Search results for: stepwise regression

Authors: Chung-Ming Lo, Chung-Chien Lee

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In many countries, the lifetime prevalence of shoulder pain is up to 70%. In America, the health care system spends 7 billion per year about the healthy issues of shoulder pain. With respect to the origin, up to 70% of shoulder pain is attributed to rotator cuff lesions This study proposed a computer-aided diagnosis (CAD) system to assist radiologists classifying rotator cuff lesions with less operator dependence. Quantitative features were extracted from the shoulder ultrasound images acquired using an ALOKA alpha-6 US scanner (Hitachi-Aloka Medical, Tokyo, Japan) with linear array probe (scan width: 36mm) ranging from 5 to 13 MHz. During examination, the postures of the examined patients are standard sitting position and are followed by the regular routine. After acquisition, the shoulder US images were drawn out from the scanner and stored as 8-bit images with pixel value ranging from 0 to 255. Upon the sonographic appearance, the boundary of each lesion was delineated by a physician to indicate the specific pattern for analysis. The three lesion categories for classification were composed of 20 cases of tendon inflammation, 18 cases of calcific tendonitis, and 18 cases of supraspinatus tear. For each lesion, second-order statistics were quantified in the feature extraction. The second-order statistics were the texture features describing the correlations between adjacent pixels in a lesion. Because echogenicity patterns were expressed via grey-scale. The grey-scale co-occurrence matrixes with four angles of adjacent pixels were used. The texture metrics included the mean and standard deviation of energy, entropy, correlation, inverse different moment, inertia, cluster shade, cluster prominence, and Haralick correlation. Then, the quantitative features were combined in a multinomial logistic regression classifier to generate a prediction model of rotator cuff lesions. Multinomial logistic regression classifier is widely used in the classification of more than two categories such as the three lesion types used in this study. In the classifier, backward elimination was used to select a feature subset which is the most relevant. They were selected from the trained classifier with the lowest error rate. Leave-one-out cross-validation was used to evaluate the performance of the classifier. Each case was left out of the total cases and used to test the trained result by the remaining cases. According to the physician’s assessment, the performance of the proposed CAD system was shown by the accuracy. As a result, the proposed system achieved an accuracy of 86%. A CAD system based on the statistical texture features to interpret echogenicity values in shoulder musculoskeletal ultrasound was established to generate a prediction model for rotator cuff lesions. Clinically, it is difficult to distinguish some kinds of rotator cuff lesions, especially partial-thickness tear of rotator cuff. The shoulder orthopaedic surgeon and musculoskeletal radiologist reported greater diagnostic test accuracy than general radiologist or ultrasonographers based on the available literature. Consequently, the proposed CAD system which was developed according to the experiment of the shoulder orthopaedic surgeon can provide reliable suggestions to general radiologists or ultrasonographers. More quantitative features related to the specific patterns of different lesion types would be investigated in the further study to improve the prediction.

Keywords: shoulder ultrasound, rotator cuff lesions, texture, computer-aided diagnosis

Procedia PDF Downloads 284

Authors: Maghsoud Nader Pilehroud, Mohmmad Alizadeh, Soheila Golipour, Sedigeh Tajabadipour

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Aim: in terms of importance, sexual issues are of the highest priority in married life issues and sexual compatibility is of the most important reasons of success in married life and consequently marital satisfaction.the present research was conducted with the aim of The role of sexual satisfaction sexual satisfaction in marital satisfaction married men. Study Design: this research is descriptive and is of correlation type.Method: The statistical population includes all the married men of Ardebil city out of which, 60 men were chosen using random sampling as the research samples. The research instruments were ENRICH couple scale and Hudson sexual satisfaction scale. The findings were analyzed using descriptive statistics method (mean and standard deviation) and inferential statistics (Pearson's correlation and regression) and SPSS-16 software. Results: the results showed that sexual satisfaction has a positive and significant relationship with marital satisfaction and all of its components, and that sexual satisfaction can predict marital satisfaction. The results also showed that sexual and marital satisfaction, are not significantly related to any of the variables of education level, duration of marriage and number of children. conclusion: according to the results, it can be claimed that sexual skills training for couples can be influential at increasing their martial satisfaction, and that also, sexual satisfaction has an important role in marital satisfaction.

