Search results for: signal spectrum

Authors: S. S. Sathiesh

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The aim of this project is to study the radiation mechanism synchrotron and Inverse Compton scattering. Theoretically, we discussed spectral energy distribution for both. Programming is done for plotting the graph of Power-law spectrum for synchrotron Radiation using fortran90. The importance of power law spectrum was discussed and studied to infer its physical parameters from the model fitting. We also discussed how to infer the physical parameters from the theoretically drawn graph, we have seen how one can infer B (magnetic field of the source), γ min, γ max, spectral indices (p1, p2) while fitting the curve to the observed data.

Keywords: blazars/quasars, beaming, synchrotron radiation, Synchrotron Self Compton, inverse Compton scattering, mrk421

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Authors: Suparman

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This paper addresses the problem of the signal segmentation within a Bayesian framework by using reversible jump MCMC algorithm. The signal is modelled by piecewise constant Moving-Average (MA) model where the numbers of segments, the position of change-point, the order and the coefficient of the MA model for each segment are unknown. The reversible jump MCMC algorithm is then used to generate samples distributed according to the joint posterior distribution of the unknown parameters. These samples allow calculating some interesting features of the posterior distribution. The performance of the methodology is illustrated via several simulation results.

Keywords: piecewise, moving-average model, reversible jump MCMC, signal segmentation

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Authors: Rohit Gupta, Ravinder Agarwal

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Surface electromyographic (sEMG) signal has the potential to identify the human activities and intention. This potential is further exploited to control the artificial limbs using the sEMG signal from residual limbs of amputees. The paper deals with the development of multichannel cost efficient sEMG signal interface for research application, along with evaluation of proposed class dependent statistical approach of the feature selection method. The sEMG signal acquisition interface was developed using ADS1298 of Texas Instruments, which is a front-end interface integrated circuit for ECG application. Further, the sEMG signal is recorded from two lower limb muscles for three locomotions namely: Plane Walk (PW), Stair Ascending (SA), Stair Descending (SD). A class dependent statistical approach is proposed for feature selection and also its performance is compared with 12 preexisting feature vectors. To make the study more extensive, performance of five different types of classifiers are compared. The outcome of the current piece of work proves the suitability of the proposed feature selection algorithm for locomotion recognition, as compared to other existing feature vectors. The SVM Classifier is found as the outperformed classifier among compared classifiers with an average recognition accuracy of 97.40%. Feature vector selection emerges as the most dominant factor affecting the classification performance as it holds 51.51% of the total variance in classification accuracy. The results demonstrate the potentials of the developed sEMG signal acquisition interface along with the proposed feature selection algorithm.

Keywords: classifiers, feature selection, locomotion, sEMG

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Authors: Hadjadj Abdechafik, Kious Mecheri, Ameur Aissa

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The objective of this study is to develop a process of treatment of the vibratory signals generated during a horizontal high speed milling process without applying any coolant in order to establish a monitoring system able to improve the machining performance. Thus, many tests were carried out on the horizontal high speed centre (PCI Météor 10), in given cutting conditions, by using a milling cutter with only one insert and measured its frontal wear from its new state that is considered as a reference state until a worn state that is considered as unsuitable for the tool to be used. The results obtained show that the first harmonic follow well the evolution of frontal wear, on another hand a wavelet transform is used for signal processing and is found to be useful for observing the evolution of the wavelet approximations through the cutting tool life. The power and the Root Mean Square (RMS) values of the wavelet transformed signal gave the best results and can be used for tool wear estimation. All this features can constitute the suitable indicators for an effective detection of tool wear and then used for the input parameters of an online monitoring system. Although we noted the remarkable influence of the machining cycle on the quality of measurements by the introduction of a bias on the signal, this phenomenon appears in particular in horizontal milling and in the majority of studies is ignored.

Keywords: flank wear, vibration, milling, signal processing, monitoring

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Authors: Razieh Khalafi

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The brain is the information processing centre of the human body. Stimuli in the form of information are transferred to the brain and then brain makes the decision on how to respond to them. In this research, we propose a new partial differential equation which analyses the EEG signals and make a relationship between the incoming stimuli and the brain response to them. In order to test the proposed model, a set of external stimuli applied to the model and the model’s outputs were checked versus the real EEG data. The results show that this model can model the EEG signal well. The proposed model is useful not only for modelling of EEG signal in case external stimuli but it can be used for modelling of brain response in case of internal stimuli.

