Search results for: cost index

Authors: Anna Ching-Yu Wong

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Introduction: Textbooks play a sizable portion of the overall cost of higher education students. It is a board consent that open education resources (OER) reduce the te4xtbook costs and provide students a way to receive high-quality learning materials at little or no cost to them. However, there is less agreement over exactly how much. This study presents an approach for calculating OER savings by using SUNY Canton NON-OER courses (N=233) to estimate the potentially textbook savings for one semester – Fall 2022. The purpose in collecting data is to understand how much potentially saved from using OER materials and to have a record for future further studies. Literature Reviews: In the past years, researchers identified the rising cost of textbooks disproportionately harm students in higher education institutions and how much an average cost of a textbook. For example, Nyamweya (2018) found that on average students save $116.94 per course when OER adopted in place of traditional commercial textbooks by using a simple formula. Student PIRGs (2015) used reports of per-course savings when transforming a course from using a commercial textbook to OER to reach an estimate of $100 average cost savings per course. Allen and Wiley (2016) presented at the 2016 Open Education Conference on multiple cost-savings studies and concluded $100 was reasonable per-course savings estimates. Ruth (2018) calculated an average cost of a textbook was $79.37 per-course. Hilton, et al (2014) conducted a study with seven community colleges across the nation and found the average textbook cost to be $90.61. There is less agreement over exactly how much would be saved by adopting an OER course. This study used SUNY Canton as a case study to create an approach for estimating OER savings. Methodology: Step one: Identify NON-OER courses from UcanWeb Class Schedule. Step two: View textbook lists for the classes (Campus bookstore prices). Step three: Calculate the average textbook prices by averaging the new book and used book prices. Step four: Multiply the average textbook prices with the number of students in the course. Findings: The result of this calculation was straightforward. The average of a traditional textbooks is $132.45. Students potentially saved $1,091,879.94. Conclusion: (1) The result confirms what we have known: Adopting OER in place of traditional textbooks and materials achieves significant savings for students, as well as the parents and taxpayers who support them through grants and loans. (2) The average textbook savings for adopting an OER course is variable depending on the size of the college and as well as the number of enrollment students.

Keywords: textbook savings, open textbooks, textbook costs assessment, open access

Procedia PDF Downloads 75

Authors: Wen Liang Chang, Mei Wei Wang, Ruey Huei Yeh

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This paper studies the comparisons of individual and group replacement policies for a series connection system with two machines. Suppose that manufacturer’s production system is a series connection system which is combined by two machines. For two machines, when machines fail within the operating time, minimal repair is performed for machines by the manufacturer. The manufacturer plans to a preventive replacement for machines at a pre-specified time to maintain system normal operation. Under these maintenance policies, the maintenance cost rate models of individual and group replacement for a series connection system with two machines is derived and further, optimal preventive replacement time is obtained such that the expected total maintenance cost rate is minimized. Finally, some numerical examples are given to illustrate the influences of individual and group replacement policies to the maintenance cost rate.

Keywords: individual replacement, group replacement, replacement time, two machines, series connection system

Procedia PDF Downloads 488

Authors: Benga Ebouele, Thomas Tengen

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Implementing either periodic or continuous inventory review model within most manufacturing-companies-supply chains as a management tool may incur higher costs. These high costs affect the system flexibility which in turn affects the level of service required to satisfy customers. However, these effects are not clearly understood because the parameters of both inventory review policies (protection demand interval, order quantity, etc.) are not designed to be fully utilized under different and uncertain conditions such as poor manufacturing, supplies and delivery performance. Coming up with a hybrid model which may combine in some sense the feature of both continuous and a periodic inventory review models should be useful. Therefore, there is a need to build and evaluate such hybrid model on the annual total cost, stock out probability and system’s flexibility in order to search for the most cost effective inventory review model. This work also seeks to find the optimal sets of parameters of inventory management under stochastic condition so as to optimise each policy independently. The results reveal that a continuous inventory system always incurs lesser cost than a periodic (R, S) inventory system, but this difference tends to decrease as time goes by. Although the hybrid inventory is the only one that can yield lesser cost over time, it is not always desirable but also natural to use it in order to help the system to meet high performance specification.

Keywords: demand and lead time randomness, hybrid Inventory model, optimization, supply chain

Procedia PDF Downloads 313

Authors: Tedros Asefaw Gebremeskel, Xaoyi Yang

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The potential of solar energy in Eritrea is relatively high, based on this truth, there are a number of isolated and remote villages situated far away from the electrical national grid which don’t get access to electricity. The core objective of this work is to design a most favorable and cost-effective power by means of standalone PV system for the electrification of a single housing in the inaccessible area of Eritrea. The sizing of the recommended PV system is achieved, such as radiation data and electrical load for the typical household of the selected site is also well thought-out in the design steps. Finally, the life cycle cost (LCC) analysis is conducted to evaluate the economic viability of the system. The outcome of the study promote the use of PV system for a residential building and show that PV system is a reasonable option to provide electricity for household applications in the rural area of Eritrea.

