Search results for: new entrepreneurship student model

Authors: Marjan Javanmard

Abstract:

The rheological properties of dairy products critically depend on the underlying organisation of proteins at multiple length scales. When heated and acidified, milk proteins form particle gel that is viscoelastic, solvent rich, ‘soft’ material. In this work recent developments on the rheology of soft particles suspensions were used to interpret and potentially define the properties of dairy gel structures. It is discovered that at volume fractions below random close packing (RCP), the Maron-Pierce-Quemada (MPQ) model accurately predicts the viscosity of the dairy gel suspensions without fitting parameters; the MPQ model has been shown previously to provide reasonable predictions of the viscosity of hard sphere suspensions from the volume fraction, solvent viscosity and RCP. This surprising finding demonstrates that up to RCP, the dairy gel system behaves as a hard sphere suspension and that the structural aggregates behave as discrete particulates akin to what is observed for microgel suspensions. At effective phase volumes well above RCP, the system is a soft solid. In this region, it is discovered that the storage modulus of the sheared AMG scales with the storage modulus of the set gel. The storage modulus in this regime is reasonably well described as a function of effective phase volume by the Evans and Lips model. Findings of this work has potential to aid in rational design and control of dairy food structure-properties.

Keywords: dairy suspensions, rheology-structure, Maron-Pierce-Quemada Model, Evans and Lips Model

Procedia PDF Downloads 207

Authors: Khandoker Akib Mohammad

Abstract:

While analyzing time-to-event data, it is possible that a certain fraction of subjects will never experience the event of interest, and they are said to be cured. When this feature of survival models is taken into account, the models are commonly referred to as cure models. In the presence of covariates, the conditional survival function of the population can be modelled by using the cure model, which depends on the probability of being uncured (incidence) and the conditional survival function of the uncured subjects (latency), and a combination of logistic regression and Cox proportional hazards (PH) regression is used to model the incidence and latency respectively. In this paper, we have shown the asymptotic normality of the profile likelihood estimator via asymptotic expansion of the profile likelihood and obtain the explicit form of the variance estimator with an implicit function in the profile likelihood. We have also shown the efficient score function based on projection theory and the profile likelihood score function are equal. Our contribution in this paper is that we have expressed the efficient information matrix as the variance of the profile likelihood score function. A simulation study suggests that the estimated standard errors from bootstrap samples (SMCURE package) and the profile likelihood score function (our approach) are providing similar and comparable results. The numerical result of our proposed method is also shown by using the melanoma data from SMCURE R-package, and we compare the results with the output obtained from the SMCURE package.

Keywords: Cox PH model, cure model, efficient score function, EM algorithm, implicit function, profile likelihood

Procedia PDF Downloads 127

Authors: Nargiza Nuralieva

Abstract:

This meta-analysis investigates the effectiveness of mental health interventions tailored for international students in China, with a specific focus on Uzbek students and Silk Road scholarship recipients. The comprehensive literature review synthesizes existing studies, papers, and reports, evaluating the outcomes, limitations, and cultural considerations of these programs. Data selection targets mental health programs for international students, honing in on a subset analysis related to Uzbek students and Silk Road scholarship recipients. The analysis encompasses diverse outcome measures, such as reported stress levels, utilization rates of mental health services, academic performance, and more. Results reveal a consistent and statistically significant reduction in reported stress levels, emphasizing the positive impact of these interventions. Utilization rates of mental health services witness a significant increase, highlighting the accessibility and effectiveness of support. Retention rates show marked improvement, though academic performance yields mixed findings, prompting nuanced exploration. Psychological well-being, quality of life, and overall well-being exhibit substantial enhancements, aligning with the overarching goal of holistic student development. Positive outcomes are observed in increased help-seeking behavior, positive correlations with social support, and significant reductions in anxiety levels. Cultural adaptation and satisfaction with interventions both indicate positive outcomes, underscoring the effectiveness of culturally sensitive mental health support. The findings emphasize the importance of tailored mental health interventions for international students, providing novel insights into the specific needs of Uzbek students and Silk Road scholarship recipients. This research contributes to a nuanced understanding of the multifaceted impact of mental health programs on diverse student populations, offering valuable implications for the design and refinement of future interventions. As educational institutions continue to globalize, addressing the mental health needs of international students remains pivotal for fostering inclusive and supportive learning environments.

