Search results for: mathematical modeling

Authors: Oluremi I. Bamgbade, Oluwayomi Babatunde

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Governments and nonprofits have been in the support of sustainability as the goal of businesses especially in the construction industry because of its considerable impacts on the environment, economy, and society. However, to measure the degree to which an organisation is being sustainable or pursuing sustainable growth can be difficult as a result of the clear sustainability strategy required to assume their commitment to the goal and competitive advantage. This research investigated the influence of organisational culture and organisational structure in achieving sustainable construction among South African construction firms. A total of 132 consultants from the nine provinces in South Africa participated in the survey. The data collected were initially screened using SPSS (version 21) while Partial Least Squares Structural Equation Modeling (PLS-SEM) algorithm and bootstrap techniques were employed to test the hypothesised paths. The empirical evidence also supported the hypothesised direct effects of organisational culture and organisational structure on sustainable construction. Similarly, the result regarding the relationship between organisational culture and organisational structure was supported. Therefore, construction industry can record a considerable level of construction sustainability and establish suitable cultures and structures within the construction organisations. Drawing upon organisational control theory, these findings supported the view that these organisational internal factors have a strong contingent effect on sustainability adoption in construction project execution. The paper makes theoretical, practical and methodological contributions within the domain of sustainable construction especially in the context of South Africa. Some limitations of the study are indicated, suggesting opportunities for future research.

Keywords: organisational culture, organisational structure, South African construction firms, sustainable construction

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Authors: Haniyeh Okhovat, Mahmood Hosseini, Omid Kaveh Ahangari, Mona Zaryoun

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Shavadoon is a type of underground living space, formerly used in urban residences of Dezful and Shooshtar cities in southwestern Iran. In spite of their high efficiency in creating cool spaces for hot summers of that area, Shavadoons were abandoned, like many other components of vernacular architecture, as a result of the modernism movement. However, Shavadoons were used by the local people as shelters during the 8-year Iran-Iraq war, and although several cases of bombardment happened during those years, no case of damage was reported in those two cities. On this basis, and regarding the high seismicity of Iran, the use of Shavadoons as post-disasters shelters can be considered as a good issue for research. This paper presents the results of a thorough study conducted on these spaces and their seismic behavior. First, the architectural aspects of Shavadoon and their construction technique are presented. Then, the results of seismic evaluation of a sample Shavadoon, conducted by a series of time history analyses, using Plaxis software and a set of selected earthquakes, are briefly explained. These results show that Shavadoons have good stability against seismic excitations. This stability is mainly because of the high strength of conglomerate materials inside which the Shavadoons have been excavated. On this basis, and considering other merits of this components of vernacular architecture in southwest of Iran, it is recommended that the revival of these components is seriously reconsidered by both architects and civil engineers.

Keywords: Shavadoon, Iran high seismicity, Conglomerate, Modeling in Plaxis, Vernacular sustainable architecture

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Authors: Madhu Aneja, Sapna Sharma

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Thermal conductivity of ordinary heat transfer fluids is not adequate to meet today’s cooling rate requirements. Nanoparticles have been shown to increase the thermal conductivity and convective heat transfer to the base fluids. One of the possible mechanisms for anomalous increase in the thermal conductivity of nanofluids is the Brownian motions of the nanoparticles in the basefluid. In this paper, the natural convection of incompressible nanofluid over a nonlinear stretching sheet in the presence of magnetic field is studied. The flow and heat transfer induced by stretching sheets is important in the study of extrusion processes and is a subject of considerable interest in the contemporary literature. Appropriate similarity variables are used to transform the governing nonlinear partial differential equations to a system of nonlinear ordinary (similarity) differential equations. For computational purpose, Finite Element Method is used. The effective thermal conductivity and viscosity of nanofluid are calculated by KKL (Koo – Klienstreuer – Li) correlation. In this model effect of Brownian motion on thermal conductivity is considered. The effect of important parameter i.e. nonlinear parameter, volume fraction, Hartmann number, heat source parameter is studied on velocity and temperature. Skin friction and heat transfer coefficients are also calculated for concerned parameters.

Keywords: Brownian motion, convection, finite element method, magnetic field, nanofluid, stretching sheet

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Authors: Ibrahim M. Metwally

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Have you ever thought that earth was not the same earth we live on? Was it bigger or smaller? Was it a great continent surrounded by huge ocean as Alfred Wegener (1912) claimed? Earth is the most amazing planet in our Milky Way galaxy and may be in the universe. It is the only deformed planet that has a variable orbit around the sun and the only planet that has water on its surface. How did earth deformation take place? What does cause earth to deform? What are the results of earth deformation? How does its orbit around the sun change? First earth size computation can be achieved only considering the quantum of iron and nickel rested into earth core. This paper introduces a new theory “Earth expansion Theory”. The principles of “Earth Expansion Theory” are leading to new approaches and concepts to interpret whole earth dynamics and its geological and environmental changes. This theory is not an attempt to unify the two divergent dominant theories of continental drift, plate tectonic theory and earth expansion theory. The new theory is unique since it has a mathematical derivation, explains all the change to and around earth in terms of geological and environmental changes, and answers all unanswered questions in other theories. This paper presents the basic of the introduced theory and discusses the mechanism of earth expansion and how it took place, the forces that made the expansion. The mechanisms of earth size change from its spherical shape with radius about 3447.6 km to an elliptic shape of major radius about 6378.1 km and minor radius of about 6356.8 km and how it took place, are introduced and discussed. This article also introduces, in a more realistic explanation the formation of oceans and seas, the preparation of river formation. It also addresses the role of iron in earth size enlargement process within the continuum mechanics framework.

