Search results for: residual life prediction

Authors: Katarzyna Pasternak

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Experiencing the meaning of life is widely recognised as a vital element of well-being and central human motivation. Studies have shown that a higher meaning of life is associated, among other things, with a higher quality of life, higher levels of happiness and better declared health. The subject of the study is the meaning in life measured with The Meaning in Life Questionnaire and the presence of such emotions as nostalgia, awe and hope, and the content of imaginations measured after temporal mental simulations in Americans and Poles. The respondents had to imagine themselves in future, in 40 years and describe two events that would take place at that time. Next, participants assessed the importance of the events described by them, recognised whether during their journey through time they felt awe, hope and nostalgia, and answered the questionnaire examining the meaning in life. 204 (102 from Poland 102 from the USA ) people aged 21 to 60 participated in the study. The study checked whether there were differences in the content of the imaginations of the respondents from Poland and USA, and whether there were statistically significant difference between the declared sense of meaning in life among participants from both countries. The result of the study hane shown that there were no differences in the overall result obtained by the participants in The Meaning in Life Questionnaire , while there were statistically significant differences among the subscales of the questionnaire. It turned out that Americans have a higher presence of meaning in life than Poles, but they obtained lower results in searching of meaning in life. Studies have also shown that there was a statistically significant difference between Poles and Americans in feeling awe after a mental simulation. Poles felt higher level of awe. Images about the future differed between Poles and Americans. Poles judged that the events they described were very important to them. Interestingly, the content of American participants’ imaginations was dominated by topics related to the future of the world, ecology and world peace. There were also ideas about nice moments spent with friends and family. Among Poles, ideas related to professional career and development as well as family events dominated. Research shows that despite the lack of differences in the general meaning in life, Poles are more focused on searching for meaning in life than Americans. The study shows interesting differences between the two cultures.

Keywords: meaning in life, mental simulations, imaginations, temporal mental simulations, future, cultural differences

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Authors: Sukhbir Singh

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This paper describes the modeling of novel solar air collector (NSAC) system by using artificial neural network (ANN) model. The objective of the study is to demonstrate the application of the ANN model to predict the performance of the NSAC with acetamide as a phase change material (PCM) storage. Input data set consist of time, solar intensity and ambient temperature wherever as outlet air temperature of NSAC was considered as output. Experiments were conducted between 9.00 and 24.00 h in June and July 2014 underneath the prevailing atmospheric condition of Kurukshetra (city of the India). After that, experimental results were utilized to train the back propagation neural network (BPNN) to predict the outlet air temperature of NSAC. The results of proposed algorithm show that the BPNN is effective tool for the prediction of responses. The BPNN predicted results are 99% in agreement with the experimental results.

Keywords: Evacuated tube solar air collector, Artificial neural network, Phase change material, solar air collector

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Authors: H. Booke, R. Nordmeier

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Sudden cardiac arrest is sometimes eye-witnessed by kids. Mostly, their (grand-)parents are affected by sudden cardiac arrest, putting these kids under enormous psychological pressure: Although they are more than desperate to help, they feel insecure and helpless and are afraid of causing harm rather than realizing their chance to help. Even years later, they may blame themselves for not having helped their beloved ones. However, the absolute majority of school children - at least in Germany - is not educated to provide first aid. Teaching young kids (5th grade) in basic life support thus may help to save lives while washing away the kids' fear from causing harm during cardio-pulmonary resuscitation. A teaching of circulatory and respiratory (patho-)physiology, followed by hands-on training of basic life support for every single child, was offered to each school in our district. The teaching was performed by anesthesiologists, and the program was called 'kids can save lives'. However, before enrollment in this program, the entire class must have had lessons in biology with a special focus on heart and circulation as well as lung and gas exchange. More than 1.000 kids were taught and trained in basic life support, giving them the knowledge and skills to provide basic life support. This may help to reduce the rate of failure to provide first aid. Therefore, educating young kids in basic life support may not only help to save lives, but it also may help to prevent any feelings of guilt because of not having helped in cases of eye-witnessed sudden cardiac arrest.

Keywords: teaching, children, basic life support, cardiac arrest, CPR

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Authors: Jan Henrik Wosnitza

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The logistic regression has developed into a standard approach for estimating conditional probabilities in a wide range of applications including credit risk prediction. The article at hand contributes to the current literature on logistic regression fourfold: First, it is demonstrated that the binary logistic regression automatically meets its model assumptions under very general conditions. This result explains, at least in part, the logistic regression's popularity. Second, the requirement of homoscedasticity in the context of binary logistic regression is theoretically substantiated. The variances among the groups of defaulted and non-defaulted obligors have to be the same across the level of the aggregated default indicators in order to achieve linear logits. Third, this article sheds some light on the question why nonlinear logits might be superior to linear logits in case of a small amount of data. Fourth, an innovative methodology for estimating correlations between obligor-specific log-odds is proposed. In order to crystallize the key ideas, this paper focuses on the example of credit risk prediction. However, the results presented in this paper can easily be transferred to any other field of application.

Keywords: correlation, credit risk estimation, default correlation, homoscedasticity, logistic regression, nonlinear logistic regression

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Authors: Mohammad Reza Dahmardeh Ghaleno, Mohammad Nohtani, Saeedeh Khaledi

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Hydrological models are applied to simulation and prediction floods in watersheds. WetSpa is a distributed, continuous and physically model with daily or hourly time step that explains of precipitation, runoff and evapotranspiration processes for both simple and complex contexts. This model uses a modified rational method for runoff calculation. In this model, runoff is routed along the flow path using Diffusion-Wave Equation which depend on the slope, velocity and flow route characteristics. Garmabrood watershed located in Mazandaran province in Iran and passing over coordinates 53° 10´ 55" to 53° 38´ 20" E and 36° 06´ 45" to 36° 25´ 30"N. The area of the catchment is about 1133 km2 and elevations in the catchment range from 213 to 3136 m at the outlet, with average slope of 25.77 %. Results of the simulations show a good agreement between calculated and measured hydrographs at the outlet of the basin. Drawing upon Nash-Sutcliffe Model Efficiency Coefficient for calibration periodic model estimated daily hydrographs and maximum flow rate with an accuracy up to 61% and 83.17 % respectively.

