Search results for: advanced statistical analysis

Authors: Ndidi F. Amulu, Patrick E. Amulu, Gordian O. Mbah, Callistus N. Ude

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Comparative analysis of the properties of melon seed, coconut fruit and their oil yield were evaluated in this work using standard analytical technique AOAC. The results of the analysis carried out revealed that the moisture contents of the samples studied are 11.15% (melon) and 7.59% (coconut). The crude lipid content are 46.10% (melon) and 55.15% (coconut).The treatment combinations used (leaching time, leaching temperature and solute: solvent ratio) showed significant difference (p < 0.05) in yield between the samples, with melon oil seed flour having a higher percentage range of oil yield (41.30 – 52.90%) and coconut (36.25 – 49.83%). The physical characterization of the extracted oil was also carried out. The values gotten for refractive index are 1.487 (melon seed oil) and 1.361 (coconut oil) and viscosities are 0.008 (melon seed oil) and 0.002 (coconut oil). The chemical analysis of the extracted oils shows acid value of 1.00mg NaOH/g oil (melon oil), 10.050mg NaOH/g oil (coconut oil) and saponification value of 187.00mg/KOH (melon oil) and 183.26mg/KOH (coconut oil). The iodine value of the melon oil gave 75.00mg I2/g and 81.00mg I2/g for coconut oil. A standard statistical package Minitab version 16.0 was used in the regression analysis and analysis of variance (ANOVA). The statistical software mentioned above was also used to optimize the leaching process. Both samples gave high oil yield at the same optimal conditions. The optimal conditions to obtain highest oil yield ≥ 52% (melon seed) and ≥ 48% (coconut seed) are solute - solvent ratio of 40g/ml, leaching time of 2hours and leaching temperature of 50oC. The two samples studied have potential of yielding oil with melon seed giving the higher yield.

Keywords: Coconut, Melon, Optimization, Processing

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Authors: Szu-Mei Hsiao

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Many nurses have concerns about the difficulties of providing spiritual care for ethnic-Chinese patients and family members within their cultural context. This is due to a lack of knowledge and training. Most family caregivers are female. There has been little research exploring the potential impact of Chinese cultural values on the spiritual distress of couple dyadic participants in Taiwan. This study explores the spiritual issues of Taiwanese women coping with their husband’s advanced cancer during palliative care to death. Qualitative multiple case studies were used. Data was collected through participant observation and in-depth face-to-face interviews. Transcribed interview data was analyzed by using qualitative content analysis. Three couples were recruited from a community-based rural hospital in Taiwan where the husbands were hospitalized in a medical ward. Four spiritual distress themes emerged from the analysis: (1) A personal conflict in trying to come to terms with love and forgiveness; the inability to forgive their husband’s mistakes; and, lack of their family’s love and support. (2) A feeling of hopelessness due to advanced cancer, such as a feeling of disappointment in their destiny and karma, including expressing doubt on survival. (3) A feeling of uncertainty in facing death peacefully, such as fear of facing the unknown world; and, (4) A feeling of doubt causing them to question the meaning and values in their lives. This research has shown that caregivers needed family support, friends, social welfare, and the help of their religion to meet their spiritual needs in coping within the final stages of life and death. The findings of this study could assist health professionals to detect the spiritual distress of ethnic-Chinese patients and caregivers in the context of their cultural or religious background as early as possible.

Keywords: advanced cancer, Buddhism, Confucianism, Taoism, qualitative research, spiritual distress

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Authors: Komal Rathore, Aydin Sunol, Gita Iranipour, Luke Mulford

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Advanced wastewater treatment plants have complex biological kinetics, time variant influent flow rates and long processing times. Due to these factors, the modeling and operational control of advanced wastewater treatment plants become complicated. However, development of a robust model for advanced wastewater treatment plants has become necessary in order to increase the efficiency of the plants, reduce energy costs and meet the discharge limits set by the government. A dynamic model was designed using the Envirosim (Canada) platform software called BioWin for several wastewater treatment plants in Hillsborough County, Florida. Proper control strategies for various parameters such as mixed liquor suspended solids, recycle activated sludge and waste activated sludge were developed for models to match the plant performance. The models were tuned using both the influent and effluent data from the plant and their laboratories. The plant SCADA was used to predict the influent wastewater rates and concentration profiles as a function of time. The kinetic parameters were tuned based on sensitivity analysis and trial and error methods. The dynamic models were validated by using experimental data for influent and effluent parameters. The dissolved oxygen measurements were taken to validate the model by coupling them with Computational Fluid Dynamics (CFD) models. The Biowin models were able to exactly mimic the plant performance and predict effluent behavior for extended periods. The models are useful for plant engineers and operators as they can take decisions beforehand by predicting the plant performance with the use of BioWin models. One of the important findings from the model was the effects of recycle and wastage ratios on the mixed liquor suspended solids. The model was also useful in determining the significant kinetic parameters for biological wastewater treatment systems.