Keywords: earth size, earth expansion, continuum mechanics, continental and ocean formation

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Authors: Goudjil kamel, Boukhatem Ghania, Jlailia Djihene

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This paper delves into the development of a sophisticated desktop application designed to calculate soil bearing capacity and predict limit pressure. Drawing from an extensive review of existing methodologies, the study meticulously examines various approaches employed in soil bearing capacity calculations, elucidating their theoretical foundations and practical applications. Furthermore, the study explores the burgeoning intersection of artificial intelligence (AI) and geotechnical engineering, underscoring the transformative potential of AI- driven solutions in enhancing predictive accuracy and efficiency.Central to the research is the utilization of cutting-edge machine learning techniques, including Artificial Neural Networks (ANN), XGBoost, and Random Forest, for predictive modeling. Through comprehensive experimentation and rigorous analysis, the efficacy and performance of each method are rigorously evaluated, with XGBoost emerging as the preeminent algorithm, showcasing superior predictive capabilities compared to its counterparts. The study culminates in a nuanced understanding of the intricate dynamics at play in geotechnical analysis, offering valuable insights into optimizing soil bearing capacity calculations and limit pressure predictions. By harnessing the power of advanced computational techniques and AI-driven algorithms, the paper presents a paradigm shift in the realm of geotechnical engineering, promising enhanced precision and reliability in civil engineering projects.

Keywords: limit pressure of soil, xgboost, random forest, bearing capacity

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Authors: Majid Haghshenas, James Wilson, Ranganathan Kumar

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In this study, an Algebraic Coupled Level Set-Volume of Fluid (A-CLSVOF) method with capillary pressure treatment is proposed for the modeling of two-phase capillary flows. The Volume of Fluid (VOF) method is utilized to incorporate one-way coupling with the Level Set (LS) function in order to further improve the accuracy of the interface curvature calculation and resulting surface tension force. The capillary pressure is determined and treated independently of the hydrodynamic pressure in the momentum balance in order to maintain consistency between cell centered and interpolated values, resulting in a reduction in parasitic currents. In this method, both VOF and LS functions are transported where the new volume fraction determines the interface seed position used to reinitialize the LS field. The Hamilton-Godunov function is used with a second order (in space and time) discretization scheme to produce a signed distance function. The performance of the current methodology has been tested against some common test cases in order to assess the reduction in non-physical velocities and improvements in the interfacial pressure jump. The cases of a static drop, non-linear Rayleigh-Taylor instability and finally a droplets impact on a liquid pool were simulated to compare the performance of the present method to other well-known methods in the area of parasitic current reduction, interface location evolution and overall agreement with experimental results.

Keywords: two-phase flow, capillary flow, surface tension force, coupled LS with VOF

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Authors: Mohsen Farhadloo, Majid Farhadloo

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Aspect-level opinion mining that aims at discovering aspects (aspect identification) and their corresponding ratings (sentiment identification) from customer reviews have increasingly attracted attention of researchers and practitioners as it provides valuable insights about products/services from customer's points of view. Instead of addressing aspect identification and sentiment identification in two separate steps, it is possible to simultaneously identify both aspects and sentiments. In recent years many graphical models based on Latent Dirichlet Allocation (LDA) have been proposed to solve both aspect and sentiment identifications in a single step. Although LDA models have been effective tools for the statistical analysis of document collections, they also have shortcomings in addressing some unique characteristics of opinion mining. Our goal in this paper is to address one of the limitations of topic models to date; that is, they fail to directly model the associations among topics. Indeed in many text corpora, it is natural to expect that subsets of the latent topics have higher probabilities. We propose a probabilistic graphical model called focus-LDA, to better capture the associations among topics when applied to aspect-level opinion mining. Our experiments on real-life data sets demonstrate the improved effectiveness of the focus-LDA model in terms of the accuracy of the predictive distributions over held out documents. Furthermore, we demonstrate qualitatively that the focus-LDA topic model provides a natural way of visualizing and exploring unstructured collection of textual data.

Keywords: aspect-level opinion mining, document modeling, Latent Dirichlet Allocation, LDA, sentiment analysis

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Authors: Husham Bayazed

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Immune responses following surgical trauma play a pivotal role in predicting postoperative outcomes from healing and recovery to postoperative complications. Postoperative complications, including infections and protracted recovery, occur in a significant number of about 300 million surgeries performed annually worldwide. Complications cause personal suffering along with a significant economic burden on the healthcare system in any community. The accurate prediction of postoperative complications and patient-targeted interventions for their prevention remain major clinical provocations. Recent Findings: Recent studies are focusing on immune dysregulation mechanisms that occur in response to surgical trauma as a key determinant of postoperative complications. Antecedent studies mainly were plunging into the detection of inflammatory plasma markers, which facilitate in providing important clues regarding their pathogenesis. However, recent Single-cell technologies, such as mass cytometry or single-cell RNA sequencing, have markedly enhanced our ability to understand the immunological basis of postoperative immunological trauma complications and to identify their prognostic biological signatures. Summary: The advent of proteomic technologies has significantly advanced our ability to predict the risk of postoperative complications. Multiomic modeling of patients' immune states holds promise for the discovery of preoperative predictive biomarkers and providing patients and surgeons with information to improve surgical outcomes. However, more studies are required to accurately predict the risk of postoperative complications in individual patients.

