Search results for: impact models

Authors: Atitallah Sofien, Missaoui Nada, Ben Rabeh Rania, Yahyaoui Salem, Mazigh Sonia, Bouyahia Olfa, Boukthir Samir

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Introduction: Acute bronchiolitis (AB) is a real public health problem on a global and national scale. Its treatment is most often outpatient. The use of audio-visual supports, such as educational videos, is an innovation in therapeutic education in outpatient treatment. The aim of our study was to evaluate the impact of an educational video on the knowledge, attitudes, and practices of mothers of infants with AB. Methodology: This was a descriptive, analytical, and cross-sectional study with prospective data collection, including mothers of infants with AB. We assessed mothers' knowledge, attitudes, and practices regarding AB, and we created an educational video. We used a questionnaire written in Tunisian Arabic concerning sociodemographic data, mothers' knowledge and attitudes regarding AB, and their opinions on the video, as well as an observation grid to evaluate their practices on the nasopharyngeal unblocking technique. We compared the different parameters before and after watching the video. Results: We noted a statistically significant improvement in mothers' knowledge scores on AB (7.46 in the pre-test versus 14.08 in the post-test; p≤0.05), practices (12.42 in the pre-test versus 18 in the post-test; p≤0.05) and attitudes (5.86 in pre-test versus 9.02 in post-test; p≤0.05). Conclusion: The use of an educational video has a positive impact on the knowledge, practices, and attitudes of mothers towards AB.

Keywords: acute bronchiolitis, therapeutic education, mothers, educational video

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Authors: Gabriel Dwomoh, Williams Kwasi Boachie, Kofi Kwarteng

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The study looked at the relationship between organizations’ acquired knowledge, skills, abilities, and shareholders wealth with training playing the mediating role. The sample of the study consisted of organizations that spent 10% or more of its annual budget on training and those whose training budget is less than 10% of the organization’s annual budget. A total of 620 questionnaires were distributed to employees working in various organizations out of which 580 representing 93.5% were retrieved. The respondents that constitute the sample were drawn using convenience sampling. The researchers used regression models for their analyses with the help of SPSS 16.0. Analyzing multiple models, it was discovered that organizations training investment plays a considerable indirect and direct effect with partial mediation between organizations acquired skills, knowledge, abilities, and shareholders wealth. Shareholders should allow their agents to invest part of their holdings to develop the human capital of the organization but this should be done with caution since shareholders returns do not depend much on how much organizations spend in developing its human resource capital.

Keywords: skills, knowledge, abilities, shareholders wealth, training investment

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Authors: G. Aloh Obianuju, C. Chukwu Kelvin, Henry Aloh

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The study was undertaken to assess the environmental and socio-economic impact of quarrying in Umuoghara quarrying community of Ebonyi State, South East Nigeria. Questionnaires were distributed targeting quarry workers and people living within the community; personal interviews with other key informants were also conducted. All these were used as data gathering instruments. The study reveals that there were actually some benefits as well as marked environmental impacts in the community as a result of quarrying activities. Recommendations that can assist in mitigating these adverse impacts were suggested.

Keywords: environment, quarrying, environmental degradation, mitigation

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Authors: Martha E. Ndeley

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Operation management is the key element within the manufacturing process. However, during this process, there are a number of unforeseen disruptions that causes the process to a standstill which are, machine breakdown, employees absenteeism, improper scheduling. When this happens, it forces the shop flow to a rescheduling process and these strategy reschedules only a limited part of the initial schedule to match up with the pre-schedule at some point with the objective to create a new schedule that is reliable which in the long run gets disrupted. In this work, we have developed feedback control system that minimizes any form of disruption before the impact becomes severe, the model was tested in a paper manufacturing industries and the results revealed that, if the disruption is minimized at the initial state, the impact becomes unnoticeable.

Keywords: disruption, machine, absenteeism, scheduling

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Authors: M. Cortés, E. Vera, O. Rojas

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The research studies of the kinetics of the corrosion process that attacks concrete and occurs within sewerage systems agree on the amount of variables that interfere in the process. This study aims to check the impact of the pH levels of the corrosive environment and the concrete surface, the concentrations of chemical sulfuric acid, and in turn, measure the resistance of concrete to this attack under controlled laboratory conditions; it also aims to contribute to the development of further research related to the topic, in order to compare the impact of biogenic sulfuric acid and chemical sulfuric acid involvement on concrete structures, especially in scenarios such as sewerage systems.