Keywords: sexual satisfaction, marital satisfaction, married men, Iran

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Authors: Narges Sadat Myrmousavy, Maryam Eslampanah

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The aim of this study was to investigate the relationship between social capital and knowledge sharing is the Ministry of Culture and Islamic Guidance. They are descriptive correlation study. The study sample consisted of all the experts in the Ministry of Culture and Islamic Guidance helping professionals headquarters in Tehran in the summer period is 2012, the number is 650. Random sampling is targeted. The sample size is 400. The data collection tool was a questionnaire that was used for the preparation of a standard questionnaire. They also examine the assumptions of the regression coefficient for the relationship between variables in order to investigate the main hypothesis test is used. The findings suggest that the structural and knowledge-sharing between components, there is a direct relationship. The components of the relationship between Impression management and knowledge sharing, there is a direct relationship. There was no significant relationship between Individual pro-social motives and knowledge sharing. Both components of the cognitive aspects of open mindedness and competence are directly related with knowledge sharing. Finally, the comparison between the different dimensions of social capital, the largest of its structure, and its relationship with knowledge sharing is the least relation.

Keywords: social capital, knowledge sharing, ministry of culture and Islamic guidance (Iran), open mindedness, pro-social motives

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Authors: Mojtaba Esmaeilzad Limoudehi

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To evaluate the model ORYZA2000, under the management of irrigation and nitrogen fertilization experiment, a split plot with a randomized complete block design with three replications on hybrid cultivars (spring) in the 1388-1387 crop year was conducted at the Rice Research Institute. Permanent flood irrigation as the main plot in the fourth level, around 5 days, from 11 days to 8 days away, and the four levels of nitrogen fertilizer as the subplots 0, 90, 120, and 150 kg N Ha were considered. Simulated and measured values of leaf area index, grain yield, and biological parameters using the regression coefficient, t-test, the root mean square error (RMSE), and normalized root mean square error (RMSEn) were performed. Results, the normalized root mean square error of 10% in grain yield, the biological yield of 9%, and 23% of maximum LAI was determined. The simulation results show that grain yield and biological ORYZA2000 model accuracy are good but do not simulate maximum LAI well. The results show that the model can support ORYZA2000 test results and can be used under conditions of nitrogen fertilizer and irrigation management.

Keywords: evaluation, rice, nitrogen fertilizer, model ORYZA2000

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Authors: Abdel-Aziz M. Mohamed, Nermeen Coutry

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Lead time is an important measure of supply chain performance. It impacts both customer satisfactions as well as the total cost of inventory. This paper presents the result of a study on the analysis of the customer order lead-time for a multinational company. In the study, the lead time was divided into three stages: order entry, order fulfillment, and order delivery. A sample of size 2,425 order lines from the company records were considered for this study. The sample data includes information regarding customer orders from the time of order entry until order delivery. Data regarding the lead time of each sage for different orders were also provided. Summary statistics on lead time data reveals that about 30% of the orders were delivered after the scheduled due date. The result of the multiple linear regression analysis technique revealed that component type, logistics parameter, order size and the customer type have significant impact on lead time. Data analysis on the stages of lead time indicates that stage 2 consumes over 50% of the lead time. Pareto analysis was made to study the reasons for the customer order delay in each of the 3 stages. Recommendation was given to resolve the problem.

Keywords: lead time reduction, customer satisfaction, service quality, statistical analysis

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Authors: Vaidehi Iyer, Konstantin Borozdin

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Time series prediction problems have many important practical applications, but are notoriously difficult for statistical modeling. Recently, machine learning methods have been attracted significant interest as a practical tool applied to a variety of problems, even though developments in this field tend to be semi-empirical. This paper explores application of Long Short Term Memory based Recurrent Neural Networks to the one-step prediction of time series for both trend and stochastic components. Two types of data are analyzed - daily stock prices, that are often considered to be a typical example of a random walk, - and weather patterns dominated by seasonal variations. Results from both analyses are compared, and reinforced learning framework is used to select more efficient between Recurrent Neural Networks and more traditional auto regression methods. It is shown that both methods are able to follow long-term trends and seasonal variations closely, but have difficulties with reproducing day-to-day variability. Future research directions and potential real world applications are briefly discussed.

Keywords: long short term memory, prediction methods, recurrent neural networks, reinforcement learning

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Authors: Qiaosi Li, Frankie Kwan Kit Wong, Tung Fung

