Search results for: 3D building models

Authors: Jose Ruiz, Jose Velasquez, Holger Lovon

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Peruvian university buildings are critical structures for which very little research about its seismic vulnerability is available. This paper develops a probabilistic methodology that predicts seismic loss for university buildings with simulated fragility functions. Two university buildings located in the city of Cusco were analyzed. Fragility functions were developed considering seismic and structural parameters uncertainty. The fragility functions were generated with the Latin Hypercube technique, an improved Montecarlo-based method, which optimizes the sampling of structural parameters and provides at least 100 reliable samples for every level of seismic demand. Concrete compressive strength, maximum concrete strain and yield stress of the reinforcing steel were considered as the key structural parameters. The seismic demand is defined by synthetic records which are compatible with the elastic Peruvian design spectrum. Acceleration records are scaled based on the peak ground acceleration on rigid soil (PGA) which goes from 0.05g to 1.00g. A total of 2000 structural models were considered to account for both structural and seismic variability. These functions represent the overall building behavior because they give rational information regarding damage ratios for defined levels of seismic demand. The university buildings show an expected Mean Damage Factor of 8.80% and 19.05%, respectively, for the 0.22g-PGA scenario, which was amplified by the soil type coefficient and resulted in 0.26g-PGA. These ratios were computed considering a seismic demand related to 10% of probability of exceedance in 50 years which is a requirement in the Peruvian seismic code. These results show an acceptable seismic performance for both buildings.

Keywords: fragility functions, university buildings, loss assessment, Montecarlo simulation, latin hypercube

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Authors: Leyla Yesilbas, M. Sukru Ozcoban, M. Ergenekon Selcuk

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From past to present, there is a constant need for engineering structures such as high-rise buildings, wide-span bridges, airports and stadiums, business towers due to technological developments and increasing population. Because of the large loads transferred from the superstructure to the ground layers in these types of structures, the bearing strength and seating problems usually occur on the floors. In order to solve these problems, piled foundations are used by passing the weak soil layers and transferring the loads from the superstructure to the solid soil layers. Considering the factors such as the characteristics of the building to be constructed, the purpose and location of the building, the basic cost of the pile should be at normal levels. When these requirements are taken into consideration, a new basic system called 'Barette Foundation' has been developed. In this thesis, an application made to provide slope stability with 'Baret Piles' was investigated. In addition, the ground parameters obtained from the field and laboratory experiments were numerically modeled using a PLAXİS 2D finite element software and barette piles. The effects of barette piles on slope stability were investigated by numerical analysis, and the results of inclinometer measurements in the field were compared with numerical analysis results.

Keywords: barette pile, PLAXİS 2D, slope, soil

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Authors: Yehjune Heo

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Fingerprint Anti-Spoofing approaches have been actively developed and applied in real-world applications. One of the main problems for Fingerprint Anti-Spoofing is not robust to unseen samples, especially in real-world scenarios. A possible solution will be to generate artificial, but realistic fingerprint samples and use them for training in order to achieve good generalization. This paper contains experimental and comparative results with currently popular GAN based methods and uses realistic synthesis of fingerprints in training in order to increase the performance. Among various GAN models, the most popular StyleGAN is used for the experiments. The CNN models were first trained with the dataset that did not contain generated fake images and the accuracy along with the mean average error rate were recorded. Then, the fake generated images (fake images of live fingerprints and fake images of spoof fingerprints) were each combined with the original images (real images of live fingerprints and real images of spoof fingerprints), and various CNN models were trained. The best performances for each CNN model, trained with the dataset of generated fake images and each time the accuracy and the mean average error rate, were recorded. We observe that current GAN based approaches need significant improvements for the Anti-Spoofing performance, although the overall quality of the synthesized fingerprints seems to be reasonable. We include the analysis of this performance degradation, especially with a small number of samples. In addition, we suggest several approaches towards improved generalization with a small number of samples, by focusing on what GAN based approaches should learn and should not learn.

Keywords: anti-spoofing, CNN, fingerprint recognition, GAN

Procedia PDF Downloads 180

Authors: C. Baidada, M. H. Abidi, A. Jakimi, E. H. El Kinani

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Reverse engineering has become a viable method to measure an existing system and reconstruct the necessary model from tis original. The reverse engineering of behavioral models consists in extracting high-level models that help understand the behavior of existing software systems. In this paper, we propose an approach for the reverse engineering of sequence diagrams from the analysis of execution traces produced dynamically by an object-oriented application using petri nets. Our methods show that this approach can produce state diagrams in reasonable time and suggest that these diagrams are helpful in understanding the behavior of the underlying application. Finally we will discuss approachs and tools that are needed in the process of reverse engineering UML behavior. This work is a substantial step towards providing high-quality methodology for effectiveand efficient reverse engineering of sequence diagram.

