Search results for: residual life prediction
7049 A Survey on Early Screen Exposure during Infancy and Autism
Authors: I. Mahmood
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This survey was conducted to explore the hypothesis that excessive screen exposure combined with a subsequent decrease in parent-child interaction during infancy might be associated with autism. The main questions being asked are: Were children with autism exposed to long hours of screen time during the first 2 years of life? And what was the reason(s) for exposure at such an early age? Other variables were also addressed in this survey. An Arabic questionnaire was administered online (June 2019) via a Facebook page, relatively well-known in Arab countries. 1725 parents of children diagnosed with autism participated in this survey. Results show that 80.9% of children surveyed who were diagnosed with autism had been exposed to screens for long periods of time during the first 2 years of life. It can be inferred from the results of this survey that over-exposure to screens disrupt the parent-child interaction which is shown to be associated with ASD. The results of this survey highlight the harmful effects of screen exposure during infancy and the importance of parent-child interaction during the critical period of brain development. This paper attempts to further explore the connection between parent-child interaction and ASD, as well as serve as a call for further research and investigation of the relation between screens and parent-child interactions during infancy and Autism.Keywords: attachment disorder, autism, screen exposure, virtual autism
Procedia PDF Downloads 1207048 Case Study of Mechanised Shea Butter Production in South-Western Nigeria Using the LCA Approach from Gate-to-Gate
Authors: Temitayo Abayomi Ewemoje, Oluwamayowa Oluwafemi Oluwaniyi
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Agriculture and food processing, industry are among the largest industrial sectors that uses large amount of energy. Thus, a larger amount of gases from their fuel combustion technologies is being released into the environment. The choice of input energy supply not only directly having affects the environment, but also poses a threat to human health. The study was therefore designed to assess each unit production processes in order to identify hotspots using life cycle assessments (LCA) approach in South-western Nigeria. Data such as machine power rating, operation duration, inputs and outputs of shea butter materials for unit processes obtained at site were used to modelled Life Cycle Impact Analysis on GaBi6 (Holistic Balancing) software. Four scenarios were drawn for the impact assessments. Material sourcing from Kaiama, Scenarios 1, 3 and Minna Scenarios 2, 4 but different heat supply sources (Liquefied Petroleum Gas ‘LPG’ Scenarios 1, 2 and 10.8 kW Diesel Heater, scenarios 3, 4). Modelling of shea butter production on GaBi6 was for 1kg functional unit of shea butter produced and the Tool for the Reduction and Assessment of Chemical and other Environmental Impacts (TRACI) midpoint assessment was tool used to was analyse the life cycle inventories of the four scenarios. Eight categories in all four Scenarios were observed out of which three impact categories; Global Warming Potential (GWP) (0.613, 0.751, 0.661, 0.799) kg CO2¬-Equiv., Acidification Potential (AP) (0.112, 0.132, 0.129, 0.149) kg H+ moles-Equiv., and Smog (0.044, 0.059, 0.049, 0.063) kg O3-Equiv., categories had the greater impacts on the environment in Scenarios 1-4 respectively. Impacts from transportation activities was also seen to contribute more to these environmental impact categories due to large volume of petrol combusted leading to releases of gases such as CO2, CH4, N2O, SO2, and NOx into the environment during the transportation of raw shea kernel purchased. The ratio of transportation distance from Minna and Kaiama to production site was approximately 3.5. Shea butter unit processes with greater impacts in all categories was the packaging, milling and with the churning processes in ascending order of magnitude was identified as hotspots that may require attention. From the 1kg shea butter functional unit, it was inferred that locating production site at the shortest travelling distance to raw material sourcing and combustion of LPG for heating would reduce all the impact categories assessed on the environment.Keywords: GaBi6, Life cycle assessment, shea butter production, TRACI
Procedia PDF Downloads 3097047 Relations of Progression in Cognitive Decline with Initial EEG Resting-State Functional Network in Mild Cognitive Impairment
Authors: Chia-Feng Lu, Yuh-Jen Wang, Yu-Te Wu, Sui-Hing Yan
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This study aimed at investigating whether the functional brain networks constructed using the initial EEG (obtained when patients first visited hospital) can be correlated with the progression of cognitive decline calculated as the changes of mini-mental state examination (MMSE) scores between the latest and initial examinations. We integrated the time–frequency cross mutual information (TFCMI) method to estimate the EEG functional connectivity between cortical regions, and the network analysis based on graph theory to investigate the organization of functional networks in aMCI. Our finding suggested that higher integrated functional network with sufficient connection strengths, dense connection between local regions, and high network efficiency in processing information at the initial stage may result in a better prognosis of the subsequent cognitive functions for aMCI. In conclusion, the functional connectivity can be a useful biomarker to assist in prediction of cognitive declines in aMCI.Keywords: cognitive decline, functional connectivity, MCI, MMSE
Procedia PDF Downloads 3807046 Evaluation of Particle Settling in Flow Chamber
Authors: Abdulrahman Alenezi, B. Stefan
