Search results for: ordinal response models
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 11299

Search results for: ordinal response models

6289 In Situ Laser-Induced Synthesis of Copper Microstructures with High Catalytic Properties and Sensory Characteristics

Authors: Maxim Panov, Evgenia Khairullina, Sergey Ermakov, Oleg Gundobin, Vladimir Kochemirovsky

Abstract:

The continuous in situ laser-induced catalysis proceeding via generation and growth of nano-sized copper particles was discussed. Also, the simple and lost-cost method for manufacturing of microstructural copper electrodes was proposed. The electrochemical properties of these electrodes were studied by cyclic voltammetry and impedance spectroscopy. The surface of the deposited copper structures (electrodes) was investigated by X-ray photoelectron spectroscopy and atomic force microscopy. These microstructures are highly conductive and porous with a dispersion of pore size ranging from 50 nm to 50 μm. An analytical response of the fabricated copper electrode is 30 times higher than those observed for a pure bulk copper with similar geometric parameters. A study of sensory characteristics for hydrogen peroxide determination showed that the value of Faraday current at the fabricated copper electrode is 2-2.5 orders of magnitude higher than for etalon one.

Keywords: laser-induced deposition, electrochemical electrodes, non-enzymatic sensors, copper

Procedia PDF Downloads 239
6288 A Methodology of Using Fuzzy Logics and Data Analytics to Estimate the Life Cycle Indicators of Solar Photovoltaics

Authors: Thor Alexis Sazon, Alexander Guzman-Urbina, Yasuhiro Fukushima

Abstract:

This study outlines the method of how to develop a surrogate life cycle model based on fuzzy logic using three fuzzy inference methods: (1) the conventional Fuzzy Inference System (FIS), (2) the hybrid system of Data Analytics and Fuzzy Inference (DAFIS), which uses data clustering for defining the membership functions, and (3) the Adaptive-Neuro Fuzzy Inference System (ANFIS), a combination of fuzzy inference and artificial neural network. These methods were demonstrated with a case study where the Global Warming Potential (GWP) and the Levelized Cost of Energy (LCOE) of solar photovoltaic (PV) were estimated using Solar Irradiation, Module Efficiency, and Performance Ratio as inputs. The effects of using different fuzzy inference types, either Sugeno- or Mamdani-type, and of changing the number of input membership functions to the error between the calibration data and the model-generated outputs were also illustrated. The solution spaces of the three methods were consequently examined with a sensitivity analysis. ANFIS exhibited the lowest error while DAFIS gave slightly lower errors compared to FIS. Increasing the number of input membership functions helped with error reduction in some cases but, at times, resulted in the opposite. Sugeno-type models gave errors that are slightly lower than those of the Mamdani-type. While ANFIS is superior in terms of error minimization, it could generate solutions that are questionable, i.e. the negative GWP values of the Solar PV system when the inputs were all at the upper end of their range. This shows that the applicability of the ANFIS models highly depends on the range of cases at which it was calibrated. FIS and DAFIS generated more intuitive trends in the sensitivity runs. DAFIS demonstrated an optimal design point wherein increasing the input values does not improve the GWP and LCOE anymore. In the absence of data that could be used for calibration, conventional FIS presents a knowledge-based model that could be used for prediction. In the PV case study, conventional FIS generated errors that are just slightly higher than those of DAFIS. The inherent complexity of a Life Cycle study often hinders its widespread use in the industry and policy-making sectors. While the methodology does not guarantee a more accurate result compared to those generated by the Life Cycle Methodology, it does provide a relatively simpler way of generating knowledge- and data-based estimates that could be used during the initial design of a system.

Keywords: solar photovoltaic, fuzzy logic, inference system, artificial neural networks

Procedia PDF Downloads 157
6287 Digital Image Correlation Based Mechanical Response Characterization of Thin-Walled Composite Cylindrical Shells

Authors: Sthanu Mahadev, Wen Chan, Melanie Lim

Abstract:

