Search results for: electrocardiogram signals
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1034

Search results for: electrocardiogram signals

344 Model Predictive Control with Unscented Kalman Filter for Nonlinear Implicit Systems

Authors: Takashi Shimizu, Tomoaki Hashimoto

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A class of implicit systems is known as a more generalized class of systems than a class of explicit systems. To establish a control method for such a generalized class of systems, we adopt model predictive control method which is a kind of optimal feedback control with a performance index that has a moving initial time and terminal time. However, model predictive control method is inapplicable to systems whose all state variables are not exactly known. In other words, model predictive control method is inapplicable to systems with limited measurable states. In fact, it is usual that the state variables of systems are measured through outputs, hence, only limited parts of them can be used directly. It is also usual that output signals are disturbed by process and sensor noises. Hence, it is important to establish a state estimation method for nonlinear implicit systems with taking the process noise and sensor noise into consideration. To this purpose, we apply the model predictive control method and unscented Kalman filter for solving the optimization and estimation problems of nonlinear implicit systems, respectively. The objective of this study is to establish a model predictive control with unscented Kalman filter for nonlinear implicit systems.

Keywords: optimal control, nonlinear systems, state estimation, Kalman filter

Procedia PDF Downloads 202
343 Tool Wear Monitoring of High Speed Milling Based on Vibratory Signal Processing

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

Procedia PDF Downloads 598
342 Number Variation of the Personal Pronoun we Used by Chinese English Learners

Authors: Qiong Hu, Ming Yue

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Language variation signals the newest usage of language community, which might become the developmental trend of that language. However, language textbooks cannot keep up with these emergent usages. Most Chinese English learners nowadays are still exposed to traditional grammar prescribed in the textbook so that some variational usages cannot be acquired. The personal pronoun we is prescribed as a plural pronoun in the textbook grammar, but its number value is more flexible in actual use. Based on the Chinese Learner English Corpus (CLEC), and with the homemade Friends corpus as reference, the present research explores the number value of the first person pronoun we used by Chinese English learners. With consideration of the subjectivity of we, this paper annotated the number value of all the wes in “we+ PCU (Perception-cognation-utterance) verbs” collocations. Results show that though exposed to traditional textbooks which prescribe the plural reference of we, there still exists some unconventional usage (singular or vague in reference) in the writings of Chinese English learners, which is less frequent than that of the native speeches. Corpus data and results from manual semantic annotation show that this could be due to the impact of formulaic sequence on the learners and the positive transfer from their native language. An improved SLA model of native language, target language and interlanguage is put forward to recognize the existence of variation in second language acquisition, which should be given more attention during teaching.

Keywords: Chinese English learners, number, PCU verbs, Personal pronoun we

Procedia PDF Downloads 355
341 Quality Evaluation of Backfill Grout in Tunnel Boring Machine Tail Void Using Impact-Echo (IE): Short-Time Fourier Transform (STFT) Numerical Analysis

Authors: Ju-Young Choi, Ki-Il Song, Kyoung-Yul Kim

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During Tunnel Boring Machine (TBM) tunnel excavation, backfill grout should be injected after the installation of segment lining to ensure the stability of the tunnel and to minimize ground deformation. If grouting is not sufficient to fill the gap between the segments and rock mass, hydraulic pressures occur in the void, which can negatively influence the stability of the tunnel. Recently the tendency to use TBM tunnelling method to replace the drill and blast(NATM) method is increasing. However, there are only a few studies of evaluation of backfill grout. This study evaluates the TBM tunnel backfill state using Impact-Echo(IE). 3-layers, segment-grout-rock mass, are simulated by FLAC 2D, FDM-based software. The signals obtained from numerical analysis and IE test are analyzed by Short-Time Fourier Transform(STFT) in time domain, frequency domain, and time-frequency domain. The result of this study can be used to evaluate the quality of backfill grouting in tail void.

Keywords: tunnel boring machine, backfill grout, impact-echo method, time-frequency domain analysis, finite difference method

Procedia PDF Downloads 266
340 Suicide in Late-Life Major Depressive Disorder: A Review of Structural and Functional Neuroimaging Studies

Authors: Wenqiu Cao

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Suicide prevention is a global problem that needs to be taken seriously. Investigating the mechanisms of suicide in major depressive disorder (MDD) separately through neuroimaging technology is essential for effective suicide prevention. And it’s particularly urgent in geriatric depressive patients since older adults are more likely to use rapidly deadly means, and suicidal behavior is more lethal for older adults. The current study reviews five studies related to suicide in geriatric MDD that uses neuroimaging methodology in order to analyze the relevant neurobiological mechanisms. The majority of the studies found significant white matter and grey matter reduction or lesion widespread in multiple brain regions, including the frontal and parietal regions, the midbrain, the external capsule, and the cerebellum. Regarding the cognitive impairment in geriatric MDD, the reward signals were found weakened in the paralimbic cortex. The functional magnetic resonance imaging (fMRI) studies also found hemodynamic changes in the right dorsolateral prefrontal cortex (DLPFC), orbitofrontal cortex (OFC), and right frontopolar cortex (FPC) regions in late-life MDD patients with suicidal ideation. Future studies should consider the age of depression onset, more accurate measurements of suicide, larger sample size, and longitudinal design.

