Search results for: root uptake models

Authors: Edson Vengesai

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Derivative products have become essential instruments in portfolio diversification, price discovery, and, most importantly, risk hedging. Derivatives are complex instruments; their valuation, volatility implications, and real impact on the underlying assets' behaviour are not well understood. Little is documented empirically, with conflicting conclusions on how these instruments affect firm risk exposures. Given the growing interest in using derivatives in risk management and portfolio engineering, this study examines the practical impact of derivative usage on the underlying stock price exposure and systematic risk. The paper uses data from South African listed firms. The study employs GARCH models to understand the effect of derivative uses on conditional stock volatility. The GMM models are used to estimate the effect of derivatives use on stocks' systematic risk as measured by Beta and on the total risk of stocks as measured by the standard deviation of returns. The results provide evidence on whether derivatives use is instrumental in reducing stock returns' systematic and total risk. The results are subjected to numerous controls for robustness, including financial leverage, firm size, growth opportunities, and macroeconomic effects.

Keywords: derivatives use, hedging, volatility, stock price exposure

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Authors: Rachida Ouysse

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This paper proposes a constrained principal components (CnPC) estimator for efficient estimation of large-dimensional factor models when errors are cross sectionally correlated and the number of cross-sections (N) may be larger than the number of observations (T). Although principal components (PC) method is consistent for any path of the panel dimensions, it is inefficient as the errors are treated to be homoskedastic and uncorrelated. The new CnPC exploits the assumption of bounded cross-sectional dependence, which defines Chamberlain and Rothschild’s (1983) approximate factor structure, as an explicit constraint and solves a constrained PC problem. The CnPC method is computationally equivalent to the PC method applied to a regularized form of the data covariance matrix. Unlike maximum likelihood type methods, the CnPC method does not require inverting a large covariance matrix and thus is valid for panels with N ≥ T. The paper derives a convergence rate and an asymptotic normality result for the CnPC estimators of the common factors. We provide feasible estimators and show in a simulation study that they are more accurate than the PC estimator, especially for panels with N larger than T, and the generalized PC type estimators, especially for panels with N almost as large as T.

Keywords: high dimensionality, unknown factors, principal components, cross-sectional correlation, shrinkage regression, regularization, pseudo-out-of-sample forecasting

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Authors: Sneha Thakur, Sanjeev Karmakar

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This paper proposed hybrid Particle Swarm Optimization (PSO) – Long-Short Term Memory (LSTM) model for groundwater level prediction. The evaluation of the performance is realized using the parameters: root mean square error (RMSE) and mean absolute error (MAE). Ground water level forecasting will be very effective for planning water harvesting. Proper calculation of water level forecasting can overcome the problem of drought and flood to some extent. The objective of this work is to develop a ground water level forecasting model using deep learning technique integrated with optimization technique PSO by applying 29 years data of Chhattisgarh state, In-dia. It is important to find the precise forecasting in case of ground water level so that various water resource planning and water harvesting can be managed effectively.

Keywords: long short-term memory, particle swarm optimization, prediction, deep learning, groundwater level

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Authors: Rituparna Nath, Shawn J. Marshall

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Glaciers are one of the main sensitive climatic indicators, as they respond strongly to small climatic shifts. We develop a flow line model of glacier dynamics to simulate the past and future extent of glaciers in the Canadian Rocky Mountains, with the aim of coupling this model within larger scale regional climate models of glacier response to climate change. This paper will focus on glacier-climate modeling and reconstructions of glacier volume from the Little Ice Age (LIA) to present for Athabasca Glacier, Alberta, Canada. Glacier thickness, volume and mass change will be constructed using flow line modelling and examination of different climate scenarios that are able to give good reconstructions of LIA ice extent. With the availability of SPOT 5 imagery, Digital elevation models and GIS Arc Hydro tool, ice catchment properties-glacier width and LIA moraines have been extracted using automated procedures. Simulation of glacier mass change will inform estimates of meltwater run off over the historical period and model calibration from the LIA reconstruction will aid in future projections of the effects of climate change on glacier recession. Furthermore, the model developed will be effective for further future studies with ensembles of glaciers.

Keywords: flow line modeling, Athabasca Glacier, glacier mass balance, Remote Sensing, Arc hydro tool, little ice age

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Authors: Yenni Anggrayni

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The lack of awareness of the significant prevalence of school absenteeism in Indonesia, which ultimately results in high rates of school dropouts, is an unresolved issue. Therefore, this study aims to investigate the root causes of chronic absenteeism qualitatively and quantitatively using the bioecological systems paradigm in secondary schools for any reason. This study used an open-ended questionnaire to collect data from 1,148 students in six West Java Province districts/cities. Univariate and stepwise multiple logistic regression analyses produced a prediction model for the components. Analysis results show that poor teacher-student relationships, bullying by peers or teachers, negative perception of education, and lack of parental involvement in learning activities are the leading causes of chronic absenteeism. Another finding is to promote home-school partnerships to improve school climate and parental involvement in learning to address chronic absenteeism.

