Search results for: dependency analysis

Authors: Valentina Bonetti

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Exergy analysis successfully helps optimizing processes in various sectors. In the built environment, a second-law approach can enhance potential interactions between constructions and their surrounding environment and minimise fossil fuel requirements. Despite the research done in this field in the last decades, practical applications are hard to encounter, and few integrated exergy simulators are available for building designers. Undoubtedly, an obstacle for the diffusion of exergy methods is the strong dependency of results on the definition of its 'reference state', a highly controversial issue. Since exergy is the combination of energy and entropy by means of a reference state (also called "reference environment", or "dead state"), the reference choice is crucial. Compared to other classical applications, buildings present two challenging elements: They operate very near to the reference state, which means that small variations have relevant impacts, and their behaviour is dynamical in nature. Not surprisingly then, the reference state definition for the built environment is still debated, especially in the case of dynamic assessments. Among the several characteristics that need to be defined, a crucial decision for a dynamic analysis is between a fixed reference environment (constant in time) and a variable state, which fluctuations follow the local climate. Even if the latter selection is prevailing in research, and recommended by recent and widely-diffused guidelines, the fixed reference has been analytically demonstrated as the only choice which defines exergy as a proper function of the state in a fluctuating environment. This study investigates the impact of that crucial choice: Fixed or variable reference. The basic element of the building energy chain, the envelope, is chosen as the object of investigation as common to any building analysis. Exergy fluctuations in the building envelope of a case study (a typical house located in a Mediterranean climate) are confronted for each time-step of a significant summer day, when the building behaviour is highly dynamical. Exergy efficiencies and fluxes are not familiar numbers, and thus, the more easy-to-imagine concept of exergy storage is used to summarize the results. Trends obtained with a fixed and a variable reference (outside air) are compared, and their meaning is discussed under the light of the underpinning dynamical energy analysis. As a conclusion, a fixed reference state is considered the best choice for dynamic exergy analysis. Even if the fixed reference is generally only contemplated as a simpler selection, and the variable state is often stated as more accurate without explicit justifications, the analytical considerations supporting the adoption of a fixed reference are confirmed by the usefulness and clarity of interpretation of its results. Further discussion is needed to address the conflict between the evidence supporting a fixed reference state and the wide adoption of a fluctuating one. A more robust theoretical framework, including selection criteria of the reference state for dynamical simulations, could push the development of integrated dynamic tools and thus spread exergy analysis for the built environment across the common practice.

Keywords: exergy, reference state, dynamic, building

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Authors: Weiran An, Junyou Shi

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Health management has become one of the design goals in the research and development of new generation avionics systems, and is an important complement and development for the testability and fault diagnosis technology. Currently, the research and application for avionics system health dividing and diagnosis technology is still at the starting stage, lack of related technologies and methods reserve. In this paper, based on the health three-state dividing of avionics products, state lateral transfer coupling modeling and diagnosis reasoning method considering sub-health are researched. With the study of typical case application, the feasibility and correctness of the method and the software are verified.

Keywords: sub-health, diagnosis reasoning, three-valued coupled logic, extended dependency model, avionics

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Authors: Gaoyuan Wang, Tian Chen

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China’s emission peak and carbon neutrality strategies lead to the transformation of development patterns and call for new green urban design thinking. This paper begins by revealing the evolution of green urban design thinking during the periods of carbon enlightenment, carbon dependency, and carbon decoupling from the perspective of the energy transition. Combined with the current energy situation, national strengths, and technological trends, the emergence of green urban design towards carbon neutrality becomes inevitable. Based on the preliminary analysis of its connotation, the characteristics of the new type of green urban design are generalized as low-carbon orientation, carbon-related objects, carbon-reduction means, and carbon-control patterns. Its theory is briefly clarified in terms of the human-earth synergism, quality-energy interconnection, and form-flow interpromotion. Then, its mechanism is analyzed combined with the core tasks of carbon neutrality, and the scope of design issues is defined, including carbon flow mapping, carbon source regulation, carbon sink construction, and carbon emission management. Finally, a multi-scale spatial response system is proposed across the region, city, cluster, and neighborhood level. The discussion aims to provide support for the innovation of green urban design theories and methods in the context of peak neutrality.

