Search results for: topic modeling

Authors: Buğra Sinmez

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In some countries, such as China, Turkey, andseveralEuropeanUnionnations, the therailwaypavementstructuralsystem has recently undergonerapid growth as a vital element of the transportation infrastructure, particularlyfortheuse of high-speed trains. It is vitaltoconsiderthe High-SpeedInfrastructureDemandwhendevelopingandconstructingtherailwaypavementstructure. HSRL can create more substantial ldifficultiestotheballastorbaselayer of regularlyusedballastedrailwaypavementsthanstandardrailwaytrains. The deterioration of the theballastorbaselayermayleadtosubstructuredegradation, which might lead to safety concerns and catastrophicincidents. As a result, the efficiency of railways will be impactedbylargecargoesorhigh-speed trains. A railwaypavement construction can be strengthened using geosyntheticmaterials in theballastorfoundationlayer as a countermeasure. However, there is still a need in the literature to quantifytheinfluence of geosynthetic materials, particularlygeogrid, on the mechanical responses of railwaypavementstructuresto HSRL loads which is essential knowledge in supporting the selection of appropriate material and geogridinstallationposition. As a result, the purpose of this research is to see how a geogridreinforcementlayermayaffectthekeyfeatures of a ballastedrailwaypavementstructure, with a particular focus on the materialtypeandgeogridplacementpositionthatmayassistreducethe rate of degradation of the therailwaypavementstructuresystem. Thisstudyusesnumericalmodeling in a genuinerailwaycontexttovalidatethebenefit of geogrid reinforcement. The usage of geogrids in the railway system has been thoroughly researched in the technical literature. Three distinct types of geogrid installed at two distinct positions (i.e.,withintheballastlayer, betweentheballastandthesub-ballast layer) within a railwaypavementconstructionwereevaluatedunder a variety of verticalwheelloadsusing a three-dimensional (3D) finite element model. As a result, fouralternativegeogridreinforcementsystemsweremodeledtoreflectdifferentconditions in the ballastedrailwaysystems (G0: no reinforcement; G1: reinforcedwithgeogridhavingthelowestdensityandYoung'smodulus; G2: reinforcedwithgeogridhavingtheintermediateYoung'smodulusanddensity; G3: reinforcedwithgeogridhavingthegreatestdensityandYoung'smodulus). Themechanicalreactions of the railway, such as verticalsurfacedeflection, maximumprimarystressandstrain, andmaximumshearstress, werestudiedandcomparedbetweenthefourgeogridreinforcementscenariosandfourverticalwheelloadlevels (i.e., 75, 100, 150, and 200 kN). Differences in the mechanical reactions of railwaypavementconstructionsowingtotheuse of differentgeogridmaterialsdemonstratethebenefits of suchgeosynthetics in ballast. In comparison to a non-reinforcedrailwaypavementconstruction, thereinforcedconstructionsfeaturedecreasedverticalsurfacedeflection, maximum shear stress at the sleeper-ballast contact, and maximum main stress at the bottom of the ballast layer. As a result, addinggeogridtotheballastlayerandbetweentheballastandsub-ballast layer in a ballastedrailwaypavementconstruction has beenfoundtolowercriticalshearand main stresses as well as verticalsurfacedeflection.

Keywords: geosynthetics, geogrid, railway, transportation

Procedia PDF Downloads 130

Authors: Sakkaphat T. Ngamake, Arunya Tuicomepee, Panrapee Suttiwan, Rewadee Watakakosol, Sompoch Iamsupasit

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Generally, 'positive' emotion regulation strategies such as cognitive reappraisal have linked to desirable outcomes while 'negative' strategies such as behavioral suppression have linked to undesirable outcomes. These trends have been found in both the elderly and professional practitioners. Hence, this study sought to investigate these trends further by examining the relationship between two dominant emotion regulation strategies in the literature (i.e., cognitive reappraisal and behavioral suppression) and well-being outcomes among the elderly (i.e., successful aging) and their caregivers (i.e., satisfaction with life), using the actor-partner interdependence model. A total of 150 elderly-caregiver dyads participated in the study. The elderly responded to two measures assessing the two emotion regulation strategies and successful aging while their caregivers responded to the same emotion regulation measure and a measure of satisfaction with life. Two criterion variables (i.e., successful aging and satisfaction with life) were specified as latent variables whereas four predictors (i.e., two strategies for the elderly and two strategies for their caregivers) were specified as observed variables in the model. Results have shown that, for the actor effect, the cognitive reappraisal strategy yielded positive relationships with the well-being outcomes for both the elderly and their caregivers. For the partner effect, a positive relationship between caregivers’ cognitive reappraisal strategy and the elderly’s successful aging was observed. The behavioral suppression strategy has not related to any well-being outcomes, within and across individual agents. This study has contributed to the literature by empirically showing that the mental activity of the elderly’s immediate environment such as their family members or close friends could affect their quality of life.

Keywords: emotion regulation, caregiver, older adult, well-being

Procedia PDF Downloads 398

Authors: Agada N. Ihuoma, Nagata Yasunori

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Artificial intelligence (AI) techniques play a crucial role in predicting the expected energy outcome and its performance, analysis, modeling, and control of renewable energy. Renewable energy is becoming more popular for economic and environmental reasons. In the face of global energy consumption and increased depletion of most fossil fuels, the world is faced with the challenges of meeting the ever-increasing energy demands. Therefore, incorporating artificial intelligence to predict solar radiation outcomes from the intermittent sunlight is crucial to enable a balance between supply and demand of energy on loads, predict the performance and outcome of solar energy, enhance production planning and energy management, and ensure proper sizing of parameters when generating clean energy. However, one of the major problems of forecasting is the algorithms used to control, model, and predict performances of the energy systems, which are complicated and involves large computer power, differential equations, and time series. Also, having unreliable data (poor quality) for solar radiation over a geographical location as well as insufficient long series can be a bottleneck to actualization. To overcome these problems, this study employs the anaconda Navigator (Jupyter Notebook) for machine learning which can combine larger amounts of data with fast, iterative processing and intelligent algorithms allowing the software to learn automatically from patterns or features to predict the performance and outcome of Solar Energy which in turns enables the balance of supply and demand on loads as well as enhance production planning and energy management.

