Search results for: coupled DPM and VOF model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 17960

Search results for: coupled DPM and VOF model

14360 Exploring Disruptive Innovation Capacity Effects on Firm Performance: An Investigation in Industries 4.0

Authors: Selma R. Oliveira, E. W. Cazarini

Abstract:

Recently, studies have referenced innovation as a key factor affecting the performance of firms. Companies make use of its innovative capacities to achieve sustainable competitive advantage. In this perspective, the objective of this paper is to contribute to innovation planning policies in industry 4.0. Thus, this paper examines the disruptive innovation capacity on firm performance in Europe. This procedure was prepared according to the following phases: Phase 1: Determination of the conceptual model; and Phase 2: Verification of the conceptual model. The research was initially conducted based on the specialized literature, which extracted the data regarding the constructs/structure and content in order to build the model. The research involved the intervention of experts knowledgeable on the object studied, selected by technical-scientific criteria. The data were extracted using an assessment matrix. To reduce subjectivity in the results achieved the following methods were used complementarily and in combination: multicriteria analysis, multivariate analysis, psychometric scaling and neurofuzzy technology. The data were extracted using an assessment matrix and the results were satisfactory, validating the modeling approach.

Keywords: disruptive innovation, capacity, performance, Industry 4.0

Procedia PDF Downloads 168
14359 Fault Analysis of Induction Machine Using Finite Element Method (FEM)

Authors: Wiem Zaabi, Yemna Bensalem, Hafedh Trabelsi

Abstract:

The paper presents a finite element (FE) based efficient analysis procedure for induction machine (IM). The FE formulation approaches are proposed to achieve this goal: the magnetostatic and the non-linear transient time stepped formulations. The study based on finite element models offers much more information on the phenomena characterizing the operation of electrical machines than the classical analytical models. This explains the increase of the interest for the finite element investigations in electrical machines. Based on finite element models, this paper studies the influence of the stator and the rotor faults on the behavior of the IM. In this work, a simple dynamic model for an IM with inter-turn winding fault and a broken bar fault is presented. This fault model is used to study the IM under various fault conditions and severity. The simulation results are conducted to validate the fault model for different levels of fault severity. The comparison of the results obtained by simulation tests allowed verifying the precision of the proposed FEM model. This paper presents a technical method based on Fast Fourier Transform (FFT) analysis of stator current and electromagnetic torque to detect the faults of broken rotor bar. The technique used and the obtained results show clearly the possibility of extracting signatures to detect and locate faults.

Keywords: Finite element Method (FEM), Induction motor (IM), short-circuit fault, broken rotor bar, Fast Fourier Transform (FFT) analysis

Procedia PDF Downloads 305
14358 Additive Manufacturing – Application to Next Generation Structured Packing (SpiroPak)

Authors: Biao Sun, Tejas Bhatelia, Vishnu Pareek, Ranjeet Utikar, Moses Tadé

Abstract:

Additive manufacturing (AM), commonly known as 3D printing, with the continuing advances in parallel processing and computational modeling, has created a paradigm shift (with significant radical thinking) in the design and operation of chemical processing plants, especially LNG plants. With the rising energy demands, environmental pressures, and economic challenges, there is a continuing industrial need for disruptive technologies such as AM, which possess capabilities that can drastically reduce the cost of manufacturing and operations of chemical processing plants in the future. However, the continuing challenge for 3D printing is its lack of adaptability in re-designing the process plant equipment coupled with the non-existent theory or models that could assist in selecting the optimal candidates out of the countless potential fabrications that are possible using AM. One of the most common packings used in the LNG process is structured packing in the packed column (which is a unit operation) in the process. In this work, we present an example of an optimum strategy for the application of AM to this important unit operation. Packed columns use a packing material through which the gas phase passes and comes into contact with the liquid phase flowing over the packing, typically performing the necessary mass transfer to enrich the products, etc. Structured packing consists of stacks of corrugated sheets, typically inclined between 40-70° from the plane. Computational Fluid Dynamics (CFD) was used to test and model various geometries to study the governing hydrodynamic characteristics. The results demonstrate that the costly iterative experimental process can be minimized. Furthermore, they also improve the understanding of the fundamental physics of the system at the multiscale level. SpiroPak, patented by Curtin University, represents an innovative structured packing solution currently at a technology readiness level (TRL) of 5~6. This packing exhibits remarkable characteristics, offering a substantial increase in surface area while significantly enhancing hydrodynamic and mass transfer performance. Recent studies have revealed that SpiroPak can reduce pressure drop by 50~70% compared to commonly used commercial packings, and it can achieve 20~50% greater mass transfer efficiency (particularly in CO2 absorption applications). The implementation of SpiroPak has the potential to reduce the overall size of columns and decrease power consumption, resulting in cost savings for both capital expenditure (CAPEX) and operational expenditure (OPEX) when applied to retrofitting existing systems or incorporated into new processes. Furthermore, pilot to large-scale tests is currently underway to further advance and refine this technology.