Anisotropy dominated continuous-fiber composite materials have garnered attention in numerous mechanical and aerospace structural applications. Tailored mechanical properties in advanced composites can exhibit superiority in terms of stiffness-to-weight ratio, strength-to-weight ratio, low-density characteristics, coupled with significant improvements in fatigue resistance as opposed to metal structure counterparts. Extensive research has demonstrated their core potential as more than just mere lightweight substitutes to conventional materials. Prior work done by Mahadev and Chan focused on formulating a modified composite shell theory based prognosis methodology for investigating the structural response of thin-walled circular cylindrical shell type composite configurations under in-plane mechanical loads respectively. The prime motivation to develop this theory stemmed from its capability to generate simple yet accurate closed-form analytical results that can efficiently characterize circular composite shell construction. It showcased the development of a novel mathematical framework to analytically identify the location of the centroid for thin-walled, open cross-section, curved composite shells that were characterized by circumferential arc angle, thickness-to-mean radius ratio, and total laminate thickness. Ply stress variations for curved cylindrical shells were analytically examined under the application of centric tensile and bending loading. This work presents a cost-effective, small-platform experimental methodology by taking advantage of the full-field measurement capability of digital image correlation (DIC) for an accurate assessment of key mechanical parameters such as in-plane mechanical stresses and strains, centroid location etc. Mechanical property measurement of advanced composite materials can become challenging due to their anisotropy and complex failure mechanisms. Full-field displacement measurements are well suited for characterizing the mechanical properties of composite materials because of the complexity of their deformation. This work encompasses the fabrication of a set of curved cylindrical shell coupons, the design and development of a novel test-fixture design and an innovative experimental methodology that demonstrates the capability to very accurately predict the location of centroid in such curved composite cylindrical strips via employing a DIC based strain measurement technique. Error percentage difference between experimental centroid measurements and previously estimated analytical centroid results are observed to be in good agreement. The developed analytical modified-shell theory provides the capability to understand the fundamental behavior of thin-walled cylindrical shells and offers the potential to generate novel avenues to understand the physics of such structures at a laminate level.

Keywords: anisotropy, composites, curved cylindrical shells, digital image correlation

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6286 Design and Performance Optimization of Isostatic Pressing Working Cylinder Automatic Exhaust Valve

Authors: Wei-Zhao, Yannian-Bao, Xing-Fan, Lei-Cao

Abstract:

An isostatic pressing working cylinder automatic exhaust valve is designed. The finite element models of valve core and valve body under ultra-high pressure work environment are built to study the influence of interact of valve core and valve body to sealing performance. The contact stresses of metal sealing surface with different sizes are calculated and the automatic exhaust valve is optimized. The result of simulation and experiment shows that the sealing of optimized exhaust valve is more reliable and the service life is greatly improved. The optimized exhaust valve has been used in the warm isostatic pressing equipment.

Keywords: exhaust valve, sealing, ultra-high pressure, isostatic pressing

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6285 Testing the Validity of Feldstein-Horioka Puzzle in BRICS Countries

Authors: Teboho J. Mosikari, Johannes T. Tsoku, Diteboho L. Xaba

Abstract:

The increase of capital mobility across emerging economies has become an interesting topic for many economic policy makers. The current study tests the validity of Feldstein–Horioka puzzle for 5 BRICS countries. The sample period of the study runs from 2001 to 2014. The study uses the following parameter estimates well known as the Fully Modified OLS (FMOLS), and Dynamic OLS (DOLS). The results of the study show that investment and savings are cointegrated in the long run. The parameters estimated using FMOLS and DOLS are 0.85 and 0.74, respectively. These results imply that policy makers within BRICS countries have to consider flexible monetary and fiscal policy instruments to influence the mobility of capital with the bloc.

Keywords: Feldstein and Horioka puzzle, saving and investment, panel models, BRICS countries

Procedia PDF Downloads 254
6284 Total Lipid of Mutant Synechococcus sp. PCC 7002

Authors: Azlin S Azmi, Mus’ab Zainal, Sarina Sulaiman, Azura Amid, Zaki Zainudin

Abstract:

Microalgae lipid is a promising feedstock for biodiesel production. The objective of this work was to study growth factors affecting marine mutant Synechococcus sp. (PCC 7002) for high lipid production. Four growth factors were investigated; nitrogen-phosporus-potassium (NPK) concentration, light intensity, temperature and NaNO3 concentration on mutant strain growth and lipid production were studied. Design Expert v8.0 was used to design the experimental and analyze the data. The experimental design selected was Min-Run Res IV which consists of 12 runs and the response surfaces measured were specific growth rate and lipid concentration. The extraction of lipid was conducted by chloroform/methanol solvents system. Based on the study, mutant Synechococcus sp. PCC 7002 gave the highest specific growth rate of 0.0014 h-1 at 0% NPK, 2500 lux, 40oC and 0% NaNO3. On the other hand, the highest lipid concentration was obtained at 0% NPK, 3500 lux, 30°C and 1% NaNO3.

