Search results for: mixed effect logistic regression model

Authors: H. Nabahat, E. Amiri, F. AzaditalabDavoudabadi, N. Zaeri

Abstract:

Tooth decay is one of the most common forms of oral and dental illness in the world, which causes huge costs of treatment, especially in high-risk groups such as people with oral dry mouth, prevention and control of it are very important. The use of traditional treatments such as extraction of drugs from medicinal plants is of paramount importance to Iran and the international community as well. The present study was conducted with the aim of investigating the antibacterial effect of the extract of Salvia officinalis and Mentha pulegium, which are the most commonly used drugs in the treatment of oral and teeth bacterial (Streptococcus mutant, Lactobacillus rhamnosis, and Actinomyces viscosis) in vitro method. In this experimental study, two herbs of Salvia and Mentha were prepared by maceration of hydroalcoholic extract, and the antibacterial effect was evaluated by broth macro dilution on streptococcal mutagen bacteria, lactobacillus rhamnosis, and viscose actinomycosis. The results were analyzed by the Whitney Mann test (P > 0.05). The results showed that the minimum inhibitory concentration (MIC) of the salmonella extract for Streptococcus mutan were 6.25 and 12.5 μg/ml, respectively, for lactobacillus of 1.56 and 3.12 μg/ml, respectively, and for actinomycosis viscose, The order of 12.5 and 100 μg/ml was obtained. As a result, broth macro dilution showed that both extracts of Salvia and Mentha had an inhibitory effect on all three species of bacteria. This effect for Salvia was significantly (P < 0.05) more than Mentha and was within the concentration range of both the extracts and had a bactericidal effect on all three bacteria.

Keywords: antibacterial effect, dental bacteria, herbal extracts , salvia officinalis, mentha pulegium

Procedia PDF Downloads 158

Authors: Elda Maraj, Shkelqim Kuka

Abstract:

Coronary heart disease causes many deaths in the world. Unfortunately, this problem will continue to increase in the future. In this paper, a fuzzy logic model to predict coronary heart disease is presented. This model has been developed with seven input variables and one output variable that was implemented for 30 patients in Albania. Here fuzzy logic toolbox of MATLAB is used. Fuzzy model inputs are considered as cholesterol, blood pressure, physical activity, age, BMI, smoking, and diabetes, whereas the output is the disease classification. The fuzzy sets and membership functions are chosen in an appropriate manner. Centroid method is used for defuzzification. The database is taken from University Hospital Center "Mother Teresa" in Tirana, Albania.

Keywords: coronary heart disease, fuzzy logic toolbox, membership function, prediction model

Procedia PDF Downloads 167

Authors: Md. Fazlul Karim, Ahmad Izani Md. Ismail, Mohammed Ashaque Meah

Abstract:

This paper focuses on the development of a 2-D Boundary Fitted and Nested Grid (BFNG) model to compute the tsunami propagation of Indonesian tsunami 2004 along the coastal region of Penang in Peninsular Malaysia. In the presence of a curvilinear coastline, boundary fitted grids are suitable to represent the model boundaries accurately. On the other hand, when large gradient of velocity within a confined area is expected, the use of a nested grid system is appropriate to improve the numerical accuracy with the least grid numbers. This paper constructs a shallow water nested and orthogonal boundary fitted grid model and presents computational results of the tsunami impact on the Penang coast due to the Indonesian tsunami of 2004. The results of the numerical simulations are compared with available data.

Keywords: boundary fitted nested model, tsunami, Penang Island, 2004 Indonesian Tsunami

Procedia PDF Downloads 326

Authors: Djemaa Megdoud, Messaoud Boudaa, Fatima Ouamrane, Salem Benamara

Abstract:

In recent years, the compression of date (Phoenix dactylifera L.) fruit powders (DP) to obtain date tablets (DT) has been suggested as a promising form of valorization of non commercial valuable date fruit (DF) varieties. To further improve and characterize DT, the present study aims to investigate the influence of the DP particle size and compression force on some physical properties of DT. The results show that independently of particle size, the hardness (y) of tablets increases with the increase of the compression force (x) following a logarithmic law (y = a ln (bx) where a and b are the constants of model). Further, a full factorial design (FFD) at two levels, applied to investigate the erosion %, reveals that the effects of time and particle size are the same in absolute value and they are beyond the effect of the compression. Regarding the disintegration time, the obtained results also by means of a FFD show that the effect of the compression force exceeds 4 times that of the DP particle size. As final stage, the color parameters in the CIELab system of DT immediately after their obtaining are differently influenced by the size of the initial powder.

Keywords: powder, tablets, date (Phoenix dactylifera L.), hardness, erosion, disintegration time, color

Procedia PDF Downloads 437

Authors: Wooyoung Jung, Ghang Lee

Abstract:

This paper paper reports the worldwide status of building information modeling (BIM) adoption from the perspectives of the engagement level, the Hype Cycle model, the technology diffusion model, and BIM-uses. An online survey was distributed, and 156 experts from six continents responded. Overall, North America was the most advanced continent, followed by Oceania and Europe. Countries in Asia perceived their phase mainly as slope of enlightenment (mature) in the Hype Cycle model. In the technology diffusion model, the main BIM-users worldwide were “early majority” (third phase), but those in the Middle East/Africa and South America were “early adopters” (second phase). In addition, the more advanced the country, the more number of BIM services employed in general. In summary, North America, Europe, Oceania, and Asia were advancing rapidly toward the mature stage of BIM, whereas the Middle East/Africa and South America were still in the early phase. The simple indexes used in this study may be used to track the worldwide status of BIM adoption in long-term surveys.