Keywords: bullying, chronic absenteeism, dropout of school, home-school partnerships, parental involvement

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Authors: Mohammed Al Sulaimani, Hamad Al Manhi

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With the development of Remote Sensing technology, the resolution of optical Remote Sensing images has greatly improved, and images have become largely available. Numerous detectors have been developed for detecting different types of objects. In the past few years, Remote Sensing has benefited a lot from deep learning, particularly Deep Convolution Neural Networks (CNNs). Deep learning holds great promise to fulfill the challenging needs of Remote Sensing and solving various problems within different fields and applications. The use of Unmanned Aerial Systems in acquiring Aerial Photos has become highly used and preferred by most organizations to support their activities because of their high resolution and accuracy, which make the identification and detection of very small features much easier than Satellite Images. And this has opened an extreme era of Deep Learning in different applications not only in feature extraction and prediction but also in analysis. This work addresses the capacity of Machine Learning and Deep Learning in detecting and extracting Oil Leaks from Flowlines (Onshore) using High-Resolution Aerial Photos which have been acquired by UAS fixed with RGB Sensor to support early detection of these leaks and prevent the company from the leak’s losses and the most important thing environmental damage. Here, there are two different approaches and different methods of DL have been demonstrated. The first approach focuses on detecting the Oil Leaks from the RAW Aerial Photos (not processed) using a Deep Learning called Single Shoot Detector (SSD). The model draws bounding boxes around the leaks, and the results were extremely good. The second approach focuses on detecting the Oil Leaks from the Ortho-mosaiced Images (Georeferenced Images) by developing three Deep Learning Models using (MaskRCNN, U-Net and PSP-Net Classifier). Then, post-processing is performed to combine the results of these three Deep Learning Models to achieve a better detection result and improved accuracy. Although there is a relatively small amount of datasets available for training purposes, the Trained DL Models have shown good results in extracting the extent of the Oil Leaks and obtaining excellent and accurate detection.

Keywords: GIS, remote sensing, oil leak detection, machine learning, aerial photos, unmanned aerial systems

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Authors: Jui-Chen Huang

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This research used artificial intelligence method to explore elderly’s opinions on the reuse of telecare, its effect on their service quality, satisfaction and the relationship between customer perceived value and intention to reuse. This study conducted a questionnaire survey on the elderly. A total of 124 valid copies of a questionnaire were obtained. It adopted Backpropagation Network (BPN) to propose an effective and feasible analysis method, which is different from the traditional method. Two third of the total samples (82 samples) were taken as the training data, and the one third of the samples (42 samples) were taken as the testing data. The training and testing data RMSE (root mean square error) are 0.022 and 0.009 in the BPN, respectively. As shown, the errors are acceptable. On the other hand, the training and testing data RMSE are 0.100 and 0.099 in the regression model, respectively. In addition, the results showed the service quality has the greatest effects on the intention to reuse, followed by the satisfaction, and perceived value. This result of the Backpropagation Network method is better than the regression analysis. This result can be used as a reference for future research.

Keywords: artificial intelligence, backpropagation network (BPN), elderly, reuse, telecare

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Authors: Abdullah Mohammed Alshehri

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The projects in the construction industry have significantly increased, given its contribution to the overall Gross Domestic Product (GDP) of the countries. Reflecting upon the complex nature and involvement of various agents, the study aims to analyze the conflicts cause within construction projects. Therefore, the study strived to come out with understanding the levels of conflict interaction across project phases. However, this conducted by investigating the association between antecedents and apparent conflicts inherent in. The study used a qualitative approach for collecting the data through a quantitative, semi-structured method. Formation of a questionnaire survey has been conducted for over 30 respondents. However, the survey came out with the identification of 25 conflict cause categories, which can take place in different construction project phases, including pre-design phase, pre-construction phase, construction phase, commissioning, and completion phase. For example, conflicts associated with inconsistencies or discrepancies within or between project documents, which took place at tendering time in the pre-construction phase were relatable with the selection of material specifications that should be supplied or used in the construction projects at the construction phase. Its analysis can provide comprehensive understanding, trace the root of the problem, which offers a roadmap to deepen the understanding of the conflict conditions and ‘course of action’ necessary for project management strategy actions toward avoiding or minimizing conflict causes at project life.

