Search results for: spatial autoregression model

Authors: Juan C. Domínguez, Belén Del Saz-Orozco, María V. Alonso, Mercedes Oliet, Francisco Rodríguez

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In the present study, the kinetics of thermal degradation of a phenolic and lignin reinforced phenolic foams, and the lignin used as reinforcement were studied and the activation energies of their degradation processes were obtained by a DAEM model. The average values for five heating rates of the mean activation energies obtained were: 99.1, 128.2, and 144.0 kJ.mol-1 for the phenolic foam, 109.5, 113.3, and 153.0 kJ.mol-1 for the lignin reinforcement, and 82.1, 106.9, and 124.4 kJ. mol-1 for the lignin reinforced phenolic foam. The standard deviation ranges calculated for each sample were 1.27-8.85, 2.22-12.82, and 3.17-8.11 kJ.mol-1 for the phenolic foam, lignin and the reinforced foam, respectively. The DAEM model showed low mean square errors (< 1x10-5), proving that is a suitable model to study the kinetics of thermal degradation of the foams and the reinforcement.

Keywords: kinetics, lignin, phenolic foam, thermal degradation

Procedia PDF Downloads 479

Authors: Fabiana Lucena Oliveira, Aristides da Rocha Oliveira Junior

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This article discusses the dependence on air transport mode of agile supply chains. The agile supply chains are the result of the analysis of the uncertainty supply chain model, which ranks the supply chain, according to the respective product. Thus, understanding the Uncertainty Model and life cycle of products considered standard and innovative is critical to understanding these. The innovative character in the intersection of supply chains arising from the uncertainty model with its most appropriate transport mode. Consider here the variables availability, security and freight as determinants for choosing these modes. Therefore, the research problem is: How agile supply chains maintains logistics competitiveness, as these are dependent on air transport mode? A case study in Manaus Industrial Pole (MIP), an agglomeration model that includes six hundred industries from different backgrounds and billings, located in the Brazilian Amazon. The sample of companies surveyed include those companies whose products are classified in agile supply chains , as innovative and therefore live with the variable uncertainty in the demand for inputs or the supply of finished products. The results confirm the hypothesis that the dependency level of air transport mode is greater than fifty percent. It follows then, that maintain agile supply chain away from suppliers base is expensive (1) , and continuity analysis needs to be remade on each twenty four months (2) , consider that additional freight, handling and storage as members of the logistics costs (3) , and the comparison with the upcoming agile supply chains the world need to consider the location effect (4).

Keywords: uncertainty model, air transport mode, competitiveness, logistics

Procedia PDF Downloads 502

Authors: Zahira Anane, Abdelhafid Bayadi

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Corona in the HV overhead transmission lines is an important source of attenuation and distortion of overvoltage surges. This phenomenon of distortion, which is superimposed on the distortion by skin effect, is due to the dissipation of energy by injection of space charges around the conductor, this process with place as soon as the instantaneous voltage exceeds the threshold voltage of the corona effect conductors. This paper presents a mathematical model to determine the corona inception voltage, the critical electric field and the corona radius, to predict the capacitive changes at conductor of transmission line due to corona. This model has been incorporated into the Alternative Transients Program version of the Electromagnetic Transients Program (ATP/EMTP) as a user defined component, using the MODELS interface with NORTON TYPE94 of this program and using the foreign subroutine. For obtained the displacement of corona charge hell, dichotomy mathematical method is used for this computation. The present corona model can be used for computing of distortion and attenuation of transient overvoltage waves being propagated in a transmission line of the very high voltage electric power.

Keywords: high voltage, corona, Type94 NORTON, dichotomy, ATP/EMTP, MODELS, distortion, foreign model

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Authors: Christian Rathgeber, Franz Winkler, Xiaoyu Kang, Steffen Müller

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In this contribution two approaches for calculating optimal trajectories for highly automated vehicles are presented and compared. The first one is based on a non-linear vehicle model, used for evaluation. The second one is based on a simplified model and can be implemented on a current ECU. In usual driving situations both approaches show very similar results.

Keywords: trajectory planning, direct method, indirect method, highly automated driving

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Authors: A. Hocine, A. Ghouaoula, S. M. Medjdoub, M. Cherifi

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The present paper proposed a meso–macro model describing the mechanical behaviour composite laminates of staking sequence [+θ/-θ]s under tensil loading. The behaviour of a layer is ex-pressed through elasticity coupled to damage. The elastic strain is due to the elasticity of the layer and can be modeled by using the classical laminate theory, and the laminate is considered as an orthotropic material. This means that no coupling effect between strain and curvature is considered. In the present work, the damage is associated to cracking of the matrix and parallel to the fibers and it being taken into account by the changes in the stiffness of the layers. The anisotropic damage is completely described by a single scalar variable and its evolution law is specified from the principle of maximum dissipation. The stress/strain relationship is investigated in plane stress loading.

