Search results for: metallurgical image processing

Authors: Yongseok Kwon, Woowon Jeong, Eunjin Cho, Sangkug Chung, Kyehan Rhee

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Steady streaming flow fields induced by a 500 um bubble oscillating at 12 kHz were measured using microscopic particle image velocimetry (PIV). The accuracy of velocity measurement using a micro PIV system was checked by comparing the measured velocity fields with the theoretical velocity profiles in fully developed laminar flow. The steady streaming flow velocities were measured in the saggital plane of the bubble attached on the wall. Measured velocity fields showed upward jet flow with two symmetric counter-rotating vortices, and the maximum streaming velocity was about 12 mm/s, which was within the velocity ranges measured by other researchers. The measured streamlines were compared with the analytic solution, and they also showed a reasonable agreement.

Keywords: oscillating bubble, particle image velocimetry, microstreaming, vortices,

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Authors: Dong Liu

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By sending a high-frequency probe wave and a low-frequency pump wave to a specimen, the vibroacoustic method evaluates the defect’s severity according to the modulation index of the received signal. Many studies experimentally proved the significant sensitivity of the modulation index to the tiny contact type defect. However, it has also been found that the modulation index was highly affected by the frequency of probe or pump waves. Therefore, the chirp signal has been introduced to the VAM method since it can assess multiple frequencies in a relatively short time duration, so the robustness of the VAM method could be enhanced. Consequently, the signal processing method needs to be modified accordingly. Various studies utilized different algorithms or combinations of algorithms for processing the VAM signal method by chirp excitation. These signal process methods were compared and used for processing a VAM signal acquired from the steel samples.

Keywords: vibroacoustic modulation, nonlinear acoustic modulation, nonlinear acoustic NDT&E, signal processing, structural health monitoring

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Authors: Robson da C. Santos, Carlos Henrique de A. S. P. Coutinho, Lucas Moreira Dias, Gerson Gomes Cunha

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The article refers to the development of an augmented reality 3D display, through the control of servo motors and projection of image with aid of video projector on the model. Augmented Reality is a branch that explores multiple approaches to increase real-world view by viewing additional information along with the real scene. The article presents the broad use of electrical, electronic, mechanical and industrial automation for geospatial visualizations, applications in mathematical models with the visualization of functions and 3D surface graphics and volumetric rendering that are currently seen in 2D layers. Application as a 3D display for representation and visualization of Digital Terrain Model (DTM) and Digital Surface Models (DSM), where it can be applied in the identification of canyons in the marine area of the Campos Basin, Rio de Janeiro, Brazil. The same can execute visualization of regions subject to landslides, as in Serra do Mar - Agra dos Reis and Serranas cities both in the State of Rio de Janeiro. From the foregoing, loss of human life and leakage of oil from pipelines buried in these regions may be anticipated in advance. The physical design consists of a table consisting of a 9 x 16 matrix of servo motors, totalizing 144 servos, a mesh is used on the servo motors for visualization of the models projected by a retro projector. Each model for by an image pre-processing, is sent to a server to be converted and viewed from a software developed in C # Programming Language.

Keywords: visualization, 3D models, servo motors, C# programming language

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Authors: Okhee Woo

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Purpose: With increasing concern of individual radiation exposure doses, studies analyzing radiation dosage in breast imaging modalities are required. Aim of this study is to compare radiation dosage and image quality between digital breast tomosynthesis (DBT) and full-field digital mammography (FFDM). Methods and Materials: 303 patients (mean age 52.1 years) who studied DBT and FFDM were retrospectively reviewed. Radiation dosage data were obtained by radiation dosage scoring and monitoring program: Radimetrics (Bayer HealthCare, Whippany, NJ). Entrance dose and mean glandular doses in each breast were obtained in both imaging modalities. To compare the image quality of DBT with two-dimensional synthesized mammogram (2DSM) and FFDM, 5-point scoring of lesion clarity was assessed and the better modality between the two was selected. Interobserver performance was compared with kappa values and diagnostic accuracy was compared using McNemar test. The parameters of radiation dosages (entrance dose, mean glandular dose) and image quality were compared between two modalities by using paired t-test and Wilcoxon rank sum test. Results: For entrance dose and mean glandular doses for each breasts, DBT had lower values compared with FFDM (p-value < 0.0001). Diagnostic accuracy did not have statistical difference, but lesion clarity score was higher in DBT with 2DSM and DBT was chosen as a better modality compared with FFDM. Conclusion: DBT showed lower radiation entrance dose and also lower mean glandular doses to both breasts compared with FFDM. Also, DBT with 2DSM had better image quality than FFDM with similar diagnostic accuracy, suggesting that DBT may have a potential to be performed as an alternative to FFDM.

