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A SQL automatic generation method based on prompt learning 5

A SQL automatic generation method based on prompt learning

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5th international conference on Telecommunications, Optics, and Computer Science, TOCS 2024

作者： Wang, Ying Zhou, Hongyan Zhang, Cheng Yu, Xuexia State Grid Info & Telecom Group Co. Ltd. Information Industry Research Institute Beijing China Marketing Department of State Grid Hubei Electric Power Co. Ltd. Hubei Wuhan China State Grid Hubei Electric Power Co. Ltd. Hubei Wuhan China Beijing CETC Information Technology Co. Ltd. Beijing China

ISBN: (纸本)9781510691667

the objective of the Structure Query Language (SQL) project is to transform spoken language into SQL commands that can be executed. Typically, creating models that generate SQL requires paired examples of SQL code and natural language queries, and these models are usually limited to specific domains. Traditional approaches struggle with broad applicability. this paper introduces a novel technique for SQL generation, known as TS-PL, which leverages prompt learning to produce functional SQL commands from input queries and data tables. the process begins with the analysis and extraction of essential details from the query;next, an SQL template is crafted and populated to create the SQL code;finally, the generated commands are executed to retrieve data. the study's findings indicate that TS-PL outperforms other methods on the Spider dataset, thereby validating its efficacy. the research underscores the potential of this method to enhance automation in natural language processing and database interactions. this advancement is crucial for easing the burden on database professionals, streamlining data operations, and fostering the evolution of intelligent querying systems. © 2025 SPIE.

关键词： Query languages

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Developing Algorithms for Adaptive Network Coding and Its Impact on Wireless Network Performance 5th

Developing Algorithms for Adaptive Network Coding and Its Im...

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5th international conference on data Science, Machine Learning and Applications, ICDSMLA 2023

作者： Garg, Aanchal Poornima, Selvaraj Savita Nachappa, M.N. Department of Electronic & Communication Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Navgaon Manduwala Dehradun India School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Karnataka Bangalore India

ISBN: (纸本)9789819780426

Adaptive network coding (ANC) is a recent technique used in Wi-Fi networks that utilizes coded transmissions to boost community performance. the concept at the back of ANC is to find the ideal combination of coded packets, considering channel conditions and network topology. By adjusting encoding techniques in response to converting environmental situations, ANC helps to maximize throughput and reduce overhead and latency. this paper proposes a set of rules for ANC that considers the evolution of channel situations to alter its encoding strategy dynamically. the proposed set of rules works by using remarks from previously transmitted packets to determine whether modifications to the current transmission scheme want to be made, which will improve community performance. the algorithm's effectiveness is then tested through simulations wherein the network's overall performance is compared to widespread Wi-Fi structures. Outcomes show that the set of rules can achieve sizable upgrades in network performance… © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Wireless local area networks (WLAN)

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Implementing Cryptographic Algorithms for Securing Online Transactions 5th

Implementing Cryptographic Algorithms for Securing Online Tr...

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5th international conference on data Science, Machine Learning and Applications, ICDSMLA 2023

作者： Bhuvana, J. Bhatt, Rahul Metre, Prakash B. Mishra, Awakash Karnataka Bangalore India Department of Computer Science and Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Navgaon Manduwala Dehradun India School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India

ISBN: (纸本)9789819780426

Cryptographic algorithms are critical in securing online transactions. they provide relaxed verbal exchange channels for fairly touchy statistics that wishes to be reliably transmitted among a couple of remote events. Cryptographic algorithms permit for at ease authentication, confidentiality, non-repudiation, and integrity amongst events for their virtual activities. Implementing those algorithms is a complex procedure, however, due to the ever-changing nature of security threats, acquiring an expertise of the way to properly implement cryptographic algorithms becomes critical. this paper makes a speciality of how to correctly enforce cryptographic algorithms for securing on-line transactions. Precise topics consist of excellent practices for deciding on an appropriate algorithms, fine techniques for key distribution, necessary gadget necessities for cozy on line communications, the process for implementing them, and the importance of securely storing encryption keys. Via expertise the specified procedures and strategies, developers and users might be capable of correctly and securely make on-line transactions. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Encryption algorithms

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Identifying and Analyzing Heavy Truck Stops from GPS data by Grid Processing 8

Identifying and Analyzing Heavy Truck Stops from GPS Data by...

