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Keyword: RobustOn Adversarial Robustness of Quantized Neural Networks Against Direct Attacks
Deep Neural Networks (DNNs) prove to be susceptible to synthetically generated samples, so-called adversarial examples. Such adversarial examples aim at generating misclassifications by specifically optimizing input data for a matching perturbation. With the increasing use of deep learning on embedded devices and the resulting use of quantization techniques to compress deep neural networks, it is…
Read MoreOn the Polytopic Modelling & Robust H∞ Control of Nonlinear Systems Subject to Cyber-attack: Application to Attitude Stabilization of Quadrotor
In the present contribution, a robust output H∞ control ensuring the stability, reliability and security for nonlinear systems when actuator attacks (data deception attacks) occur. A new design method based on the polytopic rewriting of the attacked system as an uncertain one subject to external disturbances will be detailed. Robust polytopic state feedback observer sta-…
Read MoreRobust Adaptive Feedforward Sliding Mode Current Controller for Fast-Scale Dynamics of Switching Multicellular Power Converter
Higher efficiency and lower losses are widely considered as the best metrics to optimize, in a high-power converter performance context. To provide a solution to the ever-increase of high switching frequencies challenges, we must explore soft-switching technologies to resolve interface issues and reduce the switching losses. This manuscript describes a comparative analysis between the fixed-bandwidth…
Read MoreFault Diagnosis and Noise Robustness Comparison of Rotating Machinery using CWT and CNN
For systems using rotating machinery, diagnosing the faults of the rotating machinery is critical for system maintenance. Recently, a machine learning algorithm has been employed as one of the methods for diagnosing the faults of rotating machinery. This algorithm has an advantage of automatically classifying faults without an expert knowledge. However, despite a good training…
Read MoreAdaptive Identification Method of Vehicle Model for Autonomous Driving Robust to Environmental Disturbances
Many recent studies on autonomous driving have focused on model-based control. A number of studies has addressed that simple models such as the Kinematic Bicycle Model are easier to design controls for autonomous driving systems. However, such a simple vehicle model has a weakness in that it is subject to modeling errors. This is because…
Read MoreEvaluation of Disadvantaged Regions in East Java Based-on the 33 Indicators of the Ministry of Villages, Development of Disadvantaged Regions, and Transmigration Using the Ensemble ROCK (Robust Clustering Using Link) Method
East Java province is a large province in Indonesia, in which Surabaya is the second largest metropolitan city after Jakarta. Various problems of development inequality in East Java have caused East Java to be defined as a disadvantaged area in 2015. The determination of disadvantaged regions is carried out every 5 years using 6 criteria…
Read MoreRobust Static Output-Feedback Fault Tolerant Control for a Class of T-S Fuzzy Systems using Adaptive Sliding Mode Observer Approach
In this paper, the problems of actuator and sensor fault estimation (FE) and fault-tolerant control (FTC) for uncertain nonlinear systems represented by Takagi-Sugeno (T-S) fuzzy models are investigated. First, a robust fuzzy adaptive sliding mode observer (SMO) is designed to simultaneously estimate system states and both actuator and sensor faults. Then, using the obtained on-line…
Read MorePerformance of Robust Confidence Intervals for Estimating Population Mean Under Both Non-Normality and in Presence of Outliers
We proposed two robust confidence interval estimators, namely, the median interquartile range confidence interval (MDIQR) and the trimean interquartile range confidence interval (TRIQR) for the population mean (µ) as an alternative to the classical confidence interval. The proposed methods are based on the asymptotic normal theorem (ANT) for the sample median (MD) and the sample…
Read MoreImproved Nonlinear Fuzzy Robust PCA for Anomaly-based Intrusion Detection
Among the most popular tools in security field is the anomaly based Intrusion Detection System (IDS), it detects intrusions by learning to classify the normal activities of the network. Thus if any abnormal activity or behaviour is recognized it raises an alarm to inform the users of a given network. Nevertheless, IDS is generally susceptible…
Read MoreA Word Spotting Method for Arabic Manuscripts Based on Speeded Up Robust Features Technique
The diversity of manuscripts according to their contents, forms, organizations and presentations provides a data-rich structures. The aim is to disseminate this cultural heritage in the images format to the general public via digital libraries. However, handwriting is an obstacle to text recognition algorithms in images, especially cursive writing of Arabic calligraphy. Most current search…
Read MoreRobust synchronization of nonfragile control of complex dynamical network with stochastic coupling and time-varying delays
This paper explores the problem of robust synchronization of complex dynamical network with stochastic coupling and time-varying delays through the application of nonfragile control. A well defined Lyapunov Krasovskii functional is established and by employing the widely acknowledged extended Jensen’s integral inequality and the Bernoulli’s distribution sequences, the stochastic nature of network coupling is modeled…
Read MoreRobust µController Implementations for a Linear Pneumatic Actuator Interaction
Over the years, pneumatic systems have recorded a remarkable performance in automated applications, based on their cost to efficiency ratio and ease of energy transmission. Therefore, their drawback of not being totally controllable devices in terms of position accuracy, still represents a challenge task for engineers. In this paper, a traditional three term controller (PID)…
Read MoreTIMeFoRCE: An Identity and Access Management Framework for IoT Devices in A Zero Trust Architecture
