Search results for: urban 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: Lopita Pal, Suresh V. Madha

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Wetlands are areas of marsh, fen, peat land or water, whether natural or artificial, permanent or temporary, with water that is static or flowing, fresh, brackish or salt, including areas of marine water the depth of which at low tide does not exceed six metres. The rapidly expanding human population, large scale changes in land use/land cover, burgeoning development projects and improper use of watersheds all has caused a substantial decline of wetland resources in the world. Major degradations have been impacted from agricultural, industrial and urban developments leading to various types of pollutions and hydrological perturbations. Regular fishing activities and unsustainable grazing of animals are degrading the wetlands in a slow pace. The paper focuses on the spatio-temporal change detection of the area of the water body and the main cause of this depletion. The total area under study (22°19’87’’ N, 88°20’23’’ E) is a wetland region in West Bengal of 213 sq.km. The procedure used is the Normalized Difference Water Index (NDWI) from multi-spectral imagery and Landsat to detect the presence of surface water, and the datasets have been compared of the years 2016, 2006 and 1996. The result shows a sharp decline in the area of water body due to a rapid increase in the agricultural practices and the growing urbanization.

Keywords: spatio-temporal change, NDWI, urbanization, wetland

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Authors: Hlabishi Peter Ntloana

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This paper aims to present the effectiveness of the Spatial Planning and Land Use Management Act, 2013, in addressing key spatial challenges in Fetakgomo Tubatse Local Municipality, mainly focusing on Apel nodal point. Spatial Planning and Land Use Management Act, 2013, popularly known as SPLUMA, aimed at addressing emerging and existing spatial planning and land use management challenges in South Africa. There are critical key spatial challenges that are continuously encountered in Apel Nodal Point, which include dispersed rural settlement mainly in a communal settlement. The spatial patterns and rural settlements development patterns are a challenge, and such results in uncoordinated human settlements. The objective of this research paper is to analyze the spatial planning of Apel nodal points and determine the effectiveness of the SPLUMA policy. Key Informant interviews were conducted with 20 participants, and also the municipal Spatial Development Framework was considered to explore more challenges and proposed recommendations. The results divulged that there is a huge gap in addressing spatial planning, mainly in rural areas, and correlation with the findings of the Municipal Spatial Development framework. In conclusion, spatial planning remains a critical dilemma in most rural settlements, and there must be programmes and strategies to balance the effectiveness of spatial planning in urban and rural settlements.

Keywords: land use management, rural settlement, spatial development framework, spatial planning

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Authors: Anđelka Stojanović, Ivan Mihajlović, Ivica Nikolić

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In the past years, due to the financial crisis and the tightening of conditions on the labor market, young people are facing great challenges in achieving financial independence and finding their place in society. Higher unemployment rates, poorer living conditions, separation from the labor market, and longer school-to-work transitions particularly affect rural youth and make significant differences between youth groups in rural and urban areas. Improving employability skills and development of instruments for further learning among young people “Not in Education, Employment, or Training” (NEET) should not be only the concerns of these people, already adequately be directed and supported by the institutions. According to the World Bank data, the share of youth not in education, employment or training (NEET), in the European Union in the past few years decreases but still shows a significant share in the total percentage of the youth population. In 2017 rate was 10.96% while in 2018 that value was 10.38%. When observing individual countries in Europe, especially those with lower incomes, this rate is much higher. It was concluded that this topic was not sufficiently elaborated and presented in the social and scientific environment. Therefore, the aim of this paper is to identify and systematize the problems of school-to-work transition among young NEETs living in rural areas as well as the initiatives for addressing their problems.

Keywords: NEET youth, risks and initiatives, rural youth, school-to-work transition

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Authors: K. P. Ganesh, T. Gomathi, L. Arul Pragasan

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Degradation of lake water quality is one of the serious environmental threats for the last few decades, particularly, the lakes situated in and around urban and industrial areas. The present study aimed to analyze the physicochemical and biological parameters, and metal elements to determine the water quality of Krishnampathi, Ukkadam, Kurichi, Sulur and Singanallur Lakes. Of the 23 physicochemical parameters analyzed in the five lakes, except TDS, Chloride and Total hardness values all the 20 parameters were found within the prescribed limit as recommended by World Health Organization (WHO) and Bureau of Indian Standards (BIS). In case of biological parameter, both Total Coliform and Fecal Coliform bacteria (Escherichia coli) were identified. This indicates the contamination of lakes by fecal matter, and warns of potential of disease causing by viruses, bacteria and other organisms. Among the twelve metal elements (Al, Cr, Mn, Fe, Ni, Cu, Zn, As, Se, Mo, Cd and Pb) determined by inductively coupled plasma-mass spectroscopy, except Cd (for all lakes), and Pb (for Ukkadam, Kurichi, Sulur & Singanallur), all the elements were found above the prescribed limits of BIS. The results of the present study revealed that all the five major lakes of Coimbatore were contaminated. It is recommended that proper implementation of the new wetland waste management system and monitoring of water quality be of the urgent need to sustain the water bodies for future generations.