Keywords: Cyanobacteria, lipid, mutant, marine Synechococcus sp. (PCC 7002), specific growth rate

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6283 Assessing Effectiveness of Outrigger and Belt Truss System for Tall Buildings under Wind Loadings

Authors: Nirand Anunthanakul

Abstract:

This paper is to investigate a 54-story reinforced concrete residential tall building structures—238.8 meters high. Shear walls, core walls, and columns are the primary vertical components. Other special lateral components—core-outrigger and belt trusses—are studied and combined with the structural system in order to increase the structural stability during severe lateral load events, particularly, wind loads. The wind tunnel tests are conducted using the force balance technique. The overall wind loads and dynamics response of the building are also measured for 360 degrees of azimuth—basis for 10-degree intervals. The results from numerical analysis indicate that an outrigger and belt truss system clearly engages perimeter columns to efficiently reduce acceleration index and lateral deformations at the top level so that the building structures achieve lateral stability, and meet standard provision values.

Keywords: outrigger, belt truss, tall buildings, wind loadings

Procedia PDF Downloads 563
6282 Dambreak Flood Analysis Using HEC-RAS and GIS Technologies

Authors: Oussama Derdous, Lakhdar Djemili, Hamza Bouchehed

Abstract:

The potential risks associated with dam break flooding could be considerable and result in major damage, including loss of life and property destruction. In the past, Algeria experienced such flood disasters; let’s recall the failure of Fergoug dam in 1881, this accident cost 200 lives, many houses and bridges were destroyed by the flooding. Recently the Algerian government have obligated to dam owners the development of detailed dam break Emergency Action Plans for its 64 major dams. The research presented here was conducted within this framework, Zardezas dam which is located in the city of Skikda in the North East of Algeria was the case of study. The model HEC-RAS was used for the hydrodynamic routing of the dam break flood wave. In addition, Geographic Information System (GIS) was used to create inundation maps and produce a visualization of the flood propagation in the Saf-Saf River.The simulation results that demonstrate the significance of Zardezas dam break flooding; constitute a real tool for developing emergency response plans and assisting territorial communities in land use planning.

Keywords: dam break, HEC-RAS, GIS, inundation maps, Emergency Action Plan

Procedia PDF Downloads 384
6281 Using of Particle Swarm Optimization for Loss Minimization of Vector-Controlled Induction Motors

Authors: V. Rashtchi, H. Bizhani, F. R. Tatari

Abstract:

This paper presents a new online loss minimization for an induction motor drive. Among the many loss minimization algorithms (LMAs) for an induction motor, a particle swarm optimization (PSO) has the advantages of fast response and high accuracy. However, the performance of the PSO and other optimization algorithms depend on the accuracy of the modeling of the motor drive and losses. In the development of the loss model, there is always a trade off between accuracy and complexity. This paper presents a new online optimization to determine an optimum flux level for the efficiency optimization of the vector-controlled induction motor drive. An induction motor (IM) model in d-q coordinates is referenced to the rotor magnetizing current. This transformation results in no leakage inductance on the rotor side, thus the decomposition into d-q components in the steady-state motor model can be utilized in deriving the motor loss model. The suggested algorithm is simple for implementation.

Keywords: induction machine, loss minimization, magnetizing current, particle swarm optimization

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6280 The Roles of Health Consciousness, Health Motivation, and Trust in the Purchase Intention of Meat with Traceability

Authors: Kawpong Polyorat, Nathamon Buaprommee

Abstract:

Food safety crises including mad cow disease and bird flu have raised consumers’ concern in meat safety. In response, the meat industry has adopted traceability systems to standardize quality and safety of their meat production. Traceability, however, is still rarely positioned as a marketing tool to persuade consumers who are meat endusers. Therefore, the present study attempts to understand consumer behaviors in the context of meat with traceability system by conducting a study in Thailand where research in this area is scant. The study results, based on structural equation modeling with AMOS, reveal that, while health motivation has a significant, positive impact on traceability trust, health consciousness does not directly affect traceability. Health consciousness, nevertheless, have a positive influence on health motivation. Finally, traceability trust has a positive impact on purchase intention of meat with traceability. Research implications and future study directions conclude the study report.

