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4th IEEE KhPI Week on Advanced Technology, KhPI Week 2023

作者： Zaiets, Nataliia Vlasenko, Lidiia Lutska, Nataliia Zhyltsov, Andrii Dept. of Automation and Robotic Systems National University of Life and Environmental Sciences of Ukraine Kyiv Ukraine Dept. of Software Engineering and Cyber Security State University of Trade and Economics Kyiv Ukraine Dept. of Automation and Computer Technologies of Control Systems National University of Food Technologies Kyiv Ukraine Dept. of Electromagnetic Systems The Institute of Electrodynamics The National Academy of Sciences of Ukraine Kyiv Ukraine

ISBN: (纸本)9798350395532

The paper demonstrates the process of developing mathematical models for identifying breakdowns of electric motors using machine learning methods. The authors have developed three mathematical models for identifying breakdowns of electric drives with a power of 55 kW, 1500 rpm on the example of sugar production: model for quadratic discriminant analysis;binary classification decision tree;feedforward neural network model. The best structures and parameters of the models were determined by machine learning methods. The performance of the models on the training and test sets was more than 96% by F-score. It was proposed to use all three models independently for diagnosing breakdowns of electric drives, while the decision maker makes the final decision on the replacement or repair of electrical equipment. This approach is justified and effective because of the diversity of models. The developed models, except for assessing the state of the engine, can also be used for simulation modelling, forecasting, and serve as information support for process operators in organizing equipment maintenance. The availability of real-time information about the state of equipment in production will allow timely repair or replacement of equipment, thereby reducing the risks of stopping production and increasing the resource efficiency of technological processes. © 2023 IEEE.

关键词： Decision trees

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A Generalizable Machine Learning Model for NAT Detection

A Generalizable Machine Learning Model for NAT Detection

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2023 International Conference on Intelligent Computing, Communication, Networking and Services, ICCNS 2023

作者： Nassar, Reem Elhajj, Imad H. Kayssi, Ayman Salam, Samer American University of Beirut Dept. of Elecrtical and Computer Engineering Beirut Lebanon Cisco Systems Beirut Lebanon

ISBN: (纸本)9798350339291

Network Address Translation (NAT) aimed originally at resolving the issue of IPv4 address exhaustion. NAT allows multiple devices on a local network to share a single public IP address. This enables efficient utilization of the limited number of public IP addresses and allows devices on a local network to connect to the internet. However, NAT can lead to communication problems, security vulnerabilities, difficulties in network management, and challenges in identifying network issues. This paper proposes a novel approach for NAT detection using machine learning that overcomes the limitations of traditional NAT detection methods by building a generalizable model. The proposed method incorporates techniques to achieve generalization in the presence of obfuscation, a technique used by attackers to evade detection. The experimental results show the superiority of the proposed method over existing NAT detection techniques in terms of accuracy and generalization, even in the presence of obfuscation. A decline in the classification F1 score below 70% is observed when traffic data has multiple features obfuscated and when environment changes. To tackle this issue, transfer learning was applied to enhance the model's efficiency and effectiveness. Transfer learning resulted in more promising results in new network environments and in case of obfuscation. © 2023 IEEE.

关键词： Internet protocols

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A Novel Architecture of CXL Protocol Data Link Layer for Low Latency Memory Access

A Novel Architecture of CXL Protocol Data Link Layer for Low...

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2023 International Conference on Microelectronics, ICM 2023

作者： Mohamed, Basma H. Hany, Esmail El-Tahawy, Mahmoud Abdel-Salam, Mohamed El-Kharashi, M. Watheq Safar, Mona Ain Shams University Computer and Systems Engineering Dept. Cairo Egypt Siemens Eda Cairo Egypt

