Search results for: infrared image

Authors: Kübra Taşkıran, Bahattin Türetken

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In this paper, a microstrip array antenna with circular polarization at 2.4 GHz frequency has been designed using the in order to provide image and telemetric data transmission in Unmanned Aerial Vehicle and Armed Unmanned Aerial Vehicle Systems. In addition to the antenna design, the power divider design was made and the antennas were fed in phase. As a result of the analysis, it was observed that the antenna operates at a frequency of 2.4016 GHz with 12.2 dBi directing gain. In addition, this designed array antenna was transformed into a form compatible with the rocket surface used in A-UAV Systems, and analyzes were made. As a result of these analyzes, it has been observed that the antenna operates on the surface of the missile at a frequency of 2.372 GHz with a directivity gain of 10.2 dBi.

Keywords: cicrostrip array antenna, circular polarization, 2.4 GHz, image and telemetric data, transmission, surface compatible, UAV and armed UAV

Procedia PDF Downloads 102

Authors: Andre Peres Ramos, Franklin Cesar Flores

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Colorization is the process of add colors to a monochromatic image or video. Usually, the process involves to segment the image in regions of interest and then apply colors to each one, for videos, this process is repeated for each frame, which makes it a tedious and time-consuming job. We propose a new assisted method for video colorization; the user only has to colorize one frame, and then the colors are propagated to following frames. The user can intervene at any time to correct eventual errors in color assignment. The method consists of to extract intensity and texture descriptors from the frames and then perform a feature matching to determine the best color for each segment. To reduce computation time and give a better spatial coherence we narrow the area of search and give weights for each feature to emphasize texture descriptors. To give a more natural result, we use an optimization algorithm to make the color propagation. Experimental results in several image sequences, compared to others existing methods, demonstrates that the proposed method perform a better colorization with less time and user interference.

Keywords: colorization, feature matching, texture descriptors, video segmentation

Procedia PDF Downloads 160

Authors: Jianlun Zhang, Christine Lim

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Local food is one of the most attractive elements to tourists. The role of local cuisine in destination branding is very important because it is the distinctive identity that helps tourists remember the destination. The objectives of this study are: (1) Test the direct relation between the cognitive image of destination food and tourists’ intention to eat local food. (2) Examine the mediating effect of tourists’ desire to try destination food on the relationship between the cognitive image of local food and tourists’ intention to eat destination food. (3) Study the moderating effect of tourists’ perceived difficulties in finding local food on the relationship between tourists’ desire to try destination food and tourists’ intention to eat local food. To achieve the goals of this study, Macanese cuisine is selected as the destination food. Macau is located in Southeastern China and is a former colonial city of Portugal. The taste and texture of Macanese cuisine are unique because it is a fusion of cuisine from many countries and regions of mainland China. As people travel to seek authentically exotic experience, it is important to investigate if the food image of Macau leaves a good impression on tourists and motivate them to try local cuisine. A total of 449 Chinese tourists were involved in this study. To analyze the data collected, partial least square-structural equation modelling (PLS-SEM) technique is employed. Results suggest that the cognitive image of Macanese cuisine has a direct effect on tourists’ intention to eat Macanese cuisine. Tourists’ desire to try Macanese cuisine mediates the cognitive image-intention relationship. Tourists’ perceived difficulty of finding Macanese cuisine moderates the desire-intention relationship. The lower tourists’ perceived difficulty in finding Macanese cuisine is, the stronger the desire-intention relationship it will be. There are several practical implications of this study. First, the government tourism website can develop an authentic storyline about the evolvement of local cuisine, which provides an opportunity for tourists to taste the history of the destination and create a novel experience for them. Second, the government should consider the development of food events, restaurants, and hawker businesses. Third, to lower tourists’ perceived difficulty in finding local cuisine, there should be locations of restaurants and hawker stalls with clear instructions for finding them on the websites of the government tourism office, popular tourism sites, and public transportation stations in the destination. Fourth, in the post-COVID-19 era, travel risk will be a major concern for tourists. Therefore, when promoting local food, the government tourism website should post images that show food safety and hygiene.

Keywords: cognitive image of destination food, desire to try destination food, intention to eat food in the destination, perceived difficulties of finding local cuisine, PLS-SEM

Procedia PDF Downloads 189

Authors: Po-Jen Chen, Jian-Jiun Ding, Hung-Wei Hsu, Chien-Yao Wang, Jia-Ching Wang

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A more accurate scene classification algorithm using label relations and the hierarchy neural network was developed in this work. In many classification algorithms, it is assumed that the labels are mutually exclusive. This assumption is true in some specific problems, however, for scene classification, the assumption is not reasonable. Because there are a variety of objects with a photo image, it is more practical to assign multiple labels for an image. In this paper, two label relations, which are exclusive relation and hierarchical relation, were adopted in the classification process to achieve more accurate multiple label classification results. Moreover, the hierarchy neural network (hierarchy NN) is applied to classify the image and the directed acyclic graph structure is used for predicting a more reasonable result which obey exclusive and hierarchical relations. Simulations show that, with these techniques, a much more accurate scene classification result can be achieved.

