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controlled Dropout for Uncertainty Estimation

Controlled Dropout for Uncertainty Estimation

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IEEE International Conference on systems, Man and Cybernetics

作者： Mehedi Hasan Ibrahim Hossain Ashikur Rahman Saeid Nahavandi Institute for Intelligent Systems Research and Innovation Deakin University Geelong VIC Australia Dept. of Computer Science and Engineering Bangladesh University of Engineering and Technology Dhaka Bangladesh

Uncertainty quantification in a neural network is one of the most discussed topics for safety-critical applications. Though Neural Networks (NNs) have achieved state-of-the-art performance for many applications, they still provide unreliable point predictions, which lack information about uncertainty estimates. Among various methods to enable neural networks to estimate uncertainty, Monte Carlo (MC) dropout has gained much popularity in a short period due to its simplicity. In this study, we present a new version of the traditional dropout layer where we are able to fix the number of dropout configurations. As such, each layer can take and apply the new dropout layer in the MC method to quantify the uncertainty associated with NN predictions. We conduct experiments on both toy and realistic datasets and compare the results with the MC method using the traditional dropout layer. Performance analysis utilizing uncertainty evaluation metrics corroborates that our dropout layer offers better performance in most cases.

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An Adaptive Multi-Stage Evolution Algorithm for High-Dimensional Expensive Problems

An Adaptive Multi-Stage Evolution Algorithm for High-Dimensi...

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IEEE International Conference on systems, Man and Cybernetics

作者： Boyuan Zhang Rui Lai Guanghong Gong Haitao Yuan Jinhong Yang Jia Zhang School of Automation Science and Electrical Engineering Beihang University Beijing China CSSC Systems Engineering Research Institute Beijing China Dept. of Computer Science Southern Methodist University Dallas TX USA

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

Recently, many studies have used evolutionary algorithms (EAs) to optimize complex problems across various fields, including mechanical structure design, robotics, and cloud computing. EAs simulate the process of evolution to improve solutions to a given problem iteratively. However, EAs encounter significant challenges when dealing with high-dimensional expensive problems (HEPs). The large solution space and high computing cost of fitness evaluations (FEs) make optimization with limited FEs particularly difficult. To tackle this problem, an Adaptive Multi-stage Evolution Algorithm named AMEA is proposed. In AMEA, an adaptively enhanced teaching-learning-based optimization algorithm is adopted to explore the search space and find potential areas quickly. Then, in the next stage, the Gaussian process surrogate model and a genetic learning particle swarm optimization algorithm are adopted for further exploitation. Besides, this work proposes an adaptive stage switching criterion and an individual screening mechanism to enhance the optimization ability. AMEA demonstrates strong optimization performance when applied to HEPs. We compare AMEA with several state-of-the-art HEP optimization algorithms through seven benchmark functions, and the results show that it performs competitively with other algorithms. Finally, we also validate AMEA's effectiveness with a real-world computation offloading problem.

关键词： Adaptation models Costs Switches Gaussian processes Genetics Iron Space exploration Particle swarm optimization Optimization Robots

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Methods of Pulse Width Modulation in Cascaded High Voltage Frequency Converters 3

Methods of Pulse Width Modulation in Cascaded High Voltage F...

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3rd IEEE KhPI Week on Advanced Technology, KhPI Week 2022

作者： Busher, Victor Chornyi, Oleksii Tytiuk, Valerii Glazeva, Oksana Rozlutskyi, Oleksandr Kuznetsov, Vitaliy National University 'Odessa Maritime Academy' Dept. of Electrical Engineering and Electronics Odessa Ukraine Institute of Electromechanics National University Energy Saving and Automatic Control Systems Kremenchuk Mykhailo Ostrohradskyi Kremenchuk Ukraine Kryvyi Rih National University Kryvyi Rih Ukraine Ukrainian State University of Science and Technologies Dept. of the Electrical Engineering Dnipro Ukraine