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8th international conference on Electromechanical Control technology and Transportation, ICECTT 2023

作者： Xinwu, Yuan Yang, Yang Yuanyuan, Song Enjian, Yao Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport Beijing Jiaotong University Beijing Haidian District Beijing100044 China Transportation Planning Research Institute Ministry of Transport Beijing Chaoyang District Beijing100028 China

ISBN: (纸本)9781510668331

Truck transportation occupies a dominant position in road transportation, with the increase of freight demand and the number of trucks, the traffic congestion on the road is also become an urgent problem to be solved. Different to the family cars, the trucks in the process of driving the parking need and occupy a larger space, and loading and unloading time is longer, easy to have an impact on the surrounding traffic. therefore, based on GPS track data, this paper adopts the grid processing method to identify the truck stopping points and compare it with its nearby POI data to know the POI information near the truck's stopping points. And then the parking time of the trucks is analyzed and it is found that most of the parking time of the trucks is within 100 minutes. Finally, the DBSCAN density clustering algorithm for truck hotspot area identification model is built for this paper, and the parking hotspots of trucks are analyzed and the results of clustering are derived. It can provide a basis for the road pipeline department to control the traffic in the internal area of the hotspot as well as the surrounding area, reducing congestion and reducing the hidden danger, and improving the efficiency of truck transportation. © 2023 SPIE.

关键词： Trucks

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Utilizing Machine Vision for Steerable Robotic Control 5th

Utilizing Machine Vision for Steerable Robotic Control

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5th international conference on data Science, Machine Learning and Applications, ICDSMLA 2023

作者： Agarwal, Trapty Kavitha, R. Verma, Sunny Sasi, Archana Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Karnataka Bangalore India Department of Electronic & Communication Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Navgaon Manduwala Dehradun India School of Computer Science and Engineering Presidency University Karnataka Bengaluru India

ISBN: (纸本)9789819780426

this paper describes the design and implementation of a steerable robot control device making use of machine imaginative and prescient. the machine consists of a robot car ready with a 3-d digital camera, a show and a manipulate panel. the camera captures 3-d intensity pix of the surroundings and the manage panel lets in the consumer to output instructions that manipulate the motion of the auto. the vision module of the system uses a Convolutional Neural community (CNN) to discover objects inside the environment and small variations in elevation and assign distinct that means to them. this facts is then utilized by the control module to formulate the commands in step with the person’s commands, which then get sent to the car’s pressure device. the system additionally uses an optimization set of rules to help become aware of most beneficial paths thru the environment and avoid limitations. Eventually, the gadget can be used to monitor the automobiles positioning within the surroundings permitting the user to benefit information which include the place, orientation and pace of the automobile. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Digital cameras

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Cost Sensitive Learning using Chest X-Ray with CNN for Covid -19 Detection with Lung Diseases which Lead to Class Imbalance 5

Cost Sensitive Learning using Chest X-Ray with CNN for Covid...