Keywords: BIM adoption, BIM services, hype cycle model, technology diffusion model

Procedia PDF Downloads 562

Authors: Hicham Gourgue, Ahmed Aharoune, Ahmed Ihlal

Abstract:

We present in this work our model of road traffic emissions (line sources) and dispersion of these emissions, named DISPOLSPEM (Dispersion of Poly Sources and Pollutants Emission Model). In its emission part, this model was designed to keep the consistent bottom-up and top-down approaches. It also allows to generate emission inventories from reduced input parameters being adapted to existing conditions in Morocco and in the other developing countries. While several simplifications are made, all the performance of the model results are kept. A further important advantage of the model is that it allows the uncertainty calculation and emission rate uncertainty according to each of the input parameters. In the dispersion part of the model, an improved line source model has been developed, implemented and tested against a reference solution. It provides improvement in accuracy over previous formulas of line source Gaussian plume model, without being too demanding in terms of computational resources. In the case study presented here, the biggest errors were associated with the ends of line source sections; these errors will be canceled by adjacent sections of line sources during the simulation of a road network. In cases where the wind is parallel to the source line, the use of the combination discretized source and analytical line source formulas minimizes remarkably the error. Because this combination is applied only for a small number of wind directions, it should not excessively increase the calculation time.

Keywords: air pollution, dispersion, emissions, line sources, road traffic, urban transport

Procedia PDF Downloads 450

Authors: Lynndee Kemmet

Abstract:

The U.S. military plays an increasing role in supporting political stability efforts, and this includes efforts to prevent the food insecurity that can trigger political and social instability. This paper presents a model that assists military commanders in identifying variables that impact food production and distribution in their areas of operation (AO), in identifying connections between variables and in assessing the impacts of those variables on food production and distribution. Through use of the model, military units can better target their data collection efforts and can categorize and analyze data within the data categorization framework most widely-used by military forces—PMESII-PT (Political, Military, Economic, Infrastructure, Information, Physical Environment and Time). The model provides flexibility of analysis in that commanders can target analysis to be highly focused on a specific PMESII-PT domain or variable or conduct analysis across multiple PMESII-PT domains. The model is also designed to assist commanders in mapping food systems in their AOs and then identifying components of those systems that must be strengthened or protected.

Keywords: food security, food system model, political stability, US Military

Procedia PDF Downloads 199

Authors: Mahshid Rezaei, Zahra Tajari, Zahra Esmaeily, Atefeh Eyvazkhani, Shahrzad Daei, Marjan Mansouri Dara, Mohaddesh Rezaei, Abolghassem Djazayeri, Ahmadreza Dorosti Motlagh

Abstract:

Background: Musculoskeletal pain is one of the most prevalent symptoms in elderly age. Nutrition and diet are considered important underlying factors that could affect chronic musculoskeletal pain. The purpose of this study was to identify the relationship between empirical dietary inflammatory patterns (EDII) and musculoskeletal pain. Method: In this cross-sectional study, 213 elderly individuals were selected from several health centers. The usual dietary intake was evaluated by a valid and reliable 147-items food frequency questionnaire (FFQ). To measure the intensity of pain, Visual Analogue Scale (VAS) was used. Multiple Linear Regression was applied to assess the association between EDII and musculoskeletal pain. Results: The results of multiple linear regression analysis indicate that a higher EDII score was associated with higher musculoskeletal pain (β= 0.21: 95% CI: 0.24-1.87: P= 0.003). These results stayed significant even after adjusting for covariates such as sex, marital status, height, family number, sleep, BMI, physical activity duration, waist circumference, protector, and medication use (β= 0.16: 95% CI: 0.11-1.04: P= 0.02). Conclusion: Study findings indicated that higher inflammation of diet might have a direct association with musculoskeletal pains in elderlies. However, further investigations are required to confirm these findings.

Keywords: musculoskeletal pain, empirical dietary inflammatory pattern, elderlies, dietary pattern

Procedia PDF Downloads 217

Authors: Suparman

Abstract:

This paper addresses the problem of the signal segmentation within a Bayesian framework by using reversible jump MCMC algorithm. The signal is modelled by piecewise constant Moving-Average (MA) model where the numbers of segments, the position of change-point, the order and the coefficient of the MA model for each segment are unknown. The reversible jump MCMC algorithm is then used to generate samples distributed according to the joint posterior distribution of the unknown parameters. These samples allow calculating some interesting features of the posterior distribution. The performance of the methodology is illustrated via several simulation results.

Keywords: piecewise, moving-average model, reversible jump MCMC, signal segmentation

Procedia PDF Downloads 231

Authors: Se-Han Lee, Kwang-Woo Go, Gwang-Hyun Ahn, Hee-Sung Park, Cheol-Kyu Han, Jun-Bo Shim, Geun-Chul Kang, Hyun-Jung Lee

Abstract:

In recent years, with the advent of smart cars and the expansion of the market, the announcement of 'Adventures in Automotive Networks and Control Units' at the DEFCON21 conference in 2013 revealed that cars are not safe from hacking. As a result, the HEAVENS model considering not only the functional safety of the vehicle but also the security has been suggested. However, the HEAVENS model only presents a simple process, and there are no detailed procedures and activities for each process, making it difficult to apply it to the actual vehicle security vulnerability check. In this paper, we propose an automated attack database that systematically summarizes attack vectors, attack types, and vulnerable vehicle models to prepare for various car hacking attacks, and data flow diagrams that can detect various vulnerabilities and suggest a way to materialize the HEAVENS model.

