Search results for: correlation and prediction

Authors: Mane Darbinyan, Lusine Hayrapetyan, Elen Matevosyan

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Artificial Intelligence in Education (AIED) has been created to help students get ready for the workforce, and over the past 25 years, it has grown significantly, offering a variety of technologies to support academic, institutional, and administrative services. However, this is still challenging, especially considering the labor market's rapid change. While choosing a career, people face various obstacles because they do not take into consideration their own preferences, which might lead to many other problems like shifting jobs, work stress, occupational infirmity, reduced productivity, and manual error. Besides preferences, people should evaluate properly their technical and non-technical skills, as well as their personalities. Professional counseling has become a difficult undertaking for counselors due to the wide range of career choices brought on by changing technological trends. It is necessary to close this gap by utilizing technology that makes sophisticated predictions about a person's career goals based on their personality. Hence, there is a need to create an automated model that would help in decision-making based on user inputs. Improving career guidance can be achieved by embedding machine learning into the career consulting ecosystem. There are various systems of career guidance that work based on the same logic, such as the classification of applicants, matching applications with appropriate departments or jobs, making predictions, and providing suitable recommendations. Methodologies like KNN, neural networks, K-means clustering, D-Tree, and many other advanced algorithms are applied in the fields of data and compute some data, which is helpful to predict the right careers. Besides helping users with their career choice, these systems provide numerous opportunities which are very useful while making this hard decision. They help the candidate to recognize where he/she specifically lacks sufficient skills so that the candidate can improve those skills. They are also capable of offering an e-learning platform, taking into account the user's lack of knowledge. Furthermore, users can be provided with details on a particular job, such as the abilities required to excel in that industry.

Keywords: career guidance system, machine learning, career prediction, predictive decision, data mining, technical and non-technical skills

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Authors: Kassa Endalamaw Rewnu

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The variability properties of a quasar sample, spectroscopically complete to magnitude J = 22.0, are investigated on a time baseline of 2 years using three different photometric bands (U, J and F). The original sample was obtained using a combination of different selection criteria: colors, slitless spectroscopy and variability, based on a time baseline of 1 yr. The main goals of this work are two-fold: first, to derive the percentage of variable quasars on a relatively short time baseline; secondly, to search for new quasar candidates missed by the other selection criteria; and, thus, to estimate the completeness of the spectroscopic sample. In order to achieve these goals, we have extracted all the candidate variable objects from a sample of about 1800 stellar or quasi-stellar objects with limiting magnitude J = 22.50 over an area of about 0.50 deg2. We find that > 65% of all the objects selected as possible variables are either confirmed quasars or quasar candidates on the basis of their colors. This percentage increases even further if we exclude from our lists of variable candidates a number of objects equal to that expected on the basis of `contamination' induced by our photometric errors. The percentage of variable quasars in the spectroscopic sample is also high, reaching about 50%. On the basis of these results, we can estimate that the incompleteness of the original spectroscopic sample is < 12%. We conclude that variability analysis of data with small photometric errors can be successfully used as an efficient and independent (or at least auxiliary) selection method in quasar surveys, even when the time baseline is relatively short. Finally, when corrected for the different intrinsic time lags corresponding to a fixed observed time baseline, our data do not show a statistically significant correlation between variability and either absolute luminosity or redshift.

Keywords: nuclear activity, galaxies, active quasars, variability

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Authors: Cheng-Yu Tsai, Wen-Te Liu, Chen-Chen Lo, Yin-Tzu Lin, Kang Lo

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Background: Driving fatigue related to inadequate or disordered sleep accounts for a major percentage of traffic accidents. Obstructive sleep apnea syndrome (OSAS) is a common respiratory disorder during sleep. However, the effects of OSAS severity on driving drowsiness remain unclear. Objective: The aim of this study is to investigate the relationship between OSAS severity and driving fatigue. Methodologies: The physical condition while driving was obtained from the questionnaires to classify the state of driving fatigue. OSAS severity was quantified as the polysomnography, and the mean hourly number of greater than 3% dips in oxygen saturation during examination in a hospital in New Taipei City (Taiwan). The severity of OSAS was diagnosed by the apnea and hypopnea index (AHI) with the American Academy of Sleep Medicine (AASM) guideline. The logistic regression model was used to examine the associations after adjusted age, gender, neck circumstance, waist circumstance, and body mass index (BMI). Results: There were 880 subjects recruited in this study, who had been done polysomnography for evaluating severity for OSAS as well as completed the driver condition questionnaire. 752 subjects were diagnosed with OSA, and 484 subjects had fatigue driving behavior in the past week. Patients diagnosed with OSAS had a 9.42-fold higher odds ratio (p < 0.01, 95% CI = 5.41 – 16.42) of driving drowsiness for cohorts with a normal degree. Conclusion: We observe the considerable correlation between OSAS and driving fatigue. For the purpose of promoting traffic safety, OSAS should be monitored and treated.

Keywords: obstructive sleep apnea syndrome, driving fatigue, polysomnography, apnea and hypopnea index

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Authors: Jumel Christian P. Nicha, Severino G. Salmo III

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This study investigated the concentration of heavy metals (HM) in mangrove sediments of Lake Uacon, Zambales, Philippines. The relationship among the studied HM (Cr, Ni, Pb, Cu, Cd, Fe) and the mangrove vegetation and sediment characteristics were assessed. Fourteen sampling plots were designated across the lake (10 vegetated and 4 un-vegetated) based on distance from the mining effluents. In each plot, three sediment cores were collected at 20 cm depth. Among the dominant mangrove species recorded were (in order of dominance): Sonneratia alba, Rhizophora stylosa, Avicennia marina, Excoecaria agallocha and Bruguiera gymnorrhiza. Sediment samples were digested with aqua regia, and the HM concentrations were quantified using Atomic Absorption Spectroscopy (AAS). Results showed that HM concentrations were higher in the vegetated plots as compared to the un-vegetated sites. Vegetated sites had high Ni (mean: 881.71 mg/kg) and Cr (mean: 776.36 mg/kg) that exceeded the threshold values (cf. by the United States Environmental Protection Agency; USEPA). Fe, Pb, Cu and Cd had a mean concentration of 2597.92 mg/kg, 40.94 mg/kg, 36.81 mg/kg and 2.22 mg/kg respectively. Vegetation variables were not significantly correlated with HM concentration. However, the HM concentration was significantly correlated with sediment variables particularly pH, redox, particle size, nitrogen, phosphorus, moisture and organic matter contents. The Pollution Load Index (PLI) indicated moderate to high pollution in the lake. Risk assessment and management should be designed in order to mitigate the ecological risk posed by HM. The need of a regular monitoring scheme for lake and mangrove rehabilitation programs and management should be designed.

