Search results for: advanced diagnostic obesity notation model assessment cardiac index

Authors: Ima Rahmawati, Nur Hafizul Kalam

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Development of industrial and economic sectors in various countries very rapidly caused raising the greenhouse gas (GHG) emissions. Greenhouse gases are dominated by carbon dioxide (CO2) and methane (CH4) in the atmosphere that make the surface temperature of the earth always increase. The increasing gases caused by incomplete combustion of fossil fuels such as petroleum and coals and also high rate of deforestation. Yogyakarta Special Province which every year always become tourist destination, has a great potency in increasing of greenhouse gas emissions mainly from the incomplete combustion. One of effort to reduce the concentration of gases in the atmosphere is keeping and empowering the existing forests in the Province of Yogyakarta, especially forest in Kulonprogro is to be maintained the greenness so that it can absorb and store carbon maximally. Remote sensing technology can be used to determine the ability of forests to absorb carbon and it is connected to the density of vegetation. The purpose of this study is to determine the density of the biomass of forest vegetation and determine the ability of forests to store carbon through Photo-interpretation and Geographic Information System approach. Remote sensing imagery that used in this study is LANDSAT 8 OLI year 2015 recording. LANDSAT 8 OLI imagery has 30 meters spatial resolution for multispectral bands and it can give general overview the condition of the carbon stored from every density of existing vegetation. The method is the transformation of vegetation index combined with allometric calculation of field data then doing regression analysis. The results are model maps of density and capability level of forest vegetation in Kulonprogro, Yogyakarta in storing carbon.

Keywords: remote sensing, carbon, kulonprogo, forest vegetation, vegetation index

Procedia PDF Downloads 399

Authors: Ferruh Taspinar, Gulce K. Seyyar, Gamze Kurt, Eda O. Okur, Emrah Afsar, Ismail Saracoglu, Betul Taspinar

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Overweight and obesity has been associated with postural balance. The aim of this study was to investigate the relationship between body composition and balance. One hundred and thirty two young adults (58 male, 74 female) were included in the study. Mean age of participants were found as 21.21±1.51 years. Body composition (body mass index, total body fat ratio, total body muscle ratio) and balance (right anterior, right postero-medial, right postero-lateral, left anterior, left postero-medial, left postero-lateral) were evaluated by Tanita BC-418 and Y balance test, respectively. Pearson correlation analysis was used to evaluate the correlation between the parameters. Significance level in statistical analysis was accepted as 0.05. According to results, no correlation was found between body mass index and balance parameters. There was negative correlation between total body fat ratio and balance parameters (r=0.419-0.509, p˂0.05). On the other hand, positive correlation was found between total body muscle ratio and balance parameters (r=0.390-0.494, p˂0.05). This study demonstrated that body fat and muscle ratio affects the balance. Body composition should be considered in rehabilitation programs including postural balance training.

Keywords: balance, body composition, body mass, young adults

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Authors: Hamid Rostami Jaz, Kamran Ameri Siahooei

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Up to now different methods have been used to forecast the index returns and the index rate. Artificial intelligence and artificial neural networks have been one of the methods of index returns forecasting. This study attempts to carry out a comparative study on the performance of different Radial Base Neural Network and Feed-Forward Perceptron Neural Network to forecast investment returns on the index. To achieve this goal, the return on investment in Tehran Stock Exchange index is evaluated and the performance of Radial Base Neural Network and Feed-Forward Perceptron Neural Network are compared. Neural networks performance test is applied based on the least square error in two approaches of in-sample and out-of-sample. The research results show the superiority of the radial base neural network in the in-sample approach and the superiority of perceptron neural network in the out-of-sample approach.

Keywords: exchange index, forecasting, perceptron neural network, Tehran stock exchange

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Authors: Manali Jain, Neeta Singh, Raunaq Fatima, Soniya Nityanand, Mandakini Pradhan, Chandra Prakash Chaturvedi

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Isolated Congenital Heart Defect (ICHD) is the major cause of neonatal death worldwide among all forms of CHDs. A significant proportion of fetuses with ICHD die in the neonatal period if no treatment is provided. Recently, stem cell therapies have emerged as a potential approach to ameliorate ICHD in children. ICHD is characterized by cardiac structural abnormalities during embryogenesis due to alterations in the cardiomyogenic properties of a pool of cardiac progenitors/ stem cells associated with fetal heart development. The stem cells present in the amniotic fluid (AF) are of fetal origin and may reflect the physiological and pathological changes in the fetus during embryogenesis. Therefore, in the present study, the cardiomyogenic potential of AF-MSCs derived from fetuses with ICHD (ICHD AF-MSCs) has been evaluated and compared with that of AF-MSCs of structurally normal fetuses (normal AF-MSCs). Normal and ICHD AF-MSC were analyzed for the expression of cardiac progenitor markers viz., stage-specific embryonic antigen-1 (SSEA-1), vascular endothelial growth factor 2 (VEGFR-2) and platelet-derived growth factor receptor-alpha (PDGFR-α) by flow cytometry. The immunophenotypic characterization revealed that ICHD AF-MSCs have significantly lower expression of cardiac progenitor markers VEGFR-2 (0.14% ± 0.6 vs.48.80% ± 0.9; p <0.01), SSEA-1 (70.86% ± 2.4 vs. 88.36% ±2.7; p <0.01), and PDGFR-α (3.92% ± 1.8 vs. 47.59% ± 3.09; p <0.01) in comparison to normal AF-MSCs. Upon induction with 5’-azacytidine for 21 days, ICHD AF-MSCs showed a significantly down-regulated expression of cardiac transcription factors such as GATA-4 (0.4 ± 0.1 vs. 6.8 ± 1.2; p<0.01), ISL-1 (2.3± 0.6 vs. 14.3 ± 1.12; p<0.01), NK-x 2-5 (1.1 ± 0.3 vs. 14.1 ±2.8; p<0.01), TBX-5 (0.4 ± 0.07 vs. 4.4 ± 0.3; p<0.001), and TBX-18 (1.3 ± 0.2 vs. 4.19 ± 0.3; p<0.01) when compared with the normal AF-MSCs. Furthermore, immunocytochemical staining revealed that both types of AF-MSCs could differentiate into cardiovascular lineages and express cardiomyogenic, endothelial, and smooth muscle actin markers, viz., cardiac troponin (cTNT), CD31, and alpha-smooth muscle actin (α-SMA). However, normal AF-MSCs showed an enhanced expression of cTNT (p<0.001), CD31 (p<0.01), and α-SMA (p<0.05), compared to ICHD AF-MSCs. Overall, these results suggest that the ICHD-AF-MSCs have a defective cardiomyogenic differentiation potential and that the defects in these stem cells may have a role in the pathogenesis of ICHD.

