Search results for: regression discontinuity

Authors: Javier E. García-Gallo, Nelson J. Fonseca-Ruiz, John F. Duitama-Munoz

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Sepsis is a syndrome that occurs with physiological and biochemical abnormalities induced by severe infection and carries a high mortality and morbidity, therefore the severity of its condition must be interpreted quickly. After patient admission in an intensive care unit (ICU), it is necessary to synthesize the large volume of information that is collected from patients in a value that represents the severity of their condition. Traditional severity of illness scores seeks to be applicable to all patient populations, and usually assess in-hospital mortality. However, the use of machine learning techniques and the data of a population that shares a common characteristic could lead to the development of customized mortality prediction scores with better performance. This study presents the development of a score for the one-year mortality prediction of the patients that are admitted to an ICU with a sepsis diagnosis. 5650 ICU admissions extracted from the MIMICIII database were evaluated, divided into two groups: 70% to develop the score and 30% to validate it. Comorbidities, demographics and clinical information of the first 24 hours after the ICU admission were used to develop a mortality prediction score. LASSO (least absolute shrinkage and selection operator) and SGB (Stochastic Gradient Boosting) variable importance methodologies were used to select the set of variables that make up the developed score; each of this variables was dichotomized and a cut-off point that divides the population into two groups with different mean mortalities was found; if the patient is in the group that presents a higher mortality a one is assigned to the particular variable, otherwise a zero is assigned. These binary variables are used in a logistic regression (LR) model, and its coefficients were rounded to the nearest integer. The resulting integers are the point values that make up the score when multiplied with each binary variables and summed. The one-year mortality probability was estimated using the score as the only variable in a LR model. Predictive power of the score, was evaluated using the 1695 admissions of the validation subset obtaining an area under the receiver operating characteristic curve of 0.7528, which outperforms the results obtained with Sequential Organ Failure Assessment (SOFA), Oxford Acute Severity of Illness Score (OASIS) and Simplified Acute Physiology Score II (SAPSII) scores on the same validation subset. Observed and predicted mortality rates within estimated probabilities deciles were compared graphically and found to be similar, indicating that the risk estimate obtained with the score is close to the observed mortality, it is also observed that the number of events (deaths) is indeed increasing as the outcome go from the decile with the lowest probabilities to the decile with the highest probabilities. Sepsis is a syndrome that carries a high mortality, 43.3% for the patients included in this study; therefore, tools that help clinicians to quickly and accurately predict a worse prognosis are needed. This work demonstrates the importance of customization of mortality prediction scores since the developed score provides better performance than traditional scoring systems.

Keywords: intensive care, logistic regression model, mortality prediction, sepsis, severity of illness, stochastic gradient boosting

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Authors: Hadush Kidane Meresa

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The hydrological extremes frequency analysis is the foundation for the hydraulic engineering design, flood protection, drought management and water resources management and planning to utilize the available water resource to meet the desired objectives of different organizations and sectors in a country. This spatial variation of the statistical characteristics of the extreme flood and drought events are key practice for regional flood and drought analysis and mitigation management. For different hydro-climate of the regions, where the data set is short, scarcity, poor quality and insufficient, the regionalization methods are applied to transfer at-site data to a region. This study aims in regional high and low flow frequency analysis for Poland River Basins. Due to high frequent occurring of hydrological extremes in the region and rapid water resources development in this basin have caused serious concerns over the flood and drought magnitude and frequencies of the river in Poland. The magnitude and frequency result of high and low flows in the basin is needed for flood and drought planning, management and protection at present and future. Hydrological homogeneous high and low flow regions are formed by the cluster analysis of site characteristics, using the hierarchical and C- mean clustering and PCA method. Statistical tests for regional homogeneity are utilized, by Discordancy and Heterogeneity measure tests. In compliance with results of the tests, the region river basin has been divided into ten homogeneous regions. In this study, frequency analysis of high and low flows using AM for high flow and 7-day minimum low flow series is conducted using six statistical distributions. The use of L-moment and LL-moment method showed a homogeneous region over entire province with Generalized logistic (GLOG), Generalized extreme value (GEV), Pearson type III (P-III), Generalized Pareto (GPAR), Weibull (WEI) and Power (PR) distributions as the regional drought and flood frequency distributions. The 95% percentile and Flow duration curves of 1, 7, 10, 30 days have been plotted for 10 stations. However, the cluster analysis performed two regions in west and east of the province where L-moment and LL-moment method demonstrated the homogeneity of the regions and GLOG and Pearson Type III (PIII) distributions as regional frequency distributions for each region, respectively. The spatial variation and regional frequency distribution of flood and drought characteristics for 10 best catchment from the whole region was selected and beside the main variable (streamflow: high and low) we used variables which are more related to physiographic and drainage characteristics for identify and delineate homogeneous pools and to derive best regression models for ungauged sites. Those are mean annual rainfall, seasonal flow, average slope, NDVI, aspect, flow length, flow direction, maximum soil moisture, elevation, and drainage order. The regional high-flow or low-flow relationship among one streamflow characteristics with (AM or 7-day mean annual low flows) some basin characteristics is developed using Generalized Linear Mixed Model (GLMM) and Generalized Least Square (GLS) regression model, providing a simple and effective method for estimation of flood and drought of desired return periods for ungauged catchments.

