Search results for: comprehensive model

Authors: Chico Horacio Jose Sambo

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Recently neural network has gained popularity when come to solve complex nonlinear problems. Permeability is one of fundamental reservoir characteristics system that are anisotropic distributed and non-linear manner. For this reason, permeability prediction from well log data is well suited by using neural networks and other computer-based techniques. The main goal of this paper is to predict reservoir permeability from well logs data by using neural network approach. A multi-layered perceptron trained by back propagation algorithm was used to build the predictive model. The performance of the model on net results was measured by correlation coefficient. The correlation coefficient from testing, training, validation and all data sets was evaluated. The results show that neural network was capable of reproducing permeability with accuracy in all cases, so that the calculated correlation coefficients for training, testing and validation permeability were 0.96273, 0.89991 and 0.87858, respectively. The generalization of the results to other field can be made after examining new data, and a regional study might be possible to study reservoir properties with cheap and very fast constructed models.

Keywords: neural network, permeability, multilayer perceptron, well log

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Authors: Xiangji Guo, Bo Zhang

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In this paper, the phenomenon of vortex breakdown in a vortex tube was analyzed within the scope of unsteady character in swirl flows. A 3-D Unsteady Reynolds-averaged Navier–Stokes (URANS) closed by the Reynolds Stress Model (RSM) was adopted to simulate the large-scale vortex structure in vortex tube, and the numerical model was verified by the steady results. The swirl number was calculated for the vortex tube and the flow field was classed as strong swirl flow. According to the results, a time-dependent spiral flow field gyrates around a central recirculation zone which is precessing around the axis of the tube, and manifests the flow structure is the spiral type (S-type) vortex breakdown. The vortex breakdown is crucial for the formation of the central recirculation zone (CRZ), a further discussion was about the affection on CRZ with the different external conditions of vortex tube, the study on the unsteady characters was expected to hope to design of vortex tube and analyze the energy separation effect.

Keywords: vortex tube, vortex breakdown, central recirculation zone, unsteady, energy separation

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Authors: Sarra Hasni, Sami Faiz

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In recent years, location prediction on social networks has gained significant attention, with short and unstructured texts like tweets posing additional challenges. Advanced geolocation models have been proposed, increasing the need to explain their predictions. In this paper, we provide explanations for a geolocation black-box model using LIME and SHAP, two state-of-the-art XAI (eXplainable Artificial Intelligence) methods. We extend our evaluations to Large Language Models (LLMs) as post hoc explainers for tweet geolocation. Our preliminary results show that LLMs outperform LIME and SHAP by generating more accurate explanations. Additionally, we demonstrate that prompts with examples and meta-prompts containing phonetic spelling rules improve the interpretability of these models, even with informal input data. This approach highlights the potential of advanced prompt engineering techniques to enhance the effectiveness of black-box models in geolocation tasks on social networks.

Keywords: large language model, post hoc explainer, prompt engineering, local explanation, tweet geolocation

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Authors: Ebtsam Aly Abou Hashish, Sharifah Abdulmuttalib Alsayed, Hend Abdu Alnajjar

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Background: Academic nurse educators play a crucial role in the educational environment, but the demands of their profession can lead to workaholism, which could result in an imbalance between work and personal life. Purpose: The study aimed to explore workaholism and life balance among academic nursing educators, as well as investigate the factors associated with workaholism. Methods: A mixed-methods design based on the ‘concurrent triangulation’ approach was employed. A convenience sample of 76 nurse educators completed the Dutch Work Addiction Scale (DUWAS) and the Life Balance Inventory (LBI), while a purposive sample of 20 nurse educators participated in semi-structured interviews. Inferential statistics and thematic analysis were used to analyze the data. Results: The researchers found a notable prevalence of workaholism among nurse educators, with 59.0 % reporting a mean score above 2.5 and 86.8 % perceiving an unbalanced life. Regression analysis indicated that workaholism negatively predicted life balance (B = 􀀀 0.404, p < 0.001). The qualitative findings derived three themes as determinants of workaholism: antecedents, consequences, and personal and institutional strategies to mitigate workaholism among nursing educators. Conclusion: Educational institutions should develop comprehensive approaches to support and develop their academicians, fostering a positive work environment, work-life balance, employee well-being, and professional development.

Keywords: workaholism, life balance, academic nurse educators, mixed-method

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Authors: Nazmul Haque, Syeda Tasnuva Maria

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Sheehan's Syndrome (SS), also known as postpartum hypopituitarism, is a rare but potentially serious condition resulting from ischemic necrosis of the pituitary gland, often occurring during or after childbirth. This syndrome is characterized by hypopituitarism, leading to deficiencies in various hormones produced by the pituitary gland. The primary cause is typically severe postpartum hemorrhage, leading to inadequate blood supply and subsequent necrosis of the pituitary tissue. This chronic hypopituitarism sometimes plays the role of premature atherosclerosis, which may lead to cardiovascular disease. This abstract provides a comprehensive overview of Sheehan's Syndrome with ischaemic heart disease, encompassing its pathophysiology, clinical manifestations, and current management strategies. The disorder presents a wide spectrum of symptoms, including chest pain, fatigue, amenorrhea, lactation failure, hypothyroidism, and adrenal insufficiency. Timely diagnosis is crucial, as delayed recognition can lead to complications and long-term health consequences. We herein report a patient complaining of chronic fatigue symptoms, aggressiveness, chest pain, and breathlessness with repeated LOC that were diagnosed with SS with IHD. The patient was treated with antiplatelet, antianginal, steroids, and hormone replacement with marked improvement in his overall condition.

