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Готові списки джерел за темами / Single value decomposition

Добірка наукової літератури з теми "Single value decomposition"

Автор: Grafiati

Опубліковано: 10 грудня 2022

Оновлено: 28 січня 2023

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Статті в журналах з теми "Single value decomposition"

1

KOH, MIN-SUNG. "A QUINTET SINGULAR VALUE DECOMPOSITION THROUGH EMPIRICAL MODE DECOMPOSITIONS." Advances in Adaptive Data Analysis 06, no. 02n03 (April 2014): 1450010. http://dx.doi.org/10.1142/s1793536914500101.

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A particular quintet singular valued decomposition (Quintet-SVD) is introduced in this paper via empirical mode decompositions (EMDs). The Quintet-SVD results in four specific orthogonal matrices with a diagonal matrix of singular values. Furthermore, this paper shows relationships between the Quintet-SVD and traditional SVD, generalized low rank approximations of matrices (GLRAM) of one single matrix, and EMDs. One application of the Quintet-SVD for speech enhancement is shown and compared with an application of traditional SVD.

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2

Muafak Rashied, Manar. "Iraqi Plate Number Recognition Using Single Value Decomposition (SVD)." Diyala Journal For Pure Science 14, no. 2 (April 1, 2018): 140–52. http://dx.doi.org/10.24237/djps.1402.391a.

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3

Zhao, Xuezhi, and Bangyan Ye. "Separation of Single Frequency Component Using Singular Value Decomposition." Circuits, Systems, and Signal Processing 38, no. 1 (May 25, 2018): 191–217. http://dx.doi.org/10.1007/s00034-018-0852-2.

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4

Rahul, Mayur, Vinod Kumar, Vikash Yadav, and Rishabh. "Movie Recommender System using Single Value Decomposition and K-means Clustering." IOP Conference Series: Materials Science and Engineering 1022 (January 19, 2021): 012100. http://dx.doi.org/10.1088/1757-899x/1022/1/012100.

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5

Lantsov, V. N., and I. S. Melnik. "Development of an equalizer using singular value decomposition." Journal of Physics: Conference Series 2373, no. 2 (December 1, 2022): 022030. http://dx.doi.org/10.1088/1742-6596/2373/2/022030.

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Abstract The problems of wireless communication systems are investigated. A model and hardware implementation of a system for estimating and correcting amplitude distortions of a radio signal using an algorithm based on Singular Value Decomposition (SVD) has been developed. The analysis of the efficiency of the system when processing the LTE signal is performed. The model was obtained in the Matlab system with modeling the propagation environment, as well as time and frequency tuning blocks using the LTE Toolbox library. FPGA resources with hardware implementation are estimated. Testing the signal-to-noise ratio of the two-antenna equalizer revealed its advantage over the single-antenna configuration by 2.8 dB.

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6

Kanjilal, P. P., S. Palit, and G. Saha. "Fetal ECG extraction from single-channel maternal ECG using singular value decomposition." IEEE Transactions on Biomedical Engineering 44, no. 1 (1997): 51–59. http://dx.doi.org/10.1109/10.553712.

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7

Jackson, G. M., I. M. Mason, and S. A. Greenhalgh. "Principal component transforms of triaxial recordings by singular value decomposition." GEOPHYSICS 56, no. 4 (April 1991): 528–33. http://dx.doi.org/10.1190/1.1443068.

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Polarization analysis can be achieved efficiently by treating a time window of a single‐station triaxial recording as a matrix and doing a singular value decomposition (SVD) of this seismic data matrix. SVD of the triaxial data matrix produces an eigenanalysis of the data covariance (cross‐energy) matrix and a rotation of the data onto the directions given by the eigenanalysis (Karhunen‐Loève transform), all in one step. SVD provides a complete principal components analysis of the data in the analysis time window. Selection of this time window is crucial to the success of the analysis and is governed by three considerations: the window should contain only one arrival; the window should be such that the signal‐to‐noise ratio is maximized; and the window should be long enough to be able to discriminate random noise from signal. The SVD analysis provides estimates of signal, signal polarization directions, and noise. An F‐test is proposed which gives the confidence level for the hypothesis of rectilinear polarization. This paper illustrates the analysis and interpretation of synthetic rectilinearly and elliptically polarized arrivals at a single triaxial station by SVD.

