Search results for: hybrid block methods
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 17092

Search results for: hybrid block methods

13432 Revalidation and Hormonization of Existing IFCC Standardized Hepatic, Cardiac, and Thyroid Function Tests by Precison Optimization and External Quality Assurance Programs

Authors: Junaid Mahmood Alam

Abstract:

Revalidating and harmonizing clinical chemistry analytical principles and optimizing methods through quality control programs and assessments is the preeminent means to attain optimal outcome within the clinical laboratory services. Present study reports revalidation of our existing IFCC regularized analytical methods, particularly hepatic and thyroid function tests, by optimization of precision analyses and processing through external and internal quality assessments and regression determination. Parametric components of hepatic (Bilirubin ALT, γGT, ALP), cardiac (LDH, AST, Trop I) and thyroid/pituitary (T3, T4, TSH, FT3, FT4) function tests were used to validate analytical techniques on automated chemistry and immunological analyzers namely Hitachi 912, Cobas 6000 e601, Cobas c501, Cobas e411 with UV kinetic, colorimetric dry chemistry principles and Electro-Chemiluminescence immunoassay (ECLi) techniques. Process of validation and revalidation was completed with evaluating and assessing the precision analyzed Preci-control data of various instruments plotting against each other with regression analyses R2. Results showed that: Revalidation and optimization of respective parameters that were accredited through CAP, CLSI and NEQAPP assessments depicted 99.0% to 99.8% optimization, in addition to the methodology and instruments used for analyses. Regression R2 analysis of BilT was 0.996, whereas that of ALT, ALP, γGT, LDH, AST, Trop I, T3, T4, TSH, FT3, and FT4 exhibited R2 0.998, 0.997, 0.993, 0.967, 0.970, 0.980, 0.976, 0.996, 0.997, 0.997, and R2 0.990, respectively. This confirmed marked harmonization of analytical methods and instrumentations thus revalidating optimized precision standardization as per IFCC recommended guidelines. It is concluded that practices of revalidating and harmonizing the existing or any new services should be followed by all clinical laboratories, especially those associated with tertiary care hospital. This is will ensure deliverance of standardized, proficiency tested, optimized services for prompt and better patient care that will guarantee maximum patients’ confidence.

Keywords: revalidation, standardized, IFCC, CAP, harmonized

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13431 Using Machine-Learning Methods for Allergen Amino Acid Sequence's Permutations

Authors: Kuei-Ling Sun, Emily Chia-Yu Su

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Allergy is a hypersensitive overreaction of the immune system to environmental stimuli, and a major health problem. These overreactions include rashes, sneezing, fever, food allergies, anaphylaxis, asthmatic, shock, or other abnormal conditions. Allergies can be caused by food, insect stings, pollen, animal wool, and other allergens. Their development of allergies is due to both genetic and environmental factors. Allergies involve immunoglobulin E antibodies, a part of the body’s immune system. Immunoglobulin E antibodies will bind to an allergen and then transfer to a receptor on mast cells or basophils triggering the release of inflammatory chemicals such as histamine. Based on the increasingly serious problem of environmental change, changes in lifestyle, air pollution problem, and other factors, in this study, we both collect allergens and non-allergens from several databases and use several machine learning methods for classification, including logistic regression (LR), stepwise regression, decision tree (DT) and neural networks (NN) to do the model comparison and determine the permutations of allergen amino acid’s sequence.

Keywords: allergy, classification, decision tree, logistic regression, machine learning

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13430 The Influence of Organic Waste on Vegetable Nutritional Components and Healthy Livelihood, Minna, Niger State, Nigeria

Authors: A. Abdulkadir, A. A. Okhimamhe, Y. M. Bello, H. Ibrahim, D. H. Makun, M. T. Usman

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Household waste form a larger proportion of waste generated across the state, accumulation of organic waste is an apparent problem and the existing dump sites could be overstressed. Niger state has abundant arable land and water resources thus should be one of the highest producers of agricultural crops in the country. However, the major challenge to agricultural sector today is the loss of soil nutrient coupled with high cost of fertilizer. These have continued to increase the use of fertilizer and decomposed solid waste for enhancing agricultural yield, which have varying effects on the soil as well a threat to human livelihood. Consequently, vegetable yield samples from poultry droppings decomposed household waste manure, NPK treatments and control from each replication were subjected to proximate analysis to determine the nutritional and anti-nutritional component as well as heavy metal concentration. Data collected was analyzed using SPSS software and Randomized complete Block Design means were compared. The result shows that the treatments do not devoid the concentrations of any nutritional components while the anti-nutritional analysis proved that NPK had higher oxalate content than control and organic treats. The concentration of lead and cadmium are within safe permissible level while the mercury level exceeded the FAO/WHO maximum permissible limit for the entire treatments depicts the need for urgent intervention to minimize mercury levels in soil and manure in order to mitigate its toxic effect. Thus, eco-agriculture should be widely accepted and promoted by the stakeholders for soil amendment, higher yield, strategies for sustainable environmental protection, food security, poverty eradication, attainment of sustainable development and healthy livelihood.

Keywords: anti-nutritional, healthy livelihood, nutritional waste, organic waste

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13429 ASEAN Citizenship in the Internationalization of Thai Higher Education

Authors: Bella Llego

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This research aims to study on “ASEAN Citizenship in the Internationalization of Thai Higher Education.” The purposes of this research are (1) to examine the Thai academics and scholars defined in the concept of internationalization of higher education, (2) to know how Thailand tries to fulfill its internationalization on education goal, (3) to find out the advantages and disadvantages of Thailand hub for higher education in Asia. Sequential mixed methods, qualitative and quantitative research methods were utilized to gather the data collected. By using a qualitative method (individual interviews from key Thai administrators and educators in the international higher education sector), a quantitative method (survey) was utilized to draw upon and to elaborate the recurring themes present during the interviews. The study found that many aspects of Thai international higher education programs received heavy influence from both the American and European higher education systems. Thailand’s role and leadership in the creation and launch of the ASEAN Economic Community (AEC) by 2015 gives its unique context for its internationalization efforts. English is being designated as the language of all Thai international programs; its influence further strengthened being the current language of academia, international business, and the internet, having global influence.