Keywords: brain imaging, geriatric major depressive disorder, suicidality, suicide

Procedia PDF Downloads 136
339 Reed: An Approach Towards Quickly Bootstrapping Multilingual Acoustic Models

Authors: Bipasha Sen, Aditya Agarwal

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Multilingual automatic speech recognition (ASR) system is a single entity capable of transcribing multiple languages sharing a common phone space. Performance of such a system is highly dependent on the compatibility of the languages. State of the art speech recognition systems are built using sequential architectures based on recurrent neural networks (RNN) limiting the computational parallelization in training. This poses a significant challenge in terms of time taken to bootstrap and validate the compatibility of multiple languages for building a robust multilingual system. Complex architectural choices based on self-attention networks are made to improve the parallelization thereby reducing the training time. In this work, we propose Reed, a simple system based on 1D convolutions which uses very short context to improve the training time. To improve the performance of our system, we use raw time-domain speech signals directly as input. This enables the convolutional layers to learn feature representations rather than relying on handcrafted features such as MFCC. We report improvement on training and inference times by atleast a factor of 4x and 7.4x respectively with comparable WERs against standard RNN based baseline systems on SpeechOcean's multilingual low resource dataset.

Keywords: convolutional neural networks, language compatibility, low resource languages, multilingual automatic speech recognition

Procedia PDF Downloads 123
338 Selection of Wind Farms to Add Virtual Inertia Control to Assist the Power System Frequency Regulation

Authors: W. Du, X. Wang, Jun Cao, H. F. Wang

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Due to the randomness and uncertainty of wind energy, modern power systems integrating large-scale wind generation will be significantly impacted in terms of system performance and technical challenges. System inertia with high wind penetration is decreasing when conventional thermal generators are gradually replaced by wind turbines, which do not naturally contribute to inertia response. The power imbalance caused by wind power or demand fluctuations leads to the instability of system frequency. Accordingly, the need to attach the supplementary virtual inertia control to wind farms (WFs) strongly arises. When multi-wind farms are connected to the grid simultaneously, the selection of which critical WFs to install the virtual inertia control is greatly important to enhance the stability of system frequency. By building the small signal model of wind power systems considering frequency regulation, the installation locations are identified by the geometric measures of the mode observability of WFs. In addition, this paper takes the impacts of grid topology and selection of feedback control signals into consideration. Finally, simulations are conducted on a multi-wind farms power system and the results demonstrate that the designed virtual inertia control method can effectively assist the frequency regulation.

Keywords: frequency regulation, virtual inertia control, installation locations, observability, wind farms

Procedia PDF Downloads 397
337 Fusion Models for Cyber Threat Defense: Integrating Clustering, Random Forests, and Support Vector Machines to Against Windows Malware

Authors: Azita Ramezani, Atousa Ramezani

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In the ever-escalating landscape of windows malware the necessity for pioneering defense strategies turns into undeniable this study introduces an avant-garde approach fusing the capabilities of clustering random forests and support vector machines SVM to combat the intricate web of cyber threats our fusion model triumphs with a staggering accuracy of 98.67 and an equally formidable f1 score of 98.68 a testament to its effectiveness in the realm of windows malware defense by deciphering the intricate patterns within malicious code our model not only raises the bar for detection precision but also redefines the paradigm of cybersecurity preparedness this breakthrough underscores the potential embedded in the fusion of diverse analytical methodologies and signals a paradigm shift in fortifying against the relentless evolution of windows malicious threats as we traverse through the dynamic cybersecurity terrain this research serves as a beacon illuminating the path toward a resilient future where innovative fusion models stand at the forefront of cyber threat defense.

Keywords: fusion models, cyber threat defense, windows malware, clustering, random forests, support vector machines (SVM), accuracy, f1-score, cybersecurity, malicious code detection

Procedia PDF Downloads 71
336 Signal Processing of Barkhausen Noise Signal for Assessment of Increasing Down Feed in Surface Ground Components with Poor Micro-Magnetic Response

Authors: Tanmaya Kumar Dash, Tarun Karamshetty, Soumitra Paul

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The Barkhausen Noise Analysis (BNA) technique has been utilized to assess surface integrity of steels. But the BNA technique is not very successful in evaluating surface integrity of ground steels that exhibit poor micro-magnetic response. A new approach has been proposed for the processing of BN signal with Fast Fourier transforms while Wavelet transforms has been used to remove noise from the BN signal, with judicious choice of the ‘threshold’ value, when the micro-magnetic response of the work material is poor. In the present study, the effect of down feed induced upon conventional plunge surface grinding of hardened bearing steel has been investigated along with an ultrasonically cleaned, wet polished and a sample ground with spark out technique for benchmarking. Moreover, the FFT analysis has been established, at different sets of applied voltages and applied frequency and the pattern of the BN signal in the frequency domain is analyzed. The study also depicts the wavelet transforms technique with different levels of decomposition and different mother wavelets, which has been used to reduce the noise value in BN signal of materials with poor micro-magnetic response, in order to standardize the procedure for all BN signals depending on the frequency of the applied voltage.