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8

Feng, Feng, Hamido Fujita, Young Bae Jun, and Madad Khan. "Decomposition of Fuzzy Soft Sets with Finite Value Spaces." Scientific World Journal 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/902687.

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The notion of fuzzy soft sets is a hybrid soft computing model that integrates both gradualness and parameterization methods in harmony to deal with uncertainty. The decomposition of fuzzy soft sets is of great importance in both theory and practical applications with regard to decision making under uncertainty. This study aims to explore decomposition of fuzzy soft sets with finite value spaces. Scalar uni-product and int-product operations of fuzzy soft sets are introduced and some related properties are investigated. Usingt-level soft sets, we define level equivalent relations and show that the quotient structure of the unit interval induced by level equivalent relations is isomorphic to the lattice consisting of allt-level soft sets of a given fuzzy soft set. We also introduce the concepts of crucial threshold values and complete threshold sets. Finally, some decomposition theorems for fuzzy soft sets with finite value spaces are established, illustrated by an example concerning the classification and rating of multimedia cell phones. The obtained results extend some classical decomposition theorems of fuzzy sets, since every fuzzy set can be viewed as a fuzzy soft set with a single parameter.

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9

Barnova, Katerina, Radana Kahankova, Rene Jaros, Martina Litschmannova, and Radek Martinek. "A comparative study of single-channel signal processing methods in fetal phonocardiography." PLOS ONE 17, no. 8 (August 19, 2022): e0269884. http://dx.doi.org/10.1371/journal.pone.0269884.

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Fetal phonocardiography is a non-invasive, completely passive and low-cost method based on sensing acoustic signals from the maternal abdomen. However, different types of interference are sensed along with the desired fetal phonocardiography. This study focuses on the comparison of fetal phonocardiography filtering using eight algorithms: Savitzky-Golay filter, finite impulse response filter, adaptive wavelet transform, maximal overlap discrete wavelet transform, variational mode decomposition, empirical mode decomposition, ensemble empirical mode decomposition, and complete ensemble empirical mode decomposition with adaptive noise. The effectiveness of those methods was tested on four types of interference (maternal sounds, movement artifacts, Gaussian noise, and ambient noise) and eleven combinations of these disturbances. The dataset was created using two synthetic records r01 and r02, where the record r02 was loaded with higher levels of interference than the record r01. The evaluation was performed using the objective parameters such as accuracy of the detection of S1 and S2 sounds, signal-to-noise ratio improvement, and mean error of heart interval measurement. According to all parameters, the best results were achieved using the complete ensemble empirical mode decomposition with adaptive noise method with average values of accuracy = 91.53% in the detection of S1 and accuracy = 68.89% in the detection of S2. The average value of signal-to-noise ratio improvement achieved by complete ensemble empirical mode decomposition with adaptive noise method was 9.75 dB and the average value of the mean error of heart interval measurement was 3.27 ms.

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10

Acosta, Martha N., Edgar Gomez, Francisco Gonzalez-Longatt, Manuel A. Andrade, Ernesto Vazquez, and Emilio Barocio. "Single Value Decomposition to Estimate Critical Clearing Time of a Power System Using Measurements." IEEE Access 9 (2021): 125999–6010. http://dx.doi.org/10.1109/access.2021.3111006.

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Дисертації з теми "Single value decomposition"

1

Morrison, Adrian Franklin. "An Efficient Method for Computing Excited State Properties of Extended Molecular Aggregates Based on an Ab-Initio Exciton Model." The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1509730158943602.

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2

Liao, Shin-Chiao, and 廖信樵. "Fetal ECG Separation from Single-Channel MaternalECG Using Singular Value Decomposition." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/63933774416311150367.