Keywords: ASEAN citizenship, internationalization, Thai higher education, academics

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13428 Effectiveness of Computer-Based Cognitive Training in Improving Attention-Deficit/Hyperactivity Disorder Rehabilitation

Authors: Marjan Ghazisaeedi, Azadeh Bashiri

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Background: Attention-Deficit/Hyperactivity Disorder(ADHD), is one of the most common psychiatric disorders in early childhood that in addition to its main symptoms provide significant deficits in the areas of educational, social and individual relationship. Considering the importance of rehabilitation in ADHD patients to control these problems, this study investigated the advantages of computer-based cognitive training in these patients. Methods: This review article has been conducted by searching articles since 2005 in scientific databases and e-Journals and by using keywords including computerized cognitive rehabilitation, computer-based training and ADHD. Results: Since drugs have short term effects and also they have many side effects in the rehabilitation of ADHD patients, using supplementary methods such as computer-based cognitive training is one of the best solutions. This approach has quick feedback and also has no side effects. So, it provides promising results in cognitive rehabilitation of ADHD especially on the working memory and attention. Conclusion: Considering different cognitive dysfunctions in ADHD patients, application of the computerized cognitive training has the potential to improve cognitive functions and consequently social, academic and behavioral performances in patients with this disorder.

Keywords: ADHD, computer-based cognitive training, cognitive functions, rehabilitation

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13427 Immersive Environment as an Occupant-Centric Tool for Architecture Criticism and Architectural Education

Authors: Golnoush Rostami, Farzam Kharvari

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In recent years, developments in the field of architectural education have resulted in a shift from conventional teaching methods to alternative state-of-the-art approaches in teaching methods and strategies. Criticism in architecture has been a key player both in the profession and education, but it has been mostly offered by renowned individuals. Hence, not only students or other professionals but also critics themselves may not have the option to experience buildings and rely on available 2D materials, such as images and plans, that may not result in a holistic understanding and evaluation of buildings. On the other hand, immersive environments provide students and professionals the opportunity to experience buildings virtually and reflect their evaluation by experiencing rather than judging based on 2D materials. Therefore, the aim of this study is to compare the effect of experiencing buildings in immersive environments and 2D drawings, including images and plans, on architecture criticism and architectural education. As a result, three buildings that have parametric brick facades were studied through 2D materials and in Unreal Engine v. 24 as an immersive environment among 22 architecture students that were selected using convenient sampling and were divided into two equal groups using simple random sampling. This study used mixed methods, including quantitative and qualitative methods; the quantitative section was carried out by a questionnaire, and deep interviews were used for the qualitative section. A questionnaire was developed for measuring three constructs, including privacy regulation based on Altman’s theory, the sufficiency of illuminance levels in the building, and the visual status of the view (visually appealing views based on obstructions that may have been caused by facades). Furthermore, participants had the opportunity to reflect their understanding and evaluation of the buildings in individual interviews. Accordingly, the collected data from the questionnaires were analyzed using independent t-test and descriptive analyses in IBM SPSS Statistics v. 26, and interviews were analyzed using the content analysis method. The results of the interviews showed that the participants who experienced the buildings in the immersive environment were able to have a thorough and more precise evaluation of the buildings in comparison to those who studied them through 2D materials. Moreover, the analyses of the respondents’ questionnaires revealed that there were statistically significant differences between measured constructs among the two groups. The outcome of this study suggests that integrating immersive environments into the profession and architectural education as an effective and efficient tool for architecture criticism is vital since these environments allow users to have a holistic evaluation of buildings for vigorous and sound criticism.

Keywords: immersive environments, architecture criticism, architectural education, occupant-centric evaluation, pre-occupancy evaluation

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13426 Rapid, Direct, Real-Time Method for Bacteria Detection on Surfaces

Authors: Evgenia Iakovleva, Juha Koivisto, Pasi Karppinen, J. Inkinen, Mikko Alava

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Preventing the spread of infectious diseases throughout the worldwide is one of the most important tasks of modern health care. Infectious diseases not only account for one fifth of the deaths in the world, but also cause many pathological complications for the human health. Touch surfaces pose an important vector for the spread of infections by varying microorganisms, including antimicrobial resistant organisms. Further, antimicrobial resistance is reply of bacteria to the overused or inappropriate used of antibiotics everywhere. The biggest challenges in bacterial detection by existing methods are non-direct determination, long time of analysis, the sample preparation, use of chemicals and expensive equipment, and availability of qualified specialists. Therefore, a high-performance, rapid, real-time detection is demanded in rapid practical bacterial detection and to control the epidemiological hazard. Among the known methods for determining bacteria on the surfaces, Hyperspectral methods can be used as direct and rapid methods for microorganism detection on different kind of surfaces based on fluorescence without sampling, sample preparation and chemicals. The aim of this study was to assess the relevance of such systems to remote sensing of surfaces for microorganisms detection to prevent a global spread of infectious diseases. Bacillus subtilis and Escherichia coli with different concentrations (from 0 to 10x8 cell/100µL) were detected with hyperspectral camera using different filters as visible visualization of bacteria and background spots on the steel plate. A method of internal standards was applied for monitoring the correctness of the analysis results. Distances from sample to hyperspectral camera and light source are 25 cm and 40 cm, respectively. Each sample is optically imaged from the surface by hyperspectral imaging system, utilizing a JAI CM-140GE-UV camera. Light source is BeamZ FLATPAR DMX Tri-light, 3W tri-colour LEDs (red, blue and green). Light colors are changed through DMX USB Pro interface. The developed system was calibrated following a standard procedure of setting exposure and focused for light with λ=525 nm. The filter is ThorLabs KuriousTM hyperspectral filter controller with wavelengths from 420 to 720 nm. All data collection, pro-processing and multivariate analysis was performed using LabVIEW and Python software. The studied human eye visible and invisible bacterial stains clustered apart from a reference steel material by clustering analysis using different light sources and filter wavelengths. The calculation of random and systematic errors of the analysis results proved the applicability of the method in real conditions. Validation experiments have been carried out with photometry and ATP swab-test. The lower detection limit of developed method is several orders of magnitude lower than for both validation methods. All parameters of the experiments were the same, except for the light. Hyperspectral imaging method allows to separate not only bacteria and surfaces, but also different types of bacteria, such as Gram-negative Escherichia coli and Gram-positive Bacillus subtilis. Developed method allows skipping the sample preparation and the use of chemicals, unlike all other microbiological methods. The time of analysis with novel hyperspectral system is a few seconds, which is innovative in the field of microbiological tests.

