Search results for: body image

Authors: Chinsuk Hong

Abstract:

This paper investigates the characteristics of wall pressure fluctuations in naturally developing boundary layer flows on axisymmetric bodies experimentally. The axisymmetric body has a modified ellipsoidal blunt nose. Flush-mounted microphones are used to measure the wall pressure fluctuations in the boundary layer flow over the body. The measurements are performed in a low noise wind tunnel. It is found that the correlation between the flow regime and the characteristics of the pressure fluctuations is distinct. The process from small fluctuation in laminar flow to large fluctuation in turbulent flow is investigated. Tollmien-Schlichting wave (T-S wave) is found to generate and develop in transition. Because of the T-S wave, the wall pressure fluctuations in the transition region are higher than those in the turbulent boundary layer.

Keywords: wall pressure fluctuation, boundary layer flow, transition, turbulent flow, axisymmetric body, flow noise

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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

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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

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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

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Authors: Ahmed Ghachem, Johann Colomba, Denis Prud'homme, Martin Brochu

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Background: Inactive obese postmenopausal women, are at greater risk for metabolic complications. On the other hand, high levels of cardiorespiratory fitness (CRF) are associated with a lower risk of metabolic complications. Objective: To compare inactive obese postmenopausal women displaying ‘lower’ vs ‘higher’ levels of CRF for body composition, metabolic profile, inflammatory profile and measures of energy expenditure. Methods: 132 women (age: 57.6 ± 4.8 yrs; BMI: 32.3 ± 4.6 kg/m2; Peak VO2: 17.81 ± 3.02 ml O2•kg-1•min-1) were studied. They were first divided into tertiles based on their CRF. Then, women in the first (< 16.51 ml O2•min-1•kg-1) and second tertiles (16.51 to 19.22 ml O2•min-1•kg-1) were combined (N= 88), and compared with those in the third tertile (> 19.22 ml O2•min-1•kg-1) (N= 44). Variables of interest were: Peak VO2 (stationary bike), body composition (DXA), body fat distribution (CT scan), glucose homeostasis (fasting state and euglycemic/ hyperinsulinemic clamp), fasting lipids, resting blood pressure, inflammatory profile and energy expenditure (DLW). Results: Both CRF groups (lower= 16.0 ± 2.0 ml O2•kg-1•min-1 vs higher= 21.2 ± 1.7 ml O2•kg-1•min-1; p < 0.001) were similar for age. Significant differences were observed between groups for body composition; with lower values for body weight, BMI, fat mass and visceral fat in women with higher CRF (p between 0.001 and 0.005). Also, women with higher CRF had lower values for fasting insulin (13.4 ± 4.5 vs 15.6 ± 6.6 μU/ml; p = 0.03) and CRP levels (2.31 ± 1.97 vs 3.83 ± 3.24 mg/liter; p = 0.001); and higher values for glucose disposal (6.71 ± 1.78 vs 5.92 ± 1.67 mg/kg/min; p = 0.01). However, these differences were no longer significant after controlling for visceral adipose tissue accumulations. Finally, no significant difference was observed between groups for the other variables of interest. Conclusion: Our results suggest that, among inactive overweight/obese postmenopausal women, those with higher CRF levels have a better metabolic profile; which is caused by lower visceral fat accumulations.

Keywords: cardiorespiratory fitness, metabolic profile, menopause, obesity

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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

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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

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Authors: Oluwatosin M. A. Jesuyon

