Search results for: loss model

Authors: Aqeel Zeid, Hasna Anees, Mohamed Adheeb, Mohamed Rifan, Kalpani Manathunga

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To achieve constructive alignment in a higher education program, a clear set of learning outcomes must be defined. Traditional learning outcome definition techniques such as Bloom’s taxonomy are not written to be utilized by the student. This might be disadvantageous for students in student-centric learning settings where the students are expected to formulate their own learning strategies. To solve the problem, we propose the learning outcome relation and aggregation (LORA) model. To achieve alignment, we developed learning outcome, assessment, and resource authoring tools which help teachers to tag learning outcomes during creation. A pilot study was conducted with an expert panel consisting of experienced professionals in the education domain to evaluate whether the LORA model and tools present an improvement over the traditional methods. The panel unanimously agreed that the model and tools are beneficial and effective. Moreover, it helped them model learning outcomes in a more student centric and descriptive way.

Keywords: learning design, constructive alignment, Bloom’s taxonomy, learning outcome modelling

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Authors: M. Vlahovic

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This paper presents a model of public finances, which combines three concepts: participatory budgeting, crowdfunding and blockchain technology. Participatory budgeting is defined as a process in which community members decide how to spend a part of community’s budget. Crowdfunding is a practice of funding a project by collecting small monetary contributions from a large number of people via an Internet platform. Blockchain technology is a distributed ledger that enables efficient and reliable transactions that are secure and transparent. In this hypothetical model, the government or authorities on local/regional level would set up a platform where they would propose public projects to citizens. Citizens would browse through projects and support or vote for those which they consider justified and necessary. In return, they would be entitled to a tax relief in the amount of their monetary contribution. Since the blockchain technology enables tracking of transactions, it can be used to mitigate corruption, money laundering and lack of transparency in public finances. Models of its application have already been created for e-voting, health records or land registries. By presenting a model of application of blockchain technology in public finances, this paper takes into consideration the potential of blockchain technology to disrupt governments and make processes more democratic, secure, transparent and efficient. The framework for this paper consists of multiple streams of research, including key concepts of direct democracy, public finance (especially the voluntary theory of public finance), information and communication technology, especially blockchain technology and crowdfunding. The framework defines rules of the game, basic conditions for the implementation of the model, benefits, potential problems and development perspectives. As an oversimplified map of a new form of public finances, the proposed model identifies primary factors, that influence the possibility of implementation of the model, and that could be tracked, measured and controlled in case of experimentation with the model.

Keywords: blockchain technology, distributed ledger, participatory budgeting, crowdfunding, direct democracy, internet platform, e-government, public finance

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Authors: Sunghoon Park, Hank Kim, Jinwon An, Sungzoon Cho

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Internet of Things allows one to collect data from facilities which are then used to monitor them and even predict malfunctions in advance. Conventional quality control methods focus on setting a normal range on a sensor value defined between a lower control limit and an upper control limit, and declaring as an anomaly anything falling outside it. However, interactions among sensor values are ignored, thus leading to suboptimal performance. We propose a multivariate approach which takes into account many sensor values at the same time. In particular Gaussian Mixture Model is used which is trained to maximize likelihood value using Expectation-Maximization algorithm. The number of Gaussian component distributions is determined by Bayesian Information Criterion. The negative Log likelihood value is used as an anomaly score. The actual usage scenario goes like a following. For each instance of sensor values from a facility, an anomaly score is computed. If it is larger than a threshold, an alarm will go off and a human expert intervenes and checks the system. A real world data from Building energy system was used to test the model.

Keywords: facility anomaly detection, gaussian mixture model, anomaly score, expectation maximization algorithm

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Authors: Shahram Naghizadeh Raeisi, Ali Alghooneh

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The loss of curd cohesiveness and syneresis are two common problems in the ultrafiltered cheese industry. In this study, by using membrane technology and protein modification, a modified cheese was developed and its properties were compared with a control sample. In order to decrease the lactose content and adjust the protein, acidity, dry matter and milk minerals, a combination of ultrafiltration, nanofiltration and reverse osmosis technologies was employed. For protein modification, a two-stage chemical and enzymatic reaction was employed before and after ultrafiltration. The physicochemical and microstructural properties of the modified ultrafiltered cheese were compared with the control one. Results showed that the modified protein enhanced the functional properties of the final cheese significantly (pvalue< 0.05), even if the protein content was 50% lower than the control one. The modified cheese showed 21 ± 0.70, 18 ± 1.10 & 25±1.65% higher hardness, cohesiveness and water-holding capacity values, respectively, than the control sample. This behavior could be explained by the developed microstructure of the gel network. Furthermore, chemical-enzymatic modification of milk protein induced a significant change in the network parameter of the final cheese. In this way, the indices of network linkage strength, network linkage density, and time scale of junctions were 10.34 ± 0.52, 68.50 ± 2.10 & 82.21 ± 3.85% higher than the control sample, whereas the distance between adjacent linkages was 16.77 ± 1.10% lower than the control sample. These results were supported by the results of the textural analysis. A non-linear viscoelastic study showed a triangle waveform stress of the modified protein contained cheese, while the control sample showed rectangular waveform stress, which suggested a better sliceability of the modified cheese. Moreover, to study the shelf life of the products, the acidity, as well as molds and yeast population, were determined in 120 days. It’s worth mentioning that the lactose content of modified cheese was adjusted at 2.5% before fermentation, while the lactose of the control one was at 4.5%. The control sample showed 8 weeks shelf life, while the shelf life of the modified cheese was 18 weeks in the refrigerator. During 18 weeks, the acidity of modified and control samples increased from 82 ± 1.50 to 94 ± 2.20 °D and 88 ± 1.64 to 194 ± 5.10 °D, respectively. The mold and yeast populations, with time, followed the semicircular shape model (R2 = 0.92, R2adj = 0.89, RMSE = 1.25). Furthermore, the mold and yeast counts and their growth rate in the modified cheese were lower than those for control one; Aforementioned result could be explained by the shortage of the source of energy for the microorganism in the modified cheese. The lactose content of the modified sample was less than 0.2 ± 0.05% at the end of fermentation, while this was 3.7 ± 0.68% in the control sample.