Keywords: electrification, inaccessible area, life cycle cost, residential building, stand-alone PV system

Procedia PDF Downloads 143

Authors: Faheem Ur Rehman, Muhammad Khalil Khan, Miao Qing

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This study investigated the asymmetric links and portfolio strategies between green bonds and the markets of three different cryptocurrencies, i.e., green, Islamic, and conventional, using data from January 1, 2018, to April 8, 2022, and employing asymmetric TVP-VAR model to quantify risk spillovers in the network analysis. In addition, we use the minimum variance, minimum correlation, and minimum connectedness methodologies to assess the portfolio implications. The results of the asymmetric dynamic connectedness index (TCI) model show that by adopting cryptocurrencies for digital finance, risk spillovers are found to be reduced. The findings of net directional connectedness demonstrate that during the study period, green bonds consistently get return spillovers from all other network variables. Positive return spillovers are bigger in magnitude than negative ones. These results imply that the influence of the green bond market on the cryptocurrency markets is decreasing. Positive return spillovers generate higher connectedness values for (HG, BNB, and TRX) coins and persistent net recipients in the specific network. On the other hand, Cardano and ADA coins are persistent net transmitters in the system. XLM and MIOTA's responsibilities shift over time, and there is evidence of asymmetry when both positive and negative returns are considered. According to the pairwise portfolio weights, BNB vs. BTC has the largest portfolio weights in the system, followed by BNB vs. Ethereum, suggesting the best investment strategies in the network.

Keywords: asymmetric TVP-VAR, global sustainable index, cryptocurrency, portfolios

Procedia PDF Downloads 78

Authors: Lovro Štefan

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The main purpose of the present study was to investigate the associations between the overweight/obesity status and lifestyle factors. In this cross-sectional study, participants were 1950 urban secondary-school students (54.7% of female students) aged 17-18 years old. Dependent variable was body-mass index status derived from self-reported height and weight. The outcome was binarised, where participants with value <25 kg/m2 were collapsed into „normal“, while those ≥25 kg/m2 into „overweight/obesity“ category. Independent variables were gender, type of school, physical activity, sedentary behaviour, self-rated health, self-perceived socioeconomic status and psychological distress. The associations between the dependent and independent variables were analyzed by using multiple logistic regression analysis. In the univariate model, being overweight/obese was significantly associated with being a male student (OR 0.31; 95% CI 0.23 to 0.42), attending a vocational school (OR 1.87; 95% CI 1.42 to 2.48), not meeting the recommendations for moderate-to-vigorous physical activity (OR 0.44; 95% CI 0.22 to 0.88), more time spending in sedentary behaviour (OR 1.53; 95% CI 1.07 to 2.19), poor self-rated health (OR 0.35, 95% CI 0.20 to 0.56) and lower socioeconomic status (OR 0.63; 95% CI 0.48 to 0.84). In the multivariate model, the same associations occured between the dependent and independent variable. In both models, psychological distress was not associated with being overweight/obese. In conclusion, our findings suggest, that lifestyle factors are independently associated with body-mass index

Keywords: body mass index, secondary-school students, Croatia, physical activity, sedentary behaviour, logistic regression

Procedia PDF Downloads 89

Authors: Jin Woo Hwang, Byung Kwan Oh, Yousok Kim, Hyo Seon Park

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As greenhouse effect has been recognized as serious environmental problem of the world, interests in carbon dioxide (CO₂) emission which comprises major part of greenhouse gas (GHG) emissions have been increased recently. Since construction industry takes a relatively large portion of total CO₂ emissions of the world, extensive studies about reducing CO₂ emissions in construction and operation of building have been carried out after the 2000s. Also, performance based design (PBD) methodology based on nonlinear analysis has been robustly developed after Northridge Earthquake in 1994 to assure and assess seismic performance of building more exactly because structural engineers recognized that prescriptive code based design approach cannot address inelastic earthquake responses directly and assure performance of building exactly. Although CO₂ emissions and PBD approach are recent rising issues on construction industry and structural engineering, there were few or no researches considering these two issues simultaneously. Thus, the objective of this study is to minimize the CO₂ emissions and cost of building designed by PBD approach in structural design stage considering structural materials. 4 story and 4 span reinforced concrete building optimally designed to minimize CO₂ emissions and cost of building and to satisfy specific seismic performance (collapse prevention in maximum considered earthquake) of building satisfying prescriptive code regulations using non-dominated sorting genetic algorithm-II (NSGA-II). Optimized design result showed that minimized CO₂ emissions and cost of building were acquired satisfying specific seismic performance. Therefore, the methodology proposed in this paper can be used to reduce both CO₂ emissions and cost of building designed by PBD approach.

Keywords: CO2 emissions, performance based design, optimization, sustainable design

Procedia PDF Downloads 406

Authors: Sohaib Raza, Parvez Mantry

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Frailty is a multi-system impairment associated with stressors such as age, disease, and invasive surgical procedures. This multi-system impairment can lead to increased post-transplant mortality and functional decline. Additionally, the prevalence and/or severity of frailty increases when patient pre-habilitation is unsatisfactory or lacking. We conducted a retrospective study to examine whether the COVID-19 Pandemic, and subsequent lack of patient access to pre-habilitation and physical therapy resources, led to an increase in the prevalence and severity of frailty, sarcopenia, and other comorbidities including diabetes, hypertension, and COPD. Secondarily, we examined the correlation between patient survival rate and liver frailty index as well as muscle wasting/sarcopenia. Data were analyzed in order to correlate variables associated with these parameters. Three hundred sixty-nine liver transplant candidates at Methodist Dallas Medical Center were administered pre-transplant frailty assessments, which consisted of chair stands, grip strength, and position balance time. A frailty score less than 3.2 indicated a robust condition, a score from 3.3 to 4.4 indicated a pre-frail condition, and a score greater than 4.5 indicated a frail condition. Greater than 50 percent of patients were found to have muscle wasting in the COVID-19 period (March 13, 2020 to February 28, 2022), an increase of 16.5 percent from the pre-COVID period (April 1st, 2018 to March 12, 2020). Additionally, sarcopenia was associated with a two-fold increase in patient mortality rate. Furthermore, high liver frailty index scores were associated with increased patient mortality. However, there was no significant difference in liver frailty index or number of comorbidities between patients in the two cohorts. Conclusion: The COVID-19 Pandemic exacerbated sarcopenia-related muscle wasting in liver transplant candidates, and patient survival rate was directly correlated with liver frailty index score and the presence of sarcopenia.