Keywords: carbon neutrality, green urban design, energy transition, theoretical exploration

Procedia PDF Downloads 132

Authors: Daniela Stephanie Kuenstle

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Complex industries such as banking or insurance experience slow growth in mobile sales. While today’s mobile applications are sophisticated and enable location based and personalized services, consumers prefer online or even face-to-face services to complete complex transactions. A possible reason for this reluctance is that the provided service within transactional mobile applications (apps) does not adequately correspond to users’ needs. Therefore, this paper examines the impact of the user context on mobile service (m-service) in m-commerce. Motivated by the potential which context-sensitive m-services hold for the future, the impact of temporal variations as a dimension of user context, on m-service design is examined. In particular, the research question asks: Does consumer urgency function as a determinant of m-service composition in transactional apps by moderating the relation between m-service type and m-service success? Thus, the aim is to explore the moderating influence of urgency on m-service types, which includes Technology Mediated Service and Technology Generated Service. While mobile applications generally comprise features of both service types, this thesis discusses whether unexpected urgency changes customer preferences for m-service types and how this consequently impacts the overall m-service success, represented by purchase intention, loyalty intention and service quality. An online experiment with a random sample of N=1311 participants was conducted. Participants were divided into four treatment groups varying in m-service types and urgency level. They were exposed to two different urgency scenarios (high/ low) and two different app versions conveying either technology mediated or technology generated service. Subsequently, participants completed a questionnaire to measure the effectiveness of the manipulation as well as the dependent variables. The research model was tested for direct and moderating effects of m-service type and urgency on m-service success. Three two-way analyses of variance confirmed the significance of main effects, but demonstrated no significant moderation of urgency on m-service types. The analysis of the gathered data did not confirm a moderating effect of urgency between m-service type and service success. Yet, the findings propose an additive effects model with the highest purchase and loyalty intention for Technology Generated Service and high urgency, while Technology Mediated Service and low urgency demonstrate the strongest effect for service quality. The results also indicate an antagonistic relation between service quality and purchase intention depending on the level of urgency. Although a confirmation of the significance of this finding is required, it suggests that only service convenience, as one dimension of mobile service quality, delivers conditional value under high urgency. This suggests a curvilinear pattern of service quality in e-commerce. Overall, the paper illustrates the complex interplay of technology, user variables, and service design. With this, it contributes to a finer-grained understanding of the relation between m-service design and situation dependency. Moreover, the importance of delivering situational value with apps depending on user context is emphasized. Finally, the present study raises the demand to continue researching the impact of situational variables on m-service design in order to develop more sophisticated m-services.

Keywords: mobile consumer behavior, mobile service design, mobile service success, self-service technology, situation dependency, user-context sensitivity

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Authors: Shadi Fathi, Moura Mehravar, Mujib Rahman

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The railwaytransportation network in the UK is over 100 years old and is known as one of the oldest mass transit systems in the world. This aged track network requires frequent closure for maintenance. One of the main reasons for closure is inadequate drainage due to the leakage in the buried drainage pipes. The leaking water can cause localised subgrade weakness, which subsequently can lead to major ground/substructure failure.Different condition assessment methods are available to assess the railway substructure. However, the existing condition assessment methods are not able to detect any local ground weakness/damageand provide details of the damage (e.g. size and location). To tackle this issue, a hybrid back-analysis technique based on artificial neural network (ANN) and genetic algorithm (GA) has been developed to predict the substructurelayers’ moduli and identify any soil weaknesses. At first, afinite element (FE) model of a railway track section under Falling Weight Deflection (FWD) testing was developed and validated against field trial. Then a drainage pipe and various scenarios of the local defect/ soil weakness around the buried pipe with various geometriesand physical properties were modelled. The impact of the soil local weaknesson the track surface deflection wasalso studied. The FE simulations results were used to generate a database for ANN training, and then a GA wasemployed as an optimisation tool to optimise and back-calculate layers’ moduli and soil weakness moduli (ANN’s input). The hybrid ANN-GA back-analysis technique is a computationally efficient method with no dependency on seed modulus values. The modelcan estimate substructures’ layer moduli and the presence of any localised foundation weakness.

Keywords: finite element (FE) model, drainage defect, falling weight deflectometer (FWD), hybrid ANN-GA

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Authors: Surafel Demissie, Frank Keenan, Fergal McCaffery

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Emerging medical devices are highly relying on embedded software that runs on the specific platform in real time. The development of embedded software is different from ordinary software development due to the hardware-software dependency. MDevSPICE^® has been developed to provide guidance to support such development. To increase the flexibility of this framework agile practices have been introduced. This paper outlines the challenges for embedded medical device software development and the structure of MDevSPICE^® and suggests a suitable combination of agile practices that will help to add flexibility and address corresponding challenges of embedded medical device software development.