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In order to propose a simpler tool that eliminates the age-long problems associated with the traditional index method for selection of multiple traits in broilers, the Barttlet factor regression equation is being proposed as an alternative selection tool. 100 day-old chicks each of Arbor Acres (AA) and Annak (AN) broiler strains were obtained from two rival hatcheries in Ibadan Nigeria. These were raised in deep litter system in a 56-day feeding trial at the University of Ibadan Teaching and Research Farm, located in South-west Tropical Nigeria. The body weight and body dimensions were measured and recorded during the trial period. Eight (8) zoometric measurements namely live weight (g), abdominal circumference, abdominal length, breast width, leg length, height, wing length and thigh circumference (all in cm) were recorded randomly from 20 birds within strain, at a fixed time on the first day of the new week respectively with a 5-kg capacity Camry scale. These records were analyzed and compared using completely randomized design (CRD) of SPSS analytical software, with the means procedure, Factor Scores (FS) in stepwise Multiple Linear Regression (MLR) procedure for initial live weight equations. Bartlett Factor Score (BFS) analysis extracted 2 factors for each strain, termed Body-length and Thigh-meatiness Factors for AA, and; Breast Size and Height Factors for AN. These derived orthogonal factors assisted in deducing and comparing trait-combinations that best describe body conformation and Meatiness in experimental broilers. BFS procedure yielded different body conformational traits for the two strains, thus indicating the different economic traits and advantages of strains. These factors could be useful as selection criteria for improving desired economic traits. The final Bartlett Factor Regression equations for prediction of body weight were highly significant with P < 0.0001, R2 of 0.92 and above, VIF of 1.00, and DW of 1.90 and 1.47 for Arbor Acres and Annak respectively. These FSR equations could be used as a simple and potent tool for selection during poultry flock improvement, it could also be used to estimate selection index of flocks in order to discriminate between strains, and evaluate consumer preference traits in broilers.

Keywords: alternative selection tool, Bartlet factor regression model, consumer preference trait, linear and body measurements, live body weight

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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

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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

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Authors: Leonardo Costa Pereira, Frederico Santos Santana, Mauro Karnikowski, Luís Sinésio Silva Neto, Aline Oliveira Gomes, Marisete Peralta Safons, Margô Gomes De Oliveira Karnikowski

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In Brazil, projections of population aging follow all world projections, the birth rate tends to be surpassed by the mortality rate around the year 2045. Historically, the population of Brazilian blacks suffered for several centuries from the oppression of dominant classes. A group, especially of blacks, stands out in relation to territorial, historical and social aspects, and for centuries they have isolated themselves in small communities, in order to maintain their freedom and culture. The isolation of the Quilombola communities generated socioeconomic effects as well as the health of these blacks. Thus, the objective of the present study is to verify the association of body composition parameters with lower and upper limb strength and functional capacity in Quilombola remnants. The research was approved by ethics committee (1,771,159). Anthropometric evaluations of hip and waist circumference, body mass and height were performed. In order to verify the body composition, the relationship between stature and body mass (BM) was performed, generating the body mass index (BMI), as well as the dual-energy X-ray absorptiometry (DEXA) test. The Time Up and Go (TUG) test was used to evaluate the functional capacity, and a maximum repetition test (1MR) for knee extension and handgrip (HG) was applied for strength magnitude analysis. Statistical analysis was performed using the statistical package SPSS 22.0. Shapiro Wilk's normality test was performed. For the possible correlations, the suggestions of the Pearson or Spearman tests were adopted. The results obtained after the interpretation identified that the sample (n = 18) was composed of 66.7% of female individuals with mean age of 66.07 ± 8.95 years. The sample’s body fat percentage (%BF) (35.65 ± 10.73) exceeds the recommendations for age group, as well as the anthropometric parameters of hip (90.91 ± 8.44cm) and waist circumference (80.37 ± 17.5cm). The relationship between height (1.55 ± 0.1m) and body mass (63.44 ± 11.25Kg) generated a BMI of 24.16 ± 7.09Kg/m2, that was considered normal. The TUG performance was 10.71 ± 1.85s. In the 1MR test, 46.67 ± 13.06Kg and in the HG 23.93±7.96Kgf were obtained, respectively. Correlation analyzes were characterized by the high frequency of significant correlations for height, dominant arm mass (DAM), %BF, 1MR and HG variables. In addition, correlations between HG and BM (r = 0.67, p = 0.005), height (r = 0.51, p = 0.004) and DAM (r = 0.55, p = 0.026) were also observed. The strength of the lower limbs correlates with BM (r = 0.69, p = 0.003), height (r = 0.62, p = 0.01) and DAM (r = 0.772, p = 0.001). In this way, we can conclude that not only the simple spatial relationship of mass and height can influence in predictive parameters of strength or functionality, being important the verification of the conditions of the corporal composition. For this population, height seems to be a good predictor of strength and body composition.