Keywords: heavy metals, mangrove vegetation, mining, Philippines, sediment

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Authors: Berkan Ural, Arif Eser, Sinan Apaydin

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Medical image processing is generally become a challenging task nowadays. Indeed, processing of brain MRI images is one of the difficult parts of this area. This study proposes a hybrid well-defined approach which is consisted from tumor detection, extraction and analyzing steps. This approach is mainly consisted from a computer aided diagnostics system for identifying and detecting the tumor formation in any region of the brain and this system is commonly used for early prediction of brain tumor using advanced image processing and probabilistic neural network methods, respectively. For this approach, generally, some advanced noise removal functions, image processing methods such as automatic segmentation and morphological operations are used to detect the brain tumor boundaries and to obtain the important feature parameters of the tumor region. All stages of the approach are done specifically with using MATLAB software. Generally, for this approach, firstly tumor is successfully detected and the tumor area is contoured with a specific colored circle by the computer aided diagnostics program. Then, the tumor is segmented and some morphological processes are achieved to increase the visibility of the tumor area. Moreover, while this process continues, the tumor area and important shape based features are also calculated. Finally, with using the probabilistic neural network method and with using some advanced classification steps, tumor area and the type of the tumor are clearly obtained. Also, the future aim of this study is to detect the severity of lesions through classes of brain tumor which is achieved through advanced multi classification and neural network stages and creating a user friendly environment using GUI in MATLAB. In the experimental part of the study, generally, 100 images are used to train the diagnostics system and 100 out of sample images are also used to test and to check the whole results. The preliminary results demonstrate the high classification accuracy for the neural network structure. Finally, according to the results, this situation also motivates us to extend this framework to detect and localize the tumors in the other organs.

Keywords: image processing algorithms, magnetic resonance imaging, neural network, pattern recognition

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Authors: Jarrod Sio Jyh Lih

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This paper discusses the factors contributing to student achievement in literacy and numeracy in primary schools within Sibu division. The study involved 694 level 1 primary schoolteachers. Using descriptive statistics, the study observed high levels of practice for teacher efficacy, instructional leadership and professional learning communities (PLCs). The differences between gender, teaching experience and academic qualification were analyzed using the t-test and one-way analysis of variance (ANOVA). The study reported significant differences in respondent perceptions based on teaching experience vis-à-vis teacher efficacy. Here, the post hoc Tukey test revealed that efficaciousness grows with experience. A correlation test observed positive and significant correlations between all independent variables. Binary logistic regression was applied to predict the independent variables’ influence on student achievement. The findings revealed that a dimension of instructional leadership – ‘monitoring student progress’ - emerged as the best predictor of student achievement for literacy and numeracy. The result indicated the students were more than 4 times more likely to achieve the national key performance index for both literacy and numeracy when student progress was monitored. In conclusion, ‘monitoring student progress’ had a positive influence on students’ achievement for literacy and numeracy, hence making it a possible course of action for school heads. However, more comprehensive studies are needed to ascertain its consistency within the context of Malaysia.

Keywords: efficacy, instructional, literacy, numeracy

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Authors: Martin Plener

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Developmental and democratization research has a long tradition of focusing on the relationship between democratization and economic development. However, recent studies have shown that economic development is not adequate to measure the actual living conditions of civilian people. In consequence, it is unclear if a democratization process helps to improve people’s quality of life. This work addresses this issue by investigating the influence of democratization on the Human Development Index (HDI) created by the United Nations. The main objective is to study the relationship between democracy and human development and whether democratization positively impacts the living conditions of the population over time. The main mechanism which supports a positive impact is that democratic structures promote participation and political involvement of people from all social classes resulting in a better articulation of interests and thus accountability to the government. To study this issue, a panel regression with Fixed-Effects is conducted. By that, it is examined if democracy has a positive impact on the HDI (Hypothesis 1) and secondly if the same effect weakens in more developed democracies compared to less developed democracies (Hypothesis 2). The results do not reveal a direct positive relationship between the democratization of a country and its development of the HDI, not supporting H1 which denies the first hypothesis. In contrast to the assumption of H2, the effect of democratization on human development seems to be negatively correlated in countries in which democracy is barely developed. Therefore, both hypotheses must be discarded. The results indicate rather a positive correlation between economic development on human development. Therefore, the impact of democracy on the well-being of countries’ citizens needs to be reinvestigated in order to create a better understanding of how improved human development can be achieved.