Keywords: frailty, sarcopenia, covid-19, patient mortality, pre-habilitation, liver transplant candidates

Procedia PDF Downloads 117

Authors: Obasanjo Afolabi Bolarinwa

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This study assesses the levels of knowledge of sexually transmitted infections among unmarried youths in Nigeria; examines the pattern of high risk sex among unmarried youths in Nigeria; investigate the socio-demographic factors (age, place of residence, religion, level of education, wealth index and employment status) affecting the practice of high-risk sexual behaviour and ascertain the relationships between knowledge of sexually transmitted infections and practice of high risk sex. The goal of the study is to identify the factors associated with the practice of high risk sex among youth. These were with a view to identifying critical actions needed to reduce high risk sexual behaviour among youths. The study employed secondary data. The data for the study were extracted from the 2013 Nigeria Demographic and Health Survey (NDHS). The 2013 NDHS collected information from 38,948 Women ages 15-49 years and 17,359 men ages 15-49. A total of 7,744 female and 6,027 male respondents were utilized in the study. In order to adjust for the effect of oversampling of the population, the weighting factor provided by Measure DHS was applied. The data were analysed using frequency distribution and logistic regression. The results show that both male (92.2%) and female (93.6%) have accurate knowledge of sexually transmitted infections. The study also revealed that prevalence of high risk sexual behavior is high among Nigerian youths; this is evident as 77.7% (female) and 78.4% (male) are engaging in high risk sexual behavior. The bivariate analysis shows that age of respondent (χ2=294.2; p < 0.05), religion (χ2=136.64; p < 0.05), wealth index (χ2=17.38; p < 0.05), level of education (χ2=34.73; p < 0.05) and employment status (χ2=94.54; p < 0.05) were individual factors significantly associated with high risk sexual behaviour among male while age of respondent (χ2=327.07; p < 0.05), place of residence (χ2=6.71; p < 0.05), religion (χ2=81.04; p < 0.05), wealth index (χ2=7.41; p < 0.05), level of education (χ2=18.12; p < 0.05) and employment status (χ2=51.02; p < 0.05) were individual factors significantly associated with high risk sexual behaviour among female. Furthermore, the study shows that there is a relationship between knowledge of sexually transmitted infections and high risk sex among male (χ2=38.32; p < 0.05) and female (χ2=18.37; p < 0.05). At multivariate level, the study revealed that individual characteristics such as age, religion, place of residence, wealth index, levels of education and employment status were statistically significantly related with high risk sexual behaviour among male and female (p < 0.05). Lastly, the study shows that knowledge of sexually transmitted infection was significantly related to high risk sexual behaviour among youths (p < 0.05). The study concludes that there is a high level of knowledge of sexually transmitted infections among unmarried youths in Nigeria. The practice of high risk sex is high among unmarried youths but higher among male youths. The prevalence of high risk sexual activity is higher for males when they are at disadvantage and higher for females when they are at advantage. Socio-demographic factors like age of respondents, religion, wealth index, place of residence, employment status and highest level of education are factors influencing high risk sexual behaviour among youths.

Keywords: high risk sex, wealth index, sexual behaviour, knowledge

Procedia PDF Downloads 254

Authors: Ru-Yin Yang, Chi Wu, Cheng-Yu Tsai, Yin-Tzu Lin, Wen-Te Liu

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Background: Sleep breathing disorder (SDB) is a condition demonstrated by recurrent episodes of the airway obstruction leading to intermittent hypoxia and quality fragmentation during sleep time. However, the procedures for SDB severity examination remain complicated and costly. Objective: The objective of this study is to establish a simplified examination method for SDB by the respiratory impendence pattern sensor combining the signal processing and machine learning model. Methodologies: We records heart rate variability by the electrocardiogram and respiratory pattern by impendence. After the polysomnography (PSG) been done with the diagnosis of SDB by the apnea and hypopnea index (AHI), we calculate the episodes with the absence of flow and arousal index (AI) from device record. Subjects were divided into training and testing groups. Neuron network was used to establish a prediction model to classify the severity of the SDB by the AI, episodes, and body profiles. The performance was evaluated by classification in the testing group compared with PSG. Results: In this study, we enrolled 66 subjects (Male/Female: 37/29; Age:49.9±13.2) with the diagnosis of SDB in a sleep center in Taipei city, Taiwan, from 2015 to 2016. The accuracy from the confusion matrix on the test group by NN is 71.94 %. Conclusion: Based on the models, we established a prediction model for SDB by means of the wearable sensor. With more cases incoming and training, this system may be used to rapidly and automatically screen the risk of SDB in the future.