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Abstract— The investigation of fluids containing particles or filaments includes a category of complex fluids and is vital in both theory and application. The forecast of particle behaviors plays a significant role in the existing technology as well as future technology. This paper focuses on the prediction of the particle behavior through the investigation of the particle disentrainment from a pipe on a horizontal air stream. This allows for examining the influence of the particle physical properties on its behavior when falling on horizontal air stream. This investigation was conducted on a device located at the University of Greenwich's Medway Campus. Two materials were selected to carry out this study: Salt and Glass Beads particles. The shape of the Slat particles is cubic where the shape of the Glass Beads is almost spherical. The outcome from the experimental work were presented in terms of distance travelled by the particles according to their diameters as After that, the particles sizes were measured using Laser Diffraction device and used to determine the drag coefficient and the settling velocity.Keywords: flow experiment, drag coefficient, Particle Settling, Flow Chamber
Procedia PDF Downloads 1287045 Forecasting Lake Malawi Water Level Fluctuations Using Stochastic Models
Authors: M. Mulumpwa, W. W. L. Jere, M. Lazaro, A. H. N. Mtethiwa
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The study considered Seasonal Autoregressive Integrated Moving Average (SARIMA) processes to select an appropriate stochastic model to forecast the monthly data from the Lake Malawi water levels for the period 1986 through 2015. The appropriate model was chosen based on SARIMA (p, d, q) (P, D, Q)S. The Autocorrelation function (ACF), Partial autocorrelation (PACF), Akaike Information Criteria (AIC), Bayesian Information Criterion (BIC), Box–Ljung statistics, correlogram and distribution of residual errors were estimated. The SARIMA (1, 1, 0) (1, 1, 1)12 was selected to forecast the monthly data of the Lake Malawi water levels from August, 2015 to December, 2021. The plotted time series showed that the Lake Malawi water levels are decreasing since 2010 to date but not as much as was the case in 1995 through 1997. The future forecast of the Lake Malawi water levels until 2021 showed a mean of 474.47 m ranging from 473.93 to 475.02 meters with a confidence interval of 80% and 90% against registered mean of 473.398 m in 1997 and 475.475 m in 1989 which was the lowest and highest water levels in the lake respectively since 1986. The forecast also showed that the water levels of Lake Malawi will drop by 0.57 meters as compared to the mean water levels recorded in the previous years. These results suggest that the Lake Malawi water level may not likely go lower than that recorded in 1997. Therefore, utilisation and management of water-related activities and programs among others on the lake should provide room for such scenarios. The findings suggest a need to manage the Lake Malawi jointly and prudently with other stakeholders starting from the catchment area. This will reduce impacts of anthropogenic activities on the lake’s water quality, water level, aquatic and adjacent terrestrial ecosystems thereby ensuring its resilience to climate change impacts.Keywords: forecasting, Lake Malawi, water levels, water level fluctuation, climate change, anthropogenic activities
Procedia PDF Downloads 2227044 Low-Cost, Portable Optical Sensor with Regression Algorithm Models for Accurate Monitoring of Nitrites in Environments
Authors: David X. Dong, Qingming Zhang, Meng Lu
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Nitrites enter waterways as runoff from croplands and are discharged from many industrial sites. Excessive nitrite inputs to water bodies lead to eutrophication. On-site rapid detection of nitrite is of increasing interest for managing fertilizer application and monitoring water source quality. Existing methods for detecting nitrites use spectrophotometry, ion chromatography, electrochemical sensors, ion-selective electrodes, chemiluminescence, and colorimetric methods. However, these methods either suffer from high cost or provide low measurement accuracy due to their poor selectivity to nitrites. Therefore, it is desired to develop an accurate and economical method to monitor nitrites in environments. We report a low-cost optical sensor, in conjunction with a machine learning (ML) approach to enable high-accuracy detection of nitrites in water sources. The sensor works under the principle of measuring molecular absorptions of nitrites at three narrowband wavelengths (295 nm, 310 nm, and 357 nm) in the ultraviolet (UV) region. These wavelengths are chosen because they have relatively high sensitivity to nitrites; low-cost light-emitting devices (LEDs) and photodetectors are also available at these wavelengths. A regression model is built, trained, and utilized to minimize cross-sensitivities of these wavelengths to the same analyte, thus achieving precise and reliable measurements with various interference ions. The measured absorbance data is input to the trained model that can provide nitrite concentration prediction for the sample. The sensor is built with i) a miniature quartz cuvette as the test cell that contains a liquid sample under test, ii) three low-cost UV LEDs placed on one side of the cell as light sources, with each LED providing a narrowband light, and iii) a photodetector with a built-in amplifier and an analog-to-digital converter placed on the other side of the test cell to measure the power of transmitted light. This simple optical design allows measuring the absorbance data of the sample at the three wavelengths. To train the regression model, absorbances of nitrite ions and their combination with various interference ions are first obtained at the three UV wavelengths using a conventional spectrophotometer. Then, the spectrophotometric data are inputs to different regression algorithm models for training and evaluating high-accuracy nitrite concentration prediction. Our experimental results show that the proposed approach enables instantaneous nitrite detection within several seconds. The sensor hardware costs about one hundred dollars, which is much cheaper than a commercial spectrophotometer. The ML algorithm helps to reduce the average relative errors to below 3.5% over a concentration range from 0.1 ppm to 100 ppm of nitrites. The sensor has been validated to measure nitrites at three sites in Ames, Iowa, USA. This work demonstrates an economical and effective approach to the rapid, reagent-free determination of nitrites with high accuracy. The integration of the low-cost optical sensor and ML data processing can find a wide range of applications in environmental monitoring and management.Keywords: optical sensor, regression model, nitrites, water quality
