Search results for: body images

Authors: Ciro Cursio, Giulia Cursio, Pio Luigi Cursio, Luigi Cursio

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Communication between practitioner and patient is of the utmost importance in aesthetic medicine: as of today, images of previous treatments are the most common tool used by doctors to describe and anticipate future results for their patients. However, using photos of other people often reduces the engagement of the prospective patient and is further limited by the number and quality of pictures available to the practitioner. Pre-existing work solves this issue in two ways: 3D scanning of the area with manual editing of the 3D model by the doctor or automatic prediction of the treatment by warping the image with hand-written parameters. The first approach requires the manual intervention of the doctor, while the second approach always generates results that aren’t always realistic. Thus, in one case, there is significant manual work required by the doctor, and in the other case, the prediction looks artificial. We propose an AI-based algorithm that autonomously generates a realistic prediction of treatment results. For the purpose of this study, we focus on hyaluronic acid treatments in the facial area. Our approach takes into account the individual characteristics of each face, and furthermore, the prediction system allows the patient to decide which area of the face she wants to modify. We show that the predictions generated by our system are realistic: first, the quality of the generated images is on par with real images; second, the prediction matches the actual results obtained after the treatment is completed. In conclusion, the proposed approach provides a valid tool for doctors to show patients what they will look like before deciding on the treatment.

Keywords: prediction, hyaluronic acid, treatment, artificial intelligence

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Authors: Edoghogho Ogbeifun, Charles Mbohwa, J. H. C. Pretorius

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Several research report on the factors responsible for the delays in the completion of construction projects has identified the issue of funding as a critical factor; insufficient funding, low cash-flow or lack of funds. Indeed, adequate funding plays pivotal role in the effective execution of construction projects. In the last twenty years (or so), there has been increase in the funds available for infrastructure development in tertiary institution in Nigeria, especially, through the Tertiary Education Trust Fund. This funding body ensures that there is enough fund for each approved project, which is released in three stages during the life of the construction project. However, a random tour of many of the institutions reveals striking evidence of projects not delivered on schedule, to quality and sometime out rightly abandoned. This suggests, therefore, that there are other latent factors, responsible for project delays, that should be investigated. Thus, this research, a pilot scheme, is aimed at unearthing the possible reasons for the delays being experienced in the execution of construction projects for infrastructure upgrade in public tertiary institutions in Nigeria, funded by Tertiary Education Trust Fund. The multiple site case study of qualitative research was adopted. The respondents were the Directors of Physical Planning and the Directors of Works of four Nigerian Public Universities. The findings reveal that delays can be situated within three entities, namely, the funding body, the institutions and others. Therefore, the emerging factors have been classified as external factors (haven to do with the funding body), internal factors (these concern the operations within the institutions) and general factors. The outcome of this pilot exercise provides useful information to guide the Directors as they interact with the funding body as well as challenges themselves to address the loopholes in their internal operations.

Keywords: delays, external factors, funding, general factors, Internal factors

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Authors: Ying Shen, Weihua Zhu

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Medical images are important to help identifying different diseases, for example, Magnetic resonance imaging (MRI) can be used to investigate the brain, spinal cord, bones, joints, breasts, blood vessels, and heart. Image segmentation, in medical image analysis, is usually the first step to find out some characteristics with similar color, intensity or texture so that the diagnosis could be further carried out based on these features. This paper introduces an improved C-means model to segment the MRI images. The model is based on information entropy to evaluate the segmentation results by achieving global optimization. Several contributions are significant. Firstly, Genetic Algorithm (GA) is used for achieving global optimization in this model where fuzzy C-means clustering algorithm (FCMA) is not capable of doing that. Secondly, the information entropy after segmentation is used for measuring the effectiveness of MRI image processing. Experimental results show the outperformance of the proposed model by comparing with traditional approaches.

Keywords: magnetic resonance image (MRI), c-means model, image segmentation, information entropy

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Authors: Hina Kausher, Sangita Srivastava

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In India, there is a lack of standard, systematic sizing approach for producing readymade garments. Garments manufacturing companies use their own created size tables by modifying international sizing charts of ready-made garments. The purpose of this study is to tabulate the anthropometric data which covers the variety of figure proportions in both height and girth. 3,000 data has been collected by an anthropometric survey undertaken over females between the ages of 16 to 80 years from some states of India to produce the sizing system suitable for clothing manufacture and retailing. This data is used for the statistical analysis of body measurements, the formulation of sizing systems and body measurements tables. Factor analysis technique is used to filter the control body dimensions from a large number of variables. Decision tree-based data mining is used to cluster the data. The standard and structured sizing system can facilitate pattern grading and garment production. Moreover, it can exceed buying ratios and upgrade size allocations to retail segments.

