Search results for: adaptive thermal comfort model

Authors: Yiyuan David Hu, Alex Lindqwister, Samuel B. Klein, Karen Moodie, Norman A. Paradis

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Introduction: Pseudo-Pulseless Electrical Activity (p-PEA) is a lifeless form of profound cardiac shock characterized by measurable cardiac mechanical activity without clinically detectable pulses. Patients in pseudo-PEA carry different prognoses than those in true PEA and may require different therapies. End-tidal carbon dioxide (ET-CO2) has been studied in ventricular fibrillation and true PEA but in p-PEA. We utilized an hypoxic porcine model to characterize the performance of ET-CO2 in resuscitation from p-PEA. Hypothesis: Capnography correlates to the number of required interventions for resuscitation from p-PEA. Methods: Female swine (N = 14) under intravenous anesthesia were instrumented with aortic and right atrial micromanometer pressure. ECG and ET-CO2 were measured continuously. p-PEA was induced by ventilation with 6% oxygen in 94% nitrogen and was defined as a systolic aortic (Ao) pressure less than 40 mmHg. Pigs were grouped based on the interventions required to achieve ROSC: 100%O2, 100%O2 + CPR, 100%O2 + CPR + epinephrine. Results: End tidal CO2 reliably predicted O2 therapy vs CPR-based interventions needed for resuscitation (Figure 1). Pigs who would recover with 100%O2 only had a mean ET-CO2 slope of 0.039 ± 0.013 [ R2 = 0.68], those requiring oxygen + CPR had a slope of -0.15 ± 0.016 [R2 = 0.95], and those requiring oxygen + CPR + epinephrine had a slope of -0.12 ± 0.031 [R2 = 0.79]. Conclusions: In a porcine model of hypoxic p-PEA, measured ET-CO2 appears to be strongly correlated with the required interventions needed for ROSC. If confirmed clinically, these results indicate that ET-CO2 may be useful in guiding therapy in patients suffering p-PEA cardiac arrest.

Keywords: pseudo-PEA, resuscitation, capnography, hypoxic pseudo-PEA

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Authors: Jan Dahlhaus, Alejandro Cardenas Miranda, Frederik Scholer, Maximilian Leonhardt, Matthias Moullion, Frank Beutenmuller, Julia Eckhardt, Josef Wasner, Frank Nittel, Sebastian Stoll, Devin Atukalp, Daniel Folgmann, Tobias Mayer, Obrad Dordevic, Paul Riley, Jean-Marc Le Peuvedic

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Electrical and hybrid aerospace technologies pose very challenging demands on the battery pack – especially with respect to weight and power. In the Clean Sky 2 research project LiBAT (funded by the EU), the consortium is currently building an ambitious prototype with state-of-the art cells that shows the potential of an intelligent pack design with a high level of integration, especially with respect to thermal management and power electronics. For the latter, innovative multi-level-inverter technology is used to realize the required power converting functions with reduced equipment. In this talk the key approaches and methods of the LiBat project will be presented and central results shown. Special focus will be set on the simulative methods used to support the early design and development stages from an overall system perspective. The applied methods can efficiently handle multiple domains and deal with different time and length scales, thus allowing the analysis and optimization of overall- or sub-system behavior. It will be shown how these simulations provide valuable information and insights for the efficient evaluation of concepts. As a result, the construction and iteration of hardware prototypes has been reduced and development cycles shortened.

Keywords: electric aircraft, battery, Li-ion, multi-level-inverter, Novec

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Authors: Rouhallah Bagheri, Morteza Mahmoudi, Hadi Moheb-Alizadeh

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In this paper, we develop a supplier selection and order allocation multi-objective model in stochastic environment in which purchasing cost, percentage of delivered items with delay and percentage of rejected items provided by each supplier are supposed to be stochastic parameters following any arbitrary probability distribution. To do so, we use dependent chance programming (DCP) that maximizes probability of the event that total purchasing cost, total delivered items with delay and total rejected items are less than or equal to pre-determined values given by decision maker. After transforming the above mentioned stochastic multi-objective programming problem into a stochastic single objective problem using minimum deviation method, we apply a genetic algorithm to get the later single objective problem solved. The employed genetic algorithm performs a simulation process in order to calculate the stochastic objective function as its fitness function. At the end, we explore the impact of stochastic parameters on the given solution via a sensitivity analysis exploiting coefficient of variation. The results show that as stochastic parameters have greater coefficients of variation, the value of objective function in the stochastic single objective programming problem is worsened.

Keywords: dependent chance programming, genetic algorithm, minimum deviation method, order allocation, supplier selection

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Authors: Martyna Ekiert, Andrzej Mlyniec

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Tendons are the biological structures, which primary function is to transfer force generated by muscles to the bones. Unfortunately, damages of tendons are also one of the most common injuries of the human musculoskeletal system. For the most severe cases of tendon rupture, such as the tear of calcaneus tendon or anterior cruciate ligament of the knee, a surgical procedure is the only possible way of full recovery. Tendons used as biological grafts are usually subjected to the process of deep freezing and subsequent thawing. This, in particular for multiple freezing/thawing cycles, may result in changes of tendon internal structure causing deterioration of mechanical properties of the tissue. Therefore, studies on the influence of freezing on tendons biomechanics, including internal water content in soft tissue, seems to be greatly needed. An experimental study of the influence of freezing on mechanical properties of the tendon was performed on fascicles samples dissected form bovine flexor tendons. The preparation procedure was performed with the presence of 0.9% saline solution in order to prevent an excessive tissue drying. All prepared samples were subjected to the different number of freezing/thawing cycles. For freezing part of the protocol we used -80°C temperature while for slow thawing we used fridge temperature (4°C) combined with equalizing temperatures in the standard state (25°C). After final thawing, the mechanical properties of each sample was examined using cyclic loading test. Our results may contribute for better understanding of negative effects of soft tissues freezing, resulting from abnormal thermal expansion of water. This also may help to determine the limit of freezing/thawing cycles disqualifying tissue for surgical purposes and thus help optimize tissues storage conditions.