Keywords: brain, stimuli, partial differential equation, response, EEG signal

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Authors: A. Hakimiyan, H. Namazi

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Human behavior is defined as a range of behaviors exhibited by humans who are influenced by different internal or external sources. Human behavior is the subject of much research in different areas of psychology and neuroscience. Despite some advances in studies related to forecasting of human behavior, there are not many researches which consider the effect of the time delay between the presence of stimulus and the related human response. Analysis of EEG signal as a fractal time series is one of the major tools for studying the human behavior. In the other words, the human brain activity is reflected in his EEG signal. Artificial Neural Network has been proved useful in forecasting of different systems’ behavior especially in engineering areas. In this research, a time delay neural network is trained and tested in order to forecast the human EEG signal and subsequently human behavior. This neural network, by introducing a time delay, takes care of the lagging time between the occurrence of the stimulus and the rise of the subsequent action potential. The results of this study are useful not only for the fundamental understanding of human behavior forecasting, but shall be very useful in different areas of brain research such as seizure prediction.

Keywords: human behavior, EEG signal, time delay neural network, prediction, lagging time

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Authors: Claire P. Griffin

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The education provision for students with special educational needs, including students with Autism Spectrum Disorder (ASD), has undergone significant national and international changes in recent years. In particular, an increase in resource-based provision has occurred across educational settings in an effort to support inclusive practices. This paper seeks to explore the role of the Special Needs Assistant (SNA) in supporting children with ASD in Irish schools. This research stems from the second national evaluation of ‘Education Provision for Students with Autism Spectrum Disorder in Ireland’ (NCSE, 2016). This research was commissioned by the National Council for Special Education (NCSE) in Ireland and conducted by a team of researchers from Mary Immaculate College, Limerick from February to July 2014. This study involved a multiple case study research strategy across 24 educational sites, as selected through a stratified sampling process. Research strategies included semi-structured interviews, classroom observations, documentary review and child conversations. Data analysis was conducted electronically using Nvivo software, with use of an additional quantitative recording mechanism based on scaled weighting criteria for collected data. Based on such information, key findings from the NCSE national evaluation will be presented and critically reviewed, with particular reference to the role of the SNA in supporting pupils with ASD. Examples of positive practice inherent within the SNA role will be outlined and contrasted with discrete areas for development. Based on such findings, recommendations for the evolving role of the SNA will be presented, with the aim of informing both policy and best practice within the field.

Keywords: autism spectrum disorder, inclusive education , paraprofessional, special needs assistant

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Authors: Hai Chi, Ibrahim Mehmeti, Kirill Ovchinnikov, Hegle Holo, Ingolf F. Nes, Dzung B. Diep

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By using a panel of multiple indicator strains of different bacterial species and genera, we screened a large collection of bacterial isolates (over 1800 isolates) derived from raw milk, for bacteriocin producers with broad inhibition spectra (BIS). Fourteen isolates with BIS were identified, and by 16S rDNA sequencing they were found to belong to Lactococcus garvieae (10 isolates) and Enterococcus feacalis (4 isolates). Further analysis of the ten L. garvieae isolates revealed that they were very similar, if not identical, to each other in metabolic and genetic terms: they had the same fermentation profile on different types of sugars, repetitive sequence-based PCR (rep-PCR) DNA pattern as well as they all had the same inhibition profile towards over 50 isolates of different species. The bacteriocin activity from one of the L. garvieae isolates was assessed further. The bacteriocin which was termed garvicin KS, was found to be heatstable and proteinase-labile and its inhibition spectrum contained many distantly related genera of Firmicutes, comprising most lactic acid bacteria (LAB) as well as problematic species of Bacillus, Listeria, Streptococcus and Staphylococcus and their antibiotic resistant derivatives (e.g. VRE, MRSA). Taken together, the results indicate that this is a potent bacteriocin from L. garvieae and that its very broad inhibition spectrum can be a very useful property for use in food preservation as well as in infection treatments caused by gram-positive pathogens and their antibiotic-derivatives.

Keywords: bacteriocin, lactic acid bacteria, Lactococcus garvieae, antibiotics resistance

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Authors: Hui Zhang, Ye Tian, Fang Ye, Ziming Guo

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Communication signal modulation recognition technology is one of the key technologies in the field of modern information warfare. At present, communication signal automatic modulation recognition methods are mainly divided into two major categories. One is the maximum likelihood hypothesis testing method based on decision theory, the other is a statistical pattern recognition method based on feature extraction. Now, the most commonly used is a statistical pattern recognition method, which includes feature extraction and classifier design. With the increasingly complex electromagnetic environment of communications, how to effectively extract the features of various signals at low signal-to-noise ratio (SNR) is a hot topic for scholars in various countries. To solve this problem, this paper proposes a feature extraction algorithm for the communication signal based on the improved Holder cloud feature. And the extreme learning machine (ELM) is used which aims at the problem of the real-time in the modern warfare to classify the extracted features. The algorithm extracts the digital features of the improved cloud model without deterministic information in a low SNR environment, and uses the improved cloud model to obtain more stable Holder cloud features and the performance of the algorithm is improved. This algorithm addresses the problem that a simple feature extraction algorithm based on Holder coefficient feature is difficult to recognize at low SNR, and it also has a better recognition accuracy. The results of simulations show that the approach in this paper still has a good classification result at low SNR, even when the SNR is -15dB, the recognition accuracy still reaches 76%.

