Search results for: generalized autoregressive score model

Authors: Lovorka Galetic, Zeljko Vukelic

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The advanced concepts of strategic and innovation management in the sphere of company dynamic and innovation capabilities, and achieving their mutual alignment and a synergy effect, are important elements in business today. This paper analyses the theory and empirically investigates the influence of a company’s dynamic capabilities on its innovation capabilities. A new multidimensional model of dynamic capabilities is presented, consisting of five factors appropriate to real time requirements, while innovation capabilities are considered pursuant to the official OECD and Eurostat standards. After examination of dynamic and innovation capabilities indicated their theoretical links, the empirical study testing the model and examining the influence of a company’s dynamic capabilities on its innovation capabilities showed significant results. In the study, a research model was posed to relate company dynamic and innovation capabilities. One side of the model features the variables that are the determinants of dynamic capabilities defined through their factors, while the other side features the determinants of innovation capabilities pursuant to the official standards. With regard to the research model, five hypotheses were set. The study was performed in late 2014 on a representative sample of large and very large Croatian enterprises with a minimum of 250 employees. The research instrument was a questionnaire administered to company top management. For both variables, the position of the company was tested in comparison to industry competitors, on a fivepoint scale. In order to test the hypotheses, correlation tests were performed to determine whether there is a correlation between each individual factor of company dynamic capabilities with the existence of its innovation capabilities, in line with the research model. The results indicate a strong correlation between a company’s possession of dynamic capabilities in terms of their factors, due to the new multi-dimensional model presented in this paper, with its possession of innovation capabilities. Based on the results, all five hypotheses were accepted. Ultimately, it was concluded that there is a strong association between the dynamic and innovation capabilities of a company. 

Keywords: dynamic capabilities, innovation capabilities, competitive advantage, business results

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Authors: Hamed Alqahtani, Manolya Kavakli-Thorne

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The large pose discrepancy is one of the critical challenges in face recognition during video surveillance. Due to the entanglement of pose attributes with identity information, the conventional approaches for pose-independent representation lack in providing quality results in recognizing largely posed faces. In this paper, we propose a practical approach to disentangle the pose attribute from the identity information followed by synthesis of a face using a classifier network in latent space. The proposed approach employs a modified generative adversarial network framework consisting of an encoder-decoder structure embedded with a classifier in manifold space for carrying out factorization on the latent encoding. It can be further generalized to other face and non-face attributes for real-life video frames containing faces with significant attribute variations. Experimental results and comparison with state of the art in the field prove that the learned representation of the proposed approach synthesizes more compelling perceptual images through a combination of adversarial and classification losses.

Keywords: disentanglement, face detection, generative adversarial networks, video surveillance

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Authors: Stefano Zappacosta, Cristiano Bove, Maria Carmela Marinelli, Paola di Lauro, Katarina Spasenovic, Lorenzo Ostano, Giuseppe Aiello, Marco Pietrosanto

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This paper proposes a novel neural network approach for assessing flood hazard mapping. The core of the model is a machine learning component fed by frequency ratios, namely statistical correlations between flood event occurrences and a selected number of topographic properties. The proposed hybrid model can be used to classify four different increasing levels of hazard. The classification capability was compared with the flood hazard mapping River Basin Plans (PAI) designed by the Italian Institute for Environmental Research and Defence, ISPRA (Istituto Superiore per la Protezione e la Ricerca Ambientale). The study area of Piemonte, an Italian region, has been considered without loss of generality. The frequency ratios may be used as a standalone block to model the flood hazard mapping. Nevertheless, the mixture with a neural network improves the classification power of several percentage points, and may be proposed as a basic tool to model the flood hazard map in a wider scope.

Keywords: flood modeling, hazard map, neural networks, hydrogeological risk, flood risk assessment

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Authors: J. R. Wang, H. C. Chen, C. Shih, S. W. Chen, J. H. Yang, Y. Chiang

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In this study, we focus on the establishment of the analysis model for Maanshan PWR nuclear power plant (NPP) by using RADTRAD and SNAP codes with the FSAR, manuals, and other data. In order to evaluate the cumulative dose at the Exclusion Area Boundary (EAB) and Low Population Zone (LPZ) outer boundary, Maanshan NPP RADTRAD/SNAP model was used to perform the analysis of the DBA LOCA case. The analysis results of RADTRAD were similar to FSAR data. These analysis results were lower than the failure criteria of 10 CFR 100.11 (a total radiation dose to the whole body, 250 mSv; a total radiation dose to the thyroid from iodine exposure, 3000 mSv).

Keywords: RADionuclide, transport, removal, and dose estimation (RADTRAD), symbolic nuclear analysis package (SNAP), dose, PWR

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Authors: N. Philipova

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The influence of the geometric parameters of trapezoidal labyrinth channel on the emitter discharge is investigated in this work. The impact of the dentate angle, the dentate spacing, and the dentate height are studied among the geometric parameters of the labyrinth channel. Numerical simulations of the water flow movement are performed according to central cubic composite design using Commercial codes GAMBIT and FLUENT. Inlet pressure of the dripper is set up to be 1 bar. The objective of this paper is to derive a mathematical model of the emitter discharge depending on the dentate angle, the dentate spacing, the dentate height of the labyrinth channel. As a result, the obtained mathematical model is a second-order polynomial reporting 2-way interactions among the geometric parameters. The dentate spacing has the most important and positive influence on the emitter discharge, followed by the simultaneous impact of the dentate spacing and the dentate height. The dentate angle in the observed interval has no significant effect on the emitter discharge. The obtained model can be used as a basis for a future emitter design.

