Search results for: interpolatory model reduction

Authors: Giulio Mangano, Alberto De Marco, Giovanni Zenezini

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The concept of City Logistics (CL) has emerged to improve the impacts of last mile freight distribution in urban areas. In this paper, a System Dynamics (SD) model exploring the dynamics of the diffusion of a ICT platform for CL management across different populations is proposed. For the development of the model two sources have been used. On the one hand, the major diffusion variables and feedback loops are derived from a literature review of existing diffusion models. On the other hand, the parameters are represented by the value propositions delivered by the platform as a response to some of the users’ needs. To extract the most important value propositions the Business Model Canvas approach has been used. Such approach in fact focuses on understanding how a company can create value for her target customers. These variables and parameters are thus translated into a SD diffusion model with three different populations namely municipalities, logistics service providers, and own account carriers. Results show that, the three populations under analysis fully adopt the platform within the simulation time frame, highlighting a strong demand by different stakeholders for CL projects aiming at carrying out more efficient urban logistics operations.

Keywords: city logistics, simulation, system dynamics, business model

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Authors: Moses Mwangi, Geert Verbeke, Geert Molenberghs

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Cross-over designs are commonly used in randomized clinical trials to estimate efficacy of a new treatment with respect to a reference treatment (placebo or standard). The main advantage of using cross-over design over conventional parallel design is its flexibility, where every subject become its own control, thereby reducing confounding effect. Jones & Kenward, discuss in detail more recent developments in the analysis of cross-over trials. We revisit the simple piecewise linear mixed-effects model, proposed by Mwangi et. al, (in press) for its first application in the analysis of cross-over trials. We compared performance of the proposed piecewise linear mixed-effects model with two commonly cited statistical models namely, (1) Grizzle model; and (2) Jones & Kenward model, used in estimation of the treatment effect, in the analysis of randomized cross-over trial. We estimate two performance measurements (mean square error (MSE) and coverage probability) for the three methods, using data simulated from the proposed piecewise linear mixed-effects model. Piecewise linear mixed-effects model yielded lowest MSE estimates compared to Grizzle and Jones & Kenward models for both small (Nobs=20) and large (Nobs=600) sample sizes. It’s coverage probability were highest compared to Grizzle and Jones & Kenward models for both small and large sample sizes. A piecewise linear mixed-effects model is a better estimator of treatment effect than its two competing estimators (Grizzle and Jones & Kenward models) in the analysis of cross-over trials. The data generating mechanism used in this paper captures two time periods for a simple 2-Treatments x 2-Periods cross-over design. Its application is extendible to more complex cross-over designs with multiple treatments and periods. In addition, it is important to note that, even for single response models, adding more random effects increases the complexity of the model and thus may be difficult or impossible to fit in some cases.

Keywords: Evaluation, Grizzle model, Jones & Kenward model, Performance measures, Simulation

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Authors: Dongkwon Han, Sangho Kim, Sunil Kwon

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Unconventional gas resources have dramatically changed the future energy landscape. Unlike conventional gas resources, the key challenges in unconventional gas have been the requirement that applies to advanced approaches for production forecasting due to uncertainty and complexity of fluid flow. In this study, artificial neural network (ANN) model which integrates machine learning and data-driven approach was developed to predict productivity in shale gas. The database of 129 wells of Eagle Ford shale basin used for testing and training of the ANN model. The Input data related to hydraulic fracturing, well completion and productivity of shale gas were selected and the output data is a cumulative production. The performance of the ANN using all data sets, clustering and variables importance (VI) models were compared in the mean absolute percentage error (MAPE). ANN model using all data sets, clustering, and VI were obtained as 44.22%, 10.08% (cluster 1), 5.26% (cluster 2), 6.35%(cluster 3), and 32.23% (ANN VI), 23.19% (SVM VI), respectively. The results showed that the pre-trained ANN model provides more accurate results than the ANN model using all data sets.

Keywords: unconventional gas, artificial neural network, machine learning, clustering, variables importance

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Authors: Prasenjit Singha, Ajay Kumar Shukla

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To produce high-quality steel in larger volumes, dynamic control of composition and temperature throughout the process is essential. In this paper, we developed a mass transfer model based on thermodynamics to simulate the ladle metallurgy steel-making process using FactSage and its macro facility. The overall heat and mass transfer processes consist of one equilibrium chamber, two non-equilibrium chambers, and one adiabatic reactor. The flow of material, as well as heat transfer, occurs across four interconnected unit chambers and a reactor. We used the macro programming facility of FactSage™ software to understand the thermochemical model of the secondary steel making process. In our model, we varied the oxygen content during the process and studied their effect on the composition of the final hot metal and slag. The model has been validated with respect to the plant data for the steel composition, which is similar to the ladle metallurgy steel-making process in the industry. The resulting composition profile serves as a guiding tool to optimize the process of ladle metallurgy in steel-making industries.

