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American Control Conference (ACC)

作者： Nachiket U. Bapat Randy C. Paffenroth Raghvendra V. Cowlagi Worcester Polytechnic Institute Worcester MA USA Aerospace Engineering Mathematical Sciences and Data Science.

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

Real-world data of the operation of control systems is often scarce because experiments are expensive and time-consuming. We address the problem of synthetic data generation, namely, the problem of generating data about the operation of a physical system through computational means. In this paper, we report generative adversarial network (GAN) models that can incorporate training data and governing equations underlying the operation of a control system. Instead of over-generalization, we restrict the discussion to the particular example, namely, the Zermelo navigation problem of a vehicle navigating a drift field (e.g., wind) in minimum time. Owing to the nature of the example chosen, we find algebraic governing equations. We propose GAN models that learn to generate trajectories that not only resemble the training data but also satisfy these governing equations. We compare the proposed models to a standard GAN model that uses training data, only, i.e., neglects the governing equations, to demonstrate that the proposed models outperform the standard model on several metrics. To the best of our knowledge, this is the first work on generative models for control systems.

关键词： Measurement Navigation Training data Generative adversarial networks Control systems Mathematical models data models

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Implementing A Middleware API for Facilitating Heterogeneous IoT Device Communication Protocols and data Retrieval

arXiv

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arXiv 2023年

作者： Krikorian, Sasoun Skarnes, Benjamin Vadlamudi, Sai Varun Computer Science Worcester Polytechnic Institute Worcester United States

Currently, there are over 14 billion IoT devices [7], and with many devices come many protocols, the main ones being MQTT and CoAP. We are interested in connecting the many diverse IoT devices to the cloud. To do so, we use the middleware architecture proposed by article [8] in which a device, called the middleware, acts as the middleman between the various IoT networks and the cloud. Since IoT devices typically operate in real-time, performance is of great concern. Therefore, we conducted a simulation to measure the data latency of using middleware and the overall fairness between different IoT networks. Our simulation had an MQTT and a CoAP network interacting with the middleware. The simulation results showed that CoAP always had a lower travel time than MQTT, mainly because CoAP is a more lightweight protocol. However, we also found that MQTT had slightly more throughput, which was unexpected since we initially thought that CoAP would have had higher throughput. We have shown that analyzing data via a middleware device is possible and that there are potential directions to explore, such as evaluating different Quality of Service Algorithms in the context of having a middleware device. © 2023, CC BY.

关键词： Middleware

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OblivTime: Oblivious and Efficient Interval Skyline Query Processing Over Encrypted Time-Series data

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IEEE Transactions on Services Computing 2025年第3期18卷 1602-1617页

作者： Ouyang, Huajie Zheng, Yifeng Wang, Songlei Hua, Zhongyun Harbin Institute of Technology School of Computer Science and Technology Guangdong Shenzhen518055 China The Hong Kong Polytechnic University Department of Electrical and Electronic Engineering Hong Kong Shenzhen University National Engineering Laboratory for Big Data System Computing Technology Shenzhen518055 China

Time-series data is prevalent in many applications like smart homes, smart grids, and healthcare. And it is now increasingly common to store and query time-series data in the cloud. Despite the benefits, data privacy concerns in such outsourced services are pressing, making it imperative to embed privacy assurance mechanisms from the outset. Most existing related works have been focused on querying for different types of aggregate statistics. In this article, we instead focus on the secure support for advanced interval skyline queries, which allow to identify time series that are not dominated by any other time series within a query time interval. This is valuable for time-series data analytics in applications like remote health monitoring (e.g., identifying patients with high heart rates in a certain week). We present OblivTime, a new system framework for oblivious and efficient interval skyline query processing over encrypted time-series data. OblivTime is built from a synergy of time-series data analytics, lightweight cryptography, and GPU parallel computing, achieving stronger security guarantees and lower online query latency over the state-of-the-art prior work. Extensive experiments demonstrate that OblivTime can achieve up to 666 x speedup in online query latency over the state-of-the-art prior work. © 2008-2012 IEEE.