Keywords: ischaemic heart disease, Sheehan's syndrome, post-partum haemorrhage, pituitary gland

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Authors: Ziwei Chen, Yujiang Gao

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The rapid urbanization has caused the massive physical space in Chinese cities to be in a state of duplication and dislocation through the rapid development, forming many daily spaces that cannot be standardized, typed, and identified, such as illegal construction. This phenomenon is known as urban spatial redundancy and is often excluded from mainstream architectural discussions because of its 'remaining' and 'excessive' derogatory label. In recent years, some practice architects have begun to pay attention to this phenomenon and tried to tap the value behind it. In this context, the author takes the redundancy phenomenon of resident space as the research object and explores the inspiration to the urban architectural renewal and the innovative residential area model, based on the urban survey of redundant living space in Hongkou District of Shanghai. On this basis, it shows that the changes accumulated in the long-term use of the building can be re-applied to the goals before the design, which is an important link and significance of the existence of an architecture.

Keywords: rapid urbanization, living space redundancy, architectural renewal, residential area model

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Authors: Mark Anthony A. Catiil

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Teachers are the principal actors in the delivery of quality education to the learners. Unfortunately, as time goes by, some of them got low motivation at work. Absenteeism, tardiness, under time, and non-compliance to school policies are some of the end results. There is, therefore, a need to review the different human resource management practices of the school that contribute to teachers’ work satisfaction and motivation. Hence, this study determined the level of satisfaction of teachers on the human resource management practices of Gingoog City Comprehensive National High School. This mixed-methodology research was focused on the 45 teachers chosen using a stratified random sampling technique. Reliability-tested questionnaires, interviews, and focus group discussions were used to gather the data. Results revealed that the majority of the respondents are female, Teacher I, with MA units and have served for 11-20 years. Likewise, among the human resource management practices of the school, the respondents rated the lowest satisfaction on recruitment and selection (mean=2.15; n=45). This could mean that most of the recruitment and selection practices of the school are not well communicated, disseminated, and implemented. On the other hand, retirement practices of the school were rated with the highest satisfaction among the respondents (mean=2.73; n=45). This could mean that most of the retirement practices of the school are communicated, disseminated, implemented, and functional. It was recommended that the existing human resource management practices on recruitment and selection be reviewed to find out its deficiencies and possible improvement. Moreover, future researchers may also conduct a study between private and public schools in Gingoog City on the same topic for comparison.

Keywords: education, human resource management practices, satisfaction, teachers

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Authors: Saif Hussein Abdallah Alghazo, Norshima Humaidi

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Adopting cybersecurity protective behaviour among the employees is seriously considered in the organization, especially when the Internet of Things (IoT) is widely used in Industrial Revolution 4.0 (IR 4.0) era. Cybersecurity issues arise due to weaknesses of employees’ behaviour such as carelessness and failure to adopt good practices of information security behaviour. Therefore, this study aims to explore the dimensions that might influence employees’ behaviour to adopt good cybersecurity practices and to develop a new holistic model related to this concept. The study proposed this by reviewing the existing works of literature related to this field extensively, especially by focusing on the existing theory such as Protection Motivation Theory (PMT). Moreover, this study has also explored the role of cybersecurity competency among the security manager in the organization since this construct is essential to enhance the protective behaviour towards cybersecurity among the employees in the organization. The proposed research model is important to be quantitatively tested in the future as the findings will serve as the input to the act that will enhance employee’s cybersecurity protective behaviour in the IR 4.0 environment.

Keywords: cybersecurity protective behaviour, protection motivation theory, IR 4.0, cybersecurity competency

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Authors: Xiaoxiao Li, Shuangcheng Jia, Qian Li

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Keypoint detection has always been a challenge in the field of image recognition. This paper proposes a novelty keypoint detection method which is called Multi-Scale Feature Fusion Convolutional Network with Attention (MFFCNA). We verified that the multi-scale features with the attention mechanism module have better feature expression capability. The feature fusion between different scales makes the information that the network model can express more abundant, and the network is easier to converge. On our self-made street sign corner dataset, we validate the MFFCNA model with an accuracy of 97.8% and a recall of 81%, which are 5 and 8 percentage points higher than the HRNet network, respectively. On the COCO dataset, the AP is 71.9%, and the AR is 75.3%, which are 3 points and 2 points higher than HRNet, respectively. Extensive experiments show that our method has a remarkable improvement in the keypoint recognition tasks, and the recognition effect is better than the existing methods. Moreover, our method can be applied not only to keypoint detection but also to image classification and semantic segmentation with good generality.