Procedia PDF Downloads 677043 Unsteady 3D Post-Stall Aerodynamics Accounting for Effective Loss in Camber Due to Flow Separation
Authors: Aritras Roy, Rinku Mukherjee
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The current study couples a quasi-steady Vortex Lattice Method and a camber correcting technique, ‘Decambering’ for unsteady post-stall flow prediction. The wake is force-free and discrete such that the wake lattices move with the free-stream once shed from the wing. It is observed that the time-averaged unsteady coefficient of lift sees a relative drop at post-stall angles of attack in comparison to its steady counterpart for some angles of attack. Multiple solutions occur at post-stall and three different algorithms to choose solutions in these regimes show both unsteadiness and non-convergence of the iterations. The distribution of coefficient of lift on the wing span also shows sawtooth. Distribution of vorticity changes both along span and in the direction of the free-stream as the wake develops over time with distinct roll-up, which increases with time.Keywords: post-stall, unsteady, wing, aerodynamics
Procedia PDF Downloads 3627042 Design and Implementation of an Effective Machine Learning Approach to Crime Prediction and Prevention
Authors: Ashish Kumar, Kaptan Singh, Amit Saxena
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Today, it is believed that crimes have the greatest impact on a person's ability to progress financially and personally. Identifying places where individuals shouldn't go is crucial for preventing crimes and is one of the key considerations. As society and technologies have advanced significantly, so have crimes and the harm they wreak. When there is a concentration of people in one place and changes happen quickly, it is even harder to prevent. Because of this, many crime prevention strategies have been embraced as a component of the development of smart cities in numerous cities. However, crimes can occur anywhere; all that is required is to identify the pattern of their occurrences, which will help to lower the crime rate. In this paper, an analysis related to crime has been done; information related to crimes is collected from all over India that can be accessed from anywhere. The purpose of this paper is to investigate the relationship between several factors and India's crime rate. The review has covered information related to every state of India and their associated regions of the period going in between 2001- 2014. However various classes of violations have a marginally unique scope over the years.Keywords: K-nearest neighbor, random forest, decision tree, pre-processing
Procedia PDF Downloads 847041 Fuzzy Multi-Criteria Decision-Making Based on Ignatian Discernment Process
Authors: Pathinathan Theresanathan, Ajay Minj
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Ignatian Discernment Process (IDP) is an intense decision-making tool to decide on life-issues. Decisions are influenced by various factors outside of the decision maker and inclination within. This paper develops IDP in the context of Fuzzy Multi-criteria Decision Making (FMCDM) process. Extended VIKOR method is a decision-making method which encompasses even conflict situations and accommodates weightage to various issues. Various aspects of IDP, namely three ways of decision making and tactics of inner desires, are observed, analyzed and articulated within the frame work of fuzzy rules. The decision-making situations are broadly categorized into two types. The issues outside of the decision maker influence the person. The inner feeling also plays vital role in coming to a conclusion. IDP integrates both the categories using Extended VIKOR method. Case studies are carried out and analyzed with FMCDM process. Finally, IDP is verified with an illustrative case study and results are interpreted. A confused person who could not come to a conclusion is able to take decision on a concrete way of life through IDP. The proposed IDP model recommends an integrated and committed approach to value-based decision making.Keywords: AHP, FMCDM, IDP, ignatian discernment, MCDM, VIKOR
Procedia PDF Downloads 2487040 Application of Water Soluble Polymers in Chemical Enhanced Oil Recovery
Authors: M. Shahzad Kamal, Abdullah S. Sultan, Usamah A. Al-Mubaiyedh, Ibnelwaleed A. Hussein
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Oil recovery from reservoirs using conventional oil recovery techniques like water flooding is less than 20%. Enhanced oil recovery (EOR) techniques are applied to recover additional oil. Surfactant-polymer flooding is a promising EOR technique used to recover residual oil from reservoirs. Water soluble polymers are used to increase the viscosity of displacing fluids. Surfactants increase the capillary number by reducing the interfacial tension between oil and displacing fluid. Hydrolyzed polyacrylamide (HPAM) is widely used in polymer flooding applications due to its low cost and other desirable properties. HPAM works well in low-temperature and low salinity-environment. In the presence of salts HPAM viscosity decrease due to charge screening effect and it can precipitate at high temperatures in the presence of salts. Various strategies have been adopted to extend the application of water soluble polymers to high-temperature high-salinity (HTHS) reservoir. These include addition of monomers to acrylamide chain that can protect it against thermal hydrolysis. In this work, rheological properties of various water soluble polymers were investigated to find out suitable polymer and surfactant-polymer systems for HTHS reservoirs. Polymer concentration ranged from 0.1 to 1 % (w/v). Effect of temperature, salinity and polymer concentration was investigated using both steady shear and dynamic measurements. Acrylamido tertiary butyl sulfonate based copolymer showed better performance under HTHS conditions compared to HPAM. Moreover, thermoviscosifying polymer showed excellent rheological properties and increase in the viscosity was observed with increase temperature. This property is highly desirable for EOR application.Keywords: rheology, polyacrylamide, salinity, enhanced oil recovery, polymer flooding
