Frames and operator theory in analysis and signal processing

CERN Document Server

Larson, David R; Nashed, Zuhair; Nguyen, Minh Chuong; Papadakis, Manos

2008-01-01

This volume contains articles based on talks presented at the Special Session Frames and Operator Theory in Analysis and Signal Processing, held in San Antonio, Texas, in January of 2006. Recently, the field of frames has undergone tremendous advancement. Most of the work in this field is focused on the design and construction of more versatile frames and frames tailored towards specific applications, e.g., finite dimensional uniform frames for cellular communication. In addition, frames are now becoming a hot topic in mathematical research as a part of many engineering applications, e.g., matching pursuits and greedy algorithms for image and signal processing. Topics covered in this book include: Application of several branches of analysis (e.g., PDEs; Fourier, wavelet, and harmonic analysis; transform techniques; data representations) to industrial and engineering problems, specifically image and signal processing. Theoretical and applied aspects of frames and wavelets. Pure aspects of operator theory empha...

Advances in biomedical signal and image processing – A systematic review

Directory of Open Access Journals (Sweden)

J. Rajeswari

Full Text Available Biomedical signal and image processing establish a dynamic area of specialization in both academic as well as research aspects of biomedical engineering. The concepts of signal and image processing have been widely used for extracting the physiological information in implementing many clinical procedures for sophisticated medical practices and applications. In this paper, the relationship between electrophysiological signals, i.e., electrocardiogram (ECG, electromyogram (EMG, electroencephalogram (EEG and functional image processing and their derived interactions have been discussed. Examples have been investigated in various case studies such as neurosciences, functional imaging, and cardiovascular system, by using different algorithms and methods. The interaction between the extracted information obtained from multiple signals and modalities seems to be very promising. The advanced algorithms and methods in the area of information retrieval based on time-frequency representation have been investigated. Finally, some examples of algorithms have been discussed in which the electrophysiological signals and functional images have been properly extracted and have a significant impact on various biomedical applications. Keywords: Biomedical signals and images, Processing, Analysis

Advances in independent component analysis and learning machines

CERN Document Server

Bingham, Ella; Laaksonen, Jorma; Lampinen, Jouko

2015-01-01

In honour of Professor Erkki Oja, one of the pioneers of Independent Component Analysis (ICA), this book reviews key advances in the theory and application of ICA, as well as its influence on signal processing, pattern recognition, machine learning, and data mining. Examples of topics which have developed from the advances of ICA, which are covered in the book are: A unifying probabilistic model for PCA and ICA Optimization methods for matrix decompositions Insights into the FastICA algorithmUnsupervised deep learning Machine vision and image retrieval A review of developments in the t

siGnum: graphical user interface for EMG signal analysis.

Science.gov (United States)

Kaur, Manvinder; Mathur, Shilpi; Bhatia, Dinesh; Verma, Suresh

2015-01-01

Electromyography (EMG) signals that represent the electrical activity of muscles can be used for various clinical and biomedical applications. These are complicated and highly varying signals that are dependent on anatomical location and physiological properties of the muscles. EMG signals acquired from the muscles require advanced methods for detection, decomposition and processing. This paper proposes a novel Graphical User Interface (GUI) siGnum developed in MATLAB that will apply efficient and effective techniques on processing of the raw EMG signals and decompose it in a simpler manner. It could be used independent of MATLAB software by employing a deploy tool. This would enable researcher's to gain good understanding of EMG signal and its analysis procedures that can be utilized for more powerful, flexible and efficient applications in near future.

Digital spectral analysis parametric, non-parametric and advanced methods

CERN Document Server

Castanié, Francis

2013-01-01

Digital Spectral Analysis provides a single source that offers complete coverage of the spectral analysis domain. This self-contained work includes details on advanced topics that are usually presented in scattered sources throughout the literature.The theoretical principles necessary for the understanding of spectral analysis are discussed in the first four chapters: fundamentals, digital signal processing, estimation in spectral analysis, and time-series models.An entire chapter is devoted to the non-parametric methods most widely used in industry.High resolution methods a

Hybrid soft computing systems for electromyographic signals analysis: a review.

Science.gov (United States)

Xie, Hong-Bo; Guo, Tianruo; Bai, Siwei; Dokos, Socrates

2014-02-03

Electromyographic (EMG) is a bio-signal collected on human skeletal muscle. Analysis of EMG signals has been widely used to detect human movement intent, control various human-machine interfaces, diagnose neuromuscular diseases, and model neuromusculoskeletal system. With the advances of artificial intelligence and soft computing, many sophisticated techniques have been proposed for such purpose. Hybrid soft computing system (HSCS), the integration of these different techniques, aims to further improve the effectiveness, efficiency, and accuracy of EMG analysis. This paper reviews and compares key combinations of neural network, support vector machine, fuzzy logic, evolutionary computing, and swarm intelligence for EMG analysis. Our suggestions on the possible future development of HSCS in EMG analysis are also given in terms of basic soft computing techniques, further combination of these techniques, and their other applications in EMG analysis.

Hybrid soft computing systems for electromyographic signals analysis: a review

Science.gov (United States)

2014-01-01

Electromyographic (EMG) is a bio-signal collected on human skeletal muscle. Analysis of EMG signals has been widely used to detect human movement intent, control various human-machine interfaces, diagnose neuromuscular diseases, and model neuromusculoskeletal system. With the advances of artificial intelligence and soft computing, many sophisticated techniques have been proposed for such purpose. Hybrid soft computing system (HSCS), the integration of these different techniques, aims to further improve the effectiveness, efficiency, and accuracy of EMG analysis. This paper reviews and compares key combinations of neural network, support vector machine, fuzzy logic, evolutionary computing, and swarm intelligence for EMG analysis. Our suggestions on the possible future development of HSCS in EMG analysis are also given in terms of basic soft computing techniques, further combination of these techniques, and their other applications in EMG analysis. PMID:24490979

Analysis of radiometric signal in sedimentating suspension flow in open channel

Directory of Open Access Journals (Sweden)

Zych Marcin

2015-01-01

Full Text Available The article discusses issues related to the estimation of the sedimentating solid particles average flow velocity in an open channel using radiometric methods. Due to the composition of the compound, which formed water and diatomite, received data have a very weak signal to noise ratio. In the process analysis the known determining of the solid phase transportation time delay the classical cross-correlation function is the most reliable method. The use of advanced frequency analysis based on mutual spectral density function and wavelet transform of recorded signals allows a reduction of the noise contribution.

Digital signal processing and spectral analysis for scientists concepts and applications

CERN Document Server

Alessio, Silvia Maria

2016-01-01

This book covers the basics of processing and spectral analysis of monovariate discrete-time signals. The approach is practical, the aim being to acquaint the reader with the indications for and drawbacks of the various methods and to highlight possible misuses. The book is rich in original ideas, visualized in new and illuminating ways, and is structured so that parts can be skipped without loss of continuity. Many examples are included, based on synthetic data and real measurements from the fields of physics, biology, medicine, macroeconomics etc., and a complete set of MATLAB exercises requiring no previous experience of programming is provided. Prior advanced mathematical skills are not needed in order to understand the contents: a good command of basic mathematical analysis is sufficient. Where more advanced mathematical tools are necessary, they are included in an Appendix and presented in an easy-to-follow way. With this book, digital signal processing leaves the domain of engineering to address the ne...

Guard Cell Signal Transduction Network: Advances in Understanding Abscisic Acid, CO2, and Ca2+ Signaling

KAUST Repository

Kim, Tae-Houn

2010-05-04

Stomatal pores are formed by pairs of specialized epidermal guard cells and serve as major gateways for both CO2 influx into plants from the atmosphere and transpirational water loss of plants. Because they regulate stomatal pore apertures via integration of both endogenous hormonal stimuli and environmental signals, guard cells have been highly developed as a model system to dissect the dynamics and mechanisms of plant-cell signaling. The stress hormone ABA and elevated levels of CO2 activate complex signaling pathways in guard cells that are mediated by kinases/phosphatases, secondary messengers, and ion channel regulation. Recent research in guard cells has led to a new hypothesis for how plants achieve specificity in intracellular calcium signaling: CO2 and ABA enhance (prime) the calcium sensitivity of downstream calcium-signaling mechanisms. Recent progress in identification of early stomatal signaling components are reviewed here, including ABA receptors and CO2-binding response proteins, as well as systems approaches that advance our understanding of guard cell-signaling mechanisms.

Guard Cell Signal Transduction Network: Advances in Understanding Abscisic Acid, CO2, and Ca2+ Signaling

KAUST Repository

Kim, Tae-Houn; Bö hmer, Maik; Hu, Honghong; Nishimura, Noriyuki; Schroeder, Julian I.

2010-01-01

Stomatal pores are formed by pairs of specialized epidermal guard cells and serve as major gateways for both CO2 influx into plants from the atmosphere and transpirational water loss of plants. Because they regulate stomatal pore apertures via integration of both endogenous hormonal stimuli and environmental signals, guard cells have been highly developed as a model system to dissect the dynamics and mechanisms of plant-cell signaling. The stress hormone ABA and elevated levels of CO2 activate complex signaling pathways in guard cells that are mediated by kinases/phosphatases, secondary messengers, and ion channel regulation. Recent research in guard cells has led to a new hypothesis for how plants achieve specificity in intracellular calcium signaling: CO2 and ABA enhance (prime) the calcium sensitivity of downstream calcium-signaling mechanisms. Recent progress in identification of early stomatal signaling components are reviewed here, including ABA receptors and CO2-binding response proteins, as well as systems approaches that advance our understanding of guard cell-signaling mechanisms.

Wavelet analysis for nonstationary signals

International Nuclear Information System (INIS)

Penha, Rosani Maria Libardi da

1999-01-01

Mechanical vibration signals play an important role in anomalies identification resulting of equipment malfunctioning. Traditionally, Fourier spectral analysis is used where the signals are assumed to be stationary. However, occasional transient impulses and start-up process are examples of nonstationary signals that can be found in mechanical vibrations. These signals can provide important information about the equipment condition, as early fault detection. The Fourier analysis can not adequately be applied to nonstationary signals because the results provide data about the frequency composition averaged over the duration of the signal. In this work, two methods for nonstationary signal analysis are used: Short Time Fourier Transform (STFT) and wavelet transform. The STFT is a method of adapting Fourier spectral analysis for nonstationary application to time-frequency domain. To have a unique resolution throughout the entire time-frequency domain is its main limitation. The wavelet transform is a new analysis technique suitable to nonstationary signals, which handles the STFT drawbacks, providing multi-resolution frequency analysis and time localization in a unique time-scale graphic. The multiple frequency resolutions are obtained by scaling (dilatation/compression) the wavelet function. A comparison of the conventional Fourier transform, STFT and wavelet transform is made applying these techniques to: simulated signals, arrangement rotor rig vibration signal and rotate machine vibration signal Hanning window was used to STFT analysis. Daubechies and harmonic wavelets were used to continuos, discrete and multi-resolution wavelet analysis. The results show the Fourier analysis was not able to detect changes in the signal frequencies or discontinuities. The STFT analysis detected the changes in the signal frequencies, but with time-frequency resolution problems. The wavelet continuos and discrete transform demonstrated to be a high efficient tool to detect

Advanced Analysis Methods in High Energy Physics

Energy Technology Data Exchange (ETDEWEB)

Pushpalatha C. Bhat

2001-10-03

During the coming decade, high energy physics experiments at the Fermilab Tevatron and around the globe will use very sophisticated equipment to record unprecedented amounts of data in the hope of making major discoveries that may unravel some of Nature's deepest mysteries. The discovery of the Higgs boson and signals of new physics may be around the corner. The use of advanced analysis techniques will be crucial in achieving these goals. The author discusses some of the novel methods of analysis that could prove to be particularly valuable for finding evidence of any new physics, for improving precision measurements and for exploring parameter spaces of theoretical models.

Signal flow analysis

CERN Document Server

Abrahams, J R; Hiller, N

1965-01-01

Signal Flow Analysis provides information pertinent to the fundamental aspects of signal flow analysis. This book discusses the basic theory of signal flow graphs and shows their relation to the usual algebraic equations.Organized into seven chapters, this book begins with an overview of properties of a flow graph. This text then demonstrates how flow graphs can be applied to a wide range of electrical circuits that do not involve amplification. Other chapters deal with the parameters as well as circuit applications of transistors. This book discusses as well the variety of circuits using ther

Semi-classical signal analysis

KAUST Repository

Laleg-Kirati, Taous-Meriem

2012-09-30

This study introduces a new signal analysis method, based on a semi-classical approach. The main idea in this method is to interpret a pulse-shaped signal as a potential of a Schrödinger operator and then to use the discrete spectrum of this operator for the analysis of the signal. We present some numerical examples and the first results obtained with this method on the analysis of arterial blood pressure waveforms. © 2012 Springer-Verlag London Limited.

Two-dimensional signal analysis

CERN Document Server

Garello, René

2010-01-01

This title sets out to show that 2-D signal analysis has its own role to play alongside signal processing and image processing.Concentrating its coverage on those 2-D signals coming from physical sensors (such as radars and sonars), the discussion explores a 2-D spectral approach but develops the modeling of 2-D signals and proposes several data-oriented analysis techniques for dealing with them. Coverage is also given to potential future developments in this area.

Acoustic monitoring of rotating machine by advanced signal processing technology

International Nuclear Information System (INIS)

Kanemoto, Shigeru

2010-01-01

The acoustic data remotely measured by hand held type microphones are investigated for monitoring and diagnosing the rotational machine integrity in nuclear power plants. The plant operator's patrol monitoring is one of the important activities for condition monitoring. However, remotely measured sound has some difficulties to be considered for precise diagnosis or quantitative judgment of rotating machine anomaly, since the measurement sensitivity is different in each measurement, and also, the sensitivity deteriorates in comparison with an attached type sensor. Hence, in the present study, several advanced signal processing methods are examined and compared in order to find optimum anomaly monitoring technology from the viewpoints of both sensitivity and robustness of performance. The dimension of pre-processed signal feature patterns are reduced into two-dimensional space for the visualization by using the standard principal component analysis (PCA) or the kernel based PCA. Then, the normal state is classified by using probabilistic neural network (PNN) or support vector data description (SVDD). By using the mockup test facility of rotating machine, it is shown that the appropriate combination of the above algorithms gives sensitive and robust anomaly monitoring performance. (author)

Time lens based optical fourier transformation for advanced processing of spectrally-efficient OFDM and N-WDM signals

DEFF Research Database (Denmark)

Guan, Pengyu; Røge, Kasper Meldgaard; Morioka, Toshio

2016-01-01

We review recent progress in the use of time lens based optical Fourier transformation for advanced optical signal processing, with focus on all-optical generation, detection and format conversion of spectrally-efficient OFDM and N-WDM signals.......We review recent progress in the use of time lens based optical Fourier transformation for advanced optical signal processing, with focus on all-optical generation, detection and format conversion of spectrally-efficient OFDM and N-WDM signals....

Advances in heuristic signal processing and applications

CERN Document Server

Chatterjee, Amitava; Siarry, Patrick

2013-01-01

There have been significant developments in the design and application of algorithms for both one-dimensional signal processing and multidimensional signal processing, namely image and video processing, with the recent focus changing from a step-by-step procedure of designing the algorithm first and following up with in-depth analysis and performance improvement to instead applying heuristic-based methods to solve signal-processing problems. In this book the contributing authors demonstrate both general-purpose algorithms and those aimed at solving specialized application problems, with a spec

Microwave dynamic large signal waveform characterization of advanced InGaP HBT for power amplifiers

Energy Technology Data Exchange (ETDEWEB)

Zhao Lixin; Jin Zhi; Liu Xinyu, E-mail: zhaolixin@ime.ac.c [Institute of Microelectronics, Chinese Academy of Sciences, Beijing 100029 (China)

2009-12-15

In wireless mobile communications and wireless local area networks (WLAN), advanced InGaP HBT with power amplifiers are key components. In this paper, the microwave large signal dynamic waveform characteristics of an advanced InGaP HBT are investigated experimentally for 5.8 GHz power amplifier applications. The microwave large signal waveform distortions at various input power levels, especially at large signal level, are investigated and the reasons are analyzed. The output power saturation is also explained. These analyses will be useful for power amplifier designs. (semiconductor devices)

Filtration of the FMICW radar output signals by the advanced windows

African Journals Online (AJOL)

Filtration of the FMICW radar output signals by the advanced windows. ... PROMOTING ACCESS TO AFRICAN RESEARCH ... This paper deals with the special types of windows application on the two dimensional spectrum obtained using the ...

Advanced Optical Signal Processing using Time Lens based Optical Fourier Transformation

DEFF Research Database (Denmark)

Guan, Pengyu; Røge, Kasper Meldgaard; Lillieholm, Mads

2016-01-01

An overview of recent progress on time lens based advanced optical signal processing is presented, with a special focus on all-optical ultrafast 640 Gbit/s all-channel serial-to-parallel conversion, and scalable WDM regeneration....

I. Advances in NMR Signal Processing. II. Spin Dynamics in Quantum Dissipative Systems

Energy Technology Data Exchange (ETDEWEB)

Lin, Yung-Ya [Univ. of California, Berkeley, CA (United States)

1998-11-01

the lattice fluctuations in an extended time scale. Lowtemperature measurements and classical-spin simulations are carried out to verify the above analysis. To promote the implementation and future study on the topics described in this thesis, program packages of advanced NMR signal processing and many-spin FID simulations are summarized and listed in the Appendix.

Research advances in sorafenib-induced apoptotic signaling pathways in liver cancer cells

Directory of Open Access Journals (Sweden)

ZHANG Chaoya

2016-04-01

Full Text Available Currently, sorafenib is the multi-target inhibitor for the treatment of advanced primary liver cancer, and can effectively prolong the progression-free survival and overall survival in patients with advanced primary liver cancer. The application of sorafenib in the targeted therapy for liver cancer has become a hot topic. Major targets or signaling pathways include Raf/Mek/Erk, Jak/Stat, PI3K/Akt/mTOR, VEGFR and PDGFR, STAT, microRNA, Wnt/β-catenin, autolysosome, and tumor-related proteins, and sorafenib can regulate the proliferation, differentiation, metastasis, and apoptosis of liver cancer cells through these targets. This article reviews the current research on the action of sorafenib on these targets or signaling pathways to provide useful references for further clinical research on sorafenib.

Semi-classical signal analysis

KAUST Repository

Laleg-Kirati, Taous-Meriem; Cré peau, Emmanuelle; Sorine, Michel

2012-01-01

This study introduces a new signal analysis method, based on a semi-classical approach. The main idea in this method is to interpret a pulse-shaped signal as a potential of a Schrödinger operator and then to use the discrete spectrum

Digital signal processing

CERN Document Server

O'Shea, Peter; Hussain, Zahir M

2011-01-01

In three parts, this book contributes to the advancement of engineering education and that serves as a general reference on digital signal processing. Part I presents the basics of analog and digital signals and systems in the time and frequency domain. It covers the core topics: convolution, transforms, filters, and random signal analysis. It also treats important applications including signal detection in noise, radar range estimation for airborne targets, binary communication systems, channel estimation, banking and financial applications, and audio effects production. Part II considers sel

Applying advanced digital signal processing techniques in industrial radioisotopes applications

International Nuclear Information System (INIS)

Mahmoud, H.K.A.E.

2012-01-01

Radioisotopes can be used to obtain signals or images in order to recognize the information inside the industrial systems. The main problems of using these techniques are the difficulty of identification of the obtained signals or images and the requirement of skilled experts for the interpretation process of the output data of these applications. Now, the interpretation of the output data from these applications is performed mainly manually, depending heavily on the skills and the experience of trained operators. This process is time consuming and the results typically suffer from inconsistency and errors. The objective of the thesis is to apply the advanced digital signal processing techniques for improving the treatment and the interpretation of the output data from the different Industrial Radioisotopes Applications (IRA). This thesis focuses on two IRA; the Residence Time Distribution (RTD) measurement and the defect inspection of welded pipes using a gamma source (gamma radiography). In RTD measurement application, this thesis presents methods for signal pre-processing and modeling of the RTD signals. Simulation results have been presented for two case studies. The first case study is a laboratory experiment for measuring the RTD in a water flow rig. The second case study is an experiment for measuring the RTD in a phosphate production unit. The thesis proposes an approach for RTD signal identification in the presence of noise. In this approach, after signal processing, the Mel Frequency Cepstral Coefficients (MFCCs) and polynomial coefficients are extracted from the processed signal or from one of its transforms. The Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT), and Discrete Sine Transform (DST) have been tested and compared for efficient feature extraction. Neural networks have been used for matching of the extracted features. Furthermore, the Power Density Spectrum (PDS) of the RTD signal has been also used instead of the discrete

Tracking radar advanced signal processing and computing for Kwajalein Atoll (KA) application

Science.gov (United States)

Cottrill, Stanley D.

1992-11-01

Two means are examined whereby the operations of KMR during mission execution may be improved through the introduction of advanced signal processing techniques. In the first approach, the addition of real time coherent signal processing technology to the FPQ-19 radar is considered. In the second approach, the incorporation of the MMW radar, with its very fine range precision, to the MMS system is considered. The former appears very attractive and a Phase 2 SBIR has been proposed. The latter does not appear promising enough to warrant further development.

Analysis And Augmentation Of Timing Advance Based Geolocation In Lte Cellular Networks

Science.gov (United States)

2016-12-01

measurements to validate TA-based positioning approaches in LTE . Their approach did not, however, focus on characterizing the TA. Rather, similar to...UE will measure the time difference of arrival of the LTE Positioning Reference Signal (PRS) from multiple eNBs. This information is then sent to a...NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA DISSERTATION ANALYSIS AND AUGMENTATION OF TIMING ADVANCE-BASED GEOLOCATION IN LTE CELLULAR NETWORKS by

Analysis and logical modeling of biological signaling transduction networks

Science.gov (United States)

Sun, Zhongyao

The study of network theory and its application span across a multitude of seemingly disparate fields of science and technology: computer science, biology, social science, linguistics, etc. It is the intrinsic similarities embedded in the entities and the way they interact with one another in these systems that link them together. In this dissertation, I present from both the aspect of theoretical analysis and the aspect of application three projects, which primarily focus on signal transduction networks in biology. In these projects, I assembled a network model through extensively perusing literature, performed model-based simulations and validation, analyzed network topology, and proposed a novel network measure. The application of network modeling to the system of stomatal opening in plants revealed a fundamental question about the process that has been left unanswered in decades. The novel measure of the redundancy of signal transduction networks with Boolean dynamics by calculating its maximum node-independent elementary signaling mode set accurately predicts the effect of single node knockout in such signaling processes. The three projects as an organic whole advance the understanding of a real system as well as the behavior of such network models, giving me an opportunity to take a glimpse at the dazzling facets of the immense world of network science.

Signal Diversity of Receptor for Advanced Glycation End Products.

Science.gov (United States)

Sakaguchi, Masakiyo; Kinoshita, Rie; Putranto, Endy Widya; Ruma, I Made Winarsa; Sumardika, I Wayan; Youyi, Chen; Tomonobu, Naoko; Yamamoto, Ken-Ichi; Murata, Hitoshi

2017-12-01

The receptor for advanced glycation end products (RAGE) is involved in inflammatory pathogenesis. It functions as a receptor to multiple ligands such as AGEs, HMGB1 and S100 proteins, activating multiple intracellular signaling pathways with each ligand binding. The molecular events by which ligand-activated RAGE controls diverse signaling are not well understood, but some progress was made recently. Accumulating evidence revealed that RAGE has multiple binding partners within the cytoplasm and on the plasma membrane. It was first pointed out in 2008 that RAGE's cytoplasmic tail is able to recruit Diaphanous-1 (Dia-1), resulting in the acquisition of increased cellular motility through Rac1/Cdc42 activation. We also observed that within the cytosol, RAGE's cytoplasmic tail behaves similarly to a Toll-like receptor (TLR4)-TIR domain, interacting with TIRAP and MyD88 adaptor molecules that in turn activate multiple downstream signals. Subsequent studies demonstrated the presence of an alternative adaptor molecule, DAP10, on the plasma membrane. The coupling of RAGE with DAP10 is critical for enhancing the RAGE-mediated survival signal. Interestingly, RAGE interaction on the membrane was not restricted to DAP10 alone. The chemotactic G-protein-coupled receptors (GPCRs) formyl peptide receptors1 and 2 (FPR1 and FPR2) also interacted with RAGE on the plasma membrane. Binding interaction between leukotriene B4 receptor 1 (BLT1) and RAGE was also demonstrated. All of the interactions affected the RAGE signal polarity. These findings indicate that functional interactions between RAGE and various molecules within the cytoplasmic area or on the membrane area coordinately regulate multiple ligand-mediated RAGE responses, leading to typical cellular phenotypes in several pathological settings. Here we review RAGE's signaling diversity, to contribute to the understanding of the elaborate functions of RAGE in physiological and pathological contexts.

Mathematical properties of a semi-classical signal analysis method: Noisy signal case

KAUST Repository

Liu, Dayan

2012-08-01

Recently, a new signal analysis method based on a semi-classical approach has been proposed [1]. The main idea in this method is to interpret a signal as a potential of a Schrodinger operator and then to use the discrete spectrum of this operator to analyze the signal. In this paper, we are interested in a mathematical analysis of this method in discrete case considering noisy signals. © 2012 IEEE.

Mathematical properties of a semi-classical signal analysis method: Noisy signal case

KAUST Repository

Liu, Dayan; Laleg-Kirati, Taous-Meriem

2012-01-01

Recently, a new signal analysis method based on a semi-classical approach has been proposed [1]. The main idea in this method is to interpret a signal as a potential of a Schrodinger operator and then to use the discrete spectrum of this operator to analyze the signal. In this paper, we are interested in a mathematical analysis of this method in discrete case considering noisy signals. © 2012 IEEE.

Identification of Key Pathways and Genes in Advanced Coronary Atherosclerosis Using Bioinformatics Analysis

Directory of Open Access Journals (Sweden)

Xiaowen Tan

2017-01-01

Full Text Available Background. Coronary artery atherosclerosis is a chronic inflammatory disease. This study aimed to identify the key changes of gene expression between early and advanced carotid atherosclerotic plaque in human. Methods. Gene expression dataset GSE28829 was downloaded from Gene Expression Omnibus (GEO, including 16 advanced and 13 early stage atherosclerotic plaque samples from human carotid. Differentially expressed genes (DEGs were analyzed. Results. 42,450 genes were obtained from the dataset. Top 100 up- and downregulated DEGs were listed. Functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG identification were performed. The result of functional and pathway enrichment analysis indicted that the immune system process played a critical role in the progression of carotid atherosclerotic plaque. Protein-protein interaction (PPI networks were performed either. Top 10 hub genes were identified from PPI network and top 6 modules were inferred. These genes were mainly involved in chemokine signaling pathway, cell cycle, B cell receptor signaling pathway, focal adhesion, and regulation of actin cytoskeleton. Conclusion. The present study indicated that analysis of DEGs would make a deeper understanding of the molecular mechanisms of atherosclerosis development and they might be used as molecular targets and diagnostic biomarkers for the treatment of atherosclerosis.

Advanced AEM by Comprehensive Analysis and Modeling of System Drift

Science.gov (United States)

Schiller, Arnulf; Klune, Klaus; Schattauer, Ingrid

2010-05-01

The quality of the assessment of risks outgoing from environmental hazards strongly depends on the spatial and temporal distribution of the data collected in a survey area. Natural hazards generally emerge from wide areas as it is in the case of volcanoes or land slides. Conventional surface measurements are restricted to few lines or locations and often can't be conducted in difficult terrain. So they only give a spatial and temporary limited data set and therefore limit the reliability of risk analysis. Aero-geophysical measurements potentially provide a valuable tool for completing the data set as they can be performed over a wide area, even above difficult terrain within a short time. A most desirable opportunity in course of such measurements is the ascertainment of the dynamics of such potentially hazardous environmental processes. This necessitates repeated and reproducible measurements. Current HEM systems can't accomplish this adequately due to their system immanent drift and - in some cases - bad signal to noise ratio. So, to develop comprising concepts for advancing state of the art HEM-systems to a valuable tool for data acquisition in risk assessment or hydrological problems, different studies have been undertaken which form the contents of the presented work conducted in course of the project HIRISK (Helicopter Based Electromagnetic System for Advanced Environmental Risk Assessment - FWF L-354 N10, supported by the Austrian Science Fund). The methodology is based upon two paths: A - Comprehensive experimental testing on an existing HEM system serving as an experimental platform. B - The setup of a numerical model which is continuously refined according to the results of the experimental data. The model then serves to simulate the experimental as well as alternative configurations and to analyze them subject to their drift behavior. Finally, concepts for minimizing the drift are derived and tested. Different test series - stationary on ground as well

Method of signal analysis

International Nuclear Information System (INIS)

Berthomier, Charles

1975-01-01

A method capable of handling the amplitude and the frequency time laws of a certain kind of geophysical signals is described here. This method is based upon the analytical signal idea of Gabor and Ville, which is constructed either in the time domain by adding an imaginary part to the real signal (in-quadrature signal), or in the frequency domain by suppressing negative frequency components. The instantaneous frequency of the initial signal is then defined as the time derivative of the phase of the analytical signal, and his amplitude, or envelope, as the modulus of this complex signal. The method is applied to three types of magnetospheric signals: chorus, whistlers and pearls. The results obtained by analog and numerical calculations are compared to results obtained by classical systems using filters, i.e. based upon a different definition of the concept of frequency. The precision with which the frequency-time laws are determined leads then to the examination of the principle of the method and to a definition of instantaneous power density spectrum attached to the signal, and to the first consequences of this definition. In this way, a two-dimensional representation of the signal is introduced which is less deformed by the analysis system properties than the usual representation, and which moreover has the advantage of being obtainable practically in real time [fr

Multivariate Analysis for the Processing of Signals

Directory of Open Access Journals (Sweden)

Beattie J.R.

2014-01-01

Full Text Available Real-world experiments are becoming increasingly more complex, needing techniques capable of tracking this complexity. Signal based measurements are often used to capture this complexity, where a signal is a record of a sample’s response to a parameter (e.g. time, displacement, voltage, wavelength that is varied over a range of values. In signals the responses at each value of the varied parameter are related to each other, depending on the composition or state sample being measured. Since signals contain multiple information points, they have rich information content but are generally complex to comprehend. Multivariate Analysis (MA has profoundly transformed their analysis by allowing gross simplification of the tangled web of variation. In addition MA has also provided the advantage of being much more robust to the influence of noise than univariate methods of analysis. In recent years, there has been a growing awareness that the nature of the multivariate methods allows exploitation of its benefits for purposes other than data analysis, such as pre-processing of signals with the aim of eliminating irrelevant variations prior to analysis of the signal of interest. It has been shown that exploiting multivariate data reduction in an appropriate way can allow high fidelity denoising (removal of irreproducible non-signals, consistent and reproducible noise-insensitive correction of baseline distortions (removal of reproducible non-signals, accurate elimination of interfering signals (removal of reproducible but unwanted signals and the standardisation of signal amplitude fluctuations. At present, the field is relatively small but the possibilities for much wider application are considerable. Where signal properties are suitable for MA (such as the signal being stationary along the x-axis, these signal based corrections have the potential to be highly reproducible, and highly adaptable and are applicable in situations where the data is noisy or

Signal analysis of ventricular fibrillation

NARCIS (Netherlands)

Herbschleb, J.N.; Heethaar, R.M.; Tweel, L.H. van der; Zimmerman, A.N.E.; Meijler, F.L.

Signal analysis of electro(cardio)grams during ventricular fibrillation (VF) in dogs and human patients indicates more organization and regularity than the official WHO definition suggests. The majority of the signal is characterized by a power spectrum with narrow, equidistant peaks. In a further

Biological signals classification and analysis

CERN Document Server

Kiasaleh, Kamran

2015-01-01

This authored monograph presents key aspects of signal processing analysis in the biomedical arena. Unlike wireless communication systems, biological entities produce signals with underlying nonlinear, chaotic nature that elude classification using the standard signal processing techniques, which have been developed over the past several decades for dealing primarily with standard communication systems. This book separates what is random from that which appears to be random, and yet is truly deterministic with random appearance. At its core, this work gives the reader a perspective on biomedical signals and the means to classify and process such signals. In particular, a review of random processes along with means to assess the behavior of random signals is also provided. The book also includes a general discussion of biological signals in order to demonstrate the inefficacy of the well-known techniques to correctly extract meaningful information from such signals. Finally, a thorough discussion of recently ...

Alterations in mouse hypothalamic adipokine gene expression and leptin signaling following chronic spinal cord injury and with advanced age.

Directory of Open Access Journals (Sweden)

Gregory E Bigford

Full Text Available Chronic spinal cord injury (SCI results in an accelerated trajectory of several cardiovascular disease (CVD risk factors and related aging characteristics, however the molecular mechanisms that are activated have not been explored. Adipokines and leptin signaling are known to play a critical role in neuro-endocrine regulation of energy metabolism, and are now implicated in central inflammatory processes associated with CVD. Here, we examine hypothalamic adipokine gene expression and leptin signaling in response to chronic spinal cord injury and with advanced age. We demonstrate significant changes in fasting-induced adipose factor (FIAF, resistin (Rstn, long-form leptin receptor (LepRb and suppressor of cytokine-3 (SOCS3 gene expression following chronic SCI and with advanced age. LepRb and Jak2/stat3 signaling is significantly decreased and the leptin signaling inhibitor SOCS3 is significantly elevated with chronic SCI and advanced age. In addition, we investigate endoplasmic reticulum (ER stress and activation of the uncoupled protein response (UPR as a biological hallmark of leptin resistance. We observe the activation of the ER stress/UPR proteins IRE1, PERK, and eIF2alpha, demonstrating leptin resistance in chronic SCI and with advanced age. These findings provide evidence for adipokine-mediated inflammatory responses and leptin resistance as contributing to neuro-endocrine dysfunction and CVD risk following SCI and with advanced age. Understanding the underlying mechanisms contributing to SCI and age related CVD may provide insight that will help direct specific therapeutic interventions.

Urban Traffic Signal System Control Structural Optimization Based on Network Analysis

Directory of Open Access Journals (Sweden)

Li Wang

2013-01-01

Full Text Available Advanced urban traffic signal control systems such as SCOOT and SCATS normally coordinate traffic network using multilevel hierarchical control mechanism. In this mechanism, several key intersections will be selected from traffic signal network and the network will be divided into different control subareas. Traditionally, key intersection selection and control subareas division are executed according to dynamic traffic counts and link length between intersections, which largely rely on traffic engineers’ experience. However, it omits important inherent characteristics of traffic network topology. In this paper, we will apply network analysis approach into these two aspects for traffic system control structure optimization. Firstly, the modified C-means clustering algorithm will be proposed to assess the importance of intersections in traffic network and furthermore determine the key intersections based on three indexes instead of merely on traffic counts in traditional methods. Secondly, the improved network community discovery method will be used to give more reasonable evidence in traffic control subarea division. Finally, to test the effectiveness of network analysis approach, a hardware-in-loop simulation environment composed of regional traffic control system, microsimulation software and signal controller hardware, will be built. Both traditional method and proposed approach will be implemented on simulation test bed to evaluate traffic operation performance indexes, for example, travel time, stop times, delay and average vehicle speed. Simulation results show that the proposed network analysis approach can improve the traffic control system operation performance effectively.

GELATIO: a general framework for modular digital analysis of high-purity Ge detector signals

International Nuclear Information System (INIS)

Agostini, M; Pandola, L; Zavarise, P; Volynets, O

2011-01-01

GELATIO is a new software framework for advanced data analysis and digital signal processing developed for the GERDA neutrinoless double beta decay experiment. The framework is tailored to handle the full analysis flow of signals recorded by high purity Ge detectors and photo-multipliers from the veto counters. It is designed to support a multi-channel modular and flexible analysis, widely customizable by the user either via human-readable initialization files or via a graphical interface. The framework organizes the data into a multi-level structure, from the raw data up to the condensed analysis parameters, and includes tools and utilities to handle the data stream between the different levels. GELATIO is implemented in C++. It relies upon ROOT and its extension TAM, which provides compatibility with PROOF, enabling the software to run in parallel on clusters of computers or many-core machines. It was tested on different platforms and benchmarked in several GERDA-related applications. A stable version is presently available for the GERDA Collaboration and it is used to provide the reference analysis of the experiment data.

GELATIO: a general framework for modular digital analysis of high-purity Ge detector signals

Science.gov (United States)

Agostini, M.; Pandola, L.; Zavarise, P.; Volynets, O.

2011-08-01

GELATIO is a new software framework for advanced data analysis and digital signal processing developed for the GERDA neutrinoless double beta decay experiment. The framework is tailored to handle the full analysis flow of signals recorded by high purity Ge detectors and photo-multipliers from the veto counters. It is designed to support a multi-channel modular and flexible analysis, widely customizable by the user either via human-readable initialization files or via a graphical interface. The framework organizes the data into a multi-level structure, from the raw data up to the condensed analysis parameters, and includes tools and utilities to handle the data stream between the different levels. GELATIO is implemented in C++. It relies upon ROOT and its extension TAM, which provides compatibility with PROOF, enabling the software to run in parallel on clusters of computers or many-core machines. It was tested on different platforms and benchmarked in several GERDA-related applications. A stable version is presently available for the GERDA Collaboration and it is used to provide the reference analysis of the experiment data.

Characterization of transient noise in Advanced LIGO relevant to gravitational wave signal GW150914

NARCIS (Netherlands)

Abbott, B. P.; Abbott, R.; Abbott, T. D.; Abernathy, M. R.; Acernese, F.; Ackley, K.; Adamo, M.; Adams, C.; Phythian-Adams, A.T.; Addesso, P.; Adhikari, R. X.; Adya, V. B.; Affeldt, C.; Agathos, M.; Agatsuma, K.; Aggarwal, N.T.; Aguiar, O. D.; Aiello, L.; Ain, A.; Ajith, P.; Allen, B.; Allocca, A.; Altin, P. A.; Anderson, S. B.; Anderson, W. G.; Arai, K.; Araya, M. C.; Arceneaux, C. C.; Areeda, J. S.; Arnaud, N.; Arun, K. G.; Ascenzi, S.; Ashton, G.; Ast, M.; Aston, S. M.; Astone, P.; Aufmuth, P.; Aulbert, C.; Babak, S.; Bacon, P.; Bader, M. K. M.; Baker, P. T.; Baldaccini, F.; Ballardin, G.; Ballmer, S. W.; Barayoga, J. C.; Barclay, S. E.; Barish, B. C.; Barker, R.D.; Barone, F.; Barr, B.; Barsotti, L.; Barsuglia, M.; Barta, D.; Bartlett, J.; Bartos, I.; Bassiri, R.; Basti, A.; Batch, J. C.; Baune, C.; Bavigadda, V.; Bazzan, M.; Behnke, B.; Bejger, M.; Bell, A. S.; Bell, C. J.; Berger, B. K.; Bergman, J.; Bergmann, G.; Berry, C. P. L.; Bersanetti, D.; Bertolini, A.; Betzwieser, J.; Bhagwat, S.; Bhandare, R.; Bilenko, I. A.; Billingsley, G.; Birch, M.J.; Birney, R.; Biscans, S.; Bisht, A.; Bitossi, M.; Biwer, C.; Bizouard, M. A.; Blackburn, J. K.; Blackburn, L.; Blair, C. D.; Blair, D. G.; Blair, R. M.; Bloemen, A.L.S.; Bock, O.; Bodiya, T. P.; Boer, M.; Bogaert, J.G.; Bogan, C.; Bohe, A.; Bojtos, P.; Bond, T.C; Bondu, F.; Bonnand, R.; Boom, B. A.; Bork, R.; Boschi, V.; Bose, S.; Bouffanais, Y.; Bozzi, A.; Bradaschia, C.; Brady, P. R.; Braginsky, V. B.; Branchesi, M.; Brau, J. E.; Briant, T.; Brillet, A.; Brinkmann, M.; Brisson, V.; Brockill, P.; Brooks, A. F.; Brown, A.D.; Brown, D.; Brown, N. M.; Buchanan, C. C.; Buikema, A.; Bulik, T.; Bulten, H. J.; Buonanno, A.; Buskulic, D.; Buy, C.; Byer, R. L.; Cadonati, L.; Cagnoli, G.; Cahillane, C.; Calderon Bustillo, J.; Callister, T. A.; Calloni, E.; Camp, J. B.; Cannon, K. C.; Cao, J.; Capano, C. D.; Capocasa, E.; Carbognani, F.; Caride, S.; Diaz, J. Casanueva; Casentini, C.; Caudill, S.; Cavaglia, M.; Cavalier, F.; Cavalieri, R.; Cella, G.; Cepeda, C. B.; Baiardi, L. Cerboni; Cerretani, G.; Cesarini, E.; Chakraborty, R.; Chalermsongsak, T.; Chamberlin, S. J.; Chan, M.; Chao, D. S.; Charlton, P.; Charlton, P.; Chassande-Mottin, E.; Chatterji, S.; Chen, H. Y.; Chen, Y; Cheng, C.; Chincarini, A.; Chiummo, A.; Cho, H. S.; Cho, M.; Chow, J. H.; Christensen, N.; Chu, Qian; Chua, S. E.; Chung, E.S.; Ciani, G.; Clara, F.; Clark, J. A.; Cleva, F.; Coccia, E.; Cohadon, P. -F.; Colla, A.; Collette, C. G.; Cominsky, L.; Conte, A.; Conti, L.; Cook, D.; Corbitt, T. R.; Cornish, N.; Corsi, A.; Cortese, S.; Costa, A.C.; Coughlin, M. W.; Coughlin, S. B.; Coulon, J. -P.; Countryman, S. T.; Couvares, P.; Cowan, E. E.; Coward, D. M.; Cowart, M. J.; Coyne, D. C.; Coyne, R.; Craig, K.; Creighton, J. D. E.; Cripe, J.; Crowder, S. G.; Cumming, A.; Cunningham, A.L.; Cuoco, E.; Dal Canton, T.; Danilishin, S. L.; D'Antonio, S.; Danzmann, K.; Darman, N. S.; Dattilo, V.; Dave, I.; Daveloza, H. P.; Davier, M.; Davies, G. S.; Daw, E. J.; Day, R.; Debra, D.; Debreczeni, G.; Degallaix, J.; De laurentis, M.; Deleglise, S.; Del Pozzo, W.; Denker, T.; Dent, T.; Dereli, H.; Dergachev, V.A.; DeRosa, R. T.; Rosa, R.; DeSalvo, R.; Dhurandhar, S.; Diaz, M. C.; Di Fiore, L.; Giovanni, M.G.; Di Lieto, A.; Di Pace, S.; Di Palma, I.; Di Virgilio, A.; Dojcinoski, G.; Dolique, V.; Donovan, F.; Dooley, K. L.; Doravari, S.; Douglas, R.; Downes, T. P.; Drago, M.; Drever, R. W. P.; Driggers, J. C.; Du, Z.; Ducrot, M.; Dwyer, S. E.; Edo, T. B.; Edwards, M. C.; Effler, A.; Eggenstein, H. -B.; Ehrens, P.; Eichholz, J.; Eikenberry, S. S.; Engels, W.; Essick, R. C.; Etzel, T.; Evans, T. M.; Evans, T. M.; Everett, R.; Factourovich, M.; Fafone, V.; Fair, H.; Fairhurst, S.; Fan, X.M.; Fang, Q.; Farinon, S.; Farr, B.; Farr, W. M.; Favata, M.; Fays, M.; Fehrmann, H.; Fejer, M. M.; Ferrante, I.; Ferreira, E. C.; Ferrini, F.; Fidecaro, F.; Fiori, I.; Fiorucci, D.; Fisher, R. P.; Flaminio, R.; Fletcher, M; Fournier, J. -D.; Franco, S; Frasca, S.; Frasconi, F.; Frei, Z.; Freise, A.; Frey, R.; Frey, V.; Fricke, T. T.; Fritschel, P.; Frolov, V. V.; Fulda, P.; Fyffe, M.; Gabbard, H. A. G.; Gair, J. R.; Gammaitoni, L.; Gaonkar, S. G.; Garufi, F.; Gatto, A.; Gaur, G.; Gehrels, N.; Gemme, G.; Gendre, B.; Genin, E.; Gennai, A.; George, J.; Gergely, L.; Ghosh, V. Germain Archisman; Ghosh, S.; Giaime, J. A.; Giardina, K. D.; Giazotto, A.; Gill, K.P.; Glaefke, A.; Goetz, E.; Goetz, R.; Gondan, L.; Gonzlez, G.; Castro, J. M. Gonzalez; Gopakumar, A.; Gordon, N. A.; Gorodetsky, M. L.; Gossan, S. E.; Lee-Gosselin, M.; Gouaty, R.; Graef, C.; Graff, P. B.; Granata, M.; Grant, A.; Gras, S.; Gray, C.M.; Greco, G.; Green, A. C.; Groot, P.; Grote, H.; Grunewald, S.; Guidi, G. M.; Guo, X.; Gupta, A.; Gupta, M. K.; Gushwa, K. E.; Gustafson, E. K.; Gustafson, R.; Hacker, J. J.; Buffoni-Hall, R.; Hall, E. D.; Hammond, G.L.; Haney, M.; Hanke, M. M.; Hanks, J.; Hanna, C.; Hannam, M. D.; Hanson, P.J.; Hardwick, T.; Harms, J.; Harry, G. M.; Harry, I. W.; Hart, M. J.; Hartman, M. T.; Haster, C. -J.; Haughian, K.; Heidmann, A.; Heintze, M. C.; Heitmann, H.; Hello, P.; Hemming, G.; Hendry, M.; Heng, I. S.; Hennig, J.; Heptonstall, A. W.; Heurs, M.; Hild, S.; Hoak, D.; Hodge, K. A.; Hofman, D.; Hollitt, S. E.; Holt, K.; Holz, D. E.; Hopkins, P.; Hosken, D. J.; Hough, J.; Houston, E. A.; Howell, E. J.; Hu, Y. M.; Huang, S.; Huerta, E. A.; Huet, D.; Hughey, B.; Husa, S.; Huttner, S. H.; Huynh-Dinh, T.; Idrisy, A.; Indik, N.; Ingram, D. R.; Inta, R.; Isa, H. N.; Isac, J. -M.; Isi, M.; Islas, G.; Isogai, T.; Iyer, B. R.; Izumi, K.; Jacqmin, T.; Jang, D.H.; Jani, K.; Jaranowski, P.; Jawahar, S.; Jimenez-Forteza, F.; Johnson, W.; Jones, I.D.; Jones, R.; Jonker, R. J. G.; Ju, L.; Haris, K.; Kalaghatgi, C. V.; Kalogera, V.; Kandhasamy, S.; Kang, G.H.; Kanner, J. B.; Karki, S.; Kasprzack, M.; Katsavounidis, E.; Katzman, W.; Kaufer, S.; Kaur, T.; Kawabe, K.; Kawazoe, F.; Kefelian, F.; Kehl, M. S.; Keitel, D.; Kelley, D. B.; Kells, W.; Kennedy, R.E.; Key, J. S.; Khalaidovski, A.; Khalili, F. Y.; Khan, I.; Khan., S.; Khan, Z.; Khazanov, E. A.; Kijbunchoo, N.; Kim, C.; Kim, J.; Kim, K.; Kim, Nam-Gyu; Kim, Namjun; Kim, Y.M.; King, E. J.; King, P. J.; Kinzel, D. L.; Kissel, J. S.; Kleybolte, L.; Klimenko, S.; Koehlenbeck, S. M.; Kokeyama, K.; Koley, S.; Kondrashov, V.; Kontos, A.; Korobko, M.; Korth, W. Z.; Kowalska, I.; Kozak, D. B.; Kringel, V.; Krishnan, B.; Krolak, A.; Krueger, C.; Kuehn, G.; Kumar, P.; Kuo, L.; Kutynia, A.; Lackey, B. D.; Landry, M.; Lange, J.; Lantz, B.; Lasky, P. D.; Lazzarini, A.; Lazzaro, C.; Leaci, P.; Leavey, S.; Lebigot, E. O.; Lee, C.H.; Lee, K.H.; Lee, M.H.; Lee, K.; Lenon, A.; Leonardi, M.; Leong, J. R.; Leroy, N.; Letendre, N.; Levin, Y.; Levine, B. M.; Li, T. G. F.; Libson, A.; Littenberg, T. B.; Lockerbie, N. A.; Logue, J.; Lombardi, A. L.; Lord, J. E.; Lorenzini, M.; Loriette, V.; Lormand, M.; Losurdo, G.; Lough, J. D.; Lueck, H.; Lundgren, A. P.; Luo, J.; Lynch, R.; Ma, Y.; MacDonald, T.T.; Machenschalk, B.; MacInnis, M.; Macleod, D. M.; Magana-Sandoval, F.; Magee, R. M.; Mageswaran, M.; Majorana, E.; Maksimovic, I.; Malvezzi, V.; Man, N.; Mandel, I.; Mandic, V.; Mangano, V.; Mansell, G. L.; Manske, M.; Mantovani, M.; Marchesoni, F.; Marion, F.; Marka, S.; Marka, Z.; Markosyan, A. S.; Maros, E.; Martelli, F.; Martellini, L.; Martin, I. W.; Martin, R.M.; Martynov, D. V.; Marx, J. N.; Mason, K.; Masserot, A.; Massinger, T. J.; Masso-Reid, M.; Matichard, F.; Matone, L.; Mavalvala, N.; Mazumder, N.; Mazzolo, G.; McCarthy, R.; McClelland, D. E.; McCormick, S.; McGuire, S. C.; McIntyre, G.; McIver, J.; McManus, D. J.; McWilliams, S. T.; Meacher, D.; Meadors, G. D.; Meidam, J.; Melatos, A.; Mendell, G.; Mendoza-Gandara, D.; Mercer, R. A.; Merilh, E. L.; Merzougui, M.; Meshkov, S.; Messenger, C.; Messick, C.; Meyers, P. M.; Mezzani, F.; Miao, H.; Michel, C.; Middleton, H.; Mikhailov, E. E.; Milano, L.; Miller, J.; Millhouse, M.; Minenkov, Y.; Ming, J.; Mirshekari, S.; Mishra, C.; Mitra, S.; Mitrofanov, V. P.; Mitselmakher, G.; Mittleman, R.; Moggi, A.; Mohan, M.; Mohapatra, S. R. P.; Montani, M.; Moore, B.C.; Moore, J.C.; Moraru, D.; Gutierrez Moreno, M.; Morriss, S. R.; Mossavi, K.; Mours, B.; Mow-Lowry, C. M.; Mueller, C. L.; Mueller, G.; Muir, A. W.; Mukherjee, Arunava; Mukherjee, S.D.; Mukherjee, S.; Mukund, N.; Mullavey, A.; Munch, J.; Murphy, D. J.; Murray, P.G.; Mytidis, A.; Nardecchia, I.; Naticchioni, L.; Nayak, R. K.; Necula, V.; Nedkova, K.; Nelemans, G.; Gutierrez-Neri, M.; Neunzert, A.; Newton-Howes, G.; Nguyen, T. T.; Nielsen, A. B.; Nissanke, S.; Nitz, A.; Nocera, F.; Nolting, D.; Normandin, M. E. N.; Nuttall, L. K.; Oberling, J.; Ochsner, E.; O'Dell, J.; Oelker, E.; Ogin, G. H.; Oh, J.; Oh, S. H.; Ohme, F.; Oliver, M. B.; Oppermann, P.; Oram, Richard J.; O'Reilly, B.; O'Shaughnessy, R.; Ottaway, D. J.; Ottens, R. S.; Overmier, H.; Owen, B. J.; Pai, A.; Pai, S. A.; Palamos, J. R.; Palashov, O.; Palomba, C.; Pal-Singh, A.; Pan, H.; Pankow, C.; Pannarale, F.; Pant, B. C.; Paoletti, F.; Paoli, A.; Papa, M. A.; Paris, H. R.; Parker, W.S; Pascucci, D.; Pasqualetti, A.; Passaquieti, R.; Passuello, D.; Patricelli, B.; Patrick, Z.; Pearlstone, B. L.; Pedraza, M.; Pedurand, R.; Pekowsky, L.; Pele, A.; Penn, S.; Perreca, A.; Phelps, M.; Piccinni, O. J.; Pichot, M.; Piergiovanni, F.; Pierro, V.; Pillant, G.; Pinard, L.; Pinto, I. M.; Pitkin, M.; Poggiani, R.; Popolizio, P.; Post, A.; Powell, J.; Prasad, J.; Predoi, V.; Premachandra, S. S.; Prestegard, T.; Price, L. R.; Prijatelj, M.; Principe, M.; Privitera, S.; Prodi, G. A.; Prokhorov, L. G.; Puncken, O.; Punturo, M.; Puppo, P.; Puerrer, M.; Qi, H.; Qin, J.; Quetschke, V.; Quintero, E. A.; Quitzow-James, R.; Raab, F. J.; Rabeling, D. S.; Radkins, H.; Raffai, P.; Raja, S.; Rakhmanov, M.; Rapagnani, P.; Raymond, V.; Razzano, M.; Re, V.; Read, J.; Reed, C. M.; Regimbau, T.; Rei, L.; Reid, S.; Reitze, D. H.; Rew, H.; Reyes, S. D.; Ricci, F.; Riles, K.; Robertson, N. A.; Robie, R.; Robinet, F.; Rocchi, A.; Rolland, L.; Rollins, J. G.; Roma, V. J.; Romano, R.; Romanov, G.; Romie, J. H.; Rosinska, D.; Rowan, S.; Ruediger, A.; Ruggi, P.; Ryan, K.A.; Sachdev, P.S.; Sadecki, T.; Sadeghian, L.; Salconi, L.; Saleem, M.; Salemi, F.; Samajdar, A.; Sammut, L.; Sanchez, E. J.; Sandberg, V.; Sandeen, B.; Sanders, J. R.; Sassolas, B.; Sathyaprakash, B. S.; Saulson, P. R.; Sauter, O.; Savage, R. L.; Sawadsky, A.; Schale, P.; Schilling, R.; Schmidt, J; Schmidt, P.; Schnabel, R.B.; Schofield, R. M. S.; Schoenbeck, A.; Schreiber, K.E.C.; Schuette, D.; Schutz, B. F.; Scott, J.; Scott, M.S.; Sellers, D.; Sengupta, A. S.; Sentenac, D.; Sequino, V.; Sergeev, A.; Serna, G.; Setyawati, Y.; Sevigny, A.; Shaddock, D. A.; Shah, S.; Shahriar, M. S.; Shaltev, M.; Shao, Z.M.; Shapiro, B.; Shawhan, P.; Sheperd, A.; Shoemaker, D. H.; Shoemaker, D. M.; Siellez, K.; Siemens, X.; Sigg, D.; Silva, António Dias da; Simakov, D.; Singer, A; Singer, L. P.; Singh, A.; Singh, R.; Singhal, A.; Sintes, A. M.; Slagmolen, B. J. J.; Slutsky, J.; Smith, R. J. E.; Smith, N.D.; Smith, R. J. E.; Son, E. J.; Sorazu, B.; Sorrentino, F.; Souradeep, T.; Srivastava, A. K.; Staley, A.; Steinke, M.; Steinlechner, J.; Steinlechner, S.; Steinmeyer, D.; Stephens, B. C.; Stone, J.R.; Strain, K. A.; Straniero, N.; Stratta, G.; Strauss, N. A.; Strigin, S. E.; Sturani, R.; Stuver, A. L.; Summerscales, T. Z.; Sun, L.; Sutton, P. J.; Swinkels, B. L.; Szczepanczyk, M. J.; Tacca, M.D.; Talukder, D.; Tanner, D. B.; Tapai, M.; Tarabrin, S. P.; Taracchini, A.; Taylor, W.R.; Theeg, T.; Thirugnanasambandam, M. P.; Thomas, E. G.; Thomas, M.; Thomas, P.; Thorne, K. A.; Thorne, K. S.; Thrane, E.; Tiwari, S.; Tiwari, V.; Tokmakov, K. V.; Tomlinson, C.; Tonelli, M.; Torres, C. V.; Torrie, C. I.; Toyra, D.; Travasso, F.; Traylor, G.; Trifiro, D.; Tringali, M. C.; Trozzo, L.; Tse, M.; Turconi, M.; Tuyenbayev, D.; Ugolini, D.; Unnikrishnan, C. S.; Urban, A. L.; Usman, S. A.; Vahlbruch, H.; Vajente, G.; Valdes, G.; van Bakel, N.; Van Beuzekom, Martin; van den Brand, J. F. J.; Van Den Broeck, C.F.F.; Vander-Hyde, D. C.; van der Schaaf, L.; van Heijningen, J. V.; van Veggel, A. A.; Vardaro, M.; Vass, S.; Vasuth, M.; Vaulin, R.; Vecchio, A.; Vedovato, G.; Veitch, J.; Veitch, P.J.; Venkateswara, K.; Verkindt, D.; Vetrano, F.; Vicere, A.; Vinciguerra, S.; Vine, D. J.; Vinet, J. -Y.; Vitale, S.; Vo, T.; Vocca, H.; Vorvick, C.; Voss, D. V.; Vousden, W. D.; Vyatchanin, S. P.; Wade, A. R.; Wade, L. E.; Wade, MT; Walker, M.; Wallace, L.; Walsh, S.; Wang, G.; Wang, H.; Wang, M.; Wang, X.; Wang, Y.; Ward, R. L.; Warner, J.; Was, M.; Weaver, B.; Wei, L. -W.; Weinert, M.; Weinstein, A. J.; Weiss, R.; Welborn, T.; Wen, L.M.; Wessels, P.; Westphal, T.; Wette, K.; Whelan, J. T.; Whitcomb, S. E.; White, D. J.; Whiting, B. F.; Williams, D.R.; Williamson, A. R.; Willis, J. L.; Willke, B.; Wimmer, M. H.; Winkler, W.; Wipf, C. C.; Wittel, H.; Woan, G.; Worden, J.; Wright, J.L.; Wu, G.; Yablon, J.; Yam, W.; Yamamoto, H.; Yancey, C. C.; Yap, M. J.; Yu, H.; Yvert, M.; Zadrozny, A.; Zangrando, L.; Zanolin, M.; Zendri, J. -P.; Zevin, M.; Zhang, F.; Zhang, L.; Zhang, M.; Zhang, Y.; Zhao, C.; Zhou, M.; Zhou, Z.; Zhu, X. J.; Zotov, N.; Zucker, M. E.; Zuraw, S. E.; Zweizig, J.