Keywords: keypoint detection, feature fusion, attention, semantic segmentation

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Authors: Aleksandar Hatzivelkos

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The term ”compromise” is mostly used casually within the social choice theory. It is usually used as a mere result of the social choice function, and this omits its deeper meaning and ramifications. This paper is based on a mathematical model for the description of a compromise as a version of the Sorites paradox. It introduces a formal definition of d-measure of divergence from a compromise and models a notion of compromise that is often used only colloquially. Such a model for vagueness phenomenon, which lies at the core of the notion of compromise enables the introduction of new mathematical structures. In order to maximize compromise, different methods can be used. In this paper, we explore properties of a social welfare function TdM (from Total d-Measure), which is defined as a function which minimizes the total sum of d-measures of divergence over all possible linear orderings. We prove that TdM satisfy strict Pareto principle and behaves well asymptotically. Furthermore, we show that for certain domain restrictions, TdM satisfy positive responsiveness and IIIA (intense independence of irrelevant alternatives) thus being equivalent to Borda count on such domain restriction. This result gives new opportunities in social choice, especially when there is an emphasis on compromise in the decision-making process.

Keywords: borda count, compromise, measure of divergence, minimization

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Authors: Haris Karnezi, Kevin Tierney

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Cognitive Behaviour Drama is a research-based intervention model that brought together the science of psychology with the art form of drama to create an unobtrusive and exciting approach that would provide children on the higher end of the autism spectrum the motivation to explore the rules of social interaction and develop competencies associated with communicative success. The method involves engaging the participants in exciting fictional scenarios and encouraging them to seek various solutions on a number of problems that will lead them to an understanding of causal relationships and how a different course of action may lead to a different outcome. The sessions are structured to offer opportunities to the participants to practice target behaviours and understand the functions they serve. The study involved six separate interventions and employed both single case and group designs. Overall 8 children aged between 6 to 13 years, diagnosed with ASD participated in the study. Outcomes were measured using theory of mind tests, executive functioning tests, behavioural observations, pre and post intervention standardised social competence questionnaires for parents and teachers. Collectively, the results indicated positive changes in the self esteem and behaviour of all eight participants. In particular, improvements in the ability to solve theory of mind tasks were noted in the younger group; and qualitative improvements in social communication, in terms of verbal (content) and non verbal expression (body posture, vocal expression, fluency, eye contact, reduction of ritualistic mannerisms) were noted in the older group. The need for reliable impact measures to assess the effectiveness of the model in generating global changes in the participants’ behaviour outside the therapeutic context was identified.

Keywords: autism, drama, intervention, social skills

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Authors: Bao Li, Aike Qiao, Gaoyang Li, Youjun Liu

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Background: Lumped parameter model (LPM) is a common numerical model for hemodynamic calculation. LPM uses circuit elements to simulate the human blood circulatory system. Physiological indicators and characteristics can be acquired through the model. However, due to the different physiological indicators of each individual, parameters in LPM should be personalized in order for convincing calculated results, which can reflect the individual physiological information. This study aimed to develop an automatic and effective optimization method to personalize the parameters in LPM of the blood circulatory system, which is of great significance to the numerical simulation of individual hemodynamics. Methods: A closed-loop LPM of the human blood circulatory system that is applicable for most persons were established based on the anatomical structures and physiological parameters. The patient-specific physiological data of 5 volunteers were non-invasively collected as personalized objectives of individual LPM. In this study, the blood pressure and flow rate of heart, brain, and limbs were the main concerns. The collected systolic blood pressure, diastolic blood pressure, cardiac output, and heart rate were set as objective data, and the waveforms of carotid artery flow and ankle pressure were set as objective waveforms. Aiming at the collected data and waveforms, sensitivity analysis of each parameter in LPM was conducted to determine the sensitive parameters that have an obvious influence on the objectives. Simulated annealing was adopted to iteratively optimize the sensitive parameters, and the objective function during optimization was the root mean square error between the collected waveforms and data and simulated waveforms and data. Each parameter in LPM was optimized 500 times. Results: In this study, the sensitive parameters in LPM were optimized according to the collected data of 5 individuals. Results show a slight error between collected and simulated data. The average relative root mean square error of all optimization objectives of 5 samples were 2.21%, 3.59%, 4.75%, 4.24%, and 3.56%, respectively. Conclusions: Slight error demonstrated good effects of optimization. The individual modeling algorithm developed in this study can effectively achieve the individualization of LPM for the blood circulatory system. LPM with individual parameters can output the individual physiological indicators after optimization, which are applicable for the numerical simulation of patient-specific hemodynamics.

Keywords: blood circulatory system, individual physiological indicators, lumped parameter model, optimization algorithm

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Authors: Bushra Suhail, Laith Kadim

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The behavior of model piles embedded in a very high expansive soil was investigated, a specially manufactured saturation-drying tank was used to apply three cycles of wetting and drying to the expansive soil surrounding the model straight shaft and under reamed piles, the relative movement of the piles with respect to the soil surface was recorded with time, also the exerted uplift pressure of the piles due to soil swelling was recorded. The behavior of unloaded straight shaft and under reamed piles was investigated. Two design charts were presented for straight shaft and under reamed piles one for the required pile depth for zero upward movement due to soil swelling, the other for the required pile depth to exert zero uplift pressure when the soil swells. Under reamed piles showed a decrease in upward movement of 20% to 40%, and an uplift pressure decrease of 10% to 30%.