Keywords: flood , drought, frequency, magnitude, regionalization, stochastic, ungauged, Poland

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Authors: Sepideh Yeganegi, Andre Laplume, Parshotam Dass, Cam-Loi Huynh

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This paper empirically examines organizational and institutional antecedents of entrepreneurial entry. We employ multi-level logistic regression modelling methods on a sub-sample of the Global Entrepreneurship Monitor’s 2011 survey covering 30 countries. The results reveal that employees who have experience with activities unrelated to the core technology of their organizations are more likely to spin out entrepreneurial ventures, whereas those with experiences related to the core technology are less likely to do so. In support of the recent theory, we find that the strength of intellectual property rights and the availability of venture capital have negative and positive effects, respectively, on the likelihood that employees turn into entrepreneurs. These institutional factors also moderate the effect of relatedness to core technology such that entrepreneurial entries by employees with experiences related to core technology are curbed more severely by stronger intellectual property rights protection regimes and lack of venture capital.

Keywords: spinouts, intellectual property rights, venture capital, entrepreneurship, organizational experiences, core technology

Procedia PDF Downloads 356

Authors: Pisit Potjanajaruwit

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The objective of this research was to study the influence of Integrated Marketing Communication on Buying Decision of Consumers in Bangkok. A total of 397 respondents were collected from customers who drive in Bangkok. A questionnaire was utilized as a tool to collect data. Statistics utilized in this research included frequency, percentage, mean, standard deviation, and multiple regression analysis. Data were analyzed by using Statistical Package for the Social Sciences. The findings revealed that the majority of respondents were male with the age between 25-34 years old, hold undergraduate degree, married and stay together. The average income of respondents was between 10,001-20,000 baht. In terms of occupation, the majority worked for private companies. The effect to the Buying Decision of Consumers in Bangkok to including sale promotion with the low interest and discount for an installment, selling by introducing and gave product information through sales persons, public relation by website, direct marketing by annual motor show and advertisement by television media.

Keywords: Bangkok metropolis, ECO car, integrated marketing communication, international standard

Procedia PDF Downloads 316

Authors: Mohammed Qutishat, Khaldoun Aldiabat, Khaled Bader, Mohammad Al Qadire

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Cyberchondria refers to the irrational increase of distress about the condition of one's health as a consequence of the World Wide Web quest for medical details. The aim of this study was to examine the relationship between emotional intelligence and cyberchondria among Omani university students. A descriptive correlational design was used to collect data from eligible 370 participants using the Emotional Intelligence Questionnaire, and the short-form version of the Cyberchondria Severity Scale (CSS-12) between January and May 2020 at XX University-Oman. The participants’ age ranged between 18 and 37 years (M = 20.28). The majority of the participants were female, 59.7% (n = 221), single 99.5% (368), in their second academic year, 29.2% (n =108). The mean score of cyberchondria experiences was 32.51, and the mean score of emotional intelligence was 34.91. Linear regression indicated a strong association between cyberchondria and emotional intelligence [F (34.639) = 5.885, P=.000], with a .086 R². In conclusion, the exchange of expertise and peer networking for health-related details utilizing the Internet can benefit students with and without having health problems. Further research and methods should be developed to help students track the online medical tools effectively for the right purposes.

Keywords: emotional intelligence, cyberchondria, smartphone addiction, social media

Procedia PDF Downloads 253

Authors: Anupam Deka, Indira Bardoloi

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Gender discrimination has been considered as a major obstacle in granting equal opportunity for women in higher education as education plays a pivotal role in a country’s socioeconomic development. To examine the empowerment of women in the higher education field of Assam, a case study has been carried out. In the first stage, an overview of enrollment of students in different courses has been made by considering the whole state. In the second stage, a study has been conducted regarding the enrollment of students in various degree and postgraduate courses for the period 2000-2007 at Gauhati University (one of the four universities of Assam), and the relevant data has been collected. It has been found that though the enrollment of students in the degree levels has been constantly increasing, but the enrollment of girls are not proportionately increasing, especially in commerce and law. On the other hand, in the postgraduate level, these proportions are higher in almost all subjects (except some subjects like M. COM., L.L.M, M. C. A., Mathematics, etc.), indicating that compared to boys, a higher number of girls are being admitted in postgraduate courses.

