Search results for: atmospheric transport modeling
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 6070

Search results for: atmospheric transport modeling

3970 Insulation, Sustainable Construction, and Architectural Design to Reduce Energy Consumption in Sustainable Buildings

Authors: Gholamreza Namavar, Ali Bayati

Abstract:

Nowadays according to increasing the population all around the world, consuming of fossil fuels increased dramatically. Many believe that most of the atmospheric pollution comes by using fossil fuels. The process of natural sources entering cities show one of the large challenges in consumption sources management. Nowadays, everyone considered about the consumption of fossil fuels and also reduction of consumption civil energy in megacities that play a key role in solving serious problems such as air pollution, producing greenhouse gasses, global warming and damage ozone layer. In construction industry we should use the materials with the lowest need to energy for making and carrying them, and also the materials which need the lowest energy and expenses to recycling. In this way, the kind of usage material, the way of processing, regional materials and the adaption with environment is critical. Otherwise, the isolation should be use and mention in long term. Accordingly, in this article we investigates the new ways in order to reduce environmental pollution and save more energy by using materials that are not harmful to the environment, fully insulated materials in buildings, sustainable and diversified buildings, suitable urban design and using solar energy more efficiently in order to reduce energy consumption.

Keywords: architectural design, insulation, sustainable construction, reducing energy consumption

Procedia PDF Downloads 241
3969 An Optimization Modelling to Evaluate Flights Scheduling at Tourist Airports

Authors: Dimitrios J. Dimitriou

Abstract:

Airport’s serving a tourist destination are an essential counterpart of the tourist demand supply chain, and their productivity is related to the region’s attractiveness and is enhanced by the air transport business. In this paper, the evaluation framework of the scheduled flights between two tourist airports is taken into consideration. By adopting a systemic approach, the arrivals from an airport that its connectivity heavily depended on the departures of another major airport are reviewed. The methodology framework, based on inventory control theory and the numerical example, promotes the use of the modelling formulation. The results would be essential for comparison and exercising to other similar cases.

Keywords: airport connectivity, inventory control, optimization, optimum allocation

Procedia PDF Downloads 322
3968 A Sentence-to-Sentence Relation Network for Recognizing Textual Entailment

Authors: Isaac K. E. Ampomah, Seong-Bae Park, Sang-Jo Lee

Abstract:

Over the past decade, there have been promising developments in Natural Language Processing (NLP) with several investigations of approaches focusing on Recognizing Textual Entailment (RTE). These models include models based on lexical similarities, models based on formal reasoning, and most recently deep neural models. In this paper, we present a sentence encoding model that exploits the sentence-to-sentence relation information for RTE. In terms of sentence modeling, Convolutional neural network (CNN) and recurrent neural networks (RNNs) adopt different approaches. RNNs are known to be well suited for sequence modeling, whilst CNN is suited for the extraction of n-gram features through the filters and can learn ranges of relations via the pooling mechanism. We combine the strength of RNN and CNN as stated above to present a unified model for the RTE task. Our model basically combines relation vectors computed from the phrasal representation of each sentence and final encoded sentence representations. Firstly, we pass each sentence through a convolutional layer to extract a sequence of higher-level phrase representation for each sentence from which the first relation vector is computed. Secondly, the phrasal representation of each sentence from the convolutional layer is fed into a Bidirectional Long Short Term Memory (Bi-LSTM) to obtain the final sentence representations from which a second relation vector is computed. The relations vectors are combined and then used in then used in the same fashion as attention mechanism over the Bi-LSTM outputs to yield the final sentence representations for the classification. Experiment on the Stanford Natural Language Inference (SNLI) corpus suggests that this is a promising technique for RTE.

Keywords: deep neural models, natural language inference, recognizing textual entailment (RTE), sentence-to-sentence relation

Procedia PDF Downloads 336
3967 Architectural Design, Low Energy, and Isolation Materials to Have Sustainable Buildings in Iran

Authors: Mohammadreza Azarnoush, Ali Bayati, Jamileh Azarnoush

Abstract:

Nowadays according to increasing the population all around the world, consuming of fossil fuels increased dramatically. Many believe that most of the atmospheric pollution comes by using fossil fuels. The process of natural sources entering cities shows one of the large challenges in consumption sources management. Nowadays, everyone considers the consumption of fossil fuels and also reduction of consumption civil energy in megacities as playing a key role in solving serious problems such as air pollution, producing greenhouse gasses, global warming, and damage ozone layer. In the construction industry, we should use the materials with the lowest need to energy for making and carrying them, and also the materials which need the lowest energy and expenses to recycling. In this way, the kind of usage material, the way of processing, regional materials, and the adoption to the environment is critical. Otherwise, the isolation should be use and mention in the long term. Accordingly, in this article, we investigate the new ways in order to reduce environmental pollution and save more energy by using materials that are not harmful to the environment, fully insulated materials in buildings, sustainable and diversified buildings, suitable urban design and using solar energy more efficiently in order to reduce energy consumption.

