Hasil untuk "Photography"

Martina Tomić, Romano Vrabec, Toma Babić et al.

<b>Background</b>/<b>Objectives:</b> We aimed to evaluate the diagnostic accuracy of the MONA.health artificial intelligence (AI) software (Version 1.0.0; MONA.health, Leuven, Belgium) and compare its advantages in screening for diabetic retinopathy (DR) and diabetic macular edema (DME) with standard fundus photography. <b>Methods:</b> This cross-sectional, real-life instrument validation study was conducted at the Vuk Vrhovac University Clinic in Zagreb during routine DR screening and included 296 patients (592 eyes) with diabetes. Following standard fundus photography using a 45° Zeiss VISUCAM NM/FA camera (Carl Zeiss Meditec AG, Jena, Germany), each patient also underwent imaging with an automated portable retinal camera (NFC-600, Crystalvue Ophthalmic Instruments, Taoyuan City, Taiwan). Two retina specialists independently graded images from the standard camera, while images from the NFC-600 were analyzed using the MONA.health AI software. <b>Results:</b> Among the 592 eyes, human grading identified 81 with any DR, including 17 with mild NPDR, 64 with referable DR (moderate/severe NPDR or PDR), and 13 with DME. The MONA.health AI software identified 65 eyes with referable DR and 19 with DME. For MONA DR screening compared to the standard fundus camera, the area under the curve, sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, negative likelihood ratio, kappa agreement, diagnostic odds ratio, and diagnostic effectiveness were 99.74%, 100%, 99.81%, 99.33%, 100%, 528.00, 0.00, 0.99, infinity, and 99.85%, respectively. For MONA DME screening, these metrics were 97.97%, 100%, 98.95%, 85.93%, 100%, 95.67, 0.00, 0.81, infinity, and 99.02%, respectively. The MONA AI screening process required 1 day of training and approximately 5 min for image capture and analysis, compared to 7 days of training and 13 min for image acquisition and grading with the standard method. <b>Conclusions:</b> These findings demonstrate that the MONA.health AI software matches the accuracy of standard fundus photography for screening and early detection of referable DR and DME, while offering a faster, simpler, and more user-friendly workflow that significantly reduces the time to obtain screening results.

Ioannis Antonakos, Matina Patsioti, Maria-Eleni Zachou et al.

The purpose of this study is to determine the typical diagnostic reference levels (DRLs) of radiation exposure values for chest radiographs in neonates (<1 kg) in mobile imaging at a University Hospital in Greece and compare these values with the existing DRL values from the literature. Patient and dosimetry data, including age, sex, weight, tube voltage (kV), tube current (mA), exposure time (s), exposure index of a digital detector (S), and dose area product (DAP) were obtained from a total of 80 chest radiography examinations performed on neonates (<1 kg and <30 days old). All examinations were performed in a single X-ray system, and all data (demographic and dosimetry data) were collected from the PACS of the hospital. Typical radiation exposure values were determined as the median value of DAP and ESD distribution. Afterward, these typical values were compared with DRL values from other countries. Three radiologists reviewed the images to evaluate image quality for dose optimization in neonatal chest radiography. From all examinations, the mean value and standard deviation of DAP was 0.13 ± 0.11 dGy·cm² (range: 0.01–0.46 dGy·cm²), and ESD was measured at 11.55 ± 4.96 μGy (range: 4.01–30.4 μGy). The typical values in terms of DAP and ESD were estimated to be 0.08 dGy·cm² and 9.87 μGy, respectively. The results show that the DAP value decreases as the exposure index increases. This study’s typical values were lower than the DRLs reported in the literature because our population had lower weight and age. From the subjective evaluation of image quality, it was revealed that the vast majority of radiographs (over 80%) met the criteria for being diagnostic as they received an excellent rating in terms of noise levels, contrast, and sharpness. This study contributes to the recording of typical dose values in a sensitive and rare category of patients (neonates weighing <1 kg) as well as information on the image quality of chest X-rays that were performed in this group.

Claudio Ventura, Marco Fogante, Elisabetta Marconi et al.

