Search results for: modeling technique

Authors: Rattanamanee Chomchan, Sunisa Siripongvutikorn, Panupong Puttarak

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Ricegrass or young rice sprouts can be introduced as one of functional product since cereal sprouts have been much interested in this era due to their high nutritive values. Bio-fortification of selenium is one strategy to improve plant bioactive compounds. However, the level of selenium used are varied among species of plants, hence, the proper level need to be investigated. In this current study, influence of selenium bio-fortification hydroponically in the form of sodium selenite following the range 0, 10, 20, 30 and 40 mg Se/L on growth characteristics, selenium content, total extractable phenolic content (TPC) accumulation, lipid peroxidation and anti-oxidative properties of ricegrass were investigated. Results revealed that selenium bio-fortified exogenously increased the accumulation of selenium in ricegrass by 5.3 fold at 40 mg Se/L treatment without significant changes in leaves biomass at harvesting day while root part weight were slightly decreased when increased selenium level, respectively. Selenium at low concentration (10 and 20 mg Se/L) can stimulate the production of phenolic compounds and antioxidant activities in young ricegrass as measured by DPPH, ABTS and FRAP assay. Conversely, higher level of selenium fortification reduced the accumulation of phenolics in ricegrass afterward by acting as pro-oxidant. Moreover, highest significant reduction in oxidative stress, measured as malondialdehyde content was also observed at 20 mg Se/L treatment which in correlation to high TPC and antioxidant activities. In conclusion, selenium bio-fortification can be used as a technique to improve precious to ricegrass.

Keywords: antioxidant activities, bio-fortification, ricegrass, selenium

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Authors: Barenten Suciu, Yuya Nakamoto

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Power generation effect, obtained by inserting a piezo- electric sheet in the backlash clearance of a circular arc helical gear, is evaluated. Such type of screw gear is preferred since, in comparison with the involute tooth profile, the circular arc profile leads to reduced stress-concentration effects, and improved life of the piezoelectric film. Firstly, geometry of the circular arc helical gear, and properties of the piezoelectric sheet are presented. Then, description of the test-rig, consisted of a right-hand thread gear meshing with a left-hand thread gear, and the voltage measurement procedure are given. After creating the tridimensional (3D) model of the meshing gears in SolidWorks, they are 3D-printed in acrylonitrile butadiene styrene (ABS) resin. Variation of the generated voltage versus time, during a meshing cycle of the circular arc helical gear, is measured for various values of the center distance. Then, the change of the maximal, minimal, and peak-to-peak voltage versus the center distance is illustrated. Optimal center distance of the gear, to achieve voltage maximization, is found and its significance is discussed. Such results prove that the contact pressure of the meshing gears can be measured, and also, the electrical power can be generated by employing the proposed technique.

Keywords: circular arc helical gear, contact problem, optimal center distance, piezoelectric sheet, power generation

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Authors: Rajvir Kaur, Jeewani Anupama Ginige

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With recent trends in Big Data and advancements in Information and Communication Technologies, the healthcare industry is at the stage of its transition from clinician oriented to technology oriented. Many people around the world die of cancer because the diagnosis of disease was not done at an early stage. Nowadays, the computational methods in the form of Machine Learning (ML) are used to develop automated decision support systems that can diagnose cancer with high confidence in a timely manner. This paper aims to carry out the comparative evaluation of a selected set of ML classifiers on two existing datasets: breast cancer and cervical cancer. The ML classifiers compared in this study are Decision Tree (DT), Support Vector Machine (SVM), k-Nearest Neighbor (k-NN), Logistic Regression, Ensemble (Bagged Tree) and Artificial Neural Networks (ANN). The evaluation is carried out based on standard evaluation metrics Precision (P), Recall (R), F1-score and Accuracy. The experimental results based on the evaluation metrics show that ANN showed the highest-level accuracy (99.4%) when tested with breast cancer dataset. On the other hand, when these ML classifiers are tested with the cervical cancer dataset, Ensemble (Bagged Tree) technique gave better accuracy (93.1%) in comparison to other classifiers.

Keywords: artificial neural networks, breast cancer, classifiers, cervical cancer, f-score, machine learning, precision, recall

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Authors: Nuri Onat, Omer Tatari, Gokhan Egilmez

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The U.S. buildings consume significant amount of energy and natural resources and they are responsible for approximately 40 % of the greenhouse gases emitted in the United States. Awareness of these environmental impacts paved the way for the adoption of green building movement. The green building movement is a rapidly increasing trend. Green Construction market has generated $173 billion dollars in GDP, supported over 2.4 million jobs, and provided $123 billion dollars in labor earnings. The number of LEED certified buildings is projected to be almost half of the all new, nonresidential buildings by 2015. National Science and Technology Council (NSTC) aims to increase number of net-zero energy buildings (NZB). The ultimate goal is to have all commercial NZB by 2050 in the US (NSTC 2008). Green Building Initiative (GBI) became the first green building organization that is accredited by American National Standards Institute (ANSI), which will also boost number of green buildings certified by Green Globes. However, there is much less focus on greening the residential buildings, although the environmental impacts of existing residential buildings are more than that of commercial buildings. In this regard, current research aims to model the residential green building movement with a dynamic model approach and assess the possible strategies to stabilize the carbon footprint of the U.S. residential building stock. Three aspects of sustainable development are considered in policy making, namely: high performance green building (HPGB) construction, NZB construction and building retrofitting. 19 different policy options are proposed and analyzed. Results of this study explored that increasing the construction rate of HPGBs or NZBs is not a sufficient policy to stabilize the carbon footprint of the residential buildings. Energy efficient building retrofitting options are found to be more effective strategies then increasing HPGBs and NZBs construction. Also, significance of shifting to renewable energy sources for electricity generation is stressed.