Keywords: artificial Intelligence, backward elimination, linear regression, solar energy

Procedia PDF Downloads 136

Authors: Masoud Safdari, Jacob Fish

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Despite vast amount of existing theoretical knowledge, the implementation of a universal multiscale modeling, analysis, and simulation software framework remains challenging. Existing multiscale software and solutions are often domain-specific, closed-source and mandate a high-level of experience and skills in both multiscale analysis and programming. Furthermore, tools currently existing for Atomistic-to-Continuum (AtC) multiscaling are developed with the assumptions such as accessibility of high-performance computing facilities to the users. These issues mentioned plus many other challenges have reduced the adoption of multiscale in academia and especially industry. In the current work, we introduce Multiscale Hub (MsHub), an effort towards making AtC more accessible through cloud services. As a joint effort between academia and industry, MsHub provides a universal web-enabled framework for practical multiscaling. Developed on top of universally acclaimed scientific programming language Python, the package currently provides an open-source, comprehensive, easy-to-use framework for AtC coupling. MsHub offers an easy to use interface to prominent molecular dynamics and multiphysics continuum mechanics packages such as LAMMPS and MFEM (a free, lightweight, scalable C++ library for finite element methods). In this work, we first report on the design philosophy of MsHub, challenges identified and issues faced regarding its implementation. MsHub takes the advantage of a comprehensive set of tools and algorithms developed for AtC that can be used for a variety of governing physics. We then briefly report key AtC algorithms implemented in MsHub. Finally, we conclude with a few examples illustrating the capabilities of the package and its future directions.

Keywords: atomistic, continuum, coupling, multiscale

Procedia PDF Downloads 154

Authors: R. Ziaie Moayed, M. Mortezaee

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An important and influential factor in design and determining the safety factor in Soil Nailing is the ultimate pullout capacity, or, in other words, bond strength. This important parameter depends on several factors such as material and soil texture, method of implementation, excavation diameter, friction angle between the nail and the soil, grouting pressure, the nail depth (overburden pressure), the angle of drilling and the degree of saturation in soil. Federal Highway Administration (FHWA), a customary regulation in the design of nailing, is considered only the effect of the soil type (or rock) and the method of implementation in determining the bond strength, which results in non-economic design. The other regulations are each of a kind, some of the parameters affecting bond resistance are not taken into account. Therefore, in the present paper, at first the relationships and tables presented by several valid regulations are presented for estimating the ultimate pullout capacity, and then the effect of several important factors affecting on ultimate Pullout capacity are studied. Finally, it was determined, the effect of overburden pressure (in method of injection with pressure), soil dilatation and roughness of the drilling surface on pullout strength is incremental, and effect of degree of soil saturation on pullout strength to a certain degree of saturation is increasing and then decreasing. therefore it is better to get help from nail pullout-strength test results and numerical modeling to evaluate the effect of parameters such as overburden pressure, dilatation, and degree of soil saturation, and so on to reach an optimal and economical design.

Keywords: soil nailing, pullout capacity, federal highway administration (FHWA), grout

Procedia PDF Downloads 124

Authors: B. Kulaga, A. Cinti, F. J. Mazzocchini

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Despite the fact that growing academic attention on dark tourism is a fairly recent phenomenon, among the various reasons for travelling death-related ones, are very ancient. Furthermore, the darker side of human nature has always been fascinated and curious regarding death, or at least, man has always tried to learn lessons from death. This study proposes to describe the phenomenon of dark tourism related to the 2016 earthquake in Central Italy, deadly for 302 people and highly destructive for the rural areas of Lazio, Marche, and Umbria Regions. The primary objective is to examine the motivation-experience relationship in a dark tourism site, using the structural equation model, applied for the first time to a dark tourism research in 2016, in a study conducted after the Beichuan earthquake. The findings of the current study are derived from the calculations conducted on primary data compiled from 350 tourists in the areas mostly affected by the 2016 earthquake, including the town of Amatrice, near the epicenter, Castelluccio, Norcia, Ussita and Visso, through conducting a Likert scale survey. Furthermore, we use the structural equation model to examine the motivation behind dark travel and how this experience can influence the motivation and emotional reaction of tourists. Expected findings are in line with the previous study mentioned above, indicating that: not all tourists visit the thanatourism sites for dark tourism purpose, tourists’ emotional reactions influence more heavily the emotional tourist experience than cognitive experiences do, and curious visitors are likely to engage cognitively by learning about the incident or related issues.

Keywords: dark tourism, emotional reaction, experience, motivation, structural equation model

Procedia PDF Downloads 106

Authors: Amruta Rout, Golak Bihari Mahanta, Gunji Bala Murali, Bibhuti Bhusan Biswal, B. B. V. L. Deepak

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The use of industrial robots for performing welding operation is one of the chief sign of contemporary welding in these days. The weld joint parameter and weld process parameter modeling is one of the most crucial aspects of robotic welding. As weld process parameters affect the weld joint parameters differently, a multi-objective optimization technique has to be utilized to obtain optimal setting of weld process parameter. In this paper, a hybrid optimization technique, i.e., Principal Component Analysis (PCA) combined with fuzzy logic has been proposed to get optimal setting of weld process parameters like wire feed rate, welding current. Gas flow rate, welding speed and nozzle tip to plate distance. The weld joint parameters considered for optimization are the depth of penetration, yield strength, and ultimate strength. PCA is a very efficient multi-objective technique for converting the correlated and dependent parameters into uncorrelated and independent variables like the weld joint parameters. Also in this approach, no need for checking the correlation among responses as no individual weight has been assigned to responses. Fuzzy Inference Engine can efficiently consider these aspects into an internal hierarchy of it thereby overcoming various limitations of existing optimization approaches. At last Taguchi method is used to get the optimal setting of weld process parameters. Therefore, it has been concluded the hybrid technique has its own advantages which can be used for quality improvement in industrial applications.

Keywords: robotic arc welding, weld process parameters, weld joint parameters, principal component analysis, fuzzy logic, Taguchi method

Procedia PDF Downloads 154

Authors: Agâh Tuğrul Korucu, Ismail Fatih Yavuzaslan, Lale Toraman

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Nowadays, thanks to development of technology, integration of technology into teaching and learning activities is spreading. Increasing technological literacy which is one of the expected competencies for individuals of 21st century is associated with the effective use of technology in education. The most important factor in effective use of technology in education institutions is ICT teachers. The concept of computer assisted instruction (CAI) refers to the utilization of information and communication technology as a tool aided teachers in order to make education more efficient and improve its quality in the process of educational. Teachers can use computers in different places and times according to owned hardware and software facilities and characteristics of the subject and student in CAI. Analyzing teachers’ use of computers in education is significant because teachers are the ones who manage the course and they are the most important element in comprehending the topic by students. To accomplish computer-assisted instruction efficiently is possible through having positive attitude of teachers. Determination the level of knowledge, attitude and behavior of teachers who get the professional knowledge from educational faculties and elimination of deficiencies if any are crucial when teachers are at the faculty. Therefore, the aim of this paper is to identify ICT teachers' attitudes toward computer-assisted instruction in terms of different variables. Research group consists of 200 prospective ICT teachers studying at Necmettin Erbakan University Ahmet Keleşoğlu Faculty of Education CEIT department. As data collection tool of the study; “personal information form” developed by the researchers and used to collect demographic data and "the attitude scale related to computer-assisted instruction" are used. The scale consists of 20 items. 10 of these items show positive feature, while 10 of them show negative feature. The Kaiser-Meyer-Olkin (KMO) coefficient of the scale is found 0.88 and Barlett test significance value is found 0.000. The Cronbach’s alpha reliability coefficient of the scale is found 0.93. In order to analyze the data collected by data collection tools computer-based statistical software package used; statistical techniques such as descriptive statistics, t-test, and analysis of variance are utilized. It is determined that the attitudes of prospective instructors towards computers do not differ according to their educational branches. On the other hand, the attitudes of prospective instructors who own computers towards computer-supported education are determined higher than those of the prospective instructors who do not own computers. It is established that the departments of students who previously received computer lessons do not affect this situation so much. The result is that; the computer experience affects the attitude point regarding the computer-supported education positively.