Procedia PDF Downloads 4047039 Optimization of Urea Water Solution Injector for NH3 Uniformity Improvement in Urea-SCR System
Authors: Kyoungwoo Park, Gil Dong Kim, Seong Joon Moon, Ho Kil Lee
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The Urea-SCR is one of the most efficient technologies to reduce NOx emissions in diesel engines. In the present work, the computational prediction of internal flow and spray characteristics in the Urea-SCR system was carried out by using 3D-CFD simulation to evaluate NH3 uniformity index (NH3 UI) and its activation time according to the official New European Driving Cycle (NEDC). The number of nozzle and its diameter, two types of injection directions, and penetration length were chosen as the design variables. The optimal solutions were obtained by coupling the CFD analysis with Taguchi method. The L16 orthogonal array and small-the-better characteristics of the Taguchi method were used, and the optimal values were confirmed to be valid with 95% confidence and 5% significance level through analysis of variance (ANOVA). The results show that the optimal solutions for the NH3 UI and activation time (NH3 UI 0.22) are obtained by 0.41 and 0,125 second, respectively, and their values are improved by 85.0% and 10.7%, respectively, compared with those of the base model.Keywords: computational fluid dynamics, NH3 uniformity index, optimization, Taguchi method, Urea-SCR system, UWS injector
Procedia PDF Downloads 2607038 Using Classifiers to Predict Student Outcome at Higher Institute of Telecommunication
Authors: Fuad M. Alkoot
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We aim at highlighting the benefits of classifier systems especially in supporting educational management decisions. The paper aims at using classifiers in an educational application where an outcome is predicted based on given input parameters that represent various conditions at the institute. We present a classifier system that is designed using a limited training set with data for only one semester. The achieved system is able to reach at previously known outcomes accurately. It is also tested on new input parameters representing variations of input conditions to see its prediction on the possible outcome value. Given the supervised expectation of the outcome for the new input we find the system is able to predict the correct outcome. Experiments were conducted on one semester data from two departments only, Switching and Mathematics. Future work on other departments with larger training sets and wider input variations will show additional benefits of classifier systems in supporting the management decisions at an educational institute.Keywords: machine learning, pattern recognition, classifier design, educational management, outcome estimation
Procedia PDF Downloads 2727037 Concussion Prediction for Speed Skater Impacting on Crash Mats by Computer Simulation Modeling
Authors: Yilin Liao, Hewen Li, Paula McConvey
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Concussion for speed skaters often occurs when skaters fall on the ice and impact the crash mats during practices and competition races. Gaining insight into the impact of interactions is of essential interest as it is directly related to skaters’ potential health risks and injuries. Precise concussion measurements are challenging and very difficult, making computer simulation the only reliable way to analyze accidents. This research aims to create the crash mat and skater’s multi-body model using Solidworks, develop a computer simulation model for skater-mat impact using ANSYS software, and predict the skater’s concussion degree by evaluating the “head injury criteria” (HIC) through the resulting accelerations. The developed method and results help understand the relationship between impact parameters and concussion risk for speed skaters and inform the design of crash mats and skating rink layouts more specifically by considering athletes’ health risks.Keywords: computer simulation modeling, concussion, impact, speed skater
Procedia PDF Downloads 1347036 Use the Null Space to Create Starting Point for Stochastic Programming
Authors: Ghussoun Al-Jeiroudi
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Stochastic programming is one of the powerful technique which is used to solve real-life problems. Hence, the data of real-life problems is subject to significant uncertainty. Uncertainty is well studied and modeled by stochastic programming. Each day, problems become bigger and bigger and the need for a tool, which does deal with large scale problems, increase. Interior point method is a perfect tool to solve such problems. Interior point method is widely employed to solve the programs, which arise from stochastic programming. It is an iterative technique, so it is required a starting point. Well design starting point plays an important role in improving the convergence speed. In this paper, we propose a starting point for interior point method for multistage stochastic programming. Usually, the optimal solution of stage k+1 is used as starting point for the stage k. This point has the advantage of being close to the solution of the current program. However, it has a disadvantage; it is not in the feasible region of the current program. So, we suggest to take this point and modifying it. That is by adding to it a vector in the null space of the matrix of the unchanged constraints because the solution will change only in the null space of this matrix.Keywords: interior point methods, stochastic programming, null space, starting points
Procedia PDF Downloads 4117035 Crude Oil Electrostatic Mathematical Modelling on an Existing Industrial Plant
Authors: Fatemeh Yazdanmehr, Iulian Nistor
