Search results for: acoustic signals

Authors: Huawei Bai, Jianguo Yao, Fellow, IEEE

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Atrial fibrillation (AF) is the most common form of heart arrhythmia and is closely associated with mortality and morbidity in heart failure, stroke, and coronary artery disease. The development of single spot optical sensors enables widespread photoplethysmography (PPG) screening, especially for AF, since it represents a more convenient and noninvasive approach. To our knowledge, most existing studies based on public and unbalanced datasets can barely handle the multiple noises sources in the real world and, also, lack interpretability. In this paper, we construct a large- scale PPG dataset using measurements collected from PPG wrist- watch devices worn by volunteers and propose an attention-based two-stream heterogeneous neural network (TSHNN). The first stream is a hybrid neural network consisting of a three-layer one-dimensional convolutional neural network (1D-CNN) and two-layer attention- based bidirectional long short-term memory (Bi-LSTM) network to learn representations from temporally sampled signals. The second stream extracts latent representations from the PPG time-frequency spectrogram using a five-layer CNN. The outputs from both streams are fed into a fusion layer for the outcome. Visualization of the attention weights learned demonstrates the effectiveness of the attention mechanism against noise. The experimental results show that the TSHNN outperforms all the competitive baseline approaches and with 98.09% accuracy, achieves state-of-the-art performance.

Keywords: PPG wearables, atrial fibrillation, feature fusion, attention mechanism, hyber network

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Authors: Jalal M. Abdallah

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There is a great problem in testing and investigations the reliability of different type of transformers insulation materials. It summarized in how to create and simulate the real conditions of working transformer and testing its insulation materials for Partial Discharge PD, typically as in the working mode. A lot of tests may give untrue results as the physical behavior of the insulation material differs under tests from its working condition. In this work, the real working conditions were simulated, and a large number of specimens have been tested. The investigations first stage, begin with choosing samples of different types of insulation materials (papers, pressboards, etc.). The second stage, the samples were dried in ovens at 105 C⁰and 0.01bar for 48 hours, and then impregnated with dried and gasless oil (the water content less than 6 ppm.) at 105 C⁰and 0.01bar for 48 hours, after so specimen cooling at room pressure and temperature for 24 hours. The third stage is investigating PD for the samples using ICM PD measuring device. After that, a continuous test on oil-impregnated insulation materials (paper, pressboards) was developed, and the phase resolved partial discharge pattern of PD signals was measured. The important of this work in providing the industrial sector with trusted high accurate measuring results based on real simulated working conditions. All the PD patterns (results) associated with a discharge produced in well-controlled laboratory condition. They compared with other previous and other laboratory results. In addition, the influence of different temperatures condition on the partial discharge activities was studied.

Keywords: transformers, insulation materials, voids, partial discharge

Procedia PDF Downloads 288

Authors: Han-Bin Park, Taesam Kang, SunKi Hong, Jeong Hoi Gu

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The piezoelectric material is being used widely for actuators due to its large power density with simple structure. It can generate a larger force than the conventional actuators with the same size. Furthermore, the response time of piezoelectric actuators is very short, and thus, it can be used for very fast system applications with compact size. To control the piezoelectric actuator, we need analog signal conditioning circuits as well as digital microcontrollers. Conventional microcontrollers are not equipped with analog parts and thus the control system becomes bulky compared with the small size of the piezoelectric devices. To overcome these weaknesses, we are developing one-chip micro controller that can handle analog and digital signals simultaneously using mixed signal FPGA technology. We used the SmartFusion™ FPGA device that integrates ARM®Cortex-M3, analog interface and FPGA fabric in a single chip and offering full customization. It gives more flexibility than traditional fixed-function microcontrollers with the excessive cost of soft processor cores on traditional FPGAs. In this paper we introduce the design of single chip controller using mixed signal FPGA, SmartFusion™[1] device. To demonstrate its performance, we implemented a PI controller for power driving circuit and a 5th order H-infinity controller for the system with piezoelectric actuator in the FPGA fabric. We also demonstrated the regulation of a power output and the operation speed of a 5th order H-infinity controller.

Keywords: mixed signal FPGA, PI control, piezoelectric actuator, SmartFusion™

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Authors: Nur Aimi Syairah Mohd Abdul Alim, Azilah Ajit, A. Z. Sulaiman

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The present study aimed to investigate the effects of ultrasound-assisted extraction (UAE) on the extraction of Vitexin and Iso-Vitexin from Ficus deltoidea plants. In recent years, ultrasound technology has been found to be a potential herbal extraction technique. The passage of ultrasound energy in a liquid medium generates mechanical agitation and other physical effects due to acoustic cavitation. The main goal is to optimised ultrasonic-assisted extraction condition providing the highest extraction yield with the most desirable antioxidant activity and stability. Thus, a series of experiments has been developed to investigate the effect of ultrasound energy on the vegetal material and the implemented parameters by using HPLC-photodiode array detection. The influences of several experimental parameters on the ultrasonic extraction of Ficus deltoidea leaves were investigated: extraction time (1-8 h), solvent-to-water ratio (1:10 to 1:50), temperature (50–100 °C), duty cycle (10–continuous sonication) and intensity. The extracts at the optimized condition were compared with those obtained by conventional boiling extraction, in terms of bioactive constituents yield and chemical composition. The compounds of interest identified in the extracts were Vitexin and Isovitexin, which possess anti-diabetic, anti-oxidant and anti-cancer properties. Results showed that the main variables affecting the extraction process were temperature and time. Though in less extent, solvent-to-water ratio, duty cycle and intensity are also demonstrated to be important parameters. The experimental values under optimal conditions were in good consistent with the predicted values, which suggested that ultrasonic-assisted extraction (UAE) is more efficient process as compared to conventional boiling extraction. It recommended that ultrasound extraction of Ficus deltoidea plants are feasible to replace the traditional time-consuming and low efficiency preparation procedure in the future modernized and commercialized manufacture of this highly valuable herbal medicine.

