Search results for: ANOVA score model
Commenced in January 2007
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Edition: International
Paper Count: 18726

Search results for: ANOVA score model

18396 The Effect of Articial Intelligence on Physical Education Analysis and Sports Science

Authors: Peter Adly Hamdy Fahmy

Abstract:

The aim of the study was to examine the effects of a physical education program on student learning by combining the teaching of personal and social responsibility (TPSR) with a physical education model and TPSR with a traditional teaching model, these learning outcomes involving self-learning. -Study. Athletic performance, enthusiasm for sport, group cohesion, sense of responsibility and game performance. The participants were 3 secondary school physical education teachers and 6 physical education classes, 133 participants with students from the experimental group with 75 students and the control group with 58 students, and each teacher taught the experimental group and the control group for 16 weeks. The research methods used surveys, interviews and focus group meetings. Research instruments included the Personal and Social Responsibility Questionnaire, Sports Enthusiasm Scale, Group Cohesion Scale, Sports Self-Efficacy Scale, and Game Performance Assessment Tool. Multivariate analyzes of covariance and repeated measures ANOVA were used to examine differences in student learning outcomes between combining the TPSR with a physical education model and the TPSR with a traditional teaching model. The research findings are as follows: 1) The TPSR sports education model can improve students' learning outcomes, including sports self-efficacy, game performance, sports enthusiasm, team cohesion, group awareness and responsibility. 2) A traditional teaching model with TPSR could improve student learning outcomes, including sports self-efficacy, responsibility, and game performance. 3) The sports education model with TPSR could improve learning outcomes more than the traditional teaching model with TPSR, including sports self-efficacy, sports enthusiasm, responsibility and game performance. 4) Based on qualitative data on teachers' and students' learning experience, the physical education model with TPSR significantly improves learning motivation, group interaction and sense of play. The results suggest that physical education with TPSR could further improve learning outcomes in the physical education program. On the other hand, the hybrid model curriculum projects TPSR - Physical Education and TPSR - Traditional Education are good curriculum projects for moral character education that can be used in school physics.

Keywords: approach competencies, physical, education, teachers employment, graduate, physical education and sport sciences, SWOT analysis character education, sport season, game performance, sport competence

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18395 Correlation of Unsuited and Suited 5ᵗʰ Female Hybrid III Anthropometric Test Device Model under Multi-Axial Simulated Orion Abort and Landing Conditions

Authors: Christian J. Kennett, Mark A. Baldwin

Abstract:

As several companies are working towards returning American astronauts back to space on US-made spacecraft, NASA developed a human flight certification-by-test and analysis approach due to the cost-prohibitive nature of extensive testing. This process relies heavily on the quality of analytical models to accurately predict crew injury potential specific to each spacecraft and under dynamic environments not tested. As the prime contractor on the Orion spacecraft, Lockheed Martin was tasked with quantifying the correlation of analytical anthropometric test devices (ATDs), also known as crash test dummies, against test measurements under representative impact conditions. Multiple dynamic impact sled tests were conducted to characterize Hybrid III 5th ATD lumbar, head, and neck responses with and without a modified shuttle-era advanced crew escape suit (ACES) under simulated Orion landing and abort conditions. Each ATD was restrained via a 5-point harness in a mockup Orion seat fixed to a dynamic impact sled at the Wright Patterson Air Force Base (WPAFB) Biodynamics Laboratory in the horizontal impact accelerator (HIA). ATDs were subject to multiple impact magnitudes, half-sine pulse rise times, and XZ - ‘eyeballs out/down’ or Z-axis ‘eyeballs down’ orientations for landing or an X-axis ‘eyeballs in’ orientation for abort. Several helmet constraint devices were evaluated during suited testing. Unique finite element models (FEMs) were developed of the unsuited and suited sled test configurations using an analytical 5th ATD model developed by LSTC (Livermore, CA) and deformable representations of the seat, suit, helmet constraint countermeasures, and body restraints. Explicit FE analyses were conducted using the non-linear solver LS-DYNA. Head linear and rotational acceleration, head rotational velocity, upper neck force and moment, and lumbar force time histories were compared between test and analysis using the enhanced error assessment of response time histories (EEARTH) composite score index. The EEARTH rating paired with the correlation and analysis (CORA) corridor rating provided a composite ISO score that was used to asses model correlation accuracy. NASA occupant protection subject matter experts established an ISO score of 0.5 or greater as the minimum expectation for correlating analytical and experimental ATD responses. Unsuited 5th ATD head X, Z, and resultant linear accelerations, head Y rotational accelerations and velocities, neck X and Z forces, and lumbar Z forces all showed consistent ISO scores above 0.5 in the XZ impact orientation, regardless of peak g-level or rise time. Upper neck Y moments were near or above the 0.5 score for most of the XZ cases. Similar trends were found in the XZ and Z-axis suited tests despite the addition of several different countermeasures for restraining the helmet. For the X-axis ‘eyeballs in’ loading direction, only resultant head linear acceleration and lumbar Z-axis force produced ISO scores above 0.5 whether unsuited or suited. The analytical LSTC 5th ATD model showed good correlation across multiple head, neck, and lumbar responses in both the unsuited and suited configurations when loaded in the XZ ‘eyeballs out/down’ direction. Upper neck moments were consistently the most difficult to predict, regardless of impact direction or test configuration.

Keywords: impact biomechanics, manned spaceflight, model correlation, multi-axial loading

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18394 Lineup Optimization Model of Basketball Players Based on the Prediction of Recursive Neural Networks

Authors: Wang Yichen, Haruka Yamashita

Abstract:

In recent years, in the field of sports, decision making such as member in the game and strategy of the game based on then analysis of the accumulated sports data are widely attempted. In fact, in the NBA basketball league where the world's highest level players gather, to win the games, teams analyze the data using various statistical techniques. However, it is difficult to analyze the game data for each play such as the ball tracking or motion of the players in the game, because the situation of the game changes rapidly, and the structure of the data should be complicated. Therefore, it is considered that the analysis method for real time game play data is proposed. In this research, we propose an analytical model for "determining the optimal lineup composition" using the real time play data, which is considered to be difficult for all coaches. In this study, because replacing the entire lineup is too complicated, and the actual question for the replacement of players is "whether or not the lineup should be changed", and “whether or not Small Ball lineup is adopted”. Therefore, we propose an analytical model for the optimal player selection problem based on Small Ball lineups. In basketball, we can accumulate scoring data for each play, which indicates a player's contribution to the game, and the scoring data can be considered as a time series data. In order to compare the importance of players in different situations and lineups, we combine RNN (Recurrent Neural Network) model, which can analyze time series data, and NN (Neural Network) model, which can analyze the situation on the field, to build the prediction model of score. This model is capable to identify the current optimal lineup for different situations. In this research, we collected all the data of accumulated data of NBA from 2019-2020. Then we apply the method to the actual basketball play data to verify the reliability of the proposed model.

