Search results for: ANOVA score model
Commenced in January 2007
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Edition: International
Paper Count: 18817

Search results for: ANOVA score model

18427 DenseNet and Autoencoder Architecture for COVID-19 Chest X-Ray Image Classification and Improved U-Net Lung X-Ray Segmentation

Authors: Jonathan Gong

Abstract:

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

Keywords: artificial intelligence, convolutional neural networks, deep learning, image processing, machine learning

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18426 Quality of Life among Female Sex Workers of Selected Organization of Pokhara: A Methodological Triangulation

Authors: Sharmila Dahal Paudel

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Background: There are around twenty-four thousand to twenty-eight thousand Female Sex Workers in Nepal. FSWs are the vulnerable groups for sexually transmitted infections (STIs) and human immunodeficiency virus (HIV) infections which directly and indirectly ease to reduce the quality of life of such groups. Due to their highly marginalized status, FSWs in Nepal have limited access to information about reproductive health and safe sex practices. The objectives of the study are to assess the quality of life of female sex workers and the factors affecting them. Materials and Methods: A descriptive cross-sectional study with methodological triangulation was conducted among 108 FSWs on the basis of service record of selected organization of Pokhara valley. The complete enumerative sampling was used to select FSWs. Structured interview schedule, WHOQOL-BREF and in-depth questionnaire were used to collect the data. The descriptive and inferential statistics were used to interpret the result. Results: The mean age of participants were 23.44 years and the mean quality of life score was 174.06 ranging from 56.54 to 370.78. Among the domain scores, the mean score is highest in social domain (55.89) followed by physical (45.42), psychological (39.27) and the environmental (34.23). Regarding the association of QOL with socio-demographic, occupation and health-related variables, the multi-linear regression suggests that the satisfaction with occupation was highly significant with the total QOL score (B=-50.50, SE=10.46; p= <0.001) and there is negative relation between QOL and feeling of exploitation and facing STI problems. This means those who feels exploited have significantly less QOL comparing with those who did not feel the same. In correlation analysis, all the domains are positively co-related with each domain which is found to be significant at 1% level of significance. Conclusion: The highest mean score was in social domain, and the lowest is in environmental domain which suggests that the items included in environmental domains could not be utilized or hindrance were there.

Keywords: FSWs, HIV, QOL, WHOQOL-BREF

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18425 Anxiety and Depression in Caregivers of Autistic Children

Authors: Mou Juliet Rebeiro, S. M. Abul Kalam Azad

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This study was carried out to see the anxiety and depression in caregivers of autistic children. The objectives of the research were to assess depression and anxiety among caregivers of autistic children and to find out the experience of caregivers. For this purpose, the research was conducted on a sample of 39 caregivers of autistic children. Participants were taken from a special school. To collect data for this study each of the caregivers were administered questionnaire comprising scales to measure anxiety and depression and some responses of the participants were taken through interview based on a topic guide. Obtained quantitative data were analyzed by using statistical analysis and qualitative data were analyzed according to themes. Mean of the anxiety score (55.85) and depression score (108.33) is above the cutoff point. Results showed that anxiety and depression is clinically present in caregivers of autistic children. Most of the caregivers experienced behavior, emotional, cognitive and social problems of their child that is linked with anxiety and depression.

Keywords: anxiety, autism, caregiver, depression

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18424 Impact of Customer Experience Quality on Loyalty of Mobile and Fixed Broadband Services: Case Study of Telecom Egypt Group

Authors: Nawal Alawad, Passent Ibrahim Tantawi, Mohamed Abdel Salam Ragheb

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Providing customers with quality experiences has been confirmed to be a sustainable, competitive advantage with a distinct financial impact for companies. The success of service providers now relies on their ability to provide customer-centric services. The importance of perceived service quality and customer experience is widely recognized. The focus of this research is in the area of mobile and fixed broadband services. This study is of dual importance both academically and practically. Academically, this research applies a new model investigating the impact of customer experience quality on loyalty based on modifying the multiple-item scale for measuring customers’ service experience in a new area and did not depend on the traditional models. The integrated scale embraces four dimensions: service experience, outcome focus, moments of truth and peace of mind. In addition, it gives a scientific explanation for this relationship so this research fill the gap in such relations in which no one correlate or give explanations for these relations before using such integrated model and this is the first time to apply such modified and integrated new model in telecom field. Practically, this research gives insights to marketers and practitioners to improve customer loyalty through evolving the experience quality of broadband customers which is interpreted to suggested outcomes: purchase, commitment, repeat purchase and word-of-mouth, this approach is one of the emerging topics in service marketing. Data were collected through 412 questionnaires and analyzed by using structural equation modeling.Findings revealed that both outcome focus and moments of truth have a significant impact on loyalty while both service experience and peace of mind have insignificant impact on loyalty.In addition, it was found that 72% of the variation occurring in loyalty is explained by the model. The researcher also measured the net prompters score and gave explanation for the results. Furthermore, assessed customer’s priorities of broadband services. The researcher recommends that the findings of this research will extend to be considered in the future plans of Telecom Egypt Group. In addition, to be applied in the same industry especially in the developing countries that have the same circumstances with similar service settings. This research is a positive contribution in service marketing, particularly in telecom industry for making marketing more reliable as managers can relate investments in service experience directly with the performance closest to income for instance, repurchasing behavior, positive word of mouth and, commitment. Finally, the researcher recommends that future studies should consider this model to explain significant marketing outcomes such as share of wallet and ultimately profitability.