Keywords: immune dysregulation, postoperative complications, surgical trauma, flow cytometry

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Authors: Majid Samiee Zenoozian

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The Persian Gulf is a bordering sea with an normal depth of 35 m and a supreme depth of 100 m near its narrow appearance. Its lengthen bathymetric axis divorces two main geological shires — the steady Arabian Foreland and the unbalanced Iranian Fold Belt — which are imitated in the conflicting shore and bathymetric morphologies of Arabia and Iran. The sediments were experimented with from 72 offshore positions through an oceanographic cruise in the winter of 2018. Throughout the observation era, several storms and river discharge actions happened, as well as the major flood on record since 1982. Suspended-sediment focus at all three sites varied in reaction to both wave resuspension and advection of river-derived sediments. We used hydrological models to evaluation and associate the wave height and inundation distance required to carriage the rocks inland. Our results establish that no known or possible storm happening on the Makran coast is accomplished of detaching and transporting the boulders. The fluid mud consequently is conveyed seaward due to gravitational forcing. The measured sediment focus and velocity profiles on the shelf provide a strong indication to provision this assumption. The sediment model is joined with a 3D hydrodynamic module in the Environmental Fluid Dynamics Code (EFDC) model that offers data on estuarine rotation and salinity transport under normal temperature conditions. 3-D sediment transport from model simulations specify dynamic sediment resuspension and transport near zones of highly industrious oyster beds.

Keywords: sediment transport, storm, coast, fluid dynamics

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Authors: Xu Jie

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As a key network security method, cryptographic services must fully cope with problems such as the wide variety of cryptographic algorithms, high concurrency requirements, random job crossovers, and instantaneous surges in workloads. Its complexity and dynamics also make it difficult for traditional static security policies to cope with the ever-changing situation. Cyber Threats and Environment. Traditional resource scheduling algorithms are inadequate when facing complex decision-making problems in dynamic environments. A network cryptographic resource allocation algorithm based on reinforcement learning is proposed, aiming to optimize task energy consumption, migration cost, and fitness of differentiated services (including user, data, and task security) by modeling the multi-job collaborative cryptographic service scheduling problem as a multi-objective optimized job flow scheduling problem and using a multi-agent reinforcement learning method, efficient scheduling and optimal configuration of cryptographic service resources are achieved. By introducing reinforcement learning, resource allocation strategies can be adjusted in real-time in a dynamic environment, improving resource utilization and achieving load balancing. Experimental results show that this algorithm has significant advantages in path planning length, system delay and network load balancing and effectively solves the problem of complex resource scheduling in cryptographic services.

Keywords: cloud computing, cryptography on-demand service, reinforcement learning, workflow scheduling

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Authors: Ayse Cobanoglu

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Working memory can be defined as a workspace that holds and regulates active information in mind. This study investigates individual changes in children's working memory from kindergarten to first grade. The main purpose of the study is whether parental discipline methods and child impulsive/overactive behaviors affect children's working memory initial status and growth rate, controlling for gender, minority status, and socioeconomic status (SES). A linear growth curve model with the first four waves of the Early Childhood Longitudinal Study-Kindergarten Cohort of 2011 (ECLS-K:2011) is performed to analyze the individual growth of children's working memory longitudinally (N=3915). Results revealed that there is a significant variation among students' initial status in the kindergarten fall semester as well as the growth rate during the first two years of schooling. While minority status, SES, and children's overactive/impulsive behaviors influenced children's initial status, only SES and minority status were significantly associated with the growth rate of working memory. For parental discipline methods, such as giving a warning and ignoring the child's negative behavior, are also negatively associated with initial working memory scores. Following that, students' working memory growth rate is examined, and students with lower SES as well as minorities showed a faster growth pattern during the first two years of schooling. However, the findings of parental disciplinary methods on working memory growth rates were mixed. It can be concluded that schooling helps low-SES minority students to develop their working memory.

Keywords: growth curve modeling, impulsive/overactive behaviors, parenting, working memory

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Authors: Kassahun Birhanu Tadesse, Megersa Olumana Dinka

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Reliable future river flow information is basic for planning and management of any river systems. For data scarce river system having only a river flow records like the Waterval River, a univariate time series models are appropriate for river flow forecasting. In this study, a univariate Seasonal Autoregressive Integrated Moving Average (SARIMA) model was applied for forecasting Waterval River flow using GRETL statistical software. Mean monthly river flows from 1960 to 2016 were used for modeling. Different unit root tests and Mann-Kendall trend analysis were performed to test the stationarity of the observed flow time series. The time series was differenced to remove the seasonality. Using the correlogram of seasonally differenced time series, different SARIMA models were identified, their parameters were estimated, and diagnostic check-up of model forecasts was performed using white noise and heteroscedasticity tests. Finally, based on minimum Akaike Information (AIc) and Hannan-Quinn (HQc) criteria, SARIMA (3, 0, 2) x (3, 1, 3)12 was selected as the best model for Waterval River flow forecasting. Therefore, this model can be used to generate future river information for water resources development and management in Waterval River system. SARIMA model can also be used for forecasting other similar univariate time series with seasonality characteristics.

