Search results for: Statistical%20package%20IBM%20SPSS%2020

Authors: A. Luli, A. Santona

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It is rare for individuals that are involved in a relationship to think about the possibility of having procreation problems in the near present or in the future. However, infertility is a condition that affects millions of people all around the world. Often, infertile individuals have to deal with experiences of psychological, relational and social problems. In these cases, they have to review their choices and take into consideration, if it is necessary, new ones. Different studies have examined the different decisions that infertile individuals have to go through dealing with infertility and its treatment, but none of them is focused on the decision-making style used by infertile individuals to solve their problem and on the factors that influences it. The aim of this paper is to define the style of decision-making used by infertile persons to give a solution to the ‘problem’ and the potential predictive role of the attachment and of the dyadic adjustment. The total sample is composed by 251 participants, divided in two groups: the experimental group composed by 114 participants, 62 males and 52 females, age between 25 and 59 years, and the control group composed by 137 participants, 65 males and 72 females, age between 22 and 49 years. The battery of instruments used is composed by: the General Decision Making Style (GDMS), the Experiences in Close Relationships Questionnaire Revised (ECR-R), Dyadic Adjustment Scale (DAS), and the Symptom Checklist-90-R (SCL-90-R). The results from the analysis of the samples showed a prevalence of the rational decision-making style for both males and females. No significant statistical difference was found between the experimental and control group. Also the analyses showed a significant statistical relationship between the decision making styles and the adult attachment styles for both males and females. In this case, only for males, there was a significant statistical difference between the experimental and the control group. Another significant statistical relationship was founded between the decision making styles and the adjustment scales for both males and females. Also in this case, the difference between the two groups was founded to be significant only of males. These results contribute to enrich the literature on the subject of decision-making styles in infertile individuals, showing also the predictive role of the attachment styles and the adjustment, confirming in this was the few results in the literature.

Keywords: adjustment, attachment, decision-making style, infertility

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Authors: Firsan Nova

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The average Indonesian watches 5.5 hours of TV a day. With a population of 242 million people and a Free-to-Air (FTA) TV penetration rate of 56%, that equates to 745 million hours of television watched each day. With such potential, it is no wonder that many companies are now attempting to get into the Pay TV market. Research firm Media Partner Asia has forecast in its study that the number of Indonesian pay-television subscribers will climb from 2.4 million in 2012 to 8.7 million by 2020, with penetration scaling up from 7 percent to 21 percent. Key drivers of market growth, the study says, include macro trends built around higher disposable income and a rising middle class, with leading players continuing to invest significantly in sales, distribution and content. New entrants, in the meantime, will boost overall prospects. This study aims to examine and analyze the effect of Market Attractiveness and the Core Competence on Value Creation and Competitive Advantage and its impact to Business Performance in the pay TV industry in Indonesia. The study using strategic management science approach with the census method in which all members of the population are as sample. Verification method is used to examine the relationship between variables. The unit of analysis in this research is all Indonesian Pay TV business units totaling 19 business units. The unit of observation is the director and managers of each business unit. Hypothesis testing is performed by using statistical Partial Least Square (PLS). The conclusion of the study shows that the market attractiveness affects business performance through value creation and competitive advantage. The appropriate value creation comes from the company ability to optimize its core competence and exploit market attractiveness. Value creation affects competitive advantage. The competitive advantage can be determined based on the company's ability to create value for customers and the competitive advantage has an impact on business performance.

Keywords: market attractiveness, core competence, value creation, competitive advantage, business performance

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Authors: Victor Bodell, Lukas Ekstrom, Somayeh Aghanavesi

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Fuel consumption (FC) is one of the key factors in determining expenses of operating a heavy-duty vehicle. A customer may therefore request an estimate of the FC of a desired vehicle. The modular design of heavy-duty vehicles allows their construction by specifying the building blocks, such as gear box, engine and chassis type. If the combination of building blocks is unprecedented, it is unfeasible to measure the FC, since this would first r equire the construction of the vehicle. This paper proposes a machine learning approach to predict FC. This study uses around 40,000 vehicles specific and o perational e nvironmental c onditions i nformation, such as road slopes and driver profiles. A ll v ehicles h ave d iesel engines and a mileage of more than 20,000 km. The data is used to investigate the accuracy of machine learning algorithms Linear regression (LR), K-nearest neighbor (KNN) and Artificial n eural n etworks (ANN) in predicting fuel consumption for heavy-duty vehicles. Performance of the algorithms is evaluated by reporting the prediction error on both simulated data and operational measurements. The performance of the algorithms is compared using nested cross-validation and statistical hypothesis testing. The statistical evaluation procedure finds that ANNs have the lowest prediction error compared to LR and KNN in estimating fuel consumption on both simulated and operational data. The models have a mean relative prediction error of 0.3% on simulated data, and 4.2% on operational data.