Keywords: communication signal, feature extraction, Holder coefficient, improved cloud model

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Authors: Abdelkader Elhanaoui, Mhamed Hadji, Rachid Skouri, Said Agounad

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The purpose of this paper is to study the phenomenon of acoustic scattering by using a new method. The signal processing (Fast Fourier Transform FFT Inverse Fast Fourier Transform iFFT and BESSEL functions) is widely applied to obtain information with high precision accuracy. Signal processing has a wider implementation in general-purpose pro-cessors. Our interest was focused on the use of FPGAs (Field-Programmable Gate Ar-rays) in order to minimize the computational complexity in single processor architecture, then be accelerated on FPGA and meet real-time and energy efficiency requirements. Gen-eral-purpose processors are not efficient for signal processing. We implemented the acous-tic backscattered signal processing model on the Altera DE-SOC board and compared it to Odroid xu4. By comparison, the computing latency of Odroid xu4 and FPGA is 60 sec-onds and 3 seconds, respectively. The detailed SoC FPGA-based system has shown that acoustic spectra are performed up to 20 times faster than the Odroid xu4 implementation. FPGA-based system of processing algorithms is realized with an absolute error of about 10⁻³. This study underlines the increasing importance of embedded systems in underwater acoustics, especially in non-destructive testing. It is possible to obtain information related to the detection and characterization of submerged cells. So we have achieved good exper-imental results in real-time and energy efficiency.

Keywords: DE1 FPGA, acoustic scattering, form function, signal processing, non-destructive testing

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Authors: Minjung Kim, Hyunkoo Kang, Jinkoo Kim

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In this study, a seismic retrofit scheme for a reinforced concrete shear wall structure using steel slit dampers was presented. The stiffness and the strength of the slit damper used in the retrofit were verified by cyclic loading test. A genetic algorithm was applied to find out the optimum location of the slit dampers. The effects of the slit dampers on the seismic retrofit of the model were compared with those of jacketing shear walls. The seismic performance of the model structure with optimally positioned slit dampers was evaluated by nonlinear static and dynamic analyses. Based on the analysis results, the simple procedure for determining required damping ratio using capacity spectrum method along with the damper distribution pattern proportional to the inter-story drifts was validated. The analysis results showed that the seismic retrofit of the model structure using the slit dampers was more economical than the jacketing of the shear walls and that the capacity spectrum method combined with the simple damper distribution pattern led to satisfactory damper distribution pattern compatible with the solution obtained from the genetic algorithm.

Keywords: seismic retrofit, slit dampers, genetic algorithm, jacketing, capacity spectrum method

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Authors: M.R Asghari Bejestani, Gh. R. Mohammad Khani, V.R. Nafisi

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Imagined speech recognition is one of the most interesting approaches to BCI development and a lot of works have been done in this area. Many different experiments have been designed and hundreds of combinations of feature extraction methods and classifiers have been examined. Reported classification accuracies range from the chance level to more than 90%. Based on non-stationary nature of brain signals, we have introduced 3 classification modes according to time difference in inter and intra-class samples. The modes can explain the diversity of reported results and predict the range of expected classification accuracies from the brain signal accusation procedure. In this paper, a few samples are illustrated by inspecting results of some previous works.

Keywords: brain computer interface, silent talk, imagined speech, classification, signal processing

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Authors: Rezvan Ravanfar Haghighi, V. C. Vani, Suresh Perumal, Sabyasachi Chatterjee, Pratik Kumar

