Search results for: computer vision syndrome

Authors: Nashi Khan, Amina Khalid

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Aim: The purpose of this research was to find the psychiatric morbidity and level of sexual satisfaction among women with polycystic ovarian syndrome and their comparison with women with general medical conditions and to examine the correlation between psychiatric morbidity and sexual satisfaction among these women. Design: Cross sectional research design was used. Method: A total of 176 (M age = 30, SD = 5.83) women were recruited from both private and public sector hospitals in Pakistan. About 88 (50%) of the participants were diagnosed with polycystic ovarian syndrome (cases), whereas other 50% belonged to control group. Data were collected using semi structured interview. Sexual satisfaction scale for women (SSS-W) was administered to measure sexual satisfaction level and psychiatric morbidity was assessed by Symptom Checklist-Revised. Results: Results showed that participant’s depression and anxiety level had significant negative correlation with their sexual satisfaction level, whereas, anxiety and depression shared a significant positive correlation. There was a significant difference in the scores for sexual satisfaction, depression and anxiety for both cases and controls. These results suggested that women suffering from polycystic ovarian syndrome tend to be less sexually satisfied and experienced relatively more symptoms of depression and anxiety as compared to controls.

Keywords: level of sexual satisfaction, psychiatric morbidity, polycystic ovarian syndrome

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Authors: Riaan Kleyn

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Mass wine production companies across the globe are provided with grapes from winegrowers that predominantly utilize mechanical harvesting machines to harvest wine grapes. Mechanical harvesting accelerates the rate at which grapes are harvested, allowing grapes to be delivered faster to meet the demands of wine cellars. The disadvantage of the mechanical harvesting method is the inclusion of material-other-than-grapes (MOG) in the harvested wine grape loads arriving at the cellar which degrades the quality of wine that can be produced. Currently, wine cellars do not have a method to determine the amount of MOG present within wine grape loads. This paper seeks to find an optimal computer vision method capable of detecting the amount of MOG within a wine grape load. A MOG detection method will encourage winegrowers to deliver MOG-free wine grape loads to avoid penalties which will indirectly enhance the quality of the wine to be produced. Traditional image segmentation methods were compared to deep learning segmentation methods based on images of wine grape loads that were captured at a wine cellar. The Mask R-CNN model with a ResNet-50 convolutional neural network backbone emerged as the optimal method for this study to determine the amount of MOG in an image of a wine grape load. Furthermore, a statistical analysis was conducted to determine how the MOG on the surface of a grape load relates to the mass of MOG within the corresponding grape load.

Keywords: computer vision, wine grapes, machine learning, machine harvested grapes

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Authors: Rofida Gamal, Mostafa Mohammed, Mariam Adel, Marwa Gamal, Marwa kamal, Ayat Saber, Maha Mamdouh, Amira Emad, Mai Ramadan

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Lynch Syndrome is an inherited genetic condition associated with an increased risk of colorectal and other cancers. Detecting Lynch Syndrome in individuals is crucial for early intervention and preventive measures. This study proposes a computational pipeline for Lynch Syndrome detection by integrating alignment, variant calling, and annotation. The pipeline leverages popular tools such as FastQC, Trimmomatic, BWA, bcftools, and ANNOVAR to process the input FASTQ file, perform quality trimming, align reads to the reference genome, call variants, and annotate them. It is believed that the computational pipeline was applied to a dataset of Lynch Syndrome cases, and its performance was evaluated. It is believed that the quality check step ensured the integrity of the sequencing data, while the trimming process is thought to have removed low-quality bases and adaptors. In the alignment step, it is believed that the reads were accurately mapped to the reference genome, and the subsequent variant calling step is believed to have identified potential genetic variants. The annotation step is believed to have provided functional insights into the detected variants, including their effects on known Lynch Syndrome-associated genes. The results obtained from the pipeline revealed Lynch Syndrome-related positions in the genome, providing valuable information for further investigation and clinical decision-making. The pipeline's effectiveness was demonstrated through its ability to streamline the analysis workflow and identify potential genetic markers associated with Lynch Syndrome. It is believed that the computational pipeline presents a comprehensive and efficient approach to Lynch Syndrome detection, contributing to early diagnosis and intervention. The modularity and flexibility of the pipeline are believed to enable customization and adaptation to various datasets and research settings. Further optimization and validation are believed to be necessary to enhance performance and applicability across diverse populations.

Keywords: Lynch Syndrome, computational pipeline, alignment, variant calling, annotation, genetic markers

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Authors: Li Hui, Riyadh Hindi

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Concrete structures frequently suffer from crack formation, a critical issue that can significantly reduce their lifespan by allowing damaging agents to enter. Traditional methods of crack detection depend on manual visual inspections, which heavily relies on the experience and expertise of inspectors using tools. In this study, a more efficient, computer vision-based approach is introduced by using the lightweight MobileNetV2 neural network. A dataset of 40,000 images was used to develop a specialized crack evaluation algorithm. The analysis indicates that MobileNetV2 matches the accuracy of traditional CNN methods but is more efficient due to its smaller size, making it well-suited for mobile device applications. The effectiveness and reliability of this new method were validated through experimental testing, highlighting its potential as an automated solution for crack detection in concrete structures.