Keywords: automotive security, HEAVENS, car hacking, security model, information security

Procedia PDF Downloads 369

Authors: Saheed Shittu, Lolwa Alansari, Fahed Nattouf, Tawa Olukade, Naji Abdallah, Tamara Alshdafat, Sarra Amdouni

Abstract:

Cesarean sections (CS), a highly regarded surgical intervention for improving fetal-maternal outcomes and serving as an integral part of emergency obstetric services, are not without complications. Although CS has many advantages, it poses significant risks to both mother and child and increases healthcare expenditures in the long run. The escalating global prevalence of CS, coupled with variations in rates among immigrant populations, has prompted an inquiry into the correlation between CS rates and the nationalities of women undergoing deliveries at Al-Wakra Hospital (AWH), Qatar's second-largest public maternity hospital. This inquiry is motivated by the notable CS rate of 36%, deemed high in comparison to the 34% recorded across other Hamad Medical Corporation (HMC) maternity divisions This is Qatar's first comprehensive investigation of Caesarean section rates and nationalities. A retrospective cross-sectional study was conducted, and data for all births delivered in 2019 were retrieved from the hospital's electronic medical records. The CS rate, the crude rate, and adjusted risks of Caesarean delivery for mothers from each nationality were determined. The common indications for CS were analysed based on nationality. The association between nationality and Caesarean rates was examined using binomial logistic regression analysis considering Qatari women as a standard reference group. The correlation between the CS rate in the country of nationality and the observed CS rate in Qatar was also examined using Pearson's correlation. This study included 4,816 births from 69 different nationalities. CS was performed in 1767 women, equating to 36.5%. The nationalities with the highest CS rates were Egyptian (49.6%), Lebanese (45.5%), Filipino and Indian (both 42.2%). Qatari women recorded a CS rate of 33.4%. The major indication for elective CS was previous multiple CS (39.9%) and one prior CS, where the patient declined vaginal birth after the cesarean (VBAC) option (26.8%). A distinct pattern was noticed: elective CS was predominantly performed on Arab women, whereas emergency CS was common among women of Asian and Sub-Saharan African nationalities. Moreover, a significant correlation was found between the CS rates in Qatar and the women's countries of origin. Also, a high CS rate was linked to instances of previous CS. As a result of these insights, strategic interventions were successfully implemented at the facility to mitigate unwarranted CS, resulting in a notable reduction in CS rate from 36.5% in 2019 to 34% in 2022. This proves the efficacy of the meticulously researched approach. The focus has now shifted to reducing primary CS rates and facilitating well-informed decisions regarding childbirth methods.

Keywords: maternal nationality, caesarean section rate variation, migrants, high-income country

Procedia PDF Downloads 74

Authors: Jian Li

Abstract:

The uncertainty quantification and inversion problems of subsurface oil-water phase flow usually require extensive repeated forward calculations for new runs with changed conditions. To reduce the computational time, various forms of surrogate models have been built. Related research shows that deep learning has emerged as an effective surrogate model, while most surrogate models with deep learning are purely data-driven, which always leads to poor robustness and abnormal results. To guarantee the model more consistent with the physical laws, a coupled theory-guided convolutional neural network (TgCNN) based surrogate model is built to facilitate computation efficiency under the premise of satisfactory accuracy. The model is a convolutional neural network based on multi-well reservoir simulation. The core notion of this proposed method is to bridge two separate blocks on top of an overall network. They underlie the TgCNN model in a coupled form, which reflects the coupling nature of pressure and water saturation in the two-phase flow equation. The model is driven by not only labeled data but also scientific theories, including governing equations, stochastic parameterization, boundary, and initial conditions, well conditions, and expert knowledge. The results show that the TgCNN-based surrogate model exhibits satisfactory accuracy and efficiency in subsurface oil-water phase flow under multi-well conditions.

Keywords: coupled theory-guided convolutional neural network, multi-well conditions, surrogate model, subsurface oil-water phase

Procedia PDF Downloads 89

Authors: B. Gepts, E. Meex, E. Nuyts, E. Knaepen, G. Verbeeck

Abstract:

The importance of resource efficiency and environmental impact assessment has raised the interest in knowing the amount of materials used in buildings. If no BIM model or energy performance certificate is available, material quantities can be obtained through an estimation or time-consuming calculation. For the interior wall area, no validated estimation method exists. However, in the case of environmental impact assessment or evaluating the existing building stock as future material banks, knowledge of the material quantities used in interior walls is indispensable. This paper presents a validated method for the estimation of the interior wall area for dwellings based on easy-to-collect building characteristics. A database of 4963 residential buildings spread all over Belgium is used. The data are collected through onsite measurements of the buildings during the construction phase (between mid-2010 and mid-2017). The interior wall area refers to the area of all interior walls in the building, including the inner leaf of exterior (party) walls, minus the area of windows and doors, unless mentioned otherwise. The two predictive modelling techniques used are 1) a (stepwise) linear regression and 2) a decision tree. The best estimation method is selected based on the best R² k-fold (5) fit. The research shows that the building volume is by far the most important variable to estimate the interior wall area. A stepwise regression based on building volume per building, building typology, and type of house provides the best fit, with R² k-fold (5) = 0.88. Although the best R² k-fold value is obtained when the other parameters ‘building typology’ and ‘type of house’ are included, the contribution of these variables can be seen as statistically significant but practically irrelevant. Thus, if these parameters are not available, a simplified estimation method based on only the volume of the building can also be applied (R² k-fold = 0.87). The robustness and precision of the method (output) are validated three times. Firstly, the prediction of the interior wall area is checked by means of alternative calculations of the building volume and of the interior wall area; thus, other definitions are applied to the same data. Secondly, the output is tested on an extension of the database, so it has the same definitions but on other data. Thirdly, the output is checked on an unrelated database with other definitions and other data. The validation of the estimation methods demonstrates that the methods remain accurate when underlying data are changed. The method can support environmental as well as economic dimensions of impact assessment, as it can be used in early design. As it allows the prediction of the amount of interior wall materials to be produced in the future or that might become available after demolition, the presented estimation method can be part of material flow analyses on input and on output.

Keywords: buildings as material banks, building stock, estimation method, interior wall area

Procedia PDF Downloads 37

Authors: Heriansyah Putra, Erizal Erizal, Sutoyo Sutoyo, Hideaki Yasuhara

Abstract:

This paper discusses the possibility of organic waste material, i.e., soybean, as the bio-catalyst agent on the calcite precipitation method. Several combinations of soybean powder and jack bean extract are used as the bio-catalyst and mixed with the reagent composed of calcium chloride and urea. Its productivity in promoting calcite crystal is evaluated through a transparent test-tube experiment. The morphological and mineralogical aspects of precipitated calcite are also investigated using scanning electromagnetic (SEM) and X-ray diffraction (XRD), respectively. The applicability of this material to improve the engineering properties of soil are examined using the direct shear and unconfined compressive test. The result of this study shows that the utilization of soybean powder brings about a significant effect on soil strength. In addition, the use of soybean powder as a substitution material of urease enzyme also increases the efficacy of calcite crystal as the binder materials. The low calcite content promotes the high strength of the soil. The strength of 300 kPa is obtained in the presence of 2% of calcite content within the soil. The result of this study elucidated that substitution of soybean to jack bean extract is the potential and valuable alternative to improve the applicability of calcite precipitation method as soil improvement technique.

Keywords: calcite precipitation, jack bean, soil improvement, soybean

Procedia PDF Downloads 131

Authors: Majid Hejazian, Nam-Trung Nguyen

Abstract:

Over the past few years, microfluidic devices have generated significant attention from industry and academia due to advantages such as small sample volume, low cost and high efficiency. Microfluidic devices have applications in chemical, biological and industry analysis and can facilitate assay of bio-materials and chemical reactions, separation, and sensing. Micromixers are one of the important microfluidic concepts. Micromixers can work as stand-alone devices or be integrated in a more complex microfluidic system such as a lab on a chip (LOC). Micromixers are categorized as passive and active types. Passive micromixers rely only on the arrangement of the phases to be mixed and contain no moving parts and require no energy. Active micromixers require external fields such as pressure, temperature, electric and acoustic fields. Rapid and efficient mixing is important for many applications such as biological, chemical and biochemical analysis. Achieving fast and homogenous mixing of multiple samples in the microfluidic devices has been studied and discussed in the literature recently. Improvement in mixing rely on effective mass transport in microscale, but are currently limited to molecular diffusion due to the predominant laminar flow in this size scale. Using magnetic field to elevate mass transport is an effective solution for mixing enhancement in microfluidics. The use of a non-uniform magnetic field to improve mass transfer performance in a microfluidic device is demonstrated in this work. The phenomenon of mixing ferrofluid and DI-water streams has been reported before, but mass transfer enhancement for other non-magnetic species through magnetic field have not been studied and evaluated extensively. In the present work, permanent magnets were used in a simple microfluidic device to create a non-uniform magnetic field. Two streams are introduced into the microchannel: one contains fluorescent dye mixed with diluted ferrofluid to induce enhanced mass transport of the dye, and the other one is a non-magnetic DI-water stream. Mass transport enhancement of fluorescent dye is evaluated using fluorescent measurement techniques. The concentration field is measured for different flow rates. Due to effect of magnetic field, a body force is exerted on the paramagnetic stream and expands the ferrofluid stream into non-magnetic DI-water flow. The experimental results demonstrate that without a magnetic field, both magnetic nanoparticles of the ferrofluid and the fluorescent dye solely rely on molecular diffusion to spread. The non-uniform magnetic field, created by the permanent magnets around the microchannel, and diluted ferrofluid can improve mass transport of non-magnetic solutes in a microfluidic device. The susceptibility mismatch between the fluids results in a magnetoconvective secondary flow towards the magnets and subsequently the mass transport of the non-magnetic fluorescent dye. A significant enhancement in mass transport of the fluorescent dye was observed. The platform presented here could be used as a microfluidics-based micromixer for chemical and biological applications.

