Search results for: low frequency noise

Authors: Arvind Kumar, Manoj Kumar, Dattatraya H. Nagaraj, Amanpreet Singh, Jayanthi Prattapati

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In recent years, the use of renewable energy resources instead of pollutant fossil fuels and other forms has increased. Photovoltaic generation is becoming increasingly important as a renewable resource since it does not cause in fuel costs, pollution, maintenance, and emitting noise compared with other alternatives used in power applications. In this paper, Perturb and Observe and Incremental Conductance methods are used to improve energy conversion efficiency under different environmental conditions. PI controllers are used to control easily DC-link voltage, active and reactive currents. The whole system is simulated under standard climatic conditions (1000 W/m2, 250C) in MATLAB and the irradiance is varied from 1000 W/m2 to 300 W/m2. The use of PI controller makes it easy to directly control the power of the grid connected PV system. Finally the validity of the system will be verified through the simulations in MATLAB/Simulink environment.

Keywords: incremental conductance algorithm, modeling of PV panel, perturb and observe algorithm, photovoltaic system and simulation results

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Authors: Mohamed A. Baba, Gazy Rodowan, Brigita Abakevičienė, Sigitas Tamulevičius, Bartlomiej Lemieszek, Sebastian Molin, Tomas Tamulevičius

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Solid oxide fuel cells (SOFC) efficiently convert hydrogen to energy without producing any disturbances or contaminants. The core of the cell is electrolyte. For improving the performance of electrolyte-supported cells, it is desirable to extend the available exchange surface area by micro-structuring of the electrolyte with laser-based micromachining. This study investigated the electrochemical performance of cells micro machined using a femtosecond laser. Commercial ceramic SOFC (Elcogen, AS) with a total thickness of 400 μm was structured by 1030 nm wavelength Yb: KGW fs-laser Pharos (Light Conversion) using 100 kHz repetition frequency and 290 fs pulse length light by scanning with the galvanometer scanner (ScanLab) and focused with a f-Theta telecentric lens (SillOptics). The sample height was positioned using a motorized z-stage. The microstructures were formed using a laser spiral trepanning in Ni/YSZ anode supported membrane at the central part of the ceramic piece of 5.5 mm diameter at active area of the cell. All surface was drilled with 275 µm diameter holes spaced by 275 µm. The machining processes were carried out under ambient conditions. The microstructural effects of the femtosecond laser treatment on the electrolyte surface were investigated prior to the electrochemical characterisation using a scanning electron microscope (SEM) Quanta 200 FEG (FEI). The Novo control Alpha-A was used for electrochemical impedance spectroscopy on a symmetrical cell configuration with an excitation amplitude of 25 mV and a frequency range of 1 MHz to 0.1 Hz. The fuel cell characterization of the cell was examined on open flanges test setup by Fiaxell. Using nickel mesh on the anode side and au mesh on the cathode side, the cell was electrically linked. The cell was placed in a Kittec furnace with a Process IDentifier temperature controller. The wires were connected to a Solartron 1260/1287 frequency analyzer for the impedance and current-voltage characterization. In order to determine the impact of the anode's microstructure on the performance of the commercial cells, the acquired results were compared to cells with unstructured anode. Geometrical studies verified that the depth of the -holes increased linearly according to laser energy and scanning times. On the other hand, it reduced as the scanning speed increased. The electrochemical analysis demonstrates that the open circuit voltage OCV values of the two cells are equal. Further, the modified cell's initial slope reduces to 0.209 from 0.253 of the unmodified cell, revealing that the surface modification considerably decreases energy loss. Plus, the maximum power density for the cell with the microstructure and the reference cell respectively, are 1.45 and 1.16 Wcm⁻².

Keywords: electrochemical performance, electrolyte-supported cells, laser micro-structuring, solid oxide fuel cells

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Authors: Mandeep Kumar, Hari Singh

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The effective optimization of machining process parameters affects dramatically the cost and production time of machined components as well as the quality of the final products. This paper presents the optimization aspects of a Wire Electrical Discharge Machining operation using Inconel X-750 as work material. The objective considered in this study is minimization of the dimensional deviation. Six input process parameters of WEDM namely spark gap voltage, pulse-on time, pulse-off time, wire feed rate, peak current and wire tension, were chosen as variables to study the process performance. Taguchi's design of experiments methodology has been used for planning and designing the experiments. The analysis of variance was carried out for raw data as well as for signal to noise ratio. Four input parameters and one two-factor interaction have been found to be statistically significant for their effects on the response of interest. The confirmation experiments were also performed for validating the predicted results.