Keywords: non-linear viscoelastic, protein modification, semicircular shape model, ultrafiltered cheese

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Authors: Waleed A. Basuliman, Khalid S. AlSaleh, Mohamed Z. Ramadan

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Applying the anthropometric dimensions is considered one of the important factors when designing any human-machine system. In this study, the estimation of anthropometric dimensions has been improved by developing artificial neural network that aims to predict the anthropometric measurements of the male in Saudi Arabia. A total of 1427 Saudi males from age 6 to 60 participated in measuring twenty anthropometric dimensions. These anthropometric measurements are important for designing the majority of work and life applications in Saudi Arabia. The data were collected during 8 months from different locations in Riyadh City. Five of these dimensions were used as predictors variables (inputs) of the model, and the remaining fifteen dimensions were set to be the measured variables (outcomes). The hidden layers have been varied during the structuring stage, and the best performance was achieved with the network structure 6-25-15. The results showed that the developed Neural Network model was significantly able to predict the body dimensions for the population of Saudi Arabia. The network mean absolute percentage error (MAPE) and the root mean squared error (RMSE) were found 0.0348 and 3.225 respectively. The accuracy of the developed neural network was evaluated by compare the predicted outcomes with a multiple regression model. The ANN model performed better and resulted excellent correlation coefficients between the predicted and actual dimensions.

Keywords: artificial neural network, anthropometric measurements, backpropagation, real anthropometric database

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Authors: P.-W. Tsai, C.-Y. Chen, C.-W. Chen

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In this paper, the stability analysis of a GA-Based adaptive fuzzy sliding model controller for a nonlinear system is discussed. First, a nonlinear plant is well-approximated and described with a reference model and a fuzzy model, both involving FLC rules. Then, FLC rules and the consequent parameter are decided on via an Evolved Bat Algorithm (EBA). After this, we guarantee a new tracking performance inequality for the control system. The tracking problem is characterized to solve an eigenvalue problem (EVP). Next, an adaptive fuzzy sliding model controller (AFSMC) is proposed to stabilize the system so as to achieve good control performance. Lyapunov’s direct method can be used to ensure the stability of the nonlinear system. It is shown that the stability analysis can reduce nonlinear systems into a linear matrix inequality (LMI) problem. Finally, a numerical simulation is provided to demonstrate the control methodology.

Keywords: adaptive fuzzy sliding mode control, Lyapunov direct method, swarm intelligence, evolved bat algorithm

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Authors: Maha Almumaiz, Harry Evdorides

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Change in land value typically occurs when a new interurban road construction causes an increase in accessibility; this change in the adjacent lands values differs according to land characteristics such as geographic location, land use type, land area and sale time (appraisal time). A multiple regression model is obtained to predict the percent change in land value (CLV) based on four independent variables namely land distance from the constructed road, area of land, nature of land use and time from the works completion of the road. The random values of percent change in land value were generated using Microsoft Excel with a range of up to 35%. The trend of change in land value with the four independent variables was determined from the literature references. The statistical analysis and model building process has been made by using the IBM SPSS V23 software. The Regression model suggests, for lands that are located within 3 miles as the straight distance from the road, the percent CLV is between (0-35%) which is depending on many factors including distance from the constructed road, land use, land area and time from works completion of the new road.

Keywords: interurban road, land use types, new road construction, percent CLV, regression model

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Authors: Jiahui Song

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In order to predict or explain a complicated biological process, it is important first to construct mathematical models that can be used to yield analytical solutions. Through numerical simulation, mathematical model results can be used to test scenarios that might not be easily attained in a laboratory experiment, or to predict parameters or phenomena. High-intensity, nanosecond pulse electroporation has been a recent development in bioelectrics. The dynamic pore model can be achieved by including a dynamic aspect and a dependence on the pore population density into pore formation energy equation to analyze and predict such electroporation effects. For greater accuracy, with inclusion of atomistic details, molecular dynamics (MD) simulations were also carried out during this study. Besides inducing pores in cells, external voltages could also be used in principle to modulate action potential generation in nerves. This could have an application in electrically controlled ‘pain management’. Also a simple model-based rate equation treatment of the various cellular bio-chemical processes has been used to predict the pulse number dependent cell survival trends.