Keywords: Ficus, ultrasounds, vitexin, isovitexin

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Authors: Angela U. Makolo, Temitayo A. Olagunju

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The knowledge of signaling pathways is central to understanding the biological mechanisms of organisms since it has been identified that in eukaryotic organisms, the number of signaling pathways determines the number of ways the organism will react to external stimuli. Signaling pathways are studied using protein interaction networks constructed from protein-protein interaction data obtained using high throughput experimental procedures. However, these high throughput methods are known to produce very high rates of false positive and negative interactions. In order to construct a useful protein interaction network from this noisy data, computational methods are applied to validate the protein-protein interactions. In this study, a computational technique to identify signaling pathways from a protein interaction network constructed using validated protein-protein interaction data was designed. A weighted interaction graph of the Saccharomyces cerevisiae (Baker’s Yeast) organism using the proteins as the nodes and interactions between them as edges was constructed. The weights were obtained using Bayesian probabilistic network to estimate the posterior probability of interaction between two proteins given the gene expression measurement as biological evidence. Only interactions above a threshold were accepted for the network model. A pathway was formalized as a simple path in the interaction network from a starting protein and an ending protein of interest. We were able to identify some pathway segments, one of which is a segment of the pathway that signals the start of the process of meiosis in S. cerevisiae.

Keywords: Bayesian networks, protein interaction networks, Saccharomyces cerevisiae, signalling pathways

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Authors: Yana Xiao

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The invention of Triboelectric Nanogenerators (TENGs) provides an effective approach to the sustainable power of energy. Liquid-solid interfaces-based TENGs have been researched in virtue of less friction for harvesting energy from raindrops, rivers, and oceans in the form of water flows. However, TENGs based on droplets have rarely been investigated. In this study, we have proposed a new kind of droplet tube-based TENG (DT-TENG) with free-standing and reformative grating electrodes. Both straight and curved DT-TENGs were designed, fabricated, and evaluated, including straight tubes TENG with 27 electrodes and curved tubes TENG of 25cm radius curvature- at the inclination of 30°, 45° and 60° respectively. Different materials and hydrophobicity treatments for the tubes have also been studied, together with a discussion on the mechanism and applications of DT-TENGs. As different types of liquid discrepant energy performance, this kind of DT-TENG can be potentially used in laboratories to identify liquid or solvent. In addition, a smart fishing float is contrived, which can recognize different levels of movement speeds brought about by different weights and generate corresponding electric signals to remind the angler. The electric generation performance when using a PVC helix tube around a cylinder is similar in straight situations under the inclination of 45° in this experiment. This new structure changes the direction of a water drop or flows without losing kinetic energy, which makes utilizing Helix-Tube-TENG to harvest energy from different building morphologies possible.

Keywords: triboelectric nanogenerator, energy harvest, liquid tribomaterial, structure innovation

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Authors: S. Aswath, Chinmaya Krishna Tilak, Amal Suresh, Ganesh Udupa

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There are technologies to control a humanoid robot in many ways. But the use of Electromyogram (EMG) electrodes has its own importance in setting up the control system. The EMG based control system helps to control robotic devices with more fidelity and precision. In this paper, development of an electromyogram based interface for human gesture recognition for the control of a humanoid robot is presented. To recognize control signs in the gestures, a single channel EMG sensor is positioned on the muscles of the human body. Instead of using a remote control unit, the humanoid robot is controlled by various gestures performed by the human. The EMG electrodes attached to the muscles generates an analog signal due to the effect of nerve impulses generated on moving muscles of the human being. The analog signals taken up from the muscles are supplied to a differential muscle sensor that processes the given signal to generate a signal suitable for the microcontroller to get the control over a humanoid robot. The signal from the differential muscle sensor is converted to a digital form using the ADC of the microcontroller and outputs its decision to the CM-530 humanoid robot controller through a Zigbee wireless interface. The output decision of the CM-530 processor is sent to a motor driver in order to control the servo motors in required direction for human like actions. This method for gaining control of a humanoid robot could be used for performing actions with more accuracy and ease. In addition, a study has been conducted to investigate the controllability and ease of use of the interface and the employed gestures.