Keywords: sleep breathing disorder, apnea and hypopnea index, body parameters, neuron network

Procedia PDF Downloads 150

Authors: Maziyar Nouraee

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Electronic markets in recent decades contribute remarkably in business transactions. Many organizations consider traditional ways of trade non-economical and therefore they do trade only through electronic markets. There are different categorizations of electronic markets functions. In one classification, functions of electronic markets are categorized into classes as information, transactions, and value added. In the present paper, effects of the three classes on the two major elements of the supply chain management are measured. The two elements are decrease in the product unit cost and reduction in response time to the customer. The results of the current research show that among nine minor elements related to the three classes of electronic markets functions, six factors and three factors influence on reduction of the product unit cost and reduction of response time to the customer, respectively.

Keywords: electronic commerce, electronic market, B2B trade, supply chain management

Procedia PDF Downloads 392

Authors: A.L. Tamm, N. Šott, J. Jürimäe, E. Lätt, A. Orav, Ü. Parm

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Coffee is one of the most frequently consumed beverages in the world but still its effects on human organism are not completely understood. Coffee has also been used as a method for weight loss, but its effectiveness has not been proved. There is also not similar comprehension in classifying overweight in choosing between body mass index (BMI) and fat percentage (fat%). The aim of the study was to determine associations between coffee consumption and body composition. Secondly, to detect which measure (BMI or fat%) is more accurate to use describing overweight. Altogether 103 persons enrolled the study and divided into three groups: coffee non-consumers (n=39), average coffee drinkers, who consumed 1 to 4 cups (1 cup = ca 200ml) of coffee per day (n=40) and excessive coffee consumers, who drank at least five cups of coffee per day (n=24). Body mass (medical electronic scale, A&D Instruments, Abingdon, UK) and height (Martin metal anthropometer to the nearest 0.1 cm) were measured and BMI calculated (kg/m2). Participants´ body composition was detected with dual energy X-ray absorptiometry (DXA, Hologic) and general data (history of chronic diseases included) and information about coffee consumption, and physical activity level was collected with questionnaires. Results of the study showed that excessive coffee consumption was associated with increased fat-free mass. It could be foremost due to greater physical activity level in school time or greater (not significant) male proportion in excessive coffee consumers group. For estimating the overweight the fat% in comparison to BMI recommended, as it gives more accurate results evaluating chronical disease risks. In conclusion coffee consumption probably does not affect body composition and for estimating the body composition fat% seems to be more accurate compared with BMI.

Keywords: body composition, body fat percentage, body mass index, coffee consumption

Procedia PDF Downloads 420

Authors: Jyun-Huei Huang, Ting-I Lee

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Urban heat island effect is derived from the reduction of vegetative cover by urban development. Because plants can improve air quality and microclimate, green walls have been applied as a sustainable design approach to cool building temperature. By using plants to green vertical surfaces, they decrease room temperature and, as a result, decrease the energy use for air conditioning. Based on their structures, green walls can be divided into two categories, green façades and living walls. A green façade uses the climbing ability of a plant itself, while a living wall assembles planter modules. The latter one is widely adopted in public space, as it is time-effective and less limited. Although a living wall saves energy spent on cooling, it is not necessarily cost-effective from the perspective of a lifecycle analysis. The Italian study shows that the overall benefit of a living wall is only greater than its costs after 47 years of its establishment. In Taiwan, urban greening policies encourage establishment of green walls by referring to their benefits of energy saving while neglecting their low performance on cost-effectiveness. Thus, this research aims at understanding the perception of appliers and consumers on the cost-effectiveness of their living wall products from the lifecycle viewpoint. It adopts semi-structured interviews and field observations on the maintenance of the products. By comparing the two results, it generates insights for sustainable urban greening policies. The preliminary finding shows that stakeholders do not have a holistic sense of lifecycle or cost-effectiveness. Most importantly, a living wall well maintained is often with high input due to the availability of its maintenance budget, and thus less sustainable. In conclusion, without a comprehensive sense of cost-effectiveness throughout a product’s lifecycle, it is very difficult for suppliers and consumers to maintain a living wall system while achieve sustainability.

Keywords: case study, maintenance, post-occupancy evaluation, vertical greening

Procedia PDF Downloads 265

Authors: Hemalatha Ganapathyswamy, Thirukkumar Subramani

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Celiac disease is an autoimmune response to dietary wheat gluten. Gluten is the main structure forming protein in bread and hence developing gluten-free bread is a technological challenge. The study aims at using nonwheat flours like barnyard millet and lentil flour to replace wheat in bread formulations. Other characteristics of these grains, such as high protein, soluble fiber, mineral content and bioactive components make them attractive alternatives to traditional gluten-free ingredients in the production of high protein, gluten-free bread. The composite flour formulations for the development of gluten-free bread were optimized using lentil flour (50 to 70 g), barnyard millet flour (0 to 30 g) and corn flour (0 to 30 g) by means of response surface methodology with various independent variables for physical, sensorial and nutritional characteristics. The optimized composite flour which had a desirability value of 0.517, included lentil flour –62.94 g, barnyard millet flour– 24.34 g and corn flour– 12.72 g with overall acceptability score 8.00/9.00. The optimized gluten-free bread formulation had high protein (14.99g/100g) and fiber (1.95g/100g) content. The glycemic index of the gluten-free bread was 54.58 rendering it as low glycemic which enhances the functional benefit of the gluten-free bread. Since the standardised gluten-free bread from barnyard millet and lentil flour are high protein, and gluten-free with low glycemic index, the product would serve as an ideal therapeutic food in the management of both celiac disease and diabetes mellitus with better nutritional value.

