Search results for: restructuring digital factory model

Authors: Manit Pollar

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Identifying the dengue epidemic periods early would be helpful to take necessary actions to prevent the dengue outbreaks. Providing an accurate prediction on dengue epidemic seasons will allow sufficient time to take the necessary decisions and actions to safeguard the situation for local authorities. This study aimed to develop a forecasting model on number of dengue incidences in Nakhon Si Thammarat Province, Southern Thailand using time series analysis. We develop Seasonal Autoregressive Moving Average (SARIMA) models on the monthly data collected between 2003-2011 and validated the models using data collected between January-September 2012. The result of this study revealed that the SARIMA(1,1,0)(1,2,1)12 model closely described the trends and seasons of dengue incidence and confirmed the existence of dengue fever cases in Nakhon Si Thammarat for the years between 2003-2011. The study showed that the one-step approach for predicting dengue incidences provided significantly more accurate predictions than the twelve-step approach. The model, even if based purely on statistical data analysis, can provide a useful basis for allocation of resources for disease prevention.

Keywords: SARIMA, time series model, dengue cases, Thailand

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Authors: Hyun Kyu Cho, Jun Soo Kim, Young Hoon Lee, Sang Hoon Kang, Young Chul Park

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In the study, structure for one of offshore drilling system APV(Air Pressure Vessle) modules was designed by using topology optimum design and performed structural safety evaluation according to DNV rules. 3D model created base on design area and non-design area separated by using topology optimization for the environmental loads. This model separated 17 types for wind loads and dynamic loads and performed structural analysis evaluation for each model. As a result, the maximum stress occurred 181.25MPa.

Keywords: APV, topology optimum design, DNV, structural analysis, stress

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Authors: Matthias Haenisch, Marc Godau, Julia Barreiro, Dominik Maxelon

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In times of ubiquitous digitalization and the increasing entanglement of humans and technologies in musical practices in the 21st century, it is to be asked, how popular musicians learn in the (post)digital Age. Against the backdrop of the increasing interest in transferring informal learning practices into formal settings of music education the interdisciplinary research association »MusCoDA – Musical Communities in the (Post)Digital Age« (University of Erfurt/University of Applied Sciences Clara Hoffbauer Potsdam, funded by the German Ministry of Education and Research, pursues the goal to derive an empirical model of collective songwriting practices from the study of informal lelearningf songwriters and bands that can be translated into pedagogical concepts for music education in schools. Drawing on concepts from Community of Musical Practice and Actor Network Theory, lelearnings considered not only as social practice and as participation in online and offline communities, but also as an effect of heterogeneous networks composed of human and non-human actors. Learning is not seen as an individual, cognitive process, but as the formation and transformation of actor networks, i.e., as a practice of assembling and mediating humans and technologies. Based on video stimulated recall interviews and videography of online and offline activities, songwriting practices are followed from the initial idea to different forms of performance and distribution. The data evaluation combines coding and mapping methods of Grounded Theory Methodology and Situational Analysis. This results in network maps in which both the temporality of creative practices and the material and spatial relations of human and technological actors are reconstructed. In addition, positional analyses document the power relations between the participants that structure the learning process of the field. In the area of online informal lelearninginitial key research findings reveal a transformation of the learning subject through the specific technological affordances of TikTok and Instagram and the accompanying changes in the learning practices of the corresponding online communities. Learning is explicitly shaped by the material agency of online tools and features and the social practices entangled with these technologies. Thus, any human online community member can be invited to directly intervene in creative decisions that contribute to the further compositional and structural development of songs. At the same time, participants can provide each other with intimate insights into songwriting processes in progress and have the opportunity to perform together with strangers and idols. Online Lelearnings characterized by an increase in social proximity, distribution of creative agency and informational exchange between participants. While it seems obvious that traditional notions not only of lelearningut also of the learning subject cannot be maintained, the question arises, how exactly the observed informal learning practices and the subject that emerges from the use of social media as online learning technologies can be transferred into contexts of formal learning

Keywords: informal learning, postdigitality, songwriting, actor-network theory, community of musical practice, social media, TikTok, Instagram, apps

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Authors: Hao-Hsi Tseng, Hsin-Yun Lee

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In the process of building design, the designers have to complete the spatial design and consider the evacuation performance at the same time. It is usually difficult to combine the two planning processes and it results in the gap between spatial design and evacuation performance. Then the designers cannot complete an integrated optimal design solution. In addition, the evacuation routing models proposed by previous researchers is different from the practical evacuation decisions in the real field. On the other hand, more and more building design projects are executed by Building Information Modeling (BIM) in which the design content is formed by the object-oriented framework. Thus, the integration of BIM and evacuation simulation can make a significant contribution for designers. Therefore, this research plan will establish a model that integrates spatial design and evacuation planning. The proposed model will provide the support for the spatial design modifications and optimize the evacuation planning. The designers can complete the integrated design solution in BIM. Besides, this research plan improves the evacuation routing method to make the simulation results more practical. The proposed model will be applied in a building design project for evaluation and validation when it will provide the near-optimal design suggestion. By applying the proposed model, the integration and efficiency of the design process are improved and the evacuation plan is more useful. The quality of building spatial design will be better.

