Search results for: object detection

Authors: Young-Hwan Song, Doo-Heon Kyun, Jong-Kuk Kim, Myung-Jin Bae

Abstract:

People have the habitual pitch level which is used when people say something generally. However this pitch should be changed irregularly in the presence of noise. So it is useful to estimate SNR of speech signal by pitch. In this paper, we obtain the energy of input speech signal and then we detect a stationary region on voiced speech. And we get the pitch period by NAMDF for the stationary region that is not varied pitch rapidly. After getting pitch, each frame is divided by pitch period and the likelihood of closed pitch is estimated. In this paper, we proposed new parameter, NLF, to estimate the SNR of received speech signal. The NLF is derived from the correlation of near pitch periods. The NLF is obtained for each stationary region in voiced speech. Finally we confirmed good performance of the estimation of the SNR of received input speech in the presence of noise.

Keywords: Likelihood, pitch, SNR, speech.

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Authors: Majed Omar Al-Dwairi

Abstract:

This paper evaluate the multilevel modulation for different techniques such as amplitude shift keying (M-ASK), MASK, differential phase shift keying (M-ASK-Bipolar), Quaternary Amplitude Shift Keying (QASK) and Quaternary Polarization-ASK (QPol-ASK) at a total bit rate of 107 Gbps. The aim is to find a costeffective very high speed transport solution. Numerical investigation was performed using Monte Carlo simulations. The obtained results indicate that some modulation formats can be operated at 100Gbps in optical communication systems with low implementation effort and high spectral efficiency.

Keywords: Optical communication, multilevel amplitude shift keying (M-ASK), Differential phase shift keying (DPSK), Quaternary Amplitude Shift Keying (QASK), Quaternary Polarization-ASK (QPol-ASK).

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Authors: Andrey V. Timofeev, Viktor M. Denisov

Abstract:

A robust sequential nonparametric method is proposed for adaptation to background noise parameters for real-time. The distribution of background noise was modelled like to Huber contamination mixture. The method is designed to operate as an adaptation-unit, which is included inside a detection subsystem of an integrated multichannel monitoring system. The proposed method guarantees the given size of a nonasymptotic confidence set for noise parameters. Properties of the suggested method are rigorously proved. The proposed algorithm has been successfully tested in real conditions of a functioning C-OTDR monitoring system, which was designed to monitor railways.

Keywords: Guaranteed estimation, multichannel monitoring systems, non-asymptotic confidence set, contamination mixture.

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Authors: Clio G. Vossou, Ioannis N. Koukoulis, Christopher G. Provatidis

Abstract:

The present work encounters the solution of the defect identification problem with the use of an evolutionary algorithm combined with a simplex method. In more details, a Matlab implementation of Genetic Algorithms is combined with a Simplex method in order to lead to the successful identification of the defect. The influence of the location and the orientation of the depressed ellipsoidal flaw was investigated as well as the use of different amount of static data in the cost function. The results were evaluated according to the ability of the simplex method to locate the global optimum in each test case. In this way, a clear impression regarding the performance of the novel combination of the optimization algorithms, and the influence of the geometrical parameters of the flaw in defect identification problems was obtained.

Keywords: Defect identification, genetic algorithms, optimization.

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Authors: T. Bovornvirakit, K. Viravaidya

Abstract:

Acute kidney injury (AKI) is a new worldwide public health problem. A diagnosis of this disease using creatinine is still a problem in clinical practice. Therefore, a measurement of biomarkers responsible for AKI has received much attention in the past couple years. Cytokine interleukin-18 (IL-18) was reported as one of the early biomarkers for AKI. The most commonly used method to detect this biomarker is an immunoassay. This study used a planar platform to perform an immunoassay using fluorescence for detection. In this study, anti-IL-18 antibody was immobilized onto a microscope slide using a covalent binding method. Make-up samples were diluted at the concentration between 10 to 1000 pg/ml to create a calibration curve. The precision of the system was determined using a coefficient of variability (CV), which was found to be less than 10%. The performance of this immunoassay system was compared with the measurement from ELISA.

