Search results for: cumulative exposure model

Authors: Michela Del Vicario, Walter Quattrociocchi, Antonio Scala, Ana Lucía Schmidt, Fabiana Zollo

Abstract:

Information, rumors, and debates may shape and impact public opinion heavily. In the latest years, several concerns have been expressed about social influence on the Internet and the outcome that online debates might have on real-world processes. Indeed, on online social networks users tend to select information that is coherent to their system of beliefs and to form groups of like-minded people –i.e., echo chambers– where they reinforce and polarize their opinions. In this way, the potential benefits coming from the exposure to different points of view may be reduced dramatically, and individuals' views may become more and more extreme. Such a context fosters misinformation spreading, which has always represented a socio-political and economic risk. The persistence of unsubstantiated rumors –e.g., the hypothetical and hazardous link between vaccines and autism– suggests that social media do have the power to misinform, manipulate, or control public opinion. As an example, current approaches such as debunking efforts or algorithmic-driven solutions based on the reputation of the source seem to prove ineffective against collective superstition. Indeed, experimental evidence shows that confirmatory information gets accepted even when containing deliberately false claims while dissenting information is mainly ignored, influences users’ emotions negatively and may even increase group polarization. Moreover, confirmation bias has been shown to play a pivotal role in information cascades, posing serious warnings about the efficacy of current debunking efforts. Nevertheless, mitigation strategies have to be adopted. To generalize the problem and to better understand social dynamics behind information spreading, in this work we rely on a tight quantitative analysis to investigate the behavior of more than 300M users w.r.t. news consumption on Facebook over a time span of six years (2010-2015). Through a massive analysis on 920 news outlets pages, we are able to characterize the anatomy of news consumption on a global and international scale. We show that users tend to focus on a limited set of pages (selective exposure) eliciting a sharp and polarized community structure among news outlets. Moreover, we find similar patterns around the Brexit –the British referendum to leave the European Union– debate, where we observe the spontaneous emergence of two well segregated and polarized groups of users around news outlets. Our findings provide interesting insights into the determinants of polarization and the evolution of core narratives on online debating. Our main aim is to understand and map the information space on online social media by identifying non-trivial proxies for the early detection of massive informational cascades. Furthermore, by combining users traces, we are finally able to draft the main concepts and beliefs of the core narrative of an echo chamber and its related perceptions.

Keywords: information spreading, misinformation, narratives, online social networks, polarization

Procedia PDF Downloads 291

Authors: Muneeb Ullah, Daishihan, Xiadong Young

Abstract:

Deep learning plays a crucial role in identifying COVID-19 and preventing its spread. To improve the accuracy of COVID-19 diagnoses, it is important to have access to a sufficient number of training images of CXRs (chest X-rays) depicting the disease. However, there is currently a shortage of such images. To address this issue, this paper introduces COVID-19 GAN, a model that uses generative adversarial networks (GANs) to generate realistic CXR images of COVID-19, which can be used to train identification models. Initially, a generator model is created that uses digressive channels to generate images of CXR scans for COVID-19. To differentiate between real and fake disease images, an efficient discriminator is developed by combining the dense connectivity strategy and instance normalization. This approach makes use of their feature extraction capabilities on CXR hazy areas. Lastly, the deep regret gradient penalty technique is utilized to ensure stable training of the model. With the use of 4,062 grape leaf disease images, the Leaf GAN model successfully produces 8,124 COVID-19 CXR images. The COVID-19 GAN model produces COVID-19 CXR images that outperform DCGAN and WGAN in terms of the Fréchet inception distance. Experimental findings suggest that the COVID-19 GAN-generated CXR images possess noticeable haziness, offering a promising approach to address the limited training data available for COVID-19 model training. When the dataset was expanded, CNN-based classification models outperformed other models, yielding higher accuracy rates than those of the initial dataset and other augmentation techniques. Among these models, ImagNet exhibited the best recognition accuracy of 99.70% on the testing set. These findings suggest that the proposed augmentation method is a solution to address overfitting issues in disease identification and can enhance identification accuracy effectively.

Keywords: classification, deep learning, medical images, CXR, GAN.

Procedia PDF Downloads 96

Authors: Rufus Temidayo Akinnubi, M. O. Adeniyi

Abstract:

Existing diurnal air temperature models simulate night time air temperature over Nigeria with high biases. An improved parameterization is presented for modeling the diurnal pattern of air temperature (Ta) which is applicable in the calculation of turbulent heat fluxes in Global climate models, based on Nigeria Micrometeorological Experimental site (NIMEX) surface layer observations. Five diurnal Ta models for estimating hourly Ta from daily maximum, daily minimum, and daily mean air temperature were validated using root-mean-square error (RMSE), Mean Error Bias (MBE) and scatter graphs. The original Fourier series model showed better performance for unstable air temperature parameterizations while the stable Ta was strongly overestimated with a large error. The model was improved with the inclusion of the atmospheric cooling rate that accounts for the temperature inversion that occurs during the nocturnal boundary layer condition. The MBE and RMSE estimated by the modified Fourier series model reduced by 4.45 oC and 3.12 oC during the transitional period from dry to wet stable atmospheric conditions. The modified Fourier series model gave good estimation of the diurnal weather patterns of Ta when compared with other existing models for a tropical environment.