Keywords: reverse engineering, UML behavior, sequence diagram, execution traces, petri nets

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Authors: Adel Edwar Waheeb Louka

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Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deeplearning, image processing, machine learningSarapin, intraarticular, chronic knee pain, osteoarthritisFNS, trauma, hip, neck femur fracture, minimally invasive surgery

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Authors: Justina Jor, Mahmud Pinga

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Climate change has become a significant worldwide environmental challenge with extensive implications, compelling both governments and non-governmental organizations to remain vigilant, as it seemingly impacts various sectors of the global economy, including education. The study investigates the implementation of smart climate change measures for effective primary school management in Benue State, Nigeria. Theorized by the diffusion of innovations, the study was guided by two research questions, and two null hypotheses were formulated and tested. The study used a descriptive survey design. The population comprised 12,364 teachers from 2,721 primary schools, with a sample of 618 teachers from 136 schools selected through a multistage sampling procedure. Smart climate change measures questionnaire (SCCMQ) and key informant interview (KII) were used for data collection. The data collected were analyzed using mean and standard deviation to answer the research questions, while the Chi-square (χ2) test of goodness-of-fit was used to test the hypotheses at a 0.05 level of significance, with qualitative data analyzed using simple percentages, tables, and bar charts. The findings highlight the significant positive impact of green building practices on the efficient administration of primary schools in Benue State, Nigeria. The crucial integration of environmentally sustainable construction methods is emphasized for enhancing overall management in these educational institutions. In addition, the research demonstrates a favorable impact on the adoption of renewable energy solutions and effective school management. The utilization of renewable energy not only aligns with eco-friendly practices but also contributes to the overall operational efficiency and sustainability of primary schools in the region. The study recommends that educational authorities and policymakers prioritize integrating green building practices and renewable energy solutions, pointing towards the prospect of improved governance and functionality for primary education facilities not only in Benue but throughout Nigeria.

Keywords: smart, climate change, effective management, green building, renewable energy

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Authors: Lovis Ingrid Hakala

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This paper provides an example of how the dating app Tinder can be used as a tool in queer research and what the use of the app among lesbians can tell us about the production of particular kinds of lesbian identities paired with technology. This study seeks to understand the ways in which the app is understood by lesbian women and how it is brought into their understandings of what being a lesbian means. Dating apps are becoming increasingly common as tools for meeting a potential partner and research has shown how these apps gain new meaning depending on the context. This paper will show both how Tinder has gained a particular meaning in a lesbian context in Bologna, and also how the use of Tinder produces specific ideas of what lesbians are and how they act. While doing ethnographic fieldwork among young lesbians (20-30 years old) in Bologna in the autumn of 2017, as a part of the research methodology, Tinder was used together with interviews and participant observation. By signing up on Tinder and contacting potential informants on the app the aim was to reach women who were not necessarily involved in the queer activist spaces in the city and who might thus provide a different perspective than their activist counterparts. Using Tinder as a tool in research proved to be a useful methodology both when it came to contacting potential informants as well as in gaining a better understanding for queer identity building, and the role Tinder played in defining lesbianism in Bologna. The app itself was often deemed useless, and informants often complained about the lack of women on the app who had their profile showing an interest in women. Apart from being away for the interlocutors to get in touch with potential romantic or sexual partners, the app did provide a concrete object around which to define particular lesbian behavior. Lesbians were described to be slow at answering and not being very eager to meet. This placed lesbian women, in contrast to gay men who were seen as doing the opposite, using dating apps a lot and be quick to propose meetings. Tinder among lesbians in Bologna thus proved to have a dual function as both a way of creating connections between queer women but also as a tool to define what a lesbian is. This paper provides insight into the ways in which dating apps provides a community and identity building function and how a certain behavior on said apps can be a part of defining identity. This work stands out among other literature on dating apps since it does not only focus on the methodological aspects of using Tinder as a tool in research but also provides an insight in how the way in which individuals use the app comes to add to an understanding of what a lesbian is.

Keywords: dating apps, identity, Italy, lesbian, queer

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Authors: Florian Mach, Eric Hund, Malte Stonis

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The dismantling of disused industrial facilities such as nuclear power plants or refineries is an enormous challenge for the planning and control of the logistic processes. Existing control models do not meet the requirements for a proper dismantling of industrial plants. Therefore, the paper presents an approach for the control of dismantling and post-processing processes (e.g. decontamination) in plant decommissioning. In contrast to existing approaches, the dismantling sequence and depth are selected depending on the capacity utilization of required post-processing processes by also considering individual characteristics of respective dismantling tasks (e.g. decontamination success rate, uncertainties regarding the process times). The results can be used in the dismantling of industrial plants (e.g. nuclear power plants) to reduce dismantling time and costs by avoiding bottlenecks such as capacity constraints.

Keywords: dismantling management, logistics planning and control models, nuclear power plant dismantling, reverse logistics

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Authors: I. A. Simsek, S. N. Dogan, A. S. Kipcak, E. Morodor Derun, N. Tugrul

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In this study, the drying characteristics of shrimp are studied by using the traditional drying method of oven. Drying temperatures are selected between 60-80°C. Obtained experimental drying results are applied to eleven mathematical models of Alibas, Aghbashlo et al., Henderson and Pabis, Jena and Das, Lewis, Logaritmic, Midilli and Kucuk, Page, Parabolic, Wang and Singh and Weibull. The best model was selected as parabolic based on the highest coefficient of determination (R²) (0.999990 at 80°C) and the lowest χ² (0.000002 at 80°C), and the lowest root mean square error (RMSE) (0.000976 at 80°C) values are compared to other models. The effective moisture diffusivity (Deff) values were calculated using the Fick’s second law’s cylindrical coordinate approximation and are found between 6.61×10⁻⁸ and 6.66×10⁻⁷ m²/s. The activation energy (Ea) was calculated using modified form of Arrhenius equation and is found as 18.315 kW/kg.