Contrast-enhanced mammography (CEM) combines morphological and functional imaging, enhancing breast cancer (BC) diagnosis. This study investigates the relationship between CEM morphodynamic features and histopathological characteristics of BC. In this prospective study, 50 female patients (mean age: 57.2 ± 13.7 years) with BI-RADS 4–5 lesions underwent CEM followed by surgical excision between December 2022 and May 2024. Low-energy and recombined CEM images were analyzed for breast composition, lesion characteristics, and enhancement patterns, while histopathological evaluation included tumor size, histotype, grade, lymphovascular invasion, and immunophenotype. Spearman rank correlation and multivariable regression analysis were used to evaluate the relationship between CEM findings and histopathological characteristics. Tumor size on CEM strongly correlated with histopathological tumor size (ρ = 0.788, <i>p</i> < 0.001) and was associated with high-grade lesions (<i>p</i> = 0.017). Non-circumscribed margins were linked to a Luminal-B subtype (<i>p</i> = 0.001), while high lesion conspicuity was associated with Luminal-B and triple-negative BC (<i>p</i> = 0.001) and correlated with larger tumors (ρ = 0.517, <i>p</i> < 0.001). Background parenchymal enhancement was negatively correlated with age (ρ = −0.286, <i>p</i> = 0.049). CEM provides critical insights into BC, demonstrating significant relationship between imaging features and histopathological characteristics. These findings highlight CEM’s potential as a reliable tool for tumor size estimation, subtype characterization, and prognostic assessment, suggesting its role as an alternative to MRI, particularly for patients with contraindications.

M. Rautiainen, A. Hovi, D. Schraik et al.

<p>Radiative transfer models of vegetation play a crucial role in the development of remote sensing methods by providing a theoretical framework to explain how electromagnetic radiation interacts with vegetation in different spectral regions. A limiting factor in model development has been the lack of sufficiently detailed ground reference data on both the structural and spectral characteristics of forests needed for testing and validating the models. In this data description paper, we present a dataset on the structural and spectral properties of 58 stands in temperate, hemiboreal, and boreal European forests. It is specifically designed for the development and validation of radiative transfer models for forests but can also be utilized in other remote sensing studies. It comprises detailed data on forest structure based on forest inventory measurements, terrestrial and airborne laser scanning, and digital hemispherical photography. Furthermore, the data include spectral properties of the same forests at multiple scales: reflectance spectra of tree leaves and needles (based on laboratory measurements), the forest floor (based on in situ measurements), and entire stands (based on airborne measurements), as well as transmittance spectra of tree leaves and needles and entire tree canopies (based on laboratory and in situ measurements, respectively). We anticipate that these data will have wide use in testing and validating radiative transfer models for forests and in the development of remote sensing methods for vegetation. The data can be accessed at Hovi et al. (2024a, <a href="https://doi.org/10.23729/9a8d90cd-73e2-438d-9230-94e10e61adc9">https://doi.org/10.23729/9a8d90cd-73e2-438d-9230-94e10e61adc9</a>) (for laboratory and field data) and Hovi et al. (2024b, <a href="https://doi.org/10.23729/c6da63dd-f527-4ec9-8401-57c14f77d19f">https://doi.org/10.23729/c6da63dd-f527-4ec9-8401-57c14f77d19f</a>) (for airborne data).</p>

YAN Haonan, LYU Fu, FENG Yong'an

Under natural lighting conditions, UAV (unmanned aerial vehicle) aerial images contain low-light images, which affect the accuracy of target detection, and detection tasks based on aerial images often have high real-time requirements. To address the above problems, a feature-level adaptive enhancement target detection algorithm for UAV aerial images is proposed. Firstly, an improved Laplace operator is fused with the IAT (illumination adaptive transformer) image enhancement network to enhance the edge features of the target and improve the target detection ability. Secondly, a two-branch structure is used to learn the normal image and the enhanced image in parallel, and the learnt features are fused in an adaptive selection manner to construct a BLENet (bad lighting enhancement net) feature-level adaptive enhancement network, which can adapt to the illumination and enhance the information of the image automatically. Then, the deformable convolutional FS-DC module based on frequency domain separation and the FS-C2F module with parameter sharing are designed so as to reduce the number of model parameters and computational redundancy while enhancing the ability of capturing high-frequency information. Finally, the regression loss function Wise-IoU is improved so that the model further focuses on the medium- and high-quality anchor frames, thus reducing the boundary regression loss and improving the localization accuracy. Experimental results on the publicly available dataset visDrone2023 show that compared with the baseline model, the final model improves the mAP@0.50 by 2.3 percentage points while keeping the FPS at 99 frames per second, which makes it suitable for UAV aerial photography real-time inspection and monitoring tasks under the environment of varying light in the open air.