Keywords: building design, construction masonry, insulation, sustainable construction

Procedia PDF Downloads 399
3966 Homeless Population Modeling and Trend Prediction Through Identifying Key Factors and Machine Learning

Authors: Shayla He

Abstract:

Background and Purpose: According to Chamie (2017), it’s estimated that no less than 150 million people, or about 2 percent of the world’s population, are homeless. The homeless population in the United States has grown rapidly in the past four decades. In New York City, the sheltered homeless population has increased from 12,830 in 1983 to 62,679 in 2020. Knowing the trend on the homeless population is crucial at helping the states and the cities make affordable housing plans, and other community service plans ahead of time to better prepare for the situation. This study utilized the data from New York City, examined the key factors associated with the homelessness, and developed systematic modeling to predict homeless populations of the future. Using the best model developed, named HP-RNN, an analysis on the homeless population change during the months of 2020 and 2021, which were impacted by the COVID-19 pandemic, was conducted. Moreover, HP-RNN was tested on the data from Seattle. Methods: The methodology involves four phases in developing robust prediction methods. Phase 1 gathered and analyzed raw data of homeless population and demographic conditions from five urban centers. Phase 2 identified the key factors that contribute to the rate of homelessness. In Phase 3, three models were built using Linear Regression, Random Forest, and Recurrent Neural Network (RNN), respectively, to predict the future trend of society's homeless population. Each model was trained and tuned based on the dataset from New York City for its accuracy measured by Mean Squared Error (MSE). In Phase 4, the final phase, the best model from Phase 3 was evaluated using the data from Seattle that was not part of the model training and tuning process in Phase 3. Results: Compared to the Linear Regression based model used by HUD et al (2019), HP-RNN significantly improved the prediction metrics of Coefficient of Determination (R2) from -11.73 to 0.88 and MSE by 99%. HP-RNN was then validated on the data from Seattle, WA, which showed a peak %error of 14.5% between the actual and the predicted count. Finally, the modeling results were collected to predict the trend during the COVID-19 pandemic. It shows a good correlation between the actual and the predicted homeless population, with the peak %error less than 8.6%. Conclusions and Implications: This work is the first work to apply RNN to model the time series of the homeless related data. The Model shows a close correlation between the actual and the predicted homeless population. There are two major implications of this result. First, the model can be used to predict the homeless population for the next several years, and the prediction can help the states and the cities plan ahead on affordable housing allocation and other community service to better prepare for the future. Moreover, this prediction can serve as a reference to policy makers and legislators as they seek to make changes that may impact the factors closely associated with the future homeless population trend.

Keywords: homeless, prediction, model, RNN

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3965 Nano-Pesticides: Recent Emerging Tool for Sustainable Agricultural Practices

Authors: Ekta, G. K. Darbha

Abstract:

Nanotechnology offers the potential of simultaneously increasing efficiency as compared to their bulk material as well as reducing harmful environmental impacts of pesticides in field of agriculture. The term nanopesticide covers different pesticides that are cumulative of several surfactants, polymers, metal ions, etc. of nanometer size ranges from 1-1000 nm and exhibit abnormal behavior (high efficacy and high specific surface area) of nanomaterials. Commercial formulations of pesticides used by farmers nowadays cannot be used effectively due to a number of problems associated with them. For example, more than 90% of applied formulations are either lost in the environment or unable to reach the target area required for effective pest control. Around 20−30% of pesticides are lost through emissions. A number of factors (application methods, physicochemical properties of the formulations, and environmental conditions) can influence the extent of loss during application. It is known that among various formulations, polymer-based formulations show the greatest potential due to their greater efficacy, slow release and protection against premature degradation of active ingredient as compared to other commercial formulations. However, the nanoformulations can have a significant effect on the fate of active ingredient as well as may release some new ingredients by reacting with existing soil contaminants. Environmental fate of these newly generated species is still not explored very well which is essential to field scale experiments and hence a lot to be explored in the field of environmental fate, nanotoxicology, transport properties and stability of such formulations. In our preliminary work, we have synthesized polymer based nanoformulation of commercially used weedicide atrazine. Atrazine belongs to triazine class of herbicide, which is used in the effective control of seed germinated dicot weeds and grasses. It functions by binding to the plastoquinone-binding protein in PS-II. Plant death results from starvation and oxidative damage caused by breakdown in electron transport system. The stability of the suspension of nanoformulation containing herbicide has been evaluated by considering different parameters like polydispersity index, particle diameter, zeta-potential under different environmental relevance condition such as pH range 4-10, temperature range from 25°C to 65°C and stability of encapsulation also have been studied for different amount of added polymer. Morphological characterization has been done by using SEM.

Keywords: atrazine, nanoformulation, nanopesticide, nanotoxicology

Procedia PDF Downloads 249
3964 Mid-Temperature Methane-Based Chemical Looping Reforming for Hydrogen Production via Iron-Based Oxygen Carrier Particles

Authors: Yang Li, Mingkai Liu, Qiong Rao, Zhongrui Gai, Ying Pan, Hongguang Jin

Abstract:

Hydrogen is an ideal and potential energy carrier due to its high energy efficiency and low pollution. An alternative and promising approach to hydrogen generation is the chemical looping steam reforming of methane (CL-SRM) over iron-based oxygen carriers. However, the process faces challenges such as high reaction temperature (>850 ℃) and low methane conversion. We demonstrate that Ni-mixed Fe-based oxygen carrier particles have significantly improved the methane conversion and hydrogen production rate in the range of 450-600 ℃ under atmospheric pressure. The effect on the reaction reactivity of oxygen carrier particles mixed with different Ni-based particle mass ratios has been determined in the continuous unit. More than 85% of methane conversion has been achieved at 600 ℃, and hydrogen can be produced in both reduction and oxidation steps. Moreover, the iron-based oxygen carrier particles exhibited good cyclic performance during 150 consecutive redox cycles at 600 ℃. The mid-temperature iron-based oxygen carrier particles, integrated with a moving-bed chemical looping system, might provide a powerful approach toward more efficient and scalable hydrogen production.