Keywords: damage, behavior modeling, meso-macro model, composite laminate, membrane loading

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Authors: Gustavo Cruz-Bello

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Progreso is a coastal community in Yucatan, Mexico, highly exposed to floods produced by severe storms and tropical cyclones. A participatory cartography approach was conducted to help to reduce floods disasters and assess social vulnerability within the community. The first step was to engage local authorities in risk management to facilitate the process. Two workshop were conducted, in the first, a poster size printed high spatial resolution satellite image of the town was used to gather information from the participants: eight women and seven men, among them construction workers, students, government employees and fishermen, their ages ranged between 23 and 58 years old. For the first task, participants were asked to locate emblematic places and place them in the image to familiarize with it. Then, they were asked to locate areas that get flooded, the buildings that they use as refuges, and to list actions that they usually take to reduce vulnerability, as well as to collectively come up with others that might reduce disasters. The spatial information generated at the workshops was digitized and integrated into a GIS environment. A printed version of the map was reviewed by local risk management experts, who validated feasibility of proposed actions. For the second workshop, we retrieved the information back to the community for feedback. Additionally a survey was applied in one household per block in the community to obtain socioeconomic, prevention and adaptation data. The information generated from the workshops was contrasted, through T and Chi Squared tests, with the survey data in order to probe the hypothesis that poorer or less educated people, are less prepared to face floods (more vulnerable) and live near or among higher presence of floods. Results showed that a great majority of people in the community are aware of the hazard and are prepared to face it. However, there was not a consistent relationship between regularly flooded areas with people’s average years of education, house services, or house modifications against heavy rains to be prepared to hazards. We could say that the participatory cartography intervention made participants aware of their vulnerability and made them collectively reflect about actions that can reduce disasters produced by floods. They also considered that the final map could be used as a communication and negotiation instrument with NGO and government authorities. It was not found that poorer and less educated people are located in areas with higher presence of floods.

Keywords: climate change, floods, Mexico, participatory mapping, social vulnerability

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Authors: R. Hellmuth, F. Wehner

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Factory planning has the task of designing products, plants, processes, organization, areas, and the construction of a factory. The requirements for factory planning and the building of a factory have changed in recent years. Regular restructuring is becoming more important in order to maintain the competitiveness of a factory. Restrictions in new areas, shorter life cycles of product and production technology as well as a VUCA world (Volatility, Uncertainty, Complexity & Ambiguity) lead to more frequent restructuring measures within a factory. A digital factory model is the planning basis for rebuilding measures and becomes an indispensable tool. Short-term rescheduling can no longer be handled by on-site inspections and manual measurements. The tight time schedules require up-to-date planning models. Due to the high adaptation rate of factories described above, a methodology for rescheduling factories on the basis of a modern digital factory twin is conceived and designed for practical application in factory restructuring projects. The focus is on rebuild processes. The aim is to keep the planning basis (digital factory model) for conversions within a factory up to date. This requires the application of a methodology that reduces the deficits of existing approaches. The aim is to show how a digital factory model can be kept up to date during ongoing factory operation. A method based on photogrammetry technology is presented. The focus is on developing a simple and cost-effective solution to track the many changes that occur in a factory building during operation. The method is preceded by a hardware and software comparison to identify the most economical and fastest variant. 

Keywords: digital factory model, photogrammetry, factory planning, restructuring

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Authors: Juhan Kim, Jinsoo Kim

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South Korea cannot import natural gas in any form other than LNG because of the division of South and North Korea. Further, the high proportion of natural gas in the national energy mix makes this resource crucial for energy security in Korea. Expansion of Panama Canal will allow for reducing the cost of shipping between the Far East and U.S East. Panama Canal expansion can have significant impacts on South Korea. Due to this situation, we review the natural gas optimal portfolio by considering the uniqueness of the Korean Natural gas market and expansion of Panama Canal. In order to assess Korea’s natural gas optimal portfolio, we developed natural gas portfolio model. The model comprises two steps. First, to obtain the optimal long-term spot contract ratio, the study examines the price level and the correlation between spot and long-term contracts by using the Markowitz, portfolio model. The optimal long-term spot contract ratio follows the efficient frontier of the cost/risk level related to this price level and degree of correlation. Second, by applying the obtained long-term contract purchase ratio as the constraint in the linear programming portfolio model, we determined the natural gas optimal import portfolio that minimizes total intangible and tangible costs. Using this model, we derived the optimal natural gas portfolio considering the expansion of Panama Canal. Based on these results, we assess the portfolio for natural gas import to Korea from the perspective of energy security and present some relevant policy proposals.