Keywords: radiation dose, DBT, digital mammography, image quality

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Authors: Parimalah Velo, Ahmad Zakaria

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Introduction: Monte Carlo simulations of preclinical imaging systems allow opportunity to enable new research that could range from designing hardware up to discovery of new imaging application. The simulation system which could accurately model an imaging modality provides a platform for imaging developments that might be inconvenient in physical experiment systems due to the expense, unnecessary radiation exposures and technological difficulties. The aim of present study is to validate the Monte Carlo simulation of thyroid phantom imaging using Geant4-GATE for Siemen’s e-cam single head gamma camera. Upon the validation of the gamma camera simulation model by comparing physical characteristic such as energy resolution, spatial resolution, sensitivity, and dead time, the GATE simulation of thyroid phantom imaging is carried out. Methods: A thyroid phantom is defined geometrically which comprises of 2 lobes with 80mm in diameter, 1 hot spot, and 3 cold spots. This geometry accurately resembling the actual dimensions of thyroid phantom. A planar image of 500k counts with 128x128 matrix size was acquired using simulation model and in actual experimental setup. Upon image acquisition, quantitative image analysis was performed by investigating the total number of counts in image, the contrast of the image, radioactivity distributions on image and the dimension of hot spot. Algorithm for each quantification is described in detail. The difference in estimated and actual values for both simulation and experimental setup is analyzed for radioactivity distribution and dimension of hot spot. Results: The results show that the difference between contrast level of simulation image and experimental image is within 2%. The difference in the total count between simulation and actual study is 0.4%. The results of activity estimation show that the relative difference between estimated and actual activity for experimental and simulation is 4.62% and 3.03% respectively. The deviation in estimated diameter of hot spot for both simulation and experimental study are similar which is 0.5 pixel. In conclusion, the comparisons show good agreement between the simulation and experimental data.

Keywords: gamma camera, Geant4 application of tomographic emission (GATE), Monte Carlo, thyroid imaging

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Authors: Mitat Uysal, Aynur Uysal

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Artificial Intelligence (AI) is fundamentally driven by mathematics, with many of its core algorithms rooted in mathematical principles such as linear algebra, probability theory, calculus, and optimization techniques. This paper explores the deep connection between AI and mathematics, highlighting the role of mathematical concepts in key AI techniques like machine learning, neural networks, and optimization. To demonstrate this connection, a case study involving the implementation of a neural network using Python is presented. This practical example illustrates the essential role that mathematics plays in training a model and solving real-world problems.

Keywords: AI, mathematics, machine learning, optimization techniques, image processing

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Authors: M. Y. Lee, S. H. Park, S. M. Yu, H. S. Jo, C. G. Song

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Photoacoustic imaging is the imaging technology that combines the optical imaging with ultrasound. It also provides the high contrast and resolution due to optical and ultrasound imaging, respectively. For these reasons, many studies take experiment in order to apply this method for many diagnoses. We developed the real-time photoacoustic tomography (PAT) system using linear-ultrasound transducer. In this study, we conduct the experiment using swine and detect the blood of carotid artery and femoral artery. We measured the blood of femoral and carotid artery of swine and reconstructed the image using 950nm due to the HbO₂ absorption coefficient. The photoacoustic image is overlaid with ultrasound image in order to match the position. In blood of artery, major composition of blood is HbO₂. In this result, we can measure the blood of artery.

Keywords: photoacoustic tomography, swine artery, carotid artery, femoral artery

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Authors: Krishna Mohan Bathula, Fatou Bintou Loucoubar, FNU Kaleemunnisa, Christelle Scharff, Mark Anthony De Castro

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Voice recognition algorithms such as automatic speech recognition and text-to-speech systems with African languages can play an important role in bridging the digital divide of Artificial Intelligence in Africa, contributing to the establishment of a fully inclusive information society. This paper proposes a Deep Learning model that can classify the user responses as inputs for an interactive voice response system. A dataset with Wolof language words ‘yes’ and ‘no’ is collected as audio recordings. A two stage Data Augmentation approach is adopted for enhancing the dataset size required by the deep neural network. Data preprocessing and feature engineering with Mel-Frequency Cepstral Coefficients are implemented. Convolutional Neural Networks (CNNs) have proven to be very powerful in image classification and are promising for audio processing when sounds are transformed into spectra. For performing voice response classification, the recordings are transformed into sound frequency feature spectra and then applied image classification methodology using a deep CNN model. The inference model of this trained and reusable Wolof voice response recognition system can be integrated with many applications associated with both web and mobile platforms.