Keywords: model, high-intensity, nanosecond, bioelectrics

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Authors: Hemanth K. Balaga, Prakash Nanthagopalan

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Every year a huge amount of paper gets discarded of which only a minute fraction is being recycled and the rest gets dumped as landfills. Paper fibres can be recycled only a limited number of times before they become too short or weak to make high quality recycled paper. This eventually adds to the already big figures of waste paper that is being generated and not recycled. It would be advantageous if this prodigious amount of waste can be utilized as a low-cost sustainable construction material and make it as a value added product. The generic term for the material under investigation is paper-concrete. This is a fibrous mix made of Portland cement, water and pulped paper and/or other aggregates. The advantages of this material include light weight, good heat and sound insulation capability and resistance to flame. The disadvantages include low strength compared to conventional concrete and its hydrophilic nature. The properties vary with the variation of cement and paper content in the mix. In the present study, Portland Pozzolona Cement and news print paper were used for the preparation of paper concrete cubes. Initially, investigations were performed to determine the minimum soaking period required for the softening of the paper fibres. Further different methodologies were explored for proper blending of the pulp with cement paste. The properties of paper concrete vary with the variation of cement to paper to water ratio. The study mainly addresses the parameters of strength and weight loss of the concrete cubes with age and the time that is required for the dry paper fibres to become soft enough in water to bond with the cement. The variation of compressive strength with cement content, water content, and time was studied. The water loss of the cubes with time and the minimum time required for the softening of paper fibres were investigated .Results indicate that the material loses 25-50 percent of the initial weight at the end of 28 days, and a maximum 28 day compressive strength (cubes) of 5.4 Mpa was obtained.

Keywords: soaking time, difference water, minimum water content, maximum water content

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Authors: Hande Yavuz, Grégory Girard, Jinbo Bai

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Manufacturing of hybrid composites requires particular attention to overcome various critical weaknesses that are originated from poor interfacial compatibility. A large number of parameters have to be considered to optimize the interfacial bond strength either to avoid flaw sensitivity or delamination that occurs in composites. For this reason, surface characterization of reinforcement phase is needed in order to provide necessary data to drive an assessment of fiber-matrix interfacial compatibility prior to fabrication of composite structures. Compared to conventional plasma polymerization processes such as radiofrequency and microwave, dielectric barrier discharge assisted plasma polymerization is a promising process that can be utilized to modify the surface properties of carbon fibers in a continuous manner. Finding the most suitable conditions (e.g., plasma power, plasma duration, precursor proportion) for plasma polymerization of pyrrole in post-discharge region either in the presence or in the absence of p-toluene sulfonic acid monohydrate as well as the characterization of plasma polypyrrole coated fibers are the important aspects of this work. Throughout the current investigation, atomic force microscopy (AFM) and thermogravimetric analysis (TGA) are used to characterize plasma treated hybrid fibers (CNT-grafted Toray T700-12K carbon fibers, referred as T700/CNT). TGA results show the trend in the change of decomposition process of deposited polymer on fibers as a function of temperature up to 900 °C. Within the same period of time, all plasma pyrrole treated samples began to lose weight with relatively fast rate up to 400 °C which suggests the loss of polymeric structures. The weight loss between 300 and 600 °C is attributed to evolution of CO2 due to decomposition of functional groups (e.g. carboxyl compounds). With keeping in mind the surface chemical structure, the higher the amount of carbonyl, alcohols, and ether compounds, the lower the stability of deposited polymer. Thus, the highest weight loss is observed in 1400 W 45 s pyrrole+pTSA.H2O plasma treated sample probably because of the presence of less stable polymer than that of other plasma treated samples. Comparison of the AFM images for untreated and plasma treated samples shows that the surface topography may change on a microscopic scale. The AFM image of 1800 W 45 s treated T700/CNT fiber possesses the most significant increase in roughening compared to untreated T700/CNT fiber. Namely, the fiber surface became rougher with ~3.6 fold that of the T700/CNT fiber. The increase observed in surface roughness compared to untreated T700/CNT fiber may provide more contact points between fiber and matrix due to increased surface area. It is believed to be beneficial for their application as reinforcement in composites.

Keywords: hybrid fibers, surface characterization, surface roughness, thermal stability

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Authors: Othmane Zarhali, Cécilia Aubrun, Emmanuel Bacry, Jean-Philippe Bouchaud, Jean-François Muzy

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The Nested factor model was introduced by Bouchaud and al., where the asset return fluctuations are explained by common factors representing the market economic sectors and residuals (noises) sharing with the factors a common dominant volatility mode in addition to the idiosyncratic mode proper to each residual. This construction infers that the factors-residuals log volatilities are correlated. Here, we consider the case of a single factor where the only dominant common mode is a S-fbm process (introduced by Peng, Bacry and Muzy) with Hurst exponent H around 0.11 and the residuals having in addition to the previous common mode idiosyncratic components with Hurst exponents H around 0. The reason for considering this configuration is twofold: preserve the Nested factor model’s characteristics introduced by Bouchaud and al. and propose a framework through which the stylized fact reported by Peng and al. is reproduced, where it has been observed that the Hurst exponents of stock indices are large as compared to those of individual stocks. In this work, we show that the Log S-fbm Nested factor model’s construction leads to a Hurst exponent of single stocks being the ones of the idiosyncratic volatility modes and the Hurst exponent of the index being the one of the common volatility modes. Furthermore, we propose a statistical procedure to estimate the Hurst factor exponent from the stock returns dynamics together with theoretical guarantees, with good results in the limit where the number of stocks N goes to infinity. Last but not least, we show that the factor can be seen as an index constructed from the single stocks weighted by specific coefficients.