ISBN: (纸本)9798350380828

With the increase in memory-intensive applications, there is a need to provide low latency paths for memory access and coherent caching between host processors and storage devices. This paper proposes a novel architecture for the Data Link Layer of Compute Express Link (CXL) protocol, as defined in CXL Specification Revision 2.0. The architecture presented here contains the transmission and reception chains, which ensures the reliable conveyance of the packets between two CXL components using the CXL protocol. This paper explains how the proposed architecture ensures reliable data conveyance, responses and requests, through the addition of a 16-bit Cyclic Redundancy Check (CRC) to each 512-bit FLow control unIT (FLIT) in the transmitter side, and how the packets are processed in receiver side. The architecture is intended to have simple implementation in addition to having minimum datapath delays. The whole architecture is designed using HDL then verified using test-benches for different protocol scenarios to make sure that the functionality of the system is achieved. In addition, the whole design is synthesized using United Microelectronics Corporation (UMC) 130 nm [1] and Taiwan Semicomductors Manufactor Company (TSMC) 28 nm [2] technologies to get the maximum achieved frequency and calculate the corresponding power and area. The proposed hardware implementation manages to work up to 1 GHz using TSMC 28 nm technology and 438.59 MHz using UMC 130 nm technology. Its estimated dynamic and leakage power consumption by UMC 130 nm technology at 1 GHz are 95.3698 mW and 171.17 mW, respectively. In addition, its area cost extracted after synthesis is 242124.8 μ m2. © 2023 IEEE.

关键词： Microelectronics

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Deep Learning-Based Stock Price Prediction: A Comprehensive Approach Using Bi-LSTM 4

Deep Learning-Based Stock Price Prediction: A Comprehensive ...

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4th International Conference on Ubiquitous Computing and Intelligent Information systems, ICUIS 2024

作者： Chy, Md. Kalim Amzad Masum, Abdul Kadar Muhammad Alam, Mohammed Shamsul Azad, Md. Abul Kalam Hassan, Md. Maruf Bhuiyan, Touhid International Islamic University Dept. of Computer Science and Engineering Chittagong Bangladesh Daffodil International University Dept. of Software Engineering Dhaka Bangladesh Islamic University of Technology Dept. of Business and Technology Management Gazipur Bangladesh School of It Washington University of Science and Technology VA United States

ISBN: (纸本)9798331529635

This study delves into the prediction of stock prices in the Bangladesh stock market using advanced deep learning frameworks, with a particular focus on the Bidirectional Long Short-Term Memory (Bi-LSTM) model. Traditional statistical models often struggle to effectively capture the complex, non-linear characteristics of financial data, leading to inconsistent results. The Bi-LSTM model, however, addresses this challenge by processing data in both forward and backward sequences, making it particularly suitable for analyzing the intricate dynamics of the Bangladesh stock market. A rigorous feature engineering process is undertaken, incorporating 64 distinct features that include market trends, stock-specific indicators, technical and fundamental variables, as well as crucial macroeconomic factors like gold prices and foreign exchange reserves. The dataset spans historical stock market data from 2012 to 2022, with comprehensive preprocessing steps taken to ensure data quality and consistency. Hyperparameter tuning is executed through a grid search to optimize model performance. The evaluation of the Bi-LSTM model is carried out using metrics such as Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Mean Squared Error (MSE), and the R2 score, which demonstrate its enhanced predictive power compared to traditional models. This research contributes to the growing field of deep learning in financial forecasting, offering new perspectives for stock price prediction in emerging markets, while also addressing ethical issues to minimize risks like market manipulation. © 2024 IEEE.

关键词： Mean square error

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COMBINING SIMULATION AND RECURRENT NEURAL NETWORKS FOR MODEL-BASED CONDITION MONITORING OF MACHINES

COMBINING SIMULATION AND RECURRENT NEURAL NETWORKS FOR MODEL...

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2024 Winter Simulation Conference, WSC 2024

作者： Wuttke, Alexander Rabe, Markus Hunker, Joachim Diepenbrock, Jan-Philipp Dept. IT in Production and Logistics TU Dortmund University Dortmund Germany Fraunhofer Institute for Software and Systems Engineering Dortmund Germany IVA Schmetz GmbH Menden Germany

ISBN: (纸本)9798331534202

Maintenance is pivotal in industry, with condition-based maintenance emerging as a key strategy. This involves monitoring the machine condition through sensor data analysis. Model-based approaches compare observed data with expected values from models, which requires high-quality models. An established method is to use simulation models, which in many cases produce good results but may lack precision due to uncertainties. Alternatively, models created by machine learning can detect patterns directly from data. This paper proposes combining simulation models with machine learning models, leveraging the simulation’s a-priori knowledge and machine learning’s data patterns to enhance models for condition monitoring. Recurrent neural networks are suggested as the machine learning method. The paper outlines a systematic approach and demonstrates its application in an industrial use case, which investigates vacuum processes in industrial furnaces. © 2024 IEEE.