Keywords: computer based instruction, teacher candidate, attitude, technology based instruction, information and communication technologies

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Authors: P. Hooshangitabrizi, I. Contreras, N. Bhuiyan

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This work presents an online scheduling problem which accommodates multiple requests of patients for chemotherapy treatments in a cancer center of a major metropolitan hospital in Canada. To solve the problem, an adaptive flexible approach is proposed which systematically combines two optimization models. The first model is intended to dynamically schedule arriving requests in the form of waiting lists whereas the second model is used to reschedule the already booked patients with the goal of finding better resource allocations when new information becomes available. Both models are created as mixed integer programming formulations. Various controllable and flexible parameters such as deviating the prescribed target dates by a pre-determined threshold, changing the start time of already booked appointments and the maximum number of appointments to move in the schedule are included in the proposed approach to have sufficient degrees of flexibility in handling arrival requests and unexpected changes. Several computational experiments are conducted to evaluate the performance of the proposed approach using historical data provided by the oncology clinic. Our approach achieves outstandingly better results as compared to those of the scheduling system being used in practice. Moreover, several analyses are conducted to evaluate the effect of considering different levels of flexibility on the obtained results and to assess the performance of the proposed approach in dealing with last-minute changes. We strongly believe that the proposed flexible adaptive approach is very well-suited for implementation at the clinic to provide better patient-care services and to utilize available resource more efficiently.

Keywords: chemotherapy scheduling, multi-appointment modeling, optimization of resources, satisfaction of patients, mixed integer programming

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Authors: Kim Toyer, Belinda Thompson, Louise Koelmeyer

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Lymphoedema is a chronic condition caused by dysfunction of the lymphatic system, which limits the drainage of fluid and tissue waste from the interstitial space of the affected body part. The normal physiological changes in pregnancy cause an increased load on a normal lymphatic system which can result in a transient lymphatic overload (oedema). The interaction between lymphoedema and pregnancy oedema is unclear. Women with pre-existing lymphoedema require accurate information and additional strategies to manage their lymphoedema during pregnancy. Currently, no resources are available to guide women or their healthcare providers with accurate advice and additional management strategies for coping with lymphoedema during pregnancy until they have recovered postnatally. This study explored the experiences of Australian women with pre-existing lymphoedema during recent pregnancy and the early postnatal period to determine how their usual lymphoedema management strategies were adapted and what were their additional or unmet needs. Interactions with their obstetric care providers, the hospital maternity services, and usual lymphoedema therapy services were detailed. Participants were sourced from several Australian lymphoedema community groups, including therapist networks. Opportunistic sampling is appropriate to explore this topic in a small target population as lymphoedema in women of childbearing age is uncommon, with prevalence data unavailable. Inclusion criteria were aged over 18 years, diagnosed with primary or secondary lymphoedema of the arm or leg, pregnant within the preceding ten years (since 2012), and had their pregnancy and postnatal care in Australia. Exclusion criteria were a diagnosis of lipedema and if unable to read or understand a reasonable level of English. A mixed-method qualitative design was used in two phases. This involved an online survey (REDCap platform) of the participants followed by online semi-structured interviews or focus groups to provide the transcript data for inductive thematic analysis to gain an in-depth understanding of issues raised. Women with well-managed pre-existing lymphoedema coped well with the additional oedema load of pregnancy; however, those with limited access to quality conservative care prior to pregnancy were found to be significantly impacted by pregnancy, including many reporting deterioration of their chronic lymphoedema. Misinformation and a lack of support increased fear and apprehension in planning and enjoying their pregnancy experience. Collaboration between maternity and lymphoedema therapy services did not happen despite study participants suggesting it. Helpful resources and unmet needs were identified in the recent Australian context to inform further research and the development of resources to assist women with lymphoedema who are considering or are pregnant and their supporters, including health care providers.

Keywords: lymphoedema, management strategies, pregnancy, qualitative

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Authors: T. Nakpun, T. Kanjanarach, T. Kittisopee

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Turnover of community pharmacist can affect continuity of patient care and most importantly the quality of care and also the costs of a pharmacy. It was hypothesized that organizational resources, job characteristics, and social supports had direct effect on pharmacist turnover intention, and indirect effect on pharmacist turnover intention via pharmacist engagement. This research aimed to study influencing factors on pharmacist engagement and pharmacist turnover intention by testing the proposed structural hypothesized model to explain the relationship among organizational resources, job characteristics, and social supports that effect on pharmacist turnover intention and pharmacist engagement in Thai community pharmacists. A cross sectional study design with self-administered questionnaire was conducted in 209 Thai community pharmacists. Data were analyzed using Structural Equation Modeling technique with analysis of a moment structures AMOS program. The final model showed that only organizational resources had significant negative direct effect on pharmacist turnover intention (β =-0.45). Job characteristics and social supports had significant positive relationship with pharmacist engagement (β = 0.44, and 0.55 respectively). Pharmacist engagement had significant negative relationship with pharmacist turnover intention (β = - 0.24). Thus, job characteristics and social supports had significant negative indirect effect on turnover intention via pharmacist engagement (β =-0.11 and -0.13, respectively). The model fit the data well (χ2/ degree of freedom (DF) = 2.12, the goodness of fit index (GFI)=0.89, comparative fit index (CFI) = 0.94 and root mean square error of approximation (RMSEA) = 0.07). This study can be concluded that organizational resources were the most important factor because it had direct effect on pharmacist turnover intention. Job characteristics and social supports were also help decrease pharmacist turnover intention via pharmacist engagement.