Keywords: drip irrigation, labyrinth channel hydrodynamics, numerical simulations, Reynolds stress model.

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Authors: Vincent Iacobellis, Kamran Behdinan

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A finite element cohesive zone model is used to predict the temperature dependent material properties of a polyimide matrix composite with unidirectional carbon fiber arrangement. The cohesive zone parameters have been obtained from previous research involving an atomistic-to-continuum multiscale simulation of the fiber-matrix interface using the bridging cell multiscale method. The goal of the research was to both investigate the effect of temperature change on the composite behavior with respect to transverse loading as well as the validate the use of cohesive parameters obtained from atomistic-to-continuum multiscale modeling to predict fiber-matrix interfacial cracking. From the multiscale model cohesive zone parameters (i.e. maximum traction and energy of separation) were obtained by modeling the interface between the coarse-grained polyimide matrix and graphite based carbon fiber. The cohesive parameters from this simulation were used in a cohesive zone model of the composite microstructure in order to predict the properties of the macroscale composite with respect to changes in temperature ranging from 21 ˚C to 316 ˚C. Good agreement was found between the microscale RUC model and experimental results for stress-strain response, stiffness, and material strength at low and high temperatures. Examination of the deformation of the composite through localized crack initiation at the fiber-matrix interface also agreed with experimental observations of similar phenomena. Overall, the cohesive zone model was shown to be both effective at modeling the composite properties with respect to transverse loading as well as validated the use of cohesive zone parameters obtained from the multiscale simulation.

Keywords: cohesive zone model, fiber-matrix interface, microscale damage, multiscale modeling

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Authors: Monika Florczak-Wator

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The model of positive obligations of the state concerning the protection of the rights of an individual was created within the jurisdiction of the German Federal Constitutional Court in the 1970s. That model assumes that the state should protect an individual against infringement of their fundamental rights by another individual. It is based on the idea concerning the modification of the function and duties of the state towards an individual and society. Initially the state was perceived as the main infringer of the fundamental rights of an individual formulating the individual’s obligations of negative nature (obligation of noninterference), however, at present the state is perceived as a guarantor and protector of the fundamental rights of an individual of positive nature (obligation of protection). Examination of the chosen judicial decisions of that court will enable us to determine what the obligation of protection is specifically about, when it is updated and whether it is accompanied by claims of an individual requesting the state to take actions protecting their fundamental rights against infringement by the private entities. The comparative perspective for the German model of positive obligations of the state will be an analogous model present in the jurisdiction of the European Court of Human Rights. It is justified to include it in the research as the Convention, similarly to the constitution, focuses on the protection of an individual against the infringement of their rights by the state and both models have been developed within the jurisdiction for several dozens of years. Analysis of the provisions of the Constitution of the Republic of Poland as well as judgements of the Polish Constitutional Tribunal will allow for the presentation of the application the model of the protective duties of the state in Poland.

Keywords: human rights, horizontal relationships, constitution, state protection

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Authors: Ayoub El Bourtali, Abdessamed Najine, Amrou Moussa Benmoussa

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It is becoming more and more necessary to manage flood risk, and it must include all stakeholders and all possible means available. The goal of this work is to map the vulnerability of the Oued Derna-region Tagzirt flood zone in the semi-arid region. This is about implementing predictive models and flood control. This allows for the development of flood risk prevention plans. In this study, A resistivity survey was conducted over the area to locate and evaluate soil characteristics in order to calculate discharges and prevent flooding for the study area. The development of a one-dimensional (1D) hydrodynamic model of the Derna River was carried out in HEC-RAS 5.0.4 using a combination of survey data and spatially extracted cross-sections and recorded river flows. The study area was hit by several extreme floods, causing a lot of property loss and loss of life. This research focuses on the most recent flood events, based on the collected data, the water level, river flow and river cross-section were analyzed. A set of flood levels were obtained as the outputs of the hydraulic model and the accuracy of the simulated flood levels and velocity.

Keywords: derna river, 1D hydrodynamic model, flood modelling, HEC-RAS 5.0.4

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Authors: Tadashi Watanabe, Jinya Katsuyama, Akihiro Mano

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The estimation of leak flow rates through narrow cracks in structures is of importance for nuclear reactor safety, since the leak flow could be detected before occurrence of loss-of-coolant accidents. The two-phase critical leak flow rates are calculated using the system analysis code, and two representative non-homogeneous critical flow models, Henry-Fauske model and Ransom-Trapp model, are compared. The pressure decrease and vapor generation in the crack, and the leak flow rates are found to be larger for the Henry-Fauske model. It is shown that the leak flow rates are not affected by the structural temperature, but affected largely by the roughness of crack surface.