Keywords: barkhausen noise analysis, grinding, magnetic properties, signal processing, micro-magnetic response

Procedia PDF Downloads 667
335 Epigastric Pain in Emergency Room: Median Arcuate Ligament Syndrome

Authors: Demet Devrimsel Dogan, Ecem Deniz Kirkpantur, Muharrem Dogan, Ahmet Aykut, Ebru Unal Akoglu, Ozge Ecmel Onur

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Introduction: Median Arcuate Ligament Syndrome (MALS) is a rare cause of chronic abdominal pain due to external compression of the celiac trunk by a fibrous arch that unites diaphragmatic crura on each side of the aortic hiatus. While 10-24% of the population may suffer from compression of celiac trunk, it rarely causes patients to develop symptoms. The typical clinical triad of symptoms includes postprandial epigastric pain, weight loss and vomiting. The diagnosis can be made using thin section multi-detector computed tomography (CT) scans which delineate the ligament and the compressed vessel. The treatment of MALS is aimed at relieving the compression of the celiac artery to restore adequate blood flow through the vessel and neurolysis to address chronic pain. Case: A 68-year-old male presented to our clinic with acute postprandial epigastric pain. This was patients’ first attack, and the pain was the worst pain of his life. The patient did not have any other symptoms like nausea, vomiting, chest pain or dyspnea. In his medical history, the patient has had an ischemic cerebrovascular stroke 5 years ago which he recovered with no sequel, and he was using 75 mg clopidogrel and 100 mg acetylsalicylic acid. He was not using any other medication and did not have a story of cardiovascular disease. His vital signs were stable (BP:113/72 mmHg, Spo2:97, temperature:36.3°C, HR:90/bpm). In his electrocardiogram, there was ST depression in leads II, III and AVF. In his physical examination, there was only epigastric tenderness, other system examinations were normal. Physical examination through his upper gastrointestinal system showed no bleeding. His laboratory results were as follows: creatinine:1.26 mg/dL, AST:42 U/L, ALT:17 U/L, amylase:78 U/L, lipase:26 U/L, troponin:10.3 pg/ml, WBC:28.9 K/uL, Hgb:12.7 gr/dL, Plt:335 K/uL. His serial high-sensitive troponin levels were also within normal limits, his echocardiography showed no segmental wall motion abnormalities, an acute myocardial infarction was excluded. In his abdominal ultrasound, no pathology was founded. Contrast-enhanced abdominal CT and CT angiography reported ‘thickened diaphragmatic cruras are compressing and stenosing truncus celiacus superior, this is likely compatible with MALS’. The patient was consulted to general surgery, and they admitted the patient for laparoscopic ligament release. Results: MALS is a syndrome that causes postprandial pain, nausea and vomiting as its most common symptoms. Affected patients are normally young, slim women between the ages of 30 and 50 who have undergone extensive examinations to find the source of their symptoms. To diagnose MALS, other underlying pathologies should initially be excluded. The gold standard is aortic angiography. Although diagnosis and treatment of MALS are unclear, symptom resolution has been achieved with multiple surgical modalities, including open, laparoscopic or robotic ligament release as well as celiac ganglionectomy, which often requires celiac artery revascularisation.

Keywords: differential diagnosis, epigastric pain, median arcuate ligament syndrome, celiac trunk

Procedia PDF Downloads 261
334 Authenticity of Ecuadorian Commercial Honeys

Authors: Elisabetta Schievano, Valentina Zuccato, Claudia Finotello, Patricia Vit

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Control of honey frauds is needed in Ecuador to protect bee keepers and consumers because simple syrups and new syrups with eucalyptus are sold as genuine honeys. Authenticity of Ecuadorian commercial honeys was tested with a vortex emulsion consisting on one volume of honey:water (1:1) dilution, and two volumes of diethyl ether. This method allows a separation of phases in one minute to discriminate genuine honeys that form three phase and fake honeys that form two phases; 34 of the 42 honeys analyzed from five provinces of Ecuador were genuine. This was confirmed with 1H NMR spectra of honey dilutions in deuterated water with an enhanced aminoacid region with signals for proline, phenylalanine and tyrosine. Classic quality indicators were also tested with this method (sugars, HMF), indicators of fermentation (ethanol, acetic acid), and residues of citric acid used in the syrup manufacture. One of the honeys gave a false positive for genuine, being an admixture of genuine honey with added syrup, evident for the high sucrose. Sensory analysis was the final confirmation to recognize the honey groups studied here, namely honey produced in combs by Apis mellifera, fake honey, and honey produced in cerumen pots by Geotrigona, Melipona, and Scaptotrigona. This is a valuable contribution to protect honey consumers, and to develop the beekeeping industry in Ecuador.

Keywords: fake, genuine, honey, 1H NMR, Ecuador

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333 Low Power Glitch Free Dual Output Coarse Digitally Controlled Delay Lines

Authors: K. Shaji Mon, P. R. John Sreenidhi

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In deep-submicrometer CMOS processes, time-domain resolution of a digital signal is becoming higher than voltage resolution of analog signals. This claim is nowadays pushing toward a new circuit design paradigm in which the traditional analog signal processing is expected to be progressively substituted by the processing of times in the digital domain. Within this novel paradigm, digitally controlled delay lines (DCDL) should play the role of digital-to-analog converters in traditional, analog-intensive, circuits. Digital delay locked loops are highly prevalent in integrated systems.The proposed paper addresses the glitches present in delay circuits along with area,power dissipation and signal integrity.The digitally controlled delay lines(DCDL) under study have been designed in a 90 nm CMOS technology 6 layer metal Copper Strained SiGe Low K Dielectric. Simulation and synthesis results show that the novel circuits exhibit no glitches for dual output coarse DCDL with less power dissipation and consumes less area compared to the glitch free NAND based DCDL.

