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Spatial Acoustic Loudspeaker Measurements With a Moving Microphone

AES: Journal of the Audio engineering Society 2025年第1-2期73卷 24-42页

作者： Herzog, Stephan Department of Electrical and Computer Engineering Digital Signal Processing Group RPTU University Kaiserslautern Landau Kaiserslautern Germany

Acoustic loudspeaker measurements are an essential aspect in loudspeaker development and design. Established setups usually require acoustic measurement rooms or chambers where the speaker under test has to be installed for conducting the tests. Furthermore, typical spatial measurements require that the speaker has to be rotated on one or two axes. In addition to the traditional approach, there are different methods that use near-field measurements where the microphone is usually moved and the loudspeaker remains at a fixed position. Both techniques commonly make measurements at discrete points or angles in the spatial domain. In this article, the idea of making impulse response measurements in the near-field while the microphone is in movement is proposed and described. This approach leads to much faster results that can be comparable to the results of fixed-point measurements. The focus here is on the properties and the resulting processing of appropriate test signals and on the experimental verification of the method. This method will be applied to the measurement of line arrays, where directivity is of high interest, but it can also be used for other loudspeaker configurations. © 2025 Audio engineering Society. All rights reserved.

关键词： Strain measurement

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Fine-tuning Specialized NER Model for Symptom Extraction from Slovenian Medical Texts 9

Fine-tuning Specialized NER Model for Symptom Extraction fro...

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9th International Conference on Mathematics and computers in Sciences and Industry, MCSI 2024

作者： Sallauka, Rigon Arioz, Umut Mlakar, Izidor University of Maribor Faculty of Electrical Engineering and Computer Science Laboratory of Digital Signal Processing Maribor Slovenia

ISBN: (纸本)9798350377224

In this study, we aim to develop a robust model capable of accurately extracting symptoms from clinical texts written in the Slovenian language. Our methodology involves several steps to achieve this objective. Initially, we identify datasets containing clinical texts in English and select a specialized model designed for symptom extraction from these texts. Then, we annotate the datasets and undertake the translation process into Slovenian, ensuring the preservation of annotations to maintain data integrity. Utilizing the translated dataset, we proceed to fine-tune the selected model specifically for Slovenian texts. Despite our efforts, optimal performance has not yet been attained. Challenges encountered include the translation methodology employed and the architectural limitations of the chosen model, which is primarily optimized for English texts. However, ongoing efforts are underway to address these challenges and enhance the model's performance. Our study represents a step towards improving automated symptom extraction in Slovenian clinical texts, with ongoing work focused on mitigating identified issues to achieve better outcomes. © 2024 IEEE.

关键词： Machine translation

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Fire Security Systems Analysis and Internet of Things Implications

Fire Security Systems Analysis and Internet of Things Implic...

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2023 IEEE International Conference on Electro Information Technology, eIT 2023

作者： Fuerte, Susana Rodriguez Yu, Xinrui Saniie, Jafar Illinois Institute of Technology Embedded Computing and Signal Processing Research Laboratory Department of Electrical and Computer Engineering ChicagoIL United States

ISBN: (纸本)9781665493765

This paper presents the current use of the Internet of Things (IoT) in fire evacuation and extinction. It examines the different approaches to the problem and technologies like Building Information Modeling (BIM) and mathematical algorithms that can be used to determine the optimal evacuation route. It also evaluates existing fire security solutions such as smoke, flame, motion, and gas sensors, LED lights, buzzers, and SMS modules. Entities that specialize in Residential and Commercial Security Systems and Home Automation are also discussed, along with the services they offer. The main objective of this study is to understand current systems and resources regarding fire evacuation and extinction systems and to analyze different developments in smart buildings to create an efficient system for fire detection and evacuation. © 2023 IEEE.

关键词： Internet of things

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Smart Infant Monitoring System Using computer Vision and AI

Smart Infant Monitoring System Using Computer Vision and AI

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2023 IEEE International Conference on Electro Information Technology, eIT 2023

作者： Singh, Gurpreet Shekhar, Abhishek Raj Yu, Xinrui Saniie, Jafar Illinois Institute of Technology Embedded Computing and Signal Processing Research Laboratory Department of Electrical and Computer Engineering ChicagoIL United States

ISBN: (纸本)9781665493765

The new era of technology is being greatly influenced by the field of artificial intelligence. computer vision and deep learning have become increasingly important due to their ability to process vast amounts of data and provide insights and solutions in a variety of fields. computer vision, deep learning and signal analysis have been used in a growing number of applications and services including smart devices, image, and speech recognition, healthcare, etc., one such device is an infant monitoring system. It monitors the daily activities of the infant such as their sleeping patterns, sounds, and movements. In this paper, deep learning and computer vision libraries were used to develop algorithms to detect whether the infant was in any uncomfortable situation such as sleeping on its back, face being covered and whether the infant was awake. The smart infant monitoring system detects the infant's unsafe resting situation in real time and sent immediate alerts to the caretaker's device. This paper presents the design flow of a smart infant monitoring system consisting of a night vision camera, a Jetson Nano, and a Wi-Fi internet connection. The pose estimation and awake detection algorithms were developed and tested successfully for different infant resting/sleeping situations. The smart infant monitoring system provides significant benefits for safety and an improved understanding of infants' sleep patterns and behavior. © 2023 IEEE.