Keywords: broadband services, customer experience quality, loyalty, net promoters score

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18423 Development of Creatively Integrated Teaching Skills Using Information and Communication Technology for Professional Teacher

Authors: Siwanit Autthawuttikul, Prakob Koraneekid, Sayamon Insa-ard

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The purposes of this research were to development creatively integrated teaching skills using Information and Communication Technology (ICT) for professional teacher in schools under the education area of the basic education commission, ministry of education both schools under the office of primary education and those under The office of secondary education in eight western region provinces of Thailand. This is useful in defining a vision for the school strategy and restructuring schools in addition, teachers will have developed skills in teaching creative integrated ICT. The research methodology comprises quantitative and qualitative data collection. The Baseline Survey, focus group for discussions and then the model was developed creatively integrated teaching skills using ICT. The findings showed that 7 elements were important: (1) Academy Transformation (2) Information Technology Infrastructure (3) Personal Development (4) Supervision, Monitoring and Evaluation (5) Motivating and Rewarding (6) Important factor affecting the success of teaching integrated with ICT were knowledge, skills, attitudes and (7) The role of the individual concerned. The comparison creatively integrated teaching skills before and after participating in the overall shows that the average creatively integrated teaching skills using ICT after attending the event is 3.27, and standard deviation was 0.56, higher than before which is 2.60 and the standard deviation was 0.56. There are significant differences significant statistically level of .05. The final average score of the evaluation plan design creatively integrated teaching skills using ICT teachers' average score was 26.94 at the high levels.

Keywords: integrated curriculum, information and communications technology, teachers in the western region, schools

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18422 Social Enterprise Concept in Sustaining Agro-Industry Development in Indonesia: Case Study of Yourgood Social Business

Authors: Koko Iwan Agus Kurniawan, Dwi Purnomo, Anas Bunyamin, Arif Rahman Jaya

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Fruters model is a concept of technopreneurship-based on empowerment, in which technology research results were designed to create high value-added products and implemented as a locomotive of collaborative empowerment; thereby, the impact was widely spread. This model still needs to be inventoried and validated concerning the influenced variables in the business growth process. Model validation accompanied by mapping was required to be applicable to Small Medium Enterprises (SMEs) agro-industry based on sustainable social business and existing real cases. This research explained the empowerment model of Yourgood, an SME, which emphasized on empowering the farmers/ breeders in farmers in rural areas, Cipageran, Cimahi, to housewives in urban areas, Bandung, West Java, Indonesia. This research reviewed some works of literature discussing the agro-industrial development associated with the empowerment and social business process and gained a unique business model picture with the social business platform as well. Through the mapped business model, there were several advantages such as technology acquisition, independence, capital generation, good investment growth, strengthening of collaboration, and improvement of social impacts that can be replicated on other businesses. This research used analytical-descriptive research method consisting of qualitative analysis with design thinking approach and that of quantitative with the AHP (Analytical Hierarchy Process). Based on the results, the development of the enterprise’s process was highly affected by supplying farmers with the score of 0.248 out of 1, being the most valuable for the existence of the enterprise. It was followed by university (0.178), supplying farmers (0.153), business actors (0.128), government (0.100), distributor (0.092), techno-preneurship laboratory (0.069), banking (0.033), and Non-Government Organization (NGO) (0.031).

Keywords: agro-industry, small medium enterprises, empowerment, design thinking, AHP, business model canvas, social business

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18421 A Sustainable Supplier Selection and Order Allocation Based on Manufacturing Processes and Product Tolerances: A Multi-Criteria Decision Making and Multi-Objective Optimization Approach

Authors: Ravi Patel, Krishna K. Krishnan

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In global supply chains, appropriate and sustainable suppliers play a vital role in supply chain development and feasibility. In a larger organization with huge number of suppliers, it is necessary to divide suppliers based on their past history of quality and delivery of each product category. Since performance of any organization widely depends on their suppliers, well evaluated selection criteria and decision-making models lead to improved supplier assessment and development. In this paper, SCOR® performance evaluation approach and ISO standards are used to determine selection criteria for better utilization of supplier assessment by using hybrid model of Analytic Hierchchy Problem (AHP) and Fuzzy Techniques for Order Preference by Similarity to Ideal Solution (FTOPSIS). AHP is used to determine the global weightage of criteria which helps TOPSIS to get supplier score by using triangular fuzzy set theory. Both qualitative and quantitative criteria are taken into consideration for the proposed model. In addition, a multi-product and multi-time period model is selected for order allocation. The optimization model integrates multi-objective integer linear programming (MOILP) for order allocation and a hybrid approach for supplier selection. The proposed MOILP model optimizes order allocation based on manufacturing process and product tolerances as per manufacturer’s requirement for quality product. The integrated model and solution approach are tested to find optimized solutions for different scenario. The detailed analysis shows the superiority of proposed model over other solutions which considered individual decision making models.

Keywords: AHP, fuzzy set theory, multi-criteria decision making, multi-objective integer linear programming, TOPSIS

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18420 Influence of Age and Religion on Sexual Behaviours of Undergraduates in Southwest, Nigeria

Authors: Tosin Emmanuel Akinduyo, F. O. Ojewola

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This study investigated the influence of age and religion on the sexual behaviours of undergraduates in southwest Nigeria. The aim of this study is to examine the sexual behaviour of undergraduates based on moderating variables of age and religion. The research design was a descriptive research design of the survey type. The sample for the study was 1,200 undergraduates selected through a multi-stage sampling procedure. A self-constructed questionnaire titled “Sexual Behaviours Questionnaire” (SBCUQ) with Pearson reliability (r) of 0.68 was used to elicit information from the respondents. Two research questions were answered using frequency count, percentage, means, and standard deviation. The two hypotheses were tested using t-test and ANOVA. Where the result of ANOVA showed a significant difference, the Scheffe Posthoc test was used to show where the significant difference (s) occurred. The findings of the study revealed that age and religion influenced undergraduates’ sexual behaviour. Based on the findings, the government at all tiers, in collaboration with the university management, should introduce sex education as a course to enlighten undergraduates and inform them of moderation needed as expected in their sexual expressions. Professional counsellors and religious organizations should always line up seminars and workshops for undergraduates on acceptable engagement in their sexual behaviours.