Keywords: automatic speech recognition, interactive voice response, voice response recognition, wolof word classification

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Authors: Nour-Elhouda Lecheheb

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Despite substantial tourism potentials, the Algerian tourism industry has faced a number of challenges, including the government heavy dependence on the energy sector, negative perception in the West, and a lack of effective resource management and marketing. This paper attempts to discuss the challenges hindering the development of the Algerian tourism industry from the perspective of the official tourism suppliers in Algeria both in the public and private sectors. A total of 10 semi-structured interviews were conducted during a field-trip to Algiers, Algeria, in September 2019. From the analysis of the interviews, it is evident that the Algerian tourism suppliers face a number of challenges mainly the country’s negative image in the West and a significant lack of political and financial support to contest this negative image effectively and sufficiently.

Keywords: Algerian tourism, destination development, destination image, tourism suppliers

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Authors: Lina, Arlends Chris, Bagus Mulyawan, Agus B. Dharmawan

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Blood cell analysis plays a significant role in the diagnosis of human health. As an alternative to the traditional technique conducted by laboratory technicians, this paper presents an automatic white blood cell (leukocyte) detection system using Image Stitching and Color Overlapping Windows. The advantage of this method is to present a detection technique of white blood cells that are robust to imperfect shapes of blood cells with various image qualities. The input for this application is images from a microscope-slide translation video. The preprocessing stage is performed by stitching the input images. First, the overlapping parts of the images are determined, then stitching and blending processes of two input images are performed. Next, the Color Overlapping Windows is performed for white blood cell detection which consists of color filtering, window candidate checking, window marking, finds window overlaps, and window cropping processes. Experimental results show that this method could achieve an average of 82.12% detection accuracy of the leukocyte images.

Keywords: color overlapping windows, image stitching, leukocyte detection, white blood cell detection

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Authors: Chia Jui Hsieh, Jyh Cheng Chen, Chih Wei Kuo, Ruei Teng Wang, Woei Chyn Chu

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Compressed sensing (CS) based computed tomographic (CT) reconstruction algorithm utilizes total variation (TV) to transform CT image into sparse domain and minimizes L1-norm of sparse image for reconstruction. Different from the traditional CS based reconstruction which only calculates x-coordinate and y-coordinate TV to transform CT images into sparse domain, we propose a multi-directional TV to transform tomographic image into sparse domain for low-dose reconstruction. Our method considers all possible directions of TV calculations around a pixel, so the sparse transform for CS based reconstruction is more accurate. In 2D CT reconstruction, we use eight-directional TV to transform CT image into sparse domain. Furthermore, we also use 26-directional TV for 3D reconstruction. This multi-directional sparse transform method makes CS based reconstruction algorithm more powerful to reduce noise and increase image quality. To validate and evaluate the performance of this multi-directional sparse transform method, we use both Shepp-Logan phantom and a head phantom as the targets for reconstruction with the corresponding simulated sparse projection data (angular sampling interval is 5 deg and 6 deg, respectively). From the results, the multi-directional TV method can reconstruct images with relatively less artifacts compared with traditional CS based reconstruction algorithm which only calculates x-coordinate and y-coordinate TV. We also choose RMSE, PSNR, UQI to be the parameters for quantitative analysis. From the results of quantitative analysis, no matter which parameter is calculated, the multi-directional TV method, which we proposed, is better.

Keywords: compressed sensing (CS), low-dose CT reconstruction, total variation (TV), multi-directional gradient operator

