Search results for: predict

Authors: Ons Triki, Fathi Abid

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The basic objective of this paper is twofold. It resides in designing a model for a contingent convertible lease contract that can ensure the financial stability of a company and recover the losses of the parties to the lease in the event of default. It also aims to compare the convertible lease contract on inefficiencies resulting from the debt-overhang problem and asset substitution with other financing policies. From this perspective, this paper highlights the interaction between investments and financing policies in a dynamic model with existing assets and a growth option where the investment cost is financed by a contingent convertible lease and equity. We explore the impact of the contingent convertible lease on the capital structure. We also check the reliability and effectiveness of the use of the convertible lease contract as a means of financing. Findings show that the rental convertible contract with a sufficiently high conversion ratio has less severe inefficiencies arising from risk-shifting and debt overhang than those entailed by risky debt and pure-equity financing. The problem of underinvestment pointed out by Mauer and Ott (2000) and the problem of overinvestment mentioned by Hackbarth and Mauer (2012) may be reduced under contingent convertible lease financing. Our findings predict that the firm value under contingent convertible lease financing increases globally with asset volatility instead of decreasing with business risk. The study reveals that convertible leasing contracts can stand for a reliable solution to ensure the lessee and quickly recover the counterparties of the lease upon default.

Keywords: contingent convertible lease, growth option, debt overhang, risk-shifting, capital structure

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Authors: A. Al Hinai, H. Jayasuriya, H. Kotagama

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Most Gulf Cooperation Council (GCC) countries with oil-based economy like Oman are looking for other potential revenue generation options as the crude oil price is regularly fluctuating due to changing geopolitical environment. Oman has advantage of possessing world-heritage nature tourism hotspots around the country and the government is making investments and strategies to uplift the tourism industry following Oman Vision 2040 strategies. Oman’s agriculture is not significantly contributing to the economy, but possesses specific and diversified arid cropping systems. Oman has modern farms; nevertheless some of the agricultural production activities are done with cultural practices and styles that would be attractive to tourists. The aim of this paper is to investigate the potentials for promoting agritourism industry in Oman; recognize potential sites, commodities and activities, and predict potential revenue generation as a projection from that of the tourism sector. Moreover, the study enables to foresee possible auxiliary advantages of agritourism such as, empowerment of women and youth, enhancement in the value-addition industry for agricultural produce through technology transfer and capacity building, and producing export quality products. Agritourism could increase employability, empowerment of women and youth, improve value-addition industry and export-oriented agribusiness. These efforts including provision of necessary technology-transfer and capacity-building should be rendered by the collaboration of academic institutions, relevant ministries and other public and private sector stakeholders.

Keywords: agritourism, nature-based tourism, potentials, revenue generation, value addition

Procedia PDF Downloads 120

Authors: Nicolò Vaiana, Giorgio Serino

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In this paper, a one-dimensional (1d) Parallel Elasto- Plastic Model (PEPM), able to simulate the uniaxial dynamic behavior of seismic isolators having a continuously decreasing tangent stiffness with increasing displacement, is presented. The parallel modeling concept is applied to discretize the continuously decreasing tangent stiffness function, thus allowing to simulate the dynamic behavior of seismic isolation bearings by putting linear elastic and nonlinear elastic-perfectly plastic elements in parallel. The mathematical model has been validated by comparing the experimental force-displacement hysteresis loops, obtained testing a helical wire rope isolator and a recycled rubber-fiber reinforced bearing, with those predicted numerically. Good agreement between the simulated and experimental results shows that the proposed model can be an effective numerical tool to predict the forcedisplacement relationship of seismic isolators within relatively large displacements. Compared to the widely used Bouc-Wen model, the proposed one allows to avoid the numerical solution of a first order ordinary nonlinear differential equation for each time step of a nonlinear time history analysis, thus reducing the computation effort, and requires the evaluation of only three model parameters from experimental tests, namely the initial tangent stiffness, the asymptotic tangent stiffness, and a parameter defining the transition from the initial to the asymptotic tangent stiffness.

Keywords: base isolation, earthquake engineering, parallel elasto-plastic model, seismic isolators, softening hysteresis loops

Procedia PDF Downloads 265

Authors: Sandra Mitrovic, Gaurav Singh

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In many industries, including telecommunications, churn prediction has been a topic of active research. A lot of attention has been drawn on devising the most informative features, and this area of research has gained even more focus with spread of (social) network analytics. The call detail records (CDRs) have been used to construct customer networks and extract potentially useful features. However, to the best of our knowledge, no studies including network features have yet proposed a generic way of representing network information. Instead, ad-hoc and dataset dependent solutions have been suggested. In this work, we build upon a recently presented method (node2vec) to obtain representations for nodes in observed network. The proposed approach is generic and applicable to any network and domain. Unlike node2vec, which assumes a static network, we consider a dynamic and time-evolving network. To account for this, we propose an approach that constructs the feature representation of each node by generating its node2vec representations at different timestamps, concatenating them and finally compressing using an auto-encoder-like method in order to retain reasonably long and informative feature vectors. We test the proposed method on churn prediction task in telco domain. To predict churners at timestamp ts+1, we construct training and testing datasets consisting of feature vectors from time intervals [t1, ts-1] and [t2, ts] respectively, and use traditional supervised classification models like SVM and Logistic Regression. Observed results show the effectiveness of proposed approach as compared to ad-hoc feature selection based approaches and static node2vec.