Keywords: BioWin, kinetic modeling, flowsheet simulation, dynamic modeling

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Authors: Alireza Ansariyar, Safieh Laaly

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Over the last decades, the vehicle industry has shown increased interest in integrating autonomous, connected, and electrical technologies in vehicle design with the primary hope of improving mobility and road safety while reducing transportation’s environmental impact. Using the State of Maryland (M.D.) in the United States as a pilot study, this research investigates CAVs’ fuel consumption and air pollutants (C.O., PM, and NOx) and utilizes meaningful linear regression models to predict CAV’s environmental effects. Maryland transportation network was simulated in VISUM software, and data on a set of variables were collected through a comprehensive survey. The number of pollutants and fuel consumption were obtained for the time interval 2010 to 2021 from the macro simulation. Eventually, four linear regression models were proposed to predict the amount of C.O., NOx, PM pollutants, and fuel consumption in the future. The results highlighted that CAVs’ pollutants and fuel consumption have a significant correlation with the income, age, and race of the CAV customers. Furthermore, the reliability of four statistical models was compared with the reliability of macro simulation model outputs in the year 2030. The error of three pollutants and fuel consumption was obtained at less than 9% by statistical models in SPSS. This study is expected to assist researchers and policymakers with planning decisions to reduce CAV environmental impacts in M.D.

Keywords: connected and autonomous vehicles, statistical model, environmental effects, pollutants and fuel consumption, VISUM, linear regression models

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Authors: Ndidi F. Amulu, Godian O. Mbah, Maxwel I. Onyiah, Callistus N. Ude

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Analysis of the properties of coconut (Cocos nucifera) and its oil was evaluated in this work using standard analytical techniques. The analyses carried out include proximate composition of the fruit, extraction of oil from the fruit using different process parameters and physicochemical analysis of the extracted oil. The results showed the percentage (%) moisture, crude lipid, crude protein, ash, and carbohydrate content of the coconut as 7.59, 55.15, 5.65, 7.35, and 19.51 respectively. The oil from the coconut fruit was odourless and yellowish liquid at room temperature (30oC). The treatment combinations used (leaching time, leaching temperature and solute: solvent ratio) showed significant differences (P˂0.05) in the yield of oil from coconut flour. The oil yield ranged between 36.25%-49.83%. Lipid indices of the coconut oil indicated the acid value (AV) as 10.05 Na0H/g of oil, free fatty acid (FFA) as 5.03%, saponification values (SV) as 183.26 mgKOH-1 g of oil, iodine value (IV) as 81.00 I2/g of oil, peroxide value (PV) as 5.00 ml/ g of oil and viscosity (V) as 0.002. A standard statistical package minitab version 16.0 program was used in the regression analysis and analysis of variance (ANOVA). The statistical software mentioned above was also used to generate various plots such as single effect plot, interactions effect plot and contour plot. The response or yield of oil from the coconut flour was used to develop a mathematical model that correlates the yield to the process variables studied. The maximum conditions obtained that gave the highest yield of coconut oil were leaching time of 2 hrs, leaching temperature of 50 oC and solute/solvent ratio of 0.05 g/ml.

Keywords: coconut, oil-extraction, optimization, physicochemical, proximate

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Authors: Andriati Nadhilah Widyarini, Ezra Margareth

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Introduction: Rhegmatogenous retinal detachment is a condition where there’s a break in the retina, which allows the vitreous to directly enter the subretinal space. Proliferative vitreoretinopathy (PVR) may develop due to this condition and can result in a new break, which could cause traction on the previously detached retina. Various methods of therapy can be done to treat this complication. Case: This case series involved 2 eyes of 2 patients who had total retinal detachment with advanced PVR. Pars plana vitrectomy was performed, and a 360-degree retinectomy procedure with perfluorocarbon liquid usage was done. This was followed by endo laser retinopexy to surround the border of retinectomy. 5000 cs silicone oil was used in 1 eye, whereas 12% of perfluoropropane gas was used in the other eye as a tamponade. These procedures were performed with meticulous attention to prevent any fluid from entering the subretinal space. Postoperative examination showed attachment of the retina and improvement of the patient’s visual acuity. Both eyes’ intraocular pressure was in the normal range. One eye developed retinal displacement, but no other complications occurred. Discussion: Rhegmatogenous retinal detachment with advanced PVR is a complex situation for vitreoretinal surgeons. PVR is characterized by the growth and migration of preretinal or subretinal membranes. PVR is the most common cause of retinal reattachment failure. A 360-degree retinectomy is an alternative surgical method to overcome this condition. Objectives of this procedure are releasing retinal traction caused by PVR, reducing the recurrence rate of PVR, and reattaching the retina to the pigment epithelial surface. Conclusion: 360-degree retinectomy provides satisfactory retinal reattachment and visual outcome improvement in rhegmatogenous retinal detachment with advanced PVR.