Keywords: democracy, human development, modernization theory, HDI, TSCS

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Authors: Areej Javaid, Nishat Fatima, Mehwish Naseer

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There is a tremendous use of biofertilizers in agriculture to increase crop productivity. Pakistan spends a huge amount on the purchase of synthetic fertilizers every year. The use of natural compounds to harness crop productivity is the major area of interest nowadays due to being safe for human health and the environment as well. Legumes have the intrinsic quality to enrich the nutrient status of soil because of the presence of nitrogen fixation bacteria on nodules. This research determined the effect of biofertilizer on nodulation attributes and yield of the pea plant. Seeds of pea varieties were treated with a slurry of biofertilizer prepared in a 10% sugar solution just before seed sowing. The impact of biofertilizer on different parameters of growth, yield and nodulation was observed. Analysis of variance showed that plant height, days to flowering, number of nodes, days to first pod, root length and plant height exhibited significant genetic variation. All the yield parameters, including the number of pods per plant, number of seeds per pod, seed fresh and dry weight showed significant results under treatment. Among nodulation parameters, nodule number responded positively to biofertilizer treatment. Genotypes 2001-40 showed better performance followed by 2001-20 and LINA-PAK in all the parameters, whereas 2001-40 and 2001-20 performed well in nodulation and yield parameters. Consequently, seed treatment with biofertilizer before sowing is recommended to obtain higher crop yield.

Keywords: biological nitrogen fixation, correlation analysis, quantitative inheritance, varietal responses

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Authors: Ibrahim Auwal

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This study focuses on senior secondary education towards the development of younger generation in general terms, and specifically for the enhancement of senior secondary school principals. Investigation was made to correlate between principals’ application of basic principles of educational administration and principals’ productivity in senior secondary schools in Kano State. The instrument used to collect relevant data was self designed Observation Inventory for School Principals (OISP). The observation inventory items were scrutinized by experts from the School of Education Federal College of Education Kano to ascertain the contents validity, and the reliability coefficient was 0.83. Using purposive sampling technique, 30 schools were chosen from 85 senior secondary schools in Kano state and 30 principals were deliberately sampled due to their small number. Pearson Product Moment Correlation (r) Coefficient was used to test the hypothesis generated for the study. The results of the analysis showed that principals’ application of basic principles of educational administration was significantly correlated with principals’ productivity and it promote the performance of the students. Based on the findings, it was recommended that, government should in as much as possible encourage school principals to obtain degrees in relevant and specialized areas in education specifically educational administration and planning so as to get all the necessary knowledge and skills of leader ship procedures that will definitely promote teachers morale, improve students’ academic performance and enhances principals’ productivity in senior secondary schools in Kano State.

Keywords: principles of educational administration, principals of senior secondary schools, Kano, educational sciences

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Authors: S. Aberkane, N. Djabali, S. Fafi, A. Baghezza

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Chronic illnesses affect many Algerians. It is possible to investigate the impact of illness representations and coping on quality of life and whether illness representations are indirectly associated with quality of life through their influence on coping. This study aims at investigating the relationship between illness perception, coping strategies and quality of life with chronic illness. Illness perceptions are indirectly associated with the quality of life through their influence on coping mediation. A sample of 316 participants with chronic illness living in the region of Batna, Algeria, has been adopted in this study. A correlation statistical analysis is used to determine the relationship between illness perception, coping strategies, and quality of life. Multiple regression analysis was employed to highlight the predictive ability of the dimensions of illness perception and coping strategies on the dependent variables of quality of life, where mediation analysis is considered in the exploration of the indirect effect significance of the mediator. This study provides insights about the relationship between illness perception, coping strategies and quality of life in the considered sample (r = 0.39, p < 0.01). Therefore, it proves that there is an effect of illness identity perception, external and medical attributions related to emotional role, physical functioning, and mental health perceived, and these were fully mediated by the asking for assistance (c’= 0.04, p < 0.05), the guarding (c’= 0.00, p < 0.05), and the task persistence strategy (c’= 0.05, p < 0.05). The findings imply partial support for the common-sense model of illness representations in a chronic illness population. Directions for future research are highlighted, as well as implications for psychotherapeutic interventions which target unhelpful beliefs and maladaptive coping strategies (e.g., cognitive behavioral therapy).

Keywords: chronic illness, coping, illness perception, quality of life, self- regulation model

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Authors: Ochuko K. Overen, Golden Makaka, Edson L. Meyer, Sampson Mamphweli

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Low-cost housing provided for people with small incomes in South Africa are characterized by poor thermal performance. This is due to inferior craftsmanship with no regard to energy efficient design during the building process. On average, South African households spend 14% of their total monthly income on energy needs, in particular space heating; which is higher than the international benchmark of 10% for energy poverty. Adopting energy efficient passive solar design strategies and superior thermal building materials can create a stable thermal comfort environment indoors. Thereby, reducing energy consumption for space heating. The aim of this study is to analyse the thermal behaviour of a low-cost house integrated with passive solar design features. A low-cost passive solar house with superstructure fly ash brick walls was designed and constructed in Somerset East, South Africa. Indoor and outdoor meteorological parameters of the house were monitored for a period of one year. The ASTM E741-11 Standard was adopted to perform ventilation test in the house. In summer, the house was found to be thermally comfortable for 66% of the period monitored, while for winter it was about 79%. The ventilation heat flow rate of the windows and doors were found to be 140 J/s and 68 J/s, respectively. Air leakage through cracks and openings in the building envelope was 0.16 m3/m2h with a corresponding ventilation heat flow rate of 24 J/s. The indoor carbon dioxide concentration monitored overnight was found to be 0.248%, which is less than the maximum range limit of 0.500%. The prediction percentage dissatisfaction of the house shows that 86% of the occupants will express the thermal satisfaction of the indoor environment. With a good operation of the house, it can create a well-ventilated, thermal comfortable and nature luminous indoor environment for the occupants. Incorporating passive solar design in low-cost housing can be one of the long and immediate solutions to the energy crisis facing South Africa.