Keywords: age, religion, sexual behaviuors, undergraduates

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18419 Dietary Diversity and Nutritional Status of Adolescents Attending Public Secondary Schools in Oyo State Nigeria

Authors: Nimot Opeyemi Wahab

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Poor nutritional status during adolescence is a reflection of inadequate intake of nutrients. This can also be associated with a lack of consumption of diverse food. This study assessed the nutritional status and dietary diversity score (DDS) of in-school adolescents in Ibadan North, North East, and Ibadan South West Local Government Areas (LGA) of Oyo State, Nigeria. A cross-sectional study involving 3,510 in-school adolescents from the three LGA was conducted. Nutrient intake was measured using a validated 24-hour dietary recall, and the anthropometric measurement was also taken. Dietary diversity score (DDS) was assessed using the Individual Dietary Diversity Score (WDDS) of nine food groups. Participants were between 10-19years, and the mean age was 14.76±1.68, 15.32±1.77, and 15.45±1.62 in Ibadan North, Ibadan North East, and Ibadan South West, respectively. About 48% of the participants were male (47.9%), while 52.1% were female. BMI-for-age showed that 92.1%, 5.4%, 2.1%, and 0.4% of the participants were normal, underweight, overweight, and obese, respectively. The mean energy intake (143.193±695.98) of the female respondents was more than that of the male respondents (1406.86±767.41). The macronutrients intake (protein, carbohydrates, fiber, and fats) of the female participants was also found to be more than that of the male participants, with a non-significant difference of 0.336, 0.530, 0.234, and 0.069 (at p< 0.05). Out of all the vitamin intake, only vitamin C was found to be statistically different (p=0.038) at p<0.05 between the male and female respondents. Of all the mineral intake, only phosphorus showed a higher intake (575.20±362.12) among female respondents than the male respondents. The mean DDS of all participants was 4.59±0.939. The majority of the participants, 1183 (80.9%), were within the medium DDS category, 9.9% were low, while 1.5% were in the high category: of which males were 474 (71.5%) and females were 709 (88.6%). Participants from Ibadan North were 941(88.5%), and those from South West were 242(60.5%). A non-significant difference in the mean score of participants from the two locations (p=0.467) was also found. A negative correlation exists between DDS and BMI-for age (-0.11), DDS, and energy intake (-0.46) in Ibadan North and South West LGA. The nutritional status of in-school adolescents was normal, and DDS was within the medium category. Nutrition intervention regarding the consumption of diverse food is necessary among adolescents.

Keywords: nutritional status, dietary diversity, adolescents, nutrient intake

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18418 Health Belief Model to Predict Sharps Injuries among Health Care Workers at First Level Care Facilities in Rural Pakistan

Authors: Mohammad Tahir Yousafzai, Amna Rehana Siddiqui, Naveed Zafar Janjua

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We assessed the frequency and predictors of sharp injuries (SIs) among health care workers (HCWs) at first level care facilities (FLCF) in rural Pakistan. HCWs working at public clinic (PC), privately owned licensed practitioners’ clinic (LPC) and non-licensed practitioners’ clinic (NLC) were interviewed on universal precautions (UPs) and constructs of health belief model (HBM) to assess their association with SIs through negative-binomial regression. From 365 clinics, 485 HCWs were interviewed. Overall annual rate of Sis was 192/100 HCWs/year; 78/100 HCWs among licensed prescribers, 191/100 HCWs among non-licensed prescribers, 248/100 HCWs among qualified assistants, and 321/100 HCWs among non-qualified assistants. Increasing knowledge score about bloodborne pathogens (BBPs) transmission (rate-ratio (RR): 0.93; 95%CI: 0.89–0.96), fewer years of work experience, being a non-licensed prescriber (RR: 2.02; 95%CI: 1.36–2.98) licensed (RR: 2.86; 9%CI: 1.81–4.51) or non-licensed assistant (RR: 2.78; 95%CI: 1.72–4.47) compared to a licensed prescriber, perceived barriers (RR: 1.06;95%CI: 1.03–1.08), and compliance with UPs scores (RR: 0.93; 95%CI: 0.87–0.97) were significant predictors of SIs. Improved knowledge about BBPs, compliance with UPs and reduced barriers to follow UPs could reduce SIs to HCWs.

Keywords: health belief model, sharp injuries, needle stick injuries, healthcare workers

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18417 Large Language Model Powered Chatbots Need End-to-End Benchmarks

Authors: Debarag Banerjee, Pooja Singh, Arjun Avadhanam, Saksham Srivastava

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Autonomous conversational agents, i.e., chatbots, are becoming an increasingly common mechanism for enterprises to provide support to customers and partners. In order to rate chatbots, especially ones powered by Generative AI tools like Large Language Models (LLMs), we need to be able to accurately assess their performance. This is where chatbot benchmarking becomes important. In this paper, authors propose the use of a benchmark that they call the E2E (End to End) benchmark and show how the E2E benchmark can be used to evaluate the accuracy and usefulness of the answers provided by chatbots, especially ones powered by LLMs. The authors evaluate an example chatbot at different levels of sophistication based on both our E2E benchmark as well as other available metrics commonly used in the state of the art and observe that the proposed benchmark shows better results compared to others. In addition, while some metrics proved to be unpredictable, the metric associated with the E2E benchmark, which uses cosine similarity, performed well in evaluating chatbots. The performance of our best models shows that there are several benefits of using the cosine similarity score as a metric in the E2E benchmark.