Zero Trust Architecture offers a transformative approach to network security by emphasizing ”never trust, always verify.” IoT devices, while increasingly integral to modern ecosystems, pose unique challenges for identity management and access control due to their constrained processing power, memory, and energy capabilities. In a Zero Trust framework, every IoT device is treated as a…
Read MoreCIRB-Edge for Secure, Energy-Efficient, and Real-Time Edge Computing
In this work, we present CIRB-Edge, a novel integer compression method designed specifically to overcome the limitations of traditional techniques such as Huffman coding, Delta encoding, and dictionary-based algorithms. These legacy methods often fall short in meeting the stringent requirements of secure, energy-efficient, and real-time edge computing due to their high computational overhead, memory demands,…
Read MoreExplainable AI and Active Learning for Photovoltaic System Fault Detection: A Bibliometric Study and Future Directions
Persistent anomalies in modern photovoltaic (PV) systems present a formidable challenge, impeding optimal power output and system resilience. Artificial Intelligence (AI) has surfaced as a game-changing solution, yet existing research has merely scratched the surface of solar panel prognosis, leaving a critical void in leveraging AI’s explainable nature and active learning capabilities. This pioneering study…
Read MoreHardware and Secure Implementation of Enhanced ZUC Steam Cipher Based on Chaotic Dynamic S-Box
Despite the development of the Internet and wired networks such as fiber optics, mobile networks remain the most used thanks to the mobility they offer to the user. However, data protection in these networks is more complex because of the radio channels they use for transmission. Hence,there is a need to find more sophisticated data…
Read MoreEarly Detection of SMPS Electromagnetic Interference Failures Using Fuzzy Multi-Task Functional Fusion Prediction
This study addresses the need for improved prognostics in switch-mode power supplies (SMPS) that incorporate electromagnetic interference (EMI) filters, with a focus on aluminum electrolytic capacitors, which are critical for the reliability of these systems. The primary aim is to develop a robust model-based approach that can accurately predict the degradation and operational lifetime of…
Read MoreFrom Sensors to Data: Model and Architecture of an IoT Public Network
RetePAIoT of Emilia-Romagna region is an IoT Public Network, financed by Emilia-Romagna Region and developed by Lepida Scpa, where citizens, private companies and Public Administrations can integrate free of charge their own sensors of any type and anywhere in the region. The main objective of the project is to provide a facility to implement the…
Read MoreDeploying Trusted and Immutable Predictive Models on a Public Blockchain Network
Machine learning-based predictive models often face challenges, particularly biases and a lack of trust in their predictions when deployed by individual agents. Establishing a robust deployment methodology that supports validating the accuracy and fairness of these models is a critical endeavor. In this paper, we introduce a novel approach to deploying predictive models, such as…
Read MoreOptimal Engagement of Residential Battery Storage to Alleviate Grid Upgrades Caused by EVs and Solar Systems
The integration of distributed energy resources has ushered in a host of complex challenges, significantly impacting power quality in distribution networks. This work studies these challenges, exploring issues such as voltage fluctuations and escalating power losses caused by the integration of solar systems and electric vehicle (EV) chargers. We present a robust methodology focused on…
Read MoreEnhancing the Network Anomaly Detection using CNN-Bidirectional LSTM Hybrid Model and Sampling Strategies for Imbalanced Network Traffic Data
The cybercriminal utilized the skills and freely available tools to breach the networks of internet-connected devices by exploiting confidentiality, integrity, and availability. Network anomaly detection is crucial for ensuring the security of information resources. Detecting abnormal network behavior poses challenges because of the extensive data, imbalanced attack class nature, and the abundance of features in…
Read MoreStrengthening LoRaWAN Servers: A Comprehensive Update with AES Encryption and Grafana Mapping Solutions
This work enhances the LoRaWAN server framework, focusing on an innovative approach for robust security and dynamic data visualization in network management. Migrating from RVC4 to AES encryption, it fortifies the network’s defense against cyber threats, a crucial advancement in IoT security. Furthermore, the integration with Grafana’s mapping plugin capitalizes on geolocation data, a strategic…
Read MoreEnhancing Cloud Security: A Comprehensive Framework for Real-Time Detection, Analysis and Cyber Threat Intelligence Sharing
Cloud computing has emerged as a pivotal component of contemporary IT systems, affording organizations the agility and scalability required to meet the ever-changing demands of business. However, this technological evolution has introduced a new era of cybersecurity challenges, as attackers employ increasingly sophisticated strategies to breach cloud networks. Such breaches can have far-reaching consequences, including…
Read MoreImproving License Plate Identification in Morocco: Intelligent Region Segmentation Approach, Multi-Font and Multi-Condition Training
The exponential growth in the number of automobiles over the past few decades has created a pressing need for a robust license plate identification system that can perform effectively under various conditions. In Morocco, as in other regions, local authorities, public organizations, and private companies require a reliable License Plate Recognition (LPR) system that takes…
Read MoreMeasurement System for Evaluation of Radar Algorithms using Replication of Vital Sign Micro Movement and Dynamic Clutter
In this paper we present a measurement system that is able to evaluate radar algorithms for vital signs sensing applications. For such medical applications, it is crucial to develop robust and reliable algorithms that are tested in a laboratory environment. The presented measurement system generates reproducible vital sign micro movement and dynamic clutter using loudspeakers…
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