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X-ray attenuation coefficient [µ(E)] of any substance, for energy (E), is a sum of the contributions from the Compton scattering [ μCom(E)] and photoelectric effect [µPh(E)]. In terms of the, electron density (ρe) and the effective atomic number (Zeff) we have µCom(E) is proportional to [(ρe)fKN(E)] while µPh(E) is proportional to [(ρeZeffx)/Ey] with fKN(E) being the Klein-Nishina formula, with x and y being the exponents for photoelectric effect. By taking the sample's HU at two different excitation voltages (V=V1, V2) of the CT machine, we can solve for X=ρe, Y=ρeZeffx from these two independent equations, as is attempted in DECT inversion. Since µCom(E) and µPh(E) are both energy dependent, the coefficients of inversion are also dependent on (a) the source spectrum S(E,V) and (b) the detector efficiency D(E) of the CT machine. In the present paper we tabulate these coefficients of inversion for different practical manifestations of S(E,V) and D(E). The HU(V) values from the CT follow: <µ(V)>=<µw(V)>[1+HU(V)/1000] where the subscript 'w' refers to water and the averaging process <….> accounts for the source spectrum S(E,V) and the detector efficiency D(E). Linearity of μ(E) with respect to X and Y implies that (a) <µ(V)> is a linear combination of X and Y and (b) for inversion, X and Y can be written as linear combinations of two independent observations <µ(V1)>, <µ(V2)> with V1≠V2. These coefficients of inversion would naturally depend upon S(E, V) and D(E). We numerically investigate this dependence for some practical cases, by taking V = 100 , 140 kVp, as are used for cardiological investigations. The S(E,V) are generated by using the Boone-Seibert source spectrum, being superposed on aluminium filters of different thickness lAl with 7mm≤lAl≤12mm and the D(E) is considered to be that of a typical Si[Li] solid state and GdOS scintilator detector. In the values of X and Y, found by using the calculated inversion coefficients, errors are below 2% for data with solutions of glycerol, sucrose and glucose. For low Zeff materials like propionic acid, Zeffx is overestimated by 20% with X being within1%. For high Zeffx materials like KOH the value of Zeffx is underestimated by 22% while the error in X is + 15%. These imply that the source may have additional filtering than the aluminium filter specified by the manufacturer. Also it is found that the difference in the values of the inversion coefficients for the two types of detectors is negligible. The type of the detector does not affect on the DECT inversion algorithm to find the unknown chemical characteristic of the scanned materials. The effect of the source should be considered as an important factor to calculate the coefficients of inversion.

Keywords: attenuation coefficient, computed tomography, photoelectric effect, source spectrum

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Authors: J. O. Alvarez, L. Y. Rivera

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Physical activity can reduce symptomatology in children with autism spectrum disorder (ASD). The sport of soccer has been widely applied as a therapeutic method for ASD children. However, empirical results from soccer programs are not widely known. This paper presents the case study of Golitos, the only dedicated soccer program for children on the island of Puerto Rico, and analyzes its results in the reduction of ASD social and emotional symptoms. The paper shows evidence that suggests that program approach, content, and community-based elements can make a notable difference in the effectiveness of using soccer or sports as therapeutic methods for children with ASD.

Keywords: autism, soccer, program, community

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Authors: Cherry Oo, Hnin Min Oo

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Software bug localization is one of the most costly tasks in program repair technique. Therefore, there is a high claim for automated bug localization techniques that can monitor programmers to the locations of bugs, with slight human arbitration. Spectrum-based bug localization aims to help software developers to discover bugs rapidly by investigating abstractions of the program traces to make a ranking list of most possible buggy modules. Using the Apache Commons Math library project, we study the diagnostic accuracy using our spectrum-based bug localization metric. Our outcomes show that the greater performance of a specific similarity coefficient, used to inspect the program spectra, is mostly effective on localizing of single line bugs.

Keywords: software testing, bug localization, program spectra, bug

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Authors: Abdulrahman M. Alhowikan, Nadra E. Elamin, Sarah S. Aldayel, Sara A. AlSiddiqi, Fai S. Alrowais, Laila Y. Al-Ayadhi

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Background: A growing body of research has suggested that physical activities (PA) have important implications for improving the performance of ASD children. They revealed that the physiological, cognitive, psychological, and behavioral functioning had improved after performing some physical activities. Methods: We compared the sedentary behavior and physical activities between children with autism spectrum disorder (n=21) and age-matched control group (n=30), using the ActiGraph GT3X+ for the assessments. Results: Our results revealed that the total time spent in sedentary activity and the total sedentary activity counts were highly significant in the control group compared to the ASD group (p < 0.001, p=0.001, respectively). ASD spent a significantly longer time than the controls engaging on vigorous physical activity (VPA) (p=0.017). The results also indicated that there were no significant differences between both groups for the total counts and time spent in light physical activity (LPA) and moderate physical activity (MPA). Conclusion: The finding highlights the importance of physical activity intervention for ASD children, using accurate and precise measurement tools to record all activities.