Keywords: watershed simulation, WetSpa, runoff, flood prediction

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Authors: Misuk Kim, Seokho Kang, Jehyuk Lee, Hyunchang Cho, Sungzoon Cho

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In semiconductor manufacturing, virtual metrology (VM) refers to methods to predict properties of a wafer based on machine parameters and sensor data of the production equipment, without performing the (costly) physical measurement of the wafer properties (Wikipedia). Additional benefits include avoidance of human bias and identification of important factors affecting the quality of the process which allow improving the process quality in the future. It is however rare to find VM applied to other areas of manufacturing. In this work, we propose to use VM to copper clad laminate (CCL) manufacturing. CCL is a core element of a printed circuit board (PCB) which is used in smartphones, tablets, digital cameras, and laptop computers. The manufacturing of CCL consists of three processes: Treating, lay-up, and pressing. Treating, the most important process among the three, puts resin on glass cloth, heat up in a drying oven, then produces prepreg for lay-up process. In this process, three important quality factors are inspected: Treated weight (T/W), Minimum Viscosity (M/V), and Gel Time (G/T). They are manually inspected, incurring heavy cost in terms of time and money, which makes it a good candidate for VM application. We developed prediction models of the three quality factors T/W, M/V, and G/T, respectively, with process variables, raw material, and environment variables. The actual process data was obtained from a CCL manufacturer. A variety of variable selection methods and learning algorithms were employed to find the best prediction model. We obtained prediction models of M/V and G/T with a high enough accuracy. They also provided us with information on “important” predictor variables, some of which the process engineers had been already aware and the rest of which they had not. They were quite excited to find new insights that the model revealed and set out to do further analysis on them to gain process control implications. T/W did not turn out to be possible to predict with a reasonable accuracy with given factors. The very fact indicates that the factors currently monitored may not affect T/W, thus an effort has to be made to find other factors which are not currently monitored in order to understand the process better and improve the quality of it. In conclusion, VM application to CCL’s treating process was quite successful. The newly built quality prediction model allowed one to reduce the cost associated with actual metrology as well as reveal some insights on the factors affecting the important quality factors and on the level of our less than perfect understanding of the treating process.

Keywords: copper clad laminate, predictive modeling, quality control, virtual metrology

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Authors: Jonix Owino, Heather Fuller

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Refugees flee from their home countries due to civil unrest, war, persecution and migrate to Western countries such as the United States in search of a safe haven. Transitioning into a new society and culture can be challenging, thereby affecting refugee’s quality of life and well-being in the host communities. Moreover, as individuals age, they experience physical, cognitive and socioemotional changes that may impact their quality of life. However, little is known about the predictors of quality of life among aging refugees. It is not clear how quality of life varies by age, that is, between midlife refugees in comparison to their older counterparts. In addition to age, other sociodemographic factors such as gender, socioeconomic status, or country of origin are likely to have differential associations to quality of life, yet research on such variations among older refugees is sparse. Thus the present study seeks to explore factors associated with quality of life by asking the following research questions: 1) Do sociodemographic factors (such as age and gender) predict quality of life among older refugees, 2) Is there an association between social integration and quality of life, and 3) Is there an association between migratory related experiences (such as post migratory adjustments) and quality of life. The present study recruited 90 refugees (primarily originating from Bhutan, Somalia, Burundi, and Sudan) aged 50 or older living in the US. The participants completed a structured questionnaire which assessed factors such as participant’s sociodemographic attributes (e.g., age, gender, length of residence in the US, country of origin, employment, level of education, and marital status), and validated measures of social integration, post-migration living difficulties, and quality of life. Preliminary results suggest sociodemographic variability in quality of life among these refugees. Further analyses will be conducted using hierarchical regression analyses to address the following hypotheses: first, it is hypothesized that quality of life will vary by age and gender such that younger refugees and men will report higher quality of life. Second, it is expected that refugees with greater levels of social integration will also report better quality of life. Finally, post-migration factors such as language barriers and family stress are hypothesized to predict poorer quality of life. Further results will be analyzed, including potential moderating effects of age and gender, and resulting findings will be interpreted and discussed. The findings from this study have potential implications for communities on how they can better support older refugees as well as develop social programs that can effectively cater to their well-being. Conclusions will be drawn and discussed in light of policies related to both aging and refugee migration within the context of the US.

Keywords: aging out of place, migration, older refugees, quality of life, social integration

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Authors: Ammar Alali, Mahmoud Abughaban