Keywords: energy efficiency, low-cost housing, passive solar design, rural development, thermal comfort

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Authors: Edokpa Idemudia Waziri, Salisu S. Umar

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The Hotellng’s T^2 is a well-known statistic for detecting a shift in the mean vector of a multivariate normal distribution. Control charts based on T have been widely used in statistical process control for monitoring a multivariate process. Although it is a powerful tool, the T statistic is deficient when the shift to be detected in the mean vector of a multivariate process is small and consistent. The Multivariate Exponentially Weighted Moving Average (MEWMA) control chart is one of the control statistics used to overcome the drawback of the Hotellng’s T statistic. In this paper, the probability distribution of the Average Run Length (ARL) of the MEWMA control chart when the quality characteristics exhibit substantial cross correlation and when the process is in-control and out-of-control was derived using the Markov Chain algorithm. The derivation of the probability functions and the moments of the run length distribution were also obtained and they were consistent with some existing results for the in-control and out-of-control situation. By simulation process, the procedure identified a class of ARL for the MEWMA control when the process is in-control and out-of-control. From our study, it was observed that the MEWMA scheme is quite adequate for detecting a small shift and a good way to improve the quality of goods and services in a multivariate situation. It was also observed that as the in-control average run length ARL0¬ or the number of variables (p) increases, the optimum value of the ARL0pt increases asymptotically and as the magnitude of the shift σ increases, the optimal ARLopt decreases. Finally, we use the example from the literature to illustrate our method and demonstrate its efficiency.

Keywords: average run length, markov chain, multivariate exponentially weighted moving average, optimal smoothing parameter

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Authors: Sung Yong Kim, Byung Joo Song

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Background: Circulating 25-hydroxyvitamin D (25(OH)D) levels has been considered to be inversely related to breast cancer development, recurrence risk, and mortality. Mean vitamin D levels in Korean population is lower than western countries due to higher incidence of lactose intolerance and lower exposure to sunlight. The purpose of this study was to assess incidence of 25(OH)D deficiency at diagnosis and after adjuvant chemotherapy and to investigate the correlation serum 25(OH)D levels with clinicopathologic features. Methods: From December 2011 to October 2012, 280 breast cancer patients seen at a single tertiary cancer center were enrolled. Serum 25(OH)D was measured at the time of surgery and after completion of adjuvant chemotherapy. Statistical analyses used chi-square test, Fisher's exact test, t-test, and ANOVA. Results: Mean serum 25(OH)D was 18.5 ng/ml. The 25(OH)D levels were deficient (<20 ng/ml) in 190 patients (67.9%), insufficient (20-29 ng/ml) in 51 patients(18.2%), and sufficient (30-150 ng/ml) in 39 patients(13.9%). A notable decrease in 25(OH)D concentration was observed(p<0.001) after chemotherapy but was not related to chemotherapy regimens. It was found significant lower 25(OH)D levels at winter season(from October to March, p=0.030). Subjects with invasive carcinoma (IDC or ILC) had significantly lower circulating levels of 25(OH)D than those with ductal carcinoma in situ(DCIS) (p=0.010). Patients with larger tumor size tends to have lower serum 25(OH)D but there were no statistical significance. Conclusions: Most of the breast cancer patients showed deficient or insufficient serum 25(OH)D concentration. Incidence of vitamin D deficiency was higher in invasive carcinoma than DCIS. Serum 25(OH)D levels were decreased after chemotherapy. Consideration should be given to the supplement of vitamin D to those patients.

Keywords: breast neoplasms, vitamin D, Korean population, breast cancer

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Authors: Ashit Syngle, Nidhi Garg, Pawan Krishan

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Objective: Bone marrow derived stem cells, endothelial progenitor cells (EPCs), protect against atherosclerotic vascular damage. However, EPCs are depleted in AS and contribute to the enhanced cardiovascular risk. Statins have a protective effect in CAD and diabetes by enhancing the proliferation, migration and survival of EPCs. Therapeutic potential of augmenting EPCs to treat the heightened cardiovascular risk of AS has not yet been exploited. We aimed to investigate the effect of rosuvastatin on EPCs population and inflammation in AS. Methods: 30 AS patients were randomized to receive 6 months of treatment with rosuvastatin (10 mg/day, n=15) and placebo (n=15) as an adjunct to existing stable anti-rheumatic drugs. EPCs (CD34+/CD133+) were quantified by Flow Cytometry. Inflammatory measures (BASDAI, BASFI, CRP and ESR), pro-inflammatory cytokines (TNF-α, IL-6 and IL-1) and lipids were measured at baseline and after treatment. Results: At baseline, inflammatory measures and pro-inflammatory cytokines were elevated and EPCs depleted among both groups. EPCs increased significantly (p < 0.01) after treatment with rosuvastatin. At 6 months, BASDAI, BASFI, ESR, CRP, TNF-α, and IL-6 improved significantly in rosuvastatin group. Significant negative correlation was observed between EPCs and BASDAI, CRP and IL-6 after rosuvastatin treatment. Conclusion: First study to show that rosuvastatin augments EPCs population in AS. This defines a novel mechanism of rosuvastatin treatment in AS: the augmentation of EPCs with improvement in proinflammatory cytokines and inflammatory disease activity. The augmentation of EPCs by rosuvastatin may provide a novel strategy to prevent cardiovascular events in AS.

Keywords: ankylosing spondylitis, Endothelial Progenitor Cells, inflammation, pro-inflammatory cytokines, rosuvastatin

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Authors: Chien-Song Chyang, Wei-Chih Wang

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For the incineration process, the inhibition of dioxin formation is an important issue. Many investigations indicate that adding sulfur compounds in the combustion process can be an effectively inhibition for the dioxin formation. In the process, the ratio of sulfur-to-chlorine plays an important role for the reduction efficiency of dioxin formation. Ca-base sorbent is also a common used for the acid gas removing. Moreover, that is also the indirectly way for dioxin inhibition. Although sulfur and calcium can reduce the dioxin formation, it still have some confusion exists between these additives. To understand and clarify the relationship between the dioxin and simultaneous addition of sulfur and calcium are presented in this study. The experimental data conducted in a pilot scale fluidized bed combustion system at various operating conditions are analysis comprehensively. The focus is on the dioxin of fly ash in this study. The experimental data in this study showed that the PCDD/Fs concentration in the fly ash collected from the baghouse is increased slightly as the simultaneous addition of sulfur and calcium. This work described the CO concentration with the addition of sulfur and calcium at the freeboard temperature from 800°C to 900°C, which is raised by the fuel complexity. The positive correlation exists between the dioxin concentration and CO concentration and carbon contained in the fly ash.. At the same sulfur/chlorine ratio, the toxic equivalent quantity (TEQ) can be reduced by increasing the actual concentration of sulfur and calcium. The homologue profiles showed that the P₅CDD and P₅CDF were the two major sources for the toxicity of dioxin. 2,3,7,8-TCDD and 2,3,7,8-TCDF reduced by the addition of pyrite and hydrated lime. The experimental results showed that the trend of PCDD/Fs concentration in the fly ash was different by the different sulfur/chlorine ratio with the addition of sulfur at 800°C.

