Search results for: modeling platform

Authors: Amalia Triantafillidoy, Georgios Lappas, Prodromos Yannas, Alexandros Kleftodimos

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In this paper an experiment was conducted to assess the impact of online deliberation on citizens’ attitudes. Specifically, this research compared pre and post deliberation opinions of participants who deliberated online via an asynchronous platform regarding the issue of political opinion polls. Results indicate that online deliberation had a positive effect on citizens’ attitudes since it was found that following deliberation participants changed their views regarding public opinion polls. Specifically, online deliberation improved discussants perceptions regarding the reliability of polls, while suppressing their negative views about the misuse of polls by media, polling organizations and politicians.

Keywords: attitudes change, e-democracy, online deliberation, opinion polls

Procedia PDF Downloads 325

Authors: M. Yilmaz, I. Yilmaz, M. Uysal

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The Earth system generates different phenomena that are observable at the surface of the Earth such as mass deformations and displacements leading to plate tectonics, earthquakes, and volcanism. The dynamic processes associated with the interior, surface, and atmosphere of the Earth affect the three pillars of geodesy: shape of the Earth, its gravity field, and its rotation. Geodesy establishes a characteristic structure in order to define, monitor, and predict of the whole Earth system. The traditional and new instruments, observables, and techniques in geodesy are related to the gravity field. Therefore, the geodesy monitors the gravity field and its temporal variability in order to transform the geodetic observations made on the physical surface of the Earth into the geometrical surface in which positions are mathematically defined. In this paper, the main components of the gravity field modeling, (Free-air and Bouguer) gravity anomalies are calculated via recent global models (EGM2008, EIGEN6C4, and GECO) over a selected study area. The model-based gravity anomalies are compared with the corresponding terrestrial gravity data in terms of standard deviation (SD) and root mean square error (RMSE) for determining the best fit global model in the study area at a regional scale in Turkey. The least SD (13.63 mGal) and RMSE (15.71 mGal) were obtained by EGM2008 for the Free-air gravity anomaly residuals. For the Bouguer gravity anomaly residuals, EIGEN6C4 provides the least SD (8.05 mGal) and RMSE (8.12 mGal). The results indicated that EIGEN6C4 can be a useful tool for modeling the gravity field of the Earth over the study area.

Keywords: free-air gravity anomaly, Bouguer gravity anomaly, global model, land gravity

Procedia PDF Downloads 174

Authors: Nurulasma Zainudin, Mashitah Mohd Yusoff, Kwok Feng Chong

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Functionalized reduced graphene oxide is essential importance for their end applications. Chemical functionalization of reduced graphene oxide with strange atoms is a leading strategy to modify the properties of the materials moreover maintains the inherent properties of reduced graphene oxide. A thionine functionalized reduce graphene oxide electrode was fabricated and was used to electrochemically determine nitrite. The electrochemical behaviour of thionine functionalized reduced graphene oxide towards oxidation of nitrite via cyclic voltammetry was studied and the proposed method exhibited enhanced electrocatalytic behaviour.

Keywords: nitrite, sensor, thionine, reduced graphene oxide

Procedia PDF Downloads 447

Authors: K. Mirudhula, R. Saravanan

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Bhavani basin is the fourth largest Sub Basin in the Cauvery basin. The entire command area of all three major canals that takes off from the Bhavani river falls within the Erode District i.e. Lower Bhavani Project (LBP), Kodiveri and Kalingarayan canals. The LBP canal is a major source of irrigation in Erode District. Many of these canals are unlined and leakage takes place from them. Thus the seepage from the canal helps in recharging the wells in the area, enabling to get adequate water supply for the crops when water was not released from Bhavanisagar Dam. In this study, the groundwater recharge is determined by groundwater flow modeling using Visual MODFLOW model. For this purpose, three major natural sources of groundwater recharge are taken into consideration such as rainfall infiltration, canal seepage and return flow of irrigation. The model was run and ZONEBUDGET gives an idea about the amount of recharge from lined/unlined canal to the field. Unlined canal helps to recharge the groundwater about 20% more than the lined canal. The analysis reveals that the annual rainfall also has rapidly changed in this region. In the LBP canal Head reach meets their requirement with available quantity of water from the canal system. Tail end reach does not receive the required quantity of water because of seepage loss and conveyance loss. Hence the lined canal can be provided for full length of the main canal. Branch canals and minor distributaries are suggested to maintain the canals with unlined canal system.