Keywords: Escherichia coli, Bacillus subtilis, hyperspectral imaging, microorganisms detection

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13425 Whole Body Cooling Hypothermia Treatment Modelling Using a Finite Element Thermoregulation Model

Authors: Ana Beatriz C. G. Silva, Luiz Carlos Wrobel, Fernando Luiz B. Ribeiro

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This paper presents a thermoregulation model using the finite element method to perform numerical analyses of brain cooling procedures as a contribution to the investigation on the use of therapeutic hypothermia after ischemia in adults. The use of computational methods can aid clinicians to observe body temperature using different cooling methods without the need of invasive techniques, and can thus be a valuable tool to assist clinical trials simulating different cooling options that can be used for treatment. In this work, we developed a FEM package applied to the solution of the continuum bioheat Pennes equation. Blood temperature changes were considered using a blood pool approach and a lumped analysis for intravascular catheter method of blood cooling. Some analyses are performed using a three-dimensional mesh based on a complex geometry obtained from computed tomography medical images, considering a cooling blanket and a intravascular catheter. A comparison is made between the results obtained and the effects of each case in brain temperature reduction in a required time, maintenance of body temperature at moderate hypothermia levels and gradual rewarming.

Keywords: brain cooling, finite element method, hypothermia treatment, thermoregulation

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13424 Forensic Medical Capacities of Research of Saliva Stains on Physical Evidence after Washing

Authors: Saule Mussabekova

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Recent advances in genetics have allowed increasing acutely the capacities of the formation of reliable evidence in conducting forensic examinations. Thus, traces of biological origin are important sources of information about a crime. Currently, around the world, sexual offenses have increased, and among them are those in which the criminals use various detergents to remove traces of their crime. A feature of modern synthetic detergents is the presence of biological additives - enzymes. Enzymes purposefully destroy stains of biological origin. To study the nature and extent of the impact of modern washing powders on saliva stains on the physical evidence, specially prepared test specimens of different types of tissues to which saliva was applied have been examined. Materials and Methods: Washing machines of famous manufacturers of household appliances have been used with different production characteristics and advertised brands of washing powder for test washing. Over 3,500 experimental samples were tested. After washing, the traces of saliva were identified using modern research methods of forensic medicine. Results: The influence was tested and the dependence of the use of different washing programs, types of washing machines and washing powders in the process of establishing saliva trace and identify of the stains on the physical evidence while washing was revealed. The results of experimental and practical expert studies have shown that in most cases it is not possible to draw the conclusions in the identification of saliva traces on physical evidence after washing. This is a consequence of the effect of biological additives and other additional factors on traces of saliva during washing. Conclusions: On the basis of the results of the study, the feasibility of saliva traces of the stains on physical evidence after washing is established. The use of modern molecular genetic methods makes it possible to partially solve the problems arising in the study of unlaundered evidence. Additional study of physical evidence after washing facilitates detection and investigation of sexual offenses against women and children.

Keywords: saliva research, modern synthetic detergents, laundry detergents, forensic medicine

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13423 Improvement of Plantain Leaves Nutritive Value in Goats by Urea Treatment and Nitrogen Supplements

Authors: Marie Lesly Fontin, Audalbert Bien-Aimé, Didier Marlier, Yves Beckers

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Fecal digestibility of mature plantain leaves was determined in castrated Creolegoatsin order to better assess them. Five diets made from plantain leaves were used in an in vivo digestibility study on 20 castrated Creole goats over three periods using a completely random design in order to assess their apparent fecal digestibility (Dg). These diets consisted of sun-dried leaves (DL), sun-dried urea treated leaves (DUTL, 5kg of urea per 100kg of raw product ensilaged during 90 days with 60 kg of water), sun-dried leaves + hoopvine (Trichostigma octandrum, L)(DLH, DL: 61.4% + Hoopvine: 38.6%), sun-dried leaves + urea (DLU, DL: 98.2%+ U: 1.8%), and fresh leaves. (FL).0.5% of salt diluted with water was added to diets before distribution to the goats. A mineral lick block was available for each goat in its digestibility cage. During each period, diets were distributed to meet the maintenance needs of the goats for 21 days, including 14 days of adaptation and 7 days of measurement. Offered and refused diets and feces were weighed every day, and samples were taken for laboratory analysis. Results showed that the urea treatment increasedCP (Crude Protein) content of DL by 44% (from 10.4% for DL to 15.0% for DUTL) and decreased their NDF (Neutral Detergent Fiber) content (55.5% to 52.4%). Large amounts of refused feed (around 40%) were observed in goats fed with FL, DLU, and DL diets, for which no significant difference was observed for DM (Dry Matter) intakes (40.3; 36.6 and 35.1g/kg0.75 respectively) (p>0.05). DM intakes of DUTL (59.9 g/kg0.75) were significantly (p<0.05) greater than DLH (50.2 g/kg0.75). DM Dg of DL was very low (29.2%). However, supplementation with hoopvine and urea treatment resulted in a significant increase of DM Dg (40.3% and 42.1%, respectively), but the addition of urea (DLU) had no effect on it. FL showed a DM Dg similar to DHL and DUTL diets (39.0%). OM (Organic Matter)Dg was higher for the DUTL diet (45.1%), followed by DLH (40.9%), then by DLU and FL (32.9% and 40.7% respectively) and finally by DL (29.8%). CP Dg was higher for the FL diet (65.7%) and lower for the DL diet (39.9%). NDF Dg was also increased with urea treatment (54.8% for DUTL) and with the addition of hoopvine (41.4%) compared to the DL diet (31.0% for DLH). In conclusion, urea treatment and complementation with hoopvine of plantain leaves are the best treatments among those tested for increasing the nutritive value of this foragein the castrated Creole goats.

Keywords: apparent fecal digestibility, nitrogen supplements, plantain leaves, urea treatment

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13422 Comparison of the Indocyanine Green Dye Method versus the Combined Method of Indigo Carmine Blue Dye with Indocyanine Green Fluorescence Imaging for Sentinel Lymph Node Biopsy in Breast Conservative Therapy for Early Breast Cancer

Authors: Nobuyuki Takemoto, Ai Koyanagi, Masanori Yasuda, Hiroshi Yamamoto

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Background: Fluorescence imaging (FI) is one of the methods to identify sentinel lymph nodes (SLNs). However, the procedure is technically complicated and requires procedural skills, as SLN biopsy must be conducted in dim light conditions. As an improved version of this method, we introduced a combined method (Combined mixed dye and fluorescence; CMF) consisting of indigo carmine blue dye and FI. The direct visualization of SLNs under shadowless surgical light conditions is facilitated by the addition of the blue dye. We compared the SLN detection rates of CMF with that of the indocyanine green (ICG) dye method (ICG-D). Methods: A total of 202 patients with stage ≤ IIA breast cancer who underwent breast conservative therapy with separate incision from January 2004 to February 2017 were reviewed. Details of the two methods are as follows: (1) ICG-D: 2ml of ICG (10mg) was used and the green-stained SLNs were resected via a 3-4cm axillary incision; (2) CMF: A combination of 1ml of ICG (5mg) and 1-3ml of indigo carmine (4-12mg) was used. Using Photodynamic Eye (PDE), a 1.5-2 cm incision was made near the point of disappearance of the fluorescence and SLNs with intermediate color of blue and green were resected. Results: There were 92 ICG-D and 110 CMF cases. CMF resulted in a significantly higher detection rate than ICG-D (96.4% vs. 83.7%; p=0.003). This difference was particularly notable in those aged ≥ 60 years (98.3% vs. 74.3%) and individuals with BMI ≥ 25kg/m2 (90.3% vs. 58.3%). Conclusion: CMF is an effective method to identify SLNs which is safe, efficient, and cost-effective. Furthermore, radiation exposure can be avoided, and it can be performed in institutes without nuclear medicine facilities. CMF achieves a high SLN identification rate, and most of this procedure is feasible under shadowless surgical light conditions. CMF can reliably perform SLN biopsy even in those aged ≥ 60 years and individuals with BMI ≥ 25 kg/m2.