Keywords: convolutional neural network, label relation, hierarchy neural network, scene classification

Procedia PDF Downloads 455

Authors: Subir Gupta, Subhas Ganguly

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In this paper, we demonstrate the new area of application of image processing in metallurgical images to develop the more opportunity for structure-property correlation based approaches of alloy design. The present exercise focuses on the development of image processing tools suitable for phrase segmentation, grain boundary detection and recognition of micro-constituents in SEM micrographs of ferrite and pearlite steels. A comprehensive data of micrographs have been experimentally developed encompassing the variation of ferrite and pearlite volume fractions and taking images at different magnification (500X, 1000X, 15000X, 2000X, 3000X and 5000X) under scanning electron microscope. The variation in the volume fraction has been achieved using four different plain carbon steel containing 0.1, 0.22, 0.35 and 0.48 wt% C heat treated under annealing and normalizing treatments. The obtained data pool of micrographs arbitrarily divided into two parts to developing training and testing sets of micrographs. The statistical recognition features for ferrite and pearlite constituents have been developed by learning from training set of micrographs. The obtained features for microstructure pattern recognition are applied to test set of micrographs. The analysis of the result shows that the developed strategy can successfully detect the micro constitutes across the wide range of magnification and variation of volume fractions of the constituents in the structure with an accuracy of about +/- 5%.

Keywords: SEM micrograph, metallurgical image processing, ferrite pearlite steel, microstructure

Procedia PDF Downloads 197

Authors: Pei-Jyun Hsieh, Cheng-Hsuan Li, Bor-Chen Kuo

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For hyperspectral image classification, feature reduction is an important pre-processing for avoiding the Hughes phenomena due to the difficulty for collecting training samples. Hence, lots of researches developed feature selection methods such as F-score, HSIC (Hilbert-Schmidt Independence Criterion), and etc., to improve hyperspectral image classification. However, most of them only consider the class separability in the original space, i.e., a linear class separability. In this study, we proposed a nonlinear class separability measure based on kernel trick for selecting an appropriate feature subset. The proposed nonlinear class separability was formed by a generalized RBF kernel with different bandwidths with respect to different features. Moreover, it considered the within-class separability and the between-class separability. A genetic algorithm was applied to tune these bandwidths such that the smallest with-class separability and the largest between-class separability simultaneously. This indicates the corresponding feature space is more suitable for classification. In addition, the corresponding nonlinear classification boundary can separate classes very well. These optimal bandwidths also show the importance of bands for hyperspectral image classification. The reciprocals of these bandwidths can be viewed as weights of bands. The smaller bandwidth, the larger weight of the band, and the more importance for classification. Hence, the descending order of the reciprocals of the bands gives an order for selecting the appropriate feature subsets. In the experiments, three hyperspectral image data sets, the Indian Pine Site data set, the PAVIA data set, and the Salinas A data set, were used to demonstrate the selected feature subsets by the proposed nonlinear feature selection method are more appropriate for hyperspectral image classification. Only ten percent of samples were randomly selected to form the training dataset. All non-background samples were used to form the testing dataset. The support vector machine was applied to classify these testing samples based on selected feature subsets. According to the experiments on the Indian Pine Site data set with 220 bands, the highest accuracies by applying the proposed method, F-score, and HSIC are 0.8795, 0.8795, and 0.87404, respectively. However, the proposed method selects 158 features. F-score and HSIC select 168 features and 217 features, respectively. Moreover, the classification accuracies increase dramatically only using first few features. The classification accuracies with respect to feature subsets of 10 features, 20 features, 50 features, and 110 features are 0.69587, 0.7348, 0.79217, and 0.84164, respectively. Furthermore, only using half selected features (110 features) of the proposed method, the corresponding classification accuracy (0.84168) is approximate to the highest classification accuracy, 0.8795. For other two hyperspectral image data sets, the PAVIA data set and Salinas A data set, we can obtain the similar results. These results illustrate our proposed method can efficiently find feature subsets to improve hyperspectral image classification. One can apply the proposed method to determine the suitable feature subset first according to specific purposes. Then researchers can only use the corresponding sensors to obtain the hyperspectral image and classify the samples. This can not only improve the classification performance but also reduce the cost for obtaining hyperspectral images.