Keywords: chemical looping, hydrogen production, mid-temperature, oxygen carrier particles

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3963 Enhance Construction Visual As-Built Schedule Management Using BIM Technology

Authors: Shu-Hui Jan, Hui-Ping Tserng, Shih-Ping Ho

Abstract:

Construction project control attempts to obtain real-time as-built schedule information and to eliminate project delays by effectively enhancing dynamic schedule control and management. Suitable platforms for enhancing an as-built schedule visually during the construction phase are necessary and important for general contractors. As the application of building information modeling (BIM) becomes more common, schedule management integrated with the BIM approach becomes essential to enhance visual construction management implementation for the general contractor during the construction phase. To enhance visualization of the updated as-built schedule for the general contractor, this study presents a novel system called the Construction BIM-assisted Schedule Management (ConBIM-SM) system for general contractors in Taiwan. The primary purpose of this study is to develop a web ConBIM-SM system for the general contractor to enhance visual as-built schedule information sharing and efficiency in tracking construction as-built schedule. Finally, the ConBIM-SM system is applied to a case study of a commerce building project in Taiwan to verify its efficacy and demonstrate its effectiveness during the construction phase. The advantages of the ConBIM-SM system lie in improved project control and management efficiency for general contractors, and in providing BIM-assisted as-built schedule tracking and management, to access the most current as-built schedule information through a web browser. The case study results show that the ConBIM-SM system is an effective visual as-built schedule management platform integrated with the BIM approach for general contractors in a construction project.

Keywords: building information modeling (BIM), construction schedule management, as-built schedule management, BIM schedule updating mechanism

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3962 Design, Synthesis and Pharmacological Investigation of Novel 2-Phenazinamine Derivatives as a Mutant BCR-ABL (T315I) Inhibitor

Authors: Gajanan M. Sonwane

Abstract:

Nowadays, the entire pharmaceutical industry is facing the challenge of increasing efficiency and innovation. The major hurdles are the growing cost of research and development and a concurrent stagnating number of new chemical entities (NCEs). Hence, the challenge is to select the most druggable targets and to search the equivalent drug-like compounds, which also possess specific pharmacokinetic and toxicological properties that allow them to be developed as drugs. The present research work includes the studies of developing new anticancer heterocycles by using molecular modeling techniques. The heterocycles synthesized through such methodology are much effective as various physicochemical parameters have been already studied and the structure has been optimized for its best fit in the receptor. Hence, on the basis of the literature survey and considering the need to develop newer anticancer agents, new phenazinamine derivatives were designed by subjecting the nucleus to molecular modeling, viz., GQSAR analysis and docking studies. Simultaneously, these designed derivatives were subjected to in silico prediction of biological activity through PASS studies and then in silico toxicity risk assessment studies. In PASS studies, it was found that all the derivatives exhibited a good spectrum of biological activities confirming its anticancer potential. The toxicity risk assessment studies revealed that all the derivatives obey Lipinski’s rule. Amongst these series, compounds 4c, 5b and 6c were found to possess logP and drug-likeness values comparable with the standard Imatinib (used for anticancer activity studies) and also with the standard drug methotrexate (used for antimitotic activity studies). One of the most notable mutations is the threonine to isoleucine mutation at codon 315 (T315I), which is known to be resistant to all currently available TKI. Enzyme assay planned for confirmation of target selective activity.

Keywords: drug design, tyrosine kinases, anticancer, Phenazinamine

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3961 Recurrent Neural Networks for Complex Survival Models

Authors: Pius Marthin, Nihal Ata Tutkun

Abstract:

Survival analysis has become one of the paramount procedures in the modeling of time-to-event data. When we encounter complex survival problems, the traditional approach remains limited in accounting for the complex correlational structure between the covariates and the outcome due to the strong assumptions that limit the inference and prediction ability of the resulting models. Several studies exist on the deep learning approach to survival modeling; moreover, the application for the case of complex survival problems still needs to be improved. In addition, the existing models need to address the data structure's complexity fully and are subject to noise and redundant information. In this study, we design a deep learning technique (CmpXRnnSurv_AE) that obliterates the limitations imposed by traditional approaches and addresses the above issues to jointly predict the risk-specific probabilities and survival function for recurrent events with competing risks. We introduce the component termed Risks Information Weights (RIW) as an attention mechanism to compute the weighted cumulative incidence function (WCIF) and an external auto-encoder (ExternalAE) as a feature selector to extract complex characteristics among the set of covariates responsible for the cause-specific events. We train our model using synthetic and real data sets and employ the appropriate metrics for complex survival models for evaluation. As benchmarks, we selected both traditional and machine learning models and our model demonstrates better performance across all datasets.

Keywords: cumulative incidence function (CIF), risk information weight (RIW), autoencoders (AE), survival analysis, recurrent events with competing risks, recurrent neural networks (RNN), long short-term memory (LSTM), self-attention, multilayers perceptrons (MLPs)

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3960 Parametric Analysis of Lumped Devices Modeling Using Finite-Difference Time-Domain

Authors: Felipe M. de Freitas, Icaro V. Soares, Lucas L. L. Fortes, Sandro T. M. Gonçalves, Úrsula D. C. Resende

Abstract:

The SPICE-based simulators are quite robust and widely used for simulation of electronic circuits, their algorithms support linear and non-linear lumped components and they can manipulate an expressive amount of encapsulated elements. Despite the great potential of these simulators based on SPICE in the analysis of quasi-static electromagnetic field interaction, that is, at low frequency, these simulators are limited when applied to microwave hybrid circuits in which there are both lumped and distributed elements. Usually the spatial discretization of the FDTD (Finite-Difference Time-Domain) method is done according to the actual size of the element under analysis. After spatial discretization, the Courant Stability Criterion calculates the maximum temporal discretization accepted for such spatial discretization and for the propagation velocity of the wave. This criterion guarantees the stability conditions for the leapfrogging of the Yee algorithm; however, it is known that for the field update, the stability of the complete FDTD procedure depends on factors other than just the stability of the Yee algorithm, because the FDTD program needs other algorithms in order to be useful in engineering problems. Examples of these algorithms are Absorbent Boundary Conditions (ABCs), excitation sources, subcellular techniques, grouped elements, and non-uniform or non-orthogonal meshes. In this work, the influence of the stability of the FDTD method in the modeling of concentrated elements such as resistive sources, resistors, capacitors, inductors and diode will be evaluated. In this paper is proposed, therefore, the electromagnetic modeling of electronic components in order to create models that satisfy the needs for simulations of circuits in ultra-wide frequencies. The models of the resistive source, the resistor, the capacitor, the inductor, and the diode will be evaluated, among the mathematical models for lumped components in the LE-FDTD method (Lumped-Element Finite-Difference Time-Domain), through the parametric analysis of Yee cells size which discretizes the lumped components. In this way, it is sought to find an ideal cell size so that the analysis in FDTD environment is in greater agreement with the expected circuit behavior, maintaining the stability conditions of this method. Based on the mathematical models and the theoretical basis of the required extensions of the FDTD method, the computational implementation of the models in Matlab® environment is carried out. The boundary condition Mur is used as the absorbing boundary of the FDTD method. The validation of the model is done through the comparison between the obtained results by the FDTD method through the electric field values and the currents in the components, and the analytical results using circuit parameters.

Keywords: hybrid circuits, LE-FDTD, lumped element, parametric analysis

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3959 Experimental Analysis on the Thermal Performance of Vacuum Membrane Distillation Module Using Polyvinylidene Fluoride Hollow Fiber Membrane

Authors: Hong-Jin Joo, Hee-Yoel Kwak

Abstract:

Vacuum Membrane Distillation (VMD) uses pressure lower than the atmospheric pressure. The feed seawater is capable of producing more vapor at the same temperature than Direct Contact Membrane Distillation (DCMD), Air Gap Membrane Distillation (AGMD) or Sweep Gas Membrane Distillation (SGMD). It is advantageous because it is operable at a lower temperature than other membrane distillations. However, no commercial product is available that uses the VMD method, as it is still in the study stage. In this study, therefore, thermal performance test according to the feed water conditions was performed prior to both construction of the demonstration plant, which uses VMD module of the capacity of 400m³/d in South Korea, and commercialization of VMD module with hollow fiber membrane. Such study was performed by designing and constructing the VMD module of the capacity of 2 m³/day which utilizes the polyvinylidene fluoride (PVDF) hollow fiber membrane. The results obtained from the VMD module manufactured by ECONITY Co., Ltd in South Korea, showed that the maximum performance ratio (PR) value of 0.904, feed water temperature of 75 ℃, and the flow rate of 8 m3/h. As the temperature of and flow rate of the feed water increased, the PR value of the VMD module also increased.

Keywords: membrane distillation, vacuum membrane distillation, hollow fiber membrane, desalination

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3958 Modeling Geogenic Groundwater Contamination Risk with the Groundwater Assessment Platform (GAP)

Authors: Joel Podgorski, Manouchehr Amini, Annette Johnson, Michael Berg

Abstract:

One-third of the world’s population relies on groundwater for its drinking water. Natural geogenic arsenic and fluoride contaminate ~10% of wells. Prolonged exposure to high levels of arsenic can result in various internal cancers, while high levels of fluoride are responsible for the development of dental and crippling skeletal fluorosis. In poor urban and rural settings, the provision of drinking water free of geogenic contamination can be a major challenge. In order to efficiently apply limited resources in the testing of wells, water resource managers need to know where geogenically contaminated groundwater is likely to occur. The Groundwater Assessment Platform (GAP) fulfills this need by providing state-of-the-art global arsenic and fluoride contamination hazard maps as well as enabling users to create their own groundwater quality models. The global risk models were produced by logistic regression of arsenic and fluoride measurements using predictor variables of various soil, geological and climate parameters. The maps display the probability of encountering concentrations of arsenic or fluoride exceeding the World Health Organization’s (WHO) stipulated concentration limits of 10 µg/L or 1.5 mg/L, respectively. In addition to a reconsideration of the relevant geochemical settings, these second-generation maps represent a great improvement over the previous risk maps due to a significant increase in data quantity and resolution. For example, there is a 10-fold increase in the number of measured data points, and the resolution of predictor variables is generally 60 times greater. These same predictor variable datasets are available on the GAP platform for visualization as well as for use with a modeling tool. The latter requires that users upload their own concentration measurements and select the predictor variables that they wish to incorporate in their models. In addition, users can upload additional predictor variable datasets either as features or coverages. Such models can represent an improvement over the global models already supplied, since (a) users may be able to use their own, more detailed datasets of measured concentrations and (b) the various processes leading to arsenic and fluoride groundwater contamination can be isolated more effectively on a smaller scale, thereby resulting in a more accurate model. All maps, including user-created risk models, can be downloaded as PDFs. There is also the option to share data in a secure environment as well as the possibility to collaborate in a secure environment through the creation of communities. In summary, GAP provides users with the means to reliably and efficiently produce models specific to their region of interest by making available the latest datasets of predictor variables along with the necessary modeling infrastructure.

Keywords: arsenic, fluoride, groundwater contamination, logistic regression

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3957 Deteriorating Ambient Air Quality Resulted from Invasion of Foreign Air Pollutants

Authors: Kuo-C. Lo, Chung-H. Hung

Abstract:

Invasion of foreign air pollutants to deteriorate local air quality has become an emerging international issue of concern. This study aimed to apply meteorological and air quality model, WRF-Chem (V3.1), for simulating and analyzing the phenomenon of forming of high-concentrated particulate matters, PM10 and PM2.5, in ambient air of Taiwan during January 17th to 19th, 2014. The foreign air pollutants were mainly from long-distance transport of air pollutants of China being transported with a strong continental cold high. It was observed that PM10 and PM2.5 peaked as high as 182~588 μg/m3 and 95~165 μg/m3, respectively, in the ambient air of west side of Taiwan. They were about 2~3 folds higher than the usual concentrations of particulate matters in these seasons.