Keywords: Acute kidney injury, Acute renal failure, Antibody immobilization, Interleukin-18

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Authors: Sara Ramezanzadeh, Nashid Nabian

Abstract:

Historically, pandemics in different periods have caused compulsory changes in human life. In the case of COVID-19, according to the limitations and established care instructions, spatial alignment with the conditions is important. Following the outbreak of COVID-19, the question raised in this study is how to do spatial design in five scales, namely object, space, architecture, city, and infrastructure, in response to the consequences created in the realms under study. From the beginning of the pandemic until now, some changes in the spatial realm have been created spontaneously or by space users. These transformations have been mostly applied in modifiable parts such as furniture arrangement, especially in work-related spaces. To implement other comprehensive requirements, flexibility and adaptation of space design to the conditions resulting from the pandemics are needed during and after the outbreak. Studying the effects of pandemics from the past to the present, this research covers eight major realms, including three categories of ramifications, solutions, and paradigm shifts, and analytical conclusions about the solutions that have been created in response to them. Finally, by the consideration of epidemiology as a modern discipline influencing the design, spatial solutions in the five scales mentioned (in response to the effects of the eight realms for spatial adaptation in the face of pandemics and their following conditions) are presented as a series of guidelines. Due to the unpredictability of possible pandemics in the future, the possibility of changing and updating the provided guidelines is considered.

Keywords: Pandemics, COVID-19, spatial design, ramifications, paradigm shifts, guidelines.

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Authors: Youngyoon Lee, Dahae Chong, Myungsoo Lee, Seongho Chae, Seokho Yoon

Abstract:

This paper proposes two novel schemes for pilot-aided integer frequency offset (IFO) estimation in orthogonal frequency division multiplexing (OFDM)-based digital video broadcastingterrestrial (DVB-T) systems. The conventional scheme proposed for estimating the IFO uses only partial information of combinations that pilots can provide, which stems from a rigorous assumption that the channel responses of pilots used for estimating the IFO change very rapidly. Thus, in this paper, we propose the novel IFO estimation schemes exploiting all information of combinations that pilots can provide to improve the performance of IFO estimation. The simulation results show that the proposed schemes are highly accurate in terms of the IFO detection probability.

Keywords: OFDM, DVB-T, pilot, IFO, estimation

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Authors: Nikhat Nawaz, S. Srinivasulu, P. Kesava Rao

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Feature extraction plays an important role in many remote sensing applications. Automatic extraction of water bodies is of great significance in many remote sensing applications like change detection, image retrieval etc. This paper presents a procedure for automatic extraction of water information from remote sensing images. The algorithm uses the relative location of R color component of the chromaticity diagram. This method is then integrated with the effectiveness of the spatial scale transformation of whole method. The whole method is based on water index fitted from spectral library. Experimental results demonstrate the improved accuracy and effectiveness of the integrated method for automatic extraction of water bodies.

Keywords: Chromaticity, Feature Extraction, Remote Sensing, Spectral library, Water Index.

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Authors: Sang Hoon Lee, Jong Sue Bae, Taewan Kim, Jin Mo Song, Jong Ju Kim

Abstract:

Image target detection and tracking methods based on target information such as intensity, shape model, histogram and target dynamics have been proven to be robust to target model variations and background clutters as shown by recent researches. However, no definitive answer has been given to occluded target by counter measure or limited field of view(FOV). In this paper, we will present a novel tracking method using filtering and computational geometry. This paper has two central goals: 1) to deal with vulnerable target measurements; and 2) to maintain target tracking out of FOV using non-target-originated information. The experimental results, obtained with airborne images, show a robust tracking ability with respect to the existing approaches. In exploring the questions of target tracking, this paper will be limited to consideration of airborne image.