Keywords: building information modeling, evacuation, design, floor plan

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Authors: Eva Queheille, Franck Taillandier, Nadia Saiyouri

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Waste management has become a major issue in demolition works, because of its environmental impact (energy consumption, resource consumption, pollution…). However, improving waste management requires to take also into account the overall demolition process and to consider demolition main objectives (e.g. cost, delay). Establishing a strategy with these conflicting objectives (economic and environment) remains complex. In order to provide a decision-support for demolition companies, a multi-objective optimization model was developed. In this model, a demolition strategy is computed from a set of 80 decision variables (worker team composition, machines, treatment for each type of waste, choice of treatment platform…), which impacts the demolition objectives. The model has experimented on a real-case study (demolition of several buildings in France). To process the optimization, different optimization algorithms (NSGA2, MOPSO, DBEA…) were tested. Results allow the engineer in charge of this case, to build a sustainable demolition strategy without affecting cost or delay.

Keywords: deconstruction, life cycle assessment, multi-objective optimization, waste management

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Authors: Esther Simpson, Evans Addo Tetteh

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One of the most important sectors in Ghana’s economy is the oil and gas sector. Effective supply chain management is required to ensure the timely delivery of these products to the end users, given the rise in nationwide demand for petroleum products. Contrarily, freight forwarding plays a crucial role in facilitating intra- and intra-country trade, particularly the movement of oil goods. Nevertheless, there has not been enough scientific study done on how marketing, supply chain management, and freight forwarding are integrated in the oil business. By highlighting possible areas for development in the supply chain management of petroleum products, this article seeks to close this gap. The study was predominantly qualitative and featured semi-structured interviews with influential figures in the oil and gas sector, such as marketers, distributors, freight forwarders, and regulatory organizations. The purpose of the interviews was to determine the difficulties and possibilities for enhancing the management of the petroleum products supply chain. Thematic analysis was used to examine the data obtained in order to find patterns and themes that arose. The findings from the study revealed that the oil sector faced a number of issues in terms of supply chain management. Inadequate infrastructure, insufficient storage facilities, a lack of cooperation among parties, and an inadequate regulatory framework were among the obstacles. Furthermore, the study indicated significant prospects for enhancing petroleum product supply chain management, such as the integration of more advanced digital technologies, the formation of strategic alliances, and the adoption of sustainable practices in petroleum product supply chain management. The study's conclusions have far-reaching ramifications for the oil and gas sector, freight forwarding, and Ghana’s economy as a whole. Marketing, supply chain management, and freight forwarding has high prospects from being integrated to improve the efficiency of the petroleum product supply chain, resulting in considerable cost savings for the industry. Furthermore, the use of sustainable practices will improve the industry's sustainability and lessen the environmental effect of the petroleum product supply chain. Based on the findings, we propose that stakeholders in Ghana’s oil and gas sector work together and collaborate to enhance petroleum supply chain management. This collaboration should include the use of digital technologies, the formation of strategic alliances, and the implementation of sustainable practices. Moreover, we urge that governments establish suitable rules to guarantee the efficient and sustainable management of petroleum product supply chains. In conclusion, the integration and combination of marketing, supply chain management, and freight forwarding in the oil business gives a tremendous opportunity for enhancing petroleum product supply chain management. The study's conclusions have far-reaching ramifications for the sector, freight forwarding, and the economy as a whole. Using sustainable practices, integrating digital technology, and forming strategic alliances will improve the efficiency and sustainability of the petroleum product supply chain. We expect that this conference paper will encourage more study and collaboration among oil and gas sector stakeholders to improve petroleum supply chain management.

Keywords: collaboration, logistics, sustainability, supply chain management

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Authors: Ahmad Shayeq Azizi, Yuji Toda

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In Afghanistan, floods are the most frequent and recurrent events among other natural disasters. On the other hand, lack of monitoring data is a severe problem, which increases the difficulty of making the appropriate flood countermeasures of flood forecasting. This study is carried out to simulate the flood inundation in Harirud River Basin by application of distributed hydrological model, Integrated Flood Analysis System (IFAS) and 2D hydrodynamic model, International River Interface Cooperative (iRIC) based on satellite rainfall combined with historical peak discharge and global accessed data. The results of the simulation can predict the inundation area, depth and velocity, and the hardware countermeasures such as the impact of levee installation can be discussed by using the present method. The methodology proposed in this study is suitable for the area where hydrological and geographical data including river survey data are poorly observed.