Keywords: churn prediction, dynamic networks, node2vec, auto-encoders

Procedia PDF Downloads 301

Authors: João Paulo Pascon

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In this work, a mixed 3D finite element formulation is proposed in order to analyze thermoviscoplastic materials under large strain levels and ductile damage. To this end, a tetrahedral element of linear order is employed, considering a thermoviscoplastic constitutive law together with the neo-Hookean hyperelastic relationship and a nonlocal Gurson`s porous plasticity theory The material model is capable of reproducing finite deformations, elastoplastic behavior, void growth, nucleation and coalescence, thermal effects such as plastic work heating and conductivity, strain hardening and strain-rate dependence. The nonlocal character is introduced by means of a nonlocal parameter applied to the Laplacian of the porosity field. The element degrees of freedom are the nodal values of the deformed position, the temperature and the nonlocal porosity field. The internal variables are updated at the Gauss points according to the yield criterion and the evolution laws, including the yield stress of matrix, the equivalent plastic strain, the local porosity and the plastic components of the Cauchy-Green stretch tensor. Two problems involving 3D specimens and ductile damage are numerically analyzed with the developed computational code: the necking problem and a notched sample. The effect of the nonlocal parameter and the mesh refinement is investigated in detail. Results indicate the need of a proper nonlocal parameter. In addition, the numerical formulation can predict ductile fracture, based on the evolution of the fully damaged zone.

Keywords: mixed finite element, large strains, ductile damage, thermoviscoplasticity

Procedia PDF Downloads 72

Authors: Peifei Zhu, Zisheng Li, Yasuki Kakishita, Mayumi Suzuki, Tomoaki Chono

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Segmentation of left ventricle (LV) from cardiac ultrasound images provides a quantitative functional analysis of the heart to diagnose disease. Active Shape Model (ASM) is a widely used approach for LV segmentation but suffers from the drawback that initialization of the shape model is not sufficiently close to the target, especially when dealing with abnormal shapes in disease. In this work, a two-step framework is proposed to improve the accuracy and speed of the model-based segmentation. Firstly, a robust and efficient detector based on Hough forest is proposed to localize cardiac feature points, and such points are used to predict the initial fitting of the LV shape model. Secondly, to achieve more accurate and detailed segmentation, ASM is applied to further fit the LV shape model to the cardiac ultrasound image. The performance of the proposed method is evaluated on a dataset of 800 cardiac ultrasound images that are mostly of abnormal shapes. The proposed method is compared to several combinations of ASM and existing initialization methods. The experiment results demonstrate that the accuracy of feature point detection for initialization was improved by 40% compared to the existing methods. Moreover, the proposed method significantly reduces the number of necessary ASM fitting loops, thus speeding up the whole segmentation process. Therefore, the proposed method is able to achieve more accurate and efficient segmentation results and is applicable to unusual shapes of heart with cardiac diseases, such as left atrial enlargement.

Keywords: hough forest, active shape model, segmentation, cardiac left ventricle

Procedia PDF Downloads 326

Authors: Yulmaida Amir, Fahrul Rozi, Insany C. Kamil, Fanny Aryani

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ODAPUS (Orang dengan Lupus) is an Indonesian term for people with Lupus, a chronic autoimmune disease in which immune system of the body becomes hyperactive and attacks normal tissue. The number of ODAPUS indicate an increase in Indonesia, thereby helping to improve their quality of life to be important to help their recovery. This study aims to examine the effect of resilience, self-esteem, and social support on the quality of life of women who had been diagnosed as having Lupus. Data were collected from 64 ODAPUS in Indonesia, using the World Health Organization Quality of Life (WHOQOL), Resilience Scale from Wagnil and Young (1993), self-esteem scale (developed from Coopersmith’s theory), and Social Support Questioner from Northouse (1988). Regression data analysis showed that resilience, social support, and self-esteem predict the quality of life of the ODAPUS simultaneously. If the variable was analysed individually, self-esteem did not significantly contribute to the quality of life. Resilience contributed most significantly to the quality of life, followed by social support. Of five sources of social supports included in the research, support from family members (parents and brother/sisters) has the most significant contribution to the quality of life, followed by support from spouse, and from friends. Interestingly, social support from medical personnel (medical doctors and nurses) had not a significant contribution to the quality of life of ODAPUS. As a conclusion, this research showed that the ability of ODAPUS to cope with difficulty in life, and support from family members, spouse, and friends were the significant predictors for their quality of life.

Keywords: quality of life, resilience, self-esteem, social supports

Procedia PDF Downloads 148

Authors: Seyed Sadegh Naseralavi, Sadegh Balaghi, Ehsan Khojastehfar

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Time history seismic analysis is supposed to be the most accurate method to predict the seismic demand of structures. On the other hand, the required computational time of this method toward achieving the result is its main deficiency. While being applied in optimization process, in which the structure must be analyzed thousands of time, reducing the required computational time of seismic analysis of structures makes the optimization algorithms more practical. Apparently, the invented approximate methods produce some amount of errors in comparison with exact time history analysis but the recently proposed method namely, Complete Quadratic Combination (CQC) and Sum Root of the Sum of Squares (SRSS) drastically reduces the computational time by combination of peak responses in each mode. In the present research, the Basic Modal Displacement (BMD) method is introduced and applied towards estimation of seismic demand of main structure. Seismic demand of sampled structure is estimated by calculation of modal displacement of basic structure (in which the modal displacement has been calculated). Shear steel sampled structures are selected as case studies. The error applying the introduced method is calculated by comparison of the estimated seismic demands with exact time history dynamic analysis. The efficiency of the proposed method is demonstrated by application of three types of earthquakes (in view of time of peak ground acceleration).