Keywords: desulphurization, degassing, factsage, reactor

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Authors: Mahmoud Reza Hosseini

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The universe is in a continuous expansion process, resulting in the reduction of its density and temperature. Also, by extrapolating back from its current state, the universe at its early times has been studied known as the big bang theory. According to this theory, moments after creation, the universe was an extremely hot and dense environment. However, its rapid expansion due to nuclear fusion led to a reduction in its temperature and density. This is evidenced through the cosmic microwave background and the universe structure at a large scale. However, extrapolating back further from this early state reaches singularity which cannot be explained by modern physics and the big bang theory is no longer valid. In addition, one can expect a nonuniform energy distribution across the universe from a sudden expansion. However, highly accurate measurements reveal an equal temperature mapping across the universe which is contradictory to the big bang principles. To resolve this issue, it is believed that cosmic inflation occurred at the very early stages of the birth of the universe According to the cosmic inflation theory, the elements which formed the universe underwent a phase of exponential growth due to the existence of a large cosmological constant. The inflation phase allows the uniform distribution of energy so that an equal maximum temperature could be achieved across the early universe. Also, the evidence of quantum fluctuations of this stage provides a means for studying the types of imperfections the universe would begin with. Although well-established theories such as cosmic inflation and the big bang together provide a comprehensive picture of the early universe and how it evolved into its current state, they are unable to address the singularity paradox at the time of universe creation. Therefore, a practical model capable of describing how the universe was initiated is needed. This research series aims at addressing the singularity issue by introducing an energy conversion mechanism. This is accomplished by establishing a state of energy called a “neutral state”, with an energy level which is referred to as “base energy” capable of converting into other states. Although it follows the same principles, the unique quanta state of the base energy allows it to be distinguishable from other states and have a uniform distribution at the ground level. Although the concept of base energy can be utilized to address the singularity issue, to establish a complete picture, the origin of the base energy should be also identified. This matter is the subject of the first study in the series “A Conceptual Study for Investigating the Creation of Energy and Understanding the Properties of Nothing” which is discussed in detail. Therefore, the proposed concept in this research series provides a road map for enhancing our understating of the universe's creation from nothing and its evolution and discusses the possibility of base energy as one of the main building blocks of this universe.

Keywords: big bang, cosmic inflation, birth of universe, energy creation

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Authors: Mohamed I. Mahrous, Mohamed G. Ashmawy

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Hybrid genetic algorithm (HGA) is proposed in this paper to determine the economic scheduling of electric power generation over a fixed time period under various system and operational constraints. The proposed technique can outperform conventional genetic algorithms (CGAs) in the sense that HGA make it possible to improve both the quality of the solution and reduce the computing expenses. In contrast, any carefully designed GA is only able to balance the exploration and the exploitation of the search effort, which means that an increase in the accuracy of a solution can only occure at the sacrifice of convergent speed, and vice visa. It is unlikely that both of them can be improved simultaneously. The proposed hybrid scheme is developed in such a way that a simple GA is acting as a base level search, which makes a quick decision to direct the search towards the optimal region, and a local search method (pattern search technique) is next employed to do the fine tuning. The aim of the strategy is to achieve the cost reduction within a reasonable computing time. The effectiveness of the proposed hybrid technique is verified on two real public electricity supply systems with 13 and 40 generator units respectively. The simulation results obtained with the HGA for the two real systems are very encouraging with regard to the computational expenses and the cost reduction of power generation.

Keywords: genetic algorithms, economic dispatch, pattern search

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Authors: Dora Vajda, Somayyeh Mohammadi, Sandor Rozsa

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Predicting the relationship satisfaction based on the personality characteristics of both partners has a long history. The association between relationship quality and personality traits has been previously demonstrated. Personality traits are most commonly assessed using the Five-Factor Model. The present study has focused on Cloninger's psychobiological model of personality that accounts for dimensions of both temperament and character. The goal of this study was to examine the actor and partner effect of couple's personality on relationship outcomes. In total, 184 heterosexual couples completed the Temperament and Character Inventory (TCI) and the Dyadic Adjustment Scale. The analysis was based on Actor-Partner Interdependence Model (APIM) using multilevel modeling (MLwiN). Results showed that character dimensions Self-Directedness and Cooperativeness had a statistically meaningful actor and partner effect on both partner's relationship quality. However, male's personality temperament dimension Reward Dependence had an only actor effect on his relationship quality. The findings contribute to the literature by highlighting the role of character dimensions of personality in romantic relationships.

Keywords: APIM (actor-partner interdependence model), MLwiN, personality, relationship quality

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Authors: L. R. Ferreira, R. Biscaro, C. C. Danziger, C. M. Galhardi, L. C. Biscaro, R. C. Biscaro, I. S. Vasconcelos, L. C. R. Ferreira, R. Reis, L. H. Oliveira