Keywords: lower Bhavani basin, erode, groundwater flow modeling, irrigation practice, lined canal system

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Authors: Zhen Cao, Yu Zhu, Junxue Fu

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Immunoassay, i.e., antigen-antibody reaction, is crucial for disease diagnostics. To achieve the adequate signal of the antigen protein detection, a large amount of sample and long incubation time is needed. However, the amount of protein is usually small at the early stage, which makes it difficult to detect. Unlike cells and DNAs, no valid chemical method exists for protein amplification. Thus, an alternative way to improve the signal is through particle manipulation techniques to concentrate proteins, among which dielectrophoresis (DEP) is an effective one. DEP is a technique that concentrates particles to the designated region through a force created by the gradient in a non-uniform electric field. Since DEP force is proportional to the cube of particle size and square of electric field gradient, it is relatively easy to capture larger particles such as cells. For smaller ones like proteins, a super high gradient is then required. In this work, three-dimensional Ag/SiO2 nanorods arrays, fabricated by an easy physical vapor deposition technique called as oblique angle deposition, have been integrated with a DEP device and created the field gradient as high as of 2.6×10²⁴ V²/m³. The nanorods based DEP device is able to enrich bovine serum albumin (BSA) protein by 1800-fold and the rate has reached 180-fold/s when only applying 5 V electric potential. Based on the above nanorods integrated DEP platform, an immunoassay of mouse immunoglobulin G (IgG) proteins has been performed. Briefly, specific antibodies are immobilized onto nanorods, then IgG proteins are concentrated and captured, and finally, the signal from fluorescence-labelled antibodies are detected. The limit of detection (LoD) is measured as 275.3 fg/mL (~1.8 fM), which is a 20,000-fold enhancement compared with identical assays performed on blank glass plates. Further, prostate-specific antigen (PSA), which is a cancer biomarker for diagnosis of prostate cancer after radical prostatectomy, is also quantified with a LoD as low as 2.6 pg/mL. The time to signal saturation has been significantly reduced to one minute. In summary, together with an easy nanorod fabrication and integration method, this nanorods based DEP platform has demonstrated highly sensitive immunoassay performance and thus poses great potentials in applications for early point-of-care diagnostics.

Keywords: dielectrophoresis, immunoassay, oblique angle deposition, protein concentration

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Authors: Hussain Syed Asad, Richard Kwok Kit Yuen, Gongsheng Huang

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Real-time optimization has been considered an effective approach for improving energy efficient operation of heating, ventilation, and air-conditioning (HVAC) systems. In model-based real-time optimization, model mismatches cannot be avoided. When model mismatches are significant, the performance of the real-time optimization will be impaired and hence the expected energy saving will be reduced. In this paper, the model mismatches for chiller plant on real-time optimization are considered. In the real-time optimization of the chiller plant, simplified semi-physical or grey box model of chiller is always used, which should be identified using available operation data. To overcome the model mismatches associated with the chiller model, hybrid Genetic Algorithms (HGAs) method is used for online real-time training of the chiller model. HGAs combines Genetic Algorithms (GAs) method (for global search) and traditional optimization method (i.e. faster and more efficient for local search) to avoid conventional hit and trial process of GAs. The identification of model parameters is synthesized as an optimization problem; and the objective function is the Least Square Error between the output from the model and the actual output from the chiller plant. A case study is used to illustrate the implementation of the proposed method. It has been shown that the proposed approach is able to provide reliability in decision making, enhance the robustness of the real-time optimization strategy and improve on energy performance.

Keywords: energy performance, hybrid adaptive modeling, hybrid genetic algorithms, real-time optimization, heating, ventilation, and air-conditioning

Procedia PDF Downloads 420

Authors: Gaurav Kumar Sinha

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The oil refining industry, significant in its energy consumption and carbon emissions, faces increasing pressure to reduce its environmental footprint. This article explores the application of energy efficiency and sustainability analytics as crucial tools for reducing carbon emissions in oil refineries. Through a comprehensive review of current practices and technologies, this study highlights innovative analytical approaches that can significantly enhance energy efficiency. We focus on the integration of advanced data analytics, including machine learning and predictive modeling, to optimize process controls and energy use. These technologies are examined for their potential to not only lower energy consumption but also reduce greenhouse gas emissions. Additionally, the article discusses the implementation of sustainability analytics to monitor and improve environmental performance across various operational facets of oil refineries. We explore case studies where predictive analytics have successfully identified opportunities for reducing energy use and emissions, providing a template for industry-wide application. The challenges associated with deploying these analytics, such as data integration and the need for skilled personnel, are also addressed. The paper concludes with strategic recommendations for oil refineries aiming to enhance their sustainability practices through the adoption of targeted analytics. By implementing these measures, refineries can achieve significant reductions in carbon emissions, aligning with global environmental goals and regulatory requirements.

Keywords: energy efficiency, sustainability analytics, carbon emissions, oil refineries, data analytics, machine learning, predictive modeling, process optimization, greenhouse gas reduction, environmental performance

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Authors: Hassan Parandvar, Mehrdad Farid

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In this paper, a finite element modeling is presented for large amplitude vibration of functionally graded material (FGM) plates subjected to combined random pressure and thermal load. The material properties of the plates are assumed to vary continuously in the thickness direction by a simple power law distribution in terms of the volume fractions of the constituents. The material properties depend on the temperature whose distribution along the thickness can be expressed explicitly. The von Karman large deflection strain displacement and extended Hamilton's principle are used to obtain the governing system of equations of motion in structural node degrees of freedom (DOF) using finite element method. Three-node triangular Mindlin plate element with shear correction factor is used. The nonlinear equations of motion in structural degrees of freedom are reduced by using modal reduction method. The reduced equations of motion are solved numerically by 4th order Runge-Kutta scheme. In this study, the random pressure is generated using Monte Carlo method. The modeling is verified and the nonlinear dynamic response of FGM plates is studied for various values of volume fraction and sound pressure level under different thermal loads. Snap-through type behavior of FGM plates is studied too.