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Cost reduction and drilling optimization is the goal of many drilling operators. Historically, stuck pipe incidents were a major segment of non-productive time (NPT) associated costs. Traditionally, stuck pipe problems are part of the operations and solved post-sticking. However, the real key to savings and success is in predicting the stuck pipe incidents and avoiding the conditions leading to its occurrences. Previous attempts in stuck-pipe predictions have neglected the local geology of the problem. The proposed predictive tool utilizes geophysical data processing techniques and Machine Learning (ML) algorithms to predict drilling activities events in real-time using surface drilling data with minimum computational power. The method combines two types of analysis: (1) real-time prediction, and (2) cause analysis. Real-time prediction aggregates the input data, including historical drilling surface data, geological formation tops, and petrophysical data, from wells within the same field. The input data are then flattened per the geological formation and stacked per stuck-pipe incidents. The algorithm uses two physical methods (stacking and flattening) to filter any noise in the signature and create a robust pre-determined pilot that adheres to the local geology. Once the drilling operation starts, the Wellsite Information Transfer Standard Markup Language (WITSML) live surface data are fed into a matrix and aggregated in a similar frequency as the pre-determined signature. Then, the matrix is correlated with the pre-determined stuck-pipe signature for this field, in real-time. The correlation used is a machine learning Correlation-based Feature Selection (CFS) algorithm, which selects relevant features from the class and identifying redundant features. The correlation output is interpreted as a probability curve of stuck pipe incidents prediction in real-time. Once this probability passes a fixed-threshold defined by the user, the other component, cause analysis, alerts the user of the expected incident based on set pre-determined signatures. A set of recommendations will be provided to reduce the associated risk. The validation process involved feeding of historical drilling data as live-stream, mimicking actual drilling conditions, of an onshore oil field. Pre-determined signatures were created for three problematic geological formations in this field prior. Three wells were processed as case studies, and the stuck-pipe incidents were predicted successfully, with an accuracy of 76%. This accuracy of detection could have resulted in around 50% reduction in NPT, equivalent to 9% cost saving in comparison with offset wells. The prediction of stuck pipe problem requires a method to capture geological, geophysical and drilling data, and recognize the indicators of this issue at a field and geological formation level. This paper illustrates the efficiency and the robustness of the proposed cross-disciplinary approach in its ability to produce such signatures and predicting this NPT event.

Keywords: drilling optimization, hazard prediction, machine learning, stuck pipe

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Authors: Subhamita Chakraborty, Shubhabrata Datta, Sujay Kumar Mukherjea, Partha Protim Chattopadhyay

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Manufacturing of multiphase high strength steel in hot strip mill have drawn significant attention due to the possibility of forming low temperature transformation product of austenite under continuous cooling condition. In such endeavor, reliable prediction of temperature profile of hot strip coil is essential in order to accesses the evolution of microstructure at different location of hot strip coil, on the basis of corresponding Continuous Cooling Transformation (CCT) diagram. Temperature distribution profile of the hot strip coil has been determined by using finite volume method (FVM) vis-à-vis finite difference method (FDM). It has been demonstrated that FVM offer greater computational reliability in estimation of contact pressure distribution and hence the temperature distribution for curved and irregular profiles, owing to the flexibility in selection of grid geometry and discrete point position, Moreover, use of finite volume concept allows enforcing the conservation of mass, momentum and energy, leading to enhanced accuracy of prediction.

Keywords: simulation, modeling, thermal analysis, coil cooling, contact pressure, finite volume method

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Authors: B. Harman, E. Gringart, C. Harms

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There is evidence that increasing numbers of adults of child-bearing age in Australia do not have children. While there has been research into the life experiences of non-parents, one of the issues is that the differences between people who choose not to have children – the childfree – and people who cannot have children – the childless – are not clearly defined. The qualitative research reported here adopted an interpretative phenomenological approach to examine the life experiences of non-parents. Potential participants from Australia were invited to complete an online survey describing their experiences of life without children. An examination of the data from 229 participants (188 female, 41 male) revealed that they defined their non-parent status as either childfree or childless. There are, however, five sub-categories of child freedom identified by the participants, whereas previous research has not recognized such distinctions. The variance in the definition of child freedom is important because it may be related to the life journey as a non-parent. The current paper will firstly discuss the different groups of childfree and childless people. Secondly, it will examine the life experiences and journeys of non-parents in light of how the participants defined themselves. From a social psychological perspective, the current research is important as it highlights the socially held stereotypes and the stigma experienced by non-parents in Australia.

Keywords: Australia, childfree, childless, non-parents, qualitative, social psychology

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Authors: M.Rüştü Karaman, İsmail İşeri, Kadir Saltalı, A.Reşit Brohi, Ayhan Horuz, Mümin Dizman

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Considerable relations has recently been given to the environmental hazardous caused by agricultural chemicals such as excess fertilizers. In this study, a neural network approach was investigated in the prediction of potential nitrate pollution across different land-use patterns by using a feedforward multilayered computer model of artificial neural network (ANN) with proper training. Periodical concentrations of some anions, especially nitrate (NO3-), and cations were also detected in drainage waters collected from the drain pipes placed in irrigated tomato field, unirrigated wheat field, fallow and pasture lands. The soil samples were collected from the irrigated tomato field and unirrigated wheat field on a grid system with 20 m x 20 m intervals. Site specific nitrate concentrations in the soil samples were measured for ANN based simulation of nitrate leaching potential from the land profiles. In the application of ANN model, a multi layered feedforward was evaluated, and data sets regarding with training, validation and testing containing the measured soil nitrate values were estimated based on spatial variability. As a result of the testing values, while the optimal structures of 2-15-1 was obtained (R2= 0.96, P < 0.01) for unirrigated field, the optimal structures of 2-10-1 was obtained (R2= 0.96, P < 0.01) for irrigated field. The results showed that the ANN model could be successfully used in prediction of the potential leaching levels of nitrate, based on different land use patterns. However, for the most suitable results, the model should be calibrated by training according to different NN structures depending on site specific soil parameters and varied agricultural managements.