Keywords: Tracking, Computational geometry, Homography, Filter

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Authors: Souâd Demigha

Abstract:

Early detection of breast cancer is considered as a major public health issue. Breast cancer screening is not generalized to the entire population due to a lack of resources, staff and appropriate tools. Systematic screening can result in a volume of data which can not be managed by present computer architecture, either in terms of storage capabilities or in terms of exploitation tools. We propose in this paper to design and develop a data warehouse system in radiology-senology (DWRS). The aim of such a system is on one hand, to support this important volume of information providing from multiple sources of data and images and for the other hand, to help assist breast cancer screening in diagnosis, education and research.

Keywords: Breast cancer screening, data warehouse, diagnosis, education, research.

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Authors: V. Geetha, K. S. Aprameya

Abstract:

Early diagnosis of dental caries is essential for maintaining dental health. In this paper, method for diagnosis of dental caries is proposed using Laplacian filter, adaptive thresholding, texture analysis and Support Vector Machine (SVM) classifier. Analysis of the proposed method is compared with Otsu thresholding, watershed segmentation and active contouring method. Adaptive thresholding has comparatively better performance with 96.9% accuracy and 96.1% precision. The results are validated using statistical method, two-way ANOVA, at significant level of 5%, that shows the interaction of proposed method on performance parameter measures are significant. Hence the proposed technique could be used for detection of dental caries in automated computer assisted diagnosis system.

Keywords: Computer assisted diagnosis, dental caries, dental radiography, image segmentation.

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Authors: Francesco Pia

Abstract:

Stellar objects such as black, white and worm holes can be the subject of speculative reasoning if represented in a simplified and geometric form in order to be able to move them; and the cosmological model is one of the most important contents in relation to speculations that can then open the way to other aspects that are not strictly speculative but practical, precisely in the Universe represented by us. In this work, thanks to the hypothesis of a very large number of black, white and worm holes present in our Universe, we imagine that they can be moved; it was therefore thought to align them on a plane and following a redistribution, and the boundaries of this plane were ideally joined, giving rise to a sphere that has the stellar objects examined radially distributed. Thanks to geometrical displacements of these stellar objects that do not make each one of them lose their functionality in the region in which they are located, at the end of the speculative process it is possible to highlight a spherical layer that allows a flow from the outside and inside this spherical shell allowing to relate to other external and internal spherical layers; this aspect that seems useful to describe the universe we live in, for example inside one of the spherical shells just described. The name "Jewel" was chosen because, imagining the speculative process present in this work at the end of steps, the cosmological model tends to be "luminous". This cosmological model includes, for each internal part of a generic layer, different and numerous moments of our universe thanks to an eternal flow inward. There are many aspects to explore, one of these is the connection between the outermost and the inside of the spherical layers.

Keywords: Black hole, cosmological model, cosmology, white hole.

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Authors: Madina Hamiane, May Hashim Ali

Abstract:

This paper presents the processing and analysis of ECG signals. The study is based on wavelet transform and uses exclusively the MATLAB environment. This study includes removing Baseline wander and further de-noising through wavelet transform and metrics such as signal-to noise ratio (SNR), Peak signal-to-noise ratio (PSNR) and the mean squared error (MSE) are used to assess the efficiency of the de-noising techniques. Feature extraction is subsequently performed whereby signal features such as heart rate, rise and fall levels are extracted and the QRS complex was detected which helped in classifying the ECG signal. The classification is the last step in the analysis of the ECG signals and it is shown that these are successfully classified as Normal rhythm or Abnormal rhythm.  The final result proved the adequacy of using wavelet transform for the analysis of ECG signals.

Keywords: ECG Signal, QRS detection, thresholding, wavelet decomposition, feature extraction.

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Authors: J. Umamaheswari, G. Radhamani

Abstract:

This paper describes about the process of recognition and classification of brain images such as normal and abnormal based on PSO-SVM. Image Classification is becoming more important for medical diagnosis process. In medical area especially for diagnosis the abnormality of the patient is classified, which plays a great role for the doctors to diagnosis the patient according to the severeness of the diseases. In case of DICOM images it is very tough for optimal recognition and early detection of diseases. Our work focuses on recognition and classification of DICOM image based on collective approach of digital image processing. For optimal recognition and classification Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Support Vector Machine (SVM) are used. The collective approach by using PSO-SVM gives high approximation capability and much faster convergence.