Keywords: distributed hydrological model, flood inundation, hydrodynamic model, ungauged basins

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Authors: Hamidreza Babaali, Alireza Mojtahedi, Nasim Soori, Saba Soori

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Hydraulic jump is one of the effective ways of energy dissipation in stilling basins that the ‎energy is highly dissipated by jumping. Adverse slope surface at the end stilling basin is ‎caused to increase energy dissipation and stability of the hydraulic jump. In this study, the adverse slope ‎has been added to end of United States Bureau of Reclamation (USBR) II stilling basin in hydraulic model of Nazloochay dam with scale 1:40, and flow simulated into stilling basin using Flow-3D ‎software. The numerical model is verified by experimental data of water depth in ‎stilling basin. Then, the parameters of water level profile, Froude Number, pressure, air ‎entrainment and turbulent dissipation investigated for discharging 300 m³/s using K-Ɛ and Re-Normalization Group (RNG) turbulence ‎models. The results showed a good agreement between numerical and experimental model‎ as ‎numerical model can be used to optimize of stilling basins.‎

Keywords: experimental and numerical modelling, end adverse slope, flow ‎parameters, USBR II stilling basin

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Authors: Thohaku Abdul Hadi, Hadyan Perdana Putra, Nugroho Wicaksono, Adhika Prajna Nandiwardhana, Onang Surya Nugroho, Heri Suryoatmojo, Soedibjo

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Access to electricity is now a basic requirement of mankind. Unfortunately, there are still many places around the world which have no access to electricity, such as small islands, where there could potentially be a factory, a plantation, a residential area, or resorts. Many of these places might have substantial potential for energy generation such us Photovoltaic (PV) and Wind turbine (WT), which can be used to generate electricity independently for themselves. Solar energy and wind power are renewable energy sources which are mostly found in nature and also kinds of alternative energy that are still developing in a rapid speed to help and meet the demand of electricity. PV and Wind has a characteristic of power depend on solar irradiation and wind speed based on geographical these areas. This paper presented a control methodology of hybrid small scale PV/Wind energy system that use a fuzzy logic controller (FLC) to extract the maximum power point tracking (MPPT) in different solar irradiation and wind speed. This paper discusses simulation and analysis of the generation process of hybrid resources in MPP and power conditioning unit (PCU) of Photovoltaic (PV) and Wind Turbine (WT) that is connected to the three-phase low voltage electricity grid system (380V) without battery storage. The capacity of the sources used is 2.2 kWp PV and 2.5 kW PMSG (Permanent Magnet Synchronous Generator) -WT power rating. The Modeling of hybrid PV/Wind, as well as integrated power electronics components in grid connected system, are simulated using MATLAB/Simulink.

Keywords: fuzzy MPPT, grid connected inverter, photovoltaic (PV), PMSG wind turbine

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Authors: Hai L. Tran

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Previous research on agenda setting effects has often focused on the top-down influence of the media at the aggregate level, while overlooking the capacity of audience members to select media and content to fit their individual dispositions. The decentralized characteristics of online communication and digital news create more choices and greater user control, thereby enabling each audience member to seek out a unique blend of media sources, issues, and elements of messages and to mix them into a coherent individual picture of the world. This study examines how audiences use media differently depending on their prior dispositions, thereby making sense of the world in ways that are congruent with their preferences and cognitions. The current undertaking is informed by theoretical frameworks from two distinct lines of scholarship. According to the ideological migration hypothesis, individuals choose to live in communities with ideologies like their own to satisfy their need to belong. One tends to move away from Zip codes that are incongruent and toward those that are more aligned with one’s ideological orientation. This geographical division along ideological lines has been documented in social psychology research. As an extension of agenda setting, the agendamelding hypothesis argues that audiences seek out information in attractive media and blend them into a coherent narrative that fits with a common agenda shared by others, who think as they do and communicate with them about issues of public. In other words, individuals, through their media use, identify themselves with a group/community that they want to join. Accordingly, the present study hypothesizes that because ideology plays a role in pushing people toward a physical community that fits their need to belong, it also leads individuals to receive an idiosyncratic blend of media and be influenced by such selective exposure in deciding what issues are more relevant. Consequently, the individualized focus of media choices impacts how audiences perceive political news coverage and what they know about political issues. The research project utilizes recent data from The American Trends Panel survey conducted by Pew Research Center to explore the nuanced nature of agenda setting at the individual level and amid heightened polarization. Hypothesis testing is performed with both nonparametric and parametric procedures, including regression and path analysis. This research attempts to explore the media-public relationship from a bottom-up approach, considering the ability of active audience members to select among media in a larger process that entails agenda setting. It helps encourage agenda-setting scholars to further examine effects at the individual, rather than aggregate, level. In addition to theoretical contributions, the study’s findings are useful for media professionals in building and maintaining relationships with the audience considering changes in market share due to the spread of digital and social media.