Keywords: field study, enrollment of girls in degree and postgratudate levels, regression lines, chi square test, diagrams, statistical tables

Procedia PDF Downloads 258

Authors: Mutaju Marobhe, Pastory Dickson

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This study explores the role of Foreign Direct Investment (FDI) in stimulating economic growth of emerging economies. FDIs have been associated with higher economic growth rates in developed countries due to the presence of conducive business conditions e.g. advanced financial markets which may accelerate the rate at which FDI boosts economic growth. So this study sets out to evaluate this macroeconomic phenomenon in emerging economies using the case study of Southern Africa Development Community (SADC) countries. The study uses Ease of Doing Business Index as a variable that moderates the relationship between FDI and economic growth. Panel data ranging from 2010 to 2019 from all SADC members are used and due to the unbalanced nature of the data, fixed effects regression analysis with moderation effect is used to assess this phenomenon. The conclusions and recommendations generated by this study will enable emerging economies to depict how they can be able to significantly improve FDI’s role in accelerating economic growth similarly to developed economies.

Keywords: ease of doing business, economic growth, emerging economies, foreign direct investment

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Authors: Sarah Akhtar, Rizwan Mahmood

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A detailed study of homogeneous alignment of liquid crystal molecules on a glass substrate will be presented. Thin films of polyimide were coated on several glass substrates. Various methods were employed to prepare coated surfaces to achieve desired alignment; these include traditionally rubbing the surface with a felt cloth then exposing them perpendicular to the easy axis with incandescent light (IL), linearly polarized ultraviolet (LPUVR) and un-polarized ultraviolet (UPUVR) radiation. The quality of the alignment was tested by measuring the tilt angle in the temperature range between 30°C to 55°C. Regression analysis of the data using ‘SigmaPlot’ suggests a gradual increase in tilt angle (1.1°-1.8°) for the rubbed, 0.6° to 3.6° increase for the rubbed plus IL radiated and 1.6° to 4.6° for the rubbed plus UPUVL radiated samples, respectively. However to our surprise, we found tilt angle to be decreasing from 2.4° to 1.6° for the rubbed plus LPUVL radiated samples. We hope that these findings will be helpful in the fabrication of display panels and other electro-optic devices.

Keywords: homogeneous, liquid crystals, polyimide, tilt angle

Procedia PDF Downloads 118

Authors: Sipumle Qapeshu, Bongiwe Mcata, Ajuruchukwu Obi

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Subsistence farmers practice farming for survival while commercial farmers produce to feed themselves and larger society with the motive to achieve highest profit. These types of farmers are characterised by growing what they eat, live without making regular purchases in the markets. The main objective of subsistence/peasant farmers is to ensure food security at household level. Cabbage is a crop that has been identified to have vital food nutrient sources like Vitamin A, B and C, protein, calcium, iron and antioxidative compounds beneficial for preventing cancer. This paper, therefore, looks at the potential that cabbage production has in enhancing household food security and also the challenges encountered by these cabbage producers. Primary data was obtained from 50 respondents, and linear regression model was used to analyse the data used. Income was used as food security measure. The results showed that three variables were statistically significant and they are gender (10%), education (5%) and household size (5%). Meaning that these are variables that influenced cabbage production by these households, and it also affects their food security status since income is affected.

Keywords: subsistence farmers, food security, cabbage, farming

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Authors: Ma Lei-Lei, Zhou You

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Aiming at the problems of low detection accuracy of deep learning algorithm in traffic sign detection, this paper proposes improved EfficientDet based traffic sign detection algorithm. Multi-head self-attention is introduced in the minimum resolution layer of the backbone of EfficientDet to achieve effective aggregation of local and global depth information, and this study proposes an improved feature fusion pyramid with increased vertical cross-layer connections, which improves the performance of the model while introducing a small amount of complexity, the Balanced L1 Loss is introduced to replace the original regression loss function Smooth L1 Loss, which solves the problem of balance in the loss function. Experimental results show, the algorithm proposed in this study is suitable for the task of traffic sign detection. Compared with other models, the improved EfficientDet has the best detection accuracy. Although the test speed is not completely dominant, it still meets the real-time requirement.

Keywords: convolutional neural network, transformer, feature pyramid networks, loss function

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Authors: Pisit Potjanajaruwit

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TThe research objective was to study the integrated marketing communication strategy that is affecting the student’s decision making to study at Rajabhat University in Thailand. This research is a quantitative research. The sampling for this study is the first year students of Rajabhat University for 400 sampling. The data collection is made by a questionnaire. The data analysis by the descriptive statistic include frequency, percentage, mean and standardization and influence statistic as the multiple regression. The results show that integrated marketing communication including the advertising, public relation, sale promotion is important and significant with the student’s making decision in terms of brand awareness and brand recognized. The university scholar and word of mouth have an impact on decision-making of the student. The direct marketing such as Facebook also relate to the student decision. In addition, we found that the marketing communication budget, university brand positioning and university mission have the direct effect on the marketing communication.