Keywords: community pharmacist, influencing factor, turnover intention, work engagement

Procedia PDF Downloads 165

Authors: Rowane May A. Fesalbon, Greyland C. Agno, Jodel L. Cuasay, Dindo A. Malonzo, Ma. Rosario Concepcion O. Ang

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The Department of Energy of the Republic of the Philippines estimates that the country’s energy reserves for 2015 are dwindling– observed in the rotating power outages in several localities. To aid in the energy crisis, a national hydropower resource assessment scheme is developed. Hydropower is a resource that is derived from flowing water and difference in elevation. It is a renewable energy resource that is deemed abundant in the Philippines – being an archipelagic country that is rich in bodies of water and water resources. The objectives of this study is to develop a methodology for a national hydropower resource assessment using hydrologic modeling and geospatial techniques in order to generate resource maps for future reference and use of the government and other stakeholders. The methodology developed for this purpose is focused on two models – the implementation of the Soil and Water Assessment Tool (SWAT) for the river discharge and the use of geospatial techniques to analyze the topography and obtain the head, and generate the theoretical hydropower potential sites. The methodology is highly coupled with Geographic Information Systems to maximize the use of geodatabases and the spatial significance of the determined sites. The hydrologic model used in this workflow is SWAT integrated in the GIS software ArcGIS. The head is determined by a developed algorithm that utilizes a Synthetic Aperture Radar (SAR)-derived digital elevation model (DEM) which has a resolution of 10-meters. The initial results of the developed workflow indicate hydropower potential in the river reaches ranging from pico (less than 5 kW) to mini (1-3 MW) theoretical potential.

Keywords: ArcSWAT, renewable energy, hydrologic model, hydropower, GIS

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Authors: Xiaohua Zhu, Lingling Ma, Yongguang Zhao

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Leaf Area Index (LAI) is a key structural characteristic of crops and plays a significant role in precision agricultural management and farmland ecosystem modeling. However, LAI retrieved from different resolution data contain a scaling bias due to the spatial heterogeneity and model non-linearity, that is, there is scale effect during multi-scale LAI estimate. In this article, a typical farmland in semi-arid regions of Chinese Inner Mongolia is taken as the study area, based on the combination of PROSPECT model and SAIL model, a multiple dimensional Look-Up-Table (LUT) is generated for multiple crops LAI estimation from unmanned aerial vehicle (UAV) hyperspectral data. Based on Taylor expansion method and computational geometry model, a scale transfer model considering both difference between inter- and intra-class is constructed for scale effect analysis of LAI inversion over inhomogeneous surface. The results indicate that, (1) the LUT method based on classification and parameter sensitive analysis is useful for LAI retrieval of corn, potato, sunflower and melon on the typical farmland, with correlation coefficient R2 of 0.82 and root mean square error RMSE of 0.43m2/m-2. (2) The scale effect of LAI is becoming obvious with the decrease of image resolution, and maximum scale bias is more than 45%. (3) The scale effect of inter-classes is higher than that of intra-class, which can be corrected efficiently by the scale transfer model established based Taylor expansion and Computational geometry. After corrected, the maximum scale bias can be reduced to 1.2%.

Keywords: leaf area index (LAI), scale effect, UAV-based hyperspectral data, look-up-table (LUT), remote sensing

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Authors: Ligang Wang, Theodoros Damartzis, Stefan Diethelm, Jan Van Herle, François Marechal

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Biogas production from anaerobic digestion of organic sludge from wastewater treatment as well as various urban and agricultural organic wastes is of great significance to achieve a sustainable society. Two upgrading approaches for cleaned biogas can be considered: (1) direct H₂ injection for catalytic CO₂ methanation and (2) CO₂ separation from biogas. The first approach usually employs electrolysis technologies to generate hydrogen and increases the biogas production rate; while the second one usually applies commercially-available highly-selective membrane technologies to efficiently extract CO₂ from the biogas with the latter being then sent afterward for compression and storage for further use. A straightforward way of utilizing the captured CO₂ is on-site catalytic CO₂ methanation. From the perspective of system complexity, the second approach may be questioned, since it introduces an additional expensive membrane component for producing the same amount of methane. However, given the circumstance that the sustainability of the produced biogas should be retained after biogas upgrading, renewable electricity should be supplied to drive the electrolyzer. Therefore, considering the intermittent nature and seasonal variation of renewable electricity supply, the second approach offers high operational flexibility. This indicates that these two approaches should be compared based on the availability and scale of the local renewable power supply and not only the technical systems themselves. Solid-oxide electrolysis generally offers high overall system efficiency, and more importantly, it can achieve simultaneous electrolysis of CO₂ and H₂O (namely, co-electrolysis), which may bring significant benefits for the case of CO₂ separation from the produced biogas. When taking co-electrolysis into account, two additional upgrading approaches can be proposed: (1) direct steam injection into the biogas with the mixture going through the SOE, and (2) CO₂ separation from biogas which can be used later for co-electrolysis. The case study of integrating SOE to a wastewater treatment plant is investigated with wind power as the renewable power. The dynamic production of biogas is provided on an hourly basis with the corresponding oxygen and heating requirements. All four approaches mentioned above are investigated and compared thermo-economically: (a) steam-electrolysis with grid power, as the base case for steam electrolysis, (b) CO₂ separation and co-electrolysis with grid power, as the base case for co-electrolysis, (c) steam-electrolysis and CO₂ separation (and storage) with wind power, and (d) co-electrolysis and CO₂ separation (and storage) with wind power. The influence of the scale of wind power supply is investigated by a sensitivity analysis. The results derived provide general understanding on the economic competitiveness of SOE for sustainable biogas upgrading, thus assisting the decision making for biogas production sites. The research leading to the presented work is funded by European Union’s Horizon 2020 under grant agreements n° 699892 (ECo, topic H2020-JTI-FCH-2015-1) and SCCER BIOSWEET.

Keywords: biogas upgrading, solid-oxide electrolyzer, co-electrolysis, CO₂ utilization, energy storage

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Authors: Yohannes Bisa Biramo

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This study examined the meditational role of surface acting and deep acting on the relationship between calling orientation and work engagement of teachers in secondary schools of Wolaita Zone, Wolaita, Ethiopia. A predictive non-experimental correlational design was performed among 300 secondary school teachers. Stratified random sampling followed by a systematic random sampling technique was used as the basis for selecting samples from the target population. To analyze the data, Structural Equation Modeling (SEM) was used to test the association between the independent variables and the dependent variables. Furthermore, the goodness of fit of the study variables was tested using SEM to see and explain the path influence of the independent variable on the dependent variable. Confirmatory factor analysis (CFA) was conducted to test the validity of the scales in the study and to assess the measurement model fit indices. The analysis result revealed that calling was significantly and positively correlated with surface acting, deep acting and work engagement. Similarly, surface acting was significantly and positively correlated with deep acting and work engagement. And also, deep acting was significantly and positively correlated with work engagement. With respect to mediation analysis, the result revealed that surface acting mediated the relationship between calling and work engagement and also deep acting mediated the relationship between calling and work engagement. Besides, by using the model of the present study, the school leaders and practitioners can identify a core area to be considered in recruiting and letting teachers teach, in giving induction training for newly employed teachers and in performance appraisal.