Keywords: artificial neural networks, fuel consumption, friedman test, machine learning, statistical hypothesis testing

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Authors: Punam Kumari Mandal, Namita Yangden, Bhumika Rai, Achala Niraula, Sabitra Subedi

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introduction: Family planning not only improves women’s health but also promotes gender equality, better child health, and improved education outcomes, including poverty reduction. The objective of this study is to assess the utilization of family planning methods and associated factors in Sunsari, Nepal. methodology: A cross-sectional analytical study was conducted among women of the reproductive age group (15-49 years) in Sunsari in 2020. Nonprobability purposive sampling was used to collect information from 212 respondents through face-to-face interviews using a Semi-structured interview schedule from ward no 1 of Barju rural municipality. Data processing was done by using SPSS “statistics for windows, version 17.0(SPSS Inc., Chicago, III.USA”). Descriptive analysis and inferential analysis (binary logistic regression) were used to find the association of the utilization of family planning methods with selected demographic variables. All the variables with P-value <0.1 in bivariate analysis were included in multivariate analysis. A P-value of <0.05 was considered to indicate statistical significance at a level of significance of 5%. results: This study showed that the mean age and standard deviation of the respondents were 26±7.03, and 91.5 % of respondent’s age at marriage was less than 20 years. Likewise, 67.5% of respondents use any methods of family planning, and 55.2% of respondents use family planning services from the government health facility. Furthermore, education (AOR 1.579, CI 1.013-2.462)., husband’s occupation (AOR 1.095, CI 0.744-1.610)., type of family (AOR 2.741, CI 1.210-6.210)., and no of living son (AOR 0.259 CI 0.077-0.872)are the factors associated with the utilization of family planning methods. conclusion: This study concludes that two-thirds of reproductive-age women utilize family planning methods. Furthermore, education, the husband’s occupation, the type of family, and no of living sons are the factors associated with the utilization of family planning methods. This reflects that awareness through mass media, including behavioral communication, is needed to increase the utilization of family planning methods.

Keywords: family planning methods, utilization. factors, women, community

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Authors: Chia-Hau Liu, Tai-Yue Wang

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Traditional multivariate control charts assume that measurement from manufacturing processes follows a multivariate normal distribution. However, this assumption may not hold or may be difficult to verify because not all the measurement from manufacturing processes are normal distributed in practice. This study develops a new multivariate control chart for monitoring the processes with non-normal data. We propose a mechanism based on integrating the one-class classification method and the adaptive technique. The adaptive technique is used to improve the sensitivity to small shift on one-class classification in statistical process control. In addition, this design provides an easy way to allocate the value of type I error so it is easier to be implemented. Finally, the simulation study and the real data from industry are used to demonstrate the effectiveness of the propose control charts.

Keywords: multivariate control chart, statistical process control, one-class classification method, non-normal data

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Authors: Lucas Paganin, Viliam Makis

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With the advent of globalization, the market competition has become a major issue for most companies. One of the main strategies to overcome this situation is the quality improvement of the product at a lower cost to meet customers’ expectations. In order to achieve the desired quality of products, it is important to control the process to meet the specifications, and to implement the optimal maintenance policy for the machines and the production lines. Thus, the overall objective is to reduce process variation and the production and maintenance costs. In this paper, an integrated model involving Statistical Process Control (SPC) and maintenance is developed to achieve this goal. Therefore, the main focus of this paper is to develop the jointly optimal maintenance and statistical process control policy minimizing the total long run expected average cost per unit time. In our model, the production process can go out of control due to either the deterioration of equipment or other assignable causes. The equipment is also subject to failures in any of the operating states due to deterioration and aging. Hence, the process mean is controlled by an Xbar control chart using equidistant sampling epochs. We assume that the machine inspection epochs are the times when the control chart signals an out-of-control condition, considering both true and false alarms. At these times, the production process will be stopped, and an investigation will be conducted not only to determine whether it is a true or false alarm, but also to identify the causes of the true alarm, whether it was caused by the change in the machine setting, by other assignable causes, or by both. If the system is out of control, the proper actions will be taken to bring it back to the in-control state. At these epochs, a maintenance action can be taken, which can be no action, or preventive replacement of the unit. When the equipment is in the failure state, a corrective maintenance action is performed, which can be minimal repair or replacement of the machine and the process is brought to the in-control state. SMDP framework is used to formulate and solve the joint control problem. Numerical example is developed to demonstrate the effectiveness of the control policy.

Keywords: maintenance, semi-Markov decision process, statistical process control, Xbar control chart

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Authors: Forrest Kaatz, Adhemar Bultheel

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We use an informational statistical mechanics approach to study the catalytic thermodynamics of platinum and palladium cuboctahedral nanoclusters. Nanoclusters and their adatoms are viewed as chemical graphs with a nearest neighbor adjacency matrix. We use the Morse potential to determine bond energies between cluster atoms in a coordination type calculation. We use adsorbate energies calculated from density functional theory (DFT) to study the adatom effects on the thermodynamic quantities, which are derived from a Hamiltonian. Oxygen radical and molecular adsorbates are studied on platinum clusters and hydrogen on palladium clusters. We calculate the entropy, free energy, and total energy as the coverage of adsorbates increases from bridge and hollow sites on the surface. Thermodynamic behavior versus adatom coverage is related to the structural distribution of adatoms on the nanocluster surfaces. The thermodynamic functions are characterized using a simple adsorption model, with linear trends as the coverage of adatoms increases. The data exhibits size effects for the measured thermodynamic properties with cluster diameters between 2 and 5 nm. Entropy and enthalpy calculations of Pt-O2 compare well with previous theoretical data for Pt(111)-O2, and our Pd-H results show similar trends as experimental measurements for Pd-H2 nanoclusters. Our methods are general and may be applied to wide variety of nanocluster adsorbate systems.