Keywords: ferrofluid, mass transfer, micromixer, microfluidics, magnetic

Procedia PDF Downloads 228

Authors: J. Ritonja, B. Grcar

Abstract:

For the synchronous generator simulation and analysis and for the power system stabilizer design and synthesis a mathematical model of synchronous generator is needed. The model has to accurately describe dynamics of oscillations, while at the same time has to be transparent enough for an analysis and sufficiently simplified for design of control system. To study the oscillations of the synchronous generator against to the rest of the power system, the model of the synchronous machine connected to an infinite bus through a transmission line having resistance and inductance is needed. In this paper, the linearized reduced order dynamic model of the synchronous generator connected to the infinite bus is presented and analysed in details. This model accurately describes dynamics of the synchronous generator only in a small vicinity of an equilibrium state. With the digression from the selected equilibrium point the accuracy of this model is decreasing considerably. In this paper, the equations’ descriptions and the parameters’ determinations for the linearized reduced order mathematical model of the synchronous generator are explained and summarized and represent the useful origin for works in the areas of synchronous generators’ dynamic behaviour analysis and synchronous generator’s control systems design and synthesis. The main contribution of this paper represents the detailed analysis of the accuracy of the linearized reduced order dynamic model in the entire synchronous generator’s operating range. Borders of the areas where the linearized reduced order mathematical model represents accurate description of the synchronous generator’s dynamics are determined with the systemic numerical analysis. The thorough eigenvalue analysis of the linearized models in the entire operating range is performed. In the paper, the parameters of the linearized reduced order dynamic model of the laboratory salient poles synchronous generator were determined and used for the analysis. The theoretical conclusions were confirmed with the agreement of experimental and simulation results.

Keywords: eigenvalue analysis, mathematical model, power system stability, synchronous generator

Procedia PDF Downloads 248

Authors: Han Bing, Yin Zhenjie

Abstract:

In order to analyze the status of a diesel engine, as well as conduct fault prediction, a new prediction model based on a gray system is proposed in this paper, which takes advantage of the neural network and the genetic algorithm. The proposed GBPGA prediction model builds on the GM (1.5) model and uses a neural network, which is optimized by a genetic algorithm to construct the error compensator. We verify our proposed model on the diesel faulty simulation data and the experimental results show that GBPGA has the potential to employ fault prediction on diesel.

Keywords: fault prediction, neural network, GM(1, 5) genetic algorithm, GBPGA

Procedia PDF Downloads 310

Authors: Sh. Hamada

Abstract:

The current work aims to study the rainbow like-structure observed in the elastic scattering of alpha particles on both ¹²C and ¹⁶O nuclei. We reanalyzed the experimental elastic scattering angular distributions data for α+¹²C and α+¹⁶O nuclear systems at different energies using both optical model and double folding potential of different interaction models such as: CDM3Y1, DDM3Y1, CDM3Y6 and BDM3Y1. Potential created by BDM3Y1 interaction model has the shallowest depth which reflects the necessity to use higher renormalization factor (N_r). Both optical model and double folding potential of different interaction models fairly reproduce the experimental data.

Keywords: density distribution, double folding, elastic scattering, nuclear rainbow, optical model

Procedia PDF Downloads 238

Authors: Junya Kouwa, Shinsuke Matsuno, Chihiro Inoue, Takehiro Himeno, Toshinori Watanabe

Abstract:

Bi-propellant thrusters use impinging jet atomization to atomize liquid fuel and oxidizer. Atomized propellants are mixed and combusted due to auto-ignitions. Therefore, it is important for a prediction of thruster’s performance to simulate the primary atomization phenomenon; especially, the local mixture ratio can be used as indicator of thrust performance, so it is useful to evaluate it from numerical simulations. In this research, we propose a numerical method for considering bi-liquid and the mixture and install it to CIP-LSM which is a two-phase flow simulation solver with level-set and MARS method as an interfacial tracking method and can predict local mixture ratio distribution downstream from an impingement point. A new parameter, beta, which is defined as the volume fraction of one liquid in the mixed liquid within a cell is introduced and the solver calculates the advection of beta, inflow and outflow flux of beta to a cell. By validating this solver, we conducted a simple experiment and the same simulation by using the solver. From the result, the solver can predict the penetrating length of a liquid jet correctly and it is confirmed that the solver can simulate the mixing of liquids. Then we apply this solver to the numerical simulation of impinging jet atomization. From the result, the inclination angle of fan after the impingement in the bi-liquid condition reasonably agrees with the theoretical value. Also, it is seen that the mixture of liquids can be simulated in this result. Furthermore, simulation results clarify that the injecting condition affects the atomization process and local mixture ratio distribution downstream drastically.

Keywords: bi-propellant thrusters, CIP-LSM, free-surface flow simulation, impinging jet atomization

Procedia PDF Downloads 283

Authors: Zakarya Kourdi, Mohammed Khaouani, Benyounes Bouazza, Ahlam Guen-Bouazza, Amine Boursali

Abstract:

In this paper, we have evaluated the thermal effect for high electron mobility transistors (HEMTs) heterostructure InAlN/GaN with a gate length 30nm high-performance. It also shows the analysis and simulated these devices, and how can be used in different application. The simulator Tcad-Silvaco software has used for predictive results good for the DC, AC and RF characteristic, Devices offered max drain current 0.67A; transconductance is 720 mS/mm the unilateral power gain of 180 dB. A cutoff frequency of 385 GHz, and max frequency 810 GHz These results confirm the feasibility of using HEMTs with InAlN/GaN in high power amplifiers, as well as thermal places.