Keywords: electromyogram, gesture, muscle sensor, humanoid robot, microcontroller, Zigbee

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Authors: Kun Chen, Yan Wang, Yangyu Zhao, Shufang Li, Lian Chen, Xiaoyue Guo, Jue Zhang, Jing Fang

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The coupling strength between uterine electromyography (UEMG) and Fetal heart rate (FHR) signals during peripartum reflects the fetal biophysical activities. Therefore, UEMG-FHR coupling characterization is instructive in assessing placenta function. This study introduced a physiological marker named elevated frequency of UEMG-FHR coupling (E-UFC) and explored its predictive value for pregnancies complicated by pre-eclampsia and small for gestational age (SGA). Placental insufficiency patients (n=12) and healthy volunteers (n=24) were recruited and participated. UEMG and FHR were recorded non-invasively by a trans-abdominal device in women at term with singleton pregnancy (32-37 weeks) from 10:00 pm to 8:00 am. The product of the wavelet coherence and the wavelet cross-spectral power between UEMG and FHR was used to weight these two effects in order to quantify the degree of the UEMG-FHR coupling. E-UFC was exacted from the resultant spectrogram by calculating the mean value of the high-coherence (r > 0.5) frequency band. Results showed the high-coherence between UEMG and FHR was observed in the frequency band (1/512-1/16Hz). In addition, E-UFC in placental insufficiency patients was weaker compared to healthy controls (p < 0.001) at group level. These findings suggested the proposed approach could be used to quantitatively characterize the fetal biophysical activities, which is beneficial for early detection of placental insufficiency and reduces the occurrence of adverse pregnancy.

Keywords: uterine electromyography, fetal heart rate, coupling analysis, wavelet analysis

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Authors: Ngoc Tu Truong, Nuong T. Bui, Ben Rao, Ya L. Shen

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Quorum sensing is a phenomenon present in many gram-negative bacteria that allows bacterial communication and controlled expression of a large suite of genes through quorum sensing signals - N-acyl homoserine lactones (AHLs). In order to investigate the ability of the rhlR/rhlI quorum sensing system in Pseudomonas aeruginosa to express the ß-Galactosidase reporter gene, an engineered E. coli strain EpHL02, was genetically engineered. This engineered E. coli strain EpHL02 responded to the presence of the N-butanoyl homoserine lactone and N-hexanoyl homoserine lactone to express the ß-Galactosidase reporter gene at a concentration limit of 5x10⁻⁸ M. This was also found to be comparable to AHLs extraction from Serratia marcescens H31. Moreover, we examined this ability of this engineered E. coli strain for respond of AHLs from extractions of Pseudomonas aeruginosa ATCC9027. The results demonstrated that the rhlR/rhlI quorum sensing system can express the ß-Galactosidase reporter gene by using the N-butanoyl homoserine lactone, N-hexanoyl homoserine lactone and AHLs from extractions of Serratia marcescens H31 and Pseudomonas aeruginosa ATCC9027 in the engineered E. coli strain EpHL02.

Keywords: N-butanoyl homoserine lactone, C4-HSL, N-hexanoyl homoserine lactone, C6-HSL, Pseudomonas aeruginosa, quorum sensing, Serratia marcescens, ß-galactosidase reporter gene

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Authors: Cristian Pauna

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With few steps away from the 2020, investments in financial markets is a common activity nowadays. In the electronic trading environment, the automated investment software has become a major part in the business intelligence system of any modern financial company. The investment decisions are assisted and/or made automatically by computers using mathematical algorithms today. The complexity of these algorithms requires computer assistance in the investment process. This paper will present several investment strategies that can be automated with algorithmic trading for Deutscher Aktienindex DAX30. It was found that, based on several price action mathematical models used for high-frequency trading some investment strategies can be optimized and improved for automated investments with good results. This paper will present the way to automate these investment decisions. Automated signals will be built using all of these strategies. Three major types of investment strategies were found in this study. The types are separated by the target length and by the exit strategy used. The exit decisions will be also automated and the paper will present the specificity for each investment type. A comparative study will be also included in this paper in order to reveal the differences between strategies. Based on these results, the profit and the capital exposure will be compared and analyzed in order to qualify the investment methodologies presented and to compare them with any other investment system. As conclusion, some major investment strategies will be revealed and compared in order to be considered for inclusion in any automated investment system.

Keywords: Algorithmic trading, automated investment systems, limit conditions, trading principles, trading strategies

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Authors: Naheem Olakunle Adesina

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The memristor is considered as one of the promising candidates for mamoelectronic engineering and applications. Owing to its high compatibility with CMOS, nanoscale size, and low power consumption, memristor has been employed in the design of commonly used circuits such as phase-locked loop (PLL). In this paper, we designed a memristor-based loop filter (LF) together with other components of PLL. Following this, we evaluated the noise-rejection feature of loop filter by comparing the noise levels of input and output signals of the filter. Our SPICE simulation results showed that memristor behaves like a linear resistor at high frequencies. The result also showed that loop filter blocks the high-frequency components from phase frequency detector so as to provide a stable control voltage to the voltage controlled oscillator (VCO). In addition, we examined the effects of temperature on the performance of the designed phase locked loop circuit. A critical temperature, where there is frequency drift of VCO as a result of variations in control voltage, is identified. In conclusion, the memristor is a suitable choice for nanoelectronic systems owing to a small area, low power consumption, dense nature, high switching speed, and endurance. The proposed memristor-based loop filter, together with other components of the phase locked loop, can be designed using memristive emulator and EDA tools in current CMOS technology and simulated.