ISBN: (数字)9798350399202

ISBN: (纸本)9798350399202

Purpose. The aim of this work is to compare the effectiveness of various methods for correcting cell failures in cascade high voltage frequency converters. These methods provide the smallest voltage drop on the motor, the least loads and oscillation of electromagnetic torque in an accident modes, and evaluate the effectiveness of pulse width modulation (PWM) methods with the injection of third harmonic and space-vector PWM in normal and emergency modes. Methodology. We use mathematical and geometrical interpretation of all analysed methods - Sinusoidal PWM (SPWM), Balanced sinusoidal PWM (BSPWM), Balanced PWM with injected 3rd harmonic (THPWM) and Balanced Space Vector PWM (SVPWM). Results. The method of balancing the phase-to-phase voltages by to such a shift of the zero point and rotation of the phase vectors, in which the amplitude of the phase-to-phase voltage decreases to the minimum possible value. Injection of the 3rd harmonic allows you to further increase the utilisation factor of power supplies in terms of voltage. But the violation of the symmetry of the phase voltages leads to the need to reduce the voltage amplitude to exclude saturation of the power supplies, which reduces this coefficient compared to the theoretically possible 15.6%. A distinctive feature of the method of balanced Space Vector PWM is that the amplitude of the 1st harmonic is always greater than the radius of the circle by 15.6%. Comparison of methods of space vector PWM (SVPWM), balancing of phase-to-phase voltage with the injection of the 3rd harmonic (THPWM) with sinusoidal PWM shows that SVPWM is the best method. Despite the more complex mathematical software for the implementation of this method, it provides the best performance in all considered emergency modes of 3...6 cascade converters. The Table of indicators for all methods are presented in the article. The use of a balanced SVPWM in combination with field oriented control makes it possible to obtain an electric drive in whi

关键词： Pulse width modulation

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Uncovering motifs of concurrent signaling across multiple neuronal populations 23

Uncovering motifs of concurrent signaling across multiple ne...

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Proceedings of the 37th International Conference on Neural Information Processing systems

作者： Evren Gokcen Anna I. Jasper Alison Xu Adam Kohn Christian K. Machens Byron M. Yu Dept. of Electrical and Computer Engineering Carnegie Mellon University Dominick Purpura Dept. of Neuroscience Albert Einstein College of Medicine Dominick Purpura Dept. of Neuroscience Albert Einstein College of Medicine and Dept. of Ophthalmology and Visual Sciences Albert Einstein College of Medicine and Dept. of Systems and Computational Biology Albert Einstein College of Medicine Champalimaud Neuroscience Programme Champalimaud Foundation Dept. of Electrical and Computer Engineering Carnegie Mellon University and Dept. of Biomedical Engineering Carnegie Mellon University

Modern recording techniques now allow us to record from distinct neuronal populations in different brain networks. However, especially as we consider multiple (more than two) populations, new conceptual and statistical frameworks are needed to characterize the multi-dimensional, concurrent flow of signals among these populations. Here, we develop a dimensionality reduction framework that determines (1) the subset of populations described by each latent dimension, (2) the direction of signal flow among those populations, and (3) how those signals evolve over time within and across experimental trials. We illustrate these features in simulation, and further validate the method by applying it to previously studied recordings from neuronal populations in macaque visual areas V1 and V2. Then we study interactions across select laminar compartments of areas V1, V2, and V3d, recorded simultaneously with multiple Neuropixels probes. Our approach uncovered signatures of selective communication across these three areas that related to their retinotopic alignment. This work advances the study of concurrent signaling across multiple neuronal populations.

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A Novel Technique to Parameterize Congestion control in 6TiSCH IIoT Networks

A Novel Technique to Parameterize Congestion Control in 6TiS...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Kushal Chakraborty Aritra Kumar Dutta Mohammad Avesh Hussain Syed Raafay Mohiuddin Nikumani Choudhury Rakesh Matam Mithun Mukherjee Dept. of Computer Science & Information Systems Birla Institute of Technology & Science Hyderabad India Dept. of Computer Science & Engineering Indian Institute of Information Technology Guwahati India Nanjing University of Information Science and Technology Nanjing China

The Industrial Internet of Things (IIoT) refers to the use of interconnected smart devices, sensors, and other technologies to create a network of intelligent systems that can monitor and manage industrial processes. 6TiSCH (IPv6 over the Time Slotted Channel Hopping mode of IEEE 802.15.4e) as an enabling technology facilitates low-power and low-latency communication between IoT devices in industrial environments. The Routing Protocol for Low power and lossy networks (RPL), which is used as the de-facto routing protocol for 6TiSCH networks is observed to suffer from several limitations, especially during congestion in the network. Therefore, there is an immediate need for some modifications to the RPL to deal with this problem. Under traffic load which keeps on changing continuously at different instants of time, the proposed mechanism aims at finding the appropriate parent for a node that can forward the packet to the destination through the least congested path with minimal packet loss. This facilitates congestion management under dynamic traffic loads. For this, a new metric for routing using the concept of exponential weighting has been proposed, which takes the number of packets present in the queue of the node into account when choosing the parent at a particular instance of time. Additionally, the paper proposes a parent selection and swapping mechanism for congested networks. Performance evaluations are carried out in order to validate the proposed work. The results show an improvement in the performance of RPL under heavy and dynamic traffic loads.