Keywords: Concrete crack, computer vision, deep learning, MobileNetV2 neural network

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Authors: Faezah Shekh Abdullah, Mohd. Azizuddin Mohd. Yussof, Komathy Thiagarajan, Hasnoorina Husin, Noor Azreena Abd Aziz

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Polycystic ovary syndrome has been associated with multiple disorders such as endocrine disorder, metabolic syndrome, infertility, and endometrial cancer. Women with polycystic ovary syndrome (PCOS) are anticipated to develop three times more chances for endometrial cancer than women without PCOS. This study, therefore, was conducted to determine the association between polycystic ovary syndrome and endometrial cancer and to determine the cervical cytology features of PCOS. Patients attending the Subfertility Clinic of the National Population and Family Development Board were recruited and examined physically by medical practitioners. They were categorized into two groups; i) the PCOS group if they met Rotterdam Criteria 2004 and ii) the control group if they did not meet Rotterdam Criteria 2004. Cervical sampling was done on all patients via the Liquid-Based Cytology (LBC) method in the pre-and post-subfertility treatment. A total of 167 patients participated in the study, of which 79 belonged to the PCOS group and 88 to the control group. The findings showed no cervical and endometrial cancer cases in both groups. The Liquid-Based Cytology results in the PCOS group displayed more cases with cellular changes, i.e., benign inflammation, atrophic smear and Candida sp. infection. To conclude, no association was found between polycystic ovary syndrome and endometrial cancer. A more holistic study with a higher number of participants can further determine the association between endometrial cancer and PCOS. Furthermore, a longer duration between LBC pre- and post-subfertility treatment should be implied to observe changes in the cervical cells.

Keywords: endometrial cancer, liquid-based cytology, PCOS, polycystic ovary syndrome

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Authors: D. R. Apoorva

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Ichthyosis follicularis, alopecia, and photophobia (IFAP) syndrome is a rare oculocutaneous disorder of genetic origin. This disorder results from mutations in the membrane-bound transcription factor protease site, two genes that impair cholesterol homeostasis, and the ability to cope with endoplasmic reticulum stress. We report a rare case of IFAP syndrome with an atypical presentation, and it was interesting to note that the child had patchy non-scarring alopecia over the scalp along with unilateral madarosis. To our best knowledge, this unique presentation has not been described earlier. The child presented with photophobia and unilateral ptosis. The child also had short stature and intellectual disability. Skin histopathology was nonspecific and consisted of dilated hair follicles with keratin plugs extending above the skin surface. This rare oculocutaneous disorder requires proper documentation so that identification of its variants may be possible in the future. Early recognition of atypical presentations can help in preventing cardiovascular complications, which remain the major cause of death.

Keywords: alopecia, photophobia, ichthyosis follicularis, IFAP syndrome

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Authors: Rajesh Kumar Suman, Ipseeta Ray Mohanty, Manjusha K. Borde, Ujjawala maheswari, Y. A. Deshmukh

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Background: Metabolic syndrome encompasses cluster of risk factors for cardiovascular disease which includes abdominal obesity, dyslipidemia, hypertension, and hyperglycemia. The incidence of metabolic syndrome is on the rise globally. Objective: The present study was designed to develop a unique animal model that will mimic the pathological features seen in a large pool of individuals with diabetes and metabolic syndrome; suitable for pharmacological screening of drugs beneficial in this condition. Material and Methods: A combination of high fat diet (HFD) and low dose of streptozotocin (STZ) at 30, 35 and 40 mg/kg was used to induce metabolic syndrome co-existing with diabetes mellitus in Wistar rats. Results: The 40 mg/kg STZ produced sustained hyperglycemia and the dose was thus selected for our study to induce diabetes mellitus. Rat fed HFD (HF-DC) group showed significant (p < 0.001) increase in body weight on 4th and 7th week as compared with NC (Normal Control) group rats. However, the increase in body weight of HF-DC group rats was not sustained at the end of 10th weeks. Various components of metabolic syndrome such as dyslipidemia {(Increased Triglyceride, total Cholesterol, LDL Cholesterol and decreased HDL Cholesterol)}, diabetes mellitus (Blood Glucose, HbA1c, Serum Insulin, C-peptide), hypertension {Systolic Blood pressure (p < 0.001)} were mimicked in the developed model of metabolic syndrome co existing with diabetes mellitus. In addition significant cardiac injury as indicated by CPK-MB levels, artherogenic index, hs-CRP. The decline in hepatic function {(p < 0.01) increase in the level of SGPT (U/L)} and renal function {(increase in creatinine levels (p < 0.01)} when compared to NC group rats. The histopathological assessment confirmed presence of edema, necrosis and inflammation in Heart, Pancreas, Liver and Kidney of HFD-DC group as compared to NC. Conclusion: The present study has developed a unique rodent model of metabolic syndrome; with diabetes as an essential component.