Keywords: agile practices, challenges, embedded software, MDevSPICE®, medical device

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Authors: A. M. Tahsini

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Computational study of two dimensional supersonic reacting hydrogen-air flows is performed to investigate the nitrogen effects on ignition delay time for premixed and diffusion flames. Chemical reaction is treated using detail kinetics and the advection upstream splitting method is used to calculate the numerical inviscid fluxes. The results show that only in the stoichiometric condition for both premixed and diffusion flames, there is monotone dependency of the ignition delay time to the nitrogen addition. In other situations, the optimal condition from ignition viewpoint should be found using numerical investigations.

Keywords: diffusion flame, ignition delay time, mixing layer, numerical simulation, premixed flame, supersonic flow

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Authors: Alina Gilmanova

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China’s dependency on coal for energy is causing pollution in China and abroad. To supply the increasing energy demand and being under the pressure from international society to reduce the emissions, China was pushed to develop renewable energy. The increasing subsidies in Renewable energy sources (RES) led not only to the price-cutting but also affecting the international trade in green technology sector. In order to evaluate the role of RES in foreign policy of China, I am going to give an (i) overview of RES development in China and examine the cooperation between China and (ii) developed, (ii) developing and emerging countries. The conclusive remarks are intended to address the question of how the present Chinese renewable energy development is impacting its foreign policy and international society.

Keywords: renewable energy, China, foreign affairs, brics, cooperation

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Authors: Peer M. Sathikh

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Creativity and innovation have become an important phenomenon today, whose potential is being realized through the success of Apple, Google/Android, Nike, Virgin, Dyson and other multinationals that are a household name today. Creativity and Innovation are, many times, used interchangeably, causing confusion as to what each represents and are capable of. Attempts to understand creativity and innovation clearly point to the difference, and at the same time, inter-dependency of one on the other. The assumption that having more creative personnel in a team will translate into innovation sooner or later seems generally counterproductive. What helps define the role of creativity and innovation in an organization and how can one build an innovative team? This paper points to the importance of understanding creative culture and innovation culture in order to bring about the desired innovation outcome and proposes a means to transform one to another as ideas move from mere ideas to useful innovation.

Keywords: creativity, innovation, creative culture, innovation culture, transformal operators

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Authors: Tiwi Kamidin

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After years of effort trying to integrate environmental education, studies keep revealing that Malaysian still not reached the certain level of desired commitment toward the environment. Some researchers mentioned that our planet healthy is depending on our mentally health especially our psychological and spiritual is split from the natural. Therefore, this study discussed on ecopcyhological approach in order to enhance space consciousness toward the environment. Space consciousness represents not only freedom from ego but also from dependency on the things of this world, from materialism and materiality. It is the spiritual dimension which alone can give transcendent and true meaning to this world. If pupils can balance this internal awareness will put an individual to respect the environment as part of yourself and your family against only as contributors to the continuance of human’s life. Qualitative findings showed that the informants considered their consciousness toward environment has been changed.

Keywords: ecopsychological approach, space consciousness, environmental education, environment

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Authors: K. A. Weidenmann, M. Grigo, B. Brylka, P. Elsner, T. Böhlke

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In order to reduce fuel consumption, the weight of automobiles has to be reduced. Fiber reinforced polymers offer the potential to reach this aim because of their high stiffness to weight ratio. Additionally, the use of fiber reinforced polymers in automotive applications has to allow for an economic large-scale production. In this regard, long fiber reinforced thermoplastics made by direct processing offer both mechanical performance and processability in injection moulding and compression moulding. The work presented in this contribution deals with long glass fiber reinforced polypropylene directly processed in compression moulding (D-LFT). For the use in automotive applications both the temperature and the time dependency of the materials properties have to be investigated to fulfill performance requirements during crash or the demands of service temperatures ranging from -40 °C to 80 °C. To consider both the influence of temperature and time, quasistatic tensile tests have been carried out at different temperatures. These tests have been complemented by high speed tensile tests at different strain rates. As expected, the increase in strain rate results in an increase of the elastic modulus which correlates to an increase of the stiffness with decreasing service temperature. The results are in good accordance with results determined by dynamic mechanical analysis within the range of 0.1 to 100 Hz. The experimental results from different testing methods were grouped and interpreted by using different time temperature shift approaches. In this regard, Williams-Landel-Ferry and Arrhenius approach based on kinetics have been used. As the theoretical shift factor follows an arctan function, an empirical approach was also taken into consideration. It could be shown that this approach describes best the time and temperature superposition for glass fiber reinforced polypropylene manufactured by D-LFT processing.