Keywords: freezing, soft tissue, tendon, bovine fascicles

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Authors: Massimo Ferrari, Maria Sole Pagliari

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Pollution is a classic example of economic externality: agents who produce it do not face direct costs from emissions. Therefore, there are no direct economic incentives for reducing pollution. One way to address this market failure would be directly taxing emissions. However, because emissions are global, governments might as well find it optimal to wait let foreign countries to tax emissions so that they can enjoy the benefits of lower pollution without facing its direct costs. In this paper, we first document the empirical relation between pollution and economic output with static and dynamic regression methods. We show that there is a negative relation between aggregate output and the stock of pollution (measured as the stock of CO₂ emissions). This relationship is also highly non-linear, increasing at an exponential rate. In the second part of the paper, we develop and estimate a two-country, two-sector model for the US and the euro area. With this model, we aim at analyzing how the public sector should respond to higher emissions and what are the direct costs that these policies might have. In the model, there are two types of firms, brown firms (which produce a polluting technology) and green firms. Brown firms also produce an externality, CO₂ emissions, which has detrimental effects on aggregate output. As brown firms do not face direct costs from polluting, they do not have incentives to reduce emissions. Notably, emissions in our model are global: the stock of CO₂ in the economy affects all countries, independently from where it is produced. This simplified economy captures the main trade-off between emissions and production, generating a classic market failure. According to our results, the current level of emission reduces output by between 0.4 and 0.75%. Notably, these estimates lay in the upper bound of the distribution of those delivered by studies in the early 2000s. To address market failure, governments should step in introducing taxes on emissions. With the tax, brown firms pay a cost for polluting hence facing the incentive to move to green technologies. Governments, however, might also adopt a beggar-thy-neighbour strategy. Reducing emissions is costly, as moves production away from the 'optimal' production mix of brown and green technology. Because emissions are global, a government could just wait for the other country to tackle climate change, ripping the benefits without facing any costs. We study how this strategic game unfolds and show three important results: first, cooperation is first-best optimal from a global prospective; second, countries face incentives to deviate from the cooperating equilibria; third, tariffs on imported brown goods (the only retaliation policy in case of deviation from the cooperation equilibrium) are ineffective because the exchange rate would move to compensate. We finally study monetary policy under when costs for climate change rise and show that the monetary authority should react stronger to deviations of inflation from its target.

Keywords: climate change, general equilibrium, optimal taxation, monetary policy

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Authors: Ju Shan Lin

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The challenges for traditional industries in Taiwan the past few years are the changes of overall domestic and foreign industry structure, the entrepreneurs not only need to keep on improving their profession skills but also continuously research and develop new products. It is also necessary for the all traditional industries to keep updating the business strategy, let the enterprises continue to progress, and won't be easily replaced by the other industries. The traditional industry in Taiwan attach great importance to the field of enterprises upgrading and innovation in recent years, by the enterprise innovation and transformation can enhance the overall business situation also enable them to obtain more additional profits than in the past. Except the original industry structure's need to transform and upgrade, the brand's business and marketing strategy are also essential. This study will take a certain plastic company as case analysis, for the brand promotion of traditional industries, brand values and business innovation model for further exploration. It will also be mentioned that the other traditional industries cases which were already achieved success on the enterprise's upgrading and innovation, at the same time, the difficulties which they faced with and the way they overcome will be explored as well. This study will use the case study method combined with expert interviews to discuss and analyze this certain plastic company's current business situation, the existing products and the possible trends in the future. Looking forward to providing an innovative business model that will enable this plastic company to upgrade its corporate image and the brand could transform successfully.

Keywords: brand marketing strategy, enterprise upgrade, industrial transformation, traditional industry

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Authors: Chia-Chen Chen, Mu-Yen Chen

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In recent years, with the vigorous growth of hardware and software technologies of smart mobile devices coupling with the rapid increase of social network influence, mobile commerce also presents the commercial operation mode of the future mainstream. For the time being, SoLoMo has become one of the very popular commercial models, its full name and meaning mainly refer to that users can obtain three key service types through smart mobile devices (Mobile) and omnipresent network services, and then link to the social (Social) web site platform to obtain the information exchange, again collocating with position and situational awareness technology to get the service suitable for the location (Local), through anytime, anywhere and any personal use of different mobile devices to provide the service concept of seamless integration style, and more deriving infinite opportunities of the future. The study tries to explore the use intention of users with SoLoMo mobile application formula, proposing research model to integrate TAM, ISSM, IDT and network externality, and with questionnaires to collect data and analyze results to verify the hypothesis, results show that perceived ease-of-use (PEOU), perceived usefulness (PU), and network externality have significant impact on the use intention with SoLoMo mobile application formula, and the information quality, relative advantages and observability have impacts on the perceived usefulness, and further affecting the use intention.

Keywords: SoLoMo (social, local, and mobile), technology acceptance model, innovation diffusion theory, network externality

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Authors: S. Mahdi S. Kolbadi, Ramezan Ali Alvand, Afrasiab Mirzaei

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In this study, to investigate and analyze the seismic behavior of concrete in open rectangular water storage tanks in two-dimensional and three-dimensional spaces, the Finite Element Method has been used. Through this method, dynamic responses can be investigated together in fluid storages system. Soil behavior has been simulated using tanks boundary conditions in linear form. In this research, in addition to flexibility of wall, the effects of fluid-structure interaction on seismic response of tanks have been investigated to account for the effects of flexible foundation in linear boundary conditions form, and a dynamic response of rectangular tanks in two-dimensional and three-dimensional spaces using finite element method has been provided. The boundary conditions of both rigid and flexible walls in two-dimensional finite element method have been considered to investigate the effect of wall flexibility on seismic response of fluid and storage system. Furthermore, three-dimensional model of fluid-structure interaction issue together with wall flexibility has been analyzed under the three components of earthquake. The obtained results show that two-dimensional model is also accurately near to the results of three-dimension as well as flexibility of foundation leads to absorb received energy and relative reduction of responses.