Keywords: WRF-Chem, air pollution, PM2.5, ambient air quality

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3956 The Impact Of Sedimentary Heterogeneity On Oil Recovery In Basin-plain Turbidite: An Outcrop Analogue Simulation Case Study

Authors: Bayonle Abiola Omoniyi

Abstract:

In turbidite reservoirs with volumetrically significant thin-bedded turbidites (TBTs), thin-pay intervals may be underestimated during calculation of reserve volume due to poor vertical resolution of conventional well logs. This paper demonstrates the strong control of bed-scale sedimentary heterogeneity on oil recovery using six facies distribution scenarios that were generated from outcrop data from the Eocene Itzurun Formation, Basque Basin (northern Spain). The variable net sand volume in these scenarios serves as a primary source of sedimentary heterogeneity impacting sandstone-mudstone ratio, sand and shale geometry and dimensions, lateral and vertical variations in bed thickness, and attribute indices. The attributes provided input parameters for modeling the scenarios. The models are 20-m (65.6 ft) thick. Simulation of the scenarios reveals that oil production is markedly enhanced where degree of sedimentary heterogeneity and resultant permeability contrast are low, as exemplified by Scenarios 1, 2, and 3. In these scenarios, bed architecture encourages better apparent vertical connectivity across intervals of laterally continuous beds. By contrast, low net-to-gross Scenarios 4, 5, and 6, have rapidly declining oil production rates and higher water cut with more oil effectively trapped in low-permeability layers. These scenarios may possess enough lateral connectivity to enable injected water to sweep oil to production well; such sweep is achieved at a cost of high-water production. It is therefore imperative to consider not only net-to-gross threshold but also facies stack pattern and related attribute indices to better understand how to effectively manage water production for optimum oil recovery from basin-plain reservoirs.

Keywords: architecture, connectivity, modeling, turbidites

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3955 Efficacy of Conservation Strategies for Endangered Garcinia gummi gutta under Climate Change in Western Ghats

Authors: Malay K. Pramanik

Abstract:

Climate change is continuously affecting the ecosystem, species distribution as well as global biodiversity. The assessment of the species potential distribution and the spatial changes under various climate change scenarios is a significant step towards the conservation and mitigation of habitat shifts, and species' loss and vulnerability. In this context, the present study aimed to predict the influence of current and future climate on an ecologically vulnerable medicinal species, Garcinia gummi-gutta, of the southern Western Ghats using Maximum Entropy (MaxEnt) modeling. The future projections were made for the period of 2050 and 2070 with RCP (Representative Concentration Pathways) scenario of 4.5 and 8.5 using 84 species occurrence data, and climatic variables from three different models of Intergovernmental Panel for Climate Change (IPCC) fifth assessment. Climatic variables contributions were assessed using jackknife test and AOC value 0.888 indicates the model perform with high accuracy. The major influencing variables will be annual precipitation, precipitation of coldest quarter, precipitation seasonality, and precipitation of driest quarter. The model result shows that the current high potential distribution of the species is around 1.90% of the study area, 7.78% is good potential; about 90.32% is moderate to very low potential for species suitability. Finally, the results of all model represented that there will be a drastic decline in the suitable habitat distribution by 2050 and 2070 for all the RCP scenarios. The study signifies that MaxEnt model might be an efficient tool for ecosystem management, biodiversity protection, and species re-habitation planning under climate change.

Keywords: Garcinia gummi gutta, maximum entropy modeling, medicinal plants, climate change, western ghats, MaxEnt

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3954 Enterprise Infrastructure Related to the Product Value Transferred from Intellectual Capital

Authors: Chih Chin Yang

Abstract:

The paper proposed a new theory of intellectual capital (so called IC) and a value approach in associated with production and market. After an in-depth review and research analysis of leading firms in this field, a holistic intellectual capital model is discussed, which involves transport, delivery supporting, and interface and systems of on intellectual capital. Through a quantity study, it is found that there is a significant relationship between the product value and infrastructure in a company. The product values are transferred from intellectual capital elements which includes three elements of content and the enterprise includes three elements of infrastructure in its market and product values of enterprise.

Keywords: enterprise, product value, intellectual capital, market and product values

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3953 Analyzing Defects with Failure Assessment Diagrams of Gas Pipelines

Authors: Alfred Hasanaj , Ardit Gjeta, Miranda Kullolli

Abstract:

The approach in analyzing defects on different pipe lines is conducted through Failure Assessment Diagram (FAD). These methods of analyses have further extended in recent years. This approach is used to identify and stress out a solution for the defects which randomly occur with gas pipes such are corrosion defects, gauge defects, and combination of defects where gauge and dents are included. Few of the defects are to be analyzed in this paper where our main focus will be the fracture of cast Iron pipes, elastic-plastic failure and plastic collapse of X52 steel pipes for gas transport. We need to conduct a calculation of probability of the defects in order to predict and avoid such costly defects.