Keywords: activation energy, drying, effective moisture diffusivity, modelling, oven, shrimp

Procedia PDF Downloads 183

Authors: Laura M. F. Bertens

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There is a long tradition of visually representing the art historical canon, in schematic overviews and diagrams. This is indicative of the desire for scientific, ‘objective’ knowledge of the kind (seemingly) produced in the natural sciences. These diagrams will, however, always retain an element of subjectivity and the modelling methods colour our perception of the represented information. In recent decades visualisations of art historical data, such as hand-drawn diagrams in textbooks, have been extended to include digital, computational tools. These tools significantly increase modelling strength and functionality. As such, they might be used to deconstruct and amend the very problem caused by traditional visualisations of the canon. In this paper, the use of digital tools for modelling the art historical canon is studied, in order to draw attention to the artificial nature of the static models that art historians are presented with in textbooks and lectures, as well as to explore the potential of digital, dynamic tools in creating new models. To study the way diagrams of the canon mediate the represented information, two modelling methods have been used on two case studies of existing diagrams. The tree diagram Stammbaum der neudeutschen Kunst (1823) by Ferdinand Olivier has been translated to a social network using the program Visone, and the famous flow chart Cubism and Abstract Art (1936) by Alfred Barr has been translated to an ontological model using Protégé Ontology Editor. The implications of the modelling decisions have been analysed in an art historical context. The aim of this project has been twofold. On the one hand the translation process makes explicit the design choices in the original diagrams, which reflect hidden assumptions about the Western canon. Ways of organizing data (for instance ordering art according to artist) have come to feel natural and neutral and implicit biases and the historically uneven distribution of power have resulted in underrepresentation of groups of artists. Over the last decades, scholars from fields such as Feminist Studies, Postcolonial Studies and Gender Studies have considered this problem and tried to remedy it. The translation presented here adds to this deconstruction by defamiliarizing the traditional models and analysing the process of reconstructing new models, step by step, taking into account theoretical critiques of the canon, such as the feminist perspective discussed by Griselda Pollock, amongst others. On the other hand, the project has served as a pilot study for the use of digital modelling tools in creating dynamic visualisations of the canon for education and museum purposes. Dynamic computer models introduce functionalities that allow new ways of ordering and visualising the artworks in the canon. As such, they could form a powerful tool in the training of new art historians, introducing a broader and more diverse view on the traditional canon. Although modelling will always imply a simplification and therefore a distortion of reality, new modelling techniques can help us get a better sense of the limitations of earlier models and can provide new perspectives on already established knowledge.

Keywords: canon, ontological modelling, Protege Ontology Editor, social network modelling, Visone

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Authors: Naser Alenezi, Ibrahim Alsakkaf, Osama Eid

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The main objective of this study is to develop an independent reliability based code for reinforced concrete (R/C) structural components and elements solely for the State of Kuwait and its neighboring countries. The proposed code will take into account the harsh Kuwait’s harsh environment, loading conditions and material strengths. The method for developing such a code is based on structural reliability theory that takes into accounts the specific geographical and the various prescribed societal environment of the Kuwait region. These methods were developed according to the following four components: (1) loads, (2) structural strength, (3) reliability analysis, and (4) achieving target reliability levels (reliability index ’s ). The final product from this study will be a design code for R/C structural elements that include beams and columns, and some other structural members. This reliability-based LRFD design code will provide appropriate, easy, fast, and economical approach for designing R/C structural elements such as, beams and columns, for both houses and bridges, and other concrete structures. In addition, this reliability-based codified design of R/C beams, columns, and, possibly, concrete slabs will improve the design and serviceability of R/C bridge and building systems in Kuwait and neighboring GCC countries. Also, it has the potential to reduce the cost of new concrete structures, as fewer materials are used with more design efficiency.

Keywords: live laod, design, evaluation, structural building

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Authors: Jefto Terzovic, Ana Kontic, Isidora Ilic

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In the proposed design concept, laminated glass and laminated plexiglass, as ”unconventional materials”, are considered as a filling in a steel frame on which they overlap by the intermediate rubber layer, thereby forming a composite assembly. In this way vertical elements of stiffening are formed, capable for reception of seismic force and integrated into the structural system of the building. The applicability of such a system was verified by experiments in laboratory conditions where the experimental models based on laminated glass and laminated plexiglass had been exposed to the cyclic loads that simulate the seismic force. In this way the load capacity of composite assemblies was tested for the effects of dynamic load that was parallel to assembly plane. Thus, the stress intensity to which composite systems might be exposed was determined as well as the range of the structure stiffening referring to the expressed deformation along with the advantages of a particular type of filling compared to the other one. Using specialized software whose operation is based on the finite element method, a computer model of the structure was created and processed in the case study; the same computer model was used for analyzing the problem in the first phase of the design process. The stiffening system based on composite assemblies tested in laboratories is implemented in the computer model. The results of the modal analysis and seismic calculation from the computer model with stiffeners applied showed an efficacy of such a solution, thus rounding the design procedures for aseismic stiffening by using unconventional materials.