Keywords: natural gas, Panama Canal, portfolio analysis, South Korea

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Authors: Bader Eddin Al Asali, N. Srinivasa Reddy

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Cities are dynamic in nature and are characterized by concentration of people, infrastructure, services and markets, which offer opportunities for production and consumption. Often growth and development in urban areas is not systematic, and is directed by number of factors like natural growth, land prices, housing availability, job locations-the central business district (CBD’s), transportation routes, distribution of resources, geographical boundaries, administrative policies, etc. One sided spatial and geographical development in cities leads to the unequal spatial distribution of population and jobs, resulting in high transportation activity. City development can be measured by the parameters such as urban size, urban form, urban shape, and urban structure. Urban Size is the city size and defined by the population of the city, and urban form is the location and size of the economic activity (CBD) over the geographical space. Urban shape is the geometrical shape of the city over which the distribution of population and economic activity occupied. And Urban Structure is the transport network within which the population and activity centers are connected by hierarchy of roads. Among the urban land-use systems transportation plays significant role and is one of the largest energy consuming sector. Transportation interaction among the land uses is measured in Passenger-Km and mean trip length, and is often used as a proxy for measurement of energy consumption in transportation sector. Among the trips generated in cities, work trips constitute more than 70 percent. Work trips are originated from the place of residence and destination to the place of employment. To understand the role of urban parameters on transportation interaction, theoretical cities of different size and urban specifications are generated through building block exercise using a specially developed interactive C++ programme and land use transportation modeling is carried. The land-use transportation modeling exercise helps in understanding the role of urban parameters and also to classify the cities for their urban form, structure, and shape. Muscat the capital city of Oman underwent rapid urbanization over the last four decades is taken as a case study for its classification. Also, a pilot survey is carried to capture urban travel characteristics. Analysis of land-use transportation modeling with field data classified Muscat as a linear city with polycentric CBD. Conclusions are drawn suggestion are given for policy making for the sustainability of Muscat City.

Keywords: land-use transportation, transportation modeling urban form, urban structure, urban rule parameters

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Authors: Shubham Bhonde, Nekzad Doctor, Shashwat Gawande

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For the use and the import of Keys and ID Transmitter as well as Body Control Modules with radio transmission in a lot of countries, homologation is required. Final deliverables in homologation of the product are certificates. In considering the world of homologation, there are approximately 200 certificates per product, with most of the certificates in local languages. It is challenging to manually investigate each certificate and extract relevant data from the certificate, such as expiry date, approval date, etc. It is most important to get accurate data from the certificate as inaccuracy may lead to missing re-homologation of certificates that will result in an incompliance situation. There is a scope of automation in reading the certificate data in the field of homologation. We are using deep learning as a tool for automation. We have first trained a model using machine learning by providing all country's basic data. We have trained this model only once. We trained the model by feeding pdf and jpg files using the ETL process. Eventually, that trained model will give more accurate results later. As an outcome, we will get the expiry date and approval date of the certificate with a single click. This will eventually help to implement automation features on a broader level in the database where certificates are stored. This automation will help to minimize human error to almost negligible.

Keywords: homologation, re-homologation, data science, deep learning, machine learning, ETL (extract transform loading)

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Authors: Shokoufeh Abrisham, Seyed Mahmoud Hossieni, Elham Pishbin

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In this paper, a hybrid method based on the fault tree analysis (FTA) and Bayesian networks (BNs) are employed to evaluate the team performance quality of advanced cardiac life support (ACLS) procedures in emergency department. According to American Heart Association (AHA) guidelines, a category relying on staff action leading to clinical incidents and also some discussions with emergency medicine experts, a fault tree model for ACLS procedure is obtained based on the human performance. The obtained FTA model is converted into BNs, and some different scenarios are defined to demonstrate the efficiency and flexibility of the presented model of BNs. Also, a sensitivity analysis is conducted to indicate the effects of team leader presence and uncertainty knowledge of experts on the quality of ACLS. The proposed model based on BNs shows that how the results of risk analysis can be closed to reality comparing to the obtained results based on only FTA in medical procedures.

Keywords: advanced cardiac life support, fault tree analysis, Bayesian belief networks, numan performance, healthcare systems

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Authors: Nazia Muhsin, Tofael Ahamed, Ryozo Noguchi, Tomohiro Takigawa

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One of the most challenging issues to achieve sustainable development on food security is land use changes. The crisis of lands for agricultural production mainly arises from the unplanned transformation of agricultural lands to infrastructure development i.e. urbanization and industrialization. Land use without sustainability assessment could have impact on the food security and environmental protections. Bangladesh, as the densely populated country with limited arable lands is now facing challenges to meet sustainable food security. Agricultural lands are using for economic growth by establishing industries. The industries are spreading from urban areas to the suburban areas and using the agricultural lands. To minimize the agricultural land losses for unplanned industrialization, compact economic zones should be find out in a scientific approach. Therefore, the purpose of the study was to find out suitable sites for industrial growth by land suitability analysis (LSA) by using Geographical Information System (GIS) and multi-criteria analysis (MCA). The goal of the study was to emphases both agricultural lands and industries for sustainable development in land use. The study also attempted to analysis the agricultural land use changes in a suburban area by statistical data of agricultural lands and primary data of the existing industries of the study place. The criteria were selected as proximity to major roads, and proximity to local roads, distant to rivers, waterbodies, settlements, flood-flow zones, agricultural lands for the LSA. The spatial dataset for the criteria were collected from the respective departments of Bangladesh. In addition, the elevation spatial dataset were used from the SRTM (Shuttle Radar Topography Mission) data source. The criteria were further analyzed with factors and constraints in ArcGIS®. Expert’s opinion were applied for weighting the criteria according to the analytical hierarchy process (AHP), a multi-criteria technique. The decision rule was set by using ‘weighted overlay’ tool to aggregate the factors and constraints with the weights of the criteria. The LSA found only 5% of land was most suitable for industrial sites and few compact lands for industrial zones. The developed LSA are expected to help policy makers of land use and urban developers to ensure the sustainability of land uses and agricultural production.