Keywords: Fast Fourier Transform, hysteresis curve, loop filter, memristor, noise, phase locked loop, voltage controlled oscillator

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Authors: Saad M. Darwish, Magda M. Madbouly, Murad B. Khorsheed

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Sign Languages (SL) are the most accomplished forms of gestural communication. Therefore, their automatic analysis is a real challenge, which is interestingly implied to their lexical and syntactic organization levels. Hidden Markov models (HMM’s) have been used prominently and successfully in speech recognition and, more recently, in handwriting recognition. Consequently, they seem ideal for visual recognition of complex, structured hand gestures such as are found in sign language. In this paper, several results concerning static hand gesture recognition using an algorithm based on Type-2 Fuzzy HMM (T2FHMM) are presented. The features used as observables in the training as well as in the recognition phases are based on Singular Value Decomposition (SVD). SVD is an extension of Eigen decomposition to suit non-square matrices to reduce multi attribute hand gesture data to feature vectors. SVD optimally exposes the geometric structure of a matrix. In our approach, we replace the basic HMM arithmetic operators by some adequate Type-2 fuzzy operators that permits us to relax the additive constraint of probability measures. Therefore, T2FHMMs are able to handle both random and fuzzy uncertainties existing universally in the sequential data. Experimental results show that T2FHMMs can effectively handle noise and dialect uncertainties in hand signals besides a better classification performance than the classical HMMs. The recognition rate of the proposed system is 100% for uniform hand images and 86.21% for cluttered hand images.

Keywords: hand gesture recognition, hand detection, type-2 fuzzy logic, hidden Markov Model

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Authors: Sk Shamim Hasan Abir, Karen Lozano, Mohammed Jasim Uddin

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Over the last few years, nanofiber-based triboelectric nanogenerator (TENG) has caught great attention among researchers all over the world due to its inherent capability of converting mechanical energy to usable electrical energy. In this study, poly(vinylidene fluoride) (PVDF) and thermoplastic polyurethane (TPU) nanofiber prepared by Forcespinning® (FS) technique were used to fabricate TENG for self-charging energy storage device and biomechanical body motion sensor. The surface of the TPU nanofiber was modified by uniform deposition of thin gold film to enhance the frictional properties; yielded 254 V open-circuit voltage (Voc) and 86 µA short circuit current (Isc), which were 2.12 and 1.87 times greater in contrast to bare PVDF-TPU TENG. Moreover, the as-fabricated PVDF-TPU/Au TENG was tested against variable capacitors and resistive load, and the results showed that with a 3.2 x 2.5 cm2 active contact area, it can quick charge up to 7.64 V within 30 seconds using a 1.0 µF capacitor and generate significant 2.54 mW power, enough to light 75 commercial LEDs (1.5 V each) by the hand tapping motion at 4 Hz (240 beats per minutes (bpm)) load frequency. Furthermore, the TENG was attached to different body parts to capture distinctive electrical signals for various body movements, elucidated the prospective usability of our prepared nanofiber-based TENG in wearable body motion sensor application.

Keywords: biomotion sensor, forcespinning, nanofibers, triboelectric nanogenerator

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Authors: D. Venu, N. V. Koteswara Rao

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Space – time adaptive processing (STAP) is an effective tool for detecting a moving target in spaceborne or airborne radar systems. Since airborne passive radar systems utilize broadcast, navigation and excellent communication signals to perform various surveillance tasks and also has attracted significant interest from the distinct past, therefore the need of the hour is to have cost effective systems as compared to conventional active radar systems. Moreover, requirements of small number of secondary samples for effective clutter suppression in bi-static passive radar offer abundant illuminator resources for passive surveillance radar systems. This paper presents a framework for incorporating knowledge sources directly in the space-time beam former of airborne adaptive radars. STAP algorithm for clutter mitigation for passive bi-static radar has better quantitation of the reduction in sample size thereby amalgamating the earlier data bank with existing radar data sets. Also, we proposed a novel method to estimate the clutter matrix and perform STAP for efficient clutter suppression based on small sample size. Furthermore, the effectiveness of the proposed algorithm is verified using MATLAB simulations in order to validate STAP algorithm for passive bi-static radar. In conclusion, this study highlights the importance for various applications which augments traditional active radars using cost-effective measures.

Keywords: bistatic radar, clutter, covariance matrix passive radar, STAP

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Authors: Reagan Rodriguez

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The following research is a case study of two white patients with white extremist values and their Latina Clinician. Researchers suggest that white supremacy as an ideology has been documented in the United States since the early 1800s. Ethnicity and race were growing key factors linked to central motives behind hate crimes in U.S., which may suggest that we are living in another wave of white supremacist and domestic terrorism that seek to eradicate a threatening and dangerous “other”. This research seeks to address and contribute a qualitative perspective to white supremacist ideology within a bio-psycho-social framework. The current research seeks to contribute to address the gap in literature on ethnic minority clinicians and white patients with racist ideology. The research also seeks to examine the themes not commonly found in racially matched and gendered matched therapeutic dyads where patients hold white extremist values. This case study examines white supremacist ideology from a psychodynamic perspective, examining themes such as “feeling forgotten”, reduced empathy related to “broken promises”, sexualization of the passing minority counselor, and utilizing minimal autonomy in verbal and non-verbal signals. A thematic analysis of case notes and quotes are used to further contextualize emerging therapeutic themes and the psychodynamic analysis of the manifestation of white supremacist actions ranging from active to passive forms of violence.