Keywords: air temperature, mean bias error, Fourier series analysis, surface energy balance,

Procedia PDF Downloads 230

Authors: M. Abbasi Layegh, S. Haghipour, K. Athari, R. Khosravi, M. Tafkikialamdari

Abstract:

An approach to find the optimum mel-frequency cepstral coefficients (MFCCs) for the Radif of Mirzâ Ábdollâh, which is the principal emblem and the heart of Persian music, performed by most famous Iranian masters on two Iranian stringed instruments ‘Tar’ and ‘Setar’ is proposed. While investigating the variance of MFCC for each record in themusic database of 1500 gushe of the repertoire belonging to 12 modal systems (dastgâh and âvâz), we have applied the Fuzzy C-Mean clustering algorithm on each of the 12 coefficient and different combinations of those coefficients. We have applied the same experiment while increasing the number of coefficients but the clustering accuracy remained the same. Therefore, we can conclude that the first 7 MFCCs (V-7MFCC) are enough for classification of The Radif of Mirzâ Ábdollâh. Classical machine learning algorithms such as MLP neural networks, K-Nearest Neighbors (KNN), Gaussian Mixture Model (GMM), Hidden Markov Model (HMM) and Support Vector Machine (SVM) have been employed. Finally, it can be realized that SVM shows a better performance in this study.

Keywords: radif of Mirzâ Ábdollâh, Gushe, mel frequency cepstral coefficients, fuzzy c-mean clustering algorithm, k-nearest neighbors (KNN), gaussian mixture model (GMM), hidden markov model (HMM), support vector machine (SVM)

Procedia PDF Downloads 446

Authors: Behnam Habibi Dargah

Abstract:

The economics of cost-benefit theory seeks to monitor claims and determine their final price. The cost of litigation is important because it is a measure of the efficiency of the justice system. From an economic point of view, the cost of litigation is considered to be the point of equilibrium of litigation, whereby litigation is regarded as a high-risk investment and is initiated when the costs are less than the probable and expected benefits. Costs are economically separated into private and social costs. Private cost includes material (direct and indirect) and spiritual costs. The social costs of litigation are also subsidized-centric due to the public and governmental nature of litigation and cover both types of bureaucratic bureaucracy and the costs of judicial misconduct. Macroeconomic policy in the economics of justice is the reverse engineering of controlling the social costs of litigation by employing selective litigation and working on the judicial culture to achieve rationality in the monopoly system. Procedures for controlling and managing court costs are also circumscribed to economic patterns in the field. Rational cost allocation model and cost transfer model. The rational allocation model deals with cost-tolerance systems, and the transfer model also considers three models of transferability, including legal, judicial and contractual transferability, which will be described and explored in the present article in a comparative manner.

Keywords: cost of litigation, economics of litigation, private cost, social cost, cost of litigation

Procedia PDF Downloads 129

Authors: Emmanuel Chinagorom Nwadike, Joseph Tagbo Nwabanne, Matthew Ndubuisi Abonyi, Onyemazu Andrew Azaka

Abstract:

This research focused on the modeling of the convective drying of aerial yam using finite element methods. The thermo-gravimetric analyzer was used to determine the thermal stability of the sample. An aerial yam sample of size 30 x 20 x 4 mm was cut with a mold designed for the purpose and dried in a convective dryer set at 4m/s fan speed and temperatures of 68.58 and 60.56°C. The volume shrinkage of the resultant dried sample was determined by immersing the sample in a toluene solution. The finite element analysis was done with PDE tools in Matlab 2015. Seven kinetic models were employed to model the drying process. The result obtained revealed three regions in the thermogravimetric analysis (TGA) profile of aerial yam. The maximum thermal degradation rates of the sample occurred at 432.7°C. The effective thermal diffusivity of the sample increased as the temperature increased from 60.56°C to 68.58°C. The finite element prediction of moisture content of aerial yam at an air temperature of 68.58°C and 60.56°C shows R² of 0.9663 and 0.9155, respectively. There was a good agreement between the finite element predicted moisture content and the measured moisture content, which is indicative of a highly reliable finite element model developed. The result also shows that the best kinetic model for the aerial yam under the given drying conditions was the Logarithmic model with a correlation coefficient of 0.9991.

Keywords: aerial yam, finite element, convective, effective, diffusivity

Procedia PDF Downloads 153

Authors: Ahmad B. Habieb, Gabriele Milani, Tavio Tavio, Federico Milani

Abstract:

Housings in developing countries have often inadequate seismic protection, particularly for masonry. People choose this type of structure since the cost and application are relatively cheap. Seismic protection of masonry remains an interesting issue among researchers. In this study, we develop a low-cost seismic isolation system for masonry using fiber reinforced elastomeric isolators. The elastomer proposed consists of few layers of rubber pads and fiber lamina, making it lower in cost comparing to the conventional isolators. We present a finite element (FE) analysis to predict the behavior of the low cost rubber isolators undergoing moderate deformations. The FE model of the elastomer involves a hyperelastic material property for the rubber pad. We adopt a Yeoh hyperelasticity model and estimate its coefficients through the available experimental data. Having the shear behavior of the elastomers, we apply that isolation system onto small masonry housing. To attach the isolators on the building, we model the shear behavior of the isolation system by means of a damped nonlinear spring model. By this attempt, the FE analysis becomes computationally inexpensive. Several ground motion data are applied to observe its sensitivity. Roof acceleration and tensile damage of walls become the parameters to evaluate the performance of the isolators. In this study, a concrete damage plasticity model is used to model masonry in the nonlinear range. This tool is available in the standard package of Abaqus FE software. Finally, the results show that the low-cost isolators proposed are capable of reducing roof acceleration and damage level of masonry housing. Through this study, we are also capable of monitoring the shear deformation of isolators during seismic motion. It is useful to determine whether the isolator is applicable. According to the results, the deformations of isolators on the benchmark one story building are relatively small.