Fan Xu, Chuibin Chen, Zhigao Shang et al.

Abstract Existing deep learning methods cannot achieve satisfactory ship license plate (SLP) recognition due to the harsh marine environment, such as foggy weather, unstable ship state and small targets. Therefore, a convolutional recurrent neural network (CRNN)‐based method is proposed for accurate SLP image recognition. Overall, the suggested method improves a CRNN recognition model by SLP image enhancement and data augmentation. The SLP image enhancement employs dark channel prior and Hough transform line detector to address the fog/blurriness and tilt issues existing in SLP images. As separate and joint operations, the two enhancements contribute to data augmentation for CRNN recognition. Preprocessing algorithms, including adaptive histogram equalization and image edge padding, are used to improve and unify the enlarged dataset for augmenting the CRNN model. As a final step, correction of the CRNN recognition results is made according to the character rule of SLPs, using an edit‐distance algorithm to match against a pre‐established SLP dictionary. A variety of real SLP images were collected to build an SLP image dataset for verification. The experimental results indicate that our method can reach an SLP recognition accuracy of ∼93%, which is significantly superior to other text‐based deep learning methods.

Sonia Ríos-Moyano

El trabajo de investigación que se presenta es un acercamiento a tres grandes recursos gráficos de la sociedad post digital; hablamos de la fotografía, la ilustración y la tipografía. Entre los objetivos principales se muestra un recorrido histórico para entender la longevavida de estos medios, su pervivencia y continua adaptación a los tiempos. La enumeración de algunos de los grandes hitos nos sirve para explicar su continua adaptación a los medios, a la tecnología y a la sociedad en general en un mundo globalizado donde la imagen tiene un poder persuasivo exacerbado. Sin duda, las imágenes, la publicidad y los anuncios que se han ido generando en momentos determinados de la historia actual son muy ilustrativos del protagonismo de estos en el desarrollo de grandes acontecimientos, quedando pues, con el paso de los años, una imagen residual vinculada al hecho en sí. Mostraremos algunos ejemplos concretos que han superado la función inicial para la que fue creada la imagen, la ilustración o la tipografía. Como conclusión, se insiste en la relevancia de estos recursos en la cultura visual actual hasta la era post digital, explicando cómo se insertan y conviven en los soportes y medios de comunicación de nuestro presente inmediato. Abstract The research work presented here is an approach to three major graphic resources of the post-digital society: photography, illustration, and typography. The main objectives include a historical journey to understand the long life of these media, their survival and continuous adaptation to the times. The enumeration of some of the major milestones explains their continuous adaptation to the media, technology, and society in general in a globalized world where the image has an exacerbated persuasive power. Undoubtedly, the images, publicity, and advertisements that have been generated at specific moments in history today are very illustrative of the leading role they have played in the development of major events, leaving, over the years, a residual image linked to the event itself. We will show some specific examples that have gone beyond the initial function for which the image, illustration, or typography was created. In conclusion, we will insist on the relevance of these resources in today's visual culture up to the post-digital era, explaining how they are inserted and coexist in the supports and media of our immediate present.

Fang Liu, Xing-Hui Yu, Yu-Chuan Wang et al.

