Search results for: environmental model

Authors: Otman Jai, Otman Elhajjaji, Jaouad Tajmouati

Abstract:

Several neutronic calculation codes must be used to solve the equation for different levels of discretization which all necessitate a specific modelisation. This chain of such models, known as a calculation scheme, leads to the knowledge of the neutron flux in a reactor from its own geometry, its isotopic compositions and a cross-section library. Being small in size, the 'Slowpoke-2' reactor is difficult to model due to the importance of the leaking neutrons. In the paper, the simulation model is presented (geometry, cross section library, assumption, etc.), and the results obtained by DRAGON4/DONJON4 codes were compared to the calculations performed with Monte Carlo code MCNP using detailed geometrical model of the reactor and the experimental data. Criticality calculations have been performed to verify and validate the model. Since created model properly describes the reactor core, it can be used for calculations of reactor core parameters and for optimization of research reactor application.

Keywords: transport equation, Dragon4, Donjon4, neutron flux, effective multiplication factor

Procedia PDF Downloads 464

Authors: Uvais Qidwai, Amor Moursi, Mohamed Tahar, Malek Hamad, Hamad Alansi

Abstract:

This paper focuses on the development and implementation of an advanced plant health monitoring system with an AI backbone and IoT sensory network. Our approach involves addressing the critical environmental factors essential for preserving a plant’s well-being, including air temperature, soil moisture, soil temperature, soil conductivity, pH, water levels, and humidity, as well as the presence of essential nutrients like nitrogen, phosphorus, and potassium. Central to our methodology is the utilization of computer vision technology, particularly a night vision camera. The captured data is then compared against a reference database containing different health statuses. This comparative analysis is implemented using an AI deep learning model, which enables us to generate accurate assessments of plant health status. By combining the AI-based decision-making approach, our system aims to provide precise and timely insights into the overall health and well-being of plants, offering a valuable tool for effective plant care and management.

Keywords: deep learning image model, IoT sensing, cloud-based analysis, remote monitoring app, computer vision, fuzzy control

Procedia PDF Downloads 46

Authors: Sajid Hussain

Abstract:

The complex domain approach for image segmentation based on active contour has been designed, which deforms step by step to partition an image into numerous expedient regions. A novel region-based trigonometric complex pressure force function is proposed, which propagates around the region of interest using image forces. The signed trigonometric force function controls the propagation of the active contour and the active contour stops on the exact edges of the object accurately. The proposed model makes the level set function binary and uses Gaussian smoothing kernel to adjust and escape the re-initialization procedure. The working principle of the proposed model is as follows: The real image data is transformed into complex data by iota (i) times of image data and the average iota (i) times of horizontal and vertical components of the gradient of image data is inserted in the proposed model to catch complex gradient of the image data. A simple finite difference mathematical technique has been used to implement the proposed model. The efficiency and robustness of the proposed model have been verified and compared with other state-of-the-art models.

Keywords: image segmentation, active contour, level set, Mumford and Shah model

Procedia PDF Downloads 104

Authors: S. A. Al-Qallaf, S. A. Al-Mawsawi, A. Haider

Abstract:

Among all FACTS devices, the unified power flow controller (UPFC) is considered to be the most versatile device. This is due to its capability to control all the transmission system parameters (impedance, voltage magnitude, and phase angle). With the growing interest in UPFC, the attention to develop a mathematical model has increased. Several models were introduced for UPFC in literature for different type of studies in power systems. In this paper a novel comparison study between two dynamic models of UPFC with their proposed control strategies.

Keywords: FACTS, UPFC, dynamic modeling, PWM, fundamental frequency

Procedia PDF Downloads 341

Authors: Preeti Aghalayam, Jay Shah

Abstract:

Underground coal gasification (UCG) is the in-situ gasification of unmineable coals to produce syngas. In UCG, gasifying agents are injected into the coal seam, and a reactive cavity is formed due to coal consumption. The cavity formed is typically hemispherical, and this report consists of the MATLAB model of the UCG cavity to predict the composition of the output gases. There are seven radial and two time-variant ODEs. A MATLAB solver (ode15s) is used to solve the radial ODEs from the above equations. Two for-loops are implemented in the model, i.e., one for time variations and another for radial variation. In the time loop, the radial odes are solved using the MATLAB solver. The radial loop is nested inside the time loop, and the density odes are numerically solved using the Euler method. The model is validated by comparing it with the literature results of laboratory-scale experiments. The model predicts the radial and time variation of the product gases inside the cavity.