Keywords: green building movement, residential buildings, carbon footprint, system dynamics

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Authors: P. O. Fatoki, R. S. Olaleye, B. O. Adeniji

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The study investigated farmers’ perception of the effects of climate change on rice production in Nasarawa State, Nigeria. Multi-stage sampling technique was used in selecting a total of 248 rice farmers from the study area. Data for the study were collected through the use of interview schedule. The data were analysed using both descriptive and inferential statistics. Results showed that majority (71.8%) of the respondents were married and the mean age of the respondents was 44.54 years. The results also showed that most adapted strategies for mitigating the effects of climate change on rice production were change of planting and harvesting date (67.7%), movement to another site (63.7%) and increased or reduced land size (58.5%). Relationship between the roles of extension agents in mitigating climate change effects on rice production and farmers’ perception were significant as revealed Chi-Square analysis from the study ; Dissemination of information ( = 2.16, P < 0.05) and use of demonstration methods ( = 2.15, P < 0.05). Poisson regression analysis revealed that educational status, farm size, experience and yield had significant relationship with the perception of the effects of climate change at 0.01 significance level while household size was as well significant at 0.05. It is recommended that some of the adaptive strategies and practices for mitigating the effects of climate change in rice production should be improved, while the extension outfits should be strengthened to ensure adequate dissemination of relevant information on climate change with a view to mitigate its effects on rice production.

Keywords: perception, rice farmers, climate change, mitigation, adaptive strategies

Procedia PDF Downloads 359

Authors: M. Nadeem, Y. K. Chang, C. Diallo, U. Venkatadri, P. Havard, T. Nguyen-Quang

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Uniform distribution of agro-chemicals is highly important because there is a significant loss of agro-chemicals, for example from pesticide, during spraying due to non-uniformity of droplet and off-target drift. Improving the efficiency of spray pattern for different cropping systems would reduce energy, costs and to minimize environmental pollution. In this paper, we examine the water jet patterns in order to study the performance and uniformity of water distribution during the spraying process. We present a method to quantify the water amount from a sprayer jet by using the Particle Image Velocimetry (PIV) system. The results of the study will be used to optimize sprayer or nozzles design for chemical application. For this study, ten sets of images were acquired by using the following PIV system settings: double frame mode, trigger rate is 4 Hz, and time between pulsed signals is 500 µs. Each set of images contained different numbers of double-framed images: 10, 20, 30, 40, 50, 60, 70, 80, 90 and 100 at eight different pressures 25, 50, 75, 100, 125, 150, 175 and 200 kPa. The PIV images obtained were analysed using custom-made image processing software for droplets and volume calculations. The results showed good agreement of both manual and PIV measurements and suggested that the PIV technique coupled with image processing can be used for a precise quantification of flow through nozzles. The results also revealed that the method of measuring fluid flow through PIV is reliable and accurate for sprayer patterns.

Keywords: image processing, PIV, quantifying the water volume from nozzle, spraying pattern

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Authors: Maria Pintea, Nigel Mason

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Induced chemistry is one of the newest pathways in the nanotechnology field with applications in the focused electron beam induced processes for deposition of nm scale structures. Si(OPr)₄ and Ti(OEt)₄ are two of the precursors that have not been so extensively researched, though highly sought for semiconductor and medical applications fields, the two compounds make good candidates for FEBIP and are the subject of velocity slice map imaging analysis for deposition purposes, offering information on kinetic energies, fragmentation channels, and angular distributions. The velocity slice map imaging technique is a method used for the characterization of molecular dynamics of the molecule and the fragmentation channels as a result of induced chemistry. To support the gas-phase analysis, Meso-Bio-Nano simulations of irradiation dynamics studies are employed with final results on Fe(CO)₅ deposited on various substrates. The software is capable of running large scale simulations for complex biomolecular, nano- and mesoscopic systems with applications to thermos-mechanical DNA damage, complex materials, gases, nanoparticles for cancer research and deposition applications for nanotechnology, using a large library of classical potentials, many-body force fields, molecular force fields involved in the classical molecular dynamics.

Keywords: focused electron beam induced deposition, FEBID, induced chemistry, molecular dynamics, velocity map slice imaging

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Authors: Muneera Mohammed Al-Dossary, Fatimah Mohammed Al-Dossary, Mashael Al-Shahrani, Amal Al-Tammemi

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Johns Hopkins Aramco Healthcare (JAHA), a joint venture between Saudi Aramco and Johns Hopkins Medicine, delivers comprehensive healthcare services to a diverse patient population. Despite achieving high patient satisfaction rates and surpassing several operational targets, JAHA faces challenges such as appointment delays and resource inefficiencies. These issues highlight the need for an advanced, integrated approach to operational management. This paper proposes a Business Intelligence (BI) framework to address these challenges, leveraging tools such as Epic electronic health records and Tableau dashboards. The framework focuses on data integration, real-time monitoring, and predictive analytics to streamline operations and enhance decision-making. Key outcomes include reduced wait times (e.g., a 23% reduction in specialty clinic wait times) and improved operating room efficiency (from 95.83% to 98% completion rates). These advancements align with JAHA’s strategic objectives of optimizing resource utilization and delivering superior patient care. The findings underscore the transformative potential of BI in healthcare, enabling a shift from reactive to proactive operations management. The success of this implementation lays the foundation for future innovations, including machine learning models for more precise demand forecasting and resource allocation.