Keywords: diabetes, metabolic syndrome, high fat diet, streptozotocin, rats

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Authors: Yousef Alwashahi, Ahmed Almoqbali, Mayar Albahrani, Asma Alajmi

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We report a rare case of a 49-year-old Omani woman who is a known case of primary anti-phospholipid syndrome, glucose-6-phosphate dehydrogenase deficiency, and iron deficiency anaemia. During cannulation, she was found to develop bulla that progressed to ulcerations. With chronicity and recurrent abscess formation that usually increase after surgical intervention, a pathergy phenomenon was postulated. High suspicion of pyoderma gangrenosum was considered. Fortunately, the rapid progression of the disease was slowed down with corticosteroids, cyclosporin, and biological agents.

Keywords: anti-phospholipid syndrome, pyoderma gangrenosum, bullous pyoderma gangrenosum, pathergy, pathergy phenomenon

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Authors: Harshit Mittal, Neeraj Garg

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Hand symbol recognition is a pivotal component in the domain of computer vision, with far-reaching applications spanning sign language interpretation, human-computer interaction, and accessibility. This research paper discusses the approach with the integration of the Canny Edge algorithm and convolutional neural network. The significance of this study lies in its potential to enhance communication and accessibility for individuals with hearing impairments or those engaged in gesture-based interactions with technology. In the experiment mentioned, the data is manually collected by the authors from the webcam using Python codes, to increase the dataset augmentation, is applied to original images, which makes the model more compatible and advanced. Further, the dataset of about 6000 coloured images distributed equally in 5 classes (i.e., 1, 2, 3, 4, 5) are pre-processed first to gray images and then by the Canny Edge algorithm with threshold 1 and 2 as 150 each. After successful data building, this data is trained on the Convolutional Neural Network model, giving accuracy: 0.97834, precision: 0.97841, recall: 0.9783, and F1 score: 0.97832. For user purposes, a block of codes is built in Python to enable a window for hand symbol recognition. This research, at its core, seeks to advance the field of computer vision by providing an advanced perspective on hand sign recognition. By leveraging the capabilities of the Canny Edge algorithm and convolutional neural network, this study contributes to the ongoing efforts to create more accurate, efficient, and accessible solutions for individuals with diverse communication needs.

Keywords: hand symbol recognition, computer vision, Canny edge algorithm, convolutional neural network

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Authors: Riksa Parikrama, Bremmy Laksono, Dadang S. H. Effendi

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Disorder of sexual development (DSD) covers various conditions with a specific term such as Klinefelter syndrome, Turner syndrome, androgen insensitivity syndrome, and many more. The techniques to accurately diagnose those conditions has developed extensively. However, conventional karyotype and fluorescence in situ hybridization (FISH) are still widely used in many genetic laboratories as the basic method to determine chromosomal condition of DSD patients. Cytogenetic study was conducted on 36 DSD patients in Cell Culture and Cytogenetics Laboratory, Faculty of Medicine Universitas Padjadjaran, Indonesia. Most of the patients referred to the laboratory diagnosed with primary amenorrhea, hypospadias, micropenis, genitalia ambiguity, or congenital adrenal hyperplasia. The study used G-banding technique to acquire complete karyotype and followed by FISH as either confirmation or comparison method. Among 36 patients, G-banding karyotype and FISH results showed that two were diagnosed with 45, X (Turner syndrome); three with 47, XXY (Klinefelter syndrome); five with 46, XX DSD; 22 with 46, XY DSD; and four with 46,XY complete androgen insensitivity syndrome. G-banding karyotype analysis were paired with FISH using X and Y chromosome probe produced similar results. The present analysis showed that FISH is a reliable method to attain a rapid and accurate chromosome analysis result of DSD patients. Nevertheless, conventional karyotype technique is still vital if other condition appeared in DSD patients in order to get more detailed karyotype result which FISH method cannot achieve.

Keywords: chromosome, DSD, FISH, karyotype

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Authors: David J. Thomson, Joshua C. J. Chew

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Background: Syndrome of Irreversible Lithium-Effectuated Neurotoxicity (SILENT) is a rare complication of lithium toxicity that typically causes irreversible cerebellar dysfunction. These patients may require hemodialysis and extensive supports in the intensive care. Methods: A review was performed on the available literature of SILENT with a focus on current pathophysiological hypotheses and advances in treatment. Articles were restricted to the English language. Results: Although the exact mechanism is unclear, CNS demyelination, especially in the cerebellum, was seen on the brain biopsies of a proportion of patients. There is no definitive management of SILENT but instead current management is focused on primary and tertiary prevention – detection of those at risk, and rehabilitation post onset of neurological deficits. Conclusions: This review draws conclusions from a limited amount of available literature, most of which are isolated case reports. Greater awareness of SILENT and further investigation into the risk factors and pathogenesis are required so this serious and irreversible syndrome may be avoided.

