Search results for: random search
2887 Machine Learning Prediction of Diabetes Prevalence in the U.S. Using Demographic, Physical, and Lifestyle Indicators: A Study Based on NHANES 2009-2018
Authors: Oluwafunmibi Omotayo Fasanya, Augustine Kena Adjei
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To develop a machine learning model to predict diabetes (DM) prevalence in the U.S. population using demographic characteristics, physical indicators, and lifestyle habits, and to analyze how these factors contribute to the likelihood of diabetes. We analyzed data from 23,546 participants aged 20 and older, who were non-pregnant, from the 2009-2018 National Health and Nutrition Examination Survey (NHANES). The dataset included key demographic (age, sex, ethnicity), physical (BMI, leg length, total cholesterol [TCHOL], fasting plasma glucose), and lifestyle indicators (smoking habits). A weighted sample was used to account for NHANES survey design features such as stratification and clustering. A classification machine learning model was trained to predict diabetes status. The target variable was binary (diabetes or non-diabetes) based on fasting plasma glucose measurements. The following models were evaluated: Logistic Regression (baseline), Random Forest Classifier, Gradient Boosting Machine (GBM), Support Vector Machine (SVM). Model performance was assessed using accuracy, F1-score, AUC-ROC, and precision-recall metrics. Feature importance was analyzed using SHAP values to interpret the contributions of variables such as age, BMI, ethnicity, and smoking status. The Gradient Boosting Machine (GBM) model outperformed other classifiers with an AUC-ROC score of 0.85. Feature importance analysis revealed the following key predictors: Age: The most significant predictor, with diabetes prevalence increasing with age, peaking around the 60s for males and 70s for females. BMI: Higher BMI was strongly associated with a higher risk of diabetes. Ethnicity: Black participants had the highest predicted prevalence of diabetes (14.6%), followed by Mexican-Americans (13.5%) and Whites (10.6%). TCHOL: Diabetics had lower total cholesterol levels, particularly among White participants (mean decline of 23.6 mg/dL). Smoking: Smoking showed a slight increase in diabetes risk among Whites (0.2%) but had a limited effect in other ethnic groups. Using machine learning models, we identified key demographic, physical, and lifestyle predictors of diabetes in the U.S. population. The results confirm that diabetes prevalence varies significantly across age, BMI, and ethnic groups, with lifestyle factors such as smoking contributing differently by ethnicity. These findings provide a basis for more targeted public health interventions and resource allocation for diabetes management.Keywords: diabetes, NHANES, random forest, gradient boosting machine, support vector machine
Procedia PDF Downloads 52886 Measurements of Radial Velocity in Fixed Fluidized Bed for Fischer-Tropsch Synthesis Using LDV
Authors: Xiaolai Zhang, Haitao Zhang, Qiwen Sun, Weixin Qian, Weiyong Ying
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High temperature Fischer-Tropsch synthesis process use fixed fluidized bed as a reactor. In order to understand the flow behavior in the fluidized bed better, the research of how the radial velocity affect the entire flow field is necessary. Laser Doppler Velocimetry (LDV) was used to study the radial velocity distribution along the diameter direction of the cross-section of the particle in a fixed fluidized bed. The velocity in the cross-section is fluctuating within a small range. The direction of the speed is a random phenomenon. In addition to r/R is 1, the axial velocity are more than 6 times of the radial velocity, the radial velocity has little impact on the axial velocity in a fixed fluidized bed.Keywords: Fischer-Tropsch synthesis, Fixed fluidized bed, LDV, Velocity
Procedia PDF Downloads 4022885 Non-factoid Arabic Question-Answering Systems: A Review of Existing Studies, Research Issues, and Future Trends
Authors: Aya Mousa, Mahmoud Alsaheb
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Question Answering System (QAS) aims to provide the most suitable answer to the user's question in any natural language. In the recent future, it will be a future version of web search. Much research has already been done on answering Arabic factoid questions and achieved good accuracy. In contrast, the progress in research on Arabic non-factoid question answering is still immature. In this survey, we summarize, discuss, and compare the existing Arab non-factoid question-answering systems to identify the limitations and the achievements that were accomplished. Furthermore, we investigate the challenges in developing non-factoid Arabic QAS and the possible future improvements. The survey is written to help the researchers to understand the field of Arabic non-factoid QAS and to motivate them to utilize different approaches to develop and enhance the Non-factoid Arabic QASKeywords: Arabic question answering system, non-factoid question answering, Arabic NLP, question answering
Procedia PDF Downloads 982884 On Disaggregation and Consolidation of Imperfect Quality Shipments in an Extended EPQ Model
Authors: Hung-Chi Chang
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For an extended EPQ model with random yield, the existent study revealed that both the disaggregating and consolidating shipment policies for the imperfect quality items are independent of holding cost, and recommended a model with economic benefit by comparing the least total cost for each of the three models investigated. To better capture the real situation, we generalize the existent study to include different holding costs for perfect and imperfect quality items. Through analysis, we show that the above shipment policies are dependent on holding costs. Furthermore, we derive a simple decision rule solely based on the thresholds of problem parameters to select a superior model. The results are illustrated analytically and numerically.Keywords: consolidating shipments, disaggregating shipments, EPQ, imperfect quality, inventory
