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Articles 1 - 30 of 106
Full-Text Articles in Signal Processing
Identifying Subject Bias In Wifi-Based Human Activity Recognition Evaluation Methods, Amany Elkelany, Robert J. Ross, Susan Mckeever
Identifying Subject Bias In Wifi-Based Human Activity Recognition Evaluation Methods, Amany Elkelany, Robert J. Ross, Susan Mckeever
Conference papers
WiFi-based Human Activity Recognition (HAR) has emerged as a promising approach for monitoring and analysing human activities in a non-intrusive manner, leveraging WiFi signals for activity classification. Despite advancements, existing WiFi-based HAR research lacks consideration of subject (human) bias. This results in learning models performing well on individuals used in the training samples but failing to generalise to new/unseen subjects, in contrast to known good practices in machine learning. In this paper, we address this oversight directly by systematically examining the evaluation methodology for the WiFi-based HAR context. Specifically, we investigate the impact of Leave-One-Subject-Out Cross-Validation (LOSOCV) in a hybrid …
Energy Efficiency And Fault Tolerance In Open Ran And Future Internet, Saish Urumkar, Byrav Ramamurthy, Sachin Sharma
Energy Efficiency And Fault Tolerance In Open Ran And Future Internet, Saish Urumkar, Byrav Ramamurthy, Sachin Sharma
Conference papers
Open Radio Access Networks (Open RAN) repre- sent a promising technological advancement within the realm of the future internet. Research efforts are currently directed towards enhancing energy efficiency and fault tolerance, which are critical aspects for both Open RAN and the future internet landscape. In the context of energy saving in Open RAN, there exists a spectrum of methods for achieving energy efficiency. These methods include the toggling of on/off states for different hardware resources such as base station units, distributed units, and radio units. Conversely, for enhancing fault tolerance in Open RAN, Software-Defined Networking (SDN) and OpenFlow based techniques …
Improving Energy Efficiency In Open Ran Through Dynamic Cpu Scheduling, Saish Urumkar, Byrav Ramamurthy, Sachin Sharma
Improving Energy Efficiency In Open Ran Through Dynamic Cpu Scheduling, Saish Urumkar, Byrav Ramamurthy, Sachin Sharma
Conference papers
Open RAN is a promising cellular technology that is currently undergoing extensive research for future wireless radio access networks. Achieving optimal energy efficiency in Open RAN poses a significant challenge. This paper introduces a CPU scheduling algorithm that specifically targets this chal- lenge by optimizing energy consumption at the base station while maintaining optimal performance levels. With the goal of minimizing energy consumption, the proposed algorithm dynamically adjusts the CPU core states, seamlessly switching between active and sleep modes based on the load conditions. To evaluate the algorithm’s effectiveness in terms of energy saving and performance, experimental testing is conducted …
List Of 121 Papers Citing One Or More Skin Lesion Image Datasets, Neda Alipour
List Of 121 Papers Citing One Or More Skin Lesion Image Datasets, Neda Alipour
Other resources
No abstract provided.