Keywords: recurrent neural network, players lineup, basketball data, decision making model

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18393 SVM-RBN Model with Attentive Feature Culling Method for Early Detection of Fruit Plant Diseases

Authors: Piyush Sharma, Devi Prasad Sharma, Sulabh Bansal

Abstract:

Diseases are fairly common in fruits and vegetables because of the changing climatic and environmental circumstances. Crop diseases, which are frequently difficult to control, interfere with the growth and output of the crops. Accurate disease detection and timely disease control measures are required to guarantee high production standards and good quality. In India, apples are a common crop that may be afflicted by a variety of diseases on the fruit, stem, and leaves. It is fungi, bacteria, and viruses that trigger the early symptoms of leaf diseases. In order to assist farmers and take the appropriate action, it is important to develop an automated system that can be used to detect the type of illnesses. Machine learning-based image processing can be used to: this research suggested a system that can automatically identify diseases in apple fruit and apple plants. Hence, this research utilizes the hybrid SVM-RBN model. As a consequence, the model may produce results that are more effective in terms of accuracy, precision, recall, and F1 Score, with respective values of 96%, 99%, 94%, and 93%.

Keywords: fruit plant disease, crop disease, machine learning, image processing, SVM-RBN

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18392 Enhancing Spatial Interpolation: A Multi-Layer Inverse Distance Weighting Model for Complex Regression and Classification Tasks in Spatial Data Analysis

Authors: Yakin Hajlaoui, Richard Labib, Jean-François Plante, Michel Gamache

Abstract:

This study introduces the Multi-Layer Inverse Distance Weighting Model (ML-IDW), inspired by the mathematical formulation of both multi-layer neural networks (ML-NNs) and Inverse Distance Weighting model (IDW). ML-IDW leverages ML-NNs' processing capabilities, characterized by compositions of learnable non-linear functions applied to input features, and incorporates IDW's ability to learn anisotropic spatial dependencies, presenting a promising solution for nonlinear spatial interpolation and learning from complex spatial data. it employ gradient descent and backpropagation to train ML-IDW, comparing its performance against conventional spatial interpolation models such as Kriging and standard IDW on regression and classification tasks using simulated spatial datasets of varying complexity. the results highlight the efficacy of ML-IDW, particularly in handling complex spatial datasets, exhibiting lower mean square error in regression and higher F1 score in classification.

Keywords: deep learning, multi-layer neural networks, gradient descent, spatial interpolation, inverse distance weighting

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18391 Thick Data Analytics for Learning Cataract Severity: A Triplet Loss Siamese Neural Network Model

Authors: Jinan Fiaidhi, Sabah Mohammed

Abstract:

Diagnosing cataract severity is an important factor in deciding to undertake surgery. It is usually conducted by an ophthalmologist or through taking a variety of fundus photography that needs to be examined by the ophthalmologist. This paper carries out an investigation using a Siamese neural net that can be trained with small anchor samples to score cataract severity. The model used in this paper is based on a triplet loss function that takes the ophthalmologist best experience in rating positive and negative anchors to a specific cataract scaling system. This approach that takes the heuristics of the ophthalmologist is generally called the thick data approach, which is a kind of machine learning approach that learn from a few shots. Clinical Relevance: The lens of the eye is mostly made up of water and proteins. A cataract occurs when these proteins at the eye lens start to clump together and block lights causing impair vision. This research aims at employing thick data machine learning techniques to rate the severity of the cataract using Siamese neural network.

Keywords: thick data analytics, siamese neural network, triplet-loss model, few shot learning

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18390 A Model for Academic Coaching for Success and Inclusive Excellence in Science, Technology, Engineering, and Mathematics Education

Authors: Sylvanus N. Wosu

Abstract:

Research shows that factors, such as low motivation, preparation, resources, emotional and social integration, and fears of risk-taking, are the most common barriers to access, matriculation, and retention into science, technology, engineering, and mathematics (STEM) disciplines for underrepresented (URM) students. These factors have been shown to impact students’ attraction and success in STEM fields. Standardized tests such as the SAT and ACT often used as predictor of success, are not always true predictors of success for African and Hispanic American students. Without an adequate academic support environment, even a high SAT score does not guarantee academic success in science and engineering. This paper proposes a model for Academic Coaching for building success and inclusive excellence in STEM education. Academic coaching is framed as a process of motivating students to be independent learners through relational mentorship, facilitating learning supports inside and outside of the classroom or school environment, and developing problem-solving skills and success attitudes that lead to higher performance in the specific subjects. The model is formulated based on best strategies and practices for enriching Academic Performance Impact skills and motivating students’ interests in STEM. A scaled model for measuring the Academic Performance Impact (API) index and STEM is discussed. The study correlates API with state standardized test and shows that the average impact of those skills can be predicted by the Academic Performance Impact (API) index or Academic Preparedness Index.