Keywords: expansive soil, piles, under reamed, structural and geotechnical engineering

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Authors: Eliska Smidova, Petr Kabele

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This paper describes non-linear finite element simulation of laminated veneer lumber (LVL) under tensile and shear loads that induce cracking along fibers. For this purpose, we use 2D homogeneous orthotropic constitutive model of tensile and shear fracture in timber that has been recently developed and implemented into ATENA® finite element software by the authors. The model captures (i) material orthotropy for small deformations in both linear and non-linear range, (ii) elastic behavior until anisotropic failure criterion is fulfilled, (iii) inelastic behavior after failure criterion is satisfied, (iv) different post-failure response for cracks along and across the grain, (v) unloading/reloading behavior. The post-cracking response is treated by fixed smeared crack model where Reinhardt-Hordijk function is used. The model requires in total 14 input parameters that can be obtained from standard tests, off-axis test results and iterative numerical simulation of compact tension (CT) or compact tension-shear (CTS) test. New engineered timber composites, such as laminated veneer lumber (LVL), offer improved structural parameters compared to sawn timber. LVL is manufactured by laminating 3 mm thick wood veneers aligned in one direction using water-resistant adhesives (e.g. polyurethane). Thus, 3 main grain directions, namely longitudinal (L), tangential (T), and radial (R), are observed within the layered LVL product. The core of this work consists in 3 numerical simulations of experiments where Radiata Pine LVL and Yellow Poplar LVL were involved. The first analysis deals with calibration and validation of the proposed model through off-axis tensile test (at a load-grain angle of 0°, 10°, 45°, and 90°) and CTS test (at a load-grain angle of 30°, 60°, and 90°), both of which were conducted for Radiata Pine LVL. The second finite element simulation reproduces load-CMOD curve of compact tension (CT) test of Yellow Poplar with the aim of obtaining cohesive law parameters to be used as an input in the third finite element analysis. That is four point bending test of small-size arch of 780 mm span that is made of Yellow Poplar LVL. The arch is designed with a through crack between two middle layers in the crown. Curved laminated beams are exposed to high radial tensile stress compared to timber strength in radial tension in the crown area. Let us note that in this case the latter parameter stands for tensile strength in perpendicular direction with respect to the grain. Standard tests deliver most of the relevant input data whereas traction-separation law for crack along the grain can be obtained partly by inverse analysis of compact tension (CT) test or compact tension-shear test (CTS). The initial crack was modeled as a narrow gap separating two layers in the middle the arch crown. Calculated load-deflection curve is in good agreement with the experimental ones. Furthermore, crack pattern given by numerical simulation coincides with the most important observed crack paths.

Keywords: compact tension (CT) test, compact tension shear (CTS) test, fixed smeared crack model, four point bending test, laminated arch, laminated veneer lumber LVL, off-axis test, orthotropic elasticity, orthotropic fracture criterion, Radiata Pine LVL, traction-separation law, yellow poplar LVL, 2D constitutive model

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Authors: Oumaima Khlifati, Khadija Baba

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Pavement distress is the main factor responsible for the deterioration of road structure durability, damage vehicles, and driver comfort. Transportation agencies spend a high proportion of their funds on pavement monitoring and maintenance. The auscultation of pavement distress was based on the manual survey, which was extremely time consuming, labor intensive, and required domain expertise. Therefore, the automatic distress detection is needed to reduce the cost of manual inspection and avoid more serious damage by implementing the appropriate remediation actions at the right time. Inspired by recent deep learning applications, this paper proposes an algorithm for automatic road distress detection and classification using on the Deep Convolutional Neural Network (DCNN). In this study, the types of pavement distress are classified as transverse or longitudinal cracking, alligator, pothole, and intact pavement. The dataset used in this work is composed of public asphalt pavement images. In order to learn the structure of the different type of distress, the DCNN models are trained and tested as a multi-label classification task. In addition, to get the highest accuracy for our model, we adjust the structural optimization hyper parameters such as the number of convolutions and max pooling, filers, size of filters, loss functions, activation functions, and optimizer and fine-tuning hyper parameters that conclude batch size and learning rate. The optimization of the model is executed by checking all feasible combinations and selecting the best performing one. The model, after being optimized, performance metrics is calculated, which describe the training and validation accuracies, precision, recall, and F1 score.

Keywords: distress pavement, hyperparameters, automatic classification, deep learning

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Authors: Hamza Javar Magnier, Robin Curtis

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There have been rapid advances in the upstream processing of protein therapeutics, which has shifted the bottleneck to downstream purification and formulation. Finding liquid formulations with shelf lives of up to two years is increasingly difficult for some of the newer therapeutics, which have been engineered for activity, but their formulations are often viscous, can phase separate, and have a high propensity for irreversible aggregation1. We explore means to develop improved predictive ability from a better understanding of how protein-protein interactions on formulation conditions (pH, ionic strength, buffer type, presence of excipients) and how these impact upon the initial steps in protein self-association and aggregation. In this work, we study the initial steps in the aggregation pathways using a minimal protein model based on square-well potentials and discontinuous molecular dynamics. The effect of model parameters, including range of interaction, stiffness, chain length, and chain sequence, implies that protein models fold according to various pathways. By reducing the range of interactions, the folding- and collapse- transition come together, and follow a single-step folding pathway from the denatured to the native state2. After parameterizing the model interaction-parameters, we developed an understanding of low-temperature conformational properties and fluctuations, and the correlation to the folding transition of proteins in isolation. The model fluctuations increase with temperature. We observe a low-temperature point, below which large fluctuations are frozen out. This implies that fluctuations at low-temperature can be correlated to the folding transition at the melting temperature. Because proteins “breath” at low temperatures, defining a native-state as a single structure with conserved contacts and a fixed three-dimensional structure is misleading. Rather, we introduce a new definition of a native-state ensemble based on our understanding of the core conservation, which takes into account the native fluctuations at low temperatures. This approach permits the study of a large range of length and time scales needed to link the molecular interactions to the macroscopically observed behaviour. In addition, these models studied are parameterized by fitting to experimentally observed protein-protein interactions characterized in terms of osmotic second virial coefficients.

