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International Conference on Reliability, Infocom Technologies and Optimization (ICRITO) (Trends and Future Directions)

作者： Pranav Waghanna Akash Reddy Sarthak Deshpande Siddhant Chavan Vishal R. Jaiswal Vishal Naranje BE IT Department of Pune Institute of Computer Technology Pune IT Department of Pune Institute of Computer Technology Pune School of Engineering Architecture and Interior Design Amity University Dubai

ISBN: (数字)9798350350357

ISBN: (纸本)9798350350364

In the era of Industry 4.0, Smart Manufacturing is reshaping how things are made. At the heart of it is the Industrial Internet of Things (IIoT), where smart sensors and connections create a digital system for factories. This paper highlights how IIoT facilitates real-time data exchange, aiding quick decision-making and creating adaptable manufacturing setups. Cyber-Physical Systems (CPS) integration is also discussed, showing how the line between physical and digital elements in manufacturing is getting blurred. Big Data Analytics is another game-changer, supporting data-driven decisions and predictive maintenance. The paper also digs into Artificial Intelligence and Machine Learning, showing how they automate tasks and continuously learn, improving manufacturing processes. Real-world applications are examined, including Digital Twins, advanced robotics like collaborative robots (Cobots), 3D printing, and smart supply chain management. While Smart Manufacturing offers numerous benefits, it's not without challenges. The survey talks about security and privacy concerns, emphasizing the need for strong cybersecurity. Interoperability, ensuring different technologies work seamlessly together, and addressing the workforce skills gap are also explored. The paper ends with examples of successful implementations and looks at future trends, such as the impact of 5G, blockchain in supply chain management, human augmentation, and the push for sustainability in Smart Manufacturing. This survey is a practical guide for anyone interested in understanding the current state and where Smart Manufacturing is headed in the world of Industry 4.0.

关键词： Industries Surveys Technological innovation Supply chain management Market research Fourth Industrial Revolution Sustainable development

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Cox-ResNet: A Survival Analysis Model Based on Residual Neural Networks for Gene Expression Data 19

Cox-ResNet: A Survival Analysis Model Based on Residual Neur...

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19th IEEE International Conference on Networking, Sensing and Control, ICNSC 2022

作者： Yin, Qingyan Chen, Wangwang Wu, Ruiping Wei, Zhi School of Science Xi'an University of Architecture and Technology Xi'an China New Jersey Institute of Technology Department of Computer Science Newark United States

ISBN: (纸本)9781665472432

Survival analysis with genomics data provides a deep understanding of biological processes related to prognosis and disease progression at the molecular level. However, high-dimensional small sample genome data causes computational challenges in survival analysis. To address this problem of overfitting and poor interpretation of existing models, we applied the deep learning technology to genome data and proposed a survival analysis model based on an image-based residual neural network model, called Cox-ResNet. High-dimensional gene expression data was embedded into 2D images according to gene positions on chromosomes, and then a residual network model based on Cox proportional hazards was introduced to perform survival analysis. We demonstrated the performance of Cox-ResNet on five datasets of different cancer types from TCGA, comparing it with the cutting-edge survival analysis methods. The Cox-ResNet model not only shows better performance in prediction accuracy, but also biologically interpretable, by generating heat-maps and prognostic genes for high-risk groups with the guided Grad-Cam visualization method. By performing protein-protein interaction network analysis, we examined hub genes and their biological functions for the bladder cancer. These findings confirm that Cox-ResNet model provides a new solution for discovering the driver genes of poor cancer prognosis. © 2022 IEEE.