Evaluating Large Delay Estimation Techniques For Assisted Living Environments, Swarnadeep Bagchi, Ruairí De Fréin
Evaluating Large Delay Estimation Techniques For Assisted Living Environments, Swarnadeep Bagchi, Ruairí De Fréin
Articles
Abstract Phase wraparound due to large inter-sensor spacings in multi-channel demixing limits the range of relative delays that many time–frequency relative delay estimators can estimate. The performance of a large relative delay estimation method, called the elevatogram, is evaluated in the presence of significant phase wraparound. This paper compares the elevatogram with the popular relative delay estimator used in DUET and the brute-force approach in D-AdRess and analyses its computational efficiency. The elevatogram can accurately estimate relative delays of speech signals of up to 800 samples, whereas DUET and D-AdRess were limited to delays of 7 and 35 samples, given …
An Empirical Comparison Of The Security And Performance Characteristics Of Topology Formation Algorithms For Bitcoin Networks, Muntadher Sallal, Ruairí De Fréin, Ali Malik, Benjamin Aziz
An Empirical Comparison Of The Security And Performance Characteristics Of Topology Formation Algorithms For Bitcoin Networks, Muntadher Sallal, Ruairí De Fréin, Ali Malik, Benjamin Aziz
Articles
There is an increasing demand for digital crypto-currencies to be more secure and robust to meet the following business requirements: (1) low transaction fees and (2) the privacy of users. Nowadays, Bitcoin is gaining traction and wide adoption. Many well-known businesses have begun accepting bitcoins as a means of making financial payments. However, the susceptibility of Bitcoin networks to information propagation delay, increases the vulnerability to attack of the Bitcoin network, and decreases its throughput performance. This paper introduces and critically analyses new network clustering methods, named Locality Based Clustering (LBC), Ping Time Based Approach (PTBC), Super Node Based Clustering …
Acoustic Source Localization Using Straight Line Approximations, Swarnadeep Bagchi, Ruairí De Fréin
Acoustic Source Localization Using Straight Line Approximations, Swarnadeep Bagchi, Ruairí De Fréin
Conference papers
The short paper extends an acoustic signal delay estimation method to general anechoic scenario using image processing techniques. The technique proposed in this paper localizes acoustic speech sources by creating a matrix of phase versus frequency histograms, where the same phases are stacked in appropriate bins. With larger delays and multiple sources coexisting in the same matrix, it becomes cluttered with activated bins. This results in high intensity spots on the spectrogram, making source discrimination difficult. In this paper, we have employed morphological filtering, chain-coding and straight line approximations to ignore noise and enhance the target signal features. Lastly, Hough …
Automatic Contact Tracing Using Bluetooth Low Energy Signals And Imu Sensor Readings, Suriyadeepan Ramamoorthy, Joyce Mahon, Michael O'Mahony, Jean Francois Itangayenda, Tendai Mukande, Tlamelo Makati
Automatic Contact Tracing Using Bluetooth Low Energy Signals And Imu Sensor Readings, Suriyadeepan Ramamoorthy, Joyce Mahon, Michael O'Mahony, Jean Francois Itangayenda, Tendai Mukande, Tlamelo Makati
Other resources
In this report, we present our solution to the challenge provided by the SFI Centre for Machine Learning (ML-Labs) in which the distance between two phones needs to be estimated. It is a modified version of the NIST Too Close For Too Long (TC4TL) Challenge, as the time aspect is excluded. We propose a feature-based approach based on Bluetooth RSSI and IMU sensory data, that outperforms the previous state of the art by a significant margin, reducing the error down to 0.071. We perform an ablation study of our model that reveals interesting insights about the relationship between the distance …
Soft-Mask De-Mixing For Anechoic Mixtures, Swarnadeep Bagchi, Ruairí De Fréin
Soft-Mask De-Mixing For Anechoic Mixtures, Swarnadeep Bagchi, Ruairí De Fréin
Articles
This paper extends a computationally efficient, soft-mask based source separation (SS) technique called Redress, to anechoic mixing scenarios. SS methods are an integral part of hearing aid research. We call the resulting method D-Redress. In its original form, Redress was intended for instantaneous mixing scenarios. Numerical evaluations demonstrate that soft-mask based techniques reduce the level of artifacts in the separated speech. Monte Carlo trials on 1000 real speech mixtures demonstrate that the D-Redress successfully extends Redress in terms of Overall-Perceptual (OPS), Target-Perceptual (TPS) scores and Human-Ear Intelligibility (HEI).