Keywords: composite, dynamic mechanical analysis, long fibre reinforced thermoplastics, mechanical properties, time temperature superposition

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Authors: Manish Jain, Dinesh Gopalani

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Growing dependency of mankind on software technology increases the need for thorough testing of the software applications and automated testing techniques that support testing activities. We have outlined our testing strategy for performing various types of automated testing of Java applications using AspectJ which has become the de-facto standard for Aspect Oriented Programming (AOP). Likewise JUnit, a unit testing framework is the most popular Java testing tool. In this paper, we have evaluated our proposed AOP approach for automated testing and JUnit on various parameters. First we have provided the similarity between the two approaches and then we have done a detailed comparison of the two testing techniques on factors like lines of testing code, learning curve, testing of private members etc. We established that our AOP testing approach using AspectJ has got several advantages and is thus particularly more effective than JUnit.

Keywords: aspect oriented programming, AspectJ, aspects, JU-nit, software testing

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Authors: Monica Anumula

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Nowadays human beings attain comfort zone artificially for heating, cooling and lighting the spaces they live, and their main importance is given to aesthetics of building and they are not designed to protect themselves from climate. They depend on artificial sources of energy resulting in energy wastage. In order to reduce the amount of energy being spent in the construction industry and Energy Package goals by 2020, new ways of constructing houses is required. The larger part of energy consumption of a building is directly related to architectural aspects hence nature has to be integrated into the building design to attain comfort zone and reduce the dependency on artificial source of energy. The research is to develop bioclimatic design strategies and techniques for the walls and roofs of Vijayawada houses. Study and analysis of design strategies and techniques of various cases like Kerala, Mangalore etc. for similar kind of climate is examined in this paper. Understanding the vernacular architecture and modern techniques of that various cases and implementing in the housing of Vijayawada not only decreases energy consumption but also enhances socio cultural values of Vijayawada. This study focuses on the comparison of vernacular techniques and modern building bio climatic strategies to attain thermal comfort and energy reduction in hot and humid climate. This research provides further thinking of new strategies which include both vernacular and modern bioclimatic techniques.

Keywords: bioclimatic design, energy consumption, hot and humid climates, thermal comfort

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Authors: A. Majidian

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The life prediction of thermal power plant components is necessary to prevent the unexpected outages, optimize maintenance tasks in periodic overhauls and plan inspection tasks with their schedules. One of the main critical components in a power plant is condenser because its failure can affect many other components which are positioned in downstream of condenser. This paper deals with factors affecting life of condenser. Failure rates dependency vs. these factors has been investigated using Artificial Neural Network (ANN) and fuzzy logic algorithms. These algorithms have shown their capabilities as dynamic tools to evaluate life prediction of power plant equipments.

Keywords: life prediction, condenser tube, neural network, fuzzy logic

Procedia PDF Downloads 323

Authors: Aishath Shakeela

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At a global level, water stewardship, water stress and water security are crucial factors in tourism planning and development considerations. Challenges associated with water is of particular concern to the Maldives as there is limited availability of freshwater, high dependency on desalinated water, and high unit cost associated with desalinating water. While the Maldives is promoted as an example of sustainable tourism, a key sustainability challenge facing tourism dependent communities is the efficient use and management of available water resources. A water crisis event in the capital island of Maldives highlighted how precarious water related issues are in this tourism dependent destination. Applying netnography, the focus of this working paper is to present community perceptions of how government policies addressed Malé Water and Sewerage Company (MWSC) water crisis event.

Keywords: crisis management, government policies, Maldives, tourism, water

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Authors: Kashyap L. Mokariya, Varsha A. Shah, Makarand M. Lokhande

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As the current status and growth of Indian automobile industry is remarkable, transportation sectors are the main concern in terms of Energy security and climate change. Rising demand of fuel and its dependency on other countries affects the GDP of nation. So in this context if the 10 percent of vehicle got operated in Electrical mode how much saving in terms of Rs and in terms of liters is achieved has been analyzed which is also a part of Nations Electric mobility mission plan. Analysis is also done for converting unit consumption of Electricity of Electric vehicle into equivalent fuel consumption in liters which shows that at present tariff rate Electrical operated vehicles are far more beneficial. It also gives benchmark to the authorities to set the tariff rate for Electrical vehicles. Current situation of Indian grid is shown and how the Gap between Generation and Demand can be reduced is analyzed in terms of increasing generation capacity and Energy Conservation measures. As the certain regions of country is facing serious deficit than how to take energy conservation measures in Industry and especially in rural areas where generally Energy Auditing is not carried out that is analyzed in context of Electric vehicle penetration in near future. Author was a part of Vishvakarma yojna where in 255 villages of Gujarat Energy losses were measured and solutions were given to mitigate them and corresponding report to the authorities of villages was delivered.