Keywords: hyperspectral image classification, nonlinear feature selection, kernel trick, support vector machine

Procedia PDF Downloads 262

Authors: Anuruddha Jagoda, Samiddhi Samarakoon, Anil Jasinghe

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In an emergency department ‘where every second count for patient’s management’ timely availability of X- rays play a vital role in early diagnosis and management of patients. Trauma care centers rely heavily on timely radiologic imaging for patient care and radiology plays a crucial role in the emergency department (ED) operations. A research study was carried out to assess timeliness of availability of X-rays and total turnaround time at the Accident Service of National Hospital of Sri Lanka which is the premier trauma center in the country. Digital Radiology system was implemented as an intervention to improve the timeliness of availability of X-rays. Post-implementation assessment was carried out to assess the effectiveness of the intervention. Reduction in all three aspects of waiting times namely waiting for initial examination by doctors, waiting until X –ray is performed and waiting for image availability was observed after implementation of the intervention. However, the most significant improvement was seen in waiting time for image availability and reduction in time for image availability had indirect impact on reducing waiting time for initial examination by doctors and waiting until X –ray is performed. The most significant reduction in time for image availability was observed when performing 4-5 X rays with DR system. The least improvement in timeliness was seen in patients who are categorized as critical.

Keywords: emergency department, digital radilogy, timeliness, trauma care

Procedia PDF Downloads 264

Authors: Hannatu Abubakar Sani, Abubakar Umar Birnin Yauri, Aliyu Muhammad, Mujahid Salau, Aminu Musa, Hadiza Adamu Kwazo

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The increase in the global population and advances in technology have made plastic materials to have wide applications in every aspect of life. However, the non-biodegradability of these petrochemical-based materials and their increasing accumulation in the environment has been a threat to the planet and has been a source of environmental concerns and hence, the driving force in the search for ‘green’ alternatives for which agricultural waste remains the front liner. Sorghum husk, an agricultural waste with potentials as a raw material in the production of bioplastic, was used in this research to prepare bioplastic using sulphuric acid-catalyzed acetylation process. The prepared bioplastic was characterized by X-ray diffraction and Fourier transform infrared spectroscopy (FTIR), and the structure of the prepared bioplastic was confirmed. The Fourier transform infrared spectroscopy (FTIR) spectra of the product displayed the presence of OH, C-H, C=O, and C-O absorption peaks. The bioplastic obtained is biodegradable and is affected by acid, salt, and alkali to a lesser extent. Other tests like solubility and swelling studies were carried out to ensure the commercial properties of these bioplastic materials. Therefore, this revealed that new bioplastics with better environmental and sustainable properties could be produced from agricultural waste, which may have applications in many industries.

Keywords: agricultural waste, bioplastic, characterization, Sorghum Husk

Procedia PDF Downloads 155

Authors: Radoslaw Domke

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The social history of Poland in the years 1945-1990 has already been thoroughly researched based on the so-called Classical sources. Many types of archival and press sources, diaries, memoirs, and literature on the subject were analyzed. It turns out, however, that the fictional film material remains an unknown source. In the paper, the author intends to focus on the image of Polish society that emerges from the analysis of cinematography produced by the Polish People's Republic. The conclusions presented in the paper can be the basis for further research on the visual history of post-war societies.

Keywords: visual history, history of Poland, social history, cinematography

Procedia PDF Downloads 91

Authors: Janusz Bobulski, Kamila Pasternak

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Despite many years of effort and research, the problem of waste management is still current. So far, no fully effective waste management system has been developed. Many programs and projects improve statistics on the percentage of waste recycled every year. In these efforts, it is worth using modern Computer Vision techniques supported by artificial intelligence. In the article, we present a method of identifying plastic waste based on the asymmetry analysis of the histogram of the image containing the waste. The method is simple but effective (94%), which allows it to be implemented on devices with low computing power, in particular on microcomputers. Such de-vices will be used both at home and in waste sorting plants.

Keywords: waste management, environmental protection, image processing, computer vision

Procedia PDF Downloads 117

Authors: Saumya Srivastava, Rina Maiti

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In order to achieve a better performance of vehicle detection in a complex environment, we present an efficient approach for a multi-vehicle detection system using an adaptive sliding window technique. For a given frame, image segmentation is carried out to establish the region of interest. Gradient computation followed by thresholding, denoising, and morphological operations is performed to extract the binary search image. Near-region field and far-region field are defined to generate hypotheses using the adaptive sliding window technique on the resultant binary search image. For each vehicle candidate, features are extracted using a histogram of oriented gradients, and a pre-trained support vector machine is applied for hypothesis verification. Later, the Kalman filter is used for tracking the vanishing point. The experimental results show that the method is robust and effective on various roads and driving scenarios. The algorithm was tested on highways and urban roads in India.

Keywords: gradient, vehicle detection, histograms of oriented gradients, support vector machine

Procedia PDF Downloads 121

Authors: Yousif Mohamed Y. Abdallah, Razan Manofely, Rajab M. Ben Yousef

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X-Ray images are very popular as a first tool for diagnosis. Automating the process of analysis of such images is important in order to help physician procedures. In this practice, teeth segmentation from the radiographic images and feature extraction are essential steps. The main objective of this study was to study correction preprocessing of x-rays images using local adaptive filters in order to evaluate contrast enhancement pattern in different x-rays images such as grey color and to evaluate the usage of new nonlinear approach for contrast enhancement of soft tissues in x-rays images. The data analyzed by using MatLab program to enhance the contrast within the soft tissues, the gray levels in both enhanced and unenhanced images and noise variance. The main techniques of enhancement used in this study were contrast enhancement filtering and deblurring images using the blind deconvolution algorithm. In this paper, prominent constraints are firstly preservation of image's overall look; secondly, preservation of the diagnostic content in the image and thirdly detection of small low contrast details in diagnostic content of the image.