Keywords: agenda setting, agendamelding, audience fragmentation, ideological migration, partisanship, polarization

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Authors: Hong Lu, Yongquan Zhang, Wei Fan, Xiangang Su

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Bent mandrel has been widely used as precise mould in automobile industry, shipping industry and aviation industry. To improve the versatility and efficiency of turning method of bent mandrel with fixed rotational center, an instantaneous machining model based on cutting parameters and machine dimension is prospered in this paper. The spiral-like tool path generation approach in non-axisymmetric turning process of bent mandrel is developed as well to deal with the error of part-to-part repeatability in existed turning model. The actual cutter-location points are calculated by cutter-contact points, which are obtained from the approach of spiral sweep process using equal-arc-length segment principle in polar coordinate system. The tool offset is set to avoid the interference between tool and work piece is also considered in the machining model. Depend on the spindle rotational angle, synchronization control of X-axis, Z-axis and C-axis is adopted to generate the tool-path of the turning process. The simulation method is developed to generate NC program according to the presented model, which includes calculation of cutter-location points and generation of tool-path of cutting process. With the approach of a bent mandrel taken as an example, the maximum offset of center axis is 4mm in the 3D space. Experiment results verify that the machining model and turning method are appropriate for the characteristics of bent mandrel.

Keywords: bent mandrel, instantaneous machining model, simulation method, tool-path generation

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Authors: Yungtai Lo

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Two-part random effects models have been used to fit semi-continuous longitudinal data where the response variable has a point mass at 0 and a continuous right-skewed distribution for positive values. We review methods proposed in the literature for analyzing data with excess zeros. A two-part logit-log-normal random effects model, a two-part logit-truncated normal random effects model, a two-part logit-gamma random effects model, and a two-part logit-skew normal random effects model were used to examine effects of a bottle-weaning intervention on reducing bottle use and daily milk intake from bottles in toddlers aged 11 to 13 months in a randomized controlled trial. We show in all four two-part models that the intervention promoted bottle-weaning and reduced daily milk intake from bottles in toddlers drinking from a bottle. We also show that there are no differences in model fit using either the logit link function or the probit link function for modeling the probability of bottle-weaning in all four models. Furthermore, prediction accuracy of the logit or probit link function is not sensitive to the distribution assumption on daily milk intake from bottles in toddlers not off bottles.

Keywords: two-part model, semi-continuous variable, truncated normal, gamma regression, skew normal, Pearson residual, receiver operating characteristic curve

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Authors: Jonathan Gong

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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, deep learning, image processing, machine learning

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Authors: Mukhtar Raban

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Nelson Mandela University subscribes to a humanizing pedagogy (HP), as housed under broader critical pedagogy, that underpins and informs learning and teaching activities at the institution. The investigation sought to explore the implications of humanizing and critical pedagogical considerations for a technology-enhanced language learning (TELL) environment in a university course. The paper inquires into the design of a learning resource in an online learning environment of an English communication module, that applied HP principles. With an objective of creating agentive spaces for foregrounding identity, student voice, critical self-reflection, and recognition of others’ humanity; a flexible and open 'My Presence' feature was added to the TELL environment that allowed students and lecturers to share elements of their backgrounds in a ‘mutually vulnerable’ manner as a way of establishing digital identity and a more ‘human’ presence in the online language learning encounter, serving as a catalyst for the recognition of the ‘other’. Following a qualitative research design, the study adopted an auto-ethnographic approach, complementing the critical inquiry nature embedded into the activity’s practices. The study’s findings provide critical reflections and deductions on the possibilities of leveraging digital human expression within a humanizing pedagogical framework to advance the realization of HP-adoption in language learning and teaching encounters. It was found that the consideration of humanizing pedagogical principles in the design of online learning was more effective when the critical outcomes were explicated to students and lecturers prior to the completion of the activities. The integration of humanizing pedagogy also led to a contextual advancement of ‘affective’ language learning. Upon critical reflection and analysis, student identity and agency can flourish in a technology-enhanced learning environment when humanizing, and critical pedagogy influences the learning design.

Keywords: critical reflection, humanizing pedagogy, student identity, technology-enhanced language learning

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Authors: Hasan A Al-Asadi, Ali Samir, Afrah Turki Awad, Ali Basem

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Integrating the phase change material (PCM) with photovoltaic (PV) panels is one of the effective techniques to minimize the PV panel temperature and increase their electric output. In order to investigate the impact of the PCM on the electric output of the PV panels for a whole year, a lumped-distributed parameter model for the PV-PCM module has been developed. This development has considered the impact of the PCM density variation between the solid phase and liquid phase. This contribution will increase the assessment accuracy of the electric output of the PV-PCM module. The second contribution is to assess the impact of the expanded composite graphite-PCM on the PV electric output in Milan for a whole year. The novel one-dimensional model has been solved using MATLAB software. The results of this model have been validated against literature experiment work. The weather and the solar radiation data have been collected. The impact of expanded graphite-PCM on the electric output of the PV panel for a whole year has been investigated. The results indicate this impact has an enhancement rate of 2.39% for the electric output of the PV panel in Milan for a whole year.