Keywords: ANOVA, DOE, inconel, machining, optimization

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Authors: Hyun-Woo Cho

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Unexpected operational events or abnormalities of industrial processes have a serious impact on the quality of final product of interest. In terms of statistical process control, fault detection and diagnosis of processes is one of the essential tasks needed to run the process safely. In this work, nonlinear representation of process measurement data is presented and evaluated using a simulation process. The effect of using different representation methods on the diagnosis performance is tested in terms of computational efficiency and data handling. The results have shown that the nonlinear representation technique produced more reliable diagnosis results and outperforms linear methods. The use of data filtering step improved computational speed and diagnosis performance for test data sets. The presented scheme is different from existing ones in that it attempts to extract the fault pattern in the reduced space, not in the original process variable space. Thus this scheme helps to reduce the sensitivity of empirical models to noise.

Keywords: fault diagnosis, nonlinear technique, process data, reduced spaces

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Authors: Kim Lytle, Tim Talty, Alan Michaels, Jeff Reed

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Implantable medical devices (IMDs) are medically necessary devices embedded in the human body that monitor chronic disorders or automatically deliver therapies. Most IMDs have wireless capabilities that allow them to share data with an offboard programming device to help medical providers monitor the patient’s health while giving the patient more insight into their condition. However, serious security concerns have arisen as researchers demonstrated these devices could be hacked to obtain sensitive information or harm the patient. Cooperative jamming can be used to prevent privileged information leaks by maintaining an adequate signal-to-noise ratio at the intended receiver while minimizing signal power elsewhere. This paper uses ray tracing to demonstrate how a low number of friendly nodes abiding by Bluetooth Low Energy (BLE) transmission regulations can enhance IMD communication security in an office environment, which in turn may inform how companies and individuals can protect their proprietary and personal information.

Keywords: implantable biomedical devices, communication system security, array signal processing, ray tracing

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Authors: Yushuai Wang, Feng Xu, Junbo Tan, Xueqian Wang, Bin Liang

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In this paper, a sensor fault-tolerant control (FTC) scheme using robust model predictive control (RMPC) and set theoretic fault detection and isolation (FDI) is extended to linear parameter varying (LPV) systems. First, a group of set-valued observers are designed for passive fault detection (FD) and the observer gains are obtained through minimizing the size of invariant set of state estimation-error dynamics. Second, an input set for fault isolation (FI) is designed offline through set theory for actively isolating faults after FD. Third, an RMPC controller based on state estimation for LPV systems is designed to control the system in the presence of disturbance and measurement noise and tolerate faults. Besides, an FTC algorithm is proposed to maintain the plant operate in the corresponding mode when the fault occurs. Finally, a numerical example is used to show the effectiveness of the proposed results.

Keywords: fault detection, linear parameter varying, model predictive control, set theory

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Authors: Mohamed Hafid, Marcel Lacroix

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This study presents an inverse analysis for predicting the thermal conductivities and the heat flux of a high-temperature metallurgical reactor simultaneously. Once these thermal parameters are predicted, the time-varying thickness of the protective phase-change bank that covers the inside surface of the brick walls of a metallurgical reactor can be calculated. The enthalpy method is used to solve the melting/solidification process of the protective bank. The inverse model rests on the Levenberg-Marquardt Method (LMM) combined with the Broyden method (BM). A statistical analysis for the thermal parameter estimation is carried out. The effect of the position of the temperature sensors, total number of measurements and measurement noise on the accuracy of inverse predictions is investigated. Recommendations are made concerning the location of temperature sensors.

Keywords: inverse heat transfer, phase change, metallurgical reactor, Levenberg–Marquardt method, Broyden method, bank thickness

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Authors: Elia Efraim, Boris Blostotsky

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The phenomenon of buckling of structural elements under compression is revealed in many cases of loading and found consideration in many structures and mechanisms. In the present work the method and results of dynamic test for buckling of bar loaded by a compression force directed towards the pole are considered. Experimental determination of critical force for such system has not been made previously. The tested object is a bar with semi-rigid connection to the base at one of its ends, and with a hinge moving along a circle at the other. The test includes measuring the natural frequency of the bar at different values of compression load. The lateral stiffness is calculated based on natural frequency and reduced mass on the bar's movable end. The critical load is determined by extrapolation the values of lateral stiffness up to zero value. For the experimental investigation the special test-bed was created that allows the stability testing at positive and negative curvature of the movable end's trajectory, as well as varying the rotational stiffness of the other end connection. Decreasing a friction at the movable end allows extend the diapason of applied compression force. The testing method includes : - methodology of the experiment planning, that allows determine the required number of tests under various loads values in the defined range and the type of extrapolating function; - methodology of experimental determination of reduced mass at the bar's movable end including its own mass; - methodology of experimental determination of lateral stiffness of uncompressed bar rotational semi-rigid connection at the base. For planning the experiment and for comparison of the experimental results with the theoretical values of critical load, the analytical dependencies of lateral stiffness of the bar with defined end conditions on compression load. In the particular case of perfectly rigid connection of the bar to the base, the critical load value corresponds to solution by S.P. Timoshenko. Correspondence of the calculated and experimental values was obtained.