Procedia PDF Downloads 3752883 Reading Behavior of Undergraduate Students at Suan Sunandha Rajabhat University
Authors: Ratanavadee Takerngsukvatana
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The purposes of this research were to study reading behavior of undergraduate students at Suan Sunandha Rajabhat University. A stratified random sample of 380 participants was collected. A Likert five-scale questionnaire was developed to collect data and to obtain students’ opinions regarding their reading behavior. The findings revealed that the majority of respondents read mainly for academic purpose. They preferred to read magazines. The majority of respondents read an average of 3-7 pages a day. The places to read were home and library. Buying with their own money and borrowing from the library were two main sources of books. The suggested activity to promote is planning the curriculum to suit students’ reading behavior.Keywords: reading, reading behavior, undergraduate students, Suan Sunandha Rajabhat University
Procedia PDF Downloads 3002882 Approaches of Flight Level Selection for an Unmanned Aerial Vehicle Round-Trip in Order to Reach Best Range Using Changes in Flight Level Winds
Authors: Dmitry Fedoseyev
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The ultimate success of unmanned aerial vehicles (UAVs) depends largely on the effective control of their flight, especially in variable wind conditions. This paper investigates different approaches to selecting the optimal flight level to maximize the range of UAVs. We propose to consider methods based on mathematical models of atmospheric conditions, as well as the use of sensor data and machine learning algorithms to automatically optimize the flight level in real-time. The proposed approaches promise to improve the efficiency and range of UAVs in various wind conditions, which may have significant implications for the application of these systems in various fields, including geodesy, environmental surveillance, and search and rescue operations.Keywords: drone, UAV, flight trajectory, wind-searching, efficiency
Procedia PDF Downloads 612881 Dynamic Economic Load Dispatch Using Quadratic Programming: Application to Algerian Electrical Network
Authors: A. Graa, I. Ziane, F. Benhamida, S. Souag
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This paper presents a comparative analysis study of an efficient and reliable quadratic programming (QP) to solve economic load dispatch (ELD) problem with considering transmission losses in a power system. The proposed QP method takes care of different unit and system constraints to find optimal solution. To validate the effectiveness of the proposed QP solution, simulations have been performed using Algerian test system. Results obtained with the QP method have been compared with other existing relevant approaches available in literatures. Experimental results show a proficiency of the QP method over other existing techniques in terms of robustness and its optimal search.Keywords: economic dispatch, quadratic programming, Algerian network, dynamic load
Procedia PDF Downloads 5632880 Joint Path and Push Planning among Moveable Obstacles
Authors: Victor Emeli, Akansel Cosgun
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This paper explores the navigation among movable obstacles (NAMO) problem and proposes joint path and push planning: which path to take and in what direction the obstacles should be pushed at, given a start and goal position. We present a planning algorithm for selecting a path and the obstacles to be pushed, where a rapidly-exploring random tree (RRT)-based heuristic is employed to calculate a minimal collision path. When it is necessary to apply a pushing force to slide an obstacle out of the way, the planners leverage means-end analysis through a dynamic physics simulation to determine the sequence of linear pushes to clear the necessary space. Simulation experiments show that our approach finds solutions in higher clutter percentages (up to 49%) compared to the straight-line push planner (37%) and RRT without pushing (18%).Keywords: motion planning, path planning, push planning, robot navigation
Procedia PDF Downloads 1612879 Fractal Behaviour of Earthquake Sequences in Himalaya
Authors: Kamal, Adil Ahmad
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Earthquakes are among the most versatile natural and dynamic processes, and hence a fractal model is considered to be the best representative of the same. We present a novel method to process and analyse information hidden in earthquake sequences using Fractal Dimensions and Iterative Function Systems (IFS). Spatial and temporal variations in the fractal dimensions of seismicity observed around the Indian peninsula in last 30 years are studied. This was used as a possible precursor before large earthquakes in the region. IFS images for observed seismicity in the Himalayan belt were also obtained. We scan the whole data set and coarse grain of a selected window to reduce it to four bins. A critical analysis of four-cornered chaos-game clearly shows that the spatial variation in earthquake occurrences in Himalayan range is not random. Two subzones of Himalaya have a tendency to follow each other in time.Keywords: earthquakes, fractals, Himalaya, iterated function systems
Procedia PDF Downloads 2982878 A Novel Chicken W Chromosome Specific Tandem Repeat
Authors: Alsu F. Saifitdinova, Alexey S. Komissarov, Svetlana A. Galkina, Elena I. Koshel, Maria M. Kulak, Stephen J. O'Brien, Elena R. Gaginskaya