Keywords: international students, mental health interventions, cross-cultural support, silk road scholarship, meta-analysis

Procedia PDF Downloads 38

Authors: S. Chowdhury, A. Corlett

Abstract:

Large tsunamis strike the British Columbia coast every few hundred years. The Cascadia Subduction Zone, which extends along the Pacific coast from Vancouver Island to Northern California is one of the most seismically active regions in Canada. Significant earthquakes have occurred in this region, including the 1700 Cascade Earthquake with an estimated magnitude of 9.2. Based on geological records, experts have predicted a 'great earthquake' of a similar magnitude within this region may happen any time. This earthquake is expected to generate a large tsunami that could impact the coastal communities on Vancouver Island. Since many of these communities are in remote locations, they are more likely to be vulnerable, as the post-earthquake relief efforts would be impacted by the damage to critical road infrastructures. To assess the coastal vulnerability within these communities, a hydrodynamic model has been developed using MIKE-21 software. We have considered a 500 year probabilistic earthquake design criteria including the subsidence in this model. The bathymetry information was collected from Canadian Hydrographic Services (CHS), and National Oceanic Atmospheric and Administration (NOAA). The arial survey was conducted using a Cessna-172 aircraft for the communities, and then the information was converted to generate a topographic digital elevation map. Both survey information was incorporated into the model, and the domain size of the model was about 1000km x 1300km. This model was calibrated with the tsunami occurred off the west coast of Moresby Island on October 28, 2012. The water levels from the model were compared with two tide gauge stations close to the Vancouver Island and the output from the model indicates the satisfactory result. For this study, the design water level was considered as High Water Level plus the Sea Level Rise for 2100 year. The hourly wind speeds from eight directions were collected from different wind stations and used a 200-year return period wind speed in the model for storm events. The regional model was set for 12 hrs simulation period, which takes more than 16 hrs to complete one simulation using double Xeon-E7 CPU computer plus a K-80 GPU. The boundary information for the local model was generated from the regional model. The local model was developed using a high resolution mesh to estimate the coastal flooding for the communities. It was observed from this study that many communities will be effected by the Cascadia tsunami and the inundation maps were developed for the communities. The infrastructures inside the coastal inundation area were identified. Coastal vulnerability planning and resilient design solutions will be implemented to significantly reduce the risk.

Keywords: tsunami, coastal flooding, coastal vulnerable, earthquake, Vancouver, wave propagation

Procedia PDF Downloads 122

Authors: Bet El Silisna Lagarense, Agustinus Walansendow

Abstract:

Manado Waterfront Development (MWD) occurs along the coastline of the city to meet the communities’ various needs and interests. Manado waterfront, with its various kinds of tourist attractions, is being developed to strengthen opportunities for both tourism and other businesses. There are many buildings that are used for trade and business purposes. The spatial distributions of tourism, commercial and residential land uses overlap. Field research at the study site consisted desktop scan, questionnaire-based survey, observation and in-depth interview with key informants and Focus Group Discussion (FGD) identified how MWD was initially planned and designed in the whole process of decision making in terms of resource and environmental management particularly for the waterfront tourism development in the long run. The study developed a clustered-based model for waterfront urban tourism in Manado through evaluation of spatial distribution of tourism uses along the waterfront.