Keywords: RRD, retinectomy, pars plana, advanced PVR

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Authors: Surya R. Niraula, Devendra B Chhetry, Girish K. Singh, S. Nagesh, Frederick A. Connell

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Background: Although random sampling is generally considered to be the gold standard for population-based research, the majority of drug abuse research is based on non-random sampling despite the well-known limitations of this kind of sampling. Method: We compared the statistical properties of two surveys of drug abuse in the same community: one using snowball sampling of drug users who then identified “friend controls” and the other using a random sample of non-drug users (controls) who then identified “friend cases.” Models to predict drug abuse based on risk factors were developed for each data set using conditional logistic regression. We compared the precision of each model using bootstrapping method and the predictive properties of each model using receiver operating characteristics (ROC) curves. Results: Analysis of 100 random bootstrap samples drawn from the snowball-sample data set showed a wide variation in the standard errors of the beta coefficients of the predictive model, none of which achieved statistical significance. One the other hand, bootstrap analysis of the random-sample data set showed less variation, and did not change the significance of the predictors at the 5% level when compared to the non-bootstrap analysis. Comparison of the area under the ROC curves using the model derived from the random-sample data set was similar when fitted to either data set (0.93, for random-sample data vs. 0.91 for snowball-sample data, p=0.35); however, when the model derived from the snowball-sample data set was fitted to each of the data sets, the areas under the curve were significantly different (0.98 vs. 0.83, p < .001). Conclusion: The proposed method of random sampling of controls appears to be superior from a statistical perspective to snowball sampling and may represent a viable alternative to snowball sampling.

Keywords: drug abuse, matched case-control study, non-probability sampling, probability sampling

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Authors: S. Nikpour, S. Vahidi, H. Haghani

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Introduction: Exercise has mental and physical health benefits for patients with advanced stage cancer who actively receive chemotherapy, yet little is known about patients’ levels of interest in becoming more active or their confidence in increasing their activity level. Methods and materials: A convenience sample of 200 patients with advanced-stage cancer who were receiving chemotherapy completed self-report measures assessing physical activity level, mood, and quality-of-life variables. Qualitative data on patient-perceived benefits of, and barriers to, physical activity also were collected, coded by independent raters, and organized by predominant themes. Results: Current physical activity level, physical activity outcome expectations, and positive mood were significantly associated with self-efficacy. Fatigue was the most frequently listed barrier to physical activity; improved physical strength and health were the most commonly listed benefits. Participants identified benefits related to both general health and cancer-symptom management that were related to exercise. 59.5% of participants reported that they were seriously planning to increase or maintain their physical activity level, and over 40% reported having interest in receiving an intervention to become more active. Conclusion: These results suggested that many advanced-stage cancer patients who receive chemotherapy are interested in maintaining or increasing their physical activity level and in receiving professional support for exercise. In addition, these individuals identified general health and cancer-specific benefits of, and barriers to, physical activity. Future research will investigate how these findings may be incorporated into physical activity interventions for advanced-stage oncology patients receiving medical treatment.

Keywords: physical activity, cancer, self-efficacy

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Authors: Thamir K. Ibrahim, M. M. Rahman, Marwah Noori Mohammed

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This study deals with modeling and performance enhancements of a gas-turbine combined cycle power plant. A clean and safe energy is the greatest challenges to meet the requirements of the green environment. These requirements have given way the long-time governing authority of steam turbine (ST) in the world power generation, and the gas turbine (GT) will replace it. Therefore, it is necessary to predict the characteristics of the GT system and optimize its operating strategy by developing a simulation system. The integrated model and simulation code for exploiting the performance of gas turbine power plant are developed utilizing MATLAB code. The performance code for heavy-duty GT and CCGT power plants are validated with the real power plant of Baiji GT and MARAFIQ CCGT plants the results have been satisfactory. A new technology of correlation was considered for all types of simulation data; whose coefficient of determination (R2) was calculated as 0.9825. Some of the latest launched correlations were checked on the Baiji GT plant and apply error analysis. The GT performance was judged by particular parameters opted from the simulation model and also utilized Adaptive Neuro-Fuzzy System (ANFIS) an advanced new optimization technology. The best thermal efficiency and power output attained were about 56% and 345MW respectively. Thus, the operation conditions and ambient temperature are strongly influenced on the overall performance of the GT. The optimum efficiency and power are found at higher turbine inlet temperatures. It can be comprehended that the developed models are powerful tools for estimating the overall performance of the GT plants.

Keywords: gas turbine, optimization, ANFIS, performance, operating conditions

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Authors: Madhusudan Purohit, Stephen Philip, Bharathkumar Inturi

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In this paper we report the quantitative structure activity relationship of novel bis-triazole derivatives for predicting the activity profile. The full model encompassed a dataset of 46 Bis- triazoles. Tripos Sybyl X 2.0 program was used to conduct CoMSIA QSAR modeling. The Partial Least-Squares (PLS) analysis method was used to conduct statistical analysis and to derive a QSAR model based on the field values of CoMSIA descriptor. The compounds were divided into test and training set. The compounds were evaluated by various CoMSIA parameters to predict the best QSAR model. An optimum numbers of components were first determined separately by cross-validation regression for CoMSIA model, which were then applied in the final analysis. A series of parameters were used for the study and the best fit model was obtained using donor, partition coefficient and steric parameters. The CoMSIA models demonstrated good statistical results with regression coefficient (r2) and the cross-validated coefficient (q2) of 0.575 and 0.830 respectively. The standard error for the predicted model was 0.16322. In the CoMSIA model, the steric descriptors make a marginally larger contribution than the electrostatic descriptors. The finding that the steric descriptor is the largest contributor for the CoMSIA QSAR models is consistent with the observation that more than half of the binding site area is occupied by steric regions.