Keywords: consumer behavior, health consciousness, health motivation, traceability, trust

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6279 Optimization of Process Parameters in Wire Electrical Discharge Machining of Inconel X-750 for Dimensional Deviation Using Taguchi Technique

Authors: Mandeep Kumar, Hari Singh

Abstract:

The effective optimization of machining process parameters affects dramatically the cost and production time of machined components as well as the quality of the final products. This paper presents the optimization aspects of a Wire Electrical Discharge Machining operation using Inconel X-750 as work material. The objective considered in this study is minimization of the dimensional deviation. Six input process parameters of WEDM namely spark gap voltage, pulse-on time, pulse-off time, wire feed rate, peak current and wire tension, were chosen as variables to study the process performance. Taguchi's design of experiments methodology has been used for planning and designing the experiments. The analysis of variance was carried out for raw data as well as for signal to noise ratio. Four input parameters and one two-factor interaction have been found to be statistically significant for their effects on the response of interest. The confirmation experiments were also performed for validating the predicted results.

Keywords: ANOVA, DOE, inconel, machining, optimization

Procedia PDF Downloads 198
6278 Effect of Recreational Soccer on Health Indices and Diseases Prevention

Authors: Avinash Kharel

Abstract:

Recreational soccer (RS) as a medium of small-sided soccer game (SSG) has an immense positive effect on physical health, mental health and wellbeing. The RS has reflected both acute responses and long-term effects of training on sedentary, trained and clinical population on any age, gender or health status. The enjoyable mode of training elicits greater adherence by optimising intrinsic motivation while offering health benefits that match those achieved by treadmill and cycle ergometer programmes both as continuous and interval forms of training. Additionally, recreational soccer is effective and efficient regimens with highlighted social, motivational and competitive components overcoming the barriers such as cost-efficiency, time-efficiency, assess to facilities and intrinsic motivation. Further, it can be applied as an effective broad-spectrum non-pharmacological treatment of lifestyle diseases producing a positive physiological response in healthy subjects, patients and elderly people regardless of age, gender or training experience.

Keywords: recreational soccer, health benefits, diseases prevention, physiology

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6277 Numerical Optimization of Trapezoidal Microchannel Heat Sinks

Authors: Yue-Tzu Yang, Shu-Ching Liao

Abstract:

This study presents the numerical simulation of three-dimensional incompressible steady and laminar fluid flow and conjugate heat transfer of a trapezoidal microchannel heat sink using water as a cooling fluid in a silicon substrate. Navier-Stokes equations with conjugate energy equation are discretized by finite-volume method. We perform numerical computations for a range of 50 ≦ Re ≦ 600, 0.05W ≦ P ≦ 0.8W, 20W/cm2 ≦ ≦ 40W/cm2. The present study demonstrates the numerical optimization of a trapezoidal microchannel heat sink design using the response surface methodology (RSM) and the genetic algorithm method (GA). The results show that the average Nusselt number increases with an increase in the Reynolds number or pumping power, and the thermal resistance decreases as the pumping power increases. The thermal resistance of a trapezoidal microchannel is minimized for a constant heat flux and constant pumping power.

Keywords: microchannel heat sinks, conjugate heat transfer, optimization, genetic algorithm method

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6276 Impact of Tuberculosis Co-infection on Cytokine Expression in HIV-Infected Individuals

Authors: M. Nosik, I. Rymanova, N. Adamovich, S. Sevostyanihin, K. Ryzhov, Y. Kuimova, A. Kravtchenko, N. Sergeeva, A. Sobkin

Abstract:

HIV and Tuberculosis (TB) infections each speed the other's progress. HIV-infection increases the risk of TB disease. At the same time, TB infection is associated with clinical progression of HIV-infection. HIV+TB co-infected patients are also at higher risk of acquiring new opportunistic infections. An important feature of disease progression and clinical outcome is the innate and acquired immune responses. HIV and TB, however, have a spectrum of dysfunctions of the immune response. As cytokines play a crucial role in the immunopathology of both infections, it is important to study immune interactions in patients with dual infection HIV+TB. Plasma levels of proinflammatory cytokines IL-2, IFN-γ and immunoregulating cytokines IL-4, IL-10 were evaluated in 75 patients with dual infection HIV+TB, 58 patients with HIV monoinfection and 50 patients with TB monoinfection who were previously naïve for HAART. The decreased levels of IL-2, IFN-γ, IL-4 and IL-10 were observed in patients with dual infection HIV+TB in comparison with patients who had only HIV or TB which means the profound suppression of Th1 and Th2 cytokine secretion. Thus, those cytokines could possibly serve as immunological markers of progression of HIV-infection in patients with TB.