Keywords: gluten free bread, lentil, low glycemic index, response surface methodology

Procedia PDF Downloads 188

Authors: S. Zenia, A. Menasseria, A. E. Kheidous, F. Lariouna, A. Smai, H. Saadi, F. Haddadj, A. Milla, F. Marniche

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The objective of this study was to estimate the correlation ship between different pheasant external egg quality traits. A total of 938 eggs were collected. Egg weight (g), egg length (mm), egg width (mm), volume (cm3), shape index egg, surface area and water loss were measured. The overall mean values obtained for the different variables are respectively 29.2 ± 2,24, 43.01 ± 1,84, 34.05 ± 1,44, 25.63 ± 2.88 cm3, 79.00 ± 3%, 68% and 13%. Concerning studied regressions, it was considered only the most important regressions. Those that show significant links between the different parameters studied. The ANOVA procedure was applied to estimate correlations for the examined traits. The weights of the eggs being observed before incubation and before hatching are linearly correlated with a positive correlation coefficient of order 0.75. Egg length and the weight before incubation had a good and positive correlation with a coefficient r = 0.6. However, density had high and negative correlations with egg height r = -0.78. Shape index had a good linear and negative r= - 0.71 correlation with water loss.

Keywords: correlation, egg, morphometry of eggs, analysis of variance

Procedia PDF Downloads 450

Authors: Parul Suraia, Harshit Sosan Lakra

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Indigenous communities represent some of the most marginalized populations globally, with India labeled as tribals, experiencing particularly pronounced marginalization and a concerning decline in their numbers. These communities often inhabit geographically challenging regions characterized by low population densities, posing significant challenges to providing essential infrastructure services. Jharkhand, a Schedule 5 state, is infamous for its low-level health status due to disparities in access to health care. The primary objective of this study is to investigate the spatial inequalities in healthcare accessibility among tribal populations within the state and pinpoint critical areas requiring immediate attention. Health indicators were selected based on the tribal perspective and association of Sustainable Goal 3 (Good Health and Wellbeing) with other SDGs. Focused group discussions in which tribal people and tribal experts were done in order to finalize the indicators. Employing Principal Component Analysis, two essential indices were constructed: the Tribal Health Index (THI) and the Tribal Health Intervention Index (THII). Index values were calculated based on the district-wise secondary data for Jharkhand. The bivariate spatial association technique, Moran’s I was used to assess the spatial pattern of the variables to determine if there is any clustering (positive spatial autocorrelation) or dispersion (negative spatial autocorrelation) of values across Jharkhand. The results helped in facilitating targeting policy interventions in deprived areas of Jharkhand.

Keywords: tribal health, health spatial disparities, health status, Jharkhand

Procedia PDF Downloads 96

Authors: Soheila Sadeghi

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Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.

Keywords: resource allocation, machine learning, optimization, data-driven decision-making, project management

Procedia PDF Downloads 38

Authors: Ali Kassem, Yaser Kamal, Mohamed Abdel Wahab, Mohamed Hussen

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Introduction: Atherosclerosis is one of the leading causes of death all over the world. Recently, there is an increasing interest in Carotid Intima-Medial Thickness (CIMT) and Ankle Brachial Index (ABI) as non-invasive tools for identifying subclinical atherosclerosis. We aim to examine the role of CIMT and ABI as predictors of the severity of angiographically documented coronary artery disease (CAD). Methods: A cross-sectional study conducted on 60 patients who were investigated by coronary angiography at Sohag University Hospital, Egypt. CIMT: After the carotid arteries were located by transverse scans, the probe was rotated 90 ° to obtain and record longitudinal images of bilateral carotid arteries ABI: Each patient was evaluated in the supine position after resting for 5 min. ABI was measured in each leg using a Doppler Ultrasound while the patient remained in the same position. The lowest ABI obtained for either leg was taken as the ABI measurement for the patient. Results: Patients with carotid mean IMT ≥ 0.9 mm had significantly more severe coronary artery disease than patients without thickening (mean IMT > 0.9 mm). Similarly, patients with low ABI (< 0.9) had significantly more severe coronary artery disease than patients with ABI ≥ 0.9. When the patients were divided into 4 groups (group A, n = 15, mean IMT < 0.9 mm, ABI ≥ 0.9; group B, n = 25, mean IMT < 0.9 mm, low ABI; group C, n = 5, mean IMT ≥ 0.9 mm, ABI ≥ 0.9; group D, n = 19, mean IMT ≤ 0.9 mm, low ABI), the presence of significant coronary stenosis (> 50%) of the groups were significantly different (group A, n = 5: (33.3%); group B, n = 11: (52.4%); group C, n = 4: (60%); group D, n=15, (78.9%), P = 0.001). Conclusion: CIMT and ABI provide useful information on the severity of CAD. Early and aggressive intervention should be considered in patients with CAD and abnormalities in one or both of these non-invasive modalities.

Keywords: ankle brachial index, carotid intima media thickness, coronary artery disease, predictors of severity

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Authors: Hamed Saremi, Shahla Saremi

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In this study, control and management of construction projects is evaluated through developing a dynamic model in which some means are used in order to evaluating planning assumptions and reviewing the effectiveness of some project control policies based on previous researches about time, cost, project schedule pressure management, source management, project control, adding elements and sub-systems from cost management such as estimating consumption budget from budget due to costs, budget shortage effects and etc. using sensitivity analysis, researcher has evaluated introduced model that during model simulation by VENSIM software and assuming optimistic times and adding information about doing job and changes rate and project is forecasted with 373 days (2 days sooner than forecasted) and final profit $ 1,960,670 (23% amount of contract) assuming 15% inflation rate in year and costs rate accordance with planned amounts and other input information and final profit.