Ml-Based Online Traffic Classification For Sdns, Mohammed Nsaif, Gergely Kovasznai, Mohammed Abboosh, Ali Malik, Ruairí De Fréin
Ml-Based Online Traffic Classification For Sdns, Mohammed Nsaif, Gergely Kovasznai, Mohammed Abboosh, Ali Malik, Ruairí De Fréin
Articles
Traffic classification is a crucial aspect for Software-Defined Networking functionalities. This paper is a part of an on-going project aiming at optimizing power consumption in the environment of software-defined datacenter networks. We have developed a novel routing strategy that can blindly balance between the power consumption and the quality of service for the incoming traffic flows. In this paper, we demonstrate how to classify the network traffic flows so that the quality of service of each flow-class can be guaranteed efficiently. This is achieved by creating a dataset that encompasses different types of network traffic such as video, VoIP, game …
Sediqa: Sound Emitting Document Image Quality Assessment In A Reading Aid For The Visually Impaired, Jane Courtney
Sediqa: Sound Emitting Document Image Quality Assessment In A Reading Aid For The Visually Impaired, Jane Courtney
Articles
For visually impaired people (VIPs), the ability to convert text to sound can mean a new level of independence or the simple joy of a good book. With significant advances in optical character recognition (OCR) in recent years, a number of reading aids are appearing on the market. These reading aids convert images captured by a camera to text which can then be read aloud. However, all of these reading aids suffer from a key issue—the user must be able to visually target the text and capture an image of sufficient quality for the OCR algorithm to function—no small task …
The Effects Of The Transient And Performance Loss Rates On Pv Output Performance, Chibuisi Chinasaokwu Okorieimoh, Brian Norton, Michael Conlon
The Effects Of The Transient And Performance Loss Rates On Pv Output Performance, Chibuisi Chinasaokwu Okorieimoh, Brian Norton, Michael Conlon
Conference papers
Solar photovoltaic (PV) panels experience long-term performance degradation as compared to their initial performance, resulting in lower like-per-like efficiencies and performance ratios. Manufacturers of solar photovoltaic modules normally guarantee a lifespan of more than 20 years. To meet such commitments, it is important to monitor and mitigate PV module degradation during this period, as well as beyond, to recognize maintenance and repair needs. Solar PV modules degrade over time, becoming less effective, less reliable, and eventually unusable. The effects of transient and performance loss rates on the output performance of polycrystalline silicon (p-Si) solar PV modules are the focus of …
Extending Instantaneous De-Mixing Algorithms To Anechoic Mixtures, Swarnadeep Bagchi, Ruairí De Fréin
Extending Instantaneous De-Mixing Algorithms To Anechoic Mixtures, Swarnadeep Bagchi, Ruairí De Fréin
Conference papers
The AdRess algorithm separates sources that are mixed using stereo, pan-mixing in a computationally efficient way. Pan-mixing gives the sources a location in the stereo field by introducing a relative attenuation between the versions of the sources that appear on each channel. AdRess achieves separation by constructing only a frequency-attenuation matrix. We introduce a new algorithm called Delayed-AdRess (D-AdRess), where, in addition to the frequency-attenuation matrix, two other matrices namely, frequency-delay and time-delay are used to separate sources from anechoic mixtures. By anechoic mixtures, we mean mixing scenarios where both attenuation and delays are experienced by the source signals.
An Lpc Pole Processing Method For Enhancing The Identification Of Dominant Spectral Features, Jin Xu, Mark Davis, Ruairí De Fréin
An Lpc Pole Processing Method For Enhancing The Identification Of Dominant Spectral Features, Jin Xu, Mark Davis, Ruairí De Fréin
Articles
This paper proposes a new time-resolved spectral analysis method based on a modification to the linear predictive coding (LPC) method for enhancing the identification of the dominant frequencies of a signal. The method described here is based on a z-plane analysis of the LPC poles. These poles are used to produce a series of reduced order filter transfer functions which can accurately identify and estimate the frequency of the dominant spectral features. The standard LPC method has been shown to suffer from a sensitivity to noise and its performance is dependent on the filter order. The proposed method can …
An Lpc Pole Processing Method For Enhancing The Identification Of Dominant Spectral Features, Jin Xu, Mark Davis, Ruairí De Fréin
An Lpc Pole Processing Method For Enhancing The Identification Of Dominant Spectral Features, Jin Xu, Mark Davis, Ruairí De Fréin
Articles
This paper proposes a new time-resolved spectral analysis method based on a modification to the Linear Predictive Coding (LPC) method for enhancing the identification of the dominant frequencies of a signal. The method described here is based on a z-plane analysis of the LPC poles. These poles are used to produce a series of reduced order filter transfer functions which can accurately identify and estimate the frequency of the dominant spectral features. The standard LPC method has been shown to suffer from a sensitivity to noise and its performance is dependent on the filter order. The proposed method can accurately …
The Discrete Fourier Transform - A Practical Approach, David Dorran
The Discrete Fourier Transform - A Practical Approach, David Dorran
Articles
These notes on the Discrete Fourier Transform include numerous practical examples that make use of audio signals.