Keywords: artificial intelligence, ANN, drainage water, nitrate pollution

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Authors: Ina Nasto, Denada Sota, Pudrila Haskoçelaj, Mariola Ismailaj, Hajdar Kicaj

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Most of the fishing areas of the Mediterranean Sea are considered to be overfished, consequently fishing has decreased or is static. Considering the continuous increase in demand for fish, the option of aquaculture production has had a growing development in recent decades. The environmental impact of aquaculture in the marine ecosystem has been a subject of study for several years in the Mediterranean. In the case of the Albanian waters, and in particular the Gulf of Vlora, have had a progressive growing of aquaculture activity in the last twenty years. Given the convenient and secluded location for tourist activities, the bay of Ragusa was considered as the most suitable area to install the aquaculture cage system for the breeding of sea bass and sea bream. The impact of aquaculture in on the soft bottom benthic communities has been assessed at the biggest commercial fish farm (Alb-Adriatico Sh.P.K) established in coastal waters of Ragusa bay 30–50 m deep, in the southern part of the Gulf of Vlora. In order to determine if there is a possible impact on the aquaculture cage in benthic communities, a comparative analysis was undertaken between transects and samples with differences in distances between them and with a gradient of distance from the fish cages. A total of 275 taxa were identified (1 Foraminifera, 1 Porifera, 3 Cnidaria, 2 Platyhelminthes, 2 Nemertea, 1 Bryozoa, 171 Mollusca, 39 Annelida, 35 Crustacea, 14 Echinodermata, 1 Hemichordata, and 5 Tunicata). The anaysis showed three main habitats in the area: biocoenosis of terrigenous mud, residual areas with Possidonia oceanica and also residual assemblages of algal coralligenous. Four benthic biotic indexes were calculated (Shannon H ’, BENTIX, Simpson's Diversity and Peilou’s J’) also benthic indicators as total abundance, number of taxa and species frequency to evaluate possible ecological impact of fish cages in Ragusa bay.

Keywords: Bentix index, Benthic community, invertebrates, aquaculture, Raguza bay

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Authors: Roopchand Tandon, Zaheer Khan Yusufzai, R. Manna, R. K. Mandal

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Present work describes microstructures, mechanical properties, and texture characteristics of the friction stir processed AA7075T7352 aluminum alloy. Phases were analyzed with the help of x-ray diffractometre (XRD), transmission electron microscope (TEM) along with the differential scanning calorimeter (DSC). Depth-wise microstructures and dislocation characteristics from the nugget-zone of the friction stir processed specimens were studied using the bright field (BF) and weak beam dark-field (WBDF) TEM micrographs, and variation in the microstructures as well as dislocation characteristics were the noteworthy features found. XRD analysis display changes in the chemistry as well as size of the phases in the nugget and heat affected zones (Nugget and HAZ). Whereas the base metal (BM) microstructures remain un-affected. High density dislocations were noticed in the nugget regions of the processed specimen, along with the formation of dislocation contours and tangles. .The ɳ’ and ɳ phases, along with the GP-Zones were completely dissolved and trapped by the dislocations. Such an observations got corroborated to the improved mechanical as well as stress corrosion cracking (SCC) performances. Bulk texture and residual stress measurements were done by the Panalytical Empyrean MRD system with Co- kα radiation. Nugget zone (NZ) display compressive residual stress as compared to thermo-mechanically(TM) and heat affected zones (HAZ). Typical f.c.c. deformation texture components (e.g. Copper, Brass, and Goss) were seen. Such a phenomenon is attributed to the enhanced hardening as well as other mechanical performance of the alloy. Mechanical characterizations were done using the tensile test and Anton Paar Instrumented Micro Hardness tester. Enhancement in the yield strength value is reported from the 89MPa to the 170MPa; on the other hand, highest hardness value was reported in the nugget-zone of the processed specimens.

Keywords: aluminum alloy, mechanical characterization, texture characterstics, friction stir processing

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Authors: Pan Lee Ching, Chua Bee Seok

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The experience of negative work-life interaction often confronted with work related stress includes workload. The appraisal of challenge and hindrance jobs depend on the type of workload to stimulate stress response. Nevertheless, the effects of challenge and hindrance jobs on distress and negative work-life interaction are scarcely explored. Thus, research objective was to examine the relationship among challenge appraisal job (qualitative workload), hindrance appraisal job (quantitative workload), and negative work-life interaction with the mediating role of distress. A survey with random sampling method was performed on current serving public secondary school teachers in Sabah. Collected data showed 447 respondents completed three questionnaires, namely Challenge-hindrance Appraisal Scale, Stress Professional Positive and Negative Questionnaire, and Survey Work-home Interaction-Nijmegan. Partial Least Square-Structural Equation Modeling (PLS-SEM) was used to analyse mediation effect. Results showed distress fully mediates the relationship between challenge appraisal job (qualitative workload) and negative work-life interaction. The indirect effect was significant and negative. While distress partially mediates the relationship between hindrance appraisal job (quantitative workload) and negative work-life interaction. The indirect effect was significant and positive. The study implied that challenge appraisal job could be a positive resource for teacher to facilitate work and life, whereas hindrance appraisal job could disengage the facilitation. Hence, strengthen challenge appraisal job and control hindrance appraisal job could curb distress at work and underpin life interaction among the teachers.