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碩士
中原大學
電機工程研究所
94
Health of fetal is the most important concern of pregnant women and gynecologist, and fetal ECG (F-ECG) is an index to determine the health of fetal. In general, using non-invent fetal electrocardiogram(FECG) monitoring system to observe fetal ECG is very convenient. However signals obtained from maternal abdomen are contaminated by maternal ECG (M-ECG), and interference from electric device. Therefore, if we want to obtain fetal ECG, we have to remove these non-demand signals. In order to remove the non-demand signals, our proposed method exploits this feature for selective separation of M-ECG and F-ECG components by formulating the problem in the singular value decomposition (SVD) framework. In this paper, in order to obtain QRS wavelets we used filter to remove the interference low-frequency trend component and reduce interference of M-ECG’s T wavelet. Then we used the Singular Value Ratio (SVR) spectrum, developed on the basis of the SVD, to detect the periodic components. SVR spectrum can provide an estimate of the period length of the most dominant periodic component present in any signal. Follow we according to the periodic length obtain a spectrogram matrix. Final we used Short Time Fourier Transform (STFT) and SVD to separate F-ECG.

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3

Madeira, João Falé de Carvalho. "High Performance Single Carrier Schemes for Massive MIMO Systems." Master's thesis, 2019. http://hdl.handle.net/10362/68456.

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As the demands for faster and cheaper telecommunication systems continue to grow, so to do the demands for more efficient and secure systems. There have been several solutions proposed, with the most commonly accepted ones employing Massive Multiple Input, Multiple Output (mMIMO), featuring large arrays of antennas. The downside of these systems lies mainly in the need for computationally heavy channel equalization algorithms and the high hardware requirements, namely due to the need of many Power Amplifiers (PAs), Analog-to-Digital Converters (ADCs) and Digital-to-Analog Converters (DACs). This work analyses receivers that can handle these downsides, beginning with the low complexity equalization receivers Maximal-Ratio Detector (MRD) and Equal-Gain Detector (EGD), that can lower the equalization’s computation time. Then a Singular Value Decomposition (SVD) receiver is studied, with a proposed interleaving scheme to allow for equal performance on all streams, combined with a scheme for estimating and cancelling the non-linear distortion to reduce the impact of cheaper and more powerefficient PAs. These receivers are then improved with the introduction of an error correcting convolutional code. Lastly, it is demonstrated that the SVD receiver can be appealing as a solution for Physical Layer Security (PLS) in mMIMO systems.

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4

Ghous, Hamid. "Building a robust clinical diagnosis support system for childhood cancer using data mining methods." Thesis, 2016. http://hdl.handle.net/10453/90061.