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The mystery of sex determination is one of the most ancient and still not solved until the end so far. In many species, sex determination is genetic and often accompanied by the presence of dimorphic sex chromosomes in the karyotype. Genomic sequencing gave the information about the gene content of sex chromosomes which allowed to reveal their origin from ordinary autosomes and to trace their evolutionary history. Female-specific W chromosome in birds as well as mammalian male-specific Y chromosome is characterized by the degeneration of gene content and the accumulation of repetitive DNA. Tandem repeats complicate the analysis of genomic data. Despite the best efforts chicken W chromosome assembly includes only 1.2 Mb from expected 55 Mb. Supplementing the information on the sex chromosome composition not only helps to complete the assembly of genomes but also moves us in the direction of understanding of the sex-determination systems evolution. A whole-genome survey to the assembly Gallus_gallus WASHUC 2.60 was applied for repeats search in assembled genome and performed search and assembly of high copy number repeats in unassembled reads of SRR867748 short reads datasets. For cytogenetic analysis conventional methods of fluorescent in situ hybridization was used for previously cloned W specific satellites and specifically designed directly labeled synthetic oligonucleotide DNA probe was used for bioinformatically identified repetitive sequence. Hybridization was performed with mitotic chicken chromosomes and manually isolated giant meiotic lampbrush chromosomes from growing oocytes. A novel chicken W specific satellite (GGAAA)n which is not co-localizes with any previously described classes of W specific repeats was identified and mapped with high resolution. In the composition of autosomes this repeat units was found as a part of upstream regions of gonad specific protein coding sequences. These findings may contribute to the understanding of the role of tandem repeats in sex specific differentiation regulation in birds and sex chromosome evolution. This work was supported by the postdoctoral fellowships from St. Petersburg State University (#1.50.1623.2013 and #1.50.1043.2014), the grant for Leading Scientific Schools (#3553.2014.4) and the grant from Russian foundation for basic researches (#15-04-05684). The equipment and software of Research Resource Center “Chromas” and Theodosius Dobzhansky Center for Genome Bioinformatics of Saint Petersburg State University were used.Keywords: birds, lampbrush chromosomes, sex chromosomes, tandem repeats
Procedia PDF Downloads 3872877 Predicting Football Player Performance: Integrating Data Visualization and Machine Learning
Authors: Saahith M. S., Sivakami R.
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In the realm of football analytics, particularly focusing on predicting football player performance, the ability to forecast player success accurately is of paramount importance for teams, managers, and fans. This study introduces an elaborate examination of predicting football player performance through the integration of data visualization methods and machine learning algorithms. The research entails the compilation of an extensive dataset comprising player attributes, conducting data preprocessing, feature selection, model selection, and model training to construct predictive models. The analysis within this study will involve delving into feature significance using methodologies like Select Best and Recursive Feature Elimination (RFE) to pinpoint pertinent attributes for predicting player performance. Various machine learning algorithms, including Random Forest, Decision Tree, Linear Regression, Support Vector Regression (SVR), and Artificial Neural Networks (ANN), will be explored to develop predictive models. The evaluation of each model's performance utilizing metrics such as Mean Squared Error (MSE) and R-squared will be executed to gauge their efficacy in predicting player performance. Furthermore, this investigation will encompass a top player analysis to recognize the top-performing players based on the anticipated overall performance scores. Nationality analysis will entail scrutinizing the player distribution based on nationality and investigating potential correlations between nationality and player performance. Positional analysis will concentrate on examining the player distribution across various positions and assessing the average performance of players in each position. Age analysis will evaluate the influence of age on player performance and identify any discernible trends or patterns associated with player age groups. The primary objective is to predict a football player's overall performance accurately based on their individual attributes, leveraging data-driven insights to enrich the comprehension of player success on the field. By amalgamating data visualization and machine learning methodologies, the aim is to furnish valuable tools for teams, managers, and fans to effectively analyze and forecast player performance. This research contributes to the progression of sports analytics by showcasing the potential of machine learning in predicting football player performance and offering actionable insights for diverse stakeholders in the football industry.Keywords: football analytics, player performance prediction, data visualization, machine learning algorithms, random forest, decision tree, linear regression, support vector regression, artificial neural networks, model evaluation, top player analysis, nationality analysis, positional analysis
Procedia PDF Downloads 362876 Ternary Content Addressable Memory Cell with a Leakage Reduction Technique
Authors: Gagnesh Kumar, Nitin Gupta