Keywords: business intelligence, operational efficiency, healthcare management, predictive analytics, patient care improvement, data integration, real-time monitoring, resource optimization, Johns Hopkins Aramco Healthcare, electronic health records, Tableau dashboards, predictive modeling, efficiency metrics, resource utilization, patient satisfaction

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Authors: Ben Khayut, Lina Fabri, Maya Avikhana

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The models of the modern Artificial Narrow Intelligence (ANI) cannot: a) independently and continuously function without of human intelligence, used for retraining and reprogramming the ANI’s models, and b) think, understand, be conscious, cognize, infer, and more in state of Uncertainty, and changes in situations, and environmental objects. To eliminate these shortcomings and build a new generation of Artificial Intelligence systems, the paper proposes a Conception, Model, and Method of Computational Psycholinguistic Cognitive Situational-Fuzzy Self-Controlled Brain and Mind System (CPCSFSCBMSUU) using a neural network as its computational memory, operating under uncertainty, and activating its functions by perception, identification of real objects, fuzzy situational control, forming images of these objects, modeling their psychological, linguistic, cognitive, and neural values of properties and features, the meanings of which are identified, interpreted, generated, and formed taking into account the identified subject area, using the data, information, knowledge, and images, accumulated in the Memory. The functioning of the CPCSFSCBMSUU is carried out by its subsystems of the: fuzzy situational control of all processes, computational perception, identifying of reactions and actions, Psycholinguistic Cognitive Fuzzy Logical Inference, Decision making, Reasoning, Systems Thinking, Planning, Awareness, Consciousness, Cognition, Intuition, Wisdom, analysis and processing of the psycholinguistic, subject, visual, signal, sound and other objects, accumulation and using the data, information and knowledge in the Memory, communication, and interaction with other computing systems, robots and humans in order of solving the joint tasks. To investigate the functional processes of the proposed system, the principles of Situational Control, Fuzzy Logic, Psycholinguistics, Informatics, and modern possibilities of Data Science were applied. The proposed self-controlled System of Brain and Mind is oriented on use as a plug-in in multilingual subject Applications.

Keywords: computational brain, mind, psycholinguistic, system, under uncertainty

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Authors: Mahmood Dehqan, Peyman Peyvasteh

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In recent years there has been a growing interest in issues concerning the impact of sociocultural theory (SCT) of learning on different aspects of second/foreign language learning. This study aimed to find the possible effects of sociocultural teaching techniques on reading strategy of EFL learners. Indeed, the present research compared the impact of peer and teacher scaffolding on EFL learners’ reading strategy use across two proficiency levels. To this end, a pre-test post-test quasi-experimental research design was used and two instruments were utilized to collect the data: Nelson English language test and reading strategy questionnaire. Ninety five university students participated in this study were divided into two groups of teacher and peer scaffolding. Teacher scaffolding group received scaffolded help from the teacher based on three mechanisms of effective help within ZPD: graduated, contingent, dialogic. In contrast, learners of peer scaffolding group were unleashed from the teacher-fronted classroom as they were asked to carry out the reading comprehension tasks with the feedback they provided for each other. Results obtained from ANOVA revealed that teacher scaffolding group outperformed the peer scaffolding group in terms of reading strategy use. It means teacher’s scaffolded help provided within the learners’ ZPD led to better reading strategy improvement compared with the peer scaffolded help. However, the interaction effect between proficiency factor and teaching technique was non-significant, leading to the conclusion that strategy use of the learners was not affected by their proficiency level in either teacher or peer scaffolding groups.

Keywords: peer scaffolding, proficiency level, reading strategy, sociocultural theory, teacher scaffolding

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Authors: B. O. Diyaolu

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Viability and competency during competition is the dream of every team sports so as to have a good result. But it seems factors abound which deter the performance of even a good sports team. Different individuals with different state of mind all come together to perform in team sports with different degree of satisfaction. This study investigated the role of satisfaction on performance among Afe Babalola University team sports. Descriptive survey research design was used and the population consists of all male and female athletes in the team sports that participated in the last 2019 Ekiti State Higher Institution games (ESHIGA). Total enumeration technique was used for the three team sports; football (44), basketball (24) and volleyball (24). A total of 92 participants were involved in the research. The instrument used for the study was a modified Athlete Satisfaction Scale (ASS). The questionnaire was divided into two sections. The Cronbach’s Alpha reliability coefficient of 0.71 was obtained. The hypotheses were tested at 0.05 significant levels. The completed questionnaire was collated, coded, and analyzed using descriptive statistics of frequency counts and percentage and inferential statistics of chi-square (X²). Findings of this study revealed that satisfaction significantly influences team sports performance among Athletes of Afe Babalola University. The responsibility of satisfying athlete lies on the coaches, fans, sports administrators as well as organizers of such event, as it is not only financial reward that gives satisfaction. The performance of a team sports is quiet important and its being determined by the degree of satisfaction of each individual that make up the team. All effort must be made to satisfy athlete in order to guarantee optimum performance.