Power-Weighted Lpc Formant Estimation, Ruairí De Fréin
Power-Weighted Lpc Formant Estimation, Ruairí De Fréin
Conference papers
A power-weighted formant frequency estimation procedure based on Linear Predictive Coding (LPC) is presented. It works by pre-emphasizing the dominant spectral components of an input signal, which allows a subsequent estimation step to extract formant frequencies with greater accuracy. The accuracy of traditional LPC formant estimation is improved by this new power-weighted formant estimator for different classes of synthetic signals and for speech. Power-weighted LPC significantly and reliably outperforms LPC and variants of LPC at the task of formant estimation using the VTR formants dataset, a database consisting of the Vocal Tract Resonance (VTR) frequency trajectories obtained by human experts …
Cleanpage: Fast And Clean Document And Whiteboard Capture, Jane Courtney
Cleanpage: Fast And Clean Document And Whiteboard Capture, Jane Courtney
Articles
The move from paper to online is not only necessary for remote working, it is also significantly more sustainable. This trend has seen a rising need for the high-quality digitization of content from pages and whiteboards to sharable online material. However, capturing this information is not always easy nor are the results always satisfactory. Available scanning apps vary in their usability and do not always produce clean results, retaining surface imperfections from the page or whiteboard in their output images. CleanPage, a novel smartphone-based document and whiteboard scanning system, is presented. CleanPage requires one button-tap to capture, identify, crop, and …
Remedying Sound Source Separation Via Azimuth Discrimination And Re-Synthesis, Ruairí De Fréin
Remedying Sound Source Separation Via Azimuth Discrimination And Re-Synthesis, Ruairí De Fréin
Conference papers
Commercially recorded music since the 1950s has been mixed down from many input sound sources to a two- channel reproduction of these sources. The effect of this approach is to assign sources to locations in a stereo field using a pan- position for each source. The Adress algorithm is a popular way of extracting individual music sound sources from a stereo mixture. A drawback of the Adress algorithm is that when time- frequency components in the stereo mixture are shared between two or more sources, calculating the inter-aural intensity scaling parameter for each source for that time-frequency component is challenging. …
New Robust Lpc-Based Method For Time-Resolved Morphology Of High-Noise Multiple Frequency Signals, Jin Xu, Ruairí De Fréin, Mark Davis
New Robust Lpc-Based Method For Time-Resolved Morphology Of High-Noise Multiple Frequency Signals, Jin Xu, Ruairí De Fréin, Mark Davis
Conference papers
This paper introduces a new time-resolved spectral analysis method based on the Linear Prediction Coding (LPC) method that is particularly suited to the study of the dynamics of low Signal-to-noise Ratio (SNR) signals comprising multiple frequency components. One of the challenges of the time-resolved spectral method is that they are limited by the Heisenberg-Gabor uncertainty principle. Consequently, there is a trade-off between the temporal and spectral resolution. Most of the previous studies are time-averaged methods. The proposed method is a parameterisation method which can directly extract the dominant formants. The method is based on a z-plane analysis of the poles …
Remedying Sound Source Separation Via Azimuth Discrimination And Re-Synthesis, Ruairí De Fréin
Remedying Sound Source Separation Via Azimuth Discrimination And Re-Synthesis, Ruairí De Fréin
Conference papers
Commercially recorded music since the 1950s has been mixed down from many input sound sources to a two-channel reproduction of these sources. The effect of this approach is to assign sources to locations in a stereo field using a pan-position for each source. The Adress algorithm is a popular way of extracting individual music sound sources from a stereo mixture. A drawback of the Adress algorithm is that when time-frequency components in the stereo mixture are shared between two or more sources, calculating the inter-aural intensity scaling parameter for each source for that time-frequency component is challenging. We show how …