Keywords: vehiclepenetration, feasibility, Energyconservation, future grid, Energy security, pf controller

Procedia PDF Downloads 334

Authors: A. Shoiynbek, K. Kozhakhmet, P. Menezes, D. Kuanyshbay, D. Bayazitov

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Speech emotion recognition has received increasing research interest all through current years. There was used emotional speech that was collected under controlled conditions in most research work. Actors imitating and artificially producing emotions in front of a microphone noted those records. There are four issues related to that approach, namely, (1) emotions are not natural, and it means that machines are learning to recognize fake emotions. (2) Emotions are very limited by quantity and poor in their variety of speaking. (3) There is language dependency on SER. (4) Consequently, each time when researchers want to start work with SER, they need to find a good emotional database on their language. In this paper, we propose the approach to create an automatic tool for speech emotion extraction based on facial emotion recognition and describe the sequence of actions of the proposed approach. One of the first objectives of the sequence of actions is a speech detection issue. The paper gives a detailed description of the speech detection model based on a fully connected deep neural network for Kazakh and Russian languages. Despite the high results in speech detection for Kazakh and Russian, the described process is suitable for any language. To illustrate the working capacity of the developed model, we have performed an analysis of speech detection and extraction from real tasks.

Keywords: deep neural networks, speech detection, speech emotion recognition, Mel-frequency cepstrum coefficients, collecting speech emotion corpus, collecting speech emotion dataset, Kazakh speech dataset

Procedia PDF Downloads 71

Authors: Badr Eddine Lebrouhi, Melissa Lopez Viveros, Silvia De Los Santos, Kolthoum Missaoui, Pamela Ramirez Vidal

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Since the Paris Climate Agreement, numerous countries, including France, have committed to achieving carbon neutrality by 2050 by enhancing renewable energy capacity and decarbonizing various sectors, including aviation. In this way, the Occitanie region aspires to become a renewable energy pioneer and has focused on Toulouse's Blagnac airport—a prominent hub characterized by high-energy demands. As part of a holistic strategy to reduce the airport's energy dependency, green hydrogen has emerged as a promising alternative fuel, offering the potential to significantly enhance aviation's environmental sustainability. This study assesses the technical and economic aspects of green hydrogen production, particularly its potential to replace fossil kerosene in aviation at Toulouse-Blagnac airport. It analyzes future liquid hydrogen fuel demand, calculates energy requirements for electrolysis and liquefaction, considers diverse renewable energy scenarios, and assesses the Levelized Cost of Hydrogen (LCOH) for economic viability. The research also projects LCOH evolution from 2023 to 2050, offering a comprehensive view of green hydrogen's feasibility as a sustainable aviation fuel, aligning with the region's renewable energy and sustainable aviation objectives.

Keywords: Toulouse-Blagnac Airport, green hydrogen, aviation decarbonization, electrolysis, renewable energy, technical-economic feasibility

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Authors: Bahareh Mostofian

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Foreign Direct Investment (FDI) has long been recognized as a crucial driver of economic growth and development in less-developed countries and their integration into Global Production Networks (GPNs). FDI not only brings capital from the core countries but also technology, innovation, and know-how knowledge that can upgrade the capabilities of host automotive industries. On the other hand, FDI can also have negative impacts on host countries if it leads to significant import dependency. In the case of the Iranian automotive sector, the industry greatly benefited from FDI, with Western carmakers dominating the market. Over time, various types of know-how knowledge, including joint ventures (JVs), trade licenses, and technical assistance, have been provided, helping Iran upgrade its automotive industry. While after the severe geopolitical obstacles imposed by both the EU and the U.S., the industry became over-reliant on the car and spare parts imports, and the lack of emphasis on knowledge transfer further affected the growth and development of the Iranian automotive sector. To address these challenges, current research has adopted a descriptive-analytical methodology to illustrate the gradual changes accrued with foreign suppliers through FDI. The research finding shows that after the two-phase imposed sanctions, the detrimental linkages created by overreliance on the car and spare parts imports without any industrial upgrading negatively affected the growth and development of the national and assembled products of the Iranian automotive sector.