Keywords: athlete satisfaction, optimum achievement, optimum performance, sports performance and team sports

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Authors: Rayleigh Dada Abu, Halilu Ahmad Shaba

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Siltation is a serious problem that affects public water supply infrastructures such as dams and reservoirs. It is a major problem which threatens the performance and sustainability of dams and reservoirs. It reduces the dam capacity for flood control, potable water supply, changes water stage, reduces water quality and recreational benefits. The focus of this study is the Lower Usuma reservoir. At completion the reservoir had a gross storage capacity of 100 × 106 m3 (100 million cubic metres), a maximum operational level of 587.440 m a.s.l., with a maximum depth of 49 m and a catchment area of 241 km2 at dam site with a daily designed production capacity of 10,000 cubic metres per hour. The reservoir is 1,300 m long and feeds the treatment plant mainly by gravity. The reservoir became operational in 1986 and no survey has been conducted to determine its current storage capacity and rate of siltation. Hydrographic survey of the reservoir by integrated acoustic echo-sounding technique was conducted in November 2012 to determine the level and rate of siltation. The result obtained shows that the reservoir has lost 12.0 meters depth to siltation in 26 years of its operation; indicating 24.5% loss in installed storage capacity. The present bathymetric survey provides baseline information for future work on siltation depth and annual rates of storage capacity loss for the Lower Usuma reservoir.

Keywords: sedimentation, lower Usuma reservoir, acoustic echo sounder, bathymetric survey

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Authors: Abdinasir Mohamed, Ashraf El-Hamalawi, Steven Yeomans, Matthew Frost, Andy Connell

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The evaluation and selection of appropriate software solutions to meet with an organisation’s inherent business requirements can be a problematic software engineering process that if done incorrectly can have a significant, costly and adverse effect on the business and its processes. The aim of this paper is to show the process and evaluation criteria followed to select the right engineering solution for the identified business requirement. The research adopted an action research method within an organisation in the oil and gas industry, which required a solution suitable for conducting stress analysis for soil-pipeline interaction analysis (SPIA). Through the use of the presented software selection and evaluation approach, to capture and measure key requirements, it was possible to determine a suitable software for the organisation. This paper investigates methodologies for selecting software packages, software evaluation techniques, and software evaluation criteria in evaluating software packages before providing an explanation of the developed methodology adopted. The key findings of the study are: (1) that there is a need to create a framework for software selection methodologies, (2) there are no universal selection criteria in the engineering industry, and (3) there is a need to validate the findings by creating an application based on the evaluation technique and evaluation criteria for selecting software packages for the engineering industry. The findings of the study are offered to support organisations in the oil and gas sector improve software selection methodologies for SPIA.

Keywords: software evaluation, end user programs, soil pipeline analysis, software selection

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Authors: Iwuchukwu J. C., Mbah C.

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There seems to be dearth on information on how oil bean is being exploited, processed and conserved locally. This gap stifles initiatives on the evaluation of the suitability of the methods used and the invention of new and better methods. The study; therefore, assesses activities of processors in domestication/conservation and processing of oil bean (Pentaclethra macrophylla) Enugu State, South East Nigeria. Three agricultural zones, three blocks, nine circles and seventy-two respondents that were purposively selected made up the sample for the study. Data were presented in percentage, chart and mean score. The result shows that processors of oil bean in the area were middle-aged, married with relatively large household size and long years of experience in processing. They sourced oil bean they processed from people’s farmland and sourced information on processing of oil bean from friends and relatives. Activities involved in processing of oil bean were boiling, dehulling, washing, sieving, slicing, wrapping. However, the sequence of these activities varies among these processors. Little or nothing was done by the processors towards the conservation of the crop while poor storage and processing facilities and lack of knowledge on modern preservation technique were major constraints to processing of oil bean in the area. The study concluded that efforts should be made by governments and processors through cooperative group in provision of processing and storage facility for oil bean while research institute should conserve and generate improved specie of the crop to arouse interest of the farmers and processors on the crop which will invariably increase productivity.

Keywords: conservation, domestication, oil bean, processing

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Authors: U. Borasi, Amit Kr. Jain, Rakesh, Piyush Jain

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Data collection, data preparation, model training, model evaluation, and deployment are all processes in a typical machine learning workflow. Training data needs to be gathered and organised. This often entails collecting a sizable dataset and cleaning it to remove or correct any inaccurate or missing information. Preparing the data for use in the machine learning model requires pre-processing it after it has been acquired. This often entails actions like scaling or normalising the data, handling outliers, selecting appropriate features, reducing dimensionality, etc. This pre-processed data is then used to train a model on some machine learning algorithm. After the model has been trained, it needs to be assessed by determining metrics like accuracy, precision, and recall, utilising a test dataset. Every time a new model is built, both data pre-processing and model training—two crucial processes in the Machine learning (ML) workflow—must be carried out. Thus, there are various Machine Learning algorithms that can be employed for every single approach to data pre-processing, generating a large set of combinations to choose from. Example: for every method to handle missing values (dropping records, replacing with mean, etc.), for every scaling technique, and for every combination of features selected, a different algorithm can be used. As a result, in order to get the optimum outcomes, these tasks are frequently repeated in different combinations. This paper suggests a simple architecture for organizing this largely produced “combination set of pre-processing steps and algorithms” into an automated workflow which simplifies the task of carrying out all possibilities.

Keywords: machine learning, automation, AUTOML, architecture, operator pool, configuration, scheduler

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Authors: Tapas Goswami, Debabrata Goswami

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We have studied the changes in ground state recovery dynamics of IR 144 dye using degenerate transient absorption spectroscopy technique when going from homogeneous solution phase to heterogeneous partially miscible liquid/liquid interface. Towards this aim, we set up a partially miscible liquid/liquid interface in which dye is insoluble in one solvent carbon tetrachloride (CCl₄) layer and soluble in other solvent dimethyl sulphoxide (DMSO). A gradual increase in ground state recovery time of the dye molecule is observed from homogenous bulk solution to more heterogeneous environment interface layer. In the bulk solution charge distribution of dye molecule is in equilibrium with polar DMSO solvent molecule. Near the interface micro transportation of non-polar solvent, CCl₄ disturbs the solvent equilibrium in DMSO layer and it relaxes to a new equilibrium state corresponding to a new charge distribution of dye with a heterogeneous mixture of polar and non-polar solvent. In this experiment, we have measured the time required for the dye molecule to relax to the new equilibrium state in different heterogeneous environment. As a result, dye remains longer time in the excited state such that even it can populate more triplet state. The present study of ground state recovery dynamics of a cyanine dye molecule in different solvent environment provides the important characteristics of effect of solvation on excited life time of a dye molecule.