Keywords: reduction of dioxin emissions, sulfur-to-chlorine ratio, de-chlorination, Ca-based sorbent

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Authors: Jeni A. Popescu, Sorin G. Tomescu, Valeriu A. Vilag

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The paper focuses on the potential methods of increasing the performance of a microturbine by combining additional elements available for utilization in a cogeneration plant. The activity is carried out within the framework of a project aiming to develop, manufacture and test a microturbine functional model with high potential in energetic industry utilization. The main goal of the analysis is to determine the parameters of the fluid flow passing through each section of the turbine, based on limited data available in literature for the focus output power range or provided by experimental studies, starting from a reference cycle, and considering different cycle options, including simple, intercooled and recuperated options, in order to optimize a small cogeneration plant operation. The studied configurations operate under the same initial thermodynamic conditions and are based on a series of assumptions, in terms of individual performance of the components, pressure/velocity losses, compression ratios, and efficiencies. The thermodynamic analysis evaluates the expected performance of the microturbine cycle, while providing a series of input data and limitations to be included in the development of the experimental plan. To simplify the calculations and to allow a clear estimation of the effect of heat transfer between fluids, the working fluid for all the thermodynamic evolutions is, initially, air, the combustion being modelled by simple heat addition to the system. The theoretical results, along with preliminary experimental results are presented, aiming for a correlation in terms of microturbine performance.

Keywords: cogeneration, microturbine, performance, thermodynamic analysis

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Authors: Radin Siti Aishah Radin A Rahman, Norasmah Othman, Zaidatol Akmaliah Lope Pihie, Hariyaty Ab. Wahid

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The recent instability in economy was found to be influencing the situation in Malaysia whether directly or indirectly. Taking that into consideration, the government needs to find the best approach to balance its citizen’s socio-economic strata level urgently. Through education platform is among the efforts planned and acted upon for the purpose of balancing the effects of the influence, through the exposure of social entrepreneurial activity towards youth especially those in higher institution level. Armed with knowledge and skills that they gained, with the support by entrepreneurial culture and environment while in campus; indirectly, the students will lean more on making social entrepreneurship as a career option when they graduate. Following the issues of marketability and workability of current graduates that are becoming dire, research involving how far the willingness of student to create social innovation that contribute to the society without focusing solely on personal gain is relevant enough to be conducted. With that, this research is conducted with the purpose of identifying the level of entrepreneurial intention and social entrepreneurship among higher institution students in Malaysia. Stratified random sampling involves 355 undergraduate students from five public universities had been made as research respondents and data were collected through surveys. The data was then analyzed descriptively using min score and standard deviation. The study found that the entrepreneurial intention of higher education students are on moderate level, however it is the contrary for social entrepreneurship activities, where it was shown on a high level. This means that while the students only have moderate level of willingness to be a social entrepreneur, they are very committed to created social innovation through the social entrepreneurship activities conducted. The implication from this study can be contributed towards the higher institution authorities in prediction the tendency of student in becoming social entrepreneurs. Thus, the opportunities and facilities for realizing the courses related to social entrepreneurship must be created expansively so that the vision of creating as many social entrepreneurs as possible can be achieved.

Keywords: entrepreneurial intention, higher education institutions (HEIs), social entrepreneurship, social entrepreneurial activity, gender

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Authors: Chen Zhang, Nan Chen

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High-dimensional process monitoring becomes increasingly important in many application domains, where usually the process distribution is unknown and much more complicated than the normal distribution, and the between-stream correlation can not be neglected. However, since the process dimension is generally much bigger than the reference sample size, most traditional nonparametric multivariate control charts fail in high-dimensional cases due to the curse of dimensionality. Furthermore, when the process goes out of control, the influenced variables are quite sparse compared with the whole dimension, which increases the detection difficulty. Targeting at these issues, this paper proposes a new nonparametric monitoring scheme for high-dimensional processes. This scheme first projects the high-dimensional process into several subprocesses using random projections for dimension reduction. Then, for every subprocess with the dimension much smaller than the reference sample size, a local nonparametric control chart is constructed based on the spatial rank test to detect changes in this subprocess. Finally, the results of all the local charts are fused together for decision. Furthermore, after an out-of-control (OC) alarm is triggered, a diagnostic framework is proposed. using the square-root LASSO. Numerical studies demonstrate that the chart has satisfactory detection power for sparse OC changes and robust performance for non-normally distributed data, The diagnostic framework is also effective to identify truly changed variables. Finally, a real-data example is presented to demonstrate the application of the proposed method.