Keywords: Autism spectrum disorders, motor skills, physical activity, ActiGraph GT3X+, moderate-to vigorous-intensity physical activity

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Authors: Inseon Ryoo, Soo Chin Kim, Hyena Jung, Sangil Suh

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Objectives: The purpose of this study is to evaluate the clinical significance of hyper-intense signal thyroid incidentalomas on the time of flight magnetic resonance angiography (TOF-MRA) using correlation study with ultrasound (US). Methods: We retrospectively reviewed 3,505 non-contrast TOF-MRA performed at an institution between September 2014 and May 2017. Two radiologists correlated the thyroid incidentalomas detected on TOF-MRA with US features which was obtained within three months interval between MRA and US examinations in consensus method. Results: The prevalence of hyper-intense signal thyroid nodules incidentally detected on TOF-MRA was 1.2% (43/3505). Among them, 35 people (81.4%) underwent US examinations, and total 45 hyper-intense signal thyroid nodules were detected on US exams. Of these 45 nodules, 35 nodules (72.9%) were categorized as benign (K-TIRADS category 2) on US exams. Fine needle aspiration was performed on 9 nodules according to the indications recommended by Korean Society of Thyroid Radiology. All except one high-suspicious thyroid nodule were confirmed as benign (Bethesda 2) on cytologic exams. One high-suspicious nodule on US showed a non-diagnostic result (Bethesda 1) on cytologic exam. However, this nodule collapsed after aspiration of thick colloid material. Conclusions: Our study showed that the most hyper-intense signal thyroid nodules detected on TOF-MRA were benign. Therefore, if a hyper-intense signal incidentaloma is found on TOF-MRA, further evaluation, especially invasive biopsy of the nodules could be suspended unless the patient had other symptoms or clinical factors suggesting the need for further evaluation.

Keywords: incidentaloma, thyroid nodule, TOF MR angiography, ultrasound

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Authors: Yu-Lin Shen, Ming-Kuen Chang

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In addition to a considerable amount of machinery and equipment, intricacies of the transmission pipeline exist in Petrochemical plants. Long term corrosion may lead to pipeline thinning and rupture, causing serious safety concerns. With the advances in non-destructive testing technology, more rapid and long-range ultrasonic detection techniques are often used for pipeline inspection, EMAT without coupling to detect, it is a non-contact ultrasonic, suitable for detecting elevated temperature or roughened e surface of line. In this study, we prepared artificial defects in pipeline for Electromagnetic Acoustic Transducer Testing (EMAT) to survey the relationship between the defect location, sizing and the EMAT signal. It was found that the signal amplitude of EMAT exhibited greater signal attenuation with larger defect depth and length.. In addition, with bigger flat hole diameter, greater amplitude attenuation was obtained. In summary, signal amplitude attenuation of EMAT was affected by the defect depth, defect length and the hole diameter and size.

Keywords: EMAT, artificial defect, NDT, ultrasonic testing

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Authors: Rana Zeina

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Objective: The association between Sensory problems and cognitive abilities has been studied in individuals with Autism Spectrum Disorders (ASDs). In this study, we used a neuropsychological test to evaluate memory and attention in ASDs children with sensory problems compared to the ASDs children without sensory problems. Methods: Four visual memory tests of Cambridge Neuropsychological Test Automated Battery (CANTAB) including Big/Little Circle (BLC), Simple Reaction Time (SRT), Intra/Extra Dimensional Set Shift (IED), Spatial Recognition Memory (SRM), were administered to 14 ASDs children with sensory problems compared to 13 ASDs without sensory problems aged 3 to 12 with IQ of above 70. Results: ASDs Individuals with sensory problems performed worse than the ASDs group without sensory problems on comprehension, learning, reversal and simple reaction time tasks, and no significant difference between the two groups was recorded in terms of the visual memory and visual comprehension tasks. Conclusion: The findings of this study suggest that ASDs children with sensory problems are facing deficits in learning, comprehension, reversal, and speed of response to stimuli.

Keywords: visual memory, attention, autism spectrum disorders, CANTAB eclipse

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Authors: Wenjuan Du, Jingtian Bi, Tong Wang, Haifeng Wang

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Grid connection of a large-scale wind farm affects power system small-signal angular stability in two aspects. Firstly, connection of the wind farm brings about the change of load flow and configuration of a power system. Secondly, the dynamic interaction is introduced by the wind farm with the synchronous generators (SGs) in the power system. This paper proposes a method to assess the two aspects of the effect of the wind farm on power system small-signal angular stability. The effect of the change of load flow/system configuration brought about by the wind farm can be examined separately by displacing wind farms with constant power sources, then the effect of the dynamic interaction of the wind farm with the SGs can be also computed individually. Thus, a clearer picture and better understanding on the power system small-signal angular stability as affected by grid connection of the large-scale wind farm are provided. In the paper, an example power system with grid connection of a wind farm is presented to demonstrate the proposed approach.