Keywords: amniotic fluid, cardiomyogenic potential, isolated congenital heart defect, mesenchymal stem cells

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Authors: Mustafa M. Donma, Orkide Donma

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Obesity is a low-grade inflammatory state. Childhood obesity is a multisystem disease, which is associated with a number of complications as well as potentially negative consequences. Gender is an important universal risk factor for many diseases. Hematological indices differ significantly by gender. This should be considered during the evaluation of obese children. The aim of this study is to detect hematologic indices that differ by gender in morbid obese (MO) children. A total of 134 MO children took part in this study. The parents filled an informed consent form and the approval from the Ethics Committee of Namik Kemal University was obtained. Subjects were divided into two groups based on their genders (64 females aged 10.2±3.1 years and 70 males aged 9.8±2.2 years; p ≥ 0.05). Waist-to-hip as well as head-to-neck ratios and body mass index (BMI) values were calculated. The children, whose WHO BMI-for age and sex percentile values were > 99 percentile, were defined as MO. Hematological parameters [haemoglobin, hematocrit, erythrocyte count, mean corpuscular volume, mean corpuscular haemoglobin, mean corpuscular haemoglobin concentration, red blood cell distribution width, leukocyte count, neutrophil %, lymphocyte %, monocyte %, eosinophil %, basophil %, platelet count, platelet distribution width, mean platelet volume] were determined by the automatic hematology analyzer. SPSS was used for statistical analyses. P ≤ 0.05 was the degree for statistical significance. The groups included children having mean±SD value of BMI as 26.9±3.4 kg/m² for males and 27.7±4.4 kg/m² for females (p ≥ 0.05). There was no significant difference between ages of females and males (p ≥ 0.05). Males had significantly increased waist-to-hip ratios (0.95±0.08 vs 0.91±0.08; p=0.005) and mean corpuscular hemoglobin concentration values (33.6±0.92 vs 33.1±0.83; p=0.001) compared to those of females. Significantly elevated neutrophil (4.69±1.59 vs 4.02±1.42; p=0.011) and neutrophil-to-lymphocyte ratios (1.70±0.71 vs 1.39±0.48; p=0.004) were detected in females. There was no statistically significant difference between groups in terms of C-reactive protein values (p ≥ 0.05). Adipose tissue plays important roles during the development of obesity and associated diseases such as metabolic syndrom and cardiovascular diseases (CVDs). These diseases may cause changes in complete blood cell count parameters. These alterations are even more important during childhood. Significant gender effects on the changes of neutrophils, one of the white blood cell subsets, were observed. The findings of the study demonstrate the importance of considering gender in clinical studies. The males and females may have distinct leukocyte-trafficking profiles in inflammation. Female children had more circulating neutrophils, which may be the indicator of an increased risk of CVDs, than male children within this age range during the late stage of obesity. In recent years, females represent about half of deaths from CVDs; therefore, our findings may be the indicator of the increasing tendency of this risk in females starting from childhood.

Keywords: children, gender, morbid obesity, neutrophil-to-lymphocyte ratio

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Authors: Marcos Valdez Alexander Junior, Igor Aguilar-Alonso

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Malnutrition is the root of different diseases that universally affect everyone, diseases such as obesity and malnutrition. The objective of this research is to predict the calories of the food to be eaten, developing a smart mobile application to show the user if a meal is balanced. Due to the large percentage of obesity and malnutrition in Peru, the present work is carried out. The development of the intelligent application is proposed with a three-layer architecture, and for the prediction of the nutritional value of the food, the use of pre-trained models based on convolutional neural networks is proposed.

Keywords: volume estimation, calorie estimation, artificial vision, food nutrition

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Authors: A. A. Adebayo, O. Osibanjo

