Search results for: agile factory model

Authors: Eunji Choi, Borang Park, Youngjae Choi, Jinwoo Moon

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In this study, a predictive model for estimating the metabolism (MET) of human body was developed for the optimal control of indoor thermal environment. Human body images for indoor activities and human body joint coordinated values were collected as data sets, which are used in predictive model. A deep learning algorithm was used in an initial model, and its number of hidden layers and hidden neurons were optimized. Lastly, the model prediction performance was analyzed after the model being trained through collected data. In conclusion, the possibility of MET prediction was confirmed, and the direction of the future study was proposed as developing various data and the predictive model.

Keywords: deep learning, indoor quality, metabolism, predictive model

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Authors: Alan Wan

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In recent years, the body of literature on frequentist model averaging in statistics has grown significantly. Most of this work focuses on models with different mean structures but leaves out the variance consideration. In this paper, we consider a regression model with multiplicative heteroscedasticity and develop a model averaging method that combines maximum likelihood estimators of unknown parameters in both the mean and variance functions of the model. Our weight choice criterion is based on a minimisation of a plug-in estimator of the model average estimator's squared prediction risk. We prove that the new estimator possesses an asymptotic optimality property. Our investigation of finite-sample performance by simulations demonstrates that the new estimator frequently exhibits very favourable properties compared to some existing heteroscedasticity-robust model average estimators. The model averaging method hedges against the selection of very bad models and serves as a remedy to variance function misspecification, which often discourages practitioners from modeling heteroscedasticity altogether. The proposed model average estimator is applied to the analysis of two real data sets.

Keywords: heteroscedasticity-robust, model averaging, multiplicative heteroscedasticity, plug-in, squared prediction risk

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Authors: Myung Hwan Na, Ho- Chun Song, EunHee Hong

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We widely use normal linear mixed-effects model to analysis data in repeated measurement. In case of detecting heteroscedasticity and the non-normality of the population distribution at the same time, normal linear mixed-effects model can give improper result of analysis. To achieve more robust estimation, we use heavy tailed linear mixed-effects model which gives more exact and reliable analysis conclusion than standard normal linear mixed-effects model.

Keywords: reliability, tires, field data, linear mixed-effects model

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Authors: Abdoullah Fath-Allah, Laila Cheikhi, Rafa E. Al-Qutaish, Ali Idri

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The e-government emerging concept transforms the way in which the citizens are dealing with their governments. Thus, the citizens can execute the intended services online anytime and anywhere. This results in great benefits for both the governments (reduces the number of officers) and the citizens (more flexibility and time saving). Therefore, building a maturity model to assess the e-government portals becomes desired to help in the improvement process of such portals. This paper aims at proposing an e-government maturity model based on the measurement of the best practices’ presence. The main benefit of such maturity model is to provide a way to rank an e-government portal based on the used best practices, and also giving a set of recommendations to go to the higher stage in the maturity model.

Keywords: best practices, e-government portal, maturity model, quality model

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Authors: Manotar Tampubolon

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Although the Indonesian human rights protection has increased in recent years, but human rights violations still occur in the industrial sector. Crimes against human rights continue to occur and go unnoticed in spite of the government's legislation on human rights, employment law in addition to an international treaty that has been ratified by Indonesia. The increasing number of garment companies in Bekasi, also give rise to increased human rights violations since the government does not have a commitment to protect it. The Indonesian government and industry owners should pay attention to and protect the human rights of workers and treat them accordingly. This paper will review the human rights violations experienced by workers at garment factories in the context of the law, as well as ideas to improve the protection of workers' rights.

Keywords: human rights protection, human rights violations, workers’ rights, justice, security

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Authors: I. C. Tolias, A. G. Venetsanos, N. Markatos

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In the present work, CFD simulations of a large scale open deflagration experiment are performed. Stoichiometric hydrogen-air mixture occupies a 20 m hemisphere. Two combustion models are compared and are evaluated against the experiment. The Eddy Dissipation Model and a Multi-physics combustion model which is based on Yakhot’s equation for the turbulent flame speed. The values of models’ critical parameters are investigated. The effect of the turbulence model is also examined. k-ε model and LES approach were tested.