Keywords: chatbot benchmarking, end-to-end (E2E) benchmarking, large language model, user centric evaluation.

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18416 Therapeutic Hypothermia Post Cardiac Arrest

Authors: Tahsien Mohamed Okasha

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We hypothesized that Post cardiac arrest patients with Glasgow coma scale (GCS) score of less than (8) and who will be exposed to therapeutic hypothermia protocol will exhibit improvement in their neurological performance. Purposive sample of 17 patients who were fulfilling the inclusion criteria during one year collected. The study carried out using Quasi-experimental research design. Four Tools used for data collection of this study: Demographic and medical data sheet, Post cardiac arrest health assessment sheet, Bedside Shivering Assessment Scale (BSAS), and Glasgow Pittsburgh cerebral performance category scale (CPC). Result: the mean age was X̅ ± SD = 53 ± 8.122 years, 47.1% were arrested because of cardiac etiology. 35.3% with initial arrest rhythm ventricular tachycardia (VT), 23.5% with ventricular fibrillation (VF), and 29.4% with A-Systole. Favorable neurological outcome was seen among 70.6%. There was significant statistical difference in WBC, Platelets, blood gases value, random blood sugar. Also Initial arrest rhythm, etiology of cardiac arrest, and shivering status were significantly correlated with cerebral performance categories score. therapeutic hypothermia has positive effects on neurological performance among post cardiac arrest patients with GCS score of less than (8). replication of the study on larger probability sample, with randomized control trial design. Further study for suggesting nursing protocol for patients undergoing therapeutic hypothermia.

Keywords: therapeutic hypothermia, neurological performance, after resuscitation from cardiac arrest., resuscitation

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18415 Optimization of Process Parameters Affecting on Spring-Back in V-Bending Process for High Strength Low Alloy Steel HSLA 420 Using FEA (HyperForm) and Taguchi Technique

Authors: Navajyoti Panda, R. S. Pawar

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In this study, process parameters like punch angle, die opening, grain direction, and pre-bend condition of the strip for deep draw of high strength low alloy steel HSLA 420 are investigated. The finite element method (FEM) in association with the Taguchi and the analysis of variance (ANOVA) techniques are carried out to investigate the degree of importance of process parameters in V-bending process for HSLA 420&ST12 grade material. From results, it is observed that punch angle had a major influence on the spring-back. Die opening also showed very significant role on spring back. On the other hand, it is revealed that grain direction had the least impact on spring back; however, if strip from flat sheet is taken, then it is less prone to spring back as compared to the strip from sheet metal coil. HyperForm software is used for FEM simulation and experiments are designed using Taguchi method. Percentage contribution of the parameters is obtained through the ANOVA techniques.

Keywords: bending, spring-back, v-bending, FEM, Taguchi, HSLA 420 and St12 materials, HyperForm, profile projector

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18414 Shedding Light on the Black Box: Explaining Deep Neural Network Prediction of Clinical Outcome

Authors: Yijun Shao, Yan Cheng, Rashmee U. Shah, Charlene R. Weir, Bruce E. Bray, Qing Zeng-Treitler

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Deep neural network (DNN) models are being explored in the clinical domain, following the recent success in other domains such as image recognition. For clinical adoption, outcome prediction models require explanation, but due to the multiple non-linear inner transformations, DNN models are viewed by many as a black box. In this study, we developed a deep neural network model for predicting 1-year mortality of patients who underwent major cardio vascular procedures (MCVPs), using temporal image representation of past medical history as input. The dataset was obtained from the electronic medical data warehouse administered by Veteran Affairs Information and Computing Infrastructure (VINCI). We identified 21,355 veterans who had their first MCVP in 2014. Features for prediction included demographics, diagnoses, procedures, medication orders, hospitalizations, and frailty measures extracted from clinical notes. Temporal variables were created based on the patient history data in the 2-year window prior to the index MCVP. A temporal image was created based on these variables for each individual patient. To generate the explanation for the DNN model, we defined a new concept called impact score, based on the presence/value of clinical conditions’ impact on the predicted outcome. Like (log) odds ratio reported by the logistic regression (LR) model, impact scores are continuous variables intended to shed light on the black box model. For comparison, a logistic regression model was fitted on the same dataset. In our cohort, about 6.8% of patients died within one year. The prediction of the DNN model achieved an area under the curve (AUC) of 78.5% while the LR model achieved an AUC of 74.6%. A strong but not perfect correlation was found between the aggregated impact scores and the log odds ratios (Spearman’s rho = 0.74), which helped validate our explanation.

Keywords: deep neural network, temporal data, prediction, frailty, logistic regression model

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18413 Implementation and Validation of a Damage-Friction Constitutive Model for Concrete

Authors: L. Madouni, M. Ould Ouali, N. E. Hannachi

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Two constitutive models for concrete are available in ABAQUS/Explicit, the Brittle Cracking Model and the Concrete Damaged Plasticity Model, and their suitability and limitations are well known. The aim of the present paper is to implement a damage-friction concrete constitutive model and to evaluate the performance of this model by comparing the predicted response with experimental data. The constitutive formulation of this material model is reviewed. In order to have consistent results, the parameter identification and calibration for the model have been performed. Several numerical simulations are presented in this paper, whose results allow for validating the capability of the proposed model for reproducing the typical nonlinear performances of concrete structures under different monotonic and cyclic load conditions. The results of the evaluation will be used for recommendations concerning the application and further improvements of the investigated model.