Keywords: time history dynamic analysis, basic modal displacement, earthquake-induced demands, shear steel structures

Procedia PDF Downloads 342

Authors: Suchitra Chnadrashekhar

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Earlier looked as a support function in an organization information technology has now become a critical utility to manage their daily operations. Organizations are processing huge amount of data which was unimaginable few decades before. This has opened the opportunity for IT sector to help industries across domains to handle the data in the most intelligent manner. Presence of IT has been a leverage for the Oil & Gas industry to store, manage and process the data in most efficient way possible thus deriving the economic value in their day-to-day operations. Proper synchronization between Operational data system and Information Technology system is the need of the hour. Predictive analytics supports oil and gas companies by addressing the challenge of critical equipment performance, life cycle, integrity, security, and increase their utilization. Predictive analytics go beyond early warning by providing insights into the roots of problems. To reach their full potential, oil and gas companies need to take a holistic or systems approach towards asset optimization and thus have the functional information at all levels of the organization in order to make the right decisions. This paper discusses how the use of predictive analysis in oil and gas industry is redefining the dynamics of this sector. Also, the paper will be supported by real time data and evaluation of the data for a given oil production asset on an application tool, SAS. The reason for using SAS as an application for our analysis is that SAS provides an analytics-based framework to improve uptimes, performance and availability of crucial assets while reducing the amount of unscheduled maintenance, thus minimizing maintenance-related costs and operation disruptions. With state-of-the-art analytics and reporting, we can predict maintenance problems before they happen and determine root causes in order to update processes for future prevention.

Keywords: hydrocarbon, information technology, SAS, predictive analytics

Procedia PDF Downloads 338

Authors: R. Begum, M. M. R. Jahangir, M. Jahiruddin, M. R. Islam, M. M. Rahman, M. B. Hossain, P. Hossain

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Quantifying carbon (C) sequestration in soils is necessary to help better understand the effect of agricultural practices on the C cycle. The estimated contribution of agricultural carbon dioxide (CO₂) and methane (CH₄) to global warming potential (GWP) has a wide range. The underlying causes of this huge uncertainty are the difficulties to predict the regional CO₂ and CH₄ loss due to the lack of experimental evidence on CO₂ and CH₄ emissions and associated drivers. The CH₄ and CO₂ emissions were measured in irrigated wheat in subtropical floodplain soils which have been under two soil disturbance levels (strip vs. conventional tillage; ST vs. CT being both with 30% residue retention) and three N fertilizer rates (60, 100, and 140% of the recommended N fertilizer dose, RD) in annual wheat (Triticum aestivum)-mungbean (Vigna radiata)-rice (Oryza sativa L) for seven consecutive years. The highest CH₄ and CO₂ emission peak was observed on day 3 after urea application in both tillages except CO₂ flux in CT. Nitrogen fertilizer application rate significantly influenced mean and cumulative CH₄ and CO₂ fluxes. The CH₄ and CO₂ fluxes decreased in an optimum dose of N fertilizer except for ST for CH₄. The CO₂ emission significantly showed higher emission at minimum (60% of RD) fertilizer application at both tillages. Soil microbial biomass carbon (MBC), organic carbon (SOC), Particulate organic carbon (POC), permanganate oxidisable carbon (POXC), basal respiration (BR) were significantly higher in ST which were negative and significantly correlated with CO₂. However, POC and POXC were positively and significantly correlated with CH₄ emission.

Keywords: carbon dioxide emissions, methane emission, nitrogen rate, tillage

Procedia PDF Downloads 100

Authors: Chayanoot Sangwichien, Taweesak Reungpeerakul, Kyaw Thu

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

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

Procedia PDF Downloads 189

Authors: Lai Wenfang

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Tthis study will describe how to use artificial intelligence (AI) technology to build the user-oriented platform for integrated archival service. The platform will be launched in 2020 by the National Archives Administration (NAA) in Taiwan. With the progression of information communication technology (ICT) the NAA has built many systems to provide archival service. In order to cope with new challenges, such as new ICT, artificial intelligence or blockchain etc. the NAA will try to use the natural language processing (NLP) and machine learning (ML) skill to build a training model and propose suggestions based on the data sent to the platform. NAA expects the platform not only can automatically inform the sending agencies’ staffs which records catalogues are against the transfer or destroy rules, but also can use the model to find the details hidden in the catalogues and suggest NAA’s staff whether the records should be or not to be, to shorten the auditing time. The platform keeps all the users’ browse trails; so that the platform can predict what kinds of archives user could be interested and recommend the search terms by visualization, moreover, inform them the new coming archives. In addition, according to the Archives Act, the NAA’s staff must spend a lot of time to mark or remove the personal data, classified data, etc. before archives provided. To upgrade the archives access service process, the platform will use some text recognition pattern to black out automatically, the staff only need to adjust the error and upload the correct one, when the platform has learned the accuracy will be getting higher. In short, the purpose of the platform is to deduct the government digital transformation and implement the vision of a service-oriented smart government.