Keywords: glitch free, NAND-based DCDL, CMOS, deep-submicrometer

Procedia PDF Downloads 245
332 Narrating 1968: Felipe Cazals’ Canoa (1976) and Images of Massacre

Authors: Nancy Elizabeth Naranjo Garcia

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Canoa (1976) by Felipe Cazals is a film that exposes the consequences of power that the Mexican State exercised over the 1968 student movement. The film, in this particular way, approaches the Tlatelolco Massacre from a point of view that takes into consideration the events that led up to it. Nonetheless, the reference to the political tension in Canoa remains ambiguous. Thus, the cinematographic representation refers to an event that leaves space for reflection, and as a consequence leaves evidence of an image that signals the notion of survival as Georges Didi-Huberman points out. In addition to denouncing the oppressive force by the Mexican State, the images in Canoa also emphasize what did not happen in Tlatelolco and its condensation with the student activists. To observe the images that Canoa offers in a new light, this work proposes further exploration with the following questions; How do the images in Canoa narrate? How are the images inserted in the film? In this fashion, a more profound comprehension of the objective and the essence of the images becomes feasible. As a result, it is possible to analyze the images of Canoa with the real killing at San Miguel Canoa in literature. The film visualizes a testimony of the event that once seemed unimaginable, an image that anticipates and structures the proceeding event. Therefore, this study takes a second look at how Canoa considers not only the killing at San Miguel Canoa and the Tlatlelolco Massacre, but goes further on contextualize an unimaginable image.

Keywords: cinematographic representation, student movement, Tlatelolco Massacre, unimaginable image

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331 Space Vector Pulse Width Modulation Based Design and Simulation of a Three-Phase Voltage Source Converter Systems

Authors: Farhan Beg

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A space vector based pulse width modulation control technique for the three-phase PWM converter is proposed in this paper. The proposed control scheme is based on a synchronous reference frame model. High performance and efficiency is obtained with regards to the DC bus voltage and the power factor considerations of the PWM rectifier thus leading to low losses. MATLAB/SIMULINK are used as a platform for the simulations and a SIMULINK model is presented in the paper. The results show that the proposed model demonstrates better performance and properties compared to the traditional SPWM method and the method improves the dynamic performance of the closed loop drastically. For the space vector based pulse width modulation, sine signal is the reference waveform and triangle waveform is the carrier waveform. When the value of sine signal is larger than triangle signal, the pulse will start producing to high; and then when the triangular signals higher than sine signal, the pulse will come to low. SPWM output will change by changing the value of the modulation index and frequency used in this system to produce more pulse width. When more pulse width is produced, the output voltage will have lower harmonics contents and the resolution will increase.

Keywords: power factor, SVPWM, PWM rectifier, SPWM

Procedia PDF Downloads 335
330 Study of Structure and Properties of Polyester/Carbon Blends for Technical Applications

Authors: Manisha A. Hira, Arup Rakshit

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Textile substrates are endowed with flexibility and ease of making–up, but are non-conductors of electricity. Conductive materials like carbon can be incorporated into textile structures to make flexible conductive materials. Such conductive textiles find applications as electrostatic discharge materials, electromagnetic shielding materials and flexible materials to carry current or signals. This work focuses on use of carbon fiber as conductor of electricity. Carbon fibers in staple or tow form can be incorporated in textile yarn structure to conduct electricity. The paper highlights the process for development of these conductive yarns of polyester/carbon using Friction spinning (DREF) as well as ring spinning. The optimized process parameters for processing hybrid structure of polyester with carbon tow on DREF spinning and polyester with carbon staple fiber using ring spinning have been presented. The studies have been linked to highlight the electrical conductivity of the developed yarns. Further, the developed yarns have been incorporated as weft in fabric and their electrical conductivity has been evaluated. The paper demonstrates the structure and properties of fabrics developed from such polyester/carbon blend yarns and their suitability as electrically dissipative fabrics.

Keywords: carbon fiber, conductive textiles, electrostatic dissipative materials, hybrid yarns

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329 Wind Power Forecasting Using Echo State Networks Optimized by Big Bang-Big Crunch Algorithm

Authors: Amir Hossein Hejazi, Nima Amjady

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In recent years, due to environmental issues traditional energy sources had been replaced by renewable ones. Wind energy as the fastest growing renewable energy shares a considerable percent of energy in power electricity markets. With this fast growth of wind energy worldwide, owners and operators of wind farms, transmission system operators, and energy traders need reliable and secure forecasts of wind energy production. In this paper, a new forecasting strategy is proposed for short-term wind power prediction based on Echo State Networks (ESN). The forecast engine utilizes state-of-the-art training process including dynamical reservoir with high capability to learn complex dynamics of wind power or wind vector signals. The study becomes more interesting by incorporating prediction of wind direction into forecast strategy. The Big Bang-Big Crunch (BB-BC) evolutionary optimization algorithm is adopted for adjusting free parameters of ESN-based forecaster. The proposed method is tested by real-world hourly data to show the efficiency of the forecasting engine for prediction of both wind vector and wind power output of aggregated wind power production.