Keywords: acid sulfuric, concrete, corrosion, biogenic

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Authors: Prashant Verma, Prafulla K. Swain, K. K. Singh, Mukti Khetan

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Objective: In India, around 20,000 women die every year due to abortion-related complications. In the modelling of count variables, there is sometimes a preponderance of zero counts. This article concerns the estimation of various count regression models to predict the average number of spontaneous abortion among women in the Punjab state of India. It also assesses the factors associated with the number of spontaneous abortions. Materials and methods: The study included 27,173 married women of Punjab obtained from the DLHS-4 survey (2012-13). Poisson regression (PR), Negative binomial (NB) regression, zero hurdle negative binomial (ZHNB), and zero-inflated negative binomial (ZINB) models were employed to predict the average number of spontaneous abortions and to identify the determinants affecting the number of spontaneous abortions. Results: Statistical comparisons among four estimation methods revealed that the ZINB model provides the best prediction for the number of spontaneous abortions. Antenatal care (ANC) place, place of residence, total children born to a woman, woman's education and economic status were found to be the most significant factors affecting the occurrence of spontaneous abortion. Conclusions: The study offers a practical demonstration of techniques designed to handle count variables. Statistical comparisons among four estimation models revealed that the ZINB model provided the best prediction for the number of spontaneous abortions and is recommended to be used to predict the number of spontaneous abortions. The study suggests that women receive institutional Antenatal care to attain limited parity. It also advocates promoting higher education among women in Punjab, India.

Keywords: count data, spontaneous abortion, Poisson model, negative binomial model, zero hurdle negative binomial, zero-inflated negative binomial, regression

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Authors: Saifalarab A. Mohmmed, Morgana E. Vianna, Jonathan C. Knowles

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The issue of apical periodontitis has received considerable critical attention. Bacteria is integrated into communities, attached to surfaces and consequently form biofilm. The biofilm structure provides bacteria with a series protection skills against, antimicrobial agents and enhances pathogenicity (e.g. apical periodontitis). Sodium hypochlorite (NaOCl) has become the irrigant of choice for elimination of bacteria from the root canal system based on its antimicrobial findings. The aim of the study was to investigate the effect of different agitation techniques on the efficacy of 2.5% NaOCl to eliminate the biofilm from the surface of the lateral canal using the residual biofilm, and removal rate of biofilm as outcome measures. The effect of canal complexity (lateral canal) on the efficacy of the irrigation procedure was also assessed. Forty root canal models (n = 10 per group) were manufactured using 3D printing and resin materials. Each model consisted of two halves of an 18 mm length root canal with apical size 30 and taper 0.06, and a lateral canal of 3 mm length, 0.3 mm diameter located at 3 mm from the apical terminus. E. faecalis biofilms were grown on the apical 3 mm and lateral canal of the models for 10 days in Brain Heart Infusion broth. Biofilms were stained using crystal violet for visualisation. The model halves were reassembled, attached to an apparatus and tested under a fluorescence microscope. Syringe and needle irrigation protocol was performed using 9 mL of 2.5% NaOCl irrigant for 60 seconds. The irrigant was either left stagnant in the canal or activated for 30 seconds using manual (gutta-percha), sonic and ultrasonic methods. Images were then captured every second using an external camera. The percentages of residual biofilm were measured using image analysis software. The data were analysed using generalised linear mixed models. The greatest removal was associated with the ultrasonic group (66.76%) followed by sonic (45.49%), manual (43.97%), and passive irrigation group (control) (38.67%) respectively. No marked reduction in the efficiency of NaOCl to remove biofilm was found between the simple and complex anatomy models (p = 0.098). The removal efficacy of NaOCl on the biofilm was limited to the 1 mm level of the lateral canal. The agitation of NaOCl results in better penetration of the irrigant into the lateral canals. Ultrasonic agitation of NaOCl improved the removal of bacterial biofilm.

Keywords: 3D printing, biofilm, root canal irrigation, sodium hypochlorite

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Authors: M. C. Teng, M. C. Ke, C. Y. Yang, S. S. Ke

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There are more than one thousand times a year of felt earthquakes in Taiwan. Because earthquakes are disaster threats to urban infrastructure, they often disrupt infrastructure services. For example, the highway system is very important to transportation infrastructure; however, it is vulnerable to earthquakes and typhoons in Taiwan. When a highway system is damaged by disaster, it will create a major impact on post-disaster communications and emergency relief and affect disaster relief works. In a study case on September 18th, 2022, the Taitung Chihshang earthquake, with a magnitude of 6.8 on the Richter scale with a depth of 7 km, caused one death; 171 people were injured and had a significant urban infrastructure impact. Hualien and Taitung areas have a large number of surface ruptures, road disruptions due to the collapses, over ten cases of bridges failure or closed, partial railroad section service shutdown, building collapses, and casualties. Taitung Chihshang earthquake, the peak ground acceleration is 585 gal (cm/s²), and the seismic intensity is Level 6 Upper(6+)in Chishang, Taitung County. After the earthquakes, we conducted on-site disaster investigation works in the disaster area; the disaster investigation works included a public and private building survey, a transportation facility survey, a total of ten damaged bridges, and one railroad station damaged were investigated in this investigation. The results showed that the affected locations were mainly concentrated along the Chihshang fault and the Yuli fault in the Huatung Longitudinal Valley. We recorded and described the impact and assessed its influence region in terms of its susceptibility to and the consequences of earthquake attacks. In addition, a lesson is learned from this study regarding the key issues after the Taitung Chihshang earthquake.