Keywords: Additive Manufacturing (AM), 3D printing, Computational Fluid Dynamics (CFD, structured packing (SpiroPak)

Procedia PDF Downloads 96
14357 The Turkish Anti-Nuclear Platform: A Counter-Hegemonic Struggle

Authors: Sevgi Balkan-Sahin

Abstract:

The Justice and Development Party (AKP) government has included nuclear power as a major component of Turkey’s new energy strategy by promoting it as the only alternative for Turkey to diversify energy resources, trigger economic growth, and boost competitiveness of the country. The effective promotion of such a framing has created a hegemonic discourse around nuclear energy in Turkey. However, fiercely opposing the nuclear initiative of the government, the Turkish anti-nuclear platform (ANP) composed of more than 50 civil society groups has challenged the hegemonic discourse of the AKP government by presenting nuclear energy as dangerous for human health, human rights, and the protection of environment. Based on an engagement between Gramscian perspective and Laclau and Mouffe’s discourse theory, this paper considers the discourses of the Turkish anti-nuclear platform and its associated activities as a counter-hegemonic strategy to change the ‘common sense’ on nuclear energy in Turkey. Analyzing the data from interviews with the representatives of the anti-nuclear platform coupled with primary sources, such as Parliamentary Records and official statements by civil society organizations, the paper highlights how the anti-nuclear platform exercises power through counter-hegemonic discourses in terms of the delegitimization of nuclear energy in Turkey.

Keywords: counter-hegemony, discourse, nuclear energy, Turkey

Procedia PDF Downloads 356
14356 Critical Success Factors of OCOP Business Model in Pattani Province, Thailand: A Qualitative Approach

Authors: Poonsuck Thatchaopas, Nik Kamariah Nik Mat, Nattakarn Eakuru

Abstract:

“One College One Product” OCOP business model is launched by the Vocational Education Commission to encourage college students to choose at least one product for business venture. However, the number of successful OCOP projects is still minimal. The objective of this paper is to identify the critical success factors needed to be a successful OCOP business entrepreneur. This study uses qualitative method by interviewing business partners of an OCOP business called Crispy Roti Krua Acheeva Brand (CRKAB). This project was initiated by three female alumni students of the CRKAB. The finding shows that the main critical success factors are self-confidence, creativity or innovativeness, knowledge, skills and perseverance. Additionally, they reiterated that the keys to business success are product quality, perceived price, promotion, branding, new packaging to increase sales and continuous developments. The results implies for a business SME to be successful, the company should have credible partners and effective marketing plan.

Keywords: new entrepreneurship student model, business incubator, food industry, Pattani Province, Thailand

Procedia PDF Downloads 382
14355 Gas Lift Optimization Using Smart Gas Lift Valve

Authors: Mohamed A. G. H. Abdalsadig, Amir Nourian, G. G. Nasr, M. Babaie

Abstract:

Gas lift is one of the most common forms of artificial lift, particularly for offshore wells because of its relative down hole simplicity, flexibility, reliability, and ability to operate over a large range of rates and occupy very little space at the well head. Presently, petroleum industry is investing in exploration and development fields in offshore locations where oil and gas wells are being drilled thousands of feet below the ocean in high pressure and temperature conditions. Therefore, gas-lifted oil wells are capable of failure through gas lift valves which are considered as the heart of the gas lift system for controlling the amount of the gas inside the tubing string. The gas injection rate through gas lift valve must be controlled to be sufficient to obtain and maintain critical flow, also, gas lift valves must be designed not only to allow gas passage through it and prevent oil passage, but also for gas injection into wells to be started and stopped when needed. In this paper, smart gas lift valve has been used to investigate the effect of the valve port size, depth of injection and vertical lift performance on well productivity; all these aspects have been investigated using PROSPER simulator program coupled with experimental data. The results show that by using smart gas lift valve, the gas injection rate can be controlled which leads to improved flow performance.

Keywords: Effect of gas lift valve port size, effect water cut, vertical flow performance

Procedia PDF Downloads 296
14354 A Data-Driven Compartmental Model for Dengue Forecasting and Covariate Inference

Authors: Yichao Liu, Peter Fransson, Julian Heidecke, Jonas Wallin, Joacim Rockloev

Abstract:

Dengue, a mosquito-borne viral disease, poses a significant public health challenge in endemic tropical or subtropical countries, including Sri Lanka. To reveal insights into the complexity of the dynamics of this disease and study the drivers, a comprehensive model capable of both robust forecasting and insightful inference of drivers while capturing the co-circulating of several virus strains is essential. However, existing studies mostly focus on only one aspect at a time and do not integrate and carry insights across the siloed approach. While mechanistic models are developed to capture immunity dynamics, they are often oversimplified and lack integration of all the diverse drivers of disease transmission. On the other hand, purely data-driven methods lack constraints imposed by immuno-epidemiological processes, making them prone to overfitting and inference bias. This research presents a hybrid model that combines machine learning techniques with mechanistic modelling to overcome the limitations of existing approaches. Leveraging eight years of newly reported dengue case data, along with socioeconomic factors, such as human mobility, weekly climate data from 2011 to 2018, genetic data detecting the introduction and presence of new strains, and estimates of seropositivity for different districts in Sri Lanka, we derive a data-driven vector (SEI) to human (SEIR) model across 16 regions in Sri Lanka at the weekly time scale. By conducting ablation studies, the lag effects allowing delays up to 12 weeks of time-varying climate factors were determined. The model demonstrates superior predictive performance over a pure machine learning approach when considering lead times of 5 and 10 weeks on data withheld from model fitting. It further reveals several interesting interpretable findings of drivers while adjusting for the dynamics and influences of immunity and introduction of a new strain. The study uncovers strong influences of socioeconomic variables: population density, mobility, household income and rural vs. urban population. The study reveals substantial sensitivity to the diurnal temperature range and precipitation, while mean temperature and humidity appear less important in the study location. Additionally, the model indicated sensitivity to vegetation index, both max and average. Predictions on testing data reveal high model accuracy. Overall, this study advances the knowledge of dengue transmission in Sri Lanka and demonstrates the importance of incorporating hybrid modelling techniques to use biologically informed model structures with flexible data-driven estimates of model parameters. The findings show the potential to both inference of drivers in situations of complex disease dynamics and robust forecasting models.