Keywords: case study, extremism, race and gender, white supremacist ideology

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Authors: Md Mizanur Rahman, Lotanna Micah Nneji, Adeola C. Adeniyi, Edem Archibong Eniang, Abiodun B. Onadeko, Felista Kasyoka Kilunda, Babatunde E. Adedeji, Ifeanyi C. Nneji, Adiaha A. A. Ugwumba, Jie-Qiong Jin, Min-Sheng Peng, Caroline Olory, Nsikan Eninekit, Jing Che

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Nigeria contains a number of forest habitats that believed to host highly rich amphibian diversity. However, a dearth of herpetological studies has restricted information on the amphibian diversity in Nigeria. To cover the gap of knowledge, this study focused field surveys on relatively less studied forests–Afi Forest Reserve and Ikpan forest ecosystem. The goal of this study is to make a checklist and to investigate the habitat preferences of amphibians in these two forests. The study areas were surveyed between August 2018 and July 2019 following visual and acoustic methods. Individuals were identified using the morphological and molecular (16S ribosomal RNA) approach. Literature searches were conducted to document additional species that were not encountered during the current field surveys. Using the observational records and arrays of diversity indices, the patterns of species richness and abundance across habitat types were evaluated. Voucher specimens and tissue samples were deposited in the museums of the Department of Zoology, University of Ibadan Nigeria, and the remainder at the Kunming Institute of Zoology (KIZ), Chinese Academy of Sciences, Kunming, China. The result of this study revealed the presence of 30 and 31 amphibian species from the Afi Forest Reserve and the Ikpan Forest Ecosystem, respectively. There were two unidentified species from AFR and one from IFE. In total, 324 individuals of amphibian species were observed from the two study areas. Forest and swamps showed high species diversity and richness than the agricultural field and savannah. Savannah and agricultural fields had the highest similarity in the species composition. Given the increased human disturbances and consequent threats to these forests, this study offers recommendations for the initiation of conservation plans immediately.

Keywords: biodiversity, conservation, cryptic species, ecology, integrated taxonomy, species inventory

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Authors: Ugochukwu Ejike Akpudo, Jank-Wook Hur

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The increasing demand for improved productivity, maintainability, and reliability has prompted rapidly increasing research studies on the emerging condition-based maintenance concept- Prognostics and health management (PHM). Varieties of fuel pumps serve critical functions in several hydraulic systems; hence, their failure can have daunting effects on productivity, safety, etc. The need for condition monitoring and assessment of these pumps cannot be overemphasized, and this has led to the uproar in research studies on standard feature extraction techniques for optimized condition assessment of fuel pumps. By extracting time-based, frequency-based and the more robust time-frequency based features from these vibrational signals, a more comprehensive feature assessment (and selection) can be achieved for a more accurate and reliable condition assessment of these pumps. With the aid of emerging deep classification and regression algorithms like the locally linear embedding (LLE), we propose a method for comprehensive condition assessment of electromagnetic fuel pumps (EMFPs). Results show that the LLE as a comprehensive feature extraction technique yields better feature fusion/dimensionality reduction results for condition assessment of EMFPs against the use of single features. Also, unlike other feature fusion techniques, its capabilities as a fault classification technique were explored, and the results show an acceptable accuracy level using standard performance metrics for evaluation.

Keywords: electromagnetic fuel pumps, comprehensive feature extraction, condition assessment, locally linear embedding, feature fusion

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Authors: Kuplevatsky V., Kuplevatskay, Cherkashin M., Berezina N.

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After 6 months, a violation of the differentiation of the structure of the gland due to edema in 100%. 20% retained signs of a tumor according to DWI/ADC data. By 12 months, the reduction in the size of the gland is 100%. In all cases, no diffusion restriction was observed. The study after 18 months showed no significant changes in all (100%) patients. In the study, 24 months after treatment, the size of the gland was stable in all cases (+/- up to 5%). Diffuse decrease in T2VI signals from peripheral zones, without signs of diffusion restriction in 100%. After 30 months, signs of recovery of adenomatous changes in the transient zone were revealed in 85%. After 36 and 42 months, the restoration of organ differentiation was observed in 93% of patients. In 4 patients, by the 48th month, signs of biochemical relapse were clinically noted. According to the MRI data, signs of a local relapse were revealed. After 48 months, there were signs of restoration of organ differentiation, which allowed the use of PI-RADS criteria. The study after 54 months showed no changes compared to the control. 60 months after treatment, 97% of patients showed a restoration of differentiation of the gland structure, which allows evaluating the organ according to PI-RADS criteria Conclusions: The beginning of restoration of the structure of the prostate gland began 24 months after proton radiation therapy, the PI-RADS criteria can be fully applied after 48 months of treatment. Control studies every 6 months without clinical signs of relapse are not advisable. Local control of the prostate tumor after proton radiation therapy was achieved in 95% of patients during the entire follow-up period ( 60 months).