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University of Technology Sydney. Faculty of Engineering and Information Technology.
Progress in understanding core pathways and processes of cancer requires thorough analysis of many coding and noncoding regions of the genome. Data mining and knowledge discovery have been applied to datasets across many industries, including bioinformatics. However, data mining faces a major challenge in its application to bioinformatics: the diversity and dimensionality of biomedical data. The term ‘big data’ was applied to the clinical domain by Yoo et al. (2014), specifically referring to single nucleotide polymorphism (SNP) and gene expression data. This research thesis focuses on three different types of data: gene-annotations, gene expression and single nucleotide polymorphisms. Genetic association studies have led to the discovery of single genetic variants associated with common diseases. However, complex diseases are not caused by a single gene acting alone but are the result of complex linear and non-linear interactions among different types of microarray data. In this scenario, a single gene can have a small effect on disease but cannot be the major cause of the disease. For this reason there is a critical need to implement new approaches which take into account linear and non-linear gene-gene and patient-patient interactions that can eventually help in diagnosis and prognosis of complex diseases. Several computational methods have been developed to deal with gene annotations, gene expressions and SNP data of complex diseases. However, analysis of every gene expression and SNP profile, and finding gene-to-gene relationships, is computationally infeasible because of the high-dimensionality of data. In addition, many computational methods have problems with scaling to large datasets, and with overfitting. Therefore, there is growing interest in applying data mining and machine learning approaches to understand different types of microarray data. Cancer is the disease that kills the most children in Australia (Torre et al., 2015). Within this thesis, the focus is on childhood Acute Lymphoblastic Leukaemia. Acute Lymphoblastic Leukaemia is the most common childhood malignancy with 24% of all new cancers occurring in children within Australia (Coates et al., 2001). According to the American Cancer Society (2016), a total of 6,590 cases of ALL have been diagnosed across all age groups in USA and the expected deaths are 1,430 in 2016. The project uses different data mining and visualisation methods applied on different types of biological data: gene annotations, gene expression and SNPs. This thesis focuses on three main issues in genomic and transcriptomic data studies: (i) Proposing, implementing and evaluating a novel framework to find functional relationships between genes from gene-annotation data. (ii) Identifying an optimal dimensionality reduction method to classify between relapsed and non-relapsed ALL patients using gene expression. (iii) Proposing, implementing and evaluating a novel feature selection approach to identify related metabolic pathways in ALL This thesis proposes, implements and validates an efficient framework to find functional relationships between genes based on gene-annotation data. The framework is built on a binary matrix and a proximity matrix, where the binary matrix contains information related to genes and their functionality, while the proximity matrix shows similarity between different features. The framework retrieves gene functionality information from Gene Ontology (GO), a publicly available database, and visualises the functional related genes using singular value decomposition (SVD). From a simple list of gene-annotations, this thesis retrieves features (i.e Gene Ontology terms) related to each gene and calculates a similarity measure based on the distance between terms in the GO hierarchy. The distance measures are based on hierarchical structure of Gene Ontology and these distance measures are called similarity measures. In this framework, two different similarity measures are applied: (i) A hop-based similarity measure where the distance is calculated based on the number of links between two terms. (ii) An information-content similarity measure where the similarity between terms is based on the probability of GO terms in the gene dataset. This framework also identifies which method performs better among these two similarity measures at identifying functional relationships between genes. Singular value decomposition method is used for visualisation, having the advantage that multiple types of relationships can be visualised simultaneously (gene-to-gene, term-to-term and gene-to-term) In this thesis a novel framework is developed for visualizing patient-to-patient relationships using gene expression values. The framework builds on the random forest feature selection method to filter gene expression values and then applies different linear and non-linear machine learning methods to them. The methods used in this framework are Principal Component Analysis (PCA), Kernel Principal Component Analysis (kPCA), Local Linear Embedding (LLE), Stochastic Neighbour Embedding (SNE) and Diffusion Maps. The framework compares these different machine learning methods by tuning different parameters to find the optimal method among them. Area under the curve (AUC) is used to rank the results and SVM is used to classify between relapsed and non-relapsed patients. The final section of the thesis proposes, implements and validates a framework to find active metabolic pathways in ALL using single nucleotide polymorphism (SNP) profiles. The framework is based on the random forest feature selection method. A collected dataset of ALL patient and healthy controls is constructed and later random forest is applied using different parameters to find highly-ranked SNPs. The credibility of the model is assessed based on the error rate of the confusion matrix and kappa values. Selected high ranked SNPs are used to retrieve metabolic pathways related to ALL from the KEGG metabolic pathways database. The methodologies and approaches presented in this thesis emphasise the critical role that different types of microarray data play in understanding complex diseases like ALL. The availability of flexible frameworks for the task of disease diagnosis and prognosis, as proposed in this thesis, will play an important role in understanding the genetic basis to common complex diseases. This thesis contributes to knowledge in two ways: (i) Providing novel data mining and visualisation frameworks to handle biological data. (ii) Providing novel visualisations for microarray data to increase understanding of disease.

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5

Jeans, Rhiannon. "Form perception and neural feedback: insights from V1 and V2." Thesis, 2014. http://hdl.handle.net/1885/12731.

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In the brain, every cortical inter-area feedforward projection shares a reciprocal feedback connection. Despite its pervasive nature in the brain, our understanding of the functional role of neural feedback in form perception remains incomplete, particularly in behaving animals. This problem is addressed in humans with a novel form completion paradigm. Seven subjects (5 female) had their EEG waveforms analysed using three linear models showing non-significant differences between stimulus conditions designed to produce differences by manipulating neural feedback to V1. Two of these subjects (one female), in addition to EEG waveforms, had combined magnetic resonance imaging (MRI) and functional MRI (fMRI) cortical maps that allowed anatomically close areas such as V1 and V2 to have their signals decomposed and neural feedback inferred. Differences between stimulus conditions arose once signals had been divided into V1 and V2. Significant differences (p < .05) for one subject in V1 and V2 suggests cortical interactions at 100ms and 350ms. This suggests the form completion paradigm has utility at investigating the influence of the V2 far receptive field surround on V1, given future given signal to noise issues are resolved.