Keywords: power system small-signal angular stability, power system low-frequency oscillations, electromechanical oscillation modes, wind farms, double fed induction generator (DFIG)

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Authors: Shaolin Allen Liao, Hual-Te Chien

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Various THz phase extraction algorithms have been developed for a novel THz Modulating Interferometric Doppler Radar (THz-MIDR) developed recently by the author. The THz-MIDR differs from the well-known FTIR technique in that it introduces a continuously modulating reference branch, compared to the time-consuming discrete FTIR stepping reference branch. Such change allows real-time tracking of a moving object and capturing of its Doppler signature. The working principle of the THz-MIDR is similar to the FTIR technique: the incoming THz emission from the scene is split by a beam splitter/combiner; one of the beams is continuously modulated by a vibrating mirror or phase modulator and the other split beam is reflected by a reflection mirror; finally both the modulated reference beam and reflected beam are combined by the same beam splitter/combiner and detected by a THz intensity detector (for example, a pyroelectric detector). In order to extract THz phase from the single intensity measurement signal, we have derived rigorous mathematical formulas for 3 Frequency Banded (FB) signals: 1) DC Low-Frequency Banded (LFB) signal; 2) Fundamental Frequency Banded (FFB) signal; and 3) Harmonic Frequency Banded (HFB) signal. The THz phase extraction algorithms are then developed based combinations of 2 or all of these 3 FB signals with efficient algorithms such as Levenberg-Marquardt nonlinear fitting algorithm. Numerical simulation has also been performed in Matlab with simulated THz-MIDR interferometric signal of various Signal to Noise Ratio (SNR) to verify the algorithms.

Keywords: algorithm, modulation, THz phase, THz interferometry doppler radar

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Authors: Pawel Albrycht, Monika Ksiezopolska-Gocalska, Robert Holyst

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Surface Enhanced Raman Spectroscopy (SERS) is a technique of growing importance not only in purely scientific research related to analytical chemistry. It finds more and more applications in broadly understood testing - medical, forensic, pharmaceutical, food - and everywhere works perfectly, on one condition that SERS substrates used for testing give adequate enhancement, repeatability, and homogeneity of SERS signal. This is a problem that has existed since the invention of this technique. Some laboratories use as SERS amplifiers colloids with silver or gold nanoparticles, others form rough silver or gold surfaces, but results are generally either weak or unrepeatable. Furthermore, these structures are very often highly specific - they amplify the signal only of a small group of compounds. It means that they work with some kinds of analytes but only with those which were used at a developer’s laboratory. When it comes to research on different compounds, completely new SERS 'substrates' are required. That underlay our decision to develop universal substrates for the SERS spectroscopy. Generally, each compound has different affinity for both silver and gold, which have the best SERS properties, and that's what depends on what signal we get in the SERS spectrum. Our task was to create the platform that gives a characteristic 'fingerprint' of the largest number of compounds with very high repeatability - even at the expense of the intensity of the enhancement factor (EF) (possibility to repeat research results is of the uttermost importance). As specified above SERS substrates are offered by SERSitive company. Applied method is based on cyclic potentiodynamic electrodeposition of silver or silver-gold nanoparticles on the conductive surface of ITO-coated glass at controlled temperature of the reaction solution. Silver nanoparticles are supplied in the form of silver nitrate (AgNO₃, 10 mM), gold nanoparticles are derived from tetrachloroauric acid (10 mM) while sodium sulfite (Na₂O₃, 5 mM) is used as a reductor. To limit and standardize the size of the SERS surface on which nanoparticles are deposited, photolithography is used. We secure the desired ITO-coated glass surface, and then etch the unprotected ITO layer which prevents nanoparticles from settling at these sites. On the prepared surface, we carry out the process described above, obtaining SERS surface with nanoparticles of sizes 50-400 nm. The SERSitive platforms present highly sensitivity (EF = 10⁵-10⁶), homogeneity and repeatability (70-80%).