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Informal electronic waste (e-waste) processing is a crude method of recycling, which is on the increase in Nigeria. The release of hazardous substances such as heavy metals (HMs) into the environment during informal e-waste processing has been a major concern. However, there is insufficient information on environmental contamination from e-waste recycling, associated ecological risk in Alaba International Market, a major electronic market in Lagos, Nigeria. The aims of this study were to determine the levels of HMs in soil, resulting from the e-waste recycling; and also assess associated ecological risks in Alaba international market. Samples of soils (334) were randomly collected seasonally for three years from fourteen selected e-waste activity points and two control sites. The samples were digested using standard methods and HMs analysed by inductive coupled plasma optical emission. Ecological risk was estimated using Ecological Risk index (ER), Potential Ecological Risk index (RI), Index of geoaccumulation (Igeo), Contamination factor (Cf) and degree of contamination factor (Cdeg). The concentrations range of HMs (mg/kg) in soil were: 16.7-11200.0 (Pb); 14.3-22600.0 (Cu); 1.90-6280.0 (Ni), 39.5-4570.0 (Zn); 0.79-12300.0 (Sn); 0.02-138.0 (Cd); 12.7-1710.0 (Ba); 0.18-131.0 (Cr); 0.07-28.0 (V), while As was below detection limit. Concentrations range in control soils were 1.36-9.70 (Pb), 2.06-7.60 (Cu), 1.25-5.11 (Ni), 3.62-15.9 (Zn), BDL-0.56 (Sn), BDL-0.01 (Cd), 14.6-47.6 (Ba), 0.21–12.2 (Cr) and 0.22-22.2 (V). The trend in ecological risk index was in the order Cu > Pb > Ni > Zn > Cr > Cd > Ba > V. The potential ecological risk index with respect to informal e-waste activities were: burning > dismantling > disposal > stockpiling. The index of geo accumulation indices revealed that soils were extremely polluted with Cd, Cu, Pb, Zn and Ni. The contamination factor indicated that 93% of the studied areas have very high contamination status for Pb, Cu, Ba, Sn and Co while Cr and Cd were in the moderately contaminated status. The degree of contamination decreased in the order of Sn > Cu > Pb >> Zn > Ba > Co > Ni > V > Cr > Cd. Heavy metal contamination of Alaba international market environment resulting from informal e-waste processing was established. Proper management of e-waste and remediation of the market environment are recommended to minimize the ecological risks.

Keywords: Alaba international market, ecological risk, electronic waste, heavy metal contamination

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Authors: Ella Tyuryumina, Alexey Neznanov

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This paper is devoted to mathematical modelling of the progression and stages of breast cancer. We propose Consolidated mathematical growth model of primary tumor and secondary distant metastases growth in patients with lymph nodes metastases (CoM-III) as a new research tool. We are interested in: 1) modelling the whole natural history of primary tumor and secondary distant metastases growth in patients with lymph nodes metastases; 2) developing adequate and precise CoM-III which reflects relations between primary tumor and secondary distant metastases; 3) analyzing the CoM-III scope of application; 4) implementing the model as a software tool. Firstly, the CoM-III includes exponential tumor growth model as a system of determinate nonlinear and linear equations. Secondly, mathematical model corresponds to TNM classification. It allows to calculate different growth periods of primary tumor and secondary distant metastases growth in patients with lymph nodes metastases: 1) ‘non-visible period’ for primary tumor; 2) ‘non-visible period’ for secondary distant metastases growth in patients with lymph nodes metastases; 3) ‘visible period’ for secondary distant metastases growth in patients with lymph nodes metastases. The new predictive tool: 1) is a solid foundation to develop future studies of breast cancer models; 2) does not require any expensive diagnostic tests; 3) is the first predictor which makes forecast using only current patient data, the others are based on the additional statistical data. Thus, the CoM-III model and predictive software: a) detect different growth periods of primary tumor and secondary distant metastases growth in patients with lymph nodes metastases; b) make forecast of the period of the distant metastases appearance in patients with lymph nodes metastases; c) have higher average prediction accuracy than the other tools; d) can improve forecasts on survival of breast cancer and facilitate optimization of diagnostic tests. The following are calculated by CoM-III: the number of doublings for ‘non-visible’ and ‘visible’ growth period of secondary distant metastases; tumor volume doubling time (days) for ‘non-visible’ and ‘visible’ growth period of secondary distant metastases. The CoM-III enables, for the first time, to predict the whole natural history of primary tumor and secondary distant metastases growth on each stage (pT1, pT2, pT3, pT4) relying only on primary tumor sizes. Summarizing: a) CoM-III describes correctly primary tumor and secondary distant metastases growth of IA, IIA, IIB, IIIB (T1-4N1-3M0) stages in patients with lymph nodes metastases (N1-3); b) facilitates the understanding of the appearance period and inception of secondary distant metastases.

Keywords: breast cancer, exponential growth model, mathematical model, primary tumor, secondary metastases, survival

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Authors: İsmail İnce

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The aim of this study is to determine index and mechanical properties of pyroclastic rock in a practical way by means of electrical resistivity method. For this purpose, electrical resistivity, uniaxial compressive strength, point load strength, P-wave velocity, density and porosity values of 10 different pyroclastic rocks were measured in the laboratory. A simple regression analysis was made among the index-mechanical properties of the samples compatible with electrical resistivity values. A strong exponentially relation was found between index-mechanical properties and electrical resistivity values. The electrical resistivity method can be used to assess the engineering properties of the rock from which it is difficult to obtain regular shaped samples as a non-destructive method.