2016-01-01

On 14 September 2015, a gravitational wave signal from a coalescing black hole binary system was observed by the Advanced LIGO detectors. This paper describes the transient noise backgrounds used to determine the significance of the event (designated GW150914) and presents the results of

Advanced spot quality analysis in two-colour microarray experiments

Directory of Open Access Journals (Sweden)

Vetter Guillaume

2008-09-01

Full Text Available Abstract Background Image analysis of microarrays and, in particular, spot quantification and spot quality control, is one of the most important steps in statistical analysis of microarray data. Recent methods of spot quality control are still in early age of development, often leading to underestimation of true positive microarray features and, consequently, to loss of important biological information. Therefore, improving and standardizing the statistical approaches of spot quality control are essential to facilitate the overall analysis of microarray data and subsequent extraction of biological information. Findings We evaluated the performance of two image analysis packages MAIA and GenePix (GP using two complementary experimental approaches with a focus on the statistical analysis of spot quality factors. First, we developed control microarrays with a priori known fluorescence ratios to verify the accuracy and precision of the ratio estimation of signal intensities. Next, we developed advanced semi-automatic protocols of spot quality evaluation in MAIA and GP and compared their performance with available facilities of spot quantitative filtering in GP. We evaluated these algorithms for standardised spot quality analysis in a whole-genome microarray experiment assessing well-characterised transcriptional modifications induced by the transcription regulator SNAI1. Using a set of RT-PCR or qRT-PCR validated microarray data, we found that the semi-automatic protocol of spot quality control we developed with MAIA allowed recovering approximately 13% more spots and 38% more differentially expressed genes (at FDR = 5% than GP with default spot filtering conditions. Conclusion Careful control of spot quality characteristics with advanced spot quality evaluation can significantly increase the amount of confident and accurate data resulting in more meaningful biological conclusions.

Evaluating lane-by-lane gap-out based signal control for isolated intersection under stop-line, single and multiple advance detection systems

Directory of Open Access Journals (Sweden)

Chandan Keerthi Kancharla

2016-12-01

Full Text Available In isolated intersection’s actuated signal control, inductive loop detector layout plays a crucial role in providingthe vehicle information to the signal controller. Based on vehicle actuations at the detector, the green time is extended till a pre-defined threshold gap-out occurs. The Federal Highway Administration (FHWA proposed various guidelines for detec-tor layouts on low-speed and high-speed approaches. This paper proposes single and multiple advance detection schemes for low-speed traffic movements, that utilizes vehicle actuations from advance detectors located upstream of the stop-line, which are able to detect spill-back queues. The proposed detection schemes operate with actuated signal control based on lane-by-lane gap-out criteria. The performance of the proposed schemes is compared with FHWA’s stop-line and single advance detection schemes in the VISSIM simulation tool. Results have shown that the proposed single advance detection schemes showed improved performance in reducing travel time delay and average number of stops per vehicle under low volumes while the multiple advance detection scheme performed well under high volumes.

Myostatin signaling is up-regulated in female patients with advanced heart failure.

Science.gov (United States)

Ishida, Junichi; Konishi, Masaaki; Saitoh, Masakazu; Anker, Markus; Anker, Stefan D; Springer, Jochen

2017-07-01

Myostatin, a negative regulator of skeletal muscle mass, is up-regulated in the myocardium of heart failure (HF) and increased myostatin is associated with weight loss in animal models with HF. Although there are disparities in pathophysiology and epidemiology between male and female patients with HF, it remains unclear whether there is gender difference in myostatin expression and whether it is associated with weight loss in HF patients. Heart tissue samples were collected from patients with advanced heart failure (n=31, female n=5) as well as healthy control donors (n=14, female n=6). Expression levels of myostatin and its related proteins in the heart were evaluated by western blotting analysis. Body mass index was significantly lower in female HF patients than in male counterparts (20.0±4.2 in female vs 25.2±3.8 in male, p=0.04). In female HF patients, both mature myostatin and pSmad2 were significantly up-regulated by 1.9 fold (p=0.05) and 2.5 fold (pmyostatin was not. There was no significant difference in protein expression related to myostatin signaling between male and female patients. In this study, myostatin and pSmad2 were significantly up-regulated in the failing heart of female patients, but not male patients, and female patients displayed lower body mass index. Enhanced myostatin signaling in female failing heart may causally contribute to pathogenesis of HF and cardiac cachexia. Copyright © 2017 Elsevier B.V. All rights reserved.

Advanced digital signal processing for short haul optical fiber transmission beyond 100G

Science.gov (United States)

Kikuchi, Nobuhiko

2017-01-01

Significant increase of intra and inter data center traffic has been expected by the rapid spread of various network applications like SNS, IoT, mobile and cloud computing, and the needs for ultra-high speed and cost-effective short- to medium-reach optical fiber links beyond 100-Gbit/s is becoming larger and larger. Such high-speed links typically use multilevel modulation to lower signaling speed, which in turn face serious challenges in limited loss budget and waveform distortion tolerance. One of the promising techniques to overcome them is the use of advanced digital signal processing (DSP) and we review various DSP applications for short-to-medium reach applications.

Signal-dependent independent component analysis by tunable mother wavelets

International Nuclear Information System (INIS)

Seo, Kyung Ho

2006-02-01

The objective of this study is to improve the standard independent component analysis when applied to real-world signals. Independent component analysis starts from the assumption that signals from different physical sources are statistically independent. But real-world signals such as EEG, ECG, MEG, and fMRI signals are not statistically independent perfectly. By definition, standard independent component analysis algorithms are not able to estimate statistically dependent sources, that is, when the assumption of independence does not hold. Therefore before independent component analysis, some preprocessing stage is needed. This paper started from simple intuition that wavelet transformed source signals by 'well-tuned' mother wavelet will be simplified sufficiently, and then the source separation will show better results. By the correlation coefficient method, the tuning process between source signal and tunable mother wavelet was executed. Gamma component of raw EEG signal was set to target signal, and wavelet transform was executed by tuned mother wavelet and standard mother wavelets. Simulation results by these wavelets was shown

Characterization of Transient Noise in Advanced LIGO Relevant to Gravitational Wave Signal GW150914

Science.gov (United States)

Abbott, B. P.; Abbott, R.; Abbott, T. D.; Abernathy, M. R.; Acernese, F.; Ackley, K.; Adamo, M.; Adams, C.; Adams, T.; Camp, Jordan B.

2016-01-01

On 14 September 2015, a gravitational wave signal from a coalescing black hole binary system was observed by the Advanced LIGO detectors. This paper describes the transient noise backgrounds used to determine the significance of the event (designated GW150914) and presents the results of investigations into potential correlated or uncorrelated sources of transient noise in the detectors around the time of the event. The detectors were operating nominally at the time of GW150914. We have ruled out environmental influences and non-Gaussian instrument noise at either LIGO detector as the cause of the observed gravitational wave signal.

Analog and digital signal analysis from basics to applications

CERN Document Server

Cohen Tenoudji, Frédéric

2016-01-01

This book provides comprehensive, graduate-level treatment of analog and digital signal analysis suitable for course use and self-guided learning. This expert text guides the reader from the basics of signal theory through a range of application tools for use in acoustic analysis, geophysics, and data compression. Each concept is introduced and explained step by step, and the necessary mathematical formulae are integrated in an accessible and intuitive way. The first part of the book explores how analog systems and signals form the basics of signal analysis. This section covers Fourier series and integral transforms of analog signals, Laplace and Hilbert transforms, the main analog filter classes, and signal modulations. Part II covers digital signals, demonstrating their key advantages. It presents z and Fourier transforms, digital filtering, inverse filters, deconvolution, and parametric modeling for deterministic signals. Wavelet decomposition and reconstruction of non-stationary signals are also discussed...

Compressive Sensing: Analysis of Signals in Radio Astronomy

Directory of Open Access Journals (Sweden)

Gaigals G.

2013-12-01

Full Text Available The compressive sensing (CS theory says that for some kind of signals there is no need to keep or transfer all the data acquired accordingly to the Nyquist criterion. In this work we investigate if the CS approach is applicable for recording and analysis of radio astronomy (RA signals. Since CS methods are applicable for the signals with sparse (and compressible representations, the compressibility of RA signals is verified. As a result, we identify which RA signals can be processed using CS, find the parameters which can improve or degrade CS application to RA results, describe the optimum way how to perform signal filtering in CS applications. Also, a range of virtual LabVIEW instruments are created for the signal analysis with the CS theory.

Signal analysis for failure detection

International Nuclear Information System (INIS)

Parpaglione, M.C.; Perez, L.V.; Rubio, D.A.; Czibener, D.; D'Attellis, C.E.; Brudny, P.I.; Ruzzante, J.E.

1994-01-01

Several methods for analysis of acoustic emission signals are presented. They are mainly oriented to detection of changes in noisy signals and characterization of higher amplitude discrete pulses or bursts. The aim was to relate changes and events with failure, crack or wear in materials, being the final goal to obtain automatic means of detecting such changes and/or events. Performance evaluation was made using both simulated and laboratory test signals. The methods being presented are the following: 1. Application of the Hopfield Neural Network (NN) model for classifying faults in pipes and detecting wear of a bearing. 2. Application of the Kohonnen and Back Propagation Neural Network model for the same problem. 3. Application of Kalman filtering to determine time occurrence of bursts. 4. Application of a bank of Kalman filters (KF) for failure detection in pipes. 5. Study of amplitude distribution of signals for detecting changes in their shape. 6. Application of the entropy distance to measure differences between signals. (author). 10 refs, 11 figs

Signal analysis of Hindustani classical music

CERN Document Server

Datta, Asoke Kumar; Sengupta, Ranjan; Chakraborty, Soubhik; Mahto, Kartik; Patranabis, Anirban

2017-01-01

This book presents a comprehensive overview of the basics of Hindustani music and the associated signal analysis and technological developments. It begins with an in-depth introduction to musical signal analysis and its current applications, and then moves on to a detailed discussion of the features involved in understanding the musical meaning of the signal in the context of Hindustani music. The components consist of tones, shruti, scales, pitch duration and stability, raga, gharana and musical instruments. The book covers the various technological developments in this field, supplemented with a number of case studies and their analysis. The book offers new music researchers essential insights into the use of the automatic concept for finding and testing the musical features for their applications. Intended primarily for postgraduate and PhD students working in the area of scientific research on Hindustani music, as well as other genres where the concepts are applicable, it is also a valuable resource for p...

An integrative omics perspective for the analysis of chemical signals in ecological interactions.

Science.gov (United States)

Brunetti, A E; Carnevale Neto, F; Vera, M C; Taboada, C; Pavarini, D P; Bauermeister, A; Lopes, N P

2018-03-05

All living organisms emit, detect, and respond to chemical stimuli, thus creating an almost limitless number of interactions by means of chemical signals. Technological and intellectual advances in the last two decades have enabled chemical signals analyses at several molecular levels, including gene expression, molecular diversity, and receptor affinity. These advances have also deepened our understanding of nature to encompass interactions at multiple organism levels across different taxa. This tutorial review describes the most recent analytical developments in 'omics' technologies (i.e., genomics, transcriptomics, proteomics, and metabolomics) and provide recent examples of its application in studies of chemical signals. We highlight how studies have integrated an enormous amount of information generated from different omics disciplines into one publicly available platform. In addition, we stress the importance of considering different signal modalities and an evolutionary perspective to establish a comprehensive understanding of chemical communication.

MetaboLab - advanced NMR data processing and analysis for metabolomics

Directory of Open Access Journals (Sweden)

Günther Ulrich L

2011-09-01

Full Text Available Abstract Background Despite wide-spread use of Nuclear Magnetic Resonance (NMR in metabolomics for the analysis of biological samples there is a lack of graphically driven, publicly available software to process large one and two-dimensional NMR data sets for statistical analysis. Results Here we present MetaboLab, a MATLAB based software package that facilitates NMR data processing by providing automated algorithms for processing series of spectra in a reproducible fashion. A graphical user interface provides easy access to all steps of data processing via a script builder to generate MATLAB scripts, providing an option to alter code manually. The analysis of two-dimensional spectra (1H,13C-HSQC spectra is facilitated by the use of a spectral library derived from publicly available databases which can be extended readily. The software allows to display specific metabolites in small regions of interest where signals can be picked. To facilitate the analysis of series of two-dimensional spectra, different spectra can be overlaid and assignments can be transferred between spectra. The software includes mechanisms to account for overlapping signals by highlighting neighboring and ambiguous assignments. Conclusions The MetaboLab software is an integrated software package for NMR data processing and analysis, closely linked to the previously developed NMRLab software. It includes tools for batch processing and gives access to a wealth of algorithms available in the MATLAB framework. Algorithms within MetaboLab help to optimize the flow of metabolomics data preparation for statistical analysis. The combination of an intuitive graphical user interface along with advanced data processing algorithms facilitates the use of MetaboLab in a broader metabolomics context.

Advancing Alternative Analysis: Integration of Decision Science.

Science.gov (United States)

Malloy, Timothy F; Zaunbrecher, Virginia M; Batteate, Christina M; Blake, Ann; Carroll, William F; Corbett, Charles J; Hansen, Steffen Foss; Lempert, Robert J; Linkov, Igor; McFadden, Roger; Moran, Kelly D; Olivetti, Elsa; Ostrom, Nancy K; Romero, Michelle; Schoenung, Julie M; Seager, Thomas P; Sinsheimer, Peter; Thayer, Kristina A

2017-06-13

Decision analysis-a systematic approach to solving complex problems-offers tools and frameworks to support decision making that are increasingly being applied to environmental challenges. Alternatives analysis is a method used in regulation and product design to identify, compare, and evaluate the safety and viability of potential substitutes for hazardous chemicals. We assessed whether decision science may assist the alternatives analysis decision maker in comparing alternatives across a range of metrics. A workshop was convened that included representatives from government, academia, business, and civil society and included experts in toxicology, decision science, alternatives assessment, engineering, and law and policy. Participants were divided into two groups and were prompted with targeted questions. Throughout the workshop, the groups periodically came together in plenary sessions to reflect on other groups' findings. We concluded that the further incorporation of decision science into alternatives analysis would advance the ability of companies and regulators to select alternatives to harmful ingredients and would also advance the science of decision analysis. We advance four recommendations: a ) engaging the systematic development and evaluation of decision approaches and tools; b ) using case studies to advance the integration of decision analysis into alternatives analysis; c ) supporting transdisciplinary research; and d ) supporting education and outreach efforts. https://doi.org/10.1289/EHP483.

Photoacoustic signal and noise analysis for Si thin plate: signal correction in frequency domain.

Science.gov (United States)

Markushev, D D; Rabasović, M D; Todorović, D M; Galović, S; Bialkowski, S E

2015-03-01

Methods for photoacoustic signal measurement, rectification, and analysis for 85 μm thin Si samples in the 20-20 000 Hz modulation frequency range are presented. Methods for frequency-dependent amplitude and phase signal rectification in the presence of coherent and incoherent noise as well as distortion due to microphone characteristics are presented. Signal correction is accomplished using inverse system response functions deduced by comparing real to ideal signals for a sample with well-known bulk parameters and dimensions. The system response is a piece-wise construction, each component being due to a particular effect of the measurement system. Heat transfer and elastic effects are modeled using standard Rosencweig-Gersho and elastic-bending theories. Thermal diffusion, thermoelastic, and plasmaelastic signal components are calculated and compared to measurements. The differences between theory and experiment are used to detect and correct signal distortion and to determine detector and sound-card characteristics. Corrected signal analysis is found to faithfully reflect known sample parameters.

Conditional Random Fields for Morphological Analysis of Wireless ECG Signals

OpenAIRE

Natarajan, Annamalai; Gaiser, Edward; Angarita, Gustavo; Malison, Robert; Ganesan, Deepak; Marlin, Benjamin

2014-01-01

Thanks to advances in mobile sensing technologies, it has recently become practical to deploy wireless electrocardiograph sensors for continuous recording of ECG signals. This capability has diverse applications in the study of human health and behavior, but to realize its full potential, new computational tools are required to effectively deal with the uncertainty that results from the noisy and highly non-stationary signals collected using these devices. In this work, we present a novel app...

Safety analysis of urban signalized intersections under mixed traffic.

Science.gov (United States)

S, Anjana; M V L R, Anjaneyulu

2015-02-01

This study examined the crash causative factors of signalized intersections under mixed traffic using advanced statistical models. Hierarchical Poisson regression and logistic regression models were developed to predict the crash frequency and severity of signalized intersection approaches. The prediction models helped to develop general safety countermeasures for signalized intersections. The study shows that exclusive left turn lanes and countdown timers are beneficial for improving the safety of signalized intersections. Safety is also influenced by the presence of a surveillance camera, green time, median width, traffic volume, and proportion of two wheelers in the traffic stream. The factors that influence the severity of crashes were also identified in this study. As a practical application, the safe values of deviation of green time provided from design green time, with varying traffic volume, is presented in this study. This is a useful tool for setting the appropriate green time for a signalized intersection approach with variations in the traffic volume. Copyright © 2014 Elsevier Ltd. All rights reserved.

Advanced signal separation and recovery algorithms for digital x-ray spectroscopy

International Nuclear Information System (INIS)

Mahmoud, Imbaby I.; El-Tokhy, Mohamed S.

2015-01-01

X-ray spectroscopy is widely used for in-situ applications for samples analysis. Therefore, spectrum drawing and assessment of x-ray spectroscopy with high accuracy is the main scope of this paper. A Silicon Lithium Si(Li) detector that cooled with a nitrogen is used for signal extraction. The resolution of the ADC is 12 bits. Also, the sampling rate of ADC is 5 MHz. Hence, different algorithms are implemented. These algorithms were run on a personal computer with Intel core TM i5-3470 CPU and 3.20 GHz. These algorithms are signal preprocessing, signal separation and recovery algorithms, and spectrum drawing algorithm. Moreover, statistical measurements are used for evaluation of these algorithms. Signal preprocessing based on DC-offset correction and signal de-noising is performed. DC-offset correction was done by using minimum value of radiation signal. However, signal de-noising was implemented using fourth order finite impulse response (FIR) filter, linear phase least-square FIR filter, complex wavelet transforms (CWT) and Kalman filter methods. We noticed that Kalman filter achieves large peak signal to noise ratio (PSNR) and lower error than other methods. However, CWT takes much longer execution time. Moreover, three different algorithms that allow correction of x-ray signal overlapping are presented. These algorithms are 1D non-derivative peak search algorithm, second derivative peak search algorithm and extrema algorithm. Additionally, the effect of signal separation and recovery algorithms on spectrum drawing is measured. Comparison between these algorithms is introduced. The obtained results confirm that second derivative peak search algorithm as well as extrema algorithm have very small error in comparison with 1D non-derivative peak search algorithm. However, the second derivative peak search algorithm takes much longer execution time. Therefore, extrema algorithm introduces better results over other algorithms. It has the advantage of recovering and

Development of advanced MCR task analysis methods

International Nuclear Information System (INIS)

Na, J. C.; Park, J. H.; Lee, S. K.; Kim, J. K.; Kim, E. S.; Cho, S. B.; Kang, J. S.

2008-07-01

This report describes task analysis methodology for advanced HSI designs. Task analyses was performed by using procedure-based hierarchical task analysis and task decomposition methods. The results from the task analysis were recorded in a database. Using the TA results, we developed static prototype of advanced HSI and human factors engineering verification and validation methods for an evaluation of the prototype. In addition to the procedure-based task analysis methods, workload estimation based on the analysis of task performance time and analyses for the design of information structure and interaction structures will be necessary

Multitaper spectral analysis of atmospheric radar signals

Directory of Open Access Journals (Sweden)

V. K. Anandan

2004-11-01

Full Text Available Multitaper spectral analysis using sinusoidal taper has been carried out on the backscattered signals received from the troposphere and lower stratosphere by the Gadanki Mesosphere-Stratosphere-Troposphere (MST radar under various conditions of the signal-to-noise ratio. Comparison of study is made with sinusoidal taper of the order of three and single tapers of Hanning and rectangular tapers, to understand the relative merits of processing under the scheme. Power spectra plots show that echoes are better identified in the case of multitaper estimation, especially in the region of a weak signal-to-noise ratio. Further analysis is carried out to obtain three lower order moments from three estimation techniques. The results show that multitaper analysis gives a better signal-to-noise ratio or higher detectability. The spectral analysis through multitaper and single tapers is subjected to study of consistency in measurements. Results show that the multitaper estimate is better consistent in Doppler measurements compared to single taper estimates. Doppler width measurements with different approaches were studied and the results show that the estimation was better in the multitaper technique in terms of temporal resolution and estimation accuracy.

Advanced optical signal processing of broadband parallel data signals

DEFF Research Database (Denmark)

Oxenløwe, Leif Katsuo; Hu, Hao; Kjøller, Niels-Kristian

2016-01-01

Optical signal processing may aid in reducing the number of active components in communication systems with many parallel channels, by e.g. using telescopic time lens arrangements to perform format conversion and allow for WDM regeneration.......Optical signal processing may aid in reducing the number of active components in communication systems with many parallel channels, by e.g. using telescopic time lens arrangements to perform format conversion and allow for WDM regeneration....

Quantitative analysis of phosphoinositide 3-kinase (PI3K) signaling using live-cell total internal reflection fluorescence (TIRF) microscopy.

Science.gov (United States)

Johnson, Heath E; Haugh, Jason M

2013-12-02

This unit focuses on the use of total internal reflection fluorescence (TIRF) microscopy and image analysis methods to study the dynamics of signal transduction mediated by class I phosphoinositide 3-kinases (PI3Ks) in mammalian cells. The first four protocols cover live-cell imaging experiments, image acquisition parameters, and basic image processing and segmentation. These methods are generally applicable to live-cell TIRF experiments. The remaining protocols outline more advanced image analysis methods, which were developed in our laboratory for the purpose of characterizing the spatiotemporal dynamics of PI3K signaling. These methods may be extended to analyze other cellular processes monitored using fluorescent biosensors. Copyright © 2013 John Wiley & Sons, Inc.

Radar signal analysis and processing using Matlab

CERN Document Server

Mahafza, Bassem R

2008-01-01

Offering radar-related software for the analysis and design of radar waveform and signal processing, this book provides comprehensive coverage of radar signals and signal processing techniques and algorithms. It contains numerous graphical plots, common radar-related functions, table format outputs, and end-of-chapter problems. The complete set of MATLAB[registered] functions and routines are available for download online.

On semi-classical questions related to signal analysis

KAUST Repository

Helffer, Bernard

2011-12-01

This study explores the reconstruction of a signal using spectral quantities associated with some self-adjoint realization of an h-dependent Schrödinger operator -h2(d2/dx2)-y(x), h>0, when the parameter h tends to 0. Theoretical results in semi-classical analysis are proved. Some numerical results are also presented. We first consider as a toy model the sech2 function. Then we study a real signal given by arterial blood pressure measurements. This approach seems to be very promising in signal analysis. Indeed it provides new spectral quantities that can give relevant information on some signals as it is the case for arterial blood pressure signal. © 2011 - IOS Press and the authors. All rights reserved.

Possibilities for Advanced Encoding Techniques at Signal Transmission in the Optical Transmission Medium

Directory of Open Access Journals (Sweden)

Filip Čertík

2016-01-01

Full Text Available This paper presents a possible simulation of negative effects in the optical transmission medium and an analysis for the utilization of different signal processing techniques at the optical signal transmission. An attention is focused on the high data rate signal transmission in the optical fiber influenced by linear and nonlinear environmental effects presented by the prepared simulation model. The analysis includes possible utilization of OOK, BPSK, DBPSK, BFSK, QPSK, DQPSK, 8PSK, and 16QAM modulation techniques together with RS, BCH, and LDPC encoding techniques for the signal transmission in the optical fiber. Moreover, the prepared simulation model is compared with real optical transmission systems. In the final part, a comparison of the selected modulation techniques with different encoding techniques and their implementation in real transmission systems is shown.

Advanced Concept Architecture Design and Integrated Analysis (ACADIA)

Science.gov (United States)

2017-11-03

1 Advanced Concept Architecture Design and Integrated Analysis (ACADIA) Submitted to the National Institute of Aerospace (NIA) on...Research Report 20161001 - 20161030 Advanced Concept Architecture Design and Integrated Analysis (ACADIA) W911NF-16-2-0229 8504Cedric Justin, Youngjun

Recent advances in understanding neurotrophin signaling.

Science.gov (United States)

Bothwell, Mark

2016-01-01

The nerve growth factor family of growth factors, collectively known as neurotrophins, are evolutionarily ancient regulators with an enormous range of biological functions. Reflecting this long history and functional diversity, mechanisms for cellular responses to neurotrophins are exceptionally complex. Neurotrophins signal through p75 (NTR), a member of the TNF receptor superfamily member, and through receptor tyrosine kinases (TrkA, TrkB, TrkC), often with opposite functional outcomes. The two classes of receptors are activated preferentially by proneurotrophins and mature processed neurotrophins, respectively. However, both receptor classes also possess neurotrophin-independent signaling functions. Signaling functions of p75 (NTR) and Trk receptors are each influenced by the other class of receptors. This review focuses on the mechanisms responsible for the functional interplay between the two neurotrophin receptor signaling systems.

Advanced midwifery practice: An evolutionary concept analysis.

Science.gov (United States)

Goemaes, Régine; Beeckman, Dimitri; Goossens, Joline; Shawe, Jill; Verhaeghe, Sofie; Van Hecke, Ann

2016-11-01

the concept of 'advanced midwifery practice' is explored to a limited extent in the international literature. However, a clear conception of advanced midwifery practice is vital to advance the discipline and to achieve both internal and external legitimacy. This concept analysis aims to clarify advanced midwifery practice and identify its components. a review of the literature was executed using Rodgers' evolutionary method of concept analysis to analyze the attributes, references, related terms, antecedents and consequences of advanced midwifery practice. an international consensus definition of advanced midwifery practice is currently lacking. Four major attributes of advanced midwife practitioners (AMPs) are identified: autonomy in practice, leadership, expertise, and research skills. A consensus was found on the need of preparation at master's level for AMPs. Such midwives have a broad and internationally varied scope of practice, fulfilling different roles such as clinicians, clinical and professional leaders, educators, consultants, managers, change agents, researchers, and auditors. Evidence illustrating the important part AMPs play on a clinical and strategic level is mounting. the findings of this concept analysis support a wide variety in the emergence, titles, roles, and scope of practice of AMPs. Research on clinical and strategic outcomes of care provided by AMPs supports further implementation of these roles. As the indistinctness of AMPs' titles and roles is one of the barriers for implementation, a clear conceptualization of advanced midwifery practice seems essential for successful implementation. an international debate and consensus on the defining elements of advanced midwifery practice could enhance the further development of midwifery as a profession and is a prerequisite for its successful implementation. Due to rising numbers of AMPs, extension of practice and elevated quality requirements in healthcare, more outcomes research exclusively

A Review on the Nonlinear Dynamical System Analysis of Electrocardiogram Signal.

Science.gov (United States)

Nayak, Suraj K; Bit, Arindam; Dey, Anilesh; Mohapatra, Biswajit; Pal, Kunal

2018-01-01

Electrocardiogram (ECG) signal analysis has received special attention of the researchers in the recent past because of its ability to divulge crucial information about the electrophysiology of the heart and the autonomic nervous system activity in a noninvasive manner. Analysis of the ECG signals has been explored using both linear and nonlinear methods. However, the nonlinear methods of ECG signal analysis are gaining popularity because of their robustness in feature extraction and classification. The current study presents a review of the nonlinear signal analysis methods, namely, reconstructed phase space analysis, Lyapunov exponents, correlation dimension, detrended fluctuation analysis (DFA), recurrence plot, Poincaré plot, approximate entropy, and sample entropy along with their recent applications in the ECG signal analysis.

Signal recovery in imaging photoplethysmography

International Nuclear Information System (INIS)

Holton, Benjamin D; Mannapperuma, Kavan; Lesniewski, Peter J; Thomas, John C

2013-01-01

Imaging photoplethysmography is an emerging technique for the extraction of biometric information from people using video recordings. The focus is on extracting the cardiac heart rate of the subject by analysing the luminance of the colour video signal and identifying periodic components. Advanced signal processing is needed to recover the information required. In this paper, independent component analysis (ICA), principal component analysis, auto- and cross-correlation are investigated and compared with respect to their effectiveness in extracting the relevant information from video recordings. Results obtained are compared with those recorded by a modern commercial finger pulse oximeter. It is found that ICA produces the most consistent results. (paper)

Signal recovery in imaging photoplethysmography.

Science.gov (United States)

Holton, Benjamin D; Mannapperuma, Kavan; Lesniewski, Peter J; Thomas, John C

2013-11-01

Imaging photoplethysmography is an emerging technique for the extraction of biometric information from people using video recordings. The focus is on extracting the cardiac heart rate of the subject by analysing the luminance of the colour video signal and identifying periodic components. Advanced signal processing is needed to recover the information required. In this paper, independent component analysis (ICA), principal component analysis, auto- and cross-correlation are investigated and compared with respect to their effectiveness in extracting the relevant information from video recordings. Results obtained are compared with those recorded by a modern commercial finger pulse oximeter. It is found that ICA produces the most consistent results.

A Review on the Nonlinear Dynamical System Analysis of Electrocardiogram Signal

Science.gov (United States)

Mohapatra, Biswajit

2018-01-01

Electrocardiogram (ECG) signal analysis has received special attention of the researchers in the recent past because of its ability to divulge crucial information about the electrophysiology of the heart and the autonomic nervous system activity in a noninvasive manner. Analysis of the ECG signals has been explored using both linear and nonlinear methods. However, the nonlinear methods of ECG signal analysis are gaining popularity because of their robustness in feature extraction and classification. The current study presents a review of the nonlinear signal analysis methods, namely, reconstructed phase space analysis, Lyapunov exponents, correlation dimension, detrended fluctuation analysis (DFA), recurrence plot, Poincaré plot, approximate entropy, and sample entropy along with their recent applications in the ECG signal analysis. PMID:29854361

Automatic analysis of signals during Eddy currents controls

International Nuclear Information System (INIS)

Chiron, D.

1983-06-01

A method and the corresponding instrument have been developed for automatic analysis of Eddy currents testing signals. This apparatus enables at the same time the analysis, every 2 milliseconds, of two signals at two different frequencies. It can be used either on line with an Eddy Current testing instrument or with a magnetic tape recorder [fr

Failure and damage analysis of advanced materials

CERN Document Server

Sadowski, Tomasz

2015-01-01

The papers in this volume present basic concepts and new developments in failure and damage analysis with focus on advanced materials such as composites, laminates, sandwiches and foams, and also new metallic materials. Starting from some mathematical foundations (limit surfaces, symmetry considerations, invariants) new experimental results and their analysis are shown. Finally, new concepts for failure prediction and analysis will be introduced and discussed as well as new methods of failure and damage prediction for advanced metallic and non-metallic materials. Based on experimental results the traditional methods will be revised.

Pattern theory the stochastic analysis of real-world signals

CERN Document Server

Mumford, David

2010-01-01

Pattern theory is a distinctive approach to the analysis of all forms of real-world signals. At its core is the design of a large variety of probabilistic models whose samples reproduce the look and feel of the real signals, their patterns, and their variability. Bayesian statistical inference then allows you to apply these models in the analysis of new signals. This book treats the mathematical tools, the models themselves, and the computational algorithms for applying statistics to analyze six representative classes of signals of increasing complexity. The book covers patterns in text, sound

Analysis and prediction of leucine-rich nuclear export signals

DEFF Research Database (Denmark)

La Cour, T.; Kiemer, Lars; Mølgaard, Anne

2004-01-01

We present a thorough analysis of nuclear export signals and a prediction server, which we have made publicly available. The machine learning prediction method is a significant improvement over the generally used consensus patterns. Nuclear export signals (NESs) are extremely important regulators...... this analysis is that the most important properties of NESs are accessibility and flexibility allowing relevant proteins to interact with the signal. Furthermore, we show that not only the known hydrophobic residues are important in defining a nuclear export signals. We employ both neural networks and hidden...

The effects of advanced digital signal processing concepts on VLSIC/VHSIC design

Science.gov (United States)

Jankowski, C.

Implementations of sophisticated mathematical techniques in advanced digital signal processors can significantly improve performance. Future VLSI and VHSI circuit designs must include the practical realization of these algorithms. A structured design approach is described and illustrated with examples from a RNS FIR filter processor development project. The CAE hardware and software required to support tasks of this complexity are also discussed. An EWS is recommended for controlling essential functions such as logic optimization, simulation and verification. The total IC design system is illustrated with the implementation of a new high performance algorithm for computing complex magnitude.

Systemization of Design and Analysis Technology for Advanced Reactor

International Nuclear Information System (INIS)

Kim, Keung Koo; Lee, J.; Zee, S. K.

2009-01-01

The present study is performed to establish the base for the license application of the original technology by systemization and enhancement of the technology that is indispensable for the design and analysis of the advanced reactors including integral reactors. Technical reports and topical reports are prepared for this purpose on some important design/analysis methodology; design and analysis computer programs, structural integrity evaluation of main components and structures, digital I and C systems and man-machine interface design. PPS design concept is complemented reflecting typical safety analysis results. And test plans and requirements are developed for the verification of the advanced reactor technology. Moreover, studies are performed to draw up plans to apply to current or advanced power reactors the original technologies or base technologies such as patents, computer programs, test results, design concepts of the systems and components of the advanced reactors. Finally, pending issues are studied of the advanced reactors to improve the economics and technology realization

Reliability analysis for Atucha II reactor protection system signals

International Nuclear Information System (INIS)

Roca, Jose Luis

1996-01-01

Atucha II is a 745 MW Argentine Power Nuclear Reactor constructed by ENACE SA, Nuclear Argentine Company for Electrical Power Generation and SIEMENS AG KWU, Erlangen, Germany. A preliminary modular logic analysis of RPS (Reactor Protection System) signals was performed by means of the well known Swedish professional risk and reliability software named Risk-Spectrum taking as a basis a reference signal coded as JR17ER003 which command the two moderator loops valves. From the reliability and behavior knowledge for this reference signal follows an estimation of the reliability for the other 97 RPS signals. Because the preliminary character of this analysis Main Important Measures are not performed at this stage. Reliability is by the statistic value named unavailability predicted. The scope of this analysis is restricted from the measurement elements to the RPS buffer outputs. In the present context only one redundancy is analyzed so in the Instrumentation and Control area there no CCF (Common Cause Failures) present for signals. Finally those unavailability values could be introduced in the failure domain for the posterior complete Atucha II reliability analysis which includes all mechanical and electromechanical features. Also an estimation of the spurious frequency of RPS signals defined as faulty by no trip is performed

Reliability analysis for Atucha II reactor protection system signals

International Nuclear Information System (INIS)

Roca, Jose L.

2000-01-01

Atucha II is a 745 MW Argentine power nuclear reactor constructed by Nuclear Argentine Company for Electric Power Generation S.A. (ENACE S.A.) and SIEMENS AG KWU, Erlangen, Germany. A preliminary modular logic analysis of RPS (Reactor Protection System) signals was performed by means of the well known Swedish professional risk and reliability software named Risk-Spectrum taking as a basis a reference signal coded as JR17ER003 which command the two moderator loops valves. From the reliability and behavior knowledge for this reference signal follows an estimation of the reliability for the other 97 RPS signals. Because the preliminary character of this analysis Main Important Measures are not performed at this stage. Reliability is by the statistic value named unavailability predicted. The scope of this analysis is restricted from the measurement elements to the RPS buffer outputs. In the present context only one redundancy is analyzed so in the Instrumentation and Control area there no CCF (Common Cause Failures) present for signals. Finally those unavailability values could be introduced in the failure domain for the posterior complete Atucha II reliability analysis which includes all mechanical and electromechanical features. Also an estimation of the spurious frequency of RPS signals defined as faulty by no trip is performed. (author)

Mathematical principles of signal processing Fourier and wavelet analysis

CERN Document Server

Brémaud, Pierre

2002-01-01

Fourier analysis is one of the most useful tools in many applied sciences. The recent developments of wavelet analysis indicates that in spite of its long history and well-established applications, the field is still one of active research. This text bridges the gap between engineering and mathematics, providing a rigorously mathematical introduction of Fourier analysis, wavelet analysis and related mathematical methods, while emphasizing their uses in signal processing and other applications in communications engineering. The interplay between Fourier series and Fourier transforms is at the heart of signal processing, which is couched most naturally in terms of the Dirac delta function and Lebesgue integrals. The exposition is organized into four parts. The first is a discussion of one-dimensional Fourier theory, including the classical results on convergence and the Poisson sum formula. The second part is devoted to the mathematical foundations of signal processing - sampling, filtering, digital signal proc...

Development of the effectiveness measure for an advanced alarm system using signal detection theory

International Nuclear Information System (INIS)

Park, J.K.; Choi, S.S.; Hong, J.H.; Chang, S.H.

1997-01-01

Since many alarms which are activated during major process deviations or accidents in nuclear power plants can result in negative effects for operators, various types of advanced alarm systems that can select important alarms for the identification of process deviation have been developed to reduce the operator's workload. However, the irrelevant selection of important alarms could distract the operator from correct identification of process deviation. Therefore, to evaluate the effectiveness of the advanced alarm system, a tradeoff between the alarm reduction rate (how many alarms are reduced?) and informativeness (how many important alarms that are conducive to identifying process deviation are provided?) of an advanced alarm system should be considered. In this paper, a new measure is proposed to evaluate the effectiveness of an advanced alarm system with regard to the identification of process deviation. Here, the effectiveness measure is the combination of informativeness measure and reduction rate, and the informativeness measure means the information processing capability performed by the advanced alarm system including wrong rejection and wrong acceptance, and it can be calculated using the signal detection theory (SDT). The effectiveness of the prototype alarm system was evaluated using the loss of coolant accident (LOCA) scenario, and the validity of the effectiveness measure was investigated from two types of the operator response, such as the identification accuracy and the operator's preference for the identification of LOCA

Analysis of cutting force signals by wavelet packet transform for surface roughness monitoring in CNC turning

Science.gov (United States)

García Plaza, E.; Núñez López, P. J.

2018-01-01

On-line monitoring of surface finish in machining processes has proven to be a substantial advancement over traditional post-process quality control techniques by reducing inspection times and costs and by avoiding the manufacture of defective products. This study applied techniques for processing cutting force signals based on the wavelet packet transform (WPT) method for the monitoring of surface finish in computer numerical control (CNC) turning operations. The behaviour of 40 mother wavelets was analysed using three techniques: global packet analysis (G-WPT), and the application of two packet reduction criteria: maximum energy (E-WPT) and maximum entropy (SE-WPT). The optimum signal decomposition level (Lj) was determined to eliminate noise and to obtain information correlated to surface finish. The results obtained with the G-WPT method provided an in-depth analysis of cutting force signals, and frequency ranges and signal characteristics were correlated to surface finish with excellent results in the accuracy and reliability of the predictive models. The radial and tangential cutting force components at low frequency provided most of the information for the monitoring of surface finish. The E-WPT and SE-WPT packet reduction criteria substantially reduced signal processing time, but at the expense of discarding packets with relevant information, which impoverished the results. The G-WPT method was observed to be an ideal procedure for processing cutting force signals applied to the real-time monitoring of surface finish, and was estimated to be highly accurate and reliable at a low analytical-computational cost.

Fetal Cardiac Doppler Signal Processing Techniques: Challenges and Future Research Directions

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Saeed Abdulrahman Alnuaimi

2017-12-01

Full Text Available The fetal Doppler Ultrasound (DUS is commonly used for monitoring fetal heart rate and can also be used for identifying the event timings of fetal cardiac valve motions. In early-stage fetuses, the detected Doppler signal suffers from noise and signal loss due to the fetal movements and changing fetal location during the measurement procedure. The fetal cardiac intervals, which can be estimated by measuring the fetal cardiac event timings, are the most important markers of fetal development and well-being. To advance DUS-based fetal monitoring methods, several powerful and well-advanced signal processing and machine learning methods have recently been developed. This review provides an overview of the existing techniques used in fetal cardiac activity monitoring and a comprehensive survey on fetal cardiac Doppler signal processing frameworks. The review is structured with a focus on their shortcomings and advantages, which helps in understanding fetal Doppler cardiogram signal processing methods and the related Doppler signal analysis procedures by providing valuable clinical information. Finally, a set of recommendations are suggested for future research directions and the use of fetal cardiac Doppler signal analysis, processing, and modeling to address the underlying challenges.

Detection and Processing Techniques of FECG Signal for Fetal Monitoring

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Hasan MA

2009-03-01

Full Text Available Abstract Fetal electrocardiogram (FECG signal contains potentially precise information that could assist clinicians in making more appropriate and timely decisions during labor. The ultimate reason for the interest in FECG signal analysis is in clinical diagnosis and biomedical applications. The extraction and detection of the FECG signal from composite abdominal signals with powerful and advance methodologies are becoming very important requirements in fetal monitoring. The purpose of this review paper is to illustrate the various methodologies and developed algorithms on FECG signal detection and analysis to provide efficient and effective ways of understanding the FECG signal and its nature for fetal monitoring. A comparative study has been carried out to show the performance and accuracy of various methods of FECG signal analysis for fetal monitoring. Finally, this paper further focused some of the hardware implementations using electrical signals for monitoring the fetal heart rate. This paper opens up a passage for researchers, physicians, and end users to advocate an excellent understanding of FECG signal and its analysis procedures for fetal heart rate monitoring system.

Hierarchical Colored Petri Nets for Modeling and Analysis of Transit Signal Priority Control Systems

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Yisheng An

2018-01-01

Full Text Available In this paper, we consider the problem of developing a model for traffic signal control with transit priority using Hierarchical Colored Petri nets (HCPN. Petri nets (PN are useful for state analysis of discrete event systems due to their powerful modeling capability and mathematical formalism. This paper focuses on their use to formalize the transit signal priority (TSP control model. In a four-phase traffic signal control model, the transit detection and two kinds of transit priority strategies are integrated to obtain the HCPN-based TSP control models. One of the advantages to use these models is the clear presentation of traffic light behaviors in terms of conditions and events that cause the detection of a priority request by a transit vehicle. Another advantage of the resulting models is that the correctness and reliability of the proposed strategies are easily analyzed. After their full reachable states are generated, the boundness, liveness, and fairness of the proposed models are verified. Experimental results show that the proposed control model provides transit vehicles with better effectiveness at intersections. This work helps advance the state of the art in the design of signal control models related to the intersection of roadways.

Signal and image multiresolution analysis

CERN Document Server

Ouahabi, Abdelialil

2012-01-01

Multiresolution analysis using the wavelet transform has received considerable attention in recent years by researchers in various fields. It is a powerful tool for efficiently representing signals and images at multiple levels of detail with many inherent advantages, including compression, level-of-detail display, progressive transmission, level-of-detail editing, filtering, modeling, fractals and multifractals, etc.This book aims to provide a simple formalization and new clarity on multiresolution analysis, rendering accessible obscure techniques, and merging, unifying or completing

A Statistical-Probabilistic Pattern for Determination of Tunnel Advance Step by Quantitative Risk Analysis

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sasan ghorbani

2017-12-01

Full Text Available One of the main challenges faced in design and construction phases of tunneling projects is the determination of maximum allowable advance step to maximize excavation rate and reduce project delivery time. Considering the complexity of determining this factor and unexpected risks associated with inappropriate determination of that, it is necessary to employ a method which is capable of accounting for interactions among uncertain geotechnical parameters and advance step. The main objective in the present research is to undertake optimization and risk management of advance step length in water diversion tunnel at Shahriar Dam based on uncertainty of geotechnical parameters following a statistic-probabilistic approach. In the present research, in order to determine optimum advance step for excavation operation, two hybrid methods were used: strength reduction method-discrete element method- Monte Carlo simulation (SRM/DEM/MCS and strength reduction method- discrete element method- point estimate method (SRM/DEM/PEM. Moreover, Taguchi analysis was used to investigate the sensitivity of advance step to changes in statistical distribution function of input parameters under three tunneling scenarios at sections of poor to good qualities (as per RMR classification system. Final results implied the optimality of the advance step defined in scenario 2 where 2 m advance per excavation round was proposed, according to shear strain criterion and SRM/DEM/MCS, with minimum failure probability and risk of 8.05% and 75281.56 $, respectively, at 95% confidence level. Moreover, in either of normal, lognormal, and gamma distributions, as the advance step increased from Scenario 1 to 2, failure probability was observed to increase at lower rate than that observed when advance step in scenario 2 was increased to that In Scenario 3. In addition, Taguchi tests were subjected to signal-to-noise analysis and the results indicated that, considering the three statistical

Ultra Wideband Indoor Positioning Technologies: Analysis and Recent Advances.

Science.gov (United States)

Alarifi, Abdulrahman; Al-Salman, AbdulMalik; Alsaleh, Mansour; Alnafessah, Ahmad; Al-Hadhrami, Suheer; Al-Ammar, Mai A; Al-Khalifa, Hend S

2016-05-16

In recent years, indoor positioning has emerged as a critical function in many end-user applications; including military, civilian, disaster relief and peacekeeping missions. In comparison with outdoor environments, sensing location information in indoor environments requires a higher precision and is a more challenging task in part because various objects reflect and disperse signals. Ultra WideBand (UWB) is an emerging technology in the field of indoor positioning that has shown better performance compared to others. In order to set the stage for this work, we provide a survey of the state-of-the-art technologies in indoor positioning, followed by a detailed comparative analysis of UWB positioning technologies. We also provide an analysis of strengths, weaknesses, opportunities, and threats (SWOT) to analyze the present state of UWB positioning technologies. While SWOT is not a quantitative approach, it helps in assessing the real status and in revealing the potential of UWB positioning to effectively address the indoor positioning problem. Unlike previous studies, this paper presents new taxonomies, reviews some major recent advances, and argues for further exploration by the research community of this challenging problem space.

Ultra Wideband Indoor Positioning Technologies: Analysis and Recent Advances

Directory of Open Access Journals (Sweden)

Abdulrahman Alarifi

2016-05-01

Full Text Available In recent years, indoor positioning has emerged as a critical function in many end-user applications; including military, civilian, disaster relief and peacekeeping missions. In comparison with outdoor environments, sensing location information in indoor environments requires a higher precision and is a more challenging task in part because various objects reflect and disperse signals. Ultra WideBand (UWB is an emerging technology in the field of indoor positioning that has shown better performance compared to others. In order to set the stage for this work, we provide a survey of the state-of-the-art technologies in indoor positioning, followed by a detailed comparative analysis of UWB positioning technologies. We also provide an analysis of strengths, weaknesses, opportunities, and threats (SWOT to analyze the present state of UWB positioning technologies. While SWOT is not a quantitative approach, it helps in assessing the real status and in revealing the potential of UWB positioning to effectively address the indoor positioning problem. Unlike previous studies, this paper presents new taxonomies, reviews some major recent advances, and argues for further exploration by the research community of this challenging problem space.

Signal Adaptive System for Space/Spatial-Frequency Analysis

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Veselin N. Ivanović

2009-01-01

Full Text Available This paper outlines the development of a multiple-clock-cycle implementation (MCI of a signal adaptive two-dimensional (2D system for space/spatial-frequency (S/SF signal analysis. The design is based on a method for improved S/SF representation of the analyzed 2D signals, also proposed here. The proposed MCI design optimizes critical design performances related to hardware complexity, making it a suitable system for real time implementation on an integrated chip. Additionally, the design allows the implemented system to take a variable number of clock cycles (CLKs (the only necessary ones regarding desirable—2D Wigner distribution-presentation of autoterms in different frequency-frequency points during the execution. This ability represents a major advantage of the proposed design which helps to optimize the time required for execution and produce an improved, cross-terms-free S/SF signal representation. The design has been verified by a field-programmable gate array (FPGA circuit design, capable of performing S/SF analysis of 2D signals in real time.

A Meta-Analysis of Advance-Organizer Studies.

Science.gov (United States)

Stone, Carol Leth

Long term studies of advance organizers (AO) were analyzed with Glass's meta-analysis technique. AO's were defined as bridges from reader's previous knowledge to what is to be learned. The results were compared with predictions from Ausubel's model of assimilative learning. The results of the study indicated that advance organizers were associated…

Streamlining digital signal processing a tricks of the trade guidebook

CERN Document Server

2012-01-01

Streamlining Digital Signal Processing, Second Edition, presents recent advances in DSP that simplify or increase the computational speed of common signal processing operations and provides practical, real-world tips and tricks not covered in conventional DSP textbooks. It offers new implementations of digital filter design, spectrum analysis, signal generation, high-speed function approximation, and various other DSP functions. It provides:Great tips, tricks of the trade, secrets, practical shortcuts, and clever engineering solutions from seasoned signal processing professionalsAn assortment.

Source Signals Separation and Reconstruction Following Principal Component Analysis

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WANG Cheng

2014-02-01

Full Text Available For separation and reconstruction of source signals from observed signals problem, the physical significance of blind source separation modal and independent component analysis is not very clear, and its solution is not unique. Aiming at these disadvantages, a new linear and instantaneous mixing model and a novel source signals separation reconstruction solving method from observed signals based on principal component analysis (PCA are put forward. Assumption of this new model is statistically unrelated rather than independent of source signals, which is different from the traditional blind source separation model. A one-to-one relationship between linear and instantaneous mixing matrix of new model and linear compound matrix of PCA, and a one-to-one relationship between unrelated source signals and principal components are demonstrated using the concept of linear separation matrix and unrelated of source signals. Based on this theoretical link, source signals separation and reconstruction problem is changed into PCA of observed signals then. The theoretical derivation and numerical simulation results show that, in despite of Gauss measurement noise, wave form and amplitude information of unrelated source signal can be separated and reconstructed by PCA when linear mixing matrix is column orthogonal and normalized; only wave form information of unrelated source signal can be separated and reconstructed by PCA when linear mixing matrix is column orthogonal but not normalized, unrelated source signal cannot be separated and reconstructed by PCA when mixing matrix is not column orthogonal or linear.