关键词： Structured Query Language

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An Intrusion Detection Scheme Based on Sequential Tri-Way Decisions of Multiple Granularity for Intelligent Connected Vehicles

An Intrusion Detection Scheme Based on Sequential Tri-Way De...

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International Conference on Artificial Intelligence and Autonomous Transportation, AIAT 2024

作者： Li, Yongzhong Wang, Qi Li, Yuheng Zhang, Shipeng School of Automotive Engineering Nantong Institute of Technology Nantong226010 China Internet of Things and Big Data Major of Macao Polytechnic University Macao China School of Computer Science Jiangsu University of Science and Technology Zhenjiang212003 China

ISBN: (纸本)9789819639762

With the rapid developing technology of the Internet of Things, intelligent connected vehicles are facing more and more serious cybersecurity threats and challenges. With the developing of cybersecurity technology for intelligent connected vehicles it has posed a comprehensive challenge to the existing cybersecurity technologies. Intrusion detection is an important research field of cybersecurity. An intrusion detection scheme based on sequential tri-way decisions of multiple granularities (S3WD-MG) is proposed for Intelligent Connected Vehicles. The S3WD-MG method obtains feature sets of multi-granularities through the auto-encoder of deep learning. This method combines multiple granularities and sequential tri-way decisions to make decisions by the most appropriate for network behavior through by the decision threshold. The experiment results on NSL-KDD show that S3WD-MG method does have a good performance in intrusion detection. Compared with other models, our proposed S3WD-MG method has a higher detection’s rate and the robustness of algorithm is stronger. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Network intrusion

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Lighting the Smart Way: A Technological Odyssey in Urban Street Illumination 10

Lighting the Smart Way: A Technological Odyssey in Urban Str...

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10th International Conference on Advanced Computing and Communication Systems, ICACCS 2024

作者： Vinu, M.S. Priya, P Kanaga Thilakaveni, P. Hermina, J. M. Ashforn Prashanthini, K. Misba, M. Nehru Institute of Engineering and Technology Department of Computer Science and Engineering Coimbatore India Kpr Institute of Engineering and Technology Department of Computer Science and Engineering Coimbatore India Psg Polytechnic College Department of Computer Engineering Coimbatore India Bannari Amman Institute of Technology Department of Artificial Intelligence and Data Science Erode India Sri Ramakrishna Engineering College Department of Robotics and Automation Coimbatore India Bethlahem Institute of Engineering Department of Computer Science and Engineering Nagercoil Karungal India

ISBN: (纸本)9798350384369

The development of intelligent street light systems has ushered in a new era of efficiency and sustainability in urban infrastructure. The proposed work studies the integration of modern sensors and Internet of Things (IoT) technologies to increase the functionality of street lights. The major components include Light Dependent Resistors (LDR) for automatic light management, an MQ135 sensor for air quality monitoring, and a fog detection system employing a laser module and LDR. These sensors are integrated with the ESP8266, providing cloud integration for real-time data visualization and monitoring. Additionally, solar panels are employed to enhance energy efficiency. The proposed methodology digs into the precise implementation, data analysis, and the potential of this system to alter urban lighting infrastructure © 2024 IEEE.

关键词： Air quality

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Lessons on mobile apps for COVID-19 from China

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Journal of Safety science and Resilience 2021年第2期2卷 40-49页

作者： Sophia L.Zhou Xianhan Jia Samuel P.Skinner William Yang Isabelle Claude Mass Academy of Math and Science Worcester Polytechnic Institute85 Prescott StreetWorcesterMA 01605United States Department of Computer Science Worcester Polytechnic Institute100 Institute RoadWorcesterMA 01609United States Department of Physics Worcester Polythenic Institute100 Institute RoadWorcesterMA 01609United States Department of Biomedical Engineering Worcester Polytechnic Institute100 Institute RoadWorcesterMA 10609United States