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Authors: John Toussaint

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Objective: Our society is suffering from an epidemic of body image dissatisfaction, and related disorders appear to be increasing globally for children. There is much to indicate that children's body image and eating attitudes are being affected negatively by socio-cultural factors such as parents, peers and media. Most studies and theories, however, have focused extensively on the daughter-mother relationship. Very few studies have investigated the role of attachment to the father as an important factor in the development of girls’ and women’s attitudes towards themselves and their bodies. Recently, data have shown that the father’s parenting style, as well as the quality of the relationship with him is crucial for the understanding of the development and persistence of body image disorders. This presentation is based on samples of participants with self-defined body image dissatisfaction, and the self-reported measures of their fathers’ parental behaviours, emotional warmth, support, or protection. Attachment theory does offer support in exploring these relationships and it is used in this presentation to assist in understanding the relationship between the father and his daughter in relation to body image and mental health. Clinical implications are also offered in respect to work with body image, eating disorders and relational therapy. Methods: As awareness of the increasing frequency of body image concerns in children grows, so too does the need for a simple, valid and reliable measure of body image. The Children's Body Image Scale (CBIS) designed in Australia, depicts seven male and females figures from which children are to choose their perceived body type and ideal body type. This was compared with a range of international body mass index (BMI) reference standards. These measures together with individual one-on-one interviews were completed by 158 children aged 7-12 years. Results: A high frequency of body image dissatisfaction was indicated in the children's responses. 55% of girls and 41% of boys said they would like to be thinner, and wished for an ideal BMI figure below the 10th percentile. This is an unhealthy and unattainable level of body fatness for the majority of children when considered in relation to the reported secular trend of their increasing average body size. Thin children were generally ranked as best and perceived as kind, happy, academically skilled, and socially successful. Fat children were perceived as unintelligent, lazy, greedy, unpopular, and unable to play physical games. Conclusions: Body image ideals and fat stereotypes are well entrenched among children. There is much to indicate that children's body image and eating attitudes are being affected negatively by sociocultural factors such as parents, peers and media. Teachers and health professionals could promote intervention programs for children involving knowledge and acceptance of genetic influences on body type; the dangerous effects of weight loss dieting; the importance of physical activity and eating healthy; and scepticism and critical analysis of mass media messages.

Keywords: body image, father attachment, mental health, eating disorders

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Authors: Seongsoo Lee

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Motion estimation occupies the heaviest computation in HEVC (high efficiency video coding). Many fast algorithms such as TZS (test zone search) have been proposed to reduce the computation. Still the huge computation of the motion estimation is a critical issue in the implementation of HEVC video codec. In this paper, motion estimator architecture with optimized number of PEs (processing element) is presented by exploiting early termination. It also reduces hardware size by exploiting parallel processing. The presented motion estimator architecture has 8 PEs, and it can efficiently perform TZS with very high utilization of PEs.

Keywords: motion estimation, test zone search, high efficiency video coding, processing element, optimization

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Authors: Lian Liu

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By analyzing the content of the New York Times' China-related energy reports, this study aims to explore the construction of China's national image by the mainstream media in the United States. The study analyzes three aspects of the coverage: topics, reporting tendencies, and countries involved. The results of the study show that economic issues are the main focus of the New York Times’ China-related energy coverage, followed by political issues and environmental issues. Overall, the coverage tendency was mainly negative, but positive coverage was dominated by science and technology issues. In addition, the study found that U.S.-China relations and Sino-Russian relations were important contexts for the construction of China's national image in the NYT's China-related energy coverage. These stories highlight China's interstate interactions with the United States, Japan, and Russia, which serve as important links in the coverage. The findings of this study reveal some characteristics and trends of the U.S. mainstream media's country image of China, which are important for a deeper understanding of the U.S.-China relationship and the media's influence on the construction of the country's image.

Keywords: media coverage, China, content analysis, visualization technology

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Authors: Shantam Gupta

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The objective of this study is to address the critical need for automation in the domestic food processing sector and study its impact. Food is the one of the most basic physiological needs essential for the survival of a living being. Some of them have the capacity to prepare their own food (like most plants) and henceforth are designated as primary food producers; those who depend on these primary food producers for food form the primary consumers’ class (herbivores). Some of the organisms relying on the primary food are the secondary food consumers (carnivores). There is a third class of consumers called tertiary food consumers/apex food consumers that feed on both the primary and secondary food consumers. Humans form an essential part of the apex predators and are generally at the top of the food chain. But still further disintegration of the food habits of the modern human i.e. Homo sapiens, reveals that humans depend on other individuals for preparing their own food. The old notion of eating raw/brute food is long gone and food processing has become very trenchant in lives of modern human. This has led to an increase in dependence on other individuals for ‘processing’ the food before it can be actually consumed by the modern human. This has led to a further shift of humans in the classification of food chain of consumers. The effects of the shifts shall be systematically investigated in this paper. The processing of food has a direct impact on the economy of the individual (consumer). Also most individuals depend on other processing individuals for the preparation of food. This dependency leads to establishment of a vital link of dependency in the food web which when altered can adversely affect the food web and can have dire consequences on the health of the individual. This study investigates the challenges arising out due to this dependency and the impact of food processing on the economy of the individual. A comparison of Industrial food processing and processing at domestic platforms (households and restaurants) has been made to provide an idea about the present scenario of automation in the food processing sector. A lot of time and energy is also consumed while processing food at home for consumption. The high frequency of consumption of meals (greater than 2 times a day) makes it even more laborious. Through the medium of this study a pressing need for development of an automatic cooking machine is proposed with a mission to reduce the inter-dependency & human effort of individuals required for the preparation of food (by automation of the food preparation process) and make them more self-reliant The impact of development of this product has also further been profoundly discussed. Assumption used: The individuals those who process food also consume the food that they produce. (They are also termed as ‘independent’ or ‘self-reliant’ modern human beings.)