Keywords: construction, conflict causes, levels, interaction, phases

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Authors: Ş. Çiftcioğlu, E. Efe

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In recent years, cancer has been at the top of diseases that cause death in children. Adequate and balanced nutrition plays an important role in the treatment of cancer. Cancer and cancer treatment is affecting food intake, absorption and metabolism, causing nutritional disorders. Appropriate nutrition is very important for the cancerous child to feel well before, during and after the treatment. There are various difficulties in feeding children with cancer. These are the cancer-related factors. Other factors are environmental and behavioral. As health professionals who spend more time with children in the hospital, nurses should be able to support the children on nutrition and help them to have balanced nutrition. This study aimed to evaluate the importance of nursing approaches in the nutrition of children with cancer. This article is planned as a review article by searching the literature on this field. Anorexia may develop due to psychogenic causes or chemotherapeutic agents or accompanying infections and nutrient uptake may be reduced.  In addition, stomatitis, mucositis, taste and odor changes in the mouth, the feeling of nausea, vomiting and diarrhea can also reduce oral intake and result in significant losses in the energy deficit. In assessing the nutritional status of children with cancer, determining weight loss and good nutrition is essential anamnesis of a child.  Some anthropometric measurements and biochemical tests should be used to evaluate the nutrition of the child. The nutritional status of pediatric cancer patients has been studied for a long time and malnutrition, in particular under nutrition, in this population has long been recognized. Yet, its management remains variable with many malnourished children going unrecognized and consequently untreated. Nutritional support is important to pediatric cancer patients and should be integrated into the overall treatment of these children.

Keywords: cancer treatment, children, complication, nutrition, nursing approaches

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Authors: Stephanie Jo Marchese

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This oral presentation is a reflective piece regarding current social work teaching methods that value and devalue the lived experiences of survivor students. This presentation grounds the term ‘survivor’ in feminist frameworks. A survivor-defined approach to feminist advocacy assumes an individual’s agency, considers each case and needs independent of generalizations, and provides resources and support to empower victims. Feminist ideologies are ripe arenas to update and influence the rapport-building schools of social work have with these students. Survivor-based frameworks are rooted in nuanced understandings of intersectional realities, staunchly combat both conscious and unconscious deficit lenses wielded against victims, elevate lived experiences to the realm of experiential expertise, and offer alternatives to traditional power structures and knowledge exchanges. Actively importing a survivor framework into the methodology of social work teaching breaks open barriers many survivor students have faced in institutional settings, this author included. The profession of social work is at an important crux of change, both in the United States and globally. The United States is currently undergoing a radical change in its citizenry and outlier communities have taken to the streets again in opposition to their othered-ness. New waves of students are entering this field, emboldened by their survival of personal and systemic oppressions- heavily influenced by third-wave feminism, critical race theory, queer theory, among other post-structuralist ideologies. Traditional models of sociological and psychological studies are actively being challenged. The profession of social work was not founded on the diagnosis of disorders but rather a grassroots-level activism that heralded and demanded resources for oppressed communities. Institutional and classroom acceptance and celebration of survivor narratives can catapult the resurgence of these values needed in the profession’s service-delivery models and put social workers back in the driver's seat of social change (a combined advocacy and policy perspective), moving away from outsider-based intervention models. Survivor students should be viewed as agents of change, not solely former victims and clients. The ideas of this presentation proposal are supported through various qualitative interviews, as well as reviews of ‘best practices’ in the field of education that incorporate feminist methods of inclusion and empowerment. Curriculum and policy recommendations are also offered.

Keywords: deficit lens bias, empowerment theory, feminist praxis, inclusive teaching models, strengths-based approaches, social work teaching methods

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Authors: Lauren Booker

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In the United States, over 2.5 million children have incarcerated parents. Recent studies have shown 13% of young adults and one-fourth of African Americans will experience parental incarceration. The increasing numbers of incarcerated citizens have left these children as collateral damage and are often forgotten, their special needs inadequately meet or understood. Parental arrest and incarceration creates a uniquely traumatic experience in childhood and has long-term consequences for these children. Until recently, the eating and sleeping habits following parental incarceration had been nonexistent in the literature. However, even this groundbreaking study on eating habits and sleeping disorders following parental incarceration did not touch on the root causes of unhealthy eating which may be influenced by food and housing insecurity and environmental factors that may impact a child’s healthy eating and sleeping behaviors. This study will examine those factors as it could greatly aid in the policies and programs that affect children’s health and development. This proposed study will examine the impact of traumatic stress reactions to parental incarceration by studying sleep and eating habits as the hypothesis is that parental incarceration will lead to disordered eating and sleep disturbances in early adolescents.

Keywords: parental incarceration, eating disorder, trauma, family instability

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Authors: Fateme Nokhodchi Bonab

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Studies related to magnetic resonance imaging (MRI) and drug delivery are reviewed in this study to demonstrate the role of transport theory in porous media in facilitating advances in biomedical applications. Diffusion processes are believed to be important in many therapeutic modalities such as: B. Delivery of drugs to the brain. We analyse the progress in the development of diffusion equations using the local volume average method and the evaluation of applications related to diffusion equations. Torsion and porosity have significant effects on diffusive transport. In this study, various relevant models of torsion are presented and mathematical modeling of drug release from biodegradable delivery systems is analysed. In this study, a new model of drug release kinetics from porous biodegradable polymeric microspheres under bulk and surface erosion of the polymer matrix is presented. Solute drug diffusion, drug dissolution from the solid phase, and polymer matrix erosion have been found to play a central role in controlling the overall drug release process. This work paves the way for MRI and drug delivery researchers to develop comprehensive models based on porous media theory that use fewer assumptions compared to other approaches.

