limited and mainly focus on binary classification tasks like infantile hemangiomas. Motivated by the above problem, this work develops a classification framework using clinical imaging data from Kunming Children’s Hospital, targeting six common vascular anomalies. Specifically, Swin Transformer was chosen as the backbone network for classification due to its ability to capture long-range dependencies of lesions. In addition, Modified RandAugment was employed to enrich the diversity of lesion data and enhance the robustness of the constructed Swin Transformer. Our experimental results demonstrate that the proposed framework can achieve good overall performance and excel in certain disease recognition tasks. This achievement may promote the development of high-quality CAD systems for diagnosing vascular anomalies in children. © 2024 ieee.

关键词： Pediatrics

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A Hybrid CNN-LSTM Model for Video-Based Teaching Style Evaluation 8

A Hybrid CNN-LSTM Model for Video-Based Teaching Style Evalu...

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8th international conference on Image, Vision and computing, ICIVC 2023

作者： Song, Aohua Bai, Ludi Xiong, Qingyun Guo, Junqi College of Artificial Intelligence Beijing Normal University Engineering Research Center of Intelligent Technology and Educational Application Ministry of Education Beijing China

ISBN: (纸本)9798350335231

intelligent teaching style evaluation has grown in popularity. The video is one of the most accessible resources for evaluation. Yet, there is currently no comprehensive, highly accurate method for processing teaching videos. Thankfully, there are numerous top-notch deep learning-based video categorization methods available as references. A hybrid CNN-LSTM model that is effective at modeling time-series teaching style information is what we propose, drawing on the benefits of video classification research. Our efforts' effectiveness is demonstrated through experiments on a dataset we created for in-class teaching. © 2023 ieee.

关键词： Classification (of information)

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Performance of Indian Cricket Team in Test Cricket: A comprehensive data Science analysis

Performance of Indian Cricket Team in Test Cricket: A compre...

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2022 international conference on Electronic systems and intelligent computing, ICESIC 2022

作者： Tharoor, Vishnusai Viswajith Dhanya, N.M. Amrita School of Engineering Department of Computer Science and Engineering Amrita Vishwa Vidyapeetham Coimbatore India

ISBN: (纸本)9781665483858

Cricket is a sport that is widely hailed in India. It is followed fervently in the country, such that some players are worshiped, and are considered holy. Created by shepherds of England, it has now grown significantly, and equipped some of the most advanced technologies to its armory, which help players improve their performances, and also plan strategies against opposition teams. The proposed work aims at analyzing the performance of the Indian Cricket Team in Test format. All oppositions are considered, and the data is analyzed to extract valuable information, which could help serve as an indicator for future performances. Exploratory data analysis and Visualization was done using python libraries such as pandas, numpy, matplotlib, seaborn. Classification models were implemented for the data based on number of overs, and their results were analyzed. Random Forest Classifier was the most effective among the models implemented, with an accuracy of 75%. © 2022 ieee.

关键词： Machine learning

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