关键词： Neural network models

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ROBOT PATH PLANNING WITH A HYBRID ARITHMETIC OPTIMIZATION ALGORITHM

UPB Scientific Bulletin, Series C: Electrical Engineering an...

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UPB Scientific Bulletin, Series C: Electrical engineering and computer Science 2024年第3期86卷 197-210页

作者： Song, Qiang Dept. of Computer Science and Software Engineering Zhaoqing University Zhaoqing China

To address the premature convergence and search stagnation of arithmetic optimization algorithm (AOA), the paper proposes a hybrid arithmetic optimization algorithm (HAOA) and applies it to the practical robot path planning (RPP) problem. In initialization phase, the chaotic mechanism is used to create high-quality individuals. In evolution phase, the stochastic disturbance method is applied to enhance the exchange of information between different individuals. The solution space information around the candidate solution was integrated by Levy flight to enhance gene diversity and enhance search performance. In order to better solver the RPP problem, the Spline interpolation method is adapted to the HAOA algorithm for path optimization, so as to smooth the path curve and ensure the planning accuracy. Finally, numeric experiments of benchmark functions and RPP instances verify HAOA’s excellent performance in accuracy and robustness. This research shows arithmetic optimization algorithm can quickly find the global optimal solution, and has fast convergence speed and accuracy. © 2024, Politechnica University of Bucharest. All rights reserved.

关键词： Stochastic systems

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The Effect of Balanced and Imbalanced Dataset on Voice Pathology Detection Using Online Sequential Extreme Learning Machine (OSELM)

The Effect of Balanced and Imbalanced Dataset on Voice Patho...

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2024 IEEE International Conference on Advanced Telecommunication and Networking Technologies, ATNT 2024

作者： Sazihan, N. F. S. Md Latiff, N. M. Abdul Malik, N. N. N. Abd Mashohor, S. Alaghbari, K. Al-Dhief, F.T. Universiti Teknolgi Malaysia Utm Faculty of Electrical Engineering Johor Bahru Malaysia Universiti Putra Malaysia Faculty of Engineering Dept. of Computer and Communication Systems Engineering Serdang Malaysia

ISBN: (纸本)9798350353501

Voice pathology detection is crucial for early diagnosis and treatment of vocal disorders. This research studies the effect of balanced and imbalanced datasets on the accuracy of voice pathology detection using Online Sequential Extreme Learning Machine (OSELM) on the Saarbruecken Voice Database (SVD). The dataset's balance has been identified as having a significant influence on the performance of the machine learning models. In this work, the voice signals from vowel /a/ of pathology and non-pathology classes are taken from SVD. The dataset is divided into two category which are balanced and imbalanced dataset. Then, the features of the voice signals are then extracted using Mel-Frequency Cepstral Coefficient (MFCC) and fed into classifier called OSELM. The result of balanced and imbalanced dataset is assessed for its accuracy. The results showed that the model achieved an accuracy of 66.25% with the balanced dataset compared to 48% for the imbalanced dataset. These findings highlight the importance of addressing dataset balance to enhance the reliability and effectiveness of voice pathology detection systems. © 2024 IEEE.

关键词： Adversarial machine learning

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Orchestrating Microservice-based SDN Controllers: The MSN Realistic Use Case

Orchestrating Microservice-based SDN Controllers: The MSN Re...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Herrera, Juan Luis Scotece, Domenico Galán-Jiménez, Jaime Berrocal, Javier Modica, Giuseppe Di Bellavista, Paolo Foschini, Luca University of Bologna Dipartamento di Informatica Scienza e Ingegneria Italy University of Extremadura Dept. of Computer Systems and Telematics Engineering Spain

ISBN: (纸本)9798350351255

The software-Defined Networking (SDN) paradigm disaggregates the data plane, embodied by switches that only forward data, from the control plane, embodied by SDN controllers that communicate with said switches. SDN also proposes a third, application layer, which implements various functions such as firewalls or service discovery by communicating with the controllers through the northbound interface. However, while state-of-the-art works propose the deployment of multiple, distributed SDN controllers, the software architecture of these controllers is still monolithic, requiring not only the controller runtime but also all the network-level applications to be deployed across all SDN controller hardware. On the other hand, state-of-the-art SDN controllers such as MSN allow treating network-level applications as microservices, which comes with the challenge of orchestrating the microservices across the network. In this paper, we present Grex, a framework to orchestrate network-level applications across microservice-based SDN controllers. We test and validate the optimization model of Grex by performing experiments in a realistic network testbed using the MSN controller. © 2024 IEEE.