Keywords: nonlinear vibration, finite element method, functionally graded material (FGM) plates, snap-through, random vibration, thermal effect

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Authors: Kais Ben-Ahmed, Mhamed Ali-El-Aroui

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This paper develops a Local Generalized Linear Spatial Model (LGLSM) to describe the spatial variation of Visceral Leishmaniasis (VL) infection risk in northern and central Tunisia. The response from each region is a number of affected children less than five years of age recorded from 1996 through 2006 from Tunisian pediatric departments and treated as a poison county level data. The model includes climatic factors, namely averages of annual rainfall, extreme values of low temperatures in winter and high temperatures in summer to characterize the climate of each region according to each continentality index, the pluviometric quotient of Emberger (Q2) to characterize bioclimatic regions and component for residual extra-poison variation. The statistical results show the progressive increase in the number of affected children in regions with high continentality index and low mean yearly rainfull. On the other hand, an increase in pluviometric quotient of Emberger contributed to a significant increase in VL incidence rate. When compared with the original GLSM, Bayesian locally modeling is improvement and gives a better approximation of the Tunisian VL risk estimation. According to the Bayesian approach inference, we use vague priors for all parameters model and Markov Chain Monte Carlo method.

Keywords: generalized linear spatial model, local model, extra-poisson variation, continentality index, visceral leishmaniasis, Tunisia

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Authors: Derrick Mirindi, Frederic Mirindi, Oluwakemi Oshineye

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The ongoing high rate of construction project failures worldwide is often blamed on the difficulties of managing stakeholders. This highlights the crucial role of strategic management (SM) in achieving project success. This study investigates how integrating digital tools into the SM framework can effectively address stakeholder-related challenges. This work specifically focuses on the impact of evolving digital tools, such as Project Management Software (PMS) (e.g., Basecamp and Wrike), Building Information Modeling (BIM) (e.g., Tekla BIMsight and Autodesk Navisworks), Virtual and Augmented Reality (VR/AR) (e.g., Microsoft HoloLens), drones and remote monitoring, and social media and Web-Based platforms, in improving stakeholder engagement and project outcomes. Through existing literature with examples of failed projects, the study highlights how the evolution of digital tools will serve as facilitators within the strategic management process. These tools offer benefits such as real-time data access, enhanced visualization, and more efficient workflows to mitigate stakeholder challenges in construction projects. The findings indicate that integrating digital tools with SM principles effectively addresses stakeholder challenges, resulting in improved project outcomes and stakeholder satisfaction. The research advocates for a combined approach that embraces both strategic management and digital innovation to navigate the complex stakeholder landscape in construction projects.

Keywords: strategic management, digital tools, virtual and augmented reality, stakeholder management, building information modeling, project management software

Procedia PDF Downloads 93

Authors: Pablo M. S. Vallejos

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The article aims to analyze the autobiographical practices of users on Instagram, observing the instrumentalization of image resources in the construction of visual narratives that make up that archive and digital diary. Through bibliographical review, discourse exploration and case studies, the research also aims to present a new theoretical perception about everyday records - edited with a collage of filters and aesthetic tools - that permeate that social network, understanding it as a platform fictionalizing and an expansion of life. In this way, therefore, the work reflects on possible futures in the elaboration of representations and identities in the context of digital spaces in the 21st century.

Keywords: visual culture, social media, autobiography, image

Procedia PDF Downloads 85

Authors: Afshin Keshvadi, Johari Endan, Haniff Harun, Desa Ahmad, Farah Saleena

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Experiments were conducted to develop a model for analyzing the ripening process of oil palm fresh fruits in relation to oil yield and oil quality of palm oil produced. This research was carried out on 8-year-old Tenera (Dura × Pisifera) palms planted in 2003 at the Malaysian Palm Oil Board Research Station. Fresh fruit bunches were harvested from designated palms during January till May of 2010. The bunches were divided into three regions (top, middle and bottom), and fruits from the outer and inner layers were randomly sampled for analysis at 8, 12, 16 and 20 weeks after anthesis to establish relationships between maturity and oil development in the mesocarp and kernel. Computations on data related to ripening time, oil content and oil quality were performed using several computer software programs (MSTAT-C, SAS and Microsoft Excel). Nine nonlinear mathematical models were utilized using MATLAB software to fit the data collected. The results showed mean mesocarp oil percent increased from 1.24 % at 8 weeks after anthesis to 29.6 % at 20 weeks after anthesis. Fruits from the top part of the bunch had the highest mesocarp oil content of 10.09 %. The lowest kernel oil percent of 0.03 % was recorded at 12 weeks after anthesis. Palmitic acid and oleic acid comprised of more than 73 % of total mesocarp fatty acids at 8 weeks after anthesis, and increased to more than 80 % at fruit maturity at 20 weeks. The Logistic model with the highest R2 and the lowest root mean square error was found to be the best fit model.