Keywords: masonry, low cost elastomeric isolator, finite element analysis, hyperelasticity, damped non-linear spring, concrete damage plasticity

Procedia PDF Downloads 286

Authors: Yufen Qin

Abstract:

Topic-to-Essay generation is a challenging task in Natural language processing, which aims to generate novel, diverse, and topic-related text based on user input. Previous research has overlooked the generation of articles under the constraints of event elements, resulting in issues such as incomplete event elements and logical inconsistencies in the generated results. To fill this gap, this paper proposes an event-constrained approach for a topic-to-essay generation that enforces the completeness of event elements during the generation process. Additionally, a language model is employed to verify the logical consistency of the generated results. Experimental results demonstrate that the proposed model achieves a better BLEU-2 score and performs better than the baseline in terms of subjective evaluation on a real dataset, indicating its capability to generate higher-quality topic-related text.

Keywords: event element, language model, natural language processing, topic-to-essay generation.

Procedia PDF Downloads 236

Authors: Sungjun Hong, Youah Lee, Jongwook Kim

Abstract:

In the last COP21 held in Paris on 2015, Korean government announced that Intended Nationally Determined Contributions (INDC) was 37% based on BAU by 2030. The GHG reduction rate of the transportation sector is the strongest among all sectors by 2020. In order to cope with Korean INDC, Korean government established that 3rd eco-friendly car deployment national plans at the end of 2015. In this study, we make the energy system model for estimating GHG emissions using LEAP model.

Keywords: INDC, greenhouse gas, LEAP, transportation

Procedia PDF Downloads 205

Authors: Kim Bower

Abstract:

Evaluating and researching motivation in language learning is a complex and multi-faceted activity. Various models for investigating learner motivation have been proposed in the literature, but no one model supplies a complex and coherent model for investigating a range of motivational characteristics. Here, such a methodological framework, which includes exemplification of sources of evidence and potential methods of investigation, is proposed. The process model for the investigation of motivation within language learning settings proposed is based on a complex dynamic systems perspective that takes account of cognition and affects. It focuses on three overarching aspects of motivation: the learning environment, learner engagement and learner identities. Within these categories subsets are defined: the learning environment incorporates teacher, course and group specific aspects of motivation; learner engagement addresses the principal characteristics of learners' perceived value of activities, their attitudes towards language learning, their perceptions of their learning and engagement in learning tasks; and within learner identities, principal characteristics of self-concept and mastery of the language are explored. Exemplifications of potential sources of evidence in the model reflect the multiple influences within and between learner and environmental factors and the possible changes in both that may emerge over time. The model was initially developed as a framework for investigating different models of Content and Language Integrated Learning (CLIL) in contrasting contexts in secondary schools in England. The study, from which examples are drawn to exemplify the model, aimed to address the following three research questions: (1) in what ways does CLIL impact on learner motivation? (2) what are the main elements of CLIL that enhance motivation? and (3) to what extent might these be transferable to other contexts? This new model has been tried and tested in three locations in England and reported as case studies. Following an initial visit to each institution to discuss the qualitative research, instruments were developed according to the proposed model. A questionnaire was drawn up and completed by one group prior to a 3-day data collection visit to each institution, during which interviews were held with academic leaders, the head of the department, the CLIL teacher(s), and two learner focus groups of six-eight learners. Interviews were recorded and transcribed verbatim. 2-4 naturalistic observations of lessons were undertaken in each setting, as appropriate to the context, to provide colour and thereby a richer picture. Findings were subjected to an interpretive analysis by the themes derived from the process model and are reported elsewhere. The model proved to be an effective and coherent framework for planning the research, instrument design, data collection and interpretive analysis of data in these three contrasting settings, in which different models of language learning were in place. It is hoped that the proposed model, reported here together with exemplification and commentary, will enable teachers and researchers in a wide range of language learning contexts to investigate learner motivation in a systematic and in-depth manner.

Keywords: investigate, language-learning, learner motivation model, dynamic systems perspective

Procedia PDF Downloads 269

Authors: Katarina Lazarević, Mirjana Todosijević, Tijana Vulević, Natalija Momirović, Ranka Erić

Abstract:

Due to increasing demand, climate change, and world population growth, natural resources are getting exploit fast. One of the most important natural resources is soil, which is susceptible to degradation. Erosion as one of the forms of land degradation is also one of the most global environmental problems. Ecosystem services are often defined as benefits that nature provides to humankind. Soil, as the foundation of basic ecosystem functions, provides benefits to people, erosion control, water infiltration, food, fuel, fibers… This research is using the ecosystem approach as a strategy for natural resources management for promoting sustainability and conservation. The research was done on the Topčiderska River basin (Belgrade, Serbia). The InVEST Sediment Delivery Ratio model was used, to quantify erosion intensity with a spatial distribution output map of overland sediment generation and delivery to the stream. InVEST SDR, a spatially explicit model, is using a method based on the concept of hydrological connectivity and (R) USLE model. This, combined with socio-economic and law and policy analysis, gives a full set of information to decision-makers helping them to successfully manage and deliver sustainable ecosystems.