Keywords: defects, failure assessment diagrams, steel pipes, safety factor

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3952 Modelling and Simulation of Light and Temperature Efficient Interdigitated Back- Surface-Contact Solar Cell with 28.81% Efficiency Rate

Authors: Mahfuzur Rahman

Abstract:

Back-contact solar cells improve optical properties by moving all electrically conducting parts to the back of the cell. The cell's structure allows silicon solar cells to surpass the 25% efficiency barrier and interdigitated solar cells are now the most efficient. In this work, the fabrication of a light, efficient and temperature resistant interdigitated back contact (IBC) solar cell is investigated. This form of solar cell differs from a conventional solar cell in that the electrodes are located at the back of the cell, eliminating the need for grids on the top, allowing the full surface area of the cell to receive sunlight, resulting in increased efficiency. In this project, we will use SILVACO TCAD, an optoelectronic device simulator, to construct a very thin solar cell with dimensions of 100x250um in 2D Luminous. The influence of sunlight intensity and atmospheric temperature on solar cell output power is highly essential and it has been explored in this work. The cell's optimum performance with 150um bulk thickness provides 28.81% efficiency with an 87.68% fill factor rate making it very thin, flexible and resilient, providing diverse operational capabilities.

Keywords: interdigitated, shading, recombination loss, incident-plane, drift-diffusion, luminous, SILVACO

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3951 Family Firms Performance: Examining the Impact of Digital and Technological Capabilities using Partial Least Squares Structural Equation Modeling and Necessary Condition Analysis

Authors: Pedro Mota Veiga

Abstract:

This study comprehensively evaluates the repercussions of innovation, digital advancements, and technological capabilities on the operational performance of companies across fifteen European Union countries following the initial wave of the COVID-19 pandemic. Drawing insights from longitudinal data sourced from the 2019 World Bank business surveys and subsequent 2020 World Bank COVID-19 follow-up business surveys, our extensive examination involves a diverse sample of 5763 family businesses. In exploring the relationships between these variables, we adopt a nuanced approach to assess the impact of innovation and digital and technological capabilities on performance. This analysis unfolds along two distinct perspectives: one rooted in necessity and the other insufficiency. The methodological framework employed integrates partial least squares structural equation modeling (PLS-SEM) with condition analysis (NCA), providing a robust foundation for drawing meaningful conclusions. The findings of the study underscore a positive influence on the performance of family firms stemming from both technological capabilities and digital advancements. Furthermore, it is pertinent to highlight the indirect contribution of innovation to enhanced performance, operating through its impact on digital capabilities. This research contributes valuable insights to the broader understanding of how innovation, coupled with digital and technological capabilities, can serve as pivotal factors in shaping the post-COVID-19 landscape for businesses across the European Union. The intricate analysis of family businesses, in particular adds depth to the comprehension of the dynamics at play in diverse economic contexts within the European Union.

Keywords: digital capabilities, technological capabilities, family firms performance, innovation, NCA, PLS-SEM

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3950 Modeling of Masonry In-Filled R/C Frame to Evaluate Seismic Performance of Existing Building

Authors: Tarek M. Alguhane, Ayman H. Khalil, M. N. Fayed, Ayman M. Ismail

Abstract:

This paper deals with different modeling aspects of masonry infill: no infill model, Layered shell infill model, and strut infill model. These models consider the complicated behavior of the in-filled plane frames under lateral load similar to an earthquake load. Three strut infill models are used: NBCC (2005) strut infill model, ASCE/SEI 41-06 strut infill model and proposed strut infill model based on modification to Canadian, NBCC (2005) strut infill model. Pushover and modal analyses of a masonry infill concrete frame with a single storey and an existing 5-storey RC building have been carried out by using different models for masonry infill. The corresponding hinge status, the value of base shear at target displacement as well as their dynamic characteristics have been determined and compared. A validation of the structural numerical models for the existing 5-storey RC building has been achieved by comparing the experimentally measured and the analytically estimated natural frequencies and their mode shapes. This study shows that ASCE/SEI 41-06 equation underestimates the values for the equivalent properties of the diagonal strut while Canadian, NBCC (2005) equation gives realistic values for the equivalent properties. The results indicate that both ASCE/SEI 41-06 and Canadian, NBCC (2005) equations for strut infill model give over estimated values for dynamic characteristic of the building. Proposed modification to Canadian, NBCC (2005) equation shows that the fundamental dynamic characteristic values of the building are nearly similar to the corresponding values using layered shell elements as well as measured field results.

Keywords: masonry infill, framed structures, RC buildings, non-structural elements

Procedia PDF Downloads 269
3949 Fast Track to the Physical Internet: A Cross-Industry Project from Upper Austria

Authors: Laura Simmer, Maria Kalt, Oliver Schauer

Abstract:

Freight transport is growing fast, but many vehicles are empty or just partially loaded. The vision and concepts of the Physical Internet (PI) proposes to eliminate these inefficiencies. Aiming for a radical sustainability improvement, the PI – inspired by the Digital Internet – is a hyperconnected global logistic system, enabling seamless asset sharing and flow consolidation. The implementation of a PI in its full expression will be a huge challenge: the industry needs innovation and implementation support including change management approaches, awareness creation and good practices diffusion, legislative actions to remove antitrust and international commerce barriers, standardization and public incentives policies. In order to take a step closer to this future the project ‘Atropine - Fast Track to the Physical Internet’ funded under the Strategic Economic and Research Program ‘Innovative Upper Austria 2020’ was set up. The two-year research project unites several research partners in this field, but also industrial partners and logistics service providers. With Atropine, the consortium wants to actively shape the mobility landscape in Upper Austria and make an innovative contribution to an energy-efficient, environmentally sound and sustainable development in the transport area. This paper should, on the one hand, clarify the questions what the project Atropine is about and, on the other hand, how a proof of concept will be reached. Awareness building plays an important role in the project as the PI requires a reorganization of the supply chain and the design of completely new forms of inter-company co-operation. New business models have to be developed and should be verified by simulation. After the simulation process one of these business models will be chosen and tested in real life with the partner companies. The developed results - simulation model and demonstrator - are used to determine how the concept of the PI can be applied in Upper Austria. Atropine shall pave the way for a full-scale development of the PI vision in the next few decades and provide the basis for pushing the industry toward a new level of co-operation with more shared resources and increased standardization.