Keywords: oil palm, oil yield, ripening process, anthesis, fatty acids, modeling

Procedia PDF Downloads 319

Authors: Noah Wayne, Andrea Tuka, Adrian Norbash, Bryan Garber, Paul Ritvo

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Program/Intervention Description: The Canadian Armed Forces(CAF) Mental Health Clinicstreat a full spectrum of mental disorder, addictions, and psychosocial issues that include Major Depressive Disorder, Post-Traumatic Stress Disorder, Generalized Anxiety Disorder, and other diagnoses. We evaluated the feasibility of an online health coach interventiondelivering mindfulness based cognitive behavioral therapy (M-CBT) and behaviour changesupport for individuals receiving treatment at CAF Clinics. Participants were provided accounts on NexJ Connected Wellness, a digital health platform, and 16 weeks of phone-based health coaching,emphasizingmild to moderate aerobic exercise, a healthy diet, and M-CBT content. The primary objective was to assess the feasibility of the online deliverywith CAF members. Evaluation Methods: Feasibility was evaluated in terms of recruitment, engagement, and program satisfaction. Weadditionallyevaluatedhealth behavior change, program completion, and mental health symptoms (i.e. PHQ-9, GAD-7, PCL-5) at three time points. Results: Service members were referred from Vancouver, Esquimalt, and Edmonton CAF bases between August 2020 and January 2021. N=106 CAF personnel were referred, and n=77 consented.N=66 participated, and n=44 completed 4-month and follow-up measures. The platform received a mean rating of76.5 on the System Usability Scale, and health coaching was judged the most helpful program feature (95.2% endorsement), while reminders (53.7%), secure messaging (51.2%), and notifications (51.2%) were also identified. Improvements in mental health status during active interventions were observed on the PHQ-9 (-5.4, p<0.001), GAD-7 (-4.0, p<0.001), and PCL-5 (-4.1, p<0.05). Conclusion: Online health coaching was well-received amidst the COVID-19 pandemic and related lockdowns. Uptake and engagement were positively reported. Participants valuedcontacts and reported strong therapeutic alliances with coaches. Healthy diet, regular exercise, and mindfulness practice are important for physical and mental health. Engagements in these behaviors are associated with reduced symptoms. An online health coach program appears feasible for assisting Canadian Armed Forces personnel.

Keywords: coaching, CBT, military, depression, mental health, digital

Procedia PDF Downloads 162

Authors: S. T. Kumbhar, M. S. Bhatia, R. C. Khairate

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An effective nanodrug delivery system was developed by using chitosan for increased encapsulation efficiency and retarded release of curcumin. Potential ionotropic gelation method was used for the development of chitosan nanoparticles with TPP as cross-linker. The characterization was done for analysis of size, structure, surface morphology, and thermal behavior of synthesized chitosan nanoparticles. The encapsulation efficiency was more than 80%, with improved drug loading capacity. The in-vitro drug release study showed that curcumin release rate was decreased significantly. These chitosan nanoparticles could be a suitable platform for co-delivery of curcumin and anticancer agent for enhanced cytotoxic effect on tumor cells.

Keywords: Curcumin, chitosan, nanoparticles, anticancer activity

Procedia PDF Downloads 182

Authors: Youssef R. Hassan, Mohamed S. Hasanin, Reda M. Abdelhameed

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Recently, innovations in packaging security features become more important to see the originality of packaging in industrial application. Luminescent 3d printing materials have been a promising property which can provides a unique opportunity for the design and application of 3D printing. Lack emission of terbium ions, as a source of green emission, in salt form prevent its uses in industrial applications, so searching about stable and highly emitter material become essential. Nowadays, metal organic frameworks (MOFs) play an important role in designing light emitter material. In this work, fluorescent high density polyethylene (FHDPE) composite filament with Tb-benzene 1,3,5-tricarboxylate (Tb-BTC) MOFs for 3D printing have been successfully developed.HDPE pellets were mixed with Tb-BTC and melting extrustion with single screw extruders. It was found that Tb-BTCuniformly dispersed in the HDPE matrix and significantly increased the crystallinity of PE, which not only maintained the good thermal property but also improved the mechanical properties of Tb-BTC@HDPE composites. Notably, the composite filaments emitted ultra-bright green light under UV lamp, and the fluorescence intensity increased as the content of Tb-BTC increased. Finally, several brightly luminescent exquisite articles could be manufactured by fused deposition modeling (FDM) 3D printer with these new fluorescent filaments. In this context, the development of novel fluorescent Tb-BTC@HDPE composites was combined with 3D printing technology to amplified the packaging Security Features.