Keywords: protein folding, native-ensemble, conformational fluctuation, aggregation

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Authors: Tomer Gans-Or, Shmulik Pinkert

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The determination of lateral pile capacity per unit length is a key aspect in geotechnical engineering. Traditional approaches for assessing piles lateral capacity in cohesive soils involve the application of upper-bound and lower-bound plasticity theorems. However, a comprehensive solution encompassing the entire spectrum of soil strength parameters, particularly in frictional soils with or without cohesion, is still lacking. This research introduces an innovative implementation of the slice method limit equilibrium solution for lateral capacity assessment. For any given numerical discretization of the soil's domain around the pile, the lateral capacity evaluation is based on mobilized strength concept. The critical failure geometry is then found by a unique optimization procedure which includes both factor of safety minimization and geometrical optimization. The robustness of this suggested methodology is that the solution is independent of any predefined assumptions. Validation of the solution is accomplished through a comparison with established plasticity solutions for cohesive soils. Furthermore, the study demonstrates the applicability of the limit equilibrium method to address unresolved cases related to frictional and cohesive-frictional soils. Beyond providing capacity values, the method enables the utilization of the mobilized strength concept to generate safety-factor distributions for scenarios representing pre-failure states.

Keywords: lateral pile capacity, slice method, limit equilibrium, mobilized strength

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Authors: Stephanie Liu Lu

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The course "University Chinese," an essential component of the curriculum in Hong Kong's higher education institutions, plays a crucial role in enhancing students' creative expression, narrative construction, argumentative prowess, and literary skills through its focus on non-fiction writing. Despite its significance, the comprehensive syllabus, coupled with limited classroom time, often restricts adequate practice opportunities and leads to delayed feedback, negatively impacting students' preparation for assessments. This paper investigates the potential of generative artificial intelligence (AI) tools, such as ChatGPT and POE, to provide personalized and immediate feedback for writing tasks. The primary goal of this research is to evaluate student receptiveness to AI-generated feedback and compare it to traditional feedback provided solely by human instructors. To achieve this, participants will be systematically divided into two groups: one receiving feedback from both instructors and AI tools, and a control group that receives feedback exclusively from instructors. The study will thoroughly analyze the revisions made to texts after receiving feedback, focusing particularly on enhancements in the quality of content and language proficiency across three dimensions: content/theme, language, and structural logic. This investigation aims to determine whether AI tools can enhance the efficiency of teaching practices, encourage autonomous learning, and significantly improve the overall quality of students' written work.

Keywords: AI-generated feedback, Chinese writing, non-fiction writing, student receptiveness

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Authors: Ma Yuan, Zhang Mengxi, Akbar Javadi, Chen Longqing

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The structure of sand-filled embankment with cover layer is treated with tipping clay modified with lime on the outside of the packing, and the geotextile is placed between the stuffing and the clay. The packing is usually river sand, and the improved clay protects the sand core against rainwater erosion. The sand-filled embankment with cover layer has practical problems such as high filling embankment, construction restriction, and steep slope. The reinforcement can be applied to the sand-filled embankment with cover layer to solve the complicated problems such as irregular settlement caused by poor stability of the embankment. At present, the research on the sand-filled embankment with cover layer mainly focuses on the sand properties, construction technology, and slope stability, and there are few studies in the experimental field, the deformation characteristics and stability of reinforced sand-filled embankment need further study. In addition, experimental research is relatively rare when the cyclic load is considered in tests. A subgrade structure of geogrid-reinforced sand-filled embankment with cover layer was proposed. The mechanical characteristics, the deformation properties, reinforced behavior and the ultimate bearing capacity of the embankment structure under cyclic loading were studied. For this structure, the geogrids in the sand and the tipping soil are through the geotextile which is arranged in sections continuously so that the geogrids can cross horizontally. Then, the Unsaturated/saturated Soil Triaxial Test System of Geotechnical Consulting and Testing Systems (GCTS), USA was modified to form the loading device of this test, and strain collector was used to measuring deformation and earth pressure of the embankment. A series of cyclic loading model tests were conducted on the geogrid-reinforced sand-filled embankment with a cover layer under a different number of reinforcement layers, the length of reinforcement and thickness of the cover layer. The settlement of the embankment, the normal cumulative deformation of the slope and the earth pressure were studied under different conditions. Besides cyclic loading model tests, model experiments of embankment subjected cyclic-static loading was carried out to analyze ultimate bearing capacity with different loading. The experiment results showed that the vertical cumulative settlement under long-term cyclic loading increases with the decrease of the number of reinforcement layers, length of the reinforcement arrangement and thickness of the tipping soil. Meanwhile, these three factors also have an influence on the decrease of the normal deformation of the embankment slope. The earth pressure around the loading point is significantly affected by putting geogrid in a model embankment. After cyclic loading, the decline of ultimate bearing capacity of the reinforced embankment can be effectively reduced, which is contrary to the unreinforced embankment.