Keywords: compartmental model, climate, dengue, machine learning, social-economic

Procedia PDF Downloads 90
14353 Regional Advantages Analysis: An Interactive Approach of Comparative and Competitive Advantages

Authors: Abdolrasoul Ghasemi, Ali Arabmazar Yazdi, Yasaman Boroumand, Aliasghar Banouei

Abstract:

In regional studies, choosing an appropriate approach to analyze regional success or failure has always been a challenge. Hence, this study introduces an innovative approach to establish a link between regional success and failure in the past as well as the potential success of a region in the future. The former can be sought in the historical evaluation of comparative advantages, while the latter is portrayed as competitive advantage analysis with a forward-looking approach. Based on the interaction of comparative and competitive advantages, activities are classified into four groups, including activities with no advantage, hidden advantage, fragile advantage and synergistic advantage. In analyzing the comparative advantage of activities, the location quotient method is applied, and in analyzing their competitive advantage, Porter`s diamond model using the survey method is applied. According to the results, the share of no advantage, fragile advantage, hidden advantage and synergic advantage activities are respectively 10%, 42%, 16%, and 32%. Also, to achieve economic development in regional activities, our model provides various levels of priority. First, the activities with synergistic advantage should be prioritized, then the ones with hidden advantage, and finally the activities with fragile advantage.

Keywords: regional advantage, comparative advantage, competitive advantage, Porter's diamond model

Procedia PDF Downloads 358
14352 Calculation Of Energy Gap Of (Ga,Mn)As Diluted Magnetic Semiconductor From The Eight-Band k.p Model

Authors: Khawlh A. Alzubaidi, Khadijah B. Alziyadi, Amor M. Alsayari

Abstract:

Now a days (Ga, Mn) is one of the most extensively studied and best understood diluted magnetic semiconductors. Also, the study of (Ga, Mn)As is a fervent research area since it allows to explore of a variety of novel functionalities and spintronics concepts that could be implemented in the future. In this work, we will calculate the energy gap of (Ga, Mn)As using the eight-band model. In the Hamiltonian, the effects of spin-orbit, spin-splitting, and strain will be considered. The dependence of the energy gap on Mn content, and the effect of the strain, which is varied continuously from tensile to compressive, will be studied. Finally, analytical expressions for the (Ga, Mn)As energy band gap, taking into account both parameters (Mn concentration and strain), will be provided.

Keywords: energy gap, diluted magnetic semiconductors, k.p method, strain

Procedia PDF Downloads 129
14351 Non-Singular Gravitational Collapse of a Homogeneous Scalar Field in Deformed Phase Space

Authors: Amir Hadi Ziaie

Abstract:

In the present work, we revisit the collapse process of a spherically symmetric homogeneous scalar field (in FRW background) minimally coupled to gravity, when the phase-space deformations are taken into account. Such a deformation is mathematically introduced as a particular type of noncommutativity between the canonical momenta of the scale factor and of the scalar field. In the absence of such deformation, the collapse culminates in a spacetime singularity. However, when the phase-space is deformed, we find that the singularity is removed by a non-singular bounce, beyond which the collapsing cloud re-expands to infinity. More precisely, for negative values of the deformation parameter, we identify the appearance of a negative pressure, which decelerates the collapse to finally avoid the singularity formation. While in the un-deformed case, the horizon curve monotonically decreases to finally cover the singularity, in the deformed case the horizon has a minimum value that this value depends on deformation parameter and initial configuration of the collapse. Such a setting predicts a threshold mass for black hole formation in stellar collapse and manifests the role of non-commutative geometry in physics and especially in stellar collapse and supernova explosion.

Keywords: gravitational collapse, non-commutative geometry, spacetime singularity, black hole physics

Procedia PDF Downloads 351
14350 A Grey-Box Text Attack Framework Using Explainable AI

Authors: Esther Chiramal, Kelvin Soh Boon Kai

Abstract:

Explainable AI is a strong strategy implemented to understand complex black-box model predictions in a human-interpretable language. It provides the evidence required to execute the use of trustworthy and reliable AI systems. On the other hand, however, it also opens the door to locating possible vulnerabilities in an AI model. Traditional adversarial text attack uses word substitution, data augmentation techniques, and gradient-based attacks on powerful pre-trained Bidirectional Encoder Representations from Transformers (BERT) variants to generate adversarial sentences. These attacks are generally white-box in nature and not practical as they can be easily detected by humans e.g., Changing the word from “Poor” to “Rich”. We proposed a simple yet effective Grey-box cum Black-box approach that does not require the knowledge of the model while using a set of surrogate Transformer/BERT models to perform the attack using Explainable AI techniques. As Transformers are the current state-of-the-art models for almost all Natural Language Processing (NLP) tasks, an attack generated from BERT1 is transferable to BERT2. This transferability is made possible due to the attention mechanism in the transformer that allows the model to capture long-range dependencies in a sequence. Using the power of BERT generalisation via attention, we attempt to exploit how transformers learn by attacking a few surrogate transformer variants which are all based on a different architecture. We demonstrate that this approach is highly effective to generate semantically good sentences by changing as little as one word that is not detectable by humans while still fooling other BERT models.