Keywords: dynamic planning, cost, time, performance, project management

Procedia PDF Downloads 478

Authors: Grace Rachid, Mutasem El Fadel, Mahmoud Al Hindi, Ibrahim Jamali, Daniel Abdel Nour

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This study examines the feasibility of indirect solar desalination in oil producing countries in the Middle East and North Africa (MENA) region. It relies on value engineering (VE) and cost-benefit with sensitivity analyses to identify optimal coupling configurations of desalination and solar energy technologies. A comparative return on investment was assessed as a function of water costs for varied plant capacities (25,000 to 75,000 m3/day), project lifetimes (15 to 25 years), and discount rates (5 to 15%) taking into consideration water and energy subsidies, land cost as well as environmental externalities in the form of carbon credit related to greenhouse gas (GHG) emissions reduction. The results showed reverse osmosis (RO) coupled with photovoltaic technologies (PVs) as the most promising configuration, robust across different prices for Brent oil, discount rates, as well as different project lifetimes. Environmental externalities and subsidies analysis revealed that a 16% reduction in existing subsidy on water tariffs would ensure economic viability. Additionally, while land costs affect investment attractiveness, the viability of RO coupled with PV remains possible for a land purchase cost < $ 80/m2 or a lease rate < $1/m2/yr. Beyond those rates, further subsidy lifting is required.

Keywords: solar energy, desalination, value engineering, CBA, carbon credit, subsidies

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Authors: Yike Lamu, Jieyu Tang, Jialin Wu, Jianyun Huang

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With the development of economy and science and technology, the urban heat island effect becomes more and more serious. Taking Beijing city as an example, this paper divides the value of each influence index of heat island intensity and establishes a mathematical model – neural network system based on the fuzzy comprehensive evaluation index of heat island effect. After data preprocessing, the algorithm of weight of each factor affecting heat island effect is generated, and the data of sex indexes affecting heat island intensity of Shenyang City and Shanghai City, Beijing, and Hangzhou City are input, and the result is automatically output by the neural network system. It is of practical significance to show the intensity of heat island effect by visual method, which is simple, intuitive and can be dynamically monitored.

Keywords: heat island effect, neural network, comprehensive evaluation, visualization

Procedia PDF Downloads 133

Authors: S. Jayasinghe, R. B. N. Dissanayake

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Optimization modelling together with the Network models and Linear Programming techniques is a powerful tool in problem solving and decision making in real world applications. This study developed a mathematical model to optimize the net profit by minimizing the transportation cost. This model focuses the transportation among decentralized production plants to a centralized distribution centre and then the distribution among island wide agencies considering the customer satisfaction as a requirement. This company produces basically 9 types of food items with 82 different varieties and 4 types of non-food items with 34 different varieties. Among 6 production plants, 4 were located near the city of Mawanella and the other 2 were located in Galewala and Anuradhapura cities which are 80 km and 150 km away from Mawanella respectively. The warehouse located in the Mawanella was the main production plant and also the only distribution plant. This plant distributes manufactured products to 39 agencies island-wide. The average values and average amount of the goods for 6 consecutive months from May 2013 to October 2013 were collected and then average demand values were calculated. The following constraints are used as the necessary requirement to satisfy the optimum condition of the model; there was one source, 39 destinations and supply and demand for all the agencies are equal. Using transport cost for a kilometer, total transport cost was calculated. Then the model was formulated using distance and flow of the distribution. Network optimization and linear programming techniques were used to originate the model while excel solver is used in solving. Results showed that company requires total transport cost of Rs. 146, 943, 034.50 to fulfil the customers’ requirement for a month. This is very much less when compared with data without using the model. Model also proved that company can reduce their transportation cost by 6% when distributing to island-wide customers. Company generally satisfies their customers’ requirements by 85%. This satisfaction can be increased up to 97% by using this model. Therefore this model can be used by other similar companies in order to reduce the transportation cost.

Keywords: mathematical model, network optimization, linear programming

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Authors: Osamah A. Alsayegh

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This paper contributes to the literature by updating the analysis of the impact of the recent oil prices fall on the renewable energy (RE) industry and deployment. The research analysis uses the Renewable Energy Industrial Index (RENIXX), which tracks the world’s 30 largest publicly traded companies and oil prices daily data from January 2003 to March 2016. RENIXX represents RE industries developing solar, wind, geothermal, bioenergy, hydropower and fuel cells technologies. This paper tests the hypothesis that claims high oil prices encourage the substitution of alternate energy sources for conventional energy sources. Furthermore, it discusses RENIXX performance behavior with respect to the governments’ policies factor that investors should take into account. Moreover, the paper proposes a theoretical model that relates RE industry progress with oil prices and policies through the fuzzy logic system.

Keywords: Fuzzy logic, investment, policy, stock exchange index

Procedia PDF Downloads 238

Authors: Dina K. Badawy, Dina M. Ibrahim, Alsayed A. Sallam

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Distributed database is a collection of logically related databases that cooperate in a transparent manner. Query processing uses a communication network for transmitting data between sites. It refers to one of the challenges in the database world. The development of sophisticated query optimization technology is the reason for the commercial success of database systems, which complexity and cost increase with increasing number of relations in the query. Mariposa, query trading and query trading with processing task-trading strategies developed for autonomous distributed database systems, but they cause high optimization cost because of involvement of all nodes in generating an optimal plan. In this paper, we proposed a modification on the autonomous strategy K-QTPT that make the seller’s nodes with the lowest cost have gradually high priorities to reduce the optimization time. We implement our proposed strategy and present the results and analysis based on those results.

