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arXiv 2024年

作者： Musumeci, Emanuele Brienza, Michele Suriani, Vincenzo Nardi, Daniele Bloisi, Domenico Daniele Dept. of Computer Control and Management Engineering Sapienza University of Rome Rome Italy UNINT Univeristy Via Cristoforo Colombo 200 Rome00147 Italy

In the last years' digitalization process, the creation and management of documents in various domains, particularly in Public Administration (PA), have become increasingly complex and diverse. This complexity arises from the need to handle a wide range of document types, often characterized by semi-structured forms. Semi-structured documents present a fixed set of data without a fixed format. As a consequence, a template-based solution cannot be used, as understanding a document requires the extraction of the data structure. The recent introduction of Large Language Models (LLMs) has enabled the creation of customized text output satisfying user requests. In this work, we propose a novel approach that combines the LLMs with prompt engineering and multi-agent systems for generating new documents compliant with a desired *** main contribution of this work concerns replacing the commonly used manual prompting with a task description generated by semantic retrieval from an LLM. The potential of this approach is demonstrated through a series of experiments and case studies, showcasing its effectiveness in real-world PA scenarios. © 2024, CC BY.

关键词： Multi agent systems

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Reference Tracking for Constrained Uncertain Linear Systems by Stochastic MPC

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IFAC-PapersOnLine 2023年第2期56卷 10421-10427页

作者： Jannik Hahn Olaf Stursberg Control and System Theory Dept. of Electrical Engineering and Computer Science University of Kassel 34121 Kassel Germany

This paper addresses model predictive control of a class of linear systems subject to additive stochastic disturbances and constraints. The underlying stochastic optimal control problem combines inverse cumulative distribution functions with ellipsoid-in-polyhedron formulations to reduce the conservatism induced by constraint satisfaction. By use of terminal constraints and time-varying weights within the cost functional, the presented control scheme satisfies criteria for mean-square stability and can be adapted to reference-tracking problems for arbitrary reference signals.

关键词： Probabilistic Constraints Mean-Square Stability Predictive control Stochastic control Uncertain Systems

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Robotics Process Automation Technologies for Data Collection and Analysis

Robotics Process Automation Technologies for Data Collection...

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International Conference on Computing and Networking Technology (ICCNT)

作者： K Usman Tm Hayath Mohammed Shafiulla Dadapeer Dept. of Computer Science and Engineering Ballari Institute of Technology and Management Ballari Karnataka India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

Data collection and analysis are critical aspects of various business processes. However, these tasks can be time-consuming, prone to errors, and delays employee productivity when done manually, especially when we have to deal with huge data. Robotic Process Automation (RPA) technologies offer a promising solution in form of a BOT, by automating tedious tasks related with data handling. A survey by The Economist corporation believe that automation kick launches digital transformation, robotic process automation (RPA) has evolved from an emerging technology to a must-have digital transformation tool for enterprises to compete globally. An increasing number of companies are now using RPA to automate normal business processes in a non-intrusive and cost-effective way. On the other hand, decision-making, pattern recognition, and many other business-related tasks benefit greatly from the use of big data and analytics. This paper explores the application of RPA in data collection and analysis, examining its functionalities, benefits, and limitations. In practical, Bot produces error-free work and takes 94.44% less time for data collection compared to a manual process, which encourages all firms to adopt to RPA technologies.

关键词： Intelligent automation Surveys Productivity Digital transformation Decision making Manuals Chatbots Pattern recognition Delays Business

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Software Effort Estimation using ANN (Back Propagation)

Software Effort Estimation using ANN (Back Propagation)

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International Conference on Computing Methodologies and Communication (ICCMC)

作者： Ravi Kumar B N Yeresime Suresh Dept. of Computer Science and Engineering BMS Institute of Technology and Management Bangalore India Dept. of Computer Science and Engineering Ballari Institute of Technology and Management Ballari India

Project managers often use Effort Estimating strategies to manage the human resources of current or upcoming software projects. Prior to project implementation, cost, time, and personnel estimation are basically necessary. For every project of software, getting an accuracy in Effort Estimation has always been difficult. In case of this study, estimating the labor involved in developing software determined using a Back Propagation Model. This model's goal is to investigate the capabilities and potential uses of utilizing Artificial Neural Networks (ANN) as a tool for forecasting the effort required for software development. In order to estimate the software work, we are attempting to implement a machine learning technique in this research. Out of all machine learning methods, we are applying an algorithm based on Artificial Neural Networks that is Back propagation. The Desharnais dataset, a well-known publicly available dataset for estimation of software effort, is used to test the approach. The performance and accuracy of the tested model have been evaluated using three metrics: MMRE, MRE, and Pred (0.25). In the sections below that follows, I explain the algorithm and its results.

