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26th International Symposium on Mathematical Theory of Networks and Systems, MTNS 2024

作者： Veeravalli, Tanya Raginsky, Maxim Department of Electrical and Computer Engineering The Coordinated Science Laboratory University of Illinois UrbanaIL61801 United States

This paper considers the problem of constructing finite-dimensional state space realizations for stochastic processes that can be represented as the outputs of a certain type of a causal system driven by a continuous semimartingale input process. The main assumption is that the output process is infinitely differentiable, where the notion of differentiability comes from the functional Itô calculus introduced by Dupire as a causal (nonanticipative) counterpart to Malliavin's stochastic calculus of variations. The proposed approach builds on the ideas of Hijab, who had considered the case of processes driven by a Brownian motion, and makes contact with the realization theory of deterministic systems based on formal power series and Chen-Fliess functional expansions. Copyright © 2024 The Authors.

关键词： Stochastic systems

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Security Challenges and Solutions in Smart Cities 2nd

Security Challenges and Solutions in Smart Cities

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2nd International Conference on Advances in Computing Research, ACR 2024

作者： Alzyoud, Faisal Al-Falah, Ruba Tarawneh, Monther Tarawneh, Omar Computer Science Department Isra University Amman Jordan Ministry of Local Administration Amman Jordan Software Engineering Department Amman Arab University Amman Jordan

ISBN: (纸本)9783031569494

The increase of smart devices and vast amount of telecommunication growth raise the tendency to convert convolution cities in to emerging smart cities. This paper synthesizes key findings and insights from a comprehensive presentation, addressing critical aspects of smart city security. It underscores the pivotal role of robust security strategies in the development and sustainability of smart urban environments. This paper, encompass three main areas: the integration of Artificial Intelligence (AI) and machine learning for real-time threat detection, the imperative of adopting quantum-safe cryptography, and the evolving nature of security threats in smart cities. These trends and challenges necessitate proactive measures, reinforcing the need for security to be a fundamental component of smart city blueprints. In conclusion, this paper advocates for collaborative efforts and ongoing research in smart city security. It calls upon stakeholders from diverse sectors to join forces, share knowledge, and develop innovative solutions. By doing so, we can navigate the complex security landscape of smart cities and shape a future where technology and security coexist harmoniously, ensuring the well-being and prosperity of urban communities. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Smart city

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Improving Adaptive Runoff Forecasts in Data-Scarce Watersheds Through Personalized Federated Learning 27th

Improving Adaptive Runoff Forecasts in Data-Scarce Watershe...

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27th International Conference on Pattern Recognition, ICPR 2024

作者： Xie, Zaipeng Zhang, Xiangqin Wang, Yunfei Jie, Xuanyao Fang, Wenhao Cai, Yanping Key Laboratory of Water Big Data Technology of Ministry of Water Resources Hohai University Nanjing China College of Computer Science and Software Engineering Hohai University Nanjing China

ISBN: (纸本)9783031781827

Runoff forecasting plays a crucial role in water resource management and flood mitigation, but it often faces significant challenges due to data deficiency and decentralized datasets. Inadequate hydrological data in many watersheds hinders the development of accurate prediction models, while organizational barriers and concerns about data privacy lead to information silos, preventing effective collaborative modeling. To address these issues, we propose FedHydroDSW, a novel personalized federated learning framework for runoff forecasting in data-scarce watersheds. Our approach enables decentralized model training across multiple organizations without requiring direct data sharing, thus preserving data privacy. FedHydroDSW incorporates unique model similarity metrics and parameter adaptation methods, utilizing insights from data-rich areas to refine forecasts in data-scarce regions. Experiments on the CAMELS dataset show that FedHydroDSW significantly outperforms standalone and conventional federated learning methods, with an average 30.1% increase in NSE, and reductions of 28% in RAE and 26.6% in RMSE across multiple data-scarce basins. By enabling secure cross-silo learning, our FedHydroDSW strategy paves the way toward more equitable runoff forecasting globally. The customized training and pattern recognition techniques represent major progress in deploying federated intelligence for impactful hydrological predictions. Our code is publicly available at https://***/xyjie37/FedHydroDSW. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Federated learning

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The Human Behind the Data: Reflections from an Ongoing Co-Design and Deployment of a Data-Navigation Interface for Front-Line Emergency Housing Shelter Staff

The Human Behind the Data: Reflections from an Ongoing Co-De...