Keywords: clustered-based model, Manado, urban tourism, waterfront

Procedia PDF Downloads 286

Authors: Debarati Bhaumik, Diptish Dey

Abstract:

Multilevel models, increasingly deployed in industries such as insurance, food production, and entertainment within functions such as marketing and supply chain management, need to be transparent and ethical. Applications usually result in binary classification within groups or hierarchies based on a set of input features. Using open-source datasets, we demonstrate that popular explainability methods, such as SHAP and LIME, consistently underperform inaccuracy when interpreting these models. They fail to predict the order of feature importance, the magnitudes, and occasionally even the nature of the feature contribution (negative versus positive contribution to the outcome). Besides accuracy, the computational intractability of SHAP for binomial classification is a cause of concern. For transparent and ethical applications of these hierarchical statistical models, sound audit frameworks need to be developed. In this paper, we propose an audit framework for technical assessment of multilevel regression models focusing on three aspects: (i) model assumptions & statistical properties, (ii) model transparency using different explainability methods, and (iii) discrimination assessment. To this end, we undertake a quantitative approach and compare intrinsic model methods with SHAP and LIME. The framework comprises a shortlist of KPIs, such as PoCE (Percentage of Correct Explanations) and MDG (Mean Discriminatory Gap) per feature, for each of these three aspects. A traffic light risk assessment method is furthermore coupled to these KPIs. The audit framework will assist regulatory bodies in performing conformity assessments of AI systems using multilevel binomial classification models at businesses. It will also benefit businesses deploying multilevel models to be future-proof and aligned with the European Commission’s proposed Regulation on Artificial Intelligence.

Keywords: audit, multilevel model, model transparency, model explainability, discrimination, ethics

Procedia PDF Downloads 79

Authors: Zhi-Jun Lu, Qi Lu, Meng Wu, Qian Xiang, Jun Gu

Abstract:

The analysis of perforated steel members is a 3D problem in nature, therefore the traditional analytical expressions for the ultimate load of thin-walled steel sections cannot be used for the perforated steel member design. In this study, finite element method (FEM) and artificial neural network (ANN) were used to simulate the process of stub column tests based on specific codes. Results show that compared with those of the FEM model, the ultimate load predictions obtained from ANN technique were much closer to those obtained from the physical experiments. The ANN model for the solving the hard problem of complex steel perforated sections is very promising.

Keywords: artificial neural network (ANN), finite element method (FEM), perforated sections, thin-walled Steel, ultimate load

Procedia PDF Downloads 335

Authors: Mario Gianni, Federico Nardi, Federico Ferri, Filippo Cantucci, Manuel A. Ruiz Garcia, Karthik Pushparaj, Fiora Pirri

Abstract:

In this paper, we describe a Mixed-Initiative Operational Model (MIOM) which directly intervenes on the state of the functionalities embedded into a robot for Urban Search&Rescue (USAR) domain applications. MIOM extends the reasoning capabilities of the vehicle, i.e. mapping, path planning, visual perception and trajectory tracking, with operator knowledge. Especially in USAR scenarios, this coupled initiative has the main advantage of enhancing the overall performance of a rescue mission. In-field experiments with rescue responders have been carried out to evaluate the effectiveness of this operational model.

Keywords: mixed-initiative planning and control, operator control interfaces for rescue robotics, situation awareness, urban search, rescue robotics

Procedia PDF Downloads 353

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

Abstract:

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 474

Authors: Fabiana Lucena Oliveira, Aristides da Rocha Oliveira Junior

Abstract:

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 496

Authors: Zahira Anane, Abdelhafid Bayadi

Abstract:

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

Procedia PDF Downloads 608

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

Abstract:

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

Procedia PDF Downloads 520

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

Abstract:

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

Procedia PDF Downloads 464

Authors: R. Hellmuth, F. Wehner

Abstract:

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

Procedia PDF Downloads 103

Authors: Juhan Kim, Jinsoo Kim

Abstract:

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

Procedia PDF Downloads 280

Authors: Shubham Bhonde, Nekzad Doctor, Shashwat Gawande

Abstract:

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)

Procedia PDF Downloads 149

Authors: Shokoufeh Abrisham, Seyed Mahmoud Hossieni, Elham Pishbin

Abstract:

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

Procedia PDF Downloads 136

Authors: Marzieh Eshaghi Koupaei

Abstract:

By cultivating mealworm, we reduce greenhouse gases and avoid the use of transgenic products such as soybeans, and we provide food resources rich in protein, amino acids, minerals, etc. for humans and animals, and it has created employment and entrepreneurship. We serve the environment by producing oil from mealworm in the cosmetic industry, using its waste as organic fertilizer and its powder in bodybuilding, and by breaking down plastic by mealworm. The production and breeding of mealworm requires very little infrastructure and does not require much trouble, and requires very little food, and reproduces easily and quickly, and a mealworm production workshop is noiseless, odorless, and pollution-free And the costs are very low. It is possible to use third grade fruits and unsalable fruits of farmers to feed the mealworms, which is completely economical and cost-effective. Mealworms can break down plastic in their intestines and turn it into carbon dioxide. . This process was done in only 16 days, which is a very short time compared to several centuries for plastic to decompose. By producing mealworm, we have helped to preserve the environment and provided the source of protein needed by humans and animals. This industrial insect has the ability and value of commercialization and creates employment and helps the economy of the society.

Keywords: breeding, production of insects, mealworms, research, animal feed, human feed

Procedia PDF Downloads 39

Authors: Mohammad Anwar, Shah Waliullah

Abstract:

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

Procedia PDF Downloads 61

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

Abstract:

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

Procedia PDF Downloads 123

Authors: Yifu Ding, Vijay Avinash, Malcolm McCulloch

Abstract:

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 112

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

Abstract:

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

Procedia PDF Downloads 406

Authors: Ginger Egberts, Fred Vermolen, Paul van Zuijlen

Abstract:

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

Procedia PDF Downloads 138

Authors: Jiahui Yang, John Quigley, Lesley Walls

Abstract:

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

Procedia PDF Downloads 275

Authors: Mojahid F. Saeed Osman

Abstract:

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 126

Authors: Mohamed Bendahmane, Brahim Elfalaki, Mohammed Benattou

Abstract:

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

Procedia PDF Downloads 340

Authors: Ahmad Aslizadeh, Farid Ghaderi

Abstract:

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

Procedia PDF Downloads 388

Authors: Amanda Watson

Abstract:

The goal of this project is to create the conditions wherein every teacher, especially subjectarea experts, sees themselves as a teacher of language and vocabulary. Assessment and observational data suggest that students are not getting the support they need in vocabulary and reading comprehension, and secondary teachers do not currently have the confidence or expertise to provide this support. This study seeks to examine the impact of 10-20 minutes of daily, targeted instruction around orthography and vocabulary on student competence with the navigation of complex vocabulary and comprehension of subject-specific concepts and texts. The first phase of the pilot included 6 participating classroom teachers of grades 9 and 10 English (95 students in total) who administered an initial reading comprehension assessment. The results of this assessment indicated that the vast majority of students were reading below grade level. Teachers were then provided with a slide deck of complete lessons on orthography, vocabulary (etymology, roots and affixes) and reading comprehension strategies. For five weeks, teachers delivered lessons with their students, implementing the recommended evidence-based teaching strategies. Students and teachers completed surveys to provide feedback on the value and impact of the method. The results confirmed that this was new learning for the students and that the teaching strategies improved engagement. The lessons succeeded in providing equitable access to challenge by simultaneously offering theoretical learning to proficient readers, and exposure and practice to weaker readers. A second reading comprehension was administered after 5 weeks of daily instruction. Average scores increased by 41%, and almost every student experienced progress. The first phase was not long enough to measure the impact of the method on vocabulary acquisition or reading comprehension of subject-specific texts, however. The project will use the results of the first phase to design the second phase, and new teaching and learning strategies will be added. The goals of the second phases are to increase motivation, and to grow the daily practice beyond English class and into science and / or math. This team will continue to document a continuation of the daily lessons, Commented [E1]: Please do not use rhetorical questions in the abstract. measure the impact of the strategies, and address questions about the correlation between daily practice and improvements in the skills students need for vocabulary acquisition and disciplinary reading comprehension.

Keywords: adolescent, comprehension, orthography, reading, vocabulary, etymology, word study, disciplinary, teaching strategies

Procedia PDF Downloads 56

Authors: Rattakorn Poonsuph

Abstract:

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 152

Authors: Nureni O. Adeboye, Dawud A. Agunbiade

Abstract:

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 132