Keywords: autonomous strategies, distributed database systems, high priority, query optimization

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Authors: Yehya Abdellatif, Iyad M. Muslih, Azzah Alkhalailah, Abdallah Muslih

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Hybrid Optimization Model for Electric Renewable (HOMER) software was utilized to find the optimum design of a hybrid off-Grid system, by choosing the optimal solution depending on the cost analysis of energy based on different capacity shortage percentages. A complete study for the site conditions and load profile was done to optimize the design and implementation of a hybrid off-grid power station. In addition, the solution takes into consecration the ambient temperature effect on the efficiency of the power generation and the economical aspects of selection depending on real market price. From the analysis of the HOMER model results, the optimum hybrid power station was suggested, based on wind speed, and solar conditions. The optimization function objective is to minimize the Net Price Cost (NPC) and the Cost of Energy (COE) with zero and 10 percentage of capacity shortage.

Keywords: energy modeling, HOMER, off-grid system, optimization

Procedia PDF Downloads 563

Authors: Deden Misbahudin Muayyad, Lavlimatria Esya

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Up to the month of June 2015, Indonesia has 12 Islamic Commercial Banks, 22 Islamic Business Unit, 327 offices in 33 provinces. The initial purpose of the establishment of Islamic financial institutions is to achieve and the welfare of the people in this world and in the hereafter. To realize these goals, the Islamic financial institutions in every kind of aspect of product development and in terms of operations should be based on maqashid sharia, namely keeping the faith, keep the soul, keep the sense, maintain the property, keeping the offspring. To see whether Islamic banking grounded in maqasid sharia, the Islamic banking performance measurements based on the principles of maqasid sharia. Banking performance measurement is not only focusing on profit and other financial measures, but put other values of banks reflects the size of the benefit of non-profit in accordance with the bank's objectives. The measurement using the measurement of financial performance called maqasid sharia index. Maqasid syariah index is a model of Islamic banking performance measurement in accordance with the objectives and characteristics of Islamic banking. Maqasid syariah index was developed based on three main factors, namely the education of individuals, the creation of justice, the achievement of well-being, where the three factors were in accordance with the common goal of maqasid sharia is achieving prosperity and avoid evil. Maqasid syariah index shows that maqasid sharia approach can be a strategic alternative approach to describe how good the performance of the banking system and it can be implemented in the comprehensive policy strategy. This study uses a model of performance measurement framework based on maqasid syariah, in addition to financial performance measures that already exist. Methods to develop the idea of a performance measurement framework of Islamic banking by maqasid sharia is the Sekaran method. Operationally, the methods have now able to describe the elements that will be measured by this study. This is done by observing the behavior of the dimensions illustrated through a concept that has been set. These dimensions translate into derivative elements that can be observed and more scalable, so it can establish measurement indices. This research is descriptive quantitative. Techniques are being made to collect data in this paper is by using purposive sampling method, with 12 Islamic Commercial Banks that qualify as research samples. The financial data taken at 12 banks was sourced from the annual financial statements the period 2008 to 2012 with consideration of the database and ease of access to data. The ratio measured in this study only 7 ratio used in determining the performance of Islamic banking, namely: four ratio refers to the sharia objectives related to education. three ratio while again referring to sharia objectives related to the achievement of welfare. While other ratios associated with justice can not be used in this study because of the limited data used. Total overall calculation of performance indicators and performance ratios on each goal for each bank describes the maqasid syariah index.

Keywords: Islamic banking, Maslahah, maqashid syariah, maqashid syariah index

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Authors: Nokwethaba Makhanya, Babatunde J. Abiodun, Piotr Wolski

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Climate change possibly intensifies hydrological droughts and reduces water availability in river basins. Despite this, most research on climate change effects in southern Africa has focused exclusively on meteorological droughts. This thesis projects the potential impact of climate change on the future characteristics of hydrological droughts in the Limpopo River Basin (LRB). The study uses regional climate model (RCM) measurements (from the Coordinated Regional Climate Downscaling Experiment, CORDEX) and a combination of hydrological simulations (using the Soil and Water Assessment Tool Plus model, SWAT+) to predict the impacts at four global warming levels (GWLs: 1.5℃, 2.0℃, 2.5℃, and 3.0℃) under the RCP8.5 future climate scenario. The SWAT+ model was calibrated and validated with a streamflow dataset observed over the basin, and the sensitivity of model parameters was investigated. The performance of the SWAT+LRB model was verified using the Nash-Sutcliffe efficiency (NSE), Percent Bias (PBIAS), Root Mean Square Error (RMSE), and coefficient of determination (R²). The Standardized Precipitation Evapotranspiration Index (SPEI) and the Standardized Precipitation Index (SPI) have been used to detect meteorological droughts. The Soil Water Index (SSI) has been used to define agricultural drought, while the Water Yield Drought Index (WYLDI), the Surface Run-off Index (SRI), and the Streamflow Index (SFI) have been used to characterise hydrological drought. The performance of the SWAT+ model simulations over LRB is sensitive to the parameters CN2 (initial SCS runoff curve number for moisture condition II) and ESCO (soil evaporation compensation factor). The best simulation generally performed better during the calibration period than the validation period. In calibration and validation periods, NSE is ≤ 0.8, while PBIAS is ≥ ﹣80.3%, RMSE ≥ 11.2 m³/s, and R² ≤ 0.9. The simulations project a future increase in temperature and potential evapotranspiration over the basin, but they do not project a significant future trend in precipitation and hydrological variables. However, the spatial distribution of precipitation reveals a projected increase in precipitation in the southern part of the basin and a decline in the northern part of the basin, with the region of reduced precipitation projected to increase with GWLs. A decrease in all hydrological variables is projected over most parts of the basin, especially over the eastern part of the basin. The simulations predict meteorological droughts (i.e., SPEI and SPI), agricultural droughts (i.e., SSI), and hydrological droughts (i.e., WYLDI, SRI) would become more intense and severe across the basin. SPEI-drought has a greater magnitude of increase than SPI-drought, and agricultural and hydrological droughts have a magnitude of increase between the two. As a result, this research suggests that future hydrological droughts over the LRB could be more severe than the SPI-drought projection predicts but less severe than the SPEI-drought projection. This research can be used to mitigate the effects of potential climate change on basin hydrological drought.