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The scope of the current study is the prediction of water separation in a two-stage industrial crude oil desalting plant. This research study was focused on developing a desalting operation in an existing production unit of one Iranian heavy oil field with 75 MBPD capacity. Because of some operational issues, such as oil dehydration at high temperatures, the optimization of the desalter operational parameters was essential. The mathematical desalting is modeled based on the population balance method. The existing operational data is used for tuning and validation of the accuracy of the modeling. The inlet oil temperature to desalter used was decreased from 110°C to 80°C, and the desalted electrical field was increased from 0.75 kv to 2.5 kv. The proposed condition for the desalter also meets the water oil specification. Based on these conditions of desalter, the oil recovery is increased by 574 BBL/D, and the gas flaring decrease by 2.8 MMSCF/D. Depending on the oil price, the additional production of oil can increase the annual income by about $15 MM and reduces greenhouse gas production caused by gas flaring.Keywords: desalter, demulsification, modelling, water-oil separation, crude oil emulsion
Procedia PDF Downloads 687034 Phytoadaptation in Desert Soil Prediction Using Fuzzy Logic Modeling
Authors: S. Bouharati, F. Allag, M. Belmahdi, M. Bounechada
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In terms of ecology forecast effects of desertification, the purpose of this study is to develop a predictive model of growth and adaptation of species in arid environment and bioclimatic conditions. The impact of climate change and the desertification phenomena is the result of combined effects in magnitude and frequency of these phenomena. Like the data involved in the phytopathogenic process and bacteria growth in arid soil occur in an uncertain environment because of their complexity, it becomes necessary to have a suitable methodology for the analysis of these variables. The basic principles of fuzzy logic those are perfectly suited to this process. As input variables, we consider the physical parameters, soil type, bacteria nature, and plant species concerned. The result output variable is the adaptability of the species expressed by the growth rate or extinction. As a conclusion, we prevent the possible strategies for adaptation, with or without shifting areas of plantation and nature adequate vegetation.Keywords: climate changes, dry soil, phytopathogenicity, predictive model, fuzzy logic
Procedia PDF Downloads 3157033 A Middle Way Approach for the Conflicts between Death, Impermanence and Non-Self in Buddhist Philosophy
Authors: Ruotian Wang
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Since the birth of the Buddha himself more than 2000 years ago, Buddhism has continued to lead many people’s lives. Scholars and Buddhists have contributed to give detailed explanations to all kinds of issues within the structure of Buddhist philosophy to make Buddhism more complete. Different schools have developed, therefore leading to a lot of different branches within Buddhism. Although they all follow what the Buddha himself taught, they still have various explanations to even fundamental issues. As one of the fundamental problems regarding our lives, death is widely discussed in Buddhism. The controversy regarding death is its seemly incompatibility with the idea of non-self and impermanence, which is what I will discuss in this essay. The idea of rebirth is the basic structure of birth and death, which suggests a connection between this life and the next. Therefore, according to common logic, we should tell that there is something that connects each life, an agent that receives the process of rebirth, which is normally known as a soul. In Buddhism, non-self is also an important concept which speaks to the illusion of a self or soul. The idea of rebirth and non-self seems contradicted. Many different schools of Buddhism attempt to resolve such conflicts, but there are logical flaws within the arguments they made. Thus, I raise a better solution: Different from the annihilationist view, non-self in Buddhism speaks only to the illusion of a self in each moment. There is a self that exists as a sum of all our karmas which we can achieve after Nirvana. However, the nature of such a self is still emptiness. There are no agents needed as one rebirth since the whole cycle of rebirth is the self. Then, the contradiction between rebirth and non-self can be resolved.Keywords: Buddhism, impermanence, non-self, reincarnation
Procedia PDF Downloads 1197032 An Alternative Richards’ Growth Model Based on Hyperbolic Sine Function
Authors: Samuel Oluwafemi Oyamakin, Angela Unna Chukwu
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Richrads growth equation being a generalized logistic growth equation was improved upon by introducing an allometric parameter using the hyperbolic sine function. The integral solution to this was called hyperbolic Richards growth model having transformed the solution from deterministic to a stochastic growth model. Its ability in model prediction was compared with the classical Richards growth model an approach which mimicked the natural variability of heights/diameter increment with respect to age and therefore provides a more realistic height/diameter predictions using the coefficient of determination (R2), Mean Absolute Error (MAE) and Mean Square Error (MSE) results. The Kolmogorov-Smirnov test and Shapiro-Wilk test was also used to test the behavior of the error term for possible violations. The mean function of top height/Dbh over age using the two models under study predicted closely the observed values of top height/Dbh in the hyperbolic Richards nonlinear growth models better than the classical Richards growth model.Keywords: height, diameter at breast height, DBH, hyperbolic sine function, Pinus caribaea, Richards' growth model
Procedia PDF Downloads 3867031 Time Series Regression with Meta-Clusters
Authors: Monika Chuchro