Keywords: wind power forecasting, echo state network, big bang-big crunch, evolutionary optimization algorithm

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328 Multicasting Characteristics of All-Optical Triode Based on Negative Feedback Semiconductor Optical Amplifiers

Authors: S. Aisyah Azizan, M. Syafiq Azmi, Yuki Harada, Yoshinobu Maeda, Takaomi Matsutani

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We introduced an all-optical multi-casting characteristics with wavelength conversion based on a novel all-optical triode using negative feedback semiconductor optical amplifier. This study was demonstrated with a transfer speed of 10 Gb/s to a non-return zero 231-1 pseudorandom bit sequence system. This multi-wavelength converter device can simultaneously provide three channels of output signal with the support of non-inverted and inverted conversion. We studied that an all-optical multi-casting and wavelength conversion accomplishing cross gain modulation is effective in a semiconductor optical amplifier which is effective to provide an inverted conversion thus negative feedback. The relationship of received power of back to back signal and output signals with wavelength 1535 nm, 1540 nm, 1545 nm, 1550 nm, and 1555 nm with bit error rate was investigated. It was reported that the output signal wavelengths were successfully converted and modulated with a power penalty of less than 8.7 dB, which the highest is 8.6 dB while the lowest is 4.4 dB. It was proved that all-optical multi-casting and wavelength conversion using an optical triode with a negative feedback by three channels at the same time at a speed of 10 Gb/s is a promising device for the new wavelength conversion technology.

Keywords: cross gain modulation, multicasting, negative feedback optical amplifier, semiconductor optical amplifier

Procedia PDF Downloads 684
327 Noise Source Identification on Urban Construction Sites Using Signal Time Delay Analysis

Authors: Balgaisha G. Mukanova, Yelbek B. Utepov, Aida G. Nazarova, Alisher Z. Imanov

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The problem of identifying local noise sources on a construction site using a sensor system is considered. Mathematical modeling of detected signals on sensors was carried out, considering signal decay and signal delay time between the source and detector. Recordings of noises produced by construction tools were used as a dependence of noise on time. Synthetic sensor data was constructed based on these data, and a model of the propagation of acoustic waves from a point source in the three-dimensional space was applied. All sensors and sources are assumed to be located in the same plane. A source localization method is checked based on the signal time delay between two adjacent detectors and plotting the direction of the source. Based on the two direct lines' crossline, the noise source's position is determined. Cases of one dominant source and the case of two sources in the presence of several other sources of lower intensity are considered. The number of detectors varies from three to eight detectors. The intensity of the noise field in the assessed area is plotted. The signal of a two-second duration is considered. The source is located for subsequent parts of the signal with a duration above 0.04 sec; the final result is obtained by computing the average value.

Keywords: acoustic model, direction of arrival, inverse source problem, sound localization, urban noises

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326 The Capital Expenditure Reputation from Investor Perspective: A Signal of Better Future Performance

Authors: Juniarti, Agus Arianto Toly

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This study aims to examine the effect of capital expenditure on the investors’ responses. The respondents were companies with the best stock performance in each sector in 2017. The observation period is 2017 to 2019. Top 10 companies in each sector with the best stock performance in companies listed on the Indonesia Stock Exchange were selected. The main variables are a growth signal which is proxied by growth in capital spending and capital expenditure, and risk and investor response, which is proxied by CAR. Financial performance as measured by ROA is a control variable in this study. The results showed that the signal of growth as measured by capital expenditures responded positively by the market, the risk moderates this influence, companies with high risk will be responded negatively by investors and vice versa. This finding corrects previous findings that only looked at the signal aspect of growth, without linking it to risk. In addition, these findings reinforce the argument that investors buy the future of the company, not a momentary financial performance. This can be seen from the absence of ROA influence on investor response. This study found that companies need to manage risk appropriately, because the risk aspect of the company is a crucial factor for investors. High risks will eliminate the benefits of strategic decisions in this case in the form of capital expenditures.

Keywords: capital expenditure, growth signals, investor response, risk

Procedia PDF Downloads 141
325 Fault Detection and Isolation in Sensors and Actuators of Wind Turbines

Authors: Shahrokh Barati, Reza Ramezani

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Due to the countries growing attention to the renewable energy producing, the demand for energy from renewable energy has gone up among the renewable energy sources; wind energy is the fastest growth in recent years. In this regard, in order to increase the availability of wind turbines, using of Fault Detection and Isolation (FDI) system is necessary. Wind turbines include of various faults such as sensors fault, actuator faults, network connection fault, mechanical faults and faults in the generator subsystem. Although, sensors and actuators have a large number of faults in wind turbine but have discussed fewer in the literature. Therefore, in this work, we focus our attention to design a sensor and actuator fault detection and isolation algorithm and Fault-tolerant control systems (FTCS) for Wind Turbine. The aim of this research is to propose a comprehensive fault detection and isolation system for sensors and actuators of wind turbine based on data-driven approaches. To achieve this goal, the features of measurable signals in real wind turbine extract in any condition. The next step is the feature selection among the extract in any condition. The next step is the feature selection among the extracted features. Features are selected that led to maximum separation networks that implemented in parallel and results of classifiers fused together. In order to maximize the reliability of decision on fault, the property of fault repeatability is used.