Keywords: catalytic thermodynamics, palladium nanocluster absorbates, platinum nanocluster absorbates, statistical mechanics

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Authors: Kasbparast Mehdi, Hassani Zainab

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Aim: The purpose of this research was to investigate the effectiveness of therapeutical sensorimotor exercise. The statistical population of women who were diagnosed with patellofemoral pain syndrome by a doctor and were between the ages of 35 and 45 and registered for the first time in a sports club in the 4th district of Tehran, 30 people by random sampling and according to The include and exclude criteria were selected and divided into 2 equal control and experimental and homogeneous groups (in terms of height, weight and BMI).In both control and experimental groups, the pain was measured using a Visual Analog Scale(VAS) functionality was measured using the step-down test and quality of life was measured using a World Health Organization Quality of Life Scale (WHOQOL-BREF) (pre-test). Then, only the experimental group performed sensorimotor exercises for 12 weeks and 3 sessions each week, a total of 24 sessions and each session for 1 hour, and during this period, the control group only continued their daily activities. After the end of the training period, the desired factors were evaluated again (post-test) in the same way as the pre-test was done for them (experimental group and control group), with the same quality. Findings: The statistical results showed that in the experimental group, the amount of pain, function and quality of life had a statistical improvement (P≤0.05). Conclusion: In general conclusion, it can be stated that using sensorimotor exercises not only improved functionality and quality of life but also reduced the amount of pain in people with patellofemoral pain syndrome.

Keywords: pain, PFPS, sensori motor training, functionality

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Authors: Bourama Mane, Ibrahima Fall, Mamadou Samba Camara, Alassane Bah

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At the level of the National Statistical Institutes, there is a large volume of data which is generally in a format which conditions the method of publication of the information they contain. Each household or business data collection project includes a dissemination platform for its implementation. Thus, these dissemination methods previously used, do not promote rapid access to information and especially does not offer the option of being able to link data for in-depth processing. In this paper, we present an approach to modeling these data to publish them in a format intended for the Semantic Web. Our objective is to be able to publish all this data in a single platform and offer the option to link with other external data sources. An application of the approach will be made on data from major national surveys such as the one on employment, poverty, child labor and the general census of the population of Senegal.

Keywords: Semantic Web, linked open data, database, statistic

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Authors: Liang Wang, Wei Zhang

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Nowadays, sustainable development has increasingly become an important research topic of engineering education. Existing research on Engineering Education for Sustainable Development (EESD) has highlighted the importance of perceptions for ethical responsibility to address sustainable development in practice. However, whether and how the professional engineering experience affects those perceptions has not been proved, especially in a Chinese context. Our study fills this gap by investigating the perceptions bias of EESD between experienced engineers and engineering students. We specifically examined what EESD means for experienced engineers and engineering students using a triple-dimensional model to understand if there are obvious differences between the two groups. Our goal is to make the benefits of these experiences more accessible in school context. The data (n=438) came from a questionnaire created and adapted from previously published studies containing 288 students from mechanical or civil engineering and 150 civil engineers with rich working experience, and the questionnaire was distributed during Fall 2020. T-test was used to find the difference in different dimensions between the two groups. The statistical results show that there is a significant difference in the perceptions of EESD between experienced engineers and inexperienced engineering students in China. Experienced engineers tend to consider sustainable development from ecological, economic, and social perspectives, while engineering students' answers focus more on ecology and ignore economic and social dimensions to some extend. The findings provide empirical evidence that professional experience is helpful to cultivate the cognition and ability of sustainable development in engineering education. The results of this work indicate that more practical content should be added to engineering education to promote sustainable development. In addition, for the design of engineering courses and professional practice systems for sustainable development, we should not only pay attention to the ecological aspects but also emphasize the coordination of ecological, economic, and socially sustainable development (e.g., engineer's ethical responsibility).

Keywords: engineering education, sustainable development, experienced engineers, engineering students

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Authors: Butta Singh

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This paper presents a chaotic map based approach for secured embedding of patient’s confidential data in electrocardiogram (ECG) signal. The chaotic map generates predefined locations through the use of selective control parameters. The sample value difference method effectually hides the confidential data in ECG sample pairs at these predefined locations. Evaluation of proposed method on all 48 records of MIT-BIH arrhythmia ECG database demonstrates that the embedding does not alter the diagnostic features of cover ECG. The secret data imperceptibility in stego-ECG is evident through various statistical and clinical performance measures. Statistical metrics comprise of Percentage Root Mean Square Difference (PRD) and Peak Signal to Noise Ratio (PSNR). Further, a comparative analysis between proposed method and existing approaches was also performed. The results clearly demonstrated the superiority of proposed method.

Keywords: chaotic maps, ECG steganography, data embedding, electrocardiogram

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Authors: Maximilian Engelhardt, Stephan Seeck