Keywords: CFD, deflagration, hydrogen, combustion model

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Authors: J. Rhodes, V. Cheng, P. Lok

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The aim of this study is to develop a parsimonious model that explains the effect of different stimulus on a tourist’s intention to visit a new destination. The model consists of destination trust and interest as the mediating variables. The model was tested using two different types of stimulus; both studies empirically supported the proposed model. Furthermore, the first study revealed that advertising has a stronger effect than positive online reviews. The second study found that the peripheral route of the elaboration likelihood model has a stronger influence power than the central route in this context.

Keywords: advertising, electronic word-of-mouth, elaboration likelihood model, intention to visit, trust

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Authors: Ahmad Sarfaraz, Raiyad Herwies

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In this paper, a multi-criteria decision making analysis is used to help any organization selects the best KM tool that fits and serves its needs. The AHP model is used based on a previous study to highlight and identify the main criteria and sub-criteria that are incorporated in the selection process. Different KM tools alternatives with different criteria are compared and weighted accurately to be incorporated in the GP model. The main goal is to combine the GP model with the AHP model to ensure that selecting the KM tool considers the resource constraints. Two important issues are discussed in this paper: how different factors could be taken into consideration in forming the AHP model, and how to incorporate the AHP results into the GP model for better results.

Keywords: knowledge management, analytical hierarchy process, goal programming, multi-criteria decision making

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Authors: Lu Zhao, Nadir Farhi, Yeltsin Valero, Zoi Christoforou, Nadia Haddadou

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In this paper, a long short-term memory (LSTM) neural network model is proposed to replicate simultaneously car-following and lane-changing behaviors in road networks. By combining two kinds of LSTM layers and three input designs of the neural network, six variants of the LSTM model have been created. These models were trained and tested on the NGSIM 101 dataset, and the results were evaluated in terms of longitudinal speed and lateral position, respectively. Then, we compared the LSTM model with a classical car-following model (the intelligent driving model (IDM)) in the part of speed decision. In addition, the LSTM model is compared with a model using classical neural networks. After the comparison, the LSTM model demonstrates higher accuracy than the physical model IDM in terms of car-following behavior and displays better performance with regard to both car-following and lane-changing behavior compared to the classical neural network model.

Keywords: traffic modeling, neural networks, LSTM, car-following, lane-change

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Authors: Tim Wollert, Fabian Behrendt

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Value Stream Management (VSM) is a widely used methodology in the context of Lean Management for improving end-to-end material and information flows from a supplier to a customer from a company’s perspective. Whereas the design principles, e.g. Pull, value-adding, customer-orientation and further ones are still valid against the background of an increasing digitalized and dynamic environment, the methodology itself for mapping a value stream is characterized as time- and resource-intensive due to the high degree of manual activities. The digitalization of processes in the context of Industry 4.0 enables new opportunities to reduce these manual efforts and make the VSM approach more agile. The paper at hand aims at providing a modular data and calculation framework, utilizing the available business data, provided by information and communication technologies for automizing the value stream mapping process with focus on the manufacturing process.

Keywords: lean management 4.0, value stream management (VSM) 4.0, dynamic value stream mapping, enterprise resource planning (ERP)

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Authors: Erez Cohen

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The study examines the socioeconomic impact of development of an advanced industry in Israel. The research method is based on data collected from the Israel Central Bureau of Statistics and from the National Insurance Institute (NII) databases, which provided information that allows to examine the Economic and Social Changes during the 1990s. The study examined the socioeconomic effects of the development of advanced industry in Israel. The research findings indicate that as a result of globalization processes, the weight of traditional industry began to diminish as a result of factory closures and the laying off of workers. These circumstances led to growing unemployment among the weaker groups in Israeli society, detracting from their income and thus increasing inequality among different socioeconomic groups in Israel and enhancement of social disparities.

Keywords: globalization, Israeli advanced industry, public policy, socio-economic indicators

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Authors: Coskun Serefoglu

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The study aims to analyse how a traditional sector such as agri-food could be mobilized through regional innovation strategies. A principal component analysis as well as qualitative information, such as in-depth interviews, focus group and surveys, were employed to find the priority sectors. An agri-food model was developed which includes both a linear model and interactive model. The model consists of two main components, one of which is technological integration and the other one is agricultural extension which is based on Land-grant university approach of U.S. which is not a common practice in Turkey.