Keywords: gasification agent, MATLAB model, syngas, underground coal gasification (UCG)

Procedia PDF Downloads 199

Authors: Belalia Douma Omar, Bakhta Boukhatem, Mohamed Ghrici

Abstract:

Self-compacting concrete (SCC) developed in Japan in the late 80s has enabled the construction industry to reduce demand on the resources, improve the work condition and also reduce the impact of environment by elimination of the need for compaction. Fuzzy logic (FL) approaches has recently been used to model some of the human activities in many areas of civil engineering applications. Especially from these systems in the model experimental studies, very good results have been obtained. In the present study, a model for predicting compressive strength of SCC containing various proportions of fly ash, as partial replacement of cement has been developed by using Adaptive Neuro-Fuzzy Inference System (ANFIS). For the purpose of building this model, a database of experimental data were gathered from the literature and used for training and testing the model. The used data as the inputs of fuzzy logic models are arranged in a format of five parameters that cover the total binder content, fly ash replacement percentage, water content, super plasticizer and age of specimens. The training and testing results in the fuzzy logic model have shown a strong potential for predicting the compressive strength of SCC containing fly ash in the considered range.

Keywords: self-compacting concrete, fly ash, strength prediction, fuzzy logic

Procedia PDF Downloads 331

Authors: Debabrata Auddya, Bradley J. Roth

Abstract:

The mechanical bidomain model is used to describe a colony of cells growing on a substrate. Analytical expressions are derived for the intracellular and extracellular displacements. Mechanotransduction events are driven by the difference between the displacements in the two spaces, corresponding to the force acting on integrins. The equation for the displacement consists of two terms: one proportional to the radius that is the same in the intracellular and extracellular spaces (the monodomain term) and one that is proportional to a modified Bessel function that is responsible for mechanotransduction (the bidomain term). The model predicts that mechanotransduction occurs within a few length constants of the colony’s edge, and an expression for the length constant contains the intracellular and extracellular shear moduli and the spring constant of the integrins coupling the two spaces. The model predictions are qualitatively consistent with experiments on human embryonic stem cell colonies, in which differentiation is localized near the edge.

Keywords: cell colony, integrin, mechanical bidomain model, stem cell, stress-strain, traction force

Procedia PDF Downloads 235

Authors: Arzu K. Kamberli

Abstract:

This article examines the relationship between economics and physics, starting with Adam Smith, with a new econophysics approach in Economics-Physics with the Gauss Law model proposal using for the Electric Field calculation, which will allow us to anticipate the Global Financial Crisis. For this purpose, the similarities between the Gauss Law using the electric field calculations and the global financial crisis have been explained on the formula, and a model has been suggested to predict the risks of the financial systems from the electricity field calculations. Thus, this study is expected to help for preventing the Global Financial Crisis with the contribution of the science of economics and physics from the aspect of econophysics.

Keywords: econophysics, electric field, financial system, Gauss law, global financial crisis

Procedia PDF Downloads 280

Authors: Keneilwe Maremi, Marlien Herselman, Adele Botha

Abstract:

The main purpose and focus of this paper are to determine the Interoperability Maturity Models to consider when using School Management Systems (SMS). The importance of this is to inform and help schools with knowing which Interoperability Maturity Model is best suited for their SMS. To address the purpose, this paper will apply a scoping review to ensure that all aspects are provided. The scoping review will include papers written from 2012-2019 and a comparison of the different types of Interoperability Maturity Models will be discussed in detail, which includes the background information, the levels of interoperability, and area for consideration in each Maturity Model. The literature was obtained from the following databases: IEEE Xplore and Scopus, the following search engines were used: Harzings, and Google Scholar. The topic of the paper was used as a search term for the literature and the term ‘Interoperability Maturity Models’ was used as a keyword. The data were analyzed in terms of the definition of Interoperability, Interoperability Maturity Models, and levels of interoperability. The results provide a table that shows the focus area of concern for each Maturity Model (based on the scoping review where only 24 papers were found to be best suited for the paper out of 740 publications initially identified in the field). This resulted in the most discussed Interoperability Maturity Model for consideration (Information Systems Interoperability Maturity Model (ISIMM) and Organizational Interoperability Maturity Model for C2 (OIM)).

