Search results for: meso scale parameters

Authors: A. U. Adamu, Hamisu Abdu, A. A. Saidu

Abstract:

The enzymatic synthesis of 3-O-β-D-glucopyranoside-betulinic acid using Novozyme-435 as a catalyst was studied. The effect of various parameters such as substrate molar ratio, reaction temperature, reaction time, re-used enzymes and amount of enzymes were investigated. The optimum rection conditions for the enzymatic glycosidation of betulinic acid in an organic solvent using Novozym-435 was found to be at 1:1.2 substrate molar ratio, 55oC, 24 h and 180 mg of enzymes with percentage conversion of 88.69 %.

Keywords: betulinic acid, glycosidation, novozyme-435, optimization

Procedia PDF Downloads 426

Authors: L. Hamra, J. F. Demonceau, V. Denoël

Abstract:

The aim of this paper is to study a beam extracted from a frame and subjected to blast loading. The demand of ductility depends on six dimensionless parameters: two related to the blast loading, two referring to the bending behavior of the beam and two corresponding to the dynamic behavior of the rest of the structure. We develop a full analytical procedure that provides the ductility demand as a function of these six dimensionless parameters.

Keywords: analytical procedure, blast loading, membrane force, P-I diagram

Procedia PDF Downloads 427

Authors: Alireza Pishgahi, Mohammad Rahbar, Javad Shokri, Shahla Dareshiri, Yaghoub Salekzamani, Fariba Eslamian

Abstract:

Background and Objectives: Hypertrophic scars are one of the complications following a burn injury. Intralesional corticosteroid injection is an invasive method for treatment of this complication. We had design a single blinded randomized control trial to deliver dexamethasone by phonophoresis and evaluate its efficacy on hypertrophic burn scars characteristics. Material and Methods: 56 cases of hypertrophic burn scar due to burn injury allocated randomly to dexamethasone and control group. Individuals in case group received 10 sessions of dexamethasone 0.4% phonophoresis. Patients in control group had placebo phonophoresis (ultrasound with normal routine aquatic gel without any dexamethasone) with the same protocol. At the beginning of study and one week after last session, hypertrophic scar characteristics and pruritus were measured by ‘Vancouver Scar Scale’, and ‘5-D Pruritus Scale’ respectively in both groups. Results: Despite mild improvement in Vancouver Scar Scale score one week after intervention in dexamethasone phonophoresis group in comparison to control subjects, but this difference was not significant (p=0.08). Pruritus score perceived subjectively were significantly lower one week after intervention in dexamethasone groups in comparison to control subjects (p=0.00). Conclusion: Dexamethasone phonophoresis is a safe and effective treatment method for burn hypertrophic scar pruritus, but its efficacy for scar characteristics improvement needs to be evaluated by larger studies with long-term follow-up period.

Keywords: dexamethasone, hypertrophic scar, phonophoresis, pruritus

Procedia PDF Downloads 173

Authors: Arzu K. Harmanci Seren, Burcu Alacam, Serap Altuntas, Ulku Baykal

Abstract:

Organizational justice has been evaluated as a concept related to rules developed with regards to distributing gains and making decisions of distribution such as duty, goods, service, reward, punishment, fee, organizational position, opportunity or role among those working in that organization, and to social norms on which these rules are based. Studies of organizational justice are crucial for analyzing the organizational life. It is considered that organization justice will be positively influential upon organizational behaviours such as employees’ level of work satisfaction, their performance, and behaviours of organization citizenship, management by values perception, tendency towards cooperation, and towards quitting their jobs. However, when the literature related to health and nurse management is examined, authors could not reach enough findings related to the influence of nurses’ perception of organizational justice upon the perception of management and the intention of quitting in accordance with the values. For that reason, this study has been carried out with the purpose of determining the influence of nurses’ perception of organizational justice upon the perception of management and the intention of quitting in accordance with the values. The study has been carried out with 176 nurses working in a university hospital in Istanbul and a private hospital who accepted to take part in the study, and it is definitive and relation-seeking. Before the data has been collected, ethics committee approval and institutional permissions have been taken, Organizational Justice Scale, Management by Values, Intention to Leave Scale with a questionnaire including 8 questions that aims at defining the personal and professional characteristics of the nurses have been used as a means of data collection. The data collected between 1 May and 20 June 2016 have been evaluated by the researchers in a computer via definitive, relation-seeking and psychometric statistic. As a result of the study, it has been determined that most of the nurses are working in a university hospital (70.5%), that they are 30 and over (49.4%), women (91.5%), single (52.8%) and have a Bachelor’s Degree (48.3%), working in a surgery unit (17.6), have 5 year or less institutional experience (44.9%), 11 year or more professional experience. Cronbach alpha values of the scales used in this study are .94, .95 and .56. Nurses’ average scores of Organizational Justice Scale is M= 3.35±.96, Management by Values Scale is M=3.30±.74, Intention to Leave Scale is M=8.36±3.14. As a result of the analysis carried out in order to determine the influence of nurses’ perception of organizational justice upon the perception of management and the intention of quitting in accordance with the values, it has been pointed out that the Perception of Organizational Justice influenced the perception of Management by Values positively, Intention to Leave negatively.