Keywords: regional innovation strategy, interactive model, agri-food sector, local development, planning, regional development

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Authors: Sasiporn Rattanasupha, Settapat Chinviriyasit

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The treatment function adopts a continuous and differentiable function which can describe the effect of delayed treatment when the number of infected individuals increases and the medical condition is limited. In this paper, the SEIR epidemic model with treatment function is studied to investigate the dynamics of the model due to the effect of treatment. It is assumed that the treatment rate is proportional to the number of infective patients. The stability of the model is analyzed. The model is simulated to illustrate the analytical results and to investigate the effects of treatment on the spread of infection.

Keywords: basic reproduction number, local stability, SEIR epidemic model, treatment function

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Authors: Charawee Butbumrung

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The purpose of this study is to evaluate the monetary worthiness of investment and the usefulness of risk estimation as a tool employed by a production section of an electronic factory. This study employed the case study of accidents occurring in production areas. Data is collected from interviews with six production of safety coordinators and collect the information from the relevant section. The study will present the ratio of benefits compared with the operation costs for investment. The result showed that it is worthwhile for investment with the safety measures. In addition, the organizations must be able to analyze the causes of accidents about the benefits of investing in protective working process. They also need to quickly provide the manual for the staff to learn how to protect themselves from accidents and how to use all of the safety equipment.

Keywords: cost and benefit, enterprises in Thailand, investment in safety and health, risk estimation

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Authors: Rakesh Kumar Mishra, Tarun Kumar Dan

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Lead-Lag based Internal Model Control method is proposed based on Internal Model Control (IMC) strategy. In this paper, we have designed the Lead-Lag based Internal Model Control for binary distillation column for SISO process (considering only bottom product). The transfer function has been taken from Wood and Berry model. We have find the composition control and disturbance rejection using Lead-Lag based IMC and comparing with the response of simple Internal Model Controller.

Keywords: SISO, lead-lag, internal model control, wood and berry, distillation column

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Authors: H. Namazi, H. T. N. Kuan

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It is known that in humans, the adaptation to a given odor occurs within a quite short span of time (typically one minute) after the odor is presented to the brain. Different models of human olfaction have been developed by scientists but none of these models consider the diffusion phenomenon in olfaction. A novel microscopic model of the human olfaction is presented in this paper. We develop this model by incorporating the transient diffusivity. In fact, the mathematical model is written based on diffusion of the odorant within the mucus layer. By the use of the model developed in this paper, it becomes possible to provide quantification of the objective strength of odor.

Keywords: diffusion, microscopic model, mucus layer, olfaction

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Authors: Yanshuang Zhang, Byungho Jeong

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There exists some time lag between the consumption of inputs and the production of outputs. This time lag effect should be considered in calculating efficiency of decision making units (DMU). Recently, a couple of DEA models were developed for considering time lag effect in efficiency evaluation of research activities. However, these models can’t discriminate efficient DMUs because of the nature of basic DEA model in which efficiency scores are limited to ‘1’. This problem can be resolved a super-efficiency model. However, a super efficiency model sometimes causes infeasibility problem. This paper suggests an output oriented super-efficiency model for efficiency evaluation under the consideration of time lag effect. A case example using a long term research project is given to compare the suggested model with the MpO model

Keywords: DEA, Super-efficiency, Time Lag, research activities

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Authors: Zainab Magaji Musa, Nordin M. A. Rahman, Julaily Aida Jusoh

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The web services applications for digital reference service (WSDRS) of LIS model is an informal model that claims to reduce the problems of digital reference services in libraries. It uses web services technology to provide efficient way of satisfying users’ needs in the reference section of libraries. The formal WSDRS model consists of the Z specifications of all the informal specifications of the model. This paper discusses the formal validation of the Z specifications of WSDRS model. The authors formally verify and thus validate the properties of the model using Z/EVES theorem prover.