Keywords: interoperability, interoperability maturity model, school management system, scoping review

Procedia PDF Downloads 204

Authors: Zina Benouaret, Djamil Aissani

Abstract:

In this work, we introduce the qualitative and quantitative concept of the strong stability method in the risk process modeling two lines of business of the same insurance company or an insurance and re-insurance companies that divide between them both claims and premiums with a certain proportion. The approach proposed is based on the identification of the ruin probability associate to the model considered, with a stationary distribution of a Markov random process called a reversed process. Our objective, after clarifying the condition and the perturbation domain of parameters, is to obtain the stability inequality of the ruin probability which is applied to estimate the approximation error of a model with disturbance parameters by the considered model. In the stability bound obtained, all constants are explicitly written.

Keywords: Markov chain, risk models, ruin probabilities, strong stability analysis

Procedia PDF Downloads 244

Authors: E. Channol, O. Collet, N. Kostyuchyk, T. Mesbah, Quoc Hoang Long Nguyen

Abstract:

In this paper, a pricing model is proposed for co-integrated commodities extending Larsson model. The futures formulae have been derived and tests have been performed with non-constant volatility. The model has been applied to energy commodities (gas, CO2, energy) and soft commodities (corn, wheat). Results show that non-constant volatility leads to more accurate short term prices, which provides better evaluation of value-at-risk and more generally improve the risk management.

Keywords: co-integration, soft commodities, risk management, value-at-risk

Procedia PDF Downloads 545

Authors: Timothy E. Frank, Josh R. Aldred, Sophie B. Boulware, Michelle K. Cabonce, Justin H. White

Abstract:

Materials degrade at different rates in different environments depending on factors such as temperature, aridity, salinity, and solar radiation. Therefore, predicting asset longevity depends, in part, on the environmental conditions to which the asset is exposed. Heating, ventilation, and air conditioning (HVAC) systems are critical to building operations yet are responsible for a significant proportion of their energy consumption. HVAC energy use increases substantially with slight operational inefficiencies. Understanding the environmental influences on HVAC degradation in detail will inform maintenance schedules and capital investment, reduce energy use, and increase lifecycle management efficiency. HVAC inspection records spanning 14 years from 21 locations across the United States were compiled and associated with the climate conditions to which they were exposed. Three environmental features were explored in this study: average high temperature, average low temperature, and annual precipitation, as well as four non-environmental features. Initial insights showed no correlations between individual features and the rate of HVAC component degradation. Using neighborhood component analysis, however, the most critical features related to degradation were identified. Two models were considered, and results varied between them. However, longitude and latitude emerged as potentially the best predictors of average HVAC component degradation. Further research is needed to evaluate additional environmental features, increase the resolution of the environmental data, and develop more robust models to achieve more conclusive results.

Keywords: climate, degradation, HVAC, neighborhood component analysis

Procedia PDF Downloads 426

Authors: Khaled S. Abdallah, Abdel-Aziz M. Mohamed

Abstract:

Moving industries consume numerous resources and dispose masses of used packaging materials. Proper sorting, recycling and disposing the packaging materials is necessary to avoid a sever pollution disaster. This research paper presents a conceptual model to propose sustainable truck rental operations instead of the regular one. An optimization model was developed to select the locations of truck rental centers, collection sites, maintenance and repair sites, and identify the rental fees to be charged for all routes that maximize the total closed supply chain profits. Fixed costs of vehicle purchasing, costs of constructing collection centers and repair centers, as well as the fixed costs paid to use disposal and recycling centers are considered. Operating costs include the truck maintenance, repair costs as well as the cost of recycling and disposing the packing materials, and the costs of relocating the truck are presented in the model. A mixed integer model is developed followed by a simulation model to examine the factors affecting the operation of the model.

Keywords: modeling, truck rental, supply chains management.