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This paper presents a preliminary attempt to apply classification of time series using meta-clusters in order to improve the quality of regression models. In this case, clustering was performed as a method to obtain a subgroups of time series data with normal distribution from inflow into waste water treatment plant data which Composed of several groups differing by mean value. Two simple algorithms: K-mean and EM were chosen as a clustering method. The rand index was used to measure the similarity. After simple meta-clustering, regression model was performed for each subgroups. The final model was a sum of subgroups models. The quality of obtained model was compared with the regression model made using the same explanatory variables but with no clustering of data. Results were compared by determination coefficient (R2), measure of prediction accuracy mean absolute percentage error (MAPE) and comparison on linear chart. Preliminary results allows to foresee the potential of the presented technique.Keywords: clustering, data analysis, data mining, predictive models
Procedia PDF Downloads 4627030 Research of the Three-Dimensional Visualization Geological Modeling of Mine Based on Surpac
Authors: Honggang Qu, Yong Xu, Rongmei Liu, Zhenji Gao, Bin Wang
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Today's mining industry is advancing gradually toward digital and visual direction. The three-dimensional visualization geological modeling of mine is the digital characterization of mineral deposits and is one of the key technology of digital mining. Three-dimensional geological modeling is a technology that combines geological spatial information management, geological interpretation, geological spatial analysis and prediction, geostatistical analysis, entity content analysis and graphic visualization in a three-dimensional environment with computer technology and is used in geological analysis. In this paper, the three-dimensional geological modeling of an iron mine through the use of Surpac is constructed, and the weight difference of the estimation methods between the distance power inverse ratio method and ordinary kriging is studied, and the ore body volume and reserves are simulated and calculated by using these two methods. Compared with the actual mine reserves, its result is relatively accurate, so it provides scientific bases for mine resource assessment, reserve calculation, mining design and so on.Keywords: three-dimensional geological modeling, geological database, geostatistics, block model
Procedia PDF Downloads 727029 Examining the Effects of Production Method on Aluminium A356 Alloy and A356-10%SiCp Composite for Hydro Turbine Bucket Application
Authors: Williams S. Ebhota, Freddie L. Inambao
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This study investigates the use of centrifugal casting method to fabricate functionally graded aluminium A356 Alloy and A356-10%SiCp composite for hydro turbine bucket application. The study includes the design and fabrication of a permanent mould. The mould was put into use and the buckets of A356 Alloy and A356-10%SiCp composite were cast, cut and machined into specimens. Some specimens were given T6 heat treatment and the specimens were prepared for different examinations accordingly. The SiCp particles were found to be more at inner periphery of the bucket. The maximum hardness of As-Cast A356 and A356-10%SiCp composite was recorded at the inner periphery to be 60 BRN and 95BRN, respectively. And these values were appreciated to 98BRN and 122BRN for A356 alloy and A356-10%SiCp composite, respectively. It was observed that the ultimate tensile stress and yield tensile stress prediction curves show the same trend.Keywords: A356 alloy, A356-10%SiCp composite, centrifugal casting, Pelton bucket, turbine blade
Procedia PDF Downloads 2727028 An Analysis of Illocutioary Act in Martin Luther King Jr.'s Propaganda Speech Entitled 'I Have a Dream'
Authors: Mahgfirah Firdaus Soberatta
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Language cannot be separated from human life. Humans use language to convey ideas, thoughts, and feelings. We can use words for different things for example like asserted, advising, promise, give opinions, hopes, etc. Propaganda is an attempt which seeks to obtain stable behavior to adopt everyone to his everyday life. It also controls the thoughts and attitudes of individuals in social settings permanent. In this research, the writer will discuss about the speech act in a propaganda speech delivered by Martin Luther King Jr. in Washington at Lincoln Memorial on August 28, 1963. 'I Have a Dream' is a public speech delivered by American civil rights activist MLK, he calls from an end to racism in USA. In this research, the writer uses Searle theory to analyze the types of illocutionary speech act that used by Martin Luther King Jr. in his propaganda speech. In this research, the writer uses a qualitative method described in descriptive, because the research wants to describe and explain the types of illocutionary speech acts used by Martin Luther King Jr. in his propaganda speech. The findings indicate that there are five types of speech acts in Martin Luther King Jr. speech. MLK also used direct speech and indirect speech in his propaganda speech. However, direct speech is the dominant speech act that MLK used in his propaganda speech. It is hoped that this research is useful for the readers to enrich their knowledge in a particular field of pragmatic speech acts.Keywords: speech act, propaganda, Martin Luther King Jr., speech
Procedia PDF Downloads 4337027 Thyroid-Stimulating Hormone as a Stress Biomarker in Thyroidectomy Patients: A Cohort Study
Authors: Jeonghun Lee