Keywords: diversity, equity, graduate education, inclusion, inclusive excellence, model

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18389 QSAR, Docking and E-pharmacophore Approach on Novel Series of HDAC Inhibitors with Thiophene Linker as Anticancer Agents

Authors: Harish Rajak, Preeti Patel

Abstract:

HDAC inhibitors can reactivate gene expression and inhibit the growth and survival of cancer cells. The 3D-QSAR and Pharmacophore modeling studies were performed to identify important pharmacophoric features and correlate 3D-chemical structure with biological activity. The pharmacophore hypotheses were developed using e-pharmacophore script and phase module. Pharmacophore hypothesis represents the 3D arrangement of molecular features necessary for activity. A series of 55 compounds with well-assigned HDAC inhibitory activity was used for 3D-QSAR model development. Best 3D-QSAR model, which is a five PLS factor model with good statistics and predictive ability, acquired Q2 (0.7293), R2 (0.9811) and standard deviation (0.0952). Molecular docking were performed using Histone Deacetylase protein (PDB ID: 1t69) and prepared series of hydroxamic acid based HDAC inhibitors. Docking study of compound 43 show significant binding interactions Ser 276 and oxygen atom of dioxine cap region, Gly 151 and amino group and Asp 267 with carboxyl group of CONHOH, which are essential for anticancer activity. On docking, most of the compounds exhibited better glide score values between -8 to -10.5. We have established structure activity correlation using docking, energetic based pharmacophore modelling, pharmacophore and atom based 3D QSAR model. The results of these studies were further used for the design and testing of new HDAC analogs.

Keywords: Docking, e-pharmacophore, HDACIs, QSAR, Suberoylanilidehydroxamic acid.

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18388 Neural Networks Models for Measuring Hotel Users Satisfaction

Authors: Asma Ameur, Dhafer Malouche

Abstract:

Nowadays, user comments on the Internet have an important impact on hotel bookings. This confirms that the e-reputation issue can influence the likelihood of customer loyalty to a hotel. In this way, e-reputation has become a real differentiator between hotels. For this reason, we have a unique opportunity in the opinion mining field to analyze the comments. In fact, this field provides the possibility of extracting information related to the polarity of user reviews. This sentimental study (Opinion Mining) represents a new line of research for analyzing the unstructured textual data. Knowing the score of e-reputation helps the hotelier to better manage his marketing strategy. The score we then obtain is translated into the image of hotels to differentiate between them. Therefore, this present research highlights the importance of hotel satisfaction ‘scoring. To calculate the satisfaction score, the sentimental analysis can be manipulated by several techniques of machine learning. In fact, this study treats the extracted textual data by using the Artificial Neural Networks Approach (ANNs). In this context, we adopt the aforementioned technique to extract information from the comments available in the ‘Trip Advisor’ website. This actual paper details the description and the modeling of the ANNs approach for the scoring of online hotel reviews. In summary, the validation of this used method provides a significant model for hotel sentiment analysis. So, it provides the possibility to determine precisely the polarity of the hotel users reviews. The empirical results show that the ANNs are an accurate approach for sentiment analysis. The obtained results show also that this proposed approach serves to the dimensionality reduction for textual data’ clustering. Thus, this study provides researchers with a useful exploration of this technique. Finally, we outline guidelines for future research in the hotel e-reputation field as comparing the ANNs with other technique.

Keywords: clustering, consumer behavior, data mining, e-reputation, machine learning, neural network, online hotel ‘reviews, opinion mining, scoring

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18387 Enzymatic Hydrolysis of Sugar Cane Bagasse Using Recombinant Hemicellulases

Authors: Lorena C. Cintra, Izadora M. De Oliveira, Amanda G. Fernandes, Francieli Colussi, Rosália S. A. Jesuíno, Fabrícia P. Faria, Cirano J. Ulhoa

Abstract:

Xylan is the main component of hemicellulose and for its complete degradation is required cooperative action of a system consisting of several enzymes including endo-xylanases (XYN), β-xylosidases (XYL) and α-L-arabinofuranosidases (ABF). The recombinant hemicellulolytic enzymes an endoxylanase (HXYN2), β-xylosidase (HXYLA), and an α-L-arabinofuranosidase (ABF3) were used in hydrolysis tests. These three enzymes are produced by filamentous fungi and were expressed heterologously and produced in Pichia pastoris previously. The aim of this work was to evaluate the effect of recombinant hemicellulolytic enzymes on the enzymatic hydrolysis of sugarcane bagasse (SCB). The interaction between the three recombinant enzymes during SCB pre-treated by steam explosion hydrolysis was performed with different concentrations of HXYN2, HXYLA and ABF3 in different ratios in according to a central composite rotational design (CCRD) 23, including six axial points and six central points, totaling 20 assays. The influence of the factors was assessed by analyzing the main effects and interaction between the factors, calculated using Statistica 8.0 software (StatSoft Inc. Tulsa, OK, USA). The Pareto chart was constructed with this software and showed the values of the Student’s t test for each recombinant enzyme. It was considered as response variable the quantification of reducing sugars by DNS (mg/mL). The Pareto chart showed that the recombinant enzyme ABF3 exerted more significant effect during SCB hydrolysis, with higher concentrations and with the lowest concentration of this enzyme. It was performed analysis of variance according to Fisher method (ANOVA). In ANOVA for the release of reducing sugars (mg/ml) as the variable response, the concentration of ABF3 showed significance during hydrolysis SCB. The result obtained by ANOVA, is in accordance with those presented in the analysis method based on the statistical Student's t (Pareto chart). The degradation of the central chain of xylan by HXYN2 and HXYLA was more strongly influenced by ABF3 action. A model was obtained, and it describes the performance of the interaction of all three enzymes for the release of reducing sugars, and can be used to better explain the results of the statistical analysis. The formulation capable of releasing the higher levels of reducing sugars had the following concentrations: HXYN2 with 600 U/g of substrate, HXYLA with 11.5 U.g-1 and ABF3 with 0.32 U.g-1. In conclusion, the recombinant enzyme that has a more significant effect during SCB hydrolysis was ABF3. It is noteworthy that the xylan present in the SCB is arabinoglucoronoxylan, due to this fact debranching enzymes are important to allow access of enzymes that act on the central chain.