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Книги з теми "Single value decomposition"

1

Ninul, Anatolij Sergeevič. Tenzornaja trigonometrija: Teorija i prilozenija / Theory and Applications /. Moscow, Russia: Mir Publisher, 2004.

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2

Ninul, Anatolij Sergeevič. Tensor Trigonometry. Moscow, Russia: Fizmatlit Publisher, 2021.

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3

Zabrodin, Anton. Financial applications of random matrix theory: a short review. Edited by Gernot Akemann, Jinho Baik, and Philippe Di Francesco. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198744191.013.40.

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This article reviews some applications of random matrix theory (RMT) in the context of financial markets and econometric models, with emphasis on various theoretical results (for example, the Marčenko-Pastur spectrum and its various generalizations, random singular value decomposition, free matrices, largest eigenvalue statistics) as well as some concrete applications to portfolio optimization and out-of-sample risk estimation. The discussion begins with an overview of principal component analysis (PCA) of the correlation matrix, followed by an analysis of return statistics and portfolio theory. In particular, the article considers single asset returns, multivariate distribution of returns, risk and portfolio theory, and nonequal time correlations and more general rectangular correlation matrices. It also presents several RMT results on the bulk density of states that can be obtained using the concept of matrix freeness before concluding with a description of empirical correlation matrices of stock returns.

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4

Lattman, Eaton E., Thomas D. Grant, and Edward H. Snell. Shape Reconstructions from Small Angle Scattering Data. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199670871.003.0004.

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This chapter discusses recovering shape or structural information from SAXS data. Key to any such process is the ability to generate a calculated intensity from a model, and to compare this curve with the experimental one. Models for the particle scattering density can be approximated as pure homogenenous geometric shapes. More complex particle surfaces can be represented by spherical harmonics or by a set of close-packed beads. Sometimes structural information is known for components of a particle. Rigid body modeling attempts to rotate and translate structures relative to one another, such that the resulting scattering profile calculated from the model agrees with the experimental SAXS data. More advanced hybrid modelling procedures aim to incorporate as much structural information as is available, including modelling protein dynamics. Solutions may not always contain a homogeneous set of particles. A common case is the presence of two or more conformations of a single particle or a mixture of oligomeric species. The method of singular value decomposition can extract scattering for conformationally distinct species.

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Частини книг з теми "Single value decomposition"

1

Alshebli, Sulaiman, Fatih Kurugollu, and Mahmoud Shafik. "Multimodal Biometric Recognition Using Iris and Face Features." In Advances in Transdisciplinary Engineering. IOS Press, 2021. http://dx.doi.org/10.3233/atde210045.

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Multimodal biometrics has recently gained interest over single biometric modalities. This interest stems from the fact that this technique offers improvements in recognition and more security. In this ongoing research programme, we propose a new feature extraction technique for a biometric system based on face and iris recognition. The extraction of iris and facial features is performed using the Discrete Wavelet Transform combined with the Singular Value Decomposition. Merging the relevant characteristics of the two modalities is used to create a pattern for each individual in the dataset. The evaluation process is performed using two datasets (i.e., Faces94 Faces dataset and IIT Delhi Iris dataset). The experimental results carried out in this programme showed the robustness of the proposed technique.

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2

A. Glaser, John, Endalkachew Sahle-Demessie, and Te’ri L. Richardson. "Are Reliable and Emerging Technologies Available for Plastic Recycling in a Circular Economy?" In Waste Material Recycling in the Circular Economy - Challenges and Developments. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.101350.