Keywords: random projection, high-dimensional process control, spatial rank, sequential change detection

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Authors: Javier Muro, Anja Linstadter, Florian Manner, Lisa Schwarz, Stephan Wollauer, Paul Magdon, Gohar Ghazaryan, Olena Dubovyk

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Monitoring the trade-off between biomass production and biodiversity in grasslands is critical to evaluate the effects of management practices across environmental gradients. New generations of remote sensing sensors and machine learning approaches can model grasslands’ characteristics with varying accuracies. However, studies often fail to cover a sufficiently broad range of environmental conditions, and evidence suggests that prediction models might be case specific. In this study, biomass production and biodiversity indices (species richness and Fishers’ α) are modeled in 150 grassland plots for three sites across Germany. These sites represent a North-South gradient and are characterized by distinct soil types, topographic properties, climatic conditions, and management intensities. Predictors used are derived from Sentinel-1 & 2 and a set of topoedaphic variables. The transferability of the models is tested by training and validating at different sites. The performance of feed-forward deep neural networks (DNN) is compared to a random forest algorithm. While biomass predictions across gradients and sites were acceptable (r2 0.5), predictions of biodiversity indices were poor (r2 0.14). DNN showed higher generalization capacity than random forest when predicting biomass across gradients and sites (relative root mean squared error of 0.5 for DNN vs. 0.85 for random forest). DNN also achieved high performance when using the Sentinel-2 surface reflectance data rather than different combinations of spectral indices, Sentinel-1 data, or topoedaphic variables, simplifying dimensionality. This study demonstrates the necessity of training biomass and biodiversity models using a broad range of environmental conditions and ensuring spatial independence to have realistic and transferable models where plot level information can be upscaled to landscape scale.

Keywords: ecosystem services, grassland management, machine learning, remote sensing

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Authors: Kheira Hamaida, Mohamed Salah Halati

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In this current paper, our aim work is to link as possible the obtained simulation results and the other experimental ones, just focusing on the electronic and optical properties of ZnSe. The predictive spectra of the total and partial densities of states using the Full Potential Linearized/Augmented Plane Wave method with the newly Tran-Blaha (TB) modified Becke-Johnson (mBJ) exchange-correlation potential (EXC). So the upper valence energy (UVE) levels contain the relative contribution of Se-(4p and 3d) states with considerable contribution from the electrons of Zn-2s orbital. The dielectric function of w-ZnSe, with its two parts, appears with a noticeable anisotropy character. The microscopic origins of the electronic states that are responsible for the observed peaks in the spectrum are determined through the decomposition of the spectrum to the individual contributions of the electronic transitions between the pairs of bands, where Vi is an occupied state in the valence band, and Ci is an unoccupied state in the conduction band. X-PES (X Ray-Photo Electron Spectroscopy) is an important technique used to probe the homogeneity, stoichiometry, and purity state of the title compound. In order to check the electron transitions derived from simulations and the others from Reflected Electron Energy Loss Spectroscopy (REELS) technique which was of great sensitivity, is used to determine the interband electronic transitions. In the optical window (Eg), all the electron energy states created were also determined through the specific gaussian deconvolution of the photoluminescence spectrum (PLS) that probed under a room temperature (RT).

Keywords: spectroscopy, WIEN2K, IIB-VIA semiconductors, dielectric function

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Authors: Tigabu Dagne Akal

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While advances in computer and communications technology have made the network ubiquitous, they have also rendered networked systems vulnerable to malicious attacks devised from a distance. These attacks or intrusions start with attackers infiltrating a network through a vulnerable host and then launching further attacks on the local network or Intranet. Nowadays, system administrators and network professionals can attempt to prevent such attacks by developing intrusion detection tools and systems using data mining technology. In this study, the experiments were conducted following the Knowledge Discovery in Database Process Model. The Knowledge Discovery in Database Process Model starts from selection of the datasets. The dataset used in this study has been taken from Massachusetts Institute of Technology Lincoln Laboratory. After taking the data, it has been pre-processed. The major pre-processing activities include fill in missed values, remove outliers; resolve inconsistencies, integration of data that contains both labelled and unlabelled datasets, dimensionality reduction, size reduction and data transformation activity like discretization tasks were done for this study. A total of 21,533 intrusion records are used for training the models. For validating the performance of the selected model a separate 3,397 records are used as a testing set. For building a predictive model for intrusion detection J48 decision tree and the Naïve Bayes algorithms have been tested as a classification approach for both with and without feature selection approaches. The model that was created using 10-fold cross validation using the J48 decision tree algorithm with the default parameter values showed the best classification accuracy. The model has a prediction accuracy of 96.11% on the training datasets and 93.2% on the test dataset to classify the new instances as normal, DOS, U2R, R2L and probe classes. The findings of this study have shown that the data mining methods generates interesting rules that are crucial for intrusion detection and prevention in the networking industry. Future research directions are forwarded to come up an applicable system in the area of the study.

Keywords: intrusion detection, data mining, computer science, data mining

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Authors: Jefri Draup, Antoine Ambard, Chi-Toan Nguyen

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Zirconium alloys exhibit solid-state phase transformations under thermal loading. These can lead to a significant evolution of the microstructure and associated mechanical properties of materials used in nuclear fuel cladding structures. Therefore, the ability to capture effects of phase transformation on the material constitutive behavior is of interest during conditions of severe transient thermal loading. Whilst typical Avrami, or Johnson-Mehl-Avrami-Kolmogorov (JMAK), type models for phase transformations have been shown to have a good correlation with the behavior of Zircaloy-4 under constant heating rates, the effects of variable and fast heating rates are not fully explored. The present study utilises the results of in-situ high energy synchrotron X-ray diffraction (SXRD) measurements in order to validate the phase transformation models for Zircaloy-4 under fast variable heating rates. These models are used to assess the performance of fuel cladding structures under loss of coolant accident (LOCA) scenarios. The results indicate that simple Avrami type models can provide a reasonable indication of the phase distribution in experimental test specimens under variable fast thermal loading. However, the accuracy of these models deteriorates under the faster heating regimes, i.e., 100Cs⁻¹. The studies highlight areas for improvement of simple Avrami type models, such as the inclusion of temperature rate dependence of the JMAK n-exponent.