Keywords: HEMT, Thermal Effect, Silvaco, InAlN/GaN

Procedia PDF Downloads 471

Authors: Sun-Jin Han, Deuck Hang Lee, Hyo-Eun Joo, Hyun Kang, Kang Su Kim

Abstract:

In pretensioned concrete members, the transfer length region is existed, in which the stress in prestressing strand is developed due to the bond mechanism with surrounding concrete. The stress of strands in the transfer length zone is smaller than that in the strain plateau zone, so-called effective prestress, therefore the web-shear strength in transfer length region is smaller than that in the strain plateau zone. Although the transfer length is main key factor in the shear design, a few analytical researches have been conducted to investigate the transfer length. Therefore, in this study, a theoretical approach was used to estimate the transfer length. The bond stress developed between the strands and the surrounding concrete was quantitatively calculated by using the Thick-Walled Cylinder Model (TWCM), based on this, the transfer length of strands was calculated. To verify the proposed model, a total of 209 test results were collected from the previous studies. Consequently, the analysis results showed that the main influencing factors on the transfer length are the compressive strength of concrete, the cover thickness of concrete, the diameter of prestressing strand, and the magnitude of initial prestress. In addition, the proposed model predicted the transfer length of collected test specimens with high accuracy. Acknowledgement: This research was supported by a grant(17TBIP-C125047-01) from Technology Business Innovation Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

Keywords: bond, Hoyer effect, prestressed concrete, prestressing strand, transfer length

Procedia PDF Downloads 300

Authors: Beaudoin Marie-Joelle, Poirier Nathalie

Abstract:

Introduction: Children with autism spectrum disorder (ASD) tend to lack socio-emotional skills (e.g., emotional regulation and theory of mind). Eisenberg’s theoretical model on emotion-related socialization behaviors suggests that mothers of children with ASD could play a central role in fostering the acquisition of socio-emotional skills by engaging in frequent educational conversations about emotions. Although, mothers’ perceptions of their own emotional skills and their child’s personality traits and social deficits could mitigate the benefit of their educative role. Objective: Our study aims to explore the association between mother-child conversations about emotions and the socio-emotional skills of their children when accounting for the moderating role of the mothers’ perceptions. Forty-nine mothers completed five questionnaires about emotionally related conversations, self-openness to emotions, and perceptions of personality and socio-emotional skills of their children with ASD. Results: Regression analyses showed that frequent mother-child conversations about emotions predicted better emotional regulation and theory of mind skills in children with ASD (p < 0.01). The children’s theory of mind was moderated by mothers’ perceptions of their own emotional openness (p < 0.05) and their perceptions of their children’s openness to experience (p < 0.01) and conscientiousness (p < 0.05). Conclusion: Mothers likely play an important role in the socio-emotional education of children with ASD. Further, mothers may be most helpful when they perceive that their interventions improve their child’s behaviors. Our findings corroborate those of the Eisenberg model, which claims that mother-child conversations about emotions predict socio-emotional development skills in children with ASD. Our results also help clarify the moderating role of mothers’ perceptions, which could mitigate their willingness to engage in educational conversations about emotions with their children. Therefore, in special needs' children education, school professionals could collaborate with mothers to increase the frequency of emotion-related conversations in ASD's students with emotion dysregulation or theory of mind problems.

Keywords: autism, parental socialization of emotion, emotional regulation, theory of mind

Procedia PDF Downloads 92

Authors: Moataz Medhat, Essam Khalil, Hatem Haridy

Abstract:

The present study investigates the flame structure of turbulent diffusion flame of synthesis fuel in a 300 KW swirl-stabilized burner. The three-dimensional model adopts a realizable k-ε turbulent scheme interacting with two-dimensional PDF combustion scheme by applying flamelet concept. The study reveals more characteristics on turbulent diffusion flame of synthesis fuel when changing the inlet air swirl number and the burner quarl angle. Moreover, it concerns with studying the effect of flue gas recirculation and staging with taking radiation effect into consideration. The comparison with natural gas was investigated. The study showed two zones of recirculation, the primary one is at the center of the furnace, and the location of the secondary one varies by changing the quarl angle of the burner. The results revealed an increase in temperature in the external recirculation zone as a result of increasing the swirl number of the inlet air stream. Also, it was found that recirculating part of the combustion products decreases pollutants formation especially nitrogen monoxide. The predicted results showed a great agreement when compared with the experiments.