Keywords: African Continental Ancestry Group, body composition, functional capacity, strength

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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

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Authors: Fathi Kallel, Abdulelah Alabd Uljabbar, Abdulrahman Aldukhail, Abdulaziz Alomran

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The brain is an important organ in our body since it is responsible about the majority actions such as vision, memory, etc. However, different diseases such as Alzheimer and tumors could affect the brain and conduct to a partial or full disorder. Regular diagnosis are necessary as a preventive measure and could help doctors to early detect a possible trouble and therefore taking the appropriate treatment, especially in the case of brain tumors. Different imaging modalities are proposed for diagnosis of brain tumor. The powerful and most used modality is the Magnetic Resonance Imaging (MRI). MRI images are analyzed by doctor in order to locate eventual tumor in the brain and describe the appropriate and needed treatment. Diverse image processing methods are also proposed for helping doctors in identifying and analyzing the tumor. In fact, a large Computer Aided Diagnostic (CAD) tools including developed image processing algorithms are proposed and exploited by doctors as a second opinion to analyze and identify the brain tumors. In this paper, we proposed a new advanced CAD for brain tumor identification, classification and feature extraction. Our proposed CAD includes three main parts. Firstly, we load the brain MRI. Secondly, a robust technique for brain tumor extraction is proposed. This technique is based on both Discrete Wavelet Transform (DWT) and Principal Component Analysis (PCA). DWT is characterized by its multiresolution analytic property, that’s why it was applied on MRI images with different decomposition levels for feature extraction. Nevertheless, this technique suffers from a main drawback since it necessitates a huge storage and is computationally expensive. To decrease the dimensions of the feature vector and the computing time, PCA technique is considered. In the last stage, according to different extracted features, the brain tumor is classified into either benign or malignant tumor using Support Vector Machine (SVM) algorithm. A CAD tool for brain tumor detection and classification, including all above-mentioned stages, is designed and developed using MATLAB guide user interface.

Keywords: MRI, brain tumor, CAD, feature extraction, DWT, PCA, classification, SVM

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Authors: Varsha Chorsiya, Pooja Aneja, Dhananjay Kaushik, Abhinav Yadav

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Intoduction: Women’s Health Initiatives (WHI) focuses on defining the risks and benefits of strategies that could potentially reduce the incidence of obesity, heart disease, breast cancer and colorectal cancer, and fractures in menopause women. The utility of the present research work determines to find the role of Hormone Replacement Therapy (HRT) in changing the different component of body composition during perimenopause period. Methods: A comparative cross-sectional study included 30 subjects, aged between 40 and 50 years which were assigned into 2 groups i.e. 15 subjects in HRT (Group A) and 15 subjects in non-HRT (Group B). The subjects were taken from the hospitals and clinics of Faridabad undergoing HRT in supervision of the consultant gynecologist. The informed consents were signed before including the participants in the study. The body composition and lipid profile were evaluated for all the subjects. Result and Discussion: The BMI, body density, percent body fats and fat mass in both groups showed statistically significant differences i.e. p < 0.05. Our study did not reveal any statistically significant difference between non-HRT and HRT for lipid profile composition of HDL, LDL, VLDL, ratio, triglycerides and total cholesterol although these indicators (LDL, VLDL, ratio, triglycerides and total cholesterol) showed difference clinically with a higher mean values for non-HRT as compared to HRT group. The mean value for HDL was higher for HRT group in contrast to non-HRT group. The result clearly showed that HRT group has a good lipid profile composition. Conclusion: In conclusion, our data show that HRT has statistically significant role in determining BMI, fat percent mass and fat mass. The lipid profile including LDL, HDL, VLDL, ratio, triglycerides and total cholesterol found to be clinically better in HRT group as compared to the non-HRT group. The rationale for non-significant lipid profile probably lie in the fact that hormonal changes need a particular time period and might become significant in post-menopausal period.