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Ternary Content Addressable Memory cells are mainly popular in network routers for packet forwarding and packet classification, but they are also useful in a variety of other applications that require high-speed table look-up. The main TCAM-design challenge is to decrease the power consumption associated with the large amount of parallel active circuitry, without compromising with speed or memory density. Furthermore, when the channel length decreases, leakage power becomes more significant, and it can even dominate dynamic power at lower technologies. In this paper, we propose a TCAM-design technique, called Virtual Power Supply technique that reduces the leakage by a substantial amount.Keywords: match line (ML), search line (SL), ternary content addressable memory (TCAM), Leakage power (LP)
Procedia PDF Downloads 2962875 Sustainable Housing and Urban Development: A Study on the Soon-To-Be-Old Population's Impetus to Migrate
Authors: Tristance Kee
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With the unprecedented increase in elderly population globally, it is critical to search for new sustainable housing and urban development alternatives to traditional housing options. This research examines concepts of elderly migration pattern in the context of a high density city in Hong Kong to Mainland China. The research objectives are to: 1) explore the relationships between soon-to-be-old elderly and their intentions to move to Mainland upon retirement and their demographic characteristics; and 2) What are the desired amenities, locational factors and activities that are expected in the soon-to-be-old generation’s retirement housing environment? Primary data was collected through questionnaire survey conducted using random sampling method with respondents aged between 45-64 years old. The face-to-face survey was completed by 500 respondents. The survey was divided into four sections. The first section focused on respondent’s demographic information such as gender, age, education attainment, monthly income, housing tenure type and their visits to Mainland China. The second section focused on their retirement plans in terms of intended retirement age, prospective retirement funding and retirement housing options. The third section focused on the respondent’s attitudes toward retiring in Mainland for housing. It asked about their intentions to migrate retire into Mainland and incentives to retire in Hong Kong. The fourth section focused on respondent’s ideal housing environment including preferred housing amenities, desired living environment and retirement activities. The dependent variable in this study was ‘respondent’s consideration to move to Mainland China upon retirement’. Eight primary independent variables were integrated into the study to identify the correlations between them and retirement migration plan. The independent variables include: gender, age, marital status, monthly income, present housing tenure type, property ownership in Hong Kong, relationship with Mainland and the frequency of visiting Mainland China. In addition to the above independent variables, respondents were asked to indicate their retirement plans (retirement age, funding sources and retirement housing options), incentives to migrate to retire (choices included: property ownership, family relations, cost of living, living environment, medical facilities, government welfare benefits, etc.), perceived ideal retirement life qualities including desired amenities (sports, medical and leisure facilities etc.), desired locational qualities (green open space, convenient transport options and accessibility to urban settings etc.) and desired retirement activities (home-based leisure, elderly friendly sports, cultural activities, child care, social activities, etc.). The finding shows correlations between the used independent variables and consideration to migrate for housing options. The two independent variables indicated a possible correlation were gender and the frequency of visiting Mainland at present. When considering the increasing property prices across the border and strong social relationships, potential retirement migration is a very subjective decision that could vary from person to person. This research adds knowledge to housing research and migration study. Although the research is based in Mainland, most of the characteristics identified including better medical services, government welfare and sound urban amenities are shared qualities for all sustainable urban development and housing strategies.Keywords: elderly migration, housing alternative, soon-to-be-old, sustainable environment
Procedia PDF Downloads 2092874 The Effect of Solution Density on the Synthesis of Magnesium Borate from Boron-Gypsum
Authors: N. Tugrul, E. Sariburun, F. T. Senberber, A. S. Kipcak, E. Moroydor Derun, S. Piskin
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Boron-gypsum is a waste which occurs in the boric acid production process. In this study, the boron content of this waste is evaluated for the use in synthesis of magnesium borates and such evaluation of this kind of waste is useful more than storage or disposal. Magnesium borates, which are a sub-class of boron minerals, are useful additive materials for the industries due to their remarkable thermal and mechanical properties. Magnesium borates were obtained hydrothermally at different temperatures. Novelty of this study is the search of the solution density effects to magnesium borate synthesis process for the increasing the possibility of boron-gypsum usage as a raw material. After the synthesis process, products are subjected to XRD and FT-IR to identify and characterize their crystal structure, respectively.Keywords: boron-gypsum, hydrothermal synthesis, magnesium borate, solution density