Keywords: electrical resistivity, index-mechanical properties, pyroclastic rocks, regression analysis

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Authors: Newton Muhury, Armando A. Apan, Tek Maraseni

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This study modelled the relationships between vegetation response and available water below the soil surface using the Terra’s Moderate Resolution Imaging Spectroradiometer (MODIS) generated Normalised Difference Vegetation Index (NDVI) and soil water content (SWC) data. The Soil & Water Assessment Tool (SWAT) interface known as ArcSWAT was used in ArcGIS for the groundwater analysis. The SWAT model was calibrated and validated in SWAT-CUP software using 10 years (2001-2010) of monthly streamflow data. The average Nash-Sutcliffe Efficiency during the calibration and validation was 0.54 and 0.51, respectively, indicating that the model performances were good. Twenty years (2001-2020) of monthly MODIS NDVI data for three different types of vegetation (forest, shrub, and grass) and soil water content for 43 sub-basins were analysed using the WEKA, machine learning tool with a selection of two supervised machine learning algorithms, i.e., support vector machine (SVM) and random forest (RF). The modelling results show that different types of vegetation response and soil water content vary in the dry and wet season. For example, the model generated high positive relationships (r=0.76, 0.73, and 0.81) between the measured and predicted NDVI values of all vegetation in the study area against the groundwater flow (GW), soil water content (SWC), and the combination of these two variables, respectively, during the dry season. However, these relationships were reduced by 36.8% (r=0.48) and 13.6% (r=0.63) against GW and SWC, respectively, in the wet season. On the other hand, the model predicted a moderate positive relationship (r=0.63) between shrub vegetation type and soil water content during the dry season, which was reduced by 31.7% (r=0.43) during the wet season. Our models also predicted that vegetation in the top location (upper part) of the sub-basin is highly responsive to GW and SWC (r=0.78, and 0.70) during the dry season. The results of this study indicate the study region is suitable for seasonal crop production in dry season. Moreover, the results predicted that the growth of vegetation in the top-point location is highly dependent on groundwater flow in both dry and wet seasons, and any instability or long-term drought can negatively affect these floodplain vegetation communities. This study has enriched our knowledge of vegetation responses to groundwater in each season, which will facilitate better floodplain vegetation management.

Keywords: ArcSWAT, machine learning, floodplain vegetation, MODIS NDVI, groundwater

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Authors: Jeong-Hyun Park, Young-Sik Park, Hyo-Teag Jung

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This paper presents static analysis deployment model for code quality on R&D Projects of SW Development. The proposed model includes the scope of R&D projects and index for static analysis of source code, operation model and execution process, environments and infrastructure system for R&D projects of SW development. There is the static analysis result of pilot project as case study based on the proposed deployment model and environment, and strategic considerations for success operation of the proposed static analysis deployment model for R&D Projects of SW Development. The proposed static analysis deployment model in this paper will be adapted and improved continuously for quality upgrade of R&D projects, and customer satisfaction of developed source codes and products.

Keywords: static analysis, code quality, coding rules, automation tool

Procedia PDF Downloads 524

Authors: Chaoge Wang, Xiquan Weng, Yan Meng, Wentao Lin

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Objective: Cold exposure and exercise serve as two physiological stimuli to glycolipid metabolism and insulin sensitivity. So far, it remains to be elucidated whether exercise plus cold exposure can produce an addictive effect on promoting glycolipid metabolism and insulin sensitivity. Methods: 64 SD rats were subjected to high-fat and high-sugar diets for 9-week and sucessfully to establish an obesity model. They were randomly divided into 8 groups: normal control group (NC), normal exercise group (NE), continuous cold control group (CC), continuous cold exercise group (CE), acute clod control group (AC), acute cold exercise group (AE), intermittent cold control group (IC) and intermittent cold exercise group (IE). For continuous cold exposure, the rats stayed in a cold environment all day; for acute cold exposure, the rats were exposed to cold for only 4h before the end of the experiment; for intermittent cold exposure, the rats were exposed to cold for 4h per day. The protocol for treadmill runnings were as follows: 25m/min (speed), 0°C (slope), 30 mins each time, an interval for 10 mins between two runnings, twice/two days, lasting for 5 weeks. Sampling were conducted on the 5th weekend. Blood lipids, free fatty acids, blood glucose (FBG), and serum insulin (FINS) were examined, and the insulin resistance index (HOMA-IR = FBG (mmol/L)×FINS(mIU/L)/22.5) was calculated. SPSS 22.0 was used for statistical analysis of the experimental results, and the ANOVA analysis was performed between groups (p < 0.05 was significant). Results: (1) Compared with the NC group, the FBG of the rats was significantly declined in the NE, CE, AC, AE, and IE groups (p < 0.05), the FINS of the rats was significantly declined in the AE group (p < 0.05), the HOMA-IR of the rats was significantly declined in the NE, CE, AC, AE and IE groups (p < 0.05). Compared with the NE group, the FBG of the rats was significantly declined in the CE, AE, and IE groups (p < 0.05), the FINS and HOMA-IR of the rats were significantly declined in the AE group (p < 0.05). (2) Compared with the NC group, the CHO, TG, LDL-C, and FFA of the rats were significantly declined in CE and IE groups (p < 0.05), the HDL-C of the rats was significantly higher in NE, CC, CE, AE, and IE groups (p < 0.05). Compared with the NE group, the HDL-C of the rats was significantly higher in the CE and IE groups (p < 0.05). Conclusions: Sedentariness or exercise in the acute cold doesn't make sense in the treatment of type 2 diabetes, which led to one-off increases of the body's insulin sensitivity. Exercise in the continuous and intermittent cold can effectively decline the FBG, TC, TG, LDL-C, and FFA levels and increase the HDL-C level and insulin sensitivity in obese rats. These results can impact the prevention and treatment of type 2 diabetes.

Keywords: cold, exercise, insulin sensitivity, obesity

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Authors: Yating Yang, Xue Zhang, Chengli Zhao

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Technology capability refers to the comprehensive ability that influences all factors of technological development. Among them, researchers’ resources serve as the foundation and driving force for technology capability, representing a significant manifestation of a country/region's technological capability. Therefore, the cross-border transfer behavior of researchers to some extent reflects changes in technological capability between countries/regions, providing a unique research perspective for technological capability assessment. This paper proposes a technological capability assessment model based on personnel transfer networks, which consists of a researchers' transfer network model and a country/region role evolution model. It evaluates the changes in a country/region's technological capability roles from the perspective of researcher transfers and conducts an analysis using artificial intelligence as a case study based on literature data. The study reveals that the United States, China, and the European Union are core nodes, and identifies the role evolution characteristics of several major countries/regions.