Keywords: ecosystem services, InVEST model, soil erosion, sustainability

Procedia PDF Downloads 141

Authors: K. S. Poutanen, P. Dussort, A. Erkner, S. Fiszman, K. Karnik, M. Kristensen, C. F. M. Marsaux, S. Miquel-Kergoat, S. Pentikäinen, P. Putz, R. E. Steinert, J. Slavin, D. J. Mela

Abstract:

Dietary fiber (DF) intake has been associated with lower body weight or less weight gain. These effects are generally attributed to putative effects of DF on appetite. Many intervention studies have tested the effect of DFs on appetite-related measures, with inconsistent results. However, DF includes a wide category of different compounds with diverse chemical and physical characteristics, and correspondingly diverse effects in human digestion. Thus, inconsistent results between DF consumption and appetite are not surprising. The specific contribution of different compounds with varying physico-chemical properties to appetite control and the mediating mechanisms are not well characterized. This systematic review aimed to assess the influence of specific DF characteristics, including viscosity, gel forming capacity, fermentability, and molecular weight, on appetite-related outcomes in healthy humans. Medline and FSTA databases were searched for controlled human intervention trials, testing the effects of well-characterized DFs on subjective satiety/appetite or energy intake outcomes. Studies were included only if they reported: 1) fiber name and origin, and 2) data on viscosity, gelling properties, fermentability, or molecular weight of the DF materials tested. The search generated 3001 unique records, 322 of which were selected for further consideration from title and abstract screening. Of these, 149 were excluded due to insufficient fiber characterization and 124 for other reasons (not original article, not randomized controlled trial, or no appetite related outcome), leaving 49 papers meeting all the inclusion criteria, most of which reported results from acute testing (<1 day). The eligible 49 papers described 90 comparisons of DFs in foods, beverages or supplements. DF-containing material of interest was efficacious for at least one appetite-related outcome in 51/90 comparisons. Gel-forming DF sources were most consistently efficacious but there were no clear associations between viscosity, MW or fermentability and appetite-related outcomes. A considerable number of papers had to be excluded from the review due to shortcomings in fiber characterization. To build understanding about the impact of DF on satiety/appetite specifically there should be clear hypotheses about the mechanisms behind the proposed beneficial effect of DF material on appetite, and sufficient data about the DF properties relevant for the hypothesized mechanisms to justify clinical testing. The hypothesized mechanisms should also guide the decision about relevant duration of exposure in studies, i.e. are the effects expected to occur during acute time frame (related to stomach emptying, digestion rate, etc.) or develop from sustained exposure (gut fermentation mediated mechanisms). More consistent measurement methods and reporting of fiber specifications and characterization are needed to establish reliable structure-function relationships for DF and health outcomes.

Keywords: appetite, dietary fiber, physico-chemical properties, satiety

Procedia PDF Downloads 235

Authors: Mokhtar Labiod, Nabil Ikhlef, Keltoum Bouherine, Olivier Leroy

Abstract:

A numerical model for the radio-frequency (RF) Argon discharge chamber is developed to simulate the low pressure low temperature inductively coupled plasma. This model will be of fundamental importance in the design of the plasma magnetic control system. Electric and magnetic fields inside the discharge chamber are evaluated by solving a magnetic vector potential equation. To start with, the equations of the ideal magnetohydrodynamics theory will be presented describing the basic behaviour of magnetically confined plasma and equations are discretized with finite element method in cylindrical coordinates. The discharge chamber is assumed to be axially symmetric and the plasma is treated as a compressible gas. Plasma generation due to ionization is added to the continuity equation. Magnetic vector potential equation is solved for the electromagnetic fields. A strong dependence of the plasma properties on the discharge conditions and the gas temperature is obtained.

Keywords: direct-coupled model, magnetohydrodynamic, modelling, plasma torch simulation

Procedia PDF Downloads 434

Authors: Yoonjung An, Yongtae Park

Abstract:

Knowledge flows are a critical source of faster technological progress and stouter economic growth. Knowledge flows have been accelerated dramatically with the establishment of a patent system in which each patent is required by law to disclose sufficient technical information for the invention to be recreated. Patent analysis, thus, has been widely used to help investigate technological knowledge flows. However, the existing research is limited in terms of both subject and approach. Particularly, in most of the previous studies, business method (BM) patents were not covered although they are important drivers of knowledge flows as other patents. In addition, these studies usually focus on the static analysis of knowledge flows. Some use approaches that incorporate the time dimension, yet they still fail to trace a true dynamic process of knowledge flows. Therefore, we investigate dynamic patterns of knowledge flows driven by BM patents using a Hidden Markov Model (HMM). An HMM is a popular statistical tool for modeling a wide range of time series data, with no general theoretical limit in regard to statistical pattern classification. Accordingly, it enables characterizing knowledge patterns that may differ by patent, sector, country and so on. We run the model in sets of backward citations and forward citations to compare the patterns of knowledge utilization and knowledge dissemination.