Keywords: cyclic load; geogrid; reinforcement behavior; cumulative deformation; earth pressure

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Authors: Felix Baumann, Aleksandar Milutinovic, Dieter Roller

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Up to this point business process management projects in general and business process modelling projects in particular could not rely on a practical and scientifically validated method to estimate cost and effort. Especially the model development phase is not covered by a cost estimation method or model. Further phases of business process modelling starting with implementation are covered by initial solutions which are discussed in the literature. This article proposes a method of filling this gap by deriving a cost estimation method from available methods in similar domains namely software development or software engineering. Software development is regarded as closely similar to process modelling as we show. After the proposition of this method different ideas for further analysis and validation of the method are proposed. We derive this method from COCOMO II and Function Point which are established methods of effort estimation in the domain of software development. For this we lay out similarities of the software development rocess and the process of process modelling which is a phase of the Business Process Management life-cycle.

Keywords: COCOMO II, busines process modeling, cost estimation method, BPM COCOMO

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Authors: Hamed Hedayatnia, Nathan Van Den Bossche

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Understanding the ways in which climate change accelerates or slows down the process of material deterioration is the first step towards assessing adaptive approaches for the conservation of historical heritage. Analysis of the climate change effects on the degradation risk assessment parameters like freeze-thaw cycles and wind erosion is also a key parameter when considering mitigating actions. Due to the vulnerability of cultural heritage to climate change, the impact of this phenomenon on material degradation criteria with the focus on brick masonry walls in Timurid heritage, located in Iran, was studied. The Timurids were the final great dynasty to emerge from the Central Asian steppe. Through their patronage, the eastern Islamic world in northwestern of Iran, especially in Mashhad and Herat, became a prominent cultural center. Goharshad Mosque is a mosque in Mashhad of the Razavi Khorasan Province, Iran. It was built by order of Empress Goharshad, the wife of Shah Rukh of the Timurid dynasty in 1418 CE. Choosing an appropriate regional climate model was the first step. The outputs of two different climate model: the 'ALARO-0' and 'REMO,' were analyzed to find out which model is more adopted to the area. For validating the quality of the models, a comparison between model data and observations was done in 4 different climate zones in Iran for a period of 30 years. The impacts of the projected climate change were evaluated until 2100. To determine the material specification of Timurid bricks, standard brick samples from a Timurid mosque were studied. Determination of water absorption coefficient, defining the diffusion properties and determination of real density, and total porosity tests were performed to characterize the specifications of brick masonry walls, which is needed for running HAM-simulations. Results from the analysis showed that the threatening factors in each climate zone are almost different, but the most effective factor around Iran is the extreme temperature increase and erosion. In the north-western region of Iran, one of the key factors is wind erosion. In the north, rainfall erosion and mold growth risk are the key factors. In the north-eastern part, in which our case study is located, the important parameter is wind erosion.

Keywords: brick, climate change, degradation criteria, heritage, Timurid period

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Authors: Nikola Vlahovic, Blazenka Knezevic, Petra Batalic

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In this paper, we will present a research about feasibility of implementing unmanned aerial vehicles, also known as 'drones', in logistics. Research is based on available information about current incentives and experiments in application of delivery drones in commercial use. Overview of current pilot projects and literature, as well as an overview of detected challenges, will be compiled and presented. Based on these findings, we will present a conceptual model of business process that implements delivery drones in business to business logistic operations. Business scenario is based on a pharmaceutical supply chain. Simulation modeling will be used to create models for running experiments and collecting performance data. Comparative study of the presented conceptual model will be given. The work will outline the main advantages and disadvantages of implementing unmanned aerial vehicles in delivery services as a supplementary distribution channel along the supply chain.

Keywords: business process, delivery drones, logistics, simulation modelling, unmanned aerial vehicles

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Authors: Babatunde Osabiya

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Cybersecurity has emerged as a pressing policy problem in recent years, affecting individuals, businesses, and governments worldwide. This research paper aims to critically review the literature on cybersecurity policy and apply policy theory to propose a policy approach that balances the freedom to access and use technology with the human rights risks and threats posed by cyber. Drawing on various credible sources, the paper examines the scale and seriousness of cyber threats, highlighting the growing threat posed by cybercriminals, hackers, and nation-states. The paper also identifies the key challenges facing policymakers, including the need for more significant investment in cybersecurity research and development and the importance of balancing the benefits of technological innovation with the risks to privacy, security, and human rights. To address these challenges, the paper proposes a policy approach emphasizing investing in cybersecurity research and development to maintain a technological edge over potential adversaries. This approach also highlights the need for greater collaboration between government, industry, and civil society to develop effective cybersecurity policies and practices that protect the rights and freedoms of people while mitigating the risks posed by cyber threats. This paper will contribute to the growing body of literature on cybersecurity policy and offers a policy framework for addressing this critical policy challenge.