Keywords: proton therapy, prostate cancer, MRI imaging, PI-RADS

Procedia PDF Downloads 85

Authors: Kyra Kannen, Sonja D. Roelen, Sebastian Schnieder, Jarek Krajewski, Steffen Holsteg, André Karger, Johanna Askeridis, Celina Slawik, Philip Mildner, Jens Piesk, Ruslan David, Holger Kürten, Benjamin Oster, Robert Malzan, Mike Ludemann

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Virtual Reality (VR) is increasingly recognized for its potential in transforming mental disorder treatment, offering advantages such as cost-effectiveness, time efficiency, accessibility, reduced stigma, and scalability. While the application of VR in the context of anxiety disorders has been extensively evaluated and demonstrated to be effective, the utilization of VR as a therapeutic treatment for depression remains under-investigated. Our goal is to pioneer immersive VR therapy modules for treating major depression, alongside a web-based system for home use. We develop a modular digital therapy platform grounded in psychodynamic therapy interventions which addresses stress reduction, exploration of social situations and relationship support, social skill training, avoidance behavior analysis, and psychoeducation. In addition, an automated depression monitoring system, based on acoustic voice analysis, is implemented in the form of a speech-based diary to track the affective state of the user and depression severity. The use of immersive VR facilitates patient immersion into complex and realistic interpersonal interactions with high emotional engagement, which may contribute to positive treatment acceptance and satisfaction. In a proof-of-concept study, 45 depressed patients were assigned to VR or web-platform modules, evaluating user experience, usability and additional metrics including depression severity, mindfulness, interpersonal problems, and treatment satisfaction. The findings provide valuable insights into the effectiveness and user-friendliness of VR and web modules for depression therapy and contribute to the refinement of more tailored digital interventions to improve mental health.

Keywords: virtual reality therapy, digital health, depression, psychotherapy

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Authors: B. Elshafei, X. Mao

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The demand for renewable energy is significantly increasing, major investments are being supplied to the wind power generation industry as a leading source of clean energy. The wind energy sector is entirely dependable and driven by the prediction of wind speed, which by the nature of wind is very stochastic and widely random. This s0tudy employs deep multi-fidelity Gaussian process regression, used to predict wind speeds for medium term time horizons. Data of the RUNE experiment in the west coast of Denmark were provided by the Technical University of Denmark, which represent the wind speed across the study area from the period between December 2015 and March 2016. The study aims to investigate the effect of pre-processing the data by denoising the signal using empirical wavelet transform (EWT) and engaging the vector components of wind speed to increase the number of input data layers for data fusion using deep multi-fidelity Gaussian process regression (GPR). The outcomes were compared using root mean square error (RMSE) and the results demonstrated a significant increase in the accuracy of predictions which demonstrated that using vector components of the wind speed as additional predictors exhibits more accurate predictions than strategies that ignore them, reflecting the importance of the inclusion of all sub data and pre-processing signals for wind speed forecasting models.

Keywords: data fusion, Gaussian process regression, signal denoise, temporal extrapolation

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Authors: Ahmad Samim Ranjbar, Shoshi Mizokami

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Kabul is the heart of political, commercial, cultural, educational and social life in Afghanistan and the Kabul fifth fastest growing city in the world, since 2001 with the establishment of new government Lack of adequate employment opportunities and basic utility services in remote provinces have prompted people to move to Kabul and other urban areas. From 2001 to the present, a rapid increase in population, and also less income of the people most of residence tend to use public transport, especially buses, however there is no proper bus system exist in Kabul city, because of wars, from 1992 to 2001 Kabul suffered damage and destruction of its transportation facilities including pavements, sidewalks, traffic circles, drainage systems, traffic signs and signals, trolleybuses and almost all of the public transit buses (e.g. Millie bus). This research is a primary and very important phase into Kabul city transportation and especially an initial and important step toward using large bus in Kabul city, which the main purpose of this research is to find the demand of Kabul city residence for public transport (Large Bus) and compare it with the actual supply from government. Finding of this research shows that the demand of Kabul city residence for the public transport (Large Bus) exceed the supply from the government, means that current public transportation (Large Bus) is not sufficient to serve people of Kabul city, it is mentionable that according to this research there is no need to build a new road or exclusive way for bus, this research propose to government for investment on the public transportation and exceed the number of large buses to can handle the current demand for public transport.

Keywords: transportation, planning, public transport, large bus, Kabul, Afghanistan

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Authors: Waled A. Dawoud, Abdelazim M. Negm, Nasser M. Saleh

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Offshore piling generates underwater sound at level high enough to cause physical damage or hearing impairment to the marine mammals. Several methods can be used to mitigate the effect of underwater noise from offshore pile driving on marine mammals which can be divided into three main approaches. The first approach is to keep the mammal out of the high-risk area by using aversive sound waves produced by acoustic mitigation devices such as playing-back of mammal's natural predator vocalization, alarm or distress sounds, and anthropogenic sound. The second approach is to reduce the amount of underwater noise from pile driving using noise mitigation techniques such as bubble curtains, isolation casing, and hydro-sound dampers. The third approach is to eliminate the overlap of underwater waves by using prolonged construction process. To investigate the effectiveness of different noise mitigation methods; a pile driven with 235 kJ rated energy diesel hammer near Jeddah Coast, Kingdom of Saudi Arabia was used. Using empirical sound exposure model based on Red Sea characteristics and limits of National Oceanic and Atmospheric Administration; it was found that the aversive sound waves should extend to 1.8 km around the pile location. Bubble curtains can reduce the behavioral disturbance area up to 28%; temporary threshold shift up to 36%; permanent threshold shift up to 50%; and physical injury up to 70%. Isolation casing can reduce the behavioral disturbance range up to 12%; temporary threshold shift up to 21%; permanent threshold shift up to 29%; and physical injury up to 46%. Hydro-sound dampers efficiency depends mainly on the used technology and it can reduce the behavioral disturbance range from 10% to 33%; temporary threshold shift from 18% to 25%; permanent threshold shift from 32% to 50%; and physical injury from 46% to 60%. To prolong the construction process, it was found that the single pile construction, use of soft start, and keep time between two successive hammer strikes more than 3 seconds are the most effective techniques.