Keywords: anthropometric data, data mining, decision tree, garments manufacturing, sizing systems, ready-made garments

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Authors: Kevin Klein-Cardeña

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For Julia Kristeva, contra Lacan, the instinctive body refuses to go away within discourse. Neither is the pre-Oedipal stage of maternal fusion vanquished by the emergence of language and with it, the law of the father. On the contrary, Kristeva argues, the pre-symbolic ambivalently haunts the society of speech, simultaneously animating and threatening the very foundations of signification. Kristeva invents the term “the semiotic” to refer to this continual breaking-through of the material unconscious onto the scene of meaning. This presentation examines Kristeva’s semiotic as a theoretical gesture that itself is a disruption of discourse, re-presenting the ‘return of the repressed’ body in theory—-the breaking-through of the unconscious onto the science of meaning. Faced with linguistic theories concerned with abstract sign-systems as well as Lacanian doctrine privileging the linguistic sign unequivocally over the bodily drive, Kristeva’s theoretical corpus issues the message of a psychic remainder that disrupts with a view toward replenishing theoretical accounts of language and sense. Reviewing Semiotic challenge across these two levels (the sense and science of language), the presentation suggests that Kristeva’s offerings constitute a coherent gestalt, providing an account of the feminist nature of her dual intervention. In contrast to other feminist critiques, Kristeva’s gesture hinges on its restoration of the maternal contribution to subjectivity. Against the backdrop of ‘phallogocentric’ and ‘necrophilic’ theories that strip language of a subject and strip the subject of a body, Kristeva recasts linguistic study through a metaphor of life and birthing. Yet the semiotic fragments the subject it produces, dialoguing with an unconscious curtailed by but also exceeding the symbolic order of signification. Linguistics, too, becomes fragmented in the same measure as it is more meaningfully renewed by its confrontation with the semiotic body. It is Kristeva’s own body that issues this challenge, on both sides of the boundary between the theory and the theorized. The Semiotic becomes comprehensible as a project unified by its concern to disrupt and rehabilitate language, the subject, and the scholarly discourses that treat them.

Keywords: Julia kristeva, the Semiotic, french feminism, psychoanalysic theory, linguistics

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Authors: Judith Stein, Elfriede Friedmann

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The injection of a drug into the vitreous body for the treatment of retinal diseases like wet aged-related macular degeneration (AMD) is the most common medical intervention worldwide. We develop mathematical models for drug transport in the vitreous body of a human eye to analyse the impact of different rheological models of the vitreous on drug distribution. In addition to the convection diffusion equation characterizing the drug spreading, we use porous media modeling for the healthy vitreous with a dense collagen network and include the steady permeating flow of the aqueous humor described by Darcy's law driven by a pressure drop. Additionally, the vitreous body in a healthy human eye behaves like a viscoelastic gel through the collagen fibers suspended in the network of hyaluronic acid and acts as a drug depot for the treatment of retinal diseases. In a completely liquefied vitreous, we couple the drug diffusion with the classical Navier-Stokes flow equations. We prove the global existence and uniqueness of the weak solution of the developed initial-boundary value problem describing the drug distribution in the healthy vitreous considering the permeating aqueous humor flow in the realistic three-dimensional setting. In particular, for the drug diffusion equation, results from the literature are extended from homogeneous Dirichlet boundary conditions to our mixed boundary conditions that describe the eye with the Galerkin's method using Cauchy-Schwarz inequality and trace theorem. Because there is only a small effective drug concentration range and higher concentrations may be toxic, the ability to model the drug transport could improve the therapy by considering patient individual differences and give a better understanding of the physiological and pathological processes in the vitreous.

Keywords: coupled PDE systems, drug diffusion, mixed boundary conditions, vitreous body

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Authors: Khulood Zahran

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Background and Purpose: The effects of backpack on 'school-age' children (Age 9–12) years, have been a critical subject of discussion throughout the past years. It has been one of the factors that contribute to a bad posture for 40% to 70% of developed countries. A child carrying a heavy backpack for a prolonged period, on a daily base has shown significant changes in the child's spinal posture, foot shape, and gait. The back pain caused by the compensatory posture, or "Backpack syndrome", is also known for its headaches, fatigue, cervical and lumber pain caused by the abnormal body posture. The child tends to balance himself by bending forward to match the heavy backpack, moving his Centre of Gravity forward, resulting in decreased lumber lordosis and increased thoracic kyphosis. Since currently available bags have not addressed the weight distribution issue till now. Therefore, KZ bag is believed to prevent the huge backward shift of COG due to the load, and hence all the symptoms accompanied. This is thought to be possible by combining the design of a normal backpack with a messenger bag. The purpose of this study is to investigate the improvement of the child's spine and to minimize the compensatory posture after using the KZ bag. Materials and Methods: KZ bag would compromise the pros of a messenger bag (keeping the COG in place) by a diagonal load strap and of a backpack (distributing the load on both shoulders) by connecting another load strap parallel to the sagittal plane of the body. The design would be made adjustable to match the child's height, and the bag load kept within limits, (10-15%) of the child's body weight. Measurements of Postural angles (Cervical, shoulders, and Trunk) would be taken after the use of KZ bag for a specified period. Conclusion: KZ bag will prove an improved distribution of weight of the bag on the child's body, and reduce the degree of the compensatory posture, that occurs in the attempt to balance the external weight of the bag.