Keywords: decision making of higher education, integrated marketing communication, rajabhat university, social media

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Authors: Mayantoinette F. Watson

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During such an unprecedented time of the largest public health crisis, the COVID-19 pandemic, nursing students are of the utmost concern regarding their psychological and physical well-being. Questions are emerging and circulating about what will happen to the nursing students and the long-term effects of the pandemic, especially now that hospitals are being overwhelmed with a significant need for nursing staff. Expectations, demands, change, and the fear of the unknown during this unprecedented time can only contribute to the many stressors that accompany nursing students through laborious clinical and didactic courses in nursing programs. The risk of psychological distress is at a maximum, and its effects can negatively impact not only nursing students but also nursing education and academia. The high exposures to interpersonal, economic, and academic demands contribute to the major health concerns, which include a potential risk for psychological distress. Achievement of educational success among nursing students is directly affected by the high exposure to anxiety and depression from experiences within the program. Working relationships and achieving academic success is imperative to positive student outcomes within the nursing program. The purpose of this study is to identify and establish influences and associations within multilevel factors, including the effects of the COVID-19 pandemic on psychological distress in nursing students. Neuman’s Systems Model Theory was used to determine nursing students’ responses to internal and external stressors. The research in this study utilized a mixed-methods, convergent study design. The study population included undergraduate nursing students from Southeastern U.S. The research surveyed a convenience sample of undergraduate nursing students. The quantitative survey was completed by 202 participants, and 11 participants participated in the qualitative follow-up interview surveys. Participants completed the Kessler Psychological Distress Scale (K6), the Perceived Stress Scale (PSS4), and the Dundee Readiness Educational Environment Scale (DREEM12) to measure psychological distress, perceived stress, and perceived educational environment. Participants also answered open-ended questions regarding their experience during the COVID-19 pandemic. Statistical tests, including bivariate analyses, multiple linear regression analyses, and binary logistics regression analyses were performed in effort to identify and highlight the effects of independent variables on the dependent variable, psychological distress. Coding and qualitative content analysis were performed to identify overarching themes within participants’ interviews. Quantitative data were sufficient in identifying correlations between psychological distress and multilevel factors of coping, marital status, COVID-19 stress, perceived stress, educational environment, and social support in nursing students. Qualitative data were sufficient in identifying common themes of students’ perceptions during COVID-19 and included online learning, workload, finances, experience, breaks, time, unknown, support, encouragement, unchanged, communication, and transmission. The findings are significant, specifically regarding contributing factors to nursing students’ psychological distress, which will help to improve learning in the academic environment.

Keywords: nursing education, nursing students, pandemic, psychological distress

Procedia PDF Downloads 86

Authors: Amir Ikram, Qin Su, Muhammad Fiaz, Muhammad Waqas Shabbir

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Women entrepreneurship witnessed a healthy rise in the last decade or so, and the scenario in Pakistan is not different. However female leaders are facing various, cultural, career oriented, and professional challenges. The study investigates the impact of social and industry-specific challenges on female entrepreneurship; social challenges was evaluated in terms of culture, and industry-specific challenges was measured in terms of team management and career growth. Purposive sampling was employed to collect data from 75 multicultural organizations operating in the culturally diverse and historic city of Lahore, Pakistan. Cronbach’s alpha was conducted to endorse the reliability of survey questionnaire, while correlation and regression analysis were used to test hypotheses. Industry-specific challenges were found to be more significant as compared to cultural factors. The paper also highlights the importance of female entrepreneurship for emerging economies, and suggests that bringing women to mainstream professions can lead to economic success.

Keywords: cultural challenges, emerging economy, female entrepreneurship, leadership

Procedia PDF Downloads 334

Authors: Minto Rattan, Tania Bose, Neeraj Chamoli

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The present paper investigates the effect of linear thermal gradient on the steady-state creep behavior of rotating isotropic disc using threshold stress based Sherby’s creep law. The composite discs made of aluminum matrix reinforced with silicon carbide particulate has been taken for analysis. The stress and strain rate distributions have been calculated for discs rotating at linear thermal gradation using von Mises’ yield criterion. The material parameters have been estimated by regression fit of the available experimental data. The results are displayed and compared graphically in designer friendly format for the above said temperature profile with the disc operating under uniform temperature profile. It is observed that radial and tangential stresses show minor variation and the strain rates vary significantly in the presence of thermal gradation as compared to disc having uniform temperature.