Keywords: less-developed country, FDI, GPNs, automotive industry, Iran

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Authors: Naduni Ranasinghe

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E-learning environments are getting more popular than any other due to the impact of COVID19. Even though e-learning is one of the best solutions for the teaching-learning process in the academic process, it’s not without major challenges. Nowadays, machine learning approaches are utilized in the analysis of how behavioral factors lead to better adoption and how they related to better performance of the students in eLearning environments. During the pandemic, we realized the academic process in the eLearning approach had a major issue, especially for the performance of the students. Therefore, an approach that investigates student behaviors in eLearning environments using a data-intensive machine learning approach is appreciated. A hybrid approach was used to understand how each previously told variables are related to the other. A more quantitative approach was used referred to literature to understand the weights of each factor for adoption and in terms of performance. The data set was collected from previously done research to help the training and testing process in ML. Special attention was made to incorporating different dimensionality of the data to understand the dependency levels of each. Five independent variables out of twelve variables were chosen based on their impact on the dependent variable, and by considering the descriptive statistics, out of three models developed (Random Forest classifier, SVM, and Decision tree classifier), random forest Classifier (Accuracy – 0.8542) gave the highest value for accuracy. Overall, this work met its goals of improving student performance by identifying students who are at-risk and dropout, emphasizing the necessity of using both static and dynamic data.

Keywords: academic performance prediction, e learning, learning analytics, machine learning, predictive model

Procedia PDF Downloads 116

Authors: Islem Kedidi, Rihab Bedoui Bensalem, Faysal Manssouri

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In traditional models of insurance data, the number and size of claims are assumed to be independent. Relaxing the independence assumption, this article explores the Vine copula to model dependence structure between multivariate frequency and average severity of insurance claim. To illustrate this approach, we use the Wisconsin local government property insurance fund which offers several insurance protections for motor vehicles, property and contractor’s equipment claims. Results show that the C-vine copula can better characterize the multivariate dependence structure between frequency and severity. Furthermore, we find significant dependencies especially between frequency and average severity among different coverage types.

Keywords: dependency modeling, government insurance, insurance claims, vine copula

Procedia PDF Downloads 172

Authors: S. Varnagiris, M. Urbonavicius, S. Tuckute, M. Lelis, K. Bockute

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Amongst many water purification techniques, TiO₂ photocatalysis is recognized as one of the most promising sustainable methods. It is known that for photocatalytical applications anatase is the most suitable TiO₂ phase, however heterojunction of anatase/rutile phases could improve the photocatalytical activity of TiO₂ even further. Despite the relative simplicity of TiO₂ different synthesis methods lead to the highly dispersed crystal phases and photocatalytic activity of the corresponding samples. Accordingly, suggestions and investigations of various innovative methods of TiO₂ synthesis are still needed. In this work structural and photocatalytical properties of TiO₂ films deposited by the unconventional method of simultaneous co-sputtering from two magnetrons powered by pulsed-Direct Current (pDC) and Radio Frequency (RF) power sources with negative bias voltage have been studied. More specifically, TiO₂ film thickness, microstructure, surface roughness, crystal structure, optical transmittance and photocatalytical properties were investigated by profilometer, scanning electron microscope, atomic force microscope, X-ray diffractometer and UV-Vis spectrophotometer respectively. The proposed unconventional two magnetron co-sputtering based TiO₂ film formation method showed very promising results for crystalline TiO₂ film formation while keeping process temperatures below 100 °C. XRD analysis revealed that by using proper combination of power source type and bias voltage various TiO₂ phases (amorphous, anatase, rutile or their mixture) can be synthesized selectively. Moreover, strong dependency between power source type and surface roughness, as well as between the bias voltage and band gap value of TiO₂ films was observed. Interestingly, TiO₂ films deposited by two magnetron co-sputtering without bias voltage had one of the highest band gap values between the investigated films but its photocatalytic activity was superior compared to all other samples. It is suggested that this is due to the dominating nanocrystalline anatase phase with various exposed surfaces including photocatalytically the most active {001}.