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Introduction: There is a worldwide trend for the employer to be aware of investing in health promotion that goes beyond occupational hygiene approaches with the implementation of a comprehensive program with integration between occupational health and safety, and social/psychosocial responsibility in the workplace. Work accommodation is a necessity in most companies as it allows the worker to return to its function respecting its physical limitations. This study had the objective to verify if the integration of health and safety in the companies, with the inclusion of the concept of TWH promoted by an occupational health service has impacted in the management of absenteeism of workers in work accommodation. Method: A retrospective and paired cohort study was used, in which the impact of the implementation of the Program for the Health/Safety Integration and Total Worker Health Concept (PHSITWHC) was evaluated using the indices of absenteeism, health attestations, days and hours of sick leave of workers that underwent job accommodation/rehabilitation. This was a cohort study and the data were collected from January to September of 2017, prior to the initiation of the integration program, and compared with the data obtained from January to September of 2018, after the implementation of the program. For the statistical analysis, the student's t-test was used, with statistically significant differences being made at p < 0.05. Results: The results showed a 35% reduction in the number of absenteeism rate in 2018 compared to the same period in 2017. There was also a significant reduction in the total numbers of days of attestations/absences (mean of 2,8) as well as days of attestations, absence and sick leaves (mean of 5,2) in 2018 data after the implementation of PHSITWHC compared to 2017 data, means of 4,3 and 25,1, respectively, prior to the program. Conclusion: It can be concluded that the inclusion of the PHSITWHC was associated with a reduction in the rate of absenteeism of workers that underwent job accommodation. It was observed that, once health and safety were approached and integrated with the inclusion of the TWH concept, it was possible to reduce absenteeism, and improve worker’s quality of life and wellness, and work accommodation management.

Keywords: absenteeism, health/safety integration, work accommodation management, total worker health

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Authors: Roberto de Lieto Vollaro, Emanuele de Lieto Vollaro, Gianluca Coltrinari

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The building sector is responsible, in many industrialized countries, for about 40% of the total energy requirements, so it seems necessary to devote some efforts in this area in order to achieve a significant reduction of energy consumption and of greenhouse gases emissions. The paper presents a study aiming at providing a design methodology able to identify the best configuration of the system building/plant, from a technical, economic and environmentally point of view. Normally, the classical approach involves a building's energy loads analysis under steady state conditions, and subsequent selection of measures aimed at improving the energy performance, based on previous experience made by architects and engineers in the design team. Instead, the proposed approach uses a sequence of two well known scientifically validated calculation methods (TRNSYS and RETScreen), that allow quite a detailed feasibility analysis. To assess the validity of the calculation model, an existing, historical building in Central Italy, that will be the object of restoration and preservative redevelopment, was selected as a case-study. The building is made of a basement and three floors, with a total floor area of about 3,000 square meters. The first step has been the determination of the heating and cooling energy loads of the building in a dynamic regime by means of TRNSYS, which allows to simulate the real energy needs of the building in function of its use. Traditional methodologies, based as they are on steady-state conditions, cannot faithfully reproduce the effects of varying climatic conditions and of inertial properties of the structure. With TRNSYS it is possible to obtain quite accurate and reliable results, that allow to identify effective combinations building-HVAC system. The second step has consisted of using output data obtained with TRNSYS as input to the calculation model RETScreen, which enables to compare different system configurations from the energy, environmental and financial point of view, with an analysis of investment, and operation and maintenance costs, so allowing to determine the economic benefit of possible interventions. The classical methodology often leads to the choice of conventional plant systems, while RETScreen provides a financial-economic assessment for innovative energy systems and low environmental impact. Computational analysis can help in the design phase, particularly in the case of complex structures with centralized plant systems, by comparing the data returned by the calculation model RETScreen for different design options. For example, the analysis performed on the building, taken as a case study, found that the most suitable plant solution, taking into account technical, economic and environmental aspects, is the one based on a CCHP system (Combined Cooling, Heating, and Power) using an internal combustion engine.

Keywords: energy, system, building, cooling, electrical

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Authors: Mojtaba Farzaneh, Majid Baghaei Nejad

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This article proposes a new Flexible Capacitive Tactile Sensors based on paper sheets. This method combines the parameters of sensor's material and dielectric, and forms a new model of flexible capacitive sensors. The present article tries to present a practical explanation of this method's application and advantages. With the use of this new method, it is possible to make a more flexibility and accurate sensor in comparison with the current models. To assess the performance of this model, the common capacitive sensor is simulated and the proposed model of this article and one of the existing models are assessed. The results of this article indicate that the proposed model of this article can enhance the speed and accuracy of tactile sensor and has less error in comparison with the current models. Based on the results of this study, it can be claimed that in comparison with the current models, the proposed model of this article is capable of representing more flexibility and more accurate output parameters for touching the sensor, especially in abnormal situations and uneven surfaces, and increases accuracy and practicality.

Keywords: capacitive sensor, paper sheets, flexible, tactile, uneven

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Authors: Bilgehan Gültekin, Tuba Gültekin

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Peace diplomacy is the most important international tool to keep peace all over the world. The study titled “peace diplomacy for international relations” is consist of three part. In the first part, peace diplomacy is going to be introduced as a tool of peace communication and peace management. And, in this part, peace communication will be explained by international communication perspective. In the second part of the study,public relations events and communication campaigns will be developed originally for peace diplomacy. In this part, it is aimed original public communication dialogue management tools for peace diplomacy. the aim of the final part of the study, is to produce original public communication model for international relations. The model includes peace modules, peace management projects, original dialogue procedures and protocols, dialogue education, dialogue management strategies, peace actors, communication models, peace team management and public diplomacy steps. The creative part of the study aims to develop a model used for international relations for all countries. Creative Peace Diplomacy Model will be developed in the case of Turkey-Turkey-France and Turkey-Greece relations. So, communication and public relations events and campaigns are going to be developed as original for only this study.