AIM: To explore changes in the optic disc and peripapillary atrophy (PPA) in school-age children with ametropia using color fundus photography combined with artificial intelligence (AI) technology. METHODS: Based on the retrospective case-controlled study, 226 eyes of 113 children aged aged 6–12y were enrolled from October 2021 to May 2022. According to the results of spherical equivalent (SE), the children were divided into four groups: low myopia group (66 eyes), moderate myopia group (60 eyes), high myopia group (50 eyes) and emmetropia control group (50 eyes). All subjects underwent un-aided visual acuity, dilated pupil optometry, best-corrected visual acuity (BCVA), intraocular pressure, ocular axis measurement and color fundus photography. RESULTS: The width of PPA, horizontal diameter ratio of PPA to the optic disc and area ratio of PPA to the optic disc were significantly different among the four groups (P<0.05). The width of the nasal and temporal neuroretinal rim, the roundness of the optic disc, the height of PPA, the vertical diameter ratio of PPA to the optic disc, and the average density of PPA in the high myopia group were significantly different compared with the other three groups (P<0.05). There were strong negative correlations between SE and area ratio of PPA to the optic disc (r=-0.812, P<0.001) and strong positive correlation between axial length (AL) and area ratio of PPA to the optic disc (r=0.736, P<0.001). CONCLUSION: In school-age children with high myopia, the nasal and temporal neuroretinal rims are narrowed and even lost, which have high sensitivity. The area ratio of the PPA to the optic disc could be used as an early predictor of myopia progression, which is of great significance for the development prevention and management of myopia.

João Nuno Centeno Raimundo, João Pedro Pereira Fontes, Luís Gonzaga Mendes Magalhães et al.

Replacing lung cancer as the most commonly diagnosed cancer globally, breast cancer (BC) today accounts for 1 in 8 cancer diagnoses and a total of 2.3 million new cases in both sexes combined. An estimated 685,000 women died from BC in 2020, corresponding to 16% or 1 in every 6 cancer deaths in women. BC represents a quarter of a total of cancer cases in females and by far the most commonly diagnosed cancer in women in 2020. However, when detected in the early stages of the disease, treatment methods have proven to be very effective in increasing life expectancy and, in many cases, patients fully recover. Several medical imaging modalities, such as X-rays Mammography (MG), Ultrasound (US), Computer Tomography (CT), Magnetic Resonance Imaging (MRI), and Digital Tomosynthesis (DT) have been explored to support radiologists/physicians in clinical decision-making workflows for the detection and diagnosis of BC. In this work, we propose a novel Faster R-CNN-based framework to automate the detection of BC pathological Lesions in MRI. As a main contribution, we have developed and experimentally (statistically) validated an innovative method improving the “breast MRI preprocessing phase” to select the patient’s slices (images) and associated bounding boxes representing pathological lesions. In this way, it is possible to create a more robust training (benchmarking) dataset to feed Deep Learning (DL) models, reducing the computation time and the dimension of the dataset, and more importantly, to identify with high accuracy the specific regions (bounding boxes) for each of the patient’s images, in which a possible pathological lesion (tumor) has been identified. As a result, in an experimental setting using a fully annotated dataset (released to the public domain) comprising a total of 922 MRI-based BC patient cases, we have achieved, as the most accurate trained model, an accuracy rate of 97.83%, and subsequently, applying a ten-fold cross-validation method, a mean accuracy on the trained models of 94.46% and an associated standard deviation of 2.43%.

Baoping Meng, Yuzhuo Zhang, Zhigui Yang et al.

Grassland classification is crucial for grassland management. One commonly used method utilizes remote sensing vegetation indices (VIs) to map grassland classes at various scales. However, most grassland classifications were conducted as case studies in a small area due to lack of field data sources. At a small scale, classification is reliable; however, great uncertainty emerges when extended to other areas. In this study, large amounts of field observations (more than 30,000 aerial photos) were obtained using unmanned aerial vehicle photography in Inner Mongolia, China, during the peak period of grassland growth in 2018 and 2019. Then, four machine learning classification algorithms were constructed based on characteristic indices of MODIS NDVI in the growing season to map grassland classes of Inner Mongolia. Finally, the spatial distribution and temporal variation of temperate grassland classes were analyzed. Results showed that: (1) Among all characteristic indices, the maximum, average, and sum of MODIS NDVI from July to September during 2015 to 2019 greatly affected grassland classification. (2) The random forest method exhibited the best performance with overall accuracy and kappa coefficient being 72.17% and 0.62, respectively. (3) Compared with the grassland class mapped in the 1980s, 30.98% of grassland classes have been transformed. Our study provides a technological basis for effective and accurate classification of the temperate steppe class and a theoretical foundation for sustainable development and restoration of the temperate steppe ecosystem.