Keywords: business method patents, dynamic pattern, Hidden-Markov Model, knowledge flow

Procedia PDF Downloads 328

Authors: Asim Majeed, Rehan Bhana, Mak Sharma, Rebecca Goode, Nizam Bolia, Mike Lloyd-Williams

Abstract:

This study aims to investigate and explore the underlying causes of security concerns of customers emerged when WHSmith transformed its physical system to virtualized business model through NetSuite. NetSuite is essentially fully integrated software which helps transforming the physical system to virtualized business model. Modern organisations are moving away from traditional business models to cloud based models and consequently it is expected to have a better, secure and innovative environment for customers. The vital issue of the modern age race is the security when transforming virtualized through cloud based models and designers of interactive systems often misunderstand privacy and even often ignore it, thus causing concerns for users. The content analysis approach is being used to collect the qualitative data from 120 online bloggers including TRUSTPILOT. The results and finding provide useful new insights into the nature and form of security concerns of online users after they have used the WHSmith services offered online through their website. Findings have theoretical as well as practical implications for the successful adoption of cloud computing Business-to-Business model and similar systems.

Keywords: innovation, virtualization, cloud computing, organizational flexibility

Procedia PDF Downloads 384

Authors: Ansari Mohammad Reza, Hiroko Ono

Abstract:

In this study, we investigated how much of the urban facilities are fairly distributing in the city of Kabul based on the factor of population. To find the answer to this question we simulated a fair model for the distribution of investigated facilities in the city which is proposed based on the consideration of two factors; the number of users for each facility and the average distance of reach of each facility. Then the model was evaluated to make sure about its efficiency. And finally, the two—the existing pattern and the simulation model—were compared to find the degree of bias in the existing pattern of distribution of facilities in the city. The result of the study clearly clarified that the facilities are not fairly distributed in Kabul city based on the factor of population. Our analysis also revealed that the education services and the parks are the most and the worst fair distributed facilities in this regard.

Keywords: Afghanistan, ArcGIS Software, Kabul City, fair distribution, urban facilities

Procedia PDF Downloads 179

Authors: Ma. Gracia Corazon Cayanan, Kai Yuen Cheong, Li Sha

Abstract:

Training a language model for a minority language has been a challenging task. The lack of available corpora to train and fine-tune state-of-the-art language models is still a challenge in the area of Natural Language Processing (NLP). Moreover, the need for high computational resources and bulk data limit the attainment of this task. In this paper, we presented the following contributions: (1) we introduce and used a translation pair set of Tagalog and English (TL-EN) in pre-training a language model to a minority language resource; (2) we fine-tuned and evaluated top-ranking and pre-trained semantic textual similarity binary task (STSB) models, to both TL-EN and STS dataset pairs. (3) then, we reduced the size of the model to offset the need for high computational resources. Based on our results, the models that were pre-trained to translation pairs and STS pairs can perform well for STSB task. Also, having it reduced to a smaller dimension has no negative effect on the performance but rather has a notable increase on the similarity scores. Moreover, models that were pre-trained to a similar dataset have a tremendous effect on the model’s performance scores.

Keywords: semantic matching, semantic textual similarity binary task, low resource minority language, fine-tuning, dimension reduction, transformer models

Procedia PDF Downloads 211

Authors: Amani A. Saad, Ahmed A. El-Farag, El-Sayed A. Helali

Abstract:

Cloud computing is an important and promising field in the recent decade. Cloud computing allows sharing resources, services and information among the people of the whole world. Although the advantages of using clouds are great, but there are many risks in a cloud. The data security is the most important and critical problem of cloud computing. In this research a new security model for cloud computing is proposed for ensuring secure communication system, hiding information from other users and saving the user's times. In this proposed model Blowfish encryption algorithm is used for exchanging information or data, and SHA-2 cryptographic hash algorithm is used for data integrity. For user authentication process a simple user-name and password is used, the password uses SHA-2 for one way encryption. The proposed system shows an improvement of the processing time of uploading and downloading files on the cloud in secure form.

Keywords: cloud computing, data security, SAAS, PAAS, IAAS, Blowfish

Procedia PDF Downloads 359

Authors: K. H. Oyuntungalag, Scott Kenner, O. Erdenetuya

Abstract:

The life cycle phases of mining projects are described in this guidance document, and includes initial phases (exploration, feasibility and planning), mine development (construction and operations), closure and reclamation. Initial phases relate to field programs and desktop studies intended to build the data and knowledge base, including the design of water management infrastructure and development during these initial phases. Such a model is essential to demonstrate that the water management plan (WMP) will provide adequate water for the mine operations and sufficient capacity for anticipated flows and volumes, and minimize environmental impacts on the receiving environment. The water and mass balance model must cover the whole mine life cycle, from the start of mine development to a date sufficiently far in the future where the reclaimed landscape is considered self- sustaining following complete closure of the mine (i.e., post- closure). The model simulates the movement of water within the components of the water management infrastructure and project operating areas, and calculates chemical loadings to each mine component. At Erdenet Mining company an initial water balance model reflecting the tailings dam, groundwater seepage and mine process water was developed in collaboration with Dr. Scott Kenner (visiting Fulbright scholar). From this preliminary study the following recommendations were made: 1. Develop a detailed groundwater model to simulate seepage from the tailings dam, 2. Establish an evaporation pan for improving evapotranspiration estimates, and 3. Measure changes in storage of water within the tailings dam and other water storage components within the mine processing.