Keywords: dynamic behavior, flexible wall, fluid-structure interaction, water storage tank

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Authors: Abdulwakeel B. Raji

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This paper introduces a concept of an intelligent virtual learning environment that involves communication between learners and an artificially intelligent teaching agent in an attempt to replicate classroom learning interactions. The benefits of this technology over current e-learning practices is that it creates a virtual classroom where real time adaptive learning interactions are made possible. This is a move away from the static learning practices currently being adopted by e-learning systems. Over the years, artificial intelligence has been applied to various fields, including and not limited to medicine, military applications, psychology, marketing etc. The purpose of e-learning applications is to ensure users are able to learn outside of the classroom, but a major limitation has been the inability to fully replicate classroom interactions between teacher and students. This study used comparative surveys to gain information and understanding of the current learning practices in Nigerian universities and how they compare to these practices compare to the use of a developed e-learning system. The study was conducted by attending several lectures and noting the interactions between lecturers and tutors and as an aftermath, a software has been developed that deploys the use of an artificial intelligent teaching-agent alongside an e-learning system to enhance user learning experience and attempt to create the similar learning interactions to those found in classroom and lecture hall settings. Dialogflow has been used to implement a teaching-agent, which has been developed using JSON, which serves as a virtual teacher. Course content has been created using HTML, CSS, PHP and JAVASCRIPT as a web-based application. This technology can run on handheld devices and Google based home technologies to give learners an access to the teaching agent at any time. This technology also implements the use of definite clause grammars and natural language processing to match user inputs and requests with defined rules to replicate learning interactions. This technology developed covers familiar classroom scenarios such as answering users’ questions, asking ‘do you understand’ at regular intervals and answering subsequent requests, taking advanced user queries to give feedbacks at other periods. This software technology uses deep learning techniques to learn user interactions and patterns to subsequently enhance user learning experience. A system testing has been undergone by undergraduate students in the UK and Nigeria on the course ‘Introduction to Database Development’. Test results and feedback from users shows that this study and developed software is a significant improvement on existing e-learning systems. Further experiments are to be run using the software with different students and more course contents.

Keywords: virtual learning, natural language processing, definite clause grammars, deep learning, artificial intelligence

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Authors: Misuk Kim, Seokho Kang, Jehyuk Lee, Hyunchang Cho, Sungzoon Cho

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In semiconductor manufacturing, virtual metrology (VM) refers to methods to predict properties of a wafer based on machine parameters and sensor data of the production equipment, without performing the (costly) physical measurement of the wafer properties (Wikipedia). Additional benefits include avoidance of human bias and identification of important factors affecting the quality of the process which allow improving the process quality in the future. It is however rare to find VM applied to other areas of manufacturing. In this work, we propose to use VM to copper clad laminate (CCL) manufacturing. CCL is a core element of a printed circuit board (PCB) which is used in smartphones, tablets, digital cameras, and laptop computers. The manufacturing of CCL consists of three processes: Treating, lay-up, and pressing. Treating, the most important process among the three, puts resin on glass cloth, heat up in a drying oven, then produces prepreg for lay-up process. In this process, three important quality factors are inspected: Treated weight (T/W), Minimum Viscosity (M/V), and Gel Time (G/T). They are manually inspected, incurring heavy cost in terms of time and money, which makes it a good candidate for VM application. We developed prediction models of the three quality factors T/W, M/V, and G/T, respectively, with process variables, raw material, and environment variables. The actual process data was obtained from a CCL manufacturer. A variety of variable selection methods and learning algorithms were employed to find the best prediction model. We obtained prediction models of M/V and G/T with a high enough accuracy. They also provided us with information on “important” predictor variables, some of which the process engineers had been already aware and the rest of which they had not. They were quite excited to find new insights that the model revealed and set out to do further analysis on them to gain process control implications. T/W did not turn out to be possible to predict with a reasonable accuracy with given factors. The very fact indicates that the factors currently monitored may not affect T/W, thus an effort has to be made to find other factors which are not currently monitored in order to understand the process better and improve the quality of it. In conclusion, VM application to CCL’s treating process was quite successful. The newly built quality prediction model allowed one to reduce the cost associated with actual metrology as well as reveal some insights on the factors affecting the important quality factors and on the level of our less than perfect understanding of the treating process.

Keywords: copper clad laminate, predictive modeling, quality control, virtual metrology

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Authors: Henar Martín-Sanz García, Eleni Chatzi, Eugen Brühwiler

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Located on the shore of Geneva Lake, in Switzerland, the Chillon Viaducts are two parallel structures consisted of post-tensioned concrete box girders, with a total length of 2 kilometers and 100m spans. Built in 1969, the bridges currently accommodate a traffic load of 50.000 vehicles per day, thereby holding a key role both in terms of historic value as well as socio-economic significance. Although several improvements have been carried out in the past two decades, recent inspections demonstrate an Alkali-Aggregate reaction in the concrete deck and piers reducing the concrete strength. In order to prevent further expansion of this issue, a layer of 40 mm of Ultra High Performance Fiber Reinforced cement-based Composite (UHPFRC) (incorporating rebars) was casted over the slabs, acting as a waterproof membrane and providing significant increase in resistance of the bridge structure by composite UHPFRC – RC composite action in particular of the deck slab. After completing the rehabilitation works, a Structural Monitoring campaign was installed on the deck slab in one representative span, based on accelerometers, strain gauges, thermal and humidity sensors. This campaign seeks to reveal information on the behavior of UHPFRC-concrete composite systems, such as increase in stiffness, fatigue strength, durability and long-term performance. Consequently, the structural monitoring is expected to last for at least three years. A first insight of the analyzed results from the initial months of measurements is presented herein, along with future improvements or necessary changes on the deployment.