Keywords: excited state, ground state recovery, solvation, transient absorption

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Authors: Gholam Hossein Javanmard, Roghayeh Mohammadi Garegozlo

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The present study was a randomized three-group double-blind clinical trial with repeated measures designs which aimed to determine the pure effect and combined effect of mindfulness based-relaxation (MBR) technique and Transcranial Electrical Simulation (tCES) on psychological distress decreasing of patients with type-2 diabetes. The sample of the study consisted of 30 patients with type-2 diabetes who were selected from the Diabetes Association of Bonab city in Iran. The participants were matched and then randomly assigned to the three groups of 10 subjects (MBR, CES, MBR+CES). The subjects received interventions related to their group in 10 individual sessions. Pre-test, post-test, and one-month follow-up were conducted using DASS-42. Analysis of variance with repeated measures showed a significant change in psychological distress. Multivariate covariance analysis and the paired interpersonal comparative test of Ben Foruni indicated that both interventions of MBR and CES have a similar effect on psychological distress decreasing in the post-test and follow-up phase. But, the combined therapy of MBR+CES was more efficient, and it had a more stable effect. However, all three interventions, especially combined intervention of MBR+CES, as efficient and stable treatment, are suggested for improving the psychological status of diabetic patients.

Keywords: mindfulness based-relaxation, transcranial electrical simulation, type 2 diabetes, psychological distress

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Authors: Krishnaiah Arkanti, Ramulu Malothu

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The experiments have been conducted to study the mechanical properties of commercially pure copper processing at room temperature by severe plastic deformation using equal channel angular extrusion (ECAE) through a die of 90^oangle up to 3 passes by route B_C i.e. rotating the sample in the same direction by 90^o after each pass. ECAE is used to produce from existing coarse grains to ultra-fine, equiaxed grains structure with high angle grain boundaries in submicron level by introducing a large amount of shear strain in the presence of hydrostatic pressure into the material without changing billet shape or dimension. Mechanical testing plays an important role in evaluating fundamental properties of engineering materials as well as in developing new materials and in controlling the quality of materials for use in design and construction. Yield stress, ultimate tensile stress and ductility are structure sensitive properties and vary with the structure of the material. Microhardness and tensile tests were carried out to evaluate the hardness, strength and ductility of the ECAE processed materials. The results reveal that the strength and hardness of commercially pure copper samples improved significantly without losing much ductility after each pass.

Keywords: equal channel angular extrusion, severe plastic deformation, copper, mechanical properties

Procedia PDF Downloads 191

Authors: Zurong Liang

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Chinese social work has experienced a sharp rise in staff turnover. Work-family conflict is a key risk factor for employees’ turnover intention. While the relationship between work-family conflict and turnover intention has been widely documented, little is known about its mediating and moderating mechanisms, especially among social workers in China. This study explored the mediating role of job-based and collective psychological ownership and the moderating role of person-organization value congruence. The study drew on data from the China Social Work Longitudinal Study 2019, a nationally representative sample of 1,421 Chinese social workers (79.73% female; mean age = 28.9 years old). We performed a moderated mediation analysis combining a simple slope test and the Johnson-Neyman technique. Both job-based psychological ownership and collective psychological ownership were found to mediate the association between work-family conflict and turnover intention. Person-organization value congruence moderated the indirect relationship between work-family conflict and turnover intention via collective psychological ownership. This study enhances understanding of the impact of the psychological mechanisms of work-family conflict on Chinese social workers’ turnover intention. Specific strategies should be adopted to establish a work environment that supports psychological ownership, enhances social workers’ identification with and attachment to their organizations, and thus reduces their turnover intention.

Keywords: turnover, work-family conflict, ownership, social worker, China

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Authors: M. Y. Ismail, Arslan Kiyani

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Narrow bandwidth and high loss performance limits the use of reflectarray antennas in some applications. This article reports on the feasibility of employing strategic reflectarray resonant elements to characterize the reflectivity performance of reflectarrays in X-band frequency range. Strategic reflectarray resonant elements incorporating variable substrate thicknesses ranging from 0.016λ to 0.052λ have been analyzed in terms of reflection loss and reflection phase performance. The effect of substrate thickness has been validated by using waveguide scattering parameter technique. It has been demonstrated that as the substrate thickness is increased from 0.508mm to 1.57mm the measured reflection loss of dipole element decreased from 5.66dB to 3.70dB with increment in 10% bandwidth of 39MHz to 64MHz. Similarly the measured reflection loss of triangular loop element is decreased from 20.25dB to 7.02dB with an increment in 10% bandwidth of 12MHz to 23MHz. The results also show a significant decrease in the slope of reflection phase curve as well. A Figure of Merit (FoM) has also been defined for the comparison of static phase range of resonant elements under consideration. Moreover, a novel numerical model based on analytical equations has been established incorporating the material properties of dielectric substrate and electrical properties of different reflectarray resonant elements to obtain the progressive phase distribution for each individual reflectarray resonant element.