Denoising of gravitational wave signals via dictionary learning algorithms

Science.gov (United States)

Torres-Forné, Alejandro; Marquina, Antonio; Font, José A.; Ibáñez, José M.

2016-12-01

Gravitational wave astronomy has become a reality after the historical detections accomplished during the first observing run of the two advanced LIGO detectors. In the following years, the number of detections is expected to increase significantly with the full commissioning of the advanced LIGO, advanced Virgo and KAGRA detectors. The development of sophisticated data analysis techniques to improve the opportunities of detection for low signal-to-noise-ratio events is, hence, a most crucial effort. In this paper, we present one such technique, dictionary-learning algorithms, which have been extensively developed in the last few years and successfully applied mostly in the context of image processing. However, to the best of our knowledge, such algorithms have not yet been employed to denoise gravitational wave signals. By building dictionaries from numerical relativity templates of both binary black holes mergers and bursts of rotational core collapse, we show how machine-learning algorithms based on dictionaries can also be successfully applied for gravitational wave denoising. We use a subset of signals from both catalogs, embedded in nonwhite Gaussian noise, to assess our techniques with a large sample of tests and to find the best model parameters. The application of our method to the actual signal GW150914 shows promising results. Dictionary-learning algorithms could be a complementary addition to the gravitational wave data analysis toolkit. They may be used to extract signals from noise and to infer physical parameters if the data are in good enough agreement with the morphology of the dictionary atoms.

AVSS 2007: IEEE International Conference onAdvanced Video and Signal based Surveillance, London, UK, September 2007

DEFF Research Database (Denmark)

Fihl, Preben

This technical report will cover the participation in the IEEE International Conference on Advanced Video and Signal based Surveillance in September 2007. The report will give a concise description of the most relevant topics presented at the conference, focusing on the work related to the HERMES...... project and human motion and action recognition. Our contribution to the conference will also be described....

Recent Advances in Nicotinic Receptor Signaling in Alcohol Abuse and Alcoholism.

Science.gov (United States)

Rahman, Shafiqur; Engleman, Eric A; Bell, Richard L

2016-01-01

Alcohol is the most commonly abused legal substance and alcoholism is a serious public health problem. It is a leading cause of preventable death in the world. The cellular and molecular mechanisms of alcohol reward and addiction are still not well understood. Emerging evidence indicates that unlike other drugs of abuse, such as nicotine, cocaine, or opioids, alcohol targets numerous channel proteins, receptor molecules, and signaling pathways in the brain. Previously, research has identified brain nicotinic acetylcholine receptors (nAChRs), a heterogeneous family of pentameric ligand-gated cation channels expressed in the mammalian brain, as critical molecular targets for alcohol abuse and dependence. Genetic variations encoding nAChR subunits have been shown to increase the vulnerability to develop alcohol dependence. Here, we review recent insights into the rewarding effects of alcohol, as they pertain to different nAChR subtypes, associated signaling molecules, and pathways that contribute to the molecular mechanisms of alcoholism and/or comorbid brain disorders. Understanding these cellular changes and molecular underpinnings may be useful for the advancement of brain nicotinic-cholinergic mechanisms, and will lead to a better translational and therapeutic outcome for alcoholism and/or comorbid conditions. Copyright © 2016. Published by Elsevier Inc.

Applications of wavelet transforms for nuclear power plant signal analysis

International Nuclear Information System (INIS)

Seker, S.; Turkcan, E.; Upadhyaya, B.R.; Erbay, A.S.

1998-01-01

The safety of Nuclear Power Plants (NPPs) may be enhanced by the timely processing of information derived from multiple process signals from NPPs. The most widely used technique in signal analysis applications is the Fourier transform in the frequency domain to generate power spectral densities (PSD). However, the Fourier transform is global in nature and will obscure any non-stationary signal feature. Lately, a powerful technique called the Wavelet Transform, has been developed. This transform uses certain basis functions for representing the data in an effective manner, with capability for sub-band analysis and providing time-frequency localization as needed. This paper presents a brief overview of wavelets applied to the nuclear industry for signal processing and plant monitoring. The basic theory of Wavelets is also summarized. In order to illustrate the application of wavelet transforms data were acquired from the operating nuclear power plant Borssele in the Netherlands. The experimental data consist of various signals in the power plant and are selected from a stationary power operation. Their frequency characteristics and the mutual relations were investigated using MATLAB signal processing and wavelet toolbox for computing their PSDs and coherence functions by multi-resolution analysis. The results indicate that the sub-band PSD matches with the original signal PSD and enhances the estimation of coherence functions. The Wavelet analysis demonstrates the feasibility of application to stationary signals to provide better estimates in the frequency band of interest as compared to the classical FFT approach. (author)

Analysis of signal acquisition in GPS receiver software

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Vlada S. Sokolović

2011-01-01

Full Text Available This paper presents a critical analysis of the flow signal processing carried out in GPS receiver software, which served as a basis for a critical comparison of different signal processing architectures within the GPS receiver. It is possible to achieve Increased flexibility and reduction of GPS device commercial costs, including those of mobile devices, by using radio technology software (SDR, Software Defined Radio. The SDR application can be realized when certain hardware components in a GPS receiver are replaced. Signal processing in the SDR is implemented using a programmable DSP (Digital Signal Processing or FPGA (Field Programmable Gate Array circuit, which allows a simple change of digital signal processing algorithms and a simple change of the receiver parameters. The starting point of the research is the signal generated on the satellite the structure of which is shown in the paper. Based on the GPS signal structure, a receiver is realized with a task to extract an appropriate signal from the spectrum and detect it. Based on collected navigation data, the receiver calculates the position of the end user. The signal coming from the satellite may be at the carrier frequencies of L1 and L2. Since the SPS is used in the civil service, all the tests shown in the work were performed on the L1 signal. The signal coming to the receiver is generated in the spread spectrum technology and is situated below the level of noise. Such signals often interfere with signals from the environment which presents a difficulty for a receiver to perform proper detection and signal processing. Therefore, signal processing technology is continually being improved, aiming at more accurate and faster signal processing. All tests were carried out on a signal acquired from the satellite using the SE4110 input circuit used for filtering, amplification and signal selection. The samples of the received signal were forwarded to a computer for data post processing, i. e

Advanced calculus a transition to analysis

CERN Document Server

Dence, Thomas P

2010-01-01

Designed for a one-semester advanced calculus course, Advanced Calculus explores the theory of calculus and highlights the connections between calculus and real analysis -- providing a mathematically sophisticated introduction to functional analytical concepts. The text is interesting to read and includes many illustrative worked-out examples and instructive exercises, and precise historical notes to aid in further exploration of calculus. Ancillary list: * Companion website, Ebook- http://www.elsevierdirect.com/product.jsp?isbn=9780123749550 * Student Solutions Manual- To come * Instructor

Advanced exergetic analysis of five natural gas liquefaction processes

International Nuclear Information System (INIS)

Vatani, Ali; Mehrpooya, Mehdi; Palizdar, Ali

2014-01-01

Highlights: • Advanced exergetic analysis was investigated for five LNG processes. • Avoidable/unavoidable and endogenous/exogenous irreversibilities were calculated. • Advanced exergetic analysis identifies the potentials for improving the system. - Abstract: Conventional exergy analysis cannot identify portion of inefficiencies which can be avoided. Also this analysis does not have ability to calculate a portion of exergy destruction which has been produced through performance of a component alone. In this study advanced exergetic analysis was performed for five mixed refrigerant LNG processes and four parts of irreversibility (avoidable/unavoidable) and (endogenous/exogenous) were calculated for the components with high inefficiencies. The results showed that portion of endogenous exergy destruction in the components is higher than the exogenous one. In fact interactions among the components do not affect the inefficiencies significantly. Also this analysis showed that structural optimization cannot be useful to decrease the overall process irreversibilities. In compressors high portion of the exergy destruction is related to the avoidable one, thus they have high potential to improve. But in multi stream heat exchangers and air coolers, unavoidable inefficiencies were higher than the other parts. Advanced exergetic analysis can identify the potentials and strategies to improve thermodynamic performance of energy intensive processes

Functional Impairment of Myeloid Dendritic Cells during Advanced Stage of HIV-1 Infection: Role of Factors Regulating Cytokine Signaling.

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Meenakshi Sachdeva

Full Text Available Severely immunocompromised state during advanced stage of HIV-1 infection has been linked to functionally defective antigen presentation by dendritic cells (DCs. The molecular mechanisms behind DC impairment are still obscure. We investigated changes in DC function and association of key regulators of cytokine signaling during different stages of HIV-1 infection and following antiretroviral therapy (ART.Phenotypic and functional characteristics of circulating myeloid DCs (mDCs in 56 ART-naive patients (23 in early and 33 in advanced stage of disease, 36 on ART and 24 healthy controls were evaluated. Sixteen patients were studied longitudinally prior-to and 6 months after the start of ART. For functional studies, monocyte-derived DCs (Mo-DCs were evaluated for endocytosis, allo-stimulation and cytokine secretion. The expression of suppressor of cytokine signaling (SOCS-1 and other regulators of cytokine signaling was evaluated by real-time RT-PCR.The ability to respond to an antigenic stimulation was severely impaired in patients in advanced HIV-1 disease which showed partial recovery in the treated group. Mo-DCs from patients with advanced HIV-disease remained immature with low allo-stimulation and reduced cytokine secretion even after TLR-4 mediated stimulation ex-vivo. The cells had an increased expression of negative regulatory factors like SOCS-1, SOCS-3, SH2-containing phosphatase (SHP-1 and a reduced expression of positive regulators like Janus kinase (JAK2 and Nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB1. A functional recovery after siRNA mediated silencing of SOCS-1 in these mo-DCs confirms the role of negative regulatory factors in functional impairment of these cells.Functionally defective DCs in advanced stage of HIV-1 infection seems to be due to imbalanced state of negative and positive regulatory gene expression. Whether this is a cause or effect of increased viral replication at this stage of disease

Acceleration Signal Characteristics for Intuitional Mass Analysis of Metallic Loose Parts

International Nuclear Information System (INIS)

Lee, Kwang-Hyun; Jung, Chang-Gyu

2016-01-01

Nuclear power plants (NPPs) have operated LPMS (Loose Parts Monitoring System) for early detection of the possible presence of metallic parts in the reactor coolant system (RCS); however, analysis of the metallic impact wave characteristics in the LPMS is an important issue because information, such as the mass of the metallic part and the impact location, is not provided. Most studies have concentrated on fieldwork using the frequency characteristics for the analysis of the metallic part mass. Thus, the field engineers cannot analyze signals without special software and access to the system. This paper is intended to introduce a process of intuitional mass analysis using the attenuation rate of the acceleration signal and the intervals between peak signals. Most studies related to mass analysis of a metallic part impact signal in LPMS have used the frequency spectrum. This paper presents a method of using the acceleration signal characteristics for intuitional mass analysis of loose metallic parts. With the method proposed in this paper, because the mass of a metallic part can be understood intuitionally without any special analysis program, intuitional analysis used in parallel with frequency spectrum analysis will be in effect

Acceleration Signal Characteristics for Intuitional Mass Analysis of Metallic Loose Parts

Energy Technology Data Exchange (ETDEWEB)

Lee, Kwang-Hyun; Jung, Chang-Gyu [KHNP CRI, Daejeon (Korea, Republic of)

2016-10-15

Nuclear power plants (NPPs) have operated LPMS (Loose Parts Monitoring System) for early detection of the possible presence of metallic parts in the reactor coolant system (RCS); however, analysis of the metallic impact wave characteristics in the LPMS is an important issue because information, such as the mass of the metallic part and the impact location, is not provided. Most studies have concentrated on fieldwork using the frequency characteristics for the analysis of the metallic part mass. Thus, the field engineers cannot analyze signals without special software and access to the system. This paper is intended to introduce a process of intuitional mass analysis using the attenuation rate of the acceleration signal and the intervals between peak signals. Most studies related to mass analysis of a metallic part impact signal in LPMS have used the frequency spectrum. This paper presents a method of using the acceleration signal characteristics for intuitional mass analysis of loose metallic parts. With the method proposed in this paper, because the mass of a metallic part can be understood intuitionally without any special analysis program, intuitional analysis used in parallel with frequency spectrum analysis will be in effect.

Incorporation of advanced accident analysis methodology into safety analysis reports

International Nuclear Information System (INIS)

2003-05-01

The IAEA Safety Guide on Safety Assessment and Verification defines that the aim of the safety analysis should be by means of appropriate analytical tools to establish and confirm the design basis for the items important to safety, and to ensure that the overall plant design is capable of meeting the prescribed and acceptable limits for radiation doses and releases for each plant condition category. Practical guidance on how to perform accident analyses of nuclear power plants (NPPs) is provided by the IAEA Safety Report on Accident Analysis for Nuclear Power Plants. The safety analyses are performed both in the form of deterministic and probabilistic analyses for NPPs. It is customary to refer to deterministic safety analyses as accident analyses. This report discusses the aspects of using the advanced accident analysis methods to carry out accident analyses in order to introduce them into the Safety Analysis Reports (SARs). In relation to the SAR, purposes of deterministic safety analysis can be further specified as (1) to demonstrate compliance with specific regulatory acceptance criteria; (2) to complement other analyses and evaluations in defining a complete set of design and operating requirements; (3) to identify and quantify limiting safety system set points and limiting conditions for operation to be used in the NPP limits and conditions; (4) to justify appropriateness of the technical solutions employed in the fulfillment of predetermined safety requirements. The essential parts of accident analyses are performed by applying sophisticated computer code packages, which have been specifically developed for this purpose. These code packages include mainly thermal-hydraulic system codes and reactor dynamics codes meant for the transient and accident analyses. There are also specific codes such as those for the containment thermal-hydraulics, for the radiological consequences and for severe accident analyses. In some cases, codes of a more general nature such

Signals and transforms in linear systems analysis

CERN Document Server

Wasylkiwskyj, Wasyl

2013-01-01

Signals and Transforms in Linear Systems Analysis covers the subject of signals and transforms, particularly in the context of linear systems theory. Chapter 2 provides the theoretical background for the remainder of the text. Chapter 3 treats Fourier series and integrals. Particular attention is paid to convergence properties at step discontinuities. This includes the Gibbs phenomenon and its amelioration via the Fejer summation techniques. Special topics include modulation and analytic signal representation, Fourier transforms and analytic function theory, time-frequency analysis and frequency dispersion. Fundamentals of linear system theory for LTI analogue systems, with a brief account of time-varying systems, are covered in Chapter 4 . Discrete systems are covered in Chapters 6 and 7.  The Laplace transform treatment in Chapter 5 relies heavily on analytic function theory as does Chapter 8 on Z -transforms. The necessary background on complex variables is provided in Appendix A. This book is intended to...

Advancing our thinking in presence-only and used-available analysis.

Science.gov (United States)

Warton, David; Aarts, Geert

2013-11-01

1. The problems of analysing used-available data and presence-only data are equivalent, and this paper uses this equivalence as a platform for exploring opportunities for advancing analysis methodology. 2. We suggest some potential methodological advances in used-available analysis, made possible via lessons learnt in the presence-only literature, for example, using modern methods to improve predictive performance. We also consider the converse - potential advances in presence-only analysis inspired by used-available methodology. 3. Notwithstanding these potential advances in methodology, perhaps a greater opportunity is in advancing our thinking about how to apply a given method to a particular data set. 4. It is shown by example that strikingly different results can be achieved for a single data set by applying a given method of analysis in different ways - hence having chosen a method of analysis, the next step of working out how to apply it is critical to performance. 5. We review some key issues to consider in deciding how to apply an analysis method: apply the method in a manner that reflects the study design; consider data properties; and use diagnostic tools to assess how reasonable a given analysis is for the data at hand. © 2013 The Authors. Journal of Animal Ecology © 2013 British Ecological Society.

[Computers in biomedical research: I. Analysis of bioelectrical signals].

Science.gov (United States)

Vivaldi, E A; Maldonado, P

2001-08-01

A personal computer equipped with an analog-to-digital conversion card is able to input, store and display signals of biomedical interest. These signals can additionally be submitted to ad-hoc software for analysis and diagnosis. Data acquisition is based on the sampling of a signal at a given rate and amplitude resolution. The automation of signal processing conveys syntactic aspects (data transduction, conditioning and reduction); and semantic aspects (feature extraction to describe and characterize the signal and diagnostic classification). The analytical approach that is at the basis of computer programming allows for the successful resolution of apparently complex tasks. Two basic principles involved are the definition of simple fundamental functions that are then iterated and the modular subdivision of tasks. These two principles are illustrated, respectively, by presenting the algorithm that detects relevant elements for the analysis of a polysomnogram, and the task flow in systems that automate electrocardiographic reports.

Advances in Risk Analysis with Big Data.

Science.gov (United States)

Choi, Tsan-Ming; Lambert, James H

2017-08-01

With cloud computing, Internet-of-things, wireless sensors, social media, fast storage and retrieval, etc., organizations and enterprises have access to unprecedented amounts and varieties of data. Current risk analysis methodology and applications are experiencing related advances and breakthroughs. For example, highway operations data are readily available, and making use of them reduces risks of traffic crashes and travel delays. Massive data of financial and enterprise systems support decision making under risk by individuals, industries, regulators, etc. In this introductory article, we first discuss the meaning of big data for risk analysis. We then examine recent advances in risk analysis with big data in several topic areas. For each area, we identify and introduce the relevant articles that are featured in the special issue. We conclude with a discussion on future research opportunities. © 2017 Society for Risk Analysis.

An oject oriented environment for multi-channel signal analysis and understanding

Energy Technology Data Exchange (ETDEWEB)

Maurer, W.J.; Dowla, F.U. [Lawrence Livermore National Lab., CA (United States)

1994-11-15

We describe an interactive signal analysis an understanding tool for multichannel signals. The system, written entirely in the C++ language, takes full advantage of the modern workstation GUI tools and integrates traditional signal-processing methods with intelligent domain-specific tools for the exploration and analysis of semistructured problems. By semistructured problems, we mean problems that require a high degree of interactive analysis, and further, the analysis steps are highly adaptive. In other words, a finite number of rules cannot be used to obtain a good solution to the problem.

A review of intelligent systems for heart sound signal analysis.

Science.gov (United States)

Nabih-Ali, Mohammed; El-Dahshan, El-Sayed A; Yahia, Ashraf S

2017-10-01

Intelligent computer-aided diagnosis (CAD) systems can enhance the diagnostic capabilities of physicians and reduce the time required for accurate diagnosis. CAD systems could provide physicians with a suggestion about the diagnostic of heart diseases. The objective of this paper is to review the recent published preprocessing, feature extraction and classification techniques and their state of the art of phonocardiogram (PCG) signal analysis. Published literature reviewed in this paper shows the potential of machine learning techniques as a design tool in PCG CAD systems and reveals that the CAD systems for PCG signal analysis are still an open problem. Related studies are compared to their datasets, feature extraction techniques and the classifiers they used. Current achievements and limitations in developing CAD systems for PCG signal analysis using machine learning techniques are presented and discussed. In the light of this review, a number of future research directions for PCG signal analysis are provided.

Advanced Interval Management: A Benefit Analysis

Science.gov (United States)

Timer, Sebastian; Peters, Mark

2016-01-01

This document is the final report for the NASA Langley Research Center (LaRC)- sponsored task order 'Possible Benefits for Advanced Interval Management Operations.' Under this research project, Architecture Technology Corporation performed an analysis to determine the maximum potential benefit to be gained if specific Advanced Interval Management (AIM) operations were implemented in the National Airspace System (NAS). The motivation for this research is to guide NASA decision-making on which Interval Management (IM) applications offer the most potential benefit and warrant further research.

Conventional and advanced exergoenvironmental analysis of an ammonia-water hybridabsorption-compression heat pump

DEFF Research Database (Denmark)

Jensen, Jonas Kjær; Markussen, Wiebke Brix; Reinholdt, Lars

2015-01-01

to allocate the initial and operational environmental impact to the system components, thus revealing the main sources of environmental impact. The application of the advanced exergoenvironmental analysis improves the level of detail attained.This is achieved by accounting for technological and economic...... constraints as well as component interdependencies.The advanced exergoenvironmental analysis shows that the highest avoidable environmental impact stems from the compressor, followed by the absorber. Further, it is found that the initial environmental impactof the HACHP is negligible compared...... of an advanced exergy-based analysis, comprised of both an advanced exergy, exergoeconomic and exergoenvironmental analysis. Recent studies have presented both the advanced exergy and advanced exergoeconmic analysis of the HACHP. Anexergoenvironmental analysis combines exergy analysis with life cycle assessment...

Power system small signal stability analysis and control

CERN Document Server

Mondal, Debasish; Sengupta, Aparajita

2014-01-01

Power System Small Signal Stability Analysis and Control presents a detailed analysis of the problem of severe outages due to the sustained growth of small signal oscillations in modern interconnected power systems. The ever-expanding nature of power systems and the rapid upgrade to smart grid technologies call for the implementation of robust and optimal controls. Power systems that are forced to operate close to their stability limit have resulted in the use of control devices by utility companies to improve the performance of the transmission system against commonly occurring power system

Advanced event reweighting using multivariate analysis

International Nuclear Information System (INIS)

Martschei, D; Feindt, M; Honc, S; Wagner-Kuhr, J

2012-01-01

Multivariate analysis (MVA) methods, especially discrimination techniques such as neural networks, are key ingredients in modern data analysis and play an important role in high energy physics. They are usually trained on simulated Monte Carlo (MC) samples to discriminate so called 'signal' from 'background' events and are then applied to data to select real events of signal type. We here address procedures that improve this work flow. This will be the enhancement of data / MC agreement by reweighting MC samples on a per event basis. Then training MVAs on real data using the sPlot technique will be discussed. Finally we will address the construction of MVAs whose discriminator is independent of a certain control variable, i.e. cuts on this variable will not change the discriminator shape.

Advancing our thinking in presence-only and used-available analysis

NARCIS (Netherlands)

Warton, D.; Aarts, G.M.

2013-01-01

1. The problems of analysing used-available data and presence-only data are equivalent, and this paper uses this equivalence as a platform for exploring opportunities for advancing analysis methodology. 2. We suggest some potential methodological advances in used-available analysis, made possible

Abnormal Signal Analysis for a Change of the R-C Passive Elements in a Equivalent Circuit Modeling under a High Temperature Accident Condition

International Nuclear Information System (INIS)

Koo, Kil-Mo; Song, Yong-Mann; Ahan, Kwang-Il; Ha, Jea-Joo

2007-01-01

An electrical signal should be checked to see whether it lies within its expected electrical range when there is a doubtful condition. The normal signal level for pressure, flow, level and resistance temperature detector sensors is 4 - 20mA for most instruments as an industrial process control standard. In the case of an abnormal signal level from an instrument under a severe accident condition, it is necessary to obtain a more accurate signal validation to operate a system in a control room in NPPs. Diagnostics and analysis for some abnormal signals have been performed through an important equivalent circuits modeling for passive elements under severe accident conditions. Unlike the design basis accidents, there are some inherent uncertainties for the instrumentation capabilities under severe accident conditions. In this paper, to implement a diagnostic analysis for an equivalent circuits modeling, a kind of linked LabVIEW program for each PSpice and MULTISim code is introduced as a one body order system, which can obtain some abnormal signal patterns by a special function such as an advanced simulation tool for each PSpice and Multi-SIM code as a means of a function for a PC based ASSA (abnormal signal simulation analyzer) module

Abnormal Signal Analysis for a Change of the R-C Passive Elements in a Equivalent Circuit Modeling under a High Temperature Accident Condition

Energy Technology Data Exchange (ETDEWEB)

Koo, Kil-Mo; Song, Yong-Mann; Ahan, Kwang-Il; Ha, Jea-Joo [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

2007-07-01

An electrical signal should be checked to see whether it lies within its expected electrical range when there is a doubtful condition. The normal signal level for pressure, flow, level and resistance temperature detector sensors is 4 - 20mA for most instruments as an industrial process control standard. In the case of an abnormal signal level from an instrument under a severe accident condition, it is necessary to obtain a more accurate signal validation to operate a system in a control room in NPPs. Diagnostics and analysis for some abnormal signals have been performed through an important equivalent circuits modeling for passive elements under severe accident conditions. Unlike the design basis accidents, there are some inherent uncertainties for the instrumentation capabilities under severe accident conditions. In this paper, to implement a diagnostic analysis for an equivalent circuits modeling, a kind of linked LabVIEW program for each PSpice and MULTISim code is introduced as a one body order system, which can obtain some abnormal signal patterns by a special function such as an advanced simulation tool for each PSpice and Multi-SIM code as a means of a function for a PC based ASSA (abnormal signal simulation analyzer) module.

Ultra Wideband Indoor Positioning Technologies: Analysis and Recent Advances †

Science.gov (United States)

Alarifi, Abdulrahman; Al-Salman, AbdulMalik; Alsaleh, Mansour; Alnafessah, Ahmad; Al-Hadhrami, Suheer; Al-Ammar, Mai A.; Al-Khalifa, Hend S.

2016-01-01

In recent years, indoor positioning has emerged as a critical function in many end-user applications; including military, civilian, disaster relief and peacekeeping missions. In comparison with outdoor environments, sensing location information in indoor environments requires a higher precision and is a more challenging task in part because various objects reflect and disperse signals. Ultra WideBand (UWB) is an emerging technology in the field of indoor positioning that has shown better performance compared to others. In order to set the stage for this work, we provide a survey of the state-of-the-art technologies in indoor positioning, followed by a detailed comparative analysis of UWB positioning technologies. We also provide an analysis of strengths, weaknesses, opportunities, and threats (SWOT) to analyze the present state of UWB positioning technologies. While SWOT is not a quantitative approach, it helps in assessing the real status and in revealing the potential of UWB positioning to effectively address the indoor positioning problem. Unlike previous studies, this paper presents new taxonomies, reviews some major recent advances, and argues for further exploration by the research community of this challenging problem space. PMID:27196906

Advanced PWR technology development -Development of advanced PWR system analysis technology-

Energy Technology Data Exchange (ETDEWEB)

Jang, Moon Heui; Hwang, Yung Dong; Kim, Sung Oh; Yoon, Joo Hyun; Jung, Bub Dong; Choi, Chul Jin; Lee, Yung Jin; Song, Jin Hoh [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

1995-07-01

The primary scope of this study is to establish the analysis technology for the advanced reactor designed on the basis of the passive and inherent safety concepts. This study is extended to the application of these technology to the safety analysis of the passive reactor. The study was performed for the small and medium sized reactor and the large sized reactor by focusing on the development of the analysis technology for the passive components. Among the identified concepts the once-through steam generator, the natural circulation of the integral reactor, heat pipe for containment cooling, and hydraulic valve were selected as the high priority items to be developed and the related studies are being performed for these items. For the large sized passive reactor, the study plans to extend the applicability of the best estimate computer code RELAP5/MOD3 which is widely used for the safety analyses of the reactor system. The improvement and supplementation study of the analysis modeling and the methodology is planned to be carried out for these purpose. The newly developed technologies are expected to be applied to the domestic advanced reactor design and analysis and these technologies will play a key role in extending the domestic nuclear base technology and consolidating self-reliance in the essential nuclear technology. 72 figs, 15 tabs, 124 refs. (Author).

Performance Improvement of Power Analysis Attacks on AES with Encryption-Related Signals

Science.gov (United States)

Lee, You-Seok; Lee, Young-Jun; Han, Dong-Guk; Kim, Ho-Won; Kim, Hyoung-Nam

A power analysis attack is a well-known side-channel attack but the efficiency of the attack is frequently degraded by the existence of power components, irrelative to the encryption included in signals used for the attack. To enhance the performance of the power analysis attack, we propose a preprocessing method based on extracting encryption-related parts from the measured power signals. Experimental results show that the attacks with the preprocessed signals detect correct keys with much fewer signals, compared to the conventional power analysis attacks.

Gear wear monitoring by modulation signal bispectrum based on motor current signal analysis

Science.gov (United States)

Zhang, Ruiliang; Gu, Fengshou; Mansaf, Haram; Wang, Tie; Ball, Andrew D.

2017-09-01

Gears are important mechanical components for power transmissions. Tooth wear is one of the most common failure modes, which can present throughout a gear's lifetime. It is significant to accurately monitor gear wear progression in order to take timely predictive maintenances. Motor current signature analysis (MCSA) is an effective and non-intrusive approach which is able to monitor faults from both electrical and mechanical systems. However, little research has been reported in monitoring the gear wear and estimating its severity based on MCSA. This paper presents a novel gear wear monitoring method through a modulation signal bispectrum based motor current signal analysis (MSB-MCSA). For a steady gear transmission, it is inevitable to exist load and speed oscillations due to various errors including wears. These oscillations can induce small modulations in the current signals of the driving motor. MSB is particularly effective in characterising such small modulation signals. Based on these understandings, the monitoring process was implemented based on the current signals from a run-to-failure test of an industrial two stages helical gearbox under a moderate accelerated fatigue process. At the initial operation of the test, MSB analysis results showed that the peak values at the bifrequencies of gear rotations and the power supply can be effective monitoring features for identifying faulty gears and wear severity as they exhibit agreeable changes with gear loads. A monotonically increasing trend established by these features allows a clear indication of the gear wear progression. The dismantle inspection at 477 h of operation, made when one of the monitored features is about 123% higher than its baseline, has found that there are severe scuffing wear marks on a number of tooth surfaces on the driving gear, showing that the gear endures a gradual wear process during its long test operation. Therefore, it is affirmed that the MSB-MSCA approach proposed is reliable

Social Signals, their function, and automatic analysis: A survey

NARCIS (Netherlands)

Vinciarelli, Alessandro; Pantic, Maja; Bourlard, Hervé; Pentland, Alex

2008-01-01

Social Signal Processing (SSP) aims at the analysis of social behaviour in both Human-Human and Human-Computer interactions. SSP revolves around automatic sensing and interpretation of social signals, complex aggregates of nonverbal behaviours through which individuals express their attitudes

Acoustic cardiac signals analysis: a Kalman filter–based approach

Directory of Open Access Journals (Sweden)

Salleh SH

2012-06-01

Full Text Available Sheik Hussain Salleh,1 Hadrina Sheik Hussain,2 Tan Tian Swee,2 Chee-Ming Ting,2 Alias Mohd Noor,2 Surasak Pipatsart,3 Jalil Ali,4 Preecha P Yupapin31Department of Biomedical Instrumentation and Signal Processing, Universiti Teknologi Malaysia, Skudai, Malaysia; 2Centre for Biomedical Engineering Transportation Research Alliance, Universiti Teknologi Malaysia, Johor Bahru, Malaysia; 3Nanoscale Science and Engineering Research Alliance, King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand; 4Institute of Advanced Photonics Science, Universiti Teknologi Malaysia, Johor Bahru, MalaysiaAbstract: Auscultation of the heart is accompanied by both electrical activity and sound. Heart auscultation provides clues to diagnose many cardiac abnormalities. Unfortunately, detection of relevant symptoms and diagnosis based on heart sound through a stethoscope is difficult. The reason GPs find this difficult is that the heart sounds are of short duration and separated from one another by less than 30 ms. In addition, the cost of false positives constitutes wasted time and emotional anxiety for both patient and GP. Many heart diseases cause changes in heart sound, waveform, and additional murmurs before other signs and symptoms appear. Heart-sound auscultation is the primary test conducted by GPs. These sounds are generated primarily by turbulent flow of blood in the heart. Analysis of heart sounds requires a quiet environment with minimum ambient noise. In order to address such issues, the technique of denoising and estimating the biomedical heart signal is proposed in this investigation. Normally, the performance of the filter naturally depends on prior information related to the statistical properties of the signal and the background noise. This paper proposes Kalman filtering for denoising statistical heart sound. The cycles of heart sounds are certain to follow first-order Gauss–Markov process. These cycles are observed with additional noise

A Quantitative Analysis of Pulsed Signals Emitted by Wild Bottlenose Dolphins.

Directory of Open Access Journals (Sweden)

Ana Rita Luís

Full Text Available Common bottlenose dolphins (Tursiops truncatus, produce a wide variety of vocal emissions for communication and echolocation, of which the pulsed repertoire has been the most difficult to categorize. Packets of high repetition, broadband pulses are still largely reported under a general designation of burst-pulses, and traditional attempts to classify these emissions rely mainly in their aural characteristics and in graphical aspects of spectrograms. Here, we present a quantitative analysis of pulsed signals emitted by wild bottlenose dolphins, in the Sado estuary, Portugal (2011-2014, and test the reliability of a traditional classification approach. Acoustic parameters (minimum frequency, maximum frequency, peak frequency, duration, repetition rate and inter-click-interval were extracted from 930 pulsed signals, previously categorized using a traditional approach. Discriminant function analysis revealed a high reliability of the traditional classification approach (93.5% of pulsed signals were consistently assigned to their aurally based categories. According to the discriminant function analysis (Wilk's Λ = 0.11, F3, 2.41 = 282.75, P < 0.001, repetition rate is the feature that best enables the discrimination of different pulsed signals (structure coefficient = 0.98. Classification using hierarchical cluster analysis led to a similar categorization pattern: two main signal types with distinct magnitudes of repetition rate were clustered into five groups. The pulsed signals, here described, present significant differences in their time-frequency features, especially repetition rate (P < 0.001, inter-click-interval (P < 0.001 and duration (P < 0.001. We document the occurrence of a distinct signal type-short burst-pulses, and highlight the existence of a diverse repertoire of pulsed vocalizations emitted in graded sequences. The use of quantitative analysis of pulsed signals is essential to improve classifications and to better assess the

Conditional Random Fields for Morphological Analysis of Wireless ECG Signals

Science.gov (United States)

Natarajan, Annamalai; Gaiser, Edward; Angarita, Gustavo; Malison, Robert; Ganesan, Deepak; Marlin, Benjamin

2015-01-01

Thanks to advances in mobile sensing technologies, it has recently become practical to deploy wireless electrocardiograph sensors for continuous recording of ECG signals. This capability has diverse applications in the study of human health and behavior, but to realize its full potential, new computational tools are required to effectively deal with the uncertainty that results from the noisy and highly non-stationary signals collected using these devices. In this work, we present a novel approach to the problem of extracting the morphological structure of ECG signals based on the use of dynamically structured conditional random field (CRF) models. We apply this framework to the problem of extracting morphological structure from wireless ECG sensor data collected in a lab-based study of habituated cocaine users. Our results show that the proposed CRF-based approach significantly out-performs independent prediction models using the same features, as well as a widely cited open source toolkit. PMID:26726321

Signal extraction and wave field separation in tunnel seismic prediction by independent component analysis

Science.gov (United States)

Yue, Y.; Jiang, T.; Zhou, Q.

2017-12-01

In order to ensure the rationality and the safety of tunnel excavation, the advanced geological prediction has been become an indispensable step in tunneling. However, the extraction of signal and the separation of P and S waves directly influence the accuracy of geological prediction. Generally, the raw data collected in TSP system is low quality because of the numerous disturb factors in tunnel projects, such as the power interference and machine vibration interference. It's difficult for traditional method (band-pass filtering) to remove interference effectively as well as bring little loss to signal. The power interference, machine vibration interference and the signal are original variables and x, y, z component as observation signals, each component of the representation is a linear combination of the original variables, which satisfy applicable conditions of independent component analysis (ICA). We perform finite-difference simulations of elastic wave propagation to synthetic a tunnel seismic reflection record. The method of ICA was adopted to process the three-component data, and the results show that extract the estimates of signal and the signals are highly correlated (the coefficient correlation is up to more than 0.93). In addition, the estimates of interference that separated from ICA and the interference signals are also highly correlated, and the coefficient correlation is up to more than 0.99. Thus, simulation results showed that the ICA is an ideal method for extracting high quality data from mixed signals. For the separation of P and S waves, the conventional separation techniques are based on physical characteristics of wave propagation, which require knowledge of the near-surface P and S waves velocities and density. Whereas the ICA approach is entirely based on statistical differences between P and S waves, and the statistical technique does not require a priori information. The concrete results of the wave field separation will be presented in

Monitoring fetal heart rate during pregnancy: contributions from advanced signal processing and wearable technology.

Science.gov (United States)

Signorini, Maria G; Fanelli, Andrea; Magenes, Giovanni

2014-01-01

Monitoring procedures are the basis to evaluate the clinical state of patients and to assess changes in their conditions, thus providing necessary interventions in time. Both these two objectives can be achieved by integrating technological development with methodological tools, thus allowing accurate classification and extraction of useful diagnostic information. The paper is focused on monitoring procedures applied to fetal heart rate variability (FHRV) signals, collected during pregnancy, in order to assess fetal well-being. The use of linear time and frequency techniques as well as the computation of non linear indices can contribute to enhancing the diagnostic power and reliability of fetal monitoring. The paper shows how advanced signal processing approaches can contribute to developing new diagnostic and classification indices. Their usefulness is evaluated by comparing two selected populations: normal fetuses and intra uterine growth restricted (IUGR) fetuses. Results show that the computation of different indices on FHRV signals, either linear and nonlinear, gives helpful indications to describe pathophysiological mechanisms involved in the cardiovascular and neural system controlling the fetal heart. As a further contribution, the paper briefly describes how the introduction of wearable systems for fetal ECG recording could provide new technological solutions improving the quality and usability of prenatal monitoring.

Advanced LIGO low-latency searches

Science.gov (United States)

Kanner, Jonah; LIGO Scientific Collaboration, Virgo Collaboration

2016-06-01

Advanced LIGO recently made the first detection of gravitational waves from merging binary black holes. The signal was first identified by a low-latency analysis, which identifies gravitational-wave transients within a few minutes of data collection. More generally, Advanced LIGO transients are sought with a suite of automated tools, which collectively identify events, evaluate statistical significance, estimate source position, and attempt to characterize source properties. This low-latency effort is enabling a broad multi-messenger approach to the science of compact object mergers and other transients. This talk will give an overview of the low-latency methodology and recent results.

Diagnostic analysis of vibration signals using adaptive digital filtering techniques

Science.gov (United States)

Jewell, R. E.; Jones, J. H.; Paul, J. E.

1983-01-01

Signal enhancement techniques are described using recently developed digital adaptive filtering equipment. Adaptive filtering concepts are not new; however, as a result of recent advances in microprocessor-based electronics, hardware has been developed that has stable characteristics and of a size exceeding 1000th order. Selected data processing examples are presented illustrating spectral line enhancement, adaptive noise cancellation, and transfer function estimation in the presence of corrupting noise.

Primena savremenih metoda izviđanja signala sa frekvencijskim skakanjem za formiranje elektronske slike bojišta / Advanced methods for frequency hopping signal reconnaissance for the purpose of constructing electronic order of battle

Directory of Open Access Journals (Sweden)

Desimir Vučić

2004-05-01

Full Text Available Sve veća zastupljenost savremenih tehnika digitalnih komunikacija koje primenjuju signale sa malom verovatnoćom presretanja, kao što su signali sa frekvencijskim skakanjem, nameće razvoj novih metoda i algoritama za njihovo izviđanje radi formiranja elektronske slike bojišta. U ovom radu razmatraju se principi i dostignuća u razvoju novih metoda u detekciji, karakterizaciji identifikaciji i eksploataciji ovih sofisticiranih komunikacionih signala u kontekstu elektronskog rata. / The extensive use of modern low probability-of-intercept digital communication signals, such as frequency hopping signals, requires development of new theory and algorithms for their reconnaissance for the purpose of constructing an electronic order of battle. This paper presents some principles and advances in signal processing and analysis technology for the signal interception, characterization, identification and exploitation in the context of electronic warfare.

The Photoplethismographic Signal Processed with Nonlinear Time Series Analysis Tools

International Nuclear Information System (INIS)

Hernandez Caceres, Jose Luis; Hong, Rolando; Garcia Lanz, Abel; Garcia Dominguez, Luis; Cabannas, Karelia

2001-01-01

Finger photoplethismography (PPG) signals were submitted to nonlinear time series analysis. The applied analytical techniques were: (i) High degree polynomial fitting for baseline estimation; (ii) FFT analysis for estimating power spectra; (iii) fractal dimension estimation via the Higuchi's time-domain method, and (iv) kernel nonparametric estimation for reconstructing noise free-attractors and also for estimating signal's stochastic components

Novel Signal Noise Reduction Method through Cluster Analysis, Applied to Photoplethysmography.

Science.gov (United States)

Waugh, William; Allen, John; Wightman, James; Sims, Andrew J; Beale, Thomas A W

2018-01-01

Physiological signals can often become contaminated by noise from a variety of origins. In this paper, an algorithm is described for the reduction of sporadic noise from a continuous periodic signal. The design can be used where a sample of a periodic signal is required, for example, when an average pulse is needed for pulse wave analysis and characterization. The algorithm is based on cluster analysis for selecting similar repetitions or pulses from a periodic single. This method selects individual pulses without noise, returns a clean pulse signal, and terminates when a sufficiently clean and representative signal is received. The algorithm is designed to be sufficiently compact to be implemented on a microcontroller embedded within a medical device. It has been validated through the removal of noise from an exemplar photoplethysmography (PPG) signal, showing increasing benefit as the noise contamination of the signal increases. The algorithm design is generalised to be applicable for a wide range of physiological (physical) signals.

System Level Analysis of LTE-Advanced

DEFF Research Database (Denmark)

Wang, Yuanye

This PhD thesis focuses on system level analysis of Multi-Component Carrier (CC) management for Long Term Evolution (LTE)-Advanced. Cases where multiple CCs are aggregated to form a larger bandwidth are studied. The analysis is performed for both local area and wide area networks. In local area...... reduction. Compared to the case of reuse-1, they achieve a gain of 50∼500% in cell edge user throughput, with small or no loss in average cell throughput. For the wide area network, effort is devoted to the downlink of LTE-Advanced. Such a system is assumed to be backwards compatible to LTE release 8, i...... scheme is recommended. It reduces the CQI by 94% at low load, and 79∼93% at medium to high load, with reasonable loss in downlink performance. To reduce the ACK/NACK feedback, multiple ACK/NACKs can be bundled, with slightly degraded downlink throughput....

Advanced Post-Irradiation Examination Capabilities Alternatives Analysis Report

Energy Technology Data Exchange (ETDEWEB)

Jeff Bryan; Bill Landman; Porter Hill

2012-12-01

An alternatives analysis was performed for the Advanced Post-Irradiation Capabilities (APIEC) project in accordance with the U.S. Department of Energy (DOE) Order DOE O 413.3B, “Program and Project Management for the Acquisition of Capital Assets”. The Alternatives Analysis considered six major alternatives: ? No Action ? Modify Existing DOE Facilities – capabilities distributed among multiple locations ? Modify Existing DOE Facilities – capabilities consolidated at a few locations ? Construct New Facility ? Commercial Partnership ? International Partnerships Based on the alternatives analysis documented herein, it is recommended to DOE that the advanced post-irradiation examination capabilities be provided by a new facility constructed at the Materials and Fuels Complex at the Idaho National Laboratory.

Sensor signal analysis by neural networks for surveillance in nuclear reactors

International Nuclear Information System (INIS)

Keyvan, S.; Rabelo, L.C.

1992-01-01

The application of neural networks as a tool for reactor diagnostics is examined here. Reactor pump signals utilized in a wear-out monitoring system developed for early detection of the degradation of a pump shaft are analyzed as a semi-benchmark test to study the feasibility of neural networks for monitoring and surveillance in nuclear reactors. The Adaptive Resonance Theory (ART 2 and ART 2-A) paradigm of neural networks is applied in this study. The signals are collected signals as well as generated signals simulating the wear progress. The wear-out monitoring system applies noise analysis techniques, and is capable of distinguishing these signals apart and providing a measure of the progress of the degradation. This paper presents the results of the analysis of these data, and provides an evaluation on the performance of ART 2-A and ART 2 for reactor signal analysis. The selection of ART 2 is due to its desired design principles such as unsupervised learning, stability-plasticity, search-direct access, and the match-reset tradeoffs

Advanced Signal Processing for High Temperatures Health Monitoring of Condensed Water Height in Steam Pipes

Science.gov (United States)

Lih, Shyh-Shiuh; Bar-Cohen, Yoseph; Lee, Hyeong Jae; Takano, Nobuyuki; Bao, Xiaoqi

2013-01-01

An advanced signal processing methodology is being developed to monitor the height of condensed water thru the wall of a steel pipe while operating at temperatures as high as 250deg. Using existing techniques, previous study indicated that, when the water height is low or there is disturbance in the environment, the predicted water height may not be accurate. In recent years, the use of the autocorrelation and envelope techniques in the signal processing has been demonstrated to be a very useful tool for practical applications. In this paper, various signal processing techniques including the auto correlation, Hilbert transform, and the Shannon Energy Envelope methods were studied and implemented to determine the water height in the steam pipe. The results have shown that the developed method provides a good capability for monitoring the height in the regular conditions. An alternative solution for shallow water or no water conditions based on a developed hybrid method based on Hilbert transform (HT) with a high pass filter and using the optimized windowing technique is suggested. Further development of the reported methods would provide a powerful tool for the identification of the disturbances of water height inside the pipe.

Method for forecasting an earthquake from precursor signals

International Nuclear Information System (INIS)

Farnworth, D.F.

1996-01-01

A method for forecasting an earthquake from precursor signals by employing characteristic first electromagnetic signals, second, seismically induced electromagnetic signals, seismically induced mechanical signals, and infrasonic acoustic signals which have been observed to precede an earthquake. From a first electromagnetic signal, a magnitude, depth beneath the surface of the earth, distance, latitude, longitude, and first and second forecasts of the time of occurrence of the impending earthquake may be derived. From a second, seismically induced electromagnetic signal and the mechanical signal, third and fourth forecasts of the time of occurrence of an impending earthquake determined from the analysis above, a magnitude, depth beneath the surface of the earth and fourth and fifth forecasts of the time of occurrence of the impending earthquake may be derived. The forecasts of time available from the above analyses range from up to five weeks to substantially within one hour in advance of the earthquake. (author)

A signal processing analysis of Purkinje cells in vitro

Directory of Open Access Journals (Sweden)

Ze'ev R Abrams

2010-05-01

Full Text Available Cerebellar Purkinje cells in vitro fire recurrent sequences of Sodium and Calcium spikes. Here, we analyze the Purkinje cell using harmonic analysis, and our experiments reveal that its output signal is comprised of three distinct frequency bands, which are combined using Amplitude and Frequency Modulation (AM/FM. We find that the three characteristic frequencies - Sodium, Calcium and Switching – occur in various combinations in all waveforms observed using whole-cell current clamp recordings. We found that the Calcium frequency can display a frequency doubling of its frequency mode, and the Switching frequency can act as a possible generator of pauses that are typically seen in Purkinje output recordings. Using a reversibly photo-switchable kainate receptor agonist, we demonstrate the external modulation of the Calcium and Switching frequencies. These experiments and Fourier analysis suggest that the Purkinje cell can be understood as a harmonic signal oscillator, enabling a higher level of interpretation of Purkinje signaling based on modern signal processing techniques.

Advanced Excel for scientific data analysis

CERN Document Server

De Levie, Robert

2004-01-01

Excel is by far the most widely distributed data analysis software but few users are aware of its full powers. Advanced Excel For Scientific Data Analysis takes off from where most books dealing with scientific applications of Excel end. It focuses on three areas-least squares, Fourier transformation, and digital simulation-and illustrates these with extensive examples, often taken from the literature. It also includes and describes a number of sample macros and functions to facilitate common data analysis tasks. These macros and functions are provided in uncompiled, computer-readable, easily

Electronic signal conditioning

CERN Document Server

NEWBY, BRUCE

1994-01-01

At technician level, brief references to signal conditioning crop up in a fragmented way in various textbooks, but there has been no single textbook, until now!More advanced texts do exist but they are more mathematical and presuppose a higher level of understanding of electronics and statistics. Electronic Signal Conditioning is designed for HNC/D students and City & Guilds Electronics Servicing 2240 Parts 2 & 3. It will also be useful for BTEC National, Advanced GNVQ, A-level electronics and introductory courses at degree level.

Proteomic analysis of the signaling pathway mediated by the heterotrimeric G? protein Pga1 of Penicillium chrysogenum

OpenAIRE

Carrasco-Navarro, Ulises; Vera-Estrella, Rosario; Barkla, Bronwyn J.; Z??iga-Le?n, Eduardo; Reyes-Vivas, Horacio; Fern?ndez, Francisco J.; Fierro, Francisco

2016-01-01

Background The heterotrimeric G? protein Pga1-mediated signaling pathway regulates the entire developmental program in Penicillium chrysogenum, from spore germination to the formation of conidia. In addition it participates in the regulation of penicillin biosynthesis. We aimed to advance the understanding of this key signaling pathway using a proteomics approach, a powerful tool to identify effectors participating in signal transduction pathways. Results Penicillium chrysogenum mutants with ...

Digital signal processing with Matlab examples

CERN Document Server

Giron-Sierra, Jose Maria

2017-01-01

This is the first volume in a trilogy on modern Signal Processing. The three books provide a concise exposition of signal processing topics, and a guide to support individual practical exploration based on MATLAB programs. This book includes MATLAB codes to illustrate each of the main steps of the theory, offering a self-contained guide suitable for independent study. The code is embedded in the text, helping readers to put into practice the ideas and methods discussed. The book is divided into three parts, the first of which introduces readers to periodic and non-periodic signals. The second part is devoted to filtering, which is an important and commonly used application. The third part addresses more advanced topics, including the analysis of real-world non-stationary signals and data, e.g. structural fatigue, earthquakes, electro-encephalograms, birdsong, etc. The book’s last chapter focuses on modulation, an example of the intentional use of non-stationary signals.

Features of the non-collinear one-phonon anomalous light scattering controlled by elastic waves with elevated linear losses: potentials for multi-frequency parallel spectrum analysis of radio-wave signals.

Science.gov (United States)

Shcherbakov, Alexandre S; Arellanes, Adan Omar

2017-12-01

During subsequent development of the recently proposed multi-frequency parallel spectrometer for precise spectrum analysis of wideband radio-wave signals, we study potentials of new acousto-optical cells exploiting selected crystalline materials at the limits of their capabilities. Characterizing these wide-aperture cells is non-trivial due to new features inherent in the chosen regime of an advanced non-collinear one-phonon anomalous light scattering by elastic waves with significantly elevated acoustic losses. These features can be observed simpler in uniaxial, tetragonal, and trigonal crystals possessing linear acoustic attenuation. We demonstrate that formerly studied additional degree of freedom, revealed initially for multi-phonon regimes of acousto-optical interaction, can be identified within the one-phonon geometry as well and exploited for designing new cells. We clarify the role of varying the central acoustic frequency and acoustic attenuation using the identified degree of freedom. Therewith, we are strongly restricted by a linear regime of acousto-optical interaction to avoid the origin of multi-phonon processes within carrying out a multi-frequency parallel spectrum analysis of radio-wave signals. Proof-of-principle experiments confirm the developed approaches and illustrate their applicability to innovative technique for an advanced spectrum analysis of wideband radio-wave signals with the improved resolution in an extended frequency range.

Advanced symbolic analysis for VLSI systems methods and applications

CERN Document Server

Shi, Guoyong; Tlelo Cuautle, Esteban

2014-01-01

This book provides comprehensive coverage of the recent advances in symbolic analysis techniques for design automation of nanometer VLSI systems. The presentation is organized in parts of fundamentals, basic implementation methods and applications for VLSI design. Topics emphasized include  statistical timing and crosstalk analysis, statistical and parallel analysis, performance bound analysis and behavioral modeling for analog integrated circuits . Among the recent advances, the Binary Decision Diagram (BDD) based approaches are studied in depth. The BDD-based hierarchical symbolic analysis approaches, have essentially broken the analog circuit size barrier. In particular, this book   • Provides an overview of classical symbolic analysis methods and a comprehensive presentation on the modern  BDD-based symbolic analysis techniques; • Describes detailed implementation strategies for BDD-based algorithms, including the principles of zero-suppression, variable ordering and canonical reduction; • Int...

Fetal QRS extraction from abdominal recordings via model-based signal processing and intelligent signal merging

International Nuclear Information System (INIS)

Haghpanahi, Masoumeh; Borkholder, David A

2014-01-01

Noninvasive fetal ECG (fECG) monitoring has potential applications in diagnosing congenital heart diseases in a timely manner and assisting clinicians to make more appropriate decisions during labor. However, despite advances in signal processing and machine learning techniques, the analysis of fECG signals has still remained in its preliminary stages. In this work, we describe an algorithm to automatically locate QRS complexes in noninvasive fECG signals obtained from a set of four electrodes placed on the mother’s abdomen. The algorithm is based on an iterative decomposition of the maternal and fetal subspaces and filtering of the maternal ECG (mECG) components from the fECG recordings. Once the maternal components are removed, a novel merging technique is applied to merge the signals and detect the fetal QRS (fQRS) complexes. The algorithm was trained and tested on the fECG datasets provided by the PhysioNet/CinC challenge 2013. The final results indicate that the algorithm is able to detect fetal peaks for a variety of signals with different morphologies and strength levels encountered in clinical practice. (paper)

Time-Frequency Analysis of Signals Generated by Rotating Machines

Directory of Open Access Journals (Sweden)

R. Zetik

1999-06-01

Full Text Available This contribution is devoted to the higher order time-frequency analyses of signals. Firstly, time-frequency representations of higher order (TFRHO are defined. Then L-Wigner distribution (LWD is given as a special case of TFRHO. Basic properties of LWD are illustrated based on the analysis of mono-component and multi-component synthetic signals and acoustical signals generated by rotating machine. The obtained results confirm usefulness of LWD application for the purpose of rotating machine condition monitoring.