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Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems, CHI EA 2023

作者： Masrani, Teale W. He, Helen Ai Messier, Geoffrey Department of Computer Science University of Calgary Calgary Canada Electrical and Software Engineering University of Calgary Calgary Canada

ISBN: (纸本)9781450394222

On any night in Canada, at least 35,000 individuals experience homelessness. These individuals use emergency shelters to transition out of homelessness and into permanent housing. We designed and deployed a technology to support front-line staff at the largest emergency housing shelter in Calgary, Canada. Over a period of five months in 2022, we worked closely with front-line staff to co-design an interface for supporting a holistic understanding of client context and facilitating decision-making. The tool is currently in-use and our collaboration is ongoing. In this paper, we reflect on preliminary findings regarding the second iteration of the tool. We find that supporting shelter staff in understanding the human behind the data was a critical component of design. This work contributes to literature on how data tools may be integrated into homeless shelters in a way that aligns with shelters' values. © 2023 Owner/Author.

关键词： Housing

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MQTT based monitoring and control system for remote stations in automotive industry

MQTT based monitoring and control system for remote stations...

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2023 IEEE Zooming Innovation in Consumer Technologies Conference, ZINC 2023

作者： Ivanovic, Denis Job, Josip Puntaric, Marko Herceg, Marijan TTTech-Auto CX Osijek Croatia Faculty of Electrical Engineering Computer Science and Information Technology Department of Software Engineering Osijek Croatia Faculty of Electrical Engineering Computer Science and Information Technology Department of Communications Osijek Croatia

ISBN: (纸本)9798350347722

In this paper is presented implementation of a lightweight supervisory control and data acquisition system for remote test stations as a part of a larger test house in the automotive industry. It is necessary to allow remote set up and monitoring of the test stations, which means defining the structure of a system with numerous test stations as endpoints. The test stations are meant to be virtual machines but can be both virtual and physical machines. A communication protocol must be used that enables this within the organization's network, regardless of actual distance and location. The parameters of the test stations to be monitored can be defined according to the needs and purpose. Even when creating your own tool, this function is not unique, i.e. on one test station parameters of operating system resources such as memory usage can be monitored, while on another test station logged-in users or running programs, reported system errors and others must be monitored. Data storage is one of the mandatory functions of this system. This process allows viewing data throughout history and more detailed analysis of events. There are numerous benefits that can be drawn and used from the data stored in the database. It is necessary to pay attention to the data stored as well as the scope and retention throughout history. The correct and secure setup of a database is one of the prerequisites for any serious system that processes data. Appropriate views should be created for users involved in the data monitoring process using all the elements mentioned so far. Creating a visually acceptable and easy-To-use interface that serves the main purpose is the final presentation of the entire system to users. A complete system leads to higher productivity, profitability and better organization of the company. It also allows project managers to better plan the use and occupancy of test stations. At any time, they have insight into the status of individual test stations, their activitie

关键词： Automotive industry

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Statistical Analysis of Electromagnetic Coupling to Printed Circuit Boards

Statistical Analysis of Electromagnetic Coupling to Printed ...

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2024 IEEE International Symposium on Electromagnetic Compatibility, Signal and Power Integrity, EMC+SIPI 2024

作者： Xia, Shengxuan Khilkevich, Victor Beetner, Daryl Missouri University of Science and Technology Emc Laboratory Electrical and Computer Engineering Department RollaMO United States

ISBN: (纸本)9798350360394

Determining electromagnetic (EM) coupling to printed circuit boards (PCBs) is essential to finding potential EM susceptibilities early in the design process. For realistic PCB structures, analysis usually relies heavily on time-consuming full-wave simulations because of the complexity of the geometries and the lack of analytical solutions. In this paper, we adopt a segmentation approach based on far-field reciprocity which allows for rapid estimation of the voltage induced at trace terminations over frequency, and which is then used to estimate statistical characteristic of coupling across trace geometries. Frequency-domain results can then be used to estimate time-domain responses with appropriate transformations. Super-position is then used to separate the coupling contributed by different PCB structures, which provides better insight into the mechanisms responsible for susceptibility. © 2024 IEEE.