Keywords: enhancement, x-rays, pixel intensity values, MatLab

Procedia PDF Downloads 481

Authors: Filip Rusak, Yulia Arzhaeva, Dadong Wang

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Machine learning based Computer-Aided Diagnosis (CAD) is gaining much popularity in medical imaging and diagnostic radiology. However, it requires a large amount of high quality and labeled training image datasets. The training images may come from different sources and be acquired from different radiography machines produced by different manufacturers, digital or digitized copies of film radiographs, with various sizes as well as different pixel intensity distributions. In this paper, a content-aware image augmentation method is presented to deal with these variations. The results of the proposed method have been validated graphically by plotting the removed and added seams of pixels on original images. Two different chest X-ray (CXR) datasets are used in the experiments. The CXRs in the datasets defer in size, some are digital CXRs while the others are digitized from analog CXR films. With the proposed content-aware augmentation method, the Seam Carving algorithm is employed to resize CXRs and the corresponding labels in the form of image masks, followed by histogram matching used to normalize the pixel intensities of digital radiography, based on the pixel intensity values of digitized radiographs. We implemented the algorithms, resized the well-known Montgomery dataset, to the size of the most frequently used Japanese Society of Radiological Technology (JSRT) dataset and normalized our digital CXRs for testing. This work resulted in the unified off-the-shelf CXR dataset composed of radiographs included in both, Montgomery and JSRT datasets. The experimental results show that even though the amount of augmentation is large, our algorithm can preserve the important information in lung fields, local structures, and global visual effect adequately. The proposed method can be used to augment training and testing image data sets so that the trained machine learning model can be used to process CXRs from various sources, and it can be potentially used broadly in any medical imaging applications.

Keywords: computer-aided diagnosis, image augmentation, lung segmentation, medical imaging, seam carving

Procedia PDF Downloads 220

Authors: Tso-Yen Mao, De-Yen Liu, Chun-Feng Huang

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Purpose: This research intends to investigate the reliability and validity of ventilatory threshold (VT) and respiratory compensation point (RCP) determined by skeletal muscle hemodynamic status. Methods: One hundred healthy male (age: 22±3 yrs; height: 173.1±6.0 cm; weight: 67.1±10.5 kg) performed graded cycling exercise test which ventilatory and skeletal muscle hemodynamic data were collected simultaneously. VT and RCP were determined by combined V-slope (VE vs. VCO2) and ventilatory efficiency (VE/VO2 vs. VE/VCO2) methods. Pearson correlation, paired t-test, and Bland-Altman plots were used to analyze reliability, validity, and similarities. Statistical significance was set at α =. 05. Results: There are high test-retest correlations of VT and RCP in ventilatory or near-infrared spectroscopy (NIRS) methods (VT vs. VTNIRS: 0.95 vs. 0.94; RCP vs. RCPNIRS: 0.93 vs. 0.93, p<. 05). There are high coefficient of determination at the first timing point of O2Hb decreased (R2 = 0.88, p<. 05) with VT, and high coefficient of determination at the second timing point of O2Hb declined (R2 = 0.89, p< .05) with RCP. VO2 of VT and RCP are not significantly different between ventilatory and NIRS methods (p>. 05). Conclusion: Using NIRS method to determine VT and RCP is reliable and valid in male individuals during graded exercise. Non-invasive skeletal muscle hemodynamics monitor also can be used for controlling training intensity in the future.

Keywords: anaerobic threshold, exercise intensity, hemodynamic, NIRS

Procedia PDF Downloads 311

Authors: Christine O. Wangia, Jennifer A. Orwa, Francis W. Muregi, Patrick G. Kareru, Kipyegon Cheruiyot, Eric Guantai