Keywords: automation, food processing, impact on economy, processing individual

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Authors: Samaniego Campoverde José Enrique, Rosero Muñoz Jorge Enrique, Luzcando Narea Lorena Elizabeth

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This paper presents a practical and theoretical model for the operation of the Tesla coil using digital signal processing. The research is based on the analysis of ten scientific papers exploring the development and operation of the Tesla coil. Starting from the Testa coil, several modifications were carried out on the Tesla coil, with the aim of amplifying the digital signal by making use of digital signal processing. To achieve this, an amplifier with a transistor and digital filters provided by MATLAB software were used, which were chosen according to the characteristics of the signals in question.

Keywords: tesla coil, digital signal process, equalizer, graphical environment

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Authors: Reza Shakoori

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This paper presents a structural correction of Arabic and Persian strokes using manipulation of their chain codes in order to improve the rate and performance of Persian and Arabic handwritten word recognition systems. It collects pure and effective features to represent a character with one consolidated feature vector and reduces variations in order to decrease the number of training samples and increase the chance of successful classification. Our results also show that how the proposed approaches can simplify classification and consequently recognition by reducing variations and possible noises on the chain code by keeping orientation of characters and their backbone structures.

Keywords: Arabic, chain code normalization, OCR systems, image processing

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Authors: Morteza Mohri Esfahani, Amir S. H. Rozatian, Morteza Mozaffari

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Single phase magnetite nanoparticles and Bi-substituted ones were prepared by mechanochemical processing (MCP). The effects of Bi-substitution on the structural and magnetic properties of the nanoparticles were studied by X-ray Diffraction (XRD) and magnetometry techniques, respectively. The XRD results showed that all samples have spinel phase and by increasing Bi content, the main diffraction peaks were shifted to higher angles, which means the lattice parameter decreases from 0.843 to 0.838 nm and then increases to 0.841 nm. Also, the results revealed that increasing Bi content lead to a decrease in saturation magnetization (Ms) from 74.9 to 48.8 emu/g and an increase in coercivity (Hc) from 96.8 to 137.1 Oe.

Keywords: bi-substituted magnetite nanoparticles, mechanochemical processing, X-ray diffraction, magnetism

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Authors: Ana Carolina Domingues

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This work presents the preliminary results of the above-titled doctoral research. Based on this film and on Middle East authors who discuss films made by women, it has been concluded so far, that it is part of a larger movement, which together with other productions, show the perceptions of the world of these women, who see the world otherwise, for not holding positions of power. These modes of perception revealed from the encounter of women with the cameras, educate viewers to denaturalize the impressions constructed in relation to the Middle East.

Keywords: cinema, image, middle east, women

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Authors: Hamza Nejib, Okba Taouali

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This paper presents two of the most knowing kernel adaptive filtering (KAF) approaches, the kernel least mean squares and the kernel recursive least squares, in order to predict a new output of nonlinear signal processing. Both of these methods implement a nonlinear transfer function using kernel methods in a particular space named reproducing kernel Hilbert space (RKHS) where the model is a linear combination of kernel functions applied to transform the observed data from the input space to a high dimensional feature space of vectors, this idea known as the kernel trick. Then KAF is the developing filters in RKHS. We use two nonlinear signal processing problems, Mackey Glass chaotic time series prediction and nonlinear channel equalization to figure the performance of the approaches presented and finally to result which of them is the adapted one.

Keywords: online prediction, KAF, signal processing, RKHS, Kernel methods, KRLS, KLMS

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Authors: Fan Gao, Lior Pachter

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The primary tool currently used to pre-process 10X Chromium single-cell ATAC-seq data is Cell Ranger, which can take very long to run on standard datasets. To facilitate rapid pre-processing that enables reproducible workflows, we present a suite of tools called scATAK for pre-processing single-cell ATAC-seq data that is 15 to 18 times faster than Cell Ranger on mouse and human samples. Our tool can also calculate chromatin interaction potential matrices, and generate open chromatin signal and interaction traces for cell groups. We use scATAK tool to explore the chromatin regulatory landscape of a healthy adult human brain and unveil cell-type specific features, and show that it provides a convenient and computational efficient approach for pre-processing single-cell ATAC-seq data.