Keywords: heteroscedasticity, stationarity test, trend analysis, validation, white noise

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Authors: Rao Fu, Jie Chen, Shutian Zeng, Yiping Zhuang, Agus Sudjianto

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Generative Adversarial Net (GAN) has proved to be a powerful machine learning tool in image data analysis and generation. In this paper, we propose to use Conditional Generative Adversarial Net (CGAN) to learn and simulate time series data. The conditions include both categorical and continuous variables with different auxiliary information. Our simulation studies show that CGAN has the capability to learn different types of normal and heavy-tailed distributions, as well as dependent structures of different time series. It also has the capability to generate conditional predictive distributions consistent with training data distributions. We also provide an in-depth discussion on the rationale behind GAN and the neural networks as hierarchical splines to establish a clear connection with existing statistical methods of distribution generation. In practice, CGAN has a wide range of applications in market risk and counterparty risk analysis: it can be applied to learn historical data and generate scenarios for the calculation of Value-at-Risk (VaR) and Expected Shortfall (ES), and it can also predict the movement of the market risk factors. We present a real data analysis including a backtesting to demonstrate that CGAN can outperform Historical Simulation (HS), a popular method in market risk analysis to calculate VaR. CGAN can also be applied in economic time series modeling and forecasting. In this regard, we have included an example of hypothetical shock analysis for economic models and the generation of potential CCAR scenarios by CGAN at the end of the paper.

Keywords: conditional generative adversarial net, market and credit risk management, neural network, time series

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Authors: Tasneem Halawani, Yamen Khateeb

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With customers’ ever-increasing expectations for fast services provisioning for all their business needs, information technology (IT) organizations, as business partners, have to cope with this demanding environment and deliver their services in the most effective and efficient way. The purpose of this paper is to identify optimization and automation opportunities for the top requested IT services in a heterogenic digital environment and widely spread customer base. In collaboration with systems, processes, and subject matter experts (SMEs), the processes in scope were approached by analyzing four-year related historical data, identifying and surveying stakeholders, modeling the as-is processes, and studying systems integration/automation capabilities. This effort resulted in identifying several pain areas, including standardization, unnecessary customer and IT involvement, manual steps, systems integration, and performance measurement. These pain areas were addressed by standardizing the top five requested IT services, eliminating/automating 43 steps, and utilizing a single platform for end-to-end process execution. In conclusion, the optimization of IT service request processes in a heterogenic digital environment and widely spread customer base is challenging, yet achievable without compromising the service quality and customers’ added value. Further studies can focus on measuring the value of the eliminated/automated process steps to quantify the enhancement impact. Moreover, a similar approach can be utilized to optimize other IT service requests, with a focus on business criticality.

Keywords: automation, customer value, heterogenic, integration, IT services, optimization, processes

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Authors: Penrug Pengsombut, Worawut Hamarn, Teerawuth Suwannasri, Kittiphong Songrukkiat, Kanatip Ratanachoo

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PTT Public Company Limited or simply PTT has played an important role in strengthening national energy security of the Kingdom of Thailand by transporting natural gas to customers in power, industrial and commercial sectors since 1981. PTT has been constructing and operating natural gas pipeline system of over 4,500-km network length both onshore and offshore laid through different area classifications i.e., marine, forest, agriculture, rural, urban, and city areas. During project development phase, an Environmental Impact Assessment (EIA) is conducted and submitted to the Office of Natural Resources and Environmental Policy and Planning (ONEP) for approval before project construction commencement. Knowledge and experiences gained and revealed from EIA in the past projects definitely are developed to further advance EIA study process for newly 5th Transmission Natural Gas Pipeline Project (5TP) with approximately 415 kilometers length. The preferred pipeline route is selected and justified by SMARTi map, an advance digital one-map platform with consists of multiple layers geographic and environmental information. Sensitive area impact focus (SAIF) is a practicable impact assessment methodology which appropriate for a particular long distance infrastructure project such as 5TP. An environmental modeling simulation is adopted into SAIF methodology for impact quantified in all sensitive areas whereas other area along pipeline right-of-ways is typically assessed as an impact representative. Resulting time and cost deduction is beneficial to project for early start.

Keywords: environmental impact assessment, EIA, natural gas pipeline, sensitive area impact focus, SAIF

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Authors: Sunyoung Park

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Context: Talent management is a strategic approach that has received considerable attention in recent years to improve employee competency and organizational performance in many organizations. The implementation of talent management involves identifying objectives and positions within the organization, developing a pool of high-potential employees, and establishing appropriate HR functions to promote high employee and organizational performance. This study aims to investigate the relationship between talent management, HR functions, employee competency, and organizational performance in the South Korean context. Research Aim: The main objective of this study is to investigate the structural relationships among talent management, human resources (HR) functions, employee competency, and organizational performance. Methodology: To achieve the research aim, this study used a quantitative research method. Specifically, a total of 1,478 responses were analyzed using structural equation modeling based on data obtained from the Human Capital Corporate Panel (HCCP) survey in South Korea. Findings: The study revealed that talent management has a positive influence on HR functions and employee competency. Additionally, HR functions directly affect employee competency and organizational performance. Employee competency was found to be related to organizational performance. Moreover, talent management and HR functions indirectly affect organizational performance through employee competency. Theoretical Importance: This study provides empirical evidence of the relationship between talent management, HR functions, employee competency, and organizational performance in the South Korean context. The findings suggest that organizations should focus on developing appropriate talent management and HR functions to improve employee competency, which, in turn, will lead to better organizational performance. Moreover, the study contributes to the existing literature by emphasizing the importance of the relationship between talent management and HR functions in improving organizational performance.