Su Zhang, Hays A. Barrett, Shirley V. Baros et al.

As one of the earliest forms of remote sensing, aerial photography has been regarded as an important part of the mapmaking process. Aerial photos, especially historical aerial photos, provide significant amount of valuable information for many applications and fields. However, due to limited funding support, most historical aerial photos have not been digitized and georeferenced yet, which substantially limits their utility for today’s computer-based image processing and analysis. Traditionally, historical aerial photos are georeferenced with desktop GIS software applications. However, this method is expensive, time-consuming, and labor-intensive. To address these limitations, this research developed a custom-built online georeferencing tool to enable georeferencing digitized historical aerial photos in a web environment, which is able to georeference historical aerial photos in a rapid and cost-effective manner. To evaluate the georeferencing performance, a set of 50 historical aerial photos were georeferenced with not only the developed online georeferencing tool but also two commercial desktop software programs. Research results revealed the custom-built online georeferencing tool provided the highest degree of accuracy while maximizing its accessibility.

Yongzhao Xu, Matheus A. dos Santos, Luís Fabrício F. Souza et al.

Abstract The use of computational techniques in the processing of histopathological images allows the study of the structural organization of tissues and their changes through diseases. This study aims to develop a tool for classifying histopathological images from breast lesions in the benign and malignant classes through magnification scales by an innovative way of using transfer learning techniques combined with machine learning methods and deep learning. The BreakHis dataset was used in the experiments, consisting of histopathological images of breast cancer with different tumor enlargement scales classified as Malignant or Benign. In this study, various combinations of Extractor‐Classifiers were performed, thus seeking to compare the best model. Among the results achieved, the best Extractor‐Classifier set formed was CNN DenseNet201, acting as an extractor, with the SVM RBF classifier, obtaining accuracy of 95.39% and precision of 95.43% for the 200X magnification factor. Different models were generated, compared to each other, and validated based on methods in the literature to validate the experiments, thus showing the effectiveness of the proposed model. The proposed method obtained satisfactory results, reaching results in the state‐of‐the‐art for the multi‐classification of subclasses from the different scale factors found in the BreakHis dataset and obtaining better results in the classification time.

Paolo Albertini, Matteo Tremaroli, Francesca Cremonini et al.

Objective: To evaluate the accuracy of three different digital bracket positioning systems, comparing vertical, mesiodistal and buccolingual accuracy. Material and Methods:  The same case was sent to Orapix, Insignia, and Orthocad systems and the brackets were bonded to the malocclusion models. Damon 3 MX brackets were used with all systems and the brackets were bonded to the models with the same bonding protocol and materials. The comparison of the position of each single bracket was made with digital photography, and ImageJ software was used to find the length in pixels and then convert it to hundredths of a mm for vertical, mesiodistal and buccolingual displacement, compared to the setup. Results: Insignia System reported the average higher vertical displacement (0.28 mm), compared with the other two appliances (0.22-0.23 mm), and showed the lowest average displacement for the mesiodistal and buccolingual positioning (0.14 and 0.07 mm, respectively). However, these slight bracket positioning variations between these bonding systems were not statistically different (p>0.05). Conclusion:  The three systems analyzed were shown to be accurate in positioning the brackets, and none of them was statistically better.

Ferreri W., Codebò M., Bubbi B.

In 1981 the Voyager 1 probe photographed – and later the Cassini probe confirmed – a hexagonal vortex on Saturn's North pole. This cloud features extends for almost 30,000 km keeping its shape unchanged as it rotates with the planet. But, since we see it very foreshortened, it appears to us with the greater extension of 4" and the smaller one of 1.3": this makes it virtually visible from Earth with telescopes. And in fact, after the first images of Voyager 1, many amateur astronomers managed to photograph it even with modest instruments of a few tens of centimeters in diameter, but using digital photography techniques. We therefore wondered if the hexagon had been seen by astronomers of the past mainly using their professional telescopes. Our research gave positive results: E.E. Barnard (with the Yerkes' refractor) and E.M. Antoniadi (earlier with Juvisy's and later with Meudon's refractors) pictured it since the end of the 19th century, but they never mentioned it in their writings, probably because it was at the limit of visibility and it was impossible to explain the hexagon with the knowledge of that time. These pictures prove that the hexagon has been present and active for at least 124 years on the North pole of Saturn, similar to the (longer-lived) red spot of Jupiter.