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5th international conference on Image Processing and Capsule Networks, ICIPCN 2024

作者： Annie Grace Vimala, G.S. Legapriyadharshini, N. Dhanalakshmi, R. Kesavan, R. Soundari, A. Gnana Sree Rathna Lakshmi, N.V.S. Saveetha University Saveetha School of Engineering SIMATS Department of ECE Chennai India SaveethaUniversity Saveetha Liberal Arts and Science SIMATS Chennai India Saveetha University Saveetha School of Engineering SIMATS Department of CSE Chennai India Institute of CSE Saveetha School of Engineering SIMATS Chennai India Saveetha School of Engineering SIMATS Department of CSE Chennai India Agni College of Technology Department of ECE Chennai India

ISBN: (纸本)9798350367171

Due to problems with class balance, utilizing a chest X-ray to find Covid-19 has become a very difficult task. this research suggests utilizing Convolutional Neural Networks (CNNs) to resolve the issue with class imbalance and increase the performance of Covid-19 identification. the suggested solution employs a CNN model made especially for the issue and cost-sensitive learning to solve it. In this investigation, chest X-ray pictures of people with Covid-19 and lung illnesses were employed. the dataset was quite uneven, and most of the photos were normal. there were a few COVID-19 and pneumonia images, however. In this research, cost-sensitive learning is used, which contains three distinct ways (i) data resampling, (ii) algorithm changes, and (iii) ensemble methods, to fix the uneven distribution and prevent getting biased classification results. Experimental findings display that the suggested technique outperforms previous state-of-the-art methods, with a greater rate of detecting Covid-19 and superior performance measures including accuracy, recall, and F1-score. With an accuracy of 91.67 % and a sensitivity of 88.89 %, the suggested method shows promise. the feature maps produced by the CNN model to figure out which parts of the chest X-ray pictures help to detect Covid-19. It has been suggested that cost-sensitive learning is an ideal way to deal with the class imbalance issue in Covid-19 detection using medical imaging. In the research report, the suggested method worked well for finding Covid-19 in chest X-rays of people with lung disorders that cause class imbalance. However, further research is required to confirm its generalizability and therapeutic usefulness. © 2024 IEEE.

关键词： Lung cancer

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Artificial Intelligence in Computer Network technology in the big data Era 5

Artificial Intelligence in Computer Network Technology in th...

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5th international conference on Contemporary Computing and Informatics, IC3I 2022

作者： Keer, Priyameet Kaur Al-Safi, Jehan Kadhim Shareef Babu, S B G Tilak Ramesh, G. New Horizon College of Engg. Department of Management Studies. Bangalore India University of Thi-Qar. Department of Digital Media Iraq Aditya Engineering College Dept of ECE Andhra Pradesh Surampalem India St. Martin's Engineering College Telangana Secunderabad India

ISBN: (纸本)9798350398267

While the integration of artificial intelligence and computer technology has enriched people's daily lives, it has also become an inaccessible part of people's lives. the trend of future social development is the advancement of computer network technology, which will be the tendency of future social development. Because of the artificial intelligence technology's high level of intelligence, it has emerged as one of the most promising technologies in the realm of computer networks and is dependent on computers for its development, which led to the establishment of the technology-based development. In order to hasten the incorporation of artificial intelligence into social production and living, as well as to make production and life easier, we need to make some changes. the purpose of this study was to investigate artificial intelligence, after which the model structure of intelligent anti-spam in network security management was established, and finally, the model was evaluated. According to the findings, the intelligent anti-spam model exhibited satisfactory filtering performance. © 2022 IEEE.

关键词： Artificial intelligence

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An IoT-Assisted Real-Time Urban Air Pollution data Collection System 5th

An IoT-Assisted Real-Time Urban Air Pollution Data Collectio...

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5th international conference on Computing and Network Communications, CoCoNet 2023

作者： Ghose, Banani Minsar, Sk. Ghosh, Udayan Arif Mohammad, Sk. Mallick, Adil Hossain Rehena, Zeenat Department of Information Technology Haldia Institute of Technology West Bengal Haldia India Department of Computer Science and Engineering Aliah University West Bengal Kolkata India