Keywords: intention to leave, management by values, nursing, organizational justice

Procedia PDF Downloads 267

Authors: Flordeliza L. Mercado, Teresito G. Aguinaldo, Helen F. Gavino, Victorino T. Taylan

Abstract:

Most fruits and vegetables are available in large quantities during peak season which are oftentimes marketed at low price and left to rot or fed to farm animals. The lack of efficient storage facilities, and the additional cost and unavailability of small machinery for food processing, results to low price and wastage. Incidentally, processed fresh fruits and vegetables are gaining importance nowadays and health conscious people are also into ‘juicing’. One way to reduce wastage and ensure an all-season availability of crop juices at reasonable costs is to develop equipment for effective extraction of juice. The study was conducted to design, fabricate and evaluate a multi-juice extractor using locally available materials, making it relatively cheaper and affordable for medium-scale enterprises. The study was also conducted to formulate juice blends using extracted juices and calamansi juice at different blending percentage, and evaluate its chemical properties and sensory attributes. Furthermore, the chemical properties of extracted meals were evaluated for future applications. The multi-juice extractor has an overall dimension of 963mm x 300mm x 995mm, a gross weight of 82kg and 5 major components namely; feeding hopper, extracting chamber, juice and meal outlet, transmission assembly, and frame. The machine performance was evaluated based on juice recovery, extraction efficiency, extraction rate, extraction recovery, and extraction loss considering type of crop as apple and carrot with three replications each and was analyzed using T-test. The formulated juice blends were subjected to sensory evaluation and data gathered were analyzed using Analysis of Variance appropriate for Complete Randomized Design. Results showed that the machine’s juice recovery (73.39%), extraction rate (16.40li/hr), and extraction efficiency (88.11%) for apple were significantly higher than for carrot while extraction recovery (99.88%) was higher for apple than for carrot. Extraction loss (0.12%) was lower for apple than for carrot, but was not significantly affected by crop. Based on adding percentage mark-up on extraction cost (Php 2.75/kg), the breakeven weight and payback period for a 35% mark-up is 4,710.69kg and 1.22 years, respectively and for a 50% mark-up, the breakeven weight is 3,492.41kg and the payback period is 0.86 year (10.32 months). Results on the sensory evaluation of juice blends showed that the type of juice significantly influenced all the sensory parameters while the blending percentage including their respective interaction, had no significant effect on all sensory parameters, making the apple-calamansi juice blend more preferred than the carrot-calamansi juice blend in terms of all the sensory parameter. The machine’s performance is higher for apple than for carrot and the cost analysis on the use of the machine revealed that it is financially viable with a payback period of 1.22 years (35% mark-up) and 0.86 year (50% mark-up) for machine cost, generating an income of Php 23,961.60 and Php 34,444.80 per year using 35% and 50% mark-up, respectively. The juice blends were of good qualities based on the values obtained in the chemical analysis and the extracted meal could also be used to produce another product based on the values obtained from proximate analysis.

Keywords: food processing, fruits and vegetables, juice extraction, multi-juice extractor

Procedia PDF Downloads 324

Authors: S. P. Singh, Priya, Komal Sajwan

Abstract:

With the increasing spread of organic farming in India, costs, returns, efficiency, and social and environmental sustainability of organic vis-a-vis conventional farming systems have become topics of interest among agriculture scientists, economists, and policy analysts. A study on technical efficiency estimation under these farming systems, particularly in the Ganga River Basin, where the promotion of organic farming is incentivized, can help to understand whether the inputs are utilized to their maximum possible level and what measures can be taken to improve the efficiency. This paper, therefore, analyses the technical efficiency of wheat farms operating under organic and conventional farming systems. The study is based on a primary survey of 600 farms (300 organic ad 300 conventional) conducted in 2021 in two districts located in the Middle Ganga River Basin, India. Technical, managerial, and scale efficiencies of individual farms are estimated by applying the data envelopment analysis (DEA) methodology. The per hectare value of wheat production is taken as an output variable, and values of seeds, human labour, machine cost, plant nutrients, farm yard manure (FYM), plant protection, and irrigation charges are considered input variables for estimating the farm-level efficiencies. The post-DEA analysis is conducted using the Tobit regression model to know the efficiency determining factors. The results show that technical efficiency is significantly higher in conventional than organic farming systems due to a higher gap in scale efficiency than managerial efficiency. Further, 9.8% conventional and only 1.0% organic farms are found operating at the most productive scale size (MPSS), and 99% organic and 81% conventional farms at IRS. Organic farms perform well in managerial efficiency, but their technical efficiency is lower than conventional farms, mainly due to their relatively lower scale size. The paper suggests that technical efficiency in organic wheat can be increased by upscaling the farm size by incentivizing group/collective farming in clusters.