Keywords: Abaqus, concrete, constitutive model, numerical simulation

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18412 3D Receiver Operator Characteristic Histogram

Authors: Xiaoli Zhang, Xiongfei Li, Yuncong Feng

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ROC curves, as a widely used evaluating tool in machine learning field, are the tradeoff of true positive rate and negative rate. However, they are blamed for ignoring some vital information in the evaluation process, such as the amount of information about the target that each instance carries, predicted score given by each classification model to each instance. Hence, in this paper, a new classification performance method is proposed by extending the Receiver Operator Characteristic (ROC) curves to 3D space, which is denoted as 3D ROC Histogram. In the histogram, the

Keywords: classification, performance evaluation, receiver operating characteristic histogram, hardness prediction

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18411 Preliminary Studies: Relationship between Serum Level of Vitamin D and Symptoms of Schizophrenia Measured by Positive and Negative Syndrome Scale in Sumatera Utara

Authors: Novi Prasanty, Mustafa Ma, Elmeida Effendy

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Background: Schizophrenia is a psychotic disorder that most often encountered. Nearly 1% of the world population suffers from schizophrenia during their lifetime. Schizophrenia is a severe form of psychotic disorders, and tend to be chronic. Vitamin D plays crucial roles in neuroprotection and neurodevelopment, and low levels are commonly associated with schizophrenia. Lower vitamin D levels were correlated with more severe positive, negative, and overall symptoms in schizophrenia patient men and women. Methods: 54 schizophrenic patients, male and female, who are diagnosed with semistructured MINI ICD-X. A symptom of schizophrenia was measured by using positive and negative Syndrome Scale (PANSS). Examination of serum vitamin D using ELFA. Analysis to compare the serum levels of vitamin D male and female with Independent T-test, and the relationship between serum level of vitamin D and symptom with correlation. Results: In this study serum levels in male schizophrenic patients 22.12 (4.16), and 16.54 (2.88) in female schizophrenic patients. There are differences in male schizophrenic patients and women (p < 0.001). The negative correlation between serum levels of vitamin D in the PANSS total score in patients with schizophrenic male with r -0.58, p (0,016), and the female schizophrenic patients with r -0.69, p (0.031). Conclusion and Suggestion: There is a negative correlation between serum levels of vitamin D with a total score of PANSS, the lower the serum levels of vitamin D, the higher the total score of the PANSS.

Keywords: PANSS, schizophrenia, serum levels of vitamin D, severity illness

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18410 Breast Cancer Survivability Prediction via Classifier Ensemble

Authors: Mohamed Al-Badrashiny, Abdelghani Bellaachia

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This paper presents a classifier ensemble approach for predicting the survivability of the breast cancer patients using the latest database version of the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute. The system consists of two main components; features selection and classifier ensemble components. The features selection component divides the features in SEER database into four groups. After that it tries to find the most important features among the four groups that maximizes the weighted average F-score of a certain classification algorithm. The ensemble component uses three different classifiers, each of which models different set of features from SEER through the features selection module. On top of them, another classifier is used to give the final decision based on the output decisions and confidence scores from each of the underlying classifiers. Different classification algorithms have been examined; the best setup found is by using the decision tree, Bayesian network, and Na¨ıve Bayes algorithms for the underlying classifiers and Na¨ıve Bayes for the classifier ensemble step. The system outperforms all published systems to date when evaluated against the exact same data of SEER (period of 1973-2002). It gives 87.39% weighted average F-score compared to 85.82% and 81.34% of the other published systems. By increasing the data size to cover the whole database (period of 1973-2014), the overall weighted average F-score jumps to 92.4% on the held out unseen test set.

Keywords: classifier ensemble, breast cancer survivability, data mining, SEER

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18409 The Study of Elementary School Teacher’s Behavior of Using E-books by UTAUT Model

Authors: Tzong-Shing Cheng, Chen Pei Chen, Shu-Wei Chen

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The purpose of this research is to apply Unified Theory of Acceptance and Use of Technology (UTAUT) model to investigate the factors that influence elementary school teacher’s behavior of using e-books. Based on the literature review, a questionnaire was modified and used to test the elementary school teachers in Changhua. A total of 420 questionnaires were administered and 364 of them were returned, including 328 valid and 36 invalid questionnaires. The effective response rate is 78%. The methods of data analysis include descriptive statistics, factor analysis, Pearson’s correlation coefficient, one way analysis of variance (ANOVA) and simple regression analysis. The results show that: 1. There were significant difference in the Elementary school teachers’ “Performance Expectancy”, “Effort Expectancy”, “Social Influence”, and “Facilitating Conditions” depending on their different “Demographic Variables”. 2. “Performance Expectancy” and “Behavioral Intention to Use” are positively correlated. 3. “Effort Expectancy” and “Behavioral Intention to Use” are positively correlated. 4. There was no significant relationship between “Social Influence” and “Behavioral Intention to Use”. 5. There was significant relationship between “Facilitating Conditions” and “Use Behavior”.