Keywords: peace diplomacy, public communication model, dialogue management, international relations

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Authors: Jalal Abdulkareem Sultan, Abdulhakeem Luqman Hasan

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With the development of health care systems competition, hospitals face more and more pressures. Meanwhile, resource allocation has a vital effect on achieving competitive advantages in hospitals. Selecting the appropriate number of beds is one of the most important sections in hospital management. However, in real situation, bed allocation selection is a multiple objective problem about different items with vagueness and randomness of the data. It is very complex. Hence, research about bed allocation problem is relatively scarce under considering multiple departments, nursing hours, and stochastic information about arrival and service of patients. In this paper, we develop a fuzzy multiobjective bed allocation model for overcoming uncertainty and multiple departments. Fuzzy objectives and weights are simultaneously applied to help the managers to select the suitable beds about different departments. The proposed model is solved by using Artificial Bee Colony (ABC), which is a very effective algorithm. The paper describes an application of the model, dealing with a public hospital in Iraq. The results related that fuzzy multi-objective model was presented suitable framework for bed allocation and optimum use.

Keywords: bed allocation problem, fuzzy logic, artificial bee colony, multi-objective optimization

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Authors: Melissa Lubitz

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Water scarcity is one of the crucial challenges of our time. There needs to be a focus on creating a society where people and nature flourish, regardless of climatic conditions. One of the solutions we can look to is decentralized greywater recycling. The vision is simple. Every building has its own water source being greywater from the bath, shower, sink and washing machine. By treating this in the home, you can save 25-45% of potable water use and wastewater production, a reduction in energy consumption and CO2 emissions. This reusable water is clean, and safe to be used for toilet flushing, washing machine, and outdoor irrigation. Companies like Hydraloop have been committed to the greywater recycle-ready building concept for years. This means that drinking water conservation and water reuse are included as standards in the design of all new buildings. Sustainability and renewal go hand in hand. This vision includes not only optimizing water savings and waste reduction but also forging strong partnerships that bring this ambition to life. Together with regulators, municipalities and builders, a sustainable and water-conscious future is pursued. This is an opportunity to be part of a movement that is making a difference. By pushing this initiative forward, we become part of a growing community that resists dehydration, believes in sustainability, and is committed to a living environment at the forefront of change: sustainable living, where saving water is the norm and where we shape the future together.

Keywords: greywater, wastewater treatment, water conservation, circular water society

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Authors: Tiffany Gallagher, Sheila Bennett

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Based on data from a larger study, this research is based in a small school district in Ontario, Canada, that has made a transition from self-contained classes for students with exceptionalities to inclusive classroom placements for all students with their age-appropriate peers. The school board aided this transition by hiring Inclusion Coaches with a background in special education to work alongside teachers as partners and inform their inclusive practice. Based on qualitative data from four focus groups conducted with Inclusion Coaches, as well as four blog-style reflections collected at various points over two years, six principles of inclusive practice were identified for coaches. The six principles form a model during transition: pre-requisite, process, precipice, promotion, proof, and promise. These principles are encapsulated in a visual model of a spiraling staircase displaying the conditions that exist prior to coaching, during coaching interactions and considerations for the sustainability of coaching. These six principles are re-iterative and should be re-visited each time a coaching interaction is initiated. Exploring inclusion coaching as a model emulates coaching in other contexts and allows us to examine an established process through a new lens. This research becomes increasingly important as more school boards transition toward inclusive classrooms, The Six ‘P’ Model: Principles of Inclusive Practice for Inclusion Coaches allows for a unique look into a scaffolding model of building educator capacity in an inclusive setting.

Keywords: capacity building, coaching, inclusion, special education

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Authors: Kang Lin Peng

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Space tourism emerged in 2001 and became famous in 2021, following the development of space technology. The space market is twisted because of the excess demand. Space tourism is currently rare and extremely expensive, with biased luxury product pricing, which is the seller’s market that consumers can not bargain with. Spaceship companies such as Virgin Galactic, Blue Origin, and Space X have been charged space tourism prices from 200 thousand to 55 million depending on various heights in space. There should be a reasonable price based on a fair basis. This study aims to derive a spacetime pricing model, which is different from the general pricing model on the earth’s surface. We apply general relativity theory to deduct the mathematical formula for the space tourism pricing model, which covers the traditional time-independent model. In the future, the price of space travel will be different from current flight travel when space travel is measured in lightyear units. The pricing of general commodities mainly considers the general equilibrium of supply and demand. The pricing model considers risks and returns with the dependent time variable as acceptable when commodities are on the earth’s surface, called flat spacetime. Current economic theories based on the independent time scale in the flat spacetime do not consider the curvature of spacetime. Current flight services flying the height of 6, 12, and 19 kilometers are charging with a pricing model that measures time coordinate independently. However, the emergence of space tourism is flying heights above 100 to 550 kilometers that have enlarged the spacetime curvature, which means tourists will escape from a zero curvature on the earth’s surface to the large curvature of space. Different spacetime spans should be considered in the pricing model of space travel to echo general relativity theory. Intuitively, this spacetime commodity needs to consider changing the spacetime curvature from the earth to space. We can assume the value of each spacetime curvature unit corresponding to the gradient change of each Ricci or energy-momentum tensor. Then we know how much to spend by integrating the spacetime from the earth to space. The concept is adding a price p component corresponding to the general relativity theory. The space travel pricing model degenerates into a time-independent model, which becomes a model of traditional commodity pricing. The contribution is that the deriving of the space tourism pricing model will be a breakthrough in philosophical and practical issues for space travel. The results of the space tourism pricing model extend the traditional time-independent flat spacetime mode. The pricing model embedded spacetime as the general relativity theory can better reflect the rationality and accuracy of space travel on the universal scale. The universal scale from independent-time scale to spacetime scale will bring a brand-new pricing concept for space traveling commodities. Fair and efficient spacetime economics will also bring to humans’ travel when we can travel in lightyear units in the future.