Keywords: climate change, CORDEX, drought, hydrological modelling, Limpopo River Basin

Procedia PDF Downloads 128

Authors: Xu Wang

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This research builds linear regressions of U.S. macroeconomic condition and volatility measures in the investment grade and high yield Credit Default Swap index spreads using monthly data from March 2009 to July 2016, to study the relationship between different dimensions of macroeconomy and overall credit risk quality. The most significant contribution of this research is systematically examining individual and joint effects of macroeconomic condition and volatility on CDX spreads by including macroeconomic time series that captures different dimensions of the U.S. economy. The industrial production index growth, non-farm payroll growth, consumer price index growth, 3-month treasury rate and consumer sentiment are introduced to capture the condition of real economic activity, employment, inflation, monetary policy and risk aversion respectively. The conditional variance of the macroeconomic series is constructed using ARMA-GARCH model and is used to measure macroeconomic volatility. The linear regression model is conducted to capture relationships between monthly average CDX spreads and macroeconomic variables. The Newey–West estimator is used to control for autocorrelation and heteroskedasticity in error terms. Furthermore, the sensitivity factor analysis and standardized coefficients analysis are conducted to compare the sensitivity of CDX spreads to different macroeconomic variables and to compare relative effects of macroeconomic condition versus macroeconomic uncertainty respectively. This research shows that macroeconomic condition can have a negative effect on CDX spread while macroeconomic volatility has a positive effect on determining CDX spread. Macroeconomic condition and volatility variables can jointly explain more than 70% of the whole variation of the CDX spread. In addition, sensitivity factor analysis shows that the CDX spread is the most sensitive to Consumer Sentiment index. Finally, the standardized coefficients analysis shows that both macroeconomic condition and volatility variables are important in determining CDX spread but macroeconomic condition category of variables have more relative importance in determining CDX spread than macroeconomic volatility category of variables. This research shows that the CDX spread can reflect the individual and joint effects of macroeconomic condition and volatility, which suggests that individual investors or government should carefully regard CDX spread as a measure of overall credit risk because the CDX spread is influenced by macroeconomy. In addition, the significance of macroeconomic condition and volatility variables, such as Non-farm Payroll growth rate and Industrial Production Index growth volatility suggests that the government, should pay more attention to the overall credit quality in the market when macroecnomy is low or volatile.

Keywords: autoregressive moving average model, credit spread puzzle, credit default swap spread, generalized autoregressive conditional heteroskedasticity model, macroeconomic conditions, macroeconomic uncertainty

Procedia PDF Downloads 166

Authors: Sylvanus N. Wosu

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

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

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Authors: Barbara Erjauz, Juliane Eichhorn

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Background and Purpose: The world´s population is rapidly aging, wherefore the World Health Organization (WHO) is dealing with concepts of Age-Friendly-Communities and criteria to define them. Also in Germany, we can find an aging population and a large amount of seniors is living in rural areas. Those regions are defined by unique social and environmental characteristics, which can enhance or decrease age-friendliness. To identify and work with these characteristics, we are in need of appropriate assessment instruments. To the author’s best knowledge until now, no instrument could be identified as suitable and scientifically proven for the German speaking area. The aim of the study was to identify an assessment instrument to measure the age-friendliness of rural communities and its psychometric testing regarding the content validity. Methods: A literature search was carried out to identify instruments related to concepts of Age-Friendly-Communities. According to the German situation, an instrument was chosen and modified based on a Delphi-study. In this context, the content validity was investigated by calculating the Content Validity Index (CVI). Results: An instrument consisting of 86 items based on WHO indicators and the German situation in rural areas was created. 43 items (50%) had a Content Validity Index for Items (I-CVI) of 1,00, 37 items (43%) had an I-CVI of >0,78 and > 1.00, and 6 items had an I-CVI of >0,78. The value of the Content Validity Index for Scales, averaging calculation method (S-CVI/Ave) for the entire scale was 0,91. Conclusions: The results indicate a good content validity and it can be concluded that the created instrument represents the phenomenon of age-friendliness in rural areas. Nevertheless, further psychometric testing related to reliability, validity and responsiveness is recommended.

Keywords: assessment, age-friendly, rural, psychometric testing

Procedia PDF Downloads 241