Keywords: crack, critical flow, leak, roughness

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Authors: M. V. Shivaani, P. K. Jain, Surendra S. Yadav

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Public Sector Undertakings (PSUs), being government-owned organizations have commitments for the economic and social wellbeing of the society; this commitment needs to be reflected in their risk-taking, decision-making and governance structures. Therefore, the primary objective of the study is to suggest measures that may lead to improvement in performance of PSUs. To achieve this objective two normative frameworks (one relating to risk levels and other relating to governance structure) are being put forth. The risk index is based on nine risks, such as, solvency risk, liquidity risk, accounting risk, etc. and each of the risks have been scored on a scale of 1 to 5. The governance index is based on eleven variables, such as, board independence, diversity, risk management committee, etc. Each of them are scored on a scale of 1 to five. The sample consists of 39 PSUs that featured in Nifty 500 index and, the study covers a 10 year period from April 1, 2005 to March, 31, 2015. Return on assets (ROA) and return on equity (ROE) have been used as proxies of firm performance. The control variables used in the model include, age of firm, growth rate of firm and size of firm. A dummy variable has also been used to factor in the effects of recession. Given the panel nature of data and possibility of endogeneity, dynamic panel data- generalized method of moments (Diff-GMM) regression has been used. It is worth noting that the corporate governance index is positively related to both ROA and ROE, indicating that with the improvement in governance structure, PSUs tend to perform better. Considering the components of CGI, it may be suggested that (i). PSUs ensure adequate representation of women on Board, (ii). appoint a Chief Risk Officer, and (iii). constitute a risk management committee. The results also indicate that there is a negative association between risk index and returns. These results not only validate the framework used to develop the risk index but also provide a yardstick to PSUs benchmark their risk-taking if they want to maximize their ROA and ROE. While constructing the CGI, certain non-compliances were observed, even in terms of mandatory requirements, such as, proportion of independent directors. Such infringements call for stringent penal provisions and better monitoring of PSUs. Further, if the Securities and Exchange Board of India (SEBI) and Ministry of Corporate Affairs (MCA) bring about such reforms in the PSUs and make mandatory the adherence to the normative frameworks put forth in the study, PSUs may have more effective and efficient decision-making, lower risks and hassle free management; all these ultimately leading to better ROA and ROE.

Keywords: PSU, risk governance, diff-GMM, firm performance, the risk index

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Authors: Prasita Sooksamran, Wareerat Kaewurai

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STEM is an integrated teaching approach promoted by the Ministry of Education in Thailand. STEM Education is an integrated approach to teaching Science, Technology, Engineering, and Mathematics. It has been questioned by Thai teachers on the grounds of how to integrate STEM into the classroom. Therefore, the main objective of this study is to develop a science instructional model based on the STEM approach to enhance scientific mind and problem-solving skills for primary students. This study is participatory action research, and follows the following steps: 1) develop a model 2) seek the advice of experts regarding the teaching model. Developing the instructional model began with the collection and synthesis of information from relevant documents, related research and other sources in order to create prototype instructional model. 2) The examination of the validity and relevance of instructional model by a panel of nine experts. The findings were as follows: 1. The developed instructional model comprised of principles, objective, content, operational procedures and learning evaluation. There were 4 principles: 1) Learning based on the natural curiosity of primary school level children leading to knowledge inquiry, understanding and knowledge construction, 2) Learning based on the interrelation between people and environment, 3) Learning that is based on concrete learning experiences, exploration and the seeking of knowledge, 4) Learning based on the self-construction of knowledge, creativity, innovation and 5) relating their findings to real life and the solving of real-life problems. The objective of this construction model is to enhance scientific mind and problem-solving skills. Children will be evaluated according to their achievements. Lesson content is based on science as a core subject which is integrated with technology and mathematics at grade 6 level according to The Basic Education Core Curriculum 2008 guidelines. The operational procedures consisted of 6 steps: 1) Curiosity 2) Collection of data 3) Collaborative planning 4) Creativity and Innovation 5) Criticism and 6) Communication and Service. The learning evaluation is an authentic assessment based on continuous evaluation of all the material taught. 2. The experts agreed that the Science Instructional Model based on the STEM Education Approach had an excellent level of validity and relevance (4.67 S.D. 0.50).

Keywords: instructional model, STEM education, scientific mind, problem solving

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Authors: Gu Pang, Bartosz Gebka

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We forecast the demand of total container throughput at the Indonesia’s largest seaport, Tanjung Priok Port. We propose four univariate forecasting models, including SARIMA, the additive Seasonal Holt-Winters, the multiplicative Seasonal Holt-Winters and the Vector Error Correction Model. Our aim is to provide insights into whether forecasting the total container throughput obtained by historical aggregated port throughput time series is superior to the forecasts of the total throughput obtained by summing up the best individual terminal forecasts. We test the monthly port/individual terminal container throughput time series between 2003 and 2013. The performance of forecasting models is evaluated based on Mean Absolute Error and Root Mean Squared Error. Our results show that the multiplicative Seasonal Holt-Winters model produces the most accurate forecasts of total container throughput, whereas SARIMA generates the worst in-sample model fit. The Vector Error Correction Model provides the best model fits and forecasts for individual terminals. Our results report that the total container throughput forecasts based on modelling the total throughput time series are consistently better than those obtained by combining those forecasts generated by terminal-specific models. The forecasts of total throughput until the end of 2018 provide an essential insight into the strategic decision-making on the expansion of port's capacity and construction of new container terminals at Tanjung Priok Port.