Keywords: lithium toxicity, pathogenesis, SILENT, syndrome of irreversible lithium-effectuated neurotoxicity

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Authors: Neda Jamalimoghadam, Naval Heydari, Maliheh Abootalebi, Maryam Kasraeian, M. Emamghoreishi , Akbarzadeh Marzieh

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Background: The aim was to investigate the effect of aromatherapy using Citrus aurantium blossom essential oil on premenstrual syndrome in university students. Methods: In this double-blind clinical trial was controlled on 62 students from March 2016 to February 2017. The intervention with 0.5% of C. Aurantium blossom essential oil and control was inhalation of odorless sweet almond oil in the luteal phase of the menstrual cycle. The screening questionnaire (PSST) for PMSwas filled out before and also one and two months after the intervention. Results: Mean score of overall symptoms of PMS between the Bitter orange and control groups In the first (p < 0.003) and second months (p < 0.001) of the intervention was significant. Besides, decreased the mean score of psychological symptoms in the intervention group (p < 0.001), but on physical symptoms and social function were not significant (p > 0.05). Conclusion: The aromatherapy with Citrus aurantium blossom improved the symptoms of premenstrual syndrome.

Keywords: aromatherapy, Citrus Aurantium, premenstrual syndrome, oil, students

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Authors: Mohd Noah A. Rahman, Afzaal H. Seyal, Norhafilah Bara

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Developing a software application using an interface with computers and peripheral devices using gestures of human body such as hand movements keeps growing in interest. A review on this hand gesture detection and recognition based on computer vision technique remains a very challenging task. This is to provide more natural, innovative and sophisticated way of non-verbal communication, such as sign language, in human computer interaction. Nevertheless, this paper explores hand detection and hand gesture recognition applying a vision based approach. The hand detection and recognition used skin color spaces such as HSV and YCrCb are applied. However, there are limitations that are needed to be considered. Almost all of skin color space models are sensitive to quickly changing or mixed lighting circumstances. There are certain restrictions in order for the hand recognition to give better results such as the distance of user’s hand to the webcam and the posture and size of the hand.

Keywords: hand detection, hand gesture, hand recognition, sign language

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Authors: Sandip Tambare, Revati Ghadge

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Alcohol withdrawal syndrome continue to be concerning health issue worldwide in alcoholics. Many current option for treating alcohol withdrawal signs are habit forming causing dependency of sedatives. The divine science of Ayurveda recommends Nasya for improvement of alcohol withdrawal signs. As per the latest reports 1/3 of the Indian population is using alcohol in an unhealthy manner, the complication being wide and varied among which, the Alcohol Withdrawal Syndrome is the dominant one. The presentation varies from mild sleep loss or anxiety to delirium. Ayurveda has given utmost in the context of Madatyaya(Alcoholism). Various protocols based on the identification of the status of tridoshas are explained which includes sodhana, samana and satwavachaya chikitsa. Various medications are being used, with appreciated effects in the clinical practice. As per reports, the panchakarma procedure nasya seems highly effective, in managing of the alcohol withdrawal syndrome. Nasya with Ksheerabala Taila is given for 7 days in the condition of Alcohol Withdrawal syndrome and it was the non Randomized trial with 30 subjects satisfying the DSM V criteria for alcohol withdrawl and the assessment was done using the Clinical Institute Withdrawal Assessment for Alcohol Scale revised (CIWA-Ar). Conclusion: Among the symptoms which were studied after the interventions, it was found that there was high significant response in almost all the symptoms in the given subjects. The eternal science of Ayurveda is able to answer the existing problem of alcohol and its abuse in the society.

Keywords: nasya, alcohol withdrawal, madatyaya, ksheerabala taila

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Authors: Rabab A. El Wahsh, Hatem M. Marey, Maha Yousif, Asmaa M. Ibrahim

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Background: OSA and COPD are associated with microvascular changes. Retinal microvasculature can be directly and non-invasively examined. Aim: to evaluate retinal vascular tortuosity in patients with COPD, OSA, and overlap syndrome. Subjects and method: Sixty subjects were included; 15 OSA patients, 15 COPD patients, 15 COPD-OSA overlap patients, and 15 matched controls. They underwent digital retinal photography, polysomnography, arterial blood gases, spirometry, ESS, and stop-bang questionnaires. Results: Tortuosity of most retinal vessels was higher in all patient groups compared to the control group; tortuosity was more marked in overlap syndrome. There was a negative correlation between tortuosity of retinal vessels and PO2, O2 saturation, and minimum O2 desaturation, and a positive correlation with PCO2, AHI, O2 desaturation index, BMI and smoking index. Conclusion: Retinal vascular tortuosity occurs in OSA, COPD and overlap syndrome. Retinal vascular tortuosity is correlated with arterial blood gases parameters, polysomnographic findings, smoking index and BMI.