Keywords: 3D printing, fluorescent, packaging, security

Procedia PDF Downloads 105

Authors: Yun-Hsiang Wang, Huai-Yi Chen, Kin Fong Lei

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Deoxyribonucleic acid (DNA) hybridization is a common technique used in genetic assay widely. However, the hybridization ratio and rate are usually limited by the diffusion effect. Here, microfluidic electrode platform producing electroosmosis generated by alternating current signal has been proposed to enhance the hybridization ratio and rate. The electrode was made of aurum fabricated by microfabrication technique. Thiol-modified oligo probe was immobilized on the electrode for specific capture of target, which is modified by fluorescent tag. Alternative electroosmosis can induce local microfluidic vortexes to accelerate DNA hybridization. This study provides a strategy to enhance the rate of DNA hybridization in the genetic assay.

Keywords: DNA hybridization, electroosmosis, electrical enhancement, hybridization ratio

Procedia PDF Downloads 387

Authors: Aroob Binhimd, Lyan Sayoti, Rana Almansour

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In recent years, artificial intelligence has grown drastically. This has led to the growth of educational programs to help students in solving educational problems and assist them in understanding certain topics. The purpose of this report is to investigate the Mathway application. Mathway is a mathematics software that teaches students how to solve and handle mathematical issues. The app allows students to insert questions manually on the platform or take a picture of the question, and then they get an answer to this mathematical question. It helps students enhance their performance in mathematics. This app can also be used to verify or check if their answers are correct. The report will include a questionnaire to collect data and analyze the users of this application.

Keywords: artificial intelligence, Mathway, mathematics, mathematical problems

Procedia PDF Downloads 266

Authors: Eko Adhi Setiawan, Duli Asih Siregar, Aiman Setiawan

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Solar energy is abundant in nature, particularly in the tropics which have peak sun hour that can reach 8 hours per day. In the fabrication process, Photovoltaic’s (PV) performance are tested in standard test conditions (STC). It specifies a module temperature of 25°C, an irradiance of 1000 W/ m² with an air mass 1.5 (AM1.5) spectrum and zero wind speed. Thus, the results of the performance testing of PV at STC conditions cannot fully represent the performance of PV in the tropics. For example Indonesia, which has a temperature of 20-40°C. In this paper, the effect of temperature on the choice of the 5 kW AC inverter topology on the PV system such as the Central Inverter, String Inverter and AC-Module specifically for the tropics will be discussed. The proper inverter topology can be determined by analysis of the effect of temperature and irradiation on the PV panel. The effect of temperature and irradiation will be represented in the characteristics of I-V and P-V curves. PV’s characteristics on high temperature would be analyzed using Solar panel modeling through MATLAB Simulink based on mathematical equations that form Solar panel’s characteristic curve. Based on PV simulation, it is known then that temperature coefficients of short circuit current (ISC), open circuit voltage (VOC), and maximum output power (PMAX) consecutively as high as 0.56%/oC, -0.31%/oC and -0.4%/oC. Those coefficients can be used to calculate PV’s electrical parameters such as ISC, VOC, and PMAX in certain earth’s surface’s certain point. Then, from the parameters, the utility of the 5 kW AC inverter system can be determined. As the result, for tropical area, string inverter topology has the highest utility rates with 98, 80 %. On the other hand, central inverter and AC-Module Topology has utility rates of 92.69 % and 87.7 % eventually.

Keywords: Photovoltaic, PV-Inverter Configuration, PV Modeling, Solar Panel Characteristics.

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Authors: Hannah O'Sullivan, Esther Quinn

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Purpose: The Architectural, Engineering, and Construction (AEC) industry has historically struggled to adapt to change. Although the ability to innovate and successfully implement organizational change has been demonstrated to be critical in achieving a sustainable competitive advantage in the industry, many AEC organizations continue to struggle when affecting organizational change. One prominent area of organizational change that presents many challenges in the industry is the adoption of new forms of technology, for example, Building Information Modelling (BIM). Certain Organisational Change Management (OCM) practices have been proven to be effective in supporting organizations to adopt change, but little research has been carried out on diverging employee attitudes to change relative to their roles within the organization. The purpose of this research study is to examine how OCM practices influence employee attitudes to change when adopting new forms of technology and to analyze the diverging employee perspectives within an organization on the importance of different OCM strategies. Methodology: Adopting an interview-based approach, a case study was carried out on a large-sized, prominent Irish construction organization who are currently adopting a new technology platform for its projects. Qualitative methods were used to gain insight into differing perspectives on the utilization of various OCM practices and their efficacy when adopting a new form of technology on projects. Change agents implementing the organizational change gave insight into their intentions with the technology rollout strategy, while other employees were interviewed to understand how this rollout strategy was received and the challenges that were encountered. Findings: The results of this research study are currently being finalized. However, it is expected that employees in different roles will value different OCM practices above others. Findings and conclusions will be determined within the coming weeks. Value: This study will contribute to the body of knowledge relating to the introduction of new technologies, including BIM, to AEC organizations. It will also contribute to the field of organizational change management, providing insight into methods of introducing change that will be most effective for different employees based on their roles and levels of experience within the industry. The focus of this study steers away from traditional studies of the barriers to adopting BIM in its first instance at an organizational level and centers on the direct effect on employees when a company changes the technology platform being used.

Keywords: architectural, engineering, and construction (AEC) industry, Building Information Modelling, case study, challenges, employee perspectives, organisational change management.