Keywords: SARIMA, Seasonal Holt-Winters, Vector Error Correction Model, container throughput

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Authors: Alireza Fallahfard, Ludwig Vinches, Stephane Halle

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In the workplace, the exposure level of airborne contaminants should be evaluated due to health and safety issues. It can be done by numerical models or experimental measurements, but the numerical approach can be useful when it is challenging to perform experiments. One of the simplest models is the well-mixed room (WMR) model, which has shown its usefulness to predict inhalation exposure in many situations. However, since the WMR is limited to gases and vapors, it cannot be used to predict exposure to aerosols. The main objective is to modify the WMR model to expand its application to exposure scenarios involving aerosols. To reach this objective, the standard WMR model has been modified to consider the deposition of particles by gravitational settling and Brownian and turbulent deposition. Three deposition models were implemented in the model. The time-dependent concentrations of airborne particles predicted by the model were compared to experimental results conducted in a 0.512 m3 chamber. Polystyrene particles of 1, 2, and 3 µm in aerodynamic diameter were generated with a nebulizer under two air changes per hour (ACH). The well-mixed condition and chamber ACH were determined by the tracer gas decay method. The mean friction velocity on the chamber surfaces as one of the input variables for the deposition models was determined by computational fluid dynamics (CFD) simulation. For the experimental procedure, the particles were generated until reaching the steady-state condition (emission period). Then generation stopped, and concentration measurements continued until reaching the background concentration (decay period). The results of the tracer gas decay tests revealed that the ACHs of the chamber were: 1.4 and 3.0, and the well-mixed condition was achieved. The CFD results showed the average mean friction velocity and their standard deviations for the lowest and highest ACH were (8.87 ± 0.36) ×10-2 m/s and (8.88 ± 0.38) ×10-2 m/s, respectively. The numerical results indicated the difference between the predicted deposition rates by the three deposition models was less than 2%. The experimental and numerical aerosol concentrations were compared in the emission period and decay period. In both periods, the prediction accuracy of the modified model improved in comparison with the classic WMR model. However, there is still a difference between the actual value and the predicted value. In the emission period, the modified WMR results closely follow the experimental data. However, the model significantly overestimates the experimental results during the decay period. This finding is mainly due to an underestimation of the deposition rate in the model and uncertainty related to measurement devices and particle size distribution. Comparing the experimental and numerical deposition rates revealed that the actual particle deposition rate is significant, but the deposition mechanisms considered in the model were ten times lower than the experimental value. Thus, particle deposition was significant and will affect the airborne concentration in occupational settings, and it should be considered in the airborne exposure prediction model. The role of other removal mechanisms should be investigated.

Keywords: aerosol, CFD, exposure assessment, occupational settings, well-mixed room model, zonal model

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Authors: Alan Ruiz-Padilla, Brando Villalobos-Villalobos, Yeniley Ruiz-Noa, Claudia Mendoza-Macías, Claudia Palafox-Sánchez, Miguel Marín-Rosales, Álvaro Cruz, Rubén Rangel-Salazar

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Introduction: In patients with rheumatoid arthritis, resistance or poor response to disease modifying antirheumatic drugs (DMARD) may be a reflection of the increase in g-P. The expression of g-P may be important in mediating the effluence of DMARD from the cell. In addition, P-glycoprotein is involved in the transport of cytokines, IL-1, IL-2 and IL-4, from normal lymphocytes activated to the surrounding extracellular matrix, thus influencing the activity of RA. The involvement of P-glycoprotein in the transmembrane transport of cytokines can serve as a modulator of the efficacy of DMARD. It was shown that a number of lymphocytes with glycoprotein P activity is increased in patients with RA; therefore, P-glycoprotein expression could be related to the activity of RA and could be a predictor of poor response to therapy. Objective: To evaluate in RA patients, if the G2677T/A MDR1 polymorphisms is associated with differences in the rate of therapeutic response to disease-modifying antirheumatic agents in patients with rheumatoid arthritis. Material and Methods: A prospective cohort study was conducted. Fifty seven patients with RA were included. They had an active disease according to DAS-28 (score >3.2). We excluded patients receiving biological agents. All the patients were followed during 6 months in order to identify the rate of therapeutic response according to the American College of Rheumatology (ACR) criteria. At the baseline peripheral blood samples were taken in order to identify the G2677T/A MDR1 polymorphisms using PCR- Specific allele. The fragment was identified by electrophoresis in polyacrylamide gels stained with ethidium bromide. For statistical analysis, the genotypic and allelic frequencies of MDR1 gene polymorphism between responders and non-responders were determined. Chi-square tests as well as, relative risks with 95% confidence intervals (95%CI) were computed to identify differences in the risk for achieving therapeutic response. Results: RA patients had a mean age of 47.33 ± 12.52 years, 87.7% were women with a mean for DAS-28 score of 6.45 ± 1.12. At the 6 months, the rate of therapeutic response was 68.7 %. The observed genotype frequencies were: for G/G 40%, T/T 32%, A/A 19%, G/T 7% and for A/A genotype 2%. Patients with G allele developed at 6 months of treatment, higher rate for therapeutic response assessed by ACR20 compared to patients with others alleles (p=0.039). Conclusions: Patients with G allele of the - G2677T/A MDR1 polymorphisms had a higher rate of therapeutic response at 6 months with DMARD. These preliminary data support the requirement for a deep evaluation of these and other genotypes as factors that may influence the therapeutic response in RA.