Keywords: BERT, explainable AI, Grey-box text attack, transformer

Procedia PDF Downloads 141
14349 Tracking Maximum Power Point Utilizing Artificial Immunity System

Authors: Marwa Ahmed Abd El Hamied

Abstract:

In this paper In this paper, a new technique based on Artificial Immunity System (AIS) technique has been developed to track Maximum Power Point (MPP). AIS system is implemented in a photovoltaic system that is subjected to variable temperature and insulation condition. The proposed novel is simulated using Mat Lab program. The results of simulation have been compared to those who are generated from Observation Controller. The proposed model shows promising results as it provide better accuracy comparing to classical model.

Keywords: component, artificial immunity technique, solar energy, perturbation and observation, power based methods

Procedia PDF Downloads 431
14348 Frequent-Flyer Program: The Connection between Commercial Partners and Spin-off

Authors: Changmin Jiang

Abstract:

In this paper, we build a theoretical model to investigate the relationship between two recent trends in airline frequent-flyer programs (FFPs): the adoption of the “coalition” business model with other commercial partners, and the separation from airlines’ operations. We show that commercial partners benefit from teaming up with FFP, while increasing the number of commercial partners will increase the total profit; it reduces the average profit of the parties involved. Furthermore, we show that the number of commercial partners of an FFP is negatively related with the benefit to keep the FFP in-house.

Keywords: frequent flyer program, coalition, commercial partners, spin-off

Procedia PDF Downloads 306
14347 Cognitive Behaviour Drama: Playful Method to Address Fears in Children on the Higher-End of the Autism Spectrum

Authors: H.Karnezi, K. Tierney

Abstract:

Childhood fears that persist over time and interfere with the children’s normal functioning may have detrimental effects on their social and emotional development. Cognitive behavior therapy is considered highly effective in treating fears and anxieties. However, given that many childhood fears are based on fantasy, the applicability of CBT may be hindered by cognitive immaturity. Furthermore, a lack of motivation to engage in therapy is another commonly encountered obstacle. The purpose of this study was to introduce and evaluate a more developmentally appropriate intervention model, specifically designed to provide phobic children with the motivation to overcome their fears. To this end, principles and techniques from cognitive and behavior therapies are incorporated into the ‘Drama in Education’ model. The Cognitive Behaviour Drama (CBD) method involves using the phobic children’s creativity to involve them in the therapeutic process. The children are invited to engage in exciting fictional scenarios tailored around their strengths and special interests. Once their commitment to the drama is established, a problem that they will feel motivated to solve is introduced. To resolve it, the children will have to overcome a number of obstacles culminating in an in vivo confrontation with the fear stimulus. The study examined the application of the CBD model in three single cases. Results in all three cases shown complete elimination of all fear-related symptoms. Preliminary results justify further evaluation of the Cognitive Behaviour Drama model. It is time and cost-effective, ensuring the clients' immediate engagement in the therapeutic process.

Keywords: phobias, autism, intervention, drama

Procedia PDF Downloads 133
14346 An Educational Program Based on Health Belief Model to Prevent Non-Alcoholic Fatty Liver Disease among Iranian Women

Authors: Babak Nemat

Abstract:

Background and Purpose: Non-alcoholic fatty liver is one of the most common liver disorders, which, as the most important cause of death from liver disease, has unpleasant consequences and complications. The aim of this study was to investigate the effect of an educational intervention based on a health belief model to prevent non-alcoholic fatty liver among women. Materials and Methods: This experimental study was performed among 110 women referring to comprehensive health service centers in Malayer City, west of Iran, in 2023. Using the available sampling method, 110 participants were divided into experimental and control groups. The data collection tool included demographic characteristics and a questionnaire based on the health belief model. In the experimental group, three one-hour training sessions were conducted in the form of pamphlets, lectures, and group discussions. Data were analyzed using SPSS software version 21, by correlation tests, paired t-tests, and independent t-tests. Results: The mean age of participants was 38.07±6.28 years, and most of the participants were middle-aged, married, housewives with academic education, middle-income, and overweight. After the educational intervention, the mean scores of the constructs include perceived sensitivity (p=0.01), perceived severity (p=0.01), perceived benefits (p=0.01), guidance for internal (p=0.01), and external action (p=0.01), and perceived self-efficacy (p=0.01) in the experimental group were significantly higher than the control group. The score of perceived barriers in the experimental group decreased after training. The perceived obstacles score in the test group decreased after the training (15.2 ± 3.9 v.s 11.2 ± 3.3, (p<0.01). Conclusion: The findings of the study showed that the design and implementation of educational programs based on the constructs of the health belief model can be effective in preventing women from developing higher levels of non-alcoholic fatty liver.

Keywords: non-alcoholic fatty liver, health belief model, education, women

Procedia PDF Downloads 64
14345 Big Data in Telecom Industry: Effective Predictive Techniques on Call Detail Records

Authors: Sara ElElimy, Samir Moustafa

Abstract:

Mobile network operators start to face many challenges in the digital era, especially with high demands from customers. Since mobile network operators are considered a source of big data, traditional techniques are not effective with new era of big data, Internet of things (IoT) and 5G; as a result, handling effectively different big datasets becomes a vital task for operators with the continuous growth of data and moving from long term evolution (LTE) to 5G. So, there is an urgent need for effective Big data analytics to predict future demands, traffic, and network performance to full fill the requirements of the fifth generation of mobile network technology. In this paper, we introduce data science techniques using machine learning and deep learning algorithms: the autoregressive integrated moving average (ARIMA), Bayesian-based curve fitting, and recurrent neural network (RNN) are employed for a data-driven application to mobile network operators. The main framework included in models are identification parameters of each model, estimation, prediction, and final data-driven application of this prediction from business and network performance applications. These models are applied to Telecom Italia Big Data challenge call detail records (CDRs) datasets. The performance of these models is found out using a specific well-known evaluation criteria shows that ARIMA (machine learning-based model) is more accurate as a predictive model in such a dataset than the RNN (deep learning model).