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The COVID-19 pandemic is accelerating the already growing field of e-commerce. The resulting urban freight transport volume leads to traffic and negative environmental impact. Furthermore, the service level of parcel logistics service provider is lacking far behind the expectations of consumer. These challenges can be solved by radically reorganize the urban last mile distribution structure: parcels could be consolidated in a micro hub within the inner city and delivered within time windows by cargo bike. This approach leads to a significant improvement of consumer satisfaction with their overall delivery experience. However, this approach also leads to significantly increased costs per parcel. While there is a relevant share of online shoppers that are willing to pay for such a delivery service there are no deeper insights about this target group available in the literature. Being aware of the importance of knowing target groups for businesses, the aim of this paper is to elaborate the most important factors that determine the willingness to pay for sustainable and service-oriented parcel delivery (factor analysis) and to derive customer segments (cluster analysis). In order to answer those questions, a data set is analyzed using quantitative methods of multivariate statistics. The data set was generated via an online survey in September and October 2020 within the five largest cities in Germany (n = 1.071). The data set contains socio-demographic, living-related and value-related variables, e.g. age, income, city, living situation and willingness to pay. In a prior work of the author, the data was analyzed applying descriptive and inference statistical methods that only provided limited insights regarding the above-mentioned research questions. The analysis in an exploratory way using factor and cluster analysis promise deeper insights of relevant influencing factors and segments for user behavior of the mentioned parcel delivery concept. The analysis model is built and implemented with help of the statistical software language R. The data analysis is currently performed and will be completed in December 2021. It is expected that the results will show the most relevant factors that are determining user behavior of sustainable and service-oriented parcel deliveries (e.g. age, current service experience, willingness to pay) and give deeper insights in characteristics that describe the segments that are more or less willing to pay for a better parcel delivery service. Based on the expected results, relevant implications and conclusions can be derived for startups that are about to change the way parcels are delivered: more customer-orientated by time window-delivery and parcel consolidation, more environmental-friendly by cargo bike. The results will give detailed insights regarding their target groups of parcel recipients. Further research can be conducted by exploring alternative revenue models (beyond the parcel recipient) that could compensate the additional costs, e.g. online-shops that increase their service-level or municipalities that reduce traffic on their streets.

Keywords: customer segmentation, e-commerce, last mile delivery, parcel service, urban logistics, willingness-to-pay

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Authors: Ru-Yu Lien, Shih-Hsin Hung, Shu-Fen Lu, Ju-Jen Shie, Wen-Ju Yang, Yuann-Meei Tzeng, Chien-Ying Wang

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Background: The quality of care in intensive care units (ICUs) is crucial, especially for terminally ill patients. Shared decision-making (SDM) with families is essential to ensure appropriate care and reduce suffering. Aim: This study explores the effectiveness of an end-of-life decision support Patient Decision Aid (PDA) in an ICU setting. Methods: This study employed a cross-sectional research design conducted in an ICU from August 2020 to June 2023. Participants included family members of end-of-life patients aged 20 or older. A total of 319 participants. Family members of end-of-life patients received the PDA, and data were collected after they made medical decisions. Data collection involved providing family members with a PDA during family meetings. A post-PDA questionnaire with 17 questions assessed PDA effectiveness and anxiety levels. Statistical analysis was performed using SPSS 22.0. Results: The PDA significantly reduced anxiety levels among family members (p < 0.001). It helped them organize their thoughts, prepare for discussions with doctors, and understand critical decision factors. Most importantly, it influenced decision outcomes, with a shift towards palliative care and withdrawal of life-sustaining treatment. Conclusion: This study highlights the importance of family-centered end-of-life care in ICUs. PDAs promote informed decision-making, reduce conflicts, and enhance patient and family involvement. These tools align patient values and goals with medical recommendations, ultimately leading to decisions that prioritize comfort and quality of life. Implementing PDAs in healthcare systems can ensure that patients' care aligns with their values.

Keywords: shared decision-making, patient decision aid, end-of-life care, intensive care unit, family-centered care

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Authors: Hany Mustafa, Mahmoud Roushdi, Khaled Kheireldin

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Rainfall variability is an important feature of semi-arid climates. Climate change is very likely to increase the frequency, magnitude, and variability of extreme weather events such as droughts, floods, and storms. The Blue Nile Basin is facing extreme climate change-related events such as floods and droughts and its possible impacts on ecosystem, livelihood, agriculture, livestock, and biodiversity are expected. Rainfall variability is a threat to food production in the Blue Nile Basin countries. This study investigates the long-term variations and trends of seasonal and annual precipitation over the Blue Nile Basin for 102-year period (1901-2002). Six statistical trend analysis of precipitation was performed with nonparametric Mann-Kendall test and Sen's slope estimator. On the other hands, four statistical absolute homogeneity tests: Standard Normal Homogeneity Test, Buishand Range test, Pettitt test and the Von Neumann ratio test were applied to test the homogeneity of the rainfall data, using XLSTAT software, which results of p-valueless than alpha=0.05, were significant. The percentages of significant trends obtained for each parameter in the different seasons are presented. The study recommends adaptation strategies to be streamlined to relevant policies, enhancing local farmers’ adaptive capacity for facing future climate change effects.

Keywords: Blue Nile basin, climate change, Mann-Kendall test, trend analysis

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Authors: Shinji Kawakura, Ryosuke Shibasaki

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We have been grouping and developing various kinds of practical, promising sensing applied systems concerning agricultural advancement and technical tradition (guidance). These include advanced devices to secure real-time data related to worker motion, and we analyze by methods of various advanced statistics and human dynamics (e.g. primary component analysis, Ward system based cluster analysis, and mapping). What is more, we have been considering worker daily health and safety issues. Targeted fields are mainly common farms, meadows, and gardens. After then, we observed and discussed time-line style, changing data. And, we made some suggestions. The entire plan makes it possible to improve both the aforementioned applied systems and farms.