关键词： Deep learning

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Real-Time Inference of Temporal Emotional and Behavioral Conditions of Learners in Problem Solving Within Mixed Reality Environments 1

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19th International Conference on Computing in Civil and Building Engineering, ICCCBE 2022

作者： Castets, Édouard Mutis, Ivan Agam, Gady Department of Mechanical Materials and Aerospace Engineering Illinois Institute of Technology ChicagoIL60616 United States Department of Civil Architecture and Environmental Engineering Illinois Institute of Technology ChicagoIL60616 United States Department of Computer Science Illinois Institute of Technology Chicago60616 United States

ISBN: (数字)9783031325151

ISBN: (纸本)9783031325144

Using new affordances of Machine Learning (ML) and Mixed Reality (MX) technology, the presented research looks at how learners’ decision-making in problem-solving can increase with the technology interaction. The approach empowers users for enhanced problem-solving outcomes by enabling them to perform adapted actions in an MX environment. For example, present an adapted user’s view of 3D design components in the immersive space for any action (locking and moving) in problem-solving (e.g., design interpretations). The aim is to incorporate ML to tailor the user’s ability to problem-solve complex 3D design components by capitalizing on the flexibility of MX immersive environments. The system uses a collection of physiological and pupillometry data to create real-time inferences of the user’s state (emotional and physiological conditions). This paper focuses on the first phase of developing the MX and ML system for the augmented technology-user interaction to allow inference of the data in real time. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Mixed reality

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Secured Blockchain-Based Energy Trading Framework for Smart Microgrid Networks

Secured Blockchain-Based Energy Trading Framework for Smart ...

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International Conference on Advanced Intelligent Systems for Sustainable Development, AI2SD 2023

作者： Essardi, Hafida Oukhatar, Ayoub Najib, Mehdi Bakhouya, Mohamed Ouadghiri, Driss El Department of Computer Sciences IA Laboratory Faculty of Sciences Moulay Ismail University Meknes Morocco Department of Computer Sciences Higher School of Technology of Ouarzazate Ibn Zohr University Agadir80000 Morocco College of Engineering and Architecture International University of Rabat LERMA Lab & TICLab Sala Al Jadida Morocco

ISBN: (纸本)9783031542879

In order to find a practical solution to integrate green and renewable energy technologies into the existing power system, the smart grid approach was recently developed. In this way, the Internet-connected smart microgrids, commonly referred to the Internet of Energy, is emerging as an innovative process for securing energy at any time and from any location. The concept of microgrid systems together with advanced digitization concepts (e.g., Internet of Thing) at the production/consumption and distribution level are evolving as key components of deploying intelligent energy management systems. Therefore, it has become essential to establish reliable and effective energy trading systems among networked microgrids in order to reduce transmission losses while increasing reli- ability. Thus, recent research work has started to concentrate on how energy could be efficiently shared. Hence, in order to make energy trad- ing decisions safely for managing the overall load, this paper introduces a blockchain-based secure peer-to-peer energy trading management framework. A platform’s prototype is under development for being deployed in real sitting scenarios, e.g., farms’ micro-grid systems. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Smart contract

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Exploring Children’s Strategies in Response to Robot’s Advice During a Group Task with iCub and Nao 16th

Exploring Children’s Strategies in Response to Robot’s A...

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16th International Conference on Social Robotics, ICSR + AI 2024

作者： Pusceddu, Giulia Sangineto, Mariapia Cocchella, Francesca Bogliolo, Michela Belgiovine, Giulia Lastrico, Linda Casadio, Maura Rea, Francesco Gena, Cristina Sciutti, Alessandra Robotics Brain and Cognitive Science Department Italian Institute of Technology Genoa Italy Department of Informatics Bioengineering Robotics and Systems Engineering University of Genoa Genoa Italy Department of Computer Science University of Turin Turin Italy Cognitive Architecture for Collaborative Technologies Unit Italian Institute of Technology Genoa Italy Scuola di Robotica Genoa Italy

ISBN: (纸本)9789819635184

This study investigates children’s trust in two humanoid robots, Nao and iCub, through a cooperative game designed to elicit spontaneous behaviors and group dynamics. We investigate whether participants change their choices after hearing advice from a robot, considering rounds where the advice is correct or incorrect, with the robot apologizing for its mistakes. Results reveal that, in most cases, participants prefer not to change their moves after the robot’s advice. Additionally, after the robots made mistakes, participants are less likely to actively follow their advice and more likely to reject it. No significant differences in strategies among the iCub and Nao samples are evidenced. Furthermore, we examine the influence of group dynamics, identifying "Proactive Players" who consistently initiated moves. A significant association between the strategies of this player and their teammates is found, suggesting potential influence. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Adversarial machine learning

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LoRa-Powered Energy-Effcient Object Detection Mechanism in Edge Computing Nodes 6

LoRa-Powered Energy-Effcient Object Detection Mechanism in E...