关键词： Backpropagation Computational modeling Software algorithms Estimation Artificial neural networks Machine learning Predictive models

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Tuning the Feedback controller Gains is a Simple Way to Improve Autonomous Driving Performance

Tuning the Feedback Controller Gains is a Simple Way to Impr...

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UKACC International Conference on control (control)

作者： Wenyu Liang Pablo R. Baldivieso Ross Drummond Donghwan Shin Dept. of Automatic Control and Systems Engineering University of Sheffield Sheffield UK Dept. of Computer Science University of Sheffield Sheffield UK

ISBN: (数字)9798350374261

ISBN: (纸本)9798350374278

Typical autonomous driving systems are a combination of machine learning algorithms (often involving neural networks) and classical feedback controllers. Whilst significant progress has been made in recent years on the neural network side of these systems, only limited progress has been made on the feedback controller side. Often, the feedback control gains are simply passed from paper to paper with little re-tuning taking place, even though the changes to the neural networks can alter the vehicle's closed loop dynamics. The aim of this paper is to highlight the limitations of this approach; it is shown that re-tuning the feedback controller can be a simple way to improve autonomous driving performance. To demonstrate this, the PID gains of the longitudinal controller in the TCP autonomous vehicle algorithm are tuned. This causes the driving score in CARLA to increase from 73.21 to 77.38, with the results averaged over 16 driving scenarios. Moreover, it was observed that the performance benefits were most apparent during challenging driving scenarios, such as during rain or night time, as the tuned controller led to a more assertive driving style. These results demonstrate the value of developing both the neural network and feedback control policies of autonomous driving systems simultaneously, as this can be a simple and methodical way to improve autonomous driving system performance and robustness.

关键词： Machine learning algorithms Neural networks control systems Robustness Feedback control control theory Adaptive control

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Next Generation HR: Transforming Talent management with AI and ML Innovations 2

Next Generation HR: Transforming Talent Management with AI a...

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2nd International Conference on Disruptive Technologies, ICDT 2024

作者： Singh, Niharika Singh, Pooja Chakraborty, Sudeshna Gl Bajaj Institute of Technology & Management Dept. of Master of Computer Application U.P. Greater Noida India School of Computing Science & Engineering Galgotias University Department of Cse Greater Noida India School of Computing Science and Engineering Galgotias University Department of Computer Application Greater Noida India

ISBN: (纸本)9798350371055

Artificial intelligence (AI)-based technology is now accepted as standard. Today, everything is driven by AI, which has changed our way of life. The widespread deployment of AI is helping businesses and companies by streamlining processes, increasing production, increasing effectiveness while cutting expenditures. The way businesses choose, manage, and engage their personnel is evolving as a result of the integration of artificial intelligence (AI) into HRM operations. simulated intelligence (AI) is allowing robots to make judgements that are more accurate than those made by people based on current data sets and behavioral patterns. As a result of this change, machines have taken the place of all manual labor. professionals now play more strategic roles. It is critical for businesses and professionals to comprehend how this technology operates and how it contributes to a variety of HRM activities. In order to determine how AI is bringing about change in the field a study of human resource management evaluates the work of numerous notable scholars. This review outlines the main advantages and unspoken difficulties of The use of AI in HRM and its potential in the future. This essay provides an in-dept. analysis. of the utilization of AI and ML techniques in HRM, highlighting their impacts on recruitment, employee performance management, training, and overall organizational success. © 2024 IEEE.

关键词： Artificial intelligence human resource management machine learning Natural Language Processing

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Handling Rollbacks with Separated Response control Service for Microservice Architecture 3

Handling Rollbacks with Separated Response Control Service f...

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3rd International Informatics and Software engineering Conference, IISEC 2022

作者： Gordesli, Mustafa Nasab, Ahad Varol, Asaf Maltepe University College of Engineering and Natural Sciences Department of Computer Engineering Istanbul Turkey The University of Chattanooga College of Engineering and Computer Science Dept. of Engineering Management and Technology ChattanoogaTN United States

ISBN: (数字)9781665459952

ISBN: (纸本)9781665459952

Working with large scale microservice based applications may be hard to maintain and control. The services in those applications must be isolated from each other and they must work in harmony. There must be an intelligent transaction management system to implement this kind of collaborative work of microservices. There are two main methodologies for transaction management, namely Two Phase Commit (2PC) and Saga pattern. There are two phases in 2PC that prepare phase and commit phase. In Saga pattern, there are two ways of implementing Saga pattern;choreography based, and orchestration based. When there is a problem in the whole transaction, controlling the rollback scenario may be hard because each microservice has its own rollout and rollback solutions in both ways of Saga pattern. If we separate the rollback system from the microservices, we might have simpler microservices and microservices that can run in parallel. So whole system works safer and faster. In this work we focus on parallel execution of microservices with separate rollback system that controls the whole application in error condition. © 2022 IEEE.