Keywords: buckling, dynamic method, end-fixity factor, force directed towards a pole

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Authors: Ruichong Zhang, Fadi Sawaged, Lotfi Gargab

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This paper introduces a wave-based approach for system identification of high-rise building structures with a pair of seismic recordings, which can be used to evaluate structural integrity and detect damage in post-earthquake structural condition assessment. The fundamental of the approach is based on wave features of generalized impulse and frequency response functions (GIRF and GFRF), i.e., wave responses at one structural location to an impulsive motion at another reference location in time and frequency domains respectively. With a pair of seismic recordings at the two locations, GFRF is obtainable as Fourier spectral ratio of the two recordings, and GIRF is then found with the inverse Fourier transformation of GFRF. With an appropriate continuous model for the structure, a closed-form solution of GFRF, and subsequent GIRF, can also be found in terms of wave transmission and reflection coefficients, which are related to structural physical properties above the impulse location. Matching the two sets of GFRF and/or GIRF from recordings and the model helps identify structural parameters such as wave velocity or shear modulus. For illustration, this study examines ten-story Millikan Library in Pasadena, California with recordings of Yorba Linda earthquake of September 3, 2002. The building is modelled as piecewise continuous layers, with which GFRF is derived as function of such building parameters as impedance, cross-sectional area, and damping. GIRF can then be found in closed form for some special cases and numerically in general. Not only does this study reveal the influential factors of building parameters in wave features of GIRF and GRFR, it also shows some system-identification results, which are consistent with other vibration- and wave-based results. Finally, this paper discusses the effectiveness of the proposed model in system identification.

Keywords: wave-based approach, seismic responses of buildings, wave propagation in structures, construction

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Authors: Md Al Masum Bhuiyan, Maria C. Mariani, Osei K. Tweneboah

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In the present work, we develop a technique for estimating the volatility of financial time series by using stochastic differential equation. Taking the daily closing prices from developed and emergent stock markets as the basis, we argue that the incorporation of stochastic volatility into the time-varying parameter estimation significantly improves the forecasting performance via Maximum Likelihood Estimation. While using the technique, we see the long-memory behavior of data sets and one-step-ahead-predicted log-volatility with ±2 standard errors despite the variation of the observed noise from a Normal mixture distribution, because the financial data studied is not fully Gaussian. Also, the Ornstein-Uhlenbeck process followed in this work simulates well the financial time series, which aligns our estimation algorithm with large data sets due to the fact that this algorithm has good convergence properties.

Keywords: financial time series, maximum likelihood estimation, Ornstein-Uhlenbeck type models, stochastic volatility model

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Authors: Mst. Nilufa Sultana, Shatirah Akib, Muhammad Aqeel Ashraf, Mohamed Roseli Zainal Abidin

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Most people today are aware that global Climate change, is not just a scientific theory but also a fact with worldwide consequences. Global climate change is due to rapid urbanization, industrialization, high population growth and current vulnerability of the climatic condition. Water is becoming scarce as a result of global climate change. To mitigate the problem arising due to global climate change and its drought effect, harvesting rainwater from green roofs, an environmentally-friendly and versatile technology, is becoming one of the best assessment criteria and gaining attention in Malaysia. This paper addresses the sustainability of green roofs and examines the quality of water harvested from green roofs in comparison to rainwater. The factors that affect the quality of such water, taking into account, for example, roofing materials, climatic conditions, the frequency of rainfall frequency and the first flush. A green roof was installed on the Humid Tropic Centre (HTC) is a place of the study on monitoring program for urban Stormwater Management Manual for Malaysia (MSMA), Eco-Hydrological Project in Kualalumpur, and the rainwater was harvested and evaluated on the basis of four parameters i.e., conductivity, dissolved oxygen (DO), pH and temperature. These parameters were found to fall between Class I and Class III of the Interim National Water Quality Standards (INWQS) and the Water Quality Index (WQI). Some preliminary treatment such as disinfection and filtration could likely to improve the value of these parameters to class I. This review paper clearly indicates that there is a need for more research to address other microbiological and chemical quality parameters to ensure that the harvested water is suitable for use potable water for domestic purposes. The change in all physical, chemical and microbiological parameters with respect to storage time will be a major focus of future studies in this field.