Procedia PDF Downloads 223

Authors: Todd Zhou, Mikhail Yurochkin

Abstract:

Out-of-distribution (OOD) detection is receiving increasing amounts of attention in the machine learning research community, boosted by recent technologies, such as autonomous driving and image processing. This newly-burgeoning field has called for the need for more effective and efficient methods for out-of-distribution generalization methods. Without accessing the label information, deploying machine learning models to out-of-distribution domains becomes extremely challenging since it is impossible to evaluate model performance on unseen domains. To tackle this out-of-distribution detection difficulty, we designed a model selection pipeline algorithm and developed a model selection framework with different impurity and randomness measurements to evaluate and choose the best-performing models for out-of-distribution data. By exploring different randomness scores based on predicted probabilities, we adopted the out-of-distribution entropy and developed a custom-designed score, ”CombinedScore,” as the evaluation criterion. This proposed score was created by adding labeled source information into the judging space of the uncertainty entropy score using harmonic mean. Furthermore, the prediction bias was explored through the equality of opportunity violation measurement. We also improved machine learning model performance through model calibration. The effectiveness of the framework with the proposed evaluation criteria was validated on the Folktables American Community Survey (ACS) datasets.

Keywords: model selection, domain generalization, model fairness, randomness measurements, bias index

Procedia PDF Downloads 120

Authors: Rene A. Salmingo

Abstract:

In pursuing higher educational institution’s transition to sustainable future, this research initiative was conducted. The study aimed to determine the level of sustainability, environmental impact and life cycle phase assessment of the industrial technology research projects at the Institute of Information Technology, Carlos Hilado Memorial State College (CHMSC), Alijis Campus, Bacolod City, Negros Occidental, Philippines. The research method was descriptive utilizing a researcher made questionnaire to assess the ten (10) industrial technology completed research projects. Mean was used to treat the data and instrument for Good and Scates’ validity through revisions and consultations from the environmental experts, technology specialists; and Cronbach Alpha was used to measure reliability. Results indicated that the level of sustainability and life cycle phase assessment was very high while the environmental impact of the industrial research projects was rated low. Moreover, the current research projects and environmental education courses in the college were relevant to support sustainable industrial technology research projects in the future. Hence, this research initiative will contribute to the transformation of CHMSC as a greening higher educational institution and as a center for sustainable development in the region.

Keywords: environmental impact, industrial technology research projects, life cycle phase assessment, sustainability

Procedia PDF Downloads 185

Authors: Ghassan Al-Dulaimi

Abstract:

This paper studied the biochemical parameter (BOD5) and (DO) for the Thames River (Canada-Ontario). Water samples have been collected from Thames River along different points between Chatham to Woodstock and were analysed for various water quality parameters during the low flow season (April). The study involves the application of the stream water quality model QUAL2K model to simulate and predict the dissolved oxygen (DO) and biochemical oxygen demand (BOD5) profiles for Thames River in a stretch of 251 kilometers. The model output showed that DO in the entire river was within the limit of not less than 4 mg/L. For Carbonaceous Biochemical Oxygen Demand CBOD, the entire river may be divided into two main reaches; the first one is extended from Chatham City (0 km) to London (150 km) and has a CBOD concentration of 2 mg/L, and the second reach has CBOD range (2–4) mg/L in which begins from London city and extend to near Woodstock city (73km).

Keywords: biochemical oxygen demand, dissolved oxygen, Thames river, QUAL2K model

Procedia PDF Downloads 88

Authors: Tanira Kingi, Oscar Montes Oca, Reina Tamepo

Abstract:

The introduction of the Climate Change Response (Zero Carbon) Amendment Act (2019) and the National Policy Statement for Freshwater Management (2020) both contain underpinning statements that refer to the principles of the Treaty of Waitangi and cultural concepts of stewardship and environmental protection. Maori interests in New Zealand’s agricultural, forestry, fishing and horticultural sectors are significant. The organizations that manage these investments do so on behalf of extended family groups that hold inherited interests based on genealogical connections (whakapapa) to particular tribal units (iwi and hapu) and areas of land (whenua) and freshwater bodies (wai). This paper draws on the findings of current research programmes funded by the New Zealand Agricultural Greenhouse Gas Research Centre (NZAGRC) and the Our Land & Water National Science Challenge (OLW NSC) to understand the impact of cultural knowledge and imperatives on agricultural GHG and freshwater mitigation and land-use change decisions. In particular, the research outlines mitigation and land-use change scenario decision support frameworks that model changes in emissions profiles (reductions in biogenic methane, nitrous oxide and nutrient emissions to freshwater) of agricultural and forestry production systems along with impacts on key economic indicators and socio-cultural factors. The paper also assesses the effectiveness of newly introduced partnership arrangements between Maori groups/organizations and key government agencies on policy co-design and implementation, and in particular, decisions to adopt mitigation practices and to diversify land use.

Keywords: co-design and implementation of environmental policy, indigenous environmental knowledge, Māori land tenure and agribusiness, mitigation and land use change decision support frameworks

Procedia PDF Downloads 209

Authors: S. Belhour, A. K. Ferouani, C. Azizi

Abstract:

In recent years, a considerable effort (experience, numerical simulation, and theoretical prediction models) has characterised by high efficiency and low cost. Then an improved physics analytical model for simulating is proposed. The performance of GaAs MESFETs has been developed for use in device design for high frequency. This model is based on mathematical analysis, and a new approach for the standard model is proposed, this approach allowed to conceive applicable model for MESFET’s operating in the turn-one or pinch-off region and valid for the short-channel and the long channel MESFET’s in which the two dimensional potential distribution contributed by the depletion layer under the gate is obtained by conventional approximation. More ever, comparisons between the analytical models with different values of mobility are proposed, and a good agreement is obtained.

Keywords: analytical, gallium arsenide, MESFET, mobility, models

Procedia PDF Downloads 71

Authors: Usiobaifo Agharese Rosemary, Osaseri Roseline Oghogho

Abstract:

Diabetes is a complex group of disease with a variety of causes; it is a disorder of the body metabolism in the digestion of carbohydrates food. The application of machine learning in the field of medical diagnosis has been the focus of many researchers and the use of recognition and classification model as a decision support tools has help the medical expert in diagnosis of diseases. Considering the large volume of medical data which require special techniques, experience, and high diagnostic skill in the diagnosis of diseases, the application of an artificial intelligent system to assist medical personnel in order to enhance their efficiency and accuracy in diagnosis will be an invaluable tool. In this study will propose a diabetes diagnosis model using rough set and K-nearest Neighbor classifier algorithm. The system consists of two modules: the feature extraction module and predictor module, rough data set is used to preprocess the attributes while K-nearest neighbor classifier is used to classify the given data. The dataset used for this model was taken for University of Benin Teaching Hospital (UBTH) database. Half of the data was used in the training while the other half was used in testing the system. The proposed model was able to achieve over 80% accuracy.

Keywords: classifier algorithm, diabetes, diagnostic model, machine learning

Procedia PDF Downloads 332

Authors: G. Medkour Ishak-Boushaki, A. Taibi, M. Allab

Abstract:

Quantitative environmental radioactivity measurements are needed to determine the level of exposure of a population to ionizing radiations and for the assessment of the associated risks. Gamma spectrometry remains a very powerful tool for the analysis of radionuclides present in an environmental sample but the basic problem in such measurements is the low rate of detected events. Using large environmental samples could help to get around this difficulty but, unfortunately, new issues are raised by gamma rays attenuation and self-absorption. Recently, a new method has been suggested, to detect and identify without quantification, in a short time, a gamma ray of a low count source. This method does not require, as usually adopted in gamma spectrometry measurements, a pulse height spectrum acquisition. It is based on a chronological record of each detected photon by simultaneous measurements of its energy ε and its arrival time τ on the detector, the pair parameters [ε,τ] defining an event mode sequence (EMS). The EMS serials are analyzed sequentially by a Bayesian approach to detect the presence of a given radioactive source. The main object of the present work is to test the applicability of this sequential approach in radioactive environmental materials detection. Moreover, for an appropriate health oversight of the public and of the concerned workers, the analysis has been extended to get a reliable quantification of the radionuclides present in environmental samples. For illustration, we consider as an example, the problem of detection and quantification of 238U. Monte Carlo simulated experience is carried out consisting in the detection, by a Ge(Hp) semiconductor junction, of gamma rays of 63 keV emitted by 234Th (progeny of 238U). The generated EMS serials are analyzed by a Bayesian inference. The application of the sequential Bayesian approach, in environmental radioactivity analysis, offers the possibility of reducing the measurements time without requiring large environmental samples and consequently avoids the attached inconvenient. The work is still in progress.