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Threshold Adjustment of Beta-Alpha Ratio of EEG Signal for Generation of Visual Effects in a VR Live Concert 10

Threshold Adjustment of Beta-Alpha Ratio of EEG Signal for G...

引用

10th IEEE Global Conference on Consumer Electronics, GCCE 2021

作者： Munoz-Gonzalez, Angel Horie, Ryota Shibaura Institute of Technology Functional Control Systems Tokyo Japan Shibaura Institute of Technology Dept. of Information And Communications Engineering Tokyo Japan

ISBN: (纸本)9781665436762

We have developed a Brain-computer Interface (BCI) experience combining electroencephalogram (EEG) signals with Virtual Reality (VR). In our proposal, the users can attend a VR live concert system while participating in it throughout the generation of visual effects (VE) based on their brain activity. The VE are generated according to the beta and alpha waves of the EEG signal. When the beta-alpha ratio exceeds specific values, a threshold triggers the generation of different VE. A comparison between fixed threshold values and personalized thresholds for each subject is conducted. When conducting VR lives, individual differences on the beta-alpha ratio sometimes prevent the generation of VE based on constant thresholds, causing bigger differences on the experience between users. Thus, towards conducting VR live concert with many users, automatic adjustment of the thresholds for compensating the individual differences is required. In this paper, we proposed a method for adjusting thresholds based on percentiles of the distribution of beta-alpha ratio values and implemented it to our VR live system. We show results of experiments for validating the proposed methods. © 2021 IEEE.

关键词： Electroencephalography

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Blockchain-Enhanced Framework for Secure Third-Party Vendor Risk Management and Vigilant Security controls

Blockchain-Enhanced Framework for Secure Third-Party Vendor ...

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IEEE International Conference on Big Data

作者： Deepti Gupta Lavanya Elluri Avi Jain Shafika Showkat Moni Omer Aslan Dept. of Computer Information Systems Texas A&M University - Central Texas Texas USA College of Business University of Tampa Florida USA Dept. of Electrical Engineering and Computer Science Embry-Riddle Aeronautical University Florida USA Department of Software Engineering Bandırma Onyedi Eylül University Bandırma Turkey

ISBN: (数字)9798350362480

ISBN: (纸本)9798350362497

In an era of heightened digital interconnectedness, businesses increasingly rely on third-party vendors to enhance their operational capabilities. However, this growing dependency introduces significant security risks, making it crucial to develop a robust framework to mitigate potential vulnerabilities. This paper proposes a comprehensive secure framework for managing third-party vendor risk, integrating blockchain technology to ensure transparency, traceability, and immutability in vendor assessments and interactions. By leveraging blockchain, the framework enhances the integrity of vendor security audits, ensuring that vendor assessments remain up-to-date and tamperproof. This proposed framework leverages smart contracts to reduce human error while ensuring real-time monitoring of compliance and security controls. By evaluating critical security controls—such as data encryption, access control mechanisms, multi-factor authentication, and zero-trust architecture—this approach strengthens an organization’s defense against emerging cyber threats. Additionally, continuous monitoring enabled by blockchain ensures the immutability and transparency of vendor compliance processes. In this paper, a case study on iHealth’s transition to AWS Cloud demonstrates the practical implementation of the framework, showing a significant reduction in vulnerabilities and marked improvement in incident response times. Through the adoption of this blockchain-enabled approach, organizations can mitigate vendor risks, streamline compliance, and enhance their overall security posture. Our findings highlight the importance of employing blockchain to enforce security controls and maintain compliance with healthcare regulations such as HIPAA. In this paper, we present a comprehensive set of security controls and demonstrate how blockchain technology enhances their effectiveness, ensuring greater transparency, accountability, and automation in vendor assessments. By reducing human error, enabl

关键词： Multi-factor authentication Smart contracts Organizations Real-time systems Regulation Blockchains Security Time factors Risk management Resilience

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Private Balance-Checking on Blockchain Accounts Using Private Integer Addition

Private Balance-Checking on Blockchain Accounts Using Privat...