Keywords: Green roofs, INWQS, MSMA-SME, rainwater harvesting, water treatment, water quality parameter, WQI

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Authors: Fuad Noman, Sh-Hussain Salleh, Chee-Ming Ting, Hadri Hussain, Syed Rasul

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In this paper, a data-driven dictionary approach is proposed for the automatic detection and classification of cardiovascular abnormalities. Electrocardiography (ECG) signal is represented by the trained complete dictionaries that contain prototypes or atoms to avoid the limitations of pre-defined dictionaries. The data-driven trained dictionaries simply take the ECG signal as input rather than extracting features to study the set of parameters that yield the most descriptive dictionary. The approach inherently learns the complicated morphological changes in ECG waveform, which is then used to improve the classification. The classification performance was evaluated with ECG data under two different preprocessing environments. In the first category, QT-database is baseline drift corrected with notch filter and it filters the 60 Hz power line noise. In the second category, the data are further filtered using fast moving average smoother. The experimental results on QT database confirm that our proposed algorithm shows a classification accuracy of 92%.

Keywords: electrocardiogram, dictionary learning, sparse coding, classification

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Authors: Adebayo Emmanuel Layi

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Library and Information Science Education is about six (6) decades old in Nigeria. The first Library School was established in 1962 at the University of Ibadan, and since then, several institutions have been running the programme under various certifications, providing the manpower needs of professionals for libraries. As at June 2023, Nigeria has close to a thousand (1000) tertiary institutions and all needing the services of librarians. Apart from the tertiary institutions, several libraries exit in various establishments, both government, private and non-governmental organisations. These has underscored the enormous need for trained librarians for the libraries in these places. The Nexus between LIS Education training and Practice is like a puzzle of egg and chick, which one came first and against this background, this paper examined the roles of the colonial masters in educational development in Africa and vis-à-vis the influence of great library educators such as Melvil Dewey and other educators and the journey through Nigeria institutions. Despite the sound footing of LIS Education, Noise which seems to be a major obstacle on the practice as well as mending the broken link were all examined in the paper. Strategies and the way forward for overall development are suggested.

Keywords: nexus, education, training, synergy

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Authors: Ci Lin, Tet Yeap, Iluju Kiringa

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This paper introduces the subspace rotation algorithm (SRA) to train the Restricted Hopfield Network (RHN) as an auto-associative memory. Subspace rotation algorithm is a gradient-free subspace tracking approach based on the singular value decomposition (SVD). In comparison with Backpropagation Through Time (BPTT) on training RHN, it is observed that SRA could always converge to the optimal solution and BPTT could not achieve the same performance when the model becomes complex, and the number of patterns is large. The AUTS case study showed that the RHN model trained by SRA could achieve a better structure of attraction basin with larger radius(in general) than the Hopfield Network(HNN) model trained by Hebbian learning rule. Through learning 10000 patterns from MNIST dataset with RHN models with different number of hidden nodes, it is observed that an several components could be adjusted to achieve a balance between recovery accuracy and noise resistance.

Keywords: hopfield neural network, restricted hopfield network, subspace rotation algorithm, hebbian learning rule

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Authors: Yakup Sahin, Naim Suleyman Ting, Ismail Aksoy

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In this paper, an improved active snubber cell is proposed on account of soft switching (SS) family of pulse width modulation (PWM) DC-DC converters. The improved snubber cell provides zero-voltage transition (ZVT) turn on and zero-current transition (ZCT) turn off for main switch. The snubber cell decreases EMI noise and operates with SS in a wide range of line and load voltages. Besides, all of the semiconductor devices in the converter operate with SS. There is no additional voltage and current stress on the main devices. Additionally, extra voltage stress does not occur on the auxiliary switch and its current stress is acceptable value. The improved converter has a low cost and simple structure. The theoretical analysis of converter is clarified and the operating states are given in detail. The experimental results of converter are obtained by prototype of 500 W and 100 kHz. It is observed that the experimental results and theoretical analysis of converter are suitable with each other perfectly.

Keywords: active snubber cells, DC-DC converters, zero-voltage transition, zero-current transition

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Authors: Syed Ali Shahbaz Shah

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In the last few years, Bituminous Asphaltic roads are becoming popular day by day in the world. Plenty of research has been carried out to identify many advantages like safety, environmental effects, and comfort. Some other benefits are minimal noise and skid resistance enhancement. Besides the benefits of asphaltic roads, the permeable structure of the road also causes some distress, and raveling is one of the crucial defects. The main reason behind this distress is the failure of adhesion between bitumen mortar, specifically due to excessive load from heavy traffic. The main focus of this study is to identify the root cause and propose both the long-term and the short-term solutions of raveling on a specific road section depicting the overall road situation from the bridge of Kahuta road towards the intersection of the Islamabad express highway. The methodology adopted for this purpose is visual inspections in-situ. It was noted that there were chunks of debris on the road surface, which indicates that the asphalt binder is aged the most probably. Further laboratory testing would confirm that either asphalt binder is aged or inadequate compaction was adept during cold weather paving.