Keywords: AHP (analytical hierarchy process), GIS (geographic information system), LSA (land suitability analysis), MCA (multi-criteria analysis)

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Authors: Mohammad Anwar, Shah Waliullah

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This study investigated panel data regression models. This paper used Bayesian and classical methods to study the impact of institutions on economic growth from data (1990-2014), especially in developing countries. Under the classical and Bayesian methodology, the two-panel data models were estimated, which are common effects and fixed effects. For the Bayesian approach, the prior information is used in this paper, and normal gamma prior is used for the panel data models. The analysis was done through WinBUGS14 software. The estimated results of the study showed that panel data models are valid models in Bayesian methodology. In the Bayesian approach, the effects of all independent variables were positively and significantly affected by the dependent variables. Based on the standard errors of all models, we must say that the fixed effect model is the best model in the Bayesian estimation of panel data models. Also, it was proved that the fixed effect model has the lowest value of standard error, as compared to other models.

Keywords: Bayesian approach, common effect, fixed effect, random effect, Dynamic Random Effect Model

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Authors: Theresia El Khoury, Georges Badr, Amir Hajjam El Hassani, Stéphane N’Guyen Van Ky

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The widespread adoption of machine learning and artificial intelligence across different domains can be attributed to the digitization of data over several decades, resulting in vast amounts of data, types, and structures. Thus, data processing and preparation turn out to be a crucial stage. However, applying these techniques to S1000D standard-based data poses a challenge due to its complexity and the need to preserve logical information. This paper describes SALERNO, an S1000d AppLicability dEpended pRocessiNg mOdel. This python-based model analyzes and converts the XML S1000D-based files into an easier data format that can be used in machine learning techniques while preserving the different logic and relationships in files. The model parses the files in the given folder, filters them, and extracts the required information to be saved in appropriate data frames and Excel sheets. Its main idea is to group the extracted information by applicability. In addition, it extracts the full text by replacing internal and external references while maintaining the relationships between files, as well as the necessary requirements. The resulting files can then be saved in databases and used in different models. Documents in both English and French languages were tested, and special characters were decoded. Updates on the technical manuals were taken into consideration as well. The model was tested on different versions of the S1000D, and the results demonstrated its ability to effectively handle the applicability, requirements, references, and relationships across all files and on different levels.

Keywords: aeronautics, big data, data processing, machine learning, S1000D

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Authors: Yifu Ding, Vijay Avinash, Malcolm McCulloch

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As the proliferation of decentralized energy systems, the UK power system allows small-scale entities such as microgrids (MGs) to tender multiple energy services including energy arbitrage and frequency responses (FRs). However, its operation requires the balance between the uncertain renewable generations and loads in real-time and has to fulfill their provision requirements of contract services continuously during the time window agreed, otherwise it will be penalized for the under-delivered provision. To hedge against risks due to uncertainties and maximize the economic benefits, we propose a stochastic model predictive control (SMPC) framework to optimize its operation for the multi-service provision. Distinguished from previous works, we include a detailed economic-degradation model of the lithium-ion battery to quantify the costs of different service provisions, as well as accurately describe the changing dynamics of the battery. Considering a branch of load and generation scenarios and the battery aging, we formulate a risk-averse cost function using conditional value at risk (CVaR). It aims to achieve the maximum expected net revenue and avoids severe losses. The framework will be performed on a case study of a PV-battery grid-tied microgrid in the UK with real-life data. To highlight its performance, the framework will be compared with the case without the degradation model and the deterministic formulation.