Keywords: challenge-hindrance job, distress, work-life, workload

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Authors: Sneh Laller, Kamini C. Tanwar

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Human beings are social animals. The scenario is changing and people become angry towards petty things and this may lead to committing a crime. Objective: The aim of the present research is: 1. To find out the difference between convicts and under-trials on different dimensions of Personality, Fear of Negative Evaluation (FNE) and Life-orientation; 2. To find out the difference between male and female jail inmates on different dimensions of Personality, Fear of Negative Evaluation (FNE) and Life-orientation; 3. To find out the relationship between different dimensions of Personality, Fear of Negative Evaluation (FNE) and Life-orientation in convicts and under-trials; 4. To find out the relationship between different dimensions of Personality, Fear of Negative Evaluation (FNE) and Life-orientation in male and female jail inmates. Method: The study was conducted on 100 participants (consisting of 50 convicts- 25 males and 25 females, and 50 under-trials- 25 males and 25 females); age range was 20-60 years. The NEO Five-Factor Inventory-3 by McCrae, Costa (2010), Brief Fear of Negative Evaluation scale- II by Leary (1983) and Life Orientation Test-R by Scheier et al. (1994) was used and purposive sampling technique was done for data collection. The t-test was applied to find out the comparison and Pearson correlation was applied to determine the relationship between personality, FNE and life-orientation in both the groups. Results: There is a significant difference in the dimension of personality that is neuroticism and life-orientation in convicts and under-trials and also, in the dimensions of personality such as neuroticism, extraversion, openness to experience and agreeableness, and FNE in male and female jail inmates. In convicts the dimension of personality, agreeableness shows significant positive correlation with life-orientation (r = 0.430**) whereas, in under-trials the dimension of personality, agreeableness shows significant positive correlation with FNE (r = 0.315*) and another dimension of personality, extraversion shows significant negative correlation with life-orientation (r = -0.409**). In male jail inmates, the dimension of personality, agreeableness shows significant positive correlation with FNE (r = 0.474**) whereas in female jail inmates, the dimension of personality, openness to experience shows significant negative correlation with FNE (r = -0.356*) and significant positive correlation of neuroticism with life-orientation (r = 0.292*). Conclusion: It was found that under-trials are neurotic and life-oriented than convicts, and female jail inmates are also neurotic and exhibit fear of negative evaluation whereas male jail inmates are extravert and agreeable.

Keywords: convicts, fear of negative evaluation, life-orientation, personality, under-trials

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Authors: Amin Salighehdar, Ziwen Ye, Mingzhe Liu, Ionut Florescu, Alan F. Blumberg

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Storm surge is an abnormal water level caused by a storm. Accurate prediction of a storm surge is a challenging problem. Researchers developed various ensemble modeling techniques to combine several individual forecasts to produce an overall presumably better forecast. There exist some simple ensemble modeling techniques in literature. For instance, Model Output Statistics (MOS), and running mean-bias removal are widely used techniques in storm surge prediction domain. However, these methods have some drawbacks. For instance, MOS is based on multiple linear regression and it needs a long period of training data. To overcome the shortcomings of these simple methods, researchers propose some advanced methods. For instance, ENSURF (Ensemble SURge Forecast) is a multi-model application for sea level forecast. This application creates a better forecast of sea level using a combination of several instances of the Bayesian Model Averaging (BMA). An ensemble dressing method is based on identifying best member forecast and using it for prediction. Our contribution in this paper can be summarized as follows. First, we investigate whether the ensemble models perform better than any single forecast. Therefore, we need to identify the single best forecast. We present a methodology based on a simple Bayesian selection method to select the best single forecast. Second, we present several new and simple ways to construct ensemble models. We use correlation and standard deviation as weights in combining different forecast models. Third, we use these ensembles and compare with several existing models in literature to forecast storm surge level. We then investigate whether developing a complex ensemble model is indeed needed. To achieve this goal, we use a simple average (one of the simplest and widely used ensemble model) as benchmark. Predicting the peak level of Surge during a storm as well as the precise time at which this peak level takes place is crucial, thus we develop a statistical platform to compare the performance of various ensemble methods. This statistical analysis is based on root mean square error of the ensemble forecast during the testing period and on the magnitude and timing of the forecasted peak surge compared to the actual time and peak. In this work, we analyze four hurricanes: hurricanes Irene and Lee in 2011, hurricane Sandy in 2012, and hurricane Joaquin in 2015. Since hurricane Irene developed at the end of August 2011 and hurricane Lee started just after Irene at the beginning of September 2011, in this study we consider them as a single contiguous hurricane event. The data set used for this study is generated by the New York Harbor Observing and Prediction System (NYHOPS). We find that even the simplest possible way of creating an ensemble produces results superior to any single forecast. We also show that the ensemble models we propose generally have better performance compared to the simple average ensemble technique.

Keywords: Bayesian learning, ensemble model, statistical analysis, storm surge prediction

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Authors: Priyesh Kumar Pandey, Zakir Husain, R. K. Jarial

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Condition monitoring and diagnostic is important for testing of power transformer in order to estimate the remnant life. Concentration of furan content in transformer oil can be a promising indirect measurement of the aging of transformer insulation. The oil gets contaminated mainly due to ageing. The present paper introduces adaptive neuro fuzzy technique to correlate furanic compounds obtained by high performance liquid chromatography (HPLC) test and remnant life of the power transformer. The results are obtained by conducting HPLC test at TIFAC-CORE lab, NIT Hamirpur on thirteen power transformer oil samples taken from Himachal State Electricity Board, India.

Keywords: adaptive neuro fuzzy technique, furan compounds, remnant life, transformer oil

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Authors: Tea Poklepović, Zdravka Aljinović, Branka Marasović

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Due to the importance of yield curve and its estimation it is inevitable to have valid methods for yield curve forecasting in cases when there are scarce issues of securities and/or week trade on a secondary market. Therefore in this paper, after the estimation of weekly yield curves on Croatian financial market from October 2011 to August 2012 using Nelson-Siegel and Svensson models, yield curves are forecasted using Vector auto-regressive model and Neural networks. In general, it can be concluded that both forecasting methods have good prediction abilities where forecasting of yield curves based on Nelson Siegel estimation model give better results in sense of lower Mean Squared Error than forecasting based on Svensson model Also, in this case Neural networks provide slightly better results. Finally, it can be concluded that most appropriate way of yield curve prediction is neural networks using Nelson-Siegel estimation of yield curves.