关键词： Time domain analysis

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Extracting Driving Styles from Automotive Sensor Data to Develop Personas 9

Extracting Driving Styles from Automotive Sensor Data to Dev...

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9th International Conference on computer science and engineering, UBMK 2024

作者： Kaya, M. Cagri Bouraffa, Tayssir Wnuk, Krzysztof Chalmers University of Technology University of Gothenburg Department of Computer Science and Engineering GothenburgSE-41296 Sweden Blekinge Institute of Technology Department of Software Engineering KarlskronaSE-37179 Sweden

ISBN: (纸本)9798350365887

Creating accurate and insightful personas for automotive applications requires understanding the diverse driving styles that emerge from sensor data. This paper introduces initial results of our methodology for developing personas based on the analysis of automotive sensor data, which captures various driving behaviors. We present a comprehensive process that begins with the extraction of driving events from sensor data, followed by the identification of distinct driving styles through K-Means clustering. Our approach is innovative in its use of dynamic, real-world driving data as opposed to static or direct user interaction data commonly employed in persona development. This allows for a deeper understanding of driver behaviors, which are indirectly inferred from sensor data, thus providing a foundation for creating detailed personas. © 2024 IEEE.

关键词： Automotive sensor data clustering driving styles event detection persona development

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A novel deep learning approach for investigating liquid fuel injection in combustion system

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Discover Artificial Intelligence 2025年第1期5卷 1-14页

作者： Inam, Syed Azeem Khan, Abdullah Ayub Ahmed, Noor Mazhar, Tehseen Shahzad, Tariq Khan, Sunawar Saeed, Mamoon M. Hamam, Habib Department of Artificial Intelligence and Mathematical Science Sindh Madressatul Islam University Sindh Karachi Pakistan Department of Computer Science and Information Technology Shaheed Benazir Bhutto University Lyari Karachi Pakistan Department of Computer Science Shaheed Zulfiqar Ali Bhutto Institute of Science and Technology Karachi Pakistan Department of Computer Science School Education Department Government of Punjab Layyah31200 Pakistan School of Computer Science National College of Business Administration and Economics Lahore54000 Pakistan Department of Computer Engineering COMSATS University Islamabad Sahiwal Campus Sahiwal57000 Pakistan Department of Software Engineering Islamia University of Bahawalpur Bahawalnagar62300 Pakistan Sana’a00967 Yemen Faculty of Engineering Uni de Moncton MonctonNBE1A3E9 Canada Department of Electrical and Electronic Engineering Sciences University of Johannesburg Johannesburg South Africa Av. Grandes Ecoles BP 1989 Libreville Gabon Bridges for Academic Excellence Spectrum Center-ville Tunis Tunisia

The intricacies and instability of introducing cryogenic propellants into the combustion system have piqued the curiosity of scientists studying the procedure. The latest innovation is utilizing data-driven machine learning and deep learning approaches to gain deeper insights into the related difficulties. However, the current work serves as a baseline for future research because relatively few studies have used data-driven methodologies to assess the temperature of liquid fuel injections in combustion systems. The performance of Linear Regression (LR), Random Forest (RF), Extra Trees Regressor (ETR), Polynomial Regression (PR), Support Vector Regressor (SVR), Decision Tree Regressor (DTR), Gradient Boost Regressor (GBR), XGB Regressor (XGBoost), AdaBoost Regressor (ABR), K-Neighbors Regressor (KNR), Long-Short Term Memory (LSTM), Bi-LSTM (Bi-directional Long-Short Term Memory) has all been investigated in this study. The study also suggested a Fully Connected Neural Network (FCNN) to examine its performance and paired it with an Extra Tree Regressor (ETR). The coupled FCNN and Extra Tree Regressor outperform the other algorithms with a Mean Square Error (MSE) of 0.0000005062, Root Mean Square Error (RMSE) of 0.00071148, Mean Absolute Error (MAE) of 0.00020672, and R-squared (R2) value of 0.99998689. Linear Regression, Polynomial Regression, and Support Vector Regressor are found to be the least-performing algorithms. The current work uses machine learning and deep learning methods to make data-driven decisions for liquid fuel injection in the combustion system. © The Author(s) 2025.