Keywords: artificial intelligence, natural language processing, machine learning, visualization

Procedia PDF Downloads 155

Authors: Roy Y. C. Huang, J. S. Kuang, Hamdolah Behnam

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Beam-column connections play an important role in the reinforced concrete moment resisting frame (RCMRF), which is one of the most commonly used structural systems around the world. The premature failure of such connections would severely limit the seismic performance and increase the vulnerability of RCMRF. In the past decades, researchers primarily focused on investigating the structural behaviour and failure mechanisms of conventional beam-column joints, the beam width of which is either smaller than or equal to the column width, while studies in wide beam-column joints were scarce. This paper presents the preliminary experimental results of two full-scale exterior wide beam-column connections, which are mainly designed and detailed according to ACI 318-14 and ACI 352R-02, under reversed cyclic loading. The ratios of the design shear force to the nominal shear strength of these specimens are 1.0 and 1.7, respectively, so as to probe into differences of the joint shear strength between experimental results and predictions by design codes of practice. Flexural failure dominated in the specimen with ratio of 1.0 in which full-width plastic hinges were observed, while both beam hinges and post-peak joint shear failure occurred for the other specimen. No sign of premature joint shear failure was found which is inconsistent with ACI codes’ prediction. Finally, a modification of current codes of practice is provided to accurately predict the joint shear strength in wide beam-column joint.

Keywords: joint shear strength, reversed cyclic loading, seismic vulnerability, wide beam-column joints

Procedia PDF Downloads 309

Authors: Thamir K. Ibrahim, M. M. Rahman, Marwah Noori Mohammed

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This study deals with modeling and performance enhancements of a gas-turbine combined cycle power plant. A clean and safe energy is the greatest challenges to meet the requirements of the green environment. These requirements have given way the long-time governing authority of steam turbine (ST) in the world power generation, and the gas turbine (GT) will replace it. Therefore, it is necessary to predict the characteristics of the GT system and optimize its operating strategy by developing a simulation system. The integrated model and simulation code for exploiting the performance of gas turbine power plant are developed utilizing MATLAB code. The performance code for heavy-duty GT and CCGT power plants are validated with the real power plant of Baiji GT and MARAFIQ CCGT plants the results have been satisfactory. A new technology of correlation was considered for all types of simulation data; whose coefficient of determination (R2) was calculated as 0.9825. Some of the latest launched correlations were checked on the Baiji GT plant and apply error analysis. The GT performance was judged by particular parameters opted from the simulation model and also utilized Adaptive Neuro-Fuzzy System (ANFIS) an advanced new optimization technology. The best thermal efficiency and power output attained were about 56% and 345MW respectively. Thus, the operation conditions and ambient temperature are strongly influenced on the overall performance of the GT. The optimum efficiency and power are found at higher turbine inlet temperatures. It can be comprehended that the developed models are powerful tools for estimating the overall performance of the GT plants.

Keywords: gas turbine, optimization, ANFIS, performance, operating conditions

Procedia PDF Downloads 408

Authors: Ahmed Mozamel, Kemal Yildizli

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Due to mechanical energy losses and a competitive of minimizing these losses and increases the machine efficiency, the need for contactless gearing system has raised. In this work, one stage of mechanical planetary gear transmission system integrated with one stage of magnetic planetary gear system is designed as a two-stage hybrid gearbox system. The permanent magnets internal energy in the form of the magnetic field is used to create meshing between contactless magnetic rotors in order to provide self-system protection against overloading and decrease the mechanical loss of the transmission system by eliminating the friction losses. Classical methods, such as analytical, tabular method and the theory of elasticity are used to calculate the planetary gear design parameters. The finite element method (ANSYS Maxwell) is used to predict the behaviors of a magnetic gearing system. The concentric magnetic gearing system has been modeled and analyzed by using 2D finite element method (ANSYS Maxwell). In addition to that, design and manufacturing processes of prototype components (a planetary gear, concentric magnetic gear, shafts and the bearings selection) of a gearbox system are investigated. The output force, the output moment, the output power and efficiency of the hybrid gearbox system are experimentally evaluated. The viability of applying a magnetic force to transmit mechanical power through a non-contact gearing system is presented. The experimental test results show that the system is capable to operate continuously within the range of speed from 400 rpm to 3000 rpm with the reduction ratio of 2:1 and maximum efficiency of 91%.

Keywords: hybrid gearbox, mechanical gearboxes, magnetic gears, magnetic torque

Procedia PDF Downloads 137

Authors: Segun Steven Bodunde

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Mudlogging is the continuous analysis of rock cuttings and drilling fluids to ascertain the presence or absence of oil and gas from the formation penetrated by the drilling bit. This research highlighted a case study of Well BSS-99ST from ‘Bisas Field’, Niger Delta, with depth extending from 1950m to 3640m (Measured Depth). It was focused on identifying the lithologies encountered at specified depth intervals and to accurately delineate the targeted potential reservoir on the field and prepare the lithology and Master log. Equipment such as the Microscope, Fluoroscope, spin drier, oven, and chemicals, which includes: hydrochloric acid, chloroethene, and phenolphthalein, were used to check the cuttings for their calcareous nature, for oil show and for the presence of Cement respectively. Gas analysis was done using the gas chromatograph and the Flame Ionization Detector, which was connected to the Total Hydrocarbon Analyzer (THA). Drilling Parameters and Gas concentration logs were used alongside the lithology log to predict and accurately delineate the targeted reservoir on the field. The result showed continuous intercalation of sand and shale, with the presence of small quantities of siltstone at a depth of 2300m. The lithology log was generated using Log Plot software. The targeted reservoir was identified between 3478m to 3510m after inspection of the gas analysis, lithology log, electric logs, and the drilling parameters. Total gas of about 345 units and five Alkane Gas components were identified in the specific depth range. A comparative check with the Gamma ray log from the well further confirmed the lithologic sequence and the accurate delineation of the targeted potential reservoir using mudlogging.