Keywords: Nelson-Siegel Model, neural networks, Svensson Model, vector autoregressive model, yield curve

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Authors: Julie Wittmannová, Petr Šeda

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Quality of life measurements (QLF) help to evaluate interventions programs in different groups of persons with special needs. Our presentation deals with QLF of persons with addiction in relation to the physical activity (PA), type of addiction, age, gender and other variables. The aim of presentation is to summarize the basic findings and offer thoughts for questions arose. Methods: SQUALA (Subjective Quality of Life Analysis); SEIQoL (Schedule for the Evaluation of Individual Quality of Life); questionnaire of own construction. The results are evaluated by Mann­Whitney U test and Kruskall­Wallis ANOVA test (p ≤ 0,05). Sample of 64 participants – clients of aftercare center, aged 18 plus. Findings: Application of the methods SQUALA and SEIQoL in the chosen population seems appropriate, the obtaining information regarding the QLF correlate to intervention program topics, the need of an activelifestyle and health related topics in persons with addiction is visible. Conclusions or Implications: The subjective evaluation of quality of life of Aftercare clients is an important part of evaluation process, especially used to evaluate satisfaction with offered services and programs. Techniques SQUALA and SEIQoL gave us the desired outcomes.

Keywords: adapted physical activity, addiction, quality of life, physical activity, aftercare

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Authors: Prateeksha Mahamallik, Anjali Pal

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In the present study, Co(II)-adsolubilized surfactant modified alumina (SMA) was prepared, and methylene blue (MB) degradation was carried out on Co-SMA surface by visible light photo-Fenton process. The entire reaction proceeded on solid surface as MB was embedded on Co-SMA surface. The reaction followed zero order kinetics. Response surface methodology (RSM) and artificial neural network (ANN) were used for modeling the decolorization of MB by photo-Fenton process as a function of dose of Co-SMA (10, 20 and 30 g/L), initial concentration of MB (10, 20 and 30 mg/L), concentration of H2O2 (174.4, 348.8 and 523.2 mM) and reaction time (30, 45 and 60 min). The prediction capabilities of both the methodologies (RSM and ANN) were compared on the basis of correlation coefficient (R2), root mean square error (RMSE), standard error of prediction (SEP), relative percent deviation (RPD). Due to lower value of RMSE (1.27), SEP (2.06) and RPD (1.17) and higher value of R2 (0.9966), ANN was proved to be more accurate than RSM in order to predict decolorization efficiency.

Keywords: adsolubilization, artificial neural network, methylene blue, photo-fenton process, response surface methodology

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Authors: Diana Ivanova Bakalova, Ekaterina Evtimova Dimitrova

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The purpose of this paper is to examine the predictive power of optimistic expectations and satisfaction with life in the country of origin and residence – Bulgaria, over the attitudes towards emigration among young Bulgarians with regard to their generational belonging and differences (i.e. Generation Y or Millennials, born between 1981-1995/6, and Generation Z or Zoomers, born between 1996/7-2012). Although the correlation between satisfaction with life and migration (attitudes) has been studied in some countries, it has neither been examined to date in Bulgaria – a sending rather than receiving Eastern European country, nor scrutinized in the light of generational differences. Within a national survey(N=1200), representative of young Bulgarians aged 18-35 years – Zoomers aged 18-25years (N=444) and Millennials aged 26-35 years (N=756), carried out in September-October 2021, optimistic expectations and satisfaction with life in Bulgaria were respectively measured by a 5-item and4-item scales. The scales were designed to measure optimistic expectations and satisfaction with life in the country, as both general constructs and in terms of specific areas of life (education, profession, career, and income). The findings suggest that the higher satisfaction with life in Bulgaria is associated with more optimistic expectations about one’s further professional, financial, and career growth in the country and reasonably, with more negative attitudes towards emigration of young Bulgarians. Although no significant differences were found between Millennials and Zoomers in their optimistic expectations and satisfaction with life in Bulgaria, Millennials are still significantly less likely to emigrate than Zoomers. Positively, the population of young Bulgarians demonstrates higher than average satisfaction with life and optimism for their prospects in the country combined with neutral to negative overall attitudes towards emigration. These findings have some important interdisciplinary psychological and demographic theoretical, applied, and policy implications. The survey is carried out under Project КП-06-Н35/4 “Psychological determinants of young people's attitudes to emigration and life planning in the context of demographic challenges in Bulgaria,” funded by the NSF - MES, Bulgaria.

Keywords: optimistic expectations, life satisfaction, emigration attitudes, young bulgerians

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Authors: Komang Rahayu Indrawati, Ni Wayan Sinthia Widiastuti, Ratna Dewi Santosa

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Today the career of Balinese working women has been highly developed where able to work with loyalty and high professionalism. Career for a woman is one conscious choice and a call of conscience, which provides financial support for her family. Career for women can develop their own potencies, intellectually, and socially, so women feel that their role is meaningful and beneficial for herself and others. Emotional support becomes important to understand certainly for women who have multirole like Balinese working women to meet the demands of their role and also enhancing their work motivation and the quality of work life. This research used quantitative research method with questionnaires dissemination to 120 respondents and analyzed using Multiple Regression Analysis. The purpose of this study was to see the role of emotional support for work motivation and quality of work life in working Balinese women. The results of this study showed that emotional support and work motivation give a significant role in the quality of work life on Balinese working women.