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6th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2022

作者： Jindal, Anshul Jose, Jiby Mariya Benedict, Shajulin Gerndt, Michael Technical University Munich Computer Architecture and Parallel Systems Germany Indian Institute of Information Technology Kottayam Department of Computer Science and Engg. India

ISBN: (数字)9781665469418

ISBN: (纸本)9781665469418

The ongoing accomplishments in the decades-long realization of computer vision have infused new dimensions in various research areas such as smart mobility, smart healthcare, education, finance, and so forth. Research works relating to automated object detection, deep learning-assisted data pipelines, and energy-efficient end-to-end solutions have enabled newer perceptions among researchers, albeit the existence of challenges. This paper proposes an object detection system using energy-efficient Long Range (LoRA) communication media on edge nodes such as Raspberry Pi, Coral DevBoard, and Nvidia Jetson Nano. The proposed approach utilized energy-efficient methods to collaboratively offload object detection-related tasks such as capturing images, training images, and inferring objects across a compendium of computing nodes using LoRA. In addition, this research study has attempted to reveal the inference capabilities of images on three different edge nodes. The proposed work has achieved a power difference of at least 1.2 watts during the inference period of the deep learning models without challenging the prediction accuracy with respect to the base model. © 2022 IEEE.

关键词： Object detection

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The Seeker's Dilemma: Realistic Formulation and Benchmarking for Hardware Trojan Detection

The Seeker's Dilemma: Realistic Formulation and Benchmarking...

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2024 IEEE International Performance, Computing, and Communications Conference, IPCCC 2024

作者： Sarihi, Amin Patooghy, Ahmad Badawy, Abdel-Hameed A. Jamieson, Peter New Mexico State University Klipsch School of Electrical and Computer Engineering Las CrucesNM United States MIPS Architecture and Performance AustinTX United States North Carolina A and T State University Department of Computer Systems Technology GreensboroNC United States Miami University Department of Electrical and Computer Engineering OxfordOH United States

ISBN: (纸本)9798350367942

This work focuses on advancing the security field in the hardware design space by formally defining the problem of Hardware Trojan (HT) detection. The goal is to model HT detection more closely to the real world, i.e., describing the problem as "The Seeker's Dilemma"(an extension of Hide&Seek on a graph), where a detecting agent is unaware of whether HTs infect circuits or not. Using this problem formulation, we create a benchmark that consists of a mixture of HT-free and HT-infected restructured circuits while preserving their original functionalities. The restructured circuits are randomly infected by HTs, causing a situation where the defender is uncertain if a circuit is infected. Our innovative dataset will help the community better judge the detection quality of different methods by comparing their success rates in circuit classification. We use our benchmark to evaluate three state-of-the-art HT detection tools to show baseline results for this approach. We use Principal Component Analysis to assess the strength of our benchmark, where we observe that some restructured HT-infected circuits are mapped closely to HT-free circuits, leading to significant label misclassification by detectors. © 2024 IEEE.

关键词： Hardware security

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AN ACTIVE LEARNING PROCEDURE FOR THE INTERAURAL TIME DIFFERENCE DISCRIMINATION THRESHOLD 26

AN ACTIVE LEARNING PROCEDURE FOR THE INTERAURAL TIME DIFFERE...