Keywords: organic, conventional, technical efficiency, determinants, DEA, Tobit regression

Procedia PDF Downloads 99

Authors: Ananya Das, Arun Kumar, Gazala Habib, Vivekanandan Perumal

Abstract:

Regulatory bodies has proposed limits on Particulate Matter (PM) concentration in air; however, it does not explicitly indicate the incorporation of effects of toxicities of constituents of PM in developing regulatory limits. This study aimed to provide a structured approach to incorporate toxic effects of components in developing regulatory limits on PM. A four-step human health risk assessment framework consists of - (1) hazard identification (parameters: PM and its constituents and their associated toxic effects on health), (2) exposure assessment (parameters: concentrations of PM and constituents, information on size and shape of PM; fate and transport of PM and constituents in respiratory system), (3) dose-response assessment (parameters: reference dose or target toxicity dose of PM and its constituents), and (4) risk estimation (metric: hazard quotient and/or lifetime incremental risk of cancer as applicable). Then parameters required at every step were obtained from literature. Using this information, an attempt has been made to determine limits on PM using component-specific information. An example calculation was conducted for exposures of PM_2.5 and its metal constituents from Indian ambient environment to determine limit on PM values. Identified data gaps were: (1) concentrations of PM and its constituents and their relationship with sampling regions, (2) relationship of toxicity of PM with its components.

Keywords: air, component-specific toxicity, human health risks, particulate matter

Procedia PDF Downloads 311

Authors: Ayodeji Motunrayo Omoare

Abstract:

Economically fish provides an important source of food and income for both men and women especially many households in the developing world and fishing has an important social and cultural position in river-rine communities. However, fish is highly susceptible to deterioration. Consequently, this study was carried out to correlate income generation of small-scale women fish processors in Abeokuta metropolis, Ogun State, Nigeria. Eighty small-scale women fish processors were randomly selected from five communities as the sample size for this study. Collected data were analyzed using both descriptive and inferential statistics. The results showed that the mean age of the respondents was 31.75 years with average household size of 4 people while 47.5% of the respondents had primary education. Most (86.3%) of the respondents were married and had spent more than 11 years in fish processing. The respondents were predominantly Yoruba tribe (91.2%). Majority (71.3%) of the respondents used traditional kiln for processing their fish while 23.7% of the respondents used hot vegetable oil to fry their fish. Also, the result revealed that respondents sourced capital from Personal Savings (48.8%), Cooperatives (27.5%), Friends and Family (17.5%) and Microfinance Banks (6.2%) for fish processing activities. The respondents generated an average income of ₦7,000.00 from roasted fish, ₦3,500.00 from dried fish, and ₦5,200.00 from fried fish daily. However, inadequate processing equipment (95.0%), non-availability of credit facility from microfinance banks (85.0%), poor electricity supply (77.5%), inadequate extension service support (70.0%), and fuel scarcity (68.7%) were major constraints to fish processing in the study area. Results of chi-square analysis showed that there was a significant relationship between personal characteristics (χ2 = 36.83, df = 9), processing methods (χ2 = 15.88, df = 3) and income generated at p < 0.05 level of significance. It can be concluded that significant relationship existed between processing methods and income generated. The study, therefore, recommends that modern processing equipment should be made available to the respondents at a subsidized price by the agro-allied companies.

Keywords: correlates, income, fish processors, women, small-scale

Procedia PDF Downloads 245

Authors: Gee-Cheol Kim, Joo-Won Kang

Abstract:

Structural characteristics of spatial structure are different from that of rahmen structures and it has many factors that are unpredictable experientially. Both horizontal and vertical earthquake should be considered because of seismic behaviour characteristics of spatial structures. This experimental study is conducted about seismic response characteristics of roof structure according to the effect of columns or walls, through scale model of arch structure that has the basic dynamic characteristics of spatial structure. Though remarkable response is not occurred for horizontal direction in the region of higher frequency than the region of frequency that seismic energy is concentrated, relatively large response is occurred in vertical direction. It is proved that seismic response of arch structure with column is varied according to property of column.