Keywords: employee competency, HR functions, organizational performance, talent management

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Authors: Emery A. Coppola Jr., Suna Cinar, Ferenc Szidarovszky

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Over-pumping of groundwater resources is a serious problem world-wide. In addition to depleting this valuable resource, hydraulically connected sensitive ecological resources like wetlands and surface water bodies are often impacted and even destroyed by over-pumping. Effectively managing groundwater in a way that satisfy human demand while preserving natural resources is a daunting challenge that will only worsen with growing human populations and climate change. As presented in this paper, a numerical flow model developed for a hypothetical but realistic groundwater/surface water system was combined with formal optimization. Response coefficients were used in an optimization management model to maximize groundwater pumping in a complex, multi-layered aquifer system while protecting against groundwater over-draft, streamflow depletion, and wetland impacts. Pumping optimization was performed for different constraint sets that reflect different resource protection preferences, yielding significantly different optimal pumping solutions. A sensitivity analysis on the optimal solutions was performed on select response coefficients to identify differences between wet and dry periods. Stochastic optimization was also performed, where uncertainty associated with changing irrigation demand due to changing weather conditions are accounted for. One of the strengths of this optimization approach is that it can efficiently and accurately identify superior management strategies that minimize risk and adverse environmental impacts associated with groundwater pumping under different hydrologic conditions.

Keywords: numerical groundwater flow modeling, water management optimization, groundwater overdraft, streamflow depletion

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Authors: Tsetsegmaa A., Bayarsuren B., Altantsetseg Ts.

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To make the best decision on reducing harmful emissions from buses, we need to have a clear understanding of the current state of their actual emissions. The emissions from city buses running on high sulfur fuel, particularly particulate matter (PM) and nitrogen oxides (NOx) from the exhaust gases of conventional diesel engines, have been studied and measured with and without diesel particulate filter (DPF) in Ulaanbaatar city. The study was conducted by using the PEMS (Portable Emissions Measurement System) and gravimetric method in real traffic conditions. The obtained data were used to determine the actual emission rates and to evaluate the effectiveness of the selected particulate filters. Actual road and daily PM emissions from city buses were determined during the warm and cold seasons. A bus with an average daily mileage of 242 km was found to emit 166.155 g of PM into the city's atmosphere on average per day, with 141.3 g in summer and 175.8 g in winter. The actual PM of the city bus is 0.6866 g/km. The concentration of NOx in the exhaust gas averages 1410.94 ppm. The use of DPF reduced the exhaust gas opacity of 24 buses by an average of 97% and filtered a total of 340.4 kg of soot from these buses over a period of six months. Retrofitting an old conventional diesel engine with cassette-type silicon carbide (SiC) DPF, despite the laboriousness of cleaning, can significantly reduce particulate matter emissions. Innovation: First comprehensive road PM and NOx emission dataset and actual road emissions from public buses have been identified. PM and NOx mathematical model equations have been estimated as a function of the bus technical speed and engine revolution with and without DPF.

Keywords: conventional diesel, silicon carbide, real-time onboard measurements, particulate matter, diesel retrofit, fuel sulphur

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Authors: M. Ibrahim Ali, M. El Dawi, M. A. Mohamed Ali

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In this study, the use of magnetic gradient survey, and the geoelectrical ground methods used together to explore archaeological features in Nuri’s pyramids area. Research methods used and the procedures and methodologies have taken full right during the study. The magnetic survey method was used to search for archaeological features using (Geoscan Fluxgate Gradiometer (FM36)). The study area was divided into a number of squares (networks) exactly equal (20 * 20 meters). These squares were collected at the end of the study to give a major network for each region. Networks also divided to take the sample using nets typically equal to (0.25 * 0.50 meter), in order to give a more specific archaeological features with some small bipolar anomalies that caused by buildings built from fired bricks. This definition is important to monitor many of the archaeological features such as rooms and others. This main network gives us an integrated map displayed for easy presentation, and it also allows for all the operations required using (Geoscan Geoplot software). The parallel traverse is the main way to take readings of the magnetic survey, to get out the high-quality data. The study area is very rich in old buildings that vary from small to very large. According to the proportion of the sand dunes and the loose soil, most of these buildings are not visible from the surface. Because of the proportion of the sandy dry soil, there is no connection between the ground surface and the electrodes. We tried to get electrical readings by adding salty water to the soil, but, unfortunately, we failed to confirm the magnetic readings with electrical readings as previously planned.