The COVID-19 pandemic has impacted the global society and human life *** countries have launched COVID-19 mobile apps with a wide range in how these apps *** it is hoped that these apps can assist in the fight against COVID-19,many are worried about user *** implemented“health code”systems,which assigned neighborhoods and citizens a specific health code,meant to indicate their risk of having been exposed to *** most widely used health code systems were hosted on the popular apps WeChat and Alipay,each with billions of *** experts argued that China’s use of mobile applications was essential to its successful combat against *** in this study are a summary of mobile technology usage in China,a review of previous studies of mobile technology in healthcare,and a brief survey of some existing mobile applications for COVID-19 that were *** included are outcomes of interviews with healthcare and public safety experts and a public survey to understand how mobile applications were used in China’s response to *** interviews revealed four important themes:personal privacy,community involvement,government involvement,and situational *** was found that a key concern was maintaining a balance between collecting and utilizing personal information,as well as protecting this *** addition,close collaboration between local communities and the national government was *** applications assisted in communication and coordination but did not replace the work of people such as delivery drivers and contact *** results also showed that there was room for improvement,especially accessibility for the elderly or those unfamiliar with *** results were obtained from our *** was interesting to find that the apps were mostly used for“accessing information on COVID-19.”In addition,respondents overwhelmingly identified“information”as the most valuable featur

关键词： Mobile apps COVID-19 response Survey Interview Lessons

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Marine Life Analysis Based on Ocean Water Level Rise and Climate Change Using Underwater Imaging Techniques

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Remote Sensing in Earth Systems sciences 2024年第4期7卷 657-669页

作者： Mate, Anuja Dinesh Arulananth, T.S. Sathiya, T. Jyothi, B. Swarna Raja, A. Wasim Yalawar, Mrutyunjaya S. Computer Technology Sou.Venutai Chavan Polytechnic Pune India Department of Electronics and Communication Engineering MLR Institute of Technology Telangana Hyderabad 500043 India Department of Computer Science and Engineering Sona College of Technology Tamil Nadu Salem India Computer Science & amp Engineering Madanapalle Institute of Technology & amp Science Andhra Pradesh Madanapalle India Artificial Intelligence and Data Science Sri Krishna College of Engineering and Technology Coimbatore India Department of Computer Science and Engineering CMR Engineering College Hyderabad India

Forecasting sea levels is crucial for harbour operations and coastal structure design. The oceans make up two-thirds of Earth’s surface;therefore, historically, the marine economy has been extremely diversified as well as abundant. In order to explore as well as harness this difficult environment, prominent businesses and ecological groups are developing and deploying novel gadgets backed by state-of-the-art marine mechatronics solutions. This research proposes a novel method of marine life monitoring with ocean water level rise analysis based on climate changes by underwater imaging using machine learning techniques. Here, the input has been collected as underwater images as well as processed for noise removal and normalisation. Then, these images were segmented for monitoring marine life using U-Net graph cut fuzzy clustering with a spatial neural network. Then this segmented image has been classified using multilayer region-based Q-belief vector neural networks for the analysis of sea level rise analysis based on climate change training. Experimental analysis has been carried out for various marine life monitoring datasets and climate change datasets in terms of training accuracy, specificity, recall, AUC, and Kappa-coefficient. Proposed techniques achieved specificity 93%, training accuracy 91%, AUC 95%, recall 96%, and Kappa-coefficient 90%. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Climate changes Machine learning techniques Marine life monitoring Q-belief vector Water level rise analysis

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Design and Assessment of Representative Hybrid Clinical Trials using Health Recommender System 6

Design and Assessment of Representative Hybrid Clinical Tria...

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6th International Workshop on Health Recommender Systems, HealthRecSys 2024

作者： Neehal, Nafis Anand, Vibha Bennett, Kristin P. Department of Computer Science Rensselaer Polytechnic Institute TroyNY12180 United States Biomedical AI-Healthcare and Life Sciences IBM T.J. Watson Research Center CambridgeMA02141 United States Institute of Data Exploration and Applications Mathematical Sciences and Computer Science Departments Rensselaer Polytechnic Institute TroyNY12180 United States