Keywords: transfer network, technological capability assessment, central-peripheral structure, role evolution

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Authors: Changfeng Fu

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Sustainable urban development has been widely accepted a common sense in the modern urban planning and design. However, the measurement and assessment of urban sustainability, especially the quantitative assessment have been always an issue obsessing planning and design professionals. This paper will present an on-going research on the principles and technologies to develop a quantitative urban sustainability assessment principles and techniques which aim to integrate indicators, geospatial and geo-reference data, and assessment techniques together into a mechanism. It is based on the principles and techniques of geospatial analysis with GIS and statistical analysis methods. The decision-making technologies and methods such as AHP and SMART are also adopted to address overall assessment conclusions. The possible interfaces and presentation of data and quantitative assessment results are also described. This research is based on the knowledge, situations and data sources of UK, but it is potentially adaptable to other countries or regions. The implementation potentials of the mechanism are also discussed.

Keywords: urban sustainability assessment, quantitative analysis, sustainability indicator, geospatial data, big data

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Authors: Kumaressan Ragunathan, Arisudhan Anantharachagan

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Gestational diabetes mellitus (GDM) is the subtype of diabetes that has been rapidly increasing in numbers in Australia. The annual percentage of GDM has increased more than 50 percent in the last decade. According to Diabetes Australia, more than five hundred thousand women in Australia will be diagnosed with GDM. Globally, the prevalence of GDM ranges from single-digit to more than 45%. The prevalence of GDM has increased significantly last five years after the introduction of new diagnostic criteria. Hence, we have decided to investigate the trend in GDM prevalence in a tertiary maternity unit at Western Australia and compare it to national prevalence. Data is derived from STORK Perinatal Database which has been used by Maternity services in Western Australia to populate information on pregnancy and labour. We have selected data from 2015 until 2020, which includes 17508 women. Among 17508 women, 3850 women were diagnosed with GDM. In 2015, we had a total of 2213 deliveries with 345 of them were complicated by GDM. GDM prevalence was 15.6% compared to the Australian national prevalence of 12%. In 2016, total deliveries increased to 2759 with 590 of were with GDM. GDM prevalence was 21.4% compared to the Australian national prevalence of 12%. In 2017, total deliveries further increased to 3049 with 675 with GDM. GDM prevalence was 22.1%, with an Australian national prevalence of 13%. In 2018, total deliveries continued to increase, with numbers reaching 3231 with 749 with GDM. GDM prevalence was 23.2%, with an Australian National prevalence of 14%. In 2019, total deliveries were 3110, with 712 complicated by GDM. GDM prevalence was 22.9%, with Australian national prevalence 14%. In 2020, total deliveries 3146 with 819 complicated by GDM. GDM prevalence increased to 26% and we were unable to compare this to national standard as national prevalence has not been released. Among 3890 women with GDM, 2482 (64%) of them required insulin. Apart from that, a total 1642(42%) from the GDM group were delivered via the Caesarean section. 2121 (55%) women with GDM required induction of labour. Overall, we demonstrated an increase in the prevalence of GDM in our unit from 2015 until 2020. Our prevalence is also higher compared to national prevalence. This could be contributed by the increasing number of obesity and in addition, our unit accepts referrals of women with a body mass index (BMI) of more than 40. Hence, further studies are required to look at other risk factors like ethnicity, socio-economic status, health literacy and age, which could contribute to this high prevalence.

Keywords: gestational diabetes mellitus, prevalence, Western Australia, Australia

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Authors: Mehmet Oren, Susan Pedersen, Sevket C. Cetin

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Despite the frequently criticized disadvantages of the traditional used paper and pencil assessment, it is the most frequently used method in our schools. Although assessments do an acceptable measurement, they are not capable of measuring all the aspects and the richness of learning and knowledge. Also, many assessments used in schools decontextualize the assessment from the learning, and they focus on learners’ standing on a particular topic but do not concentrate on how student learning changes over time. For these reasons, many scholars advocate that using simulations and games (S&G) as a tool for assessment has significant potentials to overcome the problems in traditionally used methods. S&G can benefit from the change in technology and provide a contextualized medium for assessment and teaching. Furthermore, S&G can serve as an instructional tool rather than a method to test students’ learning at a particular time point. To investigate the potentials of using educational games as an assessment and teaching tool, this study presents the implementation and the validation of an automated embedded assessment (AEA), which can constantly monitor student learning in the game and assess their performance without intervening their learning. The experiment was conducted on an undergraduate level engineering course (Digital Circuit Design) with 99 participant students over a period of five weeks in Spring 2016 school semester. The purpose of this research study is to examine if the proposed method of AEA is valid to assess student learning in a 3D Educational game and present the implementation steps. To address this question, this study inspects three aspects of the AEA for the validation. First, the evidence-centered design model was used to lay out the design and measurement steps of the assessment. Then, a confirmatory factor analysis was conducted to test if the assessment can measure the targeted latent constructs. Finally, the scores of the assessment were compared with an external measure (a validated test measuring student learning on digital circuit design) to evaluate the convergent validity of the assessment. The results of the confirmatory factor analysis showed that the fit of the model with three latent factors with one higher order factor was acceptable (RMSEA < 0.00, CFI =1, TLI=1.013, WRMR=0.390). All of the observed variables significantly loaded to the latent factors in the latent factor model. In the second analysis, a multiple regression analysis was used to test if the external measure significantly predicts students’ performance in the game. The results of the regression indicated the two predictors explained 36.3% of the variance (R2=.36, F(2,96)=27.42.56, p<.00). It was found that students’ posttest scores significantly predicted game performance (β = .60, p < .000). The statistical results of the analyses show that the AEA can distinctly measure three major components of the digital circuit design course. It was aimed that this study can help researchers understand how to design an AEA, and showcase an implementation by providing an example methodology to validate this type of assessment.