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A spectrum of plastics has been produced in the last 70 years, and plastic production has increased faster than any other manufactured material. Current recycling of all plastic materials is pegged at 10% or less. The social value that plastics enjoys is reflected in its myriad uses for engineered durability to single-use applications. Disposable or single-use plastic items have become a significant problem. Plastic debris has become ubiquitous to the landscape and aquatic resources, leading to human health, ecological concerns, and sustainability issues. Past disposal practices relied on waste plastic flows to certain countries for disposal, but these have been summarily curtailed, needing alternatives as productive and environmentally conscious recycling technology. Waste plastics can be repurposed using purification, decomposition, or conversion processes that are based on established and emerging mechanical and chemical technologies. Plastic recycling technologies, such as thermal, chemical, and biological depolymerization processes, including pyrolytic technologies using plastics-to-fuel strategies, are under development ranging from bench-scale demonstrations to full-scale implementation. The ideal of closed supply chain constraints offers optimal solutions to plastic recycling. Evaluation of new processes requires performance assessment to understand better how plastics recycling technologies contribute to the environment and the sustainable reuse of plastic materials.

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3

Yoo, Taejong. "Supply Chain Simulation using Business Process Modeling in Service Oriented Architecture." In Supply Chain and Logistics Management, 857–71. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-0945-6.ch040.

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For supply chain optimization, as a key determinant of strategic resources mobility along the value-added chain, simulation is widely used to test the impact on supply chain performance for the strategic level decisions, such as the number of plants, the modes of transport, or the relocation of warehouses. Traditionally, a single centralized model that encompasses multiple participants in the supply chain is built when optimization of the supply chain through simulation is required. However, due to the heterogeneity of supply chain, a centralized simulation model has a limit to reflect the dynamics of each supply chain participant. This research focuses on the conceptual and the technical issues about the supply chain simulation with a parallel and distributed simulation (PADS) concept. In particular, to ensure the decomposition of supply chain simulation model by each supply chain participant, the simulation framework is proposed using Service Oriented Architecture (SOA) in e-collaboration environment. For a clear proof of concept, the virtual supply chain simulation model is implemented and experienced using business process modeling tools in SOA. Due to the reusable, interoperable, and scalable characteristics of the proposed supply chain simulation framework, various alternatives for supply chin optimization can be generated and evaluated.

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4

Singh, Reena, and Hemant Jalota. "A Study of Good-Enough Security in the Context of Rural Business Process Outsourcing." In Advances in Digital Crime, Forensics, and Cyber Terrorism, 239–52. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-4053-3.ch014.

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Data objects having low value like insurance or data-entry forms are shared between a client and rural business process outsourcing (RBPO) organisations for tasks like translation, proofreading, and data entry. These data objects are first decomposed into smaller parts and then assigned to RBPO users. Each user in a RBPO has access to only a few parts of a complete data object which he can leak to unauthorised users. But since the value of these parts is low, there is not enough incentive for the user to leak them. Such scenarios need good-enough security models that can provide reasonable security to an aggregate number of parts of low value data objects. In this chapter, the authors study the secure data assignment and leakage in RBPO by modeling it in the form of an optimisation problem. They discuss different scenarios of object decomposition and sharing, penalty assignment, and data leakage in the context of RBPO. They use LINGO toolbox to run their model and present insights.

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5

Kröger, Johannes, Tobias Kersten, Yannick Breva, and Steffen Schön. "On the Potential of Image Similarity Metrics for Comparing Phase Center Corrections." In International Association of Geodesy Symposia. Berlin, Heidelberg: Springer Berlin Heidelberg, 2022. http://dx.doi.org/10.1007/1345_2022_146.