Keywords: MRI, porous media, drug delivery, biomedical applications

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Authors: Abed Ahmed, Mehrdad Asadi, Jennifer Martay

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Stainless steel pipelines are crucial components to transportation and storage in the oil and gas industry. However, the rise of random attacks and vandalism on these pipes for their valuable transport has led to more security and protection for incoming surface impacts. These surface impacts can lead to large global deformations of the pipe and place the pipe under strain, causing the eventual failure of the pipeline. Therefore, understanding how these surface impact loads affect the pipes is vital to improving the pipes’ security and protection. In this study, experimental test and finite element analysis (FEA) have been carried out on EN3B stainless steel specimens to study the impact behaviour. Low velocity impact tests at 9 m/s with 16 kg dome impactor was used to simulate for high momentum impact for localised failure. FEA models of clamped and deformable boundaries were modelled to study the effect of the boundaries on the pipes impact behaviour on its impact resistance, using experimental and FEA approach. Comparison of experimental and FE simulation shows good correlation to the deformable boundaries in order to validate the robustness of the FE model to be implemented in pipe models with complex anisotropic structure.

Keywords: dynamic impact, deformable boundary conditions, finite element modelling, LS-DYNA, stainless steel pipe

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Authors: Ibrahim Makram Ibrahim Salib

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Agriculture plays an essential role in providing food for the world's population. It also offers numerous benefits to countries, including non-food products, transportation, and environmental balance. Precision agriculture, which employs advanced tools to monitor variability and manage inputs, can help achieve these benefits. The increasing demand for food security puts pressure on decision-makers to ensure sufficient food production worldwide. To support sustainable agriculture, unmanned aerial vehicles (UAVs) can be utilized to manage farms and increase yields. This paper aims to provide an understanding of UAV usage and its applications in agriculture. The objective is to review the various applications of UAVs in agriculture. Based on a comprehensive review of existing research, it was found that different sensors provide varying analyses for agriculture applications. Therefore, the purpose of the project must be determined before using UAV technology for better data quality and analysis. In conclusion, identifying a suitable sensor and UAV is crucial to gather accurate data and precise analysis when using UAVs in agriculture.

Keywords: agriculture land, agriculture land loss, Kabul city, urban land expansion, urbanization agriculture yield growth, agriculture yield prediction, explorative data analysis, predictive models, regression models drone, precision agriculture, farmer income

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Authors: Manal Farea, Adam Husein, Ahmad S. Halim, Zurairah Berahim, Nurul A. Abdullah, Khairani I. Mokhtar, Kasmawati Mokhtar

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Endodontic furcal perforation remains both an endodontic and a periodontal problem. Regeneration of cementum is very essential for the perforation repair. The aim of this study was to investigate the role of Hertwig's epithelial root sheath (HERS) cells on the cementogenic differentiation of stem cells derived from human exfoliated deciduous teeth (SHED) in the presence of chitosan scaffold-TGFβ1. HERS cells were isolated and characterized then co-cultured with SHED with/without chitosan scaffold-TGFβ1. SHED proliferation was assessed by PrestoBlue. Alkaline phosphatase activity, mineralization behaviour and gene/protein expression of cemento/osteoblast phenotype of SHED were evaluated. Results of the present study showed that HERS cells in association with chitosan-TGFβ1 enhanced proliferation and cemento/osteogenic differentiation of SHED. Our novel co-culture system confirmed the potential effect of HERS cells to stimulate the differentiation of SHED along the cementoblastic lineage which was triggered in the presence of chitosan-TGFβ1. This approach possesses a novel therapeutic strategy for future endodontic perforation and periodontitis.

Keywords: cementogenesis, co-culture system, HERS, SHED

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Authors: E. D. Paul, A. D. Adams, O. Sunmonu, U. S. Ishiaku

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Activated tamarind kernel powder (ATKP) was prepared from tamarind fruit (Tamarindus indica), and utilized for the removal of Reactive Blue 29 (RB29) from its aqueous solution. The powder was activated using 4N nitric acid (HNO₃). The adsorbent was characterised using infrared spectroscopy, bulk density, ash content, pH, moisture content and dry matter content measurements. The effect of various parameters which include; temperature, pH, adsorbent dosage, ion concentration, and contact time were studied. Four different equilibrium isotherm models were tested on the experimental data, but the Temkin isotherm model was best-fitted into the experimental data. The pseudo-first order and pseudo-second-order kinetic models were also fitted into the graphs, but pseudo-second order was best fitted to the experimental data. The thermodynamic parameters showed that the adsorption of Reactive Blue 29 onto activated tamarind kernel powder is a physical process, feasible and spontaneous, exothermic in nature and there is decreased randomness at the solid/solution interphase during the adsorption process. Therefore, activated tamarind kernel powder has proven to be a very good adsorbent for the removal of Reactive Blue 29 dyes from industrial waste water.