Keywords: advanced statistical analysis, wearable sensing system, tradition of skill, supporting for workers, detecting crisis

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

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This study considers the selection of the most suitable in silico molecular descriptors that could be used for s-triazine pesticides characterization. Suitable descriptors among topological, geometrical and physicochemical are used for quantitative structure-retention relationships (QSRR) model establishment. Established models were obtained using linear regression (LR) and multiple linear regression (MLR) analysis. In this paper, MLR models were established avoiding multicollinearity among the selected molecular descriptors. Statistical quality of established models was evaluated by standard and cross-validation statistical parameters. For detection of similarity or dissimilarity among investigated s-triazine pesticides and their classification, principal component analysis (PCA) and hierarchical cluster analysis (HCA) were used and gave similar grouping. This study is financially supported by COST action TD1305.

Keywords: chemometrics, classification analysis, molecular descriptors, pesticides, regression analysis

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Authors: Bavneet Kaur Sidhu, Manoj Tiwari

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Global Developmental Delay (GDD) is a common pediatric condition. Etiologies of GDD might, however, differ in developing countries. In the last decade, sporadic families are being reported in various countries. As to the author’s best knowledge, many risk factors and their correlation with the prevalence of GDD have been studied but its statistical correlation has not been done. Thus we propose the present study by targeting the risk factor, prevalence and their statistical correlation with GDD. FMR1 gene was studied to confirm the disease and its penetrance. A complete questionnaire-based performance was designed for the statistical studies having a personal, past and present medical history along with their socio-economic status as well. Methods: We distributed the children’s age in 4 different age groups having 5-year intervals and applied structural equation modeling (SEM) techniques, Spearman’s rank correlation coefficient, Karl Pearson correlation coefficient, and chi-square test.Result: A total of 1100 families were enrolled for this study; among them, 330 were clinically and biologically confirmed (radiological studies) for the disease, 204 were males (61.8%), 126 were females (38.18%). We found that 27.87% were genetic and 72.12 were sporadic, out of 72.12 %, 43.277% cases from urban and 56.72% from the rural locality, the mothers' literacy rate was 32.12% and working women numbers were 41.21%. Conclusions: There is a significant association between mothers' age and GDD prevalence, which is also followed by mothers' literacy rate and mothers' occupation, whereas there was no association between fathers' age and GDD.

Keywords: global developmental delay, FMR1 gene, spearman’ rank correlation coefficient, structural equation modeling

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Authors: D. Beziakina, E. Bulgakova

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This study continues the research on Tuvinian intonation and presents a general cross-dialect analysis of intonation of Tuvinian declarative utterances, specifically the character of the tone movement in order to test the hypothesis about the prevalence of level tone in some Tuvinian dialects. The results of the analysis of basic pitch characteristics of Tuvinian speech (in general and in comparison with two other Turkic languages - Uzbek and Azerbaijani) are also given in this paper. The goal of our work was to obtain the ranges of pitch parameter values typical for Tuvinian speech. Such language-specific values can be used in speaker identification systems in order to get more accurate results of ethnic speech analysis. We also present the results of a cross-dialect analysis of declarative intonation in the poorly studied Tuvinian language.

Keywords: speech analysis, statistical analysis, speaker recognition, identification of person

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Authors: Apollinaire Barme, Simon Tamayo, Arthur Gaudron

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This paper presents a statistical approach to identify explanatory variables linearly related to e-commerce sales. The proposed methodology allows specifying a regression model in order to quantify the relevance between openly available data (economic and demographic) and national e-commerce sales. The proposed methodology consists in collecting data, preselecting input variables, performing regressions for choosing variables and models, testing and validating. The usefulness of the proposed approach is twofold: on the one hand, it allows identifying the variables that influence e- commerce sales with an accessible approach. And on the other hand, it can be used to model future sales from the input variables. Results show that e-commerce is linearly dependent on 11 economic and demographic indicators.

Keywords: e-commerce, statistical modeling, regression, empirical research

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Authors: Po-Wen Chen, Jin-Yu Wu, Md. Manirul Ali, Yang Peng, Chen-Te Chang, Der-Jun Jan

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Dynamics of cathode spot has become a major part of vacuum arc discharge with its high academic interest and wide application potential. In this article, using a three-dimensional statistical model, we simulate the distribution of the ignition probability of a new cathode spot occurring in different magnetic pressure on old cathode spot surface and at different arcing time. This model for the ignition probability of a new cathode spot was proposed in two typical situations, one by the pure isotropic random walk in the absence of an external magnetic field, other by the retrograde motion in external magnetic field, in parallel with the cathode surface. We mainly focus on developed relationship between the ignition probability density distribution of a new cathode spot and the external magnetic field.

Keywords: cathode spot, vacuum arc discharge, transverse magnetic field, random walk

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Authors: Elucir Gir, Laelson Rochelle Milanês Sousa, Renata Karina Reis, Soraia Assad Nasbine Rabeh, Mayra Gonçalves Menegueti, Ana Cristina de Oliveira e Silva, Sheila Araújo Teles