Keywords: body composition, hormone replacement therapy, perimenopause, women health

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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

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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

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Authors: Neda Valizadeh, Mani Mofidi, Sama Haghighi, Ali Hashemaghaee, Soudabeh Shafiee Ardestani

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Background: There are many systems and parameters to evaluate trauma patients in the emergency department. Most of these evaluations are to distinguish patients with worse conditions so that the care systems have a better prediction of condition for a better care-giving. The purpose of this study is to determine the relationship between axillary body temperature and mortality in patients hospitalized in the intensive care unit (ICU) with multiple traumas and with other clinical and para-clinical factors. Methods: All patients between 16 and 75 years old with multiple traumas who were admitted into Emergency Department then hospitalized in the ICU were included in our study. An axillary temperature in the first and the second day of admission, Glasgow cola scale (GCS), systolic blood pressure, Serum glucose levels, and white blood cell counts of all patients at the admission day were recorded and their relationship with mortality were analyzed by SPSS software with suitable statistical tests. Results: Axillary body temperatures in the first and second day were statistically lower in expired traumatic patients (p=0.001 and p<0,001 respectively). Patients with lower GCS had a significantly lower first-day temperature and a significantly higher mortality. (p=0.006 and p=0.006 respectively). Furthermore, the first-day axillary temperature was significantly lower in patients with a lower first-day systolic blood pressure (p=0.014). Conclusion: Our results showed that lower axillary body temperature in the first day is associated with higher mortality, lower GCS, and lower systolic blood pressure. Thus, this could be used as a predictor of mortality in evaluation of traumatic patients in emergency settings.

Keywords: fever, trauma, mortality, emergency

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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: Ingrid Ruzbarska, Martin Zvonar, Piotr Oleśniewicz, Julita Markiewicz-Patkowska, Krzysztof Widawski, Daniel Puciato

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Obese children will probably become obese adults, consequently exposed to an increased risk of comorbidity and premature mortality. Body weight may be indirectly determined by continuous development of coordination and motor skills. The level of motor skills and abilities is an important factor that promotes physical activity since early childhood. The aim of the study is to thoroughly understand the internal relations between motor coordination abilities and the somatic development of prepubertal children and to determine the effect of excess body weight on motor coordination by comparing the motor ability levels of children with different body mass index (BMI) values. The data were collected from 436 children aged 7–10 years, without health limitations, fully participating in school physical education classes. Body height was measured with portable stadiometers (Harpenden, Holtain Ltd.), and body mass—with a digital scale (HN-286, Omron). Motor coordination was evaluated with the Kiphard-Schilling body coordination test, Körperkoordinationstest für Kinder. The normality test by Shapiro-Wilk was used to verify the data distribution. The correlation analysis revealed a statistically significant negative association between the dynamic balance and BMI, as well as between the motor quotient and BMI (p<0.01) for both boys and girls. The results showed no effect of gender on the difference in the observed trends. The analysis of variance proved statistically significant differences between normal weight children and their overweight or obese counterparts. Coordination abilities probably play an important role in preventing or moderating the negative trajectory leading to childhood overweight and obesity. At this age, the development of coordination abilities should become a key strategy, targeted at long-term prevention of obesity and the promotion of an active lifestyle in adulthood. Motor performance is essential for implementing a healthy lifestyle in childhood already. Physical inactivity apparently results in motor deficits and a sedentary lifestyle in children, which may be accompanied by excess energy intake and overweight.

Keywords: childhood, KTK test, physical education, psychomotor competence

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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