ISBN: (纸本)9789819745395

Air pollution is one of the innumerable menaces an individual comes across every moment. Countless means to make urban lives smoother are indebted to witnessing air pollution and other types of pollution. It is contributed by unrestricted urbanization, traffic, industrial emissions, etc., causing life-threatening diseases;even death. Monitoring air pollution should be the primary objective of any society. For an effective air pollution monitoring system to run and deliver a real-time Air Quality Index (AQI) a prompt IoT-enabled air pollution sensor-based data collection system is a prerequisite. In this letter, a real-time hardware-based IoT-enabled air pollution-related data collection module is designed. this will be portable and will be recording both pollutant concentrations and meteorological factors. It consists of a number of sensors and a Wi-Fi module. Collected data will be directly sent to the cloud for further analysis. thus, as a part of the air pollution monitoring system, this module will be capable of recording real-time data, that will lead to real-time air health monitoring. It will assist urban residents and policymakers in taking decisions that will guide them to have healthier lives. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Air quality

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Impact of Bushfire Growth on the Optimal Power Flow of Distributed Generation Systems: Australia Case Study 5

Impact of Bushfire Growth on the Optimal Power Flow of Distr...

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5th international conference on System Reliability and Safety engineering, SRSE 2023

作者： Zielke, Jordan M. Wei, Bo Mo, Huadong University of New South Wales School of Engineering and Information Technology Canberra Australia University of Sydney School of Business Sydney Australia University of New South Wales School of Systems and Computing Canberra Australia

ISBN: (纸本)9798350305944

In recent years, the threat of bushfires in Australia has evolved at an unprecedented rate. With this comes increasing concerns from authorities and operators surrounding the impact of distributed generation systems (DGS) across the country. though studies have been conducted into the impact of bushfires in Australia and the optimal power flow (OPF) of DGS, there is a lack of research integrating these two concepts. therefore, this work will aim to analyse the impact of bushfires on the OPF of the Greater Sydney Region's DGS. Following extensive research into both concepts, a bushfire model and an OPF model have been integrated. the integration model outputs power flow data as the Greater Sydney region's DGS is impacted by the fire. When a transmission line is cut off by fire, the unsupplied power demand must be generated and re-distributed from another bus. Inevitably, a penalty cost will be associated with this which leads to an increase in the total operational cost of the system. the results indicate that the potential penalty cost and associated operational cost increase when a transmission line is cut off by fire. An optimal strategy that aims at protecting vulnerable buses and minimizing these costs was defined. this strategy outlines the requirement to further protect Eraring, Sydney West and Sydney North as these buses are the most critical within the network due to their fuel type and role. this work defines a new strategy to help combat the impact of bushfires on one of Australia's most essential DGS and to balance the trade-off between meeting consumer's demand and minimising operational costs. © 2023 IEEE.

关键词： Electric lines

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Designing Low-Power Industrial Networks with the Internet of things 5th

Designing Low-Power Industrial Networks with the Internet of...

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5th international conference on data Science, Machine Learning and Applications, ICDSMLA 2023

作者： Kannagi, A. Ansari, Tabish Nasurudeen Ahamed, N. Alam, Intekhab Karnataka Bangalore India Department of Civil Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Navgaon Manduwala Dehradun India School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India

ISBN: (纸本)9789819780426

the Internet of things (IoT) revolution is evolving conventional commercial networks to fulfill the demands of present-day technological advancements. Low-electricity business networks are becoming increasingly vital to allow a green communique between linked systems and remote monitoring and management of gadgets. Designing and deploying low-electricity networks for business programs brings many demanding situations, which include energy control, conversation latency, and cease-to-give-up safety. this summary will offer a top-level view of the layout issues while implementing IoT and occasional-power business networks, in addition to the capability of high-quality practices for ensuring low-strength, comfortable, and reliable communications among connected devices. Furthermore, IoT techniques for localizing network accessibility, improving facts accuracy, and boosting community performance may be discussed. Subsequently, some of the trendy trends and trends in the industrial networking area could be highlighted. Low-power business networks are getting increasingly important to allow the green conversation of connected structures and remote tracking of devices. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Capability Management Strength

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