Keywords: sentinel lymph node biopsy, identification rate, indocyanine green (ICG), indigocarmine, fluorescence

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13421 Performance of AquaCrop Model for Simulating Maize Growth and Yield Under Varying Sowing Dates in Shire Area, North Ethiopia

Authors: Teklay Tesfay, Gebreyesus Brhane Tesfahunegn, Abadi Berhane, Selemawit Girmay

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Adjusting the proper sowing date of a crop at a particular location with a changing climate is an essential management option to maximize crop yield. However, determining the optimum sowing date for rainfed maize production through field experimentation requires repeated trials for many years in different weather conditions and crop management. To avoid such long-term experimentation to determine the optimum sowing date, crop models such as AquaCrop are useful. Therefore, the overall objective of this study was to evaluate the performance of AquaCrop model in simulating maize productivity under varying sowing dates. A field experiment was conducted for two consecutive cropping seasons by deploying four maize seed sowing dates in a randomized complete block design with three replications. Input data required to run this model are stored as climate, crop, soil, and management files in the AquaCrop database and adjusted through the user interface. Observed data from separate field experiments was used to calibrate and validate the model. AquaCrop model was validated for its performance in simulating the green canopy and aboveground biomass of maize for the varying sowing dates based on the calibrated parameters. Results of the present study showed that there was a good agreement (an overall R2 =, Ef= d= RMSE =) between measured and simulated values of the canopy cover and biomass yields. Considering the overall values of the statistical test indicators, the performance of the model to predict maize growth and biomass yield was successful, and so this is a valuable tool help for decision-making. Hence, this calibrated and validated model is suggested to use for determining optimum maize crop sowing date for similar climate and soil conditions to the study area, instead of conducting long-term experimentation.

Keywords: AquaCrop model, calibration, validation, simulation

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13420 Improving Forecasting Demand for Maintenance Spare Parts: Case Study

Authors: Abdulaziz Afandi

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Minimizing the inventory cost, optimizing the inventory quantities, and increasing system operational availability are the main motivations to enhance forecasting demand of spare parts in a major power utility company in Medina. This paper reports in an effort made to optimize the orders quantities of spare parts by improving the method of forecasting the demand. The study focuses on equipment that has frequent spare parts purchase orders with uncertain demand. The pattern of the demand considers a lumpy pattern which makes conventional forecasting methods less effective. A comparison was made by benchmarking various methods of forecasting based on experts’ criteria to select the most suitable method for the case study. Three actual data sets were used to make the forecast in this case study. Two neural networks (NN) approaches were utilized and compared, namely long short-term memory (LSTM) and multilayer perceptron (MLP). The results as expected, showed that the NN models gave better results than traditional forecasting method (judgmental method). In addition, the LSTM model had a higher predictive accuracy than the MLP model.

Keywords: neural network, LSTM, MLP, forecasting demand, inventory management

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13419 Intelligent Tutor Using Adaptive Learning to Partial Discharges with Virtual Reality Systems

Authors: Hernández Yasmín, Ochoa Alberto, Hurtado Diego

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The aim of this study is developing an intelligent tutoring system for electrical operators training with virtual reality systems at the laboratory center of partials discharges LAPEM. The electrical domain requires efficient and well trained personnel, due to the danger involved in the partials discharges field, qualified electricians are required. This paper presents an overview of the intelligent tutor adaptive learning design and user interface with VR. We propose the develop of constructing a model domain of a subset of partial discharges enables adaptive training through a trainee model which represents the affective and knowledge states of trainees. According to the success of the intelligent tutor system with VR, it is also hypothesized that the trainees will able to learn the electrical domain installations of partial discharges and gain knowledge more efficient and well trained than trainees using traditional methods of teaching without running any risk of being in danger, traditional methods makes training lengthily, costly and dangerously.

Keywords: intelligent tutoring system, artificial intelligence, virtual reality, partials discharges, adaptive learning

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13418 Effects of Intercropping Maize (Zea mays L.) with Jack Beans (Canavalia ensiformis L.) at Different Spacing and Weeding Regimes on Crops Productivity

Authors: Oluseun S. Oyelakin, Olalekan W. Olaniyi

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A field experiment was conducted at Ido town in Ido Local Government Area of Oyo state, Nigeria to determine the effects of intercropping maize (Zea mays L.) with Jack bean (Canavalia ensiformis L.) at different spacing and weeding regimes on crops productivity. The treatments were 2 x 2 x 3 factorial arrangement involving two spatial crop arrangements. Spacing of 75 cm x 50 cm and 90 cm x 42 cm (41.667 cm) with two plants per stand resulted in plant population of approximately 53,000 plants/hectare. Also, Randomized Complete Block Design (RCBD) with two cropping patterns (sole and intercrop), three weeding regimes (weedy check, weeds once, and weed twice) with three replicates was used. Data were analyzed with SAS (Statistical Analysis System) and statistical means separated using Least Significant Difference (LSD) (P ≤ 0.05). Intercropping and crop spacing did not have significant influence on the growth parameters and yield parameters. The maize grain yield of 1.11 t/ha obtained under sole maize was comparable to 1.05 t/ha from maize/jack beans. Weeding regime significantly influenced growth and yields of maize in intercropping with Jack beans. Weeding twice resulted in significantly higher growth than that of the other weeding regimes. Plant height at 6 Weeks After Sowing (WAS) under weeding twice regime (3 and 6 WAS) was 83.9 cm which was significantly different from 67.75 cm and 53.47 cm for weeding once (3 WAS) and no weeding regimes respectively. Moreover, maize grain yield of 1.3 t/ha obtained from plots weeded twice was comparable to that of 1.23 t/ha from single weeding and both were significantly higher than 0.71 t/ha maize grain yield obtained from the no weeding control. The dry matter production of Jack beans reduced at some growth stages due to intercropping of maize with Jack beans though with no significance effect on the other growth parameters of the crop. There was no effect on the growth parameters of Jack beans in maize/jack beans intercrop based on cropping spacing while comparable growth and dry matter production in Jack beans were produced in maize/Jack beans mixture with single weeding.