Keywords: archaeological features, independent grids, magnetic gradient, Nuri pyramid

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Authors: Umesh Kumar Sinha, Y. K. Nayak, N. Kumar, Swapnil Saurav, Monika Kashyap

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The authors investigate the effect of system and operating parameters on the performance of high temperature solar concentrator for power generation. The effects of system and operating parameters were investigated using the developed mathematical expressions for collector efficiency, heat removal factor, fluid outlet temperature and power, etc. The results were simulated using C++program. The simulated results were plotted for investigation like effect of thermal loss parameter and radiative loss parameters on the collector efficiency, heat removal factor, fluid outlet temperature, rise of temperature and effect of mass flow rate of the fluid outlet temperature. In connection with the power generation, plots were drawn for the effect of (TM–TAMB) on the variation of concentration efficiency, concentrator irradiance on PM/PMN, evaporation temperature on thermal to electric power efficiency (Conversion efficiency) of the plant and overall efficiency of solar power plant.

Keywords: parabolic trough solar collector, radiative and thermal loss parameters, collector efficiency, heat removal factor, fluid outlet and inlet temperatures, rise of temperature, mass flow rate, conversion efficiency, concentrator irradiance

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Authors: Pratibha, Jyoti Kori

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Particles in industry, harvesting, coal mines, etc. may not necessarily be spherical in shape. In general, it is difficult to find perfectly spherical particle. The prediction of movement and deposition of non spherical particle in distinct airway generation is much more difficult as compared to spherical particles. Moreover, there is extensive inflexibility in deposition between ducts of a particular generation and inside every alveolar duct since particle concentrations can be much bigger than the mean acinar concentration. Consequently, a large number of particles fail to be exhaled during expiration. This study presents a mathematical model for the movement and deposition of those non-spherical particles by using particle aspect ratio and shape factor. We analyse the pulsatile behavior underneath sinusoidal wall oscillation due to periodic breathing condition through a non-Darcian porous medium or inside pulmonary region. Since the fluid is viscous and Newtonian, the generalized Navier-Stokes equation in two-dimensional coordinate system (r, z) is used with boundary-layer theory. Results are obtained for various values of Reynolds number, Womersley number, Forchsheimer number, particle aspect ratio and shape factor. Numerical computation is done by using finite difference scheme for very fine mesh in MATLAB. It is found that the overall air velocity is significantly increased by changes in aerodynamic diameter, aspect ratio, alveoli size, Reynolds number and the pulse rate; while velocity is decreased by increasing Forchheimer number.

Keywords: deposition, interstitial lung diseases, non-Darcian medium, numerical simulation, shape factor

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Authors: Dorit Olenik-Shemesh, Tali Heiman

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The rapid increase in the massive use of the internet in recent yearshas led to an increase in the prevalence of a phenomenon called 'Problematic Internet use' (PIU), an emerging, growing health problem, especially during adolescents, that poses a challenge for mental health research and practitioners. Problematic Internet use (PIU) is defined as an excessive overuse of the internet, including an inability to control time spent on the internet, cognitivepreoccupation with the Internet, and continued use in spite of the adverse consequences, which may lead to psychological, social, and academic difficulties in one's life and daily functioning. However, little is known about the nature of the nexusbetween PIU and subjective well-being among adolescents. The main purpose of the current study was to explore in depth the network of connections between PIU, sense of well-being, and fourpersonal-emotional factors (resilience, self-control, depressive mood, and loneliness) that may mediate these relationships. A total sample of 433 adolescents, 214 (49.4%) girls and 219 (50.6%) boys between the ages of 12–17 (mean = 14.9, SD = 2.16), completed self-reportquestionnaires relating to the study variables. In line with the hypothesis, analysis of a Structural Equation modeling (SEM) revealed the main following results: high levels of PIU predicted low levels of well-being among adolescents. In addition, low levels of resilience and high levels of depressivemood (together), as well as low levels of self control and high levels of depressivemood (together), as well as low levels of resilience and high levels of loneliness, mediated the relationships between PIU and well-being. In general, girls were found to be higher in PIU and inresilience than boys. The study results revealed specific implications for developing intervention programs for adolescents in the context of PIU; aiming at more balanced adjusted use of the Internet along withpreventingthe decrease in well being.

Keywords: probelmatic inetrent Use, well-being, adolescents, SEM model

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Authors: Lizhi Ma, Dan Liu

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Pipeline parallelism has been widely used to accelerate distributed deep learning to alleviate GPU memory bottlenecks and to ensure that models can be trained and deployed smoothly under limited graphics memory conditions. However, in highly heterogeneous distributed clusters, traditional model partitioning methods are not able to achieve load balancing. The overlap of communication and computation is also a big challenge. In this paper, HePipe is proposed, an efficient pipeline parallel training method for highly heterogeneous clusters. According to the characteristics of the neural network model pipeline training task, oriented to the 2-level heterogeneous cluster computing topology, a training method based on the 2-level stage division of neural network modeling and partitioning is designed to improve the parallelism. Additionally, a multi-forward 1F1B scheduling strategy is designed to accelerate the training time of each stage by executing the computation units in advance to maximize the overlap between the forward propagation communication and backward propagation computation. Finally, a dynamic recomputation strategy based on task memory requirement prediction is proposed to improve the fitness ratio of task and memory, which improves the throughput of the cluster and solves the memory shortfall problem caused by memory differences in heterogeneous clusters. The empirical results show that HePipe improves the training speed by 1.6×−2.2× over the existing asynchronous pipeline baselines.