Keywords: asphaltic roads, asphalt binder, distress, raveling

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Authors: Olivier Delage, Thierry Portafaix, Hassan Bencherif, Guillaume Guimbretiere

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Most observation data sequences in geophysics can be interpreted as resulting from the interaction of several physical processes at several time and space scales. As a consequence, measurements time series in geophysics have often characteristics of non-linearity and non-stationarity and thereby exhibit strong fluctuations at all time-scales and require a time-frequency representation to analyze their variability. Empirical Mode Decomposition (EMD) is a relatively new technic as part of a more general signal processing method called the Hilbert-Huang transform. This analysis method turns out to be particularly suitable for non-linear and non-stationary signals and consists in decomposing a signal in an auto adaptive way into a sum of oscillating components named IMFs (Intrinsic Mode Functions), and thereby acts as a bank of bandpass filters. The advantages of the EMD technic are to be entirely data driven and to provide the principal variability modes of the dynamics represented by the original time series. However, the main limiting factor is the frequency resolution that may give rise to the mode mixing phenomenon where the spectral contents of some IMFs overlap each other. To overcome this problem, J. Gilles proposed an alternative entitled “Empirical Wavelet Transform” (EWT) which consists in building from the segmentation of the original signal Fourier spectrum, a bank of filters. The method used is based on the idea utilized in the construction of both Littlewood-Paley and Meyer’s wavelets. The heart of the method lies in the segmentation of the Fourier spectrum based on the local maxima detection in order to obtain a set of non-overlapping segments. Because linked to the Fourier spectrum, the frequency resolution provided by EWT is higher than that provided by EMD and therefore allows to overcome the mode-mixing problem. On the other hand, if the EWT technique is able to detect the frequencies involved in the original time series fluctuations, EWT does not allow to associate the detected frequencies to a specific mode of variability as in the EMD technic. Because EMD is closer to the observation of physical phenomena than EWT, we propose here a new technic called EAWD (Empirical Adaptive Wavelet Decomposition) based on the coupling of the EMD and EWT technics by using the IMFs density spectral content to optimize the segmentation of the Fourier spectrum required by EWT. In this study, EMD and EWT technics are described, then EAWD technic is presented. Comparison of results obtained respectively by EMD, EWT and EAWD technics on time series of ozone total columns recorded at Reunion island over [1978-2019] period is discussed. This study was carried out as part of the SOLSTYCE project dedicated to the characterization and modeling of the underlying dynamics of time series issued from complex systems in atmospheric sciences

Keywords: adaptive filtering, empirical mode decomposition, empirical wavelet transform, filter banks, mode-mixing, non-linear and non-stationary time series, wavelet

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Authors: Kensho Takahashi, Ko Watanabe, Takashi Kaburagi, Hiroshi Tanaka, Kajiro Watanabe, Yosuke Kurihara

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Near-infrared spectroscopy (NIRS) has been widely used as a non-invasive method to measure brain activity, but it is corrupted by baseline drift noise. Here we present a method to measure regional cerebral blood flow as a derivative of NIRS output. We investigate whether, when listening to languages, blood flow can reasonably localize and represent regional brain activity or not. The prefrontal blood flow distribution pattern when advanced second-language listeners listened to a second language (L2) was most similar to that when listening to their first language (L1) among the patterns of mean and standard deviation. In experiments with 25 healthy subjects, the maximum blood flow was localized to the left BA46 of advanced listeners. The blood flow presented is robust to baseline drift and stably localizes regional brain activity.

Keywords: NIRS, oxy-hemoglobin, baseline drift, blood flow, working memory, BA46, first language, second language

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Authors: Hyun-Woo Cho

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The monitoring of industrial production quality has to be implemented to alarm early warning for unusual operating conditions. Furthermore, identification of their assignable causes is necessary for a quality control purpose. For such tasks many multivariate statistical techniques have been applied and shown to be quite effective tools. This work presents a process data-based monitoring scheme for production processes. For more reliable results some additional steps of noise filtering and preprocessing are considered. It may lead to enhanced performance by eliminating unwanted variation of the data. The performance evaluation is executed using data sets from test processes. The proposed method is shown to provide reliable quality control results, and thus is more effective in quality monitoring in the example. For practical implementation of the method, an on-line data system must be available to gather historical and on-line data. Recently large amounts of data are collected on-line in most processes and implementation of the current scheme is feasible and does not give additional burdens to users.

Keywords: detection, filtering, monitoring, process data

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Authors: Rozita Borhan, Hanif Che Lah, Wee Leong Son

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This paper is about method to produce a stable and accurate constant output pulse width regardless of the amplitude, period and pulse width variation of the input signal source. The pulse generated is usually being used in numerous applications as the reference input source to other circuits in the system. Therefore, it is crucial to produce a clean and constant pulse width to make sure the system is working accurately as expected.