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Ruellia (syn. Dipteracanthus) species are wild perennial creepers belonging to the Acanthaceae family. These species are reported to possess anti-inflammatory, analgesic, antioxidant, gastroprotective, anticancer, and immuno-stimulant properties. Phytochemical screening of both aqueous and methanolic extracts of Ruellia species revealed the presence of saponins. Saponins have been reported to possess anti-inflammatory, antioxidant, immuno-stimulant, antihepatotoxic, antibacterial, anticarcinogenic, and antiulcerogenic activities. The objective of this study was to quantify and analyze the Fourier transform infrared (FTIR) spectra of saponins in crude extracts of three Kenyan Ruellia species namely Ruellia prostrata (RPM), Ruellia lineari-bracteolata (RLB) and Ruellia bignoniiflora (RBK). Sequential organic extraction of the ground whole plant material was done using petroleum ether (PE), chloroform, ethyl acetate (EtOAc), and absolute methanol by cold maceration, while aqueous extraction was by hot maceration. The plant powders and extracts were mixed with spectroscopic grade KBr and compressed into a pellet. The infrared spectra were recorded using a Shimadzu FTIR spectrophotometer of 8000 series in the range of 3500 cm^-1 - 500 cm^-1. Quantitative determination of the saponins was done using standard procedures. Quantitative analysis of saponins showed that RPM had the highest quantity of crude saponins (2.05% ± 0.03), followed by RLB (1.4% ± 0.15) and RBK (1.25% ± 0.11), respectively. FTIR spectra revealed the spectral peaks characteristic for saponins in RPM, RLB, and RBK plant powders, aqueous and methanol extracts; O-H absorption (3265 - 3393 cm^-1), C-H absorption ranging from 2851 to 2924 cm^-1, C=C absorbance (1628 - 1655 cm^-1), oligosaccharide linkage (C-O-C) absorption due to sapogenins (1036 - 1042 cm^-1). The crude saponins from RPM, RLB and RBK showed similar peaks to their respective extracts. The presence of the saponins in extracts of RPM, RLB and RBK may be responsible for some of the biological activities reported in the Ruellia species.1

Keywords: Ruellia bignoniiflora, Ruellia linearibracteolata, Ruellia prostrata, Saponins

Procedia PDF Downloads 175

Authors: Catherine W. Njeru, Clarence Murithi W., Isaac W. Mwangi, Ruth Wanjau, Grace N. Kiriro, Gerald W. Mbugua

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Flesh from animals is one of the most nutritious food materials that is rich in Vitamin B12, B3 (Niacin), B6, iron, zinc, selenium, and plenty of other vitamins and minerals and a high content of fats Meat consumption projection indicates an increase from 5.5 to 13.3 million tons by 2025 and this demand has been associated with livestock revolution. This study used charcoal flue gases sourced from the combustion of charcoal briquettes to prolong beef shelf life. The FT-IR technique is based on the specific absorption of infrared radiation by carbon monoxide and carbon dioxide molecules. The characterization of the functional groups was done using Fourier transform infrared spectroscopy (Shimadzu IR Tracer-100). The fresh, treated and boiled beef was ground with potassium bromide (KBr) into pellets and analyzed using FT-IR at a range of 400-3600 cm-1. The reaction of fresh, charcoal flue gas treated and boiled beef samples are as shown in the FT-IR spectrums. The fresh and boiled beef spectrums are similar, while the charcoal flue-treated beef samples show distinct peaks at 2100 and 2290 cm-1, which correspond to carbon monoxide and carbon dioxide, respectively. The study proposes the use of FT-IR in the determination of beef for consumption quality studies.

Keywords: FT-IR, charcoal flue gases, beef, charcoal flue gases

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Authors: Faraz Tahir, M. Usman Akram, Albab Ahmad Khan, Mujahid Abbass, Ahmad Tariq, Nuzhat Qaiser

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The objective of this study was to evaluate the Degree of anemia by taking the picture of the palpebral conjunctiva using Smartphone Camera. We have first localized the region of interest from the image and then extracted certain features from that Region of interest and trained SVM classifier on those features and then, as a result, our system classifies the image in real-time on their level of hemoglobin. The proposed system has given an accuracy of 70%. We have trained our classifier on a locally gathered dataset of 30 patients.

Keywords: anemia, palpebral conjunctiva, SVM, smartphone

Procedia PDF Downloads 503

Authors: Emily Awuor, Helga Huszar, Zoltan Bozoki

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Isotope analysis has found numerous applications in the environmental science discipline, most common being the tracing of environmental contaminants on both regional and global scales. Many environmental contaminants contain ammonia (NH₃) since it is the most abundant gas in the atmosphere and its largest sources are from agricultural and industrial activities. NH₃ isotopes (¹⁴NH₃ and ¹⁵NH₃) are therefore important and can be used in the traceability studies of these atmospheric pollutants. The goal of the project is the construction of a photoacoustic spectroscopy system that is capable of measuring ¹⁵NH₃ isotope selectively in terms of its concentration. A further objective is for the system to be robust, easy-to-use, and automated. This is provided by using two telecommunication type near-infrared distributed feedback (DFB) diode lasers and a laser coupler as the light source in the photoacoustic measurement system. The central wavelength of the lasers in use was 1532 nm, with the tuning range of ± 1 nm. In this range, strong absorption lines can be found for both ¹⁴NH₃ and ¹⁵NH₃. For the selective measurement of ¹⁵NH₃, wavelengths were chosen where the cross effect of ¹⁴NH₃ and water vapor is negligible. We completed the calibration of the photoacoustic system, and as a result, the lowest detectable concentration was 3.32 ppm (3Ϭ) in the case of ¹⁵NH₃ and 0.44 ppm (3Ϭ) in the case of ¹⁴NH₃. The results are most useful in the environmental pollution measurement and analysis.