Keywords: big data analytics, machine learning, CDRs, 5G

Procedia PDF Downloads 143
14344 Using Speech Emotion Recognition as a Longitudinal Biomarker for Alzheimer’s Diseases

Authors: Yishu Gong, Liangliang Yang, Jianyu Zhang, Zhengyu Chen, Sihong He, Xusheng Zhang, Wei Zhang

Abstract:

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that affects millions of people worldwide and is characterized by cognitive decline and behavioral changes. People living with Alzheimer’s disease often find it hard to complete routine tasks. However, there are limited objective assessments that aim to quantify the difficulty of certain tasks for AD patients compared to non-AD people. In this study, we propose to use speech emotion recognition (SER), especially the frustration level, as a potential biomarker for quantifying the difficulty patients experience when describing a picture. We build an SER model using data from the IEMOCAP dataset and apply the model to the DementiaBank data to detect the AD/non-AD group difference and perform longitudinal analysis to track the AD disease progression. Our results show that the frustration level detected from the SER model can possibly be used as a cost-effective tool for objective tracking of AD progression in addition to the Mini-Mental State Examination (MMSE) score.

Keywords: Alzheimer’s disease, speech emotion recognition, longitudinal biomarker, machine learning

Procedia PDF Downloads 117
14343 Human Resources and Business Result: An Empirical Approach Based on RBV Theory

Authors: Xhevrie Mamaqi

Abstract:

Organization capacity learning is a process referring to the sum total of individual and collective learning through training programs, experience and experimentation, among others. Today, in-business ongoing training is one of the most important strategies for human capital development and it is crucial to sustain and improve workers’ knowledge and skills. Many organizations, firms and business are adopting a strategy of continuous learning, encouraging employees to learn new skills continually to be innovative and to try new processes and work in order to achieve a competitive advantage and superior business results. This paper uses the Resource Based View and Capacities (RBV) approach to construct a hypothetical relationships model between training and business results. The test of the model is applied on transversal data. A sample of 266 business of Spanish sector service has been selected. A Structural Equation Model (SEM) is used to estimate the relationship between ongoing training, represented by two latent dimension denominated Human and Social Capital resources and economic business results. The coefficients estimated have shown the efficient of some training aspects explaining the variation in business results.

Keywords: business results, human and social capital resources, training, RBV theory, SEM

Procedia PDF Downloads 304
14342 Assimilating Multi-Mission Satellites Data into a Hydrological Model

Authors: Mehdi Khaki, Ehsan Forootan, Joseph Awange, Michael Kuhn

Abstract:

Terrestrial water storage, as a source of freshwater, plays an important role in human lives. Hydrological models offer important tools for simulating and predicting water storages at global and regional scales. However, their comparisons with 'reality' are imperfect mainly due to a high level of uncertainty in input data and limitations in accounting for all complex water cycle processes, uncertainties of (unknown) empirical model parameters, as well as the absence of high resolution (both spatially and temporally) data. Data assimilation can mitigate this drawback by incorporating new sets of observations into models. In this effort, we use multi-mission satellite-derived remotely sensed observations to improve the performance of World-Wide Water Resources Assessment system (W3RA) hydrological model for estimating terrestrial water storages. For this purpose, we assimilate total water storage (TWS) data from the Gravity Recovery And Climate Experiment (GRACE) and surface soil moisture data from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) into W3RA. This is done to (i) improve model estimations of water stored in ground and soil moisture, and (ii) assess the impacts of each satellite of data (from GRACE and AMSR-E) and their combination on the final terrestrial water storage estimations. These data are assimilated into W3RA using the Ensemble Square-Root Filter (EnSRF) filtering technique over Mississippi Basin (the United States) and Murray-Darling Basin (Australia) between 2002 and 2013. In order to evaluate the results, independent ground-based groundwater and soil moisture measurements within each basin are used.

Keywords: data assimilation, GRACE, AMSR-E, hydrological model, EnSRF

Procedia PDF Downloads 293
14341 Understanding the Thermal Transformation of Random Access Memory Cards: A Pathway to Their Efficient Recycling

Authors: Khushalini N. Ulman, Samane Maroufi, Veena H. Sahajwalla

Abstract:

Globally, electronic waste (e-waste) continues to grow at an alarming rate. Several technologies have been developed to recover valuable materials from e-waste, however, their efficiency can be increased with a better knowledge of the e-waste components. Random access memory cards (RAMs) are considered as high value scrap for the e-waste recyclers. Despite their high precious metal content, RAMs are still recycled in a conventional manner resulting in huge loss of resources. Our research work highlights the precious metal rich components of a RAM. Inductively coupled plasma (ICP) analysis of RAMs of six different generations have been carried out and the trends in their metal content have been investigated. Over the past decade, the copper content of RAMs has halved and their tin content has increased by 70 %. The stricter environmental laws have facilitated ~96 % drop in the lead content of RAMs. To comprehend the fundamentals of thermal transformation of RAMs, our research provides their detailed kinetic study. This can assist the e-waste recyclers in optimising their metal recovery processes. Thus, understanding the chemical and thermal behaviour of RAMs can open new avenues for efficient e-waste recycling.