A Robust Lpc Filtering Method For Time-Resolved Morphology Of Eeg Activity Analysis, Jin Xu, Mark Davis, Ruairí De Fréin
A Robust Lpc Filtering Method For Time-Resolved Morphology Of Eeg Activity Analysis, Jin Xu, Mark Davis, Ruairí De Fréin
Conference Papers
This paper introduces a new time-resolved spectral analysis method based on Linear Prediction Coding (LPC) method that is particularly suited to the study of the dynamics of EEG (Electroencephalogram) activity. The spectral dynamic of EEG signals can be challenging to analyse as they contain multiple frequency components and are often heavily corrupted by noise. Furthermore, the temporal and spectral resolution that can be achieved is limited by the Heisenberg-Gabor uncertainty principle [1]. The method described here is based on a z-plane analysis of the poles of the LPC which allows us to identify and estimate the frequency of the dominant …
Calibration To Mitigate Near-Field Antennas Effects For A Mimo Radar Imaging System, Ha Hoang, Matthias John, Patrick Mcevoy, Max Ammann
Calibration To Mitigate Near-Field Antennas Effects For A Mimo Radar Imaging System, Ha Hoang, Matthias John, Patrick Mcevoy, Max Ammann
Articles
A calibration method for a high-resolution hybrid MIMO turntable radar imaging system is presented. A line of small metal spheres is employed as a test pattern in the calibration process to measure the position shift caused by undesired antenna effects. The unwanted effects in the antenna near-field responses are analysed, modelled and significantly mitigated based on the symmetry and differences in the responses of the MIMO configuration.
Re-Annotation Of Cough Events In The Ami Corpus, Paul Leamy, Damon Berry, David Dorran, Ted Burke
Re-Annotation Of Cough Events In The Ami Corpus, Paul Leamy, Damon Berry, David Dorran, Ted Burke
Conference papers
Cough sounds act as an important indicator of an individual's physical health, often used by medical professionals in diagnosing a patient's ailments. In recent years progress has been made in the area of automatically detecting cough events and, in certain cases, automatically identifying the ailment associated with a particular cough sound. Ethical and sensitivity issues associated with audio recordings of coughs makes it more difficult for this data to be made publicly available. However, without the public availability of a reliable database of cough sounds, developments in the area of audio event detection are likely to be hampered. The purpose …
Distance-Based Cluster Head Election For Mobile Sensing, Ruairí De Fréin, Liam O'Farrell
Distance-Based Cluster Head Election For Mobile Sensing, Ruairí De Fréin, Liam O'Farrell
Conference papers
Energy-efficient, fair, stochastic leader-selection algorithms are designed for mobile sensing scenarios which adapt the sensing strategy depending on the mobile sensing topology. Methods for electing a cluster head are crucially important when optimizing the trade-off between the number of peer-to- peer interactions between mobiles and client-server interactions with a cloud-hosted application server. The battery-life of mobile devices is a crucial constraint facing application developers who are looking to use the convergence of mobile computing and cloud computing to perform environmental sensing. We exploit the mobile network topology, specifically the location of mobiles with respect to the gateway device, to stochastically …
State Acquisition In Computer Networks, Ruairí De Fréin
State Acquisition In Computer Networks, Ruairí De Fréin
Conference papers
