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Electrical and Computer Engineering Commons™
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- Anechoic (1)
- Bitcoin (1)
- Blockchains (1)
- Classification (1)
- Clustering (1)
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- Delay Estimation (1)
- Human-Ear Intelligibility (HEI) (1)
- Information propagation (1)
- Machine learning (1)
- OpenFlow (1)
- Overall-Perceptual Score (OPS) (1)
- Performance (1)
- Relative attenuation (1)
- Security (1)
- Signal Processing (1)
- Software Defined Networks (1)
- Source Separation (1)
- Source-Separation (1)
- Speech (1)
- Target-Perceptual Score (TPS) (1)
- Time-Frequency (1)
- Traffic Classification (1)
Articles 1 - 4 of 4
Full-Text Articles in Electrical and Computer Engineering
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 …
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 …