Keywords: backpack, backpack syndrome, posture, spine

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Authors: Sophia Shi

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Acute kidney injury (AKI) is the sudden onset of kidney damage in which the kidneys cannot filter waste from the blood, requiring emergency hospitalization. AKI patient mortality rate is high in the ICU and is virtually impossible for doctors to predict because it is so unexpected. Currently, there is no hybrid model predicting AKI that takes advantage of two types of data. De-identified patient data from the MIMIC-III database and de-identified kidney images and corresponding patient records from the Beijing Hospital of the Ministry of Health were collected. Using data features including serum creatinine among others, two numeric models using MIMIC and Beijing Hospital data were built, and with the hospital ultrasounds, an image-only model was built. Convolutional neural networks (CNN) were used, VGG and Resnet for numeric data and Resnet for image data, and they were combined into a hybrid model by concatenating feature maps of both types of models to create a new input. This input enters another CNN block and then two fully connected layers, ending in a binary output after running through Softmax and additional code. The hybrid model successfully predicted AKI and the highest AUROC of the model was 0.953, achieving an accuracy of 90% and F1-score of 0.91. This model can be implemented into urgent clinical settings such as the ICU and aid doctors by assessing the risk of AKI shortly after the patient’s admission to the ICU, so that doctors can take preventative measures and diminish mortality risks and severe kidney damage.

Keywords: Acute kidney injury, Convolutional neural network, Hybrid deep learning, Patient record data, ResNet, Ultrasound kidney images, VGG

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Authors: Yi-Feng Kao, Huey-Jine Chai, Chin-I Chang, Yi-Chen Chen, June-Ru Chen

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Microglia is a macrophage that resides in brain, and overactive microglia may result in brain neuron damage or inflammation. In this study, the phospholipids was extracted from squid skin and manufactured into a liposome (SQ liposome) to mimic apoptotic body. We then evaluated anti-inflammatory effects of SQ liposome on mouse microglial cell line (BV-2) by lipopolysaccharide (LPS) induction. First, the major phospholipid constituents in the squid skin extract were including 46.2% of phosphatidylcholine, 18.4% of phosphatidylethanolamine, 7.7% of phosphatidylserine, 3.5% of phosphatidylinositol, 4.9% of Lysophosphatidylcholine and 19.3% of other phospholipids by HPLC-UV analysis. The contents of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) in the squid skin extract were 11.8 and 28.7%, respectively. The microscopic images showed that microglia cells can engulf apoptotic cells or SQ-liposome. In cell based studies, there was no cytotoxicity to BV-2 as the concentration of SQ-liposome was less than 2.5 mg/mL. The LPS induced pro-inflammatory cytokines, including tumor necrosis factor-alpha (TNF-α) and interleukin-6 (IL-6), were significant suppressed (P < 0.05) by pretreated 0.03~2.5mg/ml SQ liposome. Oppositely, the anti-inflammatory cytokines transforming growth factor-beta (TGF-β) and interleukin-10 (IL-10) secretion were enhanced (P < 0.05). The results suggested that SQ-liposome possess anti-inflammatory properties on BV-2 and may be a good strategy for against neuro-inflammatory disease.

Keywords: apoptotic mimicry, neuroinflammation, microglia, squid processing by-products

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Authors: Elham Alaee, Mousa Shamsi, Hossein Ahmadi, Soroosh Nazem, Mohammad Hossein Sedaaghi

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Human face has a fundamental role in the appearance of individuals. So the importance of facial surgeries is undeniable. Thus, there is a need for the appropriate and accurate facial skin segmentation in order to extract different features. Since Fuzzy C-Means (FCM) clustering algorithm doesn’t work appropriately for noisy images and outliers, in this paper we exploit Possibilistic C-Means (PCM) algorithm in order to segment the facial skin. For this purpose, first, we convert facial images from RGB to YCbCr color space. To evaluate performance of the proposed algorithm, the database of Sahand University of Technology, Tabriz, Iran was used. In order to have a better understanding from the proposed algorithm; FCM and Expectation-Maximization (EM) algorithms are also used for facial skin segmentation. The proposed method shows better results than the other segmentation methods. Results include misclassification error (0.032) and the region’s area error (0.045) for the proposed algorithm.

Keywords: facial image, segmentation, PCM, FCM, skin error, facial surgery

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Authors: David C. Ni

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Contemporary models for N-body systems are based on temporal, two-body, and mass point representation of Newtonian mechanics. Other mainstream models include 2D and 3D Ising models based on local neighborhood the lattice structures. In Quantum mechanics, the theories of collective modes are for superconductivity and for the long-range quantum entanglement. However, these models are still mainly for the specific phenomena with a set of designated parameters. We are therefore motivated to develop a new construction directly from the complex-variable N-body systems based on the extended Blaschke functions (EBF), which represent a non-temporal and nonlinear extension of Lorentz transformation on the complex plane – the normalized momentum spaces. A point on the complex plane represents a normalized state of particle momentums observed from a reference frame in the theory of special relativity. There are only two key parameters, normalized momentum and nonlinearity for modelling. An algorithm similar to Jenkins-Traub method is adopted for solving EBF iteratively. Through iteration, the solution sets show a form of σ + i [-t, t], where σ and t are the real numbers, and the [-t, t] shows various distributions, such as 1-peak, 2-peak, and 3-peak etc. distributions and some of them are analog to the canonical distributions. The results of the numerical analysis demonstrate continuum-to-discreteness transitions, evolutional invariance of distributions, phase transitions with conjugate symmetry, etc., which manifest the construction as a potential candidate for the unification of statistics. We hereby classify the observed distributions on the finite convergent domains. Continuous and discrete distributions both exist and are predictable for given partitions in different regions of parameter-pair. We further compare these distributions with canonical distributions and address the impacts on the existing applications.