Procedia PDF Downloads 75

Authors: Chompunuch Pongjit

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In this research, the authors have shown that social media is becoming an important platform for the dissemination of information among the younger generation who are looking for new tourist-related experiences. The focus of the younger generation in Thailand has shifted toward spiritual experiences which are close to nature, especially during the difficult and stressful time of Covid-19. We have presented the case of the Naga Cave, which is a new pilgrimage site gaining immense popularity among spiritual seekers via social media platforms. Most of the earlier studies in a similar field have focused on cultural tourism in Thailand. However, the emergence of this new spiritual site has not been studied yet.

Keywords: folklore tourism, spirituality, naga cave, thailand, pilgrimage

Procedia PDF Downloads 120

Authors: Mirindi Derrick, Mirindi Frederic, Oluwakemi Oshineye

Abstract:

Abstract: The ongoing high rate of construction project failures worldwide is often blamed on the difficulties of managing stakeholders. This highlights the crucial role of strategic management (SM) in achieving project success. This study investigates how integrating digital tools into the SM framework can effectively address stakeholder-related challenges. This work specifically focuses on the impact of evolving digital tools, such as Project Management Software (PMS) (e.g., Basecamp and Wrike), Building Information Modeling (BIM) (e.g., Tekla BIMsight and Autodesk Navisworks), Virtual and Augmented Reality (VR/AR) (e.g., Microsoft HoloLens), drones and remote monitoring, and social media and Web-Based platforms, in improving stakeholder engagement and project outcomes. Through existing literature with examples of failed projects, the study highlights how the evolution of digital tools will serve as facilitators within the strategic management process. These tools offer benefits such as real-time data access, enhanced visualization, and more efficient workflows to mitigate stakeholder challenges in construction projects. The findings indicate that integrating digital tools with SM principles effectively addresses stakeholder challenges, resulting in improved project outcomes and stakeholder satisfaction. The research advocates for a combined approach that embraces both strategic management and digital innovation to navigate the complex stakeholder landscape in construction projects.

Keywords: strategic management, digital tools, virtual and augmented reality, stakeholder management, building information modeling, project management software

Procedia PDF Downloads 56

Authors: Khaled Shehata, Hanady Hussien, Sara Yehia

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Securing the data stored on E-passport is a very important issue. RSA encryption algorithm is suitable for such application with low data size. In this paper the design and implementation of 1024 bit-key RSA encryption and decryption module on an FPGA is presented. The module is verified through comparing the result with that obtained from MATLAB tools. The design runs at a frequency of 36.3 MHz on Virtex-5 Xilinx FPGA. The key size is designed to be 1024-bit to achieve high security for the passport information. The whole design is achieved through VHDL design entry which makes it a portable design and can be directed to any hardware platform.

Keywords: RSA, VHDL, FPGA, modular multiplication, modular exponential

Procedia PDF Downloads 396

Authors: Ahmed Alghurabi, Mysara Mohyaldinn, Shiferaw Jufar, Obai Younis, Abdullah Abduljabbar

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Erosion modeling equations were typically acquired from regulated experimental trials for solid particles entrained in single-phase or multi-phase flows. Evidently, those equations were later employed to predict the erosion damage caused by the continuous impacts of solid particles entrained in streamflow. It is also well-known that the particle impact angle and velocity do not change drastically in gas-sand flow erosion prediction; hence an accurate prediction of erosion can be projected. On the contrary, high-density fluid flows, such as water flow, through complex geometries, such as sand screens, greatly affect the sand particles’ trajectories/tracks and consequently impact the erosion rate predictions. Particle tracking models and erosion equations are frequently applied simultaneously as a method to improve erosion visualization and estimation. In the present work, computational fluid dynamic (CFD)-based erosion modeling was performed using a commercially available software; ANSYS Fluent. The continuous phase (water flow) behavior was simulated using the realizable K-epsilon model, and the secondary phase (solid particles), having a 5% flow concentration, was tracked with the help of the discrete phase model (DPM). To accomplish a successful erosion modeling, three erosion equations from the literature were utilized and introduced to the ANSYS Fluent software to predict the screen wire-slot velocity surge and estimate the maximum erosion rates on the screen surface. Results of turbulent kinetic energy, turbulence intensity, dissipation rate, the total pressure on the screen, screen wall shear stress, and flow velocity vectors were presented and discussed. Moreover, the particle tracks and path-lines were also demonstrated based on their residence time, velocity magnitude, and flow turbulence. On one hand, results from the utilized erosion equations have shown similarities in screen erosion patterns, locations, and DPM concentrations. On the other hand, the model equations estimated slightly different values of maximum erosion rates of the wire-wrapped screen. This is solely based on the fact that the utilized erosion equations were developed with some assumptions that are controlled by the experimental lab conditions.