Keywords: hurst exponent, log S-fbm model, nested factor model, small intermittency approximation

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Authors: Faisal Asad Aburub

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Many organizations are investing in web applications and technologies in order to be competitive, some of them could not achieve its goals. The quality of web-based applications could play an important role for organizations to be competitive. So the aim of this study is to investigate the impact of quality of web-based applications to achieve a competitive advantage. A new model has been developed. An empirical investigation was performed on a banking sector in Jordan to test the new model. The results show that impact of web-based applications on competitive advantage is significant. Finally, further work is planned to validate and evaluate the proposed model using several domains.

Keywords: competitive advantage, web-based applications, empirical investigation, commercial banks in Jordan

Procedia PDF Downloads 346

Authors: Oloruntegbe Kunle Oke, Alake Ese Monica, Odutuyi Olubu Musili

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This research explores the differing effectiveness of cascade and cluster models in professional development programs for educators in Ondo State, Nigeria. The cascade model emphasizes a top-down approach, where training is cascaded from expert trainers to lower levels of teachers. In contrast, the cluster model, a bottom-up approach, fosters collaborative learning among teachers within specific clusters. Through a review of the literature and empirical studies of the implementations of the former in two academic sessions followed by the cluster model in another two, the study examined their effectiveness on teacher development, productivity and students’ achievements. The study also drew a comparative analysis of the strengths and weaknesses associated with each model, considering factors such as scalability, cost-effectiveness, adaptability in various contexts, and sustainability. 2500 teachers from Ondo State Primary Schools participated in the cascade with intensive training in five zones for a week each in two academic sessions. On the other hand, 1,980 and 1,663 teachers in 52 and 34 clusters, respectively, were in the first and the following session. The programs were designed for one week of rigorous training of teachers by facilitators in the former while the latter was made up of four components: sit-in-observation, need-based assessment workshop, pre-cluster and the actual cluster meetings in addition to sensitization, and took place one day a week for ten weeks. Validated Cluster Impact Survey Instruments, CISI and Teacher’s Assessment Questionnaire (TAQ) were administered to ascertain the effectiveness of the models during and after implementation. The findings from the literature detailed specific effectiveness, strengths and limitations of each approach, especially the potential for inconsistencies and resistance to change. Findings from the data collected revealed the superiority of the cluster model. Response to TAQ equally showed content knowledge and skill update in both but were more sustained in the cluster model. Overall, the study contributes to the ongoing discourse on effective strategies for improving teacher training and enhancing student outcomes, offering practical recommendations for the development and implementation of future professional development projects.

Keywords: cascade model, cluster model, teachers’ development, productivity, students’ achievement

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Authors: Afrah S. M. Al-Mahfadi

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Climate change is a global issue that has significant impacts on water resources, resulting in environmental, economic, and political consequences. Groundwater reserves, particularly in coastal areas, are facing depletion, leading to serious problems in regions such as Yemen. This study focuses on the western coastal region of Yemen, which already faces risks such as water crises, food insecurity, and widespread poverty. Climate change exacerbates these risks by causing high temperatures, sea level rise, inadequate sea level rise, and inadequate environmental policies. Research Aim: The aim of this research is to provide a comprehensive overview of the impact of climate change on the western coastal region of Yemen. Specifically, the study aims to analyze the relationship between climate change and the loss of fresh groundwater resources in this area. Methodology: The research utilizes a combination of a literature review and three case studies conducted through site visits. Arch-GIS mapping is employed to analyze and visualize the relationship between climate change and the depletion of fresh groundwater resources. Additionally, data on precipitation from 1981 to 2020 and scenarios of projected sea level rise (SLR) are considered. Findings: The study reveals several future issues resulting from climate change. It is projected that the annual temperature will increase while the rainfall rate will decrease. Furthermore, the sea level is expected to rise by approximately 0.30 to 0.72 meters by 2100. These factors contribute to the loss of wetlands, the retreat of shorelines and estuaries, and the intrusion of seawater into the coastal aquifer, rendering drinking water from wells increasingly saline. Data Collection and Analysis Procedures: Data for this research are collected through a literature review, including studies on climate change impacts in coastal areas and the hydrogeology of the study region. Furthermore, three case studies are conducted through site visits. Arch-GIS mapping techniques are utilized to analyze the relationship between climate change and the loss of fresh groundwater resources. Historical precipitation data from 1981 to 2020 and scenarios of projected sea level rise are also analyzed. Questions Addressed: (1) What is the impact of climate change on the western coastal region of Yemen? (2) How does climate change affect the availability of fresh groundwater resources in this area? Conclusion: The study concludes that the western coastal region of Yemen is facing significant challenges due to climate change. The projected increase in temperature, decrease in rainfall, and rise in sea levels have severe implications, such as the loss of wetlands, shorelines, and estuaries. Additionally, the intrusion of seawater into the coastal aquifer further exacerbates the issue of saline drinking water. Urgent measures are needed to address climate change, including improving water management, implementing integrated coastal zone planning, raising awareness among stakeholders, and implementing emergency projects to mitigate the impacts. Recommendations: To mitigate the adverse effects of climate change, several recommendations are provided. These include improving water management practices, developing integrated coastal zone planning strategies, raising awareness among all stakeholders, improving health and education, and implementing emergency projects to combat climate change. These measures aim to enhance adaptive capacity and resilience in the face of future climate change impacts.