Keywords: composite materials, rehabilitation, structural health monitoring, UHPFRC

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Authors: Mina Ganji Morad, Maziar Azadisoleimanieh, Sina Ganji Morad

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A green roof is formed by green plants alive and has many positive impacts in the regional climatic, as well as indoor. Green roof system to prevent solar radiation plays a role in the cooling space. The cooling is done by reducing thermal fluctuations on the exterior of the roof and by increasing the roof heat capacity which cause to keep the space under the roof cool in the summer and heating rate increases during the winter. A roof garden is one of the recommended ways to reduce energy consumption in large cities. Despite the scale of the city green roofs have effective functions, such as beautiful view of city and decontaminating the urban landscape and reduce mental stress, and in an exchange of energy and heat from outside to inside spaces. This article is based on a review of 20 articles and 10 books and valid survey results on the positive effects of green roofs to prevent energy waste in the building. According to these publications, three of the conventional roof, green roof typical and green roof with certain administrative details (layers of glass) and the use of resistant plants and shrubs have been analyzed and compared their heat transfer. The results of these studies showed that one of the best green roof systems for mountainous climate is tree and shrub system that in addition to being resistant to climate change in mountainous regions, will benefit from the other advantages of green roof. Due to the severity of climate change in mountainous areas it is essential to prevent the waste of buildings heating and cooling energy. Proper climate design can greatly help to reduce energy.

Keywords: green roof, heat transfer, reducing energy consumption, mountainous areas, sustainable architecture

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Authors: Marcin Szlachetka, Konrad Pietrykowski

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Modeling of a combustion process in a 9-cylinder aircraft engine is presented. The simulations of the combustion process in the IC engine have provided the information on the spatial and time distributions of selected quantities within the combustion chamber of the engine. The numerical analysis results have been compared with the results of indication process of the engine on the test stand. Modeling of combustion process an auto-ignited IC engine in the AVL Fire was carried out within the study. For the calculations, a ECFM-3Z model was used. Verification of simulation results was carried out by comparison of the pressure in the cylinder. The courses of indicated pressure, obtained from the simulations and during the engine tests mounted on a test stand were compared. The engine was braked by the propeller, which results in an adequate external power characteristics. The test object is a modified ASz-62IR engine with the injection system. The engine was running at take-off power. To check the optimum ignition timing regarding power, calculations, tests were performed for 7 different moments of ignition. The analyses of temperature distribution in the cylinder depending on the moments of ignition were carried out. Additional the course of pressure in the cylinder at different angles of ignition delays of the second spark plug were examined. The swirling of the mixture in the combustion chamber was also analysed. It has been shown that the largest vortexes occur in the middle of the chamber, and gets smaller, closer to the combustion chamber walls. This work has been financed by the Polish National Centre for Research and Development, INNOLOT, under Grant Agreement No. INNOLOT/I/1/NCBR/2013.

Keywords: CFD, combustion, internal combustion engine, aircraft engine

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Authors: Abhishek Mukherjee, Juan C. Cajas, Jenny Suckale, Guillaume Houzeaux, Oriol Lehmkuhl, Simone Marras

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The investigation of tsunami flow characteristics and the quantification of tsunami energy reduction through the coastal vegetation is important to understand the protective benefits of nature-based mitigation parks. In the present study, a three-dimensional non-hydrostatic incompressible Computational Fluid Dynamics model with a two-way coupling enabled fluid-structure interaction approach (FSI) is used. After validating the numerical model against experimental data, tsunami flow characteristics have been investigated by varying vegetation density, modulus of elasticity, the gap between stems, and arrangement or distribution of vegetation patches. Streamwise depth average velocity profiles, turbulent kinetic energy, energy flux reflection, and dissipation extracted by the numerical study will be presented in this study. These diagnostics are essential to assess the importance of different parameters to design the proper coastal defense systems. When a tsunami wave reaches the shore, it transforms into undular bores, which induce scour around offshore structures and sediment transport. The bed shear stress, instantaneous turbulent kinetic energy, and the vorticity near-bed will be presented to estimate the importance of vegetation to prevent tsunami-induced scour and sediment transport.

Keywords: coastal defense, energy flux, fluid-structure interaction, natural hazards, sediment transport, tsunami mitigation

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Authors: Kubra Dogan, Fatih Tornuk

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Due to increasing consumer demand for the high-quality food products and awareness regarding the health benefits of different nutrients in food minimal processing becomes more popular in modern food preservation. To date, heat treatment is often used for inactivation of spoilage microorganisms in foods. However, it may cause significant changes in the quality and nutritional properties of food. In order to overcome the detrimental effects of heat treatment, several alternatives of non-thermal microbial inactivation processes have been investigated. Ultraviolet (UV) inactivation is a promising and feasible method for better quality and longer shelf life as an alternative to heat treatment, which aims to inhibit spoilage and pathogenic microorganisms and to inactivate the enzymes in vegetable juice production. UV-C is a sub-class of UV treatment which shows the highest microcidal effect between 250-270 nm. The wavelength of 254 nm is used for the surface disinfection of certain liquid food products such as vegetable juice. Effects of UV-C treatment on microbiological load and quality parameter of vegetable juice which is a mix of celery, carrot, lemon and orange was investigated. Our results showed that storing of UV-C applied vegetable juice for three months, reduced the count of TMAB by 3.5 log cfu/g and yeast-mold by 2 log cfu/g compared to control sample. Total phenolic content was found to be 514.3 ± 0.6 mg gallic acid equivalent/L, and there wasn’t a significant difference compared to control. The present work suggests that UV-C treatment is an alternative method for disinfection of vegetable juice since it enables adequate microbial inactivation, longer shelf life and has minimal effect on degradation of quality parameters of vegetable juice.