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Context and significance: Nursing team professionals faced challenges in combating the COVID-19 pandemic around the world. They were subjected to exhausting workloads and prolonged use of Personal Protective Equipment. Using N95 masks for long periods of time can cause skin changes. In this context, health professionals who worked on the front lines of fighting the pandemic were more exposed to possible physical and psychological changes. Objective: The aim of the study was to analyze the factors associated with skin lesions resulting from the use of N95 masks among nursing team professionals. Method: The study was carried out in all regions of Brazil from October to December 2020, with professionals from the nursing team who worked in health care during the COVID-19 pandemic. Participants were recruited via social media, and information was collected electronically and stored on the Survey Monkey platform. Descriptive statistics were used to characterize the sample, association tests (Chi-square), with a statistical significance level of p < 0.05. Factors associated with skin lesions resulting from the use of an N95 mask were determined by Binary Logistic Regression, with a significance level of 5% (α = 0.05). Results: 8,405 nursing professionals participated in the study, 5,492 nurses (65.3%), 2,747 nursing technicians (32.7%), and 7,084 females (84.3%). Female nursing team professionals were 1.4 times more likely to develop skin lesions due to the use of N95 masks when compared to males (OR 1.4 [CI95% 1.22 – 1.59] p < 0.001). The following protective factors were identified: nursing technician (ORA 0.608 [CI95% 0.43 – 0.86] p = 0.005) and not having provided assistance in field hospitals for COVID-19 (0.73 [CI95% 0.65-0.81] p<0.000). Conclusion: It was concluded that female nursing team professionals were more likely to have skin changes related to the use of N95 masks. The need for intervention studies is emphasized in order to explore measures to prevent these types of injuries. Descritores: Nursing professionals; COVID-19; SARS-CoV-2; Brazil.

Keywords: nursing professionals, COVID-19, SARS-CoV-2, Brazil

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Authors: Amenah Galo, Mohammed Farid, Kareem Alsharkawy, Robert Warner, Karthikeyan Srinivasan, Haitham Khalil, Ruth Waters

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Introduction: The cessation of elective surgery, particularly breast reconstruction, continue to be affected by the COVID-19 pandemic. The restructuring of medical services and staff redeployment severely affected the ability to return to normality for surgical specialties. The aim of this study is to determine the decline in breast reconstruction affected by the COVID-19 pandemic in a tertiary center. Methods: A retrospective review of breast reconstruction cases (autologous, non-autologous) or mastectomies Pre- COVID (March 2019-March 2020) and during COVID (March 2020- March 2021) at Queen Elizabeth Hospital, Birmingham, were collated. Data included patient demographics, BMI, previous and recent reconstruction, length of hospital stay, and mastectomies, including risk-reducing. Results: The number of patients who had breast reconstruction was significantly lower during COVID (n=62) compared to pre-COVID (n=199). The mean age (pre-COVID 51, COVID 59 years), BMI (Pre-COVID and COVID = 27), previous reconstruction (pre-COVID n=101, 51%, COVID n=33, 53%) and length hospital stay was less during COVID (3 days) compared to Pre-COVID (4 days). The proportion of risk-reducing mastectomies and reconstruction during COVID (32%, n=20) were higher than pre-COVID (21%, n=41). A higher proportion rate of autologous reconstruction (DIEP 56, TRAM 17) Pre-COVID compared to COVID (DIEP 22, TRAM 7). Implant reconstructions were higher during COVID (n=19, 31%) than pre-COVID (n=31, 16%). Conclusion: The lack of regular provision for breast reconstruction continues to decline during the pandemic. This will have a tremendous impact on waiting lists without a timeline for reconstruction to offer patients. An international survey highlights the disparities in offering breast reconstruction and strategies to rectify this issue.

Keywords: breast reconstruction, COVID-19 pandemic, mastectomy, autologous, implant

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Authors: Mehdi Brahimi, Kamal Medjaher, Noureddine Zerhouni, Mohammed Leouatni

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The Prognostics and Health Management is a system engineering discipline which provides solutions and models to the implantation of a predictive maintenance. The approach is based on extracting useful information from monitoring data to assess the “health” state of an industrial equipment or an asset. In this paper, we examine multiple extracted features from Pantograph-Catenary contact force in order to select the most relevant ones to achieve a diagnostics function. The feature extraction methodology is based on simulation data generated thanks to a Pantograph-Catenary simulation software called INPAC and measurement data. The feature extraction method is based on both statistical and signal processing analyses. The feature selection method is based on statistical criteria.

Keywords: catenary/pantograph interaction, diagnostics, Prognostics and Health Management (PHM), quality of current collection

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Authors: Nicki Mohammadi, Emma Reford, Natalia Romano Spica, Laura Tabacof, Jenna Tosto-Mancuso, David Putrino, Christopher P. Kellner