Keywords: films, magnetron co-sputtering, photocatalysis, TiO₂

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Authors: Wilson Handoko, Farshid Pahlevani, Isha Singla, Himanish Kumar, Veena Sahajwalla

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Aluminium bronze alloys are well known for their superior abrasion, tensile strength and non-magnetic properties, due to the co-presence of iron (Fe) and aluminium (Al) as alloying elements and have been commonly used in many industrial applications. However, continuous exposure to the marine environment will accelerate the risk of a tendency to Al bronze alloys parts failures. Although a higher level of corrosion resistance properties can be achieved by modifying its elemental composition, it will come at a price through the complex manufacturing process and increases the risk of reducing the ductility of Al bronze alloy. In this research, the use of ironmaking slag and waste plastic as the input source for surface modification of Al bronze alloy was implemented. Microstructural analysis conducted using polarised light microscopy and scanning electron microscopy (SEM) that is equipped with energy dispersive spectroscopy (EDS). An electrochemical corrosion test was carried out through Tafel polarisation method and calculation of protection efficiency against the base-material was determined. Results have indicated that uniform modified surface which is as the result of selective diffusion process, has enhanced corrosion resistance properties up to 12.67%. This approach has opened a new opportunity to access various industrial utilisations in commercial scale through minimising the dependency on natural resources by transforming waste sources into the protective coating in environmentally friendly and cost-effective ways.

Keywords: aluminium bronze, waste-based surface modification, tafel polarisation, corrosion resistance

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Authors: A. N. Moulai Khatir

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SOI-Multifin-FETs are placed to be the workhorse of the industry for the coming few generations, and thus, in a few years because their excellent transistor characteristics, ideal sub-threshold swing, low drain induced barrier lowering (DIBL) without pocket implantation, and negligible body bias dependency. The corner effect may also exist in the two lower corners; this effect is called the BOX effect, which can also occur in the direction X-Z. The electric field lines from the source and drain cross the bottom oxide and arrive in the silicon. This effect is also called DIVSB (Drain Induced Virtual Substrate Basing). The potential in the silicon film in particular near the drain is increased by the drain bias. It is similar to DIBL and result in a decrease of the threshold voltage. This work provides an understanding of the limitation of this effect by reducing the fin width for components with increased fin number.

Keywords: SOI, finFET, corner effect, dual-gate, tri-gate, BOX, multi-finFET

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Authors: I. Siti Rabiatull Aisha, A. Ourdjini, O. Saliza Azlina

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The aim of this paper is to study the effectiveness of bismuth addition in the solder alloy to retard the intermetallic compound formation and growth. In this study, three categories of solders such as Sn-4Ag-xCu (x = 0.5, 0.7, 1.0) and Sn-4Ag-0.5Cu-xBi (x = 0.1, 0.2, 0.4) were used. Ni/Au surface finish substrates were dipped into the molten solder at a temperature of 180-190 ^oC and allowed to cool at room temperature. The intermetallic compound (IMCs) were subjected to the characterization in terms of composition and morphology. The IMC phases were identified by energy dispersive x-ray (EDX), whereas the optical microscope and scanning electron microscopy (SEM) were used to observe microstructure evolution of the solder joint. The results clearly showed that copper concentration dependency was high during the reflow stage. Besides, only Ni₃Sn₄ and Ni₃Sn₂ were detected for all copper concentrations. The addition of Bi was found to have no significant effect on the type of IMCs formed, but yet the grain became further refined.

Keywords: Bismuth addition, intermetallic compound, composition, morphology

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Authors: Rakesh Kumar, Fatima Electricwala

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One of the major thrusts of the Bus Rapid Transit System is to reduce the commuter’s dependency on private vehicles and increase the shares of public transport to make urban transportation system environmentally sustainable. In this study, commuter mode choice analysis is performed that examines behavioral responses to the proposed Bus Rapid Transit System (BRTS) in Surat, with estimation of the probable shift from private mode to public mode. Further, evaluation of the BRTS scenarios, using Surat’s transportation ecological footprint was done. A multi-modal simulation model was developed in Biogeme environment to explicitly consider private users behaviors and non-linear environmental impact. The data of the different factors (variables) and its impact that might cause modal shift of private mode users to proposed BRTS were collected through home-interview survey using revealed and stated preference approach. A multi modal logit model of mode-choice was then calibrated using the collected data and validated using proposed sample. From this study, a set of perception factors, with reliable and predictable data base, to explain the variation in modal shift behaviour and their impact on Surat’s ecological environment has been identified. A case study of the proposed BRTS connecting the Surat Industrial Hub to the coastal area is provided to illustrate the approach.

Keywords: BRTS, private modes, mode choice models, ecological footprint

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Authors: Marwa Hanafy

Abstract:

The objective of linking the museum with school curriculum is to focus on the values and principles of the educational standards of the fourth grade as "equality, cooperation, allegiance, belonging, participation, peace, tolerance, pride and patriotism, etc." through activities, discussion, exhibits, etc., which can help the students to develop their characters and be useful for their society. For example, there is a lesson in Module 3 assess the role of women as mothers and queens, here this research will focus on the value of women and respect them through statues or images of women which support and affect positively on the students who will apply these Morals to themselves and to the community by dependency. It cannot be denied that the students have to be a part of the museum educational programs which have designed for them, by giving them the opportunity to participate, talk, discuss and express their opinions and hear them in the museums, this may be an effective way to confirm that the interests of children are taken into account.