Keywords: earthquake, infrastructure, disaster investigation, lesson learned

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Authors: Malik Muhammad Arslan, Muneeb Ullah, Dai Shihan, Daniyal Haider, Xiaodong Yang

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Chest X-rays are instrumental in the detection and monitoring of a wide array of diseases, including viral infections such as COVID-19, tuberculosis, pneumonia, lung cancer, and various cardiac and pulmonary conditions. To enhance the accuracy of diagnosis, artificial intelligence (AI) algorithms, particularly deep learning models like Convolutional Neural Networks (CNNs), are employed. However, these deep learning models demand a substantial and varied dataset to attain optimal precision. Generative Adversarial Networks (GANs) can be employed to create new data, thereby supplementing the existing dataset and enhancing the accuracy of deep learning models. Nevertheless, GANs have their limitations, such as issues related to stability, convergence, and the ability to distinguish between authentic and fabricated data. In order to overcome these challenges and advance the detection and classification of CXR normal and abnormal images, this study introduces a distinctive technique known as DCWGAN (Diverse Conditional Wasserstein GAN) for generating synthetic chest X-ray (CXR) images. The study evaluates the effectiveness of this Idiosyncratic DCWGAN technique using the ResNet50 model and compares its results with those obtained using the traditional GAN approach. The findings reveal that the ResNet50 model trained on the DCWGAN-generated dataset outperformed the model trained on the classic GAN-generated dataset. Specifically, the ResNet50 model utilizing DCWGAN synthetic images achieved impressive performance metrics with an accuracy of 0.961, precision of 0.955, recall of 0.970, and F1-Measure of 0.963. These results indicate the promising potential for the early detection of diseases in CXR images using this Inimitable approach.

Keywords: CNN, classification, deep learning, GAN, Resnet50

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Authors: Hicham Amine, Abdelouahab Mesnaoui

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Electronic data interchange EDI is the computer-to-computer exchange of structured business information. This information typically takes the form of standardized electronic business documents, such as invoices, purchase orders, bills of lading, and so on. The purpose of this study is to identify the impact EDI might have on supply chain and typically on customer satisfaction keeping in mind the constraints the organization might face. This study included 139 subject matter experts (SMEs) who participated by responding to a survey that was distributed. 85% responded that they are extremely for the implementation while 10% were neutral and 5% were against the implementation. From the quality assurance department, we have got 75% from the clients agreed to move on with the change whereas 10% stayed neutral and finally 15% were against the change. From the legal department where 80% of the answers were for the implementation and 10% of the participants stayed neutral whereas the last 10% were against it. The survey consisted of 40% male and 60% female (sex-ratio (F/M=1,5), who had chosen to participate. Our survey also contained 3 categories in terms of technical background where 80% are from technical background and 15% were from nontechnical background and 5% had some average technical background. This study examines the impact of EDI on customer satisfaction which is the primary hypothesis and justifies the importance of the implementation which enhances the customer satisfaction.

Keywords: electronic data interchange, supply chain, subject matter experts, customer satisfaction

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Authors: Rabia Korkmaz Tan, Şebnem Bora

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The major problem encountered when modeling complex systems with agent-based modeling and simulation techniques is the existence of large parameter spaces. A complex system model cannot be expected to reflect the whole of the real system, but by specifying the most appropriate parameters, the actual system can be represented by the model under certain conditions. When the studies conducted in recent years were reviewed, it has been observed that there are few studies for parameter tuning problem in agent based simulations, and these studies have focused on tuning parameters of a single model. In this study, an approach of parameter tuning is proposed by using metaheuristic algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Artificial Bee Colonies (ABC), Firefly (FA) algorithms. With this hybrid structured study, the parameter tuning problems of the models in the different fields were solved. The new approach offered was tested in two different models, and its achievements in different problems were compared. The simulations and the results reveal that this proposed study is better than the existing parameter tuning studies.

Keywords: parameter tuning, agent based modeling and simulation, metaheuristic algorithms, complex systems