Keywords: HIV, tuberculosis (TB), HIV associated with TB, Th1/ Th2 cytokine expression

Procedia PDF Downloads 357
6275 The Effect of Microgrid on Power System Oscillatory Stability

Authors: Burak Yildirim, Muhsin Tunay Gencoglu

Abstract:

This publication shows the effects of Microgrid (MG) integration on the power systems oscillating stability. Generated MG model power systems were applied to the IEEE 14 bus test system which is widely used in stability studies. Stability studies were carried out with the help of eigenvalue analysis over linearized system models. In addition, Hopf bifurcation point detection was performed to show the effect of MGs on the system loadability margin. In the study results, it is seen that MGs affect system stability positively by increasing system loadability margin and has a damper effect on the critical modes of the system and the electromechanical local modes, but they make the damping amount of the electromechanical interarea modes reduce.

Keywords: Eigenvalue analysis, microgrid, Hopf bifurcation, oscillatory stability

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6274 Modeling Generalization in the Acquired Equivalence Paradigm with the Successor Representation

Authors: Troy M. Houser

Abstract:

The successor representation balances flexible and efficient reinforcement learning by learning to predict the future, given the present. As such, the successor representation models stimuli as what future states they lead to. Therefore, two stimuli that are perceptually dissimilar but lead to the same future state will come to be represented more similarly. This is very similar to an older behavioral paradigm -the acquired equivalence paradigm, which measures the generalization of learned associations. Here, we test via computational modeling the plausibility that the successor representation is the mechanism by which people generalize knowledge learned in the acquired equivalence paradigm. Computational evidence suggests that this is a plausible mechanism for acquired equivalence and thus can guide future empirical work on individual differences in associative-based generalization.

Keywords: acquired equivalence, successor representation, generalization, decision-making

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6273 Evaluating a Peer-To-Peer Health Education Program in Public Housing Communities during the COVID-19 Pandemic

Authors: Jane Oliver, Angeline Ferdinand, Jessica Kaufman, Peta Edler, Nicole Allard, Margie Danchin, Katherine B. Gibney

Abstract:

Background: The cohealth Health Concierge program operated in Melbourne, Australia, from July 2020 to 30 June 2022. The program was designed to provide place-based peer-to-peer COVID-19 education and support to culturally and linguistically diverse residents of high-rise public housing estates. During this time, the COVID-19 public health response changed frequently. We conducted a mixed-methods evaluation to determine the program’s impact on residents’ trust, engagement and communication with health services and public health activities. Methods: The RE-AIM model was used to assess program reach, effectiveness, adoption, implementation and maintenance and the evaluation was informed by a Project Reference Group including end-users. Data were collected between March and May 2022 in four estates where the program operated. We surveyed 301 residents, conducted qualitative interviews with 32 stakeholders and analyzed data from 20,901 forms reporting interactions between Health Concierges and residents collected from August 2021 to May 2022. These forms outlined the support provided by Health Concierges during each interaction. Results: Overall, the program was effective in guiding residents to testing and vaccination services and facilitating COVID-19 safe practices. Nearly two-thirds (191; 63.5%) of the 301 surveyed participants reported speaking with a Health Concierge in the previous six months, and some described having meaningful conversations with them. Despite this, many of the interactions residents described having with Health Concierges were superficial. When considering surveyed participants’ responses to the adapted Public Health Disaster Trust Scale, the mean score across all estates was 2.3 (or slightly more than ‘somewhat confident’) in public health authorities’ ability to respond to a localized infectious disease outbreak. While the program was valued during the rapidly changing public health response, many felt it had failed to evolve in the ‘living with COVID’ phase. Some residents expressed frustration with Health Concierges’ having perceived inactive, passive roles - although other residents felt Health Concierges were helpful and appreciated them. A perception that the true impact of Health Concierges’ work was underrecognized was widely voiced by health staff. All 20,901 Interaction Forms identified COVID-19-related supports provided to residents; almost all included provision of facemasks and/or hand sanitiser and 78% identified additional supports that were also provided, most frequently provision of other health information. Conclusions: The program disseminated up-to-date information to a diverse population within a rapidly changing public health setting. Health Concierges were able promote COVID-19-safe behaviours, including vaccine uptake, and link residents with support services. We recommend the program be revised and continued. New programs that draw on the Health Concierge model may be valuable in supporting future pandemic responses and should be considered in preparedness planning.