Keywords: pipeline parallelism, heterogeneous cluster, model training, 2-level stage partitioning

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Authors: Horng-Ji Lai

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The intuitive design features and friendly interface of smartphone attract older adults. In Taiwan, many senior education institutes offer smartphone training courses for older adult learners who are interested in learning this innovative technology. It is expected that the training courses can help them to enjoy the benefits of using smartphone and increase their life satisfaction. Therefore, it is important to investigate the factors that influence older adults’ behavior of using smartphone. The purpose of the research was to develop and test a research model that investigates the factors (self-efficacy, social connection, the need to seek health information, and the need to seek financial information) affecting older adult learners’ Internet behaviour and their life satisfaction with use of smartphone. Also, this research sought to identify the relationship between the proposed variables. Survey method was used to collect research data. A Structural Equation Modeling was performed using Partial Least Squares (PLS) regression for data exploration and model estimation. The participants were 394 older adult learners from smartphone training courses in active aging learning centers located in central Taiwan. The research results revealed that self-efficacy significantly affected older adult learner’ social connection, the need to seek health information, and the need to seek financial information. The construct of social connection yielded a positive influence in respondents’ life satisfaction. The implications of these results for practice and future research are also discussed.

Keywords: older adults, smartphone, internet behaviour, life satisfaction

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Authors: Vemula Amalakrishna, S. Pushpavanam

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Change and motion characterize and persistently reshape the world around us, on scales from molecular to global. The subtle interplay between change (Reaction) and motion (Diffusion) gives rise to an astonishing intricate spatial or temporal pattern. These pattern formation in nature has been intellectually appealing for many scientists since antiquity. Periodic precipitation patterns, also known as Liesegang patterns (LP), are one of the stimulating examples of such self-assembling reaction-diffusion (RD) systems. LP formation has a great potential in micro and nanotechnology. So far, the research on LPs has been concentrated mostly on how these patterns are forming, retrieving information to build a universal mathematical model for them. Researchers have developed various theoretical models to comprehensively construct the geometrical diversity of LPs. To the best of our knowledge, simulation studies of LPs assume an arbitrary value of RD parameters to explain experimental observation qualitatively. In this work, existing models were studied to understand the mechanism behind this phenomenon and challenges pertaining to models were understood and explained. These models are not computationally effective due to the presence of discontinuous precipitation rate in RD equations. To overcome the computational challenges, smoothened Heaviside functions have been introduced, which downsizes the computational time as well. Experiments were performed using a conventional LP system (AgNO₃-K₂Cr₂O₇) to understand the effects of different gels and temperatures on formed LPs. The model is extended for real parameter values to compare the simulated results with experimental data for both 1-D (Cartesian test tubes) and 2-D(cylindrical and Petri dish).

Keywords: reaction-diffusion, spatio-temporal patterns, nucleation and growth, supersaturation

Procedia PDF Downloads 152

Authors: M. A. Fouad, M. A. Badr, Z. S. Abd El-Rehim, Taher Halawa, Mahmoud Bayoumi, M. M. Ibrahim

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Renewable energy-based micro-grids are presently attracting significant consideration. The smart grid system is presently considered a reliable solution for the expected deficiency in the power required from future power systems. The purpose of this study is to determine the optimal components sizes of a micro-grid, investigating technical and economic performance with the environmental impacts. The micro grid load is divided into two small factories with electricity, both on-grid and off-grid modes are considered. The micro-grid includes photovoltaic cells, back-up diesel generator wind turbines, and battery bank. The estimated load pattern is 76 kW peak. The system is modeled and simulated by MATLAB/Simulink tool to identify the technical issues based on renewable power generation units. To evaluate system economy, two criteria are used: the net present cost and the cost of generated electricity. The most feasible system components for the selected application are obtained, based on required parameters, using HOMER simulation package. The results showed that a Wind/Photovoltaic (W/PV) on-grid system is more economical than a Wind/Photovoltaic/Diesel/Battery (W/PV/D/B) off-grid system as the cost of generated electricity (COE) is 0.266 $/kWh and 0.316 $/kWh, respectively. Considering the cost of carbon dioxide emissions, the off-grid will be competitive to the on-grid system as COE is found to be (0.256 $/kWh, 0.266 $/kWh), for on and off grid systems.

Keywords: renewable energy sources, micro-grid system, modeling and simulation, on/off grid system, environmental impacts

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Authors: Alexander Cho, Harsho Sanyal, Joseph Cataldo

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A quantitative analysis of the different variables on both the South and North green roofs of the Jacob K. Javits Convention Center was taken to find mathematical relationships between net radiation and evapotranspiration (ET), average outside temperature, and the lysimeter weight. Groups of datasets were analyzed, and the relationships were plotted on linear and semi-log graphs to find consistent relationships. Antecedent conditions for each rainstorm were also recorded and plotted against the volumetric water difference within the lysimeter. The first relation was the inverse parabolic relationship between the lysimeter weight and the net radiation and ET. The peaks and valleys of the lysimeter weight corresponded to valleys and peaks in the net radiation and ET respectively, with the 8/22/15 and 1/22/16 datasets showing this trend. The U-shaped and inverse U-shaped plots of the two variables coincided, indicating an inverse relationship between the two variables. Cross variable relationships were examined through graphs with lysimeter weight as the dependent variable on the y-axis. 10 out of 16 of the plots of lysimeter weight vs. outside temperature plots had R² values > 0.9. Antecedent conditions were also recorded for rainstorms, categorized by the amount of precipitation accumulating during the storm. Plotted against the change in the volumetric water weight difference within the lysimeter, a logarithmic regression was found with large R² values. The datasets were compared using the Mann Whitney U-test to see if the datasets were statistically different, using a significance level of 5%; all datasets compared showed a U test statistic value, proving the null hypothesis of the datasets being different from being true.