Keywords: single-cell, ATAC-seq, bioinformatics, open chromatin landscape, chromatin interactome

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Authors: Tengku Ezni Balqiah, Fanny Martdianty, Rifelly Dewi Astuti, Mutia Nurazizah Rachmawati

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The Corona Disease 2019 (COVID-19) pandemic has changed the world considerably and has disrupted businesses and people’s lives globally. In response to the pandemic, businesses have seen increased demand for corporate social responsibility (CSR). Businesses can increase their investments in CSR initiatives during the pandemic through various actions. This study examines how the various motives of philanthropy CSR influence perceived quality of life, company image, and advocacy. This study employed surveys of 719 respondents from seven provinces in Indonesia that had the highest number of COVID-19 cases in the country. A structural equation model was used to test the hypothesis. The results showed that value and strategic motives positively influenced the perceived quality of life and corporate image, while the egoistic motive was negatively associated with both the perceived quality of life and the image of the company. The study also suggested that advocacy was strongly related to the perceived quality of life instead of a corporate image. The results indicate that, during a pandemic, both public- (i.e. value) and firm-serving (i.e. strategic) motives can have the same impact as long as people perceive that the businesses are sincere.

Keywords: advocacy, COVID 19, CSR motive, Indonesia, quality of life

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Authors: Katri K. Cornelissen, Lise Gulli Brokjob, Kristofor McCarty, Jiri Gumancik, Martin J. Tovee, Piers L. Cornelissen

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Recent research has shown that body size estimation of healthy women is driven by independent attitudinal and perceptual components. The attitudinal component represents psychological concerns about body, coupled to low self-esteem and a tendency towards depressive symptomatology, leading to over-estimation of body size, independent of the Body Mass Index (BMI) someone actually has. The perceptual component is a normal bias known as contraction bias, which, for bodies is dependent on actual BMI. Women with a BMI less than the population norm tend to overestimate their size, while women with a BMI greater than the population norm tend to underestimate their size. Women whose BMI is close to the population mean are most accurate. This is indexed by a regression of estimated BMI on actual BMI with a slope less than one. It is well established that body dissatisfaction, i.e. an attitudinal distortion, leads to body size overestimation in eating disordered individuals. However, debate persists as to whether women with eating disorders may also suffer a perceptual body distortion. Therefore, the current study was set to ask whether women with eating disorders exhibit the normal contraction bias when they estimate their own body size. If they do not, this would suggest differences in the way that women with eating disorders process the perceptual aspects of body shape and size in comparison to healthy controls. 100 healthy controls and 33 women with a history of eating disorders were recruited. Critically, it was ensured that both groups of participants represented comparable and adequate ranges of actual BMI (e.g. ~18 to ~40). Of those with eating disorders, 19 had a history of anorexia nervosa, 6 bulimia nervosa, and 8 OSFED. 87.5% of the women with a history of eating disorders self-reported that they were either recovered or recovering, and 89.7% of them self-reported that they had had one or more instances of relapse. The mean time lapsed since first diagnosis was 5 years and on average participants had experienced two relapses. Participants were asked to fill number of psychometric measures (EDE-Q, BSQ, RSE, BDI) to establish the attitudinal component of their body image as well as their tendency to internalize socio-cultural body ideals. Additionally, participants completed a method of adjustment psychophysical task, using photorealistic avatars calibrated for BMI, in order to provide an estimate of their own body size and shape. The data from the healthy controls replicate previous findings, revealing independent contributions to body size estimation from both attitudinal and perceptual (i.e. contraction bias) body image components, as described above. For the eating disorder group, once the adequacy of their actual BMI ranges was established, a regression of estimated BMI on actual BMI had a slope greater than 1, significantly different to that from controls. This suggests that (some) eating disordered individuals process the perceptual aspects of body image differently from healthy controls. It therefore is necessary to develop interventions which are specific to the perceptual processing of body shape and size for the management of (some) individuals with eating disorders.