Keywords: evapotranspiration , monitoring program, Erdenet mining, tailings dam

Procedia PDF Downloads 477

Authors: T. C. Bera, A. Bansal, D. Nema

Abstract:

During performing turning operation, cutting force plays a significant role in metal cutting process affecting tool-work piece deflection, vibration and eventually part quality. The present research work aims to develop a mechanistic cutting force model and to study the mechanistic constants used in the force model in case of turning operation. The proposed model can be used for the reliable and accurate estimation of the cutting forces establishing relationship of various force components (cutting force and feed force) with uncut chip thickness. The accurate estimation of cutting force is required to improve thin-walled part accuracy by controlling the tool-work piece deflection induced surface errors and tool-work piece vibration.

Keywords: turning, cutting forces, cutting constants, uncut chip thickness

Procedia PDF Downloads 522

Authors: Jeetendra Yadav, Geetha Menon, Anita Pal, Rajkumar Verma

Abstract:

Even after encouraging maternal and child wellness programs at worldwide level, lower-middle income nations are not reached the goal set by the UN yet. This study quantified the contribution of socioeconomic determinants of inequality to the utilization of Antenatal Care in South Asian Countries. This study used data from Demographic Health Survey (DHS) of the selected countries were used, and Oaxaca decomposing were applied for socioeconomic inequalities in utilization of antenatal care. Finding from the multivariate analysis shows that mother’s age at the time of birth, birth order and interval, mother’s education, mass media exposure and economic status were significant determinants of the utilization of antenatal care services in South Asian countries. Considering, concentration index curve, the line of equity was greatest in Pakistan which followed by India and Nepal.

Keywords: antenatal care, decomposition, inequalities, South Asian countries

Procedia PDF Downloads 183

Authors: Gulshan Sachdeva, Vaibhav Jain, S. S. Kachhwaha

Abstract:

Cascade refrigeration systems employ series of single stage vapor compression units which are thermally coupled with evaporator/condenser cascades. Different refrigerants are used in each of the circuit depending on the optimum characteristics shown by the refrigerant for a particular application. In the present research study, a steady state thermodynamic model is developed which simulates the working of an actual cascade system. The model provides COP and all other system parameters like total compressor work, temperature, pressure, enthalpy and entropy at different state points. The working fluid in Low Temperature Circuit (LTC) is CO2 (R744) while ammonia (R717), propane (R290), propylene (R1270), R404A and R12 are the refrigerants in High Temperature Circuit (HTC). The performance curves of ammonia, propane, propylene, and R404A are compared with R12 to find its nearest substitute. Results show that ammonia is the best substitute of R12.

Keywords: cascade system, refrigerants, thermodynamic model, production engineering

Procedia PDF Downloads 361

Authors: Atiqa Marium

Abstract:

In 2015, all 193 UN Member countries adopted the 2030 Agenda for Sustainable Development, which is an ambitious 15- year plan to address some of the most pressing issues the world faces. Goal 4 is about Quality Education which highlights the importance of inclusive and quality education for sustainable development. Sustainable Development Goal 10 focuses on reducing inequalities within and among countries. In June 2019, Federal Government in Canada released “Towards Canada’s 2030 Agenda National Strategy”, which was an important step to move the 2030 Agenda forward. In April 2019, the Ontario government announced the performance-based funding model for publically assisted colleges and universities in Ontario, which is now part of the universities’ budget 2024-2025. The literature review has shown that the funding model has been implemented by different governments to achieve objectives. However, this model has also resulted in conflicting consequences like reducing university autonomy, education quality/ academic standards, and increased equity concerns. The primary focus of this paper will be to analyze the tensions and coherence between the proposed funding model for education for sustainable development goals and targets set by Canada’s 2030 Agenda National Strategy. Considering that the literature review has provided evidence that the performance-based funding model has resulted in reducing quality of education and increased equity issues in other countries, it will be interesting to see how this proposed funding will align with the SDGs of “Quality Education” and “Reduced Inequalities”. This paper will be well-suited for Volume 4, with the theme of re-visioning institutional impact and sustainability. This paper will underscore the importance of policy coherence between federal and provincial policies for higher education institutions in Ontario for better institutional impact and helping universities in the attainment of goals set in 2030 Agenda towards education for sustainable development.

Keywords: performance-based funding model, education for sustainable development, policy coherence, sustainable development gaols

Procedia PDF Downloads 116

Authors: Bokkasam Sasidhar, Ibrahim Aljasser

Abstract:

The problem of finding optimal schedules for each equipment in a production process is considered, which consists of a single stage of manufacturing and which can handle different types of products, where changeover for handling one type of product to the other type incurs certain costs. The machine capacity is determined by the upper limit for the quantity that can be processed for each of the products in a set up. The changeover costs increase with the number of set ups and hence to minimize the costs associated with the product changeover, the planning should be such that similar types of products should be processed successively so that the total number of changeovers and in turn the associated set up costs are minimized. The problem of cost minimization is equivalent to the problem of minimizing the number of set ups or equivalently maximizing the capacity utilization in between every set up or maximizing the total capacity utilization. Further, the production is usually planned against customers’ orders, and generally different customers’ orders are assigned one of the two priorities – “normal” or “priority” order. The problem of production planning in such a situation can be formulated into a Multiple Arc Network (MAN) model and can be solved sequentially using the algorithm for maximizing flow along a MAN and the algorithm for maximizing flow along a MAN with priority arcs. The model aims to provide optimal production schedule with an objective of maximizing capacity utilization, so that the customer-wise delivery schedules are fulfilled, keeping in view the customer priorities. Algorithms have been presented for solving the MAN formulation of the production planning with customer priorities. The application of the model is demonstrated through numerical examples.