Keywords: CFD simulation, erosion rate prediction, material loss due to erosion, water-sand flow

Procedia PDF Downloads 168

Authors: Srinivas Peri, Siva Abhishek Sirivella, Tejaswini Kallakuri, Uzair Ahmad

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Smart cities and intelligent transportation systems rely heavily on effective traffic management and infrastructure planning. This research tackles the data scarcity challenge by generating realistically synthetic traffic data from the PeMS-Bay dataset, enhancing predictive modeling accuracy and reliability. Advanced techniques like TimeGAN and GaussianCopula are utilized to create synthetic data that mimics the statistical and structural characteristics of real-world traffic. The future integration of Spatial-Temporal Generative Adversarial Networks (ST-GAN) is anticipated to capture both spatial and temporal correlations, further improving data quality and realism. Each synthetic data generation model's performance is evaluated against real-world data to identify the most effective models for accurately replicating traffic patterns. Long Short-Term Memory (LSTM) networks are employed to model and predict complex temporal dependencies within traffic patterns. This holistic approach aims to identify areas with low vehicle counts, reveal underlying traffic issues, and guide targeted infrastructure interventions. By combining GAN-based synthetic data generation with LSTM-based traffic modeling, this study facilitates data-driven decision-making that improves urban mobility, safety, and the overall efficiency of city planning initiatives.

Keywords: GAN, long short-term memory (LSTM), synthetic data generation, traffic management

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Authors: Jean Berger, Nassirou Lo, Martin Noel

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Perfectly suited for natural or man-made emergency and disaster management situations such as flood, earthquakes, tornadoes, or tsunami, multi-target search path planning for a team of rescue agents is known to be computationally hard, and most techniques developed so far come short to successfully estimate optimality gap. A novel mixed-integer linear programming (MIP) formulation is proposed to optimally solve the multi-target multi-agent discrete search and rescue (SAR) path planning problem. Aimed at maximizing cumulative probability of successful target detection, it captures anticipated feedback information associated with possible observation outcomes resulting from projected path execution, while modeling agent discrete actions over all possible moving directions. Problem modeling further takes advantage of network representation to encompass decision variables, expedite compact constraint specification, and lead to substantial problem-solving speed-up. The proposed MIP approach uses CPLEX optimization machinery, efficiently computing near-optimal solutions for practical size problems, while giving a robust upper bound obtained from Lagrangean integrality constraint relaxation. Should eventually a target be positively detected during plan execution, a new problem instance would simply be reformulated from the current state, and then solved over the next decision cycle. A computational experiment shows the feasibility and the value of the proposed approach.

Keywords: search path planning, search and rescue, multi-agent, mixed-integer linear programming, optimization

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Authors: Sami Meddeb, M. L Giorgi, J. L. Courouau

Abstract:

This work presents the progress of studies aiming to guarantee the lifetime of 316L(N) steel in a sodium-cooled fast reactor by determining the elementary corrosion mechanism, which is akin to an accelerated dissolution by dissolved oxygen. The mechanism involving iron, the main element of steel, is particularly studied in detail, from the viewpoint of the data available in the literature, the modeling of the various mechanisms hypothesized. Experiments performed in the CORRONa facility at controlled temperature and dissolved oxygen content are used to test both literature data and hypotheses. Current tests, performed at various temperatures and oxygen content, focus on specifying the chemical reaction at play, determining its free enthalpy, as well as kinetics rate constants. Specific test configuration allows measuring the reaction kinetics and the chemical equilibrium state in the same test. In the current state of progress of these tests, the dissolution of iron accelerated by dissolved oxygen appears as directly related to a chemical complexation reaction of mixed iron-sodium oxide (Na-Fe-O), a compound that is soluble in the liquid sodium solution. Results obtained demonstrate the presence in the solution of this corrosion product, whose kinetics is the limiting step under the conditions of the test. This compound, the object of hypotheses dating back more than 50 years, is predominant in solution compared to atomic iron, presumably even for the low oxygen concentration, and cannot be neglected for the long-term corrosion modeling of any heat transfer system.

Keywords: corrosion, sodium fast reactors, iron, oxygen

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Authors: Mojtaba Noghabaei, Khashayar Asadi, Kevin Han

Abstract:

Simultaneous Localization and Mapping (SLAM) technology has recently attracted the attention of construction companies for real-time performance monitoring. To effectively use SLAM for construction performance monitoring, SLAM results should be registered to a Building Information Models (BIM). Registring SLAM and BIM can provide essential insights for construction managers to identify construction deficiencies in real-time and ultimately reduce rework. Also, registering SLAM to BIM in real-time can boost the accuracy of SLAM since SLAM can use features from both images and 3d models. However, registering SLAM with the BIM in real-time is a challenge. In this study, a novel SLAM platform named Model-Based SLAM (MB-SLAM) is proposed, which not only provides automated registration of SLAM and BIM but also improves the localization accuracy of the SLAM system in real-time. This framework improves the accuracy of SLAM by aligning perspective features such as depth, vanishing points, and vanishing lines from the BIM to the SLAM system. This framework extracts depth features from a monocular camera’s image and improves the localization accuracy of the SLAM system through a real-time iterative process. Initially, SLAM can be used to calculate a rough camera pose for each keyframe. In the next step, each SLAM video sequence keyframe is registered to the BIM in real-time by aligning the keyframe’s perspective with the equivalent BIM view. The alignment method is based on perspective detection that estimates vanishing lines and points by detecting straight edges on images. This process will generate the associated BIM views from the keyframes' views. The calculated poses are later improved during a real-time gradient descent-based iteration method. Two case studies were presented to validate MB-SLAM. The validation process demonstrated promising results and accurately registered SLAM to BIM and significantly improved the SLAM’s localization accuracy. Besides, MB-SLAM achieved real-time performance in both indoor and outdoor environments. The proposed method can fully automate past studies and generate as-built models that are aligned with BIM. The main contribution of this study is a SLAM framework for both research and commercial usage, which aims to monitor construction progress and performance in a unified framework. Through this platform, users can improve the accuracy of the SLAM by providing a rough 3D model of the environment. MB-SLAM further boosts the application to practical usage of the SLAM.