Keywords: calling, surface acting, deep acting, work engagement, mediation, teachers

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Authors: Luis C. Parra

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The significant wave height prediction is an issue of great interest in the field of coastal activities because of the non-linear behavior of the wave height and its complexity of prediction. This study aims to present a machine learning model to forecast the significant wave height of the oceanographic wave measuring buoys anchored at Mooloolaba of the Queensland Government Data. Modeling was performed by a multilayer perceptron neural network-genetic algorithm (GA-MLP), considering Relu(x) as the activation function of the MLPNN. The GA is in charge of optimized the MLPNN hyperparameters (learning rate, hidden layers, neurons, and activation functions) and wrapper feature selection for the window width size. Results are assessed using Mean Square Error (MSE), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE). The GAMLPNN algorithm was performed with a population size of thirty individuals for eight generations for the prediction optimization of 5 steps forward, obtaining a performance evaluation of 0.00104 MSE, 0.03222 RMSE, 0.02338 MAE, and 0.71163% of MAPE. The results of the analysis suggest that the MLPNNGA model is effective in predicting significant wave height in a one-step forecast with distant time windows, presenting 0.00014 MSE, 0.01180 RMSE, 0.00912 MAE, and 0.52500% of MAPE with 0.99940 of correlation factor. The GA-MLP algorithm was compared with the ARIMA forecasting model, presenting better performance criteria in all performance criteria, validating the potential of this algorithm.

Keywords: significant wave height, machine learning optimization, multilayer perceptron neural networks, evolutionary algorithms

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Authors: Can Huang, Xiaoliang Wang, Qingquan Liu

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Soil‒water coupling is an important process in landslide-generated impulse waves (LGIW) problems, accompanied by large deformation of soil, strong interface coupling and three-dimensional effect. A meshless particle method, smooth particle hydrodynamics (SPH) has great advantages in dealing with complex interface and multiphase coupling problems. This study presents an improved soil‒water coupled model to simulate LGIW problems based on an open source code DualSPHysics (v4.0). Aiming to solve the low efficiency problem in modeling real large-scale LGIW problems, graphics processing unit (GPU) acceleration technology is implemented into this code. An experimental example, subaerial landslide-generated water waves, is simulated to demonstrate the accuracy of this model. Then, the Huangtian LGIW, a real large-scale LGIW problem is modeled to reproduce the entire disaster chain, including landslide dynamics, fluid‒solid interaction, and surge wave generation. The convergence analysis shows that a particle distance of 5.0 m can provide a converged landslide deposit and surge wave for this example. Numerical simulation results are in good agreement with the limited field survey data. The application example of the Huangtian LGIW provides a typical reference for large-scale LGIW assessments, which can provide reliable information on landslide dynamics, interface coupling behavior, and surge wave characteristics.

Keywords: soil‒water coupling, landslide-generated impulse wave, large-scale, SPH

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Authors: Hamdi Beji, Toufik Kanit, Tanguy Messager

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This study aims to construct a predictive model proficient in foreseeing the linear elastic and thermal characteristics of composite materials, drawing on a multitude of influencing parameters. These parameters encompass the shape of inclusions (circular, elliptical, square, triangle), their spatial coordinates within the matrix, orientation, volume fraction (ranging from 0.05 to 0.4), and variations in contrast (spanning from 10 to 200). A variety of machine learning techniques are deployed, including decision trees, random forests, support vector machines, k-nearest neighbors, and an artificial neural network (ANN), to facilitate this predictive model. Moreover, this research goes beyond the predictive aspect by delving into an inverse analysis using genetic algorithms. The intent is to unveil the intrinsic characteristics of composite materials by evaluating their thermomechanical responses. The foundation of this research lies in the establishment of a comprehensive database that accounts for the array of input parameters mentioned earlier. This database, enriched with this diversity of input variables, serves as a bedrock for the creation of machine learning and genetic algorithm-based models. These models are meticulously trained to not only predict but also elucidate the mechanical and thermal conduct of composite materials. Remarkably, the coupling of machine learning and genetic algorithms has proven highly effective, yielding predictions with remarkable accuracy, boasting scores ranging between 0.97 and 0.99. This achievement marks a significant breakthrough, demonstrating the potential of this innovative approach in the field of materials engineering.

Keywords: machine learning, composite materials, genetic algorithms, mechanical and thermal proprieties

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Authors: Jaci Mastrandrea

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Background: The National Comprehensive Cancer Network (NCCN) recommends that healthcare institutions have established processes for integrating palliative care (PC) into cancer treatment and that all cancer patients be screened for PC needs upon initial diagnosis as well as throughout the entire continuum of care (National Comprehensive Cancer Network, 2021). Early PC screening is directly correlated with improved patient outcomes. The Sky Lakes Cancer Treatment Center (SLCTC) is an institution that has access to PC services yet does not have protocols in place for identifying patients with palliative needs or a standardized referral process. The aim of this quality improvement project is to improve early access to PC services by establishing a standardized screening and referral process for outpatient oncology patients. Method: The sample population included all adult patients with an oncology diagnosis who presented to the SLCTC for treatment during the project timeline from March 15th, 2022, to April 29th, 2022. The “Palliative and Supportive Needs Assessment'' (PSNA) screening tool was developed from validated and evidence-based PC referral criteria. The tool was initially implemented using paper forms and later was integrated into the Epic-Beacon EHR system. Patients were screened by registered nurses on the SLCTC treatment team. Nurses responsible for screening patients received an educational inservice prior to implementation. Patients with a PSNA score of three or higher were considered to be a positive screen. Scores of five or higher triggered a PC referral order in the patient’s EHR for the oncologist to review and approve. All patients with a positive screen received an educational handout on the topic of PC, and the EHR was flagged for follow-up. Results: Prior to implementation of the PSCNA screening tool, the SLCTC had zero referrals to PC in the past year, excluding referrals to hospice. Data was collected from the first 100 patient screenings completed within the eight-week data collection period. Seventy-three percent of patients met criteria for PC referral with a score greater than or equal to three. Of those patients who met referral criteria, 53.4% (39 patients) were referred for a palliative and supportive care consultation. Patients that were not referred to PC upon meeting the criteria were flagged in the EHR for re-screening within one to three months. Patients with lung cancer, chronic hematologic malignancies, breast cancer, and gastrointestinal malignancy most frequently met criteria for PC referral and scored highest overall on the scale of 0-12. Conclusion: The implementation of a standardized PC screening tool at the SLCTC significantly increased awareness of PC needs among cancer patients in the outpatient setting. Additionally, data derived from this quality improvement project supports the national recommendation for PC to be an integral component of cancer treatment across the entire continuum of care.