Keywords: pharmacogenetics, MDR1, P-glycoprotein, therapeutic response, rheumatoid arthritis

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Authors: Kirti Gosavi, Anita Bhole

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The paper demonstrates simulation and steady-state performance of three phase squirrel cage induction motor and detection of rotor broken bar fault using MATLAB. This simulation model is successfully used in the fault detection of rotor broken bar for the induction machines. A dynamic model using PWM inverter and mathematical modelling of the motor is developed. The dynamic simulation of the small power induction motor is one of the key steps in the validation of the design process of the motor drive system and it is needed for eliminating advertent design errors and the resulting error in the prototype construction and testing. The simulation model will be helpful in detecting the faults in three phase induction motor using Motor current signature analysis.

Keywords: squirrel cage induction motor, pulse width modulation (PWM), fault diagnosis, induction motor

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Authors: Chiung-Ju Huang, Yuan-Hong Ho

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This study utilizes the International Monetary Fund (IMF) Fiscal Rules Dataset focusing on four specific fiscal rules such as expenditure rule, revenue rule, budget balance rule, and debt rule and five main characteristics of each fiscal rule those are monitoring, enforcement, coverage, legal basis, and escape clause to construct the Fiscal Rule Index for nine countries in the Asia-Pacific region from 1996 to 2015. After constructing the fiscal rule index for each country, we utilize the Panel Generalized Method of Moments (Panel GMM) by using the constructed fiscal rule index to examine the effectiveness of fiscal rules in reducing procyclicality. Empirical results show that national fiscal rules have a significantly negative impact on procyclicality of government expenditure. Additionally, stricter fiscal rules combined with high government effectiveness are effective in reducing procyclicality of government expenditure. Results of this study indicate that for nine Asia-Pacific countries, policymakers’ use of fiscal rules and government effectiveness to reducing procyclicality of fiscal policy are effective.

Keywords: counter-cyclical policy, fiscal rules, government efficiency, procyclical policy

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Authors: Shahadut Hossain

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Measurement errors in continuous covariates and/or misclassifications in categorical covariates are common in epidemiological studies. Regression analysis ignoring such mismeasurements seriously biases the estimated main and interaction effects of covariates on the outcome of interest. Thus, adjustments for such mismeasurements are necessary. In this research, we propose a Bayesian parametric framework for eliminating deleterious impacts of covariate mismeasurements in logistic regression. The proposed adjustment method is unified and thus can be applied to any generalized linear and non-linear regression models. Furthermore, adjustment for covariate mismeasurements requires validation data usually in the form of either gold standard measurements or replicates of the mismeasured covariates on a subset of the study population. Initial investigation shows that adequacy of such adjustment depends on the sizes of main and validation samples, especially when prevalences of the categorical covariates are low. Thus, we investigate the impact of main and validation sample sizes on the adjusted estimates, and provide a general guideline about these sample sizes based on simulation studies.

Keywords: measurement errors, misclassification, mismeasurement, validation sample, Bayesian adjustment

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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: Taekyoon Park, Seokgoo Lee, Sungho Kim, Ung Lee, Jong Min Lee, Chonghun Han

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CO2 capture and storage/sequestration (CCS) is a key technology for addressing the global warming issue. This paper proposes an integrated model for the whole chain of CCS, from a power plant to a reservoir. The integrated model is further utilized to determine optimal operating conditions and study responses to various changes in input variables.

Keywords: CCS, caron dioxide, carbon capture and storage, simulation, optimization

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Authors: Velázquez Alejandro, Pradhan Sujan, Yoon Rokhyun, Sanada Yasushi

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The utilization of new materials as an alternative solution to decrease the environmental impact of the construction industry has been gaining more relevance in the architectural design and construction industry. One such material is cross-laminated timber (CLT), an engineered timber solution that excels for its faster construction times, workability, lightweight, and capacity for carbon storage. This material is usually used alone for the entire structure or combined with steel frames, but a hybrid with reinforced concrete (RC) is rarer. Since RC is one of the most used materials worldwide, a hybrid with CLT would allow further utilization of the latter, and in the process, it would help reduce the environmental impact of RC construction to achieve a sustainable society, but first, the structural performance of such hybrids must be understood. This paper focuses on proposing a model to predict the seismic performance of RC frames with CLT panels as infills. A series of static horizontal cyclic loading experiments were conducted on two 40% scale specimens of reinforced concrete frames with and without CLT panels at Osaka University, Japan. An analytical model was created to simulate the seismic performance of the RC frame with CLT infill based on the experimental results. The proposed model was verified by comparing the experimental and analytical results, showing that the load-deformation relationship and the failure mechanism agreed well with limited error. Hence, the proposed analytical model can be implemented for the seismic performance evaluation of the RC frames with CLT infill.