Keywords: scheduling, maximal flow problem, multiple arc network model, optimization

Procedia PDF Downloads 402

Authors: Xiaocong Liu, Huazhen Wang, Ting He, Xiaozheng Li, Weihan Zhang, Jian Chen

Abstract:

The utilization of electronic medical record (EMR) data to establish the disease diagnosis model has become an important research content of biomedical informatics. Deep learning can automatically extract features from the massive data, which brings about breakthroughs in the study of EMR data. The challenge is that deep learning lacks semantic knowledge, which leads to impracticability in medical science. This research proposes a method of incorporating lexical-semantic knowledge from abundant entities into a convolutional neural network (CNN) framework for pediatric disease diagnosis. Firstly, medical terms are vectorized into Lexical Semantic Vectors (LSV), which are concatenated with the embedded word vectors of word2vec to enrich the feature representation. Secondly, the semantic distribution of medical terms serves as Semantic Decision Guide (SDG) for the optimization of deep learning models. The study evaluate the performance of LSV-SDG-CNN model on four kinds of Chinese EMR datasets. Additionally, CNN, LSV-CNN, and SDG-CNN are designed as baseline models for comparison. The experimental results show that LSV-SDG-CNN model outperforms baseline models on four kinds of Chinese EMR datasets. The best configuration of the model yielded an F1 score of 86.20%. The results clearly demonstrate that CNN has been effectively guided and optimized by lexical-semantic knowledge, and LSV-SDG-CNN model improves the disease classification accuracy with a clear margin.

Keywords: convolutional neural network, electronic medical record, feature representation, lexical semantics, semantic decision

Procedia PDF Downloads 126

Authors: Min-Woo Kim, Ok-Kyun Na, Jun-Ho Byun, Jong-Hwan Park, Seung-Hwa Yang, Joon-Hong Park, Young-Chul Park

Abstract:

This study is focused on the comparative analysis and improvement to grasp the flow characteristic of the Anti-Splash Device located under the P/V Valve and new concept design models using the CFD analysis and Artificial Neural Network. The P/V valve located upper deck to solve the pressure rising and vacuum condition of inner tank of the liquid cargo ships occurred oil outflow accident by transverse and longitudinal sloshing force. Anti-Splash Device is fitted to improve and prevent this problem in the shipbuilding industry. But the oil outflow accidents are still reported by ship owners. Thus, four types of new design model are presented by study. Then, comparative analysis is conducted with new models and existing model. Mostly the key criterion of this problem is flux in the outlet of the Anti-Splash Device. Therefore, the flow and velocity are grasped by transient analysis. And then it decided optimum model and design parameters to develop model. Later, it needs to develop an Anti-Splash Device by Flow Test to get certification and verification using experiment equipment.

Keywords: anti-splash device, P/V valve, sloshing, artificial neural network

Procedia PDF Downloads 590

Authors: Ahmad Odeh

Abstract:

Researchers are currently more concerned about the calculations of energy at the operational stage, mainly due to its larger environmental impact, but the fact remains, embodied energies represent a substantial contributor unaccounted for in the overall energy computation method. The calculation of materials’ embodied energy during the construction stage is complicated. This is due to the various factors involved. The equipment used, fuel needed, and electricity required for each type of materials varies with location and thus the embodied energy will differ for each project. Moreover, the method used in manufacturing, transporting and putting in place will have significant influence on the materials’ embodied energy. This anomaly has made it difficult to calculate or even bench mark the usage of such energies. This paper presents a model aimed at calculating embodied energies based on such variabilities. It presents a systematic approach that uses an efficient method of calculation to provide a new insight for the selection of construction materials. The model is developed in a BIM environment. The quantification of materials’ energy is determined over the three main stages of their lifecycle: manufacturing, transporting and placing. The model uses three major databases each of which contains set of the construction materials that are most commonly used in building projects. The first dataset holds information about the energy required to manufacture any type of materials, the second includes information about the energy required for transporting the materials while the third stores information about the energy required by machinery to place the materials in their intended locations. Through geospatial data analysis, the model automatically calculates the distances between the suppliers and construction sites and then uses dataset information for energy computations. The computational sum of all the energies is automatically calculated and then the model provides designers with a list of usable equipment along with the associated embodied energies.

Keywords: BIM, lifecycle energy assessment, building automation, energy conservation

Procedia PDF Downloads 189

Authors: Bengi Demirci

Abstract:

Out-of-pocket payments have become one of the common models adopted by health care reforms all over the world, and they have serious implications for not only the financial set-up of the health care systems in question but also for the people involved in terms of their access to the health care services provided. On the one hand, out-of-pocket payments are used in raising resources for the finance of the health care system and in decreasing non-essential health care expenses by having a deterrent role on the patients. On the other hand, out-of-pocket payment model causes regressive distribution effect by putting more burdens on the lower income groups and making them refrain from using health care services. Being a relatively incipient country having adopted the out-of-pocket payment model within the context of its Health Transformation Program which has been ongoing since the early 2000s, Turkey provides a good case for re-evaluating the pros and cons of this model in order not to sacrifice equality in access to health care for raising revenue for health care finance and vice versa. Therefore this study aims at analyzing the impact of out-of-pocket payments on the health finance system itself and on the patients’ access to healthcare services in Turkey where out-of-pocket payment model has been in use for a while. In so doing, data showing the revenue obtained from out-of-pocket payments and their share in health care finance are analyzed. In addition to this, data showing the change in the amount of expenditure made by patients on health care services after the adoption of out-of-pocket payments and the change in the use of various health care services in the meanwhile are examined. It is important for the incipient countries like Turkey to be careful in striking the right balance between the objective of cost efficiency and that of equality in accessing health care services while adopting the out-of-pocket payment model.