关键词： Federated learning Microservice architectures computer architecture control systems Informatics Software engineering

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Intelligent Parking System to Prevent Unauthorized Parking of Vehicles Using IoT and R-CNN with YOLO

Intelligent Parking System to Prevent Unauthorized Parking o...

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Intelligent Data Communication Technologies and Internet of Things (IDCIoT), International Conference on

作者： Sushma Vispute Manasi Potdar Pranjal Pawara Shreya Patil Satvika Patil Dinesh Bhaskar Ahirrao Dept. of Computer Engineering Pimpri Chinchwad College Of Engineering Pune India KCES's College Of Engineering and Management Jalgaon India

ISBN: (数字)9798331527549

ISBN: (纸本)9798331527556

In recent years., the proliferation of private vehicles has led to a significant challenge in finding adequate parking space., with unauthorized parking becoming a prevalent issue in many residential societies. To address this problem., we propose a novel solution that integrates machine learning techniques and motion detection technology to effectively manage parking spaces and curb unauthorized parking. Our approach utilizes advanced machine learning models such as RCNN for object detection and YOLOv8 for license plate detection., complemented by optical character recognition (OCR) for character recognition. Additionally., the ESP32-CAM webcam module is employed to capture real-time images., ensuring seamless integration with our system. This combination of technologies allows for the accurate detection of unauthorized parking instances in real time., providing efficient management of parking spaces within societies. Key features of the system include automated vehicle identification., real-time monitoring., and notification alerts., all of which contribute to a robust verification system for resident and guest vehicles. By leveraging these advanced technologies., our solution not only streamlines the parking process but also promotes a more organized and peaceful living environment. This innovative approach addresses a critical issue in urban settings., paving the way for more efficient and sustainable parking management practices.

关键词： YOLO Space vehicles Accuracy Webcams Machine learning Real-time systems Internet of Things Character recognition Reliability License plate recognition

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VIEGO: Malware Generating Tool 4

VIEGO: Malware Generating Tool

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4th International Conference on Advances in Computing, Communication control and Networking, ICAC3N 2022

作者： Sohan, Simha Vandhana, S. Roopashree, S. Dept. CSE-Cybersecurity Bengaluru India Rv Institute of Technology and Management Department of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9781665474368

Android has dominated the smartphone market and has become the most popular operating system for mobile devices. The architecture of android is mainly client-server based. Modern smartphone operating systems have sophisticated security features. A device that has been installed by default can only access the files in its own sandbox directories, and user privileges prevent system-wide file modification. However errors from the server side causes 60% vulnerabilities in the client side. some of the vulnerabilities are poor jailbreak, root detection ,insufficient transport layer protection, weak authentication/authorization , cryptography improper certificate validation, information leakage application cache and so on. Thus targeting the android smart phones will be more easier and will provide us a lot of critical information. One of the methods is by using the android malwares. This article focuses on generating fully undetectable malwares with unique signatures to perform attacks and gather information. © 2022 IEEE.

关键词： Smartphones

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Design of a DC/DC Converter with a PID controller and Backpropagation Neural Network for Electric Vehicles 20

Design of a DC/DC Converter with a PID Controller and Backpr...

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20th International Learning and Technology Conference, L and T 2023

作者： Hussein, Aziza I. Shigdar, Basmah Almatrafi, Lina Alaidroos, Batool Alsharif, Futoon Aly, Rabab Hamed M. Effat University Dept. of Electrical & Computer Engineering Jeddah Saudi Arabia Omas Zahid Group Jeddah Saudi Arabia The Higher Institute for Management and Information Technology Minya Egypt

ISBN: (纸本)9798350300307

Currently, global warming has become a major problem. The pollution caused because of conventional internal combustion engines are increasing dramatically. Electric Vehicles are good alternatives to conventional IC engine vehicles in promoting a green environment. controllers, converters, and modulation schemes are needed to provide a safe and reliable power transmission from energy storage systems to the electric motor in electric cars. In this paper, a design of DC/DC boost converter based on a PID controller is proposed. Moreover, a Back Propagation Neural Network (BPNN) technique is applied to generate the optimal PID parameters before using the PID. The proposed DC/DC boost converter is simulated using MATLAB software. The simulation results proved that the proposed DC/DC converter with PID-BPNN achieved higher performance and a stable output voltage. © 2023 IEEE.

关键词： DC-DC converters

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