Keywords: model predictive control (MPC), battery degradation, frequency response, microgrids

Procedia PDF Downloads 117

Authors: Gianpaolo Ghiani, Emanuela Guerriero, Emanuele Manni, Alessandro Romano

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In this article, we deal with a variant of the classical course timetabling problem that has a practical application in many areas of education. In particular, in this paper we are interested in high schools remedial courses. The purpose of such courses is to provide under-prepared students with the skills necessary to succeed in their studies. In particular, a student might be under prepared in an entire course, or only in a part of it. The limited availability of funds, as well as the limited amount of time and teachers at disposal, often requires schools to choose which courses and/or which teaching units to activate. Thus, schools need to model the training offer and the related timetabling, with the goal of ensuring the highest possible teaching quality, by meeting the above-mentioned financial, time and resources constraints. Moreover, there are some prerequisites between the teaching units that must be satisfied. We first present a Mixed-Integer Programming (MIP) model to solve this problem to optimality. However, the presence of many peculiar constraints contributes inevitably in increasing the complexity of the mathematical model. Thus, solving it through a general purpose solver may be performed for small instances only, while solving real-life-sized instances of such model requires specific techniques or heuristic approaches. For this purpose, we also propose a heuristic approach, in which we make use of a fast constructive procedure to obtain a feasible solution. To assess our exact and heuristic approaches we perform extensive computational results on both real-life instances (obtained from a high school in Lecce, Italy) and randomly generated instances. Our tests show that the MIP model is never solved to optimality, with an average optimality gap of 57%. On the other hand, the heuristic algorithm is much faster (in about the 50% of the considered instances it converges in approximately half of the time limit) and in many cases allows achieving an improvement on the objective function value obtained by the MIP model. Such an improvement ranges between 18% and 66%.

Keywords: heuristic, MIP model, remedial course, school, timetabling

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Authors: Bansal Ashwani

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Cartographic depiction and visualization of wetland changes is an important tool to map spatial-temporal information about the wetland dynamics effectively and to comprehend the response of these water bodies in maintaining the groundwater and surrounding ecosystem. This is true for the states of North Western India, i.e., J&K, Himachal, Punjab, and Haryana that are bestowed upon with several natural wetlands in the flood plains or on the courses of its rivers. Thus, the present study documents, analyses and reconstructs the lost wetlands, which existed in the flood plains of the major river basins of these states, i.e., Chenab, Jhelum, Satluj, Beas, Ravi, and Ghagar, in the beginning of the 20th century. To achieve the objective, the study has used multi-temporal datasets since the 1960s using high to medium resolution satellite datasets, e.g., Corona (1960s/70s), Landsat (1990s-2017) and Sentinel (2017). The Sentinel (2017) satellite image has been used for making the wetland inventory owing to its comparatively higher spatial resolution with multi-spectral bands. In addition, historical records, repeated photographs, historical maps, field observations including geomorphological evidence were also used. The water index techniques, i.e., band rationing, normalized difference water index (NDWI), modified NDWI (MNDWI) have been compared and used to map the wetlands. The wetland types found in the north-western states have been categorized under 19 classes suggested by Space Application Centre, India. These enable the researcher to provide with the wetlands inventory and a series of cartographic representation that includes overlaying multiple temporal wetlands extent vectors. A preliminary result shows the general state of wetland shrinkage since the 1960s with varying area shrinkage rate from one wetland to another. In addition, it is observed that majority of wetlands have not been documented so far and even do not have names. Moreover, the purpose is to emphasize their elimination in addition to establishing a baseline dataset that can be a tool for wetland planning and management. Finally, the applicability of cartographic depiction and visualization, historical map sources, repeated photographs and remote sensing data for reconstruction of long term wetlands fluctuations, especially in the northern part of India, will be addressed.

Keywords: cartographic depiction and visualization, wetland changes, NDWI/MDWI, geomorphological evidence and remote sensing

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Authors: M. Ahmadi, Sh. Damanabi, F. Sadoughi

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National Health Information System plays an important role in ensuring timely and reliable access to Health information which is essential for strategic and operational decisions that improve health, quality and effectiveness of health care. In other words, by using the National Health information system you can improve the quality of health data, information and knowledge used to support decision making at all levels and areas of the health sector. Since full identification of the components of this system for better planning and management influential factors of performance seems necessary, therefore, in this study, different attitudes towards components of this system are explored comparatively. Methods: This is a descriptive and comparative kind of study. The society includes printed and electronic documents containing components of the national health information system in three parts: input, process, and output. In this context, search for information using library resources and internet search were conducted and data analysis was expressed using comparative tables and qualitative data. Results: The findings showed that there are three different perspectives presenting the components of national health information system, Lippeveld, Sauerborn, and Bodart Model in 2000, Health Metrics Network (HMN) model from World Health Organization in 2008 and Gattini’s 2009 model. All three models outlined above in the input (resources and structure) require components of management and leadership, planning and design programs, supply of staff, software and hardware facilities, and equipment. In addition, in the ‘process’ section from three models, we pointed up the actions ensuring the quality of health information system and in output section, except Lippeveld Model, two other models consider information products, usage and distribution of information as components of the national health information system. Conclusion: The results showed that all the three models have had a brief discussion about the components of health information in input section. However, Lippeveld model has overlooked the components of national health information in process and output sections. Therefore, it seems that the health measurement model of network has a comprehensive presentation for the components of health system in all three sections-input, process, and output.