Keywords: crop spacing, intercropping, growth parameter, weeding regime, sole cropping, WAS, week after sowing

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13417 Determination of Safety Distance Around Gas Pipelines Using Numerical Methods

Authors: Omid Adibi, Nategheh Najafpour, Bijan Farhanieh, Hossein Afshin

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Energy transmission pipelines are one of the most vital parts of each country which several strict laws have been conducted to enhance the safety of these lines and their vicinity. One of these laws is the safety distance around high pressure gas pipelines. Safety distance refers to the minimum distance from the pipeline where people and equipment do not confront with serious damages. In the present study, safety distance around high pressure gas transmission pipelines were determined by using numerical methods. For this purpose, gas leakages from cracked pipeline and created jet fires were simulated as continuous ignition, three dimensional, unsteady and turbulent cases. Numerical simulations were based on finite volume method and turbulence of flow was considered using k-ω SST model. Also, the combustion of natural gas and air mixture was applied using the eddy dissipation method. The results show that, due to the high pressure difference between pipeline and environment, flow chocks in the cracked area and velocity of the exhausted gas reaches to sound speed. Also, analysis of the incident radiation results shows that safety distances around 42 inches high pressure natural gas pipeline based on 5 and 15 kW/m2 criteria are 205 and 272 meters, respectively.

Keywords: gas pipelines, incident radiation, numerical simulation, safety distance

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13416 Integrations of Students' Learning Achievements and Their Analytical Thinking Abilities with the Problem-Based Learning and the Concept Mapping Instructional Methods on Gene and Chromosome Issue at the 12th Grade Level

Authors: Waraporn Thaimit, Yuwadee Insamran, Natchanok Jansawang

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Focusing on Analytical Thinking and Learning Achievement are the critical component of visual thinking that gives one the ability to solve problems quickly and effectively that allows to complex problems into components, and the result had been achieved or acquired form of the subject students of which resulted in changes within the individual as a result of activity in learning. The aims of this study are to administer on comparisons between students’ analytical thinking abilities and their learning achievements sample size consisted of 80 students who sat at the 12th grade level in 2 classes from Chaturaphak Phiman Ratchadaphisek School, the 40-student experimental group with the Problem-Based Learning (PBL) and 40-student controlling group with the Concept Mapping Instructional (CMI) methods were designed. Research instruments composed with the 5-lesson instructional plans to be assessed with the pretest and posttest techniques on each instructional method. Students’ responses of their analytical thinking abilities were assessed with the Analytical Thinking Tests and students’ learning achievements were tested of the Learning Achievement Tests. Statistically significant differences with the paired t-test and F-test (Two-way MANCOVA) between post- and pre-tests of the whole students in two chemistry classes were found. Associations between student learning outcomes in each instructional method and their analytical thinking abilities to their learning achievements also were found (ρ < .05). The use of two instructional methods for this study is revealed that the students perceive their abilities to be highly learning achievement in chemistry classes with the PBL group ought to higher than the CMI group. Suggestions that analytical thinking ability involves the process of gathering relevant information and identifying key issues related to the learning achievement information.

Keywords: comparisons, students learning achievements, analytical thinking abilities, the problem-based learning method, the concept mapping instructional method, gene and chromosome issue, chemistry classes

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13415 Spatiotemporal Variability in Rainfall Trends over Sinai Peninsula Using Nonparametric Methods and Discrete Wavelet Transforms

Authors: Mosaad Khadr

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Knowledge of the temporal and spatial variability of rainfall trends has been of great concern for efficient water resource planning, management. In this study annual, seasonal and monthly rainfall trends over the Sinai Peninsula were analyzed by using absolute homogeneity tests, nonparametric Mann–Kendall (MK) test and Sen’s slope estimator methods. The homogeneity of rainfall time-series was examined using four absolute homogeneity tests namely, the Pettitt test, standard normal homogeneity test, Buishand range test, and von Neumann ratio test. Further, the sequential change in the trend of annual and seasonal rainfalls is conducted using sequential MK (SQMK) method. Then the trend analysis based on discrete wavelet transform technique (DWT) in conjunction with SQMK method is performed. The spatial patterns of the detected rainfall trends were investigated using a geostatistical and deterministic spatial interpolation technique. The results achieved from the Mann–Kendall test to the data series (using the 5% significance level) highlighted that rainfall was generally decreasing in January, February, March, November, December, wet season, and annual rainfall. A significant decreasing trend in the winter and annual rainfall with significant levels were inferred based on the Mann-Kendall rank statistics and linear trend. Further, the discrete wavelet transform (DWT) analysis reveal that in general, intra- and inter-annual events (up to 4 years) are more influential in affecting the observed trends. The nature of the trend captured by both methods is similar for all of the cases. On the basis of spatial trend analysis, significant rainfall decreases were also noted in the investigated stations. Overall, significant downward trends in winter and annual rainfall over the Sinai Peninsula was observed during the study period.

Keywords: trend analysis, rainfall, Mann–Kendall test, discrete wavelet transform, Sinai Peninsula

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13414 Triplex Detection of Pistacia vera, Arachis hypogaea and Pisum sativum in Processed Food Products Using Probe Based PCR

Authors: Ergün Şakalar, Şeyma Özçirak Ergün, Emrah Yalazi̇, Emine Altinkaya, Cengiz Ataşoğlu

Abstract:

In recent years, food allergies which cause serious health problems affect to public health around the world. Foodstuffs which contain allergens are either intentionally used as ingredients or are encased as contaminant in food products. The prevalence of clinical allergy to peanuts and nuts is estimated at about 0.4%-1.1% of the adult population, representing the allergy to pistachio the 7% of the cases of tree nut causing allergic reactions. In order to protect public health and enforce the legislation, methods for sensitive analysis of pistachio and peanut contents in food are required. Pea, pistachio and peanut are used together, to reduce the cost in food production such as baklava, snack foods.DNA technology-based methods in food analysis are well-established and well-roundedtools for species differentiation, allergen detection. Especially, the probe-based TaqMan real-time PCR assay can amplify target DNA with efficiency, specificity, and sensitivity.In this study, pistachio, peanut and pea were finely ground and three separate series of triplet mixtures containing 0.1, 1, 10, 100, 1000, 10,000 and 100,000 mg kg-1 of each sample were prepared for each series, to a final weight of 100 g. DNA from reference samples and industrial products was successfully extracted with the GIDAGEN® Multi-Fast DNA Isolation Kit. TaqMan probes were designed for triplex determination of ITS, Ara h 3 and pea lectin genes which are specific regions for identification pistachio, peanut and pea, respectively.The real-time PCR as quantitative detected pistachio, peanut and pea in these mixtures down to the lowest investigated level of 0.1, 0.1 and 1 mg kg-1, respectively. Also, the methods reported here are capable of detecting of as little as 0.001% level of peanut DNA, 0,000001% level of pistachio DNA and 0.000001% level of pea DNA. We accomplish that the quantitative triplex real-time PCR method developed in this study canbe applied to detect pistachio, peanut and peatraces for three allergens at once in commercial food products.