Keywords: ammonia isotope, near-infrared DFB diode laser, photoacoustic spectroscopy, environmental monitoring

Procedia PDF Downloads 144

Authors: Güzi̇n Ti̇rkeş, Özge Teki̇n, Kerem Kurtuluş, Y. Yekta Yurtseven, Murat Baran

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A scanning electron microscope (SEM) is a type of electron microscope mainly used in nanoscience and nanotechnology areas. Automatic image recognition and classification are among the general areas of application concerning SEM. In line with these usages, the present paper proposes a deep learning algorithm that classifies SEM images into nine categories by means of an online application to simplify the process. The NFFA-EUROPE - 100% SEM data set, containing approximately 21,000 images, was used to train and test the algorithm at 80% and 20%, respectively. Validation was carried out using a separate data set obtained from the Middle East Technical University (METU) in Turkey. To increase the accuracy in the results, the Inception ResNet-V2 model was used in view of the Fine-Tuning approach. By using a confusion matrix, it was observed that the coated-surface category has a negative effect on the accuracy of the results since it contains other categories in the data set, thereby confusing the model when detecting category-specific patterns. For this reason, the coated-surface category was removed from the train data set, hence increasing accuracy by up to 96.5%.

Keywords: convolutional neural networks, deep learning, image classification, scanning electron microscope

Procedia PDF Downloads 124

Authors: Adkham Paiziev, Fikrat Kerimov

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Near Infrared Spectroscopy (NIRS) is one of the biophotonic techniques which can be used to monitor oxygenation and hemodynamics in a variety of human tissues, including skeletal muscle. In the present work, we are offering tissue oximetry (OxyPrem) to measure hemodynamic parameters of skeletal muscles in rest and exercise. Purpose: - To elaborate the new wireless, portable, noninvasive, wearable NIRS device to measure skeletal muscle oxygenation during exercise. - To test this device on brachioradialis muscle of wrestler volunteers by using combined method of arterial occlusion (AO) and NIRS (AO+NIRS). Methods: Oxyprem NIRS device has been used together with AO test. AO test and Isometric brachioradialis muscle contraction experiments have been performed on one group of wrestler volunteers. ‘Accu- Measure’ caliper (USA) to measure skinfold thickness (SFT) has been used. Results: Elaborated device consists on power supply box, a sensor head and installed ‘Tubis’ software for data acquisition and to compute deoxyhemoglobin ([HHb), oxyhemoglobin ([O2Hb]), tissue oxygenation (StO2) and muscle tissue oxygen consumption (mVO2). Sensor head consists on four light sources with three light emitting diodes with nominal wavelengths of 760 nm, 805 nm, and 870 nm, and two detectors. AO and isometric voluntary forearm muscle contraction (IVFMC) on five healthy male subjects (23,2±0.84 in age, 0.43±0.05cm of SFT ) and four female subjects (22.0±1.0 in age and 0.24±0.04 cm SFT) has been measured. mVO2 for control group has been calculated (-0.65%/sec±0.07) for male and -0.69%/±0.19 for female subjects). Tissue oxygenation index for wrestlers in average about 75% whereas for control group StO2 =63%. Second experiment was connected with quality monitoring muscle activity during IVFMC at 10%,30% and 50% of MVC. It has been shown, that the concentration changes of HbO2 and HHb positively correlated to the contraction intensity. Conclusion: We have presented a portable multi-channel wireless NIRS device for real-time monitoring of muscle activity. The miniaturized NIRS sensor and the usage of wireless communication make the whole device have a compact-size, thus can be used in muscle monitoring.

Keywords: skeletal muscle, oxygenation, instrumentation, near infrared spectroscopy

Procedia PDF Downloads 274

Authors: Jesús A. Pérez, Sam Coppieters, Dimitri Debruyne

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In the past decade, the use of digital image correlation (DIC) techniques has increased significantly in the area of experimental mechanics, especially for materials behavior characterization. This non-contact tool enables full field displacement and strain measurements over a complete region of interest. The DIC algorithm requires a random contrast pattern on the surface of the specimen in order to perform properly. To create this pattern, the specimen is usually first coated using a white matt paint. Next, a black random speckle pattern is applied using any suitable method. If the applied paint coating is too thick, its top surface may not be able to exactly follow the deformation of the specimen, and consequently, the strain measurement might be underestimated. In the present article, a study of the influence of the paint thickness on the strain underestimation is performed for different strain levels. The results are then compared to typical paint coating thicknesses applied by experienced DIC users. A slight strain underestimation was observed for paint coatings thicker than about 30μm. On the other hand, this value was found to be uncommonly high compared to coating thicknesses applied by DIC users.