Keywords: mudlogging, chromatograph, drilling fluids, calcareous

Procedia PDF Downloads 135

Authors: Abdelkader Hachemi, Boualem Remini

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Seawater intrusion is a significant challenge faced by coastal aquifers in the Mediterranean basin. This study aims to determine the position of the sharp interface between seawater and freshwater in the aquifer of Wadi Nador, located in the Wilaya of Tipaza, Algeria. A numerical areal sharp interface model using the finite element method is developed to investigate the spatial and temporal behavior of seawater intrusion. The aquifer is assumed to be homogeneous and isotropic. The simulation results are compared with geophysical prospection data obtained through electrical methods in 2011 to validate the model. The simulation results demonstrate a good agreement with the geophysical prospection data, confirming the accuracy of the sharp interface model. The position of the sharp interface in the aquifer is found to be approximately 1617 meters from the sea. Two scenarios are proposed to predict the interface position for the year 2024: one without pumping and the other with pumping. The results indicate a noticeable retreat of the sharp interface position in the first scenario, while a slight decline is observed in the second scenario. The findings of this study provide valuable insights into the dynamics of seawater intrusion in the Wadi Nador aquifer. The predicted changes in the sharp interface position highlight the potential impact of pumping activities on the aquifer's vulnerability to seawater intrusion. This study emphasizes the importance of implementing measures to manage and mitigate seawater intrusion in coastal aquifers. The sharp interface model developed in this research can serve as a valuable tool for assessing and monitoring the vulnerability of aquifers to seawater intrusion.

Keywords: seawater intrusion, sharp interface, coastal aquifer, algeria

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Authors: K. Kong, E. Ferrier, L. Michel

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The purpose of this research was to investigate the creep behaviour of the heterogeneous Timber-UHPFRC beams. New developments have been done to further improve the structural performance, such as strengthening of the timber (glulam) beam by bonding composite material combine with an ultra-high performance fibre reinforced concrete (UHPFRC) internally reinforced with or without carbon fibre reinforced polymer (CFRP) bars. However, in the design of wooden structures, in addition to the criteria of strengthening and stiffness, deformability due to the creep of wood, especially in horizontal elements, is also a design criterion. Glulam, UHPFRC and CFRP may be an interesting composite mix to respond to the issue of creep behaviour of composite structures made of different materials with different rheological properties. In this paper, we describe an experimental and analytical investigation of the creep performance of the glulam-UHPFRC-CFRP beams assembled by bonding. The experimental investigations creep behaviour was conducted for different environments: in- and outside under constant loading for approximately a year. The measured results are compared with numerical ones obtained by an analytical model. This model was developed to predict the creep response of the glulam-UHPFRC-CFRP beams based on the creep characteristics of the individual components. The results show that heterogeneous glulam-UHPFRC beams provide an improvement in both the strengthening and stiffness, and can also effectively reduce the creep deflection of wooden beams.

Keywords: carbon fibre-reinforced polymer (CFRP) bars, creep behaviour, glulam, ultra-high performance fibre reinforced concrete (UHPFRC)

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Authors: Rogelio Omar Corona-Núñez, Alma Mendoza-Ponce

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The Tropical Dry Forest not only is one of the most important tropical ecosystems in terms of area, but also it is one of the most degraded ecosystems. However, little is known about the degradation impacts on carbon stocks, therefore in carbon emissions. There are different studies which explain its deforestation dynamics, but there is still a lack of understanding of how they correlate to carbon losses. Recently different authors have built current biomass maps for the tropics and Mexico. However, it is not clear how well they predict at the local scale, and how they can be used to estimate carbon emissions. This study quantifies the forest net carbon losses by comparing the potential carbon stocks and the different current biomass maps in the Southern Pacific coast in Oaxaca, Mexico. The results show important differences in the current biomass estimates with not a clear agreement. However, by the aggregation of the information, it is possible to infer the general patterns of biomass distribution and it can identify the driving forces of the carbon emissions. This study estimated that currently ~44% of the potential carbon stock estimated for the region is still present. A total of 6,764 GgC has been emitted due to deforestation and degradation of the forest at a rate of above ground biomass loss of 66.4 Mg ha-1. Which, ~62% of the total carbon emissions can be regarded as being due to forest degradation. Most of carbon losses were identified in places suitable for agriculture, close to rural areas and to roads while the lowest losses were accounted in places with high water stress and within the boundaries of the National Protected Area. Moreover, places not suitable for agriculture, but close to the coast showed carbon losses as a result of urban settlements.