Keywords: OSA, COPD, overlap syndrome, retinal vascular tortuosity

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Authors: Marzieh Sayyad, Mohsen Salesi

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Metabolic syndrome (MetS), a collection of cardiometabolic risk factors, is linked to the development of cardiovascular disease (CVD) and diabetes. The prevalence of MetS is on the rise with more women affected than men. The goal of this study was to compare the effects of resistance and aerobic exercise training on metabolic syndrome components in non-athlete, middle-aged woman. 51 non-athlete overweight female participated voluntarily in this study. Participants were divided randomly into three groups including resistance, aerobic and control group (number of each group 17). 24 hours before the beginning of training program, the blood sample was taken in fasting state. The two training groups participated in sport activities for eight weeks, three times a week duration 60-90 minutes. Two days following the end of the 8th week, all the measurements were performed similar to the pretest phase. The data was analyzed using one-way analysis of variance. The results showed that aerobic exercise training significantly decreased weight (p=.05), triglyceride (p<0.01) and systolic blood pressure (p<0.02) and HDL-c (p<0.01) was significantly increased. Also in resistance exercise training group TG decreased significantly (p<0.01) and HDL-c (p<0.05) was significantly increased. This study demonstrated that a regular physical activity program improved several metabolic and physiological parameters in healthy, previously sedentary subjects with the metabolic syndrome. In conclusion, it seems that this type of training can be efficient, safe and inexpensive way in order to reduce and prevent metabolic syndrome.

Keywords: aerobic exercise, metabolic syndrome, overweight sedentary female, resistance exercise

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Authors: Sheldon McCall, Miao Yu, Liyun Gong, Shigang Yue, Stefanos Kollias

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Falls are a significant health concern for older adults globally, and prompt identification is critical to providing necessary healthcare support. Our study proposes a new fall detection method using computer vision based on modern deep learning techniques. Our approach involves training a trans- former model on a large 2D pose dataset for general action recognition, followed by transfer learning. Specifically, we freeze the first few layers of the trained transformer model and train only the last two layers for fall detection. Our experimental results demonstrate that our proposed method outperforms both classical machine learning and deep learning approaches in fall/non-fall classification. Overall, our study suggests that our proposed methodology could be a valuable tool for identifying falls.

Keywords: healthcare, fall detection, transformer, transfer learning

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Authors: Shaik Jilani Basha, Inavolu Avinash, Alla Venu Sai Reddy, Bitragunta Taraka Ramu

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We can use the neural style transfer technique to build a picture with the same "content" as the beginning image but the "style" of the picture we've chosen. Neural style transfer is a technique for merging the style of one image into another while retaining its original information. The only change is how the image is formatted to give it an additional artistic sense. The content image depicts the plan or drawing, as well as the colors of the drawing or paintings used to portray the style. It is a computer vision programme that learns and processes images through deep convolutional neural networks. To implement software, we used to train deep learning models with the train data, and whenever a user takes an image and a styled image, the output will be as the style gets transferred to the original image, and it will be shown as the output.

Keywords: neural networks, computer vision, deep learning, convolutional neural networks

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Authors: Kazem Shakouri, Alireza Pishgahi, Homayoun Sadeghi-bBazargani, Shahla Dareshiri

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Introduction: Carpal Tunnel Syndrome has numerous nonsurgical treatments including splint, physical therapy and corticosteroid injections. Aim: The purpose of this study was to evaluate the effectiveness of an ultrasound guided treatment procedure, for individuals with severe carpal tunnel syndrome. Materials and Method: 20 patients with an electrodiagnostic evidence of severe carpal tunnel syndrome were treated by an office-based ultrasound guided procedure (combination of percutaneous needle release of carpal tunnel and corticosteroid injection). Electrodiagnostic (nerve conduction study), clinical (Boston Carpal Tunnel Questionnaire, grip strength) and ultrasonic (median nerve and carpal tunnel cross-sectional area) measurements were recorded at baseline and one month after intervention. Results: Our preliminary data analysis showed that in one month follow up, patients had a significantly smaller cross-sectional area of the median nerve compared to pretreatment values (mean difference 0.06; 95%CI: 0.02-0.1; p < 0.001). In addition, patients had significantly less functional impairment (mean difference 35; 95% CI:28.7-43.4 ; p < 0.001), and an improved hand grip strength in one month follow up (mean difference 5.4; 95%CI: 3.1-7.8; p < 0.001;). There were no significant complications. Conclusion: Patients with severe carpal tunnel syndrome, who are candidates for surgical intervention, can consider office-based ultrasound guided needle release of carpal tunnel as an alternative safe treatment.

Keywords: Carpal Tunnel Syndrome, needle release, pain, ultrasound

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Authors: Ksheeraj Sai Vepuri, Nada Attar

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We as humans use words with accompanying visual and facial cues to communicate effectively. Classifying facial emotion using computer vision methodologies has been an active research area in the computer vision field. In this paper, we propose a simple method for facial expression recognition that enhances accuracy. We tested our method on the FER-2013 dataset that contains static images. Instead of using Histogram equalization to preprocess the dataset, we used Unsharp Mask to emphasize texture and details and sharpened the edges. We also used ImageDataGenerator from Keras library for data augmentation. Then we used Convolutional Neural Networks (CNN) model to classify the images into 7 different facial expressions, yielding an accuracy of 69.46% on the test set. Our results show that using image preprocessing such as the sharpening technique for a CNN model can improve the performance, even when the CNN model is relatively simple.