Keywords: 3D QSAR, CoMSIA, triazoles, novel heterocycles

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Authors: Gaoyang Meng, Philip Harrison

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When manufacturing composite laminates, the fibre directions within the laminate are never perfectly straight and inevitably contain some degree of stochastic in-plane waviness or ‘meandering’. In this work we aim to understand the relationship between the degree of meandering of the fibre paths, and the resulting uncertainty in the laminate’s final mechanical properties. To do this, a numerical tool is developed to automatically generate meandering fibre paths in each of the laminate's 8 plies (using Matlab) and after mapping this information into finite element simulations (using Abaqus), the statistical variability of the tensile mechanical properties of a [45°/90°/-45°/0°]s carbon/epoxy (IM7/8552) laminate is predicted. The stiffness, first ply failure strength and ultimate failure strength are obtained. Results are generated by inputting the degree of variability in the fibre paths and the laminate is then examined in all directions (from 0° to 359° in increments of 1°). The resulting predictions are output as flower (polar) plots for convenient analysis. The average fibre orientation of each ply in a given laminate is determined by the laminate layup code [45°/90°/-45°/0°]s. However, in each case, the plies contain increasingly large amounts of in-plane waviness (quantified by the standard deviation of the fibre direction in each ply across the laminate. Four different amounts of variability in the fibre direction are tested (2°, 4°, 6° and 8°). Results show that both the average tensile stiffness and the average tensile strength decrease, while the standard deviations increase, with an increasing degree of fibre meander. The variability in stiffness is found to be relatively insensitive to the rotation angle, but the variability in strength is sensitive. Specifically, the uncertainty in laminate strength is relatively low at orientations centred around multiples of 45° rotation angle, and relatively high between these rotation angles. To concisely represent all the information contained in the various polar plots, rotation-angle dependent Weibull distribution equations are fitted to the data. The resulting equations can be used to quickly estimate the size of the errors bars for the different mechanical properties, resulting from the amount of fibre directional variability contained within the laminate. A longer term goal is to use these equations to quickly introduce realistic variability at the component level.

Keywords: advanced composite laminates, FE simulation, in-plane waviness, tensile properties, uncertainty quantification

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Authors: M. E. Khiav, D. J. Borah, H. T. S. Santos, V. T. Faria

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For automobile companies, it has become very important to ensure sound quality in manufacturing and assembling in order to prevent occurrence of defects and to reduce the amount of parts replacements to be done in the service centers during the warranty period. Statistical Process Control (SPC) is widely used as the tool to analyze the quality of such processes and plays a significant role in the improvement of the processes by identifying the patterns and the location of the defects. In this paper, a case study has been conducted on an Iranian automobile company. This paper performs a quality analysis of a particular component called “Internal Bearing for the Back Wheel” of a particular car model, manufactured by the company, based on the 10 million data received from its service centers located all over the country. By creating control charts including X bar–S charts and EWMA charts, it has been observed after the year 2009, the specific component underwent frequent failures and there has been a sharp dip in the average distance covered by the cars till the specific component requires replacement/maintenance. Correlation analysis was performed to find out the reasons that might have affected the quality of the specific component in all the cars produced by the company after the year 2009. Apart from manufacturing issues, some political and environmental factors have been identified to have a potential impact on the quality of the component. A maiden attempt has been made to analyze the quality issues within an Iranian automobile manufacturer; such issues often get neglected in developing countries. The paper also discusses the possibility of political scenario of Iran and the country’s environmental conditions affecting the quality of the end products, which not only strengthens the extant literature but also provides a new direction for future research.

Keywords: capability analysis, car manufacturing, statistical process control, quality control, quality tools

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Authors: Wenqian Shi, Xie He, Ziyin Huang, Zi Yu

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The dramatic changes in the global economic situation have produced dramatic changes to companies’ supply chain systems. A variety of opportunities and challenges make the traditional manufacturing industry feel pressured, and the manufacturing industry must seek a new way out as soon as possible. This paper presents a case study of the advanced planning and scheduling technology problem encountered by an electrical and electronics manufacturer. The objective is to seek the minimum cost of production planning and order management. Digitalization is applied to the problem, and the results demonstrate that significant production performances can be achieved in the face of the existing production of each link and order management systems to analyze and optimize. This paper can also provide some practical implications in various manufacturing industries. Finally, future research directions are discussed.

Keywords: advanced planning and scheduling, case study, production planning, supply chain optimization

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Authors: Sungkyung Kim, Jee-Hyeon Na, Dong-Seung Kwon

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Future mobile networks following 5th generation will be characterized by one thousand times higher gains in capacity; connections for at least one hundred billion devices; user experience capable of extremely low latency and response times. To be close to the capacity requirements and higher reliability, advanced technologies have been studied, such as multiple connectivity, small cell enhancement, heterogeneous networking, and advanced interference and mobility management. This paper is focused on the multiple connectivity in heterogeneous cellular networks. We investigate the performance of coverage and user throughput in several deployment scenarios. Using the stochastic geometry approach, the SINR distributions and the coverage probabilities are derived in case of dual connection. Also, to compare the user throughput enhancement among the deployment scenarios, we calculate the spectral efficiency and discuss our results.