Keywords: Atropine, inter-company co-operation, Physical Internet, shared resources, sustainable logistics

Procedia PDF Downloads 212
3948 The Role of Urban Agriculture in Enhancing Food Supply and Export Potential: A Case Study of Neishabour, Iran

Authors: Mohammadreza Mojtahedi

Abstract:

Rapid urbanization presents multifaceted challenges, including environmental degradation and public health concerns. As the inevitability of urban sprawl continues, it becomes essential to devise strategies to alleviate its pressures on natural ecosystems and elevate socio-economic benchmarks within cities. This research investigates urban agriculture's economic contributions, emphasizing its pivotal role in food provisioning and export potential. Adopting a descriptive-analytical approach, field survey data was primarily collected via questionnaires. The tool's validity was affirmed by expert opinions, and its reliability secured by achieving a Cronbach's alpha score over 0.70 from 30 preliminary questionnaires. The research encompasses Neishabour's populace of 264,375, extracting a sample size of 384 via Cochran's formula. Findings reveal the significance of urban agriculture in food supply and its potential for exports, underlined by a p-value < 0.05. Neishabour's urban farming can augment the export of organic commodities, fruits, vegetables, ornamental plants, and foster product branding. Moreover, it supports the provision of fresh produce, bolstering dietary quality. Urban agriculture further impacts urban development metrics—enhancing environmental quality, job opportunities, income levels, and aesthetics, while promoting rainwater utilization. Popular cultivations include peaches, Damask roses, and poultry, tailored to available spaces. Structural equation modeling indicates urban agriculture's overarching influence, accounting for a 56% variance, predominantly in food sufficiency and export proficiency.

Keywords: urban agriculture, food supply, export potential, urban development, environmental health, structural equation modeling

Procedia PDF Downloads 45
3947 Evolution of Propiconazole and Tebuconazole Residues through the Post-Harvest Application in 'Angeleno' Plum

Authors: M. J. Rodríguez, F. M. Sánchez, B. Velardo, P. Calvo, M. J. Serradilla, J. Delgado, J. M. López

Abstract:

The main problems in storage and later transport of fruits, are the decays developed that reduce the quality on destination’s markets. Nowadays, there is an increasing interest in the use of compounds to avoid decays in post-harvest. Triazole fungicides are agrochemicals widely used in the agricultural industry due to their wide spectrum of actions, and in some case, they are used in citrus fruit post-harvest. Moreover, its use is not authorized in plum post-harvest, but in order to a future possible authorization, the evolutions of propiconazole and tebuconazole residues are studied after its post-harvest application in ‘Angeleno’ plum.

Keywords: maximum residue limit (MRL), triazole fungicides, decay, Prunus salicina

Procedia PDF Downloads 303
3946 CFD Modeling of Air Stream Pressure Drop inside Combustion Air Duct of Coal-Fired Power Plant with and without Airfoil

Authors: Pakawhat Khumkhreung, Yottana Khunatorn

Abstract:

The flow pattern inside rectangular intake air duct of 300 MW lignite coal-fired power plant is investigated in order to analyze and reduce overall inlet system pressure drop. The system consists of the 45-degree inlet elbow, the flow instrument, the 90-degree mitered elbow and fans, respectively. The energy loss in each section can be determined by Bernoulli’s equation and ASHRAE standard table. Hence, computational fluid dynamics (CFD) is used in this study based on Navier-Stroke equation and the standard k-epsilon turbulence modeling. Input boundary condition is 175 kg/s mass flow rate inside the 11-m2 cross sectional duct. According to the inlet air flow rate, the Reynolds number of airstream is 2.7x106 (based on the hydraulic duct diameter), thus the flow behavior is turbulence. The numerical results are validated with the real operation data. It is found that the numerical result agrees well with the operating data, and dominant loss occurs at the flow rate measurement device. Normally, the air flow rate is measured by the airfoil and it gets high pressure drop inside the duct. To overcome this problem, the airfoil is planned to be replaced with the other type measuring instrument, such as the average pitot tube which generates low pressure drop of airstream. The numerical result in case of average pitot tube shows that the pressure drop inside the inlet airstream duct is decreased significantly. It should be noted that the energy consumption of inlet air system is reduced too.

Keywords: airfoil, average pitot tube, combustion air, CFD, pressure drop, rectangular duct

Procedia PDF Downloads 151
3945 Fast-Modulated Surface-Confined Plasma for Catalytic Nitrogen Fixation and Energy Intensification

Authors: Pradeep Lamichhane, Nima Pourali, E. V. Rebrov, Volker Hessel

Abstract:

Nitrogen fixation is critical for plants for the biosynthesis of protein and nucleic acid. Most of our atmosphere is nitrogen, yet plants cannot directly absorb it from the air, and natural nitrogen fixation is insufficient to meet the demands. This experiment used a fast-modulated surface-confined atmospheric pressure plasma created by a 6 kV (peak-peak) sinusoidal power source with a repetition frequency of 68 kHz to fix nitrogen. Plasmas have been proposed for excitation of nitrogen gas, which quickly oxidised to NOX. With different N2/O2 input ratios, the rate of NOX generation was investigated. The rate of NOX production was shown to be optimal for mixtures of 60–70% O2 with N2. To boost NOX production in plasma, metal oxide catalysts based on TiO2 were coated over the dielectric layer of a reactor. These results demonstrate that nitrogen activation was more advantageous in surface-confined plasma sources because micro-discharges formed on the sharp edges of the electrodes, which is a primary function attributed to NOX synthesis and is further enhanced by metal oxide catalysts. The energy-efficient and sustainable NOX synthesis described in this study will offer a fresh perspective for ongoing research on green nitrogen fixation techniques.