关键词： Face recognition

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Dielectric Resonator Magnetoelectric Dipole Arrays with Low Cross Polarization,Backward Radiation,and Mutual Coupling for MIMO Base Station Applications

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China Communications 2024年第6期21卷 290-304页

作者： Song Simin Da Yiran Qian Bingyi Huang Xiaoyu Chen Xiaoming Li Yingsong Ahmed A.Kishk School of Information and Communications Engineering Xi’an Jiaotong UniversityXi’an 710049China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui UniversityHefei 230039China Department of Electrical and Computer Engineering Concordia UniversityMontrealQC H3G 1M8Canada

Dielectric resonator magnetoelectric dipole(DRMED)arrays with enhanced isolation,reduced cross-polarization,and backward radiation are proposed for base station(BS)*** proposed antenna comprises an elevated dielectric resonator antenna(DRA)on a small metal plate above a sizeable common ground *** DRA is designed in its T Eδ11 mode,acting like a magnetic *** surface current excited by the differential probes flowing on the small ground plane is equivalent to an electric *** these two equivalent dipoles are orthogonal,they have the magnetoelectric dipole characteristics with reduced backward ***,the small ground planes can be treated as decoupling structures to provide a neutralization path to cancel the original coupling path.A linearly-polarized 4-element prototype array was verified experimentally in previous ***,a dual-polarized DRMED antenna is presented to construct a 2-element and 4×4 array for BS *** investigate its MIMO performance,sophisticated multi-cell scenario simulations are carried *** using the proposed dualpolarized DRMED array,the cellular system capacityis improved by 118.6%compared to a conventional DRA *** significant MIMO system improvement is mainly due to the reduced backward radiation and,therefore,reduced inter-cell *** align well with the simulations.

关键词： backward radiation dielectric resonator antennas(DRAs) isolation magnetoelectric-dipole(ME-dipole)antennas

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Robust DNN-Enabled Cooperative Spectrum Sensing 32

Robust DNN-Enabled Cooperative Spectrum Sensing

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32nd International Conference on Software, Telecommunications and computer Networks, SoftCOM 2024

作者： Serghini, Omar Serrano, Salvatore Semlali, Hayat Maali, Asmaa University of Messina Laboratory of Digital Signal Processing Department of Engineering Messina Italy Cadi Ayyad University Laboratory of Electrical Systems Energy Efficiency and Telecommunications Marrakesh Morocco Royal Naval School of Casablanca Casablanca Morocco

ISBN: (纸本)9789532901382

In this contribution, we investigate cooperative spectrum sensing in cognitive radio networks using a deep neural network approach. Our proposed architecture leverages the strengths of both a one dimentional convolutional neural network and a bidirectional long short-term memory network. This combined approach aims to effectively learn the activity patterns of primary users for accurate spectrum sensing. The signal generation process incorporates diverse modulation techniques commonly used in communication systems. Additionally, the channel model considers complexities encountered in real-world deployments. These complexities mimic the challenges of multipath propagation and relative motion, making the training data more realistic. The performance of the proposed deep neural network is compared to benchmark methods using only CNN or LSTM at the secondary user level. We evaluate the models using receiver operating characteristic curves and probability of detection for various signal-to-noise ratio levels. The simulation results showcase the effectiveness of the proposed DNN, achieving superior probability of detection compared to the benchmarks and potentially surpassing state-of-the-art methods, particularly demonstrating very good performance at very low SNR values. © 2024 University of Split, FESB.

关键词： signal to noise ratio

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Scalable weighted-cumulated methodology for fatigue estimation

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Research on Biomedical engineering 2022年第4期38卷 1087-1101页

作者： de Oliveira Nascimento, Francisco Assis de Araújo Rocha, Valdinar do Carmo, Jake Carvalho Group of Digital Signal Processing Department of Electrical Engineering University of Brasília DF BrasíliaCO 04465 Brazil Laboratory of Biological Signal Processing Faculty of Physical Education University of Brasília DF BrasíliaCO 04465 Brazil