Receptor for advanced glycation end products inhibits proliferation in osteoblast through suppression of Wnt, PI3K and ERK signaling

International Nuclear Information System (INIS)

Li, Guofeng; Xu, Jingren; Li, Zengchun

2012-01-01

Highlights: ► RAGE overexpression suppresses cell proliferation in MC3T3-E1 cells. ► RAGE overexpression decreases Wnt/β-catenin signaling. ► RAGE overexpression decreases ERK and PI3K signaling. ► Inhibition of Wnt signaling abolishes PI3K signaling restored by RAGE blockade. ► Inhibition of Wnt signaling abolishes ERK signaling restored by RAGE blockade. -- Abstract: Expression of receptor for advanced glycation end products (RAGE) plays a crucial role in bone metabolism. However, the role of RAGE in the control of osteoblast proliferation is not yet evaluated. In the present study, we demonstrate that RAGE overexpression inhibits osteoblast proliferation in vitro. The negative regulation of RAGE on cell proliferation results from suppression of Wnt, PI3K and ERK signaling, and is restored by RAGE neutralizing antibody. Prevention of Wnt signaling using Sfrp1 or DKK1 rescues RAGE-decreased PI3K and ERK signaling and cell proliferation, indicating that the altered cell growth in RAGE overexpressing cells is in part secondary to alterations in Wnt signaling. Consistently, RAGE overexpression inhibits the expression of Wnt targets cyclin D1 and c-myc, which is partially reversed by RAGE blockade. Overall, these results suggest that RAGE inhibits osteoblast proliferation via suppression of Wnt, PI3K and ERK signaling, which provides novel mechanisms by which RAGE regulates osteoblast growth.

Advanced radar detection schemes under mismatched signal models

CERN Document Server

Bandiera, Francesco

2009-01-01

Adaptive detection of signals embedded in correlated Gaussian noise has been an active field of research in the last decades. This topic is important in many areas of signal processing such as, just to give some examples, radar, sonar, communications, and hyperspectral imaging. Most of the existing adaptive algorithms have been designed following the lead of the derivation of Kelly's detector which assumes perfect knowledge of the target steering vector. However, in realistic scenarios, mismatches are likely to occur due to both environmental and instrumental factors. When a mismatched signal

Postprocessing algorithm for automated analysis of pelvic intraoperative neuromonitoring signals

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Wegner Celine

2016-09-01

Full Text Available Two dimensional pelvic intraoperative neuromonitoring (pIONM® is based on electric stimulation of autonomic nerves under observation of electromyography of internal anal sphincter (IAS and manometry of urinary bladder. The method provides nerve identification and verification of its’ functional integrity. Currently pIONM® is gaining increased attention in times where preservation of function is becoming more and more important. Ongoing technical and methodological developments in experimental and clinical settings require further analysis of the obtained signals. This work describes a postprocessing algorithm for pIONM® signals, developed for automated analysis of huge amount of recorded data. The analysis routine includes a graphical representation of the recorded signals in the time and frequency domain, as well as a quantitative evaluation by means of features calculated from the time and frequency domain. The produced plots are summarized automatically in a PowerPoint presentation. The calculated features are filled into a standardized Excel-sheet, ready for statistical analysis.

Signal correlations in biomass combustion. An information theoretic analysis

Energy Technology Data Exchange (ETDEWEB)

Ruusunen, M.

2013-09-01

Increasing environmental and economic awareness are driving the development of combustion technologies to efficient biomass use and clean burning. To accomplish these goals, quantitative information about combustion variables is needed. However, for small-scale combustion units the existing monitoring methods are often expensive or complex. This study aimed to quantify correlations between flue gas temperatures and combustion variables, namely typical emission components, heat output, and efficiency. For this, data acquired from four small-scale combustion units and a large circulating fluidised bed boiler was studied. The fuel range varied from wood logs, wood chips, and wood pellets to biomass residue. Original signals and a defined set of their mathematical transformations were applied to data analysis. In order to evaluate the strength of the correlations, a multivariate distance measure based on information theory was derived. The analysis further assessed time-varying signal correlations and relative time delays. Ranking of the analysis results was based on the distance measure. The uniformity of the correlations in the different data sets was studied by comparing the 10-quantiles of the measured signal. The method was validated with two benchmark data sets. The flue gas temperatures and the combustion variables measured carried similar information. The strongest correlations were mainly linear with the transformed signal combinations and explicable by the combustion theory. Remarkably, the results showed uniformity of the correlations across the data sets with several signal transformations. This was also indicated by simulations using a linear model with constant structure to monitor carbon dioxide in flue gas. Acceptable performance was observed according to three validation criteria used to quantify modelling error in each data set. In general, the findings demonstrate that the presented signal transformations enable real-time approximation of the studied

Spatial Analysis of Depots for Advanced Biomass Processing

Energy Technology Data Exchange (ETDEWEB)

Hilliard, Michael R. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Brandt, Craig C. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Webb, Erin [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Sokhansanj, Shahabaddine [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Eaton, Laurence M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Martinez Gonzalez, Maria I. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

2014-09-01

The objective of this work was to perform a spatial analysis of the total feedstock cost at the conversion reactor for biomass supplied by a conventional system and an advanced system with depots to densify biomass into pellets. From these cost estimates, the conditions (feedstock cost and availability) for which advanced processing depots make it possible to achieve cost and volume targets can be identified.

The speech signal segmentation algorithm using pitch synchronous analysis

Directory of Open Access Journals (Sweden)

Amirgaliyev Yedilkhan

2017-03-01

Full Text Available Parameterization of the speech signal using the algorithms of analysis synchronized with the pitch frequency is discussed. Speech parameterization is performed by the average number of zero transitions function and the signal energy function. Parameterization results are used to segment the speech signal and to isolate the segments with stable spectral characteristics. Segmentation results can be used to generate a digital voice pattern of a person or be applied in the automatic speech recognition. Stages needed for continuous speech segmentation are described.

Advanced Infantry Training: An Empirical Analysis Of (0341) Mortarman Success While Attending Advanced Mortarman Course

Science.gov (United States)

2017-12-01

system MCT Marine Combat Training MEF Marine Expeditionary Force MK Math knowledge MOS Military occupational specialty MSG Marine Security Guard...to advanced level training, specifically, the Advanced Mortarman Course (AMC). Prospective students’ success is predicated on an effective command...survival. It is evident through survival analysis that increased levels of cognitive ability have significant impacts on a Marine’s probability to

A method of signal transmission path analysis for multivariate random processes

International Nuclear Information System (INIS)

Oguma, Ritsuo

1984-04-01

A method for noise analysis called ''STP (signal transmission path) analysis'' is presentd as a tool to identify noise sources and their propagation paths in multivariate random proceses. Basic idea of the analysis is to identify, via time series analysis, effective network for the signal power transmission among variables in the system and to make use of its information to the noise analysis. In the present paper, we accomplish this through two steps of signal processings; first, we estimate, using noise power contribution analysis, variables which have large contribution to the power spectrum of interest, and then evaluate the STPs for each pair of variables to identify STPs which play significant role for the generated noise to transmit to the variable under evaluation. The latter part of the analysis is executed through comparison of partial coherence function and newly introduced partial noise power contribution function. This paper presents the procedure of the STP analysis and demonstrates, using simulation data as well as Borssele PWR noise data, its effectiveness for investigation of noise generation and propagation mechanisms. (author)

Advanced Beta Dosimetry Techniques.Final Scientific/Technical Report

International Nuclear Information System (INIS)

David M. Hamby, PhD

2006-01-01

Final report describing NEER research on Advanced Beta Dosimetry Techniques. The research funded by this NEER grant establishes the framework for a detailed understanding of the challenges in beta dosimetry, especially in the presence of a mixed radiation field. The work also stimulated the thinking of the research group which will lead to new concepts in digital signal processing to allow collection of detection signals and real-time analysis such that simultaneous beta and gamma spectroscopy can take place. The work described herein (with detail in the many publications that came out of this research) was conducted in a manner that provided dissertation and thesis topics for three students, one of which was completely funded by this grant. The overall benefit of the work came in the form of a dramatic shift in signal processing that is normally conducted in pulse shape analysis. Analog signal processing was shown not to be feasible for this type of work and that digital signal processing was a must. This, in turn, led the research team to a new understanding of pulse analysis, one in which expands the state-of-the-art in simultaneous beta and gamma spectroscopy with a single detector

Response Analysis on Electrical Pulses under Severe Nuclear Accident Temperature Conditions Using an Abnormal Signal Simulation Analysis Module

Directory of Open Access Journals (Sweden)

Kil-Mo Koo

2012-01-01

Full Text Available Unlike design basis accidents, some inherent uncertainties of the reliability of instrumentations are expected while subjected to harsh environments (e.g., high temperature and pressure, high humidity, and high radioactivity occurring in severe nuclear accident conditions. Even under such conditions, an electrical signal should be within its expected range so that some mitigating actions can be taken based on the signal in the control room. For example, an industrial process control standard requires that the normal signal level for pressure, flow, and resistance temperature detector sensors be in the range of 4~20 mA for most instruments. Whereas, in the case that an abnormal signal is expected from an instrument, such a signal should be refined through a signal validation process so that the refined signal could be available in the control room. For some abnormal signals expected under severe accident conditions, to date, diagnostics and response analysis have been evaluated with an equivalent circuit model of real instruments, which is regarded as the best method. The main objective of this paper is to introduce a program designed to implement a diagnostic and response analysis for equivalent circuit modeling. The program links signal analysis tool code to abnormal signal simulation engine code not only as a one body order system, but also as a part of functions of a PC-based ASSA (abnormal signal simulation analysis module developed to obtain a varying range of the R-C circuit elements in high temperature conditions. As a result, a special function for abnormal pulse signal patterns can be obtained through the program, which in turn makes it possible to analyze the abnormal output pulse signals through a response characteristic of a 4~20 mA circuit model and a range of the elements changing with temperature under an accident condition.

Interactive Teaching of Adaptive Signal Processing

OpenAIRE

Stewart, R W; Harteneck, M; Weiss, S

2000-01-01

Over the last 30 years adaptive digital signal processing has progressed from being a strictly graduate level advanced class in signal processing theory to a topic that is part of the core curriculum for many undergraduate signal processing classes. The key reason is the continued advance of communications technology, with its need for echo control and equalisation, and the widespread use of adaptive filters in audio, biomedical, and control applications. In this paper we will review the basi...

Research advances in Hedgehog signaling pathway in hepatocellular carcinoma

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LIU Jia

2015-02-01

Full Text Available Hedgehog (Hh signaling pathway is present in many animals and plays an important role in regulating embryonic development and differentiation. Aberrant activation of Hh signaling contributes to the pathogenesis of many malignancies. Recent studies have shown that dysregulated Hh signaling pathway participates in the tumorigenesis, tumor invasion, and metastasis of hepatocellular carcinoma (HCC. Investigation of the relationship between Hh signaling pathway and HCC will help elucidate the molecular mechanism of pathogenesis of HCC and provide a new insight into the development of novel anticancer therapy and therapeutic target.

NATO Advanced Study Institute on Advances in Microlocal Analysis

CERN Document Server

1986-01-01

The 1985 Castel vecchio-Pas coli NATO Advanced Study Institute is aimed to complete the trilogy with the two former institutes I organized : "Boundary Value Problem for Evolution Partial Differential Operators", Liege, 1976 and "Singularities in Boundary Value Problems", Maratea, 1980. It was indeed necessary to record the considerable progress realized in the field of the propagation of singularities of Schwartz Distri­ butions which led recently to the birth of a new branch of Mathema­ tical Analysis called Microlocal Analysis. Most of this theory was mainly built to be applied to distribution solutions of linear partial differential problems. A large part of this institute still went in this direction. But, on the other hand, it was also time to explore the new trend to use microlocal analysis In non linear differential problems. I hope that the Castelvecchio NATO ASI reached its purposes with the help of the more famous authorities in the field. The meeting was held in Tuscany (Italy) at Castelvecchio-P...

SURFACE ELECTROMYOGRAPHY IN BIOMECHANICS: APPLICATIONS AND SIGNAL ANALYSIS ASPECTS

Directory of Open Access Journals (Sweden)

DEAK GRAłIELA-FLAVIA

2009-12-01

Full Text Available Surface electromyography (SEMG is a technique for detecting and recording the electrical activity of the muscles using surface electrodes. The EMG signal is used in biomechanics mainly as an indicator of the initiation of muscle activation, as an indicator of the force produced by a contracting muscle, and as an index ofthe fatigue occurring within a muscle. EMG, used as a method of investigation, can tell us if the muscle is active or not, if the muscle is more or less active, when it is on or off, how much active is it, and finally, if it fatigues.The purpose of this article is to discuss some specific EMG signal analysis aspects with emphasis on comparison type analysis and frequency fatigue analysis.

Computational advances in transition phase analysis

International Nuclear Information System (INIS)

Morita, K.; Kondo, S.; Tobita, Y.; Shirakawa, N.; Brear, D.J.; Fischer, E.A.

1994-01-01

In this paper, historical perspective and recent advances are reviewed on computational technologies to evaluate a transition phase of core disruptive accidents in liquid-metal fast reactors. An analysis of the transition phase requires treatment of multi-phase multi-component thermohydraulics coupled with space- and energy-dependent neutron kinetics. Such a comprehensive modeling effort was initiated when the program of SIMMER-series computer code development was initiated in the late 1970s in the USA. Successful application of the latest SIMMER-II in USA, western Europe and Japan have proved its effectiveness, but, at the same time, several areas that require further research have been identified. Based on the experience and lessons learned during the SIMMER-II application through 1980s, a new project of SIMMER-III development is underway at the Power Reactor and Nuclear Fuel Development Corporation (PNC), Japan. The models and methods of SIMMER-III are briefly described with emphasis on recent advances in multi-phase multi-component fluid dynamics technologies and their expected implication on a future reliable transition phase analysis. (author)

The Signal and Noise Analysis of Direct Conversion EHM Transceivers

Directory of Open Access Journals (Sweden)

Shayegh

2006-01-01

Full Text Available A direct conversion modulator-demodulator with even harmonic mixers with emphasis on noise analysis is presented. The circuits consist of even harmonic mixers (EHMs realized with antiparallel diode pairs (APDPs. We evaluate the different levels of I/Q imbalances and DC offsets and use signal space concepts to analyze the bit error rate (BER of the proposed transceiver using M-ary QAM schemes. Moreover, the simultaneous analysis of the signal and noise has been presented.

Resonance detection of EEG signals using two-layer wavelet analysis

International Nuclear Information System (INIS)

Abdallah, H. M; Odeh, F.S.

2000-01-01

This paper presents the hybrid quadrature mirror filter (HQMF) algorithm applied to the electroencephalogram (EEG) signal during mental activity. The information contents of this signal, i.e., its medical diagnosis, lie in its power spectral density (PSD). The HQMF algorithm is a modified technique that is based on the shape and the details of the signal. If applied efficiently, the HQMF algorithm will produce much better results than conventional wavelet methods in detecting (diagnosing) the information of the EEG signal from its PSD. This technique is applicable not only to EEG signals, but is highly recommended to compression analysis and de noising techniques. (authors). 16 refs., 9 figs

Receptor for advanced glycation end products inhibits proliferation in osteoblast through suppression of Wnt, PI3K and ERK signaling

Energy Technology Data Exchange (ETDEWEB)

Li, Guofeng [Department of Emergency Surgery, East Hospital, Tongji University School of Medicine, Shanghai 200120 (China); Xu, Jingren [Department of Traditional Chinese Orthopaedics, East Hospital, Tongji University School of Medicine, Shanghai 200120 (China); Li, Zengchun, E-mail: lizc.2007@yahoo.com.cn [Department of Emergency Surgery, East Hospital, Tongji University School of Medicine, Shanghai 200120 (China)

2012-07-13

Highlights: Black-Right-Pointing-Pointer RAGE overexpression suppresses cell proliferation in MC3T3-E1 cells. Black-Right-Pointing-Pointer RAGE overexpression decreases Wnt/{beta}-catenin signaling. Black-Right-Pointing-Pointer RAGE overexpression decreases ERK and PI3K signaling. Black-Right-Pointing-Pointer Inhibition of Wnt signaling abolishes PI3K signaling restored by RAGE blockade. Black-Right-Pointing-Pointer Inhibition of Wnt signaling abolishes ERK signaling restored by RAGE blockade. -- Abstract: Expression of receptor for advanced glycation end products (RAGE) plays a crucial role in bone metabolism. However, the role of RAGE in the control of osteoblast proliferation is not yet evaluated. In the present study, we demonstrate that RAGE overexpression inhibits osteoblast proliferation in vitro. The negative regulation of RAGE on cell proliferation results from suppression of Wnt, PI3K and ERK signaling, and is restored by RAGE neutralizing antibody. Prevention of Wnt signaling using Sfrp1 or DKK1 rescues RAGE-decreased PI3K and ERK signaling and cell proliferation, indicating that the altered cell growth in RAGE overexpressing cells is in part secondary to alterations in Wnt signaling. Consistently, RAGE overexpression inhibits the expression of Wnt targets cyclin D1 and c-myc, which is partially reversed by RAGE blockade. Overall, these results suggest that RAGE inhibits osteoblast proliferation via suppression of Wnt, PI3K and ERK signaling, which provides novel mechanisms by which RAGE regulates osteoblast growth.

The Development of Advanced Processing and Analysis Algorithms for Improved Neutron Multiplicity Measurements

International Nuclear Information System (INIS)

Santi, P.; Favalli, A.; Hauck, D.; Henzl, V.; Henzlova, D.; Ianakiev, K.; Iliev, M.; Swinhoe, M.; Croft, S.; Worrall, L.

2015-01-01

One of the most distinctive and informative signatures of special nuclear materials is the emission of correlated neutrons from either spontaneous or induced fission. Because the emission of correlated neutrons is a unique and unmistakable signature of nuclear materials, the ability to effectively detect, process, and analyze these emissions will continue to play a vital role in the non-proliferation, safeguards, and security missions. While currently deployed neutron measurement techniques based on 3He proportional counter technology, such as neutron coincidence and multiplicity counters currently used by the International Atomic Energy Agency, have proven to be effective over the past several decades for a wide range of measurement needs, a number of technical and practical limitations exist in continuing to apply this technique to future measurement needs. In many cases, those limitations exist within the algorithms that are used to process and analyze the detected signals from these counters that were initially developed approximately 20 years ago based on the technology and computing power that was available at that time. Over the past three years, an effort has been undertaken to address the general shortcomings in these algorithms by developing new algorithms that are based on fundamental physics principles that should lead to the development of more sensitive neutron non-destructive assay instrumentation. Through this effort, a number of advancements have been made in correcting incoming data for electronic dead time, connecting the two main types of analysis techniques used to quantify the data (Shift register analysis and Feynman variance to mean analysis), and in the underlying physical model, known as the point model, that is used to interpret the data in terms of the characteristic properties of the item being measured. The current status of the testing and evaluation of these advancements in correlated neutron analysis techniques will be discussed

Advanced analysis technology for MOX fuel

International Nuclear Information System (INIS)

Hiyama, T.; Kamimura, K.

1997-01-01

PNC has developed MOX fuels for advanced thermal reactor (ATR) and fast breeder reactor (FBR). The MOX samples have been chemically analysed to characterize the MOX fuel for JOYO, MONJU, FUGEN and so on. The analysis of the MOX samples in glove box has required complicated and highly skilled operations. Therefore, for quality control analysis of the MOX fuel in a fabrication plant, simple, rapid and accurate analysis methods are necessary. To solve the above problems instrumental analysis and techniques were developed. This paper describes some of the recent developments in PNC. 2. Outline of recently developed analysis methods by PNC. 2.1 Determination of oxygen to metal atomic ratio (O/M) in MOX by non-dispersive infrared spectrophotometry after inert gas fusion. 7 refs, 9 figs, 4 tabs

Cellular signaling identifiability analysis: a case study.

Science.gov (United States)

Roper, Ryan T; Pia Saccomani, Maria; Vicini, Paolo

2010-05-21

Two primary purposes for mathematical modeling in cell biology are (1) simulation for making predictions of experimental outcomes and (2) parameter estimation for drawing inferences from experimental data about unobserved aspects of biological systems. While the former purpose has become common in the biological sciences, the latter is less common, particularly when studying cellular and subcellular phenomena such as signaling-the focus of the current study. Data are difficult to obtain at this level. Therefore, even models of only modest complexity can contain parameters for which the available data are insufficient for estimation. In the present study, we use a set of published cellular signaling models to address issues related to global parameter identifiability. That is, we address the following question: assuming known time courses for some model variables, which parameters is it theoretically impossible to estimate, even with continuous, noise-free data? Following an introduction to this problem and its relevance, we perform a full identifiability analysis on a set of cellular signaling models using DAISY (Differential Algebra for the Identifiability of SYstems). We use our analysis to bring to light important issues related to parameter identifiability in ordinary differential equation (ODE) models. We contend that this is, as of yet, an under-appreciated issue in biological modeling and, more particularly, cell biology. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Statistical analysis of oxides particles in ODS ferritic steel using advanced electron microscopy

International Nuclear Information System (INIS)

Unifantowicz, P.; Schäublin, R.; Hébert, C.; Płociński, T.; Lucas, G.; Baluc, N.

2012-01-01

In this work a combination of advanced transmission electron microscopy and spectroscopy techniques enabled a statistically significant analysis of various types of few nanometer size oxides particles in Fe–14Cr–2W–0.3Ti–0.3Y 2 O 3 ferritic steel. These methods include a scanning TEM with EDS and EFTEM coupled with EELS. In addition, principal component analysis was applied to the chemical maps obtained by EFTEM, which drastically improved the signal to noise ratio. Three types of particles were identified in a size range from 2 to 300 nm, namely Cr–Ti–O, Y–O and Y–Ti–O particles, with an average size of 33,16 and 8 nm, respectively. The Cr–Ti–O particles contain Y and Ti enriched zones, which were not observed previously. The EFTEM analysis showed that the titanium addition leads to formation of Y–Ti–O nano-particles, which constitute 84% of the oxides but also precipitation of larger Cr–Ti–O. The presence of small amount of Y–O particles indicated a not sufficient amount of Ti available for reaction during mechanical alloying or consolidation.

Introduction to applied statistical signal analysis guide to biomedical and electrical engineering applications

CERN Document Server

Shiavi, Richard

2007-01-01

Introduction to Applied Statistical Signal Analysis is designed for the experienced individual with a basic background in mathematics, science, and computer. With this predisposed knowledge, the reader will coast through the practical introduction and move on to signal analysis techniques, commonly used in a broad range of engineering areas such as biomedical engineering, communications, geophysics, and speech.Introduction to Applied Statistical Signal Analysis intertwines theory and implementation with practical examples and exercises. Topics presented in detail include: mathematical

The Real-time Frequency Spectrum Analysis of Neutron Pulse Signal Series

International Nuclear Information System (INIS)

Tang Yuelin; Ren Yong; Wei Biao; Feng Peng; Mi Deling; Pan Yingjun; Li Jiansheng; Ye Cenming

2009-01-01

The frequency spectrum analysis of neutron pulse signal is a very important method in nuclear stochastic signal processing Focused on the special '0' and '1' of neutron pulse signal series, this paper proposes new rotation-table and realizes a real-time frequency spectrum algorithm under 1G Hz sample rate based on PC with add, address and SSE. The numerical experimental results show that under the count rate of 3X10 6 s -1 , this algorithm is superior to FFTW in time-consumption and can meet the real-time requirement of frequency spectrum analysis. (authors)

Correlation analysis of respiratory signals by using parallel coordinate plots.

Science.gov (United States)

Saatci, Esra

2018-01-01

The understanding of the bonds and the relationships between the respiratory signals, i.e. the airflow, the mouth pressure, the relative temperature and the relative humidity during breathing may provide the improvement on the measurement methods of respiratory mechanics and sensor designs or the exploration of the several possible applications in the analysis of respiratory disorders. Therefore, the main objective of this study was to propose a new combination of methods in order to determine the relationship between respiratory signals as a multidimensional data. In order to reveal the coupling between the processes two very different methods were used: the well-known statistical correlation analysis (i.e. Pearson's correlation and cross-correlation coefficient) and parallel coordinate plots (PCPs). Curve bundling with the number intersections for the correlation analysis, Least Mean Square Time Delay Estimator (LMS-TDE) for the point delay detection and visual metrics for the recognition of the visual structures were proposed and utilized in PCP. The number of intersections was increased when the correlation coefficient changed from high positive to high negative correlation between the respiratory signals, especially if whole breath was processed. LMS-TDE coefficients plotted in PCP indicated well-matched point delay results to the findings in the correlation analysis. Visual inspection of PCB by visual metrics showed range, dispersions, entropy comparisons and linear and sinusoidal-like relationships between the respiratory signals. It is demonstrated that the basic correlation analysis together with the parallel coordinate plots perceptually motivates the visual metrics in the display and thus can be considered as an aid to the user analysis by providing meaningful views of the data. Copyright © 2017 Elsevier B.V. All rights reserved.

Man/machine interface algorithm for advanced delayed-neutron signal characterization system

International Nuclear Information System (INIS)

Gross, K.C.

1985-01-01

The present failed-element rupture detector (FERD) at Experimental Breeder Reactor II (EBR-II) consists of a single bank of delayed-neutron (DN) detectors at a fixed transit time from the core. Plans are currently under way to upgrade the FERD in 1986 and provide advanced DN signal characterization capability that is embodied in an equivalent-recoil-area (ERA) meter. The new configuration will make available to the operator a wealth of quantitative diagnostic information related to the condition and dynamic evolution of a fuel breach. The diagnostic parameters will include a continuous reading of the ERA value for the breach; the transit time, T/sub tr/, for DN emitters traveling from the core to the FERD; and the isotopic holdup time, T/sub h/, for the source. To enhance the processing, interpretation, and display of these parameters to the reactor operator, a man/machine interface (MMI) algorithm has been developed to run in the background on EBR-II's data acquisition system (DAS). The purpose of this paper is to describe the features and implementation of this newly developed MMI algorithm

Analysis and modelization of short-duration windows of seismic signals

International Nuclear Information System (INIS)

Berriani, B.; Lacoume, J.L.; Martin, N.; Cliet, C.; Dubesset, M.

1987-01-01

The spectral analysis of a seismic arrival is of a great interest, but unfortunately the common Fourier analysis is unserviceable on short-time windows. So, in order to obtain the spectral characteristics of the dominant components of a seismic signal on a short-time interval, the authors study parametric methods. At first, the autoregressive methods are able to localize a small number of non-stationary pure frequencies. But the amplitude determination is impossible with these methods. So, they develop a combination of AR and Capon's methods. In the Capon's method, the amplitude is conserved for a given frequency, at the very time when the contribution of the other frequencies is minimized. Finally, to characterize completely the different pure-frequency dominant components of the signal and to be able to reconstruct the signal and to be able to reconstruct the signal with these elements, the authors need also the phase and the attenuation; for that, they use the Prony's method where the signal is represented by a sum of damped sinusoids. This last method is used to modelize an offset VSP. It is shown that, using four frequencies and their attributes (amplitude, phase, attenuation), it is possible to modelize quasi-exactly the section. When reconstructing the signal, if one (or more) frequency is eliminated, an efficient filtering can be applied. The AR methods, and Prony's in particular, are efficient tools for signal component decomposition and information compression

Issues affecting advanced passive light-water reactor safety analysis

International Nuclear Information System (INIS)

Beelman, R.J.; Fletcher, C.D.; Modro, S.M.

1992-01-01

Next generation commercial reactor designs emphasize enhanced safety through improved safety system reliability and performance by means of system simplification and reliance on immutable natural forces for system operation. Simulating the performance of these safety systems will be central to analytical safety evaluation of advanced passive reactor designs. Yet the characteristically small driving forces of these safety systems pose challenging computational problems to current thermal-hydraulic systems analysis codes. Additionally, the safety systems generally interact closely with one another, requiring accurate, integrated simulation of the nuclear steam supply system, engineered safeguards and containment. Furthermore, numerical safety analysis of these advanced passive reactor designs wig necessitate simulation of long-duration, slowly-developing transients compared with current reactor designs. The composite effects of small computational inaccuracies on induced system interactions and perturbations over long periods may well lead to predicted results which are significantly different than would otherwise be expected or might actually occur. Comparisons between the engineered safety features of competing US advanced light water reactor designs and analogous present day reactor designs are examined relative to the adequacy of existing thermal-hydraulic safety codes in predicting the mechanisms of passive safety. Areas where existing codes might require modification, extension or assessment relative to passive safety designs are identified. Conclusions concerning the applicability of these codes to advanced passive light water reactor safety analysis are presented

Molecular Analysis of Microbial Diversity in Advanced Caries

OpenAIRE

Chhour, Kim-Ly; Nadkarni, Mangala A.; Byun, Roy; Martin, F. Elizabeth; Jacques, Nicholas A.; Hunter, Neil

2005-01-01

Real-time PCR analysis of the total bacterial load in advanced carious lesions has shown that the total load exceeds the number of cultivable bacteria. This suggests that an unresolved complexity exists in bacteria associated with advanced caries. In this report, the profile of the microflora of carious dentine was explored by using DNA extracted from 10 lesions selected on the basis of comparable total microbial load and on the relative abundance of Prevotella spp. Using universal primers fo...

Building Modern Vibration Diagnostics Systems Based on the Frequency-Time Transformations of A Measured Signal

Directory of Open Access Journals (Sweden)

Yasoveev Vasikh

2016-01-01

Full Text Available Basic methods of analysis of vibration transducers signals were reviewed. Continuous wavelet transform, being a time-frequency transform, was found to be an advanced mathematical tool for analysis of vibration signals. Experimental studies revealed obvious changes in the continuous wavelet transform spectrum depending on the existing defects. A method for detection and identification of technological violations based on the analysis of CWT spectrum components and normalized correlation coefficient was suggested. In accordance with the suggested method software for vibration diagnostics was developed.

A new similarity index for nonlinear signal analysis based on local extrema patterns

Science.gov (United States)

Niknazar, Hamid; Motie Nasrabadi, Ali; Shamsollahi, Mohammad Bagher

2018-02-01

Common similarity measures of time domain signals such as cross-correlation and Symbolic Aggregate approximation (SAX) are not appropriate for nonlinear signal analysis. This is because of the high sensitivity of nonlinear systems to initial points. Therefore, a similarity measure for nonlinear signal analysis must be invariant to initial points and quantify the similarity by considering the main dynamics of signals. The statistical behavior of local extrema (SBLE) method was previously proposed to address this problem. The SBLE similarity index uses quantized amplitudes of local extrema to quantify the dynamical similarity of signals by considering patterns of sequential local extrema. By adding time information of local extrema as well as fuzzifying quantized values, this work proposes a new similarity index for nonlinear and long-term signal analysis, which extends the SBLE method. These new features provide more information about signals and reduce noise sensitivity by fuzzifying them. A number of practical tests were performed to demonstrate the ability of the method in nonlinear signal clustering and classification on synthetic data. In addition, epileptic seizure detection based on electroencephalography (EEG) signal processing was done by the proposed similarity to feature the potentials of the method as a real-world application tool.

A Meta-Analysis of Advanced Organizer Studies.

Science.gov (United States)

Stone, Carol Leth

1983-01-01

Twenty-nine reports yielding 112 studies were analyzed with Glass's meta-analysis technique, and results were compared with predictions from Ausubel's model of assimilative learning. Overall, advance organizers were shown to be associated with increased learning and retention of material to be learned. (Author)

Time-Frequency Analysis and Hermite Projection Method Applied to Swallowing Accelerometry Signals

Directory of Open Access Journals (Sweden)

Ervin Sejdić

2010-01-01

Full Text Available Fast Hermite projections have been often used in image-processing procedures such as image database retrieval, projection filtering, and texture analysis. In this paper, we propose an innovative approach for the analysis of one-dimensional biomedical signals that combines the Hermite projection method with time-frequency analysis. In particular, we propose a two-step approach to characterize vibrations of various origins in swallowing accelerometry signals. First, by using time-frequency analysis we obtain the energy distribution of signal frequency content in time. Second, by using fast Hermite projections we characterize whether the analyzed time-frequency regions are associated with swallowing or other phenomena (vocalization, noise, bursts, etc.. The numerical analysis of the proposed scheme clearly shows that by using a few Hermite functions, vibrations of various origins are distinguishable. These results will be the basis for further analysis of swallowing accelerometry to detect swallowing difficulties.

Advances in heart rate variability signal analysis: joint position statement by the e-Cardiology ESC Working Group and the European Heart Rhythm Association co-endorsed by the Asia Pacific Heart Rhythm Society.

Science.gov (United States)

Sassi, Roberto; Cerutti, Sergio; Lombardi, Federico; Malik, Marek; Huikuri, Heikki V; Peng, Chung-Kang; Schmidt, Georg; Yamamoto, Yoshiharu

2015-09-01

Following the publication of the Task Force document on heart rate variability (HRV) in 1996, a number of articles have been published to describe new HRV methodologies and their application in different physiological and clinical studies. This document presents a critical review of the new methods. A particular attention has been paid to methodologies that have not been reported in the 1996 standardization document but have been more recently tested in sufficiently sized populations. The following methods were considered: Long-range correlation and fractal analysis; Short-term complexity; Entropy and regularity; and Nonlinear dynamical systems and chaotic behaviour. For each of these methods, technical aspects, clinical achievements, and suggestions for clinical application were reviewed. While the novel approaches have contributed in the technical understanding of the signal character of HRV, their success in developing new clinical tools, such as those for the identification of high-risk patients, has been rather limited. Available results obtained in selected populations of patients by specialized laboratories are nevertheless of interest but new prospective studies are needed. The investigation of new parameters, descriptive of the complex regulation mechanisms of heart rate, has to be encouraged because not all information in the HRV signal is captured by traditional methods. The new technologies thus could provide after proper validation, additional physiological, and clinical meaning. Multidisciplinary dialogue and specialized courses in the combination of clinical cardiology and complex signal processing methods seem warranted for further advances in studies of cardiac oscillations and in the understanding normal and abnormal cardiac control processes. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2015. For permissions please email: journals.permissions@oup.com.

Alleviating Border Effects in Wavelet Transforms for Nonlinear Time-varying Signal Analysis

Directory of Open Access Journals (Sweden)

SU, H.

2011-08-01

Full Text Available Border effects are very common in many finite signals analysis and processing approaches using convolution operation. Alleviating the border effects that can occur in the processing of finite-length signals using wavelet transform is considered in this paper. Traditional methods for alleviating the border effects are suitable to compression or coding applications. We propose an algorithm based on Fourier series which is proved to be appropriate to the application of time-frequency analysis of nonlinear signals. Fourier series extension method preserves the time-varying characteristics of the signals. A modified signal duration expression for measuring the extent of border effects region is presented. The proposed algorithm is confirmed to be efficient to alleviate the border effects in comparison to the current methods through the numerical examples.

Outsourced Probe Data Effectiveness on Signalized Arterials

Energy Technology Data Exchange (ETDEWEB)

Young, Stanley E [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Sharifi, Elham [University of Maryland; Eshragh, Sepideh [University of Maryland; Hamedi, Masoud [University of Maryland; Juster, Reuben M. [University of Maryland; Kaushik, Kartik [University of Maryland

2017-07-31

This paper presents results of an I-95 Corridor Coalition sponsored project to assess the ability of outsourced vehicle probe data to provide accurate travel time on signalized roadways for the purposes of real-time operations as well as performance measures. The quality of outsourced probe data on freeways has led many departments of transportation to consider such data for arterial performance monitoring. From April 2013 through June of 2014, the University of Maryland Center for Advanced Transportation Technology gathered travel times from several arterial corridors within the mid-Atlantic region using Bluetooth traffic monitoring (BTM) equipment, and compared these travel times with the data reported to the I95 Vehicle Probe Project (VPP) from an outsourced probe data vendor. The analysis consisted of several methodologies: (1) a traditional analysis that used precision and bias speed metrics; (2) a slowdown analysis that quantified the percentage of significant traffic disruptions accurately captured in the VPP data; (3) a sampled distribution method that uses overlay methods to enhance and analyze recurring congestion patterns. (4) Last, the BTM and VPP data from each 24-hour period of data collection were reviewed by the research team to assess the extent to which VPP captured the nature of the traffic flow. Based on the analysis, probe data is recommended only on arterial roadways with signal densities (measured in signals per mile) up to one, and it should be tested and used with caution for signal densities between one and two, and is not recommended when signal density exceeds two.

Advanced transport systems analysis, modeling, and evaluation of performances

CERN Document Server

Janić, Milan

2014-01-01

This book provides a systematic analysis, modeling and evaluation of the performance of advanced transport systems. It offers an innovative approach by presenting a multidimensional examination of the performance of advanced transport systems and transport modes, useful for both theoretical and practical purposes. Advanced transport systems for the twenty-first century are characterized by the superiority of one or several of their infrastructural, technical/technological, operational, economic, environmental, social, and policy performances as compared to their conventional counterparts. The advanced transport systems considered include: Bus Rapid Transit (BRT) and Personal Rapid Transit (PRT) systems in urban area(s), electric and fuel cell passenger cars, high speed tilting trains, High Speed Rail (HSR), Trans Rapid Maglev (TRM), Evacuated Tube Transport system (ETT), advanced commercial subsonic and Supersonic Transport Aircraft (STA), conventionally- and Liquid Hydrogen (LH2)-fuelled commercial air trans...

Analysis of room transfer function and reverberant signal statistics

DEFF Research Database (Denmark)

Georganti, Eleftheria; Mourjopoulos, John; Jacobsen, Finn

2008-01-01

For some time now, statistical analysis has been a valuable tool in analyzing room transfer functions (RTFs). This work examines existing statistical time-frequency models and techniques for RTF analysis (e.g., Schroeder's stochastic model and the standard deviation over frequency bands for the RTF...... magnitude and phase). RTF fractional octave smoothing, as with 1-slash 3 octave analysis, may lead to RTF simplifications that can be useful for several audio applications, like room compensation, room modeling, auralisation purposes. The aim of this work is to identify the relationship of optimal response...... and the corresponding ratio of the direct and reverberant signal. In addition, this work examines the statistical quantities for speech and audio signals prior to their reproduction within rooms and when recorded in rooms. Histograms and other statistical distributions are used to compare RTF minima of typical...

Advanced Fuel Cycle Economic Sensitivity Analysis

Energy Technology Data Exchange (ETDEWEB)

David Shropshire; Kent Williams; J.D. Smith; Brent Boore

2006-12-01

A fuel cycle economic analysis was performed on four fuel cycles to provide a baseline for initial cost comparison using the Gen IV Economic Modeling Work Group G4 ECON spreadsheet model, Decision Programming Language software, the 2006 Advanced Fuel Cycle Cost Basis report, industry cost data, international papers, the nuclear power related cost study from MIT, Harvard, and the University of Chicago. The analysis developed and compared the fuel cycle cost component of the total cost of energy for a wide range of fuel cycles including: once through, thermal with fast recycle, continuous fast recycle, and thermal recycle.

Time-frequency analysis of phonocardiogram signals using wavelet transform: a comparative study.

Science.gov (United States)

Ergen, Burhan; Tatar, Yetkin; Gulcur, Halil Ozcan

2012-01-01

Analysis of phonocardiogram (PCG) signals provides a non-invasive means to determine the abnormalities caused by cardiovascular system pathology. In general, time-frequency representation (TFR) methods are used to study the PCG signal because it is one of the non-stationary bio-signals. The continuous wavelet transform (CWT) is especially suitable for the analysis of non-stationary signals and to obtain the TFR, due to its high resolution, both in time and in frequency and has recently become a favourite tool. It decomposes a signal in terms of elementary contributions called wavelets, which are shifted and dilated copies of a fixed mother wavelet function, and yields a joint TFR. Although the basic characteristics of the wavelets are similar, each type of the wavelets produces a different TFR. In this study, eight real types of the most known wavelets are examined on typical PCG signals indicating heart abnormalities in order to determine the best wavelet to obtain a reliable TFR. For this purpose, the wavelet energy and frequency spectrum estimations based on the CWT and the spectra of the chosen wavelets were compared with the energy distribution and the autoregressive frequency spectra in order to determine the most suitable wavelet. The results show that Morlet wavelet is the most reliable wavelet for the time-frequency analysis of PCG signals.

Simulation of advanced accumulator and its application in CPR1000 LBLOCA analysis

International Nuclear Information System (INIS)

Hu, Hongwei; Shan, Jianqiang; Gou, Junli; Cao, Jianhua; Shen, Yonggang; Fu, Xiangang

2014-01-01

Highlights: • The analysis model was developed for advanced accumulator. • The sensitivity analysis of each key parameter was performed. • The LBLOCA was analyzed for the CPR1000 with advanced accumulator. • The analysis shows that advanced accumulator can improve CPR1000 safety performance. - Abstract: The advanced accumulator is designed to improve the safety and reliability of CPR1000 by providing a small injection flow to keep the reactor core in flooded condition. Thus, the core still stays in a cooling state without the intervention of low pressure safety injection and the startup grace time of the low pressure safety injection pump can be greatly extended. A new model for the advanced accumulator, which is based on the basic conservation equations, is developed and incorporated into RELAP5/MOD 3.3. The simulation of the advanced accumulator can be carried out and results show that the behavior of the advanced accumulator satisfied its primary design target. There is a large flow in the advanced accumulator at the initial stage. When the accumulator water level is lower than the stand pipe, a vortex appears in the damper, which results in a large pressure drop and a small flow. And then the sensitivity analysis is performed and the major factors which affected the flow rate of the advanced accumulator were obtained, including the damper diameter, the initial volume ratio of the water and the nitrogen and the diameter ratio of the standpipe and the small pipe. Additionally, the primary coolant loop cold leg double-ended guillotine break LBLOCA in CPR1000 with advanced accumulator is analyzed. The results show that the criterion for maximum cladding temperature limit (1477 K) (NRC, 1992) can be met ever with 200 s after the startup of the low pressure safety injection. From this point of view, passive advanced accumulator can strive a longer grace time for LPSI. Thus the reliability, safety and economy of the reactor system can be improved

Energy, Exergy and Advanced Exergy Analysis of a Milk Processing Factory

DEFF Research Database (Denmark)

Bühler, Fabian; Nguyen, Tuong-Van; Jensen, Jonas Kjær

2016-01-01

integration, an exergy analysis pinpoints the locations, causes and magnitudes of thermodynamic losses. The advanced exergy analysis further identifies the real potential for thermodynamic improvements of the system by splitting exergy destruction into its avoidable and unavoidable parts, which are related......, cream and milk powder. The results show the optimisation potential based on 1st and 2nd law analyses. An evaluation and comparison of the applicability of exergy methods, including advanced exergy methods, to the dairy industry is made. The comparison includes typical energy mappings conducted onsite......, and discusses the benefits and challenges of applying advanced thermodynamic methods to industrial processes....

Lecture notes for Advanced Time Series Analysis

DEFF Research Database (Denmark)

Madsen, Henrik; Holst, Jan

1997-01-01

A first version of this notes was used at the lectures in Grenoble, and they are now extended and improved (together with Jan Holst), and used in Ph.D. courses on Advanced Time Series Analysis at IMM and at the Department of Mathematical Statistics, University of Lund, 1994, 1997, ...

Multimedia signal coding and transmission

CERN Document Server

Ohm, Jens-Rainer

2015-01-01

This textbook covers the theoretical background of one- and multidimensional signal processing, statistical analysis and modelling, coding and information theory with regard to the principles and design of image, video and audio compression systems. The theoretical concepts are augmented by practical examples of algorithms for multimedia signal coding technology, and related transmission aspects. On this basis, principles behind multimedia coding standards, including most recent developments like High Efficiency Video Coding, can be well understood. Furthermore, potential advances in future development are pointed out. Numerous figures and examples help to illustrate the concepts covered. The book was developed on the basis of a graduate-level university course, and most chapters are supplemented by exercises. The book is also a self-contained introduction both for researchers and developers of multimedia compression systems in industry.

Application of wavelet analysis to signal processing methods for eddy-current test

International Nuclear Information System (INIS)

Chen, G.; Yoneyama, H.; Yamaguchi, A.; Uesugi, N.

1998-01-01

This study deals with the application of wavelet analysis to detection and characterization of defects from eddy-current and ultrasonic testing signals of a low signal-to-noise ratio. Presented in this paper are the methods for processing eddy-current testing signals of heat exchanger tubes of a steam generator in a nuclear power plant. The results of processing eddy-current testing signals of tube testpieces with artificial flaws show that the flaw signals corrupted by noise and/or non-defect signals can be effectively detected and characterized by using the wavelet methods. (author)

An electromagnetic signals monitoring and analysis wireless platform employing personal digital assistants and pattern analysis techniques

Science.gov (United States)

Ninos, K.; Georgiadis, P.; Cavouras, D.; Nomicos, C.

2010-05-01

This study presents the design and development of a mobile wireless platform to be used for monitoring and analysis of seismic events and related electromagnetic (EM) signals, employing Personal Digital Assistants (PDAs). A prototype custom-developed application was deployed on a 3G enabled PDA that could connect to the FTP server of the Institute of Geodynamics of the National Observatory of Athens and receive and display EM signals at 4 receiver frequencies (3 KHz (E-W, N-S), 10 KHz (E-W, N-S), 41 MHz and 46 MHz). Signals may originate from any one of the 16 field-stations located around the Greek territory. Employing continuous recordings of EM signals gathered from January 2003 till December 2007, a Support Vector Machines (SVM)-based classification system was designed to distinguish EM precursor signals within noisy background. EM-signals corresponding to recordings preceding major seismic events (Ms≥5R) were segmented, by an experienced scientist, and five features (mean, variance, skewness, kurtosis, and a wavelet based feature), derived from the EM-signals were calculated. These features were used to train the SVM-based classification scheme. The performance of the system was evaluated by the exhaustive search and leave-one-out methods giving 87.2% overall classification accuracy, in correctly identifying EM precursor signals within noisy background employing all calculated features. Due to the insufficient processing power of the PDAs, this task was performed on a typical desktop computer. This optimal trained context of the SVM classifier was then integrated in the PDA based application rendering the platform capable to discriminate between EM precursor signals and noise. System's efficiency was evaluated by an expert who reviewed 1/ multiple EM-signals, up to 18 days prior to corresponding past seismic events, and 2/ the possible EM-activity of a specific region employing the trained SVM classifier. Additionally, the proposed architecture can form a

Computational intelligence for big data analysis frontier advances and applications

CERN Document Server

Dehuri, Satchidananda; Sanyal, Sugata

2015-01-01

The work presented in this book is a combination of theoretical advancements of big data analysis, cloud computing, and their potential applications in scientific computing. The theoretical advancements are supported with illustrative examples and its applications in handling real life problems. The applications are mostly undertaken from real life situations. The book discusses major issues pertaining to big data analysis using computational intelligence techniques and some issues of cloud computing. An elaborate bibliography is provided at the end of each chapter. The material in this book includes concepts, figures, graphs, and tables to guide researchers in the area of big data analysis and cloud computing.

The interleukin-4 receptor: signal transduction by a hematopoietin receptor.

Science.gov (United States)

Keegan, A D; Pierce, J H

1994-02-01

Over the last several years, the receptors for numerous cytokines have been molecularly characterized. Analysis of their amino acid sequences shows that some of these receptors bear certain motifs in their extracellular domains that define a family of receptors called the Hematopoietin receptor superfamily. Significant advances in characterizing the structure, function, and mechanisms of signal transduction have been made for several members of this family. The purpose of this review is to discuss the recent advances made for one of the family members, the interleukin (IL) 4 receptor. Other receptor systems have recently been reviewed elsewhere. The IL-4 receptor consists of, at the minimum, the cloned 140 kDa IL-4-binding chain with the potential for associating with other chains. The IL-4 receptor transduces its signal by activating a tyrosine kinase that phosphorylates cellular substrates, including the receptor itself, and the 170 kDa substrate called 4PS. Phosphorylated 4PS interacts with the SH2 domain of the enzyme PI-3'-kinase and increases its enzymatic activity. These early events in the IL-4 receptor initiated signaling pathway may trigger a series of signals that will ultimately lead to an IL-4 specific biologic outcome.

Holistic safety analysis for advanced nuclear power plants

International Nuclear Information System (INIS)

Alvarenga, M.A.B.; Guimaraes, A.C.F.

1992-01-01

This paper reviews the basic methodology of safety analysis used in the ANGRA-I and ANGRA-II nuclear power plants, its weaknesses, the problems with public acceptance of the risks, the future of the nuclear energy in Brazil, as well as recommends a new methodology, HOLISTIC SAFETY ANALYSIS, to be used both in the design and licensing phases, for advanced reactors. (author)

Analysis of Satellite-Based Navigation Signal Reflectometry: Simulations and Observations

DEFF Research Database (Denmark)

von Benzon, Hans-Henrik; Høeg, Per; Durgonics, Tibor

2016-01-01

on different ocean characteristics. The spectra of the simulated surface reflections are analyzed, and the results from the simulations are compared to measured GPS surface reflections. The measurements were performed using a space-qualified GPS receiver placed on a mountain at the Haleakala observatory...... on the Hawaiian island of Maui. The GPS receiver was during the experiments running in an open-loop configuration. The analysis of both the simulated surface-reflection signals and the measured reflection signals will in general reveal spectral structures of the reflected signals that can lead to extraction...

Energy and advanced exergy analysis of an existing hydrocarbon recovery process

International Nuclear Information System (INIS)

Mehrpooya, Mehdi; Lazemzade, Roozbeh; Sadaghiani, Mirhadi S.; Parishani, Hossein

2016-01-01

Highlights: • Advanced exergoeconomic analysis is performed for propane refrigerant system. • Avoidable/unavoidable & endogenous/exogenous irreversibilities were calculated. • Advanced exergetic analysis identifies the potentials for improving the system. - Abstract: An advanced exergy analysis of the Ethane recovery plant in the South Pars gas field is presented. An industrial refrigeration cycle with propane refrigerant is investigated by the exergy analysis method. The equations of exergy destruction and exergetic efficiency for the main cycle units such as evaporators, condensers, compressors, and expansion valves are developed. Exergetic efficiency of the refrigeration cycle is determined to be 33.9% indicating a high potential for improvements. The simulation results reveal that the exergy loss and exergetic efficiencies of the air cooler and expansion sections respectively are the lowest among the compartments of the cycle. The coefficient of performance (COP) is obtained as 2.05. Four parts of irreversibility (avoidable/unavoidable) and (endogenous/exogenous) are calculated for the units with highest inefficiencies. The advanced exergy analysis reveals that the exergy destruction has two major contributors: (1) 59.61% of the exergy is lost in the unavoidable form in all units and (2) compressors contribute to 25.47% of the exergy destruction. So there is a high potential for improvement for these units, since 63.38% of this portion is avoidable.

Recent advances of capillary electrophoresis in pharmaceutical analysis.

Science.gov (United States)

Suntornsuk, Leena

2010-09-01

This review covers recent advances of capillary electrophoresis (CE) in pharmaceutical analysis. The principle, instrumentation, and conventional modes of CE are briefly discussed. Advances in the different CE techniques (non-aqueous CE, microemulsion electrokinetic chromatography, capillary isotachophoresis, capillary electrochromatography, and immunoaffinity CE), detection techniques (mass spectrometry, light-emitting diode, fluorescence, chemiluminescence, and contactless conductivity), on-line sample pretreatment (flow injection) and chiral separation are described. Applications of CE to assay of active pharmaceutical ingredients (APIs), drug impurity testing, chiral drug separation, and determination of APIs in biological fluids published from 2008 to 2009 are tabulated.

Large-signal analysis of DC motor drive system using state-space averaging technique

International Nuclear Information System (INIS)

Bekir Yildiz, Ali

2008-01-01

The analysis of a separately excited DC motor driven by DC-DC converter is realized by using state-space averaging technique. Firstly, a general and unified large-signal averaged circuit model for DC-DC converters is given. The method converts power electronic systems, which are periodic time-variant because of their switching operation, to unified and time independent systems. Using the averaged circuit model enables us to combine the different topologies of converters. Thus, all analysis and design processes about DC motor can be easily realized by using the unified averaged model which is valid during whole period. Some large-signal variations such as speed and current relating to DC motor, steady-state analysis, large-signal and small-signal transfer functions are easily obtained by using the averaged circuit model

Advancing Alternative Analysis: Integration of Decision Science

DEFF Research Database (Denmark)

Malloy, Timothy F; Zaunbrecher, Virginia M; Batteate, Christina

2016-01-01

Decision analysis-a systematic approach to solving complex problems-offers tools and frameworks to support decision making that are increasingly being applied to environmental challenges. Alternatives analysis is a method used in regulation and product design to identify, compare, and evaluate......, and civil society and included experts in toxicology, decision science, alternatives assessment, engineering, and law and policy. Participants were divided into two groups and prompted with targeted questions. Throughout the workshop, the groups periodically came together in plenary sessions to reflect......) engaging the systematic development and evaluation of decision approaches and tools; (2) using case studies to advance the integration of decision analysis into alternatives analysis; (3) supporting transdisciplinary research; and (4) supporting education and outreach efforts....

Modelling and Analysis of Biochemical Signalling Pathway Cross-talk

Directory of Open Access Journals (Sweden)

Robin Donaldson

2010-02-01

Full Text Available Signalling pathways are abstractions that help life scientists structure the coordination of cellular activity. Cross-talk between pathways accounts for many of the complex behaviours exhibited by signalling pathways and is often critical in producing the correct signal-response relationship. Formal models of signalling pathways and cross-talk in particular can aid understanding and drive experimentation. We define an approach to modelling based on the concept that a pathway is the (synchronising parallel composition of instances of generic modules (with internal and external labels. Pathways are then composed by (synchronising parallel composition and renaming; different types of cross-talk result from different combinations of synchronisation and renaming. We define a number of generic modules in PRISM and five types of cross-talk: signal flow, substrate availability, receptor function, gene expression and intracellular communication. We show that Continuous Stochastic Logic properties can both detect and distinguish the types of cross-talk. The approach is illustrated with small examples and an analysis of the cross-talk between the TGF-b/BMP, WNT and MAPK pathways.