Keywords: health care access, health care finance, health reform, out-of-pocket payments

Procedia PDF Downloads 372

Authors: Sarah Elshahat, Tina Moffat

Abstract:

Suboptimal mental health is a considerable global public health challenge that leads to considerable inequalities worldwide. Newcomers are at elevated risk for developing mental health issues as a result of social exclusion, stigmatization, racism, unequal employment opportunities, and discrimination. The problem can be especially serious amongst Arabic-speaking immigrants and refugees (ASIR) whose mental wellness may have already been affected by exposure to political violence, persecution, hunger or war in their countries of origin. A scoping review was conducted to investigate pre- and post-migration mental health determinants amongst ASIR in North America (the U.S. and Canada), who are a rapidly growing population in both regions. Pertinent peer-reviewed papers and grey literature were located through a systematic search of five electronic databases (Medline, Embase, PsycINFO, Anthropology Plus, and Sociology Database). A stakeholder consultation was implemented to validate the analyzed findings of the included 44 studies. About 80% of the studies were carried out in the US, underscoring a lack of Canadian ASIR-mental health research. A gap in qualitative, mixed-method, and longitudinal research was detected, where approximately two-thirds of the studies adopted a cross-sectional method. Pre-migration determinants of mental health were related to the political unrest, violence and armed conflict in the Arab world, increasing post-traumatic stress disorder and psychological distress levels among ASIR. English language illiteracy and generational variations in acculturation patterns were major post-migration mental health triggering factors. Exposure to domestic violence, stigmatization, poverty, racialization, and harassment were significant post-migration mental health determinants that stem from social inequalities, triggering depression, and distress amongst ASIR. Family conflicts linked to child-rearing and gendered norms were considered as both pre- and post-migration mental health triggering factors. Most post-migration mental health protective factors were socio-culturally related and included the maintenance of positive ethnic identity, faith, family support, and community cohesion. Individual resilience, articulated as self-esteem and hope, was a significant negative predictor of depression and psychological distress among ASIR. Community-engaged, mixed-methods, and longitudinal studies are required to address the current gap in mental health research among ASIR in North America. A more thorough determination of potential mental health triggers and protective factors would help inform the development of mental wellness and resilience-promoting programs that are culturally sensitive to ASIR. On the policy level, the Health in All Policies framework of the World Health Organization can be potentially useful for addressing social and health inequalities among ASIR, reducing mental health challenges.

Keywords: depression, post-traumatic stress disorder, psychological distress, resilience

Procedia PDF Downloads 136

Authors: Chaiyaset Promsri

Abstract:

Based on the synthesis of related literatures, this research found thirteen related dimensions that involved the development of natural disaster preparedness awareness including hazard knowledge, hazard attitude, training for disaster preparedness, rehearsal and practice for disaster preparedness, cultural development for preparedness, public relations and communication, storytelling, disaster awareness game, simulation, past experience to natural disaster, information sharing with family members, and commitment to the community (time of living).  The 40-item of natural disaster preparedness awareness questionnaire was developed based on these thirteen dimensions. Data were collected from 595 participants in Bangkok metropolitan and vicinity. Cronbach's alpha was used to examine the internal consistency for this instrument. Reliability coefficient was 97, which was highly acceptable.  Exploratory Factor Analysis where principal axis factor analysis was employed. The Kaiser-Meyer-Olkin index of sampling adequacy was .973, indicating that the data represented a homogeneous collection of variables suitable for factor analysis. Bartlett's test of Sphericity was significant for the sample as Chi-Square = 23168.657, df = 780, and p-value < .0001, which indicated that the set of correlations in the correlation matrix was significantly different and acceptable for utilizing EFA. Factor extraction was done to determine the number of factors by using principal component analysis and varimax.  The result revealed that four factors had Eigen value greater than 1 with more than 60% cumulative of variance. Factor #1 had Eigen value of 22.270, and factor loadings ranged from 0.626-0.760. This factor was named as "Knowledge and Attitude of Natural Disaster Preparedness".  Factor #2 had Eigen value of 2.491, and factor loadings ranged from 0.596-0.696. This factor was named as "Training and Development". Factor #3 had Eigen value of 1.821, and factor loadings ranged from 0.643-0.777. This factor was named as "Building Experiences about Disaster Preparedness".  Factor #4 had Eigen value of 1.365, and factor loadings ranged from 0.657-0.760. This was named as "Family and Community". The results of this study provided support for the reliability and construct validity of natural disaster preparedness awareness for utilizing with populations similar to sample employed.

Keywords: natural disaster, disaster preparedness, disaster awareness, Thai citizens

Procedia PDF Downloads 378