Keywords: experimental design, hydrolysis, recombinant enzymes, sugar cane bagasse

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18386 Integrated Approach of Quality Function Deployment, Sensitivity Analysis and Multi-Objective Linear Programming for Business and Supply Chain Programs Selection

Authors: T. T. Tham

Abstract:

The aim of this study is to propose an integrated approach to determine the most suitable programs, based on Quality Function Deployment (QFD), Sensitivity Analysis (SA) and Multi-Objective Linear Programming model (MOLP). Firstly, QFD is used to determine business requirements and transform them into business and supply chain programs. From the QFD, technical scores of all programs are obtained. All programs are then evaluated through five criteria (productivity, quality, cost, technical score, and feasibility). Sets of weight of these criteria are built using Sensitivity Analysis. Multi-Objective Linear Programming model is applied to select suitable programs according to multiple conflicting objectives under a budget constraint. A case study from the Sai Gon-Mien Tay Beer Company is given to illustrate the proposed methodology. The outcome of the study provides a comprehensive picture for companies to select suitable programs to obtain the optimal solution according to their preference.

Keywords: business program, multi-objective linear programming model, quality function deployment, sensitivity analysis, supply chain management

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18385 Re-Analyzing Energy-Conscious Design

Authors: Svetlana Pushkar, Oleg Verbitsky

Abstract:

An energy-conscious design for a classroom in a hot-humid climate is reanalyzed. The hypothesis of this study is that use of photovoltaic (PV) electricity generation in building operation energy consumption will lead to re-analysis of the energy-conscious design. Therefore, the objective of this study is to reanalyze the energy-conscious design by evaluating the environmental impact of operational energy with PV electrical generation. Using the hierarchical design structure of Eco-indicator 99, the alternatives for energy-conscious variables are statistically evaluated by applying a two-stage nested (hierarchical) ANOVA. The recommendations for the preferred solutions for application of glazing types, wall insulation, roof insulation, window size, roof mass, and window shading design alternatives were changed (for example, glazing type recommendations were changed from low-emissivity glazing, green, and double- glazed windows to low-emissivity glazing only), whereas the applications for the lighting control system and infiltration are not changed. Such analysis of operational energy can be defined as environment-conscious analysis.

Keywords: ANOVA, Eco-Indicator 99, energy-conscious design, hot–humid climate, photovoltaic

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18384 Effectiveness of Internet Psychological Counseling in Reducing Social Shyness Symptoms among Students of University of Tabuk

Authors: Khawla Saad Albalawi

Abstract:

The aim of this research was to explore the effectiveness of the internet counseling in reducing social shyness among the university's students. The sample consisted of 40 students and was divided into two groups: an experimental group and a control group. The social shyness scale (SSS) was administered to both groups before applying the counseling to the experimental group (as a pre-test). After that, the internet counseling was applied to the experimental group. Next, the SSS was administered to both groups (as a post-test). Finally, the SSS was administered to the experimental group (as an iterative application). Results suggest that: 1. There is a significant difference between the two groups in the post-test in all dimensions and the total score of the (SSS) in favor of the experimental group in all cases. 2. There is a significant difference between the pre- and the post-test of the experimental group in all dimensions and the total score of the (SSS) in favor of the post-test in all cases. 3. There is no significant difference between the post-test and the iterative application of the experimental group in all dimensions and the total score of the (SSS). The above results were discussed in light of previous research. Recommendations and future researches were suggested.

Keywords: internet psychological clinics, social interaction disorders, shyness, Twitter, Facebook

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18383 Impact of Nutritional Status on the Pubertal Transition in a Sample of Egyptian School Girls

Authors: Nayera E. Hassan, Salah Mostafa, Hamed Elkhayat, Kalled Hassan Sewidan, Sahar A. El-Masry, Manal Mouhamed Ali, Mones M. Abu Shady

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Pubertal growth is influenced by many factors including environmental and nutritional factors. Objective: To assess impact of nutritional status on pubertal staging, ovarian and uterine volumes among school girls. Method: Study was cross sectional and carried out on 1000 healthy school girls, aged 8-18 years selected randomly. They were categorized according to their ages into three groups: 8-12 years, 13-15 years and 16-18 years ±6 months, then according to their body mass index percentile to normal weight: (≥15-<85.), overweight (≥85-<95) and obese (≥95). All girls were subjected for physical, anthropometric (weight, height, body mass index), nutritional markers WAZ (weight/age Z score), HAZ (height/age Z score) and BMI-Z (body mass index Z score), pubertal assessment (Tanner stage) and pelvic transabdominal sonography (uterine and ovarian volumes). Results: Highly significant differences in ovarian and uterine volumes and nutritional markers (WAZ, HAZ and BMI-Z score) were detected among different grades of puberty in the two age groups (8-12 years, 13-15 years) coming in advance of obese girls (with increase of BMI); except HAZ in the second age group. Girls aged 16-18 years reached to final volume for the uterus and ovary with insignificant differences. Pubertal stage, ovarian and uterine sizes were highly significantly correlated with nutritional markers. Mean ages of onset: of puberty, menarche and complete puberty were, 11.65 + 1.84, 14.79 + 1.75 and 15.02 + 1.68 years respectively. Conclusion: Nutritional status has a crucial role in determining pubertal stage, ovarian and uterine volumes among Egyptian girls during the pubertal process.

Keywords: pubertal stage, nutritional markers, girls, ovarian and uterine volumes

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18382 Mathematical Model to Quantify the Phenomenon of Democracy

Authors: Mechlouch Ridha Fethi

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This paper presents a recent mathematical model in political sciences concerning democracy. The model is represented by a logarithmic equation linking the Relative Index of Democracy (RID) to Participation Ratio (PR). Firstly the meanings of the different parameters of the model were presented; and the variation curve of the RID according to PR with different critical areas was discussed. Secondly, the model was applied to a virtual group where we show that the model can be applied depending on the gender. Thirdly, it was observed that the model can be extended to different language models of democracy and that little use to assess the state of democracy for some International organizations like UNO.