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Lightweight unmanned aerial vehicle (UAV) loading with novel sensors offers a low cost approach for data acquisition in complex environment. This study established a framework for applying UAV system in complex environment quick mapping and assessed the performance of UAV-based hyperspectral image and digital surface model (DSM) derived from photogrammetric point clouds for 13 species classification in wetland area Mai Po Inner Deep Bay Ramsar Site, Hong Kong. The study area was part of shallow bay with flat terrain and the major species including reedbed and four mangroves: Kandelia obovata, Aegiceras corniculatum, Acrostichum auerum and Acanthus ilicifolius. Other species involved in various graminaceous plants, tarbor, shrub and invasive species Mikania micrantha. In particular, invasive species climbed up to the mangrove canopy caused damage and morphology change which might increase species distinguishing difficulty. Hyperspectral images were acquired by Headwall Nano sensor with spectral range from 400nm to 1000nm and 0.06m spatial resolution image. A sequence of multi-view RGB images was captured with 0.02m spatial resolution and 75% overlap. Hyperspectral image was corrected for radiative and geometric distortion while high resolution RGB images were matched to generate maximum dense point clouds. Furtherly, a 5 cm grid digital surface model (DSM) was derived from dense point clouds. Multiple feature reduction methods were compared to identify the efficient method and to explore the significant spectral bands in distinguishing different species. Examined methods including stepwise discriminant analysis (DA), support vector machine (SVM) and minimum noise fraction (MNF) transformation. Subsequently, spectral subsets composed of the first 20 most importance bands extracted by SVM, DA and MNF, and multi-source subsets adding extra DSM to 20 spectrum bands were served as input in maximum likelihood classifier (MLC) and SVM classifier to compare the classification result. Classification results showed that feature reduction methods from best to worst are MNF transformation, DA and SVM. MNF transformation accuracy was even higher than all bands input result. Selected bands frequently laid along the green peak, red edge and near infrared. Additionally, DA found that chlorophyll absorption red band and yellow band were also important for species classification. In terms of 3D data, DSM enhanced the discriminant capacity among low plants, arbor and mangrove. Meanwhile, DSM largely reduced misclassification due to the shadow effect and morphological variation of inter-species. In respect to classifier, nonparametric SVM outperformed than MLC for high dimension and multi-source data in this study. SVM classifier tended to produce higher overall accuracy and reduce scattered patches although it costs more time than MLC. The best result was obtained by combining MNF components and DSM in SVM classifier. This study offered a precision species distribution survey solution for inaccessible wetland area with low cost of time and labour. In addition, findings relevant to the positive effect of DSM as well as spectral feature identification indicated that the utility of UAV-borne hyperspectral and photogrammetry deriving 3D data is promising in further research on wetland species such as bio-parameters modelling and biological invasion monitoring.

Keywords: digital surface model (DSM), feature reduction, hyperspectral, photogrammetric point cloud, species mapping, unmanned aerial vehicle (UAV)

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Authors: Ajay Kumar

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Using data from census of India, sample registration system and national family health survey (NFHS-3), this paper traces spatial pattern, trends and the factors which have played their role differently in fertility transition in Uttar Pradesh and Tamil Nadu. For the purpose spatial variation analysis, trend line and binary logistic regression analysis has been carried out. There exist considerable regional disparities in terms of fertility decline in northern and southern states. The pace of fertility decline has been faster in southern and coastal regions, and at a slow pace in backward northern state. In Tamil Nadu fertility declined substantially among the women of lower and higher age groups in comparison to Uttar Pradesh characterized by low literacy, low female age at marriage, poor health infrastructure and low status of women. The Study shows that Fertility rates have been higher among the most vulnerable and deprived sections of the society like Illiterate women, women belong to scheduled caste, scheduled tribe and women residing in rural areas.

Keywords: age specific fertility rate, fertility transition, replacement level, total fertility rate

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Authors: Maria A. Murtiati, Ancella A. Hermawan

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The objective of this study is to examine whether the firm’s eligibility to get a bank loan is influenced by earnings management. The earnings management is distinguished between accruals and real earnings management. Hypothesis testing is carried out with logistic regression model using sample of 285 companies listed at Indonesian Stock Exchange in 2010. The result provides evidence that a greater magnitude in accruals earnings management increases the firm’s probability to be eligible to get bank loan. In contrast, real earnings management through abnormal cash flow and abnormal discretionary expenses decrease firm’s probability to be eligible to get bank loan, while real management through abnormal production cost increases such probability. The result of this study suggests that if the earnings management is assumed to be opportunistic purpose, the accruals based earnings management can distort the banks credit analysis using financial statements. Real earnings management has more impact on the cash flows, and banks are very concerned on the firm’s cash flow ability. Therefore, this study indicates that banks are more able to detect real earnings management, except abnormal production cost in real earning management.

Keywords: discretionary accruals, real earning management, bank loan, credit worthiness

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Authors: Oguzhan Cepni, Doruk Kucuksarac, M. Hasan Yilmaz

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Changes in the global risk appetite cause co-movement in emerging market risk premiums. However, the sensitivity of the changes in risk premium to the global risk appetite may vary across emerging markets. In this study, how the global risk appetite affects Credit Default Swap (CDS) premiums in emerging markets are analyzed using Principal Component Analysis (PCA) and rolling regressions. The PCA results indicate that the first common component derived by the PCA accounts for almost 76 percent of the common variation in CDS premiums. Additionally, the explanatory power of the first factor seems to be high over the sample period. However, the sensitivity to the global risk factor tends to change over time and across countries. In this regard, fixed effects panel regressions are used to identify the macroeconomic factors driving the heterogeneity across emerging markets. The panel regression results point to the significance of government debt to GDP and international reserves to GDP in explaining sensitivity. Accordingly, countries with lower government debt and higher reserves tend to be less subject to the variations in the global risk appetite.