Keywords: blaschke, lorentz transformation, complex variables, continuous, discrete, canonical, classification

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Authors: Sh. Khoshemehry, M. E. Bahram, M. J. Pourvaghar

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Sport has found a special place as an effective phenomenon in all societies of the contemporary world. The relationship between physical activity and exercise with different sciences has provided new fields for human study. The range of issues related to exercise and physical education is such that it requires specialized sciences and special studies. In this article, the psychological and social sections of exercise have been investigated for children and adults. It can be used for anyone in different age groups. Exercise and regular physical movements have a great impact on the mental and social health of the individual in addition to body health. It affects the individual's adaptability in society and his/her personality. Exercise affects the treatment of diseases such as depression, anxiety, stress, body image, and memory. Exercise is a safe haven for young people to achieve the optimum human development in its shelter. The effects of sensorimotor skills on mental actions and mental development are such a way that many psychologists and sports science experts believe these activities should be included in training programs in the first place. Familiarity of students and scholars with different programs and methods of sensorimotor activities not only causes their mental actions; but also increases mental health and vitality, enhances self-confidence and, therefore, mental health.

Keywords: anxiety, mental health, physical activity, serotonin

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Authors: Mohamed Gouda

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Antibacterial wound dressings based on cellulose nanofibers containing different metal nanoparticles (CMC-MNPs) were synthesized using an electrospinning technique. First, the composite of carboxymethyl cellulose containing different metal nanoparticles (CMC/MNPs), such as copper nanoparticles (CuNPs), iron nanoparticles (FeNPs), zinc nanoparticles (ZnNPs), cadmium nanoparticles (CdNPs) and cobalt nanoparticles (CoNPs) were synthesized, and finally, these composites were transferred to the electrospinning process. Synthesized CMC-MNPs were characterized using scanning electron microscopy (SEM) coupled with high-energy dispersive X-ray (EDX) and UV-visible spectroscopy used to confirm nanoparticle formation. The SEM images clearly showed regular flat shapes with semi-porous surfaces. All MNPs were well distributed inside the backbone of the cellulose without aggregation. The average particle diameters were 29-39 nm for ZnNPs, 29-33 nm for CdNPs, 25-33 nm for CoNPs, 23-27 nm for CuNPs and 22-26 nm for FeNPs. Surface morphology, water uptake and release of MNPs from the nanofibers in water and antimicrobial efficacy were studied. SEM images revealed that electrospun CMC-MNPs nanofibers are smooth and uniformly distributed without bead formation with average fiber diameters in the range of 300 to 450 nm. Fiber diameters were not affected by the presence of MNPs. TEM images showed that MNPs are present in/on the electrospun CMC-MNPs nanofibers. The diameter of the electrospun nanofibers containing MNPs was in the range of 300–450 nm. The MNPs were observed to be spherical in shape. The CMC-MNPs nanofibers showed good hydrophilic properties and had excellent antibacterial activity against the Gram-negative bacteria Escherichia coli and the Gram-positive bacteria Staphylococcus aureus.

Keywords: electrospinning technique, metal nanoparticles, cellulosic nanofibers, wound dressing

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Authors: Shelby Simpson, William Stanley, Namir Naba, Xiaodi Wang

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Both t-SNE and UMAP are brand new state of art tools to predominantly preserve the local structure that is to group neighboring data points together, which indeed provides a very informative visualization of heterogeneity in our data. In this research, we develop a t-SNE and UMAP base neural network image classification algorithm to embed the original dataset to a corresponding low dimensional dataset as a preprocessing step, then use this embedded database as input to our specially designed neural network classifier for image classification. We use the fashion MNIST data set, which is a labeled data set of images of clothing objects in our experiments. t-SNE and UMAP are used for dimensionality reduction of the data set and thus produce low dimensional embeddings. Furthermore, we use the embeddings from t-SNE and UMAP to feed into two neural networks. The accuracy of the models from the two neural networks is then compared to a dense neural network that does not use embedding as an input to show which model can classify the images of clothing objects more accurately.

Keywords: t-SNE, UMAP, fashion MNIST, neural networks

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Authors: Jawad Zakir, Syed Irtiza Ali Shah, Rana Shaharyar, Sidra Mahmood

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Y-force equation comprises aerodynamic forces, drag and side force with side slip angle β and weight component along with the coupled roll (φ) and pitch angles (θ). This research deals with the linearization of Y-force equation using Small Disturbance theory assuming equilibrium flight conditions for different state variables of aircraft. By using assumptions of Small Disturbance theory in non-linear Y-force equation, finally reached at linearized lateral rigid body equation of motion; which says that in linearized Y-force equation, the lateral acceleration is dependent on the other different aerodynamic and propulsive forces like vertical tail, change in roll rate (Δp) from equilibrium, change in yaw rate (Δr) from equilibrium, change in lateral velocity due to side force, drag and side force components due to side slip, and the lateral equation from coupled rotating frame to decoupled rotating frame. This paper describes implementation of this lateral linearized equation for aircraft control systems. Another significant parameter considered on which y-force equation depends is ‘c’ which shows that any change bought in the weight of aircrafts wing will cause Δφ and cause lateral force i.e. Y_c. This simplification also leads to lateral static and dynamic stability. The linearization of equations is required because much of mathematics control system design for aircraft is based on linear equations. This technique is simple and eases the linearization of the rigid body equations of motion without using any high-speed computers.