Keywords: green roof, green infrastructure, Javits Center, evapotranspiration, net radiation, lysimeter

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Authors: Jatupon Em-Udom, Nirand Pisutha-Arnond

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The phase-field-crystal, PFC, approach is a density-functional-type material model with an atomic resolution on a diffusive timescale. Spatially, the model incorporates periodic nature of crystal lattices and can naturally exhibit elasticity, plasticity and crystal defects such as grain boundaries and dislocations. Temporally, the model operates on a diffusive timescale which bypasses the need to resolve prohibitively small atomic-vibration time steps. The PFC model has been used to study many material phenomena such as grain growth, elastic and plastic deformations and solid-solid phase transformations. In this study, the pressure-controlled dynamic equation for the PFC model was developed to simulate a single-component system under externally applied pressure; these coupled equations are important for studies of deformable systems such as those under constant pressure. The formulation is based on the non-equilibrium thermodynamics and the thermodynamics of crystalline solids. To obtain the equations, the entropy variation around the equilibrium point was derived. Then the resulting driving forces and flux around the equilibrium were obtained and rewritten as conventional thermodynamic quantities. These dynamics equations are different from the recently-proposed equations; the equations in this study should provide more rigorous descriptions of the system dynamics under externally applied pressure.

Keywords: driving forces and flux, evolution equation, non equilibrium thermodynamics, Onsager’s reciprocal relation, phase field crystal model, thermodynamics of single-component solid

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Authors: M. O. Adeniyi, R. T. Akinnubi

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The parameterization of turbulent heat fluxes is needed for modeling land-atmosphere interactions in Global Climate Models (GCMs). However, current GCMs still have difficulties with producing reliable turbulent heat fluxes for humid tropical regions, which may be due to inadequate parameterization of the roughness lengths for momentum (z0m) and heat (z0h) transfer. These roughness lengths are usually expressed in term of excess resistance factor (κB^(-1)), and this factor is used to account for different resistances for momentum and heat transfers. In this paper, a more appropriate excess resistance factor (〖 κB〗^(-1)) suitable for low wind speed condition was developed and incorporated into the aerodynamic resistance approach (ARA) in the GCMs. Also, the performance of various standard GCMs κB^(-1) schemes developed for high wind speed conditions were assessed. Based on the in-situ surface heat fluxes and profile measurements of wind speed and temperature from Nigeria Micrometeorological Experimental site (NIMEX), new κB^(-1) was derived through application of the Monin–Obukhov similarity theory and Brutsaert theoretical model for heat transfer. Turbulent flux parameterizations with this new formula provides better estimates of heat fluxes when compared with others estimated using existing GCMs κB^(-1) schemes. The derived κB^(-1) MBE and RMSE in the parameterized QH ranged from -1.15 to – 5.10 Wm-2 and 10.01 to 23.47 Wm-2, while that of QE ranged from - 8.02 to 6.11 Wm-2 and 14.01 to 18.11 Wm-2 respectively. The derived 〖 κB〗^(-1) gave better estimates of QH than QE during daytime. The derived 〖 κB〗^(-1)=6.66〖 Re〗_*^0.02-5.47, where Re_* is the Reynolds number. The derived κB^(-1) scheme which corrects a well documented large overestimation of turbulent heat fluxes is therefore, recommended for most regional models within the tropic where low wind speed is prevalent.

Keywords: humid, tropic, excess resistance factor, overestimation, turbulent heat fluxes

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Authors: Rafael Alvarenga, Hubert Herbaux, Laurent Linguet

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The uncertainty concerning the power production of intermittent renewable energy is one of the main barriers to the integration of such assets into the power grid. Efforts have thus been made to develop methods to quantify this uncertainty, allowing producers to ensure more reliable and profitable engagements related to their future power delivery. Even though a diversity of probabilistic approaches was proposed in the literature giving promising results, the added value of adopting such methods for scheduling intermittent power plants is still unclear. In this study, the profits obtained by a decision-making model used to optimally schedule an existing PV power plant connected to batteries are compared when the model is fed with deterministic and probabilistic forecasts generated with two of the most recent methods proposed in the literature. Moreover, deterministic forecasts with different accuracy levels were used in the experiments, testing the utility and the capability of probabilistic methods of modeling the progressively increasing uncertainty. Even though probabilistic approaches are unquestionably developed in the recent literature, the results obtained through a study case show that deterministic forecasts still provide the best performance if accurate, ensuring a gain of 14% on final profits compared to the average performance of probabilistic models conditioned to the same forecasts. When the accuracy of deterministic forecasts progressively decreases, probabilistic approaches start to become competitive options until they completely outperform deterministic forecasts when these are very inaccurate, generating 73% more profits in the case considered compared to the deterministic approach.

Keywords: PV power forecasting, uncertainty quantification, optimal scheduling, power systems

Procedia PDF Downloads 87