Keywords: credit default swaps, emerging markets, principal components analysis, sovereign risk

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Authors: Titilola Adebowale

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Some factors are responsible for the social adjustment among the adolescents. The study investigated resiliency, peer and parental support as factors that could determine social adjustment among adolescents in Ilorin, Kwara state. The study adopted descriptive survey research design. A sample size of 300 SS1 & SS2 students from ten secondary schools, six public and four private schools were randomly selected within Ilorin Metropolis. Self-structured questionnaire that was validated and the reliability ensured was used to collect data from the respondents. Four hypotheses were postulated and tested at 0.05 level of significance. Data collected was analysed using Pearson Product Moment Correlation (PPMC) and Regression Analysis. The findings revealed that there was a positive relationship between resiliency and social adjustment: r (298) = .402, p<0.01, r2 = .162; that there was a positive relationship between peer support and social adjustment: r (298) = .570, p<0.01, r2 = .325; that there was a positive relationship between parental support and social adjustment: r (298) = .451, p<0.01, r2 = .203; also reveals significant joint contribution of the independent variables (resilience, peer support, parental support) to the prediction of social adjustment: F (3,296) = 55.587, P<0.01. Various recommendations were given which includes the roles of government, agencies, individuals, parents, teachers, religious and marriage institutions.

Keywords: resiliency, peer support, parental support, adolescents, social adjustment

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Authors: Ramona Zharfpeykan

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The concept of sustainability is generally considered as a key topic in many countries, and sustainability reporting is becoming an important tool for companies to communicate their sustainability plans and performance to their stakeholders. There have been various studies on factors that may influence sustainability reporting in companies. This study examines the possible effect of some of the organisational factors on corporate sustainability reporting. The organisational factors included in this study are a company’s type (public or private), industry, and size as well as managers’ perception of the level of importance of indicators in reporting these indicators. A survey was conducted from 240 Australian and New Zealand companies in various industries. They were asked about their perception of the importance of sustainability indicators in their performance and if they report these indicators. The GRI indicators used to develop the survey. A multiple regression model was developed using reporting strategy score as dependent and type, size, industry categorisation, and managers’ perception of the level of importance of the GRI indicators as independent factors. The results show that among all the factors included in the model, size of a company and the perception of managers of the level of importance of environmental and labour practice indicators can affect the sustainability scores of these companies.

Keywords: sustainability reporting, global reporting initiative, sustainability reporting strategy, organisational features

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Authors: Fahim Ullah, Muhammad Usman

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Energy consumption and environmental sustainability are hard challenges of 21st century. Energy richness increases environmental pollution while energy poverty hinders economic growth. Considering these two aspects, present study calculates energy deficiency and examines the role of renewable energy to overcome rising energy deficiency and carbon emission for selected countries from 1990 to 2021. For empirical analysis, this study uses methods of moments panel quantile regression analysis and to check the robustness, study used panel quantile robust analysis. Graphical analysis indicated rising global energy deficiency since last three decades where energy consumption is higher than energy production. Empirical results showed that renewable energy is a significant factor for reducing energy deficiency. Secondly, the energy deficiency increases carbon emission level and again renewable energy decreases emissions level. This study recommends that global energy deficiency and rising carbon emissions can be controlled through structural change in the form of energy transition to replace non-renewable resources with renewable resources.

Keywords: energy deficiency, renewable energy, carbon emission, energy trade, PQL analysis

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Authors: Renata Konadu

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Over the last two decades, the concept of environmental management and its related issues have received increased attention in global discourse and on management research agenda due to climate change and other environmental challenges. To abate and avert these challenges, diverse environmental policies, strategies and practices have been adopted by businesses and economies as a whole. Extant literature has placed much emphasis on whether improved environmental operational performance improves firm performance. However, there is a huge gap in the literature with regards to whether the adoption of environmental management practices and policies has a direct relationship with environmental operational performance (EOP). The current paper is intended to provide a comprehensive perspective of how different aspects of environmental management can relate to firms EOP. Using a panel regression analysis of 149 large listed firms in the UK, the study found evidence of both negative and positive statistically significant link between some Environmental Policies (EP), Environmental Processes (EPR), Environmental Management Systems (EMS) and EOP. The findings suggest that in terms of relating EP, EPR and EMS to Greenhouse Gases (GHGs) emissions for instance, the latter should be viewed separately in Scopes 1, 2 and 3 as developed by GHG protocol. The results have useful implication for policy makers and managers when designing strategies and policies to reduce negative environmental impacts.