Advance in ERG Analysis: From Peak Time and Amplitude to Frequency, Power, and Energy

Directory of Open Access Journals (Sweden)

Mathieu Gauvin

2014-01-01

Full Text Available Purpose. To compare time domain (TD: peak time and amplitude analysis of the human photopic electroretinogram (ERG with measures obtained in the frequency domain (Fourier analysis: FA and in the time-frequency domain (continuous (CWT and discrete (DWT wavelet transforms. Methods. Normal ERGs n=40 were analyzed using traditional peak time and amplitude measurements of the a- and b-waves in the TD and descriptors extracted from FA, CWT, and DWT. Selected descriptors were also compared in their ability to monitor the long-term consequences of disease process. Results. Each method extracted relevant information but had distinct limitations (i.e., temporal and frequency resolutions. The DWT offered the best compromise by allowing us to extract more relevant descriptors of the ERG signal at the cost of lesser temporal and frequency resolutions. Follow-ups of disease progression were more prolonged with the DWT (max 29 years compared to 13 with TD. Conclusions. Standardized time domain analysis of retinal function should be complemented with advanced DWT descriptors of the ERG. This method should allow more sensitive/specific quantifications of ERG responses, facilitate follow-up of disease progression, and identify diagnostically significant changes of ERG waveforms that are not resolved when the analysis is only limited to time domain measurements.

-Advanced Models for Tsunami and Rogue Waves

Directory of Open Access Journals (Sweden)

D. W. Pravica

2012-01-01

Full Text Available A wavelet , that satisfies the q-advanced differential equation for , is used to model N-wave oscillations observed in tsunamis. Although q-advanced ODEs may seem nonphysical, we present an application that model tsunamis, in particular the Japanese tsunami of March 11, 2011, by utilizing a one-dimensional wave equation that is forced by . The profile is similar to tsunami models in present use. The function is a wavelet that satisfies a q-advanced harmonic oscillator equation. It is also shown that another wavelet, , matches a rogue-wave profile. This is explained in terms of a resonance wherein two small amplitude forcing waves eventually lead to a large amplitude rogue. Since wavelets are used in the detection of tsunamis and rogues, the signal-analysis performance of and is examined on actual data.

Discrete Fourier and wavelet transforms an introduction through linear algebra with applications to signal processing

CERN Document Server

Goodman, Roe W

2016-01-01

This textbook for undergraduate mathematics, science, and engineering students introduces the theory and applications of discrete Fourier and wavelet transforms using elementary linear algebra, without assuming prior knowledge of signal processing or advanced analysis.It explains how to use the Fourier matrix to extract frequency information from a digital signal and how to use circulant matrices to emphasize selected frequency ranges. It introduces discrete wavelet transforms for digital signals through the lifting method and illustrates through examples and computer explorations how these transforms are used in signal and image processing. Then the general theory of discrete wavelet transforms is developed via the matrix algebra of two-channel filter banks. Finally, wavelet transforms for analog signals are constructed based on filter bank results already presented, and the mathematical framework of multiresolution analysis is examined.

Signalling entropy: A novel network-theoretical framework for systems analysis and interpretation of functional omic data.

Science.gov (United States)

Teschendorff, Andrew E; Sollich, Peter; Kuehn, Reimer

2014-06-01

A key challenge in systems biology is the elucidation of the underlying principles, or fundamental laws, which determine the cellular phenotype. Understanding how these fundamental principles are altered in diseases like cancer is important for translating basic scientific knowledge into clinical advances. While significant progress is being made, with the identification of novel drug targets and treatments by means of systems biological methods, our fundamental systems level understanding of why certain treatments succeed and others fail is still lacking. We here advocate a novel methodological framework for systems analysis and interpretation of molecular omic data, which is based on statistical mechanical principles. Specifically, we propose the notion of cellular signalling entropy (or uncertainty), as a novel means of analysing and interpreting omic data, and more fundamentally, as a means of elucidating systems-level principles underlying basic biology and disease. We describe the power of signalling entropy to discriminate cells according to differentiation potential and cancer status. We further argue the case for an empirical cellular entropy-robustness correlation theorem and demonstrate its existence in cancer cell line drug sensitivity data. Specifically, we find that high signalling entropy correlates with drug resistance and further describe how entropy could be used to identify the achilles heels of cancer cells. In summary, signalling entropy is a deep and powerful concept, based on rigorous statistical mechanical principles, which, with improved data quality and coverage, will allow a much deeper understanding of the systems biological principles underlying normal and disease physiology. Copyright © 2014 Elsevier Inc. All rights reserved.

Advanced exergoeconomic analysis of the multistage mixed refrigerant systems

International Nuclear Information System (INIS)

Mehrpooya, Mehdi; Ansarinasab, Hojat

2015-01-01

Highlights: • Advanced exergoeconomic analysis is performed for mixed refrigerant systems. • Cost of investment is divided into avoidable/unavoidable and endogenous/exogenous. • Results show that interactions between the components is not considerable. - Abstract: Advanced exergoeconomic analysis is applied on three multi stage mixed refrigerant liquefaction processes. They are propane precooled mixed refrigerant, dual mixed refrigerant and mixed fluid cascade. Cost of investment and exergy destruction for the components with high inefficiencies are divided into avoidable/unavoidable and endogenous/exogenous parts. According to the avoidable exergy destruction cost in propane precooled mixed refrigerant process, C-2 compressor with 455.5 ($/h), in dual mixed refrigerant process, C-1 compressor with 510.8 ($/h) and in mixed fluid cascade process, C-2/1 compressor with 338.8 ($/h) should be considered first. A comparison between the conventional and advanced exergoeconomic analysis is done by three important parameters: Exergy efficiency, exergoeconomic factor and total costs. Results show that interactions between the process components are not considerable because cost of investment and exergy destruction in most of them are endogenous. Exergy destruction cost of the compressors is avoidable while heat exchangers and air coolers destruction cost are unavoidable. Investment cost of heat exchangers and air coolers are avoidable while compressor’s are unavoidable

Study of interhemispheric asymmetries in electroencephalographic signals by frequency analysis

International Nuclear Information System (INIS)

Zapata, J F; Garzon, J

2011-01-01

This study provides a new method for the detection of interhemispheric asymmetries in patients with continuous video-electroencephalography (EEG) monitoring at Intensive Care Unit (ICU), using wavelet energy. We obtained the registration of EEG signals in 42 patients with different pathologies, and then we proceeded to perform signal processing using the Matlab program, we compared the abnormalities recorded in the report by the neurophysiologist, the images of each patient and the result of signals analysis with the Discrete Wavelet Transform (DWT). Conclusions: there exists correspondence between the abnormalities found in the processing of the signal with the clinical reports of findings in patients; according to previous conclusion, the methodology used can be a useful tool for diagnosis and early quantitative detection of interhemispheric asymmetries.

Advances in ICT for business, industry and public sector

CERN Document Server

Olszak, Celina; Pełech-Pilichowski, Tomasz

2015-01-01

This contributed volume is a result of discussions held at ABICT’13(4th International Workshop on Advances in Business ICT) in Krakow, September 8-11, 2013. The book focuses on Advances in Business ICT approached from a multidisciplinary perspective and demonstrates different ideas and tools for developing and supporting organizational creativity, as well as advances in decision support systems.This book is an interesting resource for researchers, analysts and IT professionals including software designers. The book comprises eleven chapters presenting research results on business analytics in organization, business processes modeling, problems with processing big data, nonlinear time structures and nonlinear time ontology application, simulation profiling, signal processing (including change detection problems), text processing and risk analysis.    

Receiving more than data - a signal model, theory and implementation of a cognitive IEEE 802.15.4 receiver

Directory of Open Access Journals (Sweden)

Tim Esemann

2016-09-01

Full Text Available Standard medium access schemes sense the channel immediately prior transmission, but are blind during the transmission. Therefore, standard transceivers have limited cognitive capabilities which are important for operation in heterogeneous radio environments. Specifically, mobile interferers move gradually into the reception range before actually causing collisions. These gradual interferences cannot yet be detected, and upcoming collisions cannot be predicted. We present a theoretical analysis of the received and demodulated signal. This analysis and the derived signal model verifies that the received signal contains more than transmitted data exclusively. Enhanced signal processing extracts signal components of an interference at the receiver and enables advanced interference detection to provide information about approaching mobile interferers. Our theoretical analysis is evaluated by simulations and experiments with an IEEE 802.15.4 transmitter and an extended cognitive receiver.

Development of a methodology for analysis of delayed-neutron signals

International Nuclear Information System (INIS)

Gross, K.C.; Strain, R.V.; Fryer, R.M.

1980-02-01

Experimental and analytical techniques have been developed for analysis and characterization of delayed-neutron (DN) signals that can provide diagnostic information to augment data from cover-gas analyses in the detection and identification of breached elements in an LMFBR. Eleven flow-reduction tests have been run in EBR-II to provide base data support for predicting DN signal characteristics during exposed-fuel operation. Results from the tests demonstrate the feasibility and practicability of response-analysis techniques for determining (a) the transit time, T/sub tr/, for DN emitters traveling from the core to the detector and (b) the isotropic holdup time, T/sub h/, of DN precursors in the fuel element

Stationary analysis of signals and ratio decay determination in BWR type reactors by neuronal network

International Nuclear Information System (INIS)

Sanchis, R.; Palomo, M. J.; Munoz-Cobo, J. L.

1998-01-01

The signals registered in the nuclear plants have non stationary characteristics, in numerous times. This made difficult the application of the methods of analysis. There are determinate temporal intervals in that the signal is stationary with determinate mean, value together of zones with corrupt registers, and other zones with mean value distinct, but stationary during a temporal interval. The methodology consist in a stationary analysis to the signal received of the nuclear plant. With the Gabor Transformation are determined the temporal intervals of the stationary signals, synthesised it, as previous phase to the application of the methods of the analysis of stability parameters with methods ARMA, SVD, Neural Net,... to the reconstructed signal. 4 refs. (Author)

Recent advances in quantitative high throughput and high content data analysis.

Science.gov (United States)

Moutsatsos, Ioannis K; Parker, Christian N

2016-01-01

High throughput screening has become a basic technique with which to explore biological systems. Advances in technology, including increased screening capacity, as well as methods that generate multiparametric readouts, are driving the need for improvements in the analysis of data sets derived from such screens. This article covers the recent advances in the analysis of high throughput screening data sets from arrayed samples, as well as the recent advances in the analysis of cell-by-cell data sets derived from image or flow cytometry application. Screening multiple genomic reagents targeting any given gene creates additional challenges and so methods that prioritize individual gene targets have been developed. The article reviews many of the open source data analysis methods that are now available and which are helping to define a consensus on the best practices to use when analyzing screening data. As data sets become larger, and more complex, the need for easily accessible data analysis tools will continue to grow. The presentation of such complex data sets, to facilitate quality control monitoring and interpretation of the results will require the development of novel visualizations. In addition, advanced statistical and machine learning algorithms that can help identify patterns, correlations and the best features in massive data sets will be required. The ease of use for these tools will be important, as they will need to be used iteratively by laboratory scientists to improve the outcomes of complex analyses.

Application of «Sensor signal analysis network» complex for distributed, time synchronized analysis of electromagnetic radiation

Science.gov (United States)

Mochalov, Vladimir; Mochalova, Anastasia

2017-10-01

The paper considers a developing software-hardware complex «Sensor signal analysis network» for distributed and time synchronized analysis of electromagnetic radiations. The areas of application and the main features of the complex are described. An example of application of the complex to monitor natural electromagnetic radiation sources is considered based on the data recorded in VLF range. A generalized functional scheme of stream analysis of signals by a complex functional node is suggested and its application for stream detection of atmospherics, whistlers and tweaks is considered.

Advances in statistical models for data analysis

CERN Document Server

Minerva, Tommaso; Vichi, Maurizio

2015-01-01

This edited volume focuses on recent research results in classification, multivariate statistics and machine learning and highlights advances in statistical models for data analysis. The volume provides both methodological developments and contributions to a wide range of application areas such as economics, marketing, education, social sciences and environment. The papers in this volume were first presented at the 9th biannual meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society, held in September 2013 at the University of Modena and Reggio Emilia, Italy.

Identification of potential pathway mediation targets in Toll-like receptor signaling.

Directory of Open Access Journals (Sweden)

Fan Li

2009-02-01

Full Text Available Recent advances in reconstruction and analytical methods for signaling networks have spurred the development of large-scale models that incorporate fully functional and biologically relevant features. An extended reconstruction of the human Toll-like receptor signaling network is presented herein. This reconstruction contains an extensive complement of kinases, phosphatases, and other associated proteins that mediate the signaling cascade along with a delineation of their associated chemical reactions. A computational framework based on the methods of large-scale convex analysis was developed and applied to this network to characterize input-output relationships. The input-output relationships enabled significant modularization of the network into ten pathways. The analysis identified potential candidates for inhibitory mediation of TLR signaling with respect to their specificity and potency. Subsequently, we were able to identify eight novel inhibition targets through constraint-based modeling methods. The results of this study are expected to yield meaningful avenues for further research in the task of mediating the Toll-like receptor signaling network and its effects.

Development of the advanced PHWR technology -Design and analysis of CANDU advanced fuel-

Energy Technology Data Exchange (ETDEWEB)

Suk, Hoh Chun; Shim, Kee Sub; Byun, Taek Sang; Park, Kwang Suk; Kang, Heui Yung; Kim, Bong Kee; Jung, Chang Joon; Lee, Yung Wook; Bae, Chang Joon; Kwon, Oh Sun; Oh, Duk Joo; Im, Hong Sik; Ohn, Myung Ryong; Lee, Kang Moon; Park, Joo Hwan; Lee, Eui Joon [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

1995-07-01

This is the `94 annual report of the CANDU advanced fuel design and analysis project, and describes CANFLEX fuel design and mechanical integrity analysis, reactor physics analysis and safety analysis of the CANDU-6 with the CANFLEX-NU. The following is the R and D scope of this fiscal year : (1) Detail design of CANFLEX-NU and detail analysis on the fuel integrity, reactor physics and safety. (a) Detail design and mechanical integrity analysis of the bundle (b) CANDU-6 refueling simulation, and analysis on the Xe transients and adjuster system capability (c) Licensing strategy establishment and safety analysis for the CANFLEX-NU demonstration demonstration irradiation in a commercial CANDU-6. (2) Production and revision of CANFLEX-NU fuel design documents (a) Production and approval of CANFLEX-NU reference drawing, and revisions of fuel design manual and technical specifications (b) Production of draft physics design manual. (3) Basic research on CANFLEX-SEU fuel. 55 figs, 21 tabs, 45 refs. (Author).

Artificial Intelligence at Advanced Information and Decision Systems

OpenAIRE

McCune, Brian P.

1981-01-01

Advanced Information and Decision Systems (AI-DS) is a relatively new, employee-owned company that does basic and applied research, product development, and consulting in the fields of artificial intelligence, computer science, decision analysis, operations research, control theory, estimation theory, and signal processing. AI&DS performs studies, analyses, systems design and evaluation, and software development for a variety of industrial clients and government agencies, including the Depart...

Joint time frequency analysis in digital signal processing

DEFF Research Database (Denmark)

Pedersen, Flemming

with this technique is that the resolution is limited because of distortion. To overcome the resolution limitations of the Fourier Spectogram, many new distributions have been developed. In spite of this the Fourier Spectogram is by far the prime method for the analysis of signals whose spectral content is varying...

Analysis Sparse Representation for Nonnegative Signals Based on Determinant Measure by DC Programming

Directory of Open Access Journals (Sweden)

Yujie Li

2018-01-01

Full Text Available Analysis sparse representation has recently emerged as an alternative approach to the synthesis sparse model. Most existing algorithms typically employ the l0-norm, which is generally NP-hard. Other existing algorithms employ the l1-norm to relax the l0-norm, which sometimes cannot promote adequate sparsity. Most of these existing algorithms focus on general signals and are not suitable for nonnegative signals. However, many signals are necessarily nonnegative such as spectral data. In this paper, we present a novel and efficient analysis dictionary learning algorithm for nonnegative signals with the determinant-type sparsity measure which is convex and differentiable. The analysis sparse representation can be cast in three subproblems, sparse coding, dictionary update, and signal update, because the determinant-type sparsity measure would result in a complex nonconvex optimization problem, which cannot be easily solved by standard convex optimization methods. Therefore, in the proposed algorithms, we use a difference of convex (DC programming scheme for solving the nonconvex problem. According to our theoretical analysis and simulation study, the main advantage of the proposed algorithm is its greater dictionary learning efficiency, particularly compared with state-of-the-art algorithms. In addition, our proposed algorithm performs well in image denoising.

Advances in meta-analysis: examples from internal medicine to neurology.

Science.gov (United States)

Copetti, Massimiliano; Fontana, Andrea; Graziano, Giusi; Veneziani, Federica; Siena, Federica; Scardapane, Marco; Lucisano, Giuseppe; Pellegrini, Fabio

2014-01-01

We review the state of the art in meta-analysis and data pooling following the evolution of the statistical models employed. Starting from a classic definition of meta-analysis of published data, a set of apparent antinomies which characterized the development of the meta-analytic tools are reconciled in dichotomies where the second term represents a possible generalization of the first one. Particular attention is given to the generalized linear mixed models as an overall framework for meta-analysis. Bayesian meta-analysis is discussed as a further possibility of generalization for sensitivity analysis and the use of priors as a data augmentation approach. We provide relevant examples to underline how the need for adequate methods to solve practical issues in specific areas of research have guided the development of advanced methods in meta-analysis. We show how all the advances in meta-analysis naturally merge into the unified framework of generalized linear mixed models and reconcile apparently conflicting approaches. All these complex models can be easily implemented with the standard commercial software available. © 2013 S. Karger AG, Basel.

Wavelet Analysis of Ultrasonic Echo Waveform and Application to Nondestructive Evaluation

International Nuclear Information System (INIS)

Park, Ik Keun; Park, Un Su; Ahn, Hyung Keun; Kwun, Sook In; Byeon, Jai Won

2000-01-01

Recently, advanced signal analysis which is called 'time-frequency analysis' has been used widely in nondestructive evaluation applications. Wavelet transform(WT) and Wigner Distribution are the most advanced techniques for processing signals with time-varying spectra. Wavelet analysis method is an attractive technique for evaluation of material characterization nondestructively. Wavelet transform is applied to the time-frequency analysis of ultrasonic echo waveform obtained by an ultrasonic pulse-echo technique. In this study, the feasibility of noise suppression of ultrasonic flaw signal and frequency-dependent ultrasonic group velocity and attenuation coefficient using wavelet analysis of ultrasonic echo waveform have been verified experimentally. The Gabor function is adopted the analyzing wavelet. The wavelet analysis shows that the variations of ultrasonic group velocity and attenuation coefficient due to the change of material characterization can be evaluated at each frequency. Furthermore, to assure the enhancement of detectability and new sizing performance, both computer simulated results and experimental measurements using wavelet signal processing are used to demonstrate the effectiveness of the noise suppression of ultrasonic flaw signal obtained from austenitic stainless steel weld including EDM notch

Analysis of a dynamic model of guard cell signaling reveals the stability of signal propagation

Science.gov (United States)

Gan, Xiao; Albert, RéKa

Analyzing the long-term behaviors (attractors) of dynamic models of biological systems can provide valuable insight into biological phenotypes and their stability. We identified the long-term behaviors of a multi-level, 70-node discrete dynamic model of the stomatal opening process in plants. We reduce the model's huge state space by reducing unregulated nodes and simple mediator nodes, and by simplifying the regulatory functions of selected nodes while keeping the model consistent with experimental observations. We perform attractor analysis on the resulting 32-node reduced model by two methods: 1. converting it into a Boolean model, then applying two attractor-finding algorithms; 2. theoretical analysis of the regulatory functions. We conclude that all nodes except two in the reduced model have a single attractor; and only two nodes can admit oscillations. The multistability or oscillations do not affect the stomatal opening level in any situation. This conclusion applies to the original model as well in all the biologically meaningful cases. We further demonstrate the robustness of signal propagation by showing that a large percentage of single-node knockouts does not affect the stomatal opening level. Thus, we conclude that the complex structure of this signal transduction network provides multiple information propagation pathways while not allowing extensive multistability or oscillations, resulting in robust signal propagation. Our innovative combination of methods offers a promising way to analyze multi-level models.

Advances in power system modelling, control and stability analysis

CERN Document Server

Milano, Federico

2016-01-01

Advances in Power System Modelling, Control and Stability Analysis captures the variety of new methodologies and technologies that are changing the way modern electric power systems are modelled, simulated and operated.

Analysis of monochromatic signals by using data from the detector of Allegro gravitational waves

International Nuclear Information System (INIS)

Oliveira, Fernanda Gomes de

2010-01-01

The present work is developed in the searching for monochromatic gravitational waves signals in ALLEGRO's data. We have two procedures for data analysis based on the periodogram of Welch, which a method for the detection of monochromatic signals in the middle of noise which basically makes power spectrum estimates using averaged modified periodograms. By using this method it was possible to obtain a power spectrum for the data which reinforce peaks due to monochromatic signals. The two procedures of analysis for the years 1997 and 1999, were focused on monitoring a peak that appears in the spectral density of ALLEGRO's detector, so called 'mystery mode' (near 887 Hz). We look for variations in the frequency of the mystery mode that agree with the variation of the Doppler effect. In the rst analysis we have used by the variation of daily and annual Doppler shift. For the second one, we have only searched annual Doppler shift. We have applied the periodogram of Welch in both tests in the raw data of the detector in the search for a real signal and we found some peaks that can be candidates of gravitational radiation only the second analysis. In order to test the method we used in both analysis a simulated gravitational wave signal modulated by the Doppler effect injected in the data. We detected in both methods the artificial signal of GW simulated. Therefore we have reason to conclude that both methods are efficient in the search for monochromatic signals. (author)

Inositol trisphosphate receptor mediated spatiotemporal calcium signalling.

Science.gov (United States)

Miyazaki, S

1995-04-01

Spatiotemporal Ca2+ signalling in the cytoplasm is currently understood as an excitation phenomenon by analogy with electrical excitation in the plasma membrane. In many cell types, Ca2+ waves and Ca2+ oscillations are mediated by inositol 1,4,5-trisphosphate (IP3) receptor/Ca2+ channels in the endoplasmic reticulum membrane, with positive feedback between cytosolic Ca2+ and IP3-induced Ca2+ release creating a regenerative process. Remarkable advances have been made in the past year in the analysis of subcellular Ca2+ microdomains using confocal microscopy and of Ca2+ influx pathways that are functionally coupled to IP3-induced Ca2+ release. Ca2+ signals can be conveyed into the nucleus and mitochondria. Ca2+ entry from outside the cell allows repetitive Ca2+ release by providing Ca2+ to refill the endoplasmic reticulum stores, thus giving rise to frequency-encoded Ca2+ signals.

Nuclear Fuel Cycle Analysis Technology to Develop Advanced Nuclear Fuel Cycle

Energy Technology Data Exchange (ETDEWEB)

Park, Byung Heung [Chungju National University, Chungju (Korea, Republic of); Ko, Won IL [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

2011-12-15

The nuclear fuel cycle (NFC) analysis is a study to set a NFC policy and to promote systematic researches by analyzing technologies and deriving requirements at each stage of a fuel cycle. System analysis techniques are utilized for comparative analysis and assessment of options on a considered system. In case that NFC is taken into consideration various methods of the system analysis techniques could be applied depending on the range of an interest. This study presented NFC analysis strategies for the development of a domestic advanced NFC and analysis techniques applicable to different phases of the analysis. Strategically, NFC analysis necessitates the linkage with technology analyses, domestic and international interests, and a national energy program. In this respect, a trade-off study is readily applicable since it includes various aspects on NFC as metrics and then analyzes the considered NFC options according to the derived metrics. In this study, the trade-off study was identified as a method for NFC analysis with the derived strategies and it was expected to be used for development of an advanced NFC. A technology readiness level (TRL) method and NFC simulation codes could be utilized to obtain the required metrics and data for assessment in the trade-off study. The methodologies would guide a direction of technology development by comparing and assessing technological, economical, environmental, and other aspects on the alternatives. Consequently, they would contribute for systematic development and deployment of an appropriate advanced NFC.

Nuclear Fuel Cycle Analysis Technology to Develop Advanced Nuclear Fuel Cycle

International Nuclear Information System (INIS)

Park, Byung Heung; Ko, Won IL

2011-01-01

The nuclear fuel cycle (NFC) analysis is a study to set a NFC policy and to promote systematic researches by analyzing technologies and deriving requirements at each stage of a fuel cycle. System analysis techniques are utilized for comparative analysis and assessment of options on a considered system. In case that NFC is taken into consideration various methods of the system analysis techniques could be applied depending on the range of an interest. This study presented NFC analysis strategies for the development of a domestic advanced NFC and analysis techniques applicable to different phases of the analysis. Strategically, NFC analysis necessitates the linkage with technology analyses, domestic and international interests, and a national energy program. In this respect, a trade-off study is readily applicable since it includes various aspects on NFC as metrics and then analyzes the considered NFC options according to the derived metrics. In this study, the trade-off study was identified as a method for NFC analysis with the derived strategies and it was expected to be used for development of an advanced NFC. A technology readiness level (TRL) method and NFC simulation codes could be utilized to obtain the required metrics and data for assessment in the trade-off study. The methodologies would guide a direction of technology development by comparing and assessing technological, economical, environmental, and other aspects on the alternatives. Consequently, they would contribute for systematic development and deployment of an appropriate advanced NFC.

An introduction to audio content analysis applications in signal processing and music informatics

CERN Document Server

Lerch, Alexander

2012-01-01

"With the proliferation of digital audio distribution over digital media, audio content analysis is fast becoming a requirement for designers of intelligent signal-adaptive audio processing systems. Written by a well-known expert in the field, this book provides quick access to different analysis algorithms and allows comparison between different approaches to the same task, making it useful for newcomers to audio signal processing and industry experts alike. A review of relevant fundamentals in audio signal processing, psychoacoustics, and music theory, as well as downloadable MATLAB files are also included"--

Large-Signal Lyapunov-Based Stability Analysis of DC/AC Inverters and Inverter-Based Microgrids

Science.gov (United States)

Kabalan, Mahmoud

study. This will enable future studies to save computational effort and produce the most accurate results according to the needs of the study being performed. Moreover, the effect of grid (line) impedance on the accuracy of droop control is explored using the 5th order model. Simulation results show that traditional droop control is valid up to R/X line impedance value of 2. Furthermore, the 3rd order nonlinear model improves the currently available inverter-infinite bus models by accounting for grid impedance, active power-frequency droop and reactive power-voltage droop. Results show the 3rd order model's ability to account for voltage and reactive power changes during a transient event. Finally, the large-signal Lyapunov-based stability analysis is completed for a 3 bus microgrid system (made up of 2 inverters and 1 linear load). The thesis provides a systematic state space large-signal nonlinear mathematical modeling method of inverter-based microgrids. The inverters include the dc-side dynamics associated with dc sources. The mathematical model is then used to estimate the domain of asymptotic stability of the 3 bus microgrid. The three bus microgrid system was used as a case study to highlight the design and optimization capability of a large-signal-based approach. The study explores the effect of system component sizing, load transient and generation variations on the asymptotic stability of the microgrid. Essentially, this advancement gives microgrid designers and engineers the ability to manipulate the domain of asymptotic stability depending on performance requirements. Especially important, this research was able to couple the domain of asymptotic stability of the ac microgrid with that of the dc side voltage source. Time domain simulations were used to demonstrate the mathematical nonlinear analysis results.

Multibeam swath bathymetry signal processing techniques

Digital Repository Service at National Institute of Oceanography (India)

Ranade, G.; Sudhakar, T.

Mathematical advances and the advances in the real time signal processing techniques in the recent times, have considerably improved the state of art in the bathymetry systems. These improvements have helped in developing high resolution swath...

Signal analysis and processing for SmartPET

International Nuclear Information System (INIS)

Scraggs, David; Boston, Andrew; Boston, Helen; Cooper, Reynold; Hall, Chris; Mather, Andy; Nolan, Paul; Turk, Gerard

2007-01-01

Measurement of induced transient charges on spectator electrodes is a critical requirement of the SmartPET project. Such a task requires the precise measurement of small amplitude pulses. Induced charge magnitudes on the SmartPET detectors were therefore studied and the suitability of wavelet analysis applied to de-noising signals was investigated. It was found that the absolute net maximum induced charge magnitudes from the two adjacent electrodes to the collecting electrode is 17% of the real charge magnitude for the AC side and 20% for the DC side. It was also found that wavelet analysis could identify induced charges of comparable magnitude to system noise

Application on technique of joint time-frequency analysis of seismic signal's first arrival estimation

International Nuclear Information System (INIS)

Xu Chaoyang; Liu Junmin; Fan Yanfang; Ji Guohua

2008-01-01

Joint time-frequency analysis is conducted to construct one joint density function of time and frequency. It can open out one signal's frequency components and their evolvements. It is the new evolvement of Fourier analysis. In this paper, according to the characteristic of seismic signal's noise, one estimation method of seismic signal's first arrival based on triple correlation of joint time-frequency spectrum is introduced, and the results of experiment and conclusion are presented. (authors)

METHODS ADVANCEMENT FOR MILK ANALYSIS: THE MAMA STUDY

Science.gov (United States)

The Methods Advancement for Milk Analysis (MAMA) study was designed by US EPA and CDC investigators to provide data to support the technological and study design needs of the proposed National Children=s Study (NCS). The NCS is a multi-Agency-sponsored study, authorized under the...

Advanced stress analysis of PWR containments in the region of nozzles

International Nuclear Information System (INIS)

Schauer, G.

1977-01-01

As an example of the stress analysis of a nozzle in a PWR steel containment, an advanced stress analysis of a personnel lock is presented. Contrary to the calculations by means of numerical shell programs usual till now, this advanced stress analysis was executed with the finite-element-method. Because of their theory, the shell programs compute mathematically exact results, but at the intersection of two shells the notch stresses cannot be analyzed well. A further disadvantage must be seen in the fact that there is a great distance between the real critical region near the intersection line and the calculation point, which lies on the neutral axis of the shell

Cascaded analysis of signal and noise propagation through a heterogeneous breast model

International Nuclear Information System (INIS)

Mainprize, James G.; Yaffe, Martin J.

2010-01-01

Purpose: The detectability of lesions in radiographic images can be impaired by patterns caused by the surrounding anatomic structures. The presence of such patterns is often referred to as anatomic noise. Others have previously extended signal and noise propagation theory to include variable background structure as an additional noise term and used in simulations for analysis by human and ideal observers. Here, the analytic forms of the signal and noise transfer are derived to obtain an exact expression for any input random distribution and the ''power law'' filter used to generate the texture of the tissue distribution. Methods: A cascaded analysis of propagation through a heterogeneous model is derived for x-ray projection through simulated heterogeneous backgrounds. This is achieved by considering transmission through the breast as a correlated amplification point process. The analytic forms of the cascaded analysis were compared to monoenergetic Monte Carlo simulations of x-ray propagation through power law structured backgrounds. Results: As expected, it was found that although the quantum noise power component scales linearly with the x-ray signal, the anatomic noise will scale with the square of the x-ray signal. There was a good agreement between results obtained using analytic expressions for the noise power and those from Monte Carlo simulations for different background textures, random input functions, and x-ray fluence. Conclusions: Analytic equations for the signal and noise properties of heterogeneous backgrounds were derived. These may be used in direct analysis or as a tool to validate simulations in evaluating detectability.

Random signal tomographical analysis of two-phase flow

International Nuclear Information System (INIS)

Han, P.; Wesser, U.

1990-01-01

This paper reports on radiation tomography which is a useful tool for studying the internal structures of two-phase flow. However, general tomography analysis gives only time-averaged results, hence much information is lost. As a result, it is sometimes difficult to identify the flow regime; for example, the time-averaged picture does not significantly change as an annual flow develops from a slug flow. A two-phase flow diagnostic technique based on random signal tomographical analysis is developed. It extracts more information by studying the statistical variation of the measured signal with time. Local statistical parameters, including mean value, variance, skewness and flatness etc., are reconstructed from the information obtained by a general tomography technique. More important information are provided by the results. Not only the void fraction can be easily calculated, but also the flow pattern can be identified more objectively and more accurately. The experimental setup is introduced. It consisted of a two-phase flow loop, an X-ray system, a fan-like five-beam detector system and a signal acquisition and processing system. In the experiment, for both horizontal and vertical test sections (aluminum and steel tube with Di/Do = 40/45 mm), different flow situations are realized by independently adjusting air and water mass flow. Through a glass tube connected with the test section, some typical flow patterns are visualized and used for comparing with the reconstruction results

ECG Signal Processing, Classification and Interpretation A Comprehensive Framework of Computational Intelligence

CERN Document Server

Pedrycz, Witold

2012-01-01

Electrocardiogram (ECG) signals are among the most important sources of diagnostic information in healthcare so improvements in their analysis may also have telling consequences. Both the underlying signal technology and a burgeoning variety of algorithms and systems developments have proved successful targets for recent rapid advances in research. ECG Signal Processing, Classification and Interpretation shows how the various paradigms of Computational Intelligence, employed either singly or in combination, can produce an effective structure for obtaining often vital information from ECG signals. Neural networks do well at capturing the nonlinear nature of the signals, information granules realized as fuzzy sets help to confer interpretability on the data and evolutionary optimization may be critical in supporting the structural development of ECG classifiers and models of ECG signals. The contributors address concepts, methodology, algorithms, and case studies and applications exploiting the paradigm of Comp...

Advanced Power Plant Development and Analysis Methodologies

Energy Technology Data Exchange (ETDEWEB)

A.D. Rao; G.S. Samuelsen; F.L. Robson; B. Washom; S.G. Berenyi

2006-06-30

Under the sponsorship of the U.S. Department of Energy/National Energy Technology Laboratory, a multi-disciplinary team led by the Advanced Power and Energy Program of the University of California at Irvine is defining the system engineering issues associated with the integration of key components and subsystems into advanced power plant systems with goals of achieving high efficiency and minimized environmental impact while using fossil fuels. These power plant concepts include 'Zero Emission' power plants and the 'FutureGen' H2 co-production facilities. The study is broken down into three phases. Phase 1 of this study consisted of utilizing advanced technologies that are expected to be available in the 'Vision 21' time frame such as mega scale fuel cell based hybrids. Phase 2 includes current state-of-the-art technologies and those expected to be deployed in the nearer term such as advanced gas turbines and high temperature membranes for separating gas species and advanced gasifier concepts. Phase 3 includes identification of gas turbine based cycles and engine configurations suitable to coal-based gasification applications and the conceptualization of the balance of plant technology, heat integration, and the bottoming cycle for analysis in a future study. Also included in Phase 3 is the task of acquiring/providing turbo-machinery in order to gather turbo-charger performance data that may be used to verify simulation models as well as establishing system design constraints. The results of these various investigations will serve as a guide for the U. S. Department of Energy in identifying the research areas and technologies that warrant further support.

Signal Based Mixing Analysis for the magnetohydrodynamic mode reconstruction from homodyne microwave reflectometry

International Nuclear Information System (INIS)

Ejiri, Akira; Sakakibara, Satoru; Kawahata, Kazuo.

1995-03-01

A new method 'Signal Based Mixing Analysis', to extract the components which are coherent to a certain reference signal from a noisy signal, has been developed. The method is applied to homodyne microwave reflectometry to reconstruct the radial structure of a magnetohydrodynamic (MHD) mode in heliotron/torsatron Compact Helical System (CHS) [K. Matsuoka et al. Plasma Phys. Control. Nuclear Fusion Research 1988 Vol. 2, IAEA, Vienna 411 (1989)]. In CHS plasmas, MHD fluctuations measured with magnetic probes show bursts, in which the amplitude and frequency quasi-periodically vary. The signal based mixing analysis uses a set of functions which have the same amplitude and the harmonic frequency as those of the magnetic fluctuations. The product (mixing) of the signal of reflectometer and the functions yields the amplitude and phase of the coherent components. When the plasma density gradually increases, the measuring position moves radially outward. Thus, the radial structure of MHD modes can be obtained by this method. The analysis indicates several peaks and nodes inside the resonance surface of the MHD mode. In addition, the structure does not propagate radially during a burst. (author)

Probabilistic Durability Analysis in Advanced Engineering Design

Directory of Open Access Journals (Sweden)

A. Kudzys

2000-01-01

Full Text Available Expedience of probabilistic durability concepts and approaches in advanced engineering design of building materials, structural members and systems is considered. Target margin values of structural safety and serviceability indices are analyzed and their draft values are presented. Analytical methods of the cumulative coefficient of correlation and the limit transient action effect for calculation of reliability indices are given. Analysis can be used for probabilistic durability assessment of carrying and enclosure metal, reinforced concrete, wood, plastic, masonry both homogeneous and sandwich or composite structures and some kinds of equipments. Analysis models can be applied in other engineering fields.

Can Technical Analysis Signals Detect Price Reactions Around Earnings Announcement?: Evidence from Indonesia

OpenAIRE

Dedhy Sulistiawan; Jogiyanto Hartono

2014-01-01

This study examines whether technical analysis signals can detect price reactions before and after earnings announcement dates in Indonesian stock market. Earnings announcements produce reactions, both before and after the announcements. Informed investors may use private information before earnings announcements (Christophe, Ferri and Angel, 2004; Porter, 1992). Using technical analysis signals, this study expects that retail investors (uninformed investors) can detect preannouncements react...

TMS320C25 Digital Signal Processor For 2-Dimensional Fast Fourier Transform Computation

International Nuclear Information System (INIS)

Ardisasmita, M. Syamsa

1996-01-01

The Fourier transform is one of the most important mathematical tool in signal processing and analysis, which converts information from the time/spatial domain into the frequency domain. Even with implementation of the Fast Fourier Transform algorithms in imaging data, the discrete Fourier transform execution consume a lot of time. Digital signal processors are designed specifically to perform computation intensive digital signal processing algorithms. By taking advantage of the advanced architecture. parallel processing, and dedicated digital signal processing (DSP) instruction sets. This device can execute million of DSP operations per second. The device architecture, characteristics and feature suitable for fast Fourier transform application and speed-up are discussed

Analysis of Muscle Fatigue Progression using Cyclostationary Property of Surface Electromyography Signals.

Science.gov (United States)

Karthick, P A; Venugopal, G; Ramakrishnan, S

2016-01-01

Analysis of neuromuscular fatigue finds various applications ranging from clinical studies to biomechanics. Surface electromyography (sEMG) signals are widely used for these studies due to its non-invasiveness. During cyclic dynamic contractions, these signals are nonstationary and cyclostationary. In recent years, several nonstationary methods have been employed for the muscle fatigue analysis. However, cyclostationary based approach is not well established for the assessment of muscle fatigue. In this work, cyclostationarity associated with the biceps brachii muscle fatigue progression is analyzed using sEMG signals and Spectral Correlation Density (SCD) functions. Signals are recorded from fifty healthy adult volunteers during dynamic contractions under a prescribed protocol. These signals are preprocessed and are divided into three segments, namely, non-fatigue, first muscle discomfort and fatigue zones. Then SCD is estimated using fast Fourier transform accumulation method. Further, Cyclic Frequency Spectral Density (CFSD) is calculated from the SCD spectrum. Two features, namely, cyclic frequency spectral area (CFSA) and cyclic frequency spectral entropy (CFSE) are proposed to study the progression of muscle fatigue. Additionally, degree of cyclostationarity (DCS) is computed to quantify the amount of cyclostationarity present in the signals. Results show that there is a progressive increase in cyclostationary during the progression of muscle fatigue. CFSA shows an increasing trend in muscle fatiguing contraction. However, CFSE shows a decreasing trend. It is observed that when the muscle progresses from non-fatigue to fatigue condition, the mean DCS of fifty subjects increases from 0.016 to 0.99. All the extracted features found to be distinct and statistically significant in the three zones of muscle contraction (p < 0.05). It appears that these SCD features could be useful in the automated analysis of sEMG signals for different neuromuscular conditions.

Event recognition using signal spectrograms in long pulse experiments

International Nuclear Information System (INIS)

Gonzalez, J.; Ruiz, M.; Barrera, E.; Arcas, G.; Lopez, J. M.; Vega, J.

2010-01-01

As discharge duration increases, real-time complex analysis of the signal becomes more important. In this context, data acquisition and processing systems must provide models for designing experiments which use event oriented plasma control. One example of advanced data analysis is signal classification. The off-line statistical analysis of a large number of discharges provides information to develop algorithms for the determination of the plasma parameters from measurements of magnetohydrodinamic waves, for example, to detect density fluctuations induced by the Alfven cascades using morphological patterns. The need to apply different algorithms to the signals and to address different processing algorithms using the previous results necessitates the use of an event-based experiment. The Intelligent Test and Measurement System platform is an example of architecture designed to implement distributed data acquisition and real-time processing systems. The processing algorithm sequence is modeled using an event-based paradigm. The adaptive capacity of this model is based on the logic defined by the use of state machines in SCXML. The Intelligent Test and Measurement System platform mixes a local multiprocessing model with a distributed deployment of services based on Jini.

Technical and economic effect analysis of advanced MMIS implementation in KNGR

International Nuclear Information System (INIS)

Choe, Il Nam

1997-01-01

KNGR MMIS design approaches are summarized as follows: 1) compact workstation type operator console design to reduce the operators' physical and cognitive work loads by implementing Factors Engineering (HFE) principles and advanced graphic user interface technologies. 2) Full digital control and protection system design to enhance the reliability operability and maintainability. 3) Remote signal multiplexer implementation to reduce the hard-wired cable and cable installation cost and time. 4) Licensable design to meet latest licensing requirements including HFE and safety software validation and verification. 5 refs., 1 tab., 1 fig

Analysis instruments for the performance of Advanced Practice Nursing.

Science.gov (United States)

Sevilla-Guerra, Sonia; Zabalegui, Adelaida

2017-11-29

Advanced Practice Nursing has been a reality in the international context for several decades and recently new nursing profiles have been developed in Spain as well that follow this model. The consolidation of these advanced practice roles has also led to of the creation of tools that attempt to define and evaluate their functions. This study aims to identify and explore the existing instruments that enable the domains of Advanced Practice Nursing to be defined. A review of existing international questionnaires and instruments was undertaken, including an analysis of the design process, the domains/dimensions defined, the main results and an exploration of clinimetric properties. Seven studies were analysed but not all proved to be valid, stable or reliable tools. One included tool was able to differentiate between the functions of the general nurse and the advanced practice nurse by the level of activities undertaken within the five domains described. These tools are necessary to evaluate the scope of advanced practice in new nursing roles that correspond to other international models of competencies and practice domains. Copyright © 2017 Elsevier España, S.L.U. All rights reserved.

An overview of data acquisition, signal coding and data analysis techniques for MST radars

Science.gov (United States)

Rastogi, P. K.

1986-01-01

An overview is given of the data acquisition, signal processing, and data analysis techniques that are currently in use with high power MST/ST (mesosphere stratosphere troposphere/stratosphere troposphere) radars. This review supplements the works of Rastogi (1983) and Farley (1984) presented at previous MAP workshops. A general description is given of data acquisition and signal processing operations and they are characterized on the basis of their disparate time scales. Then signal coding, a brief description of frequently used codes, and their limitations are discussed, and finally, several aspects of statistical data processing such as signal statistics, power spectrum and autocovariance analysis, outlier removal techniques are discussed.

Advanced glycation end-products (AGEs acutely impair Ca2+ signalling in bovine aortic endothelial cells

Directory of Open Access Journals (Sweden)

Nadim eNaser

2013-03-01

Full Text Available Post-translational modification of proteins in diabetes, including formation of advanced glycation end products (AGEs are believed to contribute to vascular dysfunction and disease. Impaired function of the endothelium is an early indicator of vascular dysfunction in diabetes and as many endothelial cell processes are dependent upon intracellular [Ca2+] and Ca2+ signalling, the aim of this study was to examine the acute effects of AGEs on Ca2+ signalling in bovine aortic endothelial cells (BAEC. Ca2+ signalling was studied using the fluorescent indicator dye Fura2-AM. AGEs were generated by incubating bovine serum albumin with 0 - 250 mM glucose or glucose-6-phosphate for 0 to 120 days at 37ºC. Under all conditions, the main AGE species generated was carboxymethyl lysine (CML as assayed using both GC-MS and HPLC. In Ca2+-replete solution, exposure of BAEC to AGEs for 5 min caused an elevation in basal [Ca2+] and attenuated the increase in intracellular [Ca2+] caused by ATP (100 µM. In the absence of extracellular Ca2+, exposure of BAEC to AGEs for 5 min caused an elevation in basal [Ca2+] and attenuated subsequent intracellular Ca2+ release caused by ATP, thapsigargin (0.1 µM and ionomycin (3 µM, but AGEs did not affect extracellular Ca2+ entry induced by the re-addition of Ca2+ to the bathing solution in the presence of any of these agents. The anti-oxidant α-lipoic acid (2 µM and NAD(PH oxidase inhibitors apocynin (500 µM and diphenyleneiodonium (DPI, 1 µM abolished these effects of AGEs on BAECs, as did the IP3 receptor antagonist xestospongin C (1 µM. In summary, AGEs caused an acute depletion of Ca2+ from the intracellular store in BAECs, such that the Ca2+ signal stimulated by the subsequent application other agents acting upon this store is reduced. The mechanism may involve generation of ROS from NAD(PH oxidase and possible activation of the IP3 receptor.

Advanced exergy analysis on a modified auto-cascade freezer cycle with an ejector

International Nuclear Information System (INIS)

Bai, Tao; Yu, Jianlin; Yan, Gang

2016-01-01

This paper presents a study on a modified ejector enhanced auto-cascade freezer cycle with conventional thermodynamic and advanced exergy analysis methods. The energetic analysis shows that the modified cycle exhibits better performance than the conventional auto-cascade freezer cycle, and the system COP and volumetric refrigeration capacity could be improved by 19.93% and 28.42%. Furthermore, advanced exergy analysis is adopted to better evaluate the performance of the proposed cycle. The exergy destruction within a system component is split into endogenous/exogenous and unavoidable/avoidable parts in the advanced exergy analysis. The results show that the compressor with the largest avoidable endogenous exergy destruction has highest improvement priority, followed by the condenser, evaporator and ejector, which is different from the conclusion obtained from the conventional exergy analysis. The evaporator/condenser greatly affects the exogenous exergy destruction within the system components, and the compressor has large impact on the exergy destruction within the condenser. Improving the efficiencies of the compressor efficiency and the ejector could effectively reduce the corresponding avoidable endogenous exergy destruction. The exergy destruction within the evaporator almost entirely belongs to the endogenous part, and reducing the temperature difference at the evaporator is the main approach of reducing its exergy destruction. - Highlights: • A modified ejector enhanced auto-cascade freezer cycle is proposed. • Conventional and advanced exergy analyses are performed in this study. • Compressor should be firstly improved first, followed by condenser and evaporator. • Interactions among the system components are assessed with advanced exergy analysis.

Design and Analysis of a New Hair Sensor for Multi-Physical Signal Measurement

Directory of Open Access Journals (Sweden)

Bo Yang

2016-07-01

Full Text Available A new hair sensor for multi-physical signal measurements, including acceleration, angular velocity and air flow, is presented in this paper. The entire structure consists of a hair post, a torsional frame and a resonant signal transducer. The hair post is utilized to sense and deliver the physical signals of the acceleration and the air flow rate. The physical signals are converted into frequency signals by the resonant transducer. The structure is optimized through finite element analysis. The simulation results demonstrate that the hair sensor has a frequency of 240 Hz in the first mode for the acceleration or the air flow sense, 3115 Hz in the third and fourth modes for the resonant conversion, and 3467 Hz in the fifth and sixth modes for the angular velocity transformation, respectively. All the above frequencies present in a reasonable modal distribution and are separated from interference modes. The input-output analysis of the new hair sensor demonstrates that the scale factor of the acceleration is 12.35 Hz/g, the scale factor of the angular velocity is 0.404 nm/deg/s and the sensitivity of the air flow is 1.075 Hz/(m/s2, which verifies the multifunction sensitive characteristics of the hair sensor. Besides, the structural optimization of the hair post is used to improve the sensitivity of the air flow rate and the acceleration. The analysis results illustrate that the hollow circular hair post can increase the sensitivity of the air flow and the II-shape hair post can increase the sensitivity of the acceleration. Moreover, the thermal analysis confirms the scheme of the frequency difference for the resonant transducer can prominently eliminate the temperature influences on the measurement accuracy. The air flow analysis indicates that the surface area increase of hair post is significantly beneficial for the efficiency improvement of the signal transmission. In summary, the structure of the new hair sensor is proved to be feasible by

DEAP: A Database for Emotion Analysis Using Physiological Signals

NARCIS (Netherlands)

Koelstra, Sander; Mühl, C.; Soleymani, Mohammad; Lee, Jung Seok; Yazdani, Ashkan; Ebrahimi, Touradj; Pun, Thierry; Nijholt, Antinus; Patras, Ioannis

2012-01-01

We present a multimodal dataset for the analysis of human affective states. The electroencephalogram (EEG) and peripheral physiological signals of 32 participants were recorded as each watched 40 one-minute long excerpts of music videos. Participants rated each video in terms of the levels of

Development of knowledgebase system for assisting signal validation scheme design

International Nuclear Information System (INIS)

Kitamura, M.; Baba, T.; Washio, T.; Sugiyama, K.

1987-01-01

The purpose of this study is to develop a knowledgebase system to be used as a tool for designing signal validation schemes. The outputs from the signal validation scheme can be used as; (1) auxiliary signals for detecting sensor failures, (2) inputs to advanced instrumentation such as disturbance analysis and diagnosis system or safety parameter display system, and (3) inputs to digital control systems. Conventional signal validation techniques such as comparison of redundant sensors, limit checking, and calibration tests have been employed in nuclear power plants. However, these techniques have serious drawbacks, e.g. needs for extra sensors, vulnerability to common mode failures, limited applicability to continuous monitoring, etc. To alleviate these difficulties, a new signal validation technique has been developed by using the methods called analytic redundancy and parity space. Although the new technique has been proved feasible as far as preliminary tests are concerned, further developments should be made in order to enhance its practical applicability

Signal Processing for Neuroscientists, A Companion Volume Advanced Topics, Nonlinear Techniques and Multi-Channel Analysis

CERN Document Server

van Drongelen, Wim

2010-01-01

The popularity of signal processing in neuroscience is increasing, and with the current availability and development of computer hardware and software, it is anticipated that the current growth will continue. Because electrode fabrication has improved and measurement equipment is getting less expensive, electrophysiological measurements with large numbers of channels are now very common. In addition, neuroscience has entered the age of light, and fluorescence measurements are fully integrated into the researcher's toolkit. Because each image in a movie contains multiple pixels, these measureme

Analysis and Simulation of Multi-target Echo Signals from a Phased Array Radar

OpenAIRE

Jia Zhen; Zhou Rui

2017-01-01

The construction of digital radar simulation systems has been a research hotspot of the radar field. This paper focuses on theoretical analysis and simulation of multi-target echo signals produced in a phased array radar system, and constructs an array antenna element and a signal generation environment. The antenna element is able to simulate planar arrays and optimizes these arrays by adding window functions. And the signal environment can model and simulate radar transmission signals, rada...

Using Statistical Analysis Software to Advance Nitro Plasticizer Wettability

Energy Technology Data Exchange (ETDEWEB)

Shear, Trevor Allan [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-08-29

Statistical analysis in science is an extremely powerful tool that is often underutilized. Additionally, it is frequently the case that data is misinterpreted or not used to its fullest extent. Utilizing the advanced software JMP®, many aspects of experimental design and data analysis can be evaluated and improved. This overview will detail the features of JMP® and how they were used to advance a project, resulting in time and cost savings, as well as the collection of scientifically sound data. The project analyzed in this report addresses the inability of a nitro plasticizer to coat a gold coated quartz crystal sensor used in a quartz crystal microbalance. Through the use of the JMP® software, the wettability of the nitro plasticizer was increased by over 200% using an atmospheric plasma pen, ensuring good sample preparation and reliable results.