Keywords: community health, COVID-19 pandemic, infectious diseases, public health, community health workers

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6272 Future Metro Station: Remodeling Underground Environment Based on Experience Scenarios and IoT Technology

Authors: Joo Min Kim, Dongyoun Shin

Abstract:

The project Future Station (FS) seek for a deeper understanding of metro station. The main idea of the project is enhancing the underground environment by combining new architectural design with IoT technology. This research shows the understanding of the metro environment giving references regarding traditional design approaches and IoT combined space design. Based on the analysis, this research presents design alternatives in two metro stations those are chosen for a testbed. It also presents how the FS platform giving a response to travelers and deliver the benefit to metro operators. In conclusion, the project describes methods to build future metro service and platform that understand traveler’s intentions and giving appropriate services back for enhancing travel experience. It basically used contemporary technology such as smart sensing grid, big data analysis, smart building, and machine learning technology.

Keywords: future station, digital lifestyle experience, sustainable metro, smart metro, smart city

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6271 Fractal-Wavelet Based Techniques for Improving the Artificial Neural Network Models

Authors: Reza Bazargan lari, Mohammad H. Fattahi

Abstract:

Natural resources management including water resources requires reliable estimations of time variant environmental parameters. Small improvements in the estimation of environmental parameters would result in grate effects on managing decisions. Noise reduction using wavelet techniques is an effective approach for pre-processing of practical data sets. Predictability enhancement of the river flow time series are assessed using fractal approaches before and after applying wavelet based pre-processing. Time series correlation and persistency, the minimum sufficient length for training the predicting model and the maximum valid length of predictions were also investigated through a fractal assessment.

Keywords: wavelet, de-noising, predictability, time series fractal analysis, valid length, ANN

Procedia PDF Downloads 362
6270 Serum Cortisol and Osteocalsin in Response to Eight Weeks Aerobic Training in Asthma Men with Mild to Moderate Intensity

Authors: Eizadi Mojtaba

Abstract:

This study aimed to evaluate the effect of 8 weeks aerobic training on serum osteocalsin as an osteoblasts hormone and cortisol in adult men with asthma. For this purpose, twenty four non-trained adult men with mild to moderate asthma were participated in study voluntarily and divided into exercise (aerobic training, 8 weeks/3 times per week) and control groups by randomly. Pre and post training of serum osteocalsin and cortisol were measured of two groups. Student’s paired ‘t’ test was applied to compare the pre and post training values. A p-value of less than 0.05 was considered to be statistically significant. There were no statistically significant differences with regard to all anthropometrical and biochemical markers between the exercise and control groups at baseline ( P > 0.05 ). Exercise training resulted in a significant increase in serum osteocalsin and decrease in cortisol ( P > 0.05 ), but not in control group. Based on these data, we concluded that aerobic training can be improved Processes of bone formation in asthma patients.

Keywords: osteoblasts, asthma, aerobic exercise, sedentary

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6269 DeClEx-Processing Pipeline for Tumor Classification

Authors: Gaurav Shinde, Sai Charan Gongiguntla, Prajwal Shirur, Ahmed Hambaba

Abstract:

Health issues are significantly increasing, putting a substantial strain on healthcare services. This has accelerated the integration of machine learning in healthcare, particularly following the COVID-19 pandemic. The utilization of machine learning in healthcare has grown significantly. We introduce DeClEx, a pipeline that ensures that data mirrors real-world settings by incorporating Gaussian noise and blur and employing autoencoders to learn intermediate feature representations. Subsequently, our convolutional neural network, paired with spatial attention, provides comparable accuracy to state-of-the-art pre-trained models while achieving a threefold improvement in training speed. Furthermore, we provide interpretable results using explainable AI techniques. We integrate denoising and deblurring, classification, and explainability in a single pipeline called DeClEx.