Keywords: perspective alignment, progress monitoring, slam, stereo matching.

Procedia PDF Downloads 231

Authors: L. S. Supian, Mohd Syuhaimi Ab-Rahman, Norhana Arsad

Abstract:

Experimental study has been done to study the performance on polymer optical fiber splitter characterization when different bending radii are applied on splitters with different fiber cores. The splitters with different cores pair are attached successively to splitter platform of ellipse-shape geometrical blocks of several bending radii. A force is exerted upon the blocks thus the splitter in order to encourage the splitting of energy between the two fibers. The aim of this study is to investigate which fiber core pair gives the optimum performance that goes with each bending radius in order to develop an effective splitter.

Keywords: splitter, macro-bending, cores, geometrical blocks

Procedia PDF Downloads 677

Authors: Chayanoot Sangwichien, Taweesak Reungpeerakul, Kyaw Thu

Abstract:

Oil palm mills in Southern Thailand produced a large amount of biomass solid wastes. Lignocellulose biomass is the main source for production of biofuel which can be combined or used as an alternative to fossil fuels. Biomass composed of three main constituents of cellulose, hemicellulose, and lignin. Thermochemical conversion process applied to produce biofuel from biomass. Pyrolysis of biomass is the best way to thermochemical conversion of biomass into pyrolytic products (bio-oil, gas, and char). Operating parameters play an important role to optimize the product yields from fast pyrolysis of biomass. This present work concerns with the modeling of reaction kinetics parameters for fast pyrolysis of empty fruit bunch in the fluidized bed reactor. A global kinetic model used to predict the product yields from fast pyrolysis of empty fruit bunch. The reaction temperature and vapor residence time parameters are mainly affected by product yields of EFB pyrolysis. The reaction temperature and vapor residence time parameters effects on empty fruit bunch pyrolysis are considered at the reaction temperature in the range of 450-500˚C and at a vapor residence time of 2 s, respectively. The optimum simulated bio-oil yield of 53 wt.% obtained at the reaction temperature and vapor residence time of 450˚C and 2 s, 500˚C and 1 s, respectively. The simulated data are in good agreement with the reported experimental data. These simulated data can be applied to the performance of experiment work for the fast pyrolysis of biomass.

Keywords: kinetics, empty fruit bunch, fast pyrolysis, modeling

Procedia PDF Downloads 223

Authors: Stamatis Zoras, Vasilis Evagelopoulos, Theodoros Staurakas

Abstract:

The association between elevated air pollution levels and extreme climate conditions (temperature, particulate matter, ozone levels, etc.) and mental consequences has been, recently, the focus of significant number of studies. It varies depending on the time of the year it occurs either during the hot period or cold periods but, specifically, when extreme air pollution and weather events are observed, e.g. air pollution episodes and persistent heatwaves. It also varies spatially due to different effects of air quality and climate extremes to human health when considering metropolitan or rural areas. An air pollutant concentration and a climate extreme are taking a different form of impact if the focus area is countryside or in the urban environment. In the built environment the climate extreme effects are driven through the formed microclimate which must be studied more efficiently. Variables such as biological, age groups etc may be implicated by different environmental factors such as increased air pollution/noise levels and overheating of buildings in comparison to rural areas. Gridded air quality and climate variables derived from the land surface observations network of West Macedonia in Greece will be analysed against mortality data in a spatial format in the region of West Macedonia. Artificial intelligence (AI) tools will be used for data correction and prediction of health deterioration with climatic conditions and air pollution at local scale. This would reveal the built environment implications against the countryside. The air pollution and climatic data have been collected from meteorological stations and span the period from 2000 to 2009. These will be projected against the mortality rates data in daily, monthly, seasonal and annual grids. The grids will be operated as AI-based warning models for decision makers in order to map the health conditions in rural and urban areas to ensure improved awareness of the healthcare system by taken into account the predicted changing climate conditions. Gridded data of climate conditions, air quality levels against mortality rates will be presented by AI-analysed gridded indicators of the implicated variables. An Al-based gridded warning platform at local scales is then developed for future system awareness platform for regional level.

Keywords: air quality, artificial inteligence, climatic conditions, mortality

Procedia PDF Downloads 120