Keywords: environmental management, environmental operational performance, GHGs, large listed firms

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Authors: Daniel Etim Jacob, Samuel Onadeko, Edem A. Eniang, Imaobong Ufot Nelson

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This paper examined determinants of income diversification among households in support zones communities of national parks in Nigeria. This involved the use household data collected through questionnaires administered randomly among 1009 household heads in the study area. The data obtained were analyzed using probability and non-probability statistical analysis such as regression and analysis of variance to test for mean difference between parks. The result obtained indicates that majority of the household heads were male (92.57%0, between the age class of 21 – 40 years (44.90%), had non-formal education (38.16%), were farmers (65.21%), owned land (95.44%), with a household size of 1 – 5 (36.67%) and an annual income range of ₦401,000 - ₦600,000 (24.58%). Mean Simpson index of diversity showed a general low (0.375) level of income diversification among the households. Income, age, off-farm dependence, education, household size and occupation where significant (p<0.01) factors that affected households’ income diversification. The study recommends improvement in the existing infrastructures and social capital in the communities as avenues to improve the livelihood and ensure positive conservation behaviors in the study area.

Keywords: income diversification, protected area, livelihood, poverty, Nigeria

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Authors: Mohammed Nishat, Ahmad Ghazali

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This study empirically inspects the corporate governance and firm performance, and attempts to analyze the corporate governance and control related variables which are hypothesized to have effect on firm’s performance. Current study attempts to assess the mechanism and efficiency of corporate governance to achieve high level performance for the listed firms on the Karachi Stock Exchange (KSE) for the period 2005 to 2008. To evaluate the firm performance level this study investigate the firm performance using three measures; Return on assets (ROA), Return on Equity (ROE) and Tobin’s Q. To check the link between firm performances with the corporate governance three categories of corporate governance variables are tested which includes governance, ownership and control related variables. Fixed effect regression model is used to examine the relation among governance and corporate performance for 267 KSE listed Pakistani firms. The result shows that governance related variables like block shareholding by individuals have positive impact on firm performance. When chief executive officer is also the board chairperson then it is observed that performance of firm is adversely affected. Also negative relationship is found between share held by insiders and performance of firm. Leverage has negative influence on the firm performance and size of firm is positively related with performance of the firm.

Keywords: corporate governance, agency cost, KSE, ROA, Tobin’s Q

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Authors: Emma Serwaa Obobisa

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Urbanization has become the focus for challenging goals relating to environmental performance, such as carbon neutrality. Green technological innovation and clean energy are considered the prominent factors in reducing emissions and achieving sustainable cities. Through the application of a fixed effect model, generalized method of moments, and quantile-on-quantile regression, this study explores the role of green technology innovation and clean energy in accelerating the sustainable urban transition towards net zero emissions in developing countries while controlling for nonrenewable energy consumption, and economic growth. The long-run results show that green technology innovation and renewable energy consumption reduce CO₂ emissions from urban residential buildings. In contrast, economic growth and nonrenewable energy consumption increase CO₂ emissions. This study proposes a consistent technique for encouraging green technological innovation and renewable energy projects in developing countries where the role of innovation in achieving carbon neutrality is still understudied.

Keywords: green technology innovation, renewable energy, urbanization, net zero emissions

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Authors: Kanchan Negi

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Background: Modern work culture has driven demands for people to work long hours and weekends and take work to home at times. Research on the health effects of these exhaustive temporal work patterns is scant or contradictory. This study examines the relationship between work patterns and well-being (including happiness) in a sample of working women. Method: Primary data of 360 currently married women working in the education, health, banking and IT sector in Delhi, India, were analysed. Logistic regression was used to estimate physical and psychological well-being and happiness across work characteristics. Results: Relative to 35–40 hours/week, working longer related to poor well-being (ß=0.75, 95% CI 0.12 to 1.39). Compared with not working weekends, working most or all weekends is related to poor physical (ß=0.34, 95% CI 0.08 to 0.61) and psychological well-being (ß=0.50, 95% CI 0.20 to 0.79). Rigid work patterns (ß=0.17, 95% CI −0.09 to 0.42) are also related to poor well-being. Conclusion: Decreased well-being and unhappiness are significantly linked to strenuous and rigid work patterns, suggesting that modern work culture may contribute to poor well-being. Flexible timings, compensatory holidays, work-from-home, and daycare facilities for young ones must be welcomed by companies to ease the dual burden of homemakers and career makers.