Keywords: validation, verification, formal, theorem prover

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Authors: Thomas James Bell III

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Pedagogy is thought of as one's philosophy, theory, or teaching method. This study examines the science of learning, considering the forced reconsideration of effective pedagogy brought on by the aftermath of the 2020 coronavirus pandemic. With the aid of various technologies, online education holds challenges and promises to enhance the learning environment if implemented to facilitate student learning. Behaviorism centers around the belief that the instructor is the sage on the classroom stage using repetition techniques as the primary learning instrument. This approach to pedagogy ascribes complete control of the learning environment and works best for students to learn by allowing students to answer questions with immediate feedback. Such structured learning reinforcement tends to guide students' learning without considering learners' independence and individual reasoning. And such activities may inadvertently stifle the student's ability to develop critical thinking and self-expression skills. Fundamentally liberationism pedagogy dismisses the concept that education is merely about students learning things and more about the way students learn. Alternatively, the liberationist approach democratizes the classroom by redefining the role of the teacher and student. The teacher is no longer viewed as the sage on the stage but as a guide on the side. Instead, this approach views students as creators of knowledge and not empty vessels to be filled with knowledge. Moreover, students are well suited to decide how best to learn and which areas improvements are needed. This study will explore the classroom instructor as a servant leader in the twenty-first century, which allows students to integrate technology that encapsulates more individual learning styles. The researcher will examine the Professional Scrum Master (PSM I) exam pass rate results of 124 students in six sections of an Agile scrum course. The students will be separated into two groups; the first group will follow a structured instructor-led course outlined by a course syllabus. The second group will consist of several small teams (ten or fewer) of self-led and self-empowered students. The teams will conduct several event meetings that include sprint planning meetings, daily scrums, sprint reviews, and retrospective meetings throughout the semester will the instructor facilitating the teams' activities as needed. The methodology for this study will use the compare means t-test to compare the mean of an exam pass rate in one group to the mean of the second group. A one-tailed test (i.e., less than or greater than) will be used with the null hypothesis, for the difference between the groups in the population will be set to zero. The major findings will expand the pedagogical approach that suggests pedagogy primarily exist in support of teacher-led learning, which has formed the pillars of traditional classroom teaching. But in light of the fourth industrial revolution, there is a fusion of learning platforms across the digital, physical, and biological worlds with disruptive technological advancements in areas such as the Internet of Things (IoT), artificial intelligence (AI), 3D printing, robotics, and others.

Keywords: pedagogy, behaviorism, liberationism, flipping the classroom, servant leader instructor, agile scrum in education

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Authors: Matthew C. Best

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Linear Multi-Input Multi-Output (MIMO) dynamic models can be identified, with no a priori knowledge of model structure or order, using a new Generalised Identifying Filter (GIF). Based on an Extended Kalman Filter, the new filter identifies the model iteratively, in a continuous modal canonical form, using only input and output time histories. The filter’s self-propagating state error covariance matrix allows easy determination of convergence and conditioning, and by progressively increasing model order, the best fitting reduced-order model can be identified. The method is shown to be resistant to noise and can easily be extended to identification of smoothly nonlinear systems.

Keywords: system identification, Kalman filter, linear model, MIMO, model order reduction

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Authors: Tejush Badal, Sanaa Alwidian

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Class diagrams are useful tools within the Unified Modelling Language (UML) to model and visualize the relationships between, and properties of objects within a system. As a system evolves over time and space (e.g., products), a series of models with several commonalities and variabilities create what is known as a model family. In circumstances where there are several versions of a model, examining each model individually, becomes expensive in terms of computation resources. To avoid performing redundant operations, this paper proposes an approach for representing a family of class diagrams into Union Models to represent model families using a single generic model. The paper aims to analyze and reason about a family of class diagrams using union models as opposed to individual analysis of each member model in the family. The union algorithm provides a holistic view of the model family, where the latter cannot be otherwise obtained from an individual analysis approach, this in turn, enhances the analysis performed in terms of speeding up the time needed to analyze a family of models together as opposed to analyzing individual models, one model at a time.