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In this study, we investigated the relationship between stress and thyroid dysfunction in such patients who underwent thyroidectomy. This study included 101 patients who underwent thyroidectomy from January 2015 to June 2020 and experienced hypothyroidism. The included patients had good drug compliance with the same dosage of levothyroxine (LT4). The male-to-female ratio was 1:4.6, and the mean age was 45.4 years at surgery and 50.2 years at stressful events. Eighteen patients underwent lobectomies and, of these, 12 did not take LT4. The mean follow-up period was 49(8-93) months. Statistical analyses were performed using the paired t-test, Wilcoxon signed-rank test, and McNemer test using PROC MIXED with SAS 9.4. Forty-five patients (44.6%) had hypothyroidism with thyroid-stimulating hormone (TSH) >10 μIU/mL. There was distress in 81 patients and eustress in 10 patients. TSH levels increased during a mean 5.8 months (min 1, max 12) in 24 patients who specified the date of their life events. Even though each patient took the same dose of LT4, when the patients were under stress, both the free T4 and T3 decreased and TSH increased, regardless of whether the patient experienced distress or eustress (P <0.001). While adjusting for the effect of the free T4 and T3, TSH increased significantly in the patients after stress (P <0.001). For patients with thyroid cancer who are simultaneously experiencing life events, TSH may be used as a stress biomarker to enable the implementation of appropriate treatment and counseling strategies.Keywords: endocrine, thyroid, thyroid function, biomarker, stress
Procedia PDF Downloads 817026 Online Self-Help Metacognitive Therapy for OCD: A Case Series
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Cognitive behavioural therapy (CBT) and exposure and response prevention (ERP) are currently the most efficacious treatments for Obsessive-compulsive disorder (OCD). Many clients, however, remain symptomatic following treatment. As a result, refusal of treatment, withdrawal from treatment, and partial adherence to treatment are common amongst ERP. Such limitations have caused few professionals to actually engage in ERP therapy, which has warranted the exploration of alternative treatments. This study evaluated an online self-help treatment program for OCD (the OCD Doctor Online); a 4-week Metacognitive Therapy (MCT) program which has implemented strategies from Wells’ Metacognitive model of OCD. The aim of the present study was to investigate whether an online self-help treatment using MCT would reduce symptoms of OCD, reduce unhelpful metacognitions and improve quality of life. Treatment effectiveness was assessed using a case series methodology in 3 consecutively referred individuals. At post-treatment, all participants showed reductions in unhelpful metacognitive beliefs (MCQ-30) and improvements in quality of life (Q-LES-Q), which were maintained through to 4 week follow-up. Two of the three participants showed reductions in OCD symptomology (OCI-R), which were further reduced at 4-week follow-up. The present study suggests that internet-based self-help treatment may be an effective means of delivering MCT to adults with OCD.Keywords: internet-based, metacognitive therapy, obsessive-compulsive disorder, self-help
Procedia PDF Downloads 4287025 Time Series Analysis of Radon Concentration at Different Depths in an Underground Goldmine
Authors: Theophilus Adjirackor, Frederic Sam, Irene Opoku-Ntim, David Okoh Kpeglo, Prince K. Gyekye, Frank K. Quashie, Kofi Ofori
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Indoor radon concentrations were collected monthly over a period of one year in 10 different levels in an underground goldmine, and the data was analyzed using a four-moving average time series to determine the relationship between the depths of the underground mine and the indoor radon concentration. The detectors were installed in batches within four quarters. The measurements were carried out using LR115 solid-state nuclear track detectors. Statistical models are applied in the prediction and analysis of the radon concentration at various depths. The time series model predicted a positive relationship between the depth of the underground mine and the indoor radon concentration. Thus, elevated radon concentrations are expected at deeper levels of the underground mine, but the relationship was insignificant at the 5% level of significance with a negative adjusted R2 (R2 = – 0.021) due to an appropriate engineering and adequate ventilation rate in the underground mine.Keywords: LR115, radon concentration, rime series, underground goldmine
Procedia PDF Downloads 367024 Visual Aid and Imagery Ramification on Decision Making: An Exploratory Study Applicable in Emergency Situations
Authors: Priyanka Bharti
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Decades ago designs were based on common sense and tradition, but after an enhancement in visualization technology and research, we are now able to comprehend the cognitive ability involved in the decoding of the visual information. However, many fields in visuals need intense research to deliver an efficient explanation for the events. Visuals are an information representation mode through images, symbols and graphics. It plays an impactful role in decision making by facilitating quick recognition, comprehension, and analysis of a situation. They enhance problem-solving capabilities by enabling the processing of more data without overloading the decision maker. As research proves that, visuals offer an improved learning environment by a factor of 400 compared to textual information. Visual information engages learners at a cognitive level and triggers the imagination, which enables the user to process the information faster (visuals are processed 60,000 times faster in the brain than text). Appropriate information, visualization, and its presentation are known to aid and intensify the decision-making process for the users. However, most literature discusses the role of visual aids in comprehension and decision making during normal conditions alone. Unlike emergencies, in a normal situation (e.g. our day to day life) users are neither exposed to stringent time constraints nor face the anxiety of survival and have sufficient time to evaluate various alternatives before making any decision. An emergency is an unexpected probably fatal real-life situation which may inflict serious ramifications on both human life and material possessions unless corrective measures are taken instantly. The situation demands the exposed user to negotiate in a dynamic and unstable scenario in the absence or lack of any preparation, but still, take swift and appropriate decisions to save life/lives or possessions. But the resulting stress and anxiety restricts cue sampling, decreases vigilance, reduces the capacity of working memory, causes premature closure in evaluating alternative options, and results in task shedding. Limited time, uncertainty, high stakes and vague goals negatively affect cognitive abilities to take appropriate decisions. More so, theory of natural decision making by experts has been understood with far more depth than that of an ordinary user. Therefore, in this study, the author aims to understand the role of visual aids in supporting rapid comprehension to take appropriate decisions during an emergency situation.Keywords: cognition, visual, decision making, graphics, recognition