Keywords: above ground biomass, deforestation, degradation, driving forces, tropical deciduous forest

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Authors: Christian Perrin, Nicholas Blagden, Louise Allen, Sarah Impey

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Social workers in the UK and professionals globally are faced with a particular challenge when dealing with allegations of child sexual abuse (CSA) in the community. In the absence of a conviction or incontestable evidence, staff can often find themselves unable to take decisive action to remove a child from harm, even though there may be a credible threat to their welfare. Conversely, practitioners may over-calculate risk through fear of being accountable for harm. This is, in part, due to the absence of a structured and evidence-based risk assessment tool which can predict the likelihood of a person committing child sexual abuse. Such assessments are often conducted by forensic professionals who utilise offence-specific data and personal history information to calculate risk. In situations where only allegations underpin a case, this mode of assessment is not viable. There are further ethical issues surrounding the assessment of risk in this area which require expert consideration and sensitive planning. This paper explores this entangled problem extant in the wider call to prevent sexual and child sexual abuse in the community. To this end, 32 qualitative interviews were undertaken with social workers dealing with CSA cases. Results were analysed using thematic analysis and operationalised to formulate a risk and protection protocol for use in case management. This paper reports on the early findings associated with the initial indications of protocol reliability. Implications for further research and practice are discussed.

Keywords: sexual offending, child sexual offence, offender rehabilitation, risk assessment, offence prevention

Procedia PDF Downloads 96

Authors: Warda L. Panondi, Norihiro Izumi

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Sedimentation is a significant threat to the sustainability of reservoirs and their watershed. In the Philippines, the Pulangi watershed experienced a high sediment loss mainly due to land conversions and plantations that showed critical erosion rates beyond the tolerable limit of -10 ton/ha/yr in all of its sub-basin. From this event, the prediction of runoff volume and sediment yield is essential to examine using the country's soil conservation techniques realistically. In this research, the Pulangi watershed was modeled using the soil water assessment tool (SWAT) to predict its watershed basin's annual runoff and sediment yield. For the calibration and validation of the model, the SWAT-CUP was utilized. The model was calibrated with monthly discharge data for 1990-1993 and validated for 1994-1997. Simultaneously, the sediment yield was calibrated in 2014 and validated in 2015 because of limited observed datasets. Uncertainty analysis and calculation of efficiency indexes were accomplished through the SUFI-2 algorithm. According to the coefficient of determination (R2), Nash Sutcliffe efficiency (NSE), King-Gupta efficiency (KGE), and PBIAS, the calculation of streamflow indicates a good performance for both calibration and validation periods while the sediment yield resulted in a satisfactory performance for both calibration and validation. Therefore, this study was able to identify the most critical sub-basin and severe needs of soil conservation. Furthermore, this study will provide baseline information to prevent floods and landslides and serve as a useful reference for land-use policies and watershed management and sustainability in the Pulangi watershed.

Keywords: Pulangi watershed, sediment yield, streamflow, SWAT model

Procedia PDF Downloads 186

Authors: Muhammad Shahzad Iqbal, Zobia Sarwar, Salah-ud-Din

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Tomato spotted wilt virus (TSWV) belongs to the genus Tospoviruses (family Bunyaviridae). It is one of the most devastating pathogens of tomato (Solanum Lycopersicum) and heavily damages the crop yield each year around the globe. In this study, we retrieved 329 mature miRNA sequences from two microRNA databases (miRBase and miRSoldb) and checked the putative target sites in the downloaded-genome sequence of TSWV. A consensus of three miRNA target prediction tools (RNA22, miRanda and psRNATarget) was used to screen the false-positive microRNAs targeting sites in the TSWV genome. These tools calculated different target sites by calculating minimum free energy (mfe), site-complementarity, minimum folding energy and other microRNA-mRNA binding factors. R language was used to plot the predicted target-site data. All the genes having possible target sites for different miRNAs were screened by building a consensus table. Out of these 329 mature miRNAs predicted by three algorithms, only eight miRNAs met all the criteria/threshold specifications. MC-Fold and MC-Sym were used to predict three-dimensional structures of miRNAs and further analyzed in USCF chimera to visualize the structural and conformational changes before and after microRNA-mRNA interactions. The results of the current study show that the predicted eight miRNAs could further be evaluated by in vitro experiments to develop TSWV-resistant transgenic tomato plants in the future.

Keywords: tomato spotted wild virus (TSWV), Solanum lycopersicum, plant virus, miRNAs, microRNA target prediction, mRNA

Procedia PDF Downloads 136

Authors: Wenfen Bi, Zeng Lin

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As a developing country, China is badly in need of capital and talents to develop the socialist country with Chinese characteristics. However, a large proportion of high income people with know-how technique, wealth and management experience have immigrated or plan to immigrate to other countries. Of course, this phenomenon has attracted the attention from both the government and researchers. One explanation might be that these high-income people lack confidence in China’s social development. Based on the data on W city’s comprehensive social situation surveyed by center for the social survey research of Wuhan university (CSSR) in 2014, this paper employed the structural equation model (SEM) to evaluate whether personal income affects social confidence, via the mediating effect of the sense of social equity (sense of right equity and sense of distributive equity). Bootstrap mediation analysis revealed that after controlling Demographic variables, personal income had a significant negative influence on sense of right equity and in turn, sense of rights equity can significantly positively predict social confidence. While personal income had no significant effect on sense of distributive equity, and sense of distributive equity did not significantly affect macro social confidence. Also, the direct effects of personal income on social confidence became not significant. These findings revealed the inner mechanism of the relationship between the personal income and social confidence in contemporary China, which was caused by mediating effect of sense of rights equity. That is, the higher the personal income, the lower the sense of rights equity, the lower the social confidence. Thus, the boost of the social confidence, especially for the rich, does not only depend on the equitable distribution of material wealth, but also on the right equity and making people feel rights equally in common life.