Keywords: museum education, primary school education, school curriculum, informal learning

Procedia PDF Downloads 116

Authors: Chidiebere C. Agoha, Armstong C. Awuzie, Chukwuebuka N. Onwubuariri, Joy O. Njoku

Abstract:

Spatial analysis is a field of study that utilizes geographic or spatial information to understand and analyze patterns, relationships, and trends in data. It is characterized by the use of geographic or spatial information, which allows for the analysis of data in the context of its location and surroundings. It is different from non-spatial or aspatial techniques, which do not consider the geographic context and may not provide as complete of an understanding of the data. Spatial analysis is applied in a variety of fields, which includes urban planning, environmental science, geosciences, epidemiology, marketing, to gain insights and make decisions about complex spatial problems. This review paper explores definitions of spatial analysis from various sources, including examples of its application and different analysis techniques such as Buffer analysis, interpolation, and Kernel density analysis (multi-distance spatial cluster analysis). It also contrasts spatial analysis with non-spatial analysis.

Keywords: aspatial technique, buffer analysis, epidemiology, interpolation

Procedia PDF Downloads 279

Authors: Farid Khosravikia, Patricia Clayton

Abstract:

The main objective of this work is to evaluate the advantages and disadvantages of various machine learning techniques in two key steps of seismic hazard and risk assessment of different types of structures. The first step is the development of ground-motion models, which are used for forecasting ground-motion intensity measures (IM) given source characteristics, source-to-site distance, and local site condition for future events. IMs such as peak ground acceleration and velocity (PGA and PGV, respectively) as well as 5% damped elastic pseudospectral accelerations at different periods (PSA), are indicators of the strength of shaking at the ground surface. Typically, linear regression-based models, with pre-defined equations and coefficients, are used in ground motion prediction. However, due to the restrictions of the linear regression methods, such models may not capture more complex nonlinear behaviors that exist in the data. Thus, this study comparatively investigates potential benefits from employing other machine learning techniques as statistical method in ground motion prediction such as Artificial Neural Network, Random Forest, and Support Vector Machine. The results indicate the algorithms satisfy some physically sound characteristics such as magnitude scaling distance dependency without requiring pre-defined equations or coefficients. Moreover, it is shown that, when sufficient data is available, all the alternative algorithms tend to provide more accurate estimates compared to the conventional linear regression-based method, and particularly, Random Forest outperforms the other algorithms. However, the conventional method is a better tool when limited data is available. Second, it is investigated how machine learning techniques could be beneficial for developing probabilistic seismic demand models (PSDMs), which provide the relationship between the structural demand responses (e.g., component deformations, accelerations, internal forces, etc.) and the ground motion IMs. In the risk framework, such models are used to develop fragility curves estimating exceeding probability of damage for pre-defined limit states, and therefore, control the reliability of the predictions in the risk assessment. In this study, machine learning algorithms like artificial neural network, random forest, and support vector machine are adopted and trained on the demand parameters to derive PSDMs for them. It is observed that such models can provide more accurate estimates of prediction in relatively shorter about of time compared to conventional methods. Moreover, they can be used for sensitivity analysis of fragility curves with respect to many modeling parameters without necessarily requiring more intense numerical response-history analysis.

Keywords: artificial neural network, machine learning, random forest, seismic risk analysis, seismic hazard analysis, support vector machine

Procedia PDF Downloads 80

Authors: Zheng Baichuan, Li Shenghui, Li Bingqian, Zhang Ning, Chen Kai

Abstract:

Entity alignment (EA) tasks in knowledge graphs often play a pivotal role in the integration of knowledge graphs, where structural differences often exist between the source and target graphs, such as the presence or absence of attribute information and the types of attribute information (text, timestamps, images, etc.). However, most current research efforts are focused on improving alignment accuracy, often along with an increased reliance on specific structures -a dependency that inevitably diminishes their practical value and causes difficulties when facing knowledge graph alignment tasks with varying structures. Therefore, we propose a universal knowledge graph alignment approach that only utilizes the common basic structures shared by knowledge graphs. We have demonstrated through experiments that our method achieves state-of-the-art performance in fair comparisons.

Keywords: knowledge graph, entity alignment, transformer, deep learning

Procedia PDF Downloads 8