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26th International Conference on Digital Audio Effects, DAFx 2023

作者： Gulli, Andrea Fontana, Federico Serafin, Stefania Geronazzo, Michele Department of Mathematics Computer Science and Physics Università di Udine Udine Italy Department of Architecture Design and Media Technology Aalborg University Copenhagen Denmark Department of Engineering and Management Università di Padova Padua Italy

Measuring the auditory lateralization elicited by interaural time difference (ITD) cues involves the estimation of a psychometric function (PF). The shape of this function usually follows from the analysis of the subjective data and models the probability of correctly localizing the angular position of a sound source. The present study describes and evaluates a procedure for progressively fitting a PF, using Gaussian process classification of the subjective responses produced during a binary decision experiment. The process refines adaptively an approximated PF, following Bayesian inference. At each trial, it suggests the most informative auditory stimulus for function refinement according to Bayesian active learning by disagreement (BALD) mutual information. In this paper, the procedure was modified to accommodate two-alternative forced choice (2AFC) experimental methods and then was compared with a standard adaptive "three-down, one-up" staircase procedure. Our process approximates the average threshold ITD 79.4% correct level of lateralization with a mean accuracy increase of 8.9% over the Weibull function fitted on the data of the same test. The final accuracy for the Just Noticeable Difference (JND) in ITD is achieved with only 37.6% of the trials needed by a standard lateralization test. © 2023 Andrea Gulli, Federico Fontana et al.

关键词： Inference engines

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Impurity explicit optimal Machine learning and statistical perfect construction for air quality prediction 2

Impurity explicit optimal Machine learning and statistical p...

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2nd IEEE International Conference on Networking and Communications, ICNWC 2024

作者： Nareshkumar, R. Shalinikumari, R. Kowsalya, S. Sri Nandhini Vijay Anand, P. Mohamed, Ajmal Gayathri, S. SRM Institute of Science and Technology School of Computing College of Engineering and Technology Department of Networking and Communications Tamilnadu Kattankulathur India Bharath Institute of Higher Education and Research Selaiyur Department of Architecture Tamilnadu Chennai India Veltech Multitech Dr.Rangarajan Dr.Sakunthala Engineering College Department of Information Technology Tamilnadu Chennai India CMR Institute of Technology Department of Artificial Intelligence and Data Science Bengaluru India Saveetha School of Engineering Department of Computer Science and Engineering Chennai India K. Ramakrishnan College of Technology Department of Computer Science and Engineering Tamilnadu Trichy India

ISBN: (纸本)9798350365269

The air quality index (AQI) is a metric used to report air quality levels. There has been a substantial rise in the level of air pollution in Indian cities. Multiple methodologies exist for formulating a mathematical equation to ascertain the air quality index. Multiple studies have established a correlation between exposure to air pollution and negative health effects in the general population. The objective of this study is to determine the optimal approach for predicting AQI in order to aid in climate regulation. Nine separate Machine learning (ML) algorithms have been employed in the suggested study to ascertain the AQI. The use of the SMOTE algorithm in the datasets in ML resulted in improved accuracy when comparing the outcomes. Furthermore, all of the implementations have been thoroughly documented using graphs and metrics, which clearly illustrate the differences in outcomes and aid in identifying the specific factors that led to the improvement in accuracy. © 2024 IEEE.

关键词： Machine learning

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Future connected vehicles:Communications demands,privacy and cyber-security

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Communications in Transportation Research 2022年第1期2卷 39-41页

作者： Tomas Olovsson Tommy Svensson Jiaming Wu Department of Computer Science and Engineering Chalmers University of TechnologyGothenburgSE41296Sweden Department of Electrical Engineering Chalmers University of TechnologyGothenburgSE41296Sweden Department of Architecture and Civil Engineering Chalmers University of TechnologyGothenburgSE41296Sweden

*** With the advance of data collection,data processing,telecommunication and vehicular technologies,connected vehicles(CVs)have been emerging as a crucial branch of smart mobility(Olia et al.,2015;Li et al.,2021).Its basic idea is to realize real-time exchanges and processing of essential information,such as positions and destinations,among surrounding vehicles and infrastructures.

关键词： connected branch destination

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