Keywords: security risk, legal framework, cyber security and policy, national security

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Authors: Xin Chen, Xiao Yang, Rongrong Han, Lu Chen, Lingling Gao

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Background: Leisure time physical activity (LTPA) benefits both pregnant women and their fetuses. The guidelines recommended that pregnant women should do at least 150 minutes of moderate-intensity aerobic physical activity throughout the week. The aim of this study was to investigate the rate of LTPA participation among Chinese pregnant women and to identify its predictors based on the health belief model. Methods: A cross-sectional study was conducted from June 2019 to September 2019 in Changchun, China. A total of 225 pregnant women aged 18 years or older with no severe physical or mental disease were recruited in the obstetric clinic. Self-administered questionnaires were used to collect data. LTPA was assessed by a pregnant physical activity questionnaire (PPAQ). A revised pregnancy physical activity health belief scale and social-demographic and perinatal characteristics factors were collected and used to predict LTPA participation. Data were analyzed using descriptive statistics and multivariate logistic regression. Results: The participants had a high level of perceived susceptibility, perceived severity, perceived benefits, and action clues, with mean item scores above 3.5. The predictors of LTPA in Chinese pregnant women were pre-pregnancy exercise habits [OR 3.236 (95% CI:1.632, 6.416)], perceived susceptibility score [OR 2.083 (95% CI:1.002, 4.331)], and perceived barriers score [OR 3.113 (95%CI:1.462, 6.626)]. Conclusions: The results of this study will lead to better identification of pregnant women who may not participate in LTPA. Healthcare professionals should be cognizant of issues that may affect LTPA participation among pregnant women, including pre-pregnancy exercise habits, perceived susceptibility, and perceived barriers.

Keywords: pregnancy, health belief model., leisure time physical activity, factors

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Authors: Abhisek Chakrabarty, Subhraprakash Mandal

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Flash flood is one of the catastrophic natural hazards in the mountainous region of India. The recent flood in the Mandakini River in Kedarnath (14-17th June, 2013) is a classic example of flash floods that devastated Uttarakhand by killing thousands of people.The disaster was an integrated effect of high intensityrainfall, sudden breach of Chorabari Lake and very steep topography. Every year in Himalayan Region flash flood occur due to intense rainfall over a short period of time, cloud burst, glacial lake outburst and collapse of artificial check dam that cause high flow of river water. In Sikkim-Derjeeling Himalaya one of the probable flash flood occurrence zone is Teesta Watershed. The Teesta River is a right tributary of the Brahmaputra with draining mountain area of approximately 8600 Sq. km. It originates in the Pauhunri massif (7127 m). The total length of the mountain section of the river amounts to 182 km. The Teesta is characterized by a complex hydrological regime. The river is fed not only by precipitation, but also by melting glaciers and snow as well as groundwater. The present study describes an attempt to model surface runoff in upper Teesta basin, which is directly related to catastrophic flood events, by creating a system based on GIS technology. The main object was to construct a direct unit hydrograph for an excess rainfall by estimating the stream flow response at the outlet of a watershed. Specifically, the methodology was based on the creation of a spatial database in GIS environment and on data editing. Moreover, rainfall time-series data collected from Indian Meteorological Department and they were processed in order to calculate flow time and the runoff volume. Apart from the meteorological data, background data such as topography, drainage network, land cover and geological data were also collected. Clipping the watershed from the entire area and the streamline generation for Teesta watershed were done and cross-sectional profiles plotted across the river at various locations from Aster DEM data using the ERDAS IMAGINE 9.0 and Arc GIS 10.0 software. The analysis of different hydraulic model to detect flash flood probability ware done using HEC-RAS, Flow-2D, HEC-HMS Software, which were of great importance in order to achieve the final result. With an input rainfall intensity above 400 mm per day for three days the flood runoff simulation models shows outbursts of lakes and check dam individually or in combination with run-off causing severe damage to the downstream settlements. Model output shows that 313 Sq. km area were found to be most vulnerable to flash flood includes Melli, Jourthang, Chungthang, and Lachung and 655sq. km. as moderately vulnerable includes Rangpo,Yathang, Dambung,Bardang, Singtam, Teesta Bazarand Thangu Valley. The model was validated by inserting the rain fall data of a flood event took place in August 1968, and 78% of the actual area flooded reflected in the output of the model. Lastly preventive and curative measures were suggested to reduce the losses by probable flash flood event.

Keywords: flash flood, GIS, runoff, simulation model, Teesta river basin

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Authors: Omaima Jbara, Mohame Amine Omrani, Mounir Zrigui

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The detection of violent content in animated cartoons is anessential step toward safeguarding young audiences and promoting responsible media consumption. This study introduces an automated approach to identify violent scenes in cartoons using advanced object detection models. A custom dataset comprising 1,200 frames was curated from various animated sources, focusing on four key classes: Explosion, Blood, Fight, and Gunshot. Data augmentation techniques, including rotation, scaling, and color adjustments, expanded the dataset to 2,000 frames, enhancing diversity and model generalization. YOLO versions 8, 9, and 10 were trained and evaluated on this dataset. Among these, YOLOv9 achieved the highest performance with a mean Average Precision (mAP) of 94%, demonstrating superior accuracy and robustness. These findings highlight YOLOv9’s potential as a reliable tool for detecting violent content in animated media, contributing to the development of effective content moderation systems.