Keywords: heterogeneous networks, multiple connectivity, small cell enhancement, stochastic geometry

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Authors: Mahzad Yousefi, Azin Tavakoli

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Periodontal disease is an inflammatory reaction; therefore, it is predicted that changes may occur in some inflammatory parameters that can be detected in routine blood tests. The objective of this study was to evaluate the hematological and biochemistry changes that occur in dogs affected with advanced stages of periodontal disease. 87 dogs were diagnosed with periodontal disease (PD group), and 76 healthy dogs entered the study. The PD dogs had been affected with periodontitis stage 3 or 4 and were candidates for any dental extractions. The healthy dogs were either referred for annual checkups or for issuing health travel certificates that their owners asked for complete lab tests. Neither the diseased nor healthy subjects had a history of infectious, or other general health problems or surgery in the past 3 months. Age, as well as all hematologic including PCV, WBC and RBC count, Hb, MCV, MCH, MCHC, PLT, CBC, NLR, and biochemistry data, including total protein, albumin, glucose, BUN, Creatinine, ALT, AST, and ALP, were recorded and analyzed statistically. Results confirmed that aging has a significant direct relationship with the advanced stages of periodontal disease. Mild leukocytosis occurred in the diseased group; however, it was not significant. Also, the mean total protein of the PD group was lower than that of the healthy dogs, and serum levels of albumin were found to be lower significantly in the diseased group (P<0.05). Mean ±SD amount of Platelet, MCH, and ALT were significantly higher in the diseased group in comparison to the healthy dogs (P<0.05). No significant differences were reported in other evaluated parameters. It is concluded that CBC indices of PD dogs are not systemic inflammatory; however, only a decrease in albumin showed inflammatory responses. Some indices in routine laboratory tests can be changed significantly during advanced stages of the periodontal disease dogs.

Keywords: periodontal disease, dogs, hematological factors, advanced stages, blood tests

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Authors: Tzu-Jung Tseng, Pei-Hsuen Han, Tsung-Hsueh Lu

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Background: Ensuring patients with ST-elevation myocardial infarction (STEMI) access to hospitals that could perform percutaneous coronary intervention (PCI) in time is an important concern of healthcare managers. One commonly used the method to assess the coverage of population access to PCI hospital is the use GIS-estimated linear distance (crow's fly distance) between the district centroid and the nearest PCI hospital. If the distance is within a given distance (such as 20 km), the entire population of that district is considered to have appropriate access to PCI. The premise of using district centroid to estimate the coverage of population resident in that district is that the people live in the district are evenly distributed. In reality, the population density is not evenly distributed within the administrative district, especially in rural districts. Fortunately, the Taiwan government released basic statistical area (on average 450 population within the area) recently, which provide us an opportunity to estimate the coverage of population access to PCI services more accurate. Objectives: We aimed in this study to compare the population covered by a give PCI hospital according to traditional administrative district versus basic statistical area. We further examined if the differences between two geographic units used would be larger in a rural area than in urban area. Method: We selected two hospitals in Tainan City for this analysis. Hospital A is in urban area, hospital B is in rural area. The population in each traditional administrative district and basic statistical area are obtained from Taiwan National Geographic Information System, Ministry of Internal Affairs. Results: Estimated population live within 20 km of hospital A and B was 1,515,846 and 323,472 according to traditional administrative district and was 1,506,325 and 428,556 according to basic statistical area. Conclusion: In urban area, the estimated access population to PCI services was similar between two geographic units. However, in rural areas, the access population would be overestimated.

Keywords: accessibility, basic statistical area, modifiable areal unit problem (MAUP), percutaneous coronary intervention (PCI)

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Authors: Marziyeh Yousefi, Hossein Nassaji

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This paper reports the results of a meta-analysis of studies on the effects of instruction mode on learning second language pragmatics during the last decade (from 2006 to 2016). After establishing related inclusion/ exclusion criteria, 39 published studies were retrieved and included in the present meta-analysis. Studies were later coded for face-to-face and computer-assisted mode of instruction. Statistical procedures were applied to obtain effect sizes. It was found that Computer-Assisted-Language-Learning studies generated larger effects than Face-to-Face instruction.

Keywords: meta-analysis, effect size, L2 pragmatics, comprehensive meta-analysis, face-to-face, computer-assisted language learning

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Authors: Arkaprabha Bhattacharyya, Makarand Hastak

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The COVID-19 pandemic is unprecedented in terms of its global reach and economic impacts. Historically, investment in infrastructure development projects has been touted to boost the economic growth of a nation. The State and Local governments responsible for delivering infrastructure assets work under tight budgets. Therefore, it is important to understand which infrastructure projects have the highest potential of boosting economic growth in the post-pandemic era. This paper presents relationships between infrastructure projects and economic growth. Statistical relationships between investment in different types of infrastructure projects (transit, water and wastewater, highways, power, manufacturing etc.) and indicators of economic growth are presented using historic data between 2002 and 2020 from the U.S. Census Bureau and U.S. Bureau of Economic Analysis (BEA). The outcome of the paper is the comparison of statistical correlations between investment in different types of infrastructure projects and indicators of economic growth. The comparison of the statistical correlations is useful in ranking the types of infrastructure projects based on their ability to influence economic prosperity. Therefore, investment in the infrastructures with the higher rank will have a better chance of boosting the economic growth. Once, the ranks are derived, they can be used by the decision-makers in infrastructure investment related decision-making process.