Keywords: laminated glass, laminated plexiglass, aseismic stiffening, experiment, laboratory testing, computer model, finite element method

Procedia PDF Downloads 76

Authors: Majid AghaAlikhani, Mostafa Hojati, Saeid Satari-Yuzbashkandi

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This paper studies energy use patterns and relationship between energy input and yield for soybean (Glycine max (L.) Merrill) in Mazandaran province of Iran. In this study, data were collected by administering a questionnaire in face-to-face interviews. Results revealed that the highest share of energy consumption belongs to chemical fertilizers (29.29%) followed by diesel (23.42%) and electricity (22.80%). Our investigations showed that a total energy input of 23404.1 MJ.ha-1 was consumed for soybean production. The energy productivity, specific energy, and net energy values were estimated as 0.12 kg MJ-1, 8.03 MJ kg-1, and 49412.71 MJ.ha-1, respectively. The ratio of energy outputs to energy inputs was 3.11. Obtained results indicated that direct, indirect, renewable and non-renewable energies were (56.83%), (43.17%), (15.78%) and (84.22%), respectively. Three econometric models were also developed to estimate the impact of energy inputs on yield. The results of econometric models revealed that impact of chemical, fertilizer, and water on yield were significant at 1% probability level. Also, direct and non-renewable energies were found to be rather high. Cost analysis revealed that total cost of soybean production per ha was around 518.43$. Accordingly, the benefit-cost ratio was estimated as 2.58. The energy use efficiency in soybean production was found as 3.11. This reveals that the inputs used in soybean production are used efficiently. However, due to higher rate of nitrogen fertilizer consumption, sustainable agriculture should be extended and extension staff could be proposed substitution of chemical fertilizer by biological fertilizer or green manure.

Keywords: Cobbe Douglas function, economical analysis, energy efficiency, energy use patterns, soybean

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Authors: Salah E. El-Metwally, Marwan Abdo, Basem Abdel Wahed

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Fiber-reinforced polymer (FRP) bars have been proposed as an alternative to conventional steel bars; hence, the use of these non-corrosive and nonmetallic reinforcing bars has increased in various concrete projects. This concrete material is lightweight, has a long lifespan, and needs minor maintenance; however, its non-ductile nature and weak bond with the surrounding concrete create a significant challenge. The behavior of concrete elements reinforced with FRP bars has been the subject of several experimental investigations, even with their high cost. This study aims to numerically assess the viability of using FRP bars, as longitudinal reinforcement, in comparison with traditional steel bars, and also as prestressing tendons instead of the traditional prestressing steel. The nonlinear finite element analysis has been utilized to carry out the current study. Numerical models have been developed to examine the behavior of concrete beams reinforced with FRP bars or tendons against similar models reinforced with either conventional steel or prestressing steel. These numerical models were verified by experimental test results available in the literature. The obtained results revealed that concrete beams reinforced with FRP bars, as passive reinforcement, exhibited less ductility and less stiffness than similar beams reinforced with steel bars. On the other hand, when FRP tendons are employed in prestressing concrete beams, the results show that the performance of these beams is similar to those beams prestressed by conventional active reinforcement but with a difference caused by the two tendon materials’ moduli of elasticity.

Keywords: reinforced concrete, prestressed concrete, nonlinear finite element analysis, fiber-reinforced polymer, ductility

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Authors: Maryam Khalilzadeh Poshtegal, Seyed Ahmad Mirbagheri, Mojtaba Noury

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In this paper, by application of the input yearly data of rainfall, temperature and flow to the Urmia Lake, the simulation of water level fluctuation were applied by means of three models. According to the climate change investigation the fluctuation of lakes water level are of high interest. This study investigate data-driven models, support vector machines (SVM), SVM method which is a new regression procedure in water resources are applied to the yearly level data of Lake Urmia that is the biggest and the hyper saline lake in Iran. The evaluated lake levels are found to be in good correlation with the observed values. The results of SVM simulation show better accuracy and implementation. The mean square errors, mean absolute relative errors and determination coefficient statistics are used as comparison criteria.

Keywords: simulation, water level fluctuation, urmia lake, support vector machine

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Authors: Ahsan Ahmed, Ming Lu, Syed Zaidi, Farhan Khan

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The Integrated Project Delivery (IPD) method has been proposed as the solution to tackle complexity and fragmentation in the real world while addressing the construction industry’s growing needs for productivity and sustainability. Although the private sector has taken the initiative in implementing IPD and taken advantage of new technology such as building information modeling (BIM) in delivering projects, IPD remains less known and rarely used in public sector construction. The focus of this paper is set on the use of IPD in projects in public sector, which is potentially complemented by the use of analytical functionalities for workface planning and construction oriented design enabled by recent research advances in BIM. Experiences and lessons learned from implementing IPD in the private sector and in BIM-based construction automation research would play a vital role in reducing barriers and eliminating issues in connection with project delivery in the public sector. The paper elaborates issues challenges, contractual relationships and the interactions throughout the planning, design and construction phases in the context of implementing IPD on construction projects in the public sector. A slab construction case is used as a ‘sandbox’ model to elaborate (1) the ideal way of communication, integration, and collaboration among all the parties involved in project delivery in planning and (2) the execution of projects by using IDP principles and optimization, simulation analyses.