Keywords: Recognition, classification, Relaxed Median Filter, Adaptive thresholding, clustering and Neural Networks

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Authors: Mohsen Noroozi, Maryam Khalili

Abstract:

Creating cities, objects and spaces that are economically, environmentally and socially sustainable and which meet the challenge of social interaction and generation change will be one of the biggest tasks of designers. Social sustainability is about how individuals, communities and societies live with each other and set out to achieve the objectives of development model which they have chosen for themselves. Urban lightning as one of the most important elements of urban furniture that people constantly interact with it in public spaces; can be a significant object for designers. Using intelligence by internet of things for urban lighting makes it more interactive in public environments. It can encourage individuals to carry out appropriate behaviors and provides them the social awareness through new interactions. The greatest strength of this technology is its strong impact on many aspects of everyday life and users' behaviors. The analytical phase of the research is based on a multiple method survey strategy. Smart lighting proposed in this paper is an urban lighting designed on results obtained from a collective point of view about the social sustainability. In this paper, referring to behavioral design methods, the social behaviors of the people has been studied. Data show that people demands for a deeper experience of social participation, safety perception and energy saving with the meaningful use of interactive and colourful lighting effects. By using intelligent technology, some suggestions are provided in the field of future lighting to consider the new forms of social sustainability.

Keywords: Behavior model, internet of things, social sustainability, urban lighting.

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Authors: J.W. Xiang, M. Liang

Abstract:

This paper presents a method to detect multiple cracks based on frequency information. When a structure is subjected to dynamic or static loads, cracks may develop and the modal frequencies of the cracked structure may change. To detect cracks in a structure, we construct a high precision wavelet finite element (EF) model of a certain structure using the B-spline wavelet on the interval (BSWI). Cracks can be modeled by rotational springs and added to the FE model. The crack detection database will be obtained by solving that model. Then the crack locations and depths can be determined based on the frequency information from the database. The performance of the proposed method has been numerically verified by a rotor example.

Keywords: Rotor, frequency measurement, multiple cracks, wavelet finite element method, identification.

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Authors: C. I. L. Justino, L. I. B. Silva, K. Duarte, A. C. Freitas, T. A. P. Rocha-Santos, A. C. Duarte

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This work proposes an optical fiber system (OF) for sensing various volatile organic compounds (VOCs) in human breath for the diagnosis of some metabolic disorders as a non-invasive methodology. The analyzed VOCs are alkanes (i.e., ethane, pentane, heptane, octane, and decane), and aromatic compounds (i.e., benzene, toluene, and styrene). The OF displays high analytical performance since it provides near real-time responses, rapid analysis, and low instrumentation costs, as well as it exhibits useful linear range and detection limits; the developed OF sensor is also comparable to a reference methodology (gas chromatography-mass spectrometry) for the eight tested VOCs.

Keywords: Breath analysis, gas chromatography-mass spectrometry, optical fiber sensor, volatile organic compounds

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Authors: Cem Karacal, Sohyung Cho, William Yu

Abstract:

In metal cutting industries, mathematical/statistical models are typically used to predict tool replacement time. These off-line methods usually result in less than optimum replacement time thereby either wasting resources or causing quality problems. The few online real-time methods proposed use indirect measurement techniques and are prone to similar errors. Our idea is based on identifying the optimal replacement time using an electronic nose to detect the airborne compounds released when the tool wear reaches to a chemical substrate doped into tool material during the fabrication. The study investigates the feasibility of the idea, possible doping materials and methods along with data stream mining techniques for detection and monitoring different phases of tool wear.

Keywords: Tool condition monitoring, cutting tool replacement, data stream mining, e-Nose.