Keywords: Y-force linearization, small disturbance theory, side slip, aerodynamic force drag, lateral rigid body equation of motion

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Authors: Sebastian Wójtowicz, Anna Mosiołek, Anna Słupik, Zbigniew Wroński, Dariusz Białoszewski

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Introduction: In whole-body vibration (WBV) high-frequency mechanical stimuli is generated by a vibration plate and is transferred through bone, muscle and connective tissues to the whole body. The research has shown that the implementation of a vibration plate training over a long period of time leads to improvement of neuromuscular facilitation, especially in afferent neural pathways, which are responsible for the conduction of vibration and proprioceptive stimuli, muscle function, balance, and proprioception. The vibration stimulus is suggested to briefly inhibit the conduction of afferent signals from proprioceptors and may hinder the maintenance of body balance. The purpose of this study was to evaluate the result of a single set of exercises connected with whole-body vibration on the proprioception. Material and Methods: The study enrolled 60 people aged 19-24 years. These individuals were divided into a test group (group A) and a control group (group B). Both groups consisted of 30 persons and performed the same set of exercises on a vibration plate. The following vibration parameters: frequency of 20Hz and amplitude of 3mm, were used in the group A. The vibration plate was turned off while the control group did their exercises. All participants performed six dynamic 30-seconds-long exercises with a 60-second resting period between them. Large muscle groups of the trunk, pelvis, and lower limbs were involved while taking the exercises. The results were measured before and immediately after the exercises. The proprioception of lower limbs was measured in a closed kinematic chain using a Humac 360®. Participants were instructed to perform three squats with biofeedback in a defined range of motion. Then they did three squats without biofeedback which were measured. The final result was the average of three measurements. Statistical analysis was performed using Statistica 10.0 PL software. Results: There were no significant differences between the groups, both before and after the exercise (p > 0.05). The proprioception did not change in both the group A and the group B. Conclusions: 1. Deterioration in proprioception was not observed immediately after the vibration stimulus. This suggests that vibration-induced blockage of proprioceptive stimuli conduction can only have a short-lasting effect occurring only in the presence of the vibration stimulus. 2. Short-term use of vibration seems to be safe for patients with proprioceptive impairment due to the fact that the treatment does not decrease proprioception. 3. There is a need for supplementing the results with evaluation of proprioception while vibration stimuli are being applied. Moreover, the effects of vibration parameters used in the exercises should be evaluated.

Keywords: joint position sense, proprioception, squat, whole body vibration

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Authors: Harold Mauricio Díaz-Vargas, Cristian Alfonso Jimenez-Castaño, David Augusto Cárdenas-Peña, Guillermo Alberto Ortiz-Gómez, Alvaro Angel Orozco-Gutierrez

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Precise identification of the nerves is a crucial task performed by anesthesiologists for an effective Peripheral Nerve Blocking (PNB). Now, anesthesiologists use ultrasound imaging equipment to guide the PNB and detect nervous structures. However, visual identification of the nerves from ultrasound images is difficult, even for trained specialists, due to artifacts and low contrast. The recent advances in deep learning make neural networks a potential tool for accurate nerve segmentation systems, so addressing the above issues from raw data. The most widely spread U-Net network yields pixel-by-pixel segmentation by encoding the input image and decoding the attained feature vector into a semantic image. This work proposes a conditioning approach and encoder pre-training to enhance the nerve segmentation of traditional U-Nets. Conditioning is achieved by the one-hot encoding of the kind of target nerve a the network input, while the pre-training considers five well-known deep networks for image classification. The proposed approach is tested in a collection of 619 US images, where the best C-UNet architecture yields an 81% Dice coefficient, outperforming the 74% of the best traditional U-Net. Results prove that pre-trained models with the conditional approach outperform their equivalent baseline by supporting learning new features and enriching the discriminant capability of the tested networks.

Keywords: nerve segmentation, U-Net, deep learning, ultrasound imaging, peripheral nerve blocking

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Authors: Predrag Kavaric, Vladimir L. Jubic, Maxim Cadenovic

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The patient was transferred from his dentist to our tertiary medical institution. In anamnesis, we got information that his dental intervention was two years ago when he got dental implants but because of the coronavirus pandemic event, he didn’t finish the whole procedure. After two years, he decided that he will continue his work at his dentist, then his dentist noticed that there is no earlier inserted implant in the upper jaw on the right side. They do Panoramic X-ray and find that the implant is all in the maxillary sinus cavity. The flour of the maxilla was intact without any fistula on the place where the implant was inserted in the maxilla bone, After that initial diagnostic they sent the patient to maxillofacial surgery and otorhinolaryngology. We asked for a CT scan of paranasal sinuses, which confirmed the foreign body in the right maxillary sinus. The plan was that in general anesthesia we do FESS and try to find a foreign body in the maxillary sinus or in case of failure to do Caldwel Luc on that side. After preoperative preparation in GA, we do FESS. In inspection, we find small polyps and chronically changed mucosa of osteomeatal complex and right maxillary sinus. After removing polyps we did uncinectomy and medial maxillectomy. With Heuweiser Antrum grasping forceps after several attempts we managed to extract a foreign body from the bottom of the right maxillary sinus. On the first postoperative day we did detamponade, and then we discharge the patient from hospital. The Covid pandemic has contributed to the postponement of a large number of planned operations, which has resulted in various complications in the treatment of a number of patients. In this case, it happened that the implant was most likely rejected by the bone but in the direction of the maxillary sinus, which is not a common cause. On the other hand, the success was that less traumatic intervention was able to remove the foreign body from the maxillary sinus in which it was located. Since the sinus floor is free of bone defects, it can be continued relatively quickly with dental procedures.