Keywords: economic growth, infrastructure development, infrastructure projects, strategic investment

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Authors: Kazem Sabet-Bokati, Ilia Rodionov, Marciel Gaier, Kevin Plucknett

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Protective coatings play a pivotal role in mitigating corrosion and preserving the integrity of metallic structures exposed to harsh environmental conditions. The diversity of corrosive environments necessitates the development of protective coatings suitable for various conditions. Accurately selecting and interpreting analysis methods is crucial in identifying the most suitable protective coatings for the various corrosive environments. This study conducted a comprehensive comparative analysis of traditional and advanced methods to assess the anti-corrosion performance of sacrificial and barrier coatings. The protective performance of pure epoxy, zinc-rich epoxy, and cold galvanizing coatings was evaluated using salt spray tests, together with electrochemical impedance spectroscopy (EIS) and potentiodynamic polarization methods. The performance of each coating was thoroughly differentiated under both atmospheric and immersion conditions. The distinct protective performance of each coating against atmospheric corrosion was assessed using traditional standard methods. Additionally, the electrochemical responses of these coatings in immersion conditions were systematically studied, and a detailed discussion on interpreting the electrochemical responses is provided. Zinc-rich epoxy and cold galvanizing coatings offer superior anti-corrosion performance against atmospheric corrosion, while the pure epoxy coating excels in immersion conditions.

Keywords: corrosion, barrier coatings, sacrificial coatings, salt-spray, EIS, polarization

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Authors: Lee Jeong Min, Lee Mi Hee, Eo Yang Dam

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Geospatial feature extraction is a very important issue in the remote sensing research. In the meantime, the image classification based on statistical techniques, but, in recent years, data mining and machine learning techniques for automated image processing technology is being applied to remote sensing it has focused on improved results generated possibility. In this study, artificial neural network and decision tree technique is applied to classify the high-resolution satellite images, as compared to the MLC processing result is a statistical technique and an analysis of the pros and cons between each of the techniques.

Keywords: remote sensing, artificial neural network, decision tree, maximum likelihood classification

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Authors: Tharaki S. Hettiarachchi

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Sustainable construction has gained massive attention in the present world as the construction industry is highly responsible for carbon emissions and other types of unsustainable practices. Yet, the construction industry has not been able to completely attain sustainable goals. Therefore, the present study aims to identify the extent to which sustainability has been considered within the scope of construction project management and to analyze the challenges, gaps, and constraints associated. Accordingly, this study develops a sustainable framework to integrate in construction project management. In accomplishing the research aim, this research integrates a qualitative approach while relying on secondary data sources. The data shall be then analyzed with the use of a systematic literature review (SLR) method while following the PRISMA (2020) guideline and represented in a statistical form. The outcomes of this study may become highly significant in identifying the nature of the existing sustainable frameworks associated with construction project management scopes and to develop a new framework to integrate in order to enhance the effectiveness of sustainable applications in construction management. The outcomes of this research may benefit present and future construction professionals and academicians to organize sustainable construction-related knowledge in a useful way to apply in practical implementation for effective project management. Overall, this study directs present and future construction professionals toward an advanced construction project management mechanism.

Keywords: construction, framework development, project management, sustainability

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Authors: Janos Farkas, Maria Czeller, Ildiko Tar

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A remarkable feature of today’s language teaching is the learners’ language learning motivation. It is always considered as a very important factor and has been widely discussed and investigated. This paper aims to present a research study conducted in higher education institutions among students majoring in business and administration in Hungary. The aim of the research was to investigate the motivational factors of students learning languages for business purposes and set up a multivariate statistical model of language learning motivation, and examine the model's main components by different social background variables. The research question sought to answer the question of whether the motivation of students of business learning LSP could be characterized through some main components. The principal components of LSP have been created, and the correlations with social background variables have been explored. The main principal components of learning a language for business purposes were "professional future", "abroad", "performance", and "external". In the online voluntary questionnaire, 28 questions were asked about students’ motivational attitudes. 449 students have filled in the questionnaire. Descriptive statistical calculations were performed, then the difference between the highest and lowest mean was analyzed by one-sample t-test. The assessment of LSP learning was examined by one-way analysis of variance and Tukey post-hoc test among students of parents with different qualifications. The correlations between student motivation statements and various social background variables and other variables related to LSP learning motivation (gender, place of residence, mother’s education, father’s education, family financial situation, etc.) have also been examined. The attitudes related to motivation were seperated by principal component analysis, and then the different language learning motivation between socio-economic variables and other variables using principal component values were examined using an independent two-sample t-test. The descriptive statistical analysis of language learning motivation revealed that students learn LSP because this knowledge will come in handy in the future. It can be concluded that students consider learning the language for business purposes to be essential and see its future benefits. Therefore, LSP teaching has an important role and place in higher education. The results verify the second linguistic motivational self-system where the ideal linguistic self embraces the ideas and desires that the foreign language learner wants to achieve in the future. One such desire is to recognize that students will need technical language skills in the future, and it is a powerful motivation for them to learn a language.