Keywords: cartoon violence detection, YOLO model, computer Vi sion, Real-time content analysis

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Authors: Farshad Amini, Kejun Wen

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The formation of reflective cracking of pavement overlays has confronted highway engineers for many years. Stress-relieving interlayers, such as paving fabrics, have been used in an attempt to reduce or delay reflective cracking. The effectiveness of paving fabrics in reducing reflection cracking is related to joint or crack movement in the underlying pavement, crack width, overlay thickness, subgrade conditions, climate, and traffic volume. The nonwoven geotextiles are installed between the old and new asphalt layers. Paving fabrics enhance performance through two mechanisms: stress relief and waterproofing. Several factors including proper installation, remedial work performed before overlay, overlay thickness, variability of pavement strength, existing pavement condition, base/subgrade support condition, and traffic volume affect the performance. The primary objective of this study was to conduct a long-term monitoring of the paving fabric interlayer systems to evaluate its effectiveness and performance. A comprehensive testing, monitoring, and analysis program were undertaken, where twelve 500-ft pavement sections of a four-lane highway were rehabilitated, and then monitored for seven years. A comparison between the performance of paving fabric treatment systems and control sections is reported. Lessons learned, and the various factors are discussed.

Keywords: monitoring, paving fabrics, performance, reflective cracking

Procedia PDF Downloads 335

Authors: Monir Ahmed

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The main purpose of this paper is to analyze existing conceptual papers on the divine relationship. The primary objective of the paper is to illustrate cognitive orientation as a determinant of divine relationship. A further aim of the paper is to establish whether spiritual or religious practices, rituals, or acts alone could confirm a relationship with the sacred or the divine. Searching for the sacred or the divine is known to be a novel way of understanding the meaning and purpose of human existence, including the existence of everything around us. Inevitably, searching for the sacred provides an opportunity for human beings to form a relationship with the divine. Research suggests that discovering meaning and purpose through searching for the sacred or forming relationship with the divine enhances psychological well-being and eventually helps individuals to flourish. The search for the sacred and the discovery of the divine relationship thus have become interesting areas of study in Psychology of Religion and Spirituality. The existing conceptual papers on the relationship with the transcendent source, i.e., the divine creator, were systematically reviewed and analyzed. The outcome of the review reveals that the existing understanding of the relationship with the divine source is inadequate and that such understanding is unable to indicate or confirm a relationship with psychological well-being, including spiritual well-being. The importance of cognitive orientation, including cognitive processes as well as ‘creatio ex nihilo’ doctrine in searching for the sacred, is indicated. The author of this paper proposes that cognitive-theological understanding involving faith and belief about the creation and the divine source, the transcendent God is likely to offer a comprehensive understanding of the divine relationship.

Keywords: divine, well-being, analysis, cognitive orientation, ‘creatio ex nihilo’ doctrine

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Authors: Andrey Khalov

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The rapid proliferation of unstructured data in IT infrastructure management demands innovative approaches for extracting actionable knowledge. This paper presents a framework for ontology-based knowledge extraction that combines relational graph neural networks (R-GNN) with large language models (LLMs). The proposed method leverages the DOLCE framework as the foundational ontology, extending it with concepts from ITSMO for domain-specific applications in IT service management and outsourcing. A key component of this research is the use of transformer-based models, such as DeBERTa-v3-large, for automatic entity and relationship extraction from unstructured texts. Furthermore, the paper explores how transfer learning techniques can be applied to fine-tune large language models (LLaMA) for using to generate synthetic datasets to improve precision in BERT-based entity recognition and ontology alignment. The resulting IT Ontology (ITO) serves as a comprehensive knowledge base that integrates domain-specific insights from ITIL processes, enabling more efficient decision-making. Experimental results demonstrate significant improvements in knowledge extraction and relationship mapping, offering a cutting-edge solution for enhancing cognitive computing in IT service environments.

Keywords: ontology expansion, synthetic dataset, transformer fine-tuning, concept extraction, DOLCE, BERT, taxonomy, LLM, NER

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Authors: Xavier Lorang, Ahmadali Tahmasebimoradi, Chetra Mang, Sylvain Girard

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The additive manufacturing processes (e.g. selective laser melting) allow us to produce lattice structures which have less weight, higher impact absorption capacity, and better thermal exchange property compared to the classical structures. Unfortunately, geometric imperfections (defects) in the lattice structures are by-products results of the manufacturing process. These imperfections decrease the lifetime and the strength of the lattice structures and alternate their mechanical responses. The objective of the paper is to present a simulation strategy which allows us to take into account the effect of the geometric imperfections on the mechanical response of the lattice structure. In the first part, an identification method of geometric imperfection parameters of the lattice structure based on point clouds is presented. These point clouds are based on tomography measurements. The point clouds are fed into the platform LATANA (LATtice ANAlysis) developed by IRT-SystemX to characterize the geometric imperfections. This is done by projecting the point clouds of each microbeam along the beam axis onto a 2D surface. Then, by fitting an ellipse to the 2D projections of the points, the geometric imperfections are characterized by introducing three parameters of an ellipse; semi-major/minor axes and angle of rotation. With regard to the calculated parameters of the microbeam geometric imperfections, a statistical analysis is carried out to determine a probability density law based on a statistical hypothesis. The microbeam samples are randomly drawn from the density law and are used to generate lattice structures. In the second part, a finite element model for the lattice structure with the simplified geometric imperfections (ellipse parameters) is presented. This numerical model is used to simulate the generated lattice structures. The propagation of the uncertainties of geometric imperfections is shown through the distribution of the computed mechanical responses of the lattice structures.

Keywords: additive manufacturing, finite element model, geometric imperfections, lattice structures, propagation of uncertainty

Procedia PDF Downloads 191