Procedia PDF Downloads 3922873 Advanced Machine Learning Algorithm for Credit Card Fraud Detection
Authors: Manpreet Kaur
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When legitimate credit card users are mistakenly labelled as fraudulent in numerous financial delated applications, there are numerous ethical problems. The innovative machine learning approach we have suggested in this research outperforms the current models and shows how to model a data set for credit card fraud detection while minimizing false positives. As a result, we advise using random forests as the best machine learning method for predicting and identifying credit card transaction fraud. The majority of victims of these fraudulent transactions were discovered to be credit card users over the age of 60, with a higher percentage of fraudulent transactions taking place between the specific hours.Keywords: automated fraud detection, isolation forest method, local outlier factor, ML algorithm, credit card
Procedia PDF Downloads 1112872 High Performance Computing Enhancement of Agent-Based Economic Models
Authors: Amit Gill, Lalith Wijerathne, Sebastian Poledna
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This research presents the details of the implementation of high performance computing (HPC) extension of agent-based economic models (ABEMs) to simulate hundreds of millions of heterogeneous agents. ABEMs offer an alternative approach to study the economy as a dynamic system of interacting heterogeneous agents, and are gaining popularity as an alternative to standard economic models. Over the last decade, ABEMs have been increasingly applied to study various problems related to monetary policy, bank regulations, etc. When it comes to predicting the effects of local economic disruptions, like major disasters, changes in policies, exogenous shocks, etc., on the economy of the country or the region, it is pertinent to study how the disruptions cascade through every single economic entity affecting its decisions and interactions, and eventually affect the economic macro parameters. However, such simulations with hundreds of millions of agents are hindered by the lack of HPC enhanced ABEMs. In order to address this, a scalable Distributed Memory Parallel (DMP) implementation of ABEMs has been developed using message passing interface (MPI). A balanced distribution of computational load among MPI-processes (i.e. CPU cores) of computer clusters while taking all the interactions among agents into account is a major challenge for scalable DMP implementations. Economic agents interact on several random graphs, some of which are centralized (e.g. credit networks, etc.) whereas others are dense with random links (e.g. consumption markets, etc.). The agents are partitioned into mutually-exclusive subsets based on a representative employer-employee interaction graph, while the remaining graphs are made available at a minimum communication cost. To minimize the number of communications among MPI processes, real-life solutions like the introduction of recruitment agencies, sales outlets, local banks, and local branches of government in each MPI-process, are adopted. Efficient communication among MPI-processes is achieved by combining MPI derived data types with the new features of the latest MPI functions. Most of the communications are overlapped with computations, thereby significantly reducing the communication overhead. The current implementation is capable of simulating a small open economy. As an example, a single time step of a 1:1 scale model of Austria (i.e. about 9 million inhabitants and 600,000 businesses) can be simulated in 15 seconds. The implementation is further being enhanced to simulate 1:1 model of Euro-zone (i.e. 322 million agents).Keywords: agent-based economic model, high performance computing, MPI-communication, MPI-process
Procedia PDF Downloads 1272871 Secure Image Retrieval Based on Orthogonal Decomposition under Cloud Environment
Authors: Y. Xu, L. Xiong, Z. Xu
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In order to protect data privacy, image with sensitive or private information needs to be encrypted before being outsourced to the cloud. However, this causes difficulties in image retrieval and data management. A secure image retrieval method based on orthogonal decomposition is proposed in the paper. The image is divided into two different components, for which encryption and feature extraction are executed separately. As a result, cloud server can extract features from an encrypted image directly and compare them with the features of the queried images, so that the user can thus obtain the image. Different from other methods, the proposed method has no special requirements to encryption algorithms. Experimental results prove that the proposed method can achieve better security and better retrieval precision.Keywords: secure image retrieval, secure search, orthogonal decomposition, secure cloud computing
Procedia PDF Downloads 4812870 Association Between Swallowing Disorders and Cognitive Disorders in Adults: Systematic Review and Metaanalysis
Authors: Shiva Ebrahimian Dehaghani, Afsaneh Doosti, Morteza Zare
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Background: There is no consensus regarding the association between dysphagia and cognition. Purpose: The aim of this study was to quantitatively and qualitatively analyze the available evidence on the direction and strength of association between dysphagia and cognition. Methodology: PubMed, Scopus, Embase and Web of Science were searched about the association between dysphagia and cognition. A random-effects model was used to determine weighted odds ratios (OR) and 95% confidence intervals (CI). Sensitivity analysis was performed to determine the impact of each individual study on the pooled results. Results: A total of 1427 participants showed that some cognitive disorders were significantly associated with dysphagia (OR = 3.23; 95% CI, 2.33–4.48). Conclusion: The association between cognition and swallowing disorders suggests that multiple neuroanatomical systems are involved in these two functions.Keywords: adult, association, cognitive impairment, dysphagia, systematic review