Jordyn Feingold, Laurie Keefer, Ksenia Gorbenko et al.

OBJECTIVES/GOALS: Inflammatory bowel diseases (IBD) are most often diagnosed in adolescence and young adulthood, affecting 10 in 100,000 pediatric patients in the US and Canada. Adolescents with IBD are vulnerable to poorer outcomes and higher health costs, partially attributable to disruptions in the continuity of care in the transition from pediatric to adult care settings. There is currently no consensus among providers about the timing of initiation and completion of the transition process for adolescents and young adults with IBD, and access to structured pediatric transition readiness programs are lacking, with a paucity of research to evaluate relevant clinical outcomes in such existing programs. While prior studies have primarily examined barriers and facilitators of successful transitions from the provider perspective, only few studies have systematically examined such factors from the patient and caregiver perspective. We wish to better understand the experience of living with IBD for adolescents and young adults, as well as their parents, to understand barriers and facilitators of successful transitions in care. Ultimately, we wish to articulate best practices in this domain in order to create and evaluate a transitions program for patients and parents at the Mount Sinai IBD Center. METHODS/STUDY POPULATION: We are recruiting 15-25 patient-parent dyads to complete our study. At recruitment, we collect baseline quantitative metrics from patients pertaining to demographics, disease characteristics, transition-readiness, self-efficacy, resilience, disease-specific health knowledge, and health literacy. From parents, we collect demographic information, concordance metrics (e.g. how parents perceive their children’s resilience, self-efficacy), parenting style questionnaires, and others. These data are used to understand the characteristics of the young adults and parents within our sample to ensure that the results of our study will be generalizable to a diverse range of patients and families. We then train our patient-parent dyads in Photovoice, the primary method of our study. Photovoice is a community based participatory research (CBPR) methodology used in health education and other fields. The method employs photography for participants to capture their experiences living with IBD, or being a parent to a child with IBD. We then interview all participants about the photos using a standard script employed in Photovoice. All surveys are transcribed and coded for thematic analysis. Based on our findings, we hope to determine phenotypes of patient-parent dyads who are likely undergo successful transitions as well as those at higher risk, understand competencies necessary for successful transitions, and create a comprehensive transitions program for the IBD Center that can be applied with all patients undergoing transitions from pediatric to adult GI care. RESULTS/ANTICIPATED RESULTS: We currently have 26 patients and 25 parents (1 pair of siblings) aged 14-25 enrolled in the study. We hypothesize that adolescents with higher baseline resilience, efficacy, disease-specific health knowledge, and less active disease will have more successful transitions than adolescents with lower scores on these metrics. Similarly, we predict that adolescents with lower baseline resilience, self-efficacy, disease-specific health knowledge and more active disease will be ideal candidates for a more robust transition-readiness program. Further, we hypothesize that children of more authoritarian parents will be less prepared for transition than those with assertive parents. We are currently in the process of conducting patient/parent interviews, and have collected 6 interviews thus far. We will begin the qualitative coding process once we have four interviews from each cohort. Themes emerging thus far involve: medication management, psychiatric co-morbidity, social support, direct communication with doctors, the role of surgery, school absences, travel, and others. DISCUSSION/SIGNIFICANCE OF IMPACT: Transition-readiness is defined as a series of skills in the realms of knowledge, information gathering, self-management, and decision-making that must be mastered by a patient in preparation for a healthcare transition, such as that from pediatric to adult IBD care. It has been shown that many clinicians who rely on subjective measures such as perceived health literacy overestimate transition readiness in their IBD patients. Many pediatric gastroenterologists who use more objective measures rely on a validated self-report questionnaire, the Transition Readiness Assessment Questionnaire (TRAQ) to assess readiness for transition and to facilitate discussions around the skills necessary to transition, including appointment keeping, tracking health issues, managing medications, talking with providers, and managing daily activities. However, the TRAQ has been shown to be limited in its ability to predict transition readiness independently of age, and ignores both provider and family perspectives. Given the critical role of parents in medical decision making, and the differential emphasis of the caregiver role in pediatric versus adult IBD care paradigms, it is vitally important to identify barriers to transition as well as differences in perspectives between adolescents living with IBD and their parents. Our study is the first to employ Photovoice, a method that ‘gives a voice to the voiceless’ in the gastroenterology space, in order to understand the needs that adolescents and young adults themselves perceive as critical in promoting transition-readiness. We include parents in this inquiry in order to understand how parental perceptions of their children’s transition-readiness promote or stifle successful transitions and independent disease self-management. We will ultimately use this data to create a Transitions program to evaluate in our center for adolescents with IBD and their parents.