Keywords: democracy, mathematic, modelization, quantification

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18381 Household Food Insecurity, Maternal Mental Health and Self-Efficacy

Authors: Nahid Salarkia, Nasrin Omidvar, Erfan Ghassemi, Vahideh Arab-Salari, Tirang Reza Neyestani

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Background: Household food insecurity has an adverse impact on the maternal mental health. This study was carried out to assess the relationship between household food insecurity, maternal depression and mother’s self-efficacy in Varamin, Iran, in 2014. Methods: In this cross-sectional study 423 mothers with children under 2 years old, with mean age 28.1±5.2 year; weight 66.3±13.4 kg; height 160.3± 5.7 cm and BMI 25.7±4.8 kg/m2 were selected by a multistage random sampling scheme. The instruments were: Beck Depression Inventory (BDI-III) and mother’s self-efficacy questionnaire. Data was analyzed using χ2 test, ANOVA and Pearson correlation. Results: Mildly, moderately and severely food insecure households were 39.5, 9.7 and 3.1%, respectively. Mild, moderate and sever depression was: 18.7, 13.9 and 5.7%. Mean score of depression in moderate and severe food insecure (8.6±5.3) was more than mild food insecure (4.8±4.7) and food secure (3.1±3.6) mothers. Frequency of very good, good and low mother’s self-efficacy were 62.8, 36.5, and 0.7%, respectively. Very good mother’s self-efficacy in food secure mothers (33.4%) was more than mild (25.4%) and moderate-sever food insecure groups (4%). There was a negative significant association between household food insecurity and mother’s self-efficacy (r= -0.297, p<0.01), and between mother’s depression and self-efficacy (r= -0.309, p=0.001). Conclusion: Empowerment of mothers with educational programs and social support can decrease mothers’ depression and increase self-efficacy that lead to improve maternal practices in food insecure households.

Keywords: Household food insecurity, Iran, mothers, physiological characteristics, self-efficacy

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18380 Innovation Management: A Comparative Analysis among Organizations from United Arab Emirates, Saudi Arabia, Brazil and China

Authors: Asmaa Abazaid, Maram Al-Ostah, Nadeen Abu-Zahra, Ruba Bawab, Refaat Abdel-Razek

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Innovation audit is defined as a tool that can be used to reflect on how the innovation is managed in an organization. The aim of this study is to audit innovation in the second top Engineering Firms in the world, and one of the Small Medium Enterprises (SMEs) companies that are working in United Arab Emirates (UAE). The obtained results are then compared with four international companies from China and Brazil. The Diamond model has been used for auditing innovation in the two companies in UAE to evaluate their innovation management and to identify each company’s strengths and weaknesses from an innovation perspective. The results of the comparison between the two companies (Jacobs and Hyper General Contracting) revealed that Jacobs has support for innovation, its innovation processes are well managed, the company is committed to the development of its employees worldwide and the innovation system is flexible. Jacobs was doing best in all innovation management dimensions: strategy, process, organization, linkages and learning, while Hyper General Contracting did not score as Jacobs in any of the innovation dimensions. Furthermore, the audit results of both companies were compared with international companies to examine how well the two construction companies in UAE manage innovation relative to SABIC (Saudi company), Poly Easy and Arnious (Brazilian companies), Huagong tools and Guizohou Yibai (Chinese companies). The results revealed that Jacobs is doing best in learning and organization dimensions, while PolyEasy and Jacobs are equal in the linkage dimension. Huagong Tools scored the highest score in process dimension among all the compared companies. However, the highest score of strategy dimension was given to PolyEasy. On the other hand, Hyper General Contracting scored the lowest in all of the innovation management dimensions. It needs to improve its management of all the innovation management dimensions with special attention to be given to strategy, process, and linkage as they got scores below 4 out of 7 comparing with other dimensions. Jacobs scored the highest in three innovation management dimensions related to the six companies. However, the strategy dimension is considered low, and special attention is needed in this dimension.

Keywords: Brazil, China, innovation audit, innovation evaluation, innovation management, Saudi Arabia, United Arab Emirates

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18379 A Cross-Sectional Study on Smartphone Addiction, Sleep Hygiene, and Perceived Stress

Authors: Kriti Singh, Saurabh Tripathi, Pankaj Chaudhary, Abid Ali Ansari, Seema Nigam

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Introduction: The introduction of android and iOS has changed our lives dramatically over the past few years. The new generation is more dependent on their mobile phones for carrying out their daily pursuits. Smartphones have revolutionized our lives. The cutdown in rates of mobile network services has been affecting us drastically. A new type of dependence is seen among the people for Smartphones. A cross-sectional study was conducted to determine the state of addiction among the group of medical students, along with its association with sleep hygiene and anxiety. Material and Method: Study included 50 individuals in the age group of 18-35 years. Smartphone Addiction Scale Short Version, Sleep Hygiene Index, and Perceived Stress Scales were used conducting the study. Results: Mean age of 22 years (12%). The majority of subjects were 20-year olds (15 out of 50), the majority were males with few females. Mean Smartphone addiction score 39 (very severe), Mean Sleep Hygiene Index score 26.76 (moderate maladaptive hygiene and Mean Perceived Stress score of 19.92 (moderate stress). Conclusion: In majority students were found to have a very severe Smartphone Addiction with moderate sleep hygiene and a moderate level of perceived stress. The Smartphone was being used was for surfing social media applications.

Keywords: addiction perceived stress, sleep hygiene index, smartphone

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18378 Diagnostic Yield of CT PA and Value of Pre Test Assessments in Predicting the Probability of Pulmonary Embolism

Authors: Shanza Akram, Sameen Toor, Heba Harb Abu Alkass, Zainab Abdulsalam Altaha, Sara Taha Abdulla, Saleem Imran

Abstract:

Acute pulmonary embolism (PE) is a common disease and can be fatal. The clinical presentation is variable and nonspecific, making accurate diagnosis difficult. Testing patients with suspected acute PE has increased dramatically. However, the overuse of some tests, particularly CT and D-dimer measurement, may not improve care while potentially leading to patient harm and unnecessary expense. CTPA is the investigation of choice for PE. Its easy availability, accuracy and ability to provide alternative diagnosis has lowered the threshold for performing it, resulting in its overuse. Guidelines have recommended the use of clinical pretest probability tools such as ‘Wells score’ to assess risk of suspected PE. Unfortunately, implementation of guidelines in clinical practice is inconsistent. This has led to low risk patients being subjected to unnecessary imaging, exposure to radiation and possible contrast related complications. Aim: To study the diagnostic yield of CT PA, clinical pretest probability of patients according to wells score and to determine whether or not there was an overuse of CTPA in our service. Methods: CT scans done on patients with suspected P.E in our hospital from 1st January 2014 to 31st December 2014 were retrospectively reviewed. Medical records were reviewed to study demographics, clinical presentation, final diagnosis, and to establish if Wells score and D-Dimer were used correctly in predicting the probability of PE and the need for subsequent CTPA. Results: 100 patients (51male) underwent CT PA in the time period. Mean age was 57 years (24-91 years). Majority of patients presented with shortness of breath (52%). Other presenting symptoms included chest pain 34%, palpitations 6%, collapse 5% and haemoptysis 5%. D Dimer test was done in 69%. Overall Wells score was low (<2) in 28 %, moderate (>2 - < 6) in 47% and high (> 6) in 15% of patients. Wells score was documented in medical notes of only 20% patients. PE was confirmed in 12% (8 male) patients. 4 had bilateral PE’s. In high-risk group (Wells > 6) (n=15), there were 5 diagnosed PEs. In moderate risk group (Wells >2 - < 6) (n=47), there were 6 and in low risk group (Wells <2) (n=28), one case of PE was confirmed. CT scans negative for PE showed pleural effusion in 30, Consolidation in 20, atelactasis in 15 and pulmonary nodule in 4 patients. 31 scans were completely normal. Conclusion: Yield of CT for pulmonary embolism was low in our cohort at 12%. A significant number of our patients who underwent CT PA had low Wells score. This suggests that CT PA is over utilized in our institution. Wells score was poorly documented in medical notes. CT-PA was able to detect alternative pulmonary abnormalities explaining the patient's clinical presentation. CT-PA requires concomitant pretest clinical probability assessment to be an effective diagnostic tool for confirming or excluding PE. . Clinicians should use validated clinical prediction rules to estimate pretest probability in patients in whom acute PE is being considered. Combining Wells scores with clinical and laboratory assessment may reduce the need for CTPA.

Keywords: CT PA, D dimer, pulmonary embolism, wells score

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18377 The Achievement Model of University Social Responsibility

Authors: Le Kang

Abstract:

On the research question of 'how to achieve USR', this contribution reflects the concept of university social responsibility, identify three achievement models of USR as the society - diversified model, the university-cooperation model, the government - compound model, also conduct a case study to explore characteristics of Chinese achievement model of USR. The contribution concludes with discussion of how the university, government and society balance demands and roles, make necessarily strategic adjustment and innovative approach to repair the shortcomings of each achievement model.

Keywords: modern university, USR, achievement model, compound model

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18376 Evaluation of the Families' Psychological Nature and the Relationship between the Academic Success According to the Students' Opinion

Authors: Sebnem Erismen, Ahmet Guneyli, Azize Ummanel

Abstract:

The purpose of this study is to explore the relationship between the students' academic success and families' psychological nature. The study based upon the quantitative research, and descriptive model is used. Relational descriptive model is used while evaluating the relation between families’ psychological nature and the academic success level of the students. A total of 523 secondary school students have participated the study. Personal Information Form, Family Structure Evaluation Form (FSEF) and School Reports were employed as the primary methods of data gathering. ANOVA and LSD Scheffe Test were used for analysing the data. Results of the study indicate that there are differences between the FSEF scores according to the students’ and teachers’ gender; however, no differences between the class level and seniority of the teachers were seen. Regarding the academic success of the students, it was seen that majority of them have high points. It was also seen that the academic success level of the students differentiates regarding to the classroom teachers’ gender and seniority. In conclusion, it was seen that there is a relation between the families’ psychological nature and students' academic success.

Keywords: families’ perceived psychological nature, academic success, families effect on the academic success, education

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18375 An Accurate Brain Tumor Segmentation for High Graded Glioma Using Deep Learning

Authors: Sajeeha Ansar, Asad Ali Safi, Sheikh Ziauddin, Ahmad R. Shahid, Faraz Ahsan

Abstract:

Gliomas are most challenging and aggressive type of tumors which appear in different sizes, locations, and scattered boundaries. CNN is most efficient deep learning approach with outstanding capability of solving image analysis problems. A fully automatic deep learning based 2D-CNN model for brain tumor segmentation is presented in this paper. We used small convolution filters (3 x 3) to make architecture deeper. We increased convolutional layers for efficient learning of complex features from large dataset. We achieved better results by pushing convolutional layers up to 16 layers for HGG model. We achieved reliable and accurate results through fine-tuning among dataset and hyper-parameters. Pre-processing of this model includes generation of brain pipeline, intensity normalization, bias correction and data augmentation. We used the BRATS-2015, and Dice Similarity Coefficient (DSC) is used as performance measure for the evaluation of the proposed method. Our method achieved DSC score of 0.81 for complete, 0.79 for core, 0.80 for enhanced tumor regions. However, these results are comparable with methods already implemented 2D CNN architecture.

Keywords: brain tumor segmentation, convolutional neural networks, deep learning, HGG

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18374 Impact of Emergency Medicine Department Crowding on Mortality

Authors: Morteza Gharibi, Abdolghader Pakniat, Somayeh Bahrampouri

Abstract:

Introduction: Emergency department (E.R.) crowding is a serious widespread problem in hospitals that leads to irregularities, a slower rate of delivery of services to patients, and a long-term stay. In addition, the long-term stay in the E.D. reduces the possibility of providing services with appropriate quality to other patients who are undergoing medical emergencies, which leads to dissatisfaction among patients. This study aimed to determine the relationship between ED-crowding and the mortality rate of the patients referred to the E.D. In a retrospective cohort study, all patients who expired in first 24 hours of admission were enrolled in the study. Crowding index at the moment of admission was calculated using Edwin Score. The data including history and physical examination, time of arrival in the E.D., diagnosis (using ICD 10 code), time of death, cause of death, demographic information was recoded based on triage forms on admission and patients’ medical files. Data analysis was performed by using descriptive statistics and chi square test, ANOVA tests using SPSS ver. 19. The time of arrival in E.D. to death in crowded E.D. conditions, with an average of five hours and 25 minutes, was significantly higher than the average admission Time of arrival in E.D. to death in active and crowded E.D. conditions. More physicians and nurses can be employed during crowded times to reduce staff fatigue and improve their performance during these hours.