Keywords: body image distortion, perception, recovery, relapse, BMI, eating disorders

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Authors: Adel Edwar Waheeb Louka

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Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deeplearning, image processing, machine learningSarapin, intraarticular, chronic knee pain, osteoarthritisFNS, trauma, hip, neck femur fracture, minimally invasive surgery

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Authors: Jay Patel

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This Research is about investigating the ‘image’ of the city, and asks whether this ‘image’ holds any significance that can be changed. Kevin Lynch in the book ‘The image of the city’ develops a framework that breaks down the city’s image into five physical elements. These elements (Paths, Edge, Nodes, Districts, and Landmarks), according to Lynch assess the legibility of the urbanscapes, that emerged from his perception-based study in 3 different cities (New Jersey, Los Angeles, and Boston) in the USA. The aim of this research is to investigate whether Lynch’s framework can be applied within an Indian context or not. If so, what are the possibilities and whether the imageability of Indian cities can be depicted through the Lynch’s physical elements or it demands an extension to the framework by either adding or subtracting a physical attribute. For this research project, the walled city of Jaipur was selected, as it is considered one of the futuristic designed cities of all time in India. The other significant reason for choosing Jaipur was that it is a historically planned city with solid historical, touristic and local importance; allowing an opportunity to understand the application of Lynch's elements to the city's image. In other words, it provides an opportunity to examine how the disadvantages of a city's implicit programme (its relics of bygone eras) can be converted into assets by improving the imageability of the city. To obtain data, a structured semi-open ended interview method was chosen. The reason for selecting this method explicitly was to gain qualitative data from the users rather than collecting quantitative data from closed-ended questions. This allowed in-depth understanding and applicability of Kevin Lynch’s framework while assessing what needs to be added. The interviews were conducted in Jaipur that yielded varied inferences that were different from the expected learning outcomes, highlighting the need for extension on Lynch’s physical elements to achieve city’s image. Whilst analyzing the data, there were few attributes found that defined the image of Jaipur. These were categorized into two: a Physical aspect (streets and arcade entities, natural features, temples and temporary/ informal activities) and Associational aspects (History, Culture and Tradition, Medium of help in wayfinding, and intangible aspects).

Keywords: imageability, Kevin Lynch, people’s perception, assessment, associational aspects, physical aspects

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Authors: Cholpassorn Sitthiwarongchai, Chutikarn Sriviboon

Abstract:

The two primary objectives of this research were (1) to examine the current knowledge and actual circumstance of agricultural workers about mangosteen product processing; and (2) to analyze and evaluate ways to develop capacity of mangosteen product processing. The population of this study was 15,125 people who work in the agricultural sector, in this context, mangosteen production, in the eastern part of Thailand that included Chantaburi Province, Rayong Province, Trad Province and Pracheenburi Province. The sample size based on Yamane’s calculation with 95% reliability was therefore 392 samples. Mixed method was employed included questionnaire and focus group discussion with Connoisseurship Model used in order to collect quantitative and qualitative data. Key informants were used in the focus group including agricultural business owners, academic people in agro food processing, local academics, local community development staff, OTOP subcommittee, and representatives of agro processing industry professional organizations. The study found that the majority of the respondents agreed with a high level (in five-rating scale) towards most of variables of knowledge management in agro food processing. The result of the current knowledge and actual circumstance of agricultural human resource in an arena of mangosteen product processing revealed that mostly, the respondents agreed at a high level to establish 7 variables. The guideline to developing the body of knowledge in order to enhance the capacity of the agricultural workers in mangosteen product processing was delivered in the focus group discussion. The discussion finally contributed to an idea to produce manuals for mangosteen product processing methods, with 4 products chosen: (1) mangosteen soap, (2) mangosteen juice, (3) mangosteen toffee, and (4) mangosteen preserves or jam.

Keywords: capacity enhancement, agricultural workers, mangosteen product processing, marketing management

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Authors: Salah Abdul Hameed Saleh, Ghada Hasan

Abstract:

The aim of this work is to produce an empirical model for the determination of particulate matter (PM10) concentration in the atmosphere using visible bands of Landsat 8 OLI satellite image over Kirkuk city- IRAQ. The suggested algorithm is established on the aerosol optical reflectance model. The reflectance model is a function of the optical properties of the atmosphere, which can be related to its concentrations. The concentration of PM10 measurements was collected using Particle Mass Profiler and Counter in a Single Handheld Unit (Aerocet 531) meter simultaneously by the Landsat 8 OLI satellite image date. The PM10 measurement locations were defined by a handheld global positioning system (GPS). The obtained reflectance values for visible bands (Coastal aerosol, Blue, Green and blue bands) of landsat 8 OLI image were correlated with in-suite measured PM10. The feasibility of the proposed algorithms was investigated based on the correlation coefficient (R) and root-mean-square error (RMSE) compared with the PM10 ground measurement data. A choice of our proposed multispectral model was founded on the highest value correlation coefficient (R) and lowest value of the root mean square error (RMSE) with PM10 ground data. The outcomes of this research showed that visible bands of Landsat 8 OLI were capable of calculating PM10 concentration with an acceptable level of accuracy.