Keywords: arch structure, seismic response, shaking table, spatial structure

Procedia PDF Downloads 367

Authors: Jawairia Umar, Tanveer Hussain, Zulfiqar Ali, Muhammad Maqsood

Abstract:

Different knitted structures and knitted parameters play a vital role in the stretch and recovery management of compression sportswear in addition to the materials use to generate this stretch and recovery behavior of the fabric. The present work was planned to predict the different performance indicators of a compression sportswear fabric with some ground parameters i.e. base yarn stitch length (polyester as base yarn and spandex as plating yarn involve to make a compression fabric) and linear density of the spandex which is a key material of any sportswear fabric. The prediction models were generated by response surface method for performance indicators such as stretch & recovery percentage, compression generated by the garment on body, total elongation on application of high power force and load generated on certain percentage extension in fabric. Certain physical properties of the fabric were also modeled using these two parameters.

Keywords: Compression, sportswear, stretch and recovery, statistical model, kikuhime

Procedia PDF Downloads 379

Authors: Al-Tammar M. Shahah

Abstract:

Background and Objective: A novel pneumonia caused by coronavirus disease 2019 (COVID-19), which is spreading domestically and internationally, has been identified by the Chinese city of Wuhan since the end of December 2019. Limited studies examined the psychological experience such as anxiety, depression, and stress during Corona pandemic. Moreover, to the best of author's knowledge, there is no study to date has examined the psychological resilience and mental health during Corona pandemic in Kuwait. Therefore, the present research investigates the role of psychological resilience in predicting psychological distress among Kuwaiti adults during Corona pandemic. Method: Kuwaiti citizens (N = 735) completed an online survey, which includes four scales the Hospital Anxiety and Depression Scale HADS (anxiety and depression), the Connor-Davidson Resilience Scale (CD-RISC-25), and the Perceived Stress Scale (PSS). A cross-sectional correlational design was used. Results: A high level of stress was observed, with 59% reported moderate to severe stress. In contrast, low levels of anxiety and depression were observed; with 70% reporting no anxiety symptoms and 74% report no depression symptoms. Psychological resilience was negatively correlated with anxiety, depression, and stress, consistent with previous studies. As expected, resilience was found to account for significant variance in anxiety and stress after controlling for quarantine variables and demographic variables. Conclusion: The findings suggest that increasing psychological resilience might help reduce psychological distress after confronting with stressful live events in Kuwaiti citizen.

Keywords: anxiety, corona, depression, psychological resilience, stress

Procedia PDF Downloads 123

Authors: Tolulope Aremu

Abstract:

This paper is based on the idea of using deep learning methodology for optimizing production yield by tuning a few key process parameters in a manufacturing environment. The study was explicitly on how to maximize production yield and minimize operational costs by utilizing advanced neural network models, specifically Long Short-Term Memory and Convolutional Neural Networks. These models were implemented using Python-based frameworks—TensorFlow and Keras. The targets of the research are the precision molding processes in which temperature ranges between 150°C and 220°C, the pressure ranges between 5 and 15 bar, and the material flow rate ranges between 10 and 50 kg/h, which are critical parameters that have a great effect on yield. A dataset of 1 million production cycles has been considered for five continuous years, where detailed logs are present showing the exact setting of parameters and yield output. The LSTM model would model time-dependent trends in production data, while CNN analyzed the spatial correlations between parameters. Models are designed in a supervised learning manner. For the model's loss, an MSE loss function is used, optimized through the Adam optimizer. After running a total of 100 training epochs, 95% accuracy was achieved by the models recommending optimal parameter configurations. Results indicated that with the use of RSM and DOE traditional methods, there was an increase in production yield of 12%. Besides, the error margin was reduced by 8%, hence consistent quality products from the deep learning models. The monetary value was annually around $2.5 million, the cost saved from material waste, energy consumption, and equipment wear resulting from the implementation of optimized process parameters. This system was deployed in an industrial production environment with the help of a hybrid cloud system: Microsoft Azure, for data storage, and the training and deployment of their models were performed on Google Cloud AI. The functionality of real-time monitoring of the process and automatic tuning of parameters depends on cloud infrastructure. To put it into perspective, deep learning models, especially those employing LSTM and CNN, optimize the production yield by fine-tuning process parameters. Future research will consider reinforcement learning with a view to achieving further enhancement of system autonomy and scalability across various manufacturing sectors.