Keywords: machine learning, healthcare, classification, explainability

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6268 Experimental and Numerical Study on Energy Absorption Characteristic of a Coupler Rubber Buffer Used in Rail Vehicles

Authors: Zhixiang Li, Shuguang Yao, Wen Ma

Abstract:

Coupler rubber buffer has been widely applied on the high-speed trains and the main function of the rubber buffer is dissipating the impact energy between vehicles. The rubber buffer consists of two groups of rubbers, which are both pre-compressed and then installed into the frame body. This work focuses on the energy absorption capacity of each group of buffers particularly. The quasi-static compression tests were carried out to obtain the pre-compression force and the load-defection response of the buffers. Then a finite element (FE) model was constructed using Ls_dyna program. The rubber material was modeled with a tabulated method easily, in which no more material constants need to be fitted. The simulation results agreed with the experimental results well. Numerical study of the buffers was performed using the validated FE model and the influence of the initial pressure on the buffers was obtained. In addition, the interaction between the two groups of buffers was also investigated and the optimum distribution of the two was found.

Keywords: initial pressure, rubber buffer, simulation, tabulated method

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6267 Stochastic Default Risk Estimation Evidence from the South African Financial Market

Authors: Mesias Alfeus, Kirsty Fitzhenry, Alessia Lederer

Abstract:

The present paper provides empirical studies to estimate defaultable bonds in the South African financial market. The main goal is to estimate the unobservable factors affecting bond yields for South African major banks. The maximum likelihood approach is adopted for the estimation methodology. Extended Kalman filtering techniques are employed in order to tackle the situation that the factors cannot be observed directly. Multi-dimensional Cox-Ingersoll-Ross (CIR)-type factor models are considered. Results show that default risk increased sharply in the South African financial market during COVID-19 and the CIR model with jumps exhibits a better performance.

Keywords: default intensity, unobservable state variables, CIR, α-CIR, extended kalman filtering

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6266 The Effect of Pre-Cracks on Structural Strength of the Nextel Fibers: A Multiscale Modeling Approach

Authors: Seyed Mohammad Mahdi Zamani, Kamran Behdinan

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In this study, a multiscale framework is performed to model the strength of Nextel fibers in presence of an atomistic scale pre-crack at finite temperatures. The bridging cell method (BCM) is the multiscale technique applied in this study, which decomposes the system into the atomistic, bridging and continuum domains; solves the whole system in a finite element framework; and incorporates temperature dependent calculations. Since Nextel is known to be structurally stable and retain 70% of its initial strength up to 1100°C; simulations are conducted at both of the room temperatures, 25°C, and fire temperatures, 1200°C. Two cases are modeled for a pre-crack present in either phases of alumina or mullite of the Nextel structure. The materials’ response is studied with respect to deformation behavior and ultimate tensile strength. Results show different crack growth trends for the two cases, and as the temperature increases, the crack growth resistance and material’s strength decrease.

Keywords: Nextel fibers, multiscale modeling, pre-crack, ultimate tensile strength

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6265 Numerical and Experimental Investigation of Mixed-Mode Fracture of Cement Paste and Interface Under Three-Point Bending Test

Authors: S. Al Dandachli, F. Perales, Y. Monerie, F. Jamin, M. S. El Youssoufi, C. Pelissou

Abstract:

The goal of this research is to study the fracture process and mechanical behavior of concrete under I–II mixed-mode stress, which is essential for ensuring the safety of concrete structures. For this purpose, two-dimensional simulations of three-point bending tests under variable load and geometry on notched cement paste samples of composite samples (cement paste/siliceous aggregate) are modeled by employing Cohesive Zone Models (CZMs). As a result of experimental validation of these tests, the CZM model demonstrates its capacity to predict fracture propagation at the local scale.