Keywords: Bayesian approach, event mode sequence, gamma spectrometry, Monte Carlo method

Procedia PDF Downloads 493

Authors: Lee Li

Abstract:

The strategic management literature posits that the major motive of strategic alliances is to share resources, costs and risks. However, the literature also indicates that such sharing leads to transaction costs which are positively correlated with environmental dynamism. As such, it is not clear why firms are willing to cover high transaction costs for sharing resources, costs and risks. This study categorizes resources into firm-specific and general resource; costs into accounting and non-accounting cost; and risks into visible and invisible risks. Using data from 167 Canadian firms in technology industries, we find that sharing firm-specific resources and non-accounting costs are negatively correlated with environmental dynamism but sharing general resources, accounting costs and visible risks are positively correlated with environmental dynamism. Findings suggest that sharing certain resources, costs and risks do not necessarily incur high transaction costs.

Keywords: environmental dynamism, strategic alliances, resource/cost/risk sharing

Procedia PDF Downloads 361

Authors: Kveta Olsanova, Gina Cook, Marija Zlatic

Abstract:

This paper discusses the theoretical framework suggesting the dependencies between luxury brands’ CSR (Corporate Social Responsibility) variables and the purchase intention of luxury shoppers. The framework is based on a literature review and in-depth individual interviews with a sample of luxury users and buyers. The measures of the model are based on existing research and the authors' qualitative research results. The model suggests that purchase intention in the luxury segment is dependent on the luxury values (symbolic, experiential, functional and social), individual sustainable dimension (composed of societal, environmental and economic variables) and awareness of the brand’s CSR, the last two relationships being potentially moderated by certain conditions such as demographics and general attitudes towards CSR and sustainability. The model’s output is in the formulation of several hypotheses, to be tested in an upcoming quantitative study. The qualitative phase indicated that the perceived symbolic, functional and experiential value dimensions of luxury brands were stronger drivers of purchase intention compared to the sustainable dimension. The contribution of the research consists of highlighting CSR’s impact on customer purchase intent as a potential implication for luxury brand management due to two aspects: (i) consumer awareness of the existing CSR activities of luxury brands is low, and this might be challenged by the demands of Gen Z entrants into the lux industry as they are known for their positive approach to CSR; (ii) the UN’s SDGs will bring CSR to the attention of all industries, including currently 'CSR silent' segments represented by luxury. Our research should contribute to incorporation of strategic CSR into the policies and strategies of the luxury segment by providing evidence that luxury customers do care.

Keywords: CSR, luxury shoppers, purchase intention, sustainability

Procedia PDF Downloads 147

Authors: Felix Aberu

Abstract:

The high rate of greenhouse gas (CO₂) emission and increased concentration of Carbon Dioxide in the atmosphere are not unconnected to both human and natural activities. This has caused climate change and global warming in the world. The adverse effect of these climatic changes has no doubt threatened human existence. Hence, this study examined the effects of environmental and climate influence on mortality and morbidity rates, with particular reference to the world’s leading CO₂ emission countries, using both the pre-estimation, estimation, and post-estimation techniques for more dependable outcomes. Hence, the System Generalized Method of Moments (SGMM) was adopted as the main estimation technique for the data analysis from 1996 to 2023. The coefficient of carbon emissions confirmed a positive and significant relationship among CO₂ emission, mortality, and morbidity rates in the world’s leading CO₂ emissions countries, which implies that carbon emission has contributed to mortality and morbidity rates in the world. Therefore, significant action should be taken to facilitate the expansion of environmental protection and sustainability initiatives in any CO₂ emissions nations of the world.