Keywords: electrodeposition, nanoparticles, Raman spectroscopy, SERS, SERSitive, SERS platforms, SERS substrates

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Authors: Xiang Jianhong, Wang Cong, Wang Linyu

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With the rise of medical IoT technologies, Wireless body area networks (WBANs) can collect fetal electrocardiogram (FECG) signals to support telemedicine analysis. The compressed sensing (CS)-based WBANs system can avoid the sampling of a large amount of redundant information and reduce the complexity and computing time of data processing, but the existing algorithms have poor signal compression and reconstruction performance. In this paper, a Joint block multi-orthogonal least squares (JBMOLS) algorithm is proposed. We apply the FECG signal to the Joint block sparse model (JBSM), and a comparative study of sparse transformation and measurement matrices is carried out. A FECG signal compression transmission mode based on Rbio5.5 wavelet, Bernoulli measurement matrix, and JBMOLS algorithm is proposed to improve the compression and reconstruction performance of FECG signal by CS-based WBANs. Experimental results show that the compression ratio (CR) required for accurate reconstruction of this transmission mode is increased by nearly 10%, and the runtime is saved by about 30%.

Keywords: telemedicine, fetal ECG, compressed sensing, joint sparse reconstruction, block sparse signal

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Authors: A. K. Aswathy, Asha Manoharan, Arya Manoharan

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The purpose of this study are to define the nature of oral sensory issues in children with autism spectrum disorder (ASD), identify important components of the assessment and treatment of this issues specific to this population, and delineate specific therapeutic techniques designed to improve assessment and treatment within therapeutic settings. Literature review and case example is used to define the predominant nature of the oral sensory issues that are experienced by some children on the autism spectrum. Characteristics of this complex disorder that can have an impact on feeding skill and behavior are also identified. These factors are then integrated to create assessment and intervention techniques that can be used in conjunction with traditional feeding approaches to facilitate improvements in eating as well as reducing oral apraxic component in this unique population. The complex nature of ASD and its many influences on feeding skills and behavior create the need for modification to both assessment and treatment approaches. Additional research is needed to create therapeutic protocols that can be used by speech-language pathologists to effectively assess and treat feeding and oro motor apraxic difficulties that are commonly encountered in children with ASD.

Keywords: autism, assessment, feeding, intervention, oral sensory issues, oral apraxia

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Authors: Kenneth Larsen, Astrid Aasland, Synnve Schjølberg, Trond Diseth

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Autism Spectrum Disorders (ASD) are neurodevelopmental disorders emerging in early development characterized by impairment in social communication skills and a restricted, repetitive and stereotyped patterns of behavior and interests. Early identification and interventions potentially improve development and quality of life of children with ASD. Symptoms of ASD are apparent through the second year of life, yet diagnostic age are still around 4 years of age. This study explored whether symptoms associated with ASD are possible to identify in typical Norwegian day-care centers in the second year of life. Results of this study clearly indicates that most described symptoms also are identifiable by day-care staff, and that a short observation list of 5 symptoms clearly identify children with ASD from a sample of normal developing peers.

Keywords: autism, early identification, day-care, screening

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Authors: Caroline Kim

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The designation autism spectrum disorder (ASD) groups complex disorders in the development of the brain. Autism is defined essentially as a condition in which an individual lacks a theory of mind. The theory of mind, in this sense, explains the ability of an individual to attribute feelings, emotions, or thoughts to another person. An autistic patient is characteristically unable to determine what an interlocutor is feeling, or to understand the beliefs of others. However, it is possible that autism cannot plausibly characterized as the lack of theory of mind in an individual. Genes, the bran, and its interplay with environmental factors may also cause autism. A mutation in a gene may be hereditary, or instigated by diseases such as mumps. Though an autistic patient may experience abnormalities in the cerebellum and the cortical regions, these are in fact only possible theories as to a biochemical explanation behind the disability. The prevailing theory identifying autism with lacking the theory of mind is supported by behavioral observation, but this form of observation is itself determined by socially constructed standards, limiting the possibility for empirical verification. The theory of mind infers that the beliefs and emotions of people are causally based on their behavior. This paper demonstrates the fallacy of this inference, critiquing its basis in socially constructed values, and arguing instead for a biochemical approach free from the conceptual apparatus of language and social expectation.

Keywords: autism spectrum disorder, sociology of psychology, social construction, the theory of mind

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Authors: R. Ondarza-Rovira, T. J. M. Boyd

Abstract:

Intense femtosecond laser light incident on over-critical density plasmas has shown to emit a prolific number of high-order harmonics of the driver frequency, with spectra characterized by power-law decays Pm ~ m-p, where m denotes the harmonic order and p the spectral decay index. When the laser pulse is p-polarized, plasma effects do modify the harmonic spectrum, weakening the so-called universal decay with p=8/3 to p=5/3, or below. In this work, appeal is made to a single particle radiation model in support of the predictions from particle-in-cell (PIC) simulations. Using this numerical technique we further show that the emission radiated by electrons -that are relativistically accelerated by the laser field inside the plasma, after being expelled into vacuum, the so-called Brunel electrons is characterized not only by the plasma line but also by ultraviolet harmonic orders described by the 5/3 decay index. Results obtained from these simulations suggest that for ultra-relativistic light intensities, the spectral decay index is further reduced, with p now in the range 2/3 ≤ p ≤ 4/3. This reduction is indicative of a transition from the regime where Brunel-induced plasma radiation influences the spectrum to one dominated by bremsstrahlung emission from the Brunel electrons.