Keywords: offshore pile driving, sound propagation models, noise effects on marine mammals, Underwater noise mitigation

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Authors: Prasad Pokkunuri

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Visco-elastic materials combine the stress response properties of both solids and fluids and have found use in a variety of damping applications – both vibrational and acoustic. Defense and automotive applications, in particular, are subject to high impact and shock loading – for example: aircraft landing gear, firearms, and shock absorbers. Field responsive fluids – a class of smart materials – are the preferred choice of energy absorbents because of their controllability. These fluids’ stress response can be controlled by the application of a magnetic or electric field, in a closed loop. Their rheological properties – elasticity, plasticity, and viscosity – can be varied all the way from that of a liquid such as water to a hard solid. This work presents a simplified model to study the impulse response behavior of such fluids for use in recoil damping systems. The well-known Burger’s equation, in conjunction with various visco-elastic constitutive models, is used to represent fluid behavior. The Kelvin-Voigt, Upper Convected Maxwell (UCM), and Oldroyd-B constitutive models are implemented in this study. Using these models in a one-dimensional framework eliminates additional complexities due to geometry, pressure, body forces, and other source terms. Using a finite difference formulation to numerically solve the governing equation(s), the response to an initial impulse is studied. The disturbance is confined within the problem domain with no-inflow, no-outflow boundary conditions, and its decay characteristics studied. Visco-elastic fluids typically involve a time-dependent stress relaxation which gives rise to interesting behavior when subjected to an impulsive load. For particular values of viscous damping and elastic modulus, the fluid settles into a stable oscillatory state, absorbing and releasing energy without much decay. The simplified formulation enables a comprehensive study of different modes of system response, by varying relevant parameters. Using the insights gained from this study, extension to a more detailed multi-dimensional model is considered.

Keywords: Burgers Equation, Impulse Response, Recoil Damping Systems, Visco-elastic Fluids

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Authors: Tianqi Yin

Abstract:

The sharia had been the legislative basis in the Ottoman Empire since its emergence. The authority of sharia was superlative in the Islamic society compared to the power of the sulta, the nominal ruler of the nation, regulating essentially every aspect of people’s lives according to an ethical code. In modernity, however, as European sovereignty employed forces to re-engineer the Islamic world to make it more like their own, a society ruled by a state, the Ottoman legislation system encountered a great challenge of adopting codified laws to replace sharia with the formulation of the Mecelle being a prominent case. Interpretations of this transformation have been contentious, with the key debate revolving around whether these codified laws are authentic representations of sharia or alien legal formulations authorized by the modern nation-state under heavy European colonial influence. Because of the difference in methodology of the diverse theories, challenges toward having a universal conclusion on this issue remain. This paper argues that the formulation of the Mecelle and other codified laws is a discontinuity of sharia due to European modernity’s influence and that the emphasis on elements of Islamic laws is a tactic employed to promote this process. These codified laws signals a complete social transformation from the Islamic society ruled by the sharia to a replication of the European society that is ruled by a comprehensive ruling system of the modern state. In addition to advancing the discussion on the characterization of the codification movement in the Ottoman Empire in modernity, the research also promotes the determination of the nature of the modern codification movement globally.

Keywords: codification, mecelle, modernity, sharia, ottoman empire

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Authors: Yang Yang, Lu Xin

Abstract:

The study of extant musical sites can provide a side-by-side picture of historical ethnomusicological information. In their data collection on Chinese opera houses, researchers found that one Ming Dynasty opera house reached a width of nearly 18 meters, while all opera houses of the same period and after it was far from such a width, being significantly smaller than 18 meters. The historical transient fluctuations in the data dimension of width that caused Chinese theatres to fluctuate in the absence of construction scale constraints have piqued the interest of researchers as to why there is data variation in width. What factors have contributed to the lack of further expansion in the width of theatres? To address this question, this study used a comparative approach to conduct a venue experiment between this theater stage and another theater stage for non-heritage opera performances, collecting the subjective perceptions of performers and audiences at different theater stages, as well as combining BK Connect platform software to measure data such as echo and delay. From the subjective and objective results, it is inferred that the Chinese ancients discovered and understood the acoustical phenomenon of the Haas effect by exploring the effect of stage width on musical performance and appreciation of listening states during the Ming Dynasty and utilized this discovery to serve music in subsequent stage construction. This discovery marked a node of evolution in Chinese architectural acoustics technology driven by musical demands. It is also instructive to note that, in contrast to many of the world's "unsuccessful civilizations," China can use a combination of heritage and intangible cultural research to chart a clear, demand-driven course for the evolution of human music technology, and that the findings of such research will complete the course of human exploration of music acoustics. The findings of such research will complete the journey of human exploration of music acoustics, and this practical experience can be applied to the exploration and understanding of other musical heritage base data.