Keywords: allergens, DNA, real-time PCR, TaqMan probe

Procedia PDF Downloads 241
13413 Manufacturing Anomaly Detection Using a Combination of Gated Recurrent Unit Network and Random Forest Algorithm

Authors: Atinkut Atinafu Yilma, Eyob Messele Sefene

Abstract:

Anomaly detection is one of the essential mechanisms to control and reduce production loss, especially in today's smart manufacturing. Quick anomaly detection aids in reducing the cost of production by minimizing the possibility of producing defective products. However, developing an anomaly detection model that can rapidly detect a production change is challenging. This paper proposes Gated Recurrent Unit (GRU) combined with Random Forest (RF) to detect anomalies in the production process in real-time quickly. The GRU is used as a feature detector, and RF as a classifier using the input features from GRU. The model was tested using various synthesis and real-world datasets against benchmark methods. The results show that the proposed GRU-RF outperforms the benchmark methods with the shortest time taken to detect anomalies in the production process. Based on the investigation from the study, this proposed model can eliminate or reduce unnecessary production costs and bring a competitive advantage to manufacturing industries.

Keywords: anomaly detection, multivariate time series data, smart manufacturing, gated recurrent unit network, random forest

Procedia PDF Downloads 99
13412 Building a Parametric Link between Mapping and Planning: A Sunlight-Adaptive Urban Green System Plan Formation Process

Authors: Chenhao Zhu

Abstract:

Quantitative mapping is playing a growing role in guiding urban planning, such as using a heat map created by CFX, CFD2000, or Envi-met, to adjust the master plan. However, there is no effective quantitative link between the mappings and planning formation. So, in many cases, the decision-making is still based on the planner's subjective interpretation and understanding of these mappings, which limits the improvement of scientific and accuracy brought by the quantitative mapping. Therefore, in this paper, an effort has been made to give a methodology of building a parametric link between the mapping and planning formation. A parametric planning process based on radiant mapping has been proposed for creating an urban green system. In the first step, a script is written in Grasshopper to build a road network and form the block, while the Ladybug Plug-in is used to conduct a radiant analysis in the form of mapping. Then, the research creatively transforms the radiant mapping from a polygon into a data point matrix, because polygon is hard to engage in the design formation. Next, another script is created to select the main green spaces from the road network based on the criteria of radiant intensity and connect the green spaces' central points to generate a green corridor. After that, a control parameter is introduced to adjust the corridor's form based on the radiant intensity. Finally, a green system containing greenspace and green corridor is generated under the quantitative control of the data matrix. The designer only needs to modify the control parameter according to the relevant research results and actual conditions to realize the optimization of the green system. This method can also be applied to much other mapping-based analysis, such as wind environment analysis, thermal environment analysis, and even environmental sensitivity analysis. The parameterized link between the mapping and planning will bring about a more accurate, objective, and scientific planning.

Keywords: parametric link, mapping, urban green system, radiant intensity, planning strategy, grasshopper

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13411 Mg and MgN₃ Cluster in Diamond: Quantum Mechanical Studies

Authors: T. S. Almutairi, Paul May, Neil Allan

Abstract:

The geometrical, electronic and magnetic properties of the neutral Mg center and MgN₃ cluster in diamond have been studied theoretically in detail by means of an HSE06 Hamiltonian that includes a fraction of the exact exchange term; this is important for a satisfactory picture of the electronic states of open-shell systems. Another batch of the calculations by GGA functionals have also been included for comparison, and these support the results from HSE06. The local perturbations in the lattice by introduced Mg defect are restricted in the first and second shell of atoms before eliminated. The formation energy calculated with HSE06 and GGA of single Mg agrees with the previous result. We found the triplet state with C₃ᵥ is the ground state of Mg center with energy lower than the singlet with C₂ᵥ by ~ 0.1 eV. The recent experimental ZPL (557.4 nm) of Mg center in diamond has been discussed in the view of present work. The analysis of the band-structure of the MgN₃ cluster confirms that the MgN₃ defect introduces a shallow donor level in the gap lying within the conduction band edge. This observation is supported by the EMM that produces n-type levels shallower than the P donor level. The formation energy of MgN₂ calculated from a 2NV defect (~ 3.6 eV) is a promising value from which to engineer MgN₃ defects inside the diamond. Ion-implantation followed by heating to about 1200-1600°C might induce migration of N related defects to the localized Mg center. Temperature control is needed for this process to restore the damage and ensure the mobilities of V and N, which demands a more precise experimental study.

Keywords: empirical marker method, generalised gradient approximation, Heyd–Scuseria–Ernzerhof screened hybrid functional, zero phono line

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13410 Group Learning for the Design of Human Resource Development for Enterprise

Authors: Hao-Hsi Tseng, Hsin-Yun Lee, Yu-Cheng Kuo

Abstract:

In order to understand whether there is a better than the learning function of learning methods and improve the CAD Courses for enterprise’s design human resource development, this research is applied in learning practical learning computer graphics software. In this study, Revit building information model for learning content, design of two different modes of learning curriculum to learning, learning functions, respectively, and project learning. Via a post-test, questionnaires and student interviews, etc., to study the effectiveness of a comparative analysis of two different modes of learning. Students participate in a period of three weeks after a total of nine-hour course, and finally written and hands-on test. In addition, fill in the questionnaire response by the student learning, a total of fifteen questionnaire title, problem type into the base operating software, application software and software-based concept features three directions. In addition to the questionnaire, and participants were invited to two different learning methods to conduct interviews to learn more about learning students the idea of two different modes. The study found that the ad hoc short-term courses in learning, better learning outcomes. On the other hand, functional style for the whole course students are more satisfied, and the ad hoc style student is difficult to accept the ad hoc style of learning.