Keywords: analysis, class diagram, model family, unified modeling language, union model

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Authors: D. Thawinkarn, S. Wongbutlee

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The Social Change Leadership model is strongly aligned with administration’s mission. This research aims to examine the elements of social change leadership, build and develop leadership for social change, and evaluate effectiveness of leadership development model for social change. The research operation has 3 phases: model studies by in-depth interviews and survey research; drafting and creating model which verified by the experts; and trial of model in schools. The results showed that administrators and teachers have the elements of leadership for social change in moderate level. These elements are ranged descending from consciousness of self, common purpose, congruence, collaboration, commitment, citizenship, and controversy with civility. Model of leadership for social change is included the principles, objectives, content, process. Workshop process: Results show that the model of leadership development for social change in administrators and teachers leads to higher score in leadership evaluation prior to administering the operation.

Keywords: leadership, social change model, organization, administrators

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Authors: W. Ait Ahmed, M. Aggour, M. Naciri

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Extracting energy from biomass is an important alternative to produce different types of energy (heat, electricity, or both) assuring low pollution and better efficiency. It is a new yet reliable approach to reduce green gas emission by extracting methane from industry effluents and use it to power machinery. We focused in our project on using paper and mill effluents, treated in a UASB reactor. The methane produced is used in the factory’s power supply. The aim of this work is to develop an electronic system using Arduino platform connected to a gas sensor, to measure and display the curve of daily methane production on processing. The sensor will send the gas values in ppm to the Arduino board so that the later sends the RS232 hardware protocol. The code developed with processing will transform the values into a curve and display it on the computer screen.

Keywords: biogas, Arduino, processing, code, methane, gas sensor, program

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Authors: A. Lakrim, D. Tahri

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This paper sets out a behavioral macro-model of a Merged PiN and Schottky (MPS) diode based on silicon carbide (SiC). This model holds good for both static and dynamic electrothermal simulations for industrial applications. Its parameters have been worked out from datasheets curves by drawing on the optimization method: Simulated Annealing (SA) for the SiC MPS diodes made available in the industry. The model also adopts the Analog Behavioral Model (ABM) of PSPICE in which it has been implemented. The thermal behavior of the devices was also taken into consideration by making use of Foster’ canonical network as figured out from electro-thermal measurement provided by the manufacturer of the device.

Keywords: SiC MPS diode, electro-thermal, SPICE model, behavioral macro-model

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Authors: Funda Kul, İsmail Gür

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Pension scheme providers have to price mortality risk by accurate mortality forecasting method. There are many mortality-forecasting methods constructed and used in literature. The Lee-Carter model is the first model to consider stochastic improvement trends in life expectancy. It is still precisely used. Mortality forecasting is done by mortality index in the Lee-Carter model. It is assumed that mortality index fits ARIMA time series model. In this paper, we propose and use dynamic normal inverse gaussian distribution to modeling mortality indes in the Lee-Carter model. Using population mortality data for Italy, France, and Turkey, the model is forecasting capability is investigated, and a comparative analysis with other models is ensured by some well-known benchmarking criterions.

Keywords: mortality, forecasting, lee-carter model, normal inverse gaussian distribution

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Authors: Juan C. Pérez-Mesa, Emilio Galdeano-Gómez, Jerónimo De Burgos-Jiménez, José F. Bienvenido-Bárcena, José F. Jiménez-Guerrero

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Environmental cost and transport congestion on roads resulting from product distribution in Europe have to lead to the creation of various programs and studies seeking to reduce these negative impacts. In this regard, apart from other institutions, the European Commission (EC) has designed plans in recent years promoting a more sustainable transportation model in an attempt to ultimately shift traffic from the road to the sea by using intermodality to achieve a model rebalancing. This issue proves especially relevant in supply chains from peripheral areas of the continent, where the supply of certain agrifood products is high. In such cases, the most difficult challenge is managing perishable goods. This study focuses on new approaches that strengthen the modal shift, as well as the reduction of externalities. This problem is analyzed by attempting to promote intermodal system (truck and short sea shipping) for transport, taking as point of reference highly perishable products (vegetables) exported from southeast Spain, which is the leading supplier to Europe. Methodologically, this paper seeks to contribute to the literature by proposing a different and complementary approach to establish a comparison between intermodal and the “only road” alternative. For this purpose, the multicriteria decision is utilized in a p-median model (P-M) adapted to the transport of perishables and to a means of shipping selection problem, which must consider different variables: transit cost, including externalities, time, and frequency (including agile response time). This scheme avoids bias in decision-making processes. By observing the results, it can be seen that the influence of the externalities as drivers of the modal shift is reduced when transit time is introduced as a decision variable. These findings confirm that the general strategies, those of the EC, based on environmental benefits lose their capacity for implementation when they are applied to complex circumstances. In general, the different estimations reveal that, in the case of perishables, intermodality would be a secondary and viable option only for very specific destinations (for example, Hamburg and nearby locations, the area of influence of London, Paris, and the Netherlands). Based on this framework, the general outlook on this subject should be modified. Perhaps the government should promote specific business strategies based on new trends in the supply chain, not only on the reduction of externalities, and find new approaches that strengthen the modal shift. A possible option is to redefine ports, conceptualizing them as digitalized redistribution and coordination centers and not only as areas of cargo exchange.