Keywords: heat treatment, phenolic content, shelf life, ultraviolet (UV-C), vegetable juice

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Authors: Sumandeep Kaur, Allam Srinivasa Rao, Mula Jayasimhadri

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In recent years, rare earth (RE) ions doped inorganic luminescent materials are seeking great attention due to their excellent physical and chemical properties. These materials offer high thermal and chemical stability and exhibit good luminescence properties due to the presence of RE ions. The luminescent properties of these materials are attributed to their intra-configurational f-f transitions in RE ions. A series of Tb³⁺ doped calcium aluminozincate has been synthesized via sol-gel method. The structural and morphological studies have been carried out by recording X-ray diffraction patterns and SEM image. The luminescent spectra have been recorded for a comprehensive study of their luminescence properties. The XRD profile reveals the single-phase orthorhombic crystal structure with an average crystallite size of 65 nm as calculated by using DebyeScherrer equation. The SEM image exhibits completely random, irregular morphology of micron size particles of the prepared samples. The optimization of luminescence has been carried out by varying the dopant Tb³⁺ concentration within the range from 0.5 to 2.0 mol%. The as-synthesized phosphors exhibit intense emission at 544 nm pumped at 478 nm excitation wavelength. The optimized Tb³⁺ concentration has been found to be 1.0 mol% in the present host lattice. The decay curves show bi-exponential fitting for the as-synthesized phosphor. The colorimetric studies show green emission with CIE coordinates (0.334, 0.647) lying in green region for the optimized Tb³⁺ concentration. This report reveals the potential utility of Tb³⁺ doped calcium aluminozincate phosphors for display and solid-state lighting devices.

Keywords: concentration quenching, phosphor, photoluminescence, XRD

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Authors: Walailak Atthirawong

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By the end of 2015, the Association of Southeast Asian Nations (ASEAN) countries proclaim to transform into the next stage of an economic era by having a single market and production base called ASEAN Economic Community (AEC). One objective of the AEC is to establish ASEAN as a single market and one production base making ASEAN highly competitive economic region and competitive with new mechanisms. As a result, it will open more opportunities to enterprises in both trade and investment, which offering a competitive market of US$ 2.6 trillion and over 622 million people. Location decision plays a key role in achieving corporate competitiveness. Hence, it may be necessary for enterprises to redesign their supply chains via enlarging a new production base which has low labor cost, high labor skill and numerous of labor available. This strategy will help companies especially for apparel industry in order to maintain a competitive position in the global market. Therefore, in this paper a generic model for location selection decision for Thai apparel industry using Fuzzy Analytical Network Process (FANP) is proposed. Myanmar, Vietnam and Cambodia are referred for alternative location decision from interviewing expert persons in this industry who have planned to enlarge their businesses in AEC countries. The contribution of this paper lies in proposing an approach model that is more practical and trustworthy to top management in making a decision on location selection.

Keywords: apparel industry, ASEAN Economic Community (AEC), Fuzzy Analytical Network Process (FANP), location decision

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Authors: Yazan M. Alatrash, Han-ok Kang, Hyun-gi Yoon, Shen Zhang, Juhyeon Yoon

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Flow coastdown phenomena are very important to secure nuclear fuel integrity during loss of off-site power accidents. In this study, primary coolant flow coastdown phenomena are investigated for the Jordan Research and Training Reactor (JRTR) using a simulation software package, Modular Modelling System (MMS). Two MMS models are built. The first one is a simple model to investigate the characteristics of the primary coolant pump only. The second one is a model for a simulation of the Primary Coolant System (PCS) loop, in which all the detailed design data of the JRTR PCS system are modelled, including the geometrical arrangement data. The same design data for a PCS pump are used for both models. Coastdown curves obtained from the two models are compared to study the PCS loop coolant inertia effect on a flow coastdown. Results showed that the loop coolant inertia effect is found to be small in the JRTR PCS loop, i.e., about one second increases in a coastdown half time required to halve the coolant flow rate. The effects of different flywheel inertia on the flow coastdown are also investigated. It is demonstrated that the coastdown half time increases with the flywheel inertia linearly. The designed coastdown half time is proved to be well above the design requirement for the fuel integrity.

Keywords: flow coastdown, loop inertia, modelling, research reactor

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Authors: Junior George Martin

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The purpose of this study was to explore college instructors’ integration of technology in their content area curriculum. The instructors indicated that they were in need of additional training to successfully integrate technology in their subject areas. The findings point to the implementation of a proposed the Technological, Pedagogical, and Content Knowledge (TPACK) model professional development workshop to satisfactorily address the weaknesses of the instructors in technology integration. The professional development workshop is proposed as a rational solution to adequately address the instructors’ inability to the successful integration of technology in their subject area in an effort to improve their pedagogy. The intense workshop would last for 5 days and will be designed to provide instructors with training in areas such as a use of technology applications and tools, and using modern methodologies to improve technology integration. Exposing the instructors to the specific areas identified will address the weaknesses they demonstrated during the study. Professional development is deemed the most appropriate intervention based on the opportunities it provides the instructors to access hands-on training to overcome their weaknesses. The purpose of the TPACK professional development workshop will be to improve the competence of the instructors so that they are adequately prepared to integrate technology successfully in their curricula. At the end of the period training, the instructors are expected to adopt strategies that will have a positive impact on the learning experiences of the students.