Keywords: happiness, well-being, work pattern, working women

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Authors: Ghazal Doostmohammadi, Susan Rahimzadeh

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Aim: This research aimed to investigate the relationship between empathy and interpersonal trust and recognize the mediating role of loneliness between them in both genders. Methods: With a correlational descriptive design, 192 university students (130 female and 62 male) responded to the questionnaires on “empathy quotient,” “loneliness,” and “interpersonal trust” tests. These tests were designed and validated by experts in the field. Data were analysed using Pearson correlation and path analysis, which is a statistical technique that uses standard linear regression equations to determine the degree of conformity of a theoretical causal model with reality. Results: The data analysis showed that there was no significant correlation between interpersonal trust, both with loneliness (t=0.169) and empathy (t=0.186), while there was a significant negative correlation (t=0.359) between empathy and loneliness. This means that there is an inverse correlation between empathy and loneliness. The path analysis confirmed the hypothesis of the research about the mediating role of loneliness between empathy and interpersonal trust. But gender did not play a role in this relationship. Conclusion: As an outcome, clinical professionals and education trainers should pay more attention to interpersonal trust as a basic need and try to recreate and shape it to prevent people's social breakdown, and on the other hand, self-disclosure training (especially in Men), expression of feelings and courage should be given double importance to prevent the consequences of loneliness.

Keywords: empathy, loneliness, interpersonal trust, gender

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Authors: Ojo Oo, Akinde S. B., Kiilani A. O., Jayeola Jo, Jogbodo T. M., Ajani Ka, Olaniyan So, Adeagbo Oy, Bolarinwa Ra, Durosomo Ha, Sule W. F.

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Lockdown imposed to control SARS-CoV-2 transmission hampered malaria control services in Nigeria. Considering COVID-19 vaccination, we assessed Plasmodium falciparum (Pf) antigen and SARS-CoV-2 immunoglobulin-G (IgG) positivity among adults in Osogbo, Osun State, Nigeria. Consenting attendees of four Healthcare Centres were consecutively enrolled for blood sampling; relevant socio-demographic/behavioral/clinical/environmental data were collected with a questionnaire. Samples were tested, using commercial rapid test kits, for Pf antigen and SARS-CoV-2 IgG and results were analyzed using logistic regression. Participants' mean age was 40.99 years (n=200), and they were predominantly females (84.5%), traders/businessmen/women (86.0%), with self-reported receipt of COVID-19 vaccine from 123 (61.5%). Pf antigen positivity was 17.5% (95% CI: 12.23–22.77%) with age (p=0.004), marital status (p=0.004), report of stagnant water around the workplace (p=0.041) and bush around homes (p=0.008) being associated. SARS-CoV-2 IgG positivity was 56.5% (95% CI: 49.63–63.37%) with age (p=0.012) and receipt of COVID-19 vaccination (p=0.001) being associated. Although the vaccinated had a 22.8 times higher likelihood of IgG positivity, no factor was predictive of COVID-19 vaccine receipt. We report 17.5% Pf antigen positivity with four predictors, and 56.5% SARS-CoV-2 IgG positivity with two predictors.

Keywords: COVID-19, vaccine, IgG, Plasmodium falciparum, SARS-CoV-2

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Authors: Yasmine Essafi Zouari, Aya Nasreddine

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Following a long inflationary period from the post-war era to the mid-1980s (+10.1% annually), France went through a moderate inflation period between 1986 and 2001 (+2.1% annually) and even lower inflation between 2002 and 2016 (+1.4% annually). In 2022, inflation in France increased rapidly and reached 4.5% over one year in March, according to INSEE estimates. Over a long period, even low inflation has an impact on portfolio value and households’ purchasing power. In such a context, inflation hedging should remain an important issue for investors. In particular, long-term investors, who are concerned with the protection of their wealth, seek to hold effective hedging assets. Considering a mixed-asset portfolio composed of housing assets (residential real estate in 150 Grand Paris communes) as well as financial assets, and using both correlation and regression analysis, results confirm the attribute of the direct housing investment as an inflation hedge especially particularly against its unexpected component. Further, cash and bonds were found to provide respectively a partial and an over hedge against unexpected inflation. Stocks act as a perverse hedge against unexpected inflation and provide no significant positive hedge against expected inflation.

Keywords: direct housing, inflation, hedging ability, optimal portfolio, Grand Paris metropolis

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Authors: Cornelius Femi Popoola

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This study investigated logistics information systems in the distribution of flour in Nigeria. A case study design was used and 50 staff of Honeywell Flour Mill was sampled for the study. Data generated through a questionnaire were analysed using correlation and regression analysis. The findings of the study revealed that logistic information systems such as e-commerce, interactive telephone systems and electronic data interchange positively correlated with the distribution of flour in Honeywell Flour Mill. Finding also deduced that e-commerce, interactive telephone systems and electronic data interchange jointly and positively contribute to the distribution of flour in Honeywell Flour Mill in Nigeria (R = .935; Adj. R2 = .642; F (3,47) = 14.739; p < .05). The study therefore recommended that Honeywell Flour Mill should upgrade their logistic information systems to computer-to-computer communication of business transactions and documents, as well adopt new technology such as, tracking-and-tracing systems (barcode scanning for packages and palettes), tracking vehicles with Global Positioning System (GPS), measuring vehicle performance with ‘black boxes’ (containing logistic data), and Automatic Equipment Identification (AEI) into their systems.