Keywords: digital image correlation, paint coating thickness, strain

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Authors: Selen Muftuoglu, Dilara Kefeli

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The present study was conducted by using the cross-sectional study design and to determine the relationship between body image, eating behavior and nutritional status in 80 female athletes who were basketball, volleyball, flag football, indoor soccer, and ice hockey players. This study demonstrated that 70.0% of the female athletes had skipped meal. Also, female athletes had a normal body mass index (BMI), but 65.0% of them indicated that want to be thinner. On the other hand, we analyzed that their daily nutrients intake, so we observed that 43.4% of the energy was from the fatty acids, especially saturated fatty acids, and they had lower fiber, calcium and iron intake. Also, we found that BMI, waist circumference, waist to hip ratio were negatively correlated with Multidimensional Body-Self Relations Questionnaire and The Dutch Eating Behavior Questionnaire score and they were lower in who had meal skipped or not received diet therapy. As a conclusion, nutrition education is frequently neglected in sports programs. There is a paucity of nutrition education interventions among different sports.

Keywords: body image, eating behavior, eating disorders, female athletes, nutritional status

Procedia PDF Downloads 161

Authors: S. Sushma, S. Balasubramanian, K. C. Latha, R. Sridhar

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Structural texture measures are used to address the aspect of breast cancer risk assessment in screening mammograms. The current study investigates whether texture properties characterized by local Fractal Dimension (FD) and lacunarity contribute to assess breast cancer risk. Fractal Dimension represents the complexity while the lacunarity characterize the gap of a fractal dimension. In this paper, we present our result confirming that the lacunarity value resulted in algorithm using mammogram images states that level of lacunarity will be low when the Fractal Dimension value will be high.

Keywords: breast cancer, fractal dimension, image analysis, lacunarity, mammogram

Procedia PDF Downloads 387

Authors: Dina Ahmed Selim, Eman Shawky Anwar, Rasha Mohamed Abu El-Khair

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A rapid, simple and efficient method with minimal sample treatment was developed for authentication of Garcinia cambogia fruit peel powder, along with determining undeclared active pharmaceutical ingredients (APIs) in its herbal slimming dietary supplements using near infrared spectroscopy combined with chemometrics. Five featured adulterants, including sibutramine, metformin, orlistat, ephedrine, and theophylline are selected as target compounds. The Near infrared spectral data matrix of authentic Garcinia cambogia fruit peel and specimens degraded by intentional contamination with the five selected APIs was subjected to hierarchical clustering analysis to investigate their bundling figure. SIMCA models were established to ensure the genuiness of Garcinia cambogia fruit peel which resulted in perfect classification of all tested specimens. Adulterated samples were utilized for construction of PLSR models based on different APIs contents at minute levels of fraud practices (LOQ < 0.2% w/w).The suggested approach can be applied to enhance and guarantee the safety and quality of Garcinia fruit peel powder as raw material and in dietary supplements.

Keywords: Garcinia cambogia, Quality control, NIR spectroscopy, Chemometrics

Procedia PDF Downloads 76

Authors: Muhammad Azam, Micheal Olaolu Arowolo, Fei He, Mihail Popescu, Dong Xu

Abstract:

The number of biological papers is growing quickly, which means that the number of biological pathway figures in those papers is also increasing quickly. Each pathway figure shows extensive biological information, like the names of genes and how the genes are related. However, manually annotating pathway figures takes a lot of time and work. Even though using advanced image understanding models could speed up the process of curation, these models still need to be made more accurate. To improve gene name recognition from pathway figures, we applied a Siamese network to map image segments to a library of pictures containing known genes in a similar way to person recognition from photos in many photo applications. We used a triple loss function and a triplet spatial pyramid pooling network by combining the triplet convolution neural network and the spatial pyramid pooling (TSPP-Net). We compared VGG19 and VGG16 as the Siamese network model. VGG16 achieved better performance with an accuracy of 93%, which is much higher than OCR results.

Keywords: biological pathway, image understanding, gene name recognition, object detection, Siamese network, VGG

Procedia PDF Downloads 287

Authors: Charles Q. Yu, Victoria H. Fan, Ahmed F. Al-Qahtani, Ibraim Viera

Abstract:

Introduction: Over 12 million people are blind due to opacity of the cornea, the clear tissue forming the front of the eye. Current methods use plastic implants to produce a clear optical pathway into the eye but are limited by a high rate of complications. New implants utilizing completely inside-the-eye projection technology can overcome blindness due to scarring of the eye by producing images on the retina without need for a clear optical pathway into the eye and may be free of the complications of traditional treatments. However, the interior of the eye is a challenging location for the design of optical focusing systems which can produce a sufficiently high quality image. No optical focusing systems have previously been characterized for this purpose. Methods: 3 optical focusing systems for intraocular (inside the eye) projection were designed and then modeled with ray tracing software, including a pinhole system, a planoconvex, and an achromatic system. These were then constructed using off-the-shelf components and tested in the laboratory. Weight, size, magnification, depth of focus, image quality and brightness were characterized. Results: Image quality increased with complexity of system design, as did weight and size. A dual achromatic doublet optical system produced the highest image quality. The visual acuity equivalent achieved with this system was better than 20/200. Its weight was less than that of the natural human crystalline lens. Conclusions: We demonstrate for the first time that high quality images can be produced by optical systems sufficiently small and light to be implanted within the eye.