Keywords: e-books, UTAUT, elementary school teacher, behavioral intention to use

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18408 An Efficient Propensity Score Method for Causal Analysis With Application to Case-Control Study in Breast Cancer Research

Authors: Ms Azam Najafkouchak, David Todem, Dorothy Pathak, Pramod Pathak, Joseph Gardiner

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Propensity score (PS) methods have recently become the standard analysis as a tool for the causal inference in the observational studies where exposure is not randomly assigned, thus, confounding can impact the estimation of treatment effect on the outcome. For the binary outcome, the effect of treatment on the outcome can be estimated by odds ratios, relative risks, and risk differences. However, using the different PS methods may give you a different estimation of the treatment effect on the outcome. Several methods of PS analyses have been used mainly, include matching, inverse probability of weighting, stratification, and covariate adjusted on PS. Due to the dangers of discretizing continuous variables (exposure, covariates), the focus of this paper will be on how the variation in cut-points or boundaries will affect the average treatment effect (ATE) utilizing the stratification of PS method. Therefore, we are trying to avoid choosing arbitrary cut-points, instead, we continuously discretize the PS and accumulate information across all cut-points for inferences. We will use Monte Carlo simulation to evaluate ATE, focusing on two PS methods, stratification and covariate adjusted on PS. We will then show how this can be observed based on the analyses of the data from a case-control study of breast cancer, the Polish Women’s Health Study.

Keywords: average treatment effect, propensity score, stratification, covariate adjusted, monte Calro estimation, breast cancer, case_control study

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18407 Multi-Response Optimization of CNC Milling Parameters Using Taguchi Based Grey Relational Analysis for AA6061 T6 Aluminium Alloy

Authors: Varsha Singh, Kishan Fuse

Abstract:

This paper presents a study of the grey-Taguchi method to optimize CNC milling parameters of AA6061 T6 aluminium alloy. Grey-Taguchi method combines Taguchi method based design of experiments (DOE) with grey relational analysis (GRA). Multi-response optimization of different quality characteristics as surface roughness, material removal rate, cutting forces is done using grey relational analysis (GRA). The milling parameters considered for experiments include cutting speed, feed per tooth, and depth of cut. Each parameter with three levels is selected. A grey relational grade is used to estimate overall quality characteristics performance. The Taguchi’s L9 orthogonal array is used for design of experiments. MINITAB 17 software is used for optimization. Analysis of variance (ANOVA) is used to identify most influencing parameter. The experimental results show that grey relational analysis is effective method for optimizing multi-response characteristics. Optimum results are finally validated by performing confirmation test.

Keywords: ANOVA, CNC milling, grey relational analysis, multi-response optimization

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18406 Benefits of Whole-Body Vibration Training on Lower-Extremity Muscle Strength and Balance Control in Middle-Aged and Older Adults

Authors: Long-Shan Wu, Ming-Chen Ko, Chien-Chang Ho, Po-Fu Lee, Jenn-Woei Hsieh, Ching-Yu Tseng

Abstract:

This study aimed to determine the effects of whole-body vibration (WBV) training on lower-extremity muscle strength and balance control performance among community-dwelling middle-aged and older adults in the United States. Twenty-nine participants without any contraindication of performing WBV exercise completed all the study procedures. Participants were randomly assigned to do body weight exercise with either an individualized vibration frequency and amplitude, a fixed vibration frequency and amplitude, or no vibration. Isokinetic knee extensor power, limits of stability, and sit-to-stand tests were performed at the baseline and after 8 weeks of training. Neither the individualized frequency-amplitude WBV training protocol nor the fixed frequency-amplitude WBV training protocol improved isokinetic knee extensor power. The limits of stability endpoint excursion score for the individualized frequency-amplitude group increased by 8.8 (12.9%; p = 0.025) after training. No significant differences were observed in fixed and control group. The maximum excursion score for the individualized frequency-amplitude group at baseline increased by 9.2 (11.5%; p = 0.006) after training. The average weight transfer time score significantly decreased by 0.21 s in the fixed group. The participants in the individualized group showed a significant increase (3.2%) in weight rising index score after 8 weeks of WBV training. These results suggest that 8 weeks of WBV training improved limit of stability and sit-to-stand performance. Future studies need to determine whether WBV training improves other factors that can influence posture control.

Keywords: whole-body vibration training, muscle strength, balance control, middle-aged and older adults

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18405 A Unified Webcam Proctoring Solution on Edge

Authors: Saw Thiha, Jay Rajasekera

Abstract:

A boom in video conferencing generated millions of hours of video data daily to be analyzed. However, such enormous data pose certain scalability issues to be analyzed efficiently, let alone do it in real-time, as online conferences can involve hundreds of people and can last for hours. This paper proposes an efficient online proctoring solution that can analyze the online conferences real-time on edge devices such as Android, iOS, and desktops. Since the computation can be done upfront on the devices where online conferences take place, it can scale well without requiring intensive resources such as GPU servers and complex cloud infrastructure. According to the linear models, face orientation does indeed impact the perceived eye openness. Also, the proposed z score facial landmark standardization was proven to be functional in detecting face orientation and contributed to classifying eye blinks with single eyelid distance computation while achieving a better f1 score and accuracy than the Eye Aspect Ratio (EAR) threshold method. Last but not least, the authors implemented the solution natively in the MediaPipe framework and open-sourced it along with the reproducible experimental results on GitHub. The solution provides face orientation, eye blink, facial activity, and translation detections out of the box and is highly customizable and extensible.