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Authors: Luci V. Hyett

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The criminal law of England and Wales currently deems that a person cannot consent to the infliction of injury upon their own body, where the level of harm is considered to be Actual or Grevious. This renders the defence of consent of the victim as being unavailable to those persons carrying out an Alternative Body Modification procedure. However, the criminalization of consensual injury is more appropriately deemed as being categorized as an offense against public morality and not one against the person, which renders the State’s involvement in the autonomous choices of a consenting adult, when determining what can be done to one’s own body, an arbitrary one. Furthermore, to recognise in law that a person is capable of giving a valid consent to socially acceptable cosmetic interventions that largely consist of procedures designed to aesthetically please men and, not those of people who want to modify their bodies for other reasons means that patriarchal attitudes are continuing to underpin public repulsion and inhibit social acceptance of such practices. Theoretical analysis will begin with a juridical examination of R v M(B) [2019] QB 1 where the High Court determined that Alternative Body Modification was not a special category exempting a person so performing from liability for Grevious Bodily Harm using the defence of consent. It will draw from its reasoning which considered that ‘the removal of body parts were medical procedures being carried out for no medical reason by someone not qualified to carry them out’ which will form the basis of this enquiry. It will consider the philosophical work of Georgio Agamben when analysing whether the biopolitical climate in the UK, which places the optimization of the perfect, healthy body at the centre of political concern can explain why those persons who wish to engage in Alternative Body Modification are treated as the ‘Exception’ to that which is normal using the ‘no medical reason’ canon to justify criminalisation, rather than legitimising the industry through regulation. It will consider, through a feminist lens, the current conflict in law between traditional cosmetic interventions which alter one’s physical appearance for socially accepted aesthetic purposes such as those to the breast, lip and buttock and, modifications described as more outlandish such as earlobe stretching, tooth filing and transdermal implants to create horns and spikes under the skin. It will assert that ethical principles relating to the psychological impact of body modification described as ‘alternative’ is used as a means to exclude person’s seeking such a procedure from receiving safe and competent treatment via a registered cosmetic surgeon which leads to these increasingly popular surgery’s being performed in Tattoo parlours throughout the UK as an extension to other socially acceptable forms of self-modification such as piercings. It will contend that only by ‘inclusive exclusion’ will those ‘othered’ through ostracisation be welcomed into the fold of normality and this can only be achieved through recognition of alternative body modification as a legitimate cosmetic intervention, subject to the same regulatory framework as existing practice. This would assist in refocusing the political landscape by erring on the side of liberty rather than that of biology.

Keywords: biopolitics, body modification, consent, criminal law

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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

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Authors: Elle Nielsen

Abstract:

Festival time on the island of St. Croix is an annual celebration of a melting pot of rich culture and heritage. All your senses are amplified by the colorful bodies that paint the streets with swaying hips commemorating the ancestors who didn’t have the voice to express themselves, let alone the bodily authority through movement. Within this atmosphere of jubilee, you will become a witness to how the melodies of Calypso and Soca music take full control of the body. As a result, the waist and hips in a trance follow the polyrhythmic patterns birthing the shunned movement practices of whining and wukkin up. Spectators on the sidelines of the festival events will either frown upon this spectacle of the whining bodies or gaze in awe at the performative history in a public space. The historical value of the Caribbean Carnival is being defaced by the transnational spectatorship using body politics to push more of a Eurocentric-influenced atmosphere. The themes within this investigation are the stereotypes of over-sexualization and resistance to assimilation to how black female bodies are being viewed in Carnival.

Keywords: women equity, West Indian movement vocabulary, critical dance studies, humanitarianism in dance academia

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Authors: Shouta Sora, Shizuki Kuriu, Radhika Mishra, Ariunbuyan Sukhbaatar, Maya Sakamoto, Shiro Mori, Tetsuya Kodama

Abstract:

Lymph node (LN) metastasis accounts for 20 - 30 % of all deaths in patients with head and neck cancer. Therefore, the control of metastatic lymph nodes (MLNs) is necessary to improve the life prognosis of patients with cancer. In a classical metastatic theory, tumor cells are thought to metastasize hematogenously through a bead-like network of lymph nodes. Recently, a lymph node-mediated hematogenous metastasis theory has been proposed, in which sentinel LNs are regarded as a source of distant metastasis. Therefore, the treatment of MLNs at the early stage is essential to prevent distant metastasis. Radiation therapy is one of the primary therapeutic modalities in cancer treatment. In addition, total body irradiation (TBI) has been reported to act as activation of natural killer cells and increase of infiltration of CD4+ T-cells to tumor tissues. However, the treatment effect of TBI for MLNs remains unclear. This study evaluated the possibilities of low-dose total body irradiation (L-TBI) and middle-dose total body irradiation (M-TBI) for the treatment of MLNs. Mouse breast cancer FM3A-Luc cells were injected into subiliac lymph node (SiLN) of MXH10/Mo/LPR mice to induce the metastasis to the proper axillary lymph node (PALN) and lung. Mice were irradiated for the whole body on 4 days after tumor injection. The L-TBI and M-TBI were defined as irradiations to the whole body at 0.2 Gy and 1.0 Gy, respectively. Tumor growth was evaluated by in vivo bioluminescence imaging system. In the non-irradiated group, tumor activities on SiLN and PALN significantly increased over time, and the metastasis to the lung from LNs was confirmed 28 days after tumor injection. The L-TBI led to a tumor growth delay in PALN but did not control tumor growth in SiLN and metastasis to the lung. In contrast, it was found that the M-TBI significantly delayed the tumor growth of both SiLN and PALN and controlled the distant metastasis to the lung compared with non-irradiated and L-TBI groups. These results suggest that the M-TBI is an effective treatment method for MLNs in the early stage and distant metastasis from lymph nodes via blood vessels connected with LNs.