Keywords: x-ray, surgery, maxillar sinus, complication, fees

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Authors: T. M. Samuel, O. O. Aremu, I. O. Ismaila, L. I. Onu, B. O. Adetifa, S. E. Adegbite, O. O. Olokoshe

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The imperative of anthropometry in designing to fit cannot be overemphasized. Of essence is the variability of measurements among population for which data is collected. In this paper anthropometric data were collected for the design of gari-frying facility such that work system would be designed to fit the gari-frying population in the Southwestern states of Nigeria comprising Lagos, Ogun, Oyo, Osun, Ondo, and Ekiti. Twenty-seven body dimensions were measured among 120 gari-frying processors. Statistical analysis was performed using SPSS package to determine the mean, standard deviation, minimum value, maximum value and percentiles (2nd, 5th, 25th, 50th, 75th, 95th, and 98th) of the different anthropometric parameters. One sample t-test was conducted to determine the variation within the population. The 50th percentiles of some of the anthropometric parameters were compared with those from other populations in literature. The correlation between the worker’s age and the body anthropometry was also investigated.The mean weight, height, shoulder height (sitting), eye height (standing) and eye height (sitting) are 63.37 kg, 1.57 m, 0.55 m, 1.45 m, and 0.67 m respectively.Result also shows a high correlation with other populations and a statistically significant difference in variability of data within the population in all the body dimensions measured. With a mean age of 42.36 years, results shows that age will be a wrong indicator for estimating the anthropometry for the population.

Keywords: anthropometry, cassava processing, design to fit, gari-frying, workstation design

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Authors: Vahid Anari, Leila Shahmohammadi

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Diagnosing and interpreting manually from a large cohort dataset of immunohistochemically stained tissue of tumors using an optical microscope involves subjectivity and also is tedious for pathologist specialists. Moreover, digital pathology today represents more of an evolution than a revolution in pathology. In this paper, we develop and test an unsupervised algorithm that can automatically enhance the IHC image of a meningioma tumor and classify cells into positive (proliferative) and negative (normal) cells. A dataset including 150 images is used to test the scheme. In addition, a new adaptive color image enhancement method is proposed based on a vector directional filter (VDF) and statistical properties of filtering the window. Since the cells are distinguishable by the human eye, the accuracy and stability of the algorithm are quantitatively compared through application to a wide variety of real images.

Keywords: digital pathology, cell segmentation, immunohistochemically, noise reduction

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Authors: John Davodi, Maryam Davodi-Far

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The human body is the most elaborate of all machines and technologies on Earth, while the human mind is the interdependent source that expels and absorbs the five senses: touch, smell, sight, sound, and taste. Meditation is an ancient form of mind power that has many variations. In fact, those who practice meditation may bring about a positive change in their five senses, depending on the aim of the practitioner. This paper examines the research related to meditation and its effects on individuals suffering from chronic pain. Moreover, consideration is given to whether perceptions of pain can be changed by the practice of meditation as well as whether meditation can have a noticeable and long-term positive effect on the human body. Lastly, the paper examines the type of meditation that is best suited to minimize pain sensations for those who suffer from chronic pain.

Keywords: meditation, pain, relaxation, suffering

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Authors: S. Benchelha, H. Chennaoui, M. Hakdaoui, L. Baidder, H. Mansouri, H. Ejjaaouani, T. Benchelha

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Northern Morocco is characterized by relatively young mountains experiencing a very important dynamic compared to other areas of Morocco. The dynamics associated with the formation of the Rif chain (Alpine tectonics), is accompanied by instabilities essentially related to tectonic movements. The realization of important infrastructures (Roads, Highways,...) represents a triggering factor and favoring landslides. This paper is part of the establishment of landslides susceptibility map and concerns the mapping of unstable areas in the province of Taounate. The landslide was identified using the components of the false color (FCC) of images Landsat OLI: i) the first independent component (IC1), ii) The main component (PC), iii) Normalized difference index (NDI). This mapping for landslides class is validated by in-situ surveys.

Keywords: landslides, False Color Composite (FCC), Independent Component Analysis (ICA), Principal Component Analysis (PCA), Normalized Difference Index (NDI), Normalized Difference Mid Red Index (NDMIDR)

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Authors: Donya Ashtiani Haghighi, Amirali Baniasadi

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Coronavirus (COVID-19) disease has spread abruptly all over the world since the end of 2019. Computed tomography (CT) scans and X-ray images are used to detect this disease. Different Deep Neural Network (DNN)-based diagnosis solutions have been developed, mainly based on Convolutional Neural Networks (CNNs), to accelerate the identification of COVID-19 cases. However, CNNs lose important information in intermediate layers and require large datasets. In this paper, Capsule Network (CapsNet) is used. Capsule Network performs better than CNNs for small datasets. Accuracy of 0.9885, f1-score of 0.9883, precision of 0.9859, recall of 0.9908, and Area Under the Curve (AUC) of 0.9948 are achieved on the Capsule-based framework with hyperparameter tuning. Moreover, different dropout rates are investigated to decrease overfitting. Accordingly, a dropout rate of 0.1 shows the best results. Finally, we remove one convolution layer and decrease the number of trainable parameters to 146,752, which is a promising result.