Keywords: oncology, palliative care, symptom management, symptom screening, ambulatory oncology, cancer, supportive care

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Authors: Kim Haekyoung, Au Yunkyoung

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As digital technology continues to advance and become more widely accessible, young children are also growing up experiencing various media from infancy. In this changing environment, educating young children on media literacy has become an increasingly important task. With the diversification of media, it has become more necessary for children to understand, utilize, and critically explore the meaning of multimodal texts, which include text, images, and sounds connected to each other. Early childhood is a period when media literacy can bloom, and educational and policy support are needed to enable young children to express their opinions, communicate, and participate fully. However, most current media literacy education for young children focuses solely on teaching how to use media, with limited practical application and utilization. Therefore, this study aims to develop an inquiry-based media literacy education program for young children using topic-specific media content and explore the program's potential and impact on children's media literacy learning. Based on a theoretical and literature review on media literacy education, analysis of existing educational programs, and a survey on the current status and teacher perception of media literacy education for young children, this study developed a media literacy education program for young children considering the components of media literacy (understanding media characteristics, self-regulation, self-expression, critical understanding, ethical norms, social communication). To verify the effectiveness of the program, it was implemented with 20 five-year-old children from C City S Kindergarten, starting from March 24 to May 26, 2022, once a week for a total of 6 sessions. To explore quantitative changes before and after program implementation, repeated-measures analysis of variance was conducted, and qualitative analysis was used to analyze observed changes in the process. significant improvement in media literacy levels, such as understanding media characteristics, self-regulation, self-expression, critical understanding, ethical norms, and social communication. The developed inquiry-based media literacy education program for young children in this study can be effectively applied to enhance children's media literacy education and help improve their media literacy levels. Observed changes in the process also confirmed that children improved their ability to learn various topics, express their thoughts, and communicate with others using media content. These findings emphasize the importance of developing and implementing media literacy education programs and can help children develop the ability to safely and effectively use media in their media environment. Based on exploring the potential and impact of the inquiry-based media literacy education program for young children, this study confirmed positive changes in children's media literacy levels as a result of the program's implementation. These findings suggest that beyond education on how to use media, it can help develop children's ability to safely and effectively use media in their media environment. Furthermore, to improve children's media literacy levels and create a safe media environment, a variety of content and methodologies are needed, and continuous development and evaluation of educational programs are anticipated.

Keywords: young children, media literacy, media literacy education program, media content

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Authors: Juan Huang, Hugo Ninanya

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Oil has been used as a source of energy and supply to make materials, such as asphalt or rubber for many years. This is the reason why new technologies have been implemented through time. However, research still needs to continue increasing due to new challenges engineers face every day, just like unconventional reservoirs. Various numerical methodologies have been applied in petroleum engineering as tools in order to optimize the production of reservoirs before drilling a wellbore, although not all of these have the same efficiency when talking about studying fracture propagation. Analytical methods like those based on linear elastic fractures mechanics fail to give a reasonable prediction when simulating fracture propagation in ductile materials whereas numerical methods based on the cohesive zone method (CZM) allow to represent the elastoplastic behavior in a reservoir based on a constitutive model; therefore, predictions in terms of displacements and pressure will be more reliable. In this work, a hydro-geomechanical coupled model of horizontal wells in fractured rock was developed using ABAQUS; both extended element method and cohesive elements were used to represent predefined fractures in a model (2-D). A power law for representing the rheological behavior of fluid (shear-thinning, power index <1) through fractures and leak-off rate permeating to the matrix was considered. Results have been showed in terms of aperture and length of the fracture, pressure within fracture and fluid loss. It was showed a high infiltration rate to the matrix as power index decreases. A sensitivity analysis is conclusively performed to identify the most influential factor of fluid loss.

Keywords: fracture, hydro-geomechanical model, non-Newtonian fluid, numerical analysis, sensitivity analysis

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Authors: Hui-mei Huang, Huei-Jiun Cheng

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Introduction Many patients are aware of the health benefits associated with an active lifestyle, but they are often hindered from engaging in physical activity due to the presence of pain. The majority of patients experience pain, which can fluctuate over time and is influenced by various factors, including gender. Gender differences in clinical pain and pain-related conditions are widely recognized. Existing literature strongly supports the notion that men and women exhibit distinct responses to pain. Previous studies conducted in Taiwan have highlighted gender differences in pain assessment, but only a limited number of studies have investigated the gender-related factors that influence pain during daily activities. The objective of this study was to examine gender differences in pain assessment among inpatients in Taiwan and investigate whether gender and surgical procedures are factors that impact the daily activities of pain. Method In this study, a prospective and structured questionnaire survey method was utilized, employing intentional sampling to gather data from inpatients admitted to a medical center in central Taiwan. The research period covered in this study is from October 1, 2019, to June 30, 2020. In this study, participants who were hospitalized within 48 hours were requested to self-assess their pain using the Numeric Rating Scale (NRS) and indicate the impact of pain on their activities. The data were analyzed to explore the potential influence of gender and surgical procedures on daily activities affected by pain. Result A total of 722 cases were included in the study, with the mean age of the subjects is 54.38 years old (SD=16.3), and the range varied from 18 to 93 years old. Among the subjects, 48.23% (n=348) were male, and 62.3% (n=450) of them had received more than 12 years of education., and 56.9% (n=411) underwent surgery. The results indicated that regardless of whether the participants underwent surgery or not, females experienced higher perceived severe pain intensity than males (t=2.248, P < .05). However, in surgical patients, there was no significant difference in gender (t=1.75, P > .05). Regarding the impact of pain on daily activities when pain intensity reached 7 , male subjects experienced a 5-point effect on their daily activities (AUC=0.84, 95% CI 0.79-0.89, P <0.01), while female subjects experienced a 7-point effect (AUC=0.88, 95% CI 0.80-0.87, P <0.01). Discussion Some studies suggest that women experience painful stimuli as more intense than men, this difference has been observed in various types of experimental pain, including mechanical and thermal stimuli. Our study reached the same conclusion, female patients exhibited greater intensity of pain. According to the research findings, The research findings highlight the significant impact of gender on individuals' response to intense pain (NRS>7) during their daily activities, with men showing a higher pain tolerance. The higher pain tolerance often observed in men may be attributed to societal conditioning, which encourages them to conceal outward expressions of pain. Further research in this area could help provide a more comprehensive understanding of the topic in Taiwan.

Keywords: pain assessment, gender, surgery, activities of daily living

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Authors: Armin Eilaghi, Ahmad Sedaghat, Hayder Abdurazzak, Fadi Alkhatib, Shiva Sadeghi, Martin Jaeger

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A summary of experiences, recommendations, and lessons learnt in the application of PBL in the course of “Engineering Skills” in the School of Engineering at Australian College of Kuwait in Kuwait is presented. Four projects were introduced as part of the PBL course “Engineering Skills” to 24 students in School of Engineering. These students were grouped in 6 teams to develop their skills in 10 learning outcomes. The learning outcomes targeted skills such as drawing, design, modeling, manufacturing and analysis at a preliminary level; and also some life line learning and teamwork skills as these students were exposed for the first time to the PBL (project based learning). The students were assessed for 10 learning outcomes of the course and students’ feedback was collected using an anonymous survey at the end of the course. Analyzing the students’ feedbacks, it is observed that 67% of students preferred multiple smaller projects than a single big project because it provided them with more time and attention focus to improve their “soft skills” including project management, risk assessment, and failure analysis. Moreover, it is found that 63% of students preferred to work with different team members during the course to improve their professional communication skills. Among all, 62% of students believed that working with team members from other departments helped them to increase the innovative aspect of projects and improved their overall performance. However, 70% of students counted extra time needed to regenerate momentum with the new teams as the major challenge. Project based learning provided a suitable platform for introducing students to professional engineering practice and meeting the needs of students, employers and educators. It was found that students achieved their 10 learning outcomes and gained new skills developed in this PBL unit. This was reflected in their portfolios and assessment survey.