Suhadi Suhadi, Soegiyanto Soegiyanto, Hari Amirruloh Rahman et al.

Bodily-kinesthetic intelligence model refers to a person's potential to body fact system via hand and physique movement, control, and expression. This model is still rarely known in Indonesian primary school. The aim of this research was to determine the current bodily-kinesthetic intelligence model in physical education teaching for primary schoolers. Descriptive research was conducted with a qualitative and quantitative approach. The sample of this study was physical education teachers and primary school students. Literature review of the documents, questionnaire, observation, video recordings, photography and diary were used to explore the level of the student mind and fitness body. The result showed that the current Bodily-kinesthetic intelligence model in Physical Education Teaching did not allow the appearance of increasing the maximum of their physical and mental abilities. In conclusion, this study gives the assessment model of student human kinetic in order to fix the current issue of competence evaluation. Physical education teachers need to improve their teaching methods to allow students to reach physical and mental performance.

Feng Liu, Yi Li, Xiaorui Shi

Margo L. Beggs

Young America: The Daguerreotypes of Southworth & Hawes (2005) is a monumental exhibition catalogue showcasing the work of Albert Sands Southworth and Josiah Johnson Hawes. Together the partners established a renowned daguerreotype studio in mid-nineteenth-century Boston that catered to the city’s bourgeoisie. This paper seeks to unravel the mystery of dozens of daguerreotypes found in Young America, in which elite Boston women appear to be nearly nude. The unidentified women stand in stark contrast to the carefully concealed bodies of Southworth & Hawes’ other female subjects. Why would they expose themselves in such a manner before the camera’s lens? This paper attributes the women’s state of (un)dress to their deliberate emulation of two sculptures in the classical tradition: Clytie, a marble bust dating to antiquity, and Proserpine, a mid-nineteenth-century marble bust by American neoclassical sculptor Hiram Powers. This argument first reveals how a general “classical statue” aesthetic prevailed for women’s deportment in antebellum America, then demonstrates that the busts of Clytie and Proserpine had special significance as icons of white, elite female beauty in the period. Next, this paper makes the case that Southworth & Hawes devised a special style of photography deriving from their own daguerreotypes of the two statues, in which the women’s off-shoulder drapery was deliberately obscured allowing their female clientele to pose in the guise of these famous statues. The paper concludes by arguing that the women shown in these images could pose in this style without contravening societal norms, as these mythological figures were construed by women and men in the period to reflect the central precepts of the mid-nineteenth-century “Cult of True Womanhood.” Moreover, the busts offered sartorial models that reinforced standards of female dress as they related to class and privilege. By baring their flawless, white skin, however, the women positioned themselves at the crux of contentious beliefs about race in a deeply divided nation prior to the American Civil War.

Tarek Hamd Allah

This paper aims to study the effects of light intensity on the digital image production, and therefore the accurate reproduction of details when tracing this digital image to the vector image. The paper used experimental and analytical methods to study the light intensity as the independent variable through the dependent variables "lens aperture, sensitivity speed (ISO)" and shutter speed. Next, the digital images obtained from the experiments were auto traced to vector images. Then, the results were measured and analyzed. While the results were identical to the hypotheses related to lens aperture and sensitivity speed (ISO) experiments, the shutter speed experiment results did not match the hypothesis: there is no change in the details of the vector image created through the variables shutter speed in the digital image. Therefore, using fast shutter speeds is recommended to increase the accuracy of the vector image details produced through the digital image.

Jezabeth Roca Gonzalez

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