Keywords: climate change, groundwater, coastal wetlands, Yemen

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Authors: S. Sadhu, M. Ramgopal, S. Bhattacharyya

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Natural circulation loops (NCLs) are buoyancy driven flow systems without any moving components. NCLs have vast applications in geothermal, solar and nuclear power industry where reliability and safety are of foremost concern. Due to certain favorable thermophysical properties, especially near supercritical regions, carbon dioxide can be considered as an ideal loop fluid in many applications. In the present work, a high temperature NCL that uses supercritical carbon dioxide as loop fluid is analysed. The effects of relevant design and operating variables on loop performance are studied. The system operating under steady state is modelled taking into account the axial conduction through loop fluid and loop wall, and heat transfer with surroundings. The heat source is considered to be a heater with controlled heat flux and heat sink is modelled as an end heat exchanger with water as the external cold fluid. The governing equations for mass, momentum and energy conservation are normalized and are solved numerically using finite volume method. Results are obtained for a loop pressure of 90 bar with the power input varying from 0.5 kW to 6.0 kW. The numerical results are validated against the experimental results reported in the literature in terms of the modified Grashof number (Gr_m) and Reynolds number (Re). Based on the results, buoyancy and friction dominated regions are identified for a given loop. Parametric analysis has been done to show the effect of loop diameter, loop height, ambient temperature and insulation. The results show that for the high temperature loop, heat loss to surroundings affects the loop performance significantly. Hence this conjugate heat transfer between the loop and surroundings has to be considered in the analysis of high temperature NCLs.

Keywords: conjugate heat transfer, heat loss, natural circulation loop, supercritical carbon dioxide

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Authors: Cyrillus Prabandana

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Supply chain optimisation requires multiple factors as consideration or constraints. These factors are including but not limited to demand forecasting, raw material fulfilment, production capacity, inventory level, facilities locations, transportation means, and manpower availability. By knowing all manageable factors involved and assuming the uncertainty with pre-defined percentage factors, an integrated supply chain model could be developed to manage various business scenarios. This paper analyse the utilisation of geographical point of view to develop an integrated supply chain network model to optimise the distribution of finished product appropriately according to forecasted demand and available supply. The supply chain optimisation model shows that small change in one supply chain constraint is possible to largely impact other constraints, and the new information from the model should be able to support the decision making process. The model was focused on three areas, i.e. raw material fulfilment, production capacity and finished products transportation. To validate the model suitability, it was implemented in a project aimed to optimise the concrete supply chain in a mining location. The high level of operations complexity and involvement of multiple stakeholders in the concrete supply chain is believed to be sufficient to give the illustration of the larger scope. The implementation of this geographical supply chain network modeling resulted an optimised concrete supply chain from raw material fulfilment until finished products distribution to each customer, which indicated by lower percentage of missed concrete order fulfilment to customer.

Keywords: decision making, geographical supply chain modeling, supply chain optimisation, supply chain

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Authors: Shu-Yang Zhang, Shun-Qi Zhang, Zhan-Xi Wang, Xian-Sheng Qin

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Thin-walled structures are used more and more widely in modern aircrafts and some other structures in aerospace field nowadays. Accompanied by the wider applications, the vibration of the structures has been a bigger problem. Because of the direct and converse piezoelectric effect, piezoelectric materials combined to host thin-walled structures, named as piezoelectric smart structures, can be an effective way to suppress the vibration. So, an accurate model for piezoelectric thin-walled structures in air flow is necessary and important. In our recent work, an electromechanical coupling nonlinear aerodynamic finite element model of piezoelectric smart thin-walled structures is built based on the Reissner-Mindlin plate theory and first-order piston theory for aerodynamic pressure of supersonic flow. Von Kármán type nonlinearity is considered in the present model. Finally, the model is validated by experimental and numerical results from the literature, which can describe the vibration of the structures in supersonic flow precisely.