Keywords: tamarind kernel powder, reactive blue 29, isotherms, kinetics

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Authors: Sandra T. Matarneh, Mark Danso-Amoako, Salam Al-Bizri, Mark Gaterell

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Today’s facilities are ever more sophisticated and the need for available and reliable information for operation and maintenance activities is vital. The key challenge for facilities managers is to have real-time accurate and complete information to perform their day-to-day activities and to provide their senior management with accurate information for decision-making process. Currently, there are various technology platforms, data repositories, or database systems such as Computer-Aided Facility Management (CAFM) that are used for these purposes in different facilities. In most current practices, the data is extracted from paper construction documents and is re-entered manually in one of these computerized information systems. Construction Operations Building information exchange (COBie), is a non-proprietary data format that contains the asset non-geometric data which was captured and collected during the design and construction phases for owners and facility managers use. Recently software vendors developed add-in applications to generate COBie spreadsheet automatically. However, most of these add-in applications are capable of generating a limited amount of COBie data, in which considerable time is still required to enter the remaining data manually to complete the COBie spreadsheet. Some of the data which cannot be generated by these COBie add-ins is essential for facilities manager’s day-to-day activities such as job sheet which includes preventive maintenance schedules. To facilitate a seamless data transfer between BIM models and facilities management systems, we developed a framework that enables automated data generation using the data extracted directly from BIM models to external web database, and then enabling different stakeholders to access to the external web database to enter the required asset data directly to generate a rich COBie spreadsheet that contains most of the required asset data for efficient facilities management operations. The proposed framework is a part of ongoing research and will be demonstrated and validated on a typical university building. Moreover, the proposed framework supplements the existing body of knowledge in facilities management domain by providing a novel framework that facilitates seamless data transfer between BIM models and facilities management systems.

Keywords: building information modeling, BIM, facilities management systems, interoperability, information management

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Authors: Zafer Yüce, Paşa Yayla, Alev Taşkın

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There are heaps of analytical methods to estimate the crack growth life of a component. Soft computing methods have an increasing trend in predicting fatigue life. Their ability to build complex relationships and capability to handle huge amounts of data are motivating researchers and industry professionals to employ them for challenging problems. This study focuses on soft computing methods, especially random forest regressors and artificial neural networks with hyperparameter optimization algorithms such as grid search and random grid search, to estimate the crack growth life of an aircraft wing splice joint under variable amplitude loading. TensorFlow and Scikit-learn libraries of Python are used to build the machine learning models for this study. The material considered in this work is 7050-T7451 aluminum, which is commonly preferred as a structural element in the aerospace industry, and regarding the crack type; corner crack is used. A finite element model is built for the joint to calculate fastener loads and stresses on the structure. Since finite element model results are validated with analytical calculations, findings of the finite element model are fed to AFGROW software to calculate analytical crack growth lives. Based on Fighter Aircraft Loading Standard for Fatigue (FALSTAFF), 90 unique fatigue loading spectra are developed for various load levels, and then, these spectrums are utilized as inputs to the artificial neural network and random forest regression models for predicting crack growth life. Finally, the crack growth life predictions of the machine learning models are compared with analytical calculations. According to the findings, a good correlation is observed between analytical and predicted crack growth lives.

Keywords: aircraft, fatigue, joint, life, optimization, prediction.

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Authors: Charly Julien Nyobe, Eric Jacquelin, Denis Brizard, Alexy Mercier

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The performance of road side safety barriers depends largely on the dynamic interactions between post and soil. These interactions play a key role in the response of barriers to crash testing. In the literature, soil-post interaction is modeled in crash test simulations using three approaches. Many researchers have initially used the finite element approach, in which the post is embedded in a continuum soil modelled by solid finite elements. This method represents a more comprehensive and detailed approach, employing a mesh-based continuum to model the soil’s behavior and its interaction with the post. Although this method takes all soil properties into account, it is nevertheless very costly in terms of simulation time. In the second approach, all the points of the post located at a predefined depth are fixed. Although this approach reduces CPU computing time, it overestimates soil-post stiffness. The third approach involves modeling the post as a beam supported by a set of nonlinear springs in the horizontal directions. For support in the vertical direction, the posts were constrained at a node at ground level. This approach is less costly, but the literature does not provide a simple procedure to determine the constitutive law of the springs The aim of this study is to propose a simple and low-cost procedure to obtain the constitutive law of nonlinear springs that model the soil-post interaction. To achieve this objective, we will first present a procedure to obtain the constitutive law of nonlinear springs thanks to the simulation of a soil compression test. The test consists in compressing the soil contained in the tank by a rigid solid, up to a vertical displacement of 200 mm. The resultant force exerted by the ground on the rigid solid and its vertical displacement are extracted and, a force-displacement curve was determined. The proposed procedure for replacing the soil with springs must be tested against a reference model. The reference model consists of a wooden post embedded into the ground and impacted with an impactor. Two simplified models with springs are studied. In the first model, called Kh-Kv model, the springs are attached to the post in the horizontal and vertical directions. The second Kh model is the one described in the literature. The two simplified models are compared with the reference model according to several criteria: the displacement of a node located at the top of the post in vertical and horizontal directions; displacement of the post's center of rotation and impactor velocity. The results given by both simplified models are very close to the reference model results. It is noticeable that the Kh-Kv model is slightly better than the Kh model. Further, the former model is more interesting than the latter as it involves less arbitrary conditions. The simplified models also reduce the simulation time by a factor 4. The Kh-Kv model can therefore be used as a reliable tool to represent the soil-post interaction in a future research and development of road safety barriers.