Keywords: facial expression recognittion, image preprocessing, deep learning, CNN

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Authors: Behnaz Sohani, Ifeoluwa Joshua Adigun, Amir Rahmani, Khaled Goher

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This paper provides initial results on the efficacy of the designed ergonomic-oriented neck support to mitigate and alleviate tension neck syndrome musculoskeletal disorder. This is done using both simulations and measurements. Tension Neck Syndrome Musculoskeletal Disorder (TNS MSD) causes discomfort in the muscles around the neck and shoulder. TNS MSD is one of the leading causes of early retirement. This research focuses on the design of an adaptive neck supporter by integrating a soft actuator massager to help deliver a soothing massage. The massager and adaptive neck supporter prototype were validated by finite element analysis prior to fabrication to envisage the feasibility of the design concept. Then a prototype for the massager was fabricated and tested for concept validation. Future work will be focused on fabricating the full-scale prototype and upgrading and optimizing the design concept for the adaptive neck supporter.

Keywords: adaptive neck supporter, tension neck syndrome, musculoskeletal disorder, soft actuator massager, soft robotics

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Authors: C. Vázquez, L. M. Gigirey, C. P. del Oro, S. Seoane

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Early detection of visual problems plays a key role in the aging process. However, although vision problems are common among older people, the percentage of aging people who perform regular optometric exams is low. In fact, uncorrected refractive errors are one of the main causes of visual impairment in this group of the population. Purpose: To evaluate functional vision of older residents in order to show the urgent need of visual screening programs in Galician nursing homes. Methodology: We examined 364 older adults aged 65 years and over. To measure vision of the daily living, we tested distance and near presenting visual acuity (binocular visual acuity with habitual correction if warn, directional E-Snellen) Presenting near vision was tested at the usual working distance. We defined visual impairment (distance and near) as a presenting visual acuity less than 0.3. Exclusion criteria included immobilized residents unable to reach the USC Dual Sensory Loss Unit for visual screening. Association between categorical variables was performed using chi-square tests. We used Pearson and Spearman correlation tests and the variance analysis to determine differences between groups of interest. Results: 23,1% of participants have visual impairment for distance vision and 16,4% for near vision. The percentage of residents with far and near visual impairment reaches 8,2%. As expected, prevalence of visual impairment increases with age. No differences exist with regard to the level of functional vision between gender. Differences exist between age group respect to distance vision, but not in case of near vision. Conclusion: prevalence of visual impairment is high among the older people tested in this pilot study. This means a high percentage of older people with limitations in their daily life activities. It is necessary to develop an effective vision screening program for early detection of vision problems in Galician nursing homes.

Keywords: functional vision, elders, aging, nursing homes

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Authors: Juan Sebastian Huertas Piedrahita, Jaime Arturo Lopez Duque, Eduardo Luis Perez Londoño, Julián S. Rodríguez

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The process of generating computer vision is called artificial vision. The artificial vision is a branch of artificial intelligence that allows the obtaining, processing, and analysis of any type of information especially the ones obtained through digital images. Actually the artificial vision is used in manufacturing areas for quality control and production, as these processes can be realized through counting algorithms, positioning, and recognition of objects that can be measured by a single camera (or more). On the other hand, the companies use assembly lines formed by conveyor systems with actuators on them for moving pieces from one location to another in their production. These devices must be previously programmed for their good performance and must have a programmed logic routine. Nowadays the production is the main target of every industry, quality, and the fast elaboration of the different stages and processes in the chain of production of any product or service being offered. The principal base of this project is to program a computer that recognizes geometric figures (circle, square, and triangle) through a camera, each one with a different color and link it with a group of conveyor systems to organize the mentioned figures in cubicles, which differ from one another also by having different colors. This project bases on artificial vision, therefore the methodology needed to develop this project must be strict, this one is detailed below: 1. Methodology: 1.1 The software used in this project is QT Creator which is linked with Open CV libraries. Together, these tools perform to realize the respective program to identify colors and forms directly from the camera to the computer. 1.2 Imagery acquisition: To start using the libraries of Open CV is necessary to acquire images, which can be captured by a computer’s web camera or a different specialized camera. 1.3 The recognition of RGB colors is realized by code, crossing the matrices of the captured images and comparing pixels, identifying the primary colors which are red, green, and blue. 1.4 To detect forms it is necessary to realize the segmentation of the images, so the first step is converting the image from RGB to grayscale, to work with the dark tones of the image, then the image is binarized which means having the figure of the image in a white tone with a black background. Finally, we find the contours of the figure in the image to detect the quantity of edges to identify which figure it is. 1.5 After the color and figure have been identified, the program links with the conveyor systems, which through the actuators will classify the figures in their respective cubicles. Conclusions: The Open CV library is a useful tool for projects in which an interface between a computer and the environment is required since the camera obtains external characteristics and realizes any process. With the program for this project any type of assembly line can be optimized because images from the environment can be obtained and the process would be more accurate.