Keywords: educational video games, automated embedded assessment, assessment validation, game-based assessment, assessment design

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Authors: Yingjie Zhang, Ming Li, Ying Zhang, Jing Zhang, Zuolei Hu

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In the actual start-up process of DC motors, the DC drive system often faces a conflict between energy consumption and acceleration performance. To resolve the conflict, this paper proposes a comprehensive performance index that energy consumption index is added on the basis of classical control performance index in the DC motor starting process. Taking the comprehensive performance index as the cost function, particle swarm optimization algorithm is designed to optimize the comprehensive performance. Then it conducts simulations on the optimization of the comprehensive performance of the DC motor on condition that the weight coefficient of the energy consumption index should be properly designed. The simulation results show that as the weight of energy consumption increased, the energy efficiency was significantly improved at the expense of a slight sacrifice of fastness indicators with the comprehensive performance index method. The energy efficiency was increased from 63.18% to 68.48% and the response time reduced from 0.2875s to 0.1736s simultaneously compared with traditional proportion integrals differential controller in energy saving.

Keywords: comprehensive performance index, energy consumption, acceleration performance, particle swarm optimal control

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Authors: Aminah Muchdar, Nuraeni, Eddy

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The aims of the research are: (1) to verify the cropsyst plant model of experimental data in the field of soybean plants and (2) to predict planting time and potential yield soybean plant with the use of cropsyst model. This research is divided into several stages: (1) first calibration stage which conducted in the field from June until September 2015.(2) application models stage, where the data obtained from calibration in the field will be included in cropsyst models. The required data models are climate data, ground data/soil data,also crop genetic data. The relationship between the obtained result in field with simulation cropsyst model indicated by Efficiency Index (EF) which the value is 0,939.That is showing that cropsyst model is well used. From the calculation result RRMSE which the value is 1,922%.That is showing that comparative fault prediction results from simulation with result obtained in the field is 1,92%. The conclusion has obtained that the prediction of soybean planting time cropsyst based models that have been made valid for use. and the appropriate planting time for planting soybeans mainly on rain-fed land is at the end of the rainy season, in which the above study first planting time (June 2, 2015) which gives the highest production, because at that time there was still some rain. Tanggamus varieties more resistant to slow planting time cause the percentage decrease in the yield of each decade is lower than the average of all varieties.

Keywords: soybean, Cropsyst, calibration, efficiency Index, RRMSE

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Authors: Sahar Shams

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Coeliac disease (CD) is a widely reported disease particularly in countries with predominant Caucasian populations. It presents with many signs and symptoms including iron deficiency (ID) and iron deficiency anaemia/anaemia (IDA/A). The exact association between ID, IDA/A and CD and how accurate these signs are in diagnosing CD is not fully known. This systematic review was conducted to investigate the accuracy of both ID & IDA/A as a diagnostic indicator for CD and whether it warrants point of care testing. A systematic review was performed looking at studies published in MEDLINE, Embase, Cochrane Library, and Web of Science. QUADAS-2 tool was used to assess risk of bias in each study. ROC curve and forest plots were generated as part of the meta-analysis after data extraction. 16 studies were identified in total, 13 of which were IDA/A studies and 3 ID studies. The prevalence of CD regardless of diagnostic indicator was assumed as 1%. The QUADAS-2 tool indicated most of studies as having high risk of bias. The PPV for CD was higher in those with ID than for those with IDA/A. Meta-analysis showed the overall odds of having CD is 5 times higher in individuals with ID & IDA/A. The ROC curve showed that there is definitely an association between both diagnostic indicators and CD, the association is not a particularly strong one due to great heterogeneity between studies. Whilst an association between IDA/A & ID and coeliac disease was evident, the results were not deemed significant enough to prompt coeliac disease testing in those with IDA/A & ID.

Keywords: anemia, iron deficiency anemia, coeliac disease, point of care testing

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Authors: Layal Mansour

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This paper breaks down Egypt’s financial crisis by constructing a customized financial stress index by including the vulnerable economic indicator “dollarization” as a vulnerable indicator in the credit and exchange sector. The Financial Stress Index for Egypt (FSIE) includes informative vulnerable indicators of the main financial sectors: the banking sector, the equities market, and the foreign exchange market. It is calculated on a monthly basis from 2010 to December 2022, so to report the two recent world’s most devastating financial crises: Covid 19 crisis and Ukraine-Russia War, in addition to the local 2016 and 2022 financial crises. We proceed first by a graphical analysis then by empirical analysis in running under Vector Autoregression (VAR) Model, dynamic causality tests between foreign reserves, dollarization rate, and FSIE. The graphical analysis shows that unexpectedly, Egypt’s economy seems to be immune to internal economic/political instabilities, however it is highly exposed to the foreign and exchange market. Empirical analysis confirms the graphical observations and proves that dollarization, or more precisely debt in foreign currency seems to be the main trigger of Egypt’s current financial crisis.