Keywords: numerical model, reflectarray resonant elements, scattering parameter measurements, variable substrate thickness

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Authors: Shivdayal Patel, Suhail Ahmad

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Safety assurance and failure prediction of composite material component of an offshore structure due to low velocity impact is essential for associated risk assessment. It is important to incorporate uncertainties associated with material properties and load due to an impact. Likelihood of this hazard causing a chain of failure events plays an important role in risk assessment. The material properties of composites mostly exhibit a scatter due to their in-homogeneity and anisotropic characteristics, brittleness of the matrix and fiber and manufacturing defects. In fact, the probability of occurrence of such a scenario is due to large uncertainties arising in the system. Probabilistic finite element analysis of composite plates due to low-velocity impact is carried out considering uncertainties of material properties and initial impact velocity. Impact-induced damage of composite plate is a probabilistic phenomenon due to a wide range of uncertainties arising in material and loading behavior. A typical failure crack initiates and propagates further into the interface causing de-lamination between dissimilar plies. Since individual crack in the ply is difficult to track. The progressive damage model is implemented in the FE code by a user-defined material subroutine (VUMAT) to overcome these problems. The limit state function is accordingly established while the stresses in the lamina are such that the limit state function (g(x)>0). The Gaussian process response surface method is presently adopted to determine the probability of failure. A comparative study is also carried out for different combination of impactor masses and velocities. The sensitivity based probabilistic design optimization procedure is investigated to achieve better strength and lighter weight of composite structures. Chain of failure events due to different modes of failure is considered to estimate the consequences of failure scenario. Frequencies of occurrence of specific impact hazards yield the expected risk due to economic loss.

Keywords: composites, damage propagation, low velocity impact, probability of failure, uncertainty modeling

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Authors: Abdullah Abdulsalam, Adamu Balami, Olajide Olubanji Olowe, Maryam Abdu Abdulkadir

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The development and persistence of low back pain may be influenced by several factors which include lifestyle factors, previous pain symptoms, psychological factors, workplace factors as well as socio-demographic variables. The focus of this study was to determine the socio-demographic and work related variables as a predictor of persistence of back pain and disability among civil servants receiving physiotherapy in tertiary health institutions in Kano, Nigeria. One hundred and twenty nine newly referred low back pain patients for physiotherapy participated in the study. This study was a cross sectional study involving patients that were newly diagnosed of back pain, referred and received physiotherapy. The convenience sampling technique was used to select the patients based on the inclusion criteria. The data obtained was analysed using simple percentage and multiple regression for stated hypothesis at 0.05 level of significance. The findings reveal that all the variables are not significant predictor of persistence of back pain and disability. The study recommended that determinants of low back pain recovery by clinician should include other clinical factors not only reduction in pain intensity.

Keywords: socio-demographic, work related variables, Kano state, back pain and disability

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Authors: Gabriel Sanjo Aruwajoye, E. B. Gueguim Kana

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Agricultural residues present a low-cost feedstock for bioenergy production around the world. Cassava peels waste are rich in organic molecules that can be readily converted to value added products such as biomaterials and biofuels. However, due to the presence of high proportion of structural carbohydrates and lignin, the hydrolysis of this feedstock is imperative to achieve maximum substrate utilization and energy yield. This study model and optimises the release of Fermentable Sugar (FS) from cassava peels waste using the Response Surface Methodology. The investigated pretreatment input parameters consisted of soaking temperature (oC), soaking time (hours), autoclave duration (minutes), acid concentration (% v/v), substrate solid loading (% w/v) within the range of 30 to 70, 0 to 24, 5 to 20, 0 to 5 and 2 to 10 respectively. The Box-Behnken design was used to generate 46 experimental runs which were investigated for FS release. The obtained data were used to fit a quadratic model. A coefficient of determination of 0.87 and F value of 8.73 was obtained indicating the good fitness of the model. The predicted optimum pretreatment conditions were 69.62 oC soaking temperature, 2.57 hours soaking duration, 5 minutes autoclave duration, 3.68 % v/v HCl and 9.65 % w/v solid loading corresponding to FS yield of 91.83g/l (0.92 g/g cassava peels) thus 58% improvement on the non-optimised pretreatment. Our findings demonstrate an efficient pretreatment model for fermentable sugar release from cassava peels waste for various bioprocesses.

Keywords: feedstock pretreatment, cassava peels, fermentable sugar, response surface methodology

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Authors: Samuel Abebe Ebebo

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Scale precipitation causes a major issue for geothermal power plants because it reduces the production rate of geothermal energy. Each geothermal power plant's different chemical and physical conditions can cause the scale to precipitate under a particular set of fluid-rock interactions. Depending on the mineral, it is possible to have scale in the production well, steam separators, heat exchangers, reinjection wells, and everywhere in between. The scale consists mainly of smectite and trace amounts of chlorite, magnetite, quartz, hematite, dolomite, aragonite, and amorphous silica. The smectite scale is one of the difficult scales at injection wells in geothermal power plants. X-ray diffraction and chemical composition identify this smectite as Stevensite. The characteristics and the scale of each injection well line are different depending on the fluid chemistry. The smectite scale has been widely distributed in pipelines and surface plants. Mineral water equilibrium showed that the main factors controlling the saturation indices of smectite increased pH and dissolved Mg concentration due to the precipitate on the equipment surface. This study aims to characterize the scales and geothermal fluids collected from the Onuma geothermal power plant in Akita Prefecture, Japan. Field tests were conducted on October 30–November 3, 2021, at Onuma to determine the pH control methods for preventing magnesium silicate scaling, and as exemplified, the formation of magnesium silicate hydrates (M-S-H) with MgO to SiO2 ratios of 1.0 and pH values of 10 for one day has been studied at 25 °C. As a result, M-S-H scale formation could be suppressed, and stevensite formation could also be suppressed when we can decrease the pH of the fluid by less than 8.1, 7.4, and 8 (at 97 °C) in the fluid from O-3Rb and O-6Rb, O-10Rg, and O-12R, respectively. In this context, the scales and fluids collected from injection wells at a geothermal power plant in Japan were analyzed and characterized to understand the formation conditions of Mg-silicate scales with on-site synthesis experiments. From the results of the characterizations and on-site synthesis experiments, the inhibition method of their scale formation is discussed based on geochemical modeling in this study.