Keywords: development, education, human resource, learning

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13409 Euthanasia Reconsidered: Voting and Multicriteria Decision-Making in Medical Ethics

Authors: J. Hakula

Abstract:

Discussion on euthanasia is a continuous process. Euthanasia is defined as 'deliberately ending a patient's life by administering life-ending drugs at the patient's explicit request'. With few exceptions, worldwide in most countries human societies have not been able to agree on some fundamental issues concerning ultimate decisions of life and death. Outranking methods in voting oriented social choice theory and multicriteria decision-making (MCDM) can be applied to issues in medical ethics. There is a wide range of voting methods, and using different methods the same group of voters can end up with different outcomes. In the MCDM context, decision alternatives can be substituted for candidates, and criteria for voters. The view chosen here is that of a single decision-maker. Initially, three alternatives and three criteria are chosen. Pairwise and basic positional voting rules - plurality, anti-plurality and the Borda count - are applied. In the MCDM solution, criteria are put weights by giving them the more 'votes'; the more important the decision-maker ranks them. A hypothetical example on evaluating properties of euthanasia consists of three alternatives A, B, and C, which are ranked according to three criteria - the patient’s willingness to cooperate, general action orientation (active/passive), and cost-effectiveness - the criteria having weights 7, 5, and 4, respectively. Using the plurality rule and the weights given to criteria, A is the best alternative, B and C thereafter. In pairwise comparisons, both B and C defeat A with weight scores 7 to 9. On the other hand, B is defeated by C with weights 11 to 5. Thus, C (i.e. the so-called Condorcet winner) defeats both A and B. The best alternative using the plurality principle is not necessarily the best in the pairwise sense, the conflict remaining unsolved with or without additional weights. Positional rules are sensitive to variations in alternative sets. In the example above, the plurality rule gives the rank ABC. If we leave out C, the plurality ranking between A and B results in BA. Withdrawing B or A the ranking is CA and CB, respectively. In pairwise comparisons an analogous problem emerges when the number of criteria is varied. Cyclic preferences may lead to a total tie, and no (rational) choice between the alternatives can be made. In conclusion, the choice of the best commitment to re-evaluate euthanasia, with criteria left unchanged, depends entirely on the evaluation method used. The right strategies matter, too. Future studies might concern the problem of an abstention - a situation where voters do not vote - and still their best candidate may win. Or vice versa, actively giving the ballot to their first rank choice might lead to a total loss. In MCDM terms, a decision might occur where some central criteria are not actively involved in the best choice made.

Keywords: medical ethics, euthanasia, voting methods, multicriteria decision-making

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13408 Artificial Intelligence Methods for Returns Expectations in Financial Markets

Authors: Yosra Mefteh Rekik, Younes Boujelbene

Abstract:

We introduce in this paper a new conceptual model representing the stock market dynamics. This model is essentially based on cognitive behavior of the intelligence investors. In order to validate our model, we build an artificial stock market simulation based on agent-oriented methodologies. The proposed simulator is composed of market supervisor agent essentially responsible for executing transactions via an order book and various kinds of investor agents depending to their profile. The purpose of this simulation is to understand the influence of psychological character of an investor and its neighborhood on its decision-making and their impact on the market in terms of price fluctuations. Therefore, the difficulty of the prediction is due to several features: the complexity, the non-linearity and the dynamism of the financial market system, as well as the investor psychology. The Artificial Neural Networks learning mechanism take on the role of traders, who from their futures return expectations and place orders based on their expectations. The results of intensive analysis indicate that the existence of agents having heterogeneous beliefs and preferences has provided a better understanding of price dynamics in the financial market.

Keywords: artificial intelligence methods, artificial stock market, behavioral modeling, multi-agent based simulation

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13407 Varying Frequency Application of Vermicast as Supplemented with 19-19-19+Me in the Agronomic Performance of Lettuce (Lactuca sativa)

Authors: Jesryl B. Paulite, Eixer Niel V. Enesco

Abstract:

Lettuce is not well known in the lowland locality in the tropical countries like Philippines. Farmers thought that this crop is not adaptable to the climate that we have in lowland. But some new varieties can tolerate warmer conditions. The massive use of pesticides in lettuce production might chronically affect human health and environment. The move of the Philippine government is toward organic. One of the organic material is vermicompost. It is an organic fertilizer that serves as soil conditioner and enhances soil fertility and promotes vigorous and healthy crop growth and Supplementation of 19-19-19+M.E. will make it better since it contains N-P-K and selected microelements to meet the nutritive requirements of the crop. The experiment was conducted at Purok 3, Brgy. Tiburcia, Kapalong, Davao del Norte from February 6, 2014 to March 4, 2014. The study was conducted to determine the effect of varying frequency application of vermicast as supplemented with 19-19-19+M.E. in lettuce. Specifically, this aimed to 1.) Identify the agronomic performance of lettuce as affected by varying frequency application of vermicast as supplemented with 19-19-19+M.E.; 2.) Assess the economic profitability of lettuce as applied with vermicast as supplemented with 19-19-19+M.E. The study was laid out in Randomized Complete Block Design (RCBD) with four treatments and three replications. The treatments were as follow: T1 – Untreated, T2 - Weekly Application, T3- Bi-weekly Application, and T4- Monthly Application. The data on percent (%) mortality were transformed using square root of transformation before Analysis of Variance (ANOVA). Results revealed not significant in terms of percent mortality in weekly and monthly application of the treatment having a mean of 1.76 % and 3.09 %. However, Significant differences were observed in agronomic performances such as; plant height with a mean of 10.63 cm in weekly application and 6.40 cm for the untreated, leaf width with a mean of 10.80 cm for the weekly application and 6.03 for the untreated, fresh weight with a mean of 25.67 g for the weekly application and 6.83 g for the untreated, and yield with a mean of 1,208.33 kg/ha for the weekly application and 327.08 kg/ha for the untreated, respectively. Results further exposed that profitability of lettuce in terms of Return of Production Cost (RPC) were; bi-weekly with 91.01 %, monthly with 68.20 %, weekly with 25.34 % and untreated (control) with 16.69 %.