Keywords: ultra-relativistic, laser-plasma interactions, high-order harmonic emission, radiation, spectrum

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Authors: J. Alvarez, J. Pimienta, R. Sarmiento

Abstract:

Diode lasers working in free mode present different shifting and broadening determined by external factors such as temperature, current or mechanical vibrations, and they are not more useful in applications such as spectroscopy, metrology, and cooling of atoms, among others. Different configurations can reduce the spectral width of a laser; one of the most effective is to extend the optical resonator of the laser diode and use optical feedback either with the help of a partially reflective mirror or with a diffraction grating; this latter configuration is not only allowed to reduce the spectral width of the laser line but also to coarsely adjust its working wavelength, within a wide range typically ~ 10nm by slightly varying the angle of the diffraction grating. Two settings are commonly used for this purpose, the Littrow configuration and the Littmann Metcalf. In this paper, we present the design, construction, and characterization of a compact extended laser cavity in Littrow configuration. The designed cavity is compact and was machined on an aluminum block using computer numerical control (CNC); it has a mass of only 380 g. The design was tested on laser diodes with different wavelengths, 650nm, 780nm, and 795 nm, but can be equally efficient at other wavelengths. This report details the results obtained from the extended cavity working at a wavelength of 780 nm, with an output power of around 35mW and a line width of less than 1Mhz. The cavity was used to observe the spectrum of the corresponding Rubidium D2 line. By modulating the current and with the help of phase detection techniques, a dispersion signal with an excellent signal-to-noise ratio was generated that allowed the stabilization of the laser to a transition of the hyperfine structure of Rubidium with an integral proportional controller (PI) circuit made with precision operational amplifiers.

Keywords: Littrow, Littman-Metcalf, line width, laser stabilization, hyperfine structure

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Authors: Yu-Lin Shen, Ming-Kuen Chang

Abstract:

In addition to a considerable amount of machinery and equipment, intricacies of the transmission pipeline exist in Petrochemical plants. Long term corrosion may lead to pipeline thinning and rupture, causing serious safety concerns. With the advances in non-destructive testing technology, more rapid and long-range ultrasonic detection techniques are often used for pipeline inspection, EMAT without coupling to detect, it is a non-contact ultrasonic, suitable for detecting elevated temperature or roughened e surface of line. In this study, we prepared artificial defects in pipeline for Electromagnetic Acoustic Transducer testing (EMAT) to survey the relationship between the defect location, sizing and the EMAT signal. It was found that the signal amplitude of EMAT exhibited greater signal attenuation with larger defect depth and length. In addition, with bigger flat hole diameter, greater amplitude attenuation was obtained. In summary, signal amplitude attenuation of EMAT was affected by the defect depth, defect length and the hole diameter and size.

Keywords: EMAT, artificial defect, NDT, ultrasonic testing

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Authors: Yanping Liao, Congcong He, Ruigang Zhao

Abstract:

The application of magnetocardiography signals to detect cardiac electrical function is a new technology developed in recent years. The magnetocardiography signal is detected with Superconducting Quantum Interference Devices (SQUID) and has considerable advantages over electrocardiography (ECG). It is difficult to extract Magnetocardiography (MCG) signal which is buried in the noise, which is a critical issue to be resolved in cardiac monitoring system and MCG applications. In order to remove the severe background noise, the Total Variation (TV) regularization method is proposed to denoise MCG signal. The approach transforms the denoising problem into a minimization optimization problem and the Majorization-minimization algorithm is applied to iteratively solve the minimization problem. However, traditional TV regularization method tends to cause step effect and lacks constraint adaptability. In this paper, an improved TV regularization method for denoising MCG signal is proposed to improve the denoising precision. The improvement of this method is mainly divided into three parts. First, high-order TV is applied to reduce the step effect, and the corresponding second derivative matrix is used to substitute the first order. Then, the positions of the non-zero elements in the second order derivative matrix are determined based on the peak positions that are detected by the detection window. Finally, adaptive constraint parameters are defined to eliminate noises and preserve signal peak characteristics. Theoretical analysis and experimental results show that this algorithm can effectively improve the output signal-to-noise ratio and has superior performance.

Keywords: constraint parameters, derivative matrix, magnetocardiography, regular term, total variation

Procedia PDF Downloads 124