Keywords: piezoelectric smart structures, aerodynamic, geometric nonlinearity, finite element analysis

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Authors: Mohit Chauhan, Atul Narayan

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Moisture damage is the continuous deterioration of asphalt concrete mixtures by the loss of adhesive bond between the asphalt binder and aggregates, or loss of cohesive bonds within the asphalt binder in the presence of moisture. Moisture has been known to either cause or exacerbates distresses in asphalt concrete pavements. Since moisture would often retain for a relatively long duration at the bottom of asphalt concrete layer, the movement of traffic loading in this saturated condition would cause excess stresses or strains within the mixture. This would accelerate the degradation of the adhesion and cohesion within the mixture and likely to contribute the development of fatigue cracking in asphalt concrete pavements. In view of this, it is important to investigate the effect of moisture on the fatigue behavior of asphalt concrete mixtures. In this study, changes in fatigue characteristics after moisture conditioning were evaluated by conducting four-point beam fatigue tests on dry and moisture conditioned specimens. For this purpose, mixtures with two different types of binders were prepared and saturated with moisture using 700 mm Hg vacuum. Beam specimens, in this way, were taken to a saturation level of 65-75 percent. After preconditioning specimens in this degree of saturation and 60°C for a period of 24 hours, they were subjected to four point beam fatigue tests in strain-controlled mode with a strain amplitude of 400 microstrain. The results were then compared with the fatigue test results obtained with beam specimens that were not subjected to moisture conditioning. Test results show that the conditioning reduces both fatigue life and initial flexural stiffness of specimen significantly. The moisture conditioning was also found to increase the rate of reduction of flexural stiffness. Moreover, it was observed that the fatigue life ratio (FLR), the ratio of the fatigue life of the moisture conditioned sample to that of the dry sample, is significantly lower than the flexural stiffness ratio (FSR). The study indicates that four-point bending test is an appropriate tool with FLR and FSR as the potential parameters for moisture-sensitivity evaluation.

Keywords: asphalt concrete, fatigue cracking, moisture damage, preconditioning

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Authors: Yoshinori Kitsutaka, Fumiya Ikedo

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In this study, the mechanical model of various anchors embedded in gypsum board subjected cyclic shear loading were investigated. Shear tests for anchors embedded in 200 mm square size gypsum board were conducted to measure the load - load displacement curves. The strength of the gypsum board was changed for three conditions and 12 kinds of anchors were selected which were ordinary used for gypsum board anchoring. The loading conditions were a monotonous loading and a cyclic loading controlled by a servo-controlled hydraulic loading system to achieve accurate measurement. The fracture energy for each of the anchors was estimated by the analysis of consumed energy calculated by the load - load displacement curve. The effect of the strength of gypsum board and the types of anchors on the shear properties of gypsum board anchors was cleared. A numerical model to predict the load-unload curve of shear deformation of gypsum board anchors caused by such as the earthquake load was proposed and the validity on the model was proved.

Keywords: gypsum board, anchor, shear test, cyclic loading, load-unload curve

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Authors: Sadia Arshad

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The new coronavirus disease or COVID-19 still poses an alarming situation around the world. Modeling based on the derivative of fractional order is relatively important to capture real-world problems and to analyze the realistic situation of the proposed model. Weproposed a mathematical model for the investigation of COVID-19 dynamics in a generalized fractional framework. The new model is formulated in the Caputo sense and employs a nonlinear time-varying transmission rate. The existence and uniqueness solutions of the fractional order derivative have been studied using the fixed-point theory. The associated dynamical behaviors are discussed in terms of equilibrium, stability, and basic reproduction number. For the purpose of numerical implementation, an effcient approximation scheme is also employed to solve the fractional COVID-19 model. Numerical simulations are reported for various fractional orders, and simulation results are compared with a real case of COVID-19 pandemic. According to the comparative results with real data, we find the best value of fractional orderand justify the use of the fractional concept in the mathematical modelling, for the new fractional modelsimulates the reality more accurately than the other classical frameworks.

Keywords: fractional calculus, modeling, stability, numerical solution

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Authors: Linda A. O’Higgins, Astrid Wingler, Jorge Oliveira

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The growth of Chlorella vulgaris was characterized as a function of irradiance in a laboratory turbidostat (1 L) and compared to batch growth in sunlit modules (5–25 L) of the commercial Phytobag photobioreactor. The effects of variable sunlight and culture density were deconvoluted by a mathematical model. The analysis showed that algal growth was light-limited due to shading by external construction elements and due to light attenuation within the algal bags. The model was also used to predict maximum biomass productivity. The manipulative experiments and the model predictions were confronted with data from a production season of a 10m2 pilot-scale photobioreactor, Phytobag (10,000 L). The analysis confirmed light limitation in all three photobioreactors. An additional limitation of biomass productivity was caused by the nitrogen starvation that was used to induce lipid accumulation. Reduction of shading and separation of biomass and lipid production are proposed for future optimization.

Keywords: microalgae, batch cultivation, Chlorella vulgaris, Mathematical model, photobioreactor, scale-up

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Authors: Lichung Jen, Yi Chun Liu, Kuan-Wei Lee

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Fruitful data has been accumulated in database nowadays and is commonly used as support for decision-making. In the healthcare industry, hospital, for instance, ordering pharmacy inventory is one of the key decision. With large drug inventory, the current cost increases and its expiration dates might lead to future issue, such as drug disposal and recycle. In contrast, underestimating demand of the pharmacy inventory, particularly standing drugs, affects the medical treatment and possibly hospital reputation. Prescription behaviour of hospital physicians is one of the critical factor influencing this decision, particularly irregular prescription behaviour. If a drug’s usage amount in the month is irregular and less than the regular usage, it may cause the trend of subsequent stockpiling. On the contrary, if a drug has been prescribed often than expected, it may result in insufficient inventory. We proposed a hierarchical Bayesian mixture model with two components to identify physicians’ regular/irregular prescription patterns with probabilities. Heterogeneity of hospital is considered in our proposed hierarchical Bayes model. The result suggested that modeling the prescription patterns of physician is beneficial for estimating the order quantity of medication and pharmacy inventory management of the hospital. Managerial implication and future research are discussed.