Keywords: air pollution, PM10 concentration, Lansat8 OLI image, reflectance, multispectral algorithms, Kirkuk area

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Authors: Jim Shih-Chiao Chin, Yu Ting Yeh, Shui Lien Chen, Yi-Fen Tsai

Abstract:

his study is taking Adidas Company as the object, explored the brand awareness directly or indirectly affects brand affect and word of mouth. First, explored the brand awareness on category fit and image fit, and examined the influence of category fit and image fit on extension attitude. This study then designates the effect of extension attitude on brand affect and word-of-mouth. The relationship of brand awareness on brand affect and word-of-mouth was also explored. The study participants are people who have purchased Adidas extension products. A total of 700 valid questionnaires were collected and statistical software AMOS 20.0 was used to examine the research hypotheses by using structural equation modeling (SEM). Finally, theoretical implications and research directions are provided for future studies.

Keywords: brand extension, brand awareness, product category fit, brand image fit, brand affect, word-of-mouth (WOM)

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Authors: Sameh Abaza, Mohamed Ibrahim, Tarek Mahmoud

Abstract:

Due to the development in the digital image processing, its wide use in many applications such as medical, security, and others, the need for more accurate techniques that are reliable, fast and robust is vehemently demanded. In the field of security, in particular, speed is of the essence. In this paper, a pattern recognition technique that is based on the use of Hidden Markov Model (HMM), K-means and the Sobel operator method is developed. The proposed technique is proved to be fast with respect to some other techniques that are investigated for comparison. Moreover, it shows its capability of recognizing the normal face (center part) as well as face boundary.

Keywords: HMM, K-Means, Sobel, accuracy, face recognition

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Authors: Yonggu Jang, Jisong Ryu, Woosik Lee

Abstract:

The study aims to address the limitations of existing underground facility exploration equipment in terms of exploration depth range, relative depth measurement, data processing time, and human-centered ground penetrating radar image interpretation. The study proposed the use of 3D absolute positioning technology to develop a precision underground facility exploration system. The aim of this study is to establish a precise exploration system for underground facilities based on 3D absolute positioning technology, which can accurately survey up to a depth of 5m and measure the 3D absolute location of precise underground facilities. The study developed software and hardware technologies to build the precision exploration system. The software technologies developed include absolute positioning technology, ground surface location synchronization technology of GPR exploration equipment, GPR exploration image AI interpretation technology, and integrated underground space map-based composite data processing technology. The hardware systems developed include a vehicle-type exploration system and a cart-type exploration system. The data was collected using the developed exploration system, which employs 3D absolute positioning technology. The GPR exploration images were analyzed using AI technology, and the three-dimensional location information of the explored precise underground facilities was compared to the integrated underground space map. The study successfully developed a precision underground facility exploration system based on 3D absolute positioning technology. The developed exploration system can accurately survey up to a depth of 5m and measure the 3D absolute location of precise underground facilities. The system comprises software technologies that build a 3D precise DEM, synchronize the GPR sensor's ground surface 3D location coordinates, automatically analyze and detect underground facility information in GPR exploration images and improve accuracy through comparative analysis of the three-dimensional location information, and hardware systems, including a vehicle-type exploration system and a cart-type exploration system. The study's findings and technological advancements are essential for underground safety management in Korea. The proposed precision exploration system significantly contributes to establishing precise location information of underground facility information, which is crucial for underground safety management and improves the accuracy and efficiency of exploration. The study addressed the limitations of existing equipment in exploring underground facilities, proposed 3D absolute positioning technology-based precision exploration system, developed software and hardware systems for the exploration system, and contributed to underground safety management by providing precise location information. The developed precision underground facility exploration system based on 3D absolute positioning technology has the potential to provide accurate and efficient exploration of underground facilities up to a depth of 5m. The system's technological advancements contribute to the establishment of precise location information of underground facility information, which is essential for underground safety management in Korea.

Keywords: 3D absolute positioning, AI interpretation of GPR exploration images, complex data processing, integrated underground space maps, precision exploration system for underground facilities

Procedia PDF Downloads 62