Keywords: personal income, sense of right equity, sense of social equity, social confidence

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Authors: Dana Craciun, Daniela Dascalu, Adriana Isvoran

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Phthalates are a class of plastic additives that are used to enhance the physical properties of plastics and as solvents in paintings and some of them proved to be of particular concern for the human health. There are insufficient data concerning the health risks of phthalates and further research on evaluating their effects in humans is needed. As humans are not volunteers for such experiments, computational analysis may be used to predict the biological effects of phthalates in humans. Within this study we have used some computational approaches (SwissADME, admetSAR, FAFDrugs) for predicting the absorption, distribution, metabolization, excretion and toxicity (ADME-Tox) profiles and pharmacokinetics for the most common used phthalates. These computational tools are based on quantitative structure-activity relationship modeling approach. The predictions are further compared to the known effects of each considered phthalate in humans and correlations between computational results and experimental data are discussed. Our data revealed that phthalates are a class of compounds reflecting high toxicity both when ingested and when inhaled, but by inhalation their toxicity is even greater. The predicted harmful effects of phthalates are: toxicity and irritations of the respiratory and gastrointestinal tracts, dyspnea, skin and eye irritations and disruption of the functions of liver and of the reproductive system. Many of investigated phthalates are predicted to be able to inhibit some of the cytochromes involved in the metabolism of numerous drugs and consequently to affect the efficiency of administrated treatments for many diseases and to intensify the adverse drugs reactions. The obtained predictions are in good agreement with clinical data concerning the observed effects of some phthalates in cases of acute exposures. Our study emphasizes the possible health effects of numerous phthalates and underlines the applicability of computational methods for predicting the biological effects of xenobiotics.

Keywords: phthalates, ADME-Tox, pharmacokinetics, biological effects

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Authors: Neil Jordan M. Uy, Fe Pelilia V. Hernandez

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A counselor is always regarded as a professional who embodies the willingness to help others through the process of counseling. He is knowledgeable and skillful of the different theories, tools, and techniques that are useful in aiding the client to cope with their dilemmas. The negative experiences of the clients that are shared during the counseling session can affect the professional counselor. Compassion fatigue, a professional impairment, is characterized by the decline of one’s productivity and the feeling of anxiety and stress brought about as the counselor empathizes, listens, and cares for others. This descriptive type of research aimed to explore variables that are predictors of compassion fatigue utilizing three research instruments; Demographic Profile Sheet, Professional Quality of Life Scale, and Neo-Pi-R. The 52 respondents of this study were counselors from the different Dominican schools in the Philippines. Generally, the counselors have low level of compassion fatigue across personal characteristics (age, gender, years of service, highest educational attainment, and professional status) and personality traits (extraversion, agreeableness, conscientiousness, openness, and neuroticism). ANOVA validated the findings of this that among the personal characteristics and personality traits, extraversion with f-value of 3.944 and p-value of 0.026, and conscientiousness, with f-value of 4.125 and p-value of 0.022 were found to have significant difference in the level of compassion fatigue. A very significant difference was observed with neuroticism with f-value of 6.878 and p-value 0.002. Among the personal characteristics and personal characteristics, only neuroticism was found to predict compassion fatigue. The computed r2 value of 0.204 using multiple regression analysis suggests that 20.4 percent of compassion fatigue can be predicted by neuroticism. The predicting power of neuroticism can be computed from the regression model Y=0.156x+26.464; where x is the number of neuroticism.

Keywords: big five personality traits, compassion fatigue, counselors, professional quality of life scale

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Authors: Sophia Shi

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Acute kidney injury (AKI) is the sudden onset of kidney damage in which the kidneys cannot filter waste from the blood, requiring emergency hospitalization. AKI patient mortality rate is high in the ICU and is virtually impossible for doctors to predict because it is so unexpected. Currently, there is no hybrid model predicting AKI that takes advantage of two types of data. De-identified patient data from the MIMIC-III database and de-identified kidney images and corresponding patient records from the Beijing Hospital of the Ministry of Health were collected. Using data features including serum creatinine among others, two numeric models using MIMIC and Beijing Hospital data were built, and with the hospital ultrasounds, an image-only model was built. Convolutional neural networks (CNN) were used, VGG and Resnet for numeric data and Resnet for image data, and they were combined into a hybrid model by concatenating feature maps of both types of models to create a new input. This input enters another CNN block and then two fully connected layers, ending in a binary output after running through Softmax and additional code. The hybrid model successfully predicted AKI and the highest AUROC of the model was 0.953, achieving an accuracy of 90% and F1-score of 0.91. This model can be implemented into urgent clinical settings such as the ICU and aid doctors by assessing the risk of AKI shortly after the patient’s admission to the ICU, so that doctors can take preventative measures and diminish mortality risks and severe kidney damage.