Keywords: e-commerce, electronic data interchange, flour distribution, information system, interactive telephone systems

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Authors: Lidija R. Jevrić, Sanja O. Podunavac-Kuzmanović, Strahinja Z. Kovačević

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In this paper, quantitative structure-retention relationships (QSRR) analysis was applied in order to correlate in silico biological and lipophilicity molecular descriptors with retention values for the set of selected s-triazine herbicides. In silico generated biological and lipophilicity descriptors were discriminated using generalized pair correlation method (GPCM). According to this method, the significant difference between independent variables can be noticed regardless almost equal correlation with dependent variable. Using established multiple linear regression (MLR) models some biological characteristics could be predicted. Established MLR models were evaluated statistically and the most suitable models were selected and ranked using sum of ranking differences (SRD) method. In this method, as reference values, average experimentally obtained values are used. Additionally, using SRD method, similarities among investigated s-triazine herbicides can be noticed. These analysis were conducted in order to characterize selected s-triazine herbicides for future investigations regarding their biodegradability. This study is financially supported by COST action TD1305.

Keywords: descriptors, generalized pair correlation method, pesticides, sum of ranking differences

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Authors: Adithya Jaikumar, Sudarsan Jayasingh

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The dramatic technology led changes that continue to take place at the market place has led to the emergence and implication of online brand pages on social media networks. The Facebook brand page has become extremely popular among different brands. The primary aim of this study was to identify the impact of post formats and content type on customer engagement in Facebook brand pages. Methodology used for this study was to analyze and categorize 9037 content messages posted by 20 automobile brands in India during April 2014 to March 2015 and the customer activity it generated in return. The data was obtained from Fanpage karma- an online tool used for social media analytics. The statistical technique used to analyze the count data was negative binomial regression. The study indicates that there is a statistically significant relationship between the type of post and the customer engagement. The study shows that photos are the most posted format and highest engagement is found to be related to videos. The finding also reveals that social events and entertainment related content increases engagement with the message.

Keywords: content analysis, customer engagement, digital engagement, facebook brand pages, social media

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Authors: Yusef Hedjazi, Saeedeh Nazari Nooghabi

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New information and communication technologies (ICT) as one of the main needs of Faculty members in the process of teaching and learning has used in Irans higher education system since 2000.The main purpose of this study is to investigate the role of information and communication technologies (ICT) in teaching performance of Agricultural and Natural Resources Faculties at University of Tehran. The statistical population of the study consisted of all 250 faculties in Agriculture and Natural Resources Colleges and a questionnaire was used to collect data. The reliability of the questionnaire was confirmed by computing of Cronbachs Alpha coefficient at greater than .72. The study showed a significant relationship between agricultural Faculty members teaching performance and competency in using ICT. The results of the regression analysis also explained 51.7% of the variance, teaching performance. The six independent variables that accounted for the explained variance were experience in using educational websites or software, use of educational multimedia (e.g. film and CD, etc), making a presentation using PowerPoint, familiarity with online education websites, using News group to discuss on educational subjects with colleagues and students, and using Electronic communication (messengers) to solve studentsproblems.

Keywords: information and communication technologies, agricultural and natural resources, faculties, teaching performance

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Authors: Oktia Woro Kasmini Handayani, Sri Ratna Rahayu, Efa Nugroho, Berta Kalswahermawati

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Diabetes occurs 10 years faster in the Southeast Asian region than the European region, which occurs in the most productive periods. Cultural differences as well as cultural transitions can be determinant factors of health cases in urban and rural areas. The purpose of this research is to analyze the effect of the cultural environment, behavior and the occurrence of diabetes mellitus in urban areas of Semarang, Indonesia. The research was conducted in the area of Semarang Regency, using a quantitative approach and supported by qualitative data, the population is DM type 2 patients, sample size of 200 people, with a purposive sampling technique. The independent variable consists of cultural environment, behavior, and the dependent variable is DM. The data is analyzed with regression test method. Cultural environment affects behavior positively, with t value of 4,690 and p (sig.) 0.000, this means sig <0.05, while the effect of behavior on Diabetes Mellitus obtained t value 2.950 with p-value (sig.) 0.003 this means that sig <0.05, thus it can be interpreted that the behavior has a significant effect on Diabetes Mellitus. The cultural environment directly affects the incidence of DM. It can also shape a person's behavior or lifestyle or habit, whether healthy or unhealthy one, which in turn causes symptoms of DM.