Keywords: gas turbine, syngas, analysis, recirculation

Procedia PDF Downloads 274

Authors: Aisha Musaazi Sebunya Nakitto, Anika E. Wagner, Yusuf B. Byaruhanga, John H. Muyonga

Abstract:

The prevalence and burden of diabetes are rapidly increasing globally, stemming from changes in lifestyle and dietary habits. Although several drugs are available to treat type 2 diabetes mellitus (T2DM), many are accompanied by several side effects and are often costly. Solanum anguivi Lam. fruits (SALF) are bitter berries that commonly grow in the wild and are traditionally cultivated by many globally as a remedy for T2DM. This effect is likely attributable to the presence of bioactive compounds such as phenolics, flavonoids, saponins, alkaloids, and vitamin C in SALF. In this study, we investigated the morphological characteristics of different SALF accessions and the effect of ripeness stages and thermal treatments on the bioactive compounds contents (BCC) and antioxidant activity (AA) of SALF accessions. Using the fruit fly Drosophila melanogaster (D. melanogaster) model, we explored the potential impact of dietary SALF in preventing and treating T2DM phenotypes. Morphological characterization was conducted based on descriptors of Solanum species. The BCC and AA of SALF at different ripeness stages (unripe, yellow, orange, and red) and after thermal treatments were determined using spectrophotometry, HPLC, and gravimetry. Male and female fruit flies were fed a high-sugar diet (HSD) to induce a T2DM-like phenotype, while control flies were fed on SY10 medium for up to 24 days. Experimental flies were exposed to HSD supplemented with 5 or 10 mg/ml SALF. The therapeutic and prevention effect of SALF in T2DM-like phenotype was investigated on weight, climbing activity, glucose and triglyceride contents, survival, and gene expression of PPARγ co-activator 1α fly homolog Srl and Drosophila insulin-like peptides. Methods in fly studies included Gustatory assay, Climbing assay, Glucose GOD-PAP assay, Triglyceride GPO-PAP assay, Roti-Quant®, and Real Time-PCR analysis. The ripeness stage significantly influenced SALF BCC and AA, and this was dependent on the accession. The unripe stage had the highest AA and total phenolics and flavonoids; the orange stage was rich in saponins, while the red stage had the highest alkaloid contents. Boiling and steaming increased the total phenolics and AA up to 4-fold and 3-fold, respectively. Drying at low temperatures resulted in higher phenolics and AA than the control. In the therapeutic model, the HSD-fed female flies exhibited elevated glucose levels, which exhibited a dose-dependent reduction upon exposure to a SALF-supplemented diet. Female flies fed on a SALF+ HSD exhibited a significant increase in survival compared to HSD-fed and control diet-fed flies. SALF supplementation did not alter the weights, fitness, and triglyceride levels of female flies in comparison with HSD-only-fed flies. The mRNA levels of Srl decreased in HSD-fed flies compared to the control-fed, with no effect observed in females exposed to HSD+SALF. Similarly, in the preventative model, the SALF diet resulted in higher survival of supplemented flies compared to controls. Consumption of boiled unripe SALF may result in the highest health benefits due to the high phenolic contents and antioxidant activity observed. Dietary intake of SALF significantly lowered glucose levels and increased survival of the D. melanogaster model. Additional studies in higher organisms are needed to explore the preventative and therapeutic potential of SALF in T2DM.

Keywords: antioxidant activity, bioactive compounds, bitter berries, Drosophila melanogaster, Solanum anguivi, type 2 diabetes mellitus, survival

Procedia PDF Downloads 36

Authors: Julian Thrash, Douglas Folk, Michael Ciracy, Audrey C. Tseng, Kristen M. Stromsodt, Amber Younggren, Christopher Maciolek

Abstract:

The cardiopulmonary system is comprised of the heart, lungs, and many dynamic feedback mechanisms that control its function based on a multitude of variables. The next generation of cardiopulmonary medical devices will involve adaptive control and smart pacing techniques. However, testing these smart devices on living systems may be unethical and exceedingly expensive. As a solution, a comprehensive computational model of the cardiopulmonary system was implemented in Simulink. The model contains over 240 state variables and over 100 equations previously described in a series of published articles. Simulink was chosen because of its ease of introducing machine learning elements. Initial results indicate that physiologically correct waveforms of pressures and volumes were obtained in the simulation. With the development of a comprehensive computational model, we hope to pioneer the future of predictive medicine by applying our research towards the initial stages of smart devices. After validation, we will introduce and train reinforcement learning agents using the cardiopulmonary model to assist in adaptive control system design. With our cardiopulmonary model, we will accelerate the design and testing of smart and adaptive medical devices to better serve those with cardiovascular disease.

Keywords: adaptive control, cardiopulmonary, computational model, machine learning, predictive medicine

Procedia PDF Downloads 186

Authors: Güzi̇n Ti̇rkeş, Özge Teki̇n, Kerem Kurtuluş, Y. Yekta Yurtseven, Murat Baran

Abstract:

A scanning electron microscope (SEM) is a type of electron microscope mainly used in nanoscience and nanotechnology areas. Automatic image recognition and classification are among the general areas of application concerning SEM. In line with these usages, the present paper proposes a deep learning algorithm that classifies SEM images into nine categories by means of an online application to simplify the process. The NFFA-EUROPE - 100% SEM data set, containing approximately 21,000 images, was used to train and test the algorithm at 80% and 20%, respectively. Validation was carried out using a separate data set obtained from the Middle East Technical University (METU) in Turkey. To increase the accuracy in the results, the Inception ResNet-V2 model was used in view of the Fine-Tuning approach. By using a confusion matrix, it was observed that the coated-surface category has a negative effect on the accuracy of the results since it contains other categories in the data set, thereby confusing the model when detecting category-specific patterns. For this reason, the coated-surface category was removed from the train data set, hence increasing accuracy by up to 96.5%.