Keywords: android, desktop, edge computing, blink, face orientation, facial activity and translation, MediaPipe, open source, real-time, video conference, web, iOS, Z score facial landmark standardization

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18404 Outpatient Pelvic Nerve and Muscle Treatment Reduces Pain and Improves Functionality for Patients with Chronic Pelvic Pain and Erectile Dysfunction

Authors: Allyson Augusta Shrikhande, Alexa Rains, Tayyaba Ahmed, Marjorie Mamsaang, Rakhi Vyas, Janaki Natarajan, Erika Moody, Christian Reutter, Kimberlee Leishear, Yogita Tailor, Sandra Sandhu-Restaino, Lora Liu, Neha James, Rosemarie Filart

Abstract:

Characterized by consistent difficulty getting and keeping an erection firm enough for intercourse, Erectile Dysfunction may affect up to 15% of adult men. Although awareness and access to treatment have improved in recent years, many patients do not actively seek diagnosis or treatment due to the stigma surrounding this condition. Patients who do seek treatment are often dissatisfied by the efficacy of the medication. The condition inhibits patients’ quality of life by worsening mental health and relationships. The purpose of this study was to test the effectiveness of an outpatient neuromuscular treatment protocol in treating the symptoms of Chronic Pelvic Pain and Erectile Dysfunction, improving pain and function. 56 patients ages 20-79 presented to an outpatient clinic for treatment of pelvic pain and Erectile Dysfunction symptoms. These symptoms had persisted for an average of 4 years. All patients underwent external ultrasound-guided hydro-dissection technique targeted at pelvic peripheral nerves in combination with pelvic floor musculature trigger-point injections. To measure the effects of this treatment, a five question Erectile Dysfunction questionnaire was completed by each patient at their first visit to a clinic and three months after treatment began. Answers were summed for a total score of 5-25, with a higher score indicating optimal function. The average score before treatment was 14.125 (SD 5.411) (a=0.05; CI 12.708-15.542), which increased by 18% to an average of 16.625 (SD 6.423) (a=0.05; CI 14.943-18.307) after treatment (P=0.0004). Secondary outcome variables included a Visual Analogue Scale (VAS) to measure pelvic pain intensity and the Functional Pelvic Pain Scale (FPPS) to measure function across multiple areas. VAS scores reduced by 51% after three months. Before treatment, the mean VAS score was 5.87, and the posttreatment mean VAS score was 2.89. Pelvic pain functionality improved by 34% after three months. Pretreatment FPPS scores averaged at 7.48, decreasing to 4.91 after treatment. These results indicate that this unique treatment was very effective at relieving pain and increasing function for patients with Erectile Dysfunction.

Keywords: chronic pelvic pain, erectile dysfunction, nonsurgical, outpatient, trigger point injections

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18403 Development of an Interactive Display-Control Layout Design System for Trains Based on Train Drivers’ Mental Models

Authors: Hyeonkyeong Yang, Minseok Son, Taekbeom Yoo, Woojin Park

Abstract:

Human error is the most salient contributing factor to railway accidents. To reduce the frequency of human errors, many researchers and train designers have adopted ergonomic design principles for designing display-control layout in rail cab. There exist a number of approaches for designing the display control layout based on optimization methods. However, the ergonomically optimized layout design may not be the best design for train drivers, since the drivers have their own mental models based on their experiences. Consequently, the drivers may prefer the existing display-control layout design over the optimal design, and even show better driving performance using the existing design compared to that using the optimal design. Thus, in addition to ergonomic design principles, train drivers’ mental models also need to be considered for designing display-control layout in rail cab. This paper developed an ergonomic assessment system of display-control layout design, and an interactive layout design system that can generate design alternatives and calculate ergonomic assessment score in real-time. The design alternatives generated from the interactive layout design system may not include the optimal design from the ergonomics point of view. However, the system’s strength is that it considers train drivers’ mental models, which can help generate alternatives that are more friendly and easier to use for train drivers. Also, with the developed system, non-experts in ergonomics, such as train drivers, can refine the design alternatives and improve ergonomic assessment score in real-time.

Keywords: display-control layout design, interactive layout design system, mental model, train drivers

Procedia PDF Downloads 292
18402 Exploring the Applications of Neural Networks in the Adaptive Learning Environment

Authors: Baladitya Swaika, Rahul Khatry

Abstract:

Computer Adaptive Tests (CATs) is one of the most efficient ways for testing the cognitive abilities of students. CATs are based on Item Response Theory (IRT) which is based on item selection and ability estimation using statistical methods of maximum information selection/selection from posterior and maximum-likelihood (ML)/maximum a posteriori (MAP) estimators respectively. This study aims at combining both classical and Bayesian approaches to IRT to create a dataset which is then fed to a neural network which automates the process of ability estimation and then comparing it to traditional CAT models designed using IRT. This study uses python as the base coding language, pymc for statistical modelling of the IRT and scikit-learn for neural network implementations. On creation of the model and on comparison, it is found that the Neural Network based model performs 7-10% worse than the IRT model for score estimations. Although performing poorly, compared to the IRT model, the neural network model can be beneficially used in back-ends for reducing time complexity as the IRT model would have to re-calculate the ability every-time it gets a request whereas the prediction from a neural network could be done in a single step for an existing trained Regressor. This study also proposes a new kind of framework whereby the neural network model could be used to incorporate feature sets, other than the normal IRT feature set and use a neural network’s capacity of learning unknown functions to give rise to better CAT models. Categorical features like test type, etc. could be learnt and incorporated in IRT functions with the help of techniques like logistic regression and can be used to learn functions and expressed as models which may not be trivial to be expressed via equations. This kind of a framework, when implemented would be highly advantageous in psychometrics and cognitive assessments. This study gives a brief overview as to how neural networks can be used in adaptive testing, not only by reducing time-complexity but also by being able to incorporate newer and better datasets which would eventually lead to higher quality testing.