Keywords: space tourism, spacetime pricing model, general relativity theory, spacetime curvature

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Authors: Maryam Radan, Fereshteh Nejad Dehbashi, Vahid Bayati, Mahin Dianat, Seyyed Ali Mard, Zahra Mansouri

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Pulmonary emphysema is a pathological respiratory condition identified by alveolar destruction which leads to limitation of airflow and diminished lung function. A substantial body of evidence suggests that mesenchymal stem cells (MSCs) have the ability to induce tissue repair primarily through a paracrine effect. In this study, we aimed to determine the efficacy of Intratracheal adipose-derived mesenchymal stem cells (ADSCs) therapy in comparison to this approach with that of Intravenous (Systemic) therapy. Fifty adult male Sprague–Dawley rats weighing between 180 and 200 g were used in this experiment. The animals were randomized to Control groups (Intratracheal or Intravenous vehicle), Elastase group (intratracheal administration of porcine pancreatic elastase; 25 U/kg on day 0 and day 10th), Elastase+Intratracheal ADSCs therapy (1x107 Cells, on day 28) and Elastase+Systemic ADSCs therapy (1x107 Cells, on day 28). The rats which not subjected to any treatment, considered as the control. All rats were sacrificed 3 weeks later. Morphometric findings in lung tissues (Mean linear intercept) confirmed the establishment of the emphysema model via alveolar disruption. Contrarily, ADSCs administration partially restored alveolar architecture. These results were associated with improving arterial oxygenation, reducing lung edema, and decreasing lung inflammation with higher significant effects in the Intratracheal therapy route. These results documented that the efficacy of intratracheal ADSCs was comparable with intravenous ADSCs therapy. Accordingly, the obtained data suggested that intratracheal delivery of ADSCs would enhance lung repair in pulmonary emphysema. Moreover, this method provides benefits over a systemic administration, such as the reduction of cell number and the low risk to engraft other organs.

Keywords: mesenchymal stem cell, emphysema, Intratracheal, systemic

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Authors: Champika S. Kariyawasam

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The distribution of gorse (Ulex europaeus) plants in South Australia has been modelled using 126 presence-only location data as a function of seven climate parameters. The predicted range of U. europaeus is mainly along the Mount Lofty Ranges in the Adelaide Hills and on Kangaroo Island. Annual precipitation and yearly average aridity index appeared to be the highest contributing variables to the final model formulation. The Jackknife procedure was employed to identify the contribution of different variables to gorse model outputs and response curves were used to predict changes with changing environmental variables. Based on this analysis, it was revealed that the combined effect of one or more variables could make a completely different impact to the original variables on their own to the model prediction. This work also demonstrates the need for a careful approach when selecting environmental variables for projecting correlative models to climatically distinct area. Maxent acts as a robust model when projecting the fitted species distribution model to another area with changing climatic conditions, whereas the generalized linear model, bioclim, and domain models to be less robust in this regard. These findings are important not only for predicting and managing invasive alien gorse in South Australia and Sri Lanka but also in other countries of the invasive range.

Keywords: invasive species, Maxent, species distribution modelling, Ulex europaeus

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Authors: Huijuan Liu, Fukun Li, Hao Yuan

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The bolted spherical node is a common type of joint in space steel structures. The bolt-sphere joint portion almost always controls the bearing capacity of the bolted spherical node. The investigation of the bearing performance and progressive failure in service often requires high-fidelity numerical models. This paper focuses on the constitutive models of bolt steel and sphere steel used in China’s space structure construction. The elastoplastic model is determined by a standard tensile test and calibrated Voce saturated hardening rule. The ductile damage is found dominant based on the fractography analysis. Then Rice-Tracey ductile fracture rule is selected and the model parameters are calibrated based on tensile tests of notched specimens. These calibrated material models can benefit research or engineering work in similar fields.