Keywords: magnesium silicate, scaling, inhibitor, geothermal power plant

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Authors: İlkay Özer Erselcan, Abdi Kükner, Gökhan Ceylan

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The power generated by eight point absorber type wave energy converters each having a different buoy are calculated in order to investigate the performances of buoys in this study. The calculations are carried out by modeling three different sea states observed in two different locations in the Black Sea. The floats analyzed in this study have two basic geometries and four different draft/radius (d/r) ratios. The buoys possess the shapes of a semi-ellipsoid and a semi-elliptic paraboloid. Additionally, the draft/radius ratios range from 0.25 to 1 by an increment of 0.25. The radiation forces acting on the buoys due to the oscillatory motions of these bodies are evaluated by employing a 3D panel method along with a distribution of 3D pulsating sources in frequency domain. On the other hand, the wave forces acting on the buoys which are taken as the sum of Froude-Krylov forces and diffraction forces are calculated by using linear wave theory. Furthermore, the wave energy converters are assumed to be taut-moored to the seabed so that the secondary body which houses a power take-off system oscillates with much smaller amplitudes compared to the buoy. As a result, it is assumed that there is not any significant contribution to the power generation from the motions of the housing body and the only contribution to power generation comes from the buoy. The power take-off systems of the wave energy converters are high pressure oil hydraulic systems which are identical in terms of their characteristic parameters. The results show that the power generated by wave energy converters which have semi-ellipsoid floats is higher than that of those which have semi elliptic paraboloid floats in both locations and in all sea states. It is also determined that the power generated by the wave energy converters follow an unsteady pattern such that they do not decrease or increase with changing draft/radius ratios of the floats. Although the highest power level is obtained with a semi-ellipsoid float which has a draft/radius ratio equal to 1, other floats of which the draft/radius ratio is 0.25 delivered higher power that the floats with a draft/radius ratio equal to 1 in some cases.

Keywords: Black Sea, buoys, hydraulic power take-off system, wave energy converters

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Authors: Fidelia A. Orji, Julita Vassileva

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This research aims to develop machine learning models for students' academic performance and study strategy prediction, which could be generalized to all courses in higher education. Key learning attributes (intrinsic, extrinsic, autonomy, relatedness, competence, and self-esteem) used in building the models are chosen based on prior studies, which revealed that the attributes are essential in students’ learning process. Previous studies revealed the individual effects of each of these attributes on students’ learning progress. However, few studies have investigated the combined effect of the attributes in predicting student study strategy and academic performance to reduce the dropout rate. To bridge this gap, we used Scikit-learn in python to build five machine learning models (Decision Tree, K-Nearest Neighbour, Random Forest, Linear/Logistic Regression, and Support Vector Machine) for both regression and classification tasks to perform our analysis. The models were trained, evaluated, and tested for accuracy using 924 university dentistry students' data collected by Chilean authors through quantitative research design. A comparative analysis of the models revealed that the tree-based models such as the random forest (with prediction accuracy of 94.9%) and decision tree show the best results compared to the linear, support vector, and k-nearest neighbours. The models built in this research can be used in predicting student performance and study strategy so that appropriate interventions could be implemented to improve student learning progress. Thus, incorporating strategies that could improve diverse student learning attributes in the design of online educational systems may increase the likelihood of students continuing with their learning tasks as required. Moreover, the results show that the attributes could be modelled together and used to adapt/personalize the learning process.

Keywords: classification models, learning strategy, predictive modeling, regression models, student academic performance, student motivation, supervised machine learning

Procedia PDF Downloads 132

Authors: Jaiprakash Dargad

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CdMnSe dilute semiconductor or semimagnetic semiconductors have become the focus of intense research due to their interesting combination of magnetic and semiconducting properties, and are employed in a variety of devices including solar cells, gas sensors etc. A series of thin films of this material, Cd1−xMnxSe (0 ≤ x ≤ 0.5), were therefore synthesized onto precleaned amorphous glass substrates using a solution growth technique. The sources of cadmium (Cd2+) and manganese (Mn2+) were aqueous solutions of cadmium sulphate and manganese sulphate, and selenium (Se2−) was extracted from a reflux of sodium selenosulphite. The different deposition parameters such as temperature, time of deposition, speed of mechanical churning, pH of the reaction mixture etc were optimized to yield good quality deposits. The as-grown samples were thin, relatively uniform, smooth and tightly adherent to the substrate support. The colour of the deposits changed from deep red-orange to yellowish-orange as the composition parameter, x, was varied from 0 to 0.5. The terminal layer thickness decreased with increasing value of, x. The optical energy gap decreased from 1.84 eV to 1.34 eV for the change of x from 0 to 0.5. The coefficient of optical absorption is of the order of 10-4 - 10-5 cm−1 and the type of transition (m = 0.5) is of the band-to-band direct type. The dc electrical conductivities were measured at room temperature and in the temperature range 300 K - 500 K. It was observed that the room temperature electrical conductivity increased with the composition parameter x up to 0.1, gradually decreasing thereafter. The thermo power measurements showed n-type conduction in these films.