Keywords: heavy metals, inductively coupled plasma-mass spectroscopy, physicochemical and biological parameters, water quality

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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: Emmanuel Okechukwu Nwafor, Folake Olubunmi Akintayo, Denis Alcides Rezende

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Decision tree models are versatile and interpretable machine learning algorithms widely used for both classification and regression tasks, which can be related to cities, whether physical or digital. The aim of this research is to assess how well decision tree algorithms can predict trip purposes in Makurdi, Nigeria, while also exploring their connection to the strategic digital city initiative. The research methodology involves formalizing household demographic and trips information datasets obtained from extensive survey process. Modelling and Prediction were achieved using Python Programming Language and the evaluation metrics like R-squared and mean absolute error were used to assess the decision tree algorithm's performance. The results indicate that the model performed well, with accuracies of 84% and 68%, and low MAE values of 0.188 and 0.314, on training and validation data, respectively. This suggests the model can be relied upon for future prediction. The conclusion reiterates that This model will assist decision-makers, including urban planners, transportation engineers, government officials, and commuters, in making informed decisions on transportation planning and management within the framework of a strategic digital city. Its application will enhance the efficiency, sustainability, and overall quality of transportation services in Makurdi, Nigeria.

Keywords: decision tree algorithm, trip purpose, intelligent transport, strategic digital city, travel pattern, sustainable transport

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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: Moustafa Osman Mohammed

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This paper will explore formation of HCl aerosol at atmospheric boundary layers and encourages the uptake of environmental modeling systems (EMSs) as a practice evaluation of gaseous emissions (“framework measures”) from small and medium-sized enterprises (SMEs). The conceptual model predicts greenhouse gas emissions to ecological points beyond landfill site operations. It focuses on incorporation traditional knowledge into baseline information for both measurement data and the mathematical results, regarding parameters influence model variable inputs. The paper has simplified parameters of aerosol processes based on the more complex aerosol process computations. The simple model can be implemented to both Gaussian and Eulerian rural dispersion models. Aerosol processes considered in this study were (i) the coagulation of particles, (ii) the condensation and evaporation of organic vapors, and (iii) dry deposition. The chemical transformation of gas-phase compounds is taken into account photochemical formulation with exposure effects according to HCl concentrations as starting point of risk assessment. The discussion set out distinctly aspect of sustainability in reflection inputs, outputs, and modes of impact on the environment. Thereby, models incorporate abiotic and biotic species to broaden the scope of integration for both quantification impact and assessment risks. The later environmental obligations suggest either a recommendation or a decision of what is a legislative should be achieved for mitigation measures of landfill gas (LFG) ultimately.

Keywords: air pollution, landfill emission, environmental management, monitoring/methods and impact assessment

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Authors: A. Ribeiro, N. Pacheco, M. Soares, N. Valério, L. Nascimento, A. Silva, C. Vilarinho, J. Carvalho

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Hydrogen will play a key role in changing the current global energy paradigm, associated with the high use of fossil fuels and the release of greenhouse gases. This work intended to identify and quantify the potential of Solid Recovered Fuels (SFR) existing in Portugal and project the cost of hydrogen, produced through its steam gasification in different scenarios, associated with the size or capacity of the plant and the existence of carbon capture and storage (CCS) systems. Therefore, it was performed a techno-economic analysis simulation using an ASPEN base model, the H2A Hydrogen Production Model Version 3.2018. Regarding the production of SRF, it was possible to verify the annual production of more than 200 thousand tons of SRF in Portugal in 2019. The results of the techno-economic analysis simulations showed that in the scenarios containing a high (200,000 tons/year) and medium (40,000 tons/year) amount of SFR, the cost of hydrogen production was competitive concerning the current prices of hydrogen. The results indicate that scenarios 1 and 2, which use 200,000 tons of SRF per year, have lower hydrogen production values, 1.22 USD/kg H2 and 1.63 USD/kg H2, respectively. The cost of producing hydrogen without carbon capture and storage (CCS) systems in an average amount of SFR (40,000 tons/year) was 1.70 USD/kg H2. In turn, scenarios 5 (without CCS) and 6 (with CCS), which use only 683 tons of SFR from urban sources, have the highest costs, 6.54 USD/kg H2 and 908.97 USD/kg H2, respectively. Therefore, it was possible to conclude that there is a huge potential for the use of SRF for the production of hydrogen through steam gasification in Portugal.