Keywords: Behavior, Cultural Environment, Diebetes Millitus, Urban

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Authors: Mohammad Anwar, Shah Waliullah

Abstract:

This study investigated panel data regression models. This paper used Bayesian and classical methods to study the impact of institutions on economic growth from data (1990-2014), especially in developing countries. Under the classical and Bayesian methodology, the two-panel data models were estimated, which are common effects and fixed effects. For the Bayesian approach, the prior information is used in this paper, and normal gamma prior is used for the panel data models. The analysis was done through WinBUGS14 software. The estimated results of the study showed that panel data models are valid models in Bayesian methodology. In the Bayesian approach, the effects of all independent variables were positively and significantly affected by the dependent variables. Based on the standard errors of all models, we must say that the fixed effect model is the best model in the Bayesian estimation of panel data models. Also, it was proved that the fixed effect model has the lowest value of standard error, as compared to other models.

Keywords: Bayesian approach, common effect, fixed effect, random effect, Dynamic Random Effect Model

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Authors: Chau-Kuang Chen, John Hughes, Jr., A. Dexter Samuels

Abstract:

The prediction models for the United States Medical Licensure Examination (USMLE) Steps 1 and 2 performances were constructed by the Monte Carlo simulation modeling approach via linear regression. The purpose of this study was to build robust simulation models to accurately identify the most important predictors and yield the valid range estimations of the Steps 1 and 2 scores. The application of simulation modeling approach was deemed an effective way in predicting student performances on licensure examinations. Also, sensitivity analysis (a/k/a what-if analysis) in the simulation models was used to predict the magnitudes of Steps 1 and 2 affected by changes in the National Board of Medical Examiners (NBME) Basic Science Subject Board scores. In addition, the study results indicated that the Medical College Admission Test (MCAT) Verbal Reasoning score and Step 1 score were significant predictors of the Step 2 performance. Hence, institutions could screen qualified student applicants for interviews and document the effectiveness of basic science education program based on the simulation results.

Keywords: prediction model, sensitivity analysis, simulation method, USMLE

Procedia PDF Downloads 339

Authors: P. Neeraj, Anurag Sharma, Harsukhpreet Singh

Abstract:

In current years, Brain-Computer Interface (BCI) scheme based on steady-state Visual Evoked Potential (SSVEP) have earned much consideration. This study tries to evolve an SSVEP based BCI scheme that can regulate any gadget mock-up in two unique positions ON and OFF. In this paper, two distinctive gleam frequencies in low-frequency part were utilized to evoke the SSVEPs and were shown on a Liquid Crystal Display (LCD) screen utilizing Lab View. Two stimuli shading, Yellow, and Blue were utilized to prepare the system in SSVEPs. The Electroencephalogram (EEG) signals recorded from the occipital part. Elements of the brain were separated by utilizing discrete wavelet Transform. A prominent system for multilayer system diverse Neural Network Algorithm (NNA), is utilized to characterize SSVEP signals. During training of the network with diverse calculation Regression plot results demonstrated that when Levenberg-Marquardt preparing calculation was utilized the exactness turns out to be 93.9%, which is superior to another training algorithm.

Keywords: brain computer interface, electroencephalography, steady-state visual evoked potential, wavelet transform, neural network

Procedia PDF Downloads 334

Authors: Kadio Valere R. Angaman, Birahim Bouna Niang

Abstract:

Land degradation is a serious problem in developing countries, including Cote d’Ivoire, which has its economy focused on agriculture. It occurs in all kinds of ecosystems over the world. However, the drivers of land degradation vary from one region to another and from one ecosystem to another. Thus, identifying these drivers is an essential prerequisite to developing and implementing appropriate policies to reverse the trend of land degradation in the country, especially in the trays ecosystem. Using the binary logistic model with primary data obtained through 780 farmers surveyed, we analyze and identify the drivers of land degradation in the trays ecosystem. The descriptive statistics show that 52% of farmers interviewed have stated facing land degradation in their farmland. This high rate shows the extent of land degradation in this ecosystem. Also, the results obtained from the binary logit regression reveal that land degradation is significantly influenced by a set of variables such as sex, education, slope, erosion, pesticide, agricultural activity, deforestation, and temperature. The drivers identified are mostly local; as a result, the government must implement some policies and strategies that facilitate and incentive the adoption of sustainable land management practices by farmers to reverse the negative trend of land degradation.

Keywords: drivers, land degradation, trays ecosystem, sustainable land management

Procedia PDF Downloads 145