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AbstractFor highly precise and accurate positioning and navigation with Global Navigation Satellite Systems (GNSS), it is mandatory to take phase center corrections (PCC) into account. These corrections are provided by different calibration facilities and methods. Currently, discussions in the framework of the International GNSS Service (IGS) antenna working group (AWG) are ongoing on how to accept new calibration facilities as an official IGS calibration facility.In this paper, different image similarity measures and their potential for comparing PCC are presented. Currently used comparison strategies are discussed and their performance is illustrated with several geodetic antennas. We show that correlation coefficients are an appropriate measure to compare different sets of PCC since they perform independently of a constant part within the patterns. However, feature detection algorithms like the Speeded-Up Robust Features (SURF) mostly do not find distinctive structures within the PCC differences due to the smooth character of PCC. Therefore, they are inapplicable for comparing PCC. Singular Value Decomposition (SVD) of PCC differences (ΔPCC) can be used to analyse which structures ΔPCC are composed of. We show that characteristic structures can be found within ΔPCC. Therefore, the SVD is a promising tool to analyse the impact of PCC differences in the coordinate domain.

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6

Russo, Roberta, Maria Acanfora, Tommaso Coppola, and Luca Micoli. "Technical Feasibility Study of an Ammonia-Fuelled Mega-Yacht Powered by PEM Fuel Cells." In Progress in Marine Science and Technology. IOS Press, 2022. http://dx.doi.org/10.3233/pmst220049.

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The maritime sector forecasts that ammonia will play a pivotal role in decarbonizing ships since it does not emit carbon dioxide (CO2). Nevertheless, burning ammonia in ICE produces nitrogen oxides (NO2 and N2O), which are GHG more dangerous than CO2. The use of Proton Exchange Membrane Fuel Cell (PEM) systems instead of ICE avoids the emissions of harmful compounds. In this study, a PEM system is considered for the electric power generation onboard a 63 m length mega-yacht, replacing a traditional MGO gen-set. The pure hydrogen required for fuelling the PEM is produced through an ammonia decomposition reactor and a purification system, to be installed onboard as well. It results that an ammonia processing system for generating hydrogen requires additional power, in this case study is in the range of 360–475 kWe, and it is heavier and bulkier than the gen-set. Despite these cons, its installation onboard seems to be feasible and it does not involve significant modifications to the original configuration of the mega-yacht. The ammonia-fuelled mega-yacht reduces the original duration of navigation from 11 to about 5 days, nevertheless, this value appears still adequate considering the innovative solution at zero-emission proposed.

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Kumar Bhuyan, Ranjan, Bhagban Kisan, Santosh Kumar Parida, Soumya Patra, and Sunil Kumar. "Synthesis of Nano-Composites Mg2TiO4 Powders via Mechanical Alloying Method and Characterization." In Magnesium Alloys [Working Title]. IntechOpen, 2020. http://dx.doi.org/10.5772/intechopen.94275.

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In this chapter a systematic investigation of impact of mechanical activation on structural, microstructural, thermal and optical properties of MgO – TiO2 nanocrystalline composite system, synthesized via high energy ball milling techniques. Williamson-Hall (W-H) plot method was employed to understand the signature of the broadening in the XRD peaks and for the estimation of crystallite size of MgO – TiO2 nanocrystalline composite system. It revealed that the peak broadening is not only due to reduced coherently diffracting domain size but also due to a significant strain distribution. The calculated strain was 9.01× 10−3 and the average crystallite sizes were 40–60 nm for 35 hours (hrs) milled powder and this result is very much consistent with transmission electron microscopy (TEM) analysis. The SAED ring pattern indicates that the phase of Mg2TiO4 - nanoparticles was polycrystalline in structure and the distance between crystalline planes was consistent with the standard pattern for a spinel Mg2TiO4 crystal structure. To analyze the lattice fringes for the 35 hrs milled samples high resolution-TEM (HR-TEM) study was carried out and the result revealed that the each particle has single crystalline structure. Morphological studies were carried out by using SEM analysis. The thermal decomposition behavior of the milled powders was examined by a thermo-gravimetric analyzer (TGA) in argon atmosphere. Also, MTO nanoparticles showed a strong absorption at ~356 nm and the band gap values ranged between 3.26-3.78 eV with an increase of milling time from 0 to 35 hr. The mechanically derived MTO nanoparticles showed promising optical properties which are suitable for commercial optoelectronic applications.

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Тези доповідей конференцій з теми "Single value decomposition"

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Huynh, Hieu Trung, and Yonggwan Won. "Training Single Hidden Layer Feedforward Neural Networks by Singular Value Decomposition." In 2009 Fourth International Conference on Computer Sciences and Convergence Information Technology. IEEE, 2009. http://dx.doi.org/10.1109/iccit.2009.170.