Keywords: computer adaptive tests, item response theory, machine learning, neural networks

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18401 Bridging Urban Planning and Environmental Conservation: A Regional Analysis of Northern and Central Kolkata

Authors: Tanmay Bisen, Aastha Shayla

Abstract:

This study introduces an advanced approach to tree canopy detection in urban environments and a regional analysis of Northern and Central Kolkata that delves into the intricate relationship between urban development and environmental conservation. Leveraging high-resolution drone imagery from diverse urban green spaces in Kolkata, we fine-tuned the deep forest model to enhance its precision and accuracy. Our results, characterized by an impressive Intersection over Union (IoU) score of 0.90 and a mean average precision (mAP) of 0.87, underscore the model's robustness in detecting and classifying tree crowns amidst the complexities of aerial imagery. This research not only emphasizes the importance of model customization for specific datasets but also highlights the potential of drone-based remote sensing in urban forestry studies. The study investigates the spatial distribution, density, and environmental impact of trees in Northern and Central Kolkata. The findings underscore the significance of urban green spaces in met-ropolitan cities, emphasizing the need for sustainable urban planning that integrates green infrastructure for ecological balance and human well-being.

Keywords: urban greenery, advanced spatial distribution analysis, drone imagery, deep learning, tree detection

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18400 Optimization of Surface Roughness by Taguchi’s Method for Turning Process

Authors: Ashish Ankus Yerunkar, Ravi Terkar

Abstract:

Study aimed at evaluating the best process environment which could simultaneously satisfy requirements of both quality as well as productivity with special emphasis on reduction of cutting tool flank wear, because reduction in flank wear ensures increase in tool life. The predicted optimal setting ensured minimization of surface roughness. Purpose of this paper is focused on the analysis of optimum cutting conditions to get lowest surface roughness in turning SCM 440 alloy steel by Taguchi method. Design for the experiment was done using Taguchi method and 18 experiments were designed by this process and experiments conducted. The results are analyzed using ANOVA method. Taguchi method has depicted that the depth of cut has significant role to play in producing lower surface roughness followed by feed. The Cutting speed has lesser role on surface roughness from the tests. The vibrations of the machine tool, tool chattering are the other factors which may contribute poor surface roughness to the results and such factors ignored for analyses. The inferences by this method will be useful to other researches for similar type of study and may be vital for further research on tool vibrations, cutting forces etc.

Keywords: surface roughness (ra), machining, dry turning, taguchi method, turning process, anova method, mahr perthometer

Procedia PDF Downloads 362
18399 Factors Affecting the Uptake of Modern Contraception Services in Oyo State, Nigeria

Authors: Folajinmi Oluwasina, Magbagbeola Dairo, Ikeoluwapo Ajayi

Abstract:

Contraception has proven to be an effective way of controlling fertility and spacing births. Studies have shown that contraception can avert the high-risk pregnancies and consequently reduce maternal deaths up to 32%. Uptake of modern contraception is promoted as a mechanism to address the reproductive health needs of men and women, as well as the crucial challenge of rapid population increase. A cross- sectional descriptive study using a two- stage systematic sampling technique was used to select 530 women of reproductive age out of 20,000 households. Respondents were interviewed using a semi-structured questionnaire. Knowledge was assessed on a 5 point score in which a score of ≤ 2 rated poor while perception was scored on 36 points score in which a score of ≤ 18 was rated low. Data were analyzed using descriptive statistics, Chi-square test and logistic regression at p< 0.05. There were 530 respondents. Age of respondents was 30.3 ±7.8 years, and 73.0% were married. About 90% had good knowledge of contraception while 60.8% had used contraceptives. The commonest source of information about contraception was mass media (72.8%). Minority (26.1%) obtained husbands approval before using contraceptive while 20.0% had used modern contraceptives before the first birth. Many (54.5%) of the respondents agreed that contraception helps in improving standard of living and 64.7% had good perception about contraception. Factors that hindered effective uptake of contraception services included poor service provider’s attitude (33.3%) and congestion at the service centers (4.5%). Respondents with nonuse of contraceptive before first birth are less likely to subsequently use contraceptives (OR= 0.324, 95% CI= 0.1-0.5). Husband approval of contraceptives use was the major determinant of women’s contraceptive use (OR = 3.4, 95% CI = 1.3-8.7). Respondents who had family planning centers not more than 5 kilometers walking distance to their residence did not significantly use contraception services (41.5%) more than 21.1% of those who had to take means of transportation to the service venues. This study showed that majority of the respondents were knowledgeable and aware of contraception services, but husband’s agreement on the use of modern contraceptives remains poor. Programmes that enhances husbands approval of modern contraception is thus recommended.

Keywords: contraception services, service provider’s attitude, uptake, husbands approval

Procedia PDF Downloads 350
18398 Evaluation of Cirata Reservoir Sustainability Using Multi Dimensionalscaling (MDS)

Authors: Kholil Kholil, Aniwidayati

Abstract:

MDS (Multi-Dimensional Scaling) is one method that has been widely used to evaluate the use of natural resources. By using Raffish software tool, we will able to analyze sustainability level of the natural resources use. This paper will discuss the level of sustainability of the reservoir using MDS (Multi-Dimensional Scaling) based on five dimensions: (1) Ecology & Layout, (2) Economics, (3) Social & Culture, (4) Regulations & Institutional, and (5) Infrastructure and Technology. MDS analysis results show that the dimension of ecological and layout, institutional and the regulation are lack of sustainability due to the low index score of 45.76 and 42.24. While for the economic, social and culture, and infrastructure and technology dimension reach each score of 63.12, 64.42, and 68.64 (only the sufficient sustainability category). It means that the sustainability performance of Cirata Reservoir seriously threatened.

Keywords: MDS, cirata reservoir, carrying capacity, water quality, sustainable development, sedimentation, sustainability index

Procedia PDF Downloads 371