Keywords: PV panel efficiency, PCM, numerical model, solar energy

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Authors: Xiaoyun Li, Suoang Longzhou

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This paper derives the analytical solution of stellar distance according to its redshift based on the photon-dominated universe expansion model. Firstly, it calculates stellar separation speed and the farthest distance of observable stars via simulation. Then the analytical solution of stellar distance according to its redshift is derived. It shows that when the redshift is large, the stellar distance (and its separation speed) is not proportional to its redshift due to the relativity effect. It also reveals the relationship between stellar age and its redshift. The correctness of the analytical solution is verified by the latest astronomic observations of Ia supernovas in 2020.

Keywords: redshift, cosmic expansion model, analytical solution, stellar distance

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Authors: Laleh Taheri, Noraini C. Pa, Rusli Abdullah, Salfarina Abdullah

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Knowledge plays an important role to the success of any organization. Software development organizations are highly knowledge-intensive organizations especially in their Requirement Elicitation Process (REP). There are several problems regarding communicating and using the knowledge in REP such as misunderstanding, being out of scope, conflicting information and changes of requirements. All of these problems occurred in transmitting the requirements knowledge during REP. Several researches have been done in REP in order to solve the problem towards requirements. Knowledge Audit (KA) approaches were proposed in order to solve managing knowledge in human resources, financial, and manufacturing. There is lack of study applying the KA in requirements elicitation process. Therefore, this paper proposes a KA model for REP in supporting to acquire good requirements.

Keywords: knowledge audit, requirement elicitation process, KA model, knowledge in requirement elicitation

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Authors: Stefanie Jeanette Huber

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This paper explores the relevance and implications of preferences for housing services on house price fluctuations through the lens of an overlapping generation’s model. The model implies that an economy whose agents have lower preferences for housing services is characterized with lower expenditure shares on housing services and will tend to experience more frequent and more volatile housing bubbles. These model predictions are tested empirically in the companion paper Housing Booms and Busts - Convergences and Divergences across OECD countries. Between 1970 - 2013, countries who spend less on housing services as a share of total income experienced significantly more housing cycles and the associated housing boom-bust cycles were more violent. Finally, the model is used to study the impact of rental subsidies and help-to-buy schemes on rational housing bubbles. Rental subsidies are found to contribute to the control of housing bubbles, whereas help-to- buy scheme makes the economy more bubble-prone.

Keywords: housing bubbles, housing booms and busts, preference for housing services, expenditure shares for housing services, rental and purchase subsidies

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Authors: Mohammed A. Zidan, Alaa Sagheer, Nasser Metwally

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Real-time learning is an important goal that most of artificial intelligence researches try to achieve it. There are a lot of problems and applications which require low cost learning such as learn a robot to be able to classify and recognize patterns in real time and real-time recall. In this contribution, we suggest a model of quantum competitive learning based on a series of quantum gates and additional operator. The proposed model enables to recognize any incomplete patterns, where we can increase the probability of recognizing the pattern at the expense of the undesired ones. Moreover, these undesired ones could be utilized as new patterns for the system. The proposed model is much better compared with classical approaches and more powerful than the current quantum competitive learning approaches.

Keywords: competitive learning, quantum gates, quantum gates, winner-take-all

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Authors: Riznaldi Akbar

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In this study, we compared the performance of the Artificial Neural Network (ANN) model with back-propagation algorithm in correctly predicting in-sample and out-of-sample external debt crisis in Indonesia. We found that exchange rate, foreign reserves, and exports are the major determinants to experiencing external debt crisis. The ANN in-sample performance provides relatively superior results. The ANN model is able to classify correctly crisis of 89.12 per cent with reasonably low false alarms of 7.01 per cent. In out-of-sample, the prediction performance fairly deteriorates compared to their in-sample performances. It could be explained as the ANN model tends to over-fit the data in the in-sample, but it could not fit the out-of-sample very well. The 10-fold cross-validation has been used to improve the out-of-sample prediction accuracy. The results also offer policy implications. The out-of-sample performance could be very sensitive to the size of the samples, as it could yield a higher total misclassification error and lower prediction accuracy. The ANN model could be used to identify past crisis episodes with some accuracy, but predicting crisis outside the estimation sample is much more challenging because of the presence of uncertainty.