Keywords: integrated project delivery, IPD, building information modeling, BIM

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Authors: Shinji Ukita, Naohiro Nakamura, Yuji Miyazu

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In considering the dynamic characteristics of structure, natural frequency and damping ratio are useful indicator. When performing dynamic design, it's necessary to select an appropriate initial damping model and hysteretic model. In the linear region, the setting of initial damping model influences the response, and in the nonlinear region, the combination of initial damping model and hysteretic model influences the response. However, the dynamic characteristics of structure in the nonlinear region remain unclear. In this paper, we studied the effect of setting of initial damping model and hysteretic model on the dynamic characteristics of structure. On initial damping model setting, Initial stiffness proportional, Tangent stiffness proportional, and Rayleigh-type were used. On hysteretic model setting, TAKEDA model and Normal-trilinear model were used. As a study method, dynamic analysis was performed using a lumped mass model of base-fixed. During analysis, the maximum acceleration of input earthquake motion was gradually increased from 1 to 600 gal. The dynamic characteristics were calculated using the ARX model. Then, the characteristics of 1st and 2nd natural frequency and 1st damping ratio were evaluated. Input earthquake motion was simulated wave that the Building Center of Japan has published. On the building model, an RC building with 30×30m planes on each floor was assumed. The story height was 3m and the maximum height was 18m. Unit weight for each floor was 1.0t/m2. The building natural period was set to 0.36sec, and the initial stiffness of each floor was calculated by assuming the 1st mode to be an inverted triangle. First, we investigated the difference of the dynamic characteristics depending on the difference of initial damping model setting. With the increase in the maximum acceleration of the input earthquake motions, the 1st and 2nd natural frequency decreased, and the 1st damping ratio increased. Then, in the natural frequency, the difference due to initial damping model setting was small, but in the damping ratio, a significant difference was observed (Initial stiffness proportional≒Rayleigh type>Tangent stiffness proportional). The acceleration and the displacement of the earthquake response were largest in the tangent stiffness proportional. In the range where the acceleration response increased, the damping ratio was constant. In the range where the acceleration response was constant, the damping ratio increased. Next, we investigated the difference of the dynamic characteristics depending on the difference of hysteretic model setting. With the increase in the maximum acceleration of the input earthquake motions, the natural frequency decreased in TAKEDA model, but in Normal-trilinear model, the natural frequency didn’t change. The damping ratio in TAKEDA model was higher than that in Normal-trilinear model, although, both in TAKEDA model and Normal-trilinear model, the damping ratio increased. In conclusion, in initial damping model setting, the tangent stiffness proportional was evaluated the most. In the hysteretic model setting, TAKEDA model was more appreciated than the Normal-trilinear model in the nonlinear region. Our results would provide useful indicator on dynamic design.

Keywords: initial damping model, damping ratio, dynamic analysis, hysteretic model, natural frequency

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Authors: Chander Shekhar Kohli

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In the field of international relations, countries have been experiencing distinct nature of conflicts. But, in the case of Association of Southeast Asian Nations (ASEAN) for a long time, the members have witnessed conflicts, small and large. These conflicts, as a result, have given catastrophic outcomes, such as killings and destroying properties. For the resolution of such conflicts, nonetheless, efforts likewise have been made, simultaneously, in terms of establishing peace and security. In this background, the ASEAN presents a significant example as before it had faced several wars, like Vietnam War, Cambodia conflicts, and so on. This research paper, therefore, strives to examine the ASEAN as a case with the help of both primary and secondary sources. It likewise will be dealt with how changing norms and identity building facilitate the ASEAN countries to deal with their conflicts both internal and external. This paper also will discuss how internal developments within countries affect conflict resolution process as each member of ASEAN is guided by its national interest. It is then argued that conflict resolution in the ASEAN is moving from its existing power-based solution to norms and identity-based solution as member countries have become more dependent on other countries. The research, therefore, is concluded by saying that the conflicts could only be resolved through building norms and common identities, which of course are recognized crucial mechanisms among the ASEAN countries with some exceptions.

Keywords: ASEAN, conflict resolution, norms and identities, peace and security

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Authors: Alanoud Moraya Aldalan, Abdulaziz Almaleh

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A crucial component of maintaining a customer-oriented business as in the telecom industry is understanding the reasons and factors that lead to customer churn. Competition between telecom companies has greatly increased in recent years. It has become more important to understand customers’ needs in this strong market of telecom industries, especially for those who are looking to turn over their service providers. So, predictive churn is now a mandatory requirement for retaining those customers. Machine learning can be utilized to accomplish this. Churn Prediction has become a very important topic in terms of machine learning classification in the telecommunications industry. Understanding the factors of customer churn and how they behave is very important to building an effective churn prediction model. This paper aims to predict churn and identify factors of customers’ churn based on their past service usage history. Aiming at this objective, the study makes use of feature selection, normalization, and feature engineering. Then, this study compared the performance of four different machine learning algorithms on the Orange dataset: Logistic Regression, Random Forest, Decision Tree, and Gradient Boosting. Evaluation of the performance was conducted by using the F1 score and ROC-AUC. Comparing the results of this study with existing models has proven to produce better results. The results showed the Gradients Boosting with feature selection technique outperformed in this study by achieving a 99% F1-score and 99% AUC, and all other experiments achieved good results as well.