We establish that State Acquisition should be per- formed in networks at a rate which is consistent with the rate-of-change of the element or service being observed. We demonstrate that many existing monitoring and service-level prediction tools do not acquire network state in an appropriate manner. To address this challenge: (1) we define the rate-of- change of different applications; (2) we use methods for analysis of unevenly spaced time series, specifically, time series arising from video and voice applications, to estimate the rate-of-change of these services; and finally, (3) we demonstrate how to acquire network state accurately for a number …
Ambiqual – A Full Reference Objective Quality Metric For Ambisonic Spatial Audio, Miroslaw Narbutt, Andrew Allen, Jan Skoglund, Michael Chinen, Andrew Hines
Ambiqual – A Full Reference Objective Quality Metric For Ambisonic Spatial Audio, Miroslaw Narbutt, Andrew Allen, Jan Skoglund, Michael Chinen, Andrew Hines
Conference papers
Streaming spatial audio over networks requires efficient encoding techniques that compress the raw audio content without compromising quality of experience. Streaming service providers such as YouTube need a perceptually relevant objective audio quality metric to monitor users’ perceived quality and spatial localization accuracy. In this paper we introduce a full reference objective spatial audio quality metric, AMBIQUAL, which assesses both Listening Quality and Localization Accuracy. In our solution both metrics are derived directly from the B-format Ambisonic audio. The metric extends and adapts the algorithm used in ViSQOLAudio, a full reference objective metric designed for assessing speech and audio quality. …
Tiled Time Delay Estimation In Mobile Cloud Computing Environments, Ruairí De Fréin
Tiled Time Delay Estimation In Mobile Cloud Computing Environments, Ruairí De Fréin
Conference papers
We present a tiled delay estimation technique in the context of Mobile Cloud Computing (MCC) environments. We examine its accuracy in the presence of multiple sources for (1) sub-sample delays and also (2) in the presence of phase-wrap around. Phase wrap-around is prevalent in MCC because the separation of acoustic sources may be large. We show that tiling a histogram of instantaneous phase estimates can improve delay estimates when phase-wrap around is sig- nificantly present and also when multiple sources are present. We report that error in the delay estimator is generally less than 5% of a sample, when the …
Objective Assessment Of Perceptual Audio Quality Using Visqolaudio, Colm Sloan, Damien Kelly, Naomi Harte, Anil C. Kokaram, Andrew Hines
Objective Assessment Of Perceptual Audio Quality Using Visqolaudio, Colm Sloan, Damien Kelly, Naomi Harte, Anil C. Kokaram, Andrew Hines
Conference papers
Digital audio broadcasting services transmit substantial amounts of data that is encoded to minimize bandwidth whilst maximizing user quality of experience. Many large service providers continually alter codecs to improve the encoding process. Performing subjective tests to validate each codec alteration would be impractical, necessitating the use of objective perceptual audio quality models. This paper evaluates the quality scores from ViSQOLAudio, an objective perceptual audio quality model, against the quality scores of PEAQ, POLQA, and PEMO-Q on three datasets containing fullband audio encoded with a variety of codecs and bitrates. The results show that ViSQOLAudio was more accurate than all …
Power-Weighted Divergences For Relative Attenuation And Delay Estimation, Ruairí De Fréin, Scott T. Rickard Prof
Power-Weighted Divergences For Relative Attenuation And Delay Estimation, Ruairí De Fréin, Scott T. Rickard Prof
Articles
Power-weighted estimators have recently been proposed for relative attenuation and delay estimation in blind source separation. Their provenance lies in the observation that speech is approximately windowed-disjoint orthogonal (WDO) in the time-frequency (TF) domain; it has been reported that using WDO, derived from TF representations of speech, improves mixing parameter estimation. We show that power-weighted relative attenuation and delay estimators can be derived from a particular case of a weighted Bregman divergence. We then propose a wider class of estimators, which we tune to give better parameter estimates for speech.