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Authors: Adama NS Bah

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Background: Loss of teeth has a negative influence on essential oral functions such as phonetics, mastication, and aesthetics. Dentists treat people with prosthodontic rehabilitation to recover essential oral functions. The oral health quality of life inventory reflects the success of prosthodontic rehabilitation. In many countries, the current conventional care delivered to replace missing teeth for adult patients involves the provision of removable partial dentures. Aim: The aim of this systematic review and meta-analysis is to gather the best available evidence to determine patients’ oral health-related quality of life improvement after treatment with partial dentures. Methods: We searched electronic databases from January 2010 to September 2019, including PubMed, ProQuest, Science Direct, Scopus and Google Scholar. In this paper, studies were included only if the average age was 30 years and above and also published in English. Two reviewers independently screened and selected all the references based on inclusion criteria using the PRISMA guideline, and assessed the quality of the included references using the Joanna Briggs Institute quality assessment tools. Data extracted were analyzed in RevMan 5.0 software, the heterogeneity between the studies was assessed using Forest plot, I2 statistics and chi-square test with a statistical P value less than 0.05 to indicate statistical significance. Random effect models were used in case of moderate or high heterogeneity. Four studies were included in the systematic review and three studies were pooled for meta-analysis. Results: Four studies included in the systematic review and three studies included in the meta-analysis with a total of 285 patients comparing the improvement in oral health-related quality of life before and after rehabilitation with partial denture, the pooled results showed a better improvement of oral health-related quality of life after treatment with partial dentures (mean difference 5.25; 95% CI [3.81, 6.68], p < 0.00001) favoring the wearing of partial dentures. In order to ascertain the reliability of the included studies for meta-analysis risk of bias was assessed and found to be low in all included studies for meta-analysis using the Cochrane collaboration tool for risk of bias assessment. Conclusion: There is high evidence that rehabilitation with partial dentures can improve the patient’s oral health-related quality of life measured with Oral Health Impact Profile 14. This review has clinical evidence value for dentists treating the expanding vulnerable adult population.

Keywords: meta-analysis, oral health impact profile, partial dentures, systematic review

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Authors: Nikolaos Papadimas, Joanna Bennett, Amir Sakhaei, Timothy Dodwell

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Composite modeling of consolidation processes is playing an important role in the process and part design by indicating the formation of possible unwanted prior to expensive experimental iterative trial and development programs. Composite materials in their uncured state display complex constitutive behavior, which has received much academic interest, and this with different models proposed. Errors from modeling and statistical which arise from this fitting will propagate through any simulation in which the material model is used. A general hyperelastic polynomial representation was proposed, which can be readily implemented in various nonlinear finite element packages. In our case, FEniCS was chosen. The coefficients are assumed uncertain, and therefore the distribution of parameters learned using Markov Chain Monte Carlo (MCMC) methods. In engineering, the approach often followed is to select a single set of model parameters, which on average, best fits a set of experiments. There are good statistical reasons why this is not a rigorous approach to take. To overcome these challenges, A hierarchical Bayesian framework was proposed in which population distribution of model parameters is inferred from an ensemble of experiments tests. The resulting sampled distribution of hyperparameters is approximated using Maximum Entropy methods so that the distribution of samples can be readily sampled when embedded within a stochastic finite element simulation. The methodology is validated and demonstrated on a set of consolidation experiments of AS4/8852 with various stacking sequences. The resulting distributions are then applied to stochastic finite element simulations of the consolidation of curved parts, leading to a distribution of possible model outputs. With this, the paper, as far as the authors are aware, represents the first stochastic finite element implementation in composite process modelling.

Keywords: data-driven , material consolidation, stochastic finite elements, surrogate models

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Authors: Müzeyyen Balçikanli, Erdoğan Özbay, Hakan Tacettin Türker, Okan Karahan, Cengiz Duran Atiş

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In this research, effect of curing time (TC), curing temperature (CT), sodium concentration (SC) and silicate modules (SM) on the compressive strength, chloride ion permeability, and water absorption capacity of alkali activated slag (AAS) concretes were investigated. For maximization of compressive strength while for minimization of chloride ion permeability and water absorption capacity of AAS concretes, best possible combination of CT, CTime, SC and SM were determined. An experimental program was conducted by using the central composite design method. Alkali solution-slag ratio was kept constant at 0.53 in all mixture. The effects of the independent parameters were characterized and analyzed by using statistically significant quadratic regression models on the measured properties (dependent parameters). The proposed regression models are valid for AAS concretes with the SC from 0.1% to 7.5%, SM from 0.4 to 3.2, CT from 20 °C to 94 °C and TC from 1.2 hours to 25 hours. The results of test and analysis indicate that the most effective parameter for the compressive strength, chloride ion permeability and water absorption capacity is the sodium concentration.

Keywords: alkali activation, slag, rapid chloride permeability, water absorption capacity

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Authors: Muhammad Azam, Micheal Olaolu Arowolo, Fei He, Mihail Popescu, Dong Xu

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The number of biological papers is growing quickly, which means that the number of biological pathway figures in those papers is also increasing quickly. Each pathway figure shows extensive biological information, like the names of genes and how the genes are related. However, manually annotating pathway figures takes a lot of time and work. Even though using advanced image understanding models could speed up the process of curation, these models still need to be made more accurate. To improve gene name recognition from pathway figures, we applied a Siamese network to map image segments to a library of pictures containing known genes in a similar way to person recognition from photos in many photo applications. We used a triple loss function and a triplet spatial pyramid pooling network by combining the triplet convolution neural network and the spatial pyramid pooling (TSPP-Net). We compared VGG19 and VGG16 as the Siamese network model. VGG16 achieved better performance with an accuracy of 93%, which is much higher than OCR results.