Keywords: nitrogen fixation, fast-modulated, surface-confined, sustainable

Procedia PDF Downloads 94
3944 Investigation of the Effect of Lecturers' Attributes on Students' Interest in Learning Statistic Ghanaian Tertiary Institutions

Authors: Samuel Asiedu-Addo, Jonathan Annan, Yarhands Dissou Arthur

Abstract:

The study aims to explore the relational effect of lecturers’ personal attribute on student’s interest in statistics. In this study personal attributes of lecturers’ such as lecturer’s dynamism, communication strategies and rapport in the classroom as well as applied knowledge during lecture were examined. Here, exploratory research design was used to establish the effect of lecturer’s personal attributes on student’s interest. Data were analyzed by means of confirmatory factor analysis and structural equation modeling (SEM) using the SmartPLS 3 program. The study recruited 376 students from the faculty of technical and vocational education of the University of Education Winneba Kumasi campus, and Ghana Technology University College as well as Kwame Nkrumah University of science and Technology. The results revealed that personal attributes of an effective lecturer were lecturer’s dynamism, rapport, communication and applied knowledge contribute (52.9%) in explaining students interest in statistics. Our regression analysis and structural equation modeling confirm that lecturers personal attribute contribute effectively by predicting student’s interest of 52.9% and 53.7% respectively. The paper concludes that the total effect of a lecturer’s attribute on student’s interest is moderate and significant. While a lecturer’s communication and dynamism were found to contribute positively to students’ interest, they were insignificant in predicting students’ interest. We further showed that a lecturer’s personal attributes such as applied knowledge and rapport have positive and significant effect on tertiary student’s interest in statistic, whilst lecturers’ communication and dynamism do not significantly affect student interest in statistics; though positively related.

Keywords: student interest, effective teacher, personal attributes, regression and SEM

Procedia PDF Downloads 350
3943 Modeling Average Paths Traveled by Ferry Vessels Using AIS Data

Authors: Devin Simmons

Abstract:

At the USDOT’s Bureau of Transportation Statistics, a biannual census of ferry operators in the U.S. is conducted, with results such as route mileage used to determine federal funding levels for operators. AIS data allows for the possibility of using GIS software and geographical methods to confirm operator-reported mileage for individual ferry routes. As part of the USDOT’s work on the ferry census, an algorithm was developed that uses AIS data for ferry vessels in conjunction with known ferry terminal locations to model the average route travelled for use as both a cartographic product and confirmation of operator-reported mileage. AIS data from each vessel is first analyzed to determine individual journeys based on the vessel’s velocity, and changes in velocity over time. These trips are then converted to geographic linestring objects. Using the terminal locations, the algorithm then determines whether the trip represented a known ferry route. Given a large enough dataset, routes will be represented by multiple trip linestrings, which are then filtered by DBSCAN spatial clustering to remove outliers. Finally, these remaining trips are ready to be averaged into one route. The algorithm interpolates the point on each trip linestring that represents the start point. From these start points, a centroid is calculated, and the first point of the average route is determined. Each trip is interpolated again to find the point that represents one percent of the journey’s completion, and the centroid of those points is used as the next point in the average route, and so on until 100 points have been calculated. Routes created using this algorithm have shown demonstrable improvement over previous methods, which included the implementation of a LOESS model. Additionally, the algorithm greatly reduces the amount of manual digitizing needed to visualize ferry activity.

Keywords: ferry vessels, transportation, modeling, AIS data

Procedia PDF Downloads 160
3942 Flood-Induced River Disruption: Geomorphic Imprints and Topographic Effects in Kelantan River Catchment from Kemubu to Kuala Besar, Kelantan, Malaysia

Authors: Mohamad Muqtada Ali Khan, Nor Ashikin Shaari, Donny Adriansyah bin Nazaruddin, Hafzan Eva Bt Mansoor

Abstract:

Floods play a key role in landform evolution of an area. This process is likely to alter the topography of the earth’s surface. The present study area, Kota Bharu is very prone to floods extends from upstream of Kelantan River near Kemubu to the downstream area near Kuala Besar. These flood events which occur every year in the study area exhibit a strong bearing on river morphological set-up. In the present study, three satellite imageries of different time periods have been used to manifest the post-flood landform changes. The pre-processing of the images such as subset, geometric corrections and atmospheric corrections were carried-out using ENVI 4.5 followed by the analysis processes. Twenty sets of cross sections were plotted using software Erdas 9.2, ERDAS and ArcGis 10 for the all three images. The results show a significant change in the length of the cross section which suggest that the geomorphological processes play a key role in carving and shaping the river banks during the floods.

Keywords: flood induced, geomorphic imprints, Kelantan river, Malaysia

Procedia PDF Downloads 534
3941 Alternative Key Exchange Algorithm Based on Elliptic Curve Digital Signature Algorithm Certificate and Usage in Applications

Authors: A. Andreasyan, C. Connors

Abstract:

The Elliptic Curve Digital Signature algorithm-based X509v3 certificates are becoming more popular due to their short public and private key sizes. Moreover, these certificates can be stored in Internet of Things (IoT) devices, with limited resources, using less memory and transmitted in network security protocols, such as Internet Key Exchange (IKE), Transport Layer Security (TLS) and Secure Shell (SSH) with less bandwidth. The proposed method gives another advantage, in that it increases the performance of the above-mentioned protocols in terms of key exchange by saving one scalar multiplication operation.

Keywords: cryptography, elliptic curve digital signature algorithm, key exchange, network security protocol

Procedia PDF Downloads 138