Keywords: crash tests, nonlinear springs, soil-post interaction modeling, constitutive law

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Authors: Keisuke Fujioka, Yuta Itoh, Masaru Minagawa, Shunji Kusayanagi

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In this study, building information models of the underground temporary structures and adjacent embedded pipes were constructed to show the importance of the information on underground pipes adjacent to the structures to enhance the productivity of execution of construction. Next, the bar chart used in actual construction process were employed to make the Gantt chart, and the critical pass analysis was carried out to show that accurate information on the arrangement of underground existing pipes can be used for the enhancement of the productivity of the construction of underground structures. In the analyzed project, significant construction delay was not caused by unforeseeable existence of underground pipes by the management ability of the construction manager. However, in many cases of construction executions in the developing countries, the existence of unforeseeable embedded pipes often causes substantial delay of construction. Design change based on uncertainty on the position information of embedded pipe can be also important risk for contractors in domestic construction. So CPM analyses were performed by a project-management-software to the situation that influence of the tasks causing construction delay was assumed more significant. Through the analyses, the efficiency of information management on underground pipes and BIM analysis in the design stage for workability improvement was indirectly confirmed.

Keywords: building-information modelling, construction information modelling, design improvement, infrastructure

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Authors: Kuo-Wei Hsu, Shu-Fang Huang

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Global trend in creative economies promoted the modernization process of the development of cultural and creative industries and technology coincided with the craft industry towards value-added industrial restructuring. Due to government support and economic motivation in the private sector, regional craft products have emerged across counties and cities all over Taiwan which have led to an increased focus on craft culture promotion. However, most craft industry corporations in Taiwan are micro-enterprise, restricted operating profitability. This phenomenon shows the weakness of craft industry constitution when facing the rapid expansion of global economic commerce and manufacturing. In recent years, combining public and private enterprise, Platform business models revolutionary changed in craft industries’ original operation and transaction models. Therefore, this study attempts to explore the effects by implementing platform strategy on bamboo industry development in Nantou, the hometown of crafts in Taiwan, with an experimental investigation. This study concluded that platform strategy increases essence and insubstantial value for the bamboo industry in Taiwan. This study explored the economic value added of Taiwan bamboo village with three perspectives: Community participation, Culture Conservation, Regional Rejuvenation.

Keywords: platform strategy, craft industry, economic value-added

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Authors: Rafeza Begum, Mohammad Mokhlesur Rahman, Safikul Moula, Rafiqul Islam

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Potassium (K) is crucial for healthy soil and plant growth. However, K fertilization is either disregarded or poorly underutilized in Bangladesh agriculture, despite the great demand for crops. This could eventually result in a significant depletion of the soil's potassium reserves, irreversible alteration of the minerals that contain potassium, and detrimental effects on crop productivity. Soil K mining in Bangladesh is a worrying problem, and we need to evaluate it thoroughly and find remedies. A pot culture experiment was conducted in the greenhouse of Bangladesh Institute of Nuclear Agriculture (BINA) using eleven soil series of Bangladesh in order to see the depletion behaviour of potassium (K) by continuous cropping using rice (var. Iratom-24) as the test crop. The soil series were Ranishankhail, Kaonia. Sonatala, Silmondi, Gopalpur, Ishurdi, Sara, Kongsha, Nunni, Lauta and Amnura on which four successive rice plants (45 days duration) were raised with (100 ppm K) or without addition of potassium. Nitrogen, phosphorus, sulfur and zinc were applied as basal to all pots. Potassium application resulted in higher dry matter yield, increased K concentration and uptake in all the soils compared with no K treatment; which gradually decreased in the subsequent harvests. Furthermore, plant takes up K not only from exchangeable pool but also from non-exchangeable sites and a minimum replenishment of K from the soil reserve was observed. Continuous cropping has resulted in the depletion of available K of the soil. The result indicated that in order to sustain higher crop yield under intensive cultivation, the addition of potash fertilizer is necessary.