Carotid artery stenosis: Performance of advanced vessel analysis software in evaluating CTA

International Nuclear Information System (INIS)

Tsiflikas, Ilias; Biermann, Christina; Thomas, Christoph; Ketelsen, Dominik; Claussen, Claus D.; Heuschmid, Martin

2012-01-01

Objectives: The aim of this study was to evaluate time efficiency and diagnostic reproducibility of an advanced vessel analysis software for diagnosis of carotid artery stenosis. Material and methods: 40 patients with suspected carotid artery stenosis received head and neck DE-CTA as part of their pre-interventional workup. Acquired data were evaluated by 2 independent radiologists. Stenosis grading was performed by MPR eyeballing with freely adjustable MPRs and with a preliminary prototype of the meanwhile available client-server and advanced visualization software syngo.via CT Vascular (Siemens Healthcare, Erlangen, Germany). Stenoses were graded according to the following 5 categories: I: 0%, II: 1–50%, III: 51–69%, IV: 70–99% and V: total occlusion. Furthermore, time to diagnosis for each carotid artery was recorded. Results: Both readers achieved very good specificity values and good respectively very good sensitivity values without significant differences between both reading methods. Furthermore, there was a very good correlation between both readers for both reading methods without significant differences (kappa value: standard image interpretation k = 0.809; advanced vessel analysis software k = 0.863). Using advanced vessel analysis software resulted in a significant time saving (p < 0.0001) for both readers. Time to diagnosis could be decreased by approximately 55%. Conclusions: Advanced vessel analysis application CT Vascular of the new imaging software syngo.via (Siemens Healthcare, Forchheim, Germany) provides a high rate of reproducibility in assessment of carotid artery stenosis. Furthermore a significant time saving in comparison to standard image interpretation is achievable

Carotid artery stenosis: Performance of advanced vessel analysis software in evaluating CTA

Energy Technology Data Exchange (ETDEWEB)

Tsiflikas, Ilias, E-mail: ilias.tsiflikas@med.uni-tuebingen.de [University Hospital of Tuebingen, Diagnostic and Interventional Radiology, Hoppe-Seyler-Str. 3, 72076 Tuebingen (Germany); Biermann, Christina, E-mail: christina.biermann@siemens.com [University Hospital of Tuebingen, Diagnostic and Interventional Radiology, Hoppe-Seyler-Str. 3, 72076 Tuebingen (Germany); Siemens AG, Siemens Healthcare Consulting, Allee am Röthelheimpark 3A, 91052 Erlangen (Germany); Thomas, Christoph, E-mail: christoph.thomas@med.uni-tuebingen.de [University Hospital of Tuebingen, Diagnostic and Interventional Radiology, Hoppe-Seyler-Str. 3, 72076 Tuebingen (Germany); Ketelsen, Dominik, E-mail: dominik.ketelsen@med.uni-tuebingen.de [University Hospital of Tuebingen, Diagnostic and Interventional Radiology, Hoppe-Seyler-Str. 3, 72076 Tuebingen (Germany); Claussen, Claus D., E-mail: claus.claussen@med.uni-tuebingen.de [University Hospital of Tuebingen, Diagnostic and Interventional Radiology, Hoppe-Seyler-Str. 3, 72076 Tuebingen (Germany); Heuschmid, Martin, E-mail: martin.heuschmid@med.uni-tuebingen.de [University Hospital of Tuebingen, Diagnostic and Interventional Radiology, Hoppe-Seyler-Str. 3, 72076 Tuebingen (Germany)

2012-09-15

Objectives: The aim of this study was to evaluate time efficiency and diagnostic reproducibility of an advanced vessel analysis software for diagnosis of carotid artery stenosis. Material and methods: 40 patients with suspected carotid artery stenosis received head and neck DE-CTA as part of their pre-interventional workup. Acquired data were evaluated by 2 independent radiologists. Stenosis grading was performed by MPR eyeballing with freely adjustable MPRs and with a preliminary prototype of the meanwhile available client-server and advanced visualization software syngo.via CT Vascular (Siemens Healthcare, Erlangen, Germany). Stenoses were graded according to the following 5 categories: I: 0%, II: 1–50%, III: 51–69%, IV: 70–99% and V: total occlusion. Furthermore, time to diagnosis for each carotid artery was recorded. Results: Both readers achieved very good specificity values and good respectively very good sensitivity values without significant differences between both reading methods. Furthermore, there was a very good correlation between both readers for both reading methods without significant differences (kappa value: standard image interpretation k = 0.809; advanced vessel analysis software k = 0.863). Using advanced vessel analysis software resulted in a significant time saving (p < 0.0001) for both readers. Time to diagnosis could be decreased by approximately 55%. Conclusions: Advanced vessel analysis application CT Vascular of the new imaging software syngo.via (Siemens Healthcare, Forchheim, Germany) provides a high rate of reproducibility in assessment of carotid artery stenosis. Furthermore a significant time saving in comparison to standard image interpretation is achievable.

Mixed-signal instrumentation for large-signal device characterization and modelling

NARCIS (Netherlands)

Marchetti, M.

2013-01-01

This thesis concentrates on the development of advanced large-signal measurement and characterization tools to support technology development, model extraction and validation, and power amplifier (PA) designs that address the newly introduced third and fourth generation (3G and 4G) wideband

Implications of advanced warning messages on eliminating sun glare disturbances at signalized intersections

Directory of Open Access Journals (Sweden)

Qing Li

2016-08-01

Full Text Available Due to sun glare disturbances, drivers encounter fatal threats on roadways, particularly at signalized intersections. Many studies have attempted to develop applicable solutions, such as avoiding sun positions, applying road geometric re-directions, and wearing anti-glare glasses. None of these strategies have fully solved the problem. As one of the “Connected Vehicle” practices proposed by the U.S. Department of Transportation, advanced warning messages (AWMs are capable of providing wireless information about traffic controls. AWM acts as a supplement to conventional signs and signals, which can be blocked by obstacles or natural disturbances, such as sun glare. The drivers' smart advisory system (DSAS can provide drivers with AWM. Using a driving simulator this research explores the effects of DSAS messages on driving behaviors under sun glare disturbance. Statistical analyses were applied to assess (1 the negative impacts of sun glare, (2 the compensation of the DSAS AWM to sun glare effects, and (3 the improvement in driving performance due to DSAS AWM. Four performance indexes were measured, including (1 half kinetic energy speed, (2 mean approach speed, (3 brake response time, and (4 braking distance. The effects of the socio-demographic factors, such as gender, age, educational background, and driving experience were also studied. The analytical results illustrate that the DSAS can compensate for reduced visibility due to sun glare and improve driving performance to a normal visual situation, particularly for left turn and through movement.

SVM-Based Spectral Analysis for Heart Rate from Multi-Channel WPPG Sensor Signals.

Science.gov (United States)

Xiong, Jiping; Cai, Lisang; Wang, Fei; He, Xiaowei

2017-03-03

Although wrist-type photoplethysmographic (hereafter referred to as WPPG) sensor signals can measure heart rate quite conveniently, the subjects' hand movements can cause strong motion artifacts, and then the motion artifacts will heavily contaminate WPPG signals. Hence, it is challenging for us to accurately estimate heart rate from WPPG signals during intense physical activities. The WWPG method has attracted more attention thanks to the popularity of wrist-worn wearable devices. In this paper, a mixed approach called Mix-SVM is proposed, it can use multi-channel WPPG sensor signals and simultaneous acceleration signals to measurement heart rate. Firstly, we combine the principle component analysis and adaptive filter to remove a part of the motion artifacts. Due to the strong relativity between motion artifacts and acceleration signals, the further denoising problem is regarded as a sparse signals reconstruction problem. Then, we use a spectrum subtraction method to eliminate motion artifacts effectively. Finally, the spectral peak corresponding to heart rate is sought by an SVM-based spectral analysis method. Through the public PPG database in the 2015 IEEE Signal Processing Cup, we acquire the experimental results, i.e., the average absolute error was 1.01 beat per minute, and the Pearson correlation was 0.9972. These results also confirm that the proposed Mix-SVM approach has potential for multi-channel WPPG-based heart rate estimation in the presence of intense physical exercise.

1st International Conference on Computational Advancement in Communication Circuits and Systems

CERN Document Server

Dalapati, Goutam; Banerjee, P; Mallick, Amiya; Mukherjee, Moumita

2015-01-01

This book comprises the proceedings of 1st International Conference on Computational Advancement in Communication Circuits and Systems (ICCACCS 2014) organized by Narula Institute of Technology under the patronage of JIS group, affiliated to West Bengal University of Technology. The conference was supported by Technical Education Quality Improvement Program (TEQIP), New Delhi, India and had technical collaboration with IEEE Kolkata Section, along with publication partner by Springer. The book contains 62 refereed papers that aim to highlight new theoretical and experimental findings in the field of Electronics and communication engineering including interdisciplinary fields like Advanced Computing, Pattern Recognition and Analysis, Signal and Image Processing. The proceedings cover the principles, techniques and applications in microwave & devices, communication & networking, signal & image processing, and computations & mathematics & control. The proceedings reflect the conference’s emp...

A bibliometric analysis of the Journal of Advanced Nursing, 1976-2015.

Science.gov (United States)

Železnik, Danica; Blažun Vošner, Helena; Kokol, Peter

2017-10-01

The aim of this study was to examine the publication characteristics and development of Journal of Advanced Nursing during its 40-year history. Bibliometric studies of single journals have been performed, but to the best of our knowledge, bibliometric analysis and bibliometric mapping have not yet been used to analyse the literature production of the Journal of Advanced Nursing. Using descriptive bibliometrics, we studied the dynamics and trend patterns of literature production and identified document types and the most prolific authors, papers, institutions and countries. Bibliometric mapping was used to visualize the content of published articles and determine the most prolific research terms and themes published in Journal of Advanced Nursing and their evolution through time. We were also interested in determining whether there were any 'Sleeping Beauties' among the articles published in the journal. The study revealed a positive trend in literature production, although recently, the number of articles published in Journal of Advanced Nursing has slightly decreased. The most productive institutions are from the United Kingdom, which ranks in the highest place in terms of successful publishing in the journal. Thematic analysis showed that the most prolific themes corresponded to the basic aims and scope of the journal. Journal of Advanced Nursing contributes to advances in nursing research, practice and education as well as the quality of health care, teamwork and family care, with an emphasis on knowledge transfer and partnership between various healthcare professionals. © 2017 John Wiley & Sons Ltd.

Unveiling Hidden Dynamics of Hippo Signalling: A Systems Analysis

Directory of Open Access Journals (Sweden)

Sung-Young Shin

2016-08-01

Full Text Available The Hippo signalling pathway has recently emerged as an important regulator of cell apoptosis and proliferation with significant implications in human diseases. In mammals, the pathway contains the core kinases MST1/2, which phosphorylate and activate LATS1/2 kinases. The pro-apoptotic function of the MST/LATS signalling axis was previously linked to the Akt and ERK MAPK pathways, demonstrating that the Hippo pathway does not act alone but crosstalks with other signalling pathways to coordinate network dynamics and cellular outcomes. These crosstalks were characterised by a multitude of complex regulatory mechanisms involving competitive protein-protein interactions and phosphorylation mediated feedback loops. However, how these different mechanisms interplay in different cellular contexts to drive the context-specific network dynamics of Hippo-ERK signalling remains elusive. Using mathematical modelling and computational analysis, we uncovered that the Hippo-ERK network can generate highly diverse dynamical profiles that can be clustered into distinct dose-response patterns. For each pattern, we offered mechanistic explanation that defines when and how the observed phenomenon can arise. We demonstrated that Akt displays opposing, dose-dependent functions towards ERK, which are mediated by the balance between the Raf-1/MST2 protein interaction module and the LATS1 mediated feedback regulation. Moreover, Ras displays a multi-functional role and drives biphasic responses of both MST2 and ERK activities; which are critically governed by the competitive protein interaction between MST2 and Raf-1. Our study represents the first in-depth and systematic analysis of the Hippo-ERK network dynamics and provides a concrete foundation for future studies.

Sensitivity analysis of intracellular signaling pathway kinetics predicts targets for stem cell fate control.

Directory of Open Access Journals (Sweden)

Alborz Mahdavi

2007-07-01

Full Text Available Directing stem cell fate requires knowledge of how signaling networks integrate temporally and spatially segregated stimuli. We developed and validated a computational model of signal transducer and activator of transcription-3 (Stat3 pathway kinetics, a signaling network involved in embryonic stem cell (ESC self-renewal. Our analysis identified novel pathway responses; for example, overexpression of the receptor glycoprotein-130 results in reduced pathway activation and increased ESC differentiation. We used a systematic in silico screen to identify novel targets and protein interactions involved in Stat3 activation. Our analysis demonstrates that signaling activation and desensitization (the inability to respond to ligand restimulation is regulated by balancing the activation state of a distributed set of parameters including nuclear export of Stat3, nuclear phosphatase activity, inhibition by suppressor of cytokine signaling, and receptor trafficking. This knowledge was used to devise a temporally modulated ligand delivery strategy that maximizes signaling activation and leads to enhanced ESC self-renewal.

Generalized sample entropy analysis for traffic signals based on similarity measure

Science.gov (United States)

Shang, Du; Xu, Mengjia; Shang, Pengjian

2017-05-01

Sample entropy is a prevailing method used to quantify the complexity of a time series. In this paper a modified method of generalized sample entropy and surrogate data analysis is proposed as a new measure to assess the complexity of a complex dynamical system such as traffic signals. The method based on similarity distance presents a different way of signals patterns match showing distinct behaviors of complexity. Simulations are conducted over synthetic data and traffic signals for providing the comparative study, which is provided to show the power of the new method. Compared with previous sample entropy and surrogate data analysis, the new method has two main advantages. The first one is that it overcomes the limitation about the relationship between the dimension parameter and the length of series. The second one is that the modified sample entropy functions can be used to quantitatively distinguish time series from different complex systems by the similar measure.

Constant versus variable response signal delays in speed--accuracy trade-offs: effects of advance preparation for processing time.

Science.gov (United States)

Miller, Jeff; Sproesser, Gudrun; Ulrich, Rolf

2008-07-01

In two experiments, we used response signals (RSs) to control processing time and trace out speed--accuracy trade-off(SAT) functions in a difficult perceptual discrimination task. Each experiment compared performance in blocks of trials with constant and, hence, temporally predictable RS lags against performance in blocks with variable, unpredictable RS lags. In both experiments, essentially equivalent SAT functions were observed with constant and variable RS lags. We conclude that there is little effect of advance preparation for a given processing time, suggesting that the discrimination mechanisms underlying SAT functions are driven solely by bottom-up information processing in perceptual discrimination tasks.

Non-destructive testing of full-length bonded rock bolts based on HHT signal analysis

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Shi, Z. M.; Liu, L.; Peng, M.; Liu, C. C.; Tao, F. J.; Liu, C. S.

2018-04-01

Full-length bonded rock bolts are commonly used in mining, tunneling and slope engineering because of their simple design and resistance to corrosion. However, the length of a rock bolt and grouting quality do not often meet the required design standards in practice because of the concealment and complexity of bolt construction. Non-destructive testing is preferred when testing a rock bolt's quality because of the convenience, low cost and wide detection range. In this paper, a signal analysis method for the non-destructive sound wave testing of full-length bonded rock bolts is presented, which is based on the Hilbert-Huang transform (HHT). First, we introduce the HHT analysis method to calculate the bolt length and identify defect locations based on sound wave reflection test signals, which includes decomposing the test signal via empirical mode decomposition (EMD), selecting the intrinsic mode functions (IMF) using the Pearson Correlation Index (PCI) and calculating the instantaneous phase and frequency via the Hilbert transform (HT). Second, six model tests are conducted using different grouting defects and bolt protruding lengths to verify the effectiveness of the HHT analysis method. Lastly, the influence of the bolt protruding length on the test signal, identification of multiple reflections from defects, bolt end and protruding end, and mode mixing from EMD are discussed. The HHT analysis method can identify the bolt length and grouting defect locations from signals that contain noise at multiple reflected interfaces. The reflection from the long protruding end creates an irregular test signal with many frequency peaks on the spectrum. The reflections from defects barely change the original signal because they are low energy, which cannot be adequately resolved using existing methods. The HHT analysis method can identify reflections from the long protruding end of the bolt and multiple reflections from grouting defects based on mutations in the instantaneous

Implementation of advanced finite element technology in structural analysis computer codes

International Nuclear Information System (INIS)

Kohli, T.D.; Wiley, J.W.; Koss, P.W.

1975-01-01

Advances in finite element technology over the last several years have been rapid and have largely outstripped the ability of general purpose programs in the public domain to assimilate them. As a result, it has become the burden of the structural analyst to incorporate these advances himself. This paper discusses the implementation and extension of specific technological advances in Bechtel structural analysis programs. In general these advances belong in two categories: (1) the finite elements themselves and (2) equation solution algorithms. Improvements in the finite elements involve increased accuracy of the elements and extension of their applicability to various specialized modelling situations. Improvements in solution algorithms have been almost exclusively aimed at expanding problem solving capacity. (Auth.)

Targeting Wnt signaling in colorectal cancer. A Review in the Theme: Cell Signaling: Proteins, Pathways and Mechanisms

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Novellasdemunt, Laura; Antas, Pedro

2015-01-01

The evolutionarily conserved Wnt signaling pathway plays essential roles during embryonic development and tissue homeostasis. Notably, comprehensive genetic studies in Drosophila and mice in the past decades have demonstrated the crucial role of Wnt signaling in intestinal stem cell maintenance by regulating proliferation, differentiation, and cell-fate decisions. Wnt signaling has also been implicated in a variety of cancers and other diseases. Loss of the Wnt pathway negative regulator adenomatous polyposis coli (APC) is the hallmark of human colorectal cancers (CRC). Recent advances in high-throughput sequencing further reveal many novel recurrent Wnt pathway mutations in addition to the well-characterized APC and β-catenin mutations in CRC. Despite attractive strategies to develop drugs for Wnt signaling, major hurdles in therapeutic intervention of the pathway persist. Here we discuss the Wnt-activating mechanisms in CRC and review the current advances and challenges in drug discovery. PMID:26289750

Continuous EEG signal analysis for asynchronous BCI application.

Science.gov (United States)

Hsu, Wei-Yen

2011-08-01

In this study, we propose a two-stage recognition system for continuous analysis of electroencephalogram (EEG) signals. An independent component analysis (ICA) and correlation coefficient are used to automatically eliminate the electrooculography (EOG) artifacts. Based on the continuous wavelet transform (CWT) and Student's two-sample t-statistics, active segment selection then detects the location of active segment in the time-frequency domain. Next, multiresolution fractal feature vectors (MFFVs) are extracted with the proposed modified fractal dimension from wavelet data. Finally, the support vector machine (SVM) is adopted for the robust classification of MFFVs. The EEG signals are continuously analyzed in 1-s segments, and every 0.5 second moves forward to simulate asynchronous BCI works in the two-stage recognition architecture. The segment is first recognized as lifted or not in the first stage, and then is classified as left or right finger lifting at stage two if the segment is recognized as lifting in the first stage. Several statistical analyses are used to evaluate the performance of the proposed system. The results indicate that it is a promising system in the applications of asynchronous BCI work.

Signal processing for smart cards

Science.gov (United States)

Quisquater, Jean-Jacques; Samyde, David

2003-06-01

In 1998, Paul Kocher showed that when a smart card computes cryptographic algorithms, for signatures or encryption, its consumption or its radiations leak information. The keys or the secrets hidden in the card can then be recovered using a differential measurement based on the intercorrelation function. A lot of silicon manufacturers use desynchronization countermeasures to defeat power analysis. In this article we detail a new resynchronization technic. This method can be used to facilitate the use of a neural network to do the code recognition. It becomes possible to reverse engineer a software code automatically. Using data and clock separation methods, we show how to optimize the synchronization using signal processing. Then we compare these methods with watermarking methods for 1D and 2D signal. The very last watermarking detection improvements can be applied to signal processing for smart cards with very few modifications. Bayesian processing is one of the best ways to do Differential Power Analysis, and it is possible to extract a PIN code from a smart card in very few samples. So this article shows the need to continue to set up effective countermeasures for cryptographic processors. Although the idea to use advanced signal processing operators has been commonly known for a long time, no publication explains that results can be obtained. The main idea of differential measurement is to use the cross-correlation of two random variables and to repeat consumption measurements on the processor to be analyzed. We use two processors clocked at the same external frequency and computing the same data. The applications of our design are numerous. Two measurements provide the inputs of a central operator. With the most accurate operator we can improve the signal noise ratio, re-synchronize the acquisition clock with the internal one, or remove jitter. The analysis based on consumption or electromagnetic measurements can be improved using our structure. At first sight

Novel advances in shotgun lipidomics for biology and medicine.

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Wang, Miao; Wang, Chunyan; Han, Rowland H; Han, Xianlin

2016-01-01

The field of lipidomics, as coined in 2003, has made profound advances and been rapidly expanded. The mass spectrometry-based strategies of this analytical methodology-oriented research discipline for lipid analysis are largely fallen into three categories: direct infusion-based shotgun lipidomics, liquid chromatography-mass spectrometry-based platforms, and matrix-assisted laser desorption/ionization mass spectrometry-based approaches (particularly in imagining lipid distribution in tissues or cells). This review focuses on shotgun lipidomics. After briefly introducing its fundamentals, the major materials of this article cover its recent advances. These include the novel methods of lipid extraction, novel shotgun lipidomics strategies for identification and quantification of previously hardly accessible lipid classes and molecular species including isomers, and novel tools for processing and interpretation of lipidomics data. Representative applications of advanced shotgun lipidomics for biological and biomedical research are also presented in this review. We believe that with these novel advances in shotgun lipidomics, this approach for lipid analysis should become more comprehensive and high throughput, thereby greatly accelerating the lipidomics field to substantiate the aberrant lipid metabolism, signaling, trafficking, and homeostasis under pathological conditions and their underpinning biochemical mechanisms. Copyright © 2015 Elsevier B.V. All rights reserved.

Condition Monitoring Through Advanced Sensor and Computational Technology

International Nuclear Information System (INIS)

Kim, Jung Taek; Park, Won Man; Kim, Jung Soo; Seong, Soeng Hwan; Hur, Sub; Cho, Jae Hwan; Jung, Hyung Gue

2005-05-01

The overall goal of this joint research project was to develop and demonstrate advanced sensors and computational technology for continuous monitoring of the condition of components, structures, and systems in advanced and next-generation nuclear power plants (NPPs). This project included investigating and adapting several advanced sensor technologies from Korean and US national laboratory research communities, some of which were developed and applied in non-nuclear industries. The project team investigated and developed sophisticated signal processing, noise reduction, and pattern recognition techniques and algorithms. The researchers installed sensors and conducted condition monitoring tests on two test loops, a check valve (an active component) and a piping elbow (a passive component), to demonstrate the feasibility of using advanced sensors and computational technology to achieve the project goal. Acoustic emission (AE) devices, optical fiber sensors, accelerometers, and ultrasonic transducers (UTs) were used to detect mechanical vibratory response of check valve and piping elbow in normal and degraded configurations. Chemical sensors were also installed to monitor the water chemistry in the piping elbow test loop. Analysis results of processed sensor data indicate that it is feasible to differentiate between the normal and degraded (with selected degradation mechanisms) configurations of these two components from the acquired sensor signals, but it is questionable that these methods can reliably identify the level and type of degradation. Additional research and development efforts are needed to refine the differentiation techniques and to reduce the level of uncertainties

Analysis Spectrum of ECG Signal and QRS Detection during Running on Treadmill

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Agung Suhendra, M.; Ilham R., M.; Simbolon, Artha I.; Faizal A., M.; Munandar, A.

2018-03-01

The heart is an important organ in our metabolism in which it controls circulatory and oxygen. The heart exercise is needed one of them using the treadmill to prevent health. To analysis, it using electrocardiograph (ECG) to investigating and diagnosing anomalies of the heart. In this paper, we would like to analysis ECG signals during running on the treadmill with kinds of speeds. There are two analysis ECG signals i.e. QRS detection and power spectrum density (PSD). The result of PSD showed that subject 3 has highly for all subject and the result of QRS detection using pan Tomkins algorithm that a percentage of failed detection is an approaching to 0 % for all subject.

Methods for the Analysis of Protein Phosphorylation-Mediated Cellular Signaling Networks

Science.gov (United States)

White, Forest M.; Wolf-Yadlin, Alejandro

2016-06-01

Protein phosphorylation-mediated cellular signaling networks regulate almost all aspects of cell biology, including the responses to cellular stimulation and environmental alterations. These networks are highly complex and comprise hundreds of proteins and potentially thousands of phosphorylation sites. Multiple analytical methods have been developed over the past several decades to identify proteins and protein phosphorylation sites regulating cellular signaling, and to quantify the dynamic response of these sites to different cellular stimulation. Here we provide an overview of these methods, including the fundamental principles governing each method, their relative strengths and weaknesses, and some examples of how each method has been applied to the analysis of complex signaling networks. When applied correctly, each of these techniques can provide insight into the topology, dynamics, and regulation of protein phosphorylation signaling networks.

Application of a structural model for advanced analysis in the evaluation of nuclear safety

International Nuclear Information System (INIS)

Landesmann, Alexandre; Barros, Francisco Claudio Pereira de; Batista, Eduardo de Miranda

2003-01-01

The Advanced Analysis concept, which means the direct consideration of both physical and geometric nonlinear effects in the analysis and design of steel buildings structures, represents the state-of-art in the field of structural analysis by this beginning of the 21 st century. In this context, the present paper presents an Advanced Analysis methodology applied to the Safety Evaluation of high hazardous civil structures. This Safety Evaluation plays an important part in the regulators position as a step in the licensing process performed by CNEN - Brazilian Nuclear Energy Commission. The proposed Advance Analysis procedure is implemented by a refined second-order plastic hinge model. The application of this model allows to carry out: the description of the inelastic structural behavior; the identification of the collapse mechanism; the ultimate load level; structural safety's level and the service ability limit. (author)

Signalling crosstalk in plants: emerging issues.

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Taylor, Jane E; McAinsh, Martin R

2004-01-01

The Oxford English Dictionary defines crosstalk as 'unwanted transfer of signals between communication channels'. How does this definition relate to the way in which we view the organization and function of signalling pathways? Recent advances in the field of plant signalling have challenged the traditional view of a signalling transduction cascade as isolated linear pathways. Instead the picture emerging of the mechanisms by which plants transduce environmental signals is of the interaction between transduction chains. The manner in which these interactions occur (and indeed whether the transfer of these signals is 'unwanted' or beneficial) is currently the topic of intense research.

Dynamic strain analysis of structures employing digital signal processing, storage and display

Energy Technology Data Exchange (ETDEWEB)

Patwardhan, P K; Misra, V M; Kumar, Surendra

1975-01-01

A multi-channel digital technique has been adopted for analysing wave patterns of stresses and strains in structures, particularly under dynamic conditions. This technique provides adequate signal to noise discrimination and high sensitivity for very small (few milli-volts) and slow varying signals (few Hz to 100 Hz.), and A-D conversion accompined by live display during the course of data gathering and computer compatible output. This system also provides fast response because of inherent 50 MHz digitising speed and a large dynamic range of 1024 discrete signal steps. The signals can be suitably fed to the A-D converter (50 MHz) or can be analysed employing frequency modulation techniques and time mode operation of the analyser. The data can be gathered in the field on cassette tapes and replayed in the laboratory for detailed analysis. This technique would provide a versatile system for dynamic analysis of structures under varying conditions. e.g. structures in nuclear power systems, such as testing of end fittings, calandria, vibration testing and measurements exploying pressure transducers.

Dynamic strain analysis of structures employing digital signal processing, storage and display

International Nuclear Information System (INIS)

Patwardhan, P.K.; Misra, V.M.; Kumar, Surendra

1975-01-01

A multi-channel digital technique has been adopted for analysing wave patterns of stresses and strains in structures, particularly under dynamic conditions. This technique provides adequate signal to noise discrimination and high sensitivity for very small (few milli-volts) and slow varying signals (few Hz to 100 Hz.), A-D conversion accompined by live display during the course of data gathering and computer compatible output. This system also provides fast response because of inherent 50 MHz digitising speed and a large dynamic range of 1024 discrete signal steps. The signals can be suitably fed to the A-D converter (50 MHz) or can be analysed employing frequency modulation techniques and time mode operation of the analyser. The data can be gathered in the field on cassette tapes and replayed in the laboratory for detailed analysis. This technique would provide a versatile system for dynamic analysis of structures under varying conditions. e.g. structures in nuclear power systems, such as testing of end fittings, calandria, vibration testing and measurements exploying pressure transducers. (author)

Biomedical signal and image processing.

Science.gov (United States)

Cerutti, Sergio; Baselli, Giuseppe; Bianchi, Anna; Caiani, Enrico; Contini, Davide; Cubeddu, Rinaldo; Dercole, Fabio; Rienzo, Luca; Liberati, Diego; Mainardi, Luca; Ravazzani, Paolo; Rinaldi, Sergio; Signorini, Maria; Torricelli, Alessandro

2011-01-01

Generally, physiological modeling and biomedical signal processing constitute two important paradigms of biomedical engineering (BME): their fundamental concepts are taught starting from undergraduate studies and are more completely dealt with in the last years of graduate curricula, as well as in Ph.D. courses. Traditionally, these two cultural aspects were separated, with the first one more oriented to physiological issues and how to model them and the second one more dedicated to the development of processing tools or algorithms to enhance useful information from clinical data. A practical consequence was that those who did models did not do signal processing and vice versa. However, in recent years,the need for closer integration between signal processing and modeling of the relevant biological systems emerged very clearly [1], [2]. This is not only true for training purposes(i.e., to properly prepare the new professional members of BME) but also for the development of newly conceived research projects in which the integration between biomedical signal and image processing (BSIP) and modeling plays a crucial role. Just to give simple examples, topics such as brain–computer machine or interfaces,neuroengineering, nonlinear dynamical analysis of the cardiovascular (CV) system,integration of sensory-motor characteristics aimed at the building of advanced prostheses and rehabilitation tools, and wearable devices for vital sign monitoring and others do require an intelligent fusion of modeling and signal processing competences that are certainly peculiar of our discipline of BME.

Broadband analysis of landslides seismic signal : example of the Oso-Steelhead landslide and other recent events

Science.gov (United States)

Hibert, C.; Stark, C. P.; Ekstrom, G.

2014-12-01

Landslide failures on the scale of mountains are spectacular, dangerous, and spontaneous, making direct observations hard to obtain. Measurement of their dynamic properties during runout is a high research priority, but a logistical and technical challenge. Seismology has begun to help in several important ways. Taking advantage of broadband seismic stations, recent advances now allow: (i) the seismic detection and location of large landslides in near-real-time, even for events in very remote areas that may have remain undetected, such as the 2014 Mt La Perouse supraglacial failure in Alaska; (ii) inversion of long-period waves generated by large landslides to yield an estimate of the forces imparted by the bulk accelerating mass; (iii) inference of the landslide mass, its center-of-mass velocity over time, and its trajectory.Key questions persist, such as: What can the short-period seismic data tell us about the high-frequency impacts taking place within the granular flow and along its boundaries with the underlying bedrock? And how does this seismicity relate to the bulk acceleration of the landslide and the long-period seismicity generated by it?Our recent work on the joint analysis of short- and long-period seismic signals generated by past and recent events, such as the Bingham Canyon Mine and the Oso-Steelhead landslides, provides new insights to tackle these issues. Qualitative comparison between short-period signal features and kinematic parameters inferred from long-period surface wave inversion helps to refine interpretation of the source dynamics and to understand the different mechanisms for the origin of the short-period wave radiation. Our new results also suggest that quantitative relationships can be derived from this joint analysis, in particular between the short-period seismic signal envelope and the inferred momentum of the center-of-mass. In the future, these quantitative relationships may help to constrain and calibrate parameters used in

Improved Protein Arrays for Quantitative Systems Analysis of the Dynamics of Signaling Pathway Interactions

Energy Technology Data Exchange (ETDEWEB)

Yang, Chin-Rang [National Inst. of Health (NIH), Bethesda, MD (United States). National Heart, Lung and Blood Inst.

2013-12-11

Astronauts and workers in nuclear plants who repeatedly exposed to low doses of ionizing radiation (IR, <10 cGy) are likely to incur specific changes in signal transduction and gene expression in various tissues of their body. Remarkable advances in high throughput genomics and proteomics technologies enable researchers to broaden their focus from examining single gene/protein kinetics to better understanding global gene/protein expression profiling and biological pathway analyses, namely Systems Biology. An ultimate goal of systems biology is to develop dynamic mathematical models of interacting biological systems capable of simulating living systems in a computer. This Glue Grant is to complement Dr. Boothman’s existing DOE grant (No. DE-FG02-06ER64186) entitled “The IGF1/IGF-1R-MAPK-Secretory Clusterin (sCLU) Pathway: Mediator of a Low Dose IR-Inducible Bystander Effect” to develop sensitive and quantitative proteomic technology that suitable for low dose radiobiology researches. An improved version of quantitative protein array platform utilizing linear Quantum dot signaling for systematically measuring protein levels and phosphorylation states for systems biology modeling is presented. The signals are amplified by a confocal laser Quantum dot scanner resulting in ~1000-fold more sensitivity than traditional Western blots and show the good linearity that is impossible for the signals of HRP-amplification. Therefore this improved protein array technology is suitable to detect weak responses of low dose radiation. Software is developed to facilitate the quantitative readout of signaling network activities. Kinetics of EGFRvIII mutant signaling was analyzed to quantify cross-talks between EGFR and other signaling pathways.

A novel SNP analysis method to detect copy number alterations with an unbiased reference signal directly from tumor samples

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LaFramboise William A

2011-01-01

Full Text Available Abstract Background Genomic instability in cancer leads to abnormal genome copy number alterations (CNA as a mechanism underlying tumorigenesis. Using microarrays and other technologies, tumor CNA are detected by comparing tumor sample CN to normal reference sample CN. While advances in microarray technology have improved detection of copy number alterations, the increase in the number of measured signals, noise from array probes, variations in signal-to-noise ratio across batches and disparity across laboratories leads to significant limitations for the accurate identification of CNA regions when comparing tumor and normal samples. Methods To address these limitations, we designed a novel "Virtual Normal" algorithm (VN, which allowed for construction of an unbiased reference signal directly from test samples within an experiment using any publicly available normal reference set as a baseline thus eliminating the need for an in-lab normal reference set. Results The algorithm was tested using an optimal, paired tumor/normal data set as well as previously uncharacterized pediatric malignant gliomas for which a normal reference set was not available. Using Affymetrix 250K Sty microarrays, we demonstrated improved signal-to-noise ratio and detected significant copy number alterations using the VN algorithm that were validated by independent PCR analysis of the target CNA regions. Conclusions We developed and validated an algorithm to provide a virtual normal reference signal directly from tumor samples and minimize noise in the derivation of the raw CN signal. The algorithm reduces the variability of assays performed across different reagent and array batches, methods of sample preservation, multiple personnel, and among different laboratories. This approach may be valuable when matched normal samples are unavailable or the paired normal specimens have been subjected to variations in methods of preservation.

Advanced exergy analysis for a bottoming organic rankine cycle coupled to an internal combustion engine

International Nuclear Information System (INIS)

Galindo, J.; Ruiz, S.; Dolz, V.; Royo-Pascual, L.

2016-01-01

Highlights: • Advanced exergy analysis were carried out using experimental data of an ORC. • Exergy destruction analyzed as endogenous/exogenous and unavoidable/avoidable. • Exergy destruction was estimated by considering technological restrictions. - Abstract: This paper deals with the evaluation and analysis of a bottoming ORC cycle coupled to an IC engine by means of conventional and advanced exergy analysis. Using experimental data of an ORC coupled to a 2 l turbocharged engine, both conventional and advanced exergy analysis are carried out. Splitting the exergy in the advanced exergy analysis into unavoidable and avoidable provides a measure of the potential of improving the efficiency of this component. On the other hand, splitting the exergy into endogenous and exogenous provides information between interactions among system components. The result of this study shows that there is a high potential of improvement in this type of cycles. Although, from the conventional analysis, the exergy destruction rate of boiler is greater than the one of the expander, condenser and pump, the advanced exergy analysis suggests that the first priority of improvement should be given to the expander, followed by the pump, the condenser and the boiler. A total amount of 3.75 kW (36.5%) of exergy destruction rate could be lowered, taking account that only the avoidable part of the exergy destruction rate can be reduced.

Design and prototyping of a wristband-type wireless photoplethysmographic device for heart rate variability signal analysis.

Science.gov (United States)

Ghamari, M; Soltanpur, C; Cabrera, S; Romero, R; Martinek, R; Nazeran, H

2016-08-01

Heart Rate Variability (HRV) signal analysis provides a quantitative marker of the Autonomic Nervous System (ANS) function. A wristband-type wireless photoplethysmographic (PPG) device was custom-designed to collect and analyze the arterial pulse in the wrist. The proposed device is comprised of an optical sensor to monitor arterial pulse, a signal conditioning unit to filter and amplify the analog PPG signal, a microcontroller to digitize the analog PPG signal, and a Bluetooth module to transfer the data to a smart device. This paper proposes a novel model to represent the PPG signal as the summation of two Gaussian functions. The paper concludes with a verification procedure for HRV signal analysis during sedentary activities.

SVM-Based Spectral Analysis for Heart Rate from Multi-Channel WPPG Sensor Signals

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Jiping Xiong

2017-03-01

Full Text Available Although wrist-type photoplethysmographic (hereafter referred to as WPPG sensor signals can measure heart rate quite conveniently, the subjects’ hand movements can cause strong motion artifacts, and then the motion artifacts will heavily contaminate WPPG signals. Hence, it is challenging for us to accurately estimate heart rate from WPPG signals during intense physical activities. The WWPG method has attracted more attention thanks to the popularity of wrist-worn wearable devices. In this paper, a mixed approach called Mix-SVM is proposed, it can use multi-channel WPPG sensor signals and simultaneous acceleration signals to measurement heart rate. Firstly, we combine the principle component analysis and adaptive filter to remove a part of the motion artifacts. Due to the strong relativity between motion artifacts and acceleration signals, the further denoising problem is regarded as a sparse signals reconstruction problem. Then, we use a spectrum subtraction method to eliminate motion artifacts effectively. Finally, the spectral peak corresponding to heart rate is sought by an SVM-based spectral analysis method. Through the public PPG database in the 2015 IEEE Signal Processing Cup, we acquire the experimental results, i.e., the average absolute error was 1.01 beat per minute, and the Pearson correlation was 0.9972. These results also confirm that the proposed Mix-SVM approach has potential for multi-channel WPPG-based heart rate estimation in the presence of intense physical exercise.

Cash Advance Accounting: Accounting Regulations and Practices

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Aristita Rotila

2012-12-01

Full Text Available It is known the fact that often the entities offer to staff or third parties certain amounts of money, in order to make payments for the entities, such sums being registered differently in the accounting as cash advances. In the case in which the advances are offered in a foreign currency, there is the problem of the exchange rate used when justifying the advance, for the conversion in lei of payments that were carried out. In this article we wanted to signal the effect that the exchange rate, used in the assessment for reflecting in the accounting operations concerning cash advance reimbursements in a foreign currency, has on the information presented in the financial statement. Therewith, we signal some aspects from the content of the accounting regulations, with reference at defining the cash advances, meaning, and the presentation in the balance sheet of cash advances, which, in our opinion, impose clarifications.

EMD-Based Symbolic Dynamic Analysis for the Recognition of Human and Nonhuman Pyroelectric Infrared Signals

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Jiaduo Zhao

2016-01-01

Full Text Available In this paper, we propose an effective human and nonhuman pyroelectric infrared (PIR signal recognition method to reduce PIR detector false alarms. First, using the mathematical model of the PIR detector, we analyze the physical characteristics of the human and nonhuman PIR signals; second, based on the analysis results, we propose an empirical mode decomposition (EMD-based symbolic dynamic analysis method for the recognition of human and nonhuman PIR signals. In the proposed method, first, we extract the detailed features of a PIR signal into five symbol sequences using an EMD-based symbolization method, then, we generate five feature descriptors for each PIR signal through constructing five probabilistic finite state automata with the symbol sequences. Finally, we use a weighted voting classification strategy to classify the PIR signals with their feature descriptors. Comparative experiments show that the proposed method can effectively classify the human and nonhuman PIR signals and reduce PIR detector’s false alarms.

EMD-Based Symbolic Dynamic Analysis for the Recognition of Human and Nonhuman Pyroelectric Infrared Signals.

Science.gov (United States)

Zhao, Jiaduo; Gong, Weiguo; Tang, Yuzhen; Li, Weihong

2016-01-20

In this paper, we propose an effective human and nonhuman pyroelectric infrared (PIR) signal recognition method to reduce PIR detector false alarms. First, using the mathematical model of the PIR detector, we analyze the physical characteristics of the human and nonhuman PIR signals; second, based on the analysis results, we propose an empirical mode decomposition (EMD)-based symbolic dynamic analysis method for the recognition of human and nonhuman PIR signals. In the proposed method, first, we extract the detailed features of a PIR signal into five symbol sequences using an EMD-based symbolization method, then, we generate five feature descriptors for each PIR signal through constructing five probabilistic finite state automata with the symbol sequences. Finally, we use a weighted voting classification strategy to classify the PIR signals with their feature descriptors. Comparative experiments show that the proposed method can effectively classify the human and nonhuman PIR signals and reduce PIR detector's false alarms.

Investigation of mental fatigue through EEG signal processing based on nonlinear analysis: Symbolic dynamics

International Nuclear Information System (INIS)

Azarnoosh, Mahdi; Motie Nasrabadi, Ali; Mohammadi, Mohammad Reza; Firoozabadi, Mohammad

2011-01-01

Highlights: Mental fatigue indices’ variation discussed during simple long-term attentive task. Symbolic dynamics of reaction time and EEG signal determine mental state variation. Nonlinear quantifiers such as entropy can display chaotic behaviors of the brain. Frontal and central lobes of the brain are effective in attention investigations. Mental fatigue causes a reduction in the complexity of the brain’s activity. Abstract: To investigate nonlinear analysis of attention physiological indices this study used a simple repetitive attentive task in four consecutive trials that resulted in mental fatigue. Traditional performance indices, such as reaction time, error responses, and EEG signals, were simultaneously recorded to evaluate differences between the trials. Performance indices analysis demonstrated that a selected task leads to mental fatigue. In addition, the study aimed to find a method to determine mental fatigue based on nonlinear analysis of EEG signals. Symbolic dynamics was selected as a qualitative method used to extract some quantitative qualifiers such as entropy. This method was executed on the reaction time of responses, and EEG signals to distinguish mental states. The results revealed that nonlinear analysis of reaction time, and EEG signals of the frontal and central lobes of the brain could differentiate between attention, and occurrence of mental fatigue in trials. In addition, the trend of entropy variation displayed a reduction in the complexity of mental activity as fatigue occurred.

Meta-analysis of melanin-concentrating hormone signaling-deficient mice on behavioral and metabolic phenotypes.

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Kenkichi Takase

Full Text Available The demand for meta-analyses in basic biomedical research has been increasing because the phenotyping of genetically modified mice does not always produce consistent results. Melanin-concentrating hormone (MCH has been reported to be involved in a variety of behaviors that include feeding, body-weight regulation, anxiety, sleep, and reward behavior. However, the reported behavioral and metabolic characteristics of MCH signaling-deficient mice, such as MCH-deficient mice and MCH receptor 1 (MCHR1-deficient mice, are not consistent with each other. In the present study, we performed a meta-analysis of the published data related to MCH-deficient and MCHR1-deficient mice to obtain robust conclusions about the role of MCH signaling. Overall, the meta-analysis revealed that the deletion of MCH signaling enhanced wakefulness, locomotor activity, aggression, and male sexual behavior and that MCH signaling deficiency suppressed non-REM sleep, anxiety, responses to novelty, startle responses, and conditioned place preferences. In contrast to the acute orexigenic effect of MCH, MCH signaling deficiency significantly increased food intake. Overall, the meta-analysis also revealed that the deletion of MCH signaling suppressed the body weight, fat mass, and plasma leptin, while MCH signaling deficiency increased the body temperature, oxygen consumption, heart rate, and mean arterial pressure. The lean phenotype of the MCH signaling-deficient mice was also confirmed in separate meta-analyses that were specific to sex and background strain (i.e., C57BL/6 and 129Sv. MCH signaling deficiency caused a weak anxiolytic effect as assessed with the elevated plus maze and the open field test but also caused a weak anxiogenic effect as assessed with the emergence test. MCH signaling-deficient mice also exhibited increased plasma corticosterone under non-stressed conditions, which suggests enhanced activity of the hypothalamic-pituitary-adrenal axis. To the best of our

Advanced concepts, analysis approaches and criteria for nuclear piping system design

International Nuclear Information System (INIS)

Tang, H.T.; Tagart, S.W. Jr.; Tang, Y.K.

1992-01-01

Recent research in piping system design and analysis has resulted in advancements on damping values, independent support motion (ISM), static coefficient method, simplified inelastic method and ASME code criteria changes. In the support area, passive type of supports such as energy-absorbing device and gap stopper have been developed. These advancements provide bases for improved and cost-effective design of future nuclear piping systems. (author)

Recent Advances in Multidisciplinary Analysis and Optimization, part 3

Science.gov (United States)

Barthelemy, Jean-Francois M. (Editor)

1989-01-01

This three-part document contains a collection of technical papers presented at the Second NASA/Air Force Symposium on Recent Advances in Multidisciplinary Analysis and Optimization, held September 28-30, 1988 in Hampton, Virginia. The topics covered include: aircraft design, aeroelastic tailoring, control of aeroelastic structures, dynamics and control of flexible structures, structural design, design of large engineering systems, application of artificial intelligence, shape optimization, software development and implementation, and sensitivity analysis.

High-Selectivity Filter Banks for Spectral Analysis of Music Signals

Directory of Open Access Journals (Sweden)

Luiz W. P. Biscainho

2007-01-01

Full Text Available This paper approaches, under a unified framework, several algorithms for the spectral analysis of musical signals. Such algorithms include the fast Fourier transform (FFT, the fast filter bank (FFB, the constant-Q transform (CQT, and the bounded-Q transform (BQT, previously known from the associated literature. Two new methods are then introduced, namely, the constant-Q fast filter bank (CQFFB and the bounded-Q fast filter bank (BQFFB, combining the positive characteristics of the previously mentioned algorithms. The provided analyses indicate that the proposed BQFFB achieves an excellent compromise between the reduced computational effort of the FFT, the high selectivity of each output channel of the FFB, and the efficient distribution of frequency channels associated to the CQT and BQT methods. Examples are included to illustrate the performances of these methods in the spectral analysis of music signals.

Advanced Seismic Fragility Modeling using Nonlinear Soil-Structure Interaction Analysis

Energy Technology Data Exchange (ETDEWEB)

Bolisetti, Chandu [Idaho National Lab. (INL), Idaho Falls, ID (United States); Coleman, Justin [Idaho National Lab. (INL), Idaho Falls, ID (United States); Talaat, Mohamed [Simpson-Gupertz & Heger, Waltham, MA (United States); Hashimoto, Philip [Simpson-Gupertz & Heger, Waltham, MA (United States)

2015-09-01

The goal of this effort is to compare the seismic fragilities of a nuclear power plant system obtained by a traditional seismic probabilistic risk assessment (SPRA) and an advanced SPRA that utilizes Nonlinear Soil-Structure Interaction (NLSSI) analysis. Soil-structure interaction (SSI) response analysis for a traditional SPRA involves the linear analysis, which ignores geometric nonlinearities (i.e., soil and structure are glued together and the soil material undergoes tension when the structure uplifts). The NLSSI analysis will consider geometric nonlinearities.

The DECMU: a digital device for delayed analysis of multi-frequency eddy current signals

International Nuclear Information System (INIS)

Pigeon, Michel.

1981-08-01

A delayed data analysis system has been realized by the CEA and Intercontrole for in-service inspection of steam generators of nuclear plants by multifrequency eddy current testing. This device allows, out of the plant, adjustment during switching of the probes, graph recording and analysis for defect signal qualification. The equipment contains an analog mixing device, as IC3FA multi-frequency appartus, but has in addition a memory allowing data cycling and signal isolation for adjustment or analysis [fr

IQM: an extensible and portable open source application for image and signal analysis in Java.

Science.gov (United States)

Kainz, Philipp; Mayrhofer-Reinhartshuber, Michael; Ahammer, Helmut

2015-01-01

Image and signal analysis applications are substantial in scientific research. Both open source and commercial packages provide a wide range of functions for image and signal analysis, which are sometimes supported very well by the communities in the corresponding fields. Commercial software packages have the major drawback of being expensive and having undisclosed source code, which hampers extending the functionality if there is no plugin interface or similar option available. However, both variants cannot cover all possible use cases and sometimes custom developments are unavoidable, requiring open source applications. In this paper we describe IQM, a completely free, portable and open source (GNU GPLv3) image and signal analysis application written in pure Java. IQM does not depend on any natively installed libraries and is therefore runnable out-of-the-box. Currently, a continuously growing repertoire of 50 image and 16 signal analysis algorithms is provided. The modular functional architecture based on the three-tier model is described along the most important functionality. Extensibility is achieved using operator plugins, and the development of more complex workflows is provided by a Groovy script interface to the JVM. We demonstrate IQM's image and signal processing capabilities in a proof-of-principle analysis and provide example implementations to illustrate the plugin framework and the scripting interface. IQM integrates with the popular ImageJ image processing software and is aiming at complementing functionality rather than competing with existing open source software. Machine learning can be integrated into more complex algorithms via the WEKA software package as well, enabling the development of transparent and robust methods for image and signal analysis.

Combined analysis of cortical (EEG) and nerve stump signals improves robotic hand control.

Science.gov (United States)

Tombini, Mario; Rigosa, Jacopo; Zappasodi, Filippo; Porcaro, Camillo; Citi, Luca; Carpaneto, Jacopo; Rossini, Paolo Maria; Micera, Silvestro

2012-01-01

Interfacing an amputee's upper-extremity stump nerves to control a robotic hand requires training of the individual and algorithms to process interactions between cortical and peripheral signals. To evaluate for the first time whether EEG-driven analysis of peripheral neural signals as an amputee practices could improve the classification of motor commands. Four thin-film longitudinal intrafascicular electrodes (tf-LIFEs-4) were implanted in the median and ulnar nerves of the stump in the distal upper arm for 4 weeks. Artificial intelligence classifiers were implemented to analyze LIFE signals recorded while the participant tried to perform 3 different hand and finger movements as pictures representing these tasks were randomly presented on a screen. In the final week, the participant was trained to perform the same movements with a robotic hand prosthesis through modulation of tf-LIFE-4 signals. To improve the classification performance, an event-related desynchronization/synchronization (ERD/ERS) procedure was applied to EEG data to identify the exact timing of each motor command. Real-time control of neural (motor) output was achieved by the participant. By focusing electroneurographic (ENG) signal analysis in an EEG-driven time window, movement classification performance improved. After training, the participant regained normal modulation of background rhythms for movement preparation (α/β band desynchronization) in the sensorimotor area contralateral to the missing limb. Moreover, coherence analysis found a restored α band synchronization of Rolandic area with frontal and parietal ipsilateral regions, similar to that observed in the opposite hemisphere for movement of the intact hand. Of note, phantom limb pain (PLP) resolved for several months. Combining information from both cortical (EEG) and stump nerve (ENG) signals improved the classification performance compared with tf-LIFE signals processing alone; training led to cortical reorganization and

ALIF: A New Promising Technique for the Decomposition and Analysis of Nonlinear and Nonstationary Signals

Science.gov (United States)

Cicone, A.; Zhou, H.; Piersanti, M.; Materassi, M.; Spogli, L.

2017-12-01

Nonlinear and nonstationary signals are ubiquitous in real life. Their decomposition and analysis is of crucial importance in many research fields. Traditional techniques, like Fourier and wavelet Transform have been proved to be limited in this context. In the last two decades new kind of nonlinear methods have been developed which are able to unravel hidden features of these kinds of signals. In this poster we present a new method, called Adaptive Local Iterative Filtering (ALIF). This technique, originally developed to study mono-dimensional signals, unlike any other algorithm proposed so far, can be easily generalized to study two or higher dimensional signals. Furthermore, unlike most of the similar methods, it does not require any a priori assumption on the signal itself, so that the technique can be applied as it is to any kind of signals. Applications of ALIF algorithm to real life signals analysis will be presented. Like, for instance, the behavior of the water level near the coastline in presence of a Tsunami, length of the day signal, pressure measured at ground level on a global grid, radio power scintillation from GNSS signals,

The Advanced Modeling, Simulation and Analysis Capability Roadmap Vision for Engineering

Science.gov (United States)

Zang, Thomas; Lieber, Mike; Norton, Charles; Fucik, Karen

2006-01-01

This paper summarizes a subset of the Advanced Modeling Simulation and Analysis (AMSA) Capability Roadmap that was developed for NASA in 2005. The AMSA Capability Roadmap Team was chartered to "To identify what is needed to enhance NASA's capabilities to produce leading-edge exploration and science missions by improving engineering system development, operations, and science understanding through broad application of advanced modeling, simulation and analysis techniques." The AMSA roadmap stressed the need for integration, not just within the science, engineering and operations domains themselves, but also across these domains. Here we discuss the roadmap element pertaining to integration within the engineering domain, with a particular focus on implications for future observatory missions. The AMSA products supporting the system engineering function are mission information, bounds on information quality, and system validation guidance. The Engineering roadmap element contains 5 sub-elements: (1) Large-Scale Systems Models, (2) Anomalous Behavior Models, (3) advanced Uncertainty Models, (4) Virtual Testing Models, and (5) space-based Robotics Manufacture and Servicing Models.

Real-Time EEG Signal Enhancement Using Canonical Correlation Analysis and Gaussian Mixture Clustering

Directory of Open Access Journals (Sweden)

Chin-Teng Lin

2018-01-01

Full Text Available Electroencephalogram (EEG signals are usually contaminated with various artifacts, such as signal associated with muscle activity, eye movement, and body motion, which have a noncerebral origin. The amplitude of such artifacts is larger than that of the electrical activity of the brain, so they mask the cortical signals of interest, resulting in biased analysis and interpretation. Several blind source separation methods have been developed to remove artifacts from the EEG recordings. However, the iterative process for measuring separation within multichannel recordings is computationally intractable. Moreover, manually excluding the artifact components requires a time-consuming offline process. This work proposes a real-time artifact removal algorithm that is based on canonical correlation analysis (CCA, feature extraction, and the Gaussian mixture model (GMM to improve the quality of EEG signals. The CCA was used to decompose EEG signals into components followed by feature extraction to extract representative features and GMM to cluster these features into groups to recognize and remove artifacts. The feasibility of the proposed algorithm was demonstrated by effectively removing artifacts caused by blinks, head/body movement, and chewing from EEG recordings while preserving the temporal and spectral characteristics of the signals that are important to cognitive research.

TSLP signaling pathway map: a platform for analysis of TSLP-mediated signaling.