Keywords: biological pathway, image understanding, gene name recognition, object detection, Siamese network, VGG

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Authors: Abu Afree Andalib, Rafiur Rahman, Md Mezbah Uddin

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The main objective of this work is to anatomize on the various parameters of AGM 88 missile anatomized using FSI module in Ansys. Computational fluid dynamics is used for the study of fluid flow pattern and fluidic phenomenon such as drag, pressure force, energy dissipation and shockwave distribution in water. Using finite element analysis module of Ansys, structural parameters such as stress and stress density, localization point, deflection, force propagation is determined. Separate analysis on structural parameters is done on Abacus. State of the art coupling module is used for FSI analysis. Fine mesh is considered in every case for better result during simulation according to computational machine power. The result of the above-mentioned parameters is analyzed and compared for two phases using graphical representation. The result of Ansys and Abaqus are also showed. Computational Fluid Dynamics and Finite Element analyses and subsequently the Fluid-Structure Interaction (FSI) technique is being considered. Finite volume method and finite element method are being considered for modelling fluid flow and structural parameters analysis. Feasible boundary conditions are also utilized in the research. Significant change in the interaction and interference pattern while the impact was found. Theoretically as well as according to simulation angled condition was found with higher impact.

Keywords: FSI (Fluid Surface Interaction), impact, missile, high viscous fluid, CFD (Computational Fluid Dynamics), FEM (Finite Element Analysis), FVM (Finite Volume Method), fluid flow, fluid pattern, structural analysis, AGM-88, Ansys, Abaqus, meshing, k-omega, turbulence model

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Authors: S. H. Iranmanesh, L. Aliabadi, A. Mollajan

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Integrated resilience engineering (IRE) is capable of returning banking systems to the normal state in extensive economic circumstances. In this study, information system of a large bank (with several branches) is assessed and optimized under severe economic conditions. Data envelopment analysis (DEA) models are employed to achieve the objective of this study. Nine IRE factors are considered to be the outputs, and a dummy variable is defined as the input of the DEA models. A standard questionnaire is designed and distributed among executive managers to be considered as the decision-making units (DMUs). Reliability and validity of the questionnaire is examined based on Cronbach's alpha and t-test. The most appropriate DEA model is determined based on average efficiency and normality test. It is shown that the proposed integrated design provides higher efficiency than the conventional RE design. Results of sensitivity and perturbation analysis indicate that self-organization, fault tolerance, and reporting culture respectively compose about 50 percent of total weight.

Keywords: banking system, Data Envelopment Analysis (DEA), Integrated Resilience Engineering (IRE), performance evaluation, perturbation analysis

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Authors: Atheer Al-Nuaimi, Harry Evdorides

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Every day many people die or get disabled or injured on roads around the world, which necessitates more specific treatments for transportation safety issues. International road assessment program (iRAP) model is one of the comprehensive road safety models which accounting for many factors that affect road safety in a cost-effective way in low and middle income countries. In iRAP model road safety has been divided into five star ratings from 1 star (the lowest level) to 5 star (the highest level). These star ratings are based on star rating score which is calculated by iRAP methodology depending on road attributes, traffic volumes and operating speeds. The outcome of iRAP methodology are the treatments that can be used to improve road safety and reduce fatalities and serious injuries (FSI) numbers. These countermeasures can be used separately as a single countermeasure or mix as multiple countermeasures for a location. There is general agreement that the adequacy of a countermeasure is liable to consistent losses when it is utilized as a part of mix with different countermeasures. That is, accident diminishment appraisals of individual countermeasures cannot be easily added together. The iRAP model philosophy makes utilization of a multiple countermeasure adjustment factors to predict diminishments in the effectiveness of road safety countermeasures when more than one countermeasure is chosen. A multiple countermeasure correction factors are figured for every 100-meter segment and for every accident type. However, restrictions of this methodology incorporate a presumable over-estimation in the predicted crash reduction. This study aims to adjust this correction factor by developing new models to calculate the effect of using multiple countermeasures on the number of fatalities for a location or an entire road. Regression models have been used to establish relationships between crash frequencies and the factors that affect their rates. Multiple linear regression, negative binomial regression, and Poisson regression techniques were used to develop models that can address the effectiveness of using multiple countermeasures. Analyses are conducted using The R Project for Statistical Computing showed that a model developed by negative binomial regression technique could give more reliable results of the predicted number of fatalities after the implementation of road safety multiple countermeasures than the results from iRAP model. The results also showed that the negative binomial regression approach gives more precise results in comparison with multiple linear and Poisson regression techniques because of the overdispersion and standard error issues.