Keywords: creep, isotropic, steady-state, thermal gradient

Procedia PDF Downloads 269

Authors: Laatra Zemmouri, Said Boukhechem, Samia Haffaf, Mohamed Lafri

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A study was conducted in order to determine the prevalence and risk factors associated with abortion in ewes in the region of M’sila, located in central-eastern Algeria. A questionnaire was carried out to obtain information about the occurrence of abortion, sheep housing conditions, vaccination, feeding and management practices, and whether the farmers kept other livestock. This cross-sectional study was conducted for 36 months (between 2016 and 2019). A total of 71 sheep flocks were visited. Among 8168 ewes, we recorded 734 (8.99%) abortions and 3861 lambings. The risk factor analysis using multivariable logistic regression showed an association between abortion and vaccination against brucellosis (CI 95%= 2,76-1,35; p<0,001). Abortion decreased when dogs are owned (CI 95%= 0,36-0,84; p= 0.006), however, abortion increased with the presence of cats in farms (CI 95%= 1,24-2,8; p=0.003). There was a significant association between abortion and keeping goats (CI 95%= 1,18-2,40; p= 0.004), bovins (CI 95%= 0,3-0,68; p<0,001) and poultry CI 95%= 0,39-0,77; p= 0.001) in farms. Through this study, it is noticed that a strong association between the occurrence of abortion and estrus synchronization, stillbirth occurrence, and feed supplementation (p<0.05). Identification of the causes of abortion is an important task to reduce foetal losses and to improve livestock productivity.

Keywords: abortion, ewes, questionnaire, risk factors

Procedia PDF Downloads 227

Authors: Yan Lyu, Yiqun Pan, Zhizhong Huang

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In the design stage of a new building, the energy model of this building is often required for the analysis of the performance on energy efficiency. In practice, a certain degree of geometric simplification should be done in the establishment of building energy models, since the detailed geometric features of a real building are hard to be described perfectly in most energy simulation engine, such as ESP-r, eQuest or EnergyPlus. Actually, the detailed description is not necessary when the result with extremely high accuracy is not demanded. Therefore, this paper analyzed the relationship between the error of the simulation result from building energy models and the geometric simplification of the models. Finally, the following two parameters are selected as the indices to characterize the geometric feature of in building energy simulation: the southward projected area and total side surface area of the building, Based on the parameterization method, the simplification from an arbitrary column building to a typical shape (a cuboid) building can be made for energy modeling. The result in this study indicates that this simplification would only lead to the error that is less than 7% for those buildings with the ratio of southward projection length to total perimeter of the bottom of 0.25~0.35, which can cover most situations.

Keywords: building energy model, simulation, geometric simplification, design, regression

Procedia PDF Downloads 181

Authors: Ugochukwu D. Abasilim, Aize I. Obayan, Adedayo J. Odukoya, Godwyns Agube, Power A. I. Wogu, Nchekwube Excellence-Oluye

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This paper examines the effect of transformational leadership style on organizational commitment among Private University employees in Nigeria. A quantitative methodology was adopted for this study. A structured Multi-factor Leadership Questionnaire (MLQ) developed by Bass and Avolio (1997) and Organizational Commitment Questionnaire (OCQ) developed by Meyer and Allen (1997) were the major instruments used for data collection. Simple linear regression was used for testing the hypothesis. The results indicated that there was no significant positive effect of transformational leadership style on organizational commitment among employees of the Nigerian private university studied. Though the respondents rated their leaders high on transformational leadership style, their organizational commitment rating was average for majority, which implies that employees’ level of commitment could be accounted for by transformational leadership style existing in the institution. This finding is antithetical to the common submission in literature that transformational leadership style has a significant effect on organizational commitment. It was therefore recommended that further studies may want to further explore the reasons for this variance.

Keywords: leadership style, Nigeria, organizational, commitment, transformational leadership

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Authors: Nattapong Techarattanased

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This survey research aimed to study the influence of attitude in services, product, and marketing mix affected intention to revisit in boutique hotel of foreign travelers in Bangkok, Thailand. The total 400 sets of closed-ended questionnaires were utilized for conducting data from foreign tourists who come to boutique hotel and can communicate in English. The descriptive statistics and multiple regression analysis were used to analyze data. The research found that tourists’ attitude towards the service of check in and check out process, food and beverage, guest room and other facilities affected in opportunity of revisiting, recommending to others and possibility of revisiting in the future at 0.05 statistically significant levels. Tourists’ attitude towards service and marketing mix in term of people, physical evidence, price, process and channel of distribution could forecast intention to revisit in term of recommending to others and intention to revisit in the future at 0.05 statistically significant levels.