Keywords: Haas effect, musical acoustics, history of acoustical technology, Chinese opera stage, structure

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Authors: Jie Ding, Yingying Pan, Shammy Raj, Lindy Schaffrick, Jolene Wong, Antoinette Nguyen, Sharada Manchikanti, Larry Unsworth, Peter Kwan, Edward E. Tredget

Abstract:

Background: Exosomes (EXOs) have been considered a new target that is thought to be involved in and treat wound healing. More research is needed to fully understand the EXO characteristics and mechanisms of EXO-mediated wound healing, especially wound healing after burn injury. Methods: Total EXOs were isolated from 85 serum samples of 29 burn patients and 13 healthy individuals. We characterized the EXOs for morphology and density, serum concentration, protein level, marker expression, size distribution, and cytokine content. After confirmation of EXO uptake by dermal fibroblasts, we also explored functional regulation of primary human normal skin and hypertrophic scar fibroblast cell lines by the EXOs in vitro, including cell proliferation and apoptosis. Results: EXOs dynamically changed their morphology, density, size, and cytokine level during wound healing in burn patients, which were correlated with burn severity and the stages of wound healing. EXOs from both burn patients and healthy individuals stimulated dermal fibroblast proliferation and apoptosis. Conclusion: EXO features may be important signals that influence wound healing after burn injury; however, to understand the mechanisms by which EXOs regulated the fibroblasts in healing wounds, further studies will be required in the future.

Keywords: exosome, burn, wound healing, hypertrophic scarring, cytokines

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Authors: Tien S. H. Pham, Peter J. Mahon, Aimin Yu

Abstract:

The detection of drug molecules by voltammetry has attracted great interest over the past years. However, many drug molecules exhibit poor electrochemical signals at common electrodes which result in low sensitivity in detection. An efficient way to overcome this problem is to modify electrodes with functional materials. Since discovered in 2004, graphene (or reduced graphene oxide) has emerged as one of the most studied two-dimensional carbon materials in condensed matter physics, electrochemistry, and so on due to its exceptional physicochemical properties. Additionally, the continuous development of technology has opened the new window for the successful fabrications of many novel graphene-based nanomaterials to serve in electrochemical analysis. This research aims to synthesize and characterize gold nanoparticle coated beta-cyclodextrin functionalized reduced graphene oxide (Au NP–β-CD–RGO) nanocomposites with highly conductive and strongly electro-catalytic properties as well as excellent supramolecular recognition abilities for the modification of electrodes. The electrochemical responses of ciprofloxacin at the as-prepared nanocomposite modified electrode was effectively amplified was much higher in comparison with that at the bare electrode. The linear concentration range was from 0.01 to 120 µM, with a detection limit of 2.7 nM using differential pulse voltammetry. Thus, Au NP–β-CD–RGO nanocomposite has great potential as an ideal material to construct sensitive sensors for the electrochemical determination of ciprofloxacin or similar antibacterial drugs in the future based on its excellent stability, selectivity, and reproducibility.

Keywords: Au nanoparticles, β-CD, ciprofloxacin, electrochemical determination, graphene based nanomaterials

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Authors: Ahmed Noor Al-qayyim, Barlas Özden Çağlayan

Abstract:

Structural failure is caused mainly by damage that often occurs on structures. Many researchers focus on obtaining very efficient tools to detect the damage in structures in the early state. In the past decades, a subject that has received considerable attention in literature is the damage detection as determined by variations in the dynamic characteristics or response of structures. This study presents a new damage identification technique. The technique detects the damage location for the incomplete structure system using output data only. The method indicates the damage based on the free vibration test data by using “Two Points - Condensation (TPC) technique”. This method creates a set of matrices by reducing the structural system to two degrees of freedom systems. The current stiffness matrices are obtained from optimization of the equation of motion using the measured test data. The current stiffness matrices are compared with original (undamaged) stiffness matrices. High percentage changes in matrices’ coefficients lead to the location of the damage. TPC technique is applied to the experimental data of a simply supported steel beam model structure after inducing thickness change in one element. Where two cases are considered, the method detects the damage and determines its location accurately in both cases. In addition, the results illustrate that these changes in stiffness matrix can be a useful tool for continuous monitoring of structural safety using ambient vibration data. Furthermore, its efficiency proves that this technique can also be used for big structures.

Keywords: damage detection, optimization, signals processing, structural health monitoring, two points–condensation

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Authors: AlHanoof A. Alharbi, Fatima M. Alamoudi, Razan A. Albrahim, Sarah F. Alharbi, Abdullah M Almuhaideb, Norah A. Almubairik, Abdulrahman Alharby, Naya M. Nagy

Abstract:

Recently, drones received a rapid interest in different industries worldwide due to its powerful impact. However, limitations still exist in this emerging technology, especially privacy violation. These aircrafts consistently threaten the security of entities by entering restricted areas accidentally or deliberately. Therefore, this research project aims to develop drone detection and prevention mechanism to protect the restricted area. Until now, none of the solutions have met the optimal requirements of detection which are cost-effectiveness, high accuracy, long range, convenience, unaffected by noise and generalization. In terms of prevention, the existing methods are focusing on impractical solutions such as catching a drone by a larger drone, training an eagle or a gun. In addition, the practical solutions have limitations, such as the No-Fly Zone and PITBULL jammers. According to our study and analysis of previous related works, none of the solutions includes detection and prevention at the same time. The proposed solution is a combination of detection and prevention methods. To implement the detection system, a passive radar will be used to properly identify the drone against any possible flying objects. As for the prevention, jamming signals and forceful safe landing of the drone integrated together to stop the drone’s operation. We believe that applying this mechanism will limit the drone’s invasion of privacy incidents against highly restricted properties. Consequently, it effectively accelerates drones‘ usages at personal and governmental levels.

Keywords: detection, drone, jamming, prevention, privacy, RF, radar, UAV

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

Abstract:

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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