Procedia PDF Downloads 1582869 Percolation Transition in an Agglomeration of Spherical Particles
Authors: Johannes J. Schneider, Mathias S. Weyland, Peter Eggenberger Hotz, William D. Jamieson, Oliver Castell, Alessia Faggian, Rudolf M. Füchslin
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Agglomerations of polydisperse systems of spherical particles are created in computer simulations using a simplified stochastic-hydrodynamic model: Particles sink to the bottom of the cylinder, taking into account gravity reduced by the buoyant force, the Stokes friction force, the added mass effect, and random velocity changes. Two types of particles are considered, with one of them being able to create connections to neighboring particles of the same type, thus forming a network within the agglomeration at the bottom of a cylinder. Decreasing the fraction of these particles, a percolation transition occurs. The critical regime is determined by investigating the maximum cluster size and the percolation susceptibility.Keywords: binary system, maximum cluster size, percolation, polydisperse
Procedia PDF Downloads 582868 Relationship between Depression, Stress, and Life Satisfaction among Students
Authors: Rexa Pasha
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The aim of this study was to examine the relationship between depression, stress and life satisfaction with sleep disturbance among Islamic Azad University Ahvaz Branch students. Samples in the study included 230 students who were selected by stratified random sampling. For data collection, the Beck Depression Inventory, stress, life satisfaction and quality of sleep (PSQI) was used. Which all have acceptable reliability and validity. This study was correlation and Data analysis using Pearson correlation and multivariate regression significance level (p2867 Uses of Fibrinogen Concentrate in the Management of Trauma-Induced Coagulopathy in the Prehospital Environment: A Scoping Review
Authors: Nura Khattab, Fayad Al-Haimus, Teruko Kishibe, Netanel Krugliak, Melissa McGowan, Brodie Nolan
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Trauma-induced coagulopathy remains a significant contributor to mortality in severely injured patients. Fibrinogen is essential for early hemostasis and is recognized as the first coagulation factor to fall below critical levels, compromising the coagulation cascade. Early administration of fibrinogen concentrate may be feasible and effective to prevent coagulopathy. We conducted this scoping review to characterize the existing quantity of literature, and to explore the usage of prehospital fibrinogen concentrate products in improving clinical outcomes in trauma patients. Methods: A search strategy was developed in consultation with an information specialist. We searched MEDLINE, Embase, Cochrane, and Scopus from inception to May 6th 2024. English studies evaluating prehospital/military usage of fibrinogen concentrate in trauma patients were included. Studies were assessed by three independent reviewers for meeting inclusion and exclusion criteria. Reference lists of included articles were reviewed to identify additional studies meeting inclusion criteria. Clinical endpoints regarding fibrinogen concentrate were extracted and synthesized. Results: The literature search returned 1301 articles with seven studies meeting the inclusion criteria. Five studies (71%) were conducted in civilian settings and two studies (29%) were conducted in military settings. Of the included studies, three (43%) utilized a randomized control trial. We identified seven outcomes that compared varying concentrations of fibrinogen or fibrinogen concentrate to a placebo group. The outcomes included overall mortality, death from hemorrhage, thromboembolic events, clotting time, maximum clot firmness, clot stability at ER admission, and fibrinogen concentration at ER admission. Apart from thromboembolic events, all other reported outcomes showed statistically significant differences in group comparisons, determined using p values. The four (57%) non-clinical studies underscored the robustness, practicality, and degree of fibrinogen concentrate utilization in military environments and retrieval services. Conclusion: Preliminary research suggests that prehospital fibrinogen concentrate administration in traumatic bleeding patients is both feasible and effective, improving mortality and clotting parameters. While implementing a time-saving and proactive approach with fibrinogen holds potential for enhancing trauma care, the current evidence is limited. Further studies in this novel field are warranted.Keywords: fibrinogen concentrate, prehospital, military, trauma, trauma-induced coagulopathy
Procedia PDF Downloads 232866 Defining of the Shape of the Spine Using Moiré Method in Case of Patients with Scheuermann Disease
Authors: Petra Balla, Gabor Manhertz, Akos Antal
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Nowadays spinal deformities are very frequent problems among teenagers. Scheuermann disease is a one dimensional deformity of the spine, but it has prevalence over 11% of the children. A traditional technology, the moiré method was used by us for screening and diagnosing this type of spinal deformity. A LabVIEW program has been developed to evaluate the moiré pictures of patients with Scheuermann disease. Two different solutions were tested in this computer program, the extreme and the inflexion point calculation methods. Effects using these methods were compared and according to the results both solutions seemed to be appropriate. Statistical results showed better efficiency in case of the extreme search method where the average difference was only 6,09⁰.Keywords: spinal deformity, picture evaluation, Moiré method, Scheuermann disease, curve detection, Moiré topography