Keywords: amplitude, Constant Pulse Width, frequency divider, pulse generator

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Authors: M. A. Alavianmehr, A. Tashk, A. Sodagaran

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Modeling background and moving objects are significant techniques for video surveillance and other video processing applications. This paper presents a foreground detection algorithm that is robust against illumination changes and noise based on adaptive mixture Gaussian model (GMM), and provides a novel and practical choice for intelligent video surveillance systems using static cameras. In the previous methods, the image of still objects (background image) is not significant. On the contrary, this method is based on forming a meticulous background image and exploiting it for separating moving objects from their background. The background image is specified either manually, by taking an image without vehicles, or is detected in real-time by forming a mathematical or exponential average of successive images. The proposed scheme can offer low image degradation. The simulation results demonstrate high degree of performance for the proposed method.

Keywords: image processing, background models, video surveillance, foreground detection, Gaussian mixture model

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Authors: Fabricio Costa Silva, Samuel Xavier de Souza

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A Global Positioning System (GPS) receiver is responsible to determine position, velocity and timing information by using satellite information. To get this information are necessary to combine an incoming and a locally generated signal. The procedure called acquisition need to found two information, the frequency and phase of the incoming signal. This is very time consuming, so there are several techniques to reduces the computational complexity, but each of then put projects issues in conflict. I this papers we present a method that can reduce the computational complexity by reducing the search space and paralleling the search.

Keywords: GPS, acquisition, complexity, parallelism

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Authors: Cóndor C. José, Rodrigues E. Camila, Noronha L. Irene, Dos Santos Fernando, Irigoyen M. Claudia, Andrade Lúcia

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Sepsis induces alterations in hemodynamics and autonomic nervous system (ASN). The autonomic activity can be calculated by measuring heart rate variability (HRV) that represents the complex interplay between ASN and cardiac pacemaker cells. Wharton’s jelly mesenchymal stem cells (WJ-MSCs) are known to express genes and secreted factors involved in neuroprotective and immunological effects, also to improve the survival in experimental septic animals. We hypothesized, that WJ-MSCs present an important role in the autonomic activity and in the hemodynamic effects in a cecal ligation and puncture (CLP) model of sepsis. Methods: We used flow cytometry to evaluate WJ-MSCs phenotypes. We divided Wistar rats into groups: sham (shamoperated); CLP; and CLP+MSC (106 WJ-MSCs, i.p., 6 h after CLP). At 24 h post-CLP, we recorded the systolic arterial pressure (SAP) and heart rate (HR) over 20 min. The spectral analysis of HR and SAP; also the spontaneous baroreflex sensitivity (measure by bradycardic and tachycardic responses) were evaluated after recording. The one-way ANOVA and the post hoc Student– Newman– Keuls tests (P< 0.05) were used to data comparison Results: WJ-MSCs were negative for CD3, CD34, CD45 and HLA-DR, whereas they were positive for CD73, CD90 and CD105. The CLP group showed a reduction in variance of overall variability and in high-frequency power of HR (heart parasympathetic activity); furthermore, there is a low-frequency reduction of SAP (blood vessels sympathetic activity). The treatment with WJ-MSCs improved the autonomic activity by increasing the high and lowfrequency power; and restore the baroreflex sensitive. Conclusions: WJ-MSCs attenuate the impairment of autonomic control of the heart and vessels and might therefore play a protective role in sepsis. (Supported by FAPESP).

Keywords: baroreflex response, heart rate variability, sepsis, wharton’s jelly-derived mesenchymal stem cells

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Authors: Ayman A. Al Hayek, Asirvatham A. Robert, Mohamed A. Al Dawish, Rim B. Braham, Hanouf S. Goudeh, Fahad S. Al Sabaan

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Introduction: The aim of this study was to explore the impact of insulin pump therapy on diabetes treatment satisfaction and glycemic control among patients with type 1 diabetes mellitus (T1DM) in Saudi Arabia. Methods: A 6-month, prospective study was conducted among 47 patients (aged17–24 years) with T1DM who attended the Insulin Pump Clinic at Prince Sultan Military Medical City, Riyadh, Saudi Arabia, between April 2014 and November 2014. The respondents were purposively and conveniently selected and were interviewed using the Arabic version of the Diabetes Treatment Satisfaction Questionnaire at baseline, 3, and 6 months. Demographics and clinical variables including hemoglobin A1c (HbA1c) were also collected. Results: The mean (±standard deviation) age of the study cohort was 19.1 ± 1.93 years. Seventeen patients were male (36.2%) and 30 were female (63.8%). Compared to baseline, significant positive differences were found in treatment satisfaction among female patients and patients with long-standing T1DM at 6 months. Frequency of hyperglycemia and hypoglycemia declined significantly in female patient’s at 6 months and in patients who had a shorter duration of T1DM. Furthermore, significant positive differences were found in HbA1c levels among female patients and among those who had a shorter duration of T1DM compared to baseline. Both female and male patients and those with a shorter duration of T1DM showed significant decline in insulin necessity at6months when compared to baseline. Conclusion: Although multiple daily injections is a feasible preference for insulin supply, insulin pumps should also be considered for patients with T1DM as it appears to increase patients’ treatment satisfaction, decrease the frequency of hypoglycemia, hyperglycemia, and reduce HbA1c levels.