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IEEE International Symposium on Information Theory

作者： Birenjith Sasidharan Emanuele Viterbo Dept. of Electronics &amp Communication Engineering Govt. Engineering College Trivandrum India Dept. of Electrical and Computer Systems Engineering Monash University Clayton Australia

ISBN: (数字)9781665421591

ISBN: (纸本)9781665421607

A transaction record in a sharded blockchain can be represented as a two-dimensional array of integers with row-index associated to an account, column-index to a shard and the entry to the transaction amount. In a blockchain-based cryptocurrency system with coded sharding, a transaction record of a given epoch of time is encoded using a maximum-distance-separable code considering the entries as finite-field symbols. Each column of the resultant coded array is then stored in a server. In this paper, we propose a privacy-preserving multi-round protocol that allows a remote client to retrieve from a coded blockchain system the sum of transaction amounts belonging to two different epochs of time, but to the same ac-count. At the core of the protocol lies an algorithm for a remote client to privately compute a non-linear function referred to as integer addition of two finite-field symbols representing integer numbers, in the presence of curious-but-honest adversaries. Applying it to balance-checking in a cryptocurrency system, the protocol guarantees information-theoretic privacy on account number and shard number thereby ensuring perfect user anonymity, and also maintains confidentiality of half of the input bits on average. The protocol turns out to be a useful primitive for balance-checking in lightweight clients of a PolyShard-ed blockchain.

关键词： Privacy Protocols Codes Symbols Blockchains Cryptocurrency Servers

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A New Robust Hybrid Active Noise control System

A New Robust Hybrid Active Noise Control System

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IEEE International Conference on Signal and Image Processing (ICSIP)

作者： Z. Wang Y. Xiao Y. Ma L. Ma K. Khorasani Dept. of Management & Information Systems Prefectural University of Hiroshima Hiroshima Japan Institute of Automation Jiangnan University Wuxi China Dept. of Electrical & Computer Engineering Concordia University Montreal Canada

The conventional hybrid active noise control (ANC, HANC) may significantly degrade if the reference signal for the feedforward ANC (FFANC) subcontroller consists of not only a broadband component but also a low-frequency sinusoidal component that is uncorrelated or partially correlated with the narrowband noise component that is attenuated by the feedback ANC (FBANC) subcontroller. In this paper, a new robust HANC system is proposed to mitigate the performance degradation resulting from the low-frequency sinusoidal component. A band-pass filter bank (BPFB) is applied to the FFANC reference signal to separate the low-frequency sinusoidal component from the broadband one and each of them is fed to an FFANC subcontroller that solely focuses on a single noise component. A supporting filter takes the extracted broadband component and the residual error as its input and desired signal, respectively. The same BPFB is then applied to the supporting filter error in order to separate the remaining low-frequency sinusoidal component from the narrowband component that persists in the residual error. The use of the two BPFBs and the supporting filter allows the three HANC subcontrollers to operate practically independently, each taking care of one of the pre-processed noise components which are uncorrelated with each other irrespective of the relationship between the two original noise sources. Extensive simulations are provided to demonstrate the improved effectiveness and robust capability of the proposed HANC as compared to its counterpart, even in a case that the low-frequency sinusoidal component in the FFANC reference signal is partially corrected with the primary narrowband noise component that is targeted by the FBANC.

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A Sentiment Analysis Study of Twitter Users' Reactions to the COVID-19 Vaccine

A Sentiment Analysis Study of Twitter Users' Reactions to th...

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International Conference on Information and Communication systems (ICICS)

作者： Suboh Alkhushayni Zakaria Alomari Du'a Al-Zaleq Dept. Information Systems Faculty of Information Technology and Computer Science Yarmouk University Irbid Jordan Dept. Computer Science New York Institute of Technology Vancouver BC Canada Dept. Robotics and Artificial Intelligence Engineering Al-Ahliyya Amman University Amman Jordan

This study investigates public attitudes towards the COVID-19 vaccine through Twitter data analysis. Using the Twitter API, tweets were collected, preprocessed, and labeled. Features were extracted using the Bag of Words representation, and sentiment analysis was conducted using Text Blob and Vader. Machine learning and deep learning models were trained and tested, revealing that deep learning models achieved the highest accuracy and F1 score. The research underscores the efficacy of machine learning and deep learning in analyzing COVID-19 vaccine-related tweets, shedding light on factors influencing vaccine resistance. These insights are crucial for pharmaceutical companies and public health officials, enabling them to address barriers to vaccine acceptance and enhance the societal benefits of widespread vaccination, contributing to the pandemic's resolution.

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