Keywords: international road assessment program, negative binomial, road multiple countermeasures, road safety

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Authors: Mehrnaz Alibeikloo, Hadi Khabbaz, Behzad Fatahi

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Probabilistic analysis has become one of the most popular methods to quantify and manage geotechnical risks due to the spatial variability of soil input parameters. The correlation length is one of the key factors of quantifying spatial variability of soil parameters which is defined as a distance within which the random variables are correlated strongly. This paper aims to assess the impact of correlation length on the long-term settlement of soft soils improved with preloading. The concept of 'worst-case' spatial correlation length was evaluated by determining the probability of failure of a real case study of Vasby test fill. For this purpose, a finite difference code was developed based on axisymmetric consolidation equations incorporating the non-linear elastic visco-plastic model and the Karhunen-Loeve expansion method. The results show that correlation length has a significant impact on the post-construction settlement of soft soils in a way that by increasing correlation length, probability of failure increases and the approach to asymptote.

Keywords: Karhunen-Loeve expansion, probability of failure, soft soil settlement, 'worst case' spatial correlation length

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Authors: Neslihan Şahin Çelik, Ali Eraslan

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In recent years, mathematics educators have frequently stressed the necessity of instructing students about models and modeling approaches that encompass cognitive and metacognitive thought processes, starting from the first years of school and continuing on through the years of higher education. The purpose of this study is to examine the thought processes of 4th-grade primary school students in their modeling activities and to explore the difficulties encountered in these processes, if any. The study, of qualitative design, was conducted in the 2015-2016 academic year at a public state-school located in a central city in the Black Sea Region of Turkey. A preliminary study was first implemented with designated 4th grade students, after which the criterion sampling method was used to select three students that would be recruited into the focus group. The focus group that was thus formed was asked to work on the model eliciting activity of the Paper Airplane Problem and the entire process was recorded on video. The Paper Airplane Problem required the students to determine the winner with respect to: (a) the plane that stays in the air for the longest time; (b) the plane that travels the greatest distance in a straight-line path; and (c) the overall winner for the contest. A written transcript was made of the video recording, after which the recording and the students' worksheets were analyzed using the Blum and Ferri modeling cycle. The results of the study revealed that the students tested the hypotheses related to daily life that they had set up, generated ideas of their own, verified their models by making connections with real life, and tried to make their models generalizable. On the other hand, the students had some difficulties in terms of their interpretation of the table of data and their ways of operating on the data during the modeling processes.

Keywords: primary school students, model eliciting activity, mathematical modeling, modeling process, paper airplane problem

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Authors: Jing Ren, Kun Wu

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Over the last decade or so, China's urbanization has shown a rapid development trend. At the same time, it has also had a great negative impact on the habitat quality. Therefore, it is of great significance to study the impact of land use change on the level of habitat quality in mountain cities for sustainable urban development. This paper analyzed the spatial and temporal land use changes in Chongqing from 2010 to 2020 using ArcGIS 10.6, as well as the evolutionary trend of habitat quality during this period based on the InVEST 3.13.0, to obtain the impact of land use changes on habitat quality. The results showed that the habitat quality in the western part of Chongqing decreased significantly between 2010 and 2020, while the northeastern and southeastern parts remained stable. The main reason for this is the continuous expansion of urban construction land in the western area, which leads to serious habitat fragmentation and the continuous decline of habitat quality. while, in the northeast and southeast areas, due to the greater emphasis on ecological priority and urban-rural coordination in the development process, land use change is characterized by a benign transfer, which maintains the urbanization process while maintaining the coordinated development of habitat quality. This study can provide theoretical support for the sustainable development of mountain cities.

Keywords: mountain cities, ecological environment, habitat quality, sustainable development

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Authors: Mohammad Abu-Shaira, Weishi Shi

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Adaptive learning, a commonly employed solution to drift, involves updating predictive models online during their operation to react to concept drifts, thereby serving as a critical component and natural extension for online learning systems that learn incrementally from each example. This paper introduces LSTM-SCCM “Long Short-Term Memory Stream Cruise Control Method”, a drift adaptation-as-a-service framework for online learning. LSTM-SCCM automates drift adaptation through prompt detection, drift magnitude quantification, dynamic hyperparameter tuning, performing shortterm optimization and model recalibration for immediate adjustments, and, when necessary, conducting long-term model recalibration to ensure deeper enhancements in model performance. LSTM-SCCM is incorporated into a suite of cutting-edge online regression models, assessing their performance across various types of concept drift using diverse datasets with varying characteristics. The findings demonstrate that LSTM-SCCM represents a notable advancement in both model performance and efficacy in handling concept drift occurrences. LSTM-SCCM stands out as the sole framework adept at effectively tackling concept drifts within regression scenarios. Its proactive approach to drift adaptation distinguishes it from conventional reactive methods, which typically rely on retraining after significant degradation to model performance caused by drifts. Additionally, LSTM-SCCM employs an in-memory approach combined with the Self-Adjusting Memory (SAM) architecture to enhance real-time processing and adaptability. The framework incorporates variable thresholding techniques and does not assume any particular data distribution, making it an ideal choice for managing high-dimensional datasets and efficiently handling large-scale data. Our experiments, which include abrupt, incremental, and gradual drifts across both low- and high-dimensional datasets with varying noise levels, and applied to four state-of-the-art online regression models, demonstrate that LSTM-SCCM is versatile and effective, rendering it a valuable solution for online regression models to address concept drift.