Keywords: electronic waste, kinetic study, recycling, thermal transformation

Procedia PDF Downloads 151
14340 Contextualizing the Translation and Reconstruction of “Zhengqueyiliguan” in Promoting China-Africa Diplomatic Discourse

Authors: Queen Modestus

Abstract:

China’s diplomatic discourse is a complicated system underpinned by divergent translations. As such, the concept of “Zhengque Yi Li Guan” (or zhèngquè Yì Lì Guān in Pinyin), like numerous other Chinese concepts, is not well appreciated due, mainly, to the dearth of a uniform official translation and poor interpretation. So, the paper seeks to draw awareness to this vital issue that has been neglected in the China-Africa diplomatic discourse. As a way of filling this gap in the literature, the author argues that literal translation is not enough in diplomatic discourse. To identify the English equivalent of “Zhenque,” “Yi,” “Li,” and “Guan,” searches of Chinese classical works were carried out. Based on the scope of this paper, emphasis will be placed on “Yi” because it plays a critical role in the “zhèngquèyìlìguān” concept and has been the term with the most controversial interpretation. From a diplomatic-linguistic standpoint coupled with the help of the Critical Discourse Analysis (CDA) developed by Norman Fairclough and Teun A. van Dijk as this paper’s theoretical framework, this paper seeks to address the above issue by exploring the philosophical translations and interpretations of ZqYLG in China-Africa diplomatic discourse, with emphasis place on the discourse reconstruction of “Yi.” As a way of reconstructing “Yi” to fit the present reality of China-Africa diplomatic discourse, the author argues that “justice” (meaning impartiality) is a better translation for “Yi.”

Keywords: Africa, diplomatic discourse, reconstruction, translation, 正确义利观, interests

Procedia PDF Downloads 92
14339 Estimate of Maximum Expected Intensity of One-Half-Wave Lines Dancing

Authors: A. Bekbaev, M. Dzhamanbaev, R. Abitaeva, A. Karbozova, G. Nabyeva

Abstract:

In this paper, the regression dependence of dancing intensity from wind speed and length of span was established due to the statistic data obtained from multi-year observations on line wires dancing accumulated by power systems of Kazakhstan and the Russian Federation. The lower and upper limitations of the equations parameters were estimated, as well as the adequacy of the regression model. The constructed model will be used in research of dancing phenomena for the development of methods and means of protection against dancing and for zoning plan of the territories of line wire dancing.

Keywords: power lines, line wire dancing, dancing intensity, regression equation, dancing area intensity

Procedia PDF Downloads 317
14338 The Effects of Health Education Programme on Knowledge and Prevention of Cerebrovascular Disease among Hypertensive Patients in University College Hospital, Ibadan

Authors: T. A. Ajiboye

Abstract:

This study examines the effects of health education programme on knowledge and prevention of cerebrovascular disease among hypertensive patients in University College Hospital, Ibadan. A quasi-experimental design was adopted for the study. 100 hypertensive patients were conveniently selected from general outpatient department in UCH. Data generated were analyzed using ANOVA at 0.05 alpha levels. The findings of the study revealed that health education programme significantly influenced both the knowledge of hypertensive patients (F=22.70; DF=1/99; p < .05) and their attitude (F=10.377; DF=1/99; p < .05) on cerebrovascular disease. Findings also discovered that health education programme significantly reduce the complication of hypertension to cerebrovascular disease (F= 16.41; DF=7/286; p < 0.05) among the hypertensive patients at UCH. Based on the findings, it is recommended that hypertensive patients should relieve themselves from stress, engage themselves on regular exercises, compliance with drug and diet regimes coupled with keeping up of regular appointment. Government should design health information that will center on hypertension and cerebrovascular disease so as to keep health and community development problems to the barest minimum. Finally, there should be provision of social amenities and recreational centers, as this will prevents hypertension problems.

Keywords: cerebrovascular disease, effectiveness, health education, hypertension, knowledge, prevention

Procedia PDF Downloads 304
14337 Intelligent Computing with Bayesian Regularization Artificial Neural Networks for a Nonlinear System of COVID-19 Epidemic Model for Future Generation Disease Control

Authors: Tahir Nawaz Cheema, Dumitru Baleanu, Ali Raza

Abstract:

In this research work, we design intelligent computing through Bayesian Regularization artificial neural networks (BRANNs) introduced to solve the mathematical modeling of infectious diseases (Covid-19). The dynamical transmission is due to the interaction of people and its mathematical representation based on the system's nonlinear differential equations. The generation of the dataset of the Covid-19 model is exploited by the power of the explicit Runge Kutta method for different countries of the world like India, Pakistan, Italy, and many more. The generated dataset is approximately used for training, testing, and validation processes for every frequent update in Bayesian Regularization backpropagation for numerical behavior of the dynamics of the Covid-19 model. The performance and effectiveness of designed methodology BRANNs are checked through mean squared error, error histograms, numerical solutions, absolute error, and regression analysis.