Keywords: egypt, financial crisis, financial stress index, dollarization, VAR model, causality tests

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Authors: Karl Bryant Buan, Owaida Macadadaya Jr., Mon Eleazar Nonato, Zeke Andrew Palabrica, Charistabelle Mae Santiago

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This study explored the occupational health risks faced by employees in the Business Process Outsourcing (BPO) industry, particularly in the Telco Account department of Alorica. The study used a stratified sampling method and a diagnostic tool called Workplace Integrated Safety and Health (WISH) Assessment to measure and evaluate the employees' perception of workplace health and safety. The results showed that more than 50% of call center workers reported feeling emotionally drained, sleep deprived, burnt out, and in need of anxiety or stress medication due to their work. Additionally, there was a significant difference in the perception of employee diversity, specifically in terms of leadership commitment, participation, policies, programs, and practices. The Cornell Musculoskeletal Discomfort Questionnaire (CMDQ) results revealed that most employees complained of discomfort in their lower back, shoulder, upper back, neck, and hip. The researchers recommended an implementation plan for alternative work set-up, a satisfaction survey for employees, team-building activities or programs, and motivational approaches through benefits, incentives, and rewards.

Keywords: WISH assessment, CMDQ, ANOVA, diverse SOGIESC

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Authors: Zhanfeng Ma, Zhiping Xiong, Hu Yin, Zhengwei She, Aditya P. Gurajada, Tianlun Chen, Ying Li

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Many RDBMS vendors use B-tree index to achieve high performance for point queries and range queries, and some of them also employ hash index to further enhance the performance as hash table is more efficient for point queries. However, there are extra overheads to maintain a separate hash index, for example, hash mapping for all data records must always be maintained, which results in more memory space consumption; locking, logging and other mechanisms are needed to guarantee ACID, which affects the concurrency and scalability of the system. To relieve the overheads, Hash Cached B-tree (HCB) index is proposed in this paper, which consists of a standard disk-based B-tree index and an additional in-memory lock-free hash table. Initially, only the B-tree index is constructed for all data records, the hash table is built on the fly based on runtime workload, only data records accessed by point queries are indexed using hash table, this helps reduce the memory footprint. Changes to hash table are done using compare-and-swap (CAS) without performing locking and logging, this helps improve the concurrency and avoid contention. The hash table is also optimized to be cache conscious. HCB index is implemented in SAP ASE database, compared with the standard B-tree index, early experiments and customer adoptions show significant performance improvement. This paper provides an overview of the design of HCB index and reports the experimental results.

Keywords: B-tree, compare-and-swap, lock-free hash table, point queries, range queries, SAP ASE database

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Authors: Enikő Bene

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Our sowing date experiment took place in the Demonstration Garden of Institution of Plant Sciences, Agricultural Center of University of Debrecen, in 2012-2014. The thesis contains data of test year 2014. Our purpose, besides several other examinations, was to observe how sowing date influences leaf area index and activity of photosynthesis of maize hybrids, and how those factors affect fruiting. In the experiment we monitored the change of the leaf area index and the photosynthesis of hybrids with four different growing seasons. The results obtained confirm that not only the environmental and agricultural factors in the growing season have effect on the yield, but also other factors like the leaf area index and the photosynthesis are determinative parameters, and all those factors together, modifying effects of each other, develop average yields

Keywords: sowing date, hybrid, leaf area index, photosynthetic capacity

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Authors: Nasrin Bakhshizadeh, Ashkan Forootan

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A major problem that affects the quality control of polymer in the industrial polymerization is the lack of suitable on-line measurement tools to evaluate the properties of the polymer such as melt and density indices. Controlling the polymerization in ordinary method is performed manually by taking samples, measuring the quality of polymer in the lab and registry of results. This method is highly time consuming and leads to producing large number of incompatible products. An online application for estimating melt index and density proposed in this study is a neural network based on the input-output data of the polyethylene production plant. Temperature, the level of reactors' bed, the intensity of ethylene mass flow, hydrogen and butene-1, the molar concentration of ethylene, hydrogen and butene-1 are used for the process to establish the neural model. The neural network is taught based on the actual operational data and back-propagation and Levenberg-Marquart techniques. The simulated results indicate that the neural network process model established with three layers (one hidden layer) for forecasting the density and the four layers for the melt index is able to successfully predict those quality properties.

Keywords: polyethylene, polymerization, density, melt index, neural network

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Authors: Beenish Urooj, Ubaid Ullah, Sidra Riasat

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National Testing Service-Pakistan (NTS) is an agency in Pakistan that conducts student success appraisal examinations. In this research paper, we must present a security model for the NTS organization. The security model will depict certain security countermeasures for a better defense against certain types of breaches and system malware. We will provide a security roadmap, which will help the company to execute its further goals to maintain security standards and policies. We also covered multiple aspects in securing the environment of the organization. We introduced the processes, architecture, data classification, auditing approaches, survey responses, data handling, and also training and awareness of risk for the company. The primary contribution is the Risk Survey, based on the maturity model meant to assess and examine employee training and knowledge of risks in the company's activities.

Keywords: NTS, risk assessment, threat factors, security, services

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Authors: Mikhail Gritskevich, Sebastian Hohenstein

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The paper presents the results of a detailed assessment of several modern Reynolds Averaged Navier-Stokes (RANS) turbulence models for prediction of C3X vane film cooling at various injection regimes. Three models are considered, namely the Shear Stress Transport (SST) model, the modification of the SST model accounting for the streamlines curvature (SST-CC), and the Explicit Algebraic Reynolds Stress Model (EARSM). It is shown that all the considered models face with a problem in prediction of the adiabatic effectiveness in the vicinity of the cooling holes; however, accounting for the Reynolds stress anisotropy within the EARSM model noticeably increases the solution accuracy. On the other hand, further downstream all the models provide a reasonable agreement with the experimental data for the adiabatic effectiveness and among the considered models the most accurate results are obtained with the use EARMS.