Keywords: environmental externalities, intermodal transport, perishable food, transit time

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Authors: Piotr Fiszeder, Marcin Fałdziński, Peter Molnár

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The dynamic conditional correlation model of Engle (2002) is one of the most popular multivariate volatility models. However, this model is based solely on closing prices. It has been documented in the literature that the high and low price of the day can be used in an efficient volatility estimation. We, therefore, suggest a model which incorporates high and low prices into the dynamic conditional correlation framework. Empirical evaluation of this model is conducted on three datasets: currencies, stocks, and commodity exchange-traded funds. The utilisation of realized variances and covariances as proxies for true variances and covariances allows us to reach a strong conclusion that our model outperforms not only the standard dynamic conditional correlation model but also a competing range-based dynamic conditional correlation model.

Keywords: volatility, DCC model, high and low prices, range-based models, covariance forecasting

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Authors: C. Shih, J. R. Wang, H. C. Chang, S. W. Chen, S. C. Chiang, T. Y. Yu

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After the measurement uncertainty recapture (MUR) power uprates, Kuosheng nuclear power plant (NPP) was uprated the power from 2894 MWt to 2943 MWt. For power upgrade, several codes (e.g., TRACE, RELAP5, etc.) were applied to assess the safety of Kuosheng NPP. Hence, the main work of this research is to establish a RELAP5/MOD3.3 model of Kuosheng NPP with SNAP interface. The establishment of RELAP5/SNAP model was referred to the FSAR, training documents, and TRACE model which has been developed and verified before. After completing the model establishment, the startup test scenarios would be applied to the RELAP5/SNAP model. With comparing the startup test data and TRACE analysis results, the applicability of RELAP5/SNAP model would be assessed.

Keywords: RELAP5, TRACE, SNAP, BWR

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Authors: Ming Luo

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In this real world, a manufacturer may produce more than one product. The products produced by the same manufacturer may share the same type of parts, similar design, and be produced in the same factory, i.e. some common causes. From the perspective of warranty management, the frequencies of those products’ warranty claims may have statistical dependence caused by the common causes. Warranty policy optimisation in the existing research, majorly, has not considered such dependence, which may increase bias in decision making. In the market, renewing warranty policies are provided to some unrepairable products and consumer electronic products. This paper optimises the renewing warranty policy collectively in a multi-product scenario with a consideration of the dependence among the warranty claims of the products produced by the same manufacturer. The existence of the optimal solution is proved. Numerical examples are used to validate the applicability of the proposed methods.

Keywords: mean-risk framework, modern portfolio theory, renewing warranty policy, warranty policy optimisation

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Authors: Hoda Ghavamipoor, S. Alireza Hashemi Golpayegani

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An approach to model the customer interaction with e-commerce websites is presented. Considering the service quality level as a predictive feature, we offer an improved method based on the Customer Behavior Model Graph (CBMG), a state-transition graph model. To derive the Quality of Service sensitive-CBMG (QoS-CBMG) model, process-mining techniques is applied to pre-processed website server logs which are categorized as ‘buy’ or ‘visit’. Experimental results on an e-commerce website data confirmed that the proposed method outperforms CBMG based method.

Keywords: customer behavior model, electronic commerce, quality of service, customer behavior model graph, process mining

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