Science.gov (United States)

Zhong, Jun; Sharma, Jyoti; Raju, Rajesh; Palapetta, Shyam Mohan; Prasad, T S Keshava; Huang, Tai-Chung; Yoda, Akinori; Tyner, Jeffrey W; van Bodegom, Diederik; Weinstock, David M; Ziegler, Steven F; Pandey, Akhilesh

2014-01-01

Thymic stromal lymphopoietin (TSLP) is a four-helix bundle cytokine that plays a critical role in the regulation of immune responses and in the differentiation of hematopoietic cells. TSLP signals through a heterodimeric receptor complex consisting of an interleukin-7 receptor α chain and a unique TSLP receptor (TSLPR) [also known as cytokine receptor-like factor 2 (CRLF2)]. Cellular targets of TSLP include dendritic cells, B cells, mast cells, regulatory T (Treg) cells and CD4+ and CD8+ T cells. The TSLP/TSLPR axis can activate multiple signaling transduction pathways including the JAK/STAT pathway and the PI-3 kinase pathway. Aberrant TSLP/TSLPR signaling has been associated with a variety of human diseases including asthma, atopic dermatitis, nasal polyposis, inflammatory bowel disease, eosinophilic eosophagitis and, most recently, acute lymphoblastic leukemia. A centralized resource of the TSLP signaling pathway cataloging signaling events is not yet available. In this study, we present a literature-annotated resource of reactions in the TSLP signaling pathway. This pathway map is publicly available through NetPath (http://www.netpath.org/), an open access signal transduction pathway resource developed previously by our group. This map includes 236 molecules and 252 reactions that are involved in TSLP/TSLPR signaling pathway. We expect that the TSLP signaling pathway map will provide a rich resource to study the biology of this important cytokine as well as to identify novel therapeutic targets for diseases associated with dysregulated TSLP/TSLPR signaling. Database URL: http://www.netpath.org/pathways?path_id=NetPath_24.

Multi-Scale Factor Analysis of High-Dimensional Brain Signals

KAUST Repository

Ting, Chee-Ming

2017-05-18

In this paper, we develop an approach to modeling high-dimensional networks with a large number of nodes arranged in a hierarchical and modular structure. We propose a novel multi-scale factor analysis (MSFA) model which partitions the massive spatio-temporal data defined over the complex networks into a finite set of regional clusters. To achieve further dimension reduction, we represent the signals in each cluster by a small number of latent factors. The correlation matrix for all nodes in the network are approximated by lower-dimensional sub-structures derived from the cluster-specific factors. To estimate regional connectivity between numerous nodes (within each cluster), we apply principal components analysis (PCA) to produce factors which are derived as the optimal reconstruction of the observed signals under the squared loss. Then, we estimate global connectivity (between clusters or sub-networks) based on the factors across regions using the RV-coefficient as the cross-dependence measure. This gives a reliable and computationally efficient multi-scale analysis of both regional and global dependencies of the large networks. The proposed novel approach is applied to estimate brain connectivity networks using functional magnetic resonance imaging (fMRI) data. Results on resting-state fMRI reveal interesting modular and hierarchical organization of human brain networks during rest.

Denoising of chaotic signal using independent component analysis and empirical mode decomposition with circulate translating

International Nuclear Information System (INIS)

Wang Wen-Bo; Zhang Xiao-Dong; Chang Yuchan; Wang Xiang-Li; Wang Zhao; Chen Xi; Zheng Lei

2016-01-01

In this paper, a new method to reduce noises within chaotic signals based on ICA (independent component analysis) and EMD (empirical mode decomposition) is proposed. The basic idea is decomposing chaotic signals and constructing multidimensional input vectors, firstly, on the base of EMD and its translation invariance. Secondly, it makes the independent component analysis on the input vectors, which means that a self adapting denoising is carried out for the intrinsic mode functions (IMFs) of chaotic signals. Finally, all IMFs compose the new denoised chaotic signal. Experiments on the Lorenz chaotic signal composed of different Gaussian noises and the monthly observed chaotic sequence on sunspots were put into practice. The results proved that the method proposed in this paper is effective in denoising of chaotic signals. Moreover, it can correct the center point in the phase space effectively, which makes it approach the real track of the chaotic attractor. (paper)

The signal-to-noise analysis of the Little-Hopfield model revisited

International Nuclear Information System (INIS)

Bolle, D; Blanco, J Busquets; Verbeiren, T

2004-01-01

Using the generating functional analysis an exact recursion relation is derived for the time evolution of the effective local field of the fully connected Little-Hopfield model. It is shown that, by leaving out the feedback correlations arising from earlier times in this effective dynamics, one precisely finds the recursion relations usually employed in the signal-to-noise approach. The consequences of this approximation as well as the physics behind it are discussed. In particular, it is pointed out why it is hard to notice the effects, especially for model parameters corresponding to retrieval. Numerical simulations confirm these findings. The signal-to-noise analysis is then extended to include all correlations, making it a full theory for dynamics at the level of the generating functional analysis. The results are applied to the frequently employed extremely diluted (a)symmetric architectures and to sequence processing networks

Time-frequency analysis of non-stationary fusion plasma signals using an improved Hilbert-Huang transform

International Nuclear Information System (INIS)

Liu, Yangqing; Tan, Yi; Xie, Huiqiao; Wang, Wenhao; Gao, Zhe

2014-01-01

An improved Hilbert-Huang transform method is developed to the time-frequency analysis of non-stationary signals in tokamak plasmas. Maximal overlap discrete wavelet packet transform rather than wavelet packet transform is proposed as a preprocessor to decompose a signal into various narrow-band components. Then, a correlation coefficient based selection method is utilized to eliminate the irrelevant intrinsic mode functions obtained from empirical mode decomposition of those narrow-band components. Subsequently, a time varying vector autoregressive moving average model instead of Hilbert spectral analysis is performed to compute the Hilbert spectrum, i.e., a three-dimensional time-frequency distribution of the signal. The feasibility and effectiveness of the improved Hilbert-Huang transform method is demonstrated by analyzing a non-stationary simulated signal and actual experimental signals in fusion plasmas

Pan-cancer analysis of TCGA data reveals notable signaling pathways

International Nuclear Information System (INIS)

Neapolitan, Richard; Horvath, Curt M.; Jiang, Xia

2015-01-01

A signal transduction pathway (STP) is a network of intercellular information flow initiated when extracellular signaling molecules bind to cell-surface receptors. Many aberrant STPs have been associated with various cancers. To develop optimal treatments for cancer patients, it is important to discover which STPs are implicated in a cancer or cancer-subtype. The Cancer Genome Atlas (TCGA) makes available gene expression level data on cases and controls in ten different types of cancer including breast cancer, colon adenocarcinoma, glioblastoma, kidney renal papillary cell carcinoma, low grade glioma, lung adenocarcinoma, lung squamous cell carcinoma, ovarian carcinoma, rectum adenocarcinoma, and uterine corpus endometriod carcinoma. Signaling Pathway Impact Analysis (SPIA) is a software package that analyzes gene expression data to identify whether a pathway is relevant in a given condition. We present the results of a study that uses SPIA to investigate all 157 signaling pathways in the KEGG PATHWAY database. We analyzed each of the ten cancer types mentioned above separately, and we perform a pan-cancer analysis by grouping the data for all the cancer types. In each analysis several pathways were found to be markedly more significant than all the other pathways. We call them notable. Research has already established a connection between many of these pathways and the corresponding cancer type. However, some of our discovered pathways appear to be new findings. Altogether there were 37 notable findings in the separate analyses, 26 of them occurred in 7 pathways. These 7 pathways included the 4 notable pathways discovered in the pan-cancer analysis. So, our results suggest that these 7 pathways account for much of the mechanisms of cancer. Furthermore, by looking at the overlap among pathways, we identified possible regions on the pathways where the aberrant activity is occurring. We obtained 37 notable findings concerning 18 pathways. Some of them appear to be

Spatial modeling of the membrane-cytosolic interface in protein kinase signal transduction.

Directory of Open Access Journals (Sweden)

Wolfgang Giese

2018-04-01

Full Text Available The spatial architecture of signaling pathways and the interaction with cell size and morphology are complex, but little understood. With the advances of single cell imaging and single cell biology, it becomes crucial to understand intracellular processes in time and space. Activation of cell surface receptors often triggers a signaling cascade including the activation of membrane-attached and cytosolic signaling components, which eventually transmit the signal to the cell nucleus. Signaling proteins can form steep gradients in the cytosol, which cause strong cell size dependence. We show that the kinetics at the membrane-cytosolic interface and the ratio of cell membrane area to the enclosed cytosolic volume change the behavior of signaling cascades significantly. We suggest an estimate of average concentration for arbitrary cell shapes depending on the cell volume and cell surface area. The normalized variance, known from image analysis, is suggested as an alternative measure to quantify the deviation from the average concentration. A mathematical analysis of signal transduction in time and space is presented, providing analytical solutions for different spatial arrangements of linear signaling cascades. Quantification of signaling time scales reveals that signal propagation is faster at the membrane than at the nucleus, while this time difference decreases with the number of signaling components in the cytosol. Our investigations are complemented by numerical simulations of non-linear cascades with feedback and asymmetric cell shapes. We conclude that intracellular signal propagation is highly dependent on cell geometry and, thereby, conveys information on cell size and shape to the nucleus.

Acoustic Emission Signal Processing Technique to Characterize Reactor In-Pile Phenomena

Energy Technology Data Exchange (ETDEWEB)

Vivek Agarwal; Magdy Samy Tawfik; James A Smith

2014-07-01

Existing and developing advanced sensor technologies and instrumentation will allow non-intrusive in-pile measurement of temperature, extension, and fission gases when coupled with advanced signal processing algorithms. The transmitted measured sensor signals from inside to the outside of containment structure are corrupted by noise and are attenuated, thereby reducing the signal strength and signal-to-noise ratio. Identification and extraction of actual signal (representative of an in-pile phenomenon) is a challenging and complicated process. In this paper, empirical mode decomposition technique is proposed to reconstruct actual sensor signal by partially combining intrinsic mode functions. Reconstructed signal corresponds to phenomena and/or failure modes occurring inside the reactor. In addition, it allows accurate non-intrusive monitoring and trending of in-pile phenomena.

Small-Signal Stability Analysis of Full-Load Converter Interfaced Wind Turbines

DEFF Research Database (Denmark)

Knüppel, Thyge; Akhmatov, Vladislav; Nielsen, Jørgen Nygård

2009-01-01

focus since the share of wind power increases substituting power generation from conventional power plants. Here, a study based on modal analysis is presented which investigate the effect of large scale integration of full-load converter interfaced wind turbines on inter-area oscillations in a three...... generator network. A detailed aggregated wind turbine model is employed which includes all necessary control functions. It is shown that the wind urbines have very low participation in the inter-area power oscillation.......Power system stability investigations of wind farms often cover the tasks of low-voltage-fault-ride-through, voltage and reactive power control, and power balancing, but not much attention has yet been paid to the task of small-signal stability. Small-signal stability analysis needs increasing...

Variability of signal-to-noise ratio and the network analysis of gravitational wave burst signals

International Nuclear Information System (INIS)

Mohanty, S D; Rakhmanov, M; Klimenko, S; Mitselmakher, G

2006-01-01

The detection and estimation of gravitational wave burst signals, with a priori unknown polarization waveforms, requires the use of data from a network of detectors. Maximizing the network likelihood functional over all waveforms and sky positions yields point estimates for them as well as a detection statistic. However, the transformation from the data to estimates can become ill-conditioned over parts of the sky, resulting in significant errors in estimation. We modify the likelihood procedure by introducing a penalty functional which suppresses candidate solutions that display large signal-to-noise ratio (SNR) variability as the source is displaced on the sky. Simulations show that the resulting network analysis method performs significantly better in estimating the sky position of a source. Further, this method can be applied to any network, irrespective of the number or mutual alignment of detectors

Signaling aggression.

Science.gov (United States)

van Staaden, Moira J; Searcy, William A; Hanlon, Roger T

2011-01-01

From psychological and sociological standpoints, aggression is regarded as intentional behavior aimed at inflicting pain and manifested by hostility and attacking behaviors. In contrast, biologists define aggression as behavior associated with attack or escalation toward attack, omitting any stipulation about intentions and goals. Certain animal signals are strongly associated with escalation toward attack and have the same function as physical attack in intimidating opponents and winning contests, and ethologists therefore consider them an integral part of aggressive behavior. Aggressive signals have been molded by evolution to make them ever more effective in mediating interactions between the contestants. Early theoretical analyses of aggressive signaling suggested that signals could never be honest about fighting ability or aggressive intentions because weak individuals would exaggerate such signals whenever they were effective in influencing the behavior of opponents. More recent game theory models, however, demonstrate that given the right costs and constraints, aggressive signals are both reliable about strength and intentions and effective in influencing contest outcomes. Here, we review the role of signaling in lieu of physical violence, considering threat displays from an ethological perspective as an adaptive outcome of evolutionary selection pressures. Fighting prowess is conveyed by performance signals whose production is constrained by physical ability and thus limited to just some individuals, whereas aggressive intent is encoded in strategic signals that all signalers are able to produce. We illustrate recent advances in the study of aggressive signaling with case studies of charismatic taxa that employ a range of sensory modalities, viz. visual and chemical signaling in cephalopod behavior, and indicators of aggressive intent in the territorial calls of songbirds. Copyright © 2011 Elsevier Inc. All rights reserved.

Constraint-based modeling and kinetic analysis of the Smad dependent TGF-beta signaling pathway.

Directory of Open Access Journals (Sweden)

Zhike Zi

Full Text Available BACKGROUND: Investigation of dynamics and regulation of the TGF-beta signaling pathway is central to the understanding of complex cellular processes such as growth, apoptosis, and differentiation. In this study, we aim at using systems biology approach to provide dynamic analysis on this pathway. METHODOLOGY/PRINCIPAL FINDINGS: We proposed a constraint-based modeling method to build a comprehensive mathematical model for the Smad dependent TGF-beta signaling pathway by fitting the experimental data and incorporating the qualitative constraints from the experimental analysis. The performance of the model generated by constraint-based modeling method is significantly improved compared to the model obtained by only fitting the quantitative data. The model agrees well with the experimental analysis of TGF-beta pathway, such as the time course of nuclear phosphorylated Smad, the subcellular location of Smad and signal response of Smad phosphorylation to different doses of TGF-beta. CONCLUSIONS/SIGNIFICANCE: The simulation results indicate that the signal response to TGF-beta is regulated by the balance between clathrin dependent endocytosis and non-clathrin mediated endocytosis. This model is useful to be built upon as new precise experimental data are emerging. The constraint-based modeling method can also be applied to quantitative modeling of other signaling pathways.

Advanced LIGO: sources and astrophysics

International Nuclear Information System (INIS)

Creighton, Teviet

2003-01-01

Second-generation detectors in LIGO will take us from the discovery phase of gravitational-wave observations to the phase of true gravitational-wave astrophysics, with hundreds or thousands of potential sources. This paper surveys the most likely and interesting potential sources for Advanced LIGO, and the astrophysical processes that each one will probe. I conclude that binary inspiral signals are expected, while continuous signals from pulsars are plausible but not guaranteed. Other sources, such as core-collapse bursts, cosmic strings and primordial stochastic backgrounds, are speculative sources for Advanced LIGO, but also potentially the most interesting, since they push the limits of our theoretical knowledge

Embedding Dimension Selection for Adaptive Singular Spectrum Analysis of EEG Signal.

Science.gov (United States)

Xu, Shanzhi; Hu, Hai; Ji, Linhong; Wang, Peng

2018-02-26

The recorded electroencephalography (EEG) signal is often contaminated with different kinds of artifacts and noise. Singular spectrum analysis (SSA) is a powerful tool for extracting the brain rhythm from a noisy EEG signal. By analyzing the frequency characteristics of the reconstructed component (RC) and the change rate in the trace of the Toeplitz matrix, it is demonstrated that the embedding dimension is related to the frequency bandwidth of each reconstructed component, in consistence with the component mixing in the singular value decomposition step. A method for selecting the embedding dimension is thereby proposed and verified by simulated EEG signal based on the Markov Process Amplitude (MPA) EEG Model. Real EEG signal is also collected from the experimental subjects under both eyes-open and eyes-closed conditions. The experimental results show that based on the embedding dimension selection method, the alpha rhythm can be extracted from the real EEG signal by the adaptive SSA, which can be effectively utilized to distinguish between the eyes-open and eyes-closed states.

Embedding Dimension Selection for Adaptive Singular Spectrum Analysis of EEG Signal

Directory of Open Access Journals (Sweden)

Shanzhi Xu

2018-02-01

Full Text Available The recorded electroencephalography (EEG signal is often contaminated with different kinds of artifacts and noise. Singular spectrum analysis (SSA is a powerful tool for extracting the brain rhythm from a noisy EEG signal. By analyzing the frequency characteristics of the reconstructed component (RC and the change rate in the trace of the Toeplitz matrix, it is demonstrated that the embedding dimension is related to the frequency bandwidth of each reconstructed component, in consistence with the component mixing in the singular value decomposition step. A method for selecting the embedding dimension is thereby proposed and verified by simulated EEG signal based on the Markov Process Amplitude (MPA EEG Model. Real EEG signal is also collected from the experimental subjects under both eyes-open and eyes-closed conditions. The experimental results show that based on the embedding dimension selection method, the alpha rhythm can be extracted from the real EEG signal by the adaptive SSA, which can be effectively utilized to distinguish between the eyes-open and eyes-closed states.

LC-MS/MS signal suppression effects in the analysis of pesticides in complex environmental matrices.

Science.gov (United States)

Choi, B K; Hercules, D M; Gusev, A I

2001-02-01

The application of LC separation and mobile phase additives in addressing LC-MS/MS matrix signal suppression effects for the analysis of pesticides in a complex environmental matrix was investigated. It was shown that signal suppression is most significant for analytes eluting early in the LC-MS analysis. Introduction of different buffers (e.g. ammonium formate, ammonium hydroxide, formic acid) into the LC mobile phase was effective in improving signal correlation between the matrix and standard samples. The signal improvement is dependent on buffer concentration as well as LC separation of the matrix components. The application of LC separation alone was not effective in addressing suppression effects when characterizing complex matrix samples. Overloading of the LC column by matrix components was found to significantly contribute to analyte-matrix co-elution and suppression of signal. This signal suppression effect can be efficiently compensated by 2D LC (LC-LC) separation techniques. The effectiveness of buffers and LC separation in improving signal correlation between standard and matrix samples is discussed.

CADDIS Volume 4. Data Analysis: Advanced Analyses - Controlling for Natural Variability

Science.gov (United States)

Methods for controlling natural variability, predicting environmental conditions from biological observations method, biological trait data, species sensitivity distributions, propensity scores, Advanced Analyses of Data Analysis references.

Structural weights analysis of advanced aerospace vehicles using finite element analysis

Science.gov (United States)

Bush, Lance B.; Lentz, Christopher A.; Rehder, John J.; Naftel, J. Chris; Cerro, Jeffrey A.

1989-01-01

A conceptual/preliminary level structural design system has been developed for structural integrity analysis and weight estimation of advanced space transportation vehicles. The system includes a three-dimensional interactive geometry modeler, a finite element pre- and post-processor, a finite element analyzer, and a structural sizing program. Inputs to the system include the geometry, surface temperature, material constants, construction methods, and aerodynamic and inertial loads. The results are a sized vehicle structure capable of withstanding the static loads incurred during assembly, transportation, operations, and missions, and a corresponding structural weight. An analysis of the Space Shuttle external tank is included in this paper as a validation and benchmark case of the system.

A Sparse Modulation Signal Bispectrum Analysis Method for Rolling Element Bearing Diagnosis

Directory of Open Access Journals (Sweden)

Guangbin Wang

2018-01-01

Full Text Available Modulation signal bispectrum (MSB analysis is an effective method to obtain the fault frequency for rolling bearing, but harmonics make fault frequency dense and even frequency aliasing. Carrier frequency of bearing is generally determined by its structure and inherent characteristics and changes with the increase of the damage degree, so it is hard to be accurately found. To solve these problems, this paper proposes a sparse modulation signal bispectrum analysis method. Firstly the vibration signal is demodulated by MSB analysis and its bispectrum is obtained. After the frequency domain filtering, the carrier frequency is computed based on the characteristics of energy concentration at the carrier frequency on MSB. By shift-frequency MSB (SF-MSB, the carrier frequency is moved to the coordinate origin, the entire MSB is shifted for the same distance, and SF-MSB is obtained. At last, the bispectrum is shifted to the frequency zero point and diagonal slices are performed to obtain a sparse representation of MSB. Experimental results show that sparse MSB (S-MSB method can not only eliminate the interference of harmonic frequency, but also make the extracted characteristic frequency of fault more obvious.

Frequency Analysis of Acoustic Emission Signal to Monitor Damage Evolution in Masonry Structures

International Nuclear Information System (INIS)

Masera, D; Bocca, P; Grazzini, A

2011-01-01

A crucial aspect in damage evaluation of masonry structures is the analysis of long-term behaviour and for this reason fatigue analysis has a great influence on safety assessment of this structures. Acoustic Emission (AE) are very effective non-destructive techniques applied to identify micro and macro-defects and their temporal evolution in several materials. This technique permits to estimate the velocity of ultrasound waves propagation and the amount of energy released during fracture propagation to obtain information on the criticality of the ongoing process. By means of AE monitoring, an experimental analysis on a set of reinforced and unreinforced masonry walls under variable amplitude and static loading has been carried out. During these tests, the AE signals were recorded. The AE signals were analysed using Fast Fourier Transform (FFT) to examine the frequency distribution of the micro and macro cracking. It possible to evaluate the evolution of the wavelength of the AE signal through the two characteristic peak in the AE spectrum signals and the wave speed of the P or S waves. This wavelength evolution can be represent the microcrak and macrocrack evolution in masonry walls. This procedure permits to estimate the fracture dimension characteristic in several loading condition and for several masonry reinforced condition.

Quantitative Analysis of Diverse Lactobacillus Species Present in Advanced Dental Caries

OpenAIRE

Byun, Roy; Nadkarni, Mangala A.; Chhour, Kim-Ly; Martin, F. Elizabeth; Jacques, Nicholas A.; Hunter, Neil

2004-01-01

Our previous analysis of 65 advanced dental caries lesions by traditional culture techniques indicated that lactobacilli were numerous in the advancing front of the progressive lesion. Production of organic acids by lactobacilli is considered to be important in causing decalcification of the dentinal matrix. The present study was undertaken to define more precisely the diversity of lactobacilli found in this environment and to quantify the major species and phylotypes relative to total load o...

Function analysis and function assignment of NPP advanced main control room

International Nuclear Information System (INIS)

Zheng Mingguang; Xu Jijun

2001-01-01

The author addresses the requirements of function analysis and function assignment, which should be carried out in the design of main control room in nuclear power plant according to the design research of advanced main control room, then states its contents, functions, importance and necessity as well as how to implement these requirements and how to do design verification and validation in the design of advanced main control room of nuclear power plant

Repeatability study of replicate crash tests: A signal analysis approach.

Science.gov (United States)

Seppi, Jeremy; Toczyski, Jacek; Crandall, Jeff R; Kerrigan, Jason

2017-10-03

To provide an objective basis on which to evaluate the repeatability of vehicle crash test methods, a recently developed signal analysis method was used to evaluate correlation of sensor time history data between replicate vehicle crash tests. The goal of this study was to evaluate the repeatability of rollover crash tests performed with the Dynamic Rollover Test System (DRoTS) relative to other vehicle crash test methods. Test data from DRoTS tests, deceleration rollover sled (DRS) tests, frontal crash tests, frontal offset crash tests, small overlap crash tests, small overlap impact (SOI) crash tests, and oblique crash tests were obtained from the literature and publicly available databases (the NHTSA vehicle database and the Insurance Institute for Highway Safety TechData) to examine crash test repeatability. Signal analysis of the DRoTS tests showed that force and deformation time histories had good to excellent repeatability, whereas vehicle kinematics showed only fair repeatability due to the vehicle mounting method for one pair of tests and slightly dissimilar mass properties (2.2%) in a second pair of tests. Relative to the DRS, the DRoTS tests showed very similar or higher levels of repeatability in nearly all vehicle kinematic data signals with the exception of global X' (road direction of travel) velocity and displacement due to the functionality of the DRoTS fixture. Based on the average overall scoring metric of the dominant acceleration, DRoTS was found to be as repeatable as all other crash tests analyzed. Vertical force measures showed good repeatability and were on par with frontal crash barrier forces. Dynamic deformation measures showed good to excellent repeatability as opposed to poor repeatability seen in SOI and oblique deformation measures. Using the signal analysis method as outlined in this article, the DRoTS was shown to have the same or better repeatability of crash test methods used in government regulatory and consumer evaluation test

Advanced Analog Signal Processing for Fuzing Final Report CRADA No. TC-1306-96

Energy Technology Data Exchange (ETDEWEB)

Fu, C. Y. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Spencer, D. [Raymond Engineering, Middletown, CT (United States)

2018-01-24

The purpose of this CRADA between LLNL and Kaman Aerospace/Raymond Engineering Operations (Raymond) was to demonstrate the feasibility of using Analog/Digital Neural Network (ANN) Technology for advanced signal processing, fuzing, and other applications. This cooperation sought to Ieverage the expertise and capabilities of both parties--Raymond to develop the signature recognition hardware system, using Raymond’s extensive experience in the area of system development plus Raymond’s knowledge of military applications, and LLNL to apply ANN and related technologies to an area of significant interest to the United States government. This CRADA effort was anticipated to be a three-year project consisting of three phases: Phase I, Proof-of-Principle Demonstration; Phase II, Proof-of-Design, involving the development of a form-factored integrated sensor and ANN technology processo~ and Phase III, Final Design and Release of the integrated sensor and ANN fabrication process: Under Phase I, to be conducted during calendar year 1996, Raymond was to deliver to LLNL an architecture (design) for an ANN chip. LLNL was to translate the design into a stepper mask and to produce and test a prototype chip from the Raymond design.

Ultrahigh bandwidth signal processing

DEFF Research Database (Denmark)

Oxenløwe, Leif Katsuo

2016-01-01

Optical time lenses have proven to be very versatile for advanced optical signal processing. Based on a controlled interplay between dispersion and phase-modulation by e.g. four-wave mixing, the processing is phase-preserving, an hence useful for all types of data signals including coherent multi......-level modulation founats. This has enabled processing of phase-modulated spectrally efficient data signals, such as orthogonal frequency division multiplexed (OFDM) signa In that case, a spectral telescope system was used, using two time lenses with different focal lengths (chirp rates), yielding a spectral...... regeneratio These operations require a broad bandwidth nonlinear platform, and novel photonic integrated nonlinear platform like aluminum gallium arsenide nano-waveguides used for 1.28 Tbaud optical signal processing will be described....

Enhancement of MS Signal Processing For Improved Cancer Biomarker Discovery

Science.gov (United States)

Si, Qian

Technological advances in proteomics have shown great potential in detecting cancer at the earliest stages. One way is to use the time of flight mass spectroscopy to identify biomarkers, or early disease indicators related to the cancer. Pattern analysis of time of flight mass spectra data from blood and tissue samples gives great hope for the identification of potential biomarkers among the complex mixture of biological and chemical samples for the early cancer detection. One of the keys issues is the pre-processing of raw mass spectra data. A lot of challenges need to be addressed: unknown noise character associated with the large volume of data, high variability in the mass spectroscopy measurements, and poorly understood signal background and so on. This dissertation focuses on developing statistical algorithms and creating data mining tools for computationally improved signal processing for mass spectrometry data. I have introduced an advanced accurate estimate of the noise model and a half-supervised method of mass spectrum data processing which requires little knowledge about the data.

Common genomic signaling among initial DNA damage and radiation-induced apoptosis in peripheral blood lymphocytes from locally advanced breast cancer patients

DEFF Research Database (Denmark)

Henríquez-Hernández, Luis Alberto; Pinar, Beatriz; Carmona-Vigo, Ruth

2013-01-01

PURPOSE: To investigate the genomic signaling that defines sensitive lymphocytes to radiation and if such molecular profiles are consistent with clinical toxicity; trying to disclose the radiobiology mechanisms behind these cellular processes. PATIENTS AND METHODS: Twelve consecutive patients...... suffering from locally advanced breast cancer and treated with high-dose hyperfractionated radiotherapy were recruited. Initial DNA damage was measured by pulsed-field gel electrophoresis and radiation-induced apoptosis was measured by flow cytometry. Gene expression was assessed by DNA microarray. RESULTS...

pyAudioAnalysis: An Open-Source Python Library for Audio Signal Analysis.

Science.gov (United States)

Giannakopoulos, Theodoros

2015-01-01

Audio information plays a rather important role in the increasing digital content that is available today, resulting in a need for methodologies that automatically analyze such content: audio event recognition for home automations and surveillance systems, speech recognition, music information retrieval, multimodal analysis (e.g. audio-visual analysis of online videos for content-based recommendation), etc. This paper presents pyAudioAnalysis, an open-source Python library that provides a wide range of audio analysis procedures including: feature extraction, classification of audio signals, supervised and unsupervised segmentation and content visualization. pyAudioAnalysis is licensed under the Apache License and is available at GitHub (https://github.com/tyiannak/pyAudioAnalysis/). Here we present the theoretical background behind the wide range of the implemented methodologies, along with evaluation metrics for some of the methods. pyAudioAnalysis has been already used in several audio analysis research applications: smart-home functionalities through audio event detection, speech emotion recognition, depression classification based on audio-visual features, music segmentation, multimodal content-based movie recommendation and health applications (e.g. monitoring eating habits). The feedback provided from all these particular audio applications has led to practical enhancement of the library.

CERN Technical Training 2003: Learning for the LHC ! DISP-2003 - Digital Signal Processing

CERN Multimedia

2003-01-01

DISP-2003 - Digital Signal Processing DISP-2003 is a two-term course given by CERN and University of Lausanne (UNIL) experts within the framework of the Technical Training Programme. The course will review the current techniques dealing with Digital Signal Processing, and it is intended for an audience who work or will work on digital signal processing aspects, and who need an introductory or refresher/update course. The course will be in English, with question and answers also in French. Spring 2 Term: DISP-2003: Advanced Digital Signal Processing 30 April 2003 - 21 May 2003, 4 lectures, Wednesdays afternoon (attendance cost: 40.- CHF, registration required) Lecturers: Léonard Studer, UNIL; Laurent Deniau, AT-MTM; Elena Wildner, AT-MAS Programme: Intelligent signal processing (ISP). Non-linear time series analysis. Image processing. Wavelets. (Basic concepts and definitions have been introduced during the previous Spring 1 Term: DISP-2003: Introduction to Digital Signal Processing). DISP-2003 is open...

Mitochondrial Energy and Redox Signaling in Plants

Science.gov (United States)

Schwarzländer, Markus

2013-01-01

Abstract Significance: For a plant to grow and develop, energy and appropriate building blocks are a fundamental requirement. Mitochondrial respiration is a vital source for both. The delicate redox processes that make up respiration are affected by the plant's changing environment. Therefore, mitochondrial regulation is critically important to maintain cellular homeostasis. This involves sensing signals from changes in mitochondrial physiology, transducing this information, and mounting tailored responses, by either adjusting mitochondrial and cellular functions directly or reprogramming gene expression. Recent Advances: Retrograde (RTG) signaling, by which mitochondrial signals control nuclear gene expression, has been a field of very active research in recent years. Nevertheless, no mitochondrial RTG-signaling pathway is yet understood in plants. This review summarizes recent advances toward elucidating redox processes and other bioenergetic factors as a part of RTG signaling of plant mitochondria. Critical Issues: Novel insights into mitochondrial physiology and redox-regulation provide a framework of upstream signaling. On the other end, downstream responses to modified mitochondrial function have become available, including transcriptomic data and mitochondrial phenotypes, revealing processes in the plant that are under mitochondrial control. Future Directions: Drawing parallels to chloroplast signaling and mitochondrial signaling in animal systems allows to bridge gaps in the current understanding and to deduce promising directions for future research. It is proposed that targeted usage of new technical approaches, such as quantitative in vivo imaging, will provide novel leverage to the dissection of plant mitochondrial signaling. Antioxid. Redox Signal. 18, 2122–2144. PMID:23234467

Comparative analysis of chosen transforms in the context of de-noising harmonic signals

Directory of Open Access Journals (Sweden)

Artur Zacniewski

2015-09-01

Full Text Available In the article, comparison of popular transforms used i.a. in denoising harmonical signals was presented. The division of signals submitted to mathematical analysis was shown and chosen transforms such as Short Time Fourier Transform, Wigner-Ville Distribution, Wavelet Transform and Discrete Cosine Transform were presented. Harmonic signal with white noise added was submitted for research. During research, the parameters of noise were changed to analyze the effects of using particular transform on noised signal. The importance of right choice for transform and its parameters (different for particular kind of transform was shown. Small changes in parameters or different functions used in transform can lead to considerably different results.[b]Keywords[/b]: denoising of harmonical signals, wavelet transform, discrete cosine transform, DCT

An Optimization-Driven Analysis Pipeline to Uncover Biomarkers and Signaling Paths: Cervix Cancer

Directory of Open Access Journals (Sweden)

Enery Lorenzo

2015-05-01

Full Text Available Establishing how a series of potentially important genes might relate to each other is relevant to understand the origin and evolution of illnesses, such as cancer. High‑throughput biological experiments have played a critical role in providing information in this regard. A special challenge, however, is that of trying to conciliate information from separate microarray experiments to build a potential genetic signaling path. This work proposes a two-step analysis pipeline, based on optimization, to approach meta-analysis aiming to build a proxy for a genetic signaling path.

Development of advanced spent fuel management process. System analysis of advanced spent fuel management process

International Nuclear Information System (INIS)

Ro, S.G.; Kang, D.S.; Seo, C.S.; Lee, H.H.; Shin, Y.J.; Park, S.W.

1999-03-01

The system analysis of an advanced spent fuel management process to establish a non-proliferation model for the long-term spent fuel management is performed by comparing the several dry processes, such as a salt transport process, a lithium process, the IFR process developed in America, and DDP developed in Russia. In our system analysis, the non-proliferation concept is focused on the separation factor between uranium and plutonium and decontamination factors of products in each process, and the non-proliferation model for the long-term spent fuel management has finally been introduced. (Author). 29 refs., 17 tabs., 12 figs

TERMA Framework for Biomedical Signal Analysis: An Economic-Inspired Approach

Directory of Open Access Journals (Sweden)

Mohamed Elgendi

2016-11-01

Full Text Available Biomedical signals contain features that represent physiological events, and each of these events has peaks. The analysis of biomedical signals for monitoring or diagnosing diseases requires the detection of these peaks, making event detection a crucial step in biomedical signal processing. Many researchers have difficulty detecting these peaks to investigate, interpret and analyze their corresponding events. To date, there is no generic framework that captures these events in a robust, efficient and consistent manner. A new method referred to for the first time as two event-related moving averages (“TERMA” involves event-related moving averages and detects events in biomedical signals. The TERMA framework is flexible and universal and consists of six independent LEGO building bricks to achieve high accuracy detection of biomedical events. Results recommend that the window sizes for the two moving averages ( W 1 and W 2 have to follow the inequality ( 8 × W 1 ≥ W 2 ≥ ( 2 × W 1 . Moreover, TERMA is a simple yet efficient event detector that is suitable for wearable devices, point-of-care devices, fitness trackers and smart watches, compared to more complex machine learning solutions.

Systems analysis and engineering of the X-1 Advanced Radiation Source

International Nuclear Information System (INIS)

Rochau, G.E.; Hands, J.A.; Raglin, P.S.; Ramirez, J.J.

1998-01-01

The X-1 Advanced Radiation Source, which will produce ∼ 16 MJ in x-rays, represents the next step in providing US Department of Energy's Stockpile Stewardship program with the high-energy, large volume, laboratory x-ray sources needed for the Radiation Effects Science and Simulation (RES), Inertial Confinement Fusion (ICF), and Weapon Physics (WP) Programs. Advances in fast pulsed power technology and in z-pinch hohlraums on Sandia National Laboratories' Z Accelerator in 1997 provide sufficient basis for pursuing the development of X-1. This paper will introduce the X-1 Advanced Radiation Source Facility Project, describe the systems analysis and engineering approach being used, and identify critical technology areas being researched

Recent advances in segmented gamma scanner analysis

International Nuclear Information System (INIS)

Sprinkle, J.K. Jr.; Hsue, S.T.

1987-01-01

The segmented gamma scanner (SGS) is used in many facilities to assay low-density scrap and waste generated in the facilities. The procedures for using the SGS can cause a negative bias if the sample does not satisfy the assumptions made in the method. Some process samples do not comply with the assumptions. This paper discusses the effect of the presence of lumps on the SGS assay results, describes a method to detect the presence of lumps, and describes an approach to correct for the lumps. Other recent advances in SGS analysis are also discussed

Development of a central PC-based system for reactor signal monitoring and analysis

International Nuclear Information System (INIS)

Karim, A.; Ansari, S.A.; Baig, A.R.

1996-05-01

A personal computer based system was developed for on-line monitoring, signal processing and display of important parameters of the Pakistan Reactor-1. The system was designed for assistance to both reactor operator and users. It performs three main functions. The first is the centralized radiation monitoring in and around the reactor building. The computer acquires signals from radiation monitoring channels and continuously displays them on distributed monitors. Trend monitoring and alarm generation is also done. In case of any abnormal condition the radiation level data is automatically stored in computer memory for detailed off-line analysis. In the second part the computer does the performance testing of nuclear instrumentation channels by signal statistical analysis and generates alarm in case the channel standard deviation error exceeds the permissible error. Mean values of important nuclear signals are also displayed on distributed monitors as a part of reactor safety parameters display system. The third function is on-line computation of reactor physics parameters of the core which are important from operational and safety point-of-view. The signals from radiation protection system and nuclear instrumentation channels in the reactor were interfaced with the computer for this purpose. The development work was done under an IAEA research contract as a part of coordinated research programme. (author) 12 figs

Development of a central PC-based system for reactor signal monitoring and analysis

International Nuclear Information System (INIS)

Karim, A.; Ansari, S.A.; Rauf Baig, A.

1998-01-01

A personal computer based system was developed for on-line monitoring, signal processing and display of important reactor parameters of the Pakistan Research Reactor-1. The system was designed for assistance to both reactor operator and users. It performs three main functions. The first is the centralized radiation monitoring in and around the reactor building. The computer acquires signals from radiation monitoring channels and continuously displays them on distributed monitors. Trend monitoring and alarm generation is also done. In case of any abnormal condition the radiation level data is automatically stored in computer memory for detailed off-line analysis. In the second part the computer does the performance testing of nuclear instrumentation channels by signal statistical analysis, and generates alarm in case the channel standard deviation error exceeds the permissible error. Mean values of important nuclear signals are also displayed on distributed monitors as a part of reactor safety parameters display system. The third function is on-line computation of reactor physics parameters of the core which are important from operational and safety points-of-view. The signals from radiation protection system and nuclear instrumentation channels in the reactor were interfaced with the computer for this purpose. The development work was done under an IAEA research contract as a part of coordinated research programme. (author)

Fluorescence In Situ Hybridization (FISH Signal Analysis Using Automated Generated Projection Images

Directory of Open Access Journals (Sweden)

Xingwei Wang

2012-01-01

Full Text Available Fluorescence in situ hybridization (FISH tests provide promising molecular imaging biomarkers to more accurately and reliably detect and diagnose cancers and genetic disorders. Since current manual FISH signal analysis is low-efficient and inconsistent, which limits its clinical utility, developing automated FISH image scanning systems and computer-aided detection (CAD schemes has been attracting research interests. To acquire high-resolution FISH images in a multi-spectral scanning mode, a huge amount of image data with the stack of the multiple three-dimensional (3-D image slices is generated from a single specimen. Automated preprocessing these scanned images to eliminate the non-useful and redundant data is important to make the automated FISH tests acceptable in clinical applications. In this study, a dual-detector fluorescence image scanning system was applied to scan four specimen slides with FISH-probed chromosome X. A CAD scheme was developed to detect analyzable interphase cells and map the multiple imaging slices recorded FISH-probed signals into the 2-D projection images. CAD scheme was then applied to each projection image to detect analyzable interphase cells using an adaptive multiple-threshold algorithm, identify FISH-probed signals using a top-hat transform, and compute the ratios between the normal and abnormal cells. To assess CAD performance, the FISH-probed signals were also independently visually detected by an observer. The Kappa coefficients for agreement between CAD and observer ranged from 0.69 to 1.0 in detecting/counting FISH signal spots in four testing samples. The study demonstrated the feasibility of automated FISH signal analysis that applying a CAD scheme to the automated generated 2-D projection images.

Molecular analysis of microbial diversity in advanced caries.

Science.gov (United States)

Chhour, Kim-Ly; Nadkarni, Mangala A; Byun, Roy; Martin, F Elizabeth; Jacques, Nicholas A; Hunter, Neil

2005-02-01

Real-time PCR analysis of the total bacterial load in advanced carious lesions has shown that the total load exceeds the number of cultivable bacteria. This suggests that an unresolved complexity exists in bacteria associated with advanced caries. In this report, the profile of the microflora of carious dentine was explored by using DNA extracted from 10 lesions selected on the basis of comparable total microbial load and on the relative abundance of Prevotella spp. Using universal primers for the 16S rRNA gene, PCR amplicons were cloned, and approximately 100 transformants were processed for each lesion. Phylogenetic analysis of 942 edited sequences demonstrated the presence of 75 species or phylotypes in the 10 carious lesions. Up to 31 taxa were represented in each sample. A diverse array of lactobacilli were found to comprise 50% of the species, with prevotellae also abundant, comprising 15% of the species. Other taxa present in a number of lesions or occurring with high abundance included Selenomonas spp., Dialister spp., Fusobacterium nucleatum, Eubacterium spp., members of the Lachnospiraceae family, Olsenella spp., Bifidobacterium spp., Propionibacterium sp., and Pseudoramibacter alactolyticus. The mechanisms by which such diverse patterns of bacteria extend carious lesions, including the aspect of infection of the vital dental pulp, remain unclear.

Optical coherence tomography signal analysis: LIDAR like equation and inverse methods

International Nuclear Information System (INIS)

Amaral, Marcello Magri

2012-01-01

Optical Coherence Tomography (OCT) is based on the media backscattering properties in order to obtain tomographic images. In a similar way, LIDAR (Light Detection and Range) technique uses these properties to determine atmospheric characteristics, specially the signal extinction coefficient. Exploring this similarity allowed the application of signal inversion methods to the OCT images, allowing to construct images based in the extinction coefficient, original result until now. The goal of this work was to study, propose, develop and implement algorithms based on OCT signal inversion methodologies with the aim of determine the extinction coefficient as a function of depth. Three inversion methods were used and implemented in LABView R : slope, boundary point and optical depth. Associated errors were studied and real samples (homogeneous and stratified) were used for two and three dimension analysis. The extinction coefficient images obtained from the optical depth method were capable to differentiate air from the sample. The images were studied applying PCA and cluster analysis that established the methodology strength in determining the sample's extinction coefficient value. Moreover, the optical depth methodology was applied to study the hypothesis that there is some correlation between signal extinction coefficient and the enamel teeth demineralization during a cariogenic process. By applying this methodology, it was possible to observe the variation of the extinction coefficient as depth function and its correlation with microhardness variation, showing that in deeper layers its values tends to a healthy tooth values, behaving as the same way that the microhardness. (author)

A Review of Sleep Disorder Diagnosis by Electromyogram Signal Analysis.

Science.gov (United States)

Shokrollahi, Mehrnaz; Krishnan, Sridhar

2015-01-01

Sleep and sleep-related problems play a role in a large number of human disorders and affect every field of medicine. It is estimated that 50 to 70 million Americans suffer from a chronic sleep disorder, which hinders their daily life, affects their health, and confers a significant economic burden to society. The negative public health consequences of sleep disorders are enormous and could have long-term effects, including increased risk of hypertension, diabetes, obesity, heart attack, stroke and in some cases death. Polysomnographic modalities can monitor sleep cycles to identify disrupted sleep patterns, adjust the treatments, increase therapeutic options and enhance the quality of life of recording the electroencephalogram (EEG), electromyogram (EMG) and electrocardiogram (ECG). Although the skills acquired by medical facilitators are quite extensive, it is just as important for them to have access to an assortment of technologies and to further improve their monitoring and treatment capabilities. Computer-aided analysis is one advantageous technique that could provide quantitative indices for sleep disorder screening. Evolving evidence suggests that Parkinson's disease may be associated with rapid eye movement sleep behavior disorder (RBD). With this article, we are reviewing studies that are related to EMG signal analysis for detection of neuromuscular diseases that result from sleep movement disorders. As well, the article describes the recent progress in analysis of EMG signals using temporal analysis, frequency-domain analysis, time-frequency, and sparse representations, followed by the comparison of the recent research.

Analysis of physiological signals for recognition of boredom, pain, and surprise emotions.

Science.gov (United States)

Jang, Eun-Hye; Park, Byoung-Jun; Park, Mi-Sook; Kim, Sang-Hyeob; Sohn, Jin-Hun

2015-06-18

The aim of the study was to examine the differences of boredom, pain, and surprise. In addition to that, it was conducted to propose approaches for emotion recognition based on physiological signals. Three emotions, boredom, pain, and surprise, are induced through the presentation of emotional stimuli and electrocardiography (ECG), electrodermal activity (EDA), skin temperature (SKT), and photoplethysmography (PPG) as physiological signals are measured to collect a dataset from 217 participants when experiencing the emotions. Twenty-seven physiological features are extracted from the signals to classify the three emotions. The discriminant function analysis (DFA) as a statistical method, and five machine learning algorithms (linear discriminant analysis (LDA), classification and regression trees (CART), self-organizing map (SOM), Naïve Bayes algorithm, and support vector machine (SVM)) are used for classifying the emotions. The result shows that the difference of physiological responses among emotions is significant in heart rate (HR), skin conductance level (SCL), skin conductance response (SCR), mean skin temperature (meanSKT), blood volume pulse (BVP), and pulse transit time (PTT), and the highest recognition accuracy of 84.7% is obtained by using DFA. This study demonstrates the differences of boredom, pain, and surprise and the best emotion recognizer for the classification of the three emotions by using physiological signals.

Performance Analysis of a Utility Helicopter with Standard and Advanced Rotors

National Research Council Canada - National Science Library

Yeo, Hyeonsoo; Bousman, William G; Johnson, Wayne

2002-01-01

Flight test measurements of the performance of the UH-60 Black Hawk helicopter with both standard and advanced rotors are compared with calculations obtained using the comprehensive helicopter analysis CAMRAD II...

Development of Advanced Suite of Deterministic Codes for VHTR Physics Analysis

Energy Technology Data Exchange (ETDEWEB)

Kim, Kang Seog; Cho, J. Y.; Lee, K. H. (and others)

2007-07-15

Advanced Suites of deterministic codes for VHTR physics analysis has been developed for detailed analysis of current and advanced reactor designs as part of a US-ROK collaborative I-NERI project. These code suites include the conventional 2-step procedure in which a few group constants are generated by a transport lattice calculation, and the reactor physics analysis is performed by a 3-dimensional diffusion calculation, and a whole core transport code that can model local heterogeneities directly at the core level. Particular modeling issues in physics analysis of the gas-cooled VHTRs were resolved, which include a double heterogeneity of the coated fuel particles, a neutron streaming in the coolant channels, a strong core-reflector interaction, and large spectrum shifts due to changes of the surrounding environment, temperature and burnup. And the geometry handling capability of the DeCART code were extended to deal with the hexagonal fuel elements of the VHTR core. The developed code suites were validated and verified by comparing the computational results with those of the Monte Carlo calculations for the benchmark problems.

Features of an advanced human reliability analysis method, AGAPE-ET

Energy Technology Data Exchange (ETDEWEB)

Kim, Jae Whan; Jung, Won Dea; Park, Jin Kyun [Korea Atomic Energy Research Institute, Taejeon (Korea, Republic of)

2005-11-15

This paper presents the main features of an advanced human reliability analysis (HRA) method, AGAPE-ET. It has the capabilities to deal with the diagnosis failures and the errors of commission (EOC), which have not been normally treated in the conventional HRAs. For the analysis of the potential for diagnosis failures, an analysis framework, which is called the misdiagnosis tree analysis (MDTA), and a taxonomy of the misdiagnosis causes with appropriate quantification schemes are provided. For the identification of the EOC events from the misdiagnosis, some procedural guidance is given. An example of the application of the method is also provided.

Features of an advanced human reliability analysis method, AGAPE-ET

International Nuclear Information System (INIS)

Kim, Jae Whan; Jung, Won Dea; Park, Jin Kyun

2005-01-01

This paper presents the main features of an advanced human reliability analysis (HRA) method, AGAPE-ET. It has the capabilities to deal with the diagnosis failures and the errors of commission (EOC), which have not been normally treated in the conventional HRAs. For the analysis of the potential for diagnosis failures, an analysis framework, which is called the misdiagnosis tree analysis (MDTA), and a taxonomy of the misdiagnosis causes with appropriate quantification schemes are provided. For the identification of the EOC events from the misdiagnosis, some procedural guidance is given. An example of the application of the method is also provided

Interleukin-2 signaling pathway analysis by quantitative phosphoproteomics

DEFF Research Database (Denmark)

Osinalde, Nerea; Moss, Helle; Arrizabalaga, Onetsine

2011-01-01

among which 79 were found with increased abundance in the tyrosine-phosphorylated complexes, including several previously not reported IL-2 downstream effectors. Combinatorial site-specific phosphoproteomic analysis resulted in identification of 99 phosphorylated sites mapping to the identified proteins...... with increased abundance in the tyrosine-phosphorylated complexes, of which 34 were not previously described. In addition, chemical inhibition of the identified IL-2-mediated JAK, PI3K and MAPK signaling pathways, resulted in distinct alteration on the IL-2 dependent proliferation....

Combined EGFR and VEGFR versus single EGFR signaling pathways inhibition therapy for NSCLC: a systematic review and meta-analysis.

Directory of Open Access Journals (Sweden)

Xinji Zhang

Full Text Available BACKGROUND: Lung cancer is a heterogeneous disease with multiple signaling pathways influencing tumor cell survival and proliferation, and it is likely that blocking only one of these pathways allows others to act as salvage or escape mechanisms for cancer cells. Whether combined inhibition therapy has greater anti-tumor activity than single inhibition therapy is a matter of debate. Hence, a meta-analysis comparing therapy inhibiting both VEGFR and EGFR signaling pathways with that inhibiting EGFR signaling pathway alone was performed. METHODOLOGY AND PRINCIPAL FINDINGS: We searched PubMed, EMBASE database and the proceedings of major conferences for relevant clinical trials. Outcomes analyzed were objective tumor response rate (ORR, progression-free survival (PFS, overall survival (OS and toxicity. Besides, subgroup analyses were performed to investigate whether the combined inhibition therapy is best performed using combination of selective agents or a single agent with multiple targets. Six trials recruiting 3,302 patients were included in the analysis. Combined inhibition therapy was associated with a 3% improvement in OS as compared with single-targeted therapy, but this difference was not statistically significant (HR, 0.97; 95% CI, 0.89-1.05; P=0.472. Patients receiving combined inhibition therapy had significant longer PFS than the group with single-targeted therapy (HR, 0.80; 95% CI, 0.67-0.95; P=0.011. There was no difference in the ORR between the groups (OR, 1.44; 95% CI, 0.95-2.18; P=0.085. Subgroup analysis revealed that combined inhibition therapy using combination regimens was associated with statistically significant improvement in both ORR and PFS. Toxicity was greater in combined inhibition therapy. CONCLUSIONS: There is no evidence to support the use of combined inhibition therapy in unselected patients with advanced NSCLC. However, given the significant advantage in ORR and PFS, combined inhibition therapy using combination

Extending Differential Fault Analysis to Dynamic S-Box Advanced Encryption Standard Implementations

Science.gov (United States)

2014-09-18

number. As a result decryption is a different function which relies on a different key to efficiently undo the work of encryption . RSA is the most...EXTENDING DIFFERENTIAL FAULT ANALYSIS TO DYNAMIC S-BOX ADVANCED ENCRYPTION STANDARD IMPLEMENTATIONS THESIS Bradley M. Flamm, Civilian AFIT-ENG-T-14-S...ADVANCED ENCRYPTION STANDARD IMPLEMENTATIONS THESIS Presented to the Faculty Department of Electrical and Computer Engineering Graduate School of

Symbolic transfer entropy-based premature signal analysis

International Nuclear Information System (INIS)

Wang Jun; Yu Zheng-Feng

2012-01-01

In this paper, we use symbolic transfer entropy to study the coupling strength between premature signals. Numerical experiments show that three types of signal couplings are in the same direction. Among them, normal signal coupling is the strongest, followed by that of premature ventricular contractions, and that of atrial premature beats is the weakest. The T test shows that the entropies of the three signals are distinct. Symbolic transfer entropy requires less data, can distinguish the three types of signals and has very good computational efficiency. (interdisciplinary physics and related areas of science and technology)

Advances in oriental document analysis and recognition techniques

CERN Document Server

Lee, Seong-Whan

1999-01-01

In recent years, rapid progress has been made in computer processing of oriental languages, and the research developments in this area have resulted in tremendous changes in handwriting processing, printed oriental character recognition, document analysis and recognition, automatic input methodologies for oriental languages, etc. Advances in computer processing of oriental languages can also be seen in multimedia computing and the World Wide Web. Many of the results in those domains are presented in this book.

Analysis of MRI signal changes in the adjacent pedicle of adolescent patients with fresh lumbar spondylolysis.

Science.gov (United States)

Goda, Yuichiro; Sakai, Toshinori; Sakamaki, Tadanori; Takata, Yoichiro; Higashino, Kosaku; Sairyo, Koichi

2014-09-01

The purpose of this study is to investigate a discrepancy between MRI and computed tomography (CT) findings in the spinal level distribution of spondylolysis. Recent advances in MRI have led to the early diagnosis of spondylolysis. Therefore, bony healing can be expected before the condition has a chance to worsen. In this study, we used MRI to examine the changes in spinal level signals in the pedicles adjacent to the pars interarticularis in adolescents with fresh lumbar spondylolysis. We then compared spinal level distribution of spondylolysis with that of previous results obtained by multidetector CT. The study included 98 adolescent patients (31 women and 67 men; mean age, 13.6 years; age range, 9-18 years) with fresh lumbar spondylolysis who showed MRI signal changes in the adjacent pedicle. An MRI signal change was defined as a high signal change on fat-suppressed imaging. MRI signal changes were detected in 150 adjacent pedicles of 101 vertebrae. Of these vertebrae, MRI signal changes in only 67 (66.3%) corresponded to L5, while changes in 34 (33.7%) corresponded to L3 or L4. In our follow-up study, the bone-healing rate with no vertebral defect was 100% at L3, 97.1% at L4, and 84.4% at L5. In addition, 11 of 34 (32.4%) vertebrae with signal changes at L3 or L4 occurred with L5 terminal-stage spondylolysis (no MRI signal change). MRI revealed a higher prevalence of L3 or L4 spondylolysis than observed with CT.