Keywords: environmental, mortality, morbidity, health outcomes, carbon emissions

Procedia PDF Downloads 49

Authors: S. Jursová, P. Pustějovská, S. Brožová, J. Bilík

Abstract:

The paper deals with possibilities of interpretation of iron ore reducibility tests. It presents a mathematical model developed at Centre ENET, VŠB–Technical University of Ostrava, Czech Republic for an evaluation of metallurgical material of blast furnace feedstock such as iron ore, sinter or pellets. According to the data from the test, the model predicts its usage in blast furnace technology and its effects on production parameters of shaft aggregate. At the beginning, the paper sums up the general concept and experience in mathematical modelling of iron ore reduction. It presents basic equation for the calculation and the main parts of the developed model. In the experimental part, there is an example of usage of the mathematical model. The paper describes the usage of data for some predictive calculation. There are presented material, method of carried test of iron ore reducibility. Then there are graphically interpreted effects of used material on carbon consumption, rate of direct reduction and the whole reduction process.

Keywords: blast furnace technology, iron ore reduction, mathematical model, prediction of iron ore reduction

Procedia PDF Downloads 669

Authors: Rungrot Trongsakul

Abstract:

This paper was aimed to study the strategic cooperation development of Thailand in accordance with the door open policy of Myanmar, by use of DIMES Model: Diplomacy, Information, Military and Economics, Socio-Culture. This research employed qualitative method, aiming to study, analyze and synthesize the content of laws, policies, relevant research papers and documents, and relevant theories, and to study external environment and national power based on DIMES Model. The five steps of strategic development utilized in this study included (1) conceptual framework and definition; (2) environmental scanning; (3) assessing; (4) determining; and (5) drafting strategic plan. The suggested strategies were based on the concept of 'Soft Power'. Therefore, the determination of measures, action plans or projects as strategic means of public and private organizations should be based on sincere participation among people and communities living on the borders shared by both countries. Adoption of education, learning and sharing process is a key to building sustainability of the countries’ strategic cooperation, while an application of 'Soft Power' in all dimensions of the cooperation between the two countries was suggested.

Keywords: education, strategic cooperation, Thailand-Myanmar borders, sustainability

Procedia PDF Downloads 350

Authors: Jose Francisco Ferreira Ribeiro, Alexandre Bevilacqua Leoneti, Andre Lucirton Costa

Abstract:

This paper presents a mathematical model in binary variables 0/1 to make the assignment of surgical procedures to the operating rooms in a hospital. The proposed mathematical model is based on the generalized assignment problem, which maximizes the sum of preferences for the use of the operating rooms by doctors, respecting the time available in each room. The corresponding program was written in Visual Basic of Microsoft Excel, and tested to schedule surgeries at St. Lydia Hospital in Ribeirao Preto, Brazil.

Keywords: generalized assignment problem, logistics, optimization, scheduling

Procedia PDF Downloads 287

Authors: Mohammad Parvaresh, Mahdi Babaee, Bahareh Arghand, Davood Nourmohammadi

Abstract:

Environmental degradation is caused by social inequalities and the inappropriate use of nature and a factor in the violation of human rights. Indeed, the right to a safe, healthy and ecologically-balanced environment is an independent human right. Therefore, the relationship between human rights and environmental protection is crucial for the study of social justice and sustainable development, and environmental problems are a result of the failure to realize social and economic justice. In this regard, 'article 50 of the constitution of the Islamic Republic of Iran as a general principle have many of the concepts of sustainable development, including: the growth and improvement of human life, the rights of present and future generations, and the integrity of the inner and outer generation, the prohibition of any environmental degradation'. Also, Charter on Citizen’s Rights, which was conveyed by the President of the Islamic Republic of Iran, Mr. Rouhani refers to the right to a healthy environment and sustainable development. In this regard in 2013, Tehran Province Water and Wastewater Co. defined a plan called 'Tehran’s Health Line' was includes Western and Eastern part by about 26 kilometers of water transferring pipelines varied 1000 to 2000 mm diameters. This project aims to: (1) Transfer water from the northwest water treatment plant to the southwest areas, which suffer from qualitative and quantitative water, in order to mix with the improper wells’ water; (2) Reducing the water consumption provided by harvesting from wells which results in improving the underground water resources, causing the large settlements and stopping the immigrating slums into the center or north side of the city. All of the financial resources accounted for 53,000,000 US$ which is mobilized by Tehran Province Water and Wastewater Co. to expedite the work. The present study examines the Tehran Health Line plan and the purpose of implementation of this plan to achieve environmental protection, environmental justice and citizenship rights for all people who live in Tehran.