Keywords: bolt-sphere joint, steel, constitutive model, ductile damage, model calibration

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Authors: Morteza Hadi

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This research investigates the potential enhancement of the rollability of Cu-Ge-Ni alloy through the mitigation of microstructural and compositional inhomogeneities via two distinct heat treatment methods: homogenization and solution treatment. To achieve this objective, the alloy with the desired composition was fabricated using a vacuum arc remelting furnace (VAR), followed by sample preparation for microstructural, compositional, and heat treatment analyses at varying temperatures and durations. Characterization was conducted employing optical and scanning electron microscopy (SEM), X-ray diffraction (XRD), and Vickers hardness testing. The results obtained indicate that a minimum duration of 10 hours is necessary for adequate homogenization of the alloy at 750°C. This heat treatment effectively removes coarse dendrites from the casting microstructure and significantly reduces elemental separations. However, despite these improvements, the presence of a second phase with markedly different hardness from the matrix results in poor rolling ability for the alloy. The optimal time for solution treatment at various temperatures was determined, with the most effective cycle identified as 750°C for 2 hours, followed by rapid quenching in water. This process induces the formation of a single-phase microstructure and complete elimination of the second  phase, as confirmed by X-ray diffraction analysis. Results demonstrate a reduction in hardness by 30 Vickers, and the elimination of microstructural unevenness enables successful thickness reduction by up to 50% through rolling without encountering cracking.

Keywords: Cu-Ge-Ni alloy, homogenization. solution treatment, rollability

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Authors: Francesca Croce

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Governmental development strategies aimed at entrepreneurship as a major resource for economic development and poverty reduction of indigenous people. As initiatives and programs are local based, there is a need to better understand the contextual factors of indigenous entrepreneurial models. The purpose of this paper is, therefore, to analyze and integrated the indigenous entrepreneurship literature in order to identify the main models of indigenous entrepreneurship. To answer this need, a systematic literature review was conducted. Relevant articles were identified in selected electronic databases (ABI/Inform Global, Business Source Premier, Web of Science; International Bibliography of the Social Sciences, Academic Search, Sociological Abstract, Entrepreneurial Studies Sources and Bibliography of Native North America) and in selected electronic review. Beginning to 1st January 1995 (first International Day of the World’s Indigenous People), 59 academic articles were selected from 1411. Through systematic analysis of the cultural, social and organizational variables, the paper highlights that a typology of indigenous entrepreneurial models is possible thought the concept of entrepreneurial ecosystem, which includes the geographical position and the environment of the indigenous communities. The results show three models of indigenous entrepreneurship: the urban indigenous entrepreneurship, the semi-urban indigenous entrepreneurship, and rural indigenous entrepreneurship. After the introduction, the paper is organized as follows. In the first part theoretical and practical needs of a systematic literature review on indigenous entrepreneurship are provided. In the second part, the methodology, the selection process and evaluation of the articles are explained. In the third part, findings are presented and each indigenous entrepreneurial model characteristics are discussed. The results of this study bring a new theorization about indigenous entrepreneurship and may be useful for scientists in the field in search of overcoming the cognitive border of Indigenous business models still too little known. Also, the study is addressed to policy makers in charge of indigenous entrepreneurial development strategies more focused on contextual factors studies.

Keywords: community development, entrepreneurial ecosystem, indigenous entrepreneurship model, indigenous people, systematic literature review

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Authors: Longqing Li

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The paper addresses the inefficiency of the classical model in measuring the Value-at-Risk (VaR) using a normal distribution or a Student’s t distribution. Specifically, the paper focuses on the one day ahead Value-at-Risk (VaR) of major stock market’s daily returns in US, UK, China and Hong Kong in the most recent ten years under 95% confidence level. To improve the predictable power and search for the best performing model, the paper proposes using two leading alternatives, Extreme Value Theory (EVT) and a family of GARCH models, and compares the relative performance. The main contribution could be summarized in two aspects. First, the paper extends the GARCH family model by incorporating EGARCH and TGARCH to shed light on the difference between each in estimating one day ahead Value-at-Risk (VaR). Second, to account for the non-normality in the distribution of financial markets, the paper applies Generalized Error Distribution (GED), instead of the normal distribution, to govern the innovation term. A dynamic back-testing procedure is employed to assess the performance of each model, a family of GARCH and the conditional EVT. The conclusion is that Exponential GARCH yields the best estimate in out-of-sample one day ahead Value-at-Risk (VaR) forecasting. Moreover, the discrepancy of performance between the GARCH and the conditional EVT is indistinguishable.

Keywords: Value-at-Risk, Extreme Value Theory, conditional EVT, backtesting

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Authors: Bo Hu, Shibo Wang, Haoyang Zhang, Jie Shi

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With the development of sonar detection technology, the acoustic stealth technology of underwater vehicles is facing severe challenges. The underwater acoustic coating is developing towards the direction of low-frequency absorption capability and broad absorption frequency bandwidth. In this paper, an acoustic model of underwater acoustic coating of composite material embedded with periodical steel structure is presented. The model has multiple high absorption peaks in the frequency range of 1kHz-8kHz, where achieves high sound absorption and broad bandwidth performance. It is found that the frequencies of the absorption peaks are related to the classic half-wavelength transmission principle. The sound absorption performance of the acoustic model is investigated by the finite element method using COMSOL software. The sound absorption mechanism of the proposed model is explained by the distributions of the displacement vector field. The influence of geometric parameters of periodical steel structure, including thickness and distance, on the sound absorption ability of the proposed model are further discussed. The acoustic model proposed in this study provides an idea for the design of underwater low-frequency broadband acoustic coating, and the results shows the possibility and feasibility for practical underwater application.