Keywords: convolutional neural networks, deep learning, image classification, scanning electron microscope

Procedia PDF Downloads 130

Authors: F. M. Ali, R. Nazar, N. M. Arifin, I. Pop

Abstract:

In this paper, the problem of unsteady stagnation-point flow and heat transfer induced by a shrinking sheet in the presence of radiation effect is studied. The transformed boundary layer equations are solved numerically by the shooting method. The influence of radiation, unsteadiness and shrinking parameters, and the Prandtl number on the reduced skin friction coefficient and the heat transfer coefficient, as well as the velocity and temperature profiles are presented and discussed in detail. It is found that dual solutions exist and the temperature distribution becomes less significant with radiation parameter.

Keywords: heat transfer, radiation effect, shrinking sheet unsteady flow

Procedia PDF Downloads 386

Authors: Debajyoti Mukherjee, Arathy B. S., Arpita Sahu, Saranga P. Pogula

Abstract:

A Functional Model to mimic the functional correctness of a Neural Network Compute Accelerator IP is very crucial for design validation. Neural network workloads are based on a Brain Floating Point (BF-16) data type. The major challenge we were facing was the incompatibility of gcc compilers to BF-16 datatype, which we addressed with a native BF-16 generator integrated to our functional model. Moreover, working with big GEMM (General Matrix Multiplication) or SpMM (Sparse Matrix Multiplication) Work Loads (Dense or Sparse) and debugging the failures related to data integrity is highly painstaking. In this paper, we are addressing the quality challenge of such a complex Neural Network Accelerator design by proposing a Functional Model-based scoreboard or Software model using SystemC. The proposed Functional Model executes the assembly code based on the ISA of the processor IP, decodes all instructions, and executes as expected to be done by the DUT. The said model would give a lot of visibility and debug capability in the DUT bringing up micro-steps of execution.

Keywords: ISA (instruction set architecture), NN (neural network), TLM (transaction-level modeling), GEMM (general matrix multiplication)

Procedia PDF Downloads 90

Authors: Sebastian Kölbl, Thomas Reitmaier, Mathias Hartmann

Abstract:

Trial and error approaches to adapt wearable support structures to human physiology are time consuming and elaborate. However, during preliminary design, the focus lies on understanding the interaction between exoskeleton and the human body in terms of forces and moments, namely body mechanics. For the study at hand, a multi-body simulation approach has been enhanced to evaluate actual forces and moments in a human dummy model with and without a digital mock-up of an active exoskeleton. Therefore, different motion data have been gathered and processed to perform a musculosceletal analysis. The motion data are ground reaction forces, electromyography data (EMG) and human motion data recorded with a marker-based motion capture system. Based on the experimental data, the response of the human dummy model has been calibrated. Subsequently, the scalable human dummy model, in conjunction with the motion data, is connected with the exoskeleton structure. The results of the human-machine interaction (HMI) simulation platform are in particular resulting contact forces and human joint forces to compare with admissible values with regard to the human physiology. Furthermore, it provides feedback for the sizing of the exoskeleton structure in terms of resulting interface forces (stress justification) and the effect of its compliance. A stepwise approach for the setup and validation of the modeling strategy is presented and the potential for a more time and cost-effective development of wearable support structures is outlined.

Keywords: assistive devices, ergonomic design, inverse dynamics, inverse kinematics, multibody simulation

Procedia PDF Downloads 168

Authors: Vikrant Gupta, Amrit Goswami

Abstract:

The fixed income market forms the basis of the modern financial market. All other assets in financial markets derive their value from the bond market. Owing to its over-the-counter nature, corporate bonds have relatively less data publicly available and thus is researched upon far less compared to Equities. Bond price prediction is a complex financial time series forecasting problem and is considered very crucial in the domain of finance. The bond prices are highly volatile and full of noise which makes it very difficult for traditional statistical time-series models to capture the complexity in series patterns which leads to inefficient forecasts. To overcome the inefficiencies of statistical models, various machine learning techniques were initially used in the literature for more accurate forecasting of time-series. However, simple machine learning methods such as linear regression, support vectors, random forests fail to provide efficient results when tested on highly complex sequences such as stock prices and bond prices. hence to capture these intricate sequence patterns, various deep learning-based methodologies have been discussed in the literature. In this study, a recurrent neural network-based deep learning model using long short term networks for prediction of corporate bond prices has been discussed. Long Short Term networks (LSTM) have been widely used in the literature for various sequence learning tasks in various domains such as machine translation, speech recognition, etc. In recent years, various studies have discussed the effectiveness of LSTMs in forecasting complex time-series sequences and have shown promising results when compared to other methodologies. LSTMs are a special kind of recurrent neural networks which are capable of learning long term dependencies due to its memory function which traditional neural networks fail to capture. In this study, a simple LSTM, Stacked LSTM and a Masked LSTM based model has been discussed with respect to varying input sequences (three days, seven days and 14 days). In order to facilitate faster learning and to gradually decompose the complexity of bond price sequence, an Empirical Mode Decomposition (EMD) has been used, which has resulted in accuracy improvement of the standalone LSTM model. With a variety of Technical Indicators and EMD decomposed time series, Masked LSTM outperformed the other two counterparts in terms of prediction accuracy. To benchmark the proposed model, the results have been compared with traditional time series models (ARIMA), shallow neural networks and above discussed three different LSTM models. In summary, our results show that the use of LSTM models provide more accurate results and should be explored more within the asset management industry.

Keywords: bond prices, long short-term memory, time series forecasting, empirical mode decomposition

Procedia PDF Downloads 140