Keywords: environmental justice, international environmental law, erga omnes, charter on citizen's rights, Tehran health line

Procedia PDF Downloads 268

Authors: Özge Selin Çevik, Leyla Şahin, Gülhan Örekeci Temel

Abstract:

The early postnatal period is critical for the development of cognitive and emotional functions. Maternal separation is a detrimental postnatal influence, whereas environmental enrichment is a therapeutic and protective agent. It is unclear if long-term environmental enrichment can compensate for the effects of maternal separation stress on anxiety behavior. This study was designed to examine how environmental enrichment affects anxiety levels and corticosterone levels in maternally separated rats. There are six main groups in this study: control (C), maternal separation+standard cage (MS), maternal separation+enriched environment (MSE), enriched environment (E), the maternal separation that decapitated at postnatal (PN) 21 (MS21), and standard cage that decapitated at PN21 (STD21). The maternal separation procedure consisted of PN for 21 days (between 09:00 a.m and 12:00 a.m). Enriched (E, MSE) or standard cage environment rats (MS, C) spent PN (22-55) days in either enriched cages or standard cages. Anxiety and locomotor activity were examined with the open field and elevated plus-maze test. Blood corticosterone level was evaluated by the enzyme-linked immunosorbent assay (ELISA) method. Results showed that maternal separation (MS) increased locomotor activity and anxiety. An enriched environment (E) did not change the locomotor activity. MSE group’s anxiety and locomotor activity did not change. Corticosterone levels increased in the maternal separation group that decapitated at the PN 21 days. Maternal separation increases anxiety. Environmental enrichment alone was insufficient to cause alterations in the anxiety level. In addition, environmental enrichment did not ameliorate the anxiety level in maternally separated rats. However, environmental enrichment decreased the locomotor activity in the maternally separated rats.

Keywords: maternal separation, environment enrichment, stress, hippocampus, anxiety, memory, rat

Procedia PDF Downloads 87

Authors: Abhijeet Ostawal, Parmjit Lall

Abstract:

The run times for a large strategic model that we were managing had become too long leading to delays in project delivery, increased costs and loss in productivity. Software developers are continuously working towards developing more efficient tools by changing their algorithms and processes. The issue faced by our team was how do you apply the latest technologies on validated existing models which are based on much older versions of software that do not have the latest software capabilities. The multi-model transport model that we had could only be run in sequential assignment order. Recent upgrades to the software now allowed the assignment to be run in parallel, a concept called parallelization. Parallelization is a Python script working only within the latest version of the software. A full model transfer to the latest version was not possible due to time, budget and the potential changes in trip assignment. This article is to show the method to adapt and update the Python script in such a way that it can be used in older software versions by calling the latest version and then recalling the old version for assignment model without affecting the results. Through a process of trial-and-error run time savings of up to 30-40% have been achieved. Assignment results were maintained within the older version and through this learning process we’ve applied this methodology to other even older versions of the software resulting in huge time savings, more productivity and efficiency for both client and consultant.

Keywords: model run time, demand model, parallelisation, python scripting

Procedia PDF Downloads 113

Authors: F. A. Al-Awadhi, D. Al-Hulail

Abstract:

In this study, we applied the Bayesian hierarchical model to detect single and multiple change points for daily earthquake body wave magnitude. The change point analysis is used in both backward (off-line) and forward (on-line) statistical research. In this study, it is used with the backward approach. Different types of change parameters are considered (mean, variance or both). The posterior model and the conditional distributions for single and multiple change points are derived and implemented using BUGS software. The model is applicable for any set of data. The sensitivity of the model is tested using different prior and likelihood functions. Using Mb data, we concluded that during January 2002 and December 2003, three changes occurred in the mean magnitude of Mb in Kuwait and its vicinity.

Keywords: multiple change points, Markov Chain Monte Carlo, earthquake magnitude, hierarchical Bayesian mode

Procedia PDF Downloads 452