Keywords: machine learning, gradient boosting, logistic regression, churn, random forest, decision tree, ROC, AUC, F1-score

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Authors: Valeria Piccioni, Matthias Leschok, Ina Cheibas, Illias Hischier, Benjamin Dillenburger, Arno Schlueter, Matthias Kohler, Fabio Gramazio

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The decarbonisation of the building sector requires the development of building components that provide energy efficiency while producing minimal environmental impact. Recent advancements in large-scale 3D printing have shown that it is possible to fabricate components with embedded performances that can be tuned for their specific application. We investigate the potential of polymer 3D printing for the fabrication of translucent facade components. In this study, we explore the effect of geometry on thermal insulation of printed cavity structures following a Hot Box test method. The experimental results are used to calibrate a finite-element simulation model which can support the informed design of 3D printed insulation structures. We show that it is possible to fabricate components providing thermal insulation ranging from 1.7 to 0.95 W/m2K only by changing the internal cavity distribution and size. Moreover, we identify design guidelines that can be used to fabricate components for different climatic conditions and thermal insulation requirements. The research conducted provides the first insights into the thermal behaviour of polymer 3DP facades on a large scale. These can be used as design guidelines for further research toward performant and low-embodied energy 3D printed facade components.

Keywords: 3D printing, thermal performance, polymers, facade components, hot-box method

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Authors: Samira Mahmoudkelayeh, Katayoun Taghizade, Mitra Pourvaziri, Elnaz Asadian

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Over the recent decades, depletion of resources and environmental concerns made researchers and practitioners present sustainable approaches. Since construction process consumes a great deal of both renewable and non-renewable resources, it is of great significance regarding environmental impacts. Choosing sustainable construction materials is a remarkable strategy presented in many researches and has a significant effect on building’s environmental footprint. This paper represents an assessment framework for selecting best sustainable materials for exterior enclosure in the city of Tehran based on sustainability principles (eco-friendly, cost effective and socio-cultural viable solutions). To perform a comprehensive analysis of environmental impacts, life cycle assessment, a cradle to grave approach is used. A questionnaire survey of construction experts has been conducted to determine the relative importance of criteria. Analytic Network Process (ANP) is applied as a multi-criteria decision-making method to choose sustainable material which consider interdependencies of criteria and sub-criteria. Finally, it prioritizes and aggregates relevant criteria into ultimate assessed score.

Keywords: sustainable materials, building, analytic network process, life cycle assessment

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Authors: Lo Kar Yin

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In view of the increasing speed and quantity of the housing supply, building, and civil engineering infrastructure works triggered by the pandemic across the globe, contractors, professional services providers (PSP), including consultants (e.g., architect, project manager, civil/geotechnical/structural engineer, building services engineer, quantity surveyor/cost manager, etc.) and suppliers have faced tremendous challenges of the fierce market, limited manpower, and resources under contract prices fluctuation and competitive fee and price. With qualitative analysis, this paper is to review the available information from the industry stakeholders with a view to finding solutions for enhancing efficiency, safety, and quality of construction value chain services for public and private organizations/companies’ sustainable growth, not limited to checking the deliverables and data transfer from multi-disciplinary parties. Technology, contracts, and people are the key requirements for shaping the construction industry. With the integration of a modern engineering contract (e.g., NEC) collaborative approach, practical workflows are designed to address loopholes together with different levels of people employment/retention and technology adoption to achieve the best value for money.

Keywords: efficiency, safety, quality, technology, contract, people, sustainable solutions, construction, services, integration

Procedia PDF Downloads 128

Authors: Melissa Angus Baboun

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Utilizing a Critical Discourse Analysis (CDA) methodology and a theoretical framework based on disability studies, how Jamaican and Trinidadian newspapers discussed issues relating to the Deaf community were examined. The term deaf was inputted into the search engine tool of the online website for the Jamaica Observer and the Trinidad & Tobago Guardian. All 27 articles that contained the term deaf in its content and were written between August 1, 2017 and November 15, 2017 were chosen for the study. The data analysis was divided into three steps: (1) listing and analysis instances of metaphorical deafness (e.g. fall on deaf ears), (2) categorization of the content of the articles into the models of disability discourse (the medical, socio-cultural, and superscrip models of disability narratives), and (3) the analysis of any additional data found. A total of 42% of the articles pulled for this study did not deal with the Deaf community in any capacity, but rather instances of the use of idiomatic expressions that use deafness as a metaphor for a non-physical, undesirable trait. The most common idiomatic expression found was fall on deaf ears. Regarding the models of disability discourse, eight articles were found to follow the socio-cultural model, two were found to follow the medical model, and two were found to follow the superscrip model. The additional data found in these articles include two instances of the term deaf and mute, an overwhelming use of lower case d for the term deaf, and the misuse of the term translator (to mean interpreter).