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Authors: A. Boveiri Monji, H. Yousefnia, S. Zolghadri, B. Salimi

Abstract:

The main goal of this paper was to make use of green reagents as a substitute of perilous synthetic reagents and organic solvents for spectrophotometric determination of hafnium(IV). The extracts taken from six different kinds of tree leaves including Acer negundo, Ficus carica, Cerasus avium, Chimonanthus, Salix babylonica and Pinus brutia, were applied as green reagents for the experiments. In 6-M hydrochloric acid, hafnium reacted with the reagent to form a yellow product and showed maximum absorbance at 421 nm. Among tree leaves, Chimonanthus showed satisfactory results with a molar absorptivity value of 0.61 × 10⁴ l mol^-1 cm^-1 and the method was linear in the 0.3-9 µg mL ^-1 concentration range. The detection limit value was 0.064 µg mL^-1. The proposed method was simple, low cost, clean, and selective.

Keywords: Spectrophotometric determination, tree leaves, synthetic reagents, hafnium.

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Authors: J.-H. Moon, D.-O Kim, R.-H. Park

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This paper presents a video matting method, which extracts the foreground and alpha matte from a video sequence. The objective of video matting is finding the foreground and compositing it with the background that is different from the one in the original image. By finding the motion vectors (MVs) using a sliced block matching algorithm (SBMA), we can extract moving regions from the video sequence under the assumption that the foreground is moving and the background is stationary. In practice, foreground areas are not moving through all frames in an image sequence, thus we accumulate moving regions through the image sequence. The boundaries of moving regions are found by Canny edge detector and the foreground region is separated in each frame of the sequence. Remaining regions are defined as background regions. Extracted backgrounds in each frame are combined and reframed as an integrated single background. Based on the estimated background, we compute the frame difference (FD) of each frame. Regions with the FD larger than the threshold are defined as foreground regions, boundaries of foreground regions are defined as unknown regions and the rest of regions are defined as backgrounds. Segmentation information that classifies an image into foreground, background, and unknown regions is called a trimap. Matting process can extract an alpha matte in the unknown region using pixel information in foreground and background regions, and estimate the values of foreground and background pixels in unknown regions. The proposed video matting approach is adaptive and convenient to extract a foreground automatically and to composite a foreground with a background that is different from the original background.

Keywords: Background estimation, Object segmentation, Blockmatching algorithm, Video matting.

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Authors: Thomas Fuhrmann

Abstract:

In this paper an algorithm for fast wavelength calibration of Optical Spectrum Analyzers (OSAs) using low power reference gas spectra is proposed. In existing OSAs a reference spectrum with low noise for precise detection of the reference extreme values is needed. To generate this spectrum costly hardware with high optical power is necessary. With this new wavelength calibration algorithm it is possible to use a noisy reference spectrum and therefore hardware costs can be cut. With this algorithm the reference spectrum is filtered and the key information is extracted by segmenting and finding the local minima and maxima. Afterwards slope and offset of a linear correction function for best matching the measured and theoretical spectra are found by correlating the measured with the stored minima. With this algorithm a reliable wavelength referencing of an OSA can be implemented on a microcontroller with a calculation time of less than one second.

Keywords: correlation, gas reference, optical spectrum analyzer, wavelength calibration

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Authors: K. M. Faraoun, A. Boukelif

Abstract:

In the present work, we propose a new technique to enhance the learning capabilities and reduce the computation intensity of a competitive learning multi-layered neural network using the K-means clustering algorithm. The proposed model use multi-layered network architecture with a back propagation learning mechanism. The K-means algorithm is first applied to the training dataset to reduce the amount of samples to be presented to the neural network, by automatically selecting an optimal set of samples. The obtained results demonstrate that the proposed technique performs exceptionally in terms of both accuracy and computation time when applied to the KDD99 dataset compared to a standard learning schema that use the full dataset.

Keywords: Neural networks, Intrusion detection, learningenhancement, K-means clustering

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Authors: Xu Huang, Jing Fan, Maonian Wu, Yonggen Gu

Abstract:

This paper discusses the design of an indoor mobile robot positioning system. The problem of indoor positioning is solved through Wi-Fi fingerprint positioning to implement a low cost deployment. A wireless fingerprint matching algorithm based on the similarity of unequal length sequences is presented. Candidate sequences selection is defined as a set of mappings, and detection errors caused by wireless hotspot stability and the change of interior pattern can be corrected by transforming the unequal length sequences into equal length sequences. The presented scheme was verified experimentally to achieve the accuracy requirements for an indoor positioning system with low deployment cost.