Incorporating real-world data (RWD) into clinical trials can enhance trial efficiency, diversity, and generalizability. This paper introduces the Framework for Research in Synthetic Control Arms (FRESCA), which uses a novel Recommender System combined with Equity Adjustment strategies to design and evaluate Representative Hybrid Clinical Trials (HCTs). FRESCA employs a novel matching algorithm through its recommendation system to select suitable patients from RWD while ensuring that the selected population is representative of the target demographic. This dual approach improves both patient selection and trial outcomes by balancing statistical appropriateness and equity. Simulations based on data from two existing randomized clinical trials (RCTs) show that using FRESCA to recommend patients from RWD and apply equity adjustments enhances internal validity and generalizability. Our analysis indicates that combining matching and equity adjustments yields more accurate treatment effect estimates and fair population representation, even with reduced RCT control group sizes. In contrast, using either method alone may result in biased outcomes. The flexibility of FRESCA to simulate various HCT scenarios makes it a valuable tool for advancing equitable and efficient clinical trial designs. © 2024 Copyright for this paper by its authors.

关键词： Clinical research

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Interpretability of time series forecasting models 26

Interpretability of time series forecasting models

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26th ISSAT International Conference on Reliability and Quality in Design, RQD 2021

作者： Aishwarya, Ramakrishnan Akshay, Sadanandan Erika, Dsouza Lyzanne Somesh, Patel Worcester Polytechnic Institute Master of Science in Data Science WorcesterMA United States

ISBN: (纸本)9780991057696

Interpretability is the degree to which a human can understand the cause of a decision. The higher the interpretability of a machine learning model, the easier it is for someone to comprehend why certain decisions or predictions have been made. The problem statement of this paper focuses on interpreting several time series models and explaining the predictions produced by the system. The four aspects based on Prediction Based Interpretability that our project aims at solving are as follows: 1) Feature Impact 2) Feature Effect 3) Prediction Explanation 4) WhatIF Explainer. In this project, we followed a model agnostic approach to implement the interpretability for time series models. These time series models include several flavors of ARIMA and a few neural net models. We also created a custom explainer in Python for the FB Prophet time series algorithm and a respective translator for it in the R language. This project can help benefit the AI (Artificial Intelligence) and ML (Machine Learning) industry by developing an approach to interpret time series models and identify bias in their forecasts. The approaches described in this paper implements interpretability on six forecasting algorithms, thereby helping in demystifying the black box nature of these models. © 2021 Proceedings - 26th ISSAT International Conference on Reliability and Quality in Design, RQD 2021. All rights reserved.

关键词： Python

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The Collaborative Sensemaking Play of Jubensha Games: A Deconstruction, Taxonomy, and Analysis

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Games: Research and Practice 2025年第1期3卷 1-34页

作者： Shano Liang Max Chen Phoebe O. Toups Dugas Gillian Smith Rose Bohrer Interactive Media and Game Development Worcester Polytechnic Institute Worcester United States Human-Centred Computing / Faculty of Information Technology / Exertion Games Lab Monash University Melbourne Australia Computer Science Worcester Polytechnic Institute Worcester United States

Jubensha games, popular in China, combine storytelling, social deduction, and script-centered group play, sparking widespread interest among gamers and researchers worldwide. However, enthusiasts and researchers have struggled to accurately describe Jubensha, often defaulting to comparisons with genres like murder mystery and live-action role-playing games. This reliance on comparisons hinders efforts to generalize Jubensha or to deconstruct and adapt its unique design components, dynamics of player interaction, and playing experience into other games. This research provides a taxonomy and analysis of Jubensha games, based on a thematic analysis of over 80 Jubensha games accessed through mobile applications and physical copies. The analysis combines the authors’ positionalities as native Chinese and English speakers and lenses from close reading of the games, discourse analysis, and distributed cognition. We provide summative case studies to exemplify our taxonomy and discuss design implications for Jubensha games for future projects. Our work provides a descriptive tool and vocabulary for researchers and designers to facilitate communication and theorize the evolving Jubensha gaming phenomenon highlighting how gameplay centers collaborative sensemaking. In addition, we argue that the design of game narratives in Jubensha games, including structures in scripts and the evolving performance of players, can be generalized and transferred to the design of a wider range of analog and video games.

关键词： Jubensha murder mystery games taxonomy game analysis game design cross-cultural context

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