Keywords: deafness, disability, news coverage, Caribbean newspapers

Procedia PDF Downloads 231

Authors: Satpreet Singh

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This paper introduces the new LACGC model to sustain the academic and non-academic business to future educational and organizational generations. The consumption of knowledge and the creation of new knowledge is a strength and focal interest of all academics and Non-academic organizations. Implementing newly created knowledge sustains the businesses to the next generation with growth without detriment. Existing models like the Scholar-practitioner model and Organization knowledge creation models focus specifically on academic or non-academic, not both. LACGC model can be used for both Academic and Non-academic at the domestic or international level. Researchers and scholars play a substantial role in finding literature and practice gaps in academic and non-academic disciplines. LACGC model has unrestricted the number of recurrences because the Consumption, Creation, and implementation of new ideas, disciplines, systems, and knowledge is a never-ending process and must continue from one generation to the next.

Keywords: academics, consumption, creation, generations, non-academics, research, sustainability

Procedia PDF Downloads 190

Authors: A. O. Idris, J. Virgone, A. I. Ibrahim, D. David, E. Vergnault

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In hot countries, the major challenge is the air conditioning. The increase in energy consumption by air conditioning stems from the need to live in more comfortable buildings, which is understandable. But in Djibouti, one of the countries with the most expensive electricity in the world, this need is exacerbated by an architecture that is inappropriate and unsuitable for climatic conditions. This paper discusses the design of the roof which is the surface receiving the most solar radiation. The roof determines the general behavior of the building. The study presents Computational Fluid Dynamics (CFD) modeling and analysis of the energy performance of a double skin ventilated roof. The particularity of this study is that it considers the climate of Djibouti characterized by hot and humid conditions in winter and very hot and humid in summer. Roof simulations are carried out using the Ansys Fluent software to characterize the flow and the heat transfer induced in the ventilated roof in steady state. This modeling is carried out by comparing the influence of several parameters such as the internal emissivity of the upper surface, the thickness of the insulation of the roof and the thickness of the ventilated channel on heat gain through the roof. The energy saving potential compared to the current construction in Djibouti is also presented.

Keywords: building, double skin roof, CFD, thermo-fluid analysis, energy saving, forced convection, natural convection

Procedia PDF Downloads 260

Authors: Hanan A. Abdulhameed, Huda Y. Alyami

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The study presents a new international direction to conduct collaborative educational research. It follows a qualitative and quantitative methodology in investigating the main requirements to build an e-platform for Virtual Research Teams (VRTs). The e-platform considers three main components: First, the human and cultural structure, second, the institutional/organizational structure, and third, the technological structure. The study mainly focuses on the third component, the technological structure (the e-platform), and studies how to incorporate the other components: The human/cultural structure and the institutional/organizational structure in order to build an effective e-platform. The importance of the study is that it presents a comprehensive study about VRTs in terms of definition, types, structure, and main challenges. In addition, it suggests a practical way that benefits from the information and communication technology to conduct collaborative educational research by building and managing virtual research teams through an effective e-platform. The study draws the main framework to build an e-platform for collaborative educational research teams in Arab World. Thus, it tackles mainly the theoretical aspects, the framework of an effective e-platform. Then, it presents the evaluation of 18 Arab educational experts' to the proposed e-platform.

Keywords: collaborative research, educational science, E-platform, social research networks sites (SRNS), virtual research teams (VRTs)

Procedia PDF Downloads 455

Authors: Pragati Sirohi, Vivek Singh Rana

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Brand is a name, term, sign, symbol or design or a combination of all these which is intended to identify the goods or services of one seller or a group of sellers and to differentiate them from those of the competitors and perception influences purchase decisions here and so building that perception is critical. The FMCG industry is a low margin business. Volumes hold the key to success in this industry. Therefore, the industry has a strong emphasis on marketing. Creating strong brands is important for FMCG companies and they devote considerable money and effort in developing brands. Brand loyalty is fickle. Companies know this and that is why they relentlessly work towards brand building. The purpose of the study is a comparison between Indian and Multinational companies with regard to FMCG sector in India. It has been hypothesized that after liberalization the Indian companies has taken up the challenge of globalization and some of these are giving a stiff competition to MNCs. There is an existence of strong brand image of MNCs compared to Indian companies. Advertisement expenditures of MNCs are proportionately higher compared to Indian counterparts. The operational area of the study is the country as a whole. Continuous time series data is available from 1996-2014 for the selected 8 companies. The selection of these companies is done on the basis of their large market share, brand equity and prominence in the market. Research methodology focuses on finding trend growth rates of market capitalization, net worth, and brand values through regression analysis by the usage of secondary data from prowess database developed by CMIE (Centre for monitoring Indian Economy). Estimation of brand values of selected FMCG companies is being attempted, which can be taken to be the excess of market capitalization over the net worth of a company. Brand value indices are calculated. Correlation between brand values and advertising expenditure is also measured to assess the effect of advertising on branding. Major results indicate that although MNCs enjoy stronger brand image but few Indian companies like ITC is the outstanding leader in terms of its market capitalization and brand values. Dabur and Tata Global Beverages Ltd are competing equally well on these values. Advertisement expenditures are the highest for HUL followed by ITC, Colgate and Dabur which shows that Indian companies are not behind in the race. Although advertisement expenditures are playing a role in brand building process there are many other factors which affect the process. Also, brand values are decreasing over the years for FMCG companies in India which show that competition is intense with aggressive price wars and brand clutter. Implications for Indian companies are that they have to consistently put in proactive and relentless efforts in their brand building process. Brands need focus and consistency. Brand longevity without innovation leads to brand respect but does not create brand value.

