Search results for: drift flow model

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: Khalid Kaddoura, Ahmed Assad, Tarek Zayed

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Sewer pipelines are prone to deterioration over-time. In fact, their deterioration does not follow a fixed downward pattern. This is in fact due to the defects that propagate through their service life. Sewer pipeline defects are categorized into distinct groups. However, the main two groups are the structural and operational defects. By definition, the structural defects influence the structural integrity of the sewer pipelines such as deformation, cracks, fractures, holes, etc. However, the operational defects are the ones that affect the flow of the sewer medium in the pipelines such as: roots, debris, attached deposits, infiltration, etc. Yet, the process for each defect to emerge follows a cause and effect relationship. Deformation, which is the change of the sewer pipeline geometry, is one type of an influencing defect that could be found in many sewer pipelines due to many surrounding factors. This defect could lead to collapse if the percentage exceeds 15%. Therefore, it is essential to predict the deformation percentage before confronting such a situation. Accordingly, this study will predict the percentage of the deformation defect in sewer pipelines adopting the multiple regression analysis. Several factors will be considered in establishing the model, which are expected to influence the defamation defect severity. Besides, this study will construct a time-based curve to understand how the defect would evolve overtime. Thus, this study is expected to be an asset for decision-makers as it will provide informative conclusions about the deformation defect severity. As a result, inspections will be minimized and so the budgets.

Keywords: deformation, prediction, regression analysis, sewer pipelines

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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: 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: Kamel A. Elshorbagy, Mohamed A. Hussein, Rola S. Afify

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Natural gas pressure reduction is typically achieved using pressure reducing valves, where isenthalpic expansion takes place with considerable amount of wasted energy in an irreversible throttling process of the gas. Replacing gas-throttling process by an expansion process in a turbo expander (TE) converts the pressure of natural gas into mechanical energy transmitted to a loading device (i.e. an electric generator). This paper investigates the performance of a turboexpander system for power recovery at natural gas pressure reduction stations. There is a considerable temperature drop associated with the turboexpander process. Essential preheating is required, using gas fired boilers, to avoid undesirable effects of a low outlet temperature. Various system configurations were simulated by the general flow sheet simulator HYSYS and factors affecting the overall performance of the systems were investigated. Power outputs and fuel requirements were found using typical gas flow variation data. The simulation was performed for two case studies in which real input data are used. These case studies involve a domestic (commercial) and an industrial natural gas pressure reduction stations in Egypt. Economic studies of using the turboexpander system in both of the two natural gas pressure reduction stations are conducted using precise data obtained through communication with several companies working in this field. The results of economic analysis, for the two case studies, prove that using turboexpander systems in Egyptian natural gas reduction stations can be a successful project for energy conservation.

Keywords: natural gas, power recovery, reduction stations, turboexpander systems

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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: Abhiyan Paudel, Maheshwaran M Pillai

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This paper deals with the optimization and comparison of slender delta wing and blended wing body. The objective is to study the difference between the two wing types and analyze the various aerodynamic characteristics of both of these types.The blended-wing body is an aircraft configuration that has the potential to be more efficient than conventional large transport aircraft configurations with the same capability. The purported advantages of the BWB approach are efficient high-lift wings and a wide airfoil-shaped body. Similarly, symmetric separation vortices over slender delta wing may become asymmetric as the angle of attack is increased beyond a certain value, causing asymmetric forces even at symmetric flight conditions. The transition of the vortex pattern from being symmetric to asymmetric over symmetric bodies under symmetric flow conditions is a fascinating fluid dynamics problem and of major importance for the performance and control of high-maneuverability flight vehicles that favor the use of slender bodies. With the use of Star CCM, we analyze both the fluid properties. The CL, CD and CM were investigated in steady state CFD of BWB at Mach 0.3 and through wind tunnel experiments on 1/6th model of BWB at Mach 0.1. From CFD analysis pressure variation, Mach number contours and turbulence area was observed.

Keywords: Coefficient of Lift, Coefficient of Drag, CFD=Computational Fluid Dynamics, BWB=Blended Wing Body, slender delta wing

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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

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Authors: Ali Alzeyadi, Edward Loffill, Rafid Alkhaddar Ali Alattabi

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Phosphate, ammonium, and nitrates are forms of nutrients; they are released from different sources. High nutrient levels contribute to the eutrophication of water bodies by accelerating the extraordinary growth of algae. Recently, many filtration and treatment systems were developed and used for different removal processes. Due to enhanced operational aspects for the up-flow, continuous, granular Media filter researchers became more interested in further developing this technology and its performance for nutrient removal from wastewater. Environmental factors significantly affect the filtration process performance, and understanding their impact will help to maintain the nutrient removal process. Phosphate removal by phosphate sorption materials PSMs and nitrogen removal biologically are the methods of nutrient removal that have been discussed in this paper. Hence, the focus on the factors that influence these processes is the scope of this work. The finding showed the presence of factors affecting both removal processes; the size, shape, and roughness of the filter media particles play a crucial role in supporting biofilm formation. On the other hand, all of which are effected on the reactivity of surface between the media and phosphate. Many studies alluded to factors that have significant influence on the biological removal for nitrogen such as dissolved oxygen, temperature, and pH; this is due to the sensitivity of biological processes while the phosphate removal by PSMs showed less affected by these factors. This review work provides help to the researchers in create a comprehensive approach in regards study the nutrient removal in up flow filtration systems.