Keywords: higher education, modern technology tools, professional development, technology integration

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Authors: Omer Burak Iskender, Keck Voon Ling, Vincent Dubanchet, Luca Simonini

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This paper presents Guidance and Control (G&C) strategy to approach and synchronize with potentially rotating targets. The proposed strategy generates and tracks a safe trajectory for space servicing missions, including tasks like approaching, inspecting, and capturing. The main objective of this paper is to validate the G&C laws using a Hardware-In-the-Loop (HIL) setup with realistic rendezvous and docking equipment. Throughout this work, the assumption of full relative state feedback is relaxed by onboard sensors that bring realistic errors and delays and, while the proposed closed loop approach demonstrates the robustness to the above mentioned challenge. Moreover, G&C blocks are unified via the Model Predictive Control (MPC) paradigm, and the coupling between translational motion and rotational motion is addressed via dual quaternion based kinematic description. In this work, G&C is formulated as a convex optimization problem where constraints such as thruster limits and the output constraints are explicitly handled. Furthermore, the Monte-Carlo method is used to evaluate the robustness of the proposed method to the initial condition errors, the uncertainty of the target's motion and attitude, and actuator errors. A capture scenario is tested with the robotic test bench that has onboard sensors which estimate the position and orientation of a drifting satellite through camera imagery. Finally, the approach is compared with currently used robust H-infinity controllers and guidance profile provided by the industrial partner. The HIL experiments demonstrate that the proposed strategy is a potential candidate for future space servicing missions because 1) the algorithm is real-time implementable as convex programming offers deterministic convergence properties and guarantee finite time solution, 2) critical physical and output constraints are respected, 3) robustness to sensor errors and uncertainties in the system is proven, 4) couples translational motion with rotational motion.

Keywords: dual quaternion, model predictive control, real-time experimental test, rendezvous and docking, spacecraft autonomy, space servicing

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Authors: N. K. Thakur

Abstract:

A major proportion of the formations drilled for the production of hydrocarbons consists of clay containing shales. The petroleum industry has hugely investigated the role of clay minerals and their subsequent effect on wellbore stability during the drilling and production of hydrocarbons. It has been found that when the shale formation comes in contact with water-based drilling fluid, the interaction of clay minerals like montmorillonite with infiltrated water leads to hydration of the clay minerals, which causes shale swelling. When shale swelling proceeds further, it may lead to major drilling complications like caving, pipe sticking, which invariably influences wellbore stability, wellbore diameter, the mechanical strength of shale, stress distribution in the wellbore, etc. These problems ultimately lead to an increase in nonproductive time and additional costs during drilling. Several additives are used to prevent shale instability. Among the popular additives used for shale inhibition in drilling muds, ionic liquids and nanoparticles are emerging to be the best additives. The efficiency of the proposed additives will be studied and compared with conventional clay inhibitors like KCl. The main objective is to develop a highly efficient water-based mud for mitigating shale instability and reducing fluid loss which is environmentally friendly and does not alter the formation permeability. The use of nanoparticles has been exploited to enhance the rheological and fluid loss properties in water-based drilling fluid ionic liquid have attracted significant research interest due to its unique thermal stability. It is referred to as ‘green chemical’. The preliminary experimental studies performed are promising. The application of more effective mud additives is always desirable to make the drilling process techno-economically proficient.

Keywords: ionic liquid, shale inhibitor, wellbore stability, unconventional

Procedia PDF Downloads 186

Authors: Kishore Kumar R., Kaustav Sengupta, Shalini Sood Sehgal, Poornima Santhanam

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Fashion is a human expression that is constantly changing. One of the prime factors that consistently influences fashion is the change in colour preferences. The role of colour in our everyday lives is very significant. It subconsciously explains a lot about one’s mindset and mood. Analyzing the colours by extracting them from the outfit images is a critical study to examine the individual’s/consumer behaviour. Several research works have been carried out on extracting colours from images, but to the best of our knowledge, there were no studies that extract colours to specific apparel and identify colour patterns geographically. This paper proposes a framework for accurately extracting colours from T-shirt images and predicting dominant colours geographically. The proposed method consists of two stages: first, a U-Net deep learning model is adopted to segment the T-shirts from the images. Second, the colours are extracted only from the T-shirt segments. The proposed method employs the iMaterialist (Fashion) 2019 dataset for the semantic segmentation task. The proposed framework also includes a mechanism for gathering data and analyzing India’s general colour preferences. From this research, it was observed that black and grey are the dominant colour in different regions of India. The proposed method can be adapted to study fashion’s evolving colour preferences.

Keywords: colour analysis in t-shirts, convolutional neural network, encoder-decoder, k-means clustering, semantic segmentation, U-Net model

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Authors: Mercedes Bertotto, Marcelo Bello, Hector Goicoechea, Veronica Fusca

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The National Service of Agri-Food Health and Quality (SENASA), controls honey to detect contamination by synthetic or natural chemical substances and establishes and controls the traceability of the product. The utility of near-infrared spectroscopy for the detection of adulteration of honey with high fructose corn syrup (HFCS) was investigated. First of all, a mixture of different authentic artisanal Argentinian honey was prepared to cover as much heterogeneity as possible. Then, mixtures were prepared by adding different concentrations of high fructose corn syrup (HFCS) to samples of the honey pool. 237 samples were used, 108 of them were authentic honey and 129 samples corresponded to honey adulterated with HFCS between 1 and 10%. They were stored unrefrigerated from time of production until scanning and were not filtered after receipt in the laboratory. Immediately prior to spectral collection, honey was incubated at 40°C overnight to dissolve any crystalline material, manually stirred to achieve homogeneity and adjusted to a standard solids content (70° Brix) with distilled water. Adulterant solutions were also adjusted to 70° Brix. Samples were measured by NIR spectroscopy in the range of 650 to 7000 cm⁻¹. The technique of specular reflectance was used, with a lens aperture range of 150 mm. Pretreatment of the spectra was performed by Standard Normal Variate (SNV). The ant colony optimization genetic algorithm sample selection (ACOGASS) graphical interface was used, using MATLAB version 5.3, to select the variables with the greatest discriminating power. The data set was divided into a validation set and a calibration set, using the Kennard-Stone (KS) algorithm. A combined method of Potential Functions (PF) was chosen together with Partial Least Square Linear Discriminant Analysis (PLS-DA). Different estimators of the predictive capacity of the model were compared, which were obtained using a decreasing number of groups, which implies more demanding validation conditions. The optimal number of latent variables was selected as the number associated with the minimum error and the smallest number of unassigned samples. Once the optimal number of latent variables was defined, we proceeded to apply the model to the training samples. With the calibrated model for the training samples, we proceeded to study the validation samples. The calibrated model that combines the potential function methods and PLSDA can be considered reliable and stable since its performance in future samples is expected to be comparable to that achieved for the training samples. By use of Potential Functions (PF) and Partial Least Square Linear Discriminant Analysis (PLS-DA) classification, authentic honey and honey adulterated with HFCS could be identified with a correct classification rate of 97.9%. The results showed that NIR in combination with the PT and PLS-DS methods can be a simple, fast and low-cost technique for the detection of HFCS in honey with high sensitivity and power of discrimination.