Keywords: hierarchical Bayesian model, poission mixture model, medicines prescription behavior, irregular behavior

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Authors: George Zhou, Yunchan Chen, Candace Chien

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Kidney replacement therapy is the current standard of care for end-stage renal diseases. In-center or home hemodialysis remains an integral component of the therapeutic regimen. Arteriovenous fistulas (AVF) make up the vascular circuit through which blood is filtered and returned. Naturally, AVF patency determines whether adequate clearance and filtration can be achieved and directly influences clinical outcomes. Our aim was to build a deep learning model for automated AVF stenosis screening based on the sound of blood flow through the AVF. A total of 311 patients with AVF were enrolled in this study. Blood flow sounds were collected using a digital stethoscope. For each patient, blood flow sounds were collected at 6 different locations along the patient’s AVF. The 6 locations are artery, anastomosis, distal vein, middle vein, proximal vein, and venous arch. A total of 1866 sounds were collected. The blood flow sounds are labeled as “patent” (normal) or “stenotic” (abnormal). The labels are validated from concurrent ultrasound. Our dataset included 1527 “patent” and 339 “stenotic” sounds. We show that blood flow sounds vary significantly along the AVF. For example, the blood flow sound is loudest at the anastomosis site and softest at the cephalic arch. Contextualizing the sound with location metadata significantly improves classification performance. How to encode and incorporate categorical metadata is an active area of research1. Herein, we study ordinal (i.e., integer) encoding schemes. The numerical representation is concatenated to the flattened feature vector. We train a vision transformer (ViT) on spectrogram image representations of the sound and demonstrate that using scalar multiples of our integer encodings improves classification performance. Models are evaluated using a 10-fold cross-validation procedure. The baseline performance of our ViT without any location metadata achieves an AuROC and AuPRC of 0.68 ± 0.05 and 0.28 ± 0.09, respectively. Using the following encodings of Artery:0; Arch: 1; Proximal: 2; Middle: 3; Distal 4: Anastomosis: 5, the ViT achieves an AuROC and AuPRC of 0.69 ± 0.06 and 0.30 ± 0.10, respectively. Using the following encodings of Artery:0; Arch: 10; Proximal: 20; Middle: 30; Distal 40: Anastomosis: 50, the ViT achieves an AuROC and AuPRC of 0.74 ± 0.06 and 0.38 ± 0.10, respectively. Using the following encodings of Artery:0; Arch: 100; Proximal: 200; Middle: 300; Distal 400: Anastomosis: 500, the ViT achieves an AuROC and AuPRC of 0.78 ± 0.06 and 0.43 ± 0.11. respectively. Interestingly, we see that using increasing scalar multiples of our integer encoding scheme (i.e., encoding “venous arch” as 1,10,100) results in progressively improved performance. In theory, the integer values do not matter since we are optimizing the same loss function; the model can learn to increase or decrease the weights associated with location encodings and converge on the same solution. However, in the setting of limited data and computation resources, increasing the importance at initialization either leads to faster convergence or helps the model escape a local minimum.

Keywords: arteriovenous fistula, blood flow sounds, metadata encoding, deep learning

Procedia PDF Downloads 94

Authors: Mariusz Hofman

Abstract:

The paper ‘Theoretical framework for value creation in Project-Oriented Companies’ is designed to determine, how organisations create value and whether this allows them to achieve market success. An assumption has been made that there are two routes to achieving this value. The first one is to create intangible assets (i.e. the resources of human, structural and relational capital), while the other one is to create added value (understood as the surplus of revenue over costs). It has also been assumed that the combination of the achieved added value and unique intangible assets translates to the success of a project-oriented company. The purpose of the paper is to present hypothetical and deductive model which describing the modus operandi of such companies and approach to model operationalisation. All the latent variables included in the model are theoretical constructs with observational indicators (measures). The existence of a latent variable (construct) and also submodels will be confirmed based on a covariance matrix which in turn is based on empirical data, being a set of observational indicators (measures). This will be achieved with a confirmatory factor analysis (CFA). Due to this statistical procedure, it will be verified whether the matrix arising from the adopted theoretical model differs statistically from the empirical matrix of covariance arising from the system of equations. The fit of the model with the empirical data will be evaluated using χ2, RMSEA and CFI (Comparative Fit Index). How well the theoretical model fits the empirical data is assessed through a number of indicators. If the theoretical conjectures are confirmed, an interesting development path can be defined for project-oriented companies. This will let such organisations perform efficiently in the face of the growing competition and pressure on innovation.