Keywords: capsule network, dropout, hyperparameter tuning, classification

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Authors: Turki J. Alharbi, Jencia Wong, Dennis Yue, Tania P. Markovic, Julie Hetherington, Ted Wu, Belinda Brooks, Radhika Seimon, Alice Gibson, Stephanie L. Silviera, Amanda Sainsbury, Tanya J. Little

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Fasting has been practiced for centuries and is incorporated into the practices of different religions including Islam, whose followers intermittently fast throughout the month of Ramadan. Thus, Ramadan presents a unique model of prolonged intermittent fasting (IF). Despite a growing body of evidence for a cardio-metabolic and endocrine benefit of IF, detailed studies of the effects of IF on these indices in type 2 diabetes are scarce. We studied 5 subjects with type 2 diabetes (T2DM) and 7 healthy controls (C) at baseline (pre), and in the last week of Ramadan (post). Fasting circulating levels of glucose, HbA1c and lipids, as well as body composition (with DXA) and resting energy expenditure (REE) were measured. Plasma gut hormone levels and appetite responses to a mixed meal were also studied. Data are means±SEM. Ramadan decreased total fat mass (-907±92 g, p=0.001) and trunk fat (-778±190 g, p=0.014) in T2DM but not in controls, without any reductions in lean mass or REE. There was a trend towards a decline in plasma FFA in both groups. Ramadan had no effect on body weight, glycemia, blood pressure, or plasma lipids in either group. In T2DM only, the area under the curve for post-meal plasma ghrelin concentrations increased after Ramadan (pre:6632±1737 vs. post:9025±2518 pg/ml.min-1, p=0.045). Despite this increase in orexigenic ghrelin, subjective appetite scores were not altered by Ramadan. Meal-induced plasma concentrations of the satiety hormone pancreatic polypeptide did not change during Ramadan, but were higher in T2DM compared to controls (post: C: 23486±6677 vs. T2DM: 62193±6880 pg/ml.min-1, p=0.003. In conclusion, Ramadan, as a model for IF appears to have more favourable effects on body composition in T2DM, without adverse effects on metabolic control or subjective appetite. These data suggest that IF may be particularly beneficial in T2DM as a nutritional intervention. Larger studies are warranted.

Keywords: type 2 diabetes, obesity, intermittent fasting, appetite regulating hormones

Procedia PDF Downloads 296

Authors: M. M. Islam, S. Sharmin, M. Shah Newaz, N. S. Juyena, M. M. Rahman, P. K. Jha, F. Y. Bari

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The aim of the present study was to select the high quality ram by measuring the scrotal biometry which has an effect on semen parameters. Ten rams were selected in the present study. Eight ejaculates were collected from each ram using artificial vagina method. Scrotal circumference was measured before and after semen collection on weekly basis using the Scrotal tape. Bio-metries of scrotum (scrotal length and scrotal volume) were calculated. Semen was evaluated for macroscopic and microscopic characteristics. The average estimated scrotal circumference (cm) and scrotal volume (cm3) in 8 different age groups were 17.16±0.05 cm and 61.30±0.70 cm3, 17.17±0.62 cm and 63.67±4.49 cm3, 17.22±0.52 cm and 64.90±4.21 cm3, 17.72±0.37 cm and 67.10±4.20 cm3, 18.41±0.35cm and 69.52±4.12cm3, 18.45±0.36cm and 77.17±3.81 cm3, 18.55±0.41 cm and 78.72±4.90 cm3, 19.10±0.30 cm and 87.35±5.45 cm3 respectively. The body weight, scrotal circumference and scrotal volume increased with the progress of age (P < 0.05). Body weight of age group 381-410 days (13.62+1.48 kg) was significantly higher than group 169-200 days (10.17±0.05 kg) and 201-230 days (10.42±1.18 kg) (p < 0.05). Scrotal circumference (SC) of age group 381-410 days (19.10±0.30 cm) was significantly higher (p < 0.05) than other groups. In age group 381-410 days, scrotal volume (SCV) (87.35±5.45 cm3) was significantly higher than other first five groups (p < 0.05). Both scrotal circumference and scrotal volume development was positively correlated with the increasing of body weight (R2= 0.51). Semen volume increased accordingly with the increasing of ages, varied from 0.35±0.00 ml to 1.15+0.26 ml. Semen volume of age group 381-410 days (1.15±0.26 ml) was significantly higher than other age groups (p < 0.05) except age group 351-380 days (p > 0.05). Mass activity of different age groups varied from 2.75 (±0.35) to 4.25 (±0.29) ml in the scale of 1-5. Sperm concentration, progressive motility (%),progressively improved according to the increasing of ages, but significant changes in these parameters were seen when the animals reaches the age 291 days or more (p < 0.05). However, normal spermatozoa (%) improved significantly from the age of 261 days or more. Mass activity (mass) was positively correlated with sperm concentration (R2=0.568) and progressive motility (%) (R2=0.616). The relationships of semen volume with body weight and scrotal measurements and sperm concentration indicate that they are useful in evaluating rams for breeding soundness and genetic improvement for fertility in indigenous ram.