Keywords: FDI, wind turbines, sensors and actuators faults, renewable energy

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324 Studying the Dynamical Response of Nano-Microelectromechanical Devices for Nanomechanical Testing of Nanostructures

Authors: Mohammad Reza Zamani Kouhpanji

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Characterizing the fatigue and fracture properties of nanostructures is one of the most challenging tasks in nanoscience and nanotechnology due to lack of a MEMS/NEMS device for generating uniform cyclic loadings at high frequencies. Here, the dynamic response of a recently proposed MEMS/NEMS device under different inputs signals is completely investigated. This MEMS/NEMS device is designed and modeled based on the electromagnetic force induced between paired parallel wires carrying electrical currents, known as Ampere’s Force Law (AFL). Since this MEMS/NEMS device only uses two paired wires for actuation part and sensing part, it represents highly sensitive and linear response for nanostructures with any stiffness and shapes (single or arrays of nanowires, nanotubes, nanosheets or nanowalls). In addition to studying the maximum gains at different resonance frequencies of the MEMS/NEMS device, its dynamical responses are investigated for different inputs and nanostructure properties to demonstrate the capability, usability, and reliability of the device for wide range of nanostructures. This MEMS/NEMS device can be readily integrated into SEM/TEM instruments to provide real time study of the fatigue and fracture properties of nanostructures as well as their softening or hardening behaviors, and initiation and/or propagation of nanocracks in them.

Keywords: MEMS/NEMS devices, paired wire actuators and sensors, dynamical response, fatigue and fracture characterization, Ampere’s force law

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323 The Disruptive Effect of COVID-19 on the Informativeness of Dividend Increases: Some Evidence from Johannesburg Stock Exchange-Listed Companies

Authors: Faustina Masocha

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This study sought to determine if the Covid-19 pandemic played a disruptive role in the signalling effect of dividend increases for the Top 40 companies listed on the Johannesburg Stock Exchange. With the use of Event Study Methodologies, it was found that dividend increases that were announced in the 2018 and 2019 financial years resulted in Cumulative Abnormal Returns (CARs) that were significantly different from zero, as confirmed by a p-value of 0,0300. This resulted in the conclusion that, under normal circumstances, dividend increases follow the precepts outlined in signalling theories which indicate that the announcement of dividend increases sent positive signals about the expected financial performance of a company. To prove the notion that Covid-19 plays a disruptive role on the signalling hypothesis, it was found from both parametric and non-parametric tests of significance that CARs related to dividend increases that were announced during the 2020 and 2021 financial years, when the Covid-19 pandemic was at its peak, were not significantly different from zero. Therefore, although the dividend increases still resulted in some CARs, such CARs were not statistically different from zero to confirm the signalling hypothesis. A p-value of 0.9830 from parametric t-tests and a p-value of 0.8971 from the Wilcoxon signed-rank test were used as a gauge that led to the conclusion that Covid-19 plays a disruptive effect on the signalling process of dividend increases.

Keywords: cumulative abnormal returns, dividend increases, event study methodology, signalling

Procedia PDF Downloads 120
322 Instant Location Detection of Objects Moving at High Speed in C-OTDR Monitoring Systems

Authors: Andrey V. Timofeev

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The practical efficient approach is suggested to estimate the high-speed objects instant bounds in C-OTDR monitoring systems. In case of super-dynamic objects (trains, cars) is difficult to obtain the adequate estimate of the instantaneous object localization because of estimation lag. In other words, reliable estimation coordinates of monitored object requires taking some time for data observation collection by means of C-OTDR system, and only if the required sample volume will be collected the final decision could be issued. But it is contrary to requirements of many real applications. For example, in rail traffic management systems we need to get data off the dynamic objects localization in real time. The way to solve this problem is to use the set of statistical independent parameters of C-OTDR signals for obtaining the most reliable solution in real time. The parameters of this type we can call as 'signaling parameters' (SP). There are several the SP’s which carry information about dynamic objects instant localization for each of C-OTDR channels. The problem is that some of these parameters are very sensitive to dynamics of seismoacoustic emission sources but are non-stable. On the other hand, in case the SP is very stable it becomes insensitive as a rule. This report contains describing the method for SP’s co-processing which is designed to get the most effective dynamic objects localization estimates in the C-OTDR monitoring system framework.

Keywords: C-OTDR-system, co-processing of signaling parameters, high-speed objects localization, multichannel monitoring systems

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321 Prediction of Music Track Popularity: A Machine Learning Approach

Authors: Syed Atif Hassan, Luv Mehta, Syed Asif Hassan

Abstract:

Hit song science is a field of investigation wherein machine learning techniques are applied to music tracks in order to extract such features from audio signals which can capture information that could explain the popularity of respective tracks. Record companies invest huge amounts of money into recruiting fresh talents and churning out new music each year. Gaining insight into the basis of why a song becomes popular will result in tremendous benefits for the music industry. This paper aims to extract basic musical and more advanced, acoustic features from songs while also taking into account external factors that play a role in making a particular song popular. We use a dataset derived from popular Spotify playlists divided by genre. We use ten genres (blues, classical, country, disco, hip-hop, jazz, metal, pop, reggae, rock), chosen on the basis of clear to ambiguous delineation in the typical sound of their genres. We feed these features into three different classifiers, namely, SVM with RBF kernel, a deep neural network, and a recurring neural network, to build separate predictive models and choosing the best performing model at the end. Predicting song popularity is particularly important for the music industry as it would allow record companies to produce better content for the masses resulting in a more competitive market.