Keywords: potassium, exchangeable pool, depletion behavior., Soil series

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Authors: Champika S. Kariyawasam

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The distribution of gorse (Ulex europaeus) plants in South Australia has been modelled using 126 presence-only location data as a function of seven climate parameters. The predicted range of U. europaeus is mainly along the Mount Lofty Ranges in the Adelaide Hills and on Kangaroo Island. Annual precipitation and yearly average aridity index appeared to be the highest contributing variables to the final model formulation. The Jackknife procedure was employed to identify the contribution of different variables to gorse model outputs and response curves were used to predict changes with changing environmental variables. Based on this analysis, it was revealed that the combined effect of one or more variables could make a completely different impact to the original variables on their own to the model prediction. This work also demonstrates the need for a careful approach when selecting environmental variables for projecting correlative models to climatically distinct area. Maxent acts as a robust model when projecting the fitted species distribution model to another area with changing climatic conditions, whereas the generalized linear model, bioclim, and domain models to be less robust in this regard. These findings are important not only for predicting and managing invasive alien gorse in South Australia and Sri Lanka but also in other countries of the invasive range.

Keywords: invasive species, Maxent, species distribution modelling, Ulex europaeus

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Authors: H. Trabelsi, A. Chehma, I. Benseddik

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Animals can play an important role in the seed dispersal cycle through the active or passive uptake of seeds and the subsequent external (epizoochory) or internal transport (endozoochory) of seeds. In Algeria, small ruminants and camels are generally conducted in extensive livestock exploiting the Saharan and steppe rangelands. To get an idea on the ecological potential role of these animals in the spontaneous plants proliferation, we propose to make a study of seeds dispersal and germination possibilities by camel faeces compared to those of small ruminants. Manual faeces decortication of the two animals categories has allowed to inventory 72 seed which 71% are in good condition, while 29% of the seeds that are encountered are partially altered and could not be identified. The species that have been identified, from small ruminants dung are weeds of cultures, while those identified from camel dung are spontaneous plants of Saharan rangeland. Concerning germination in the laboratory, only 3 species seeds were germinated from camel feces, whose germination rate varies from 25% to 100%. Contrary to Sheep-Goat feces, a single species germinated with 71%. The three months seed germination in greenhouse allowed to identify 10 species belonging to 4 botanical families (5 species from small ruminants dung and 3 species from Camel dung). In general, the results show the positive effect played by two animals categories for plants seed dispersal with the camel particularity for spontaneous plants due to its capacity to cover long distances in different rangeland types.

Keywords: Algeria, camel, endozoochory, seeds, sheep-goat, rangeland

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Authors: Hawa Khan

Abstract:

Autism is a complex disorder related to abnormalities in the development of brain structure and neurological function and a new phenomenon which is epidemically on the increase. The Muslim community, with its profound commitment to the all-encompassing Islamic precedence, views all phenomena in the light of religious imperatives. How autism is understood and treated in these communities is key to successful inclusive services. Moreover, parents mentioned their Islamic faith as a coping mechanism for the challenges they faced while caring for their child. This study utilises interpretative phenomenology analysis as a methodology that seeks to interpret the meaning the participants make of their experiences, which extends descriptive analysis. Semi-structured interviews were conducted with 5 family units that included fathers, mothers, grandparents, and siblings. In the preliminary stage, this study found families give high importance of accessible Islamic education for their child and questioning the accountability of the child who might not be able to follow the Islamic way of life entirely or understand the concept of Allah. Moreover, the families expressed their beliefs in traditional and religious treatment as an effective way to treat and cure autism. This poses a major barrier between families seeking support and professionals providing services. Consequentially, it can also result in a low uptake of mainstream services from the Muslim community. Exploring the lived experiences of parents from the Muslim community and how ASD is conceptualised in this community could have implications for improved and effective home, community, and service collaboration.

Keywords: autism spectrum disorder, Islamic education, religious beliefs, mainstream services

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Authors: Saowapa Phaithayawat

Abstract:

The purposes of this study are: 1) to study the impact of the 3-community-core model: House (H), Temple (T), and School (S) with the co-operation of official departments on community development to ASEAN economic community involvement, and 2) to study the procedures and extension of the model. The research which is a qualitative research based on formal and informal interviews. Local people in a community are observed. Group interview is also operated by executors and cooperators in the school in the community. In terms of social and cultural dimension, the 3-community-core model consisting of house, temple and school is the base of Thai cultures bringing about understanding, happiness and unity to the community. The result of this research is that the official departments in accompanied with this model developers cooperatively work together in the community to support such factors as budget, plan, activities. Moreover, the need of community, and the continual result to sustain the community are satisfied by the model implementation. In terms of the procedures of the model implementation, executors and co-operators can work, coordinate, think, and launch their public relation altogether. Concerning the model development, this enables the community to achieve its goal to prepare the community’s readiness for ASEAN Economic Community involvement.