Keywords: cement paste, interface, cohesive zone model, fracture, three-point flexural test bending

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6264 The Bloom of 3D Printing in the Health Care Industry

Authors: Mihika Shivkumar, Krishna Kumar, C. Perisamy

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3D printing is a method of manufacturing wherein materials, such as plastic or metal, are deposited in layers one on top of the other to produce a three dimensional object. 3D printing is most commonly associated with creating engineering prototypes. However, its applications in the field of human health care have been frequently disregarded. Medical applications for 3D printing are expanding rapidly and are envisaged to revolutionize health care. Medical applications for 3D printing, both present and its potential, can be categorized broadly, including: creation of customized prosthetics tissue and organ fabrication; creation of implants, and anatomical models and pharmaceutical research regarding drug dosage forms. This piece breaks down bioprinting in the healthcare sector. It focuses on the better subtle elements of every particular point, including how 3D printing functions in the present, its impediments, and future applications in the health care sector.

Keywords: bio-printing, prototype, drug delivery, organ regeneration

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6263 Non-Destructive Prediction System Using near Infrared Spectroscopy for Crude Palm Oil

Authors: Siti Nurhidayah Naqiah Abdull Rani, Herlina Abdul Rahim

Abstract:

Near infrared (NIR) spectroscopy has always been of great interest in the food and agriculture industries. The development of predictive models has facilitated the estimation process in recent years. In this research, 176 crude palm oil (CPO) samples acquired from Felda Johor Bulker Sdn Bhd were studied. A FOSS NIRSystem was used to tak e absorbance measurements from the sample. The wavelength range for the spectral measurement is taken at 1600nm to 1900nm. Partial Least Square Regression (PLSR) prediction model with 50 optimal number of principal components was implemented to study the relationship between the measured Free Fatty Acid (FFA) values and the measured spectral absorption. PLSR showed predictive ability of FFA values with correlative coefficient (R) of 0.9808 for the training set and 0.9684 for the testing set.

Keywords: palm oil, fatty acid, NIRS, PLSR

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6262 The Importance of Electronic Medical Record Systems in Health Care Economics

Authors: Mutaz Shurahabeel Ahmed Ombada

Abstract:

This paper investigates potential health and financial settlement of health information technology, this paper evaluates health care with the use of IT and other associated industries. It assesses prospective savings and costs of extensive acceptance of Electronic Medical Record Systems (EMRS), models significant to health as well as safety remuneration, and conclude that efficient EMRS execution and networking could ultimately save more than US $55 billion annually through recuperating health care effectiveness and that Health Information Technology -enabled prevention and administration of chronic disease could eventually double those savings while rising health and other social remuneration. On the contrary, this is improbable to be realized without related to significant modifications to the health care system.

Keywords: electronic medical record systems, health care economics, EMRS

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6261 SVID: Structured Vulnerability Intelligence for Building Deliberated Vulnerable Environment

Authors: Wenqing Fan, Yixuan Cheng, Wei Huang

Abstract:

The diversity and complexity of modern IT systems make it almost impossible for internal teams to find vulnerabilities in all software before the software is officially released. The emergence of threat intelligence and vulnerability reporting policy has greatly reduced the burden on software vendors and organizations to find vulnerabilities. However, to prove the existence of the reported vulnerability, it is necessary but difficult for security incident response team to build a deliberated vulnerable environment from the vulnerability report with limited and incomplete information. This paper presents a structured, standardized, machine-oriented vulnerability intelligence format, that can be used to automate the orchestration of Deliberated Vulnerable Environment (DVE). This paper highlights the important role of software configuration and proof of vulnerable specifications in vulnerability intelligence, and proposes a triad model, which is called DIR (Dependency Configuration, Installation Configuration, Runtime Configuration), to define software configuration. Finally, this paper has also implemented a prototype system to demonstrate that the orchestration of DVE can be automated with the intelligence.

Keywords: DIR triad model, DVE, vulnerability intelligence, vulnerability recurrence

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6260 Uplink Throughput Prediction in Cellular Mobile Networks

Authors: Engin Eyceyurt, Josko Zec

Abstract:

The current and future cellular mobile communication networks generate enormous amounts of data. Networks have become extremely complex with extensive space of parameters, features and counters. These networks are unmanageable with legacy methods and an enhanced design and optimization approach is necessary that is increasingly reliant on machine learning. This paper proposes that machine learning as a viable approach for uplink throughput prediction. LTE radio metric, such as Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), and Signal to Noise Ratio (SNR) are used to train models to estimate expected uplink throughput. The prediction accuracy with high determination coefficient of 91.2% is obtained from measurements collected with a simple smartphone application.

Keywords: drive test, LTE, machine learning, uplink throughput prediction

Procedia PDF Downloads 150