Keywords: classifier, machine learning, music tracks, popularity, prediction

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320 Analysis of the Elastic Energy Released and Characterization of the Eruptive Episodes Intensity’s during 2014-2015 at El Reventador Volcano, Ecuador

Authors: Paúl I. Cornejo

Abstract:

The elastic energy released through Strombolian explosions has been quite studied, detailing various processes, sources, and precursory events at several volcanoes. We realized an analysis based on the relative partitioning of the elastic energy radiated into the atmosphere and ground by Strombolian-type explosions recorded at El Reventador volcano, using infrasound and seismic signals at high and moderate seismicity episodes during intense eruptive stages of explosive and effusive activity. Our results show that considerable values of Volcano Acoustic-Seismic Ratio (VASR or η) are obtained at high seismicity stages. VASR is a physical diagnostic of explosive degassing that we used to compare eruption mechanisms at El Reventador volcano for two datasets of explosions recorded at a Broad-Band BB seismic and infrasonic station located at ~5 kilometers from the vent. We conclude that the acoustic energy EA released during explosive activity (VASR η = 0.47, standard deviation σ = 0.8) is higher than the EA released during effusive activity; therefore, producing the highest values of η. Furthermore, we realized the analysis and characterization of the eruptive intensity for two episodes at high seismicity, calculating a η three-time higher for an episode of effusive activity with an occasional explosive component (η = 0.32, and σ = 0.42), than a η for an episode of only effusive activity (η = 0.11, and σ = 0.18), but more energetic.

Keywords: effusive, explosion quakes, explosive, Strombolian, VASR

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319 Effect of Far Infrared and Endothelial Cell Growth Supplement on Human Umbilical Vascular Endothelial Cells

Authors: Ming-Tzu Tsai, Jui-Ting Hsu, Chia-Chieh Lin, Feng-Tsai Chiang, Cheng-Chin Huang

Abstract:

Far infrared (FIR), an invisible and short electromagnetic waves ranges from 6-14 μm also defines as the “growth ray.” Although the mechanism of FIR is still unknown, most data have suggested that FIR could accelerate the skin microcirculation by elevating the blood flow and nitric-oxide (NO) synthesis. In this present work, the effect of FIR irradiation and endothelial cell growth supplement (ECGS) on human umbilical vascular endothelial cells (HUVECs) was evaluated. To understand whether the cell viability and NO production of HUVECs affected by NO, cells with/without ECGS were treated in the presence or absence of L-NAME, an eNOS inhibitor. For FIR exposure, FIR-emitted ceramic powders consisted of a variety of well-mixed metal oxides were developed. The results showed that L-NAME did had a strong effect on the inhibition of NO production, especially in the ECGS-treated group. However, the cell viability of each group was rarely affected in the presence of L-NAME. Cells with the incubation of ECGS showed much higher cell viability compared to the control. Moreover, NO production of HUVECs exposed to FIR irradiation was significantly inhibited in the presence of L-NAME. It suggested that NO could play a role modulating the downstream signals of HUVECs during FIR exposure.

Keywords: far-infrared irradiation (FIR), nitric oxide (NO), endothelial nitric oxide synthase (eNOS), endothelial cell growth supplement (ECGS)

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318 Lennox-gastaut Syndrome Associated with Dysgenesis of Corpus Callosum

Authors: A. Bruce Janati, Muhammad Umair Khan, Naif Alghassab, Ibrahim Alzeir, Assem Mahmoud, M. Sammour

Abstract:

Rationale: Lennox-Gastaut syndrome(LGS) is an electro-clinical syndrome composed of the triad of mental retardation, multiple seizure types, and the characteristic generalized slow spike-wave complexes in the EEG. In this article, we report on two patients with LGS whose brain MRI showed dysgenesis of corpus callosum(CC). We review the literature and stress the role of CC in the genesis of secondary bilateral synchrony(SBS). Method: This was a clinical study conducted at King Khalid Hospital. Results: The EEG was consistent with LGS in patient 1 and unilateral slow spike-wave complexes in patient 2. The MRI showed hypoplasia of the splenium of CC in patient 1, and global hypoplasia of CC combined with Joubert syndrome in patient 2. Conclusion: Based on the data, we proffer the following hypotheses: 1-Hypoplasia of CC interferes with functional integrity of this structure. 2-The genu of CC plays a pivotal role in the genesis of secondary bilateral synchrony. 3-Electrodecremental seizures in LGS emanate from pacemakers generated in the brain stem, in particular the mesencephalon projecting abnormal signals to the cortex via thalamic nuclei. 4-Unilateral slow spike-wave complexes in the context of mental retardation and multiple seizure types may represent a variant of LGS, justifying neuroimaging studies.