Keywords: higher education, language learning motivation, LSP, statistical analysis

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Authors: Helena López-Moreno, Antoni Rodríguez-Sánchez, Carmen Viñas-Arrebola, Cesar Porras-Amores

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The ventilated façade has great advantages when compared to traditional façades as it reduces the air conditioning thermal loads due to the stack effect induced by solar radiation in the air chamber. Optimizing energy consumption by using a ventilated façade can be used not only in newly built buildings but also it can be implemented in existing buildings, opening the field of implementation to energy building retrofitting works. In this sense, the following three prototypes of façade where designed, built and further analyzed in this research: non-ventilated façade (NVF); slightly ventilated façade (SLVF) and strongly ventilated façade (STVF). The construction characteristics of the three facades are based on the Spanish regulation of building construction “Technical Building Code”. The façades have been monitored by type-k thermocouples in a representative day of the summer season in Madrid (Spain). Moreover, an analysis of variance (ANOVA) with repeated measures, studying the thermal lag in the ventilated and no-ventilated façades has been designed. Results show that STVF façade presents higher levels of thermal inertia as the thermal lag reduces up to 100% (daily mean) compared to the non-ventilated façade. In addition, the statistical analysis proves that an increase of the ventilation holes size in STVF façades does not improve the thermal lag significantly (p > 0.05) when compared to the SLVF façade.

Keywords: ventilated façade, energy efficiency, thermal behavior, statistical analysis

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Authors: F. Sangiorgio, J. Silfwerbrand, G. Mancini

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Geometric and mechanical properties all influence the resistance of RC structures and may, in certain combination of property values, increase the risk of a brittle failure of the whole system. This paper presents a statistical and probabilistic investigation on the resistance of RC beams designed according to Eurocodes 2 and 8, and subjected to multiple failure modes, under both the natural variation of material properties and the uncertainty associated with cross-section and transverse reinforcement geometry. A full probabilistic model based on JCSS Probabilistic Model Code is derived. Different beams are studied through material nonlinear analysis via Monte Carlo simulations. The resistance model is consistent with Eurocode 2. Both a multivariate statistical evaluation and the data clustering analysis of outcomes are then performed. Results show that the ultimate load behaviour of RC beams subjected to flexural and shear failure modes seems to be mainly influenced by the combination of the mechanical properties of both longitudinal reinforcement and stirrups, and the tensile strength of concrete, of which the latter appears to affect the overall response of the system in a nonlinear way. The model uncertainty of the resistance model used in the analysis plays undoubtedly an important role in interpreting results.

Keywords: modelling, Monte Carlo simulations, probabilistic models, data clustering, reinforced concrete members, structural design

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Authors: Alaa Al Hawari, Mohammad Khader, Tarek Zayed, Osama Moselhi

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In this paper, an effective non-destructive, non-invasive approach for leak detection was proposed. The process relies on analyzing thermal images collected by an IR viewer device that captures thermo-grams. In this study a statistical analysis of the collected thermal images of the ground surface along the expected leak location followed by a visual inspection of the thermo-grams was performed in order to locate the leak. In order to verify the applicability of the proposed approach the predicted leak location from the developed approach was compared with the real leak location. The results showed that the expected leak location was successfully identified with an accuracy of more than 95%.

Keywords: thermography, leakage, water pipelines, thermograms

Procedia PDF Downloads 336

Authors: Andra Yount

Abstract:

The purpose of this research project is to understand how focusing on movement can help English language learners acquire better reading, writing, and speaking skills. More specifically, this case study tests how Laban movement analysis, a tool often used in dance and physical education classes, contributes to advanced-level high school students’ English language acquisition at an international Swiss boarding school. This article shares theoretical bases for and findings from a teaching experiment in which LMA categories (body, effort, space, and shape) were adapted and introduced to students to encourage basic language acquisition and also cultural awareness and sensitivity. As part of the participatory action research process, data collection included pseudonym-protected questionnaires and written/video-taped responses to LMA language and task prompts. Responses from 43 participants were evaluated to determine the efficacy of using this system. Participants (ages 16-19) were enrolled in advanced English as an Additional Language (EAL) courses at a private, co-educational Swiss international boarding school. Final data analysis revealed that drawing attention to movement using LMA language as a stimulus creates better self-awareness and understanding/retention of key literary concepts and vocabulary but does not necessarily contribute to greater cultural sensitivity or eliminate the use of problematic (sexist, racist, or classist) language. Possibilities for future exploration and development are also explored.

Keywords: dance, English, Laban, pedagogy

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Authors: Luyao Zhang, Tianyu Wu, Jiayi Li, Carlos-Gustavo Salas-Flores, Saad Lahrichi

Abstract:

Recent advances in AI have made algorithmic trading a central role in finance. However, current research and applications are disconnected information islands. We propose a generally applicable pipeline for designing, programming, and evaluating algorithmic trading of stock and crypto tokens. Moreover, we provide comparative case studies for four conventional algorithms, including moving average crossover, volume-weighted average price, sentiment analysis, and statistical arbitrage. Our study offers a systematic way to program and compare different trading strategies. Moreover, we implement our algorithms by object-oriented programming in Python3, which serves as open-source software for future academic research and applications.