Keywords: National Health Information System, components of the NHIS, Lippeveld Model

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Authors: Ginger Egberts, Fred Vermolen, Paul van Zuijlen

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One of the common complications in post-burn scars is contractions. Depending on the extent of contraction and the wound dimensions, the contracture can cause a limited range-of-motion of joints. A one-dimensional morphoelastic continuum hypothesis-based model describing post-burn scar contractions is considered. The beauty of the one-dimensional model is the speed; hence it quickly yields new results and, therefore, insight. This model describes the movement of the skin and the development of the strain present. Besides these mechanical components, the model also contains chemical components that play a major role in the wound healing process. These components are fibroblasts, myofibroblasts, the so-called signaling molecules, and collagen. The dermal layer is modeled as an isotropic morphoelastic solid, and pulling forces are generated by myofibroblasts. The solution to the model equations is approximated by the finite-element method using linear basis functions. One of the major challenges in biomechanical modeling is the estimation of parameter values. Therefore, this study provides a comprehensive description of skin mechanical parameter values and a sensitivity analysis. Further, since skin mechanical properties change with aging, it is important that the model is feasible for predicting the development of contraction in burn patients of different ages, and hence this study provides a feasibility study. The variability in the solutions is caused by varying the values for some parameters simultaneously over the domain of computation, for which the results of the sensitivity analysis are used. The sensitivity analysis shows that the most sensitive parameters are the equilibrium concentration of collagen, the apoptosis rate of fibroblasts and myofibroblasts, and the secretion rate of signaling molecules. This suggests that most of the variability in the evolution of contraction in burns in patients of different ages might be caused mostly by the decreasing equilibrium of collagen concentration. As expected, the feasibility study shows this model can be used to show distinct extents of contractions in burns in patients of different ages. Nevertheless, contraction formation in children differs from contraction formation in adults because of the growth. This factor has not been incorporated in the model yet, and therefore the feasibility results for children differ from what is seen in the clinic.

Keywords: biomechanics, burns, feasibility, fibroblasts, morphoelasticity, sensitivity analysis, skin mechanics, wound contraction

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Authors: Jiahui Yang, John Quigley, Lesley Walls

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In this paper, the authors develop a stochastic model regarding the investment in supplier delivery performance development from a buyer’s perspective. The authors propose a multivariate model through a Multinomial-Dirichlet distribution within an Empirical Bayesian inference framework, representing both the epistemic and aleatory uncertainties in deliveries. A closed form solution is obtained and the lower and upper bound for both optimal investment level and expected profit under uncertainty are derived. The theoretical properties provide decision makers with useful insights regarding supplier delivery performance improvement problems where multiple delivery statuses are involved. The authors also extend the model from a single supplier investment into a supplier portfolio, using a Lagrangian method to obtain a theoretical expression for an optimal investment level and overall expected profit. The model enables a buyer to know how the marginal expected profit/investment level of each supplier changes with respect to the budget and which supplier should be invested in when additional budget is available. An application of this model is illustrated in a simulation study. Overall, the main contribution of this study is to provide an optimal investment decision making framework for supplier development, taking into account multiple delivery statuses as well as multiple projects.

Keywords: decision making, empirical bayesian, portfolio optimization, supplier development, supply chain management

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Authors: Mojahid F. Saeed Osman

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Repairable items inventory system is a management tool used to incorporate all information concerning inventory levels and movements for repaired and new items. This paper presents development of an effective simulation model for managing the inventory of repairable items for a production system where production lines send their faulty items to a repair shop considering the stochastic failure behavior and repair times. The developed model imitates the process of handling the on-hand inventory of repaired items and the replenishment of the inventory of new items using Economic Order Quantity and Reorder Point ordering policy in a flexible and risk-free environment. We demonstrate the appropriateness and effectiveness of the proposed simulation model using an illustrative case problem. The developed simulation model can be used as a reliable tool for estimating a healthy on-hand inventory of new and repaired items, backordered items, and downtime due to unavailability of repaired items, and validating and examining Economic Order Quantity and Reorder Point ordering policy, which would further be compared with other ordering strategies as future work.

Keywords: inventory system, repairable items, simulation, maintenance, economic order quantity, reorder point

Procedia PDF Downloads 136

Authors: Mohamed Bendahmane, Brahim Elfalaki, Mohammed Benattou

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One of the major sources of learners' professional difficulties is their heterogeneity. Whether on cognitive, social, cultural or emotional level, learners being part of the same group have many differences. These differences do not allow to apply the same learning process at all learners. Thus, an optimal learning path for one, is not necessarily the same for the other. We present in this paper a model-oriented service to offer to each learner a personalized learning path to acquire the targeted skills.