Keywords: debt crisis, external debt, artificial neural network, ANN

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Authors: Soudabeh Shemehsavar

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In this paper, we consider the situation under a life test, in which the failure time of the test units are not related deterministically to an observable stochastic time varying covariate. In such a case, the joint distribution of failure time and a marker value would be useful for modeling the step stress life test. The problem of accelerating such an experiment is considered as the main aim of this paper. We present a step stress accelerated model based on a bivariate Wiener process with one component as the latent (unobservable) degradation process, which determines the failure times and the other as a marker process, the degradation values of which are recorded at times of failure. Parametric inference based on the proposed model is discussed and the optimization procedure for obtaining the optimal time for changing the stress level is presented. The optimization criterion is to minimize the approximate variance of the maximum likelihood estimator of a percentile of the products’ lifetime distribution.

Keywords: bivariate normal, Fisher information matrix, inverse Gaussian distribution, Wiener process

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Authors: Muhanad Al-Jubouri

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A local scour is the most important of the several scours impacting bridge performance and security. Even though scour is widespread in bridges, especially during flood seasons, the experimental tests could not be applied to many standard highway bridges. A computational fluid dynamics numerical model was used to solve the problem of calculating local scouring and deposition for non-cohesive silt and clear water conditions near single and double cylindrical piers with the effect of floating debris. When FLOW-3D software is employed with the Rang turbulence model, the Nilsson bed-load transfer equation and fine mesh size are considered. The numerical findings of single cylindrical piers correspond pretty well with the physical model's results. Furthermore, after parameter effectiveness investigates the range of outcomes based on predicted user inputs such as the bed-load equation, mesh cell size, and turbulence model, the final numerical predictions are compared to experimental data. When the findings are compared, the error rate for the deepest point of the scour is equivalent to 3.8% for the single pier example.

Keywords: local scouring, non-cohesive, clear water, computational fluid dynamics, turbulence model, bed-load equation, debris

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Authors: Bagireanu Astrid, Bros-Williamson Julio, Duncheva Mila, Currie John

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Digital Twins (DT) are an innovative concept of cyber-physical integration of data between an asset and its virtual replica. They have originated in established industries such as manufacturing and aviation and have garnered increasing attention as a potentially transformative technology within the built environment. With the potential to support decision-making, real-time simulations, forecasting abilities and managing operations, DT do not fall under a singular scope. This makes defining and leveraging the potential uses of DT a potential missed opportunity. Despite its recognised potential in established industries, literature on DT in the built environment remains limited. Inadequate attention has been given to the implementation of DT in construction projects, as opposed to its operational stage applications. Additionally, the absence of a standardised definition has resulted in inconsistent interpretations of DT in both industry and academia. There is a need to consolidate research to foster a unified understanding of the DT. Such consolidation is indispensable to ensure that future research is undertaken with a solid foundation. This paper aims to present a comprehensive systematic literature review on the role of DT in the built environment. To accomplish this objective, a review and thematic analysis was conducted, encompassing relevant papers from the last five years. The identified papers are categorised based on their specific areas of focus, and the content of these papers was translated into a through classification of DT. In characterising DT and the associated data processes identified, this systematic literature review has identified 6 DT opportunities specifically relevant to the built environment: Facilitating collaborative procurement methods, Supporting net-zero and decarbonization goals, Supporting Modern Methods of Construction (MMC) and off-site manufacturing (OSM), Providing increased transparency and stakeholders collaboration, Supporting complex decision making (real-time simulations and forecasting abilities) and Seamless integration with Internet of Things (IoT), data analytics and other DT. Finally, a discussion of each area of research is provided. A table of definitions of DT across the reviewed literature is provided, seeking to delineate the current state of DT implementation in the built environment context. Gaps in knowledge are identified, as well as research challenges and opportunities for further advancements in the implementation of DT within the built environment. This paper critically assesses the existing literature to identify the potential of DT applications, aiming to harness the transformative capabilities of data in the built environment. By fostering a unified comprehension of DT, this paper contributes to advancing the effective adoption and utilisation of this technology, accelerating progress towards the realisation of smart cities, decarbonisation, and other envisioned roles for DT in the construction domain.

Keywords: built environment, design, digital twins, literature review

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Authors: Arkadiusz P. Wójcik, Tetsuya Sato, Shin-Ichiro Shima, Mateusz Malanowski