关键词： Deep learning

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Enhancing engineering Education Through LLM-Driven Adaptive Quiz Generation: A RAG-Based Approach 54

Enhancing Engineering Education Through LLM-Driven Adaptive ...

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54th IEEE Frontiers in Education Conference, FIE 2024

作者： Gopi, Sreekanth Sreekanth, Devananda Dehbozorgi, Nasrin Kennesaw State University Department of Computer Science KennesawGA United States Kennesaw State University Department of Software Engineering KennesawGA United States

ISBN: (纸本)9798350351507

This research-to-practice study aims to develop an Artificial Intelligence (AI) MCQ generation system for engineering students, with a focus on adaptive learning, educational technology, and innovative assessment tools, to enhance personalized learning. engineering education faces significant academic performance challenges, with first-year retention rates in STEM fields ranging between 27% to 46%, largely due to poor academic achievements. Multiple Choice Questions (MCQs) identify misconceptions, reinforce knowledge retention, and offer efficient assessment methods for engineering education. This interactive method improves attention and memory retention, reinforces knowledge, and improves comprehension. In this context, the emergence of Large Language Models (LLMs) such as GPT-4 has marked a significant advancement. Our literature review method employed a systematic approach, analyzing peer-reviewed articles, conference papers, and authoritative reports to uncover the trends and challenges in AI-driven quiz generation. The notable gap identified in our literature review is the lack of LLM-based adaptive quiz generation methods specifically for engineering education. Our methodology involved sourcing relevant structured datasets, data pre-processing, embedding generation, vector database storage, hybrid-search retrieval, LLM query results feed, prompt engineering, and context-based response. In this research, we adopted Vectara as a vector database tool for its automatic data ingestion capabilities and seamless integration with generative AI applications. Prompt engineering involves a dual-prompt approach, where the Contextual Question Prompt formulates questions based on user topics and chat history, while the Answer Question Prompt manages MCQ responses with explanations, ensuring relevant and contextually accurate interactions. Evaluation includes topic relevancy, answer relevancy, and a contextual relevancy score. Preliminary results indicate promising results

关键词： engineering education

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Implementation of an Effective Framework in Merging Cybersecurity and software engineering 6

Implementation of an Effective Framework in Merging Cybersec...

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6th International Conference of Women in Data science at Prince Sultan University, WiDS-PSU 2023

作者： Alhuqail, Sara Khalid Jamail, Nor Shahida Mohd Prince Sultan University College of Computer Science and Information Sciences Department of Software Engineering Riyadh Saudi Arabia

ISBN: (纸本)9781665477239

Cyberattacks have increased. Security throughout software development reduces the program's attack surface. Despite several fixes. new research indicates software security weaknesses and hackers are rising. SSD security methods must be studied. 28 academic and government SSD approaches are examined in this study. Security is implemented throughout SDLC. We studied organizational. behavioral. legal. policy. and governance issues as well as SSD approaches. Method effectiveness strategies were investigated. We conclude with scientific problems. Our survey should help academics an institutions understand software security development (SSD). Nontechnical software security experts may benefit from our bridge. Our literature gaps may improve software security. Today's fast-paced. modern world requires software security for product success. CIA-classified data. software. and services (Confidentiality. Integrity. and Availability). © 2023 IEEE.

关键词： Life cycle

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