Keywords: Fingerprint match, indoor positioning, mobile robot positioning system, Wi-Fi, wireless fingerprint.

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Authors: Petra Balla, Gabor Manhertz, Akos Antal

Abstract:

Nowadays spinal deformities are very frequent problems among teenagers. Scheuermann disease is a one dimensional deformity of the spine, but it has prevalence over 11% of the children. A traditional technology, the moiré method was used by us for screening and diagnosing this type of spinal deformity. A LabVIEW program has been developed to evaluate the moiré pictures of patients with Scheuermann disease. Two different solutions were tested in this computer program, the extreme and the inflexion point calculation methods. Effects using these methods were compared and according to the results both solutions seemed to be appropriate. Statistical results showed better efficiency in case of the extreme search method where the average difference was only 6,09⁰.

Keywords: Spinal deformity, picture evaluation, moiré method, Scheuermann disease, curve detection, moiré topography.

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Authors: Yong ZHANG, Xiamu NIU, Dongning ZHAO

Abstract:

With the development of Internet and databases application techniques, the demand that lots of databases in the Internet are permitted to remote query and access for authorized users becomes common, and the problem that how to protect the copyright of relational databases arises. This paper simply introduces the knowledge of cloud model firstly, includes cloud generators and similar cloud. And then combined with the property of the cloud, a method of protecting relational databases copyright with cloud watermark is proposed according to the idea of digital watermark and the property of relational databases. Meanwhile, the corresponding watermark algorithms such as cloud watermark embedding algorithm and detection algorithm are proposed. Then, some experiments are run and the results are analyzed to validate the correctness and feasibility of the watermark scheme. In the end, the foreground of watermarking relational database and its research direction are prospected.

Keywords: cloud watermark, copyright protection, digitalwatermark, relational database

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Authors: A. Naamane, M. Hasnaoui

Abstract:

Numerical modeling of fluid flows, whether compressible or incompressible, laminar or turbulent presents a considerable contribution in the scientific and industrial fields. However, the development of an approximate model of a supersonic flow requires the introduction of specific and more precise techniques and methods. For this purpose, the object of this paper is modeling a supersonic flow of inviscid fluid around a dihedral airfoil. Based on the thin airfoils theory and the non-dimensional stationary Steichen equation of a two-dimensional supersonic flow in isentropic evolution, we obtained a solution for the downstream velocity potential of the oblique shock at the second order of relative thickness that characterizes a perturbation parameter. This result has been dealt with by the asymptotic analysis and characteristics method. In order to validate our model, the results are discussed in comparison with theoretical and experimental results. Indeed, firstly, the comparison of the results of our model has shown that they are quantitatively acceptable compared to the existing theoretical results. Finally, an experimental study was conducted using the AF300 supersonic wind tunnel. In this experiment, we have considered the incident upstream Mach number over a symmetrical dihedral airfoil wing. The comparison of the different Mach number downstream results of our model with those of the existing theoretical data (relative margin between 0.07% and 4%) and with experimental results (concordance for a deflection angle between 1° and 11°) support the validation of our model with accuracy.

Keywords: Asymptotic modelling, dihedral airfoil, supersonic flow, supersonic wind tunnel.

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Authors: Katsumi Hirata

Abstract:

To develop the useful acoustic environmental recognition system, the method of estimating 3D-position of a stationary random acoustic source using bispectral analysis of 4-point detected signals is proposed. The method uses information about amplitude attenuation and propagation delay extracted from amplitude ratios and angles of auto- and cross-bispectra of the detected signals. It is expected that using bispectral analysis affects less influence of Gaussian noises than using conventional power spectral one. In this paper, the basic principle of the method is mentioned first, and its validity and features are considered from results of the fundamental experiments assumed ideal circumstances.