Keywords: automated drift detection and adaptation, concept drift, hyperparameters optimization, online and adaptive learning, regression

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Authors: Shu-Hui Chuang, Shao-Chun Chiu, Shu-Hsin Chuang

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While the marketing management literature is regarding the direct benefits of market orientation (MO) on firm value, the impact of such MO-based value co-creation remains largely an unexplored area of research. Thus, the primary objective of this study is to provide some new perspectives in examining how MO can enhance value co-creation for customers and sellers. In particular, drawing from the relational view of the firm and IT literature, we propose that the chain of MO-based co-creation of value and how adopt e-marketing systems between partners can facilitate this chain. Using data on use of the e-marketing system, we empirically validate that the sellers’ integrated MO is critical in increasing the e-marketing adoption, which in turn helps to creation co-creation value for both parties.

Keywords: market orientation, value co-creation, e-marketing system, relational view of the firm

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Authors: Mushty Srividya

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Humans that inhabit a designed space consciously or unconsciously accept the spaces which have an impact on how they perceive, feel and act accordingly. Spaces that are more interactive and communicative with the human senses become more interesting. Interaction in architecture is the art of building relationships between the user and the spaces. Often spaces are form-based, function-based or aesthetically pleasing spaces but they are not interactive with the user which actually has a greater impact on how the user perceives the designed space and appreciate it. It is very necessary for a designer to understand and appreciate the human character and design accordingly, wherein the user gets the flexibility to explore and experience it for themselves rather than the designed space dictating the user how to perceive or feel in that space. In this interaction between designed spaces and the user, a designer needs to understand the spatial potential and user’s needs because the design language varies with varied situations in accordance with these factors. Designers often have the tendency to construct spaces with their perspectives, observations, and sense the space in their range of different angles rather than the users. It is, therefore, necessary to understand the potential of the space by understanding different factors and improve the quality of space with the help of creating better interactive spaces. For an interaction to occur between the user and space, there is a need for some medium. In this paper, light, color, and sound will be used as the mediums to understand and create interactions between the user and space, considering these to be the primary sources which would not require any physical touch in the space and would help in triggering the human senses. This paper involves in studying and understanding the impact of light, color and sound on different typologies of spaces on the user through different findings, articles, case studies and surveys and try to get links between these three mediums to create an interaction. This paper also deals with understanding in which medium takes an upper hand in a varied typology of spaces and identify different techniques which would create interactions between the user and space with the help of light, color, and sound.

Keywords: color, communicative spaces, human factors, interactive spaces, light, sound

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Authors: Vaishali Joshi

Abstract:

Purpose: A literature gap exists on the concept of sensory marketing elements, such as tactile elements, auditory elements, visual elements, and olfactory elements, studied together in the context of retailing. An investigation is required to study the impact of these sensory cues together on consumer behaviour. So, this study will undertake the impact of sensory marketing in fashion accessories stores on female shoppers’ purchasing activities. The present research study highlights the role of sensory cues, such as tactile cues, visual cues, auditory cues, and olfactory cues, on the shopper’s emotional states and their purchase intention. Design/methodology/approach: The emotional states and the purchase intention of the female shoppers influenced by the visual, tactile, olfactory, and auditory cues present in the fashion accessories stores were measured. The mall intercept technique was used for the data collection. Data analysis was done through Structural Equation Modelling. Research limitations/implications: The restricted geographical range and limited sample size of the study had a substantial poor influence on the wide usage of the study’s outcome. Also, here, the sample was female respondents only.

Keywords: sensory marketing, visual cues, olfactory cues, tactile cues, auditory cues

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Authors: Radul Shishkov, Orlin Davchev

Abstract:

The digital era has revolutionized architectural practices, with building information modeling (BIM) emerging as a pivotal tool for architects, engineers, and construction professionals. However, the transition from traditional methods to BIM-centric approaches poses significant challenges, particularly in the context of existing structures. This research introduces a technical approach to bridge this gap through the development of algorithms that facilitate the automated transformation of 3D point cloud data into detailed BIM models. The core of this research lies in the application of algorithmic modeling and computational design methods to interpret and reconstruct point cloud data -a collection of data points in space, typically produced by 3D scanners- into comprehensive BIM models. This process involves complex stages of data cleaning, feature extraction, and geometric reconstruction, which are traditionally time-consuming and prone to human error. By automating these stages, our approach significantly enhances the efficiency and accuracy of creating BIM models for existing buildings. The proposed algorithms are designed to identify key architectural elements within point clouds, such as walls, windows, doors, and other structural components, and to translate these elements into their corresponding BIM representations. This includes the integration of parametric modeling techniques to ensure that the generated BIM models are not only geometrically accurate but also embedded with essential architectural and structural information. Our methodology has been tested on several real-world case studies, demonstrating its capability to handle diverse architectural styles and complexities. The results showcase a substantial reduction in time and resources required for BIM model generation while maintaining high levels of accuracy and detail. This research contributes significantly to the field of architectural technology by providing a scalable and efficient solution for the integration of existing structures into the BIM framework. It paves the way for more seamless and integrated workflows in renovation and heritage conservation projects, where the accuracy of existing conditions plays a critical role. The implications of this study extend beyond architectural practices, offering potential benefits in urban planning, facility management, and historic preservation.