Keywords: Acute kidney injury, Convolutional neural network, Hybrid deep learning, Patient record data, ResNet, Ultrasound kidney images, VGG

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Authors: Marcelo Costa Cardoso, Luciano Pessanha Moreira

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In this work, the plastic behaviour of cold-rolled zinc coated dual-phase steel sheets DP600 and DP800 grades is firstly investigated with the help of uniaxial, hydraulic bulge and Forming Limit Curve (FLC) tests. The uniaxial tensile tests were performed in three angular orientations with respect to the rolling direction to evaluate the strain-hardening and plastic anisotropy. True stress-strain curves at large strains were determined from hydraulic bulge testing and fitted to a work-hardening equation. The limit strains are defined at both localized necking and fracture conditions according to Nakajima’s hemispherical punch procedure. Also, an elasto-plastic localization model is proposed in order to predict strain and stress based forming limit curves. The investigated dual-phase sheets showed a good formability in the biaxial stretching and drawing FLC regions. For both DP600 and DP800 sheets, the corresponding numerical predictions overestimated and underestimated the experimental limit strains in the biaxial stretching and drawing FLC regions, respectively. This can be attributed to the restricted failure necking condition adopted in the numerical model, which is not suitable to describe the tensile and shear fracture mechanisms in advanced high strength steels under equibiaxial and biaxial stretching conditions.

Keywords: advanced high strength steels, forming limit curve, numerical modelling, sheet metal forming

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Authors: Velázquez Alejandro, Pradhan Sujan, Yoon Rokhyun, Sanada Yasushi

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The utilization of new materials as an alternative solution to decrease the environmental impact of the construction industry has been gaining more relevance in the architectural design and construction industry. One such material is cross-laminated timber (CLT), an engineered timber solution that excels for its faster construction times, workability, lightweight, and capacity for carbon storage. This material is usually used alone for the entire structure or combined with steel frames, but a hybrid with reinforced concrete (RC) is rarer. Since RC is one of the most used materials worldwide, a hybrid with CLT would allow further utilization of the latter, and in the process, it would help reduce the environmental impact of RC construction to achieve a sustainable society, but first, the structural performance of such hybrids must be understood. This paper focuses on proposing a model to predict the seismic performance of RC frames with CLT panels as infills. A series of static horizontal cyclic loading experiments were conducted on two 40% scale specimens of reinforced concrete frames with and without CLT panels at Osaka University, Japan. An analytical model was created to simulate the seismic performance of the RC frame with CLT infill based on the experimental results. The proposed model was verified by comparing the experimental and analytical results, showing that the load-deformation relationship and the failure mechanism agreed well with limited error. Hence, the proposed analytical model can be implemented for the seismic performance evaluation of the RC frames with CLT infill.

Keywords: analytical model, multi spring, performance evaluation, reinforced concrete, rocking mechanism, wooden wall

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Authors: Hassan Gholibeigian, Kazem Gholibeigian

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In this paper, our goal is determination of loading versus time in crust. For this goal, we present a computational procedure to propose a cumulative strain energy time profile which can be used to predict the approximate location and time of the next major earthquake (M > 4.5) along a specific fault, which we believe, is more accurate than many of the methods presently in use. In the coming pages, after a short review of the research works presently going on in the area of earthquake analysis and prediction, earthquake mechanisms in both the jerk and sequence earthquake direction is discussed, then our computational procedure is presented using differential equations of equilibrium which govern the nonlinear dynamic response of a system of finite elements, modified with an extra term to account for the jerk produced during the quake. We then employ Von Mises developed model for the stress strain relationship in our calculations, modified with the addition of an extra term to account for thermal effects. For calculation of the strain energy the idea of Pulsating Mantle Hypothesis (PMH) is used. This hypothesis, in brief, states that the mantle is under diurnal cyclic pulsating loads due to unbalanced gravitational attraction of the sun and the moon. A brief discussion is done on the Denali fault as a case study. The cumulative strain energy is then graphically represented versus time. At the end, based on some hypothetic earthquake data, the final results are verified.

Keywords: pulsating mantle hypothesis, inner core’s dislocation, outer core’s bulge, constitutive model, transient hydro-magneto-thermo-mechanical load, diurnal stress, jerk, fault behaviour

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Authors: R. Khenata, T. Djied, R. Ahmed, H. Baltache, S. Bin-Omran, A. Bouhemadou

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We predict structural, phase transition as well as opto-electronic properties of the filled-tetrahedral (Nowotny-Juza) NaZnAs compound in this study. Calculations are carried out by employing the full potential (FP) linearized augmented plane wave (LAPW) plus local orbitals (lo) scheme developed within the structure of density functional theory (DFT). Exchange-correlation energy/potential (EXC/VXC) functional is treated using Perdew-Burke and Ernzerhof (PBE) parameterization for generalized gradient approximation (GGA). In addition to Trans-Blaha (TB) modified Becke-Johnson (mBJ) potential is incorporated to get better precision for optoelectronic properties. Geometry optimization is carried out to obtain the reliable results of the total energy as well as other structural parameters for each phase of NaZnAs compound. Order of the structural transitions as a function of pressure is found as: Cu2Sb type → β → α phase in our study. Our calculated electronic energy band structures for all structural phases at the level of PBE-GGA as well as mBJ potential point out; NaZnAs compound is a direct (Γ–Γ) band gap semiconductor material. However, as compared to PBE-GGA, mBJ potential approximation reproduces higher values of fundamental band gap. Regarding the optical properties, calculations of real and imaginary parts of the dielectric function, refractive index, reflectivity coefficient, absorption coefficient and energy loss-function spectra are performed over a photon energy ranging from 0.0 to 30.0 eV by polarizing incident radiation in parallel to both [100] and [001] crystalline directions.

Keywords: NaZnAs, FP-LAPW+lo, structural properties, phase transition, electronic band-structure, optical properties

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