Keywords: 4-point detection, a stationary random acoustic source, auto- and cross-bispectra, estimation of 3D-position.

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Authors: J. H. Choi, S. J. Kim, M. S. Jung, S. J. Kim, S. J. Joo, S. C. Kim

Abstract:

There are a many of needs for the development of SiC-based hydrogen sensor for harsh environment applications. We fabricated and investigated Pd/Ta2O5/SiC-based hydrogen sensors with MOS capacitor structure for high temperature process monitoring and leak detection applications in such automotive, chemical and petroleum industries as well as direct monitoring of combustion processes. In this work, we used silicon carbide (SiC) as a substrate to replace silicon which operating temperatures are limited to below 200°C. Tantalum oxide was investigated as dielectric layer which has high permeability for hydrogen gas and high dielectric permittivity, compared with silicon dioxide or silicon nitride. Then, electrical response properties, such as I-V curve and dependence of capacitance on hydrogen concentrations were analyzed in the temperature ranges of room temperature to 500°C for performance evaluation of the sensor.

Keywords: High temperature, hydrogen sensor, SiC, Ta2O5 dielectric layer.

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Authors: Mohammad H. Taheri, David J. Brown, Nasser Sherkat

Abstract:

Engagement is one of the most important factors in determining successful outcomes and deep learning in students. Existing approaches to detect student engagement involve periodic human observations that are subject to inter-rater reliability. Our solution uses real-time multimodal multisensor data labeled by objective performance outcomes to infer the engagement of students. The study involves four students with a combined diagnosis of cerebral palsy and a learning disability who took part in a 3-month trial over 59 sessions. Multimodal multisensor data were collected while they participated in a continuous performance test. Eye gaze, electroencephalogram, body pose, and interaction data were used to create a model of student engagement through objective labeling from the continuous performance test outcomes. In order to achieve this, a type of continuous performance test is introduced, the Seek-X type. Nine features were extracted including high-level handpicked compound features. Using leave-one-out cross-validation, a series of different machine learning approaches were evaluated. Overall, the random forest classification approach achieved the best classification results. Using random forest, 93.3% classification for engagement and 42.9% accuracy for disengagement were achieved. We compared these results to outcomes from different models: AdaBoost, decision tree, k-Nearest Neighbor, naïve Bayes, neural network, and support vector machine. We showed that using a multisensor approach achieved higher accuracy than using features from any reduced set of sensors. We found that using high-level handpicked features can improve the classification accuracy in every sensor mode. Our approach is robust to both sensor fallout and occlusions. The single most important sensor feature to the classification of engagement and distraction was shown to be eye gaze. It has been shown that we can accurately predict the level of engagement of students with learning disabilities in a real-time approach that is not subject to inter-rater reliability, human observation or reliant on a single mode of sensor input. This will help teachers design interventions for a heterogeneous group of students, where teachers cannot possibly attend to each of their individual needs. Our approach can be used to identify those with the greatest learning challenges so that all students are supported to reach their full potential.

Keywords: Affective computing in education, affect detection, continuous performance test, engagement, flow, HCI, interaction, learning disabilities, machine learning, multimodal, multisensor, physiological sensors, Signal Detection Theory, student engagement.

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Authors: Yong-Gyu Lee, Gilwon Yoon

Abstract:

Image processing for capsule endoscopy requires large memory and it takes hours for diagnosis since operation time is normally more than 8 hours. A real-time analysis algorithm of capsule images can be clinically very useful. It can differentiate abnormal tissue from health structure and provide with correlation information among the images. Bleeding is our interest in this regard and we propose a method of detecting frames with potential bleeding in real-time. Our detection algorithm is based on statistical analysis and the shapes of bleeding spots. We tested our algorithm with 30 cases of capsule endoscopy in the digestive track. Results were excellent where a sensitivity of 99% and a specificity of 97% were achieved in detecting the image frames with bleeding spots.

Keywords: bleeding, capsule endoscopy, image processing, real time analysis

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