Keywords: brand value, FMCG, market capitalization, net worth

Procedia PDF Downloads 354

Authors: Shanshan Zhu, Mohammad Nasim

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Financial fraud continues to be a major threat to financial institutions across the world, causing colossal money losses and undermining public trust. Fraud prevention techniques, based on hard rules, have become ineffective due to evolving patterns of fraud in recent times. Against such a background, the present study probes into distinct methodologies that exploit emergent AI-driven techniques to further strengthen fraud detection. We would like to compare the performance of generative adversarial networks and graph neural networks with other popular techniques, like gradient boosting, random forests, and neural networks. To this end, we would recommend integrating all these state-of-the-art models into one robust, flexible, and smart system for real-time anomaly and fraud detection. To overcome the challenge, we designed synthetic data and then conducted pattern recognition and unsupervised and supervised learning analyses on the transaction data to identify which activities were fishy. With the use of actual financial statistics, we compare the performance of our model in accuracy, speed, and adaptability versus conventional models. The results of this study illustrate a strong signal and need to integrate state-of-the-art, AI-driven fraud detection solutions into frameworks that are highly relevant to the financial domain. It alerts one to the great urgency that banks and related financial institutions must rapidly implement these most advanced technologies to continue to have a high level of security.

Keywords: AI-driven fraud detection, financial security, machine learning, anomaly detection, real-time fraud detection

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Authors: Signe Voltelen, Kristin Astrup Aas

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In the Scandinavian cities, there is a raised focus on the potential of using urban agriculture in city development, both as a tool for handling challenges provoked by climate change and to develop new, and stronger social communities. During the last couple of years, Copenhagen has experienced an increase in extreme weather resulting in dramatical floods with huge humanitarian and economic consequences. As an approach for climate adaption and mitigation the government has made a strategy for changing a significant amount of the cities hard surfaces into green and absorbing surfaces. Including urban farms and gardens. In close collaboration with the municipality, it has been possible to implement citizen-run gardens under the different concepts climate adaption and food literacy. Like other European cities, Copenhagen has a historical tradition of small-scale farming for food security inside the city, and in the outskirts of the urban area. Lately, this tradition has gotten new relevance, and new initiatives are popping up. In addition to providing local food, the urban farm becomes a semi-public, semi-private room that invites to community and integration across ethnicity, social background, and age. The direct interaction in the process of farming creates a connection between the urban and the rural and are educational for people growing up and living their whole life in the dense city. In the paper, three local example models of urban agriculture are presented, and the experiences of their potential as tools for developing social and environmental sustainable cities is examined.

Keywords: city development, climate mitigation, community building, urban agriculture, urban- rural transition, food security

Procedia PDF Downloads 278

Authors: Javier Muro, Anja Linstadter, Florian Manner, Lisa Schwarz, Stephan Wollauer, Paul Magdon, Gohar Ghazaryan, Olena Dubovyk

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Monitoring the trade-off between biomass production and biodiversity in grasslands is critical to evaluate the effects of management practices across environmental gradients. New generations of remote sensing sensors and machine learning approaches can model grasslands’ characteristics with varying accuracies. However, studies often fail to cover a sufficiently broad range of environmental conditions, and evidence suggests that prediction models might be case specific. In this study, biomass production and biodiversity indices (species richness and Fishers’ α) are modeled in 150 grassland plots for three sites across Germany. These sites represent a North-South gradient and are characterized by distinct soil types, topographic properties, climatic conditions, and management intensities. Predictors used are derived from Sentinel-1 & 2 and a set of topoedaphic variables. The transferability of the models is tested by training and validating at different sites. The performance of feed-forward deep neural networks (DNN) is compared to a random forest algorithm. While biomass predictions across gradients and sites were acceptable (r2 0.5), predictions of biodiversity indices were poor (r2 0.14). DNN showed higher generalization capacity than random forest when predicting biomass across gradients and sites (relative root mean squared error of 0.5 for DNN vs. 0.85 for random forest). DNN also achieved high performance when using the Sentinel-2 surface reflectance data rather than different combinations of spectral indices, Sentinel-1 data, or topoedaphic variables, simplifying dimensionality. This study demonstrates the necessity of training biomass and biodiversity models using a broad range of environmental conditions and ensuring spatial independence to have realistic and transferable models where plot level information can be upscaled to landscape scale.

Keywords: ecosystem services, grassland management, machine learning, remote sensing

Procedia PDF Downloads 215