Keywords: mathematical models, beysian regularization, bayesian-regularization backpropagation networks, regression analysis, numerical computing

Procedia PDF Downloads 152
14336 Meaning beyond Pleasure in Leisure: Comparison between Korea and France

Authors: Joane Adeclas, Yoonyoung Kim, Taekyun Hur

Abstract:

This study investigates individual’s intrinsic motivation to practice their leisure activities, as well as, how the cultural environment may influence their motivation to practice their activities. Focused on the positive psychology, the present study proposed redefinition of leisure activities considering two factors. First, leisure activities could be as any activities that provide pleasure or meaning to individuals. Second, they can be practiced alone or in groups. In fact, based on this definition, a four-dimensional model of leisure activities was developed, to measure individual’s perception of their leisure experience, based on four factors that are: personal pleasure, social pleasure, personal meaning and social meaning. Furthermore, recent studies have argued that leisure activities can be interpreted and understood differently across cultures. Therefore, the present study proposed to examine the possible role of the cultural context of individual’s leisure practices. To do so, two cultural groups (Koreans vs. French) were compared in terms of the four-dimensional model of leisure activities. Three hundred Koreans and three hundred French participants were asked to answer an online survey about their leisure activities. Participants had to respond to questions related to several aspects of leisure practices as followed: the reason why their practice their leisure activities, the reason why they fail to practice their leisure, and their obsession relate to their leisure activities. Factor analyses based on participant’s responses proposed a moderate fit of the four-dimensional model of leisure activities. Furthermore, significant cultural differences were also found. As a result, the cultural context seems to influence the reason why individuals practice their leisure activities based on our model. In fact, Koreans explained more than French, the practice of their leisure activities with social-pleasurable reasons. At a contrary, French explained more than Koreans, the practice of their leisure activities with social-meaningful reasons. The two cultural groups also significantly differ on their perception of failure. The results showed that French participants used more meaningful social factors to explain why they failed to practice their leisure activities than did Koreans participants. Finally, Koreans and French significantly differed regarding their obsession on their leisure activities. In general, French tend to have more obsession than Koreans about their leisure activities. Those results validated the four-dimensional model of leisure, as well as, the cultural differences in leisure practices. However, further studies are needed to validate this model at an individual and cultural level.

Keywords: culture, leisure, meaning, pleasure

Procedia PDF Downloads 268
14335 Predication Model for Leukemia Diseases Based on Data Mining Classification Algorithms with Best Accuracy

Authors: Fahd Sabry Esmail, M. Badr Senousy, Mohamed Ragaie

Abstract:

In recent years, there has been an explosion in the rate of using technology that help discovering the diseases. For example, DNA microarrays allow us for the first time to obtain a "global" view of the cell. It has great potential to provide accurate medical diagnosis, to help in finding the right treatment and cure for many diseases. Various classification algorithms can be applied on such micro-array datasets to devise methods that can predict the occurrence of Leukemia disease. In this study, we compared the classification accuracy and response time among eleven decision tree methods and six rule classifier methods using five performance criteria. The experiment results show that the performance of Random Tree is producing better result. Also it takes lowest time to build model in tree classifier. The classification rules algorithms such as nearest- neighbor-like algorithm (NNge) is the best algorithm due to the high accuracy and it takes lowest time to build model in classification.

Keywords: data mining, classification techniques, decision tree, classification rule, leukemia diseases, microarray data

Procedia PDF Downloads 327
14334 A Game-Based Product Modelling Environment for Non-Engineer

Authors: Guolong Zhong, Venkatesh Chennam Vijay, Ilias Oraifige

Abstract:

In the last 20 years, Knowledge Based Engineering (KBE) has shown its advantages in product development in different engineering areas such as automation, mechanical, civil and aerospace engineering in terms of digital design automation and cost reduction by automating repetitive design tasks through capturing, integrating, utilising and reusing the existing knowledge required in various aspects of the product design. However, in primary design stages, the descriptive information of a product is discrete and unorganized while knowledge is in various forms instead of pure data. Thus, it is crucial to have an integrated product model which can represent the entire product information and its associated knowledge at the beginning of the product design. One of the shortcomings of the existing product models is a lack of required knowledge representation in various aspects of product design and its mapping to an interoperable schema. To overcome the limitation of the existing product model and methodologies, two key factors are considered. First, the product model must have well-defined classes that can represent the entire product information and its associated knowledge. Second, the product model needs to be represented in an interoperable schema to ensure a steady data exchange between different product modelling platforms and CAD software. This paper introduced a method to provide a general product model as a generative representation of a product, which consists of the geometry information and non-geometry information, through a product modelling framework. The proposed method for capturing the knowledge from the designers through a knowledge file provides a simple and efficient way of collecting and transferring knowledge. Further, the knowledge schema provides a clear view and format on the data that needed to be gathered in order to achieve a unified knowledge exchange between different platforms. This study used a game-based platform to make product modelling environment accessible for non-engineers. Further the paper goes on to test use case based on the proposed game-based product modelling environment to validate the effectiveness among non-engineers.

Keywords: game-based learning, knowledge based engineering, product modelling, design automation

Procedia PDF Downloads 158
14333 Feedback from Experiments on Managing Methods against Japanese Knotweed on a River Appendix of the RhôNe between 2015 and 2020

Authors: William Brasier, Nicolas Rabin, Celeste Joly

Abstract:

Japanese knotweed (Fallopia japonica) is very present on the banks of the Rhone, colonizing more and more areas along the river. The Compagnie Nationale du Rhone (C.N.R.), which manages the river, has experimented with several control techniques in recent years. Since 2015, 15 experimental plots have been monitored on the banks of a restored river appendix to measure the effect of three control methods: confinement by felt, repeated mowing and the planting of competing species and/or species with allelopathic power: Viburnum opulus, Rhamnus frangula, Sambucus ebulus and Juglans regia. Each year, the number of stems, the number of elderberry plants, the height of the plants and photographs were collected. After six years of monitoring, the results showed that the density of knotweed stems decreased by 50 to 90% on all plots. The control methods are sustainable and are gradually gaining in efficiency. The establishment of native plants coupled with regular manual maintenance can reduce the development of Japanese knotweed. Continued monitoring over the next few years will determine the kinetics of the total eradication (i.e. 0 stem/plot) of the Japanese knotweed by these methods.