Keywords: artificial intelligence, artificial vision, binarized, grayscale, images, RGB

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Authors: Esther Moraleda Sepúlveda, Soraya Delgado Matute, Paula Salido Escudero, Raquel Mimoso García, M Cristina Alcón Lancho

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Although there is some consensus when it comes to establishing the lexicon as one of the strengths of language in people with Down Syndrome (DS), little is known about its evolution throughout development and changes based on age. The objective of this study was to find out if there are differences in receptive vocabulary between adolescence and adulthood. In this research, 30 people with DS between 11 and 40 years old, divided into two age ranges (11-18; 19 - 30) and matched in mental age, were evaluated through the Peabody Vocabulary Test. The results show significant differences between both groups in favor of the group with the oldest chronological age and a direct correlation between chronological age and receptive vocabulary development, regardless of mental age. These data support the natural evolution of the passive lexicon in people with DS.

Keywords: down syndrome, language, receptive vocabulary, adolescents, adults

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Authors: Hamna Choudhary

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Background: This clinical case report follows the orthodontic journey of a teenage girl being treated in the Oxfordshire Community Dental Service. She presents with a rare genetic disorder – Moebius syndrome – characterised by unilateral or bilateral facial (CN VII) and abducens (CN VI) nerve palsy. This report seeks to educate Dental professionals on the impact of Moebius syndrome on Dental treatment, and how to make reasonable adjustments to make orthodontic care accessible to these patients. Methodology: Moebius syndrome is a very rare genetic disorder. Across the Oxfordshire Community Dental Service, only two patients with this condition have been identified who are undergoing orthodontic treatment. One of these patients was selected and observed, while the orthodontist (Heather Nevard) was providing orthodontic treatment with fixed appliances. The patient is undergoing treatment to correct her class II division 2 incisor relationship complicated by buccally excluded, transposed maxillary canines. Conclusions: Specific oral presentations of Moebius syndrome include microstomia, micrognathia, tongue malformation, high or cleft palate, bifid uvula and Dental malocclusion. Orthodontics plays a major role in managing and correcting many of these conditions. This emphasises the importance for Dental professionals to be informed on the condition and highlights the need for Dental input in multidisciplinary teams responsible for the care of these patients. Receiving corrective treatment has a significant impact on an individual’s quality of life. In this case, the patient felt much more confident in herself, and having aligned teeth will allow her to better maintain a healthy dentition throughout life. By understanding and educating oneself on Moebius syndrome, one is able to better cater to patient needs and make orthodontic treatment accessible.

Keywords: dentistry, facial palsy, moebius syndrome, orthodontics

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Authors: Ayca Bilginoglu, Belma Turan

Abstract:

Metabolic syndrome, is associated impaired blood glucose level, insulin resistance, dyslipidemia caused by abdominal obesity. Also, it is related with cardiovascular risk accumulation and cardiomyopathy. The hypothesis of this study was to examine the effect of thiazolidinediones such as pioglitazone which is widely used insulin-sensitizing agents that improve glycemic control, on intracellular Na+ homeostasis in metabolic syndrome-induced cardiomyopathy in male rats. Male Wistar-Albino rats were randomly divided into three groups, namely control (Con, n=7), metabolic syndrome (MetS, n=7) and pioglitazone treated metabolic syndrome group (MetS+PGZ, n=7). Metabolic syndrome was induced by providing drinking water that was 32% sucrose, for 18 weeks. All of the animals were exposed to a 12 h light – 12 h dark cycle. Abdominal obesity and glucose intolerance had measured as a marker of metabolic syndrome. Intracellular Na+ ([Na+]i) is an important modulator of excitation–contraction coupling in heart. [Na+]i at rest and [Na+]i during pacing with electrical field stimulation in 0.2 Hz, 0.8 Hz, 2.0 Hz stimulation frequency were recorded in cardiomyocytes. Also, Na+ channel current (INa) density and I-V curve were measured to understand [Na+]i homeostasis. In results, high sucrose intake, as well as the normal daily diet, significantly increased body mass and blood glucose level of the rats in the metabolic syndrome group as compared with the non-treated control group. In MetS+PZG group, the blood glucose level and body inclined to decrease to the Con group. There was a decrease in INa density and there was a shift both activation and inactivation curve of INa. Pioglitazone reversed the shift to the control side. Basal [Na+]i either MetS and Con group were not significantly different, but there was a significantly increase in [Na+]i in stimulated cardiomyocytes in MetS group. Furthermore, pioglitazone had not effect on basal [Na+]i but it reversed the increase in [Na+]i in stimulated cardiomyocytes to the that of Con group. Results of the present study suggest that pioglitazone has a significant effect on the Na+ homeostasis in the metabolic syndrome induced cardiomyopathy in rats. All animal procedures and experiments were approved by the Animal Ethics Committee of Ankara University Faculty of Medicine (2015-2-37).