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Over the last decades, new technologies have significantly changed the way information is transmitted and stored. Renewable energy sources have become prevalent and affordable. Cooperation of the Information and Communication Technology industry and Renewable Energy industry makes it possible to create a next generation, decentralized power grid. In this context, the study seeks to identify the wider benefits to the local Japanese economy as a result of the development of a decentralised electricity market. Our general approach aims to integrate an economic analysis (monetary appraisal of costs and benefits to society) with externalities that are not quantifiable in monetary terms (e.g. social impact, environmental impact). The study also highlights opportunities and sets out recommendations for the citizens of the island and the local government. The simulation is the scientific basis for economic impact analysis. Various types of sources of energy have been taken into account: residential wind farm, residential wind turbine, solar farm, residential solar panels and private solar farms. Analysis of local geographic and economic conditions allowed creating a customized business model. Very often farmers on Awaji Island are using crop cycle. During each cycle, one part of the field is resting and replenishing nutrients. In the next year another part of the field is resting. Portable solar panels could be freely set up in this part of the field. At the end of the crop cycle, portable solar panels would be moved to the next resting part. Because of spacious area, for a single household 500 square meters of portable solar panels has been proposed and simulated. The devised simulation shows that the Rate of Return on Investment for solar panels, which are on the island, could reach up to 37.21%. Supposing that about 20% of households install solar panels they could produce 49.11% of the electric energy consumed by households on the island. The analysis shows that rest of the energy supply can be produced by currently existing one huge solar farm and two wind farms to meet 97.59% of demand on electricity for households on the island. Although there are more than 7,000 agricultural fields on the island, young people tend to avoid agricultural work and prefer to move from the island to big cities, live there in little mansions and work until late night. The business model proposed in this study could increase farmer’s monthly income by ¥200,000 - ¥300,000 (1,600 euro – 2,400 euro). Young people could work less and have a higher standard of living than in a city. Creation of a decentralized electricity market can unlock significant benefits in other industries (e.g. electric vehicles), providing a welcome boost to economic growth, jobs and quality of life.

Keywords: digital twin, Matlab, model-based systems engineering, simulink, smart grid, systems engineering

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Authors: Pablo J. Valverde, Jaime E. Fernandez

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This paper shows under which conditions public corruption can emerge. The theoretical model includes variables such as the public employee wage (w), a control corruption parameter (c), and the group size of interactions (GS) between clusters of public officers and contractors. The system behavior is analyzed using phase diagrams based on combinations of such parameters (c, w, GS). Numerical simulations are implemented in order to contrast analytic results based on Nash equilibria of the theoretical model. Major findings include the functional relationship between wages and network topology, which attempts to reduce the emergence of corrupt behavior.

Keywords: public corruption, game theory, complex systems, Nash equilibrium.

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Authors: Tejaswi Agarwal, Amritansh Agarwal

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Forest ecosystem plays very important role in the global carbon cycle. It stores about 80% of all above ground and 40% of all below ground terrestrial organic carbon. There is much interest in the extent of tropical forests and their rates of deforestation for two reasons: greenhouse gas contributions and the impact of profoundly negative biodiversity. Deforestation has many ecological, social and economic consequences, one of which is the loss of biological diversity. The rapid deployment of remote sensing (RS) satellites and development of RS analysis techniques in the past three decades have provided a reliable, effective, and practical way to characterize terrestrial ecosystem properties. Global estimates of tropical deforestation vary widely and range from 50,000 to 170,000km2 /yr Recent FAO tropical deforestation estimates for 1990–1995 cite 116,756km2 / yr globally. Remote Sensing can prove to be a very useful tool in monitoring of forests and associated deforestation to a sufficient level of accuracy without the need of physically surveying the forest areas as many of them are physically inaccessible. The methodology for the assessment of forest cover using digital image processing (ERDAS) has been followed. The satellite data for the study was procured from Indian institute of remote Sensing (IIRS), Dehradoon in the digital format. While procuring the satellite data, care was taken to ensure that the data was cloud free and did not belong to dry and leafless season. The Normalized Difference Vegetation Index (NDVI) has been used as a numerical indicator of the reduction in ground biomass. NDVI = (near I.R - Red)/ (near I.R + Red). After calculating the NDVI variations and associated mean, we have analysed the change in ground biomass. Through this paper, we have tried to indicate the rate of deforestation over a given period of time by comparing the forest cover at different time intervals. With the help of remote sensing and GIS techniques, it is clearly shown that the total forest cover is continuously degrading and transforming into various land use/land cover category.

Keywords: remote sensing, deforestation, supervised classification, NDVI, change detection

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Authors: Marilei Amadeu Sabino

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The aim of this study is to establish differences between the terms ‘false cognates’, ‘false friends’ and ‘deceptive cognates’, usually considered to be synonyms. It will be shown they are not synonyms, since they do not designate the same linguistic process or phenomenon. Despite their differences in meaning, many pairs of formally similar words in two (or more) different languages are true cognates, although they are usually known as ‘false’ cognates – such as, for instance, the English and Italian lexical items ‘assist x assistere’; ‘attend x attendere’; ‘argument x argomento’; ‘apology x apologia’; ‘camera x camera’; ‘cucumber x cocomero’; ‘fabric x fabbrica’; ‘factory x fattoria’; ‘firm x firma’; ‘journal x giornale’; ‘library x libreria’; ‘magazine x magazzino’; ‘parent x parente’; ‘preservative x preservativo’; ‘pretend x pretendere’; ‘vacancy x vacanza’, to name but a few examples. Thus, one of the theoretical objectives of this paper is firstly to elaborate definitions establishing a distinction between the words that are definitely ‘false cognates’ (derived from different etyma) and those that are just ‘deceptive cognates’ (derived from the same etymon). Secondly, based on Set Theory and on the concepts of equal sets, subsets, intersection of sets and disjoint sets, this study is intended to elaborate some theoretical and practical questions that will be useful in identifying more precisely similarities and differences between cognate words of different languages, and according to graphic interpretation of sets it will be possible to classify them and provide discernment about the processes of semantic changes. Therefore, these issues might be helpful not only to the Learning of Second and Foreign Languages, but they could also give insights into Foreign and Second Language Teaching Methodology. Acknowledgements: FAPESP – São Paulo State Research Support Foundation – the financial support offered (proc. n° 2017/02064-7).