关键词： Network layers

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BioPoint: Enhancing Human-computer Interaction through Single-Site, Multi-Sensor Gesture Recognition 46

BioPoint: Enhancing Human-Computer Interaction through Singl...

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46th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Isabel, Xavier Campbell, Evan Olivier, Loïc Gagné, Gabriel Scheme, Erik Côté-Allard, Ulysse Gagnon-Turcotte, Gabriel Laval University Dept. of Electrical and Computer Engineering QC Canada University of New Brunswick Department of Electrical and Computer Engineering FrederictonNBE3B 5A3 Canada University of Oslo Dept. of Technology Systems Oslo Norway

ISBN: (纸本)9798350371499

Advancements in human-computer interaction (HCI) and machine learning are seen as key avenues to help individuals living with upper limb disabilities in accomplishing their activities of daily living. Multi-channel myoelectric systems are a promising approach for HCI due to their intuitive and accurate capture of user intent through muscle activity. However, such systems are still bulky compared to widely accepted smartwatches-like devices and as such pose a challenge for seamless integration into daily life. Consequently, this work presents the first single-site EMG-IMU-PPG system for multi-gesture recognition from the wrist. Overall, when evaluated on eight able-bodied participant, the system achieves an average accuracy of 65.28%±10.45% on 17 finger and wrist gestures and 90.98%±5.65% on eight hand gestures. This study also introduces "Myo Hero", an online environment inspired by "Guitar Hero."Myo Hero provides a dynamic method for testing multi-gesture recognition systems, improving the evaluation process's appeal. Online evaluation of the multimodal system substantially outperformed random play, signifying EMG-IMU-PPG's potential for human-computer interaction. © 2024 IEEE.

关键词： Electromyography

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Design and Simulation of an Affordable Vehicle Speed Detection System

Design and Simulation of an Affordable Vehicle Speed Detecti...

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2023 International Conference on Modeling and E-Information Research, Artificial Learning and Digital Applications, ICMERALDA 2023

作者： Thabet, Hassaan Th. H. Al-Hilali, Aqeel A. Al-Safi, Mohammed G. S. Thabit, Thabit H. Mahmood, Firas M. Al-Hadba University College Dept. of Computer Technology Engineering Mosul Iraq Al-Farahidi University Dept. of Medical Instruments Engineering Techniques Baghdad Iraq Al-Esraa University College Dept. of Accounting Baghdad Iraq Ninevah University Dept. of Computer Engineering and Information Mosul Iraq Cihan University-Erbil Dept. of Informatics and Software Engineering Kurdistan Region Iraq

ISBN: (纸本)9798350369359

The objective of this paper is to detect the over speed of vehicles on the roads. Although maximum speed limit signs exist on the roads, many accidents keep on because of high-speed driving. It is necessary to solve these problems through automation techniques. This paper describes a speed detection system for vehicles, the traffic police can easily check the speed of vehicles by using this system. This system consists of a PLC (Programmable Logic Controller) LOGO! V8.3, two Laser sensors, an HMI (Human Machine Interface), a speed camera, and a LOGO! CMR (Communication Module Radio). The detected speed is displayed on the HMI display, moreover, if a vehicle crosses the limited speed, this system displays the over-speed on HMI, and the speed camera is activated to capture an image of that vehicle. Also, an SMS (Short Messages Service) will be sent by the CMR to the traffic authority informing them about the violation to take the necessary legal actions. The system can also store the collected data for documentation purposes. The authors describe a simple, affordable technique for monitoring vehicles' speeds in this paper. © 2023 IEEE.

关键词： Vehicles

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