Keywords: nitrogen biological treatment, nutrients, psms, upflow filter, wastewater treatment

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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: 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: Zoran Herceg, Višnja Stulić, Tomislava Vukušić, Anet Režek Jambrak

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High voltage electrical discharge is a new technology used for inactivation of pathogen microorganisms. Pathogen yeasts can cause diseases in humans if they are ingested. Nowadays new technologies have become the focus of researching all over the world. Rhodotorula is known as yeast that can cause diseases in humans. The aim of this study was to examine whether the high voltage electrical discharge treatment generated in gas phase has an influence on yeast reduction and recovery of Rhodotorula spp 74 in pure culture. Rhodotorula spp. 74 was treated in 200 mL of model solution. Treatment time (5 and 10 min), frequency (60 and 90 Hz) and injected gas (air or argon 99,99%) were changed. Titanium high voltage needle was used as high voltage electrode (positive polarity) through which air or argon was injected at the gas flow of 0.6 L/min. Experimental design and statistical analyses were obtained by Statgraphics Centurion software (StatPoint Technologies, Inc., VA, USA). The best inactivation rate 1.7 log10 reduction was observed after the 10 min of treatment, frequency of 90 Hz and injected air. Also with a longer treatment time inactivation rate was higher. After the 24 h recovery of treated samples was observed. Therefore the further optimization of method is needed to understand the mechanism of yeasts inactivation and cells recovery after the treatment. Acknowledgements: The authors would like to acknowledge the support by Croatian Science Foundation and research project ‘Application of electrical discharge plasma for preservation of liquid foods’.

Keywords: rhodotorula spp. 74, electrical discharge plasma, inactivation, stress response

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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: Justin Orimisan Ijigbade

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The study was conducted to assess the effect of climate variability on honeybee’s production in Ondo State, Nigeria. Multistage sampling technique was employed to collect the data from 60 beekeepers across six Local Government Areas in Ondo State. Data collected were subjected to descriptive statistics and multiple regression model analyses. The results showed that 93.33% of the respondents were male with 80% above 40 years of age. Majority of the respondents (96.67%) had formal education and 90% produced honey for commercial purpose. The result revealed that 90% of the respondents admitted that low temperature as a result of long hours/period of rainfall affected the foraging efficiency of the worker bees, 73.33% claimed that long period of low humidity resulted in low level of nectar flow, while 70% submitted that high temperature resulted in improper composition of workers, dunes and queen in the hive colony. The result of multiple regression showed that beekeepers’ experience, educational level, access to climate information, temperature and rainfall were the main factors affecting honey bees production in the study area. Therefore, beekeepers should be given more education on climate variability and its adaptive strategies towards ensuring better honeybees production in the study area.

Keywords: climate variability, honeybees production, humidity, rainfall and temperature

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Authors: Mariusz Hofman

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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

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Authors: Chhordaneath Hen, Ty Sok, Ilan Ich, Ratboren Chan, Chantha Oeurng

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The damages caused by hydrological extremes such as flooding have been severe globally, and several research studies indicated extreme precipitations play a crucial role. Cambodia is one of the most vulnerable countries exposed to floods and drought as consequences of climate impact. Prek Thnot River Basin in the southwest part of Cambodia, which is in the plate and plateau region and a part of the Mekong Delta, was selected to investigate the changes in extreme precipitation and hydrological extreme. Furthermore, to develop a statistical relationship between these phenomena in this basin from 1995 to 2020 using Multiple Linear Regression. The precipitation and hydrological extreme were assessed via the attributes and trends of rainfall patterns during the study periods. The extreme flow was defined as a dependent variable, while the independent variables are various extreme precipitation indices. The study showed that all extreme precipitations indices (R10, R20, R35, CWD, R95p, R99p, and PRCPTOT) had increasing decency. However, the number of rain days per year had a decreasing tendency, which can conclude that extreme rainfall was more intense in a shorter period of the year. The study showed a similar relationship between extreme precipitation and hydrological extreme and land use change association with hydrological extreme. The direct combination of land use and precipitation equals 37% of the flood causes in this river. This study provided information on these two causes of flood events and an understanding of expectations of climate change consequences for flood and water resources management.