Keywords: mortality, emergency, department, crowding

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18373 Effects of Some Characteristics of Gynecological Cancer Diagnosis and Treatment on Women's Sexual Life Quality

Authors: Buse Bahitli, Samiye Mete

Abstract:

The aim of the study was to evaluate the quality of sexual life of women with diagnosed gynecological cancer and receive treatment. The study was a descriptive and cross-sectional type, and it was carried out with 276 women. Information Form and Sexual Quality of Life Scale-Female (SQOL) form was used in the study. The data was evaluated using Mann-Whitney U and Kruskal-Wallis test. In the study, Sexual Quality of Life Scale-Female average score was 68.83 ± 21.17. The %43.1 of women was endometrial cancer, %30.8 was cervical cancer, %24.6 was ovarian cancer, and %1.4 was vulvar cancer. The average time to diagnosis of patients is 41.80 ± 47.64 months. There was no significant difference mean SQOL according to individual/sociodemographic characteristics like age, education. Gynecological cancer-related characteristics like gynaecological cancer type, treatment type, surgery type were found not to affect the mean score of SQOL. However, it was found that the difference was due to the higher SQOL score in the group with a diagnosis time of 25 months and over (X²KW= 6.356, p= 0.046). The reason of significant difference means SQOL according to diagnosis over time might be that women adapted to cancer diagnosis. While women with gynaecologic cancer are evaluating their sexual lives, it is necessary to evaluate them with good evaluation tools.

Keywords: gynecological cancers, sexuality, quality of sexual life, SQOL

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18372 A Methodological Approach to Development of Mental Script for Mental Practice of Micro Suturing

Authors: Vaikunthan Rajaratnam

Abstract:

Intro: Motor imagery (MI) and mental practice (MP) can be an alternative to acquire mastery of surgical skills. One component of using this technique is the use of a mental script. The aim of this study was to design and develop a mental script for basic micro suturing training for skill acquisition using a low-fidelity rubber glove model and to describe the detailed methodology for this process. Methods: This study was based on a design and development research framework. The mental script was developed with 5 expert surgeons performing a cognitive walkthrough of the repair of a vertical opening in a rubber glove model using 8/0 nylon. This was followed by a hierarchal task analysis. A draft script was created, and face and content validity assessed with a checking-back process. The final script was validated with the recruitment of 28 participants, assessed using the Mental Imagery Questionnaire (MIQ). Results: The creation of the mental script is detailed in the full text. After assessment by the expert panel, the mental script had good face and content validity. The average overall MIQ score was 5.2 ± 1.1, demonstrating the validity of generating mental imagery from the mental script developed in this study for micro suturing in the rubber glove model. Conclusion: The methodological approach described in this study is based on an instructional design framework to teach surgical skills. This MP model is inexpensive and easily accessible, addressing the challenge of reduced opportunities to practice surgical skills. However, while motor skills are important, other non-technical expertise required by the surgeon is not addressed with this model. Thus, this model should act a surgical training augment, but not replace it.

Keywords: mental script, motor imagery, cognitive walkthrough, verbal protocol analysis, hierarchical task analysis

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18371 Application of Response Surface Methodology to Optimize the Factor Influencing the Wax Deposition of Malaysian Crude Oil

Authors: Basem Elarbe, Ibrahim Elganidi, Norida Ridzuan, Norhyati Abdullah

Abstract:

Wax deposition in production pipelines and transportation tubing from offshore to onshore is critical in the oil and gas industry due to low-temperature conditions. It may lead to a reduction in production, shut-in, plugging of pipelines and increased fluid viscosity. The most significant popular approach to solve this issue is by injection of a wax inhibitor into the channel. This research aims to determine the amount of wax deposition of Malaysian crude oil by estimating the effective parameters using (Design-Expert version 7.1.6) by response surface methodology (RSM) method. Important parameters affecting wax deposition such as cold finger temperature, inhibitor concentration and experimental duration were investigated. It can be concluded that SA-co-BA copolymer had a higher capability of reducing wax in different conditions where the minimum point of wax reduction was found at 300 rpm, 14℃, 1h, 1200 ppmThe amount of waxes collected for each parameter were 0.12g. RSM approach was applied using rotatable central composite design (CCD) to minimize the wax deposit amount. The regression model’s variance (ANOVA) results revealed that the R2 value of 0.9906, indicating that the model can be clarified 99.06% of the data variation, and just 0.94% of the total variation were not clarified by the model. Therefore, it indicated that the model is extremely significant, confirming a close agreement between the experimental and the predicted values. In addition, the result has shown that the amount of wax deposit decreased significantly with the increase of temperature and the concentration of poly (stearyl acrylate-co-behenyl acrylate) (SABA), which were set at 14°C and 1200 ppm, respectively. The amount of wax deposit was successfully reduced to the minimum value of 0.01 g after the optimization.

Keywords: wax deposition, SABA inhibitor, RSM, operation factors

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18370 Botulinum Toxin a in the Treatment of Late Facial Nerve Palsy Complications

Authors: Akulov M. A., Orlova O. R., Zaharov V. O., Tomskij A. A.

Abstract:

Introduction: One of the common postoperative complications of posterior cranial fossa (PCF) and cerebello-pontine angle tumor treatment is a facial nerve palsy, which leads to multiple and resistant to treatment impairments of mimic muscles structure and functions. After 4-6 months after facial nerve palsy with insufficient therapeutic intervention patients develop a postparalythic syndrome, which includes such symptoms as mimic muscle insufficiency, mimic muscle contractures, synkinesis and spontaneous muscular twitching. A novel method of treatment is the use of a recent local neuromuscular blocking agent– botulinum toxin A (BTA). Experience of BTA treatment enables an assumption that it can be successfully used in late facial nerve palsy complications to significantly increase quality of life of patients. Study aim. To evaluate the efficacy of botulinum toxin A (BTA) (Xeomin) treatment in patients with late facial nerve palsy complications. Patients and Methods: 31 patients aged 27-59 years 6 months after facial nerve palsy development were evaluated. All patients received conventional treatment, including massage, movement therapy etc. Facial nerve palsy developed after acoustic nerve tumor resection in 23 (74,2%) patients, petroclival meningioma resection – in 8 (25,8%) patients. The first group included 17 (54,8%) patients, receiving BT-therapy; the second group – 14 (45,2%) patients continuing conventional treatment. BT-injections were performed in synkinesis or contracture points 1-2 U on injured site and 2-4 U on healthy side (for symmetry). Facial nerve function was evaluated on 2 and 4 months of therapy according to House-Brackman scale. Pain syndrome alleviation was assessed on VAS. Results: At baseline all patients in the first and second groups demonstrated аpostparalytic syndrome. We observed a significant improvement in patients receiving BTA after only one month of treatment. Mean VAS score at baseline was 80,4±18,7 and 77,9±18,2 in the first and second group, respectively. In the first group after one month of treatment we observed a significant decrease of pain syndrome – mean VAS score was 44,7±10,2 (р<0,01), whereas in the second group VAS score was as high as 61,8±9,4 points (p>0,05). By the 3d month of treatment pain syndrome intensity continued to decrease in both groups, but, the first group demonstrated significantly better results; mean score was 8,2±3,1 and 31,8±4,6 in the first and second group, respectively (р<0,01). Total House-Brackman score at baseline was 3,67±0,16 in the first group and 3,74±0,19 in the second group. Treatment resulted in a significant symptom improvement in the first group, with no improvement in the second group. After 4 months of treatment House-Brockman score in the first group was 3,1-fold lower, than in the second group (р<0,05). Conclusion: Botulinum toxin injections decrease postparalytic syndrome symptoms in patients with facial nerve palsy.

Keywords: botulinum toxin, facial nerve palsy, postparalytic syndrome, synkinesis

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18369 Patient Satisfaction Measurement Using Face-Q for Non-Incisional Double-Eyelid Blepharoplasty with Modified Single-Knot Continuous Buried Suture Technique

Authors: Kwei Huan Liw, Sashi B. Darshan

Abstract:

Background: Double eyelid surgery has become one of the most sought-after aesthetic procedures among Asians. Many surgeons perform surgical blepharoplasty and various other methods of non-incisional blepharoplasty. Face-Q is a validated method of measuring patient satisfaction for facial aesthetic procedures. Here we have analyzed the overall eye satisfaction score, the upper eyelid appraisal score and the adverse effect on eyes score Methods: 274 patients (548 eyes), aged between 18 to 40 years old, were recruited from 2015-2018. Each patient underwent a non-incisional double-eyelid blepharoplasty using a single-knotted continuous buried suture. 3 – 5 stab incisions were made depending on the upper eyelid size. A needle loaded with 7-0 nylon is passed from the lateral most wound through the dermis and the conjunctiva in an alternate fashion into the remaining stab wounds. The suture is then tunneled back laterally in the deeper dermis and knotted securely with the suture end. The knot is then buried within the orbicularis oculi muscle. Each patient was required to fill the Face-Q questionnaire before the procedure and 2 weeks post procedure. The results are described based on the percentage of the maximum achievable score. Patients were reviewed after 12 to 18 months to assess the long-term outcome. Results: The overall eye satisfaction score demonstrated a high level of post-operative satisfaction (97.85%), compared to 27.32% pre-operatively. The appraisal of upper eyelid scores showed drastic improvement in perception post-operatively (95.31%) compared to 21.44% pre-operatively. Adverse effect on eyes score showed a very low post-operative complication rate (0.4%) The long-term follow-up showed 6 cases that had developed asymmetrical folds. Only 1 patient agreed for revision surgery. The other 5 patients were still satisfied with the outcome and were not keen for revision surgery. None of the cases had loosening of knots. Conclusion: Modified single-knot continuous buried suture technique is a simple and non-invasive method to create aesthetically pleasing non-surgical double-eyelids, which has long-term effects. Proper patient selection is crucial and good surgical technique is required to achieve a desirable outcome.

Keywords: blepharoplasty, double-eyelid, face-Q, non-incisional

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18368 An Analytical Approach to Assess and Compare the Vulnerability Risk of Operating Systems

Authors: Pubudu K. Hitigala Kaluarachchilage, Champike Attanayake, Sasith Rajasooriya, Chris P. Tsokos

Abstract:

Operating system (OS) security is a key component of computer security. Assessing and improving OSs strength to resist against vulnerabilities and attacks is a mandatory requirement given the rate of new vulnerabilities discovered and attacks occurring. Frequency and the number of different kinds of vulnerabilities found in an OS can be considered an index of its information security level. In the present study five mostly used OSs, Microsoft Windows (windows 7, windows 8 and windows 10), Apple’s Mac and Linux are assessed for their discovered vulnerabilities and the risk associated with each. Each discovered and reported vulnerability has an exploitability score assigned in CVSS score of the national vulnerability database. In this study the risk from vulnerabilities in each of the five Operating Systems is compared. Risk Indexes used are developed based on the Markov model to evaluate the risk of each vulnerability. Statistical methodology and underlying mathematical approach is described. Initially, parametric procedures are conducted and measured. There were, however, violations of some statistical assumptions observed. Therefore the need for non-parametric approaches was recognized. 6838 vulnerabilities recorded were considered in the analysis. According to the risk associated with all the vulnerabilities considered, it was found that there is a statistically significant difference among average risk levels for some operating systems, indicating that according to our method some operating systems have been more risk vulnerable than others given the assumptions and limitations. Relevant test results revealing a statistically significant difference in the Risk levels of different OSs are presented.

Keywords: cybersecurity, Markov chain, non-parametric analysis, vulnerability, operating system

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18367 Work Happiness for Personnel of Suan Sunandha Rajabhat University

Authors: Adisai Thovicha

Abstract:

This study is the survey research, designed to study the work happiness level of personnel at Suan Sunandha Rajabhat University. The sample group consisted of 329 personnel. The results were collected by stratified sampling, using work positions for each stage. The results were analyzed and calculated by computer program. Statistics used during analyzing were percentage, mean, and standard deviation. From the study, the work happiness level of personnel were in very high score range in both overall and specific category. The top category which received the most score was positive attitude, work satisfaction, life satisfaction, and negative attitude.

Keywords: work happiness, Suan Sunandha Rajabhat University, personnel, positive attitude

Procedia PDF Downloads 351