Keywords: metastatic lymph node, lung metastasis, radiation therapy, total body irradiation, lymphatic system

Procedia PDF Downloads 181

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

Procedia PDF Downloads 132

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

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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

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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

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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 417

Authors: Hao Cheng, Zhiwu Wang, Guozheng Yan, Pingping Jiang, Shijia Qin, Shuai Kuang

Abstract:

Autofluorescence Imaging (AFI) is a technology for detecting early carcinogenesis of the gastrointestinal tract in recent years. Compared with traditional white light endoscopy (WLE), this technology greatly improves the detection accuracy of early carcinogenesis, because the colors of normal tissues are different from cancerous tissues. Thus, edge detection can distinguish them in grayscale images. In this paper, based on the traditional Sobel edge detection method, optimization has been performed on this method which considers the environment of the gastrointestinal, including adaptive threshold and morphological processing. All of the processes are implemented on our self-designed system based on the image sensor OV6930 and Field Programmable Gate Array (FPGA), The system can capture the gastrointestinal image taken by the lens in real time and detect edges. The final experiments verified the feasibility of our system and the effectiveness and accuracy of the edge detection algorithm.

Keywords: AFI, edge detection, adaptive threshold, morphological processing, OV6930, FPGA

Procedia PDF Downloads 230

Authors: Elitza Z. Ambrus, Bjoern Hartig, Ryan McKay

Abstract:

Individuals’ self-judgments might be malleable and influenced by comparison with a random value. On the one hand, self-judgments reflect our self-image, which is typically considered to be stable in adulthood. Indeed, people also strive hard to maintain a fixed, positive moral image of themselves. On the other hand, research has shown the robustness of the so-called anchoring effect on judgments and decisions. The anchoring effect refers to the influence of a previously considered comparative value (anchor) on a consecutive absolute judgment and reveals that individuals’ estimates of various quantities are flexible and can be influenced by a salient random value. The present study extends the anchoring paradigm to the domain of the self. We also investigate whether participants are more susceptible to self-serving anchors, i.e., anchors that enhance participant’s self-image, especially their moral self-image. In a pre-reregistered study via the online platform Prolific, 249 participants (156 females, 89 males, 3 other and 1 who preferred not to specify their gender; M = 35.88, SD = 13.91) ranked themselves on eight personality characteristics. However, in the anchoring conditions, respondents were asked to first indicate whether they thought they would rank higher or lower than a given anchor value before providing their estimated rank in comparison to 100 other anonymous participants. A high and a low anchor value were employed to differentiate between anchors in a desirable (self-serving) direction and anchors in an undesirable (self-diminishing) direction. In the control treatment, there was no comparison question. Subsequently, participants provided their self-rankings on the eight personality traits with two personal characteristics for each combination of the factors desirable/undesirable and moral/non-moral. We found evidence of an anchoring effect for self-judgments. Moreover, anchoring was more efficient when people were anchored in a self-serving direction: the anchoring effect was enhanced when supporting a more favorable self-view and mitigated (even reversed) when implying a deterioration of the self-image. The self-serving anchoring was more pronounced for moral than for non-moral traits. The data also provided evidence in support of a better-than-average effect in general as well as a magnified better-than-average effect for moral traits. Taken together, these results suggest that self-judgments might not be as stable in adulthood as previously thought. In addition, considerations of constructing and maintaining a positive self-image might interact with the anchoring effect on self-judgments. Potential implications of our results concern the construction and malleability of self-judgments as well as the psychological mechanism shaping anchoring.

Keywords: anchoring, better-than-average effect, self-judgments, self-serving anchoring

Procedia PDF Downloads 180