Keywords: ASEAN Economic Community, the applying models and sufficiency development, house, temple, school

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Authors: Minho Lee, Donghyun Back, Jaemoon Jung, Woojin Park

Abstract:

The current 3-dimensional (3D) posture prediction models commonly provide only a few optimal postures to achieve a specific objective. The problem with such models is that they are incapable of rapidly providing several optimal posture candidates according to various situations. In order to solve this problem, this paper presents a 3D memory-based posture planning (3D MBPP) model, which is a new digital human model that can analyze the feasible postures in 3D space for reaching tasks that have postural constraints and specific reaching space. The 3D MBPP model can be applied to the types of works that are done with constrained working postures and have specific reaching space. The examples of such works include driving an excavator, driving automobiles, painting buildings, working at an office, pitching/batting, and boxing. For these types of works, a limited amount of space is required to store all of the feasible postures, as the hand reaches boundary can be determined prior to perform the task. This prevents computation time from increasing exponentially, which has been one of the major drawbacks of memory-based posture planning model in 3D space. This paper validates the utility of 3D MBPP model using a practical example of analyzing baseball batting posture. In baseball, batters swing with both feet fixed to the ground. This motion is appropriate for use with the 3D MBPP model since the player must try to hit the ball when the ball is located inside the strike zone (a limited area) in a constrained posture. The results from the analysis showed that the stored and the optimal postures vary depending on the ball’s flying path, the hitting location, the batter’s body size, and the batting objective. These results can be used to establish the optimal postural strategies for achieving the batting objective and performing effective hitting. The 3D MBPP model can also be applied to various domains to determine the optimal postural strategies and improve worker comfort.

Keywords: baseball, memory-based, posture prediction, reaching area, 3D digital human models

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Authors: S. Sharan Sundar, Nithish B. Moudhgalya, Nidhi Bhandari, Vineeth Vijayaraghavan

Abstract:

Automatic Short Answer Grading is one of the prime applications of artificial intelligence in education. Several approaches involving the utilization of selective handcrafted features, graphical matching techniques, concept identification and mapping, complex deep frameworks, sentence embeddings, etc. have been explored over the years. However, keeping in mind the real-world application of the task, these solutions present a slight overhead in terms of computations and resources in achieving high performances. In this work, a simple and effective solution making use of elemental features based on statistical, linguistic properties, and word-based similarity measures in conjunction with tree-based classifiers and regressors is proposed. The results for classification tasks show improvements ranging from 1%-30%, while the regression task shows a stark improvement of 35%. The authors attribute these improvements to the addition of multiple similarity scores to provide ensemble of scoring criteria to the models. The authors also believe the work could reinstate that classical natural language processing techniques and simple machine learning models can be used to achieve high results for short answer grading.

Keywords: artificial intelligence, intelligent systems, natural language processing, text mining

Procedia PDF Downloads 133

Authors: Gopal Ji, Priyanka Dwivedi, Shanthi Sundaram, Rajiv Prakash

Abstract:

Inhibition effect of aqueous Argemone Mexicana root extract (AMRE) on mild steel corrosion in 1 M HCl has been studied by weight loss, Tafel polarization curves, electrochemical impedance spectroscopy (EIS), scanning electron microscopy (SEM) and atomic force microscopy (AFM) techniques. Results indicate that inhibition ability of AMRE increases with the increasing amount of the extract. A maximum corrosion inhibition of 94% is acknowledged at the extract concentration of 400 mg L-1. Polarization curves and impedance spectra reveal that both cathodic and anodic reactions are suppressed due to passive layer formation at metal-acid interface. It is also confirmed by SEM micro graphs and FTIR studies. Furthermore, the effects of acid concentration (1-5 M), immersion time (120 hours) and temperature (30-60˚C) on inhibition potential of AMRE have been investigated by weight loss method and electrochemical techniques. Adsorption mechanism is also proposed on the basis of weight loss results, which shows good agreement with Langmuir isotherm.

Keywords: mild steel, polarization, SEM, acid corrosion, EIS, green inhibition

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Authors: Effort M. Magoso

Abstract:

This study analyses urban institutional arrangements and their implications on allocation of wetlands for development purposes in Zimbabwe using a case study of Harare. It was driven by the need to get to the root of the current urban assault on wetlands. The study sought to analyse institutions that influence wetlands governance in Harare, to ascertain level of wetlands loss and to determine the adequacy of the legal and regulatory framework for governing wetlands. Theories of common property resources and of institutions are the paradigms that undergird this study. A qualitative research methodology was employed, while in-depth interviews, observations and document review were used to gather data. The study found out that unchecked infrastructure developments are taking place in the city’s wetlands. Urban institutional arrangements in Harare were exposed as having negative implications on the protection of wetlands. It is the key argument of this study that good institutional arrangements are priceless in the protection of commons such as wetlands. This study also recommends a new framework that has environmentalists and technocrats as the final decision maker in land allocation as the solution to protect wetlands from undue anthropogenic activities.

Keywords: institutional arrangements, common property resources, wetlands, institutions

Procedia PDF Downloads 388