Keywords: accident, fuel, modelling, zirconium

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Authors: Georgiana Onicescu, Yuqian Shen

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Due to the complex nature of geo-referenced data, multicollinearity of the risk factors in public health spatial studies is a commonly encountered issue, which leads to low parameter estimation accuracy because it inflates the variance in the regression analysis. To address this issue, we proposed a two-stage variable selection method by extending the least absolute shrinkage and selection operator (Lasso) to the Bayesian spatial setting, investigating the impact of risk factors to health outcomes. Specifically, in stage I, we performed the variable selection using Bayesian Lasso and several other variable selection approaches. Then, in stage II, we performed the model selection with only the selected variables from stage I and compared again the methods. To evaluate the performance of the two-stage variable selection methods, we conducted a simulation study with different distributions for the risk factors, using geo-referenced count data as the outcome and Michigan as the research region. We considered the cases when all candidate risk factors are independently normally distributed, or follow a multivariate normal distribution with different correlation levels. Two other Bayesian variable selection methods, Binary indicator, and the combination of Binary indicator and Lasso were considered and compared as alternative methods. The simulation results indicated that the proposed two-stage Bayesian Lasso variable selection method has the best performance for both independent and dependent cases considered. When compared with the one-stage approach, and the other two alternative methods, the two-stage Bayesian Lasso approach provides the highest estimation accuracy in all scenarios considered.

Keywords: Lasso, Bayesian analysis, spatial analysis, variable selection

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Authors: O. B. Oriolowo, O. J. John

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Empirical findings have shown insects to be nutritious and good source of food for man. However, human food preferences are not only determined by nutritional values of food consumed but, more importantly, by sociology and economic pressure. This study examined the interrelation between science and sociology in sustaining the acceptance of entomophagy among college students to combat food insecurity. A twenty items five Likert scale, College Students Entomophagy Questionnaire (CSEQ), was used to elucidate information from the respondents. The reliability coefficient was obtained to be 0.91 using Spearman-Brown Prophecy formula. Three research questions and three hypotheses were raised. Also, quantitative nutritional analysis of few insects and some established conventional protein sources were undertaking in order to compare their nutritional status. The data collected were analyzed using descriptive statistics of percentages and inferential statistics of correlation and Analysis of Variance (ANOVA). The results obtained showed that entomophagy has cultural heritage among different tribes in Nigeria and is an acceptable practice; it cuts across every social stratum and is practiced among both major religions. Moreover, insects compared favourably in term of nutrient contents when compared with the conventional animal protein sources analyzed. However, there is a gradual decline in the practice of entomophagy among students, which may be attributed to the influence of western civilization. This study, therefore, recommended an intensification of research and enlightenment of people on the usefulness of entomophagy so as to preserve its cultural heritage as well as boost human food security.

Keywords: entomophagy, food security, malnutrition, poverty alleviation, sociology

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Authors: Alla Tvardovskaya

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The family of a child with disabilities is an important mechanism of socialization. The relationship of mother and child with developmental difficulties is a significant predictor of the emergence, development and interiorization of various forms of mental activity. Complex impairments of the child form nonconstructive maternal attitude and destructive behavior strategies that complicate the dyadic relationship ‘mother-child’. The study of psychological characteristics of mother's personality was conducted within four years, and adaptive abilities of a child with a complex disorder were evaluated as well. 25 diads (25 mothers and 25 preschool children aged between 4-7 years with complex developmental disorders) took part in the study. Typological features of mothers rearing deafblind preschoolers are described. Constructive and non-constructive types of mothers’ attitude to a pre-school child with complex disorders are specified. The research shows that mothers of deafblind children are more depressed, they are engaged in children’s rearing more, and at the same time they experience difficulties to control negative emotions towards children or demonstrate impulsive behavior with a high level of anxiety. The correlation analysis of relationships between Vineland scales and the dominant type of mothers’ attitude to a child shows the presence of both general and specific links. Adaptive profile analysis of a child with complex disabilities allows to plan specific ways to increase their adaptation by developing a dyadic constructive relationship system. Techniques to develop constructive parental attitudes toward the child are proposed.

Keywords: adaptive behavior, complex disorder, constructive maternal attitude, deaf-blindness, pre-school child

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Authors: G. Murtaza, H. Faiza, M. Rafiq, S. Gul, F. Raza, Sarwat Anjum

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Our objective was to investigate whether and how extensively there is a correlation between aging in men, gonadotropin hormone regulation, and a decline in sperm parameters and whether it is possible to identify an age limit beyond which the decrease in sperm feature and hormonal regulation reaches statistical significance. A total of one hundred and twenty men (age: 20–50 years) were divided into two groups; each group contained 60 males (Group A with a young age of 20–35 years and Group B with an older age of 36–50 years) who visited the Center for Reproductive Medicine (CRM) in Peshawar General Hospital (PGH) Peshawar, Pakistan. Clinical assessment and sperm analysis were investigated. Hormone testing and semen analysis were carried out in accordance with World Health Organization (WHO) guidelines. Hormone tests, sperm morphology, and the total motile spermatozoa count (TMS) were computed. SPSS 20.0 (SPSS Inc., Chicago, IL, USA) was used for the statistical analysis. It was observed that the testosterone levels in Group A (mean = 3.770) and Group B (mean = 3.995) were comparable, with a significant P-value <0.005 in both age groups. Furthermore, similar levels are shown by follicle-stimulating hormone (FSH) (Group A mean = 19.73, Group B mean = 15.64) and luteinizing hormone (LH) (Group A mean = 12.25, Group B mean = 11.93) in both groups, with a significant P = <0.005. Sperm concentrations were most similar in Group A, with a mean of 4.44, and in Group B, with a mean of 4.42 and a significant P value of 0.005 in both groups. Additionally, it was discovered that sperm motility was higher in Group A, with a mean of 22.40 and a P-value of 0.052, which was non-significant when compared to Group B. Morphological differences were also observed in both age groups. This research found that advancing in male age does not affect sex hormone regulation; in contrast, the fraction of motile and morphologically normal spermatozoa decreases as male age increases, with the strongest evidence being when the age exceeds 40 years. To clarify the causes and clinical implications of these correlations, more research is necessary.