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Kota, Kishore, and Joseph R. Cavallaro. "Pipelining multiple singular value decomposition (SVDs) on a single processor array." In SPIE's 1994 International Symposium on Optics, Imaging, and Instrumentation, edited by Franklin T. Luk. SPIE, 1994. http://dx.doi.org/10.1117/12.190872.

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Manenti, Rafael, and Milton Porsani. "Spectral whitening using single-trace singular value decomposition applied to vibroseis data." In SEG Technical Program Expanded Abstracts 2016. Society of Exploration Geophysicists, 2016. http://dx.doi.org/10.1190/segam2016-13960140.1.

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Hajipour, Sepideh, Mohammad B. Shamsollahi, Hossein Mamaghanian, and Vahid Abootalebi. "Extracting Single Trial Visual Evoked Potentials Using Iterative Generalized Eigen Value Decomposition." In 2008 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT). IEEE, 2008. http://dx.doi.org/10.1109/isspit.2008.4775708.

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Telles Jr, Miguel, Antonio Rosa, and Paulo Quintiliano. "Single Value Decomposition to Maximize the Signal-to-Noise Ratio on Digital Image." In The Second International Conference on Forensic Computer Science. ABEAT, 2007. http://dx.doi.org/10.5769/c2007005.

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Chan, Hoi, Tieu Chieu, and Thomas Kwok. "Autonomic Ranking and Selection of Web Services by Using Single Value Decomposition Technique." In 2008 IEEE International Conference on Web Services (ICWS). IEEE, 2008. http://dx.doi.org/10.1109/icws.2008.124.

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Rodriguez, Richmond Roi B., Ruby Jane A. Mapolon, and Rosula S. J. Reyes. "A Non-intrusive Single Channel Abdominal Fetal Electrocardiogram Monitor Using Singular Value Decomposition." In 2021 3rd International Conference on Electrical, Control and Instrumentation Engineering (ICECIE). IEEE, 2021. http://dx.doi.org/10.1109/icecie52348.2021.9664665.

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Silva, Michelangelo, Milton Porsani, and Bjorn Ursin. "A single-trace singular-value decomposition method with application to the ground-roll removal." In SEG Technical Program Expanded Abstracts 2016. Society of Exploration Geophysicists, 2016. http://dx.doi.org/10.1190/segam2016-13866459.1.

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Ferris, John B. "Singular Value Decomposition of Road Events Into Characteristic Shapes." In ASME 2001 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2001. http://dx.doi.org/10.1115/imece2001/dsc-24515.

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Abstract Road profiles are typically characterized by their spectral content. It has been noted by several researches, however, that road profiles are generally nonstationary signals that contain significant irregularities such as potholes. Such signals are not well described in the spectral domain. The objective of this work is to describe road profiles in the spatial domain by developing a set of characteristic shapes onto which individual events can be cast. A set of analytical functions describing these shapes is also developed. In order to develop a set a characteristic shapes, more than a million events are investigated from a mixture of road types (from highways to gravel roads) and a variety of locations throughout the United States. A set of characteristic shapes is developed for each road type and location. Although the events were drawn from diverse samples, the resulting sets of characteristic shapes are nearly indistinguishable. This similarity allows a single set of characteristic shapes to describe events for a wide class of roads. Variations in these sets are discussed and used in deriving a set of orthogonal analytical functions that describe the characteristic shapes. Individual road events are then mapped onto this set of characteristic shapes. The implications of decomposing road events into these characteristic shapes are discussed.

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van Hees, Roy P. M., Min Wu, Frans N. van de Vosse, Richard G. P. Lopata, and Marcel C. M. Rutten. "Intraplaque haemorrhage detection using single-wavelength PAI and singular value decomposition in the carotid artery." In Opto-Acoustic Methods and Applications in Biophotonics, edited by Vasilis Ntziachristos and Roger Zemp. SPIE, 2019. http://dx.doi.org/10.1117/12.2527186.

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