Keywords: acoustic coating, composite material, broad frequency bandwidth, sound absorption performance

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Authors: Sajeeha Ansar, Asad Ali Safi, Sheikh Ziauddin, Ahmad R. Shahid, Faraz Ahsan

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The most aggressive form of brain tumor is called glioma. Glioma is kind of tumor that arises from glial tissue of the brain and occurs quite often. A fully automatic 2D-CNN model for brain tumor segmentation is presented in this paper. We performed pre-processing steps to remove noise and intensity variances using N4ITK and standard intensity correction, respectively. We used Keras open-source library with Theano as backend for fast implementation of CNN model. In addition, we used BRATS 2015 MRI dataset to evaluate our proposed model. Furthermore, we have used SimpleITK open-source library in our proposed model to analyze images. Moreover, we have extracted random 2D patches for proposed 2D-CNN model for efficient brain segmentation. Extracting 2D patched instead of 3D due to less dimensional information present in 2D which helps us in reducing computational time. Dice Similarity Coefficient (DSC) is used as performance measure for the evaluation of the proposed method. Our method achieved DSC score of 0.77 for complete, 0.76 for core, 0.77 for enhanced tumor regions. However, these results are comparable with methods already implemented 2D CNN architecture.

Keywords: brain tumor segmentation, convolutional neural networks, deep learning, LGG

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Authors: Neerav Kumar, Naumaan Nayyar, Sharath Kashyap

Abstract:

Most companies see an increase in the adoption of machine learning (ML) applications across internal and external-facing use cases. ML applications vend output either in batch or real-time patterns. A complete batch ML pipeline architecture comprises data sourcing, feature engineering, model training, model deployment, model output vending into a data store for downstream application. Due to unclear role expectations, we have observed that scientists specializing in building and optimizing models are investing significant efforts into building the other components of the architecture, which we do not believe is the best use of scientists’ bandwidth. We propose a system architecture created using AWS services that bring industry best practices to managing the workflow and simplifies the process of model deployment and end-to-end data integration for an ML application. This narrows down the scope of scientists’ work to model building and refinement while specialized data engineers take over the deployment, pipeline orchestration, data quality, data permission system, etc. The pipeline infrastructure is built and deployed as code (using terraform, cdk, cloudformation, etc.) which makes it easy to replicate and/or extend the architecture to other models that are used in an organization.

Keywords: data pipeline, machine learning, AWS, architecture, batch machine learning

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Authors: Kannapha Amaruchkul

Abstract:

We formulate a dynamic overbooking model for a tour operator, in which most reservations contain at least two people. The cancellation rate and the timing of the cancellation may depend on the group size. We propose two overbooking policies, namely economic- and service-based. In an economic-based policy, we want to minimize the expected oversold and underused cost, whereas, in a service-based policy, we ensure that the probability of an oversold situation does not exceed the pre-specified threshold. To illustrate the applicability of our approach, we use tour package data in 2016-2018 from a tour operator in Thailand to build a data-driven robust optimization model, and we tested the proposed overbooking policy in 2019. We also compare the data-driven approach to the conventional approach of fitting data into a probability distribution.

Keywords: applied stochastic model, data-driven robust optimization, overbooking, revenue management, tour operator

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Authors: Moustafa Osman Mohammed

Abstract:

This paper is mapping air quality model to engineering the industrial system that ultimately utilized in extensive range of energy systems, distribution resources, and end-user technologies. The model is determining long-range transport patterns contribution as area source can either traced from 48 hrs backward trajectory model or remotely described from background measurements data in those days. The trajectory model will be run within stable conditions and quite constant parameters of the atmospheric pressure at the most time of the year. Air parcel trajectory is necessary for estimating the long-range transport of pollutants and other chemical species. It provides a better understanding of airflow patterns. Since a large amount of meteorological data and a great number of calculations are required to drive trajectory, it will be very useful to apply HYPSLIT model to locate areas and boundaries influence air quality at regional location of Windsor. 2–days backward trajectories model at high and low concentration measurements below and upward the benchmark which was areas influence air quality measurement levels. The benchmark level will be considered as 30 (μg/m3) as the moderate level for Ontario region. Thereby, air quality model is incorporating a midpoint concept between biotic and abiotic components to broaden the scope of quantification impact. The later outcomes’ theories of environmental obligation suggest either a recommendation or a decision of what is a legislative should be achieved in mitigation measures of air emission impact ultimately.

Keywords: air quality, management systems, environmental impact assessment, industrial ecology, climate change

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Authors: E. Salem

Abstract:

Combustion has been used for a long time as a means of energy extraction. However, in recent years, there has been a further increase in air pollution, through pollutants such as nitrogen oxides, acid etc. In order to solve this problem, there is a need to reduce carbon and nitrogen oxides through learn burning modifying combustors and fuel dilution. A numerical investigation has been done to investigate the effectiveness of several reduced mechanisms in terms of computational time and accuracy, for the combustion of the hydrocarbons/air or diluted with hydrogen in a micro combustor. The simulations were carried out using the ANSYS Fluent 19.1. To validate the results “PREMIX and CHEMKIN” codes were used to calculate 1D premixed flame based on the temperature, composition of burned and unburned gas mixtures. Numerical calculations were carried for several hydrocarbons by changing the equivalence ratios and adding small amounts of hydrogen into the fuel blends then analyzing the flammable limit, the reduction in NOx and CO emissions, then comparing it to experimental data. By solving the conservations equations, several global reduced mechanisms (2-9-12) were obtained. These reduced mechanisms were simulated on a 2D cylindrical tube with dimensions of 40 cm in length and 2.5 cm diameter. The mesh of the model included a proper fine quad mesh, within the first 7 cm of the tube and around the walls. By developing a proper boundary layer, several simulations were performed on hydrocarbon/air blends to visualize the flame characteristics than were compared with experimental data. Once the results were within acceptable range, the geometry of the combustor was modified through changing the length, diameter, adding hydrogen by volume, and changing the equivalence ratios from lean to rich in the fuel blends, the results on flame temperature, shape, velocity and concentrations of radicals and emissions were observed. It was determined that the reduced mechanisms provided results within an acceptable range. The variation of the inlet velocity and geometry of the tube lead to an increase of the temperature and CO2 emissions, highest temperatures were obtained in lean conditions (0.5-0.9) equivalence ratio. Addition of hydrogen blends into combustor fuel blends resulted in; reduction in CO and NOx emissions, expansion of the flammable limit, under the condition of having same laminar flow, and varying equivalence ratio with hydrogen additions. The production of NO is reduced because the combustion happens in a leaner state and helps in solving environmental problems.

Keywords: combustor, equivalence-ratio, hydrogenation, premixed flames

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Authors: Saleh Alkarri, Melinda Frame, Dimple Sharma, John Cairney, Lee Maddan, Jin H. Kim, Jonathan O. Rayner, Teresa M. Bergholz, Muhammad Rabnawaz

Abstract:

Reported herein is an investigation of anti-bacterial and anti-virus properties, mode of action of Mg(OH)₂ and copper-infused Mg(OH)₂ nanoplatelets (NPs) on melt-compounded and thermally embossed polypropylene (PP) surfaces. The anti-viral activity for the NPs was studied in aqueous liquid suspensions against SARS-CoV-2, and the mode of action was investigated on neat NPs and PP samples that were thermally embossed with NPs. Anti-bacterial studies for melt-compounded NPs in PP confirmed approximately 1 log reduction of E. coli populations in 24 h, while for thermally embossed NPs, an 8 log reduction of E. coli populations was observed. In addition, the NPs exhibit anti-viral activity against SARS-CoV-2. Fluorescence microscopy revealed that reactive oxygen species (ROS) is the main mode of action through which Mg(OH)₂ and Cu-Infused Mg(OH)₂act against microbes. Plastics with anti-microbial surfaces from where biocides are non-leachable are highly desirable. This work provides a general fabrication strategy for developing anti-microbial plastic surfaces.

Keywords: anti-microbial activity, E. coli K-12 MG1655, anti-viral activity, SARS-CoV-2, copper-infused magnesium hydroxide, non-leachable, ROS, compounding, surface embossing, dyes

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Authors: Okolie Chukwulozie Paul, Iwenofu Chinwe Onyedika, Sinebe Jude Ebieladoh, M. C. Nwosu

Abstract:

The research work is based on the statistical analysis of the processing data. The essence is to analyze the data statistically and to generate a design model for the production mix of soap manufacturing products in Bejoy manufacturing company Nkpologwu, Aguata Local Government Area, Anambra state, Nigeria. The statistical analysis shows the statistical analysis and the correlation of the data. T test, Partial correlation and bi-variate correlation were used to understand what the data portrays. The design model developed was used to model the data production yield and the correlation of the variables show that the R2 is 98.7%. However, the results confirm that the data is fit for further analysis and modeling. This was proved by the correlation and the R-squared.

Keywords: General Linear Model, correlation, variables, pearson, significance, T-test, soap, production mix and statistic

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Authors: Chandra Prayaga, Aaron Wade, Lakshmi Prayaga, Gopi Shankar Mallu

Abstract:

This paper presents the use of machine learning algorithms to predict the success of students in an introductory physics course. Data having 140 rows pertaining to the performance of two batches of students was used. The lack of sufficient data to train robust machine learning models was compensated for by generating synthetic data similar to the real data. CTGAN and CTGAN with Gaussian Copula (Gaussian) were used to generate synthetic data, with the real data as input. To check the similarity between the real data and each synthetic dataset, pair plots were made. The synthetic data was used to train machine learning models using the PyCaret package. For the CTGAN data, the Ada Boost Classifier (ADA) was found to be the ML model with the best fit, whereas the CTGAN with Gaussian Copula yielded Logistic Regression (LR) as the best model. Both models were then tested for accuracy with the real data. ROC-AUC analysis was performed for all the ten classes of the target variable (Grades A, A-, B+, B, B-, C+, C, C-, D, F). The ADA model with CTGAN data showed a mean AUC score of 0.4377, but the LR model with the Gaussian data showed a mean AUC score of 0.6149. ROC-AUC plots were obtained for each Grade value separately. The LR model with Gaussian data showed consistently better AUC scores compared to the ADA model with CTGAN data, except in two cases of the Grade value, C- and A-.

Keywords: machine learning, student success, physics course, grades, synthetic data, CTGAN, gaussian copula CTGAN

Procedia PDF Downloads 39