Keywords: type 1 diabetes, insulin pump, Saudi Arabia, T1DM

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Authors: R. B. Knudsen, O. T. Rasmussen, R. A. Alphinas

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The reason for conducting this research is to develop an algorithm that is capable of classifying news articles from the automobile industry, according to the competitive actions that they entail, with the use of Text Mining (TM) methods. It is needed to test how to properly preprocess the data for this research by preparing pipelines which fits each algorithm the best. The pipelines are tested along with nine different classification algorithms in the realm of regression, support vector machines, and neural networks. Preliminary testing for identifying the optimal pipelines and algorithms resulted in the selection of two algorithms with two different pipelines. The two algorithms are Logistic Regression (LR) and Artificial Neural Network (ANN). These algorithms are optimized further, where several parameters of each algorithm are tested. The best result is achieved with the ANN. The final model yields an accuracy of 0.79, a precision of 0.80, a recall of 0.78, and an F1 score of 0.76. By removing three of the classes that created noise, the final algorithm is capable of reaching an accuracy of 94%.

Keywords: Artificial Neural network, Competitive dynamics, Logistic Regression, Text classification, Text mining

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Authors: Carlos Herrera Sierralta, Husain M. Muslim, Meshal T. Alsaiari, Daniel Fischer

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Preventing piping fatigue flow induced vibration in the Oil & Gas sector demands not only the constant development of engineering design methodologies based on available software packages, but also special piping support technologies for designing safe and reliable piping systems. The vast majority of piping vibration problems in the Oil & Gas industry are provoked by the process flow characteristics which are basically intrinsically related to the fluid properties, the type of service and its different operational scenarios. In general, the corrective actions recommended for flow induced vibration in piping systems can be grouped in two major areas: those which affect the excitation mechanisms typically associated to process variables, and those which affect the response mechanism of the pipework per se, and the pipework associated steel support structure. Where possible the first option is to try to solve the flow induced problem from the excitation mechanism perspective. However, in producing facilities the approach of changing process parameters might not always be convenient as it could lead to reduction of production rates or it may require the shutdown of the system in order to perform the required piping modification. That impediment might lead to a second option, which is to modify the response of the piping system to excitation generated by the type of process flow. In principle, the action of shifting the natural frequency of the system well above the frequency inherent to the process always favours the elimination, or considerably reduces, the level of vibration experienced by the piping system. Tightening up the clearances at the supports (ideally zero gap), and adding new static supports at the system, are typical ways of increasing the natural frequency of the piping system. However, only stiffening the piping system may not be sufficient to resolve the vibration problem, and in some cases, it might not be feasible to implement it at all, as the available piping layout could create limitations on adding supports due to thermal expansion/contraction requirements. In these cases, utilization of viscous damper supports could be recommended as these devices can allow relatively large quasi-static movement of piping while providing sufficient capabilities of dissipating the vibration. Therefore, when correctly selected and installed, viscous damper supports can provide a significant effect on the response of the piping system over a wide range of frequencies. Viscous dampers cannot be used to support sustained, static loads. This paper shows over a real case example, a methodology which allows to determine the selection of the viscous damper supports via a dynamic analysis model. By implementing this methodology, it was possible to resolve the piping vibration problem throughout redesigning adequately the existing static piping supports and by adding new viscous dampers supports. This was conducted on-stream at the oil crude pipeline in question without the necessity of reducing the production of the plant. Concluding that the application of the methodology of this paper can be applied to solve similar cases in a straightforward manner.