Keywords: learning path, web service, trace analysis, personalization

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Authors: Adel Francis

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Most of scheduling methods and software apply the critical path logic. This logic schedule activities, apply constraints between these activities and try to optimize and level the allocated resources. The extensive use of this logic produces a complex an erroneous network hard to present, follow and update. Planning and management building projects should tackle the coordination of works and the management of limited spaces, traffic, and supplies. Activities cannot be performed without the resources available and resources cannot be used beyond the capacity of workplaces. Otherwise, workspace congestion will negatively affect the flow of works. The objective of the space planning is to link the spatial and temporal aspects, promote efficient use of the site, define optimal site occupancy rates, and ensures suitable rotation of the workforce in the different spaces. The Chronographic scheduling modelling belongs to this category and models construction operations as well as their processes, logical constraints, association and organizational models, which help to better illustrate the schedule information using multiple flexible approaches. The model defined three categories of areas (punctual, surface and linear) and four different layers (space creation, systems, closing off space, finishing, and reduction of space). The Chronographical modelling is a more complete communication method, having the ability to alternate from one visual approach to another by manipulation of graphics via a set of parameters and their associated values. Each individual approach can help to schedule a certain project type or specialty. Visual communication can also be improved through layering, sheeting, juxtaposition, alterations, and permutations, allowing for groupings, hierarchies, and classification of project information. In this way, graphic representation becomes a living, transformable image, showing valuable information in a clear and comprehensible manner, simplifying the site management while simultaneously utilizing the visual space as efficiently as possible.

Keywords: building projects, chronographic modelling, CPM, critical path, precedence diagram, scheduling

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Authors: Ahmad Aslizadeh, Farid Ghaderi

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Mapping organizational knowledge is an innovative concept and useful instrument of representation, capturing and visualization of implicit and explicit knowledge. There are a diversity of methods, instruments and techniques presented by different researchers following mapping organizational knowledge to reach determined goals. Implicating of these methods, it is necessary to know their exigencies and conditions in which those can be used. Integrating identified methods of knowledge mapping and comparing them would help knowledge managers to select the appropriate methods. This research conducted to presenting a model and framework to map organizational knowledge. At first, knowledge maps, their applications and necessity are introduced because of extracting comparative framework and detection of their structure. At the next step techniques of researchers such as Eppler, Kim, Egbu, Tandukar and Ebner as knowledge mapping models are presented and surveyed. Finally, they compare and a superior model would be introduced.

Keywords: knowledge mapping, knowledge management, comparative study, business and management

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Authors: Rattakorn Poonsuph

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Technological innovation plays a crucial role in virtual healthcare services. A growing number of telehealth platforms are concentrating on using digital tools to improve the quality and availability of care. As a result, telehealth represents an opportunity to redesign the way health services are delivered. The research objective is to discover a new business model for digital health services and related industries to participate with telehealth solutions. The business opportunity is valuable for healthcare investors as a startup company to further investigations or implement the telehealth platform. The paper presents a digital healthcare business model and business opportunities to related industries. These include digital healthcare services extending from a traditional business model and use cases of business opportunities to related industries. Although there are enormous business opportunities, telehealth is still challenging due to the patient adaption and digital transformation process within a healthcare organization.

Keywords: telehealth, Internet hospital, HealthTech, InsurTech

Procedia PDF Downloads 164

Authors: Kamal Agrawal, Ved Prakash Nayak, Akshay Patil

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Raipur is known as a city of water bodies. The city had around 200 man-made and natural lakes of varying sizes. These structures were constructed to collect rainwater and control flooding in the city. Due to the transition from community participation to state government, as well as rapid urbanisation, Raipur now has only about 80 lakes left. Rapid and unplanned growth has resulted in pollution, encroachment, and eutrophication of the city's lakes. The state government keeps these lakes in good condition by cleaning them and proposing lakefront developments. However, maintaining individual lakes is insufficient because urban lakes are not distinct entities. It is a system comprised of the lake, shore, catchment, and other components. While Urban lake system (ULS) is a combination of multiple such lake systems interacting in a complex urban setting. Thus, the project aims to propose a co-evolution model for urban lake systems (ULS) and rapid urbanization in Raipur. The goals are to comprehend the ULS and to identify elements and dimensions of urbanization that influence the ULS. Evaluate the impact of rapid urbanization on the ULS & vice versa in the study area. Determine how to maximize the positive impact while minimizing the negative impact identified in the study area. Propose short-, medium-, and long-term planning interventions to support the ULS's co-evolution with rapid urbanization. A complexity approach is used to investigate the ULS. It is a technique for understanding large, complex systems. A complex system is one with many interconnected and interdependent elements and dimensions. Thus, elements of ULS and rapid urbanization are identified through a literature study to evaluate statements of their impacts (Beneficial/ Adverse) on one another. Rapid urbanization has been identified as having elements such as demography, urban legislation, informal settlement, urban infrastructure, and tourism. Similarly, the catchment area of the lake, the lake's water quality, the water spread area, and lakefront developments are all being impacted by rapid urbanisation. These nine elements serve as parameters for the subsequent analysis. Elements are limited to physical parameters only. The city has designated a study area based on the definition provided by the National Plan for the Conservation of Aquatic Ecosystems. Three lakes are discovered within a one-kilometer radius, establishing a tiny urban lake system. Because the condition of a lake is directly related to the condition of its catchment area, the catchment area of these three lakes is delineated as the study area. Data is collected to identify impact statements, and the interdependence diagram generated between the parameters yields results in terms of interlinking between each parameter and their impact on the system as a whole. The planning interventions proposed for the ULS and rapid urbanisation co-evolution model include spatial proposals as well as policy recommendations for the short, medium, and long term. This study's next step will be to determine how to implement the proposed interventions based on the availability of resources, funds, and governance patterns.