Procedia PDF Downloads 2647023 Russian, Soviet and Post-Soviet Studies on Ismailism
Authors: Dagikhudo Dagiev
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This paper is a thorough contribution to the analysis of Russian, Soviet and post-Soviet scholarship on the study of Ismailism in Central Asia. It focuses on the lengthy development of Russian studies on Ismailism from the Russian colonial domination to the entire period of Soviet rule, down to the collapse of the Soviet Union and the last two decades of post-Soviet history. These studies, conducted along the lines of various disciplines in the span of more than one hundred years, have resulted in a large amount of scholarly contributions. This paper aims at probing the virtues and shortcoming of such scholarship. Particularly, our investigation of the specialised fields in the Russian-Soviet Studies has required laborious researches in Russian and Central Asian libraries, which have enabled us to provide a guide through this literature, assessing its ideological leanings and qualities, institutions and level of scholarship. Despite some shortcomings, due to Marxism and the authoritarian rule of the Communist Party over the socio-religious life of the people and religious communities, Soviet studies have produced many positive insights on Ismailis studies. These captured almost every aspects of the life of the Ismaili community from anthropology to archaeology, ethnography, history, philosophy, ritual practice and, most importantly, collection and preservation of Ismaiili manuscripts, which will be examined and assessed in this study.Keywords: Central Asian Studies, Ismailism, Russian Studies, Soviet Studies
Procedia PDF Downloads 2867022 The Effects of Nanoemulsions Based on Commercial Oils: Sunflower, Canola, Corn, Olive, Soybean, and Hazelnut Oils for the Quality of Farmed Sea Bass at 2±2°C
Authors: Yesim Ozogul, Mustafa Durmuş, Fatih Ozogul, Esmeray Kuley Boğa, Yılmaz Uçar, Hatice Yazgan
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The effects of oil-in-water nanoemulsions on the sensory, chemical (total volatile basic nitrogen (TVB-N), thiobarbituric acid (TBA), peroxide value (PV) and free fatty acids (FFA), and microbiological qualities (total viable count (TVC), total psychrophilic bacteria, and total Enterbactericaea bacteria) of sea bream fillets stored at 2 ± 2°C were investigated. Physical properties of emulsions (viscosity, the particle size of droplet, thermodynamic stability, refractive index and surface tension) were determined. The results showed that the use of nanoemulsion extended the shelf life of fish 2 days when compared with the control. Treatment with nanoemulsions significantly (p<0.05) decreased the values of biochemical parameters during storage period. Bacterial growth was inhibited by the use of nanoemulsions. Based on the results, it can be concluded that nanoemulsions based on commercial oils extended the shelf life and improved the quality of sea bass fillets during storage period.Keywords: lipid oxidation, nanoemulsion, sea bass, quality parameters
Procedia PDF Downloads 4757021 Application of Artificial Neural Network in Assessing Fill Slope Stability
Authors: An-Jui. Li, Kelvin Lim, Chien-Kuo Chiu, Benson Hsiung
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This paper details the utilization of artificial intelligence (AI) in the field of slope stability whereby quick and convenient solutions can be obtained using the developed tool. The AI tool used in this study is the artificial neural network (ANN), while the slope stability analysis methods are the finite element limit analysis methods. The developed tool allows for the prompt prediction of the safety factors of fill slopes and their corresponding probability of failure (depending on the degree of variation of the soil parameters), which can give the practicing engineer a reasonable basis in their decision making. In fact, the successful use of the Extreme Learning Machine (ELM) algorithm shows that slope stability analysis is no longer confined to the conventional methods of modeling, which at times may be tedious and repetitive during the preliminary design stage where the focus is more on cost saving options rather than detailed design. Therefore, similar ANN-based tools can be further developed to assist engineers in this aspect.Keywords: landslide, limit analysis, artificial neural network, soil properties
Procedia PDF Downloads 1957020 Numerical Crashworthiness Investigations of a Full-Scale Composite Fuselage Section
Authors: Redouane Lombarkia
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To apply a new material model developed and validated for plain weave fabric CFRP composites usually used in stanchions in sub-cargo section in aircrafts. This work deals with the development of a numerical model of the fuselage section of commercial aircraft based on the pure explicit finite element method FEM within Abaqus/Explicit commercial code. The aim of this work is the evaluation of the energy absorption capabilities of a full-scale composite fuselage section, including sub-cargo stanchions, Drop tests were carried out from a free fall height of about 5 m and impact velocity of about 6 m∕s. To asses, the prediction efficiency of the proposed numerical modeling procedure, a comparison with literature existed experimental results was performed. We demonstrate the efficiency of the proposed methodology to well capture crash damage mechanisms compared to experimental resultsKeywords: crashworthiness, fuselage section, finite elements method (FEM), stanchions, specific energy absorption SEA
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