Keywords: gonadotropins, motility, spermatozoa, testosterone

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Authors: Junaid Mahmood Alam, Howarh Humaira Ali, Ishrat Sultana

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Long term irregularity in the glycemic state, especially in Type 2 diabetes mellitus (T2DM) patients, depicted by higher levels of HbA1c, is noted to be correlated with the development of microalbuminuria. The aim of the current study is to investigate the association of urinary microalbumin with HbA1c and with duration of diabetes mellitus in selected male and female T2DM patients. This cross-sectional study was carried out in a total of 70 patients, thirty-five each male and females with diagnosed T2DM, within the age group of 35-60 years. Biochemical parameters of urea, creatinine, urinary microalbumin, HbA1c, fasting blood glucose and post- parendial blood glucose were determined by standard methods. Data was statistically examined by student’s t-test and Pearson’s correlation. Results showed that comparison of healthy control subjects with both male and female T2DM patients depicted significantly elevated levels of all parameters in (P < 0.05 to P < 0.001). Comparison of duration of T2DM with the existence of urinary microalbumin was moderately significant (P < 0.05) when duration was less than 4 years, significant (P < 0.01) with duration of 4-6 years and markedly significant (P < 0.001) with duration of more than 6 years. It is concluded that in male and female T2DM patients, duration of DM as well as poor glycemic control, depicted by higher levels of HbA1c is significantly correlated with elevated levels of urinary microalbumin.

Keywords: type 2 diabetes mellitus, glycosylated hemoglobin, urinary microalbumin, T2DM, HbA1c

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Authors: Umaiza Bashir, Ushna Farukh

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The present study examined the perspective of school students regarding teacher’s behavioral pattern during a teaching in classroom and its influence on the students’ socialization particularly forming peer relationships with the development of emotional, behavioral problems in school children. To study these dimension of teacher-student classroom relationship, 210 school children (105 girls and 105 boys) within the age range of 14 to 18 years were taken from the government, private schools. The cross-sectional research design was used in which stratified random sampling was done. Teacher-student interaction scale was used to assess the teacher-student relationship in the classroom, which had two factors such as positive and negative interaction. Peer relationship scale was administered to investigate the socialization of students, and School Children Problem Scale was also given to the participants to explore their emotional, behavioral issues. The analysis of Pearson correlation showed that there is a significant positive relationship between negative teacher-student interaction and student’s emotional-behavioral as well as social problems. Another analysis of t-test revealed that boys perceived more positive interaction with teachers than girls (p < 0.01). Girls showed more emotional behavioral problems than boys (p < 0.001) Linear regression explained that age, gender, negative teacher’s interaction with students and victimization in social gathering predicts mental health problems in school children. This study suggests and highlights the need for the school counselors for the better mental health of students and teachers.

Keywords: teacher-student interaction, school psychology, student’s emotional behavioral problems

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Authors: V. M. B. K. T. Malwanage, S. Samita

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Core stability is one of the major determinants that contribute to preventing injuries, enhance performance, and improve quality of life of the human. Endurance of the four major muscle groups of the central ‘core’ of the human body is identified as the most reliable determinant of core stability amongst the other numerous causes which contribute to readily make one’s core stability. This study aimed to develop a ‘Core Stability Index’ to confer a single value for an individual’s core stability based on the four endurance test scores. Since it is possible that at least some of the test scores are not independent, possibility of constructing a single index using the multivariate method exploratory factor analysis was investigated in the study. The study sample was consisted of 400 healthy young individuals with the mean age of 23.74 ± 1.51 years and mean BMI (Body Mass Index) of 21.1 ± 4.18. The correlation analysis revealed highly significant (P < 0.0001) correlations between test scores and thus construction an index using these highly inter related test scores using the technique factor analysis was justified. The mean values of all test scores were significantly different between males and females (P < 0.0001), and therefore two separate core stability indices were constructed for the two gender groups. Moreover, having eigen values 3.103 and 2.305 for males and females respectively, indicated one factor exists for all four test scores and thus a single factor based index was constructed. The 95% reference intervals constructed using the index scores were -1.64 to 2.00 and -1.56 to 2.29 for males and females respectively. These intervals can effectively be used to diagnose those who need improvement in core stability. The practitioners should find that with a single value measure, they could be more consistent among themselves.

Keywords: construction of indices, endurance test scores, muscle endurance, quality of life

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Authors: Kwak, Hyo-Gyung, Gang, Han Gul

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In the context of an increasing need for reliability and safety in concrete structures under blast and impact loading condition, the behavior of concrete under high strain rate condition has been an important issue. Since concrete subjected to impact loading associated with high strain rate shows quite different material behavior from that in the static state, several material models are proposed and used to describe the high strain rate behavior under blast and impact loading. In the process of modelling, in advance, mesh dependency in the used finite element (FE) is the key problem because simulation results under high strain-rate condition are quite sensitive to applied FE mesh size. It means that the accuracy of simulation results may deeply be dependent on FE mesh size in simulations. This paper introduces an improved criterion which can minimize the mesh-dependency of simulation results on the basis of the fracture energy concept, and HJC (Holmquist Johnson Cook), CSC (Continuous Surface Cap) and K&C (Karagozian & Case) models are examined to trace their relative sensitivity to the used FE mesh size. To coincide with the purpose of the penetration test with a concrete plate under a projectile (bullet), the residual velocities of projectile after penetration are compared. The correlation studies between analytical results and the parametric studies associated with them show that the variation of residual velocity with the used FE mesh size is quite reduced by applying a unique failure strain value determined according to the proposed criterion.

Keywords: high strain rate concrete, penetration simulation, failure strain, mesh-dependency, fracture energy

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