Keywords: analytical model, multi spring, performance evaluation, reinforced concrete, rocking mechanism, wooden wall

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Authors: Leo Laine, Morgan Johansson

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To meet the civilizations future needs for safe living and low environmental footprint, the engineers designing the complex systems of tomorrow will need efficient ways to model and optimize these systems for their intended purpose. For example, a civil defence shelter and its subsystem components needs to withstand, e.g. airblast and ground shock from decided design level explosion which detonates with a certain distance from the structure. In addition, the complex civil defence shelter needs to have functioning air filter systems to protect from toxic gases and provide clean air, clean water, heat, and electricity needs to also be available through shock and vibration safe fixtures and connections. Similar complex building systems can be found in any concentrated living or office area. In this paper, the authors use a multidomain modelling language called Modelica to model a concrete wall as a single degree of freedom (SDOF) system with elastoplastic properties with the implemented option of plastic hardening. The elastoplastic model was developed and implemented in the open source tool OpenModelica. The simulation model was tested on the case with a transient equivalent reflected pressure time history representing an airblast from 100 kg TNT detonating 15 meters from the wall. The concrete wall is approximately regarded as a concrete strip of 1.0 m width. This load represents a realistic threat on any building in a city like area. The OpenModelica model results were compared with an Excel implementation of a SDOF model with an elastic-plastic spring using simple fixed timestep central difference solver. The structural displacement results agreed very well with each other when it comes to plastic displacement magnitude, elastic oscillation displacement, and response times.

Keywords: airblast from explosives, elastoplastic spring model, Modelica modelling language, SDOF, structural response of concrete structure

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Authors: Simrin Kafle, Ulrika Enemark

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Catastrophic health expenditure (CHE) is a critical issue in low- and middle-income countries like Nepal, exacerbating financial hardship among vulnerable households. This study assesses the effectiveness of Nepal’s National Health Insurance Program (NHIP), launched in 2015, to reduce out-of-pocket (OOP) healthcare costs and mitigate CHE. Conducted in Pokhara Metropolitan City, the study used an analytical cross-sectional design, sampling 1276 households through a two-stage random sampling method. Data was collected via face-to-face interviews between May and October 2023. The analysis was conducted using SPSS version 29, incorporating propensity score matching to minimize biases and create comparable groups of enrolled and non-enrolled households in the NHIP. PSM helped reduce confounding effects by matching households with similar baseline characteristics. Additionally, a doubly robust methodology was employed, combining propensity score adjustment with regression modeling to enhance the reliability of the results. This comprehensive approach ensured a more accurate estimation of the impact of NHIP enrollment on CHE. Among the 1276 samples, 534 households (41.8%) were enrolled in NHIP. Of them, 84.3% of households renewed their insurance card, though some cited long waiting times, lack of medications, and complex procedures as barriers to renewal. Approximately 57.3% of households reported known diseases before enrollment, with 49.8% attending routine health check-ups in the past year. The primary motivation for enrollment was encouragement from insurance employees (50.2%). The data indicates that 12.5% of enrolled households experienced CHE versus 7.5% among non-enrolled. Enrollment into NHIP does not contribute to lower CHE (AOR: 1.98, 95% CI: 1.21-3.24). Key factors associated with increased CHE risk were presence of non-communicable diseases (NCDs) (AOR: 3.94, 95% CI: 2.10-7.39), acute illnesses/injuries (AOR: 6.70, 95% CI: 3.97-11.30), larger household size (AOR: 3.09, 95% CI: 1.81-5.28), and households below the poverty line (AOR: 5.82, 95% CI: 3.05-11.09). Other factors such as gender, education level, caste/ethnicity, presence of elderly members, and under-five children also showed varying associations with CHE, though not all were statistically significant. The study concludes that enrollment in the NHIP does not significantly reduce the risk of CHE. The reason for this could be inadequate coverage, where high-cost medicines, treatments, and transportation costs are not fully included in the insurance package, leading to significant out-of-pocket expenses. We also considered the long waiting time, lack of medicines, and complex procedures for the utilization of NHIP benefits, which might result in the underuse of covered services. Finally, gaps in enrollment and retention might leave certain households vulnerable to CHE despite the existence of NHIP. Key factors contributing to increased CHE include NCDs, acute illnesses, larger household sizes, and poverty. To improve the program’s effectiveness, it is recommended that NHIP benefits and coverage be expanded to better protect against high healthcare costs. Additionally, simplifying the renewal process, addressing long waiting times, and enhancing the availability of services could improve member satisfaction and retention. Targeted financial protection measures should be implemented for high-risk groups, and efforts should be made to increase awareness and encourage routine health check-ups to prevent severe health issues that contribute to CHE.