Keywords: dynamic analysis, flow induced vibration, piping supports, turbulent flow, slug flow, viscous damper

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Authors: Aleksandra Majchrzak, Katarzyna Baruch, Monika Sobolewska, Bartlomiej Chojnacki, Adam Pilch

Abstract:

Scaled modeling is very common in the areas of science such as aerodynamics or fluid mechanics, since defining characteristic numbers enables to determine relations between objects under test and their models. In acoustics, scaled modeling is aimed mainly at investigation of room acoustics, sound insulation and sound absorption phenomena. Despite such a range of application, there is no method developed that would enable scaling acoustical perforated panels freely, maintaining their sound absorption coefficient in a desired frequency range. However, conducted theoretical and numerical analyses have proven that it is not physically possible to obtain given sound absorption coefficient in a desired frequency range by directly scaling only all of the physical dimensions of a perforated panel, according to a defined characteristic number. This paper is a continuation of the research mentioned above and presents practical evaluation of theoretical and numerical analyses. The measurements of sound absorption coefficient of perforated panels were performed in order to verify previous analyses and as a result find the relations between full-scale perforated panels and their models which will enable to scale them properly. The measurements were conducted in a one-to-eight model of a reverberation chamber of Technical Acoustics Laboratory, AGH. Obtained results verify theses proposed after theoretical and numerical analyses. Finding the relations between full-scale and modeled perforated panels will allow to produce measurement samples equivalent to the original ones. As a consequence, it will make the process of designing acoustical perforated panels easier and will also lower the costs of prototypes production. Having this knowledge, it will be possible to emulate in a constructed model panels used, or to be used, in a full-scale room more precisely and as a result imitate or predict the acoustics of a modeled space more accurately.

Keywords: characteristic numbers, dimensional analysis, model study, scaled modeling, sound absorption coefficient

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Authors: S. Alotaibi, S. Omer, Y. Su

Abstract:

The conventional Internal Combustion Engine (ICE) based vehicles are a threat to the environment as they account for a large proportion of the overall greenhouse gas (GHG) emissions in the world. Hence, it is required to replace these vehicles with more environment-friendly vehicles. Electric Vehicles (EVs) are promising technologies which offer both human comfort “noise, pollution” as well as reduced (or no) emissions of GHGs. In this paper, different types of EVs are reviewed and their advantages and disadvantages are identified. It is found that in terms of fuel economy, Plug-in Hybrid EVs (PHEVs) have the best fuel economy, followed by Hybrid EVs (HEVs) and ICE vehicles. Since Battery EVs (BEVs) do not use any fuel, their fuel economy is estimated as price per kilometer. Similarly, in terms of GHG emissions, BEVs are the most environmentally friendly since they do not result in any emissions while HEVs and PHEVs produce less emissions compared to the conventional ICE based vehicles. Fuel Cell EVs (FCEVs) are also zero-emission vehicles, but they have large costs associated with them. Finally, if the electricity is provided by using the renewable energy technologies through grid connection, then BEVs could be considered as zero emission vehicles.

Keywords: electric vehicles, zero emission car, fuel economy, CO₂ footprint

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Authors: Patrizia Bonaventura, Magda Di Renzo

Abstract:

This project aims to measure and assess the voice quality in children with autism. Few previous studies exist which have analyzed the voice quality of individuals with autism: abnormal voice characteristics have been found, like a high pitch, great pitch range, and sing-song quality. Existing studies did not focus specifically on Italian-speaking children’s voices and provided analysis of a few acoustic parameters. The present study aimed to gather more data and to perform acoustic analysis of the voice of children with autism in order to identify patterns of abnormal voice features that might shed some light on the causes of the dysphonia and possibly be used to create a pediatric assessment tool for early identification of autism. The participants were five native Italian-speaking boys with autism between the age of 4 years and 10 years (mean 6.8 ± SD 1.4). The children had a diagnosis of autism, were verbal, and had no other comorbid conditions (like Down syndrome or ADHD). The voices of the autistic children were recorded in the production of sustained vowels [ah] and [ih] and of sentences from the Italian version of the CAPE-V voice assessment test. The following voice parameters, representative of normal quality, were analyzed by acoustic spectrography through Praat: Speaking Fundamental Frequency, F0 range, average intensity, and dynamic range. The results showed that the pitch parameters (Speaking Fundamental Frequency and F0 range), as well as the intensity parameters (average intensity and dynamic range), were significantly different from the relative normal reference thresholds. Also, variability among children was found, so confirming a tendency revealed in previous studies of individual variation in these aspects of voice quality. The results indicate a general pattern of abnormal voice quality characterized by a high pitch and large variations in pitch and intensity. These acoustic voice characteristics found in Italian-speaking autistic children match those found in children speaking other languages, indicating that autism symptoms affecting voice quality might be independent of the native language of the children.

Keywords: autism, voice disorders, speech science, acoustic analysis of voice

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Authors: Fabricio Costa Silva, Samuel Xavier de Souza

Abstract:

A Global Positioning System (GPS) receiver is responsible to determine position, velocity and timing information by using satellite information. To get this information's are necessary to combine an incoming and a locally generated signal. The procedure called acquisition need to found two information, the frequency and phase of the incoming signal. This is very time consuming, so there are several techniques to reduces the computational complexity, but each of then put projects issues in conflict. I this papers we present a method that can reduce the computational complexity by reducing the search space and paralleling the search.

Keywords: GPS, acquisition, low complexity, parallelism

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