Keywords: gasification, hydrogen, solid recovered fuels, techno-economic analysis, waste-to-energy

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Authors: Abubakar Samaila

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Pastoralism has been an old practice in the Sahel region of west Africa. In recent years, pastoralists in Nigeria have increasingly been migrating on seasonal transhumance southward from the neighboring countries, especially Niger Republic, in search of better grazing conditions due to mainly, climate change. This has increased pressure on farm lands which instigate farmer-herder conflicts. These conflicts occur mainly between farmers and pastoralists but also between pastoralist groups themselves. However, there has been a shift in these conflicts recently to involve traditional institutions and, in some cases, the local authorities along the borderlands. The involvement of local institutions in the conflict has created an incentive to local actors, particularly pastoralcommunity-based groups, in responding to these violent threats. As pastoralists are mobile, these conflicts became difficult to contain and, thus, spill across borders. Consequently, the conflict has now transformed into an urbanized regional conflicts that involve some major cities along the Nigeria-Niger borderlands; Sokoto, Zamfara, and Katsina on the Nigerian side andDosso, Tahoa andMaradi in Niger republic. These areas are now experiencing unprecedented growing wave of violence that have become complex and escalates into a hydra-social conflict. The aim of this research is to investigate how the fluidities of Nigeria-Niger borderland intensified armed conflicts between the local pastoral organizations and sedentary populationspreading to some urban cities along the borderlands. The paper further suggests alternative approaches towards addressing the perennial crisis in African borderlands.

Keywords: pastoralism, climate change, conflict, nigeria, niger, borderlands

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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: Azadeh Rezafar

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Iran is one of the oldest countries with traditional culture in the world. All over the history Iranians had traditional architectural designs, which were at the same time sustainable, ecological, functional and environmental consistent. These human scale architectures were built for maximum use, comfort, climate adaptation with available resources and techniques. Climate variability of the country caused developing of variety design methods. More of these methods such as windcatchers in Yazd City or Panam (Insulation) were scientific solutions at the same time. Renewable energy resources were used in these methods that featured in them. While climate and ecological issues were dominant parts of these traditional designs, aesthetic and beauty issues were not ignored. Conformity with the community’s culture caused more compact designs that the visual aesthetics of them can be seen inside of them. Different organizations of space were used for these visual aesthetic issues inside the houses as well as historical urban designs. For example dry and hot climates in central parts of the country designed with centralized organization. Most central parts of these designs functioned as a courtyard for temperate the air in the summer. This paper will give summary descriptive information about traditional Iranian architectural style by figures all around the country with different climate conditions, while focus of the paper is traditional architectural design of the central part of the country, with dry and hot climate condition. This information may be useful for contemporary architectural designs, which are designed without noticing to the vernacular condition and caused cities look like each other.

Keywords: architectural design, traditional design, Iran, sustainability

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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: Joao Garretto, R. J. Yarwood, Vamsi Borra, Frank Li

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Bluetooth Low Energy (BLE) has emerged as one of the main wireless communication technologies used in low-power electronics, such as wearables, beacons, and Internet of Things (IoT) devices. BLE’s energy efficiency characteristic, smart mobiles interoperability, and Over the Air (OTA) capabilities are essential features for ultralow-power devices, which are usually designed with size and cost constraints. Most current research regarding the power analysis of BLE devices focuses on the theoretical aspects of the advertising and scanning cycles, with most results being presented in the form of mathematical models and computer software simulations. Such computer modeling and simulations are important for the comprehension of the technology, but hardware measurement is essential for the understanding of how BLE devices behave in real operation. In addition, recent literature focuses mostly on the BLE technology, leaving possible applications and its analysis out of scope. In this paper, a coin cell battery-powered BLE Data Acquisition Device, with a 4-in-1 sensor and one accelerometer, is proposed and evaluated with respect to its Power Consumption. First, evaluations of the device in advertising mode with the sensors turned off completely, followed by the power analysis when each of the sensors is individually turned on and data is being transmitted, and concluding with the power consumption evaluation when both sensors are on and respectively broadcasting the data to a mobile phone. The results presented in this paper are real-time measurements of the electrical current consumption of the BLE device, where the energy levels that are demonstrated are matched to the BLE behavior and sensor activity.