Keywords: BIM, 3D point cloud, algorithmic modeling, computational design, architectural reconstruction

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Authors: Mahmoud Ahmed Farrag, Ali Zain Elabdeen Heikal, Mohamed Shawky Ahmed, Ahmed Osama Amer

Abstract:

Crowd-sourced data refers to data that is collected and shared by a large number of individuals or organizations, often through the use of digital technologies such as mobile devices and social media. The shortage in crash data collection in developing countries makes it difficult to fully understand and address road safety issues in these regions. In developing countries, crowd-sourced data can be a valuable tool for improving road safety, particularly in urban areas where the majority of road crashes occur. This study is -to our best knowledge- the first to develop safety performance functions using crowd-sourced data by adopting a negative binomial structure model and the Full Bayes model to investigate traffic safety for urban road networks and provide insights into the impact of roadway characteristics. Furthermore, as a part of the safety management process, network screening has been undergone through applying two different methods to rank the most hazardous road segments: PCR method (adopted in the Highway Capacity Manual HCM) as well as a graphical method using GIS tools to compare and validate. Lastly, recommendations were suggested for policymakers to ensure safer roads.

Keywords: crowdsourced data, road crashes, safety performance functions, Full Bayes models, network screening

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Authors: Reza Zakerinejad

Abstract:

Gully erosion is a serious problem that threading the sustainability of agricultural area and rangeland and water in a large part of Iran. This type of water erosion is the main source of sedimentation in many catchment areas in the north of Iran. Since in many national assessment approaches just qualitative models were applied the aim of this study is to predict the spatial distribution of gully erosion processes by means of detail terrain analysis and GIS -based logistic regression in the loess deposition in a case study in the Golestan Province. This study the DEM with 25 meter result ion from ASTER data has been used. The Landsat ETM data have been used to mapping of land use. The TreeNet model as a stochastic modeling was applied to prediction the susceptible area for gully erosion. In this model ROC we have set 20 % of data as learning and 20 % as learning data. Therefore, applying the GIS and satellite image analysis techniques has been used to derive the input information for these stochastic models. The result of this study showed a high accurate map of potential for gully erosion.

Keywords: TreeNet model, terrain analysis, Golestan Province, Iran

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Authors: Nikolaos Konstantopoulos, Aristeidis Samitas, Vasileiou Evangelos

Abstract:

The purpose of this study is to examine if the financial trends influence not only the stock markets’ returns, but also their anomalies. We choose to study the day of the week effect (DOW) for the Greek stock market during the Euro period (2002-12), because during the specific period there are not significant structural changes and there are long term financial trends. Moreover, in order to avoid possible methodological counterarguments that usually arise in the literature, we apply several linear (OLS) and nonlinear (GARCH family) models to our sample until we reach to the conclusion that the TGARCH model fits better to our sample than any other. Our results suggest that in the Greek stock market there is a long term predisposition for positive/negative returns depending on the weekday. However, the statistical significance is influenced from the financial trend. This influence may be the reason why there are conflict findings in the literature through the time. Finally, we combine the DOW’s empirical findings from 1985-2012 and we may assume that in the Greek case there is a tendency for long lived turn of the week effect.

Keywords: day of the week effect, GARCH family models, Athens stock exchange, economic growth, crisis

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Authors: Venkata Venugopal Rao Gudlur

Abstract:

The Proposed Policies referred to as “SOP”, on the Internet of Things (IoT) based Forensic Investigation into Process Management is the latest revolution to save time and quick solution for investigators. The forensic investigation process has been developed over many years from time to time it has been given the required information with no policies in investigation processes. This research reveals that the current IoT based forensic investigation into Process Management based is more connected to devices which is the latest revolution and policies. All future development in real-time information on gathering monitoring is evolved with smart sensor-based technologies connected directly to IoT. This paper present conceptual framework on process management. The smart devices are leading the way in terms of automated forensic models and frameworks established by different scholars. These models and frameworks were mostly focused on offering a roadmap for performing forensic operations with no policies in place. These initiatives would bring a tremendous benefit to process management and IoT forensic investigators proposing policies. The forensic investigation process may enhance more security and reduced data losses and vulnerabilities.

Keywords: Internet of Things, Process Management, Forensic Investigation, M2M Framework

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