Keywords: boutique hotel, foreign tourists, intention to revisit, service marketing mix

Procedia PDF Downloads 247

Authors: Aimen Batool Bint-E-Rashid, Syed Muhammad Dawood Ali Shah, Muhammad Usman Farooq, Mahgul Anwar

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As the world is progressing, the needs and demands of the consumer market are also changing. Nowadays the trends of consumer purchase decisions are dependent upon multiple factors. This study aims to identify the influential impact of country of origin over the perception and devotion towards daily personal care products specifically in reference to the knowledge and awareness regarding that particular brand in Pakistan. To corroborate this study, a 30-item brand origin questionnaire has been used with 300 purchase decision makers belonging to different age groups. To illustrate this study, a model has been developed based on brand origin, brand awareness and brand loyalty. Correlation and regression analysis have been used to find out the results which conclude the findings on the perspective of Pakistan’s consumer market as that brand origin has a direct relationship with brand loyalty provided that the consumer has a positive brand awareness. Support for the fact that brand origin impacts brand loyalty through brand awareness has been presented in this study.

Keywords: brand awareness, brand loyalty, brand origin, personal care products, P&G, Unilever

Procedia PDF Downloads 241

Authors: Marjan Heidarian Dehkordi, Hossein Allahyari, Bruce Parker, Reza Talaee-Hassanlouei

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The Western flower thrips, Frankliniella occidentalis Priesner (Thysanoptera: Thripidae), is a significant pest of many economically important crops. This study evaluated the functional responses, prey-stage preferences and mutual interference of Amblyseius swirskii Anthias-Henriot (Acari: Phytoseiidae) with F. occidentalis as the host under laboratory conditions. The predator species showed no prey stage preference for either prey 1st or 2nd instar. Logistic regression analysis suggested Type II (convex) functional response for the predator species. Consequently, the per capita searching efficiency decreased significantly from 1.2425 to -7.4987 as predator densities increased from 2 to 8. The findings from this study could help select better biological control agents for effective control of F. occidentalis and other pests in vegetable production.

Keywords: biological control, functional responses, mutual interference, prey-stage preferences

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Authors: Nermin Mahmoud Gohar, Aisha Tarek Noour

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Learner satisfaction has been a vital field of interest in the literature. Accordingly, the paper will explore the reasons behind individual differences in motivation and satisfaction. This study examines the effect of both; Herzberg’s and Maslow’s theories on learners satisfaction. A self-administered questionnaire was used to collect data from learners who were geographically widely spread around the College of Maritime Transport and Technology (CMTT) at the Arab Academy for Science, Technology and Maritime Transport (AAST&MT) in Egypt. One hundred and fifty undergraduates responded to a questionnaire survey. Respondents were drawn from two branches in Alexandria and Port Said. The data analysis used was SPSS 22 and AMOS 18. Factor analysis technique was used to find out the dimensions under study verified by Herzberg’s and Maslow’s theories. In addition, regression analysis and structural equation modeling were applied to find the effect of the above-mentioned theories on maritime transport learners’ satisfaction. Concerning the limitation of this study, it used the available number of learners in the CMTT due to the relatively low population in this field.

Keywords: motivation, satisfaction, needs, education, Herzberg’s and Maslow’s theories

Procedia PDF Downloads 436

Authors: Eui Jun Jeong, Hye Rim Lee, Ji Hye Yoo

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Recent studies have verified the significant relationship of user personality with Internet use. However, in game studies, little research has emphasized on the effects of personality traits on game addiction. This study examined whether big five personality traits affect game addiction with control of psychological, social, and demographic factors. Specifically, using data from a survey of 789 game users in Korea, we conducted a regression analysis to see the associations of psychological (loneliness/depression), social (activities with family/friends), self-efficacy (game/general), gaming (daily gaming time/perception), demographic (age/gender), and personality traits (extraversion, neuroticism conscientiousness, agreeableness, & openness) with the degree of game addiction. Results showed that neuroticism increase game addiction with no effect of extraversion on the addiction. General self-efficacy negatively affected game addiction, whereas game self-efficacy increased the degree of game addiction. Loneliness enhanced game addiction while depression showed a negative effect on the addiction. Results and implications are discussed.

Keywords: game addiction, big five personality, social activities, self-efficacy, loneliness, depression

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Authors: Norbayah Mohd Suki, Norazah Mohd Suki

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This study aims to examine relationships between attitude, self-efficacy, and subjective norm with students’ behavioural intention to use public computing facilities at a library. Data was collected from 200 undergraduate students enrolled at a higher learning institution in the Federal Territory of Labuan, Malaysia via a structured questionnaire comprising closed-ended questions. Data was analyzed using multiple regression analysis. The results show that students’ behavioural intention to use public computing facilities at the library is widely affected by subjective norm factor i.e. influence of the support of family members, friends and neighbours. The findings of this study provide a better understanding of factors likely to influence students’ behavioural intention to use public computing facilities at a library. It also offers valuable insights into factors which university librarians need to focus on to improve students’ behavioural intention to actively use public computing facilities at a library for quality information retrieval. Direction for future research is also presented.