Purpose: The objective measurement of muscle fatigue through the analysis of surface electromyographic signals (S-EMG) has been the object of study in recent decades. The use of S-EMG is interesting because it allows accessing the muscular structure and function through the use of a noninvasive technique. This is a subject of interest to many areas of science such as clinical and orthopedic medicine, biomechanics, physiotherapy and rehabilitation, telemedicine, control of interfaces, intelligent prosthetics, and exoskeletons control and for expert systems to support medical diagnosis to neuromuscular diseases. Changes in the spectral signature of the S-EMG signal such as spectral shift for low frequencies and the increase in the dynamic range of the signal indicate the installation of the biological phenomenon of fatigue. For instance, classical techniques such as zero-crossing, median frequency (MDF), and mean power frequency (MPF) are able to perceive the spectral shift in S-EMG signals. On the other hand, techniques such as root mean square (RMS) values can only perceive the variation in the dynamic range of the S-EMG signal. Methods: In this work, new mathematical models for the objective assessment of muscle fatigue are presented. We sought to design models for objective fatigue estimators that simultaneously perceive the spectral shift for low frequencies and the increase in the dynamic range in the S-EMG signal during the instauration of the fatigue process. The new approach is integrated to the weighted-cumulated methodology framework previously proposed. Three new objective muscle fatigue estimators were conceived: the scalable weighted-cumulated Fourier estimator, the weighted-cumulated wavelet estimator (SWCW), and the weighted-cumulated p-side lobe attenuation algorithm (p-SL). Results: To evaluate the proposed tools based on the scalable weighted-cumulated methodology, we investigated two dynamic protocols with muscle fatigue production. The S-EMG signa

关键词： Wavelet transforms

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Fine-tuning Specialized NER Model for Symptom Extraction from Slovenian Medical Texts

Fine-tuning Specialized NER Model for Symptom Extraction fro...

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International Conference on Mathematics and computers in Sciences and in Industry (MCSI)

作者： Rigon Sallauka Umut Arioz Izidor Mlakar Laboratory of Digital Signal Processing University of Maribor Faculty of Electrical Engineering and Computer Science Maribor Slovenia

ISBN: (数字)9798350377224

ISBN: (纸本)9798350377231

关键词： Adaptation models Translation Accuracy Text analysis Annotations Computational modeling Data models Mathematical models Reliability Tuning

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Artificial Intelligence System for Emotion Recognition and Text Analytics

Artificial Intelligence System for Emotion Recognition and T...

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2022 IEEE International Conference on Electro Information Technology, eIT 2022

作者： Chaudhari, Namrata Agarwal, Reshu Narwade, Meghna Yu, Xinrui Saniie, Jafar Illinois Institute of Technology Embedded Computing and Signal Processing Department of Electrical and Computer Engineering Research Laboratory ChicagoIL United States

ISBN: (纸本)9781665480093

Harnessing the power of emotional intelligence by analyzing a person's behavioral and linguistic skills can help humans improve their approach to social interactions. In this paper, we propose an artificial intelligence-based stand-alone system that will allow us to classify and analyze facial expressions in real-time and perform sentiment analysis by examining the body of the text (extracted from audio) to understand the opinion expressed by it. This helps us provide a deeper understanding of how humans really feel at a given time. The proposed system uses a deep neural network (DNN) for classifying eight basic emotions based on features extracted from facial expressions and uses pretrained sentiment analysis tools to quantify text (extracted from audio) based on polarity. The system is implemented by extracting the audio and visual cues from real-time scenarios and using these extracted cues to perform facial expression recognition and text sentiment analysis. The integrated system extracts video and audio simultaneously with a frame rate of 4-5 fps. The facial emotion detection system successfully detects facial expressions of faces detected in real-time video with an accuracy of about 86.75%. The speech extracted is converted to text, cleaned, and processed to determine if the attitude of the speaker in a given situation is positive, negative, or neutral. © 2022 IEEE.

关键词： Deep neural networks

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High Precision Analog Gauge Reader Using Optical Flow and computer Vision

High Precision Analog Gauge Reader Using Optical Flow and Co...

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2022 IEEE International Conference on Electro Information Technology, eIT 2022

作者： Chavan, Shruti Yu, Xinrui Saniie, Jafar Illinois Institute of Technology Embedded Computing and Signal Processing Department of Electrical and Computer Engineering Research Laboratory ChicagoIL United States

ISBN: (纸本)9781665480093

This paper aims at developing algorithms to automate the process of reading analog gauges at different operational industries, healthcare sector and automobiles using Artificial Intelligence (AI) techniques. Proposed algorithms start with video stabilization using optical flow followed by image processing which performs segmentation using HSV color space and morphological operations. Next, Hough transform is applied to determine the dial region and pointer. Using the coordinates locating the pointer in the frame, angle made with minimum valued scale mark is calculated using trigonometry and evaluated reading is displayed in the form of text and a progress bar. The proposed algorithms for Analog Gauge Reader (AGR) is executed using open-source libraries such as OpenCV, NumPy, PIL with Python programming and it is developed in the PyCharm environment. The experimental results show significant decrease in the error with the introduction of image preprocessing and the generalizability of the algorithm to different types of analog gauges captured in different conditions of illuminance. The accuracy and precision of the algorithms is 99% to 100% in the experimental studies. © 2022 IEEE.

关键词： Hough transforms

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