Keywords: Balinese working women, emotional support, quality of work life, work motivation

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Authors: Ayedh Alqahtani, Andrew Whyte

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Life Cycle Cost (LCC) is one of the goals and key pillars of the construction management science because it comprises many of the functions and processes necessary, which assist organisations and agencies to achieve their goals. It has therefore become important to design and control assets during their whole life cycle, from the design and planning phase through to disposal phase. LCCA is aimed to improve the decision making system in the ownership of assets by taking into account all the cost elements including to the asset throughout its life. Current application of LCC approach is impractical during misunderstanding of the advantages of LCC. This main objective of this research is to show a different relationship between capital cost and long-term running costs. One hundred and thirty eight actual building projects in United Kingdom (UK) were used in order to achieve and measure the above-mentioned objective of the study. The result shown that LCC is one of the most significant tools should be considered on the decision making process.

Keywords: building projects, capital cost, life cycle cost, maintenance costs, operation costs

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Authors: M. Kuzhko, M. Gumeniuk, D. Butov, T. Tlustova, O. Denysov, T. Sprynsian

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Abstract: The objective of this work was to study the efficacy and safety of inhaled nebulized chemotherapy in the treatment of patients with newly diagnosed pulmonary tuberculosis in comparison with standard antimycobacterial therapy. Materials and methods: The study involved 68 patients aged between 20 and 70 years with newly diagnosed pulmonary tuberculosis. Patients were allocated to two groups. The first (main, n=21) group of patients received standard chemotherapy and further 0.15 g of isoniazid and rifampicin 0.15 g inhaled through a nebulizer, also they received salmeterol 50 mcg + fluticasone propionate 250 mcg at 2 breaths twice a day for 2 months. The second (control, n=47) group of patients received standard chemotherapy, consisting of orally administered isoniazid (0.3 g), rifampicin (0.6 g), pyrazinamide (2 g), ethambutol (1.2 g) with a dose reduction after the intensive phase of the therapy. The anti-TB drugs were procured through the Ukraine’s centralized national supply system. Results: Intoxication symptoms in the first group reduced following 1.39±0.18 months, whereas in the second group, intoxication symptoms reduced following 2.7±0.1 months, p<.001. Moreover, respiratory symptoms regression in the first group was observed following 1.6±0.2 months, whereas in the second group – following 2.5±0.2 months, p<0.05. Bacillary excretion period evaluated within 1 month was reduced, as it was shown by 66.6±10.5% in the main group compared to 27.6±6.5%, p<0.05, in the control group. In addition, period of cavities healing was reduced to 2.9±0.2 months in the main group compared to 3.7±0.1 months, p<0.05, in the control group. Residual radiological lung damage findings (large residual changes) were observed in 22 (23.8±9.5 %) patients of the main group versus 24 (51.0±7.2 %) patients in the control group, p<0.05. After completion of treatment scar stenosis of the bronchi II-III art. diagnosed in 3 (14.2±7.8%) patients in main group and 17 (68.0±6.8%) - control group, p<0.05. The duration of hospital treatment was 2.4±0.4 months in main group and 4.1±0.4 months in control group, p<0.05. Conclusion: Administration of of inhaled nebulized chemotherapy in patients with newly diagnosed pulmonary tuberculosis resulted in a comparatively quick reduction of disease manifestation.

Keywords: inhaled nebulized chemotherapy, pulmonary tuberculosis, tuberculosis, treatment of tuberculosis

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Authors: Moustafa Osman

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Modeling of air pollutants from the accidental release is performed for quantifying the impact of industrial facilities into the ambient air. The mathematical methods are requiring for the prediction of the accidental scenario in probability of failure-safe mode and analysis consequences to quantify the environmental damage upon human health. The initial statement of mitigation plan is supporting implementation during production and maintenance periods. In a number of mathematical methods, the flow rate at which gaseous and liquid pollutants might be accidentally released is determined from various types in term of point, line and area sources. These emissions are integrated meteorological conditions in simplified stability parameters to compare dispersion coefficients from non-continuous air pollution plumes. The differences are reflected in concentrations levels and greenhouse effect to transport the parcel load in both urban and rural areas. This research reveals that the elevation effect nearby buildings with other structure is higher 5 times more than open terrains. These results are agreed with Sutton suggestion for dispersion coefficients in different stability classes.

Keywords: air pollutants, dispersion modeling, GIS, health effect, urban planning

Procedia PDF Downloads 365

Authors: Sanja Pfeifer, Nataša Šarlija, Marina Jeger, Ana Bilandžić

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The purpose of this study is to explore the different facets of growth among micro, small and medium-sized firms in Croatia and to analyze the differences between models designed for all micro, small and medium-sized firms and those in creative industries. Three growth prediction models were designed and tested using the growth of sales, employment and assets of the company as dependent variables. The key drivers of sales growth are: prudent use of cash, industry affiliation and higher share of intangible assets. Growth of assets depends on retained profits, internal and external sources of financing, as well as industry affiliation. Growth in employment is closely related to sources of financing, in particular, debt and it occurs less frequently than growth in sales and assets. The findings confirm the assumption that growth strategies of small and medium-sized enterprises (SMEs) in creative industries have specific differences in comparison to SMEs in general. Interestingly, only 2.2% of growing enterprises achieve growth in employment, assets and sales simultaneously.

Keywords: creative industries, growth prediction model, growth determinants, growth measures

Procedia PDF Downloads 324

Authors: Piyas Palit, Urbi Pal, Jitendra Mathur, Santanu Das

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Bearing is an important machinery part in the industry. When bearings fail to meet their expected life the consequences are increased downtime, loss of revenue and missed the delivery. This article describes the failure of a gearbox bearing in rolling contact fatigue. The investigation consists of visual observation, chemical analysis, characterization of microstructures using optical microscopes and hardness test. The present study also considers bearing life as well as the operational condition of bearings. Surface-initiated rolling contact fatigue, leading to a surface failure known as pitting, is a life-limiting failure mode in many modern machine elements, particularly rolling element bearings. Metallography analysis of crack propagation, crack morphology was also described. Indication of fatigue spalling in the ferrography test was also discussed. The analysis suggested the probable reasons for such kind of failure in operation. This type of spalling occurred due to (1) heavier external loading condition or (2) exceeds its service life.