Keywords: value creation, project-oriented company, structural equation modelling

Procedia PDF Downloads 302

Authors: Ibnorachid Zakaria, El Bikri Khalid, Benamar Rhali, Farah Abdoun

Abstract:

The aim of the present work is to study the linear free symmetric vibration of three-layer sandwich beam using the energy method. The zigzag model is used to describe the displacement field. The theoretical model is based on the top and bottom layers behave like Euler-Bernoulli beams while the core layer like a Timoshenko beam. Based on Hamilton’s principle, the governing equation of motion sandwich beam is obtained in order to calculate the linear frequency parameters for a clamped-clamped and simple supported-simple-supported beams. The effects of material properties and geometric parameters on the natural frequencies are also investigated.

Keywords: linear vibration, sandwich, shear deformation, Timoshenko zig-zag model

Procedia PDF Downloads 477

Authors: A. Miloud

Abstract:

In this work, the results of numerical simulations of the turbulent flow with 3D heat transfer are presented for the case of two U-shaped channels and rotating rectangular section. The purpose of this investigation was to study the effect of the corrugated walls of the heated portion on the improved cooling, in particular the influence of the wavelength. The calculations were performed for a Reynolds number ranging from 10 000 to 100 000, two values of the number of rotation (Ro = 0.0 to 0.14) and a ratio of the restricted density to 0.13. In these simulations, ANSYS FLUENT code was used to solve the Reynolds equations expressing relations between different fields averaged variables over time. Model performance k-omega SST model and RSM are evaluated through a comparison of the numerical results for each model and the experimental and numerical data available. In this work, detailed average temperature predictions, the scope of the secondary flow and distributions of local Nusselt are presented. It turns out that the corrugated configuration further urges the heat exchange provided to reduce the velocity of the coolant inside the channel.

Keywords: cooling blades, corrugated walls, model k-omega SST and RSM, fluent code, rotation effect

Procedia PDF Downloads 253

Authors: Sherry Ann Ganase, Sandra Sookram

Abstract:

This study investigates the level of awareness to climate change and major factors that influence such awareness in Grande Riviere, Trinidad. Through the development of an Awareness Index and application of a Structural Equation Model to survey data, the findings suggest an Awareness index value of 0.459 in Grande Riviere. These results suggest that households have climate smart attitudes and behaviors but climate knowledge is lacking. This is supported by the structural equation model which shows a negative relationship between awareness and causes of climate change. The study concludes by highlighting the need for immediate action on increasing knowledge.

Keywords: awareness, climate change, climate education, index structural equation model

Procedia PDF Downloads 473

Authors: Kaustubh Chakradeo, Michael Delves, Sofya Titarenko

Abstract:

Malaria is a serious disease which affects hundreds of millions of people around the world, each year. If not treated in time, it can be fatal. Despite recent developments in malaria diagnostics, the microscopy method to detect malaria remains the most common. Unfortunately, the accuracy of microscopic diagnostics is dependent on the skill of the microscopist and limits the throughput of malaria diagnosis. With the development of Artificial Intelligence tools and Deep Learning techniques in particular, it is possible to lower the cost, while achieving an overall higher accuracy. In this paper, we present a VGG-based model and compare it with previously developed models for identifying infected cells. Our model surpasses most previously developed models in a range of the accuracy metrics. The model has an advantage of being constructed from a relatively small number of layers. This reduces the computer resources and computational time. Moreover, we test our model on two types of datasets and argue that the currently developed deep-learning-based methods cannot efficiently distinguish between infected and contaminated cells. A more precise study of suspicious regions is required.

Keywords: convolution neural network, deep learning, malaria, thin blood smears

Procedia PDF Downloads 135

Authors: Chiung-Hui Chen

Abstract:

Diagram and drawing are important ways to communicate and the reproduce of architectural design, Due to the development of information and communication technology, the professional thinking of architecture and interior design are also change rapidly. In development process of design, diagram always play very important role. This study is based on diagram theories, observe and record interaction between man and objects, objects and space, and space and time in a modern nuclear family. Construct a method for diagram to systematically and visualized describe the space plan of a modern nuclear family toward a intelligent design, to assist designer to retrieve information and check/review event pattern of past and present.

Keywords: digital diagram, information model, context aware, data analysis

Procedia PDF Downloads 338

Authors: Cihan Çetinkaya, Eren Özceylan, Kerem Elibal

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This paper presents a solution method for selection of production facility. The motivation has been taken from a real life case, an automotive subcontractor which has two production facilities at different cities and parts. The problem is to decide which part(s) should be produced at which facility. To the best of our knowledge, until this study, there was no scientific approach about this problem at the firm and decisions were being given intuitively. In this study, some logistic cost parameters have been defined and with these parameters a mathematical model has been constructed. Defined and collected cost parameters are handling cost of parts, shipment cost of parts and shipment cost of welding fixtures. Constructed multi-objective mathematical model aims to minimize these costs while aims to balance the workload between two locations. Results showed that defined model can give optimum solutions in reasonable computing times. Also, this result gave encouragement to develop the model with addition of new logistic cost parameters.

Keywords: automotive subcontract, facility assignment, logistic costs, multi-objective models

Procedia PDF Downloads 369