Keywords: project-based learning, engineering skills, undergraduate engineering, problem-based learning

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Authors: Riad Benelmir, Muhammad Shoaib Ahmed Khan

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The socio-economic importance of the olive oil production is significant in the Mediterranean region, both in terms of wealth and tradition. However, the extraction of olive oil generates huge quantities of wastes that may have a great impact on land and water environment because of their high phytotoxicity. Especially olive mill wastewater (OMWW) is one of the major environmental pollutants in olive oil industry. This work projects to design a smart and sustainable integrated thermochemical catalytic processes of residues from olive mills by hydrothermal carbonization (HTC) of olive mill wastewater (OMWW) and fast pyrolysis of olive mill wastewater sludge (OMWS). The byproducts resulting from OMWW-HTC treatment are a solid phase enriched in carbon, called biochar and a liquid phase (residual water with less dissolved organic and phenolic compounds). HTC biochar can be tested as a fuel in combustion systems and will also be utilized in high-value applications, such as soil bio-fertilizer and as catalyst or/and catalyst support. The HTC residual water is characterized, treated and used in soil irrigation since the organic and the toxic compounds will be reduced under the permitted limits. This project’s concept includes also the conversion of OMWS to a green diesel through a catalytic pyrolysis process. The green diesel is then used as biofuel in an internal combustion engine (IC-Engine) for automotive application to be used for clean transportation. In this work, a theoretical study is considered for the use of heat from the pyrolysis non-condensable gases in a sorption-refrigeration machine for pyrolysis gases cooling and condensation of bio-oil vapors.

Keywords: biomass, olive oil extraction, adsorption cooling, pyrolisis

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Authors: Asghar Ali, Narjis Khatoon

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This study focuses on the presence of wage differentials in Pakistan and also on the determinants that originate it. Since there are a smaller number of studies that are conducted on this topic in Pakistan, the current study aims to contribute in bridging the existing gap in this particular research genre. Hence, this study not only generates the desired results specific focus but it also contributes to the overall empirical work on the Pakistan economy. The preceding works which have been done to research wage determinants and wage differentials have used numerous different theories and approaches to reach their goals. The current study, in order to analyze the determinants of wage differentials in the developing economy, deals with the study of a number of such theories and approaches that are supposed as being beneficial for the purpose. This study undertakes the explanation of wage differentials in Pakistan by focusing on wage differentials in public and private sectors, formal and informal sectors, and major occupational groups. The study uses 'Wage Theory' to examine wage differentials among male and female employees in public and private sectors on varied levels of working conditions. This study also uses 'Segmented Labor Market Theory' to determine the wage differential in both public and private sectors, formal and informal, and major occupational groups in Pakistan. So the author has used various econometric techniques in order to explain and test these theories and to find out the required results. This study has employed seven different cross-sectional Labour Force Surveys for the time period between 2006-07 to 2012-13. Gender equality is not only a policy reform agenda for developing countries but also an important goal of Millennium Development Goals. This study investigates the nexus between wage inequality and economic growth and detects co-integration between gender wage differential and economic growth using ARDL bound test. It is confirmed from the empirical results that there exists long-run relationship between economic growth and wage differential. Our study indicated that half of the total female employees from fourteen major cities of Pakistan were employed in the public sector. Out of total female employees in private sector, 66 percent are employed in the formal sector, and 33 percent are working in the informal sector. Results also indicated that both men and women were paid more in the public sector compared to the private sector counterparts. Among the total female employees, only 9 percent had received any formal training, 52% were married and average years of schooling were 11 years. Further, our findings regarding wage differential between genders indicate that wage gap is lower in public sector as compared to private sector. In proportion, gender wage ratio was found to be 0.96, 0.62 and 0.66 in public, formal private and informal private sectors respectively. This suggests that in this case, private sector female employees with the same pay structure are compensated at a lower endowments rate as then public sector workers as compared to their counter parts.

Keywords: wage differentials, formal, informal, economic growth

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Authors: Muhammad Umar Kiani, Muhammad Shahbaz

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Performance of any vehicle can be predicted by its design/modeling and optimization. Design optimization leads to efficient performance. Followed by horizontal launch, the air launch re-entry vehicle undergoes a launch maneuver by introducing a carefully selected angle of attack profile. This angle of attack profile is the basic element to complete a specified mission. Flight program of said vehicle is optimized under the constraints of the maximum allowed angle of attack, lateral and axial loads and with the objective of reaching maximum altitude. The main focus of this study is the endo-atmospheric phase of the ascent trajectory. A three degrees of freedom trajectory model is simulated in MATLAB. The optimization process uses evolutionary algorithm, because of its robustness and efficient capacity to explore the design space in search of the global optimum. Evolutionary Algorithm based trajectory optimization also offers the added benefit of being a generalized method that may work with continuous, discontinuous, linear, and non-linear performance matrix. It also eliminates the requirement of a starting solution. Optimization is particularly beneficial to achieve maximum advantage without increasing the computational cost and affecting the output of the system. For the case of launch vehicles we are immensely anxious to achieve maximum performance and efficiency under different constraints. In a launch vehicle, flight program means the prescribed variation of vehicle pitching angle during the flight which has substantial influence reachable altitude and accuracy of orbit insertion and aerodynamic loading. Results reveal that the angle of attack profile significantly affects the performance of the vehicle.