Keywords: insulin resistance, intracellular sodium, metabolic syndrome, sodium current

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Authors: Maha Salah, Hanaa Hashem, Mahmoud M. Alsagheir, Mohammed Salah

Abstract:

Acute respiratory distress syndrome (ARDS) represents a complex clinical syndrome and carries a high risk for mortality. The severity of the clinical course, the uncertainty of the outcome, and the reliance on the full spectrum of critical care resources for treatment mean that the entire health care team is challenged. Researchers and clinicians have investigated the nature of the pathological process and explored treatment options with the goal of improving outcome. Through this application of research to practice, we know that some previous strategies have been ineffective, and innovations in mechanical ventilation, sedation, nutrition, and pharmacological intervention remain important research initiatives. Developed Clinical pathway is multidisciplinary plans of best clinical practice for this specified groups of patients that aid in the coordination and delivery of high quality care. They are a documented sequence of clinical interventions that help a patient to move, progressively through a clinical experience to a desired outcome. Although there is a lot of heterogeneity in patients with ARDS, this suggested developed clinical pathway with alternatives was built depended on a lot of researches and evidence based medicine and nursing practices which may be helping these patients to improve outcomes, quality of life and decrease mortality.

Keywords: acute respiratory distress syndrome (ARDS), clinical pathway, clinical syndrome

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Authors: Jennifer M. Glennon, Hana D'Souza, Luke Mason, Annette Karmiloff-Smith, Michael S. C. Thomas

Abstract:

Genetic syndrome groups that feature high rates of autism comorbidity, like Down syndrome (DS) and fragile X syndrome (FXS), have been presented as useful models for understanding risk and protective factors involved in the emergence of autistic traits. Yet despite reaching clinical thresholds, these ‘syndromic’ forms of autism appear to differ in important ways from the idiopathic or ‘non-syndromic’ autism phenotype. To uncover the true nature of these comorbidities, it is necessary to extend definitions of autism to include the cognitive characteristics of the disorder and to then apply this broadened conceptualisation to the study of syndromic autism profiles. The current study employs a variety of well-established eye-tracking paradigms to assess visual attentional performance in children with DS and FXS who reach thresholds for autism on the Social Communication Questionnaire. It investigates whether autism profiles in these children are accompanied by visual orienting difficulties (‘sticky attention’), decreased social attention, and enhanced visual search performance, all of which are characteristic of the idiopathic autism phenotype. Data is collected from children with DS and FXS aged between 6 and 10 years, in addition to two control groups matched on age and intellectual ability (i.e., children with idiopathic autism and neurotypical controls). Cross-sectional developmental trajectory analyses are conducted to enable visuo-attentional profile comparisons. Significant differences in the visuo-attentional processes underpinning autism presentations in children with FXS and DS are hypothesised, supporting notions of syndrome specificity. The study provides insight into the complex heterogeneity associated with syndromic autism presentations and autism per se, with clinical implications for the utility of autism intervention programmes in DS and FXS populations.

Keywords: autism, down syndrome, fragile X syndrome, eye tracking

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Authors: Farah Al Zaabi, Sarah Amrani

Abstract:

Complex regional pain syndrome (CRPS) is a chronic pain condition that develops in an extremity following a fracture, soft tissue injury, or surgery. It is a neuropathic pain disorder that is accompanied by the characteristic skin manifestations that are needed for the diagnosis. We report the case of a 30 year old male, who has findings consistent with CRPS and has been followed for over two years by multiple specialties within the healthcare system without obtaining a diagnosis. The symptoms he presented with were treated based on the specialty he was seeing, rather than unified and recognized as a single disease process. Our case highlights the complexity of chronic pain, which can sometimes present with skin manifestations, and the importance of involving a pain specialist early for both the medical and physical recovery of CRPS patients.

Keywords: complex regional pain syndrome, chronic pain, skin changes of CRPS, dermatological manifestions of CRPS

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Authors: Revoti Prasad Bora, Saurabh Yadav, Nikita Katyal

Abstract:

In the context of educational data mining, the use case of extracting information from images containing both text and diagrams is of high importance. Hence, document analysis requires the extraction of diagrams from such images and processes the text and diagrams separately. To the author’s best knowledge, none among plenty of approaches for extracting tables, figures, etc., suffice the need for real-time processing with high accuracy as needed in multiple applications. In the education domain, diagrams can be of varied characteristics viz. line-based i.e. geometric diagrams, chemical bonds, mathematical formulas, etc. There are two broad categories of approaches that try to solve similar problems viz. traditional computer vision based approaches and deep learning approaches. The traditional computer vision based approaches mainly leverage connected components and distance transform based processing and hence perform well in very limited scenarios. The existing deep learning approaches either leverage YOLO or faster-RCNN architectures. These approaches suffer from a performance-accuracy tradeoff. This paper proposes a U-Net based architecture that formulates the diagram extraction as a segmentation problem. The proposed method provides similar accuracy with a much faster extraction time as compared to the mentioned state-of-the-art approaches. Further, the segmentation mask in this approach allows the extraction of diagrams of irregular shapes.

Keywords: computer vision, deep-learning, educational data mining, faster-RCNN, figure extraction, image segmentation, real-time document analysis, text extraction, U-Net, YOLO

Procedia PDF Downloads 109