Keywords: adulteration, multivariate analysis, potential functions, regression

Procedia PDF Downloads 119

Authors: Pukhtoon Yar

Abstract:

Peshawar City is experiencing a rapid spatial urban growth primarily as a result of high rate of urbanization along with economic development. This paper was designed to understand the impacts of urbanization on agriculture land use change by particularly focusing on land use change trajectories from the past (1991-2014). We used Landsat imageries (30 meters) for1991along with Spot images (2.5 meters) for year 2014. . The ground truthing of the satellite data was performed by collecting information from Peshawar Development Authority, revenue department, real estate agents and interviews with the officials of city administration. The temporal satellite images were processed by applying supervised maximum likelihood classification technique in ArcGIS 9.3. The procedure resulted into five main classes of land use i.e. built-up area, farmland, barren land, cultivable-wasteland and water bodies. The analysis revealed that, in Peshawar City the built-up environment has been doubled from 8.1 percent in 1991 to over 18.2 percent in 2014 by predominantly encroaching land producing food. Furthermore, the CA-Markov Model predicted that the area under impervious surfaces would continue to flourish during the next three decades. This rapid increase in built-up area is accredited to the lack of proper land use planning and management, which has caused chaotic urban sprawl with detrimental social and environmental consequences.

Keywords: Urban Expansion, Land use, GIS, Remote Sensing, Markov Model, Peshawar City

Procedia PDF Downloads 182

Authors: Yongseok Hong, Kurt Louis Solis

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In the present study, a hybrid sorbent using the metal organic framework (MOF), UiO-66, and powdered activated carbon (pAC) is synthesized to remove cationic and anionic metals simultaneously. UiO-66 is an octahedron-shaped MOF with a Zr₆O₄(OH)₄ metal node and 1,4-benzene dicarboxylic acid (BDC) organic linker. Zr-based MOFs are attractive for trace element remediation in wastewaters, because Zr is relatively non-toxic as compared to other classes of MOF and, therefore, it will not cause secondary pollution. Most remediation studies with UiO-66 target anions such as fluoride, but trace element oxyanions such as arsenic, selenium, and antimony have also been investigated. There have also been studies involving mercury removal by UiO-66 derivatives, however these require post-synthetic modifications or have lower effective surface areas. Activated carbon is known for being a readily available, well-studied, effective adsorbent for metal contaminants. Solvothermal method was employed to prepare hybrid sorbent from UiO66 and activated carbon, which could be used to remove mercury and selenium simultaneously. The hybrid sorbent was characterized using FSEM-EDS, FT-IR, XRD, and TGA. The results showed that UiO66 and activated carbon are successfully composited. From BET studies, the hybrid sorbent has a SBET of 1051 m² g⁻¹. Adsorption studies were performed, where the hybrid showed maximum adsorption of 204.63 mg g⁻¹ and 168 mg g⁻¹ for Hg (II) and selenite, respectively, and follows the Langmuir model for both species. Kinetics studies have revealed that the Hg uptake of the hybrid is pseudo-2nd order and has rate constant of 5.6E-05 g mg⁻¹ min⁻¹ and the selenite uptake follows the simplified Elovich model with α = 2.99 mg g⁻¹ min⁻¹, β = 0.032 g mg⁻¹.

Keywords: adsorption, flue gas wastewater, mercury, selenite, metal organic framework

Procedia PDF Downloads 173

Authors: Alessandro Balbo, Gianvito Colucci, Matteo Nicoli, Laura Savoldi

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Hydrogen is expected to become a game changer in the energy transition, especially enabling sector coupling possibilities and the decarbonization of hard-to-abate end-uses. The Italian National Recovery and Resilience Plan identifies hydrogen as one of the key elements of the ecologic transition to meet international decarbonization objectives, also including it in several pilot projects for the early development in Italy. This matches the European energy strategy, which aims to make hydrogen a leading energy carrier of the future, setting ambitious goals to be accomplished by 2030. The huge efforts needed to achieve the announced targets require to carefully investigate of their feasibility in terms of economic expenditures and technical aspects. In order to quantitatively assess the hydrogen potential within the Italian context and the feasibility of the planned investments and projects, this work uses the TEMOA-Italy energy system model to study pathways to meet the strict objectives above cited. The possible hydrogen development has been studied both in the supply-side and demand-side of the energy system, also including storage options and distribution chains. The assessment comprehends alternative hydrogen production technologies involved in a competition market, reflecting the several possible investments declined by the Italian National Recovery and Resilience Plan to boost the development and spread of this infrastructure, including the sector coupling potential with natural gas through the currently existing infrastructure and CO2 capture for the production of synfuels. On the other hand, the hydrogen end-uses phase covers a wide range of consumption alternatives, from fuel-cell vehicles, for which both road and non-road transport categories are considered, to steel, and chemical industries uses and cogeneration for residential and commercial buildings. The model includes both high and low TRL technologies in order to provide a consistent outcome for the future decades as it does for the present day, and since it is developed through the use of an open-source code instance and database, transparency and accessibility are fully granted.