Keywords: attitude, self-efficacy, subjective norm, behavioural intention

Procedia PDF Downloads 447

Authors: Shivanand Pawar

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In India, a collective range of measurements had been adopted to control the massive spread of the COVID-19 pandemic, but World Health Organization (2022) revealed 525 930 fatalities and 43,847,065 confirmed cases. There are currently 30,857 cases per million people. Lack of knowledge, attitude and practices are the main causes thought to be increased COVID-19. The present study aims to assess the knowledge, attitude, and practice among Tamil Nadu residents. The participants (N=332) were aged 20 to 50 (mean=42.78, & SD=13.98) and were selected using purposive sampling, and data were collected online using knowledge, attitude and practice scale. Data were analyzed using person correlation and multiple regression analysis. The result found that 31.30% had satisfactory knowledge, 68.70% had non-satisfactory knowledge, followed by 45.20% had a positive attitude, 54.80% had a negative attitude, and 34.30% had a good practice, and 65.70% had poor practice towards COVID-19. Correlation results revealed that age has a negative and significant relationship with Knowledge and Practice towards COVID-19. The current study results contribute to the existing literature on knowledge, attitude and practice of COVID-19 to reduce the COVID-19 cases by managing unhealthy knowledge, attitude and practice to control the massive spread of COVID-19.

Keywords: COVID-19, knowledge, practice, attitude, Fisherman community

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Authors: Mohieddine Benghersallah, Mohamed Zakaria Zahaf, Ali Medjber, Idriss Tibakh

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The objective of this study is to analyse the effects of cutting parameters on surface roughness in dry face milling using statistical techniques. We studied the effect of the microstructure of AISI 52100 steel on machinability before and after hardening. The machining tests were carried out on a high rigidity vertical milling machine with a 25 mm diameter face milling cutter equipped with micro-grain bicarbide inserts with PVD (Ti, AlN) coating in GC1030 grade. A Taguchi L9 experiment plan is adopted. Analysis of variance (ANOVA) was used to determine the effects of cutting parameters (Vc, fz, ap) on the roughness (Ra) of the machined surface. Regression analysis to assess the machinability of steel presented mathematical models of roughness and the combination of parameters to minimize it. The recorded results show that feed per tooth has the most significant effect on the surface condition for both steel treatment conditions. The best roughnesses were obtained for the hardened AISI 52100 steel.

Keywords: machinability, heat treatment, microstructure, surface roughness, Taguchi method

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Authors: David F. Nettleton, Elodie Bugnicourt, Christian Wasiak, Alejandro Rosales

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In this presentation, preliminary results are given for the modeling and calibration of two different industrial winding MIMO (Multiple Input Multiple Output) processes using machine learning techniques. In contrast to previous approaches which have typically used ‘black-box’ linear statistical methods together with a definition of the mechanical behavior of the process, we use non-linear machine learning algorithms together with a ‘white-box’ rule induction technique to create a supervised model of the fitting error between the expected and real force measures. The final objective is to build a precise model of the winding process in order to control de-tension of the material being wound in the first case, and the friction of the material passing through the die, in the second case. Case 1, Tension Control of a Winding Process. A plastic web is unwound from a first reel, goes over a traction reel and is rewound on a third reel. The objectives are: (i) to train a model to predict the web tension and (ii) calibration to find the input values which result in a given tension. Case 2, Friction Force Control of a Micro-Pullwinding Process. A core+resin passes through a first die, then two winding units wind an outer layer around the core, and a final pass through a second die. The objectives are: (i) to train a model to predict the friction on die2; (ii) calibration to find the input values which result in a given friction on die2. Different machine learning approaches are tested to build models, Kernel Ridge Regression, Support Vector Regression (with a Radial Basis Function Kernel) and MPART (Rule Induction with continuous value as output). As a previous step, the MPART rule induction algorithm was used to build an explicative model of the error (the difference between expected and real friction on die2). The modeling of the error behavior using explicative rules is used to help improve the overall process model. Once the models are built, the inputs are calibrated by generating Gaussian random numbers for each input (taking into account its mean and standard deviation) and comparing the output to a target (desired) output until a closest fit is found. The results of empirical testing show that a high precision is obtained for the trained models and for the calibration process. The learning step is the slowest part of the process (max. 5 minutes for this data), but this can be done offline just once. The calibration step is much faster and in under one minute obtained a precision error of less than 1x10-3 for both outputs. To summarize, in the present work two processes have been modeled and calibrated. A fast processing time and high precision has been achieved, which can be further improved by using heuristics to guide the Gaussian calibration. Error behavior has been modeled to help improve the overall process understanding. This has relevance for the quick optimal set up of many different industrial processes which use a pull-winding type process to manufacture fibre reinforced plastic parts. Acknowledgements to the Openmind project which is funded by Horizon 2020 European Union funding for Research & Innovation, Grant Agreement number 680820