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Introductory Statement: The onset of the COVID-19 pandemic demanded an unprecedented need for the rapid development, dispersal, and application of infection testing. However, despite the impressive mobilization of resources, individuals were incredibly limited in their access to tests, particularly during the initial months of the pandemic (March-April 2020) in New York City (NYC). Access to COVID-19 testing is crucial in understanding patients’ illness experiences and integral to the development of COVID-19 standard-of-care protocols, especially in the context of overall access to healthcare resources. Succinct Description of basic methodologies: 18 Patients in a COVID-19 Remote Patient Monitoring Program (Precision Recovery within the Mount Sinai Health System) were interviewed regarding their experience with COVID-19 during the first wave (March-May 2020) of the COVID-19 pandemic in New York City. Patients were asked about their experiences navigating COVID-19 diagnoses, the health care system, and their recovery process. Transcribed interviews were analyzed for thematic codes, using grounded theory to guide the identification of emergent themes and codebook development through an iterative process. Data coding was performed using NVivo12. References for the domain “testing” were then extracted and analyzed for themes and statistical patterns. Clear Indication of Major Findings of the study: 100% of participants (18/18) referenced COVID-19 testing in their interviews, with a total of 79 references across the 18 transcripts (average: 4.4 references/interview; 2.7% interview coverage). 89% of participants (16/18) discussed the difficulty of access to testing, including denial of testing without high severity of symptoms, geographical distance to the testing site, and lack of testing resources at healthcare centers. Participants shared varying perspectives on how the lack of certainty regarding their COVID-19 status affected their course of recovery. One participant shared that because she never tested positive she was shielded from her anxiety and fear, given the death toll in NYC. Another group of participants shared that not having a concrete status to share with family, friends and professionals affected how seriously onlookers took their symptoms. Furthermore, the absence of a positive test barred some individuals from access to treatment programs and employment support. Concluding Statement: Lack of access to COVID-19 testing in the first wave of the pandemic in NYC was a prominent element of patients’ illness experience, particularly during their recovery phase. While for some the lack of concrete results was protective, most emphasized the invalidating effect this had on the perception of illness for both self and others. COVID-19 testing is now widely accessible; however, those who are unable to demonstrate a positive test result but who are still presumed to have had COVID-19 in the first wave must continue to adapt to and live with the effects of this gap in knowledge and care on their recovery. Future efforts are required to ensure that patients do not face barriers to care due to the lack of testing and are reassured regarding their access to healthcare. Affiliations- 1Department of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY 2Abilities Research Center, Department of Rehabilitation and Human Performance, Icahn School of Medicine at Mount Sinai, New York, NY

Keywords: accessibility, COVID-19, recovery, testing

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Authors: Jasper Kevin C. Dionisio, Denise Mae M. Unsay

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In a manufacturing firm, controlling the process ensures that optimum efficiency, productivity, and quality in an organization are achieved. An operation with no standardized procedure yields a poor productivity, inefficiency, and an out of control process. This study focuses on controlling the small intestine processing of a chicken dressing plant through the use of Statistical Process Control (SPC). Since the operation does not employ a standard procedure and does not have an established standard time, the process through the assessment of the observed time of the overall operation of small intestine processing, through the use of X-Bar R Control Chart, is found to be out of control. In the solution of this problem, the researchers conduct a motion and time study aiming to establish a standard procedure for the operation. The normal operator was picked through the use of Westinghouse Rating System. Instead of utilizing the traditional motion and time study, the researchers used the X-Bar R Control Chart in determining the process average of the process that is used for establishing the standard time. The observed time of the normal operator was noted and plotted to the X-Bar R Control Chart. Out of control points that are due to assignable cause were removed and the process average, or the average time the normal operator conducted the process, which was already in control and free form any outliers, was obtained. The process average was then used in determining the standard time of small intestine processing. As a recommendation, the researchers suggest the implementation of the standard time established which is with consonance to the standard procedure which was adopted from the normal operator. With that recommendation, the whole operation will induce a 45.54 % increase in their productivity.

Keywords: motion and time study, process controlling, statistical process control, X-Bar R Control chart

Procedia PDF Downloads 181

Authors: Sintija Miļuna, Ričards Melderis, Loreta Briuka, Dagnija Rostoka, Ingus Skadiņš, Juta Kroiča

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Objectives Smokeless tobacco products in Latvia become more available and favorable to young adults, especially students and athletes like hockey and floorball players. The aim of the research was to detect visual mucosal changes in the oral cavity in smokeless tobacco users and to evaluate pro - inflammatory and anti - inflammatory cytokine (IL-6, IL-1, IL-8, TNF Alpha) levels in saliva from smokeless tobacco users. Methods A smokeless tobacco group (n=10) and a control group (non-tobacco users) (n=10) were intraorally examined for oral lesions and 5 ml of saliva were collected. Saliva was analysed for Il-6, IL-1, Il-8, TNF Alpha using ELISA Sigma-Aldrich. For statistical analysis IBM Statistics 27 was used (Mann - Whitney U test, Spearman’s Rank Correlation coefficient). This research was approved by the Ethics Committee of Rīga Stradiņš University No.22/28.01.2016. This research has been developed with financing from the European Social Fund and Latvian state budget within the project no. 8.2.2.0/20/I/004 “Support for involving doctoral students in scientific research and studies” at Rīga Stradiņš University. Results IL-1, IL-6, IL-8, TNF Alpha levels were higher in the smokeless tobacco group (IL-1 83.34 pg/ml vs. 74.26 pg/ml; IL-6 195.10 pg/ml vs. 6.16 pg/ml; IL-8 736.34 pg/ml vs. 285.26 pg/ml; TNF Alpha 489.27 pg/ml vs. 200.9 pg/ml), but statistically there is no difference between control group and smokeless tobacco group (IL1 p=0.190, IL6 p=0.052, IL8 p=0.165, TNF alpha p=0.089). There was statistical correlation between IL1 and IL6 (p=0.023), IL6 and TNF alpha (p=0.028), IL8 and IL6 (p=0.005). Conclusions White localized lesions were detected in places where smokeless tobacco users placed sachets. There is a statistical correlation between IL6 and IL1 levels, IL6 and TNF alpha levels, IL8 and IL6 levels in saliva. There are no differences in the inflammatory cytokine levels between control group and smokeless tobacco group.