Keywords: algorithmic trading, AI for finance, fintech, machine learning, moving average crossover, volume weighted average price, sentiment analysis, statistical arbitrage, pair trading, object-oriented programming, python3

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Authors: Amira Masood, Zainah Alshouri, Noor Bantan, Samira Kutbi

Abstract:

Artificial intelligence is continuously becoming more advanced and more widespread and is present in many of our day-to-day lives as a means of assistance in numerous different fields. A growing number of people, companies, and corporations are utilizing Canva and its AI tools as a method of quick and easy media production. Hence, in order to test the integrity of the rapid growth of AI, this paper will explore the usefulness of Canva's advanced design features as well as their accuracy by determining user satisfaction through a survey-based research approach and by investigating whether or not AI is successful enough that it eliminates the need for human alterations.

Keywords: artificial intelligence, canva, features, users, satisfaction

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Authors: Gülcan Taşkıran, Ayla Bayık Temel

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Background: Florence Nightingale, the modern founder of the nursing, is most famous for her role as a nurse. But not so much known about her contributions as a mathematician and statistician. Aim: In this conceptual article it is aimed to examine Florence Nightingale's statistics education, how she used her passion for statistics and applied statistical data in nursing care and her scientific contributions to statistical science. Design: Literature review method was used in the study. The databases of Istanbul University Library Search Engine, Turkish Medical Directory, Thesis Scanning Center of Higher Education Council, PubMed, Google Scholar, EBSCO Host, Web of Science were scanned to reach the studies. The keywords 'statistics' and 'Florence Nightingale' have been used in Turkish and English while being screened. As a result of the screening, totally 41 studies were examined from the national and international literature. Results: Florence Nightingale has interested in mathematics and statistics at her early ages and has received various training in these subjects. Lessons learned by Nightingale in a cultured family environment, her talent in mathematics and numbers, and her religious beliefs played a crucial role in the direction of the statistics. She was influenced by Quetelet's ideas in the formation of the statistical philosophy and received support from William Farr in her statistical studies. During the Crimean War, she applied statistical knowledge to nursing care, developed many statistical methods and graphics, so that she made revolutionary reforms in the health field. Conclusions: Nightingale's interest in statistics, her broad vision, the statistical ideas fused with religious beliefs, the innovative graphics she has developed and the extraordinary statistical projects that she carried out has been influential on the basis of her professional achievements. Florence Nightingale has also become a model for women in statistics. Today, using and teaching of statistics and research in nursing care practices and education programs continues with the light she gave.

Keywords: Crimean war, Florence Nightingale, nursing, statistics

Procedia PDF Downloads 283

Authors: Uraib Sharaha, Ahmad Salman, Eladio Rodriguez-Diaz, Elad Shufan, Klaris Riesenberg, Irving J. Bigio, Mahmoud Huleihel

Abstract:

Antimicrobial drugs have played an indispensable role in controlling illness and death associated with infectious diseases in animals and humans. However, the increasing resistance of bacteria to a broad spectrum of commonly used antibiotics has become a global healthcare problem. Many antibiotics had lost their effectiveness since the beginning of the antibiotic era because many bacteria have adapted defenses against these antibiotics. Rapid determination of antimicrobial susceptibility of a clinical isolate is often crucial for the optimal antimicrobial therapy of infected patients and in many cases can save lives. The conventional methods for susceptibility testing require the isolation of the pathogen from a clinical specimen by culturing on the appropriate media (this culturing stage lasts 24 h-first culturing). Then, chosen colonies are grown on media containing antibiotic(s), using micro-diffusion discs (second culturing time is also 24 h) in order to determine its bacterial susceptibility. Other methods, genotyping methods, E-test and automated methods were also developed for testing antimicrobial susceptibility. Most of these methods are expensive and time-consuming. Fourier transform infrared (FTIR) microscopy is rapid, safe, effective and low cost method that was widely and successfully used in different studies for the identification of various biological samples including bacteria; nonetheless, its true potential in routine clinical diagnosis has not yet been established. The new modern infrared (IR) spectrometers with high spectral resolution enable measuring unprecedented biochemical information from cells at the molecular level. Moreover, the development of new bioinformatics analyses combined with IR spectroscopy becomes a powerful technique, which enables the detection of structural changes associated with resistivity. The main goal of this study is to evaluate the potential of the FTIR microscopy in tandem with machine learning algorithms for rapid and reliable identification of bacterial susceptibility to antibiotics in time span of few minutes. The UTI E.coli bacterial samples, which were identified at the species level by MALDI-TOF and examined for their susceptibility by the routine assay (micro-diffusion discs), are obtained from the bacteriology laboratories in Soroka University Medical Center (SUMC). These samples were examined by FTIR microscopy and analyzed by advanced statistical methods. Our results, based on 700 E.coli samples, were promising and showed that by using infrared spectroscopic technique together with multivariate analysis, it is possible to classify the tested bacteria into sensitive and resistant with success rate higher than 90% for eight different antibiotics. Based on these preliminary results, it is worthwhile to continue developing the FTIR microscopy technique as a rapid and reliable method for identification antibiotic susceptibility.

Keywords: antibiotics, E.coli, FTIR, multivariate analysis, susceptibility, UTI

Procedia PDF Downloads 163