Keywords: data model, machine learning, industrial winding, calibration

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Authors: Fanqiang Kong, Chending Bian

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Sparse unmixing is a promising approach in a semisupervised fashion by assuming that the observed pixels of a hyperspectral image can be expressed in the form of linear combination of only a few pure spectral signatures (end members) in an available spectral library. However, the sparse unmixing problem still remains a great challenge at finding the optimal subset of endmembers for the observed data from a large standard spectral library, without considering the spatial information. Under such circumstances, a sparse unmixing algorithm termed as non-local simultaneous sparse unmixing (NLSSU) is presented. In NLSSU, the non-local simultaneous sparse representation method for endmember selection of sparse unmixing, is used to finding the optimal subset of endmembers for the similar image patch set in the hyperspectral image. And then, the non-local means method, as a regularizer for abundance estimation of sparse unmixing, is used to exploit the abundance image non-local self-similarity. Experimental results on both simulated and real data demonstrate that NLSSU outperforms the other algorithms, with a better spectral unmixing accuracy.

Keywords: hyperspectral unmixing, simultaneous sparse representation, sparse regression, non-local means

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Authors: Devina Aprilia Gunawan, Tasya Aspiranti, Inugrah Ratia Pratiwi

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This research aims to classify the mining sector companies based on Altman’s Z-score model, and providing an analysis based on the Altman’s Z-score model’s financial ratios to provide a picture about the financial condition in mining sector companies in Indonesia and their viability in the future, and to find out the partial and simultaneous impact of each of the financial ratio variables in the Altman’s Z-score model, namely (WC/TA), (RE/TA), (EBIT/TA), (MVE/TL), and (S/TA), toward the financial condition represented by the Z-score itself. Among 38 mining sector companies listed in Indonesia Stock Exchange (IDX), 28 companies are selected as research sample according to the purposive sampling criteria.The results of this research showed that during 3 years research period at 2010-2012, the amount of the companies that was predicted to be healthy in each year was less than half of the total sample companies and not even reach up to 50%. The multiple regression analysis result showed that all of the research hypotheses are accepted, which means that (WC/TA), (RE/TA), (EBIT/TA), (MVE/TL), and (S/TA), both partially and simultaneously had an impact towards company’s financial condition.

Keywords: Altman’s Z-score model, financial condition, mining companies, Indonesia

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Authors: Jiashu Shen

Abstract:

This study aims at exploring the characteristics of sexual knowledge, attitudes, and behaviors of Chinese college students from the 'one-child' families compared with those with siblings. This study utilized the data from the 'National College Student Survey on Sexual and Reproductive Health 2019'. Multiple logistic regression analyses were used to assess the association between the 'only-child' and their sexual knowledge, sexual attitudes, sexual behaviors, and risky sexual behaviors (RSB) stratified by sex and home regions, respectively. Compared with students with siblings, the 'only-child' students scored higher in sex-related knowledge (only-child students: 4.49 ± 2.28, students with siblings: 3.60 ± 2.27). Stronger associations between only-child and more liberal sexual attitudes were found in urban areas, including the approval of premarital sexual intercourse (OR: 1.51, 95% CI: 1.50-1.65) and multiple sexual partners (OR: 1.85, 95% CI: 1.72-1.99). For risky sexual behaviors, being only-child is more likely to use condoms in first sexual intercourse, especially among male students (OR: 0.68, 95% CI: 0.58-0.80). Only-child students are more likely to have more sexual knowledge, more liberal sexual attitude, and less risky sexual behavior. Further health policy and sex education should focus more on students with siblings.

Keywords: attitudes and behaviors, only-child students, sexual knowledge, students with siblings

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Authors: Neeta Kumari, Gopal Pathak

Abstract:

Artificial neural network has been proved to be an efficient tool for non-parametric modeling of data in various applications where output is non-linearly associated with input. It is a preferred tool for many predictive data mining applications because of its power , flexibility, and ease of use. A standard feed forward networks (FFN) is used to predict the groundwater fluoride content. The ANN model is trained using back propagated algorithm, Tansig and Logsig activation function having varying number of neurons. The models are evaluated on the basis of statistical performance criteria like Root Mean Squarred Error (RMSE) and Regression coefficient (R2), bias (mean error), Coefficient of variation (CV), Nash-Sutcliffe efficiency (NSE), and the index of agreement (IOA). The results of the study indicate that Artificial neural network (ANN) can be used for groundwater fluoride prediction in the limited data situation in the hard rock region like western parts of Jharkhand with sufficiently good accuracy.

Keywords: Artificial neural network (ANN), FFN (Feed-forward network), backpropagation algorithm, Levenberg-Marquardt algorithm, groundwater fluoride contamination

Procedia PDF Downloads 550