Keywords: smokeless tobacco, Snus, inflammatory biomarkers, oral lesions, oral pathology

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Authors: Mohamad Ghozali Hassan, Abdul Aziz Othman, Mohd Azril Ismail

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Adapting quickly to environmental dynamism is essential for an organization to develop outsourcing strategic and management in order to sustain competitive advantage. This research used the Partial Least Squares Structural Equation Modeling (PLS-SEM) tool to investigate the factors of environmental dynamism impact on the strategic outsourcing success among electrical and electronic manufacturing industries in outsourcing management. Statistical results confirm that the inclusion of customer demand, technological change, and competition level as a new combination concept of environmental dynamism, has positive effects on outsourcing success. Additionally, this research demonstrates the acceptability of PLS-SEM as a statistical analysis to furnish a better understanding of environmental dynamism in outsourcing management in Malaysia. A practical finding contributes to academics and practitioners in the field of outsourcing management.

Keywords: environmental dynamism, customer demand, technological change, competition level, outsourcing success

Procedia PDF Downloads 472

Authors: Pratap Sing, Chaman. K. Jadon, H. P. Meena, D. L.yadav, S. L. Yadav, Uditi Dhakad

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The experiment was conducted at Agricultural Research Station, Agriculture University, Kota, Rajasthan, India during kharif and rabi 2020-21 and 2021-22 to study the biofficacy of diclosulam and its residual effect on succeeding wheat crop. The treatments comprised of Diclosulam 84 % WDG viz. 6.25, 12.50, 25.00 and 37.50 g/ha as pre emergence (PE), Pendimethalin 30% EC 3.33 l/ha, Sulfentrazon 48% SC 750 g/ha, hand weeding at 30 and 45 DAS and weedy check, were evaluated in randomized block design in three replications. The experimental soil was clay in texture and non-calcareous. Experimental field was mainly dominated by grasses-Echinochloa colonum, E.crusgalli,Cynodon dactylon, Sedges-Cyperus rotundus and broad leaved weeds Celosia argentea and Digera arvensis.The result revealed that application of Diclosulam 84 % WDG 25 g/ha PE was found effective in controlling mostly weed species and registered higher weed control efficiency 81.2, 74.3, 69.6 per cent at 30, 45 days after sowing and at harvest. Diclosulam 84 % WDG (6.25-25.0 g/ha) was found selective to the soybean crop as no any phytotoxicity symptoms were observed. Among the herbicidal treatments, Diclosulam 84 % WDG 25 g/ha registered maximum and significantly higher soybean seed yield (1889 and 1431 kg/ha during kharif 2020 and 2021, respectively and was at par with Sulfentrazone 48% SC 750 g/ha and over weedy check( 1027 and 667 kg/ha).The wheat crop growth, yield attributes and seed yield were not influenced due to carry over effect of the Diclosulam 84 % WDG( 6.25-25.0 g/ha) and no any phytotoxicity symptoms were observed. Henceforth, the Diclosulam 84 % WDG 25.0 g/ha as pre emergence may be used in the soybean for effective weed control without carry over effect on succeeding wheat crop.

Keywords: Diclosulam, soybean, carry over effect, succeeding wheat

Procedia PDF Downloads 80

Authors: Goksel Ezgi Guzey, Bihrat Onoz

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The scarcity of streamflow gauging stations and the increasing effects of global warming cause designing water management systems to be very difficult. This study is a significant contribution to assessing regional regression models for estimating streamflow. In this study, simulated meteorological data was related to the observed streamflow data from 1971 to 2020 for 33 stream gauging stations of the Euphrates-Tigris Basin. Ordinary least squares regression was used to predict flow for 2020-2100 with the simulated meteorological data. CORDEX- EURO and CORDEX-MENA domains were used with 0.11 and 0.22 grids, respectively, to estimate climate conditions under certain climate scenarios. Twelve meteorological variables simulated by two regional climate models, RCA4 and RegCM4, were used as independent variables in the ordinary least squares regression, where the observed streamflow was the dependent variable. The variability of streamflow was then calculated with 5-6 meteorological variables and watershed characteristics such as area and height prior to the application. Of the regression analysis of 31 stream gauging stations' data, the stations were subjected to a clustering analysis, which grouped the stations in two clusters in terms of their hydrometeorological properties. Two streamflow equations were found for the two clusters of stream gauging stations for every domain and every regional climate model, which increased the efficiency of streamflow estimation by a range of 10-15% for all the models. This study underlines the importance of homogeneity of a region in estimating streamflow not only in terms of the geographical location but also in terms of the meteorological characteristics of that region.

Keywords: hydrology, streamflow estimation, climate change, hydrologic modeling, HBV, hydropower

Procedia PDF Downloads 97

Authors: Marcho Setiawan Handok, Samuel S. Lemma, Abdoulaye Fofana, Naseef Mansoor

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This paper is proposing a method to predict the outcome of the National Football League match with data from 2019 to 2022 and compare it with other popular models. The model uses open-source statistical data of each team, such as passing yards, rushing yards, fumbles lost, and scoring. Each statistical data has offensive and defensive. For instance, a data set of anticipated values for a specific matchup is created by comparing the offensive passing yards obtained by one team to the defensive passing yards given by the opposition. We evaluated the model’s performance by contrasting its result with those of established prediction algorithms. This research is using a neural network to predict the score of a National Football League match and then predict the winner of the game.

Keywords: game prediction, NFL, football, artificial neural network

Procedia PDF Downloads 58