Keywords: decarbonization, energy system optimization models, hydrogen, open-source modeling, TEMOA

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Authors: Ning Gong, Michael Korostelev, Qiangguo Ren, Li Bai, Saroj K. Biswas, Frank Ferrese

Abstract:

This paper investigates the joint effect of the interconnected (n,k)-star network topology and Multi-Agent automated control on restoration and reconfiguration of power systems. With the increasing trend in development in Multi-Agent control technologies applied to power system reconfiguration in presence of faulty components or nodes. Fault tolerance is becoming an important challenge in the design processes of the distributed power system topology. Since the reconfiguration of a power system is performed by agent communication, the (n,k)-star interconnected network topology is studied and modeled in this paper to optimize the process of power reconfiguration. In this paper, we discuss the recently proposed (n,k)-star topology and examine its properties and advantages as compared to the traditional multi-bus power topologies. We design and simulate the topology model for distributed power system test cases. A related lemma based on the fault tolerance and conditional diagnosability properties is presented and proved both theoretically and practically. The conclusion is reached that (n,k)-star topology model has measurable advantages compared to standard bus power systems while exhibiting fault tolerance properties in power restoration, as well as showing efficiency when applied to power system route discovery.

Keywords: (n, k)-star topology, fault tolerance, conditional diagnosability, multi-agent system, automated power system

Procedia PDF Downloads 508

Authors: Ning Gong, Michael Korostelev, Qiangguo Ren, Li Bai, Saroj Biswas, Frank Ferrese

Abstract:

This paper investigates the joint effect of the interconnected (n,k)-star network topology and Multi-Agent automated control on restoration and reconfiguration of power systems. With the increasing trend in development in Multi-Agent control technologies applied to power system reconfiguration in presence of faulty components or nodes. Fault tolerance is becoming an important challenge in the design processes of the distributed power system topology. Since the reconfiguration of a power system is performed by agent communication, the (n,k)-star interconnected network topology is studied and modeled in this paper to optimize the process of power reconfiguration. In this paper, we discuss the recently proposed (n,k)-star topology and examine its properties and advantages as compared to the traditional multi-bus power topologies. We design and simulate the topology model for distributed power system test cases. A related lemma based on the fault tolerance and conditional diagnosability properties is presented and proved both theoretically and practically. The conclusion is reached that (n,k)-star topology model has measurable advantages compared to standard bus power systems while exhibiting fault tolerance properties in power restoration, as well as showing efficiency when applied to power system route discovery.

Keywords: (n, k)-star topology, fault tolerance, conditional diagnosability, multi-agent system, automated power system

Procedia PDF Downloads 458

Authors: Aleksandra Łochowicz, Daria Świętochowska, Loredano Pollegioni, Nazim Ocal, Franck Charmantray, Laurence Hecquet, Katarzyna Szymańska

Abstract:

Multienzymatic cascade reactions are nowadays widely used in pharmaceutical, chemical and cosmetics industries to produce high valuable compounds. They can be carried out in two ways, step by step and one-pot. If two or more enzymes are in the same reaction vessel is necessary to work out the compromise to run the reaction in optimal conditions for each enzyme. So far most of the reports of multienzymatic cascades concern on usage of free enzymes. Unfortunately using free enzymes as catalysts of reactions accomplish high cost. What is more, free enzymes are soluble in solvents which makes reuse impossible. To overcome this obstacle enzymes can be immobilized what provides heterogeneity of biocatalyst that enables reuse and easy separation of the enzyme from solvents and reaction products. Usually, immobilization increase also the thermal and operational stability of enzyme. The advantages of using immobilized multienzymes are enhanced enzyme stability, improved cascade enzymatic activity via substrate channeling, and ease of recovery for reuse. The one-pot immobilized multienzymatic cascade can be carried out in mixed or coimmobilized type. When biocatalysts are coimmobilized on the same carrier the are in close contact to each other which increase the reaction rate and catalytic efficiency, and eliminate the lag time. However, in this type providing the optimal conditions both in the process of immobilization and cascade reaction for each enzyme is complicated. Herein, we examined immobilization of 3 enzymes: D-amino acid oxidase from Rhodotorula gracilis, commercially available catalase and transketolase from Geobacillus stearothermophilus. As a support we used silica monoliths with hierarchical structure of pores. Then we checked their stability and reusability in one-pot cascade of L-erythrulose and hydroxypuryvate acid synthesis.

Keywords: biocatalysts, enzyme immobilization, multienzymatic reaction, silica carriers

Procedia PDF Downloads 146

Authors: Young Yoon, Jinsoo Kim

Abstract:

The adoption of information and communication technologies (ICT) in all industry is growing under industry 4.0. Many oil companies also are increasingly adopting ICT to improve the efficiency of existing operations, take more accurate and quicker decision making and reduce entire cost by optimization. It is true that ICT is playing an important role in the process of unconventional oil and gas development and companies must take advantage of ICT to gain competitive advantage. In this study, real option approach has been applied to Unconventional gas R&D project to evaluate ICT of them. Many unconventional gas reserves such as shale gas and coal-bed methane(CBM) has developed due to technological improvement and high energy price. There are many uncertainties in unconventional development on the three stage(Exploration, Development, Production). The traditional quantitative benefits-cost method, such as net present value(NPV) is not sufficient for capturing ICT value. We attempted to evaluate the ICT valuation by applying the compound option model; the model is applied to real CBM project case, showing how it consider uncertainties. Variables are treated as uncertain and a Monte Carlo simulation is performed to consider variables effect. Acknowledgement—This work was supported by the Energy Efficiency & Resources Core Technology Program of the Korea Institute of Energy Technology Evaluation and Planning (KETEP) granted financial resource from the Ministry of Trade, Industry & Energy, Republic of Korea (No. 20152510101880) and by the National Research Foundation of Korea Grant funded by the Korean Government (NRF-205S1A3A2046684).

Keywords: information and communication technologies, R&D, real option, unconventional gas

Procedia PDF Downloads 228