Keywords: catastrophic health expenditure, effectiveness, national health insurance program, Nepal

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Authors: Ece A. Irmak, Amdulla O. Mekhrabov, M. Vedat Akdeniz

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There is a growing interest in the modeling and simulation of magnetic nanoalloys by various computational methods. Magnetic crystalline/amorphous nanoparticles (NP) are interesting materials from both the applied and fundamental points of view, as their properties differ from those of bulk materials and are essential for advanced applications such as high-performance permanent magnets, high-density magnetic recording media, drug carriers, sensors in biomedical technology, etc. As an important magnetic material, Fe-Ni based nanoalloys have promising applications in the chemical industry (catalysis, battery), aerospace and stealth industry (radar absorbing material, jet engine alloys), magnetic biomedical applications (drug delivery, magnetic resonance imaging, biosensor) and computer hardware industry (data storage). The physical and chemical properties of the nanoalloys depend not only on the particle or crystallite size but also on composition and atomic ordering. Therefore, computer modeling is an essential tool to predict structural, electronic, magnetic and optical behavior at atomistic levels and consequently reduce the time for designing and development of new materials with novel/enhanced properties. Although first-principles quantum mechanical methods provide the most accurate results, they require huge computational effort to solve the Schrodinger equation for only a few tens of atoms. On the other hand, molecular dynamics method with appropriate empirical or semi-empirical inter-atomic potentials can give accurate results for the static and dynamic properties of larger systems in a short span of time. In this study, structural evolutions, magnetic and electronic properties of Fe-Ni based nanoalloys have been studied by using molecular dynamics (MD) method in Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) and Density Functional Theory (DFT) in the Vienna Ab initio Simulation Package (VASP). The effects of particle size (in 2-10 nm particle size range) and temperature (300-1500 K) on stability and structural evolutions of amorphous and crystalline Fe-Ni bulk/nanoalloys have been investigated by combining molecular dynamic (MD) simulation method with Embedded Atom Model (EAM). EAM is applicable for the Fe-Ni based bimetallic systems because it considers both the pairwise interatomic interaction potentials and electron densities. Structural evolution of Fe-Ni bulk and nanoparticles (NPs) have been studied by calculation of radial distribution functions (RDF), interatomic distances, coordination number, core-to-surface concentration profiles as well as Voronoi analysis and surface energy dependences on temperature and particle size. Moreover, spin-polarized DFT calculations were performed by using a plane-wave basis set with generalized gradient approximation (GGA) exchange and correlation effects in the VASP-MedeA package to predict magnetic and electronic properties of the Fe-Ni based alloys in bulk and nanostructured phases. The result of theoretical modeling and simulations for the structural evolutions, magnetic and electronic properties of Fe-Ni based nanostructured alloys were compared with experimental and other theoretical results published in the literature.

Keywords: density functional theory, embedded atom model, Fe-Ni systems, molecular dynamics, nanoalloys

Procedia PDF Downloads 237

Authors: V. Sathya Narayanan, P. Sidharth, V. R. Sanal Kumar

Abstract:

The success of any retail business is predisposed by its swift response and its knack in understanding the constraints and the requirements of customers. In this paper a conceptual design model of an automated customer-friendly supermarket has been proposed. In this model a 10-sided, space benefited, regular polygon shaped gravity shelves have been designed for goods storage and effective customer-specific algorithms have been built-in for quick automatic delivery of the randomly listed goods. The algorithm is developed with two main objectives, viz., delivery time and priority. For meeting these objectives the randomly listed items are reorganized according to the critical-path of the robotic arm specific to the identified shop and its layout and the items are categorized according to the demand, shape, size, similarity and nature of the product for an efficient pick-up, packing and delivery process. We conjectured that the proposed automated supermarket model reduces business operating costs with much customer satisfaction warranting a win-win situation.

Keywords: automated supermarket, electronic shopping, polygon-shaped rack, shortest path algorithm for shopping

Procedia PDF Downloads 400

Authors: Benga Ebouele, Thomas Tengen

Abstract:

Implementing either periodic or continuous inventory review model within most manufacturing-companies-supply chains as a management tool may incur higher costs. These high costs affect the system flexibility which in turn affects the level of service required to satisfy customers. However, these effects are not clearly understood because the parameters of both inventory review policies (protection demand interval, order quantity, etc.) are not designed to be fully utilized under different and uncertain conditions such as poor manufacturing, supplies and delivery performance. Coming up with a hybrid model which may combine in some sense the feature of both continuous and a periodic inventory review models should be useful. Therefore, there is a need to build and evaluate such hybrid model on the annual total cost, stock out probability and system’s flexibility in order to search for the most cost effective inventory review model. This work also seeks to find the optimal sets of parameters of inventory management under stochastic condition so as to optimise each policy independently. The results reveal that a continuous inventory system always incurs lesser cost than a periodic (R, S) inventory system, but this difference tends to decrease as time goes by. Although the hybrid inventory is the only one that can yield lesser cost over time, it is not always desirable but also natural to use it in order to help the system to meet high performance specification.

Keywords: demand and lead time randomness, hybrid Inventory model, optimization, supply chain

Procedia PDF Downloads 306

Authors: Ali Soroush, Mehdi Mirzaei Alavijeh, Touraj Ahmadi Jouybari, Fazel Zinat-Motlagh, Abbas Aghaei, Mari Ataee

Abstract:

Diabetes is a disease with long cardiovascular, renal, ophthalmic and neural complications. It is prevalent all around the world including Iran, and its prevalence is increasing. The aim of this study was to determine the factors related to self-care behavior based on health belief model among sample of Iranian diabetic patients. This cross-sectional study was conducted among 301 type 2 diabetic patients in Gachsaran, Iran. Data collection was based on an interview and the data were analyzed by SPSS version 20 using ANOVA, t-tests, Pearson correlation, and linear regression statistical tests at 95% significant level. Linear regression analyses showed the health belief model variables accounted for 29% of the variation in self-care behavior; and perceived severity and perceived self-efficacy are more influential predictors on self-care behavior among diabetic patients.