Keywords: discrete holes film cooling, Reynolds Averaged Navier-Stokes (RANS), Reynolds stress tensor anisotropy, turbulent heat transfer

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Authors: Renu Pattanshetty

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The aim of this narrative review is to highlight the impact of menopause on osteoporosis and weight gain. The review also aims to summarize physiotherapeutic strategies to combat the same.A thorough literature search was conducted using electronic databases like MEDline, PUBmed, Highwire Press, PUBmed Central for English language studies that included search terms like menopause, osteoporosis, obesity, weight gain, exercises, physical activity, physiotherapy strategies from the year 2000 till date. Out of 157 studies that included metanalyses, critical reviews and randomized clinical trials, a total of 84 were selected that met the inclusion criteria. Prevalence of obesity is increasing world - wide and is reaching epidemic proportions even in the menopausal women. Prevalence of abdominal obesity is almost double than that general obesity with rates in the US with 65.5% in women ages 40-59 years and 73.8 in women aged 60 years or more. Physical activities and exercises play a vital role in prevention and treatment of osteoporosis and weight gain related to menopause that aim to boost the general well-being and any symptoms brought about by natural body changes. Endurance exercises lasting about 30 minutes /day for 5 days/ week has shown to decrease weight and prevent weight gain. In addition, strength training with at least 8 exercises of 8-12 repetitions working for whole body and for large muscle groups has shown to result positive outcomes. Hot flashes can be combatted through yogic breathing and relaxation exercises. Prevention of fall strategies and resistance training are key to treat diagnosed cases of osteoporosis related to menopause. One to three sets with five to eight repetitions of four to six weight bearing exercises have shown positive results. Menopause marks an important time for women to evaluate their risk of obesity and osteoporosis. It is known fact that bone benefit from exercises are lost when training is stopped, hence, practicing bone smart habits and strict adherence to recommended physical activity programs are recommended which are enjoyable, safe and effective.

Keywords: menopause, osteoporosis, obesity, weight gain, exercises, physical activity, physiotherapy strategies

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Authors: Marcin Michalak

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Due to the increasing efforts on saving our natural environment a change in the structure of energy resources can be observed - an increasing fraction of a renewable energy sources. In many countries traditional underground coal mining loses its significance but there are still countries, like Poland or Germany, in which the coal based technologies have the greatest fraction in a total energy production. This necessitates to make an effort to limit the costs and negative effects of underground coal mining. The longwall complex is as essential part of the underground coal mining. The safety and the effectiveness of the work is strongly dependent of the diagnostic state of powered roof supports. The building of a useful and reliable diagnostic system requires a lot of data. As the acquisition of a data of any possible operating conditions it is important to have a possibility to generate a demanded artificial working characteristics. In this paper a new approach of modelling a leg pressure in the single unit of powered roof support. The model is a result of the analysis of a typical working cycles.

Keywords: machine modelling, underground mining, coal mining, structure

Procedia PDF Downloads 370

Authors: Eki Farlen, Akas

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Condition assessment of oil-paper-insulated power transformers, particularly of water content, is becoming increasingly important for aged transformers. As insulation ages, it can produce water, which reduces its dielectric strength, accelerates the cellulose ageing process, and causes gas bubbles to form at high temperatures. This paper mainly assesses the life condition of oil-paper insulation system of Inter Bus Transformer (IBT) 30 MVA, 150/30 kV in PT PLN-Substation Jelok that has been operating for 41 years, since 1974. Valuable information about the condition of high voltage insulation may be obtained by measuring its dielectric response. This paper describes in detail the interpretation of Dielectric Response Analysis (DIRANA) measurements and the test result compared to other insulation tests to get deep information for diagnostic, such as Tan delta test, oil characteristic test and Dissolve Gas Analysis (DGA) test. This paper mainly discusses the parameter relationship between moisture content, water content, acidity, oil conductivity and dissipation factor. The result and analysis show that IBT 30 MVA Jelok phase U and W had just been ageing due to high acidity level (>0.2 mgKOH/g) which cause high moisture in cellulose/paper (%) are in wet category about 4.7% and 5% and water content in oil (ppm) about 3.13 ppm and 3.33 ppm at temperature 20°C. High acidity level can make oxidation process and produce water in paper and particle which can decrease the value of Interfacial Tension (IFT) below 22 mN/m (poor category) for both phase U and W. Even if paper insulation of transformer are in wet condition, dissipation factor and capacitance at the same frequency (50 Hz) from both measurement DIRANA test and Tangent delta test give the same result (almost), the results are 0.69% and 0.71% (<1%), it may be acceptable and should not be investigated. The DGA results show that TDCG are in level one (1) condition and there are no found a Key Gases, it means that transformers had no failure during operation like arching, partial discharge and thermal in oil or cellulose.

Keywords: diagnostic, inter-bus transformer, oil-paper insulation, moisture, dissipation factor

Procedia PDF Downloads 280

Authors: Nandu C. Nair, Kamal Bijlani

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This paper proposes a concept-based assessment to track the performance of the students. The idea behind this approach is to map the exam questions with the concepts learned in the course. So at the end of the course, each student will know how well he learned each concept. This system will give a self assessment for the students as well as instructor. By analyzing the score of all students, instructor can decide some concepts need to be teaching again or not. The system’s efficiency is proved using three courses from M-tech program in E-Learning technologies and results show that the concept-wise assessment improved the score in final exam of majority students on various courses.

Keywords: assessment, concept, examination, question, score

Procedia PDF Downloads 474