Keywords: bluetooth low energy, power analysis, BLE advertising cycle, wireless sensor node

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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: Manavjit Singh Dhindsa, Ursula Das, Kshirasagar Naik, Marzia Zaman, Richard Purcell, Srinivas Sampalli, Abdul Mutakabbir, Chung-Horng Lung, Thambirajah Ravichandran

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These days, wildland fires, also known as forest fires, are more prevalent than ever. Wildfires have major repercussions that affect ecosystems, communities, and the environment in several ways. Wildfires lead to habitat destruction and biodiversity loss, affecting ecosystems and causing soil erosion. They also contribute to poor air quality by releasing smoke and pollutants that pose health risks, especially for individuals with respiratory conditions. Wildfires can damage infrastructure, disrupt communities, and cause economic losses. The economic impact of firefighting efforts, combined with their direct effects on forestry and agriculture, causes significant financial difficulties for the areas impacted. This research explores different forest fire spread models and presents a comprehensive review of various techniques and methodologies used in the field. A forest fire spread model is a computational or mathematical representation that is used to simulate and predict the behavior of a forest fire. By applying scientific concepts and data from empirical studies, these models attempt to capture the intricate dynamics of how a fire spreads, taking into consideration a variety of factors like weather patterns, topography, fuel types, and environmental conditions. These models assist authorities in understanding and forecasting the potential trajectory and intensity of a wildfire. Emphasizing the need for a comprehensive understanding of wildfire dynamics, this research explores the approaches, assumptions, and findings derived from various models. By using a comparison approach, a critical analysis is provided by identifying patterns, strengths, and weaknesses among these models. The purpose of the survey is to further wildfire research and management techniques. Decision-makers, researchers, and practitioners can benefit from the useful insights that are provided by synthesizing established information. Fire spread models provide insights into potential fire behavior, facilitating authorities to make informed decisions about evacuation activities, allocating resources for fire-fighting efforts, and planning for preventive actions. Wildfire spread models are also useful in post-wildfire mitigation strategies as they help in assessing the fire's severity, determining high-risk regions for post-fire dangers, and forecasting soil erosion trends. The analysis highlights the importance of customized modeling approaches for various circumstances and promotes our understanding of the way forest fires spread. Some of the known models in this field are Rothermel’s wildland fuel model, FARSITE, WRF-SFIRE, FIRETEC, FlamMap, FSPro, cellular automata model, and others. The key characteristics that these models consider include weather (includes factors such as wind speed and direction), topography (includes factors like landscape elevation), and fuel availability (includes factors like types of vegetation) among other factors. The models discussed are physics-based, data-driven, or hybrid models, also utilizing ML techniques like attention-based neural networks to enhance the performance of the model. In order to lessen the destructive effects of forest fires, this initiative aims to promote the development of more precise prediction tools and effective management techniques. The survey expands its scope to address the practical needs of numerous stakeholders. Access to enhanced early warning systems enables decision-makers to take prompt action. Emergency responders benefit from improved resource allocation strategies, strengthening the efficacy of firefighting efforts.

Keywords: artificial intelligence, deep learning, forest fire management, fire risk assessment, fire simulation, machine learning, remote sensing, wildfire modeling

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Authors: Elizabeth Spink

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The United Nations' Sustainable Development Goal 6 sets a target for safe and affordable drinking water for all. Developing country governments aiming to achieve this goal often face significant challenges when trying to service last mile customers, particularly those in peri-urban and rural areas. Expansion of water networks often requires high connection fees from households, and demand for connections may be low if there are cheaper substitute sources of water available. This research studies the effect of the availability of substitute sources of water on demand for individual water connections in Livingstone, Zambia, using an event study analysis of metering campaigns. Metering campaigns reduce the share of a household's neighbors that can provide free water to the household if their water connection becomes disconnected due to nonpayment. The results show that household payments in newly metered regions increase by 10 percentage points in the months following metering events, with a decrease in disconnections of 6 percentage points for low-income households. To isolate the effect of changes in a household's substitution possibilities, a similar analysis is conducted among households that neighbor the metered region. These results show mixed evidence of the impact of substitutes on payment behavior and disconnections. The results suggest that metering may be effective in increasing household demand for individual water connections primarily through a lower monthly cost burden for newly metered households.