Keywords: fallopia japonica, interspecific plant competition , Rhone river, riparian trees

Procedia PDF Downloads 134
14332 Analysis of Urban Flooding in Wazirabad Catchment of Kabul City with Help of Geo-SWMM

Authors: Fazli Rahim Shinwari, Ulrich Dittmer

Abstract:

Like many megacities around the world, Kabul is facing severe problems due to the rising frequency of urban flooding. Since 2001, Kabul is experiencing rapid population growth because of the repatriation of refugees and internal migration. Due to unplanned development, green areas inside city and hilly areas within and around the city are converted into new housing towns that had increased runoff. Trenches along the roadside comprise the unplanned drainage network of the city that drains the combined sewer flow. In rainy season overflow occurs, and after streets become dry, the dust particles contaminate the air which is a major cause of air pollution in Kabul city. In this study, a stormwater management model is introduced as a basis for a systematic approach to urban drainage planning in Kabul. For this purpose, Kabul city is delineated into 8 watersheds with the help of one-meter resolution LIDAR DEM. Storm, water management model, is developed for Wazirabad catchment by using available data and literature values. Due to lack of long term metrological data, the model is only run for hourly rainfall data of a rain event that occurred in April 2016. The rain event from 1st to 3rd April with maximum intensity of 3mm/hr caused huge flooding in Wazirabad Catchment of Kabul City. Model-estimated flooding at some points of the catchment as an actual measurement of flooding was not possible; results were compared with information obtained from local people, Kabul Municipality and Capital Region Independent Development Authority. The model helped to identify areas where flooding occurred because of less capacity of drainage system and areas where the main reason for flooding is due to blockage in the drainage canals. The model was used for further analysis to find a sustainable solution to the problem. The option to construct new canals was analyzed, and two new canals were proposed that will reduce the flooding frequency in Wazirabad catchment of Kabul city. By developing the methodology to develop a stormwater management model from digital data and information, the study had fulfilled the primary objective, and similar methodology can be used for other catchments of Kabul city to prepare an emergency and long-term plan for drainage system of Kabul city.

Keywords: urban hydrology, storm water management, modeling, SWMM, GEO-SWMM, GIS, identification of flood vulnerable areas, urban flooding analysis, sustainable urban drainage

Procedia PDF Downloads 158
14331 The Forms of Representation in Architectural Design Teaching: The Cases of Politecnico Di Milano and Faculty of Architecture of the University of Porto

Authors: Rafael Sousa Santos, Clara Pimena Do Vale, Barbara Bogoni, Poul Henning Kirkegaard

Abstract:

The representative component, a determining aspect of the architect's training, has been marked by an exponential and unprecedented development. However, the multiplication of possibilities has also multiplied uncertainties about architectural design teaching, and by extension, about the very principles of architectural education. In this paper, it is intended to present the results of a research developed on the following problem: the relation between the forms of representation and the architectural design teaching-learning processes. The research had as its object the educational model of two schools – the Politecnico di Milano (POLIMI) and the Faculty of Architecture of the University of Porto (FAUP) – and was led by three main objectives: to characterize the educational model followed in both schools focused on the representative component and its role; to interpret the relation between forms of representation and the architectural design teaching-learning processes; to consider their possibilities of valorisation. Methodologically, the research was conducted according to a qualitative embedded multiple-case study design. The object – i.e., the educational model – was approached in both POLIMI and FAUP cases considering its Context and three embedded unities of analysis: the educational Purposes, Principles, and Practices. In order to guide the procedures of data collection and analysis, a Matrix for the Characterization (MCC) was developed. As a methodological tool, the MCC allowed to relate the three embedded unities of analysis with the three main sources of evidence where the object manifests itself: the professors, expressing how the model is assumed; the architectural design classes, expressing how the model is achieved; and the students, expressing how the model is acquired. The main research methods used were the naturalistic and participatory observation, in-person-interview and documentary and bibliographic review. The results reveal the importance of the representative component in the educational model of both cases, despite the differences in its role. In POLIMI's model, representation is particularly relevant in the teaching of architectural design, while in FAUP’s model, it plays a transversal role – according to an idea of 'general training through hand drawing'. In fact, the difference between models relative to representation can be partially understood by the level of importance that each gives to hand drawing. Regarding the teaching of architectural design, the two cases are distinguished in the relation with the representative component: while in POLIMI the forms of representation serve essentially an instrumental purpose, in FAUP they tend to be considered also for their methodological dimension. It seems that the possibilities for valuing these models reside precisely in the relation between forms of representation and architectural design teaching. It is expected that the knowledge base developed in this research may have three main contributions: to contribute to the maintenance of the educational model of POLIMI and FAUP; through the precise description of the methodological procedures, to contribute by transferability to similar studies; through the critical and objective framework of the problem underlying the forms of representation and its relation with architectural design teaching, to contribute to the broader discussion concerning the contemporary challenges on architectural education.

Keywords: architectural design teaching, architectural education, educational models, forms of representation

Procedia PDF Downloads 127