Keywords: focusing, projection, blindness, cornea , achromatic, pinhole

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Authors: H. G. C. P. Dinesh, G. Tharshini, M. P. B. Ekanayake, G. M. R. I. Godaliyadda

Abstract:

This paper presents a new spatial feature extraction method based on principle component analysis (PCA) and Fisher Discernment Analysis (FDA) for facial expression recognition. It not only extracts reliable features for classification, but also reduces the feature space dimensions of pattern samples. In this method, first each gray scale image is considered in its entirety as the measurement matrix. Then, principle components (PCs) of row vectors of this matrix and variance of these row vectors along PCs are estimated. Therefore, this method would ensure the preservation of spatial information of the facial image. Afterwards, by incorporating the spectral information of the eigen-filters derived from the PCs, a feature vector was constructed, for a given image. Finally, FDA was used to define a set of basis in a reduced dimension subspace such that the optimal clustering is achieved. The method of FDA defines an inter-class scatter matrix and intra-class scatter matrix to enhance the compactness of each cluster while maximizing the distance between cluster marginal points. In order to matching the test image with the training set, a cosine similarity based Bayesian classification was used. The proposed method was tested on the Cohn-Kanade database and JAFFE database. It was observed that the proposed method which incorporates spatial information to construct an optimal feature space outperforms the standard PCA and FDA based methods.

Keywords: facial expression recognition, principle component analysis (PCA), fisher discernment analysis (FDA), eigen-filter, cosine similarity, bayesian classifier, f-measure

Procedia PDF Downloads 423

Authors: Zoubida Mahi

Abstract:

A successful satellite mission in space requires a reliable attitude and orbit control system to command, control and position the satellite in appropriate orbits. Several sensors are used for attitude control, such as magnetic sensors, earth sensors, horizon sensors, gyroscopes, and solar sensors. The star tracker is the most accurate sensor compared to other sensors, and it is able to offer high-accuracy attitude control without the need for prior attitude information. There are mainly three approaches in star sensor research: digital simulation, hardware in the loop simulation, and field test of star observation. In the digital simulation approach, all of the processes are done in software, including star image simulation. Hence, it is necessary to develop star image simulation software that could simulate real space environments and various star sensor configurations. In this paper, we present a new stellar image simulation tool that is used to test and validate the stellar sensor algorithms; the developed tool allows to simulate of stellar images with several types of noise, such as background noise, gaussian noise, Poisson noise, multiplicative noise, and several scenarios that exist in space such as the presence of the moon, the presence of optical system problem, illumination and false objects. On the other hand, we present in this paper a new star extraction algorithm based on a new centroid calculation method. We compared our algorithm with other star extraction algorithms from the literature, and the results obtained show the star extraction capability of the proposed algorithm.

Keywords: star tracker, star simulation, star detection, centroid, noise, scenario

Procedia PDF Downloads 94

Authors: Sandro Nikolaishvili

Abstract:

The end of the eleventh and the beginning of the twelfth century was a transitional period for the Byzantine empire as well as for the Caucasus. The empire was struggling for its survival under Alexios I Komnenos while Medieval Georgia was emerging as a dominant player in the Caucasus under Davit IV the Builder. The reigns of these two rulers were periods of renewal and transformation. I aim to compare the imperial image of Alexios I Komnenos with the renewed kingship ideology under Davit IV. I will hypothesize about the possible translation of the Byzantine political culture into the Medieval Georgia.

Keywords: Byzantium, Georgia, imperial, image

Procedia PDF Downloads 416

Authors: Han Xiao

Abstract:

The development of nanomedicines has recently achieved several breakthroughs in the field of cancer treatment; however, the biocompatibility and targeted burst release of these medications remain a limitation, which leads to serious side effects and significantly narrows the scope of their applications. The self-assembly of intermediate filament protein (IFP) peptides was triggered by a hydrophobic cation drug 7-amino actinomycin D (7-AAD) to synthesize pH-activatable nanoparticles (NPs) that could simultaneously locate tumors and produce antitumor effects. The designed IFP peptide included a target peptide (arginine–glycine–aspartate), a negatively charged region, and an α-helix sequence. It also possessed the ability to encapsulate 7-AAD molecules through the formation of hydrogen bonds and hydrophobic interactions by a one-step method. 7-AAD molecules with excellent near-infrared fluorescence properties could be target delivered into tumor cells by NPs and released immediately in the acidic environments of tumors and endosome/lysosomes, ultimately inducing cytotoxicity by arresting the tumor cell cycle with inserted DNA. It is noteworthy that the IFP/7-AAD NPs tail vein injection approach demonstrated not only high tumor-targeted imaging potential, but also strong antitumor therapeutic effects in vivo. The proposed strategy may be used in the delivery of cationic antitumor drugs for precise imaging and cancer therapy.

Keywords: 7-amino actinomycin D, intermediate filament protein, nanoparticle, tumor image

Procedia PDF Downloads 136