Keywords: urban lake system, co-evolution, rapid urbanization, complex system

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Authors: Nureni O. Adeboye, Dawud A. Agunbiade

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This research attempts to investigate the effects of heteroscedasticity and periodicity in a Panel Data Regression Model (PDRM) by extending previous works on balanced panel data estimation within the context of fitting PDRM for Banks audit fee. The estimation of such model was achieved through the derivation of Joint Lagrange Multiplier (LM) test for homoscedasticity and zero-serial correlation, a conditional LM test for zero serial correlation given heteroscedasticity of varying degrees as well as conditional LM test for homoscedasticity given first order positive serial correlation via a two-way error component model. Monte Carlo simulations were carried out for 81 different variations, of which its design assumed a uniform distribution under a linear heteroscedasticity function. Each of the variation was iterated 1000 times and the assessment of the three estimators considered are based on Variance, Absolute bias (ABIAS), Mean square error (MSE) and the Root Mean Square (RMSE) of parameters estimates. Eighteen different models at different specified conditions were fitted, and the best-fitted model is that of within estimator when heteroscedasticity is severe at either zero or positive serial correlation value. LM test results showed that the tests have good size and power as all the three tests are significant at 5% for the specified linear form of heteroscedasticity function which established the facts that Banks operations are severely heteroscedastic in nature with little or no periodicity effects.

Keywords: audit fee lagrange multiplier test, heteroscedasticity, lagrange multiplier test, Monte-Carlo scheme, periodicity

Procedia PDF Downloads 137

Authors: Almagul Assainova , Dariya Abykenova, Liudmila Goncharenko, Sergey Sybachin, Saule Rakhimova, Abay Aman

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The recognition of a handwritten Kazakh text is a relevant objective today for the digitization of materials. The study presents a model of a hybrid neural network for handwriting recognition, which includes a convolutional neural network and a multi-layer perceptron. Each network includes 1024 input neurons and 42 output neurons. The model is implemented in the program, written in the Python programming language using the EMNIST database, NumPy, Keras, and Tensorflow modules. The neural network training of such specific letters of the Kazakh alphabet as ә, ғ, қ, ң, ө, ұ, ү, h, і was conducted. The neural network model and the program created on its basis can be used in electronic document management systems to digitize the Kazakh text.

Keywords: handwriting recognition system, image recognition, Kazakh font, machine learning, neural networks

Procedia PDF Downloads 253

Authors: Ruxandra Barbulescu, Daniel Ioan, Gabriela Ciuprina

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The saltatory conduction is the way the action potential is transmitted along a myelinated axon. The potential diffuses along the myelinated compartments and it is regenerated in the Ranvier nodes due to the ion channels allowing the flow across the membrane. For an efficient simulation of populations of neurons, it is important to use reduced order models both for myelinated compartments and for Ranvier nodes and to have control over their accuracy and inner parameters. The paper presents a reduced order model of this neural system which allows an efficient simulation method for the saltatory conduction in myelinated axons. This model is obtained by concatenating reduced order linear models of 1D myelinated compartments and nonlinear 0D models of Ranvier nodes. The models for the myelinated compartments are selected from a series of spatially distributed models developed and hierarchized according to their modeling errors. The extracted model described by a nonlinear PDE of hyperbolic type is able to reproduce the saltatory conduction with acceptable accuracy and takes into account the finite propagation speed of potential. Finally, this model is again reduced in order to make it suitable for the inclusion in large-scale neural circuits.

Keywords: action potential, myelinated segments, nonlinear models, Ranvier nodes, reduced order models, saltatory conduction

Procedia PDF Downloads 154

Authors: Usama Shahid

Abstract:

Be it written documents, news columns, or students' essays, verifying the content can be a time-consuming task. Apart from the spelling and grammar mistakes, the proofreader is also supposed to verify whether the content included in the essay or document is relevant or not. The irrelevant content in any document or essay is referred to as off-topic text and in this paper, we will address the problem of off-topic text detection from a document using machine learning techniques. Our study aims to identify the off-topic content from a document using Echo state network model and we will also compare data with other models. The previous study uses Convolutional Neural Networks and TFIDF to detect off-topic text. We will rearrange the existing datasets and take new classifiers along with new word embeddings and implement them on existing and new datasets in order to compare the results with the previously existing CNN model.

Keywords: off topic, text detection, eco state network, machine learning

Procedia PDF Downloads 81