Procedia PDF Downloads 3512865 Predicting the Uniaxial Strength Distribution of Brittle Materials Based on a Uniaxial Test
Authors: Benjamin Sonnenreich
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Brittle fracture failure probability is best described using a stochastic approach which is based on the 'weakest link concept' and the connection between a microstructure and macroscopic fracture scale. A general theoretical and experimental framework is presented to predict the uniaxial strength distribution according to independent uniaxial test data. The framework takes as input the applied stresses, the geometry, the materials, the defect distributions and the relevant random variables from uniaxial test results and gives as output an overall failure probability that can be used to improve the reliability of practical designs. Additionally, the method facilitates comparisons of strength data from several sources, uniaxial tests, and sample geometries.Keywords: brittle fracture, strength distribution, uniaxial, weakest link concept
Procedia PDF Downloads 3222864 RAPD Analysis of the Genetic Polymorphism in the Collection of Rye Cultivars
Authors: L. Petrovičová, Ž. Balážová, Z. Gálová, M. Wójcik-Jagła, M. Rapacz
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In the present study, RAPD-PCR was used to assess genetic diversity of the rye including landrances and new rye cultivars coming from Central Europe and the Union of Soviet Socialist Republics (SUN). Five arbitrary random primers were used to determine RAPD polymorphism in the set of 38 rye genotypes. These primers amplified altogether 43 different DNA fragments with an average number of 8.6 fragments per genotypes. The number of fragments ranged from 7 (RLZ 8, RLZ 9 and RLZ 10) to 12 (RLZ 6). DI and PIC values of all RAPD markers were higher than 0.8 that generally means high level of polymorphism detected between rye genotypes. The dendrogram based on hierarchical cluster analysis using UPGMA algorithm was prepared. The cultivars were grouped into two main clusters. In this experiment, RAPD proved to be a rapid, reliable and practicable method for revealing of polymorphism in the rye cultivars.Keywords: genetic diversity, polymorphism, RAPD markers, Secale cereale L.
Procedia PDF Downloads 4412863 Automatic Threshold Search for Heat Map Based Feature Selection: A Cancer Dataset Analysis
Authors: Carlos Huertas, Reyes Juarez-Ramirez
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Public health is one of the most critical issues today; therefore, there is great interest to improve technologies in the area of diseases detection. With machine learning and feature selection, it has been possible to aid the diagnosis of several diseases such as cancer. In this work, we present an extension to the Heat Map Based Feature Selection algorithm, this modification allows automatic threshold parameter selection that helps to improve the generalization performance of high dimensional data such as mass spectrometry. We have performed a comparison analysis using multiple cancer datasets and compare against the well known Recursive Feature Elimination algorithm and our original proposal, the results show improved classification performance that is very competitive against current techniques.Keywords: biomarker discovery, cancer, feature selection, mass spectrometry
Procedia PDF Downloads 3362862 Benefits of Tourist Experiences for Families: A Systematic Literature Review Using Nvivo
Authors: Diana Cunha, Catarina Coelho, Ana Paula Relvas, Elisabeth Kastenholz
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Context: Tourist experiences have a recognized impact on the well-being of individuals. However, studies on the specific benefits of tourist experiences for families are scattered across different disciplines. This study aims to systematically review the literature to synthesize the evidence on the benefits of tourist experiences for families. Research Aim: The main objective is to systematize the evidence in the literature regarding the benefits of tourist experiences for families. Methodology: A systematic literature review was conducted using Nvivo, analyzing 33 scientific studies obtained from various databases. The search terms used were "family"/ "couple" and "tourist experience". The studies included quantitative, qualitative, mixed methods, and literature reviews. All works prior to the year 2000 were excluded, and the search was restricted to full text. A language filter was also used, considering articles in Portuguese, English, and Spanish. For NVivo analysis, information was coded based on both deductive and inductive perspectives. To minimize the subjectivity of the selection and coding process, two of the authors discussed the process and agreed on criteria that would make the coding more objective. Once the coding process in NVivo was completed, the data relating to the identification/characterization of the works were exported to the Statistical Package for the Social Sciences (SPPS), to characterize the sample. Findings: The results highlight that tourist experiences have several benefits for family systems, including the strengthening of family and marital bonds, the creation of family memories, and overall well-being and life satisfaction. These benefits contribute to both immediate relationship quality improvement and long-term family identity construction