Proteomic analysis of the signaling pathway mediated by the heterotrimeric Gα protein Pga1 of Penicillium chrysogenum.

Science.gov (United States)

Carrasco-Navarro, Ulises; Vera-Estrella, Rosario; Barkla, Bronwyn J; Zúñiga-León, Eduardo; Reyes-Vivas, Horacio; Fernández, Francisco J; Fierro, Francisco

2016-10-06

The heterotrimeric Gα protein Pga1-mediated signaling pathway regulates the entire developmental program in Penicillium chrysogenum, from spore germination to the formation of conidia. In addition it participates in the regulation of penicillin biosynthesis. We aimed to advance the understanding of this key signaling pathway using a proteomics approach, a powerful tool to identify effectors participating in signal transduction pathways. Penicillium chrysogenum mutants with different levels of activity of the Pga1-mediated signaling pathway were used to perform comparative proteomic analyses by 2D-DIGE and LC-MS/MS. Thirty proteins were identified which showed differences in abundance dependent on Pga1 activity level. By modifying the intracellular levels of cAMP we could establish cAMP-dependent and cAMP-independent pathways in Pga1-mediated signaling. Pga1 was shown to regulate abundance of enzymes in primary metabolic pathways involved in ATP, NADPH and cysteine biosynthesis, compounds that are needed for high levels of penicillin production. An in vivo phosphorylated protein containing a pleckstrin homology domain was identified; this protein is a candidate for signal transduction activity. Proteins with possible roles in purine metabolism, protein folding, stress response and morphogenesis were also identified whose abundance was regulated by Pga1 signaling. Thirty proteins whose abundance was regulated by the Pga1-mediated signaling pathway were identified. These proteins are involved in primary metabolism, stress response, development and signal transduction. A model describing the pathways through which Pga1 signaling regulates different cellular processes is proposed.

Advanced stress analysis of PWR containments in the region of nozzles

International Nuclear Information System (INIS)

Schauer, G.

1977-01-01

As an example of the stress analysis of a nozzle in a PWR steel containment, an advanced stress analysis of a personnel lock is presented. Contrary to the calculations by means of numerical shell programs usual till now, this advanced stress analysis was executed with the finite-element-method. Because of their theory, the shell programs compute mathematically exact results, but at the intersection of two shells the notch stresses cannot be analyzed well. A further disadvantage must be seen in the fact that there is a great distance between the real critical region near the intersection line and the calculation point, which lies on the neutral axis of the shell. The study shows that the results obtained to date which are based on the shell theory and calculate stresses at a fictitious intersection line can be improved and that there is a possibility to get stress values adjacent to the real intersection line. (Auth.)

Time-frequency feature analysis and recognition of fission neutrons signal based on support vector machine

International Nuclear Information System (INIS)

Jin Jing; Wei Biao; Feng Peng; Tang Yuelin; Zhou Mi

2010-01-01

Based on the interdependent relationship between fission neutrons ( 252 Cf) and fission chain ( 235 U system), the paper presents the time-frequency feature analysis and recognition in fission neutron signal based on support vector machine (SVM) through the analysis on signal characteristics and the measuring principle of the 252 Cf fission neutron signal. The time-frequency characteristics and energy features of the fission neutron signal are extracted by using wavelet decomposition and de-noising wavelet packet decomposition, and then applied to training and classification by means of support vector machine based on statistical learning theory. The results show that, it is effective to obtain features of nuclear signal via wavelet decomposition and de-noising wavelet packet decomposition, and the latter can reflect the internal characteristics of the fission neutron system better. With the training accomplished, the SVM classifier achieves an accuracy rate above 70%, overcoming the lack of training samples, and verifying the effectiveness of the algorithm. (authors)

Prediction of Chemoresistance in Women Undergoing Neo-Adjuvant Chemotherapy for Locally Advanced Breast Cancer: Volumetric Analysis of First-Order Textural Features Extracted from Multiparametric MRI.

Science.gov (United States)

Panzeri, M M; Losio, C; Della Corte, A; Venturini, E; Ambrosi, A; Panizza, P; De Cobelli, F

2018-01-01

To assess correlations between volumetric first-order texture parameters on baseline MRI and pathological response after neoadjuvant chemotherapy (NAC) for locally advanced breast cancer (BC). 69 patients with locally advanced BC candidate to neoadjuvant chemotherapy underwent MRI within 4 weeks from the start of therapeutic regimen. T2, DWI, and DCE sequences were analyzed and maps were generated for Apparent Diffusion Coefficient (ADC), T2 signal intensity, and the following dynamic parameters: k -trans, peak enhancement, area under curve (AUC), time to maximal enhancement (TME), wash-in rate, and washout rate. Volumetric analysis of these parameters was performed, yielding a histogram analysis including first-order texture kinetics (percentiles, maximum value, minimum value, range, standard deviation, mean, median, mode, skewness, and kurtosis). Finally, correlations between these values and response to NAC (evaluated on the surgical specimen according to RECIST 1.1 criteria) were assessed. Out of 69 tumors, 33 (47.8%) achieved complete pathological response, 26 (37.7%) partial response, and 10 (14.5%) no response. Higher levels of AUCmax ( p value = 0.0338), AUCrange ( p value = 0.0311), and TME 75 ( p value = 0.0452) and lower levels of washout 10 ( p value = 0.0417), washout 20 ( p value = 0.0138), washout 25 ( p value = 0.0114), and washout 30 ( p value = 0.05) were predictive of noncomplete response. Histogram-derived texture analysis of MRI images allows finding quantitative parameters predictive of nonresponse to NAC in women affected by locally advanced BC.

Bilinear Time-frequency Analysis for Lamb Wave Signal Detected by Electromagnetic Acoustic Transducer

Science.gov (United States)

Sun, Wenxiu; Liu, Guoqiang; Xia, Hui; Xia, Zhengwu

2018-03-01

Accurate acquisition of the detection signal travel time plays a very important role in cross-hole tomography. The experimental platform of aluminum plate under the perpendicular magnetic field is established and the bilinear time-frequency analysis methods, Wigner-Ville Distribution (WVD) and the pseudo-Wigner-Ville distribution (PWVD), are applied to analyse the Lamb wave signals detected by electromagnetic acoustic transducer (EMAT). By extracting the same frequency component of the time-frequency spectrum as the excitation frequency, the travel time information can be obtained. In comparison with traditional linear time-frequency analysis method such as short-time Fourier transform (STFT), the bilinear time-frequency analysis method PWVD is more appropriate in extracting travel time and recognizing patterns of Lamb wave.

Analysis of pulse-shape discrimination techniques for BC501A using GHz digital signal processing

International Nuclear Information System (INIS)

Rooney, B.D.; Dinwiddie, D.R.; Nelson, M.A.; Rawool-Sullivan, Mohini W.

2001-01-01

A comparison study of pulse-shape analysis techniques was conducted for a BC501A scintillator using digital signal processing (DSP). In this study, output signals from a preamplifier were input directly into a 1 GHz analog-to-digital converter. The digitized data obtained with this method was post-processed for both pulse-height and pulse-shape information. Several different analysis techniques were evaluated for neutron and gamma-ray pulse-shape discrimination. It was surprising that one of the simplest and fastest techniques resulted in some of the best pulse-shape discrimination results. This technique, referred to here as the Integral Ratio technique, was able to effectively process several thousand detector pulses per second. This paper presents the results and findings of this study for various pulse-shape analysis techniques with digitized detector signals.

Sentiment analysis for PTSD signals

CERN Document Server

Kagan, Vadim; Sapounas, Demetrios

2013-01-01

This book describes a computational framework for real-time detection of psychological signals related to Post-Traumatic Stress Disorder (PTSD) in online text-based posts, including blogs and web forums. Further, it explores how emerging computational techniques such as sentiment mining can be used in real-time to identify posts that contain PTSD-related signals, flag those posts, and bring them to the attention of psychologists, thus providing an automated flag and referral capability.

Tidal Analysis Using Time–Frequency Signal Processing and Information Clustering

Directory of Open Access Journals (Sweden)

Antonio M. Lopes

2017-07-01

Full Text Available Geophysical time series have a complex nature that poses challenges to reaching assertive conclusions, and require advanced mathematical and computational tools to unravel embedded information. In this paper, time–frequency methods and hierarchical clustering (HC techniques are combined for processing and visualizing tidal information. In a first phase, the raw data are pre-processed for estimating missing values and obtaining dimensionless reliable time series. In a second phase, the Jensen–Shannon divergence is adopted for measuring dissimilarities between data collected at several stations. The signals are compared in the frequency and time–frequency domains, and the HC is applied to visualize hidden relationships. In a third phase, the long-range behavior of tides is studied by means of power law functions. Numerical examples demonstrate the effectiveness of the approach when dealing with a large volume of real-world data.

Analysis and Classification of Acoustic Emission Signals During Wood Drying Using the Principal Component Analysis

Energy Technology Data Exchange (ETDEWEB)

Kang, Ho Yang [Korea Research Institute of Standards and Science, Daejeon (Korea, Republic of); Kim, Ki Bok [Chungnam National University, Daejeon (Korea, Republic of)

2003-06-15

In this study, acoustic emission (AE) signals due to surface cracking and moisture movement in the flat-sawn boards of oak (Quercus Variablilis) during drying under the ambient conditions were analyzed and classified using the principal component analysis. The AE signals corresponding to surface cracking showed higher in peak amplitude and peak frequency, and shorter in rise time than those corresponding to moisture movement. To reduce the multicollinearity among AE features and to extract the significant AE parameters, correlation analysis was performed. Over 99% of the variance of AE parameters could be accounted for by the first to the fourth principal components. The classification feasibility and success rate were investigated in terms of two statistical classifiers having six independent variables (AE parameters) and six principal components. As a result, the statistical classifier having AE parameters showed the success rate of 70.0%. The statistical classifier having principal components showed the success rate of 87.5% which was considerably than that of the statistical classifier having AE parameters

Analysis and Classification of Acoustic Emission Signals During Wood Drying Using the Principal Component Analysis

International Nuclear Information System (INIS)

Kang, Ho Yang; Kim, Ki Bok

2003-01-01

In this study, acoustic emission (AE) signals due to surface cracking and moisture movement in the flat-sawn boards of oak (Quercus Variablilis) during drying under the ambient conditions were analyzed and classified using the principal component analysis. The AE signals corresponding to surface cracking showed higher in peak amplitude and peak frequency, and shorter in rise time than those corresponding to moisture movement. To reduce the multicollinearity among AE features and to extract the significant AE parameters, correlation analysis was performed. Over 99% of the variance of AE parameters could be accounted for by the first to the fourth principal components. The classification feasibility and success rate were investigated in terms of two statistical classifiers having six independent variables (AE parameters) and six principal components. As a result, the statistical classifier having AE parameters showed the success rate of 70.0%. The statistical classifier having principal components showed the success rate of 87.5% which was considerably than that of the statistical classifier having AE parameters

An integrated approach for signal validation in nuclear power plants

International Nuclear Information System (INIS)

Upadhyaya, B.R.; Kerlin, T.W.; Gloeckler, O.; Frei, Z.; Qualls, L.; Morgenstern, V.

1987-08-01

A signal validation system, based on several parallel signal processing modules, is being developed at the University of Tennessee. The major modules perform (1) general consistency checking (GCC) of a set of redundant measurements, (2) multivariate data-driven modeling of dynamic signal components for maloperation detection, (3) process empirical modeling for prediction and redundancy generation, (4) jump, pulse, noise detection, and (5) an expert system for qualitative signal validation. A central database stores information related to sensors, diagnostics rules, past system performance, subsystem models, etc. We are primarily concerned with signal validation during steady-state operation and slow degradations. In general, the different modules will perform signal validation during all operating conditions. The techniques have been successfully tested using PWR steam generator simulation, and efforts are currently underway in applying the techniques to Millstone-III operational data. These methods could be implemented in advanced reactors, including advanced liquid metal reactors

Prospects for Observing and Localizing Gravitational-Wave Transients with Advanced LIGO and Advanced Virgo

Science.gov (United States)

Abbott, B. P.; Abbott, R.; Abbott, T. D.; Abernathy, M. R.; Acernese, F.; Ackley, K.; Adams, C.; Adams, T.; Addesso, P.; Adhikari, R. X.;

Prospects for Observing and Localizing Gravitational-Wave Transients with Advanced LIGO and Advanced Virgo

Science.gov (United States)

Abbott, B. P.; Abbott, R.; Abbott, T. D.; Abernathy, M. R.; Acernese, F.; Ackley, K.; Adams, C.; Adams, T.; Addesso, P.; Adhikari, R. X.; Adya, V. B.; Affeldt, C.; Agathos, M.; Agatsuma, K.; Aggarwal, N.; Aguiar, O. D.; Ain, A.; Ajith, P.; Allen, B.; Allocca, A.; Altin, P. A.; Amariutei, D. V.; Anderson, S. B.; Anderson, W. G.; Arai, K.; Araya, M. C.; Arceneaux, C. C.; Areeda, J. S.; Arnaud, N.; Arun, K. G.; Ashton, G.; Ast, M.; Aston, S. M.; Astone, P.; Aufmuth, P.; Aulbert, C.; Babak, S.; Baker, P. T.; Baldaccini, F.; Ballardin, G.; Ballmer, S. W.; Barayoga, J. C.; Barclay, S. E.; Barish, B. C.; Barker, D.; Barone, F.; Barr, B.; Barsotti, L.; Barsuglia, M.; Barta, D.; Bartlett, J.; Bartos, I.; Bassiri, R.; Basti, A.; Batch, J. C.; Baune, C.; Bavigadda, V.; Bazzan, M.; Behnke, B.; Bejger, M.; Belczynski, C.; Bell, A. S.; Bell, C. J.; Berger, B. K.; Bergman, J.; Bergmann, G.; Berry, C. P. L.; Bersanetti, D.; Bertolini, A.; Betzwieser, J.; Bhagwat, S.; Bhandare, R.; Bilenko, I. A.; Billingsley, G.; Birch, J.; Birney, R.; Biscans, S.; Bisht, A.; Bitossi, M.; Biwer, C.; Bizouard, M. A.; Blackburn, J. K.; Blair, C. D.; Blair, D.; Blair, R. M.; Bloemen, S.; Bock, O.; Bodiya, T. P.; Boer, M.; Bogaert, G.; Bogan, C.; Bohe, A.; Bojtos, P.; Bond, C.; Bondu, F.; Bonnand, R.; Bork, R.; Boschi, V.; Bose, S.; Bozzi, A.; Bradaschia, C.; Brady, P. R.; Braginsky, V. B.; Branchesi, M.; Brau, J. E.; Briant, T.; Brillet, A.; Brinkmann, M.; Brisson, V.; Brockill, P.; Brooks, A. F.; Brown, D. A.; Brown, D. D.; Brown, N. M.; Buchanan, C. C.; Buikema, A.; Bulik, T.; Bulten, H. J.; Buonanno, A.; Buskulic, D.; Buy, C.; Byer, R. L.; Cadonati, L.; Cagnoli, G.; Cahillane, C.; Calderón Bustillo, J.; Callister, T.; Calloni, E.; Camp, J. B.; Cannon, K. C.; Cao, J.; Capano, C. D.; Capocasa, E.; Carbognani, F.; Caride, S.; Casanueva Diaz, J.; Casentini, C.; Caudill, S.; Cavaglià, M.; Cavalier, F.; Cavalieri, R.; Cella, G.; Cepeda, C.; Cerboni Baiardi, L.; Cerretani, G.; Cesarini, E.; Chakraborty, R.; Chalermsongsak, T.; Chamberlin, S. J.; Chan, M.; Chao, S.; Charlton, P.; Chassande-Mottin, E.; Chen, H. Y.; Chen, Y.; Cheng, C.; Chincarini, A.; Chiummo, A.; Cho, H. S.; Cho, M.; Chow, J. H.; Christensen, N.; Chu, Q.; Chua, S.; Chung, S.; Ciani, G.; Clara, F.; Clark, J. A.; Cleva, F.; Coccia, E.; Cohadon, P.-F.; Colla, A.; Collette, C. G.; Constancio, M.; Conte, A.; Conti, L.; Cook, D.; Corbitt, T. R.; Cornish, N.; Corsi, A.; Cortese, S.; Costa, C. A.; Coughlin, M. W.; Coughlin, S. B.; Coulon, J.-P.; Countryman, S. T.; Couvares, P.; Coward, D. M.; Cowart, M. J.; Coyne, D. C.; Coyne, R.; Craig, K.; Creighton, J. D. E.; Cripe, J.; Crowder, S. G.; Cumming, A.; Cunningham, L.; Cuoco, E.; Dal Canton, T.; Danilishin, S. L.; D'Antonio, S.; Danzmann, K.; Darman, N. S.; Dattilo, V.; Dave, I.; Daveloza, H. P.; Davier, M.; Davies, G. S.; Daw, E. J.; Day, R.; DeBra, D.; Debreczeni, G.; Degallaix, J.; De Laurentis, M.; Deléglise, S.; Del Pozzo, W.; Denker, T.; Dent, T.; Dereli, H.; Dergachev, V.; DeRosa, R.; De Rosa, R.; DeSalvo, R.; Dhurandhar, S.; Díaz, M. C.; Di Fiore, L.; Di Giovanni, M.; Di Lieto, A.; Di Palma, I.; Di Virgilio, A.; Dojcinoski, G.; Dolique, V.; Donovan, F.; Dooley, K. L.; Doravari, S.; Douglas, R.; Downes, T. P.; Drago, M.; Drever, R. W. P.; Driggers, J. C.; Du, Z.; Ducrot, M.; Dwyer, S. E.; Edo, T. B.; Edwards, M. C.; Effler, A.; Eggenstein, H.-B.; Ehrens, P.; Eichholz, J. M.; Eikenberry, S. S.; Engels, W.; Essick, R. C.; Etzel, T.; Evans, M.; Evans, T. M.; Everett, R.; Factourovich, M.; Fafone, V.; Fair, H.; Fairhurst, S.; Fan, X.; Fang, Q.; Farinon, S.; Farr, B.; Farr, W. M.; Favata, M.; Fays, M.; Fehrmann, H.; Fejer, M. M.; Ferrante, I.; Ferreira, E. C.; Ferrini, F.; Fidecaro, F.; Fiori, I.; Fisher, R. P.; Flaminio, R.; Fletcher, M.; Fournier, J.-D.; Franco, S.; Frasca, S.; Frasconi, F.; Frei, Z.; Freise, A.; Frey, R.; Fricke, T. T.; Fritschel, P.; Frolov, V. V.; Fulda, P.; Fyffe, M.; Gabbard, H. A. G.; Gair, J. R.; Gammaitoni, L.; Gaonkar, S. G.; Garufi, F.; Gatto, A.; Gaur, G.; Gehrels, N.; Gemme, G.; Gendre, B.; Genin, E.; Gennai, A.; George, J.; Gergely, L.; Germain, V.; Ghosh, A.; Ghosh, S.; Giaime, J. A.; Giardina, K. D.; Giazotto, A.; Gill, K.; Glaefke, A.; Goetz, E.; Goetz, R.; Gondan, L.; González, G.; Gonzalez Castro, J. M.; Gopakumar, A.; Gordon, N. A.; Gorodetsky, M. L.; Gossan, S. E.; Gosselin, M.; Gouaty, R.; Graef, C.; Graff, P. B.; Granata, M.; Grant, A.; Gras, S.; Gray, C.; Greco, G.; Green, A. C.; Groot, P.; Grote, H.; Grunewald, S.; Guidi, G. M.; Guo, X.; Gupta, A.; Gupta, M. K.; Gushwa, K. E.; Gustafson, E. K.; Gustafson, R.; Hacker, J. J.; Hall, B. R.; Hall, E. D.; Hammond, G.; Haney, M.; Hanke, M. M.; Hanks, J.; Hanna, C.; Hannam, M. D.; Hanson, J.; Hardwick, T.; Harms, J.; Harry, G. M.; Harry, I. W.; Hart, M. J.; Hartman, M. T.; Haster, C.-J.; Haughian, K.; Heidmann, A.; Heintze, M. C.; Heitmann, H.; Hello, P.; Hemming, G.; Hendry, M.; Heng, I. S.; Hennig, J.; Heptonstall, A. W.; Heurs, M.; Hild, S.; Hoak, D.; Hodge, K. A.; Hofman, D.; Hollitt, S. E.; Holt, K.; Holz, D. E.; Hopkins, P.; Hosken, D. J.; Hough, J.; Houston, E. A.; Howell, E. J.; Hu, Y. M.; Huang, S.; Huerta, E. A.; Huet, D.; Hughey, B.; Husa, S.; Huttner, S. H.; Huynh-Dinh, T.; Idrisy, A.; Indik, N.; Ingram, D. R.; Inta, R.; Isa, H. N.; Isac, J.-M.; Isi, M.; Islas, G.; Isogai, T.; Iyer, B. R.; Izumi, K.; Jacqmin, T.; Jang, H.; Jani, K.; Jaranowski, P.; Jawahar, S.; Jiménez-Forteza, F.; Johnson, W. W.; Jones, D. I.; Jones, R.; Jonker, R. J. G.; Ju, L.; K, Haris; Kalaghatgi, C. V.; Kalogera, V.; Kandhasamy, S.; Kang, G.; Kanner, J. B.; Karki, S.; Kasprzack, M.; Katsavounidis, E.; Katzman, W.; Kaufer, S.; Kaur, T.; Kawabe, K.; Kawazoe, F.; Kéfélian, F.; Kehl, M. S.; Keitel, D.; Kelley, D. B.; Kells, W.; Kennedy, R.; Key, J. S.; Khalaidovski, A.; Khalili, F. Y.; Khan, S.; Khan, Z.; Khazanov, E. A.; Kijbunchoo, N.; Kim, C.; Kim, J.; Kim, K.; Kim, N.; Kim, N.; Kim, Y.-M.; King, E. J.; King, P. J.; Kinzel, D. L.; Kissel, J. S.; Kleybolte, L.; Klimenko, S.; Koehlenbeck, S. M.; Kokeyama, K.; Koley, S.; Kondrashov, V.; Kontos, A.; Korobko, M.; Korth, W. Z.; Kowalska, I.; Kozak, D. B.; Kringel, V.; Krishnan, B.; Królak, A.; Krueger, C.; Kuehn, G.; Kumar, P.; Kuo, L.; Kutynia, A.; Lackey, B. D.; Landry, M.; Lange, J.; Lantz, B.; Lasky, P. D.; Lazzarini, A.; Lazzaro, C.; Leaci, P.; Leavey, S.; Lebigot, E.; Lee, C. H.; Lee, H. K.; Lee, H. M.; Lee, K.; Lenon, A.; Leonardi, M.; Leong, J. R.; Leroy, N.; Letendre, N.; Levin, Y.; Levine, B. M.; Li, T. G. F.; Libson, A.; Littenberg, T. B.; Lockerbie, N. A.; Logue, J.; Lombardi, A. L.; Lord, J. E.; Lorenzini, M.; Loriette, V.; Lormand, M.; Losurdo, G.; Lough, J. D.; Lück, H.; Lundgren, A. P.; Luo, J.; Lynch, R.; Ma, Y.; MacDonald, T.; Machenschalk, B.; MacInnis, M.; Macleod, D. M.; Magana-Sandoval, F.; Magee, R. M.; Mageswaran, M.; Majorana, E.; Maksimovic, I.; Malvezzi, V.; Man, N.; Mandel, I.; Mandic, V.; Mangano, V.; Mansell, G. L.; Manske, M.; Mantovani, M.; Marchesoni, F.; Marion, F.; Márka, S.; Márka, Z.; Markosyan, A. S.; Maros, E.; Martelli, F.; Martellini, L.; Martin, I. W.; Martin, R. M.; Martynov, D. V.; Marx, J. N.; Mason, K.; Masserot, A.; Massinger, T. J.; Masso-Reid, M.; Matichard, F.; Matone, L.; Mavalvala, N.; Mazumder, N.; Mazzolo, G.; McCarthy, R.; McClelland, D. E.; McCormick, S.; McGuire, S. C.; McIntyre, G.; McIver, J.; McManus, D. J.; McWilliams, S. T.; Meacher, D.; Meadors, G. D.; Meidam, J.; Melatos, A.; Mendell, G.; Mendoza-Gandara, D.; Mercer, R. A.; Merilh, E.; Merzougui, M.; Meshkov, S.; Messenger, C.; Messick, C.; Meyers, P. M.; Mezzani, F.; Miao, H.; Michel, C.; Middleton, H.; Mikhailov, E. E.; Milano, L.; Miller, J.; Millhouse, M.; Minenkov, Y.; Ming, J.; Mirshekari, S.; Mishra, C.; Mitra, S.; Mitrofanov, V. P.; Mitselmakher, G.; Mittleman, R.; Moggi, A.; Mohan, M.; Mohapatra, S. R. P.; Montani, M.; Moore, B. C.; Moore, C. J.; Moraru, D.; Moreno, G.; Morriss, S. R.; Mossavi, K.; Mours, B.; Mow-Lowry, C. M.; Mueller, C. L.; Mueller, G.; Muir, A. W.; Mukherjee, Arunava; Mukherjee, D.; Mukherjee, S.; Mullavey, A.; Munch, J.; Murphy, D. J.; Murray, P. G.; Mytidis, A.; Nardecchia, I.; Naticchioni, L.; Nayak, R. K.; Necula, V.; Nedkova, K.; Nelemans, G.; Neri, M.; Neunzert, A.; Newton, G.; Nguyen, T. T.; Nielsen, A. B.; Nissanke, S.; Nitz, A.; Nocera, F.; Nolting, D.; Normandin, M. E. N.; Nuttall, L. K.; Oberling, J.; Ochsner, E.; O'Dell, J.; Oelker, E.; Ogin, G. H.; Oh, J. J.; Oh, S. H.; Ohme, F.; Oliver, M.; Oppermann, P.; Oram, Richard J.; O'Reilly, B.; O'Shaughnessy, R.; Ott, C. D.; Ottaway, D. J.; Ottens, R. S.; Overmier, H.; Owen, B. J.; Pai, A.; Pai, S. A.; Palamos, J. R.; Palashov, O.; Palomba, C.; Pal-Singh, A.; Pan, H.; Pankow, C.; Pannarale, F.; Pant, B. C.; Paoletti, F.; Paoli, A.; Papa, M. A.; Paris, H. R.; Parker, W.; Pascucci, D.; Pasqualetti, A.; Passaquieti, R.; Passuello, D.; Patrick, Z.; Pearlstone, B. L.; Pedraza, M.; Pedurand, R.; Pekowsky, L.; Pele, A.; Penn, S.; Pereira, R.; Perreca, A.; Phelps, M.; Piccinni, O.; Pichot, M.; Piergiovanni, F.; Pierro, V.; Pillant, G.; Pinard, L.; Pinto, I. M.; Pitkin, M.; Poggiani, R.; Post, A.; Powell, J.; Prasad, J.; Predoi, V.; Premachandra, S. S.; Prestegard, T.; Price, L. R.; Prijatelj, M.; Principe, M.; Privitera, S.; Prodi, G. A.; Prokhorov, L.; Punturo, M.; Puppo, P.; Pürrer, M.; Qi, H.; Qin, J.; Quetschke, V.; Quintero, E. A.; Quitzow-James, R.; Raab, F. J.; Rabeling, D. S.; Radkins, H.; Raffai, P.; Raja, S.; Rakhmanov, M.; Rapagnani, P.; Raymond, V.; Razzano, M.; Re, V.; Read, J.; Reed, C. M.; Regimbau, T.; Rei, L.; Reid, S.; Reitze, D. H.; Rew, H.; Ricci, F.; Riles, K.; Robertson, N. A.; Robie, R.; Robinet, F.; Rocchi, A.; Rolland, L.; Rollins, J. G.; Roma, V. J.; Romano, J. D.; Romano, R.; Romanov, G.; Romie, J. H.; Rosińska, D.; Rowan, S.; Rüdiger, A.; Ruggi, P.; Ryan, K.; Sachdev, S.; Sadecki, T.; Sadeghian, L.; Saleem, M.; Salemi, F.; Samajdar, A.; Sammut, L.; Sanchez, E. J.; Sandberg, V.; Sandeen, B.; Sanders, J. R.; Sassolas, B.; Sathyaprakash, B. S.; Saulson, P. R.; Sauter, O.; Savage, R. L.; Sawadsky, A.; Schale, P.; Schilling, R.; Schmidt, J.; Schmidt, P.; Schnabel, R.; Schofield, R. M. S.; Schönbeck, A.; Schreiber, E.; Schuette, D.; Schutz, B. F.; Scott, J.; Scott, S. M.; Sellers, D.; Sentenac, D.; Sequino, V.; Sergeev, A.; Serna, G.; Setyawati, Y.; Sevigny, A.; Shaddock, D. A.; Shah, S.; Shahriar, M. S.; Shaltev, M.; Shao, Z.; Shapiro, B.; Shawhan, P.; Sheperd, A.; Shoemaker, D. H.; Shoemaker, D. M.; Siellez, K.; Siemens, X.; Sigg, D.; Silva, A. D.; Simakov, D.; Singer, A.; Singer, L. P.; Singh, A.; Singh, R.; Sintes, A. M.; Slagmolen, B. J. J.; Smith, J. R.; Smith, N. D.; Smith, R. J. E.; Son, E. J.; Sorazu, B.; Sorrentino, F.; Souradeep, T.; Srivastava, A. K.; Staley, A.; Steinke, M.; Steinlechner, J.; Steinlechner, S.; Steinmeyer, D.; Stephens, B. C.; Stone, R.; Strain, K. A.; Straniero, N.; Stratta, G.; Strauss, N. A.; Strigin, S.; Sturani, R.; Stuver, A. L.; Summerscales, T. Z.; Sun, L.; Sutton, P. J.; Swinkels, B. L.; Szczepanczyk, M. J.; Tacca, M.; Talukder, D.; Tanner, D. B.; Tápai, M.; Tarabrin, S. P.; Taracchini, A.; Taylor, R.; Theeg, T.; Thirugnanasambandam, M. P.; Thomas, E. G.; Thomas, M.; Thomas, P.; Thorne, K. A.; Thorne, K. S.; Thrane, E.; Tiwari, S.; Tiwari, V.; Tokmakov, K. V.; Tomlinson, C.; Tonelli, M.; Torres, C. V.; Torrie, C. I.; Töyrä, D.; Travasso, F.; Traylor, G.; Trifirò, D.; Tringali, M. C.; Trozzo, L.; Tse, M.; Turconi, M.; Tuyenbayev, D.; Ugolini, D.; Unnikrishnan, C. S.; Urban, A. L.; Usman, S. A.; Vahlbruch, H.; Vajente, G.; Valdes, G.; van Bakel, N.; van Beuzekom, M.; van den Brand, J. F. J.; van den Broeck, C.; Vander-Hyde, D. C.; van der Schaaf, L.; van der Sluys, M. V.; van Heijningen, J. V.; van Veggel, A. A.; Vardaro, M.; Vass, S.; Vasúth, M.; Vaulin, R.; Vecchio, A.; Vedovato, G.; Veitch, J.; Veitch, P. J.; Venkateswara, K.; Verkindt, D.; Vetrano, F.; Viceré, A.; Vinciguerra, S.; Vine, D. J.; Vinet, J.-Y.; Vitale, S.; Vo, T.; Vocca, H.; Vorvick, C.; Vousden, W. D.; Vyatchanin, S. P.; Wade, A. R.; Wade, L. E.; Wade, M.; Walker, M.; Wallace, L.; Walsh, S.; Wang, G.; Wang, H.; Wang, M.; Wang, X.; Wang, Y.; Ward, R. L.; Warner, J.; Was, M.; Weaver, B.; Wei, L.-W.; Weinert, M.; Weinstein, A. J.; Weiss, R.; Welborn, T.; Wen, L.; Weßels, P.; Westphal, T.; Wette, K.; Whelan, J. T.; White, D. J.; Whiting, B. F.; Williams, R. D.; Williamson, A. R.; Willis, J. L.; Willke, B.; Wimmer, M. H.; Winkler, W.; Wipf, C. C.; Wittel, H.; Woan, G.; Worden, J.; Wright, J. L.; Wu, G.; Yablon, J.; Yam, W.; Yamamoto, H.; Yancey, C. C.; Yap, M. J.; Yu, H.; Yvert, M.; Zadrożny, A.; Zangrando, L.; Zanolin, M.; Zendri, J.-P.; Zevin, M.; Zhang, F.; Zhang, L.; Zhang, M.; Zhang, Y.; Zhao, C.; Zhou, M.; Zhou, Z.; Zhu, X. J.; Zucker, M. E.; Zuraw, S. E.; Zweizig, J.; LIGO Scientific Collaboration; Virgo Collaboration

2016-02-01

We present a possible observing scenario for the Advanced LIGO and Advanced Virgo gravitational-wave detectors over the next decade, with the intention of providing information to the astronomy community to facilitate planning for multi-messenger astronomy with gravitational waves. We determine the expected sensitivity of the network to transient gravitational-wave signals, and study the capability of the network to determine the sky location of the source. We report our findings for gravitational-wave transients, with particular focus on gravitational-wave signals from the inspiral of binary neutron-star systems, which are considered the most promising for multi-messenger astronomy. The ability to localize the sources of the detected signals depends on the geographical distribution of the detectors and their relative sensitivity, and 90% credible regions can be as large as thousands of square degrees when only two sensitive detectors are operational. Determining the sky position of a significant fraction of detected signals to areas of 5 deg2 to 20 deg2 will require at least three detectors of sensitivity within a factor of ˜ 2 of each other and with a broad frequency bandwidth. Should the third LIGO detector be relocated to India as expected, a significant fraction of gravitational-wave signals will be localized to a few square degrees by gravitational-wave observations alone.

CERN Technical Training 2003: Learning for the LHC! DISP-2003 - Digital Signal Processing

CERN Multimedia

2003-01-01

DISP-2003 is a two-term course given by CERN and University of Lausanne (UNIL) experts within the framework of the Technical Training Programme. The course will review the current techniques dealing with Digital Signal Processing, and it is intended for an audience who work or will work on digital signal processing aspects, and who need an introductory or refresher/update course. The course will be in English, with question and answers also in French. Spring 2 Term: DISP-2003: Advanced Digital Signal Processing 30 April 2003 - 21 May 2003, 4 lectures, Wednesdays afternoon. Attendance cost: 40.- CHF, registration required. Lecturers: Léonard Studer, UNIL; Laurent Deniau, AT-MTM; Elena Wildner, AT-MAS. Programme: Intelligent signal processing (ISP). Non-linear time series analysis. Image processing. Wavelets. Basic concepts and definitions have been introduced during the previous Spring 1 Term: DISP-2003: Introduction to Digital Signal Processing. DISP-2003 is open to all people interested, but registrat...

Transient signal analysis in power reactors by means of the wavelet technique

International Nuclear Information System (INIS)

Wentzeis, Luis

1999-01-01

The application of the wavelet technique, had enabled to study the time evolution of the properties (amplitude and frequency content) of a signals set, measured in the Embalse nuclear power plant (CANDU 600 M we), in the low frequency range and for different operating conditions. Particularly, by means of this technique, we studied the time evolution of the signals in the non-stationary state of the reactor (during a raise in power), where the Fourier analysis results inadequate. (author)

Status of advanced UT systems for the nuclear industry

International Nuclear Information System (INIS)

Behravesh, M.; Avioli, M.; Dau, G.; Liu, S.

1987-01-01

An advanced ultrasonic testing (UT) system is a configuration of hardware that includes some type of computer. The computer may be hardwired to perform specific functions or have appropriate software. It may typically be used for data acquisition, signal processing, image generation, pattern recognition and data analysis. Additionally, advanced systems have data storage and are, therefore, different from the standard transducer-pulser/receiver systems that rely on human filtering and written documentation of the filtered data. The number of systems becoming commercially available is growing each year. The NDE managers of utilities, the end users of these systems, are often faced with the decision as to What system is right for my inspection problem? Is an advanced UT system a cost effective way to go? To help this group, the Electric Power Research Institute (EPRI) has initiated a project whose end product will be a Utility NDE Manager's Guide to Advanced UT Systems. A short summary of the available data to date presented here. Tables are used to give an immediate overview of capabilities

Stochastic resonance is applied to quantitative analysis for weak chromatographic signal of glyburide in plasma

International Nuclear Information System (INIS)

Zhang Wei; Xiang Bingren; Wu Yanwei; Shang Erxin

2005-01-01

Based on the theory of stochastic resonance, a new method carried on the quantitive analysis to weak chromatographic signal of glyburide in plasma, which was embedded in the noise background and the signal-to-noise ratio (SNR) of HPLC-UV is enhanced remarkably. This method enhances the quantification limit to 1 ng ml -1 , which is the same as HPLC-MS, and makes it possible to detect the weak signal accurately by HPLC-UV, which was not suitable before. The results showed good recovery and linear range from 1 to 50 ng ml -1 of glyburide in plasma and the method can be used for quantitative analysis of glyburide

20% inlet header break analysis of Advanced Heavy Water Reactor

International Nuclear Information System (INIS)

Srivastava, A.; Gupta, S.K.; Venkat Raj, V.; Singh, R.; Iyer, K.

2001-01-01

The proposed Advanced Heavy Water Reactor (AHWR) is a 750 MWt vertical pressure tube type boiling light water cooled and heavy water moderated reactor. A passive design feature of this reactor is that the heat removal is achieved through natural circulation of primary coolant at all power levels, with no primary coolant pumps. Loss of coolant due to failure of inlet header results in depressurization of primary heat transport (PHT) system and containment pressure rise. Depressurization activates various protective and engineered safety systems like reactor trip, isolation condenser and advanced accumulator, limiting the consequences of the event. This paper discusses the thermal hydraulic transient analysis for evaluating the safety of the reactor, following 20% inlet header break using RELAP5/MOD3.2. For the analysis, the system is discretized appropriately to simulate possible flow reversal in one of the core paths during the transient. Various modeling aspects are discussed in this paper and predictions are made for different parameters like pressure, temperature, steam quality and flow in different parts of the Primary Heat Transport (PHT) system. Flow and energy discharges into the containment are also estimated for use in containment analysis. (author)

Analysis of Seasonal Signal in GPS Short-Baseline Time Series

Science.gov (United States)

Wang, Kaihua; Jiang, Weiping; Chen, Hua; An, Xiangdong; Zhou, Xiaohui; Yuan, Peng; Chen, Qusen

2018-04-01

Proper modeling of seasonal signals and their quantitative analysis are of interest in geoscience applications, which are based on position time series of permanent GPS stations. Seasonal signals in GPS short-baseline (paper, to better understand the seasonal signal in GPS short-baseline time series, we adopted and processed six different short-baselines with data span that varies from 2 to 14 years and baseline length that varies from 6 to 1100 m. To avoid seasonal signals that are overwhelmed by noise, each of the station pairs is chosen with significant differences in their height (> 5 m) or type of the monument. For comparison, we also processed an approximately zero baseline with a distance of pass-filtered (BP) noise is valid for approximately 40% of the baseline components, and another 20% of the components can be best modeled by a combination of the first-order Gauss-Markov (FOGM) process plus white noise (WN). The TEM displacements are then modeled by considering the monument height of the building structure beneath the GPS antenna. The median contributions of TEM to the annual amplitude in the vertical direction are 84% and 46% with and without additional parts of the monument, respectively. Obvious annual signals with amplitude > 0.4 mm in the horizontal direction are observed in five short-baselines, and the amplitudes exceed 1 mm in four of them. These horizontal seasonal signals are likely related to the propagation of daily/sub-daily TEM displacement or other signals related to the site environment. Mismodeling of the tropospheric delay may also introduce spurious seasonal signals with annual amplitudes of 5 and 2 mm, respectively, for two short-baselines with elevation differences greater than 100 m. The results suggest that the monument height of the additional part of a typical GPS station should be considered when estimating the TEM displacement and that the tropospheric delay should be modeled cautiously, especially with station pairs with

Acoustic signal analysis in the creeping discharge

International Nuclear Information System (INIS)

Nakamiya, T; Sonoda, Y; Tsuda, R; Ebihara, K; Ikegami, T

2008-01-01

We have previously succeeded in measuring the acoustic signal due to the dielectric barrier discharge and discriminating the dominant frequency components of the acoustic signal. The dominant frequency components appear over 20kHz of acoustic signal by the dielectric barrier discharge. Recently surface discharge control technology has been focused from practical applications such as ozonizer, NO X reactors, light source or display. The fundamental experiments are carried to examine the creeping discharge using the acoustic signal. When the high voltage (6kV, f = 10kHz) is applied to the electrode, the discharge current flows and the acoustic sound is generated. The current, voltage waveforms of creeping discharge and the sound signal detected by the condenser microphone are stored in the digital memory scope. In this scheme, Continuous Wavelet Transform (CWT) is applied to discriminate the acoustic sound of the micro discharge and the dominant frequency components are studied. CWT results of sound signal show the frequency spectrum of wideband up to 100kHz. In addition, the energy distributions of acoustic signal are examined by CWT

Programmable delay circuit for sparker signal analysis

Digital Repository Service at National Institute of Oceanography (India)

Pathak, D.

The sparker echo signal had been recorded along with the EPC recorder trigger on audio cassettes in a dual channel analog recorder. The sparker signal in the analog form had to be digitised for further signal processing techniques to be performed...

Detailed Analysis of Torque Ripple in High Frequency Signal Injection based Sensor less PMSM Drives

Directory of Open Access Journals (Sweden)

Ravikumar Setty A.

2017-01-01

Full Text Available High Frequency Signal Injection based techniques are robust and well proven to estimate the rotor position from stand still to low speed. However, Injected high frequency signal introduces, high frequency harmonics in the motor phase currents and results in significant Output Torque ripple. There is no detailed analysis exist in the literature, to study the effect of injected signal frequency on Torque ripple. Objective of this work is to study the Torque Ripple resulting from High Frequency signal injection in PMSM motor drives. Detailed MATLAB/Simulink simulations are carried to quantify the Torque ripple at different Signal frequencies.

New trends in applied harmonic analysis sparse representations, compressed sensing, and multifractal analysis

CERN Document Server

Cabrelli, Carlos; Jaffard, Stephane; Molter, Ursula

2016-01-01

This volume is a selection of written notes corresponding to courses taught at the CIMPA School: "New Trends in Applied Harmonic Analysis: Sparse Representations, Compressed Sensing and Multifractal Analysis". New interactions between harmonic analysis and signal and image processing have seen striking development in the last 10 years, and several technological deadlocks have been solved through the resolution of deep theoretical problems in harmonic analysis. New Trends in Applied Harmonic Analysis focuses on two particularly active areas that are representative of such advances: multifractal analysis, and sparse representation and compressed sensing. The contributions are written by leaders in these areas, and covers both theoretical aspects and applications. This work should prove useful not only to PhD students and postdocs in mathematics and signal and image processing, but also to researchers working in related topics.

Expert system for eddy current signal analysis: non destructive testing of steam generator tubings

International Nuclear Information System (INIS)

Benoist, B.

1991-01-01

Automatic analysis, by computer, of defect signals in steam generator tubes, based on Eddy current multifrequency technique, is must often inefficient due to pilgrim noise. The first step is to use a method that allows us to eleminate the noise: the adaptative interpolation. Thanks to this method, which ensures reliable data on each channel, the analysis can be realised by taking into account the data corresponding to each basic or mixed channel. By correlating these diverse data, we can class the signals according to two types of defects: single defects (symmetrical), multiple defects (several in the same place). The second step is to use an expert system which allows a reliable diagnosis for whatever family the defect belongs to. According to this classification, analysis is continued and results in the characterization of the defect. The expert system has already been developed with the general purpose application expert system shell SUPER, which is briefly described. The knowledge base (SOCRATE) and the specific tools developed for this application are thoroughly described. The first results obtained with signals corresponding to real defects, that have been recorded in different places, are presented and discussed. The expert system is revealed efficient in all the studied cases, even with signals obtained in very noisy environments [fr

A Comparison of Physiological Signal Analysis Techniques and Classifiers for Automatic Emotional Evaluation of Audiovisual Contents.

Science.gov (United States)

Colomer Granero, Adrián; Fuentes-Hurtado, Félix; Naranjo Ornedo, Valery; Guixeres Provinciale, Jaime; Ausín, Jose M; Alcañiz Raya, Mariano

2016-01-01

This work focuses on finding the most discriminatory or representative features that allow to classify commercials according to negative, neutral and positive effectiveness based on the Ace Score index. For this purpose, an experiment involving forty-seven participants was carried out. In this experiment electroencephalography (EEG), electrocardiography (ECG), Galvanic Skin Response (GSR) and respiration data were acquired while subjects were watching a 30-min audiovisual content. This content was composed by a submarine documentary and nine commercials (one of them the ad under evaluation). After the signal pre-processing, four sets of features were extracted from the physiological signals using different state-of-the-art metrics. These features computed in time and frequency domains are the inputs to several basic and advanced classifiers. An average of 89.76% of the instances was correctly classified according to the Ace Score index. The best results were obtained by a classifier consisting of a combination between AdaBoost and Random Forest with automatic selection of features. The selected features were those extracted from GSR and HRV signals. These results are promising in the audiovisual content evaluation field by means of physiological signal processing.

Empirical Analysis and Characterization of Indoor GPS Signal Fading and Multipath Conditions

DEFF Research Database (Denmark)

Blunck, Henrik; Kjærgaard, Mikkel Baun; Godsk, Torben

2009-01-01

of earlier measurement campaigns to characterize GNSS signal conditions in indoor environments have been published prominently in the GNSS research literature, see, e.g. [1,2,3]. To allow for in-depth signal analysis, these campaigns use a variety of measuring machinery such as channel sounders, mobile...... signal generators and spectrum analyzers. Furthermore, the use-case-specific usability of GPS as an indoor positioning technology as been evaluated empirically on a higher level, see, e.g. [4]. In this paper we present results of a measurement campaign, designed to characterize indoor GNSS signal...... conditions. The work presented can therefore be seen as an effort to the campaigns mentioned above. As the focus of our work lies on the real-world usability of current GNSS technology for indoor use, we employ in our measurement campaign foremost commercial receivers with features, typical for the use cases...

Advances in fMRI Real-Time Neurofeedback.

Science.gov (United States)

Watanabe, Takeo; Sasaki, Yuka; Shibata, Kazuhisa; Kawato, Mitsuo

2017-12-01

Functional magnetic resonance imaging (fMRI) neurofeedback is a type of biofeedback in which real-time online fMRI signals are used to self-regulate brain function. Since its advent in 2003 significant progress has been made in fMRI neurofeedback techniques. Specifically, the use of implicit protocols, external rewards, multivariate analysis, and connectivity analysis has allowed neuroscientists to explore a possible causal involvement of modified brain activity in modified behavior. These techniques have also been integrated into groundbreaking new neurofeedback technologies, specifically decoded neurofeedback (DecNef) and functional connectivity-based neurofeedback (FCNef). By modulating neural activity and behavior, DecNef and FCNef have substantially advanced both basic and clinical research. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Multidimensional Signal Processing for Sensing & Communications

Science.gov (United States)

2015-07-29

Spectrum Sensing,” submitted to IEEE Intl. Workshop on Computational Advances in Multi-Sensor Adaptive Processing, Cancun, Mexico , 13-16 Dec. 2015...Sensing,” submitted to IEEE Intl. Workshop on Computational Advances in Multi-Sensor Adaptive Processing, Cancun, Mexico , 13-16 Dec. 2015...diversity in echolocating mammals ,” IEEE Signal Processing Magazine, vol. 26, no. 1, pp. 65- 75, Jan. 2009. DISTRIBUTION A: Distribution approved for

Canonical Wnt signaling in diabetic retinopathy.

Science.gov (United States)

Chen, Qian; Ma, Jian-Xing

2017-10-01

Diabetic retinopathy (DR) is a common eye complication of diabetes, and the pathogenic mechanism of DR is still under investigation. The canonical Wnt signaling pathway is an evolutionarily conserved pathway that plays fundamental roles in embryogenesis and adult tissue homeostasis. Wnt signaling regulates expression of multiple genes that control retinal development and eye organogenesis, and dysregulated Wnt signaling plays pathophysiological roles in many ocular diseases, including DR. This review highlights recent progress in studies of Wnt signaling in DR. We discuss Wnt signaling regulation in the retina and dysregulation of Wnt signaling associated with ocular diseases with an emphasis on DR. We also discuss the therapeutic potential of modulating Wnt signaling in DR. Continued studies in this field will advance our current understanding on DR and contribute to the development of new treatments. Copyright © 2017 Elsevier Ltd. All rights reserved.

Electromagnetic modeling method for eddy current signal analysis

International Nuclear Information System (INIS)

Lee, D. H.; Jung, H. K.; Cheong, Y. M.; Lee, Y. S.; Huh, H.; Yang, D. J.

2004-10-01

An electromagnetic modeling method for eddy current signal analysis is necessary before an experiment is performed. Electromagnetic modeling methods consists of the analytical method and the numerical method. Also, the numerical methods can be divided by Finite Element Method(FEM), Boundary Element Method(BEM) and Volume Integral Method(VIM). Each modeling method has some merits and demerits. Therefore, the suitable modeling method can be chosen by considering the characteristics of each modeling. This report explains the principle and application of each modeling method and shows the comparison modeling programs

Advanced TCA Backplane Tester

CERN Document Server

Oltean, Alexandra Dana

2004-01-01

At the beginning of 2003, the PICMG group adopted the AdvancedTCA (Advanced Telecom Computing Architecture) standard. The 10Gb/s backplane of the AdvancedTCA chassis is well specified in the standard but it remains however a high end product, which can be itself subject to printed circuit board manufacturing control problems that could greatly affect its quality control. In order to study the practical aspects of high speed Ethernet switching at 10Gb/s and to validate the signal integrity of the AdvancedTCA backplane, we developed a Backplane Tester. The tester system is able of running monitored PRBS traffic at 3.125Gb/s over every link on the AdvancedTCA backplane simultaneously and to monitor any possible connectivity failure immediately in terms of link and slot position inside the chassis. The present report presents the architectural hardware design, the control structure and software aspects of the AdvancedTCA Backplane Tester design.

Advanced Technology Lifecycle Analysis System (ATLAS)

Science.gov (United States)

O'Neil, Daniel A.; Mankins, John C.

2004-01-01

Developing credible mass and cost estimates for space exploration and development architectures require multidisciplinary analysis based on physics calculations, and parametric estimates derived from historical systems. Within the National Aeronautics and Space Administration (NASA), concurrent engineering environment (CEE) activities integrate discipline oriented analysis tools through a computer network and accumulate the results of a multidisciplinary analysis team via a centralized database or spreadsheet Each minute of a design and analysis study within a concurrent engineering environment is expensive due the size of the team and supporting equipment The Advanced Technology Lifecycle Analysis System (ATLAS) reduces the cost of architecture analysis by capturing the knowledge of discipline experts into system oriented spreadsheet models. A framework with a user interface presents a library of system models to an architecture analyst. The analyst selects models of launchers, in-space transportation systems, and excursion vehicles, as well as space and surface infrastructure such as propellant depots, habitats, and solar power satellites. After assembling the architecture from the selected models, the analyst can create a campaign comprised of missions spanning several years. The ATLAS controller passes analyst specified parameters to the models and data among the models. An integrator workbook calls a history based parametric analysis cost model to determine the costs. Also, the integrator estimates the flight rates, launched masses, and architecture benefits over the years of the campaign. An accumulator workbook presents the analytical results in a series of bar graphs. In no way does ATLAS compete with a CEE; instead, ATLAS complements a CEE by ensuring that the time of the experts is well spent Using ATLAS, an architecture analyst can perform technology sensitivity analysis, study many scenarios, and see the impact of design decisions. When the analyst is

Analysis of acoustic sound signal for ONB measurement

International Nuclear Information System (INIS)

Park, S. J.; Kim, H. I.; Han, K. Y.; Chai, H. T.; Park, C.

2003-01-01

The onset of nucleate boiling (ONB) was measured in a test fuel bundle composed of several fuel element simulators (FES) by analysing the aquatic sound signals. In order measure ONBs, a hydrophone, a pre-amplifier, and a data acquisition system to acquire/process the aquatic signal was prepared. The acoustic signal generated in the coolant is converted to the current signal through the microphone. When the signal is analyzed in the frequency domain, each sound signal can be identified according to its origin of sound source. As the power is increased to a certain degree, a nucleate boiling is started. The frequent formation and collapse of the void bubbles produce sound signal. By measuring this sound signal one can pinpoint the ONB. Since the signal characteristics is identical for different mass flow rates, this method can be applicable for ascertaining ONB

Preliminary code development for seismic signal analysis related to test ban treaty questions

International Nuclear Information System (INIS)

Brolley, J.E.

1977-01-01

Forensic seismology, from a present day viewpoint, appears to be divided into several areas. Overwhelmingly important, in view of current Complete Test Ban (CTB) discussions, is the seismological study of waves generated in the earth by underground nuclear explosions. Over the last two decades intensive effort has been devoted to developing improved observational apparatus and to the interpretation of the data produced by this equipment. It is clearly desirable to extract the maximum amount of information from seismic signals. It is, therefore, necessary to quantitatively compare various modes of analysis to establish which mode or combination of modes provides the most useful information. Preliminary code development for application of some modern developments in signal processing to seismic signals is described. Applications of noncircular functions are considered and compared with circular function results. The second portion of the discussion concerns maximum entropy analysis. Lastly, the multivariate aspects of the general problem are considered

Advanced biofeedback from surface electromyography signals using fuzzy system

DEFF Research Database (Denmark)