Keywords: diabetes, patients, self-care behaviors, health belief model

Procedia PDF Downloads 464

Authors: Aminah Muchdar, Nuraeni, Eddy

Abstract:

The aims of the research are: (1) to verify the cropsyst plant model of experimental data in the field of soybean plants and (2) to predict planting time and potential yield soybean plant with the use of cropsyst model. This research is divided into several stages: (1) first calibration stage which conducted in the field from June until September 2015.(2) application models stage, where the data obtained from calibration in the field will be included in cropsyst models. The required data models are climate data, ground data/soil data,also crop genetic data. The relationship between the obtained result in field with simulation cropsyst model indicated by Efficiency Index (EF) which the value is 0,939.That is showing that cropsyst model is well used. From the calculation result RRMSE which the value is 1,922%.That is showing that comparative fault prediction results from simulation with result obtained in the field is 1,92%. The conclusion has obtained that the prediction of soybean planting time cropsyst based models that have been made valid for use. and the appropriate planting time for planting soybeans mainly on rain-fed land is at the end of the rainy season, in which the above study first planting time (June 2, 2015) which gives the highest production, because at that time there was still some rain. Tanggamus varieties more resistant to slow planting time cause the percentage decrease in the yield of each decade is lower than the average of all varieties.

Keywords: soybean, Cropsyst, calibration, efficiency Index, RRMSE

Procedia PDF Downloads 174

Authors: Omar Farahat Hassanein, A. Samer Ezeldin

Abstract:

The construction industry is a very dynamic field. Every day new technologies and methods are developing to fasten the process and increase its efficiency. Hence, if a project uses fewer resources, it will be more efficient. This paper examines the recycling of concrete construction and demolition (C&D) waste to reuse it as aggregates in on-site applications for construction projects in Egypt and possibly in the Middle East. The study focuses on a stationary plant setting. The machinery set-up used in the plant is analyzed technically and financially. The findings are gathered and grouped to obtain a comprehensive cost-benefit financial model to demonstrate the feasibility of establishing and operating a concrete recycling plant. Furthermore, a detailed business plan including the time and hierarchy is proposed.

Keywords: construction wastes, recycling, sustainability, financial model, concrete recycling, concrete life cycle

Procedia PDF Downloads 408

Authors: Ezil Sam Leni, Shalen S.

Abstract:

Transport service monitoring and upkeep are essential components of smart city initiatives. The main risks to the relevant departments and authorities are the ever-increasing vehicular traffic and the conditions of the roads. In India, the economy is greatly impacted by the road transport sector. In 2021, the Ministry of Road Transport and Highways Transport, Government of India, produced a report with statistical data on traffic accidents. The data included the number of fatalities, injuries, and other pertinent criteria. This study proposes a distributed infrastructure for the monitoring, detection, and reporting of potholes to the appropriate authorities. In a distributed environment, the nodes are the edge devices, and local edge servers, and global servers. The edge devices receive the initial model to be employed from the global server. The YOLOv8 model for pothole detection is used in the edge devices. The edge devices run the pothole detection model, gather the pothole images on their path, and send the updates to the nearby edge server. The local edge server selects the clients for its aggregation process, aggregates the model updates and sends the updates to the global server. The global server collects the updates from the local edge servers, performs aggregation and derives the updated model. The updated model has the information about the potholes received from the local edge servers and notifies the updates to the local edge servers and concerned authorities for monitoring and maintenance of road conditions. The entire process is implemented in FedCV distributed environment with the implementation using the client-server model and aggregation entities. After choosing the clients for its aggregation process, the local edge server gathers the model updates and transmits them to the global server. After gathering the updates from the regional edge servers, the global server aggregates them and creates the updated model. Performance indicators and the experimentation environment are assessed, discussed, and presented. Accelerometer data may be taken into consideration for improved performance in the future development of this study, in addition to the images captured from the transportation routes.

Keywords: federated Learning, pothole detection, distributed framework, federated averaging

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Authors: Vasilij Djackov, Tomas Zapnickas, Evgenii Iamshchikov, Lukas Norkevicius, Rima Mickeviciene, Larisa Vasiljeva

Abstract:

In this paper, the resistance and pitching values of the test of an electric ferry are presented. The research was carried out in the open flow channel of Klaipėda University with a multi-axis dynamometer. The received model resistance values were recalculated to the real vessel and the preliminary chosen propulsion unit power was compared. After analyzing the results of the pitching of the model, it was concluded that the shape of the hull needs to be further improved, taking into account the possible uneven weight distribution at the ends of the ferry. Further investigation of the hull of the electric ferry is recommended, including experiments with various water depths and activation of propulsion units.

Keywords: electrical ferry, model tests, open flow channel, pitching, resistance

Procedia PDF Downloads 86