Keywords: deceptive cognates, false cognates, foreign language learning, teaching methodology

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Authors: Vivek Anand, Rainer Naegele

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Industry 4.0 envisages 'smart' manufacturing and services, taking the automation of the 3rd Industrial Revolution to the autonomy of the 4th Industrial Revolution. Powered by innovations in technology and business models, this disruptive transformation is revitalising industry by integrating silos across and beyond value chains. Motivated by the challenges faced by SMEs and Startups in understanding and adopting Industry 4.0, this paper aims to analyse the concept of Growth Poles and evaluate the possibility of its application to Innovation Clusters that strive to propel Industry 4.0 adoption and capacity building. The proposed paper applies qualitative research methodologies including focus groups and survey questionnaires to identify the various factors that affect formation and development of Innovation Clusters. Employing content analysis, the interaction between SMEs and other ecosystem players in such clusters is studied. A strong collaborative culture is a key driver of digital transformation and technology adoption across sectors, value chains and supply chains; and will position these cluster-based growth poles at the forefront of industrial renaissance. Motivated by this argument, and based on the results of the qualitative research, a roadmap will be proposed to position Innovation Clusters as Growth Poles and effective ecosystems to support Industry 4.0 adoption in a region in the medium to long term. This paper will contribute to the current understanding of the role of Innovation Clusters in capacity building. Relevant management and policy implications stem from the analysis. Furthermore, the findings will be helpful for academicians and policymakers alike, who can leverage an ‘innovation cluster policy’ to enable Industry 4.0 Growth Poles in their regions.

Keywords: digital transformation, fourth industrial revolution, growth poles, industry 4.0, innovation clusters, innovation policy, SMEs and startups

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Authors: Duncan Oteki, Andebut Yeneneh, Daba Gedafa, Nabil Suleiman

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Most agencies lack the equipment required to measure the dynamic modulus (|E*|) of asphalt mixtures, necessitating the need to use predictive models. This study compared measured |E*| values for nine North Dakota asphalt mixes using the original Witczak, modified Witczak, and Hirsch models. The influence of temperature on the |E*| models was investigated, and Pavement ME simulations were conducted using measured |E*| and predictions from the most accurate |E*| model. The results revealed that the original Witczak model yielded the lowest Se/Sy and highest R² values, indicating the lowest bias and highest accuracy, while the poorest overall performance was exhibited by the Hirsch model. Using predicted |E*| as inputs in the Pavement ME generated conservative distress predictions compared to using measured |E*|. The original Witczak model was recommended for predicting |E*| for low-reliability pavements in North Dakota.

Keywords: asphalt mixture, binder, dynamic modulus, MEPDG, pavement ME, performance, prediction

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Authors: Shreekumari Patel, Prabhjot Kaur, Paras Solanki

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Moon Mineralogy Mapper (M3), Miniature Radio Frequency (Mini-RF), Kaguya Terrain Camera images, Lunar Orbiter Laser Altimeter (LOLA) digital elevation model (DEM) and Lunar Reconnaissance Orbiter Camera (LROC)- Narrow angle camera (NAC) and Wide angle camera (WAC) images were used to study mineralogy, surface physical properties, and age of the 42 km diameter Kopff crater. M3 indicates the low albedo crater floor to be high-Ca pyroxene dominated associated with floor fracture suggesting the igneous activity of the gabbroic material. Signature of anorthositic material is sampled on the eastern edge as target material is excavated from ~3 km diameter impact crater providing access to the crustal composition. Several occurrences of spinel were detected in northwestern rugged terrain. Our observation can be explained by exposure of spinel by this crater that impacted onto the inner rings of Orientale basin. Spinel was part of the pre-impact target, an intrinsic unit of basin ring. Crater floor was dated by crater counts performed on Kaguya TC images. Nature of surface was studied in detail with LROC NAC and Mini-RF. Freshly exposed surface and boulder or debris seen in LROC NAC images have enhanced radar signal in comparison to mature terrain of Kopff crater. This multidisciplinary analysis of remote sensing data helps to assess lunar surface in detail.

Keywords: crater, mineralogy, moon, radar observations

Procedia PDF Downloads 151