Keywords: EEG, Lennox-Gastaut syndrome, corpus callosum , MRI

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317 Implementation of Congestion Management Strategies on Arterial Roads: Case Study of Geelong

Authors: A. Das, L. Hitihamillage, S. Moridpour

Abstract:

Natural disasters are inevitable to the biodiversity. Disasters such as flood, tsunami and tornadoes could be brutal, harsh and devastating. In Australia, flooding is a major issue experienced by different parts of the country. In such crisis, delays in evacuation could decide the life and death of the people living in those regions. Congestion management could become a mammoth task if there are no steps taken before such situations. In the past to manage congestion in such circumstances, many strategies were utilised such as converting the road shoulders to extra lanes or changing the road geometry by adding more lanes. However, expansion of road to resolving congestion problems is not considered a viable option nowadays. The authorities avoid this option due to many reasons, such as lack of financial support and land space. They tend to focus their attention on optimising the current resources they possess and use traffic signals to overcome congestion problems. Traffic Signal Management strategy was considered a viable option, to alleviate congestion problems in the City of Geelong, Victoria. Arterial road with signalised intersections considered in this paper and the traffic data required for modelling collected from VicRoads. Traffic signalling software SIDRA used to model the roads, and the information gathered from VicRoads. In this paper, various signal parameters utilised to assess and improve the corridor performance to achieve the best possible Level of Services (LOS) for the arterial road.

Keywords: congestion, constraints, management, LOS

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316 A Micro-Scale of Electromechanical System Micro-Sensor Resonator Based on UNO-Microcontroller for Low Magnetic Field Detection

Authors: Waddah Abdelbagi Talha, Mohammed Abdullah Elmaleeh, John Ojur Dennis

Abstract:

This paper focuses on the simulation and implementation of a resonator micro-sensor for low magnetic field sensing based on a U-shaped cantilever and piezoresistive configuration, which works based on Lorentz force physical phenomena. The resonance frequency is an important parameter that depends upon the highest response and sensitivity through the frequency domain (frequency response) of any vibrated micro-scale of an electromechanical system (MEMS) device. And it is important to determine the direction of the detected magnetic field. The deflection of the cantilever is considered for vibrated mode with different frequencies in the range of (0 Hz to 7000 Hz); for the purpose of observing the frequency response. A simple electronic circuit-based polysilicon piezoresistors in Wheatstone's bridge configuration are used to transduce the response of the cantilever to electrical measurements at various voltages. Microcontroller-based Arduino program and PROTEUS electronic software are used to analyze the output signals from the sensor. The highest output voltage amplitude of about 4.7 mV is spotted at about 3 kHz of the frequency domain, indicating the highest sensitivity, which can be called resonant sensitivity. Based on the resonant frequency value, the mode of vibration is determined (up-down vibration), and based on that, the vector of the magnetic field is also determined.

Keywords: resonant frequency, sensitivity, Wheatstone bridge, UNO-microcontroller

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315 Emotional State and Cognitive Workload during a Flight Simulation: Heart Rate Study

Authors: Damien Mouratille, Antonio R. Hidalgo-Muñoz, Nadine Matton, Yves Rouillard, Mickael Causse, Radouane El Yagoubi

Abstract:

Background: The monitoring of the physiological activity related to mental workload (MW) on pilots will be useful to improve aviation safety by anticipating human performance degradation. The electrocardiogram (ECG) can reveal MW fluctuations due to either cognitive workload or/and emotional state since this measure exhibits autonomic nervous system modulations. Arguably, heart rate (HR) is one of its most intuitive and reliable parameters. It would be particularly interesting to analyze the interaction between cognitive requirements and emotion in ecologic sets such as a flight simulator. This study aims to explore by means of HR the relation between cognitive demands and emotional activation. Presumably, the effects of cognition and emotion overloads are not necessarily cumulative. Methodology: Eight healthy volunteers in possession of the Private Pilot License were recruited (male; 20.8±3.2 years). ECG signal was recorded along the whole experiment by placing two electrodes on the clavicle and left pectoral of the participants. The HR was computed within 4 minutes segments. NASA-TLX and Big Five inventories were used to assess subjective workload and to consider the influence of individual personality differences. The experiment consisted in completing two dual-tasks of approximately 30 minutes of duration into a flight simulator AL50. Each dual-task required the simultaneous accomplishment of both a pre-established flight plan and an additional task based on target stimulus discrimination inserted between Air Traffic Control instructions. This secondary task allowed us to vary the cognitive workload from low (LC) to high (HC) levels, by combining auditory and visual numerical stimuli to respond to meeting specific criteria. Regarding emotional condition, the two dual-tasks were designed to assure analogous difficulty in terms of solicited cognitive demands. The former was realized by the pilot alone, i.e. Low Arousal (LA) condition. In contrast, the latter generates a high arousal (HA), since the pilot was supervised by two evaluators, filmed and involved into a mock competition with the rest of the participants. Results: Performance for the secondary task showed significant faster reaction times (RT) for HA compared to LA condition (p=.003). Moreover, faster RT was found for LC compared to HC (p < .001) condition. No interaction was found. Concerning HR measure, despite the lack of main effects an interaction between emotion and cognition is evidenced (p=.028). Post hoc analysis showed smaller HR for HA compared to LA condition only for LC (p=.049). Conclusion. The control of an aircraft is a very complex task including strong cognitive demands and depends on the emotional state of pilots. According to the behavioral data, the experimental set has permitted to generate satisfactorily different emotional and cognitive levels. As suggested by the interaction found in HR measure, these two factors do not seem to have a cumulative impact on the sympathetic nervous system. Apparently, low cognitive workload makes pilots more sensitive to emotional variations. These results hint the independency between data processing and emotional regulation. Further physiological data are necessary to confirm and disentangle this relation. This procedure may be useful for monitoring objectively pilot’s mental workload.

Keywords: cognitive demands, emotion, flight simulator, heart rate, mental workload

Procedia PDF Downloads 275