Keywords: dilute semiconductor, reflux, CBD, thin film

Procedia PDF Downloads 233

Authors: Xiao Yang, Ji Zhang, Yingli Song, Hui Huang, Jing Zhang, Yan Wang, Rongrong Han, Zhixuan Xiang, Lu Chen, Lingling Gao

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Aim and Objectives: To examine physical activity self-efficacy, identify its predictors, and further explore the mechanism of action among the predictors in mainland Chinese pregnant women with high risk for gestational diabetes mellitus (GDM). Background: Physical activity could protect pregnant women from developing GDM. Physical activity self-efficacy was the key predictor of physical activity. Design: A cross-sectional study was conducted from October 2021 to May 2022 in Zhengzhou, China. Methods: 252 eligible pregnant women completed the Pregnancy Physical Activity Self-efficacy Scale, the Social Support for Physical Activity Scale, the Knowledge on Physical Activity Questionnaire, the 7-item Generalized Anxiety Disorder scale, the Edinburgh Postnatal Depression Scale, and a socio-demographic data sheet. Multiple linear regression was applied to explore the predictors of physical activity self-efficacy. Structural equation modeling was used to explore the mechanism of action among the predictors. Results: Chinese pregnant women with a high risk for GDM reported a moderate level of physical activity self-efficacy. The best-fit regression analysis revealed four variables explained 17.5% of the variance in physical activity self-efficacy. Social support for physical activity was the strongest predictor, followed by knowledge of the physical activity, intention to do physical activity, and anxiety symptoms. The model analysis indicated that knowledge of physical activity could release anxiety and depressive symptoms and then increase physical activity self-efficacy. Conclusion: The present study revealed a moderate level of physical activity self-efficacy. Interventions targeting pregnant women with high risk for GDM need to include the predictors of physical activity self-efficacy. Relevance to clinical practice: To facilitate pregnant women with high risk for GDM to engage in physical activity, healthcare professionals may find assess physical activity self-efficacy and intervene as soon as possible on their first antenatal visit. Physical activity intervention programs focused on self-efficacy may be conducted in further research.

Keywords: physical activity, gestational diabetes, self-efficacy, predictors

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Authors: Bahattin Abay

Abstract:

Thin film of polycyclic aromatic hydrocarbon rubrene, C₄₂H₂₈ (5,6,11,12-tetraphenyltetracene), has been surfaced on Moderately Doped (MD) n-InP substrate as an interfacial layer by means of spin coating technique for the electronic modification of Au/MD n-InP structure. Ex situ annealing has been carried out at 150 °C for three minutes under a brisk flow of nitrogen for the better adhesion of the deposited film with the substrate surface. Room temperature electrical characterization has been performed on the C₄₂H₂₈/MD n-InP hybrid junctions by current-voltage (I-V) and capacitance-voltage (C-V) measurement in the dark. It has been seen that the C₄₂H₂₈/MD n-InP structure demonstrated extraordinary rectifying behavior. An effective barrier height (BH) as high as 0.743 eV, along with an ideality factor very close to unity (n=1.203), has been achieved for C₄₂H₂₈/n-InP organic/inorganic device. A thin C₄₂H₂₈ interfacial layer between Au and MD n-InP also reduce the reverse leakage current by almost four orders of magnitude and enhance the BH about 0.278 eV. This good performance of the device is ascribed to the passivation effect of organic interfacial layer between Au and n-InP. By using C-V measurement, in addition, the value of BH of the C₄₂H₂₈/n-InP organic/inorganic hybrid junctions have been obtained as 0.796 eV. It has been seen that both of the BH value (0.743 and 0.796 eV) for the organic/inorganic hybrid junction obtained I-V and C-V measurement, respectively are significantly larger than that of the conventional Au/n-InP structure (0.465 and 0.503 eV). It was also seen that the device had good sensitivity to the light under 100 mW/cm² illumination conditions. The obtained results indicated that modification of the interfacial potential barrier for Metal/n-InP junctions might be attained using polycyclic aromatic hydrocarbon thin interlayer C₄₂H₂₈.

Keywords: I-V and C-V measurements, heterojunction, n-InP, rubrene, surface passivation

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Authors: Muhammad Ajmair

Abstract:

This empirical study followed structural vector auto regression (SVAR) approach proposed by the so-called AB-model of Amisano and Giannini (1997) to check the impact of relevant macroeconomic determinants on economic growth in Pakistan. Before that auto regressive distributive lag (ARDL) bound testing technique and time varying parametric approach along with general to specific approach was employed to find out relevant significant determinants of economic growth. To our best knowledge, no author made such a study that employed auto regressive distributive lag (ARDL) bound testing and time varying parametric approach with general to specific approach in empirical literature, but current study will bridge this gap. Annual data was taken from World Development Indicators (2014) during period 1976-2014. The widely-used Schwarz information criterion and Akaike information criterion were considered for the lag length in each estimated equation. Main findings of the study are that remittances received, gross national expenditures and inflation are found to be the best relevant positive and significant determinants of economic growth. Based on these empirical findings, we conclude that government should focus on overall economic growth augmenting factors while formulating any policy relevant to the concerned sector.

Keywords: economic growth, gross national expenditures, inflation, remittances

Procedia PDF Downloads 201