Keywords: endo-atmospheric, evolutionary algorithm, efficient performance, optimization process

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Authors: Amita Rana

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From the ancient to modern times, the nature of fitness activities has varied. We can choose any form of exercise that is suitable for our particular need. Watchers of fitness trends say that the road to better health is paved with new possibilities along with some old ones that are poised to make a comeback. Educated, certified and experienced fitness professionals; strength training; fitness programmes for older adults; exercise and weight loss; children and obesity; personal training; core training; group personal training; Zumba and other dance workouts; functional fitness; yoga; comprehensive health promotion programmes at worksite; boot-camp; outdoor activities; reaching new markets; spinning; sport-specific training; worker incentive programmes; wellness coaching; and physician referrals are among the fitness trends included in worldwide surveys. However, trends related to fitness in India could be the same or different. Hence, the present paper makes an attempt to analyze the latest fitness trends in India. A total of eighteen (18) surveys were shortlisted on the basis of their relevance to the present topic of study and were arranged in descending order of their chronology. Content analysis was done after the preliminary set of data collection, which formed the basis of a group of data. Further, frequency and percentage were used to statistically represent the data. It can be concluded from the analysis of data regarding recent fitness trends in India that yoga dominates the fitness activity list, followed by numerous other activities including running, Zumba and sh’bam, boot camp, boxing, kickboxing, cycling, swimming, TRX, ass-pocalypse, ballet, biking, bokwa fitness, dance-iso-bic, masala bhangra, outdoor activities, pilates, planks, push-ups, sofa workouts, stairs Workouts, tabata training, and twerking. The body weight/ gym-specified/ strength training as well as high intensity interval training dominate the preferred workouts; followed by mixed work-outs, cross training work-outs, express work-outs, functional fitness, natural body movements, personalized training, and stay-at-home workouts. General areas that featured in the latest fitness trends in India demonstrates that the fitness is making an impact on all sections of the society be it children, women, older adults, senior citizens, worksite fitness. Fitness is becoming the lifestyle of the masses. People are doing exercise for weight-loss, combining diet with exercising; prefer sweating, making groups participate in fitness activities and wellness programmes. Technology is another area which has a high impact on the lives of people. They are using wearable technology for workout tracking and following numerous mobile friendly apps.

Keywords: fitness, India, survey, trend

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Authors: Fei Wang, Jie Meng, Qingxiang Meng

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China is rich in straw and by-product resources, whose utilization has always been a hot topic. The objective of this study was to investigate the effect of feeding soybean straw and wine distiller’s grain as a replacement for corn stover on performance of beef cattle. Sixty Simmental×local crossbred bulls averaging 12 months old and 335.7 ± 39.1 kg of body weight (BW) were randomly assigned into four groups (15 animals per group) and allocated to a diet with 40% maize stover (MSD), a diet with 40% wrapping package maize silage (PMSD), a diet with 12% soybean straw plus 28% maize stover (SSD) and a diet with 12% wine distiller’s grain plus 28% maize stover (WDD). Bulls were fed ad libitum an TMR consisting of 36.0% maize, 12.5% of DDGS, 5.0% of cottonseed meal, 4.0% of soybean meal and 40.0% of by-product as described above. Treatment period lasted for 22 weeks, consisting of 1 week of dietary adaptation. The results showed that dry matter intake (DMI) was significantly higher (P < 0.01) for PMSD group than MSD and SSD groups during 0-7 week and 8-14week, and PMSD and WDD groups had higher (P < 0.05) DMI values than MSD and SSD groups during the whole period. Average daily gain (ADG) values were 1.56, 1.72, 1.68 and 1.58 kg for MSD, PMSD, SSD and WDD groups respectively, although the differences were not significant (P > 0.05). The value of blood sugar concentration was significantly higher (P < 0.01) for MSD group than WDD group, and the blood urea nitrogen concentration of SSD group was lower (P < 0.05) than MSD and WDD groups. No significant difference (P > 0.05) of serum total cholesterol, triglycerides or total protein content was observed among the different groups. Ten bulls with similar body weight were selected at the end of feeding trial and slaughtered for measurement of slaughtering performance, carcass quality and meat chemical composition. SSD group had significantly lower (P < 0.05) shear force value and cooking loss than MSD and PMSD groups. The pH values of MSD and SSD groups were lower (P < 0.05) than PMSD and WDD groups. WDD group had a higher fat color brightness (L*) value than PMSD and SSD groups. There were no significant differences in dressing percentage, meat percentage, top grade meat weight, ribeye area, marbling score, meat color and meat chemical compositions among different dietary treatments. Based on these results, the packed maize stover silage showed a potential of improving the average daily gain and feed intake of beef cattle. Soybean straw had a significant effect on improving the tenderness and reducing cooking loss of beef. In general, soybean straw and packed maize stover silage would be beneficial to nitrogen deposition and showed a potential to substitute maize stover in beef cattle diets.

Keywords: beef cattle, by-products, carcass quality, growth performance

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Authors: Abubakar Mukhtar Yakasai, Muhammad Tahir Jan

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Purpose: This paper is aimed at exploring factors influencing online shopping intention among the young consumers in Nigeria. Design/Methodology/approach: The paper adopted and extended Technology Acceptance Model (TAM) as the basis for literature review. Additionally, the paper proposed a framework with the inclusion of culture as a moderating factor of consumer online shopping intention among consumers in Nigeria. Findings: Despite high rate of internet penetration in Nigerian, as well as the rapid advancement of online shopping in the world, little attention was paid to this important revolution specifically among Nigeria’s consumers. Based on the review of extant literature, the TAM extended to include perceived risk and enjoyment (PR and PE) was discovered to be a better alternative framework for predicting Nigeria’s young consumers’ online shopping intention. The moderating effect of culture in the proposed model is shown to help immensely in ascertaining differences, if any, between various cultural groups among online shoppers in Nigeria. Originality/ value: The critical analysis of different factors will assist practitioners (like online retailers, e-marketing managers, website developers, etc.) by signifying which combinations of factors can best predict consumer online shopping behaviour in particular instances, thereby resulting in effective value delivery. Online shopping is a newly adopted technology in Nigeria, hence the paper will give a clear focus for effective e-marketing strategy. In addition, the proposed framework in this paper will guide future researchers by providing a tool for systematic evaluation and testing of real empirical situation of online shopping in Nigeria.

Keywords: online shopping, perceived ease of use, perceived usefulness, perceived enjoyment, technology acceptance model, Nigeria

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Authors: Jingling Li, Yi Zhang, Wei Liang, Tao Cui, Jun Li

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Compared with terrestrial network, the traffic of spatial information network has both self-similarity and short correlation characteristics. By studying its traffic prediction method, the resource utilization of spatial information network can be improved, and the method can provide an important basis for traffic planning of a spatial information network. In this paper, considering the accuracy and complexity of the algorithm, the spatial information network traffic is decomposed into approximate component with long correlation and detail component with short correlation, and a time series hybrid prediction model based on wavelet decomposition is proposed to predict the spatial network traffic. Firstly, the original traffic data are decomposed to approximate components and detail components by using wavelet decomposition algorithm. According to the autocorrelation and partial correlation smearing and truncation characteristics of each component, the corresponding model (AR/MA/ARMA) of each detail component can be directly established, while the type of approximate component modeling can be established by ARIMA model after smoothing. Finally, the prediction results of the multiple models are fitted to obtain the prediction results of the original data. The method not only considers the self-similarity of a spatial information network, but also takes into account the short correlation caused by network burst information, which is verified by using the measured data of a certain back bone network released by the MAWI working group in 2018. Compared with the typical time series model, the predicted data of hybrid model is closer to the real traffic data and has a smaller relative root means square error, which is more suitable for a spatial information network.

Keywords: spatial information network, traffic prediction, wavelet decomposition, time series model

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