Keywords: bearing, rolling contact fatigue, bearing life

Procedia PDF Downloads 165

Authors: Kumar Gular, Viswanathan S., Mastour Saeed Alshahrani, Ravi Shankar Reddy, Jaya Shanker Tedla, Snehil Dixit, Ajay Prasad Gautam, Venkata Nagaraj Kakaraparthi, Devika Rani Sangadala

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Background: Despite trunk control’s significant contribution to improving various functional activity components, the independent effect of trunk performance on quality of life is yet to be estimated in stroke survivors. Ascertaining the correlation between trunk control and self-reported quality of life while evaluating the effect of demographic and clinical characteristics on their relationship will guide concerned healthcare professionals in designing ideal rehabilitation protocols during the late sub-acute stroke stage of recovery. The aims of the present research were to (1) investigate the associations of trunk performance with self-rated quality of life and (2) evaluate if age, body mass index (BMI), and clinical characteristics mediate the relationship between trunk motor performance and perceived quality of life in the sub-acute stroke population. Methods: Trunk motor functions and quality of life among the late sub-acute stroke population aged 57.53 ± 6.42 years were evaluated through the trunk Impairment Scale (TIS) and Stroke specific quality of life (SSQOL) questionnaire, respectively. Pearson correlation coefficients and mediation analysis were performed to elucidate the relationship of trunk motor function with quality of life and determine the mediation impact of demographic and clinical characteristics on their association, respectively. Results: The current study observed significant correlations between trunk motor functions (TIS) and quality of life (SSQOL) with r=0.68 (p<0.001). Age, BMI, and type of stroke were detected as potential mediating factors in the association between trunk performance and quality of life. Conclusion: Validated associations between trunk motor functions and perceived quality of life among the late sub-acute stroke population emphasize the importance of comprehensive evaluation of trunk control. Rehabilitation specialists should focus on appropriate strategies to enhance trunk performance anticipating the potential effects of age, BMI, and type of stroke to improve health-related quality of life in stroke survivors.

Keywords: sub-acute stroke, quality of life, functional independence, trunk control

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Authors: Babak Bahri, Fatemeh Yassaee Meybodi, Changiz Eslahchi

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In the pursuit of effective cancer therapies, the exploration of combinatorial drug regimens is crucial to leverage synergistic interactions between drugs, thereby improving treatment efficacy and overcoming drug resistance. However, identifying synergistic drug pairs poses challenges due to the vast combinatorial space and limitations of experimental approaches. This study introduces ClusterSyn, a machine learning (ML)-powered framework for classifying anti-cancer drug synergy scores. ClusterSyn employs a two-step approach involving drug clustering and synergy score prediction using a fully connected deep neural network. For each cell line in the training dataset, a drug graph is constructed, with nodes representing drugs and edge weights denoting synergy scores between drug pairs. Drugs are clustered using the Markov clustering (MCL) algorithm, and vectors representing the similarity of drug pairs to each cluster are input into the deep neural network for synergy score prediction (synergy or antagonism). Clustering results demonstrate effective grouping of drugs based on synergy scores, aligning similar synergy profiles. Subsequently, neural network predictions and synergy scores of the two drugs on others within their clusters are used to predict the synergy score of the considered drug pair. This approach facilitates comparative analysis with clustering and regression-based methods, revealing the superior performance of ClusterSyn over state-of-the-art methods like DeepSynergy and DeepDDS on diverse datasets such as Oniel and Almanac. The results highlight the remarkable potential of ClusterSyn as a versatile tool for predicting anti-cancer drug synergy scores.

Keywords: drug synergy, clustering, prediction, machine learning., deep learning

Procedia PDF Downloads 68

Authors: Sophia Cyril Vincent

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Background: As per the Indian Census 2011, there is nearly 104 million elderly population aged above 60 years (53 million females and 51 males), and the count is expected to be 173 million by the end of 2026. Nearly 5.5% of women and 1.5% of men are living alone.1 In India, even though it is the moral duty of the children to take care of aged parents, many elders are landing in old age homes due to the social transformation factors like mushrooming of nuclear families, migration of children, cultural echoes, differences in mindset and values. Nearly 728 old age homes are seen across the country, out of which 78 old age homes with approximately 3000 inmates are seen only in Bangalore2. The existing literature shows that elderly women residing in old age homes experience the challenges like- loneliness, health issues, rejection from children, grief, death anxiety, etc, which leads to mental and physical wellbeing in numerous and tangible ways3. Hence the best and cost-effective way to improve the meaning and quality of life among elderly females is logotherapy, a type of psychotherapeutic analysis and treatment, motivating and driving force4 within the human experience to lead a decent life. Aim: The current research is aimed at studying the effectiveness of a logotherapy intervention on meaning and quality of life among elderly women of old age homes. Samples:200 women aged < 60 years and staying in the old age home for more than 1 year were randomly allocated to the control group and experimental group. Methodology: Using the Meaning in life questionnaire (MLQ)and the World health organization quality of life (WHOQOL) questionnaire, meaning and quality of life were assessed among both groups' women. Intensive Logotherapy and meaning in life program for five days were provided for the experimental group and the control group, with no treatment. Result: Under analysis. Conclusion: It is the right of the elderly woman to lead a happy and peaceful life till her death irrespective of the residing place. Hence, continuous monitoring and effective management are necessary for elderly women.

Keywords: quality of life, meaning of life, logo therapy, old age home

Procedia PDF Downloads 197