Keywords: agronomic performance, economic profitability, vermicast, percent mortality, 19-19-19+ME

Procedia PDF Downloads 428
13406 Optimizing Resource Allocation and Indoor Location Using Bluetooth Low Energy

Authors: Néstor Álvarez-Díaz, Pino Caballero-Gil, Héctor Reboso-Morales, Francisco Martín-Fernández

Abstract:

The recent tendency of "Internet of Things" (IoT) has developed in the last years, causing the emergence of innovative communication methods among multiple devices. The appearance of Bluetooth Low Energy (BLE) has allowed a push to IoT in relation to smartphones. In this moment, a set of new applications related to several topics like entertainment and advertisement has begun to be developed but not much has been done till now to take advantage of the potential that these technologies can offer on many business areas and in everyday tasks. In the present work, the application of BLE technology and smartphones is proposed on some business areas related to the optimization of resource allocation in huge facilities like airports. An indoor location system has been developed through triangulation methods with the use of BLE beacons. The described system can be used to locate all employees inside the building in such a way that any task can be automatically assigned to a group of employees. It should be noted that this system cannot only be used to link needs with employees according to distances, but it also takes into account other factors like occupation level or category. In addition, it has been endowed with a security system to manage business and personnel sensitive data. The efficiency of communications is another essential characteristic that has been taken into account in this work.

Keywords: bluetooth low energy, indoor location, resource assignment, smartphones

Procedia PDF Downloads 379
13405 Implicit U-Net Enhanced Fourier Neural Operator for Long-Term Dynamics Prediction in Turbulence

Authors: Zhijie Li, Wenhui Peng, Zelong Yuan, Jianchun Wang

Abstract:

Turbulence is a complex phenomenon that plays a crucial role in various fields, such as engineering, atmospheric science, and fluid dynamics. Predicting and understanding its behavior over long time scales have been challenging tasks. Traditional methods, such as large-eddy simulation (LES), have provided valuable insights but are computationally expensive. In the past few years, machine learning methods have experienced rapid development, leading to significant improvements in computational speed. However, ensuring stable and accurate long-term predictions remains a challenging task for these methods. In this study, we introduce the implicit U-net enhanced Fourier neural operator (IU-FNO) as a solution for stable and efficient long-term predictions of the nonlinear dynamics in three-dimensional (3D) turbulence. The IU-FNO model combines implicit re-current Fourier layers to deepen the network and incorporates the U-Net architecture to accurately capture small-scale flow structures. We evaluate the performance of the IU-FNO model through extensive large-eddy simulations of three types of 3D turbulence: forced homogeneous isotropic turbulence (HIT), temporally evolving turbulent mixing layer, and decaying homogeneous isotropic turbulence. The results demonstrate that the IU-FNO model outperforms other FNO-based models, including vanilla FNO, implicit FNO (IFNO), and U-net enhanced FNO (U-FNO), as well as the dynamic Smagorinsky model (DSM), in predicting various turbulence statistics. Specifically, the IU-FNO model exhibits improved accuracy in predicting the velocity spectrum, probability density functions (PDFs) of vorticity and velocity increments, and instantaneous spatial structures of the flow field. Furthermore, the IU-FNO model addresses the stability issues encountered in long-term predictions, which were limitations of previous FNO models. In addition to its superior performance, the IU-FNO model offers faster computational speed compared to traditional large-eddy simulations using the DSM model. It also demonstrates generalization capabilities to higher Taylor-Reynolds numbers and unseen flow regimes, such as decaying turbulence. Overall, the IU-FNO model presents a promising approach for long-term dynamics prediction in 3D turbulence, providing improved accuracy, stability, and computational efficiency compared to existing methods.

Keywords: data-driven, Fourier neural operator, large eddy simulation, fluid dynamics

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13404 Application of Metaverse Service to Construct Nursing Education Theory and Platform in the Post-pandemic Era

Authors: Chen-Jung Chen, Yi-Chang Chen

Abstract:

While traditional virtual reality and augmented reality only allow for small movement learning and cannot provide a truly immersive teaching experience to give it the illusion of movement, the new technology of both content creation and immersive interactive simulation of the metaverse can just reach infinite close to the natural teaching situation. However, the mixed reality virtual classroom of metaverse has not yet explored its theory, and it is rarely implemented in the situational simulation teaching of nursing education. Therefore, in the first year, the study will intend to use grounded theory and case study methods and in-depth interviews with nursing education and information experts. Analyze the interview data to investigate the uniqueness of metaverse development. The proposed analysis will lead to alternative theories and methods for the development of nursing education. In the second year, it will plan to integrate the metaverse virtual situation simulation technology into the alternate teaching strategy in the pediatric nursing technology course and explore the nursing students' use of this teaching method as the construction of personal technology and experience. By leveraging the unique features of distinct teaching platforms and developing processes to deliver alternative teaching strategies in a nursing technology teaching environment. The aim is to increase learning achievements without compromising teaching quality and teacher-student relationships in the post-pandemic era. A descriptive and convergent mixed methods design will be employed. Sixty third-grade nursing students will be recruited to participate in the research and complete the pre-test. The students in the experimental group (N=30) agreed to participate in 4 real-time mixed virtual situation simulation courses in self-practice after class and conducted qualitative interviews after each 2 virtual situation courses; the control group (N=30) adopted traditional practice methods of self-learning after class. Both groups of students took a post-test after the course. Data analysis will adopt descriptive statistics, paired t-tests, one-way analysis of variance, and qualitative content analysis. This study addresses key issues in the virtual reality environment for teaching and learning within the metaverse, providing valuable lessons and insights for enhancing the quality of education. The findings of this study are expected to contribute useful information for the future development of digital teaching and learning in nursing and other practice-based disciplines.

Keywords: metaverse, post-pandemic era, online virtual classroom, immersive teaching

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13403 Affordable, Adaptable, and Resilient Industrial Precincts

Authors: Peter Ned Wales

Abstract:

This paper is the result of a substantial amount of data looking at how industrially zoned land is changing post COVID in the 21st Century. With the impact of global megatrends such as globalisation, the rapid adaption of innovative technologies and elevated demands on the design typologies, the tradition view of employment lands is quickly evolving. The research findings discussed here clearly show that land use conflicts have begun to take their toll across numerous light industrial precincts within the booming City of the Gold Coast. The recent global pandemic has placed enormous pressures on land values and industrial lands in Southeast Queensland. considered a highly desirable place to live, work and play are morphing in new ways. This region of Australia has become one of the most desirable places to locate after extended pandemic lock downs in Sydney and Melbourne. Findings in the current business trends have highlighted a new way of applying land use zones that provide a sustainable hybrid of acceptable land uses for prosperous business activity. In the wake of a rapid rise in the knowledge economy and boutique products that reflect the younger demographic has resulted in new emerging business activities that are significantly different from business trends two decades ago, when these industrial land use controls were originally applied. This paper explores what are the new demands on these established employment precincts and how local governments can better support start-ups and a broad variety of land uses not previously considered relevant to local government planners.

Keywords: sustainable urban, urban design, industrial lands, employment lands, sustainable communities

Procedia PDF Downloads 60