and transgenerational transmission. Theoretical Importance: This study emphasizes the systemic nature of the effects and relationships within family systems. It also shows that no harm was reported within these experiences, with only some challenges related to positive outcomes. Data Collection and Analysis Procedures: The study collected data from 33 scientific studies published predominantly after 2013. The data were analyzed using Nvivo, employing a systematic review approach. Question Addressed: The study addresses the question of the benefits of tourist experiences for families and how these experiences contribute to family functioning and individual well-being. Conclusion: Tourist experiences provide opportunities for families to enhance their interpersonal relationships and create lasting memories. The findings suggest that formal interventions based on evidence could further enhance the potential benefits of these experiences and be a valuable preventive tool in therapeutic interventions.Keywords: family systems, individual and family well-being, marital satisfaction, tourist experiences
Procedia PDF Downloads 682861 Artificial Intelligence Approach to Manage Human Resources Information System Process in the Construction Industry
Authors: Ahmed Emad Ahmed
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This paper aims to address the concept of human resources information systems (HRIS) and how to link it to new technologies such as artificial intelligence (AI) to be implemented in two human resources processes. A literature view has been collected to cover the main points related to HRIS, AI, and BC. A study case has been presented by generating a random HRIS to apply some AI operations to it. Then, an algorithm was applied to the database to complete some human resources processes, including training and performance appraisal, using a pre-trained AI model. After that, outputs and results have been presented and discussed briefly. Finally, a conclusion has been introduced to show the ability of new technologies such as AI and ML to be applied to the human resources management processes.Keywords: human resources new technologies, HR artificial intelligence, HRIS AI models, construction AI HRIS
Procedia PDF Downloads 1682860 Information Literacy: Concept and Importance
Authors: Gaurav Kumar
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An information literate person is one who uses information effectively in all its forms. When presented with questions or problems, an information literate person would know what information to look for, how to search efficiently and be able to access relevant sources. In addition, an information literate person would have the ability to evaluate and select appropriate information sources and to use the information effectively and ethically to answer questions or solve problems. Information literacy has become an important element in higher education. The information literacy movement has internationally recognized standards and learning outcomes. The step-by-step process of achieving information literacy is particularly crucial in an era where knowledge could be disseminated through a variety of media. What is the relationship between information literacy as we define it in higher education and information literacy among non-academic populations? What forces will change how we think about the definition of information literacy in the future and how we will apply the definition in all environments?Keywords: information literacy, human beings, visual media and computer network etc, information literacy
Procedia PDF Downloads 3352859 The Human Resources Management for the Temple in Northeastern Thailand
Authors: Routsukol Sunalai
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This research purpose is to study and compare the administration of Buddhist monks at northeastern Thailand. The samples used in the study are the priest in the Northeast by simple random sampling for 190 sampling. The tools used in this study is questioner were created in the 40 question items. The statistics used for data analysis were percentage, average, and standard deviation. The research found that the human resources management for the Buddhist monks as a whole is moderate. But it was found that the highest average is the policy followed by the management information. The Buddhist monks aged less than 25 years old with the overall difference was not significant. The priests who are less than 10 years in the monk experience and the priest has long held in the position for 10 years are not different in the significant level.Keywords: employee job-related outcomes, ethical institutionalization, quality of work life, stock exchange of Thailand
Procedia PDF Downloads 2082858 Investigation of Acidizing Corrosion Inhibitors for Mild Steel in Hydrochloric Acid: Theoretical and Experimental Approaches
Authors: Ambrish Singh
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The corrosion inhibition performance of pyran derivatives (AP) on mild steel in 15% HCl was investigated by electrochemical impedance spectroscopy (EIS), potentiodynamic polarization, weight loss, contact angle, and scanning electron microscopy (SEM) measurements, DFT and molecular dynamic simulation. The adsorption of APs on the surface of mild steel obeyed Langmuir isotherm. The potentiodynamic polarization study confirmed that inhibitors are mixed type with cathodic predominance. Molecular dynamic simulation was applied to search for the most stable configuration and adsorption energies for the interaction of the inhibitors with Fe (110) surface. The theoretical data obtained are, in most cases, in agreement with experimental results.Keywords: acidizing inhibitor, pyran derivatives, DFT, molecular simulation, mild steel, EIS
Procedia PDF Downloads 193