Keywords: extreme precipitation, hydrological extreme, land use, land cover, Prek Thnot river basin

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

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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

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Authors: Stefano Sorace, Gloria Terenzi, Giulia Mazzieri, Iacopo Costoli

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The prolonged earthquake sequence that struck several urban agglomerations and villages in Central Italy, starting from 24 August 2016 through January 2017, highlighted once again the seismic vulnerability of pre-normative reinforced concrete (R/C) structures. At the same time, considerable damages were surveyed in recently retrofitted R/C buildings too, one of which also by means of a dissipative bracing system. The solution adopted for the latter did not expressly take into account the performance of non-structural elements, and namely of infills and partitions, confirming the importance of their dynamic interaction with the structural skeleton. Based on this consideration, an alternative supplemental damping-based retrofit solution for this representative building, i.e., a school with an R/C structure situated in the municipality of Norcia, is examined in this paper. It consists of the incorporation of dissipative braces equipped with pressurized silicone fluid viscous (FV) dampers, instead of the BRAD system installed in the building, the delayed activation of which -caused by the high stiffness of the constituting metallic dampers- determined the observed non-structural damages. Indeed, the alternative solution proposed herein, characterized by dissipaters with mainly damping mechanical properties, guarantees an earlier activation of the protective system. A careful assessment analysis, preliminarily carried out to simulate and check the case study building performance in originally BRAD-retrofitted conditions, confirms that the interstorey drift demand related to the Norcia earthquake's mainshock and aftershocks is beyond the response capacity of infills. The verification analyses developed on the R/C structure, including the FV-damped braces, highlight their higher performance, giving rise to a completely undamaged response both of structural and non-structural elements up to the basic design earthquake normative level of seismic action.

Keywords: dissipative technologies, performance assessment analysis, concrete structures, seismic retrofit

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Authors: Sherry Ann Ganase, Sandra Sookram

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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

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Authors: Kaustubh Chakradeo, Michael Delves, Sofya Titarenko

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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

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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

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Authors: Cihan Çetinkaya, Eren Özceylan, Kerem Elibal

Abstract:

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

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Authors: Natalia Efremova, Sergey Tarasenko

Abstract:

We propose a novel neural network architecture for visual saliency detections, which utilizes neuro physiologically plausible mechanisms for extraction of salient regions. The model has been significantly inspired by recent findings from neuro physiology and aimed to simulate the bottom-up processes of human selective attention. Two types of features were analyzed: color and direction of maximum variance. The mechanism we employ for processing those features is PCA, implemented by means of normalized Hebbian learning and the waves of spikes. To evaluate performance of our model we have conducted psychological experiment. Comparison of simulation results with those of experiment indicates good performance of our model.

Keywords: neural network models, visual saliency detection, normalized Hebbian learning, Oja's rule, psychological experiment

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Authors: Supasak Ngaoprasertwong

Abstract:

The purpose of this research was to develop a model for Muay Thai competition management for promoting sport tourism in the next decade. Moreover, the model was appropriately initiated for practical use. This study also combined several methodologies, both quantitative research and qualitative research, to entirely cover all aspects of data, especially the tourists’ satisfaction toward Muay Thai competition. The data were collected from 400 tourists watching Muay Thai competition in 4 stadiums to create the model for Muay Thai competition to support the sport tourism in the next decade. Besides, Ethnographic Delphi Futures Research (EDFR) was applied to gather the data from certain experts in boxing industry or having significant role in Muay Thai competition in both public sector and private sector. The first step of data collection was an in-depth interview with 27 experts associated with Muay Thai competition, Muay Thai management, and tourism. The second step and the third step of data collection were conducted to confirm the experts’ opinions toward various elements. When the 3 steps of data collection were completely accomplished, all data were assembled to draft the model. Then the model was proposed to 8 experts to conduct a brainstorming to affirm it. According to the results of quantitative research, it found that the tourists were satisfied with personnel of competition at high level (x=3.87), followed by facilities, services, and safe high level (x=3.67). Furthermore, they were satisfied with operation in competition field at high level (x=3.62).Regarding the qualitative methodology including literature review, theories, concepts and analysis of qualitative research development of the model for Muay Thai competition to promote the sport tourism in the next decade, the findings indicated that there were 2 data sets as follows: The first one was related to Muay Thai competition to encourage the sport tourism and the second one was associated with Muay Thai stadium management to support the sport tourism. After the brain storming, “EE Muay Thai Model” was finally developed for promoting the sport tourism in the next decade (2015-2024).

Keywords: Muay Thai competition management, Muay Thai sport tourism, Muay Thai, Muay Thai for sport tourism management

Procedia PDF Downloads 316