Keywords: piped-water access, water demand, water utilities, water sharing

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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: Radek Richtr, Petr Paus

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The connection to the primal environment, living and growing nature is disappearing for most of the residents in urban core areas nowadays. Most of the residents perceive scattered green mass like more technical objects than sentient living organisms. The Arboretum is a type of application from the 'serious games' genre -it is a research experiment masked as a gaming environment. In used virtual and augmented reality environments, every city district is represented by central objects; Pillars created as a result of resident’s consensus. Every player can furthermore plant and grow virtual organic seeds everywhere he wants. Seeds sprout, and their form is determined by both players’ choice and nearest pillar. Every house, private rooms, and even workspace get their new living virtual avatar-connected 'residents' growing from player-planted seeds. Every room or workspace is transformed into (calming) nature scene, reflecting in some way both players and community spirit and together create a vicinity environment. The conceptual design phase of the project is crucial and allows for the identification of the fundamental problems through abstraction. The project that centers on wide community usage needs a clear and accessible interface. Simultaneously the conceptual design allows early sharing of project ideas and creating public concern. The paper discusses the current conceptual model of an Arboretum project (which is part of a whole widespread project) and its validation.

Keywords: augmented reality, conceptual design, mixed reality, social engineering

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Authors: Murat Zencirkiran, Nilufer Seyidoglu Akdeniz, Elvan Ender Altay, Zeynep Pirselimoglu Batman

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Monumental trees make an important contribution to the cultural interaction between societies. At the same time, monument trees, which are considered as symbols of some beliefs, are living beings that are transmitted from generation to generation. Mystical, folkloric and dimensional aspects of our cultural heritage and the link between the past and present, the memorial trees of the generations of the stories conveyed the story of the legends at the same time with the aesthetic features of the objects attract attention. There are many monumental trees that witness historical processes in Bursa, which is a land of very different cultures from the Prusias (BC 232-192). Within this scope, monumental trees located within the boundaries of Bursa province and their contribution to urban culture were evaluated. Monument plane trees recorded in Bursa and its districts were determined by the Ministry of Environment and Urbanization, the Governorship of Bursa, the Provincial Directorate of Environment and Urbanism, the Directorate of Protection of Natural Assets, and these trees were examined in situ. As a result of the inspections made, the monument trees living today are classified according to their species. Within the scope of the study, it was determined that there were 1001 monumental tree species in different species within the boundaries of Bursa province. 71.83% of the recorded species were Platanus species and 11.79% were Pinus species. On the other hand, the stories about the contribution of cultural landscapes to the examples of living or now-disappearing examples of Bursa history from these monumental trees have been compiled and presented in the study.

Keywords: Bursa, cultural landscape, landscape, monumental trees

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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: Maher El-Masri, Jamie Crawley, Judy Bornais, Abeer Omar

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Background: Misuse of Emergency Department (ED) for non-urgent healthcare results in unnecessary crowdedness that can result in long ED waits and delays in treatment, diversion of ambulances to other hospitals, poor health outcomes for patients, and increased risk of death Objectives: The main purpose of this study was to explore the independent predictors of non-urgent ED visits in Erie St. Clair LHIN. Secondary purposes of the study include comparison of the rates of non-urgent ED visits between urban and rural hospitals Design: A secondary analysis of archived population-based data on 597,373 ED visits in southwestern Ontario Results The results suggest that older (OR = .992; 95% CI .992 – .993) and female patients (OR = .940; 95% CI .929 - .950) were less likely to visit ED for non-urgent causes. Non-urgent ED visits during the winter, spring, and fall were 13%, 5.8%, and 7.5%, respectively, lesser than they were during the summer time. The data further suggest that non-urgent visits were 19.6% and 21.3% less likely to occur in evening and overnight shifts compared to the day shift. Non-urgent visits were 2.76 times more likely to present to small community hospitals than large community hospitals. Health care providers were 1.92 times more likely to refer patients with non-urgent health problem to the ED than the decision taken by patients, family member or caretakers. Conclusion: In conclusion, our study highlights a number of important factors that are associated with inappropriate use of ED visits for non-urgent health problems. Knowledge of these factors could be used to address the issue of unnecessary ED crowdedness.

Keywords: emergency department, non-urgent visits, predictors, logistic regression

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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

Abstract:

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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