Keywords: breeding soundness, ram, semen quality, scrotal biometry

Procedia PDF Downloads 345

Authors: Bang Young Kim, Sang Hoon Park, Chul Gyu Song

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A conventional optical coherence tomography (OCT) system has limited imaging depth, which is 1-2 mm, and suffers unwanted noise such as speckle noise. The motorized-stage-based OCT system, using a common-path Fourier-domain optical coherence tomography (CP-FD-OCT) configuration, provides enhanced imaging depth and less noise so that we can overcome these limitations. Using this OCT systems, OCT images were obtained from an onion, and their subsurface structure was observed. As a result, the images obtained using the developed motorized-stage-based system showed enhanced imaging depth than the conventional system, since it is real-time accurate depth tracking. Consequently, the developed CP-FD-OCT systems and algorithms have good potential for the further development of endoscopic OCT for microsurgery.

Keywords: common-path OCT, FD-OCT, OCT, tracking algorithm

Procedia PDF Downloads 368

Authors: J. Jasmee, I. Roslina, A. Mohammed Yaziz & A.H Juazer Rizal

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The need of an effective building information collection method is vital to support a diversity of land development activities. At present, advances in remote sensing such as airborne LiDAR (Light Detection and Ranging) is an established technology for building information collection, location, and elevation of the reflecting laser points towards the construction of 3D building models. In this study, LiDAR datasets and terrestrial photographic images of buildings towards the construction of 3D building models is explored. It is found that, the quantitative accuracy of the constructed 3D building model, namely in the horizontal and vertical components were ± 0.31m (RMSEx,y) and ± 0.145m (RMSEz) respectively. The accuracies were computed based on sixty nine (69) horizontal and twenty (20) vertical surveyed points. As for the qualitative assessment, it is shown that the appearance of the 3D building model is adequate to support the requirements of LOD3 presentation based on the OGC (Open Geospatial Consortium) standard CityGML.

Keywords: LiDAR datasets, DSM, DTM, 3D building models

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Authors: Saad Algharib, Jay Lee

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Urbanization is a complex phenomenon that occurs during the city’s development from one form to another. In other words, it is the process when the activities in the land use/land cover change from rural to urban. Since the oil exploration, Kuwait City has been growing rapidly due to its urbanization and population growth by both natural growth and inward immigration. The main objective of this study is to detect changes in urban land use/land cover and to examine the changing spatial patterns of urban growth in and around Kuwait City between 1989 and 2001. In addition, this study also evaluates the spatial patterns of the changes detected and how they can be related to the spatial configuration of the city. Recently, the use of remote sensing and geographic information systems became very useful and important tools in urban studies because of the integration of them can allow and provide the analysts and planners to detect, monitor and analyze the urban growth in a region effectively. Moreover, both planners and users can predict the trends of the growth in urban areas in the future with remotely sensed and GIS data because they can be effectively updated with required precision levels. In order to identify the new urban areas between 1989 and 2001, the study uses satellite images of the study area and remote sensing technology for classifying these images. Unsupervised classification method was applied to classify images to land use and land cover data layers. After finishing the unsupervised classification method, GIS overlay function was applied to the classified images for detecting the locations and patterns of the new urban areas that developed during the study period. GIS was also utilized to evaluate the distribution of the spatial patterns. For example, Moran’s index was applied for all data inputs to examine the urban growth distribution. Furthermore, this study assesses if the spatial patterns and process of these changes take place in a random fashion or with certain identifiable trends. During the study period, the result of this study indicates that the urban growth has occurred and expanded 10% from 32.4% in 1989 to 42.4% in 2001. Also, the results revealed that the largest increase of the urban area occurred between the major highways after the forth ring road from the center of Kuwait City. Moreover, the spatial distribution of urban growth occurred in cluster manners.

Keywords: geographic information systems, remote sensing, urbanization, urban growth

Procedia PDF Downloads 152

Authors: Yao-Hong Tsai

Abstract:

This paper presents an efficient fusion algorithm for iris images to generate stable feature for recognition in unconstrained environment. Recently, iris recognition systems are focused on real scenarios in our daily life without the subject’s cooperation. Under large variation in the environment, the objective of this paper is to combine information from multiple images of the same iris. The result of image fusion is a new image which is more stable for further iris recognition than each original noise iris image. A wavelet-based approach for multi-resolution image fusion is applied in the fusion process. The detection of the iris image is based on Adaboost algorithm and then local binary pattern (LBP) histogram is then applied to texture classification with the weighting scheme. Experiment showed that the generated features from the proposed fusion algorithm can improve the performance for verification system through iris recognition.

Keywords: image fusion, iris recognition, local binary pattern, wavelet

Procedia PDF Downloads 353

Authors: Te-Jen Chang, I-Hui Pan, Kuang-Hsiung Tan, Shan-Jen Cheng, Chien-Wu Lan, Chih-Chan Hu

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With the event of multimedia age in order to protect data not to be tampered, damaged, and faked, information hiding technologies are proposed. Information hiding means important secret information is hidden into cover multimedia and then camouflaged media is produced. This camouflaged media has the characteristic of natural protection. Under the undoubted situation, important secret information is transmitted out.Reversible information hiding technologies for high capacity is proposed in this paper. The gray images are as cover media in this technology. We compress gray images and compare with the original image to produce the estimated differences. By using the estimated differences, expression information hiding is used, and higher information capacity can be achieved. According to experimental results, the proposed technology can be approved. For these experiments, the whole capacity of information payload and image quality can be satisfied.

Keywords: cover media, camouflaged media, reversible information hiding, gray image

Procedia PDF Downloads 314