Keywords: production yield optimization, deep learning, tuning of process parameters, LSTM, CNN, precision manufacturing, TensorFlow, Keras, cloud infrastructure, cost saving

Procedia PDF Downloads 29

Authors: Seema Paul, John Mango Magero, Prosun Bhattacharya, Zahra Kalantari, Steve W. Lyon

Abstract:

The purpose of this review paper is to develop an understanding of lake hydrodynamics and the potential climate impact on the Lake Victoria (LV) catchment scale. This paper briefly discusses the main problems of lake hydrodynamics and its’ solutions that are related to quality assessment and climate effect. An empirical methodology in modeling and mapping have considered for understanding lake hydrodynamic and visualizing the long-term observational daily, monthly, and yearly mean dataset results by using geographical information system (GIS) and Comsol techniques. Data were obtained for the whole lake and five different meteorological stations, and several geoprocessing tools with spatial analysis are considered to produce results. The linear regression analyses were developed to build climate scenarios and a linear trend on lake rainfall data for a long period. A potential evapotranspiration rate has been described by the MODIS and the Thornthwaite method. The rainfall effect on lake water level observed by Partial Differential Equations (PDE), and water quality has manifested by a few nutrients parameters. The study revealed monthly and yearly rainfall varies with monthly and yearly maximum and minimum temperatures, and the rainfall is high during cool years and the temperature is high associated with below and average rainfall patterns. Rising temperatures are likely to accelerate evapotranspiration rates and more evapotranspiration is likely to lead to more rainfall, drought is more correlated with temperature and cloud is more correlated with rainfall. There is a trend in lake rainfall and long-time rainfall on the lake water surface has affected the lake level. The onshore and offshore have been concentrated by initial literature nutrients data. The study recommended that further studies should consider fully lake bathymetry development with flow analysis and its’ water balance, hydro-meteorological processes, solute transport, wind hydrodynamics, pollution and eutrophication these are crucial for lake water quality, climate impact assessment, and water sustainability.

Keywords: climograph, climate scenarios, evapotranspiration, linear trend flow, rainfall event on LV, concentration

Procedia PDF Downloads 99

Authors: Jasvinder Singh, Manjinder Singh

Abstract:

Welding of dissimilar materials is a complicated process due to the difference in melting point of two materials. Thermal conductivity and coefficient of thermal expansion of dissimilar materials also different; therefore, residual stresses produced in the weldment and base metal are the most critical problem associated with the joining of dissimilar materials. Tensile strength and impact toughness also reduced due to the residual stresses. In the present research work, an attempt has been made to weld SS304 and MS1018 dissimilar materials by submerged arc welding (SAW). By conducting trail, runs most effective parameters welding current, Arc voltage, welding speed and nozzle to plate distance were selected to weld these materials. The fractional factorial technique was used to optimize the welding parameters. Effect on tensile strength (TS), fracture toughness (FT) and microhardness of weldment were studied. It was concluded that by optimizing welding current, voltage and welding speed the properties of weldment can be enhanced.

Keywords: SAW, Tensile Strength (TS), fracture toughness, micro hardness

Procedia PDF Downloads 538

Authors: Pamir Gogoi, Ratree Wayland

Abstract:

This study investigates the acoustic measures of breathiness when coarticulated with nasality. The acoustic correlates of breathiness and nasality that has already been well established after years of empirical research. Some of these acoustic parameters - like low frequency peaks and wider bandwidths- are common for both nasal and breathy voice. Therefore, it is likely that these parameters interact when a sound is coarticulated with breathiness and nasality. This leads to the hypothesis that the acoustic parameters, which usually act as robust cues in differentiating between breathy and modal voice, might not be reliable cues for differentiating between breathy and modal voice when breathiness is coarticulated with nasality. The effect of nasality on the perception of breathiness has been explored in earlier studies using synthesized speech. The results showed that perceptually, nasality and breathiness do interact. The current study investigates if a similar pattern is observed in natural speech. The study is conducted on Marathi, an Indo-Aryan language which has a three-way contrast between nasality and breathiness. That is, there is a phonemic distinction between nasals, breathy voice and breathy-nasals. Voice quality parameters like – H1-H2 (Difference between the amplitude of first and second harmonic), H1-A3 (Difference between the amplitude of first harmonic and third formant, CPP (Cepstral Peak Prominence), HNR (Harmonics to Noise ratio) and B1 (Bandwidth of first formant) were extracted. Statistical models like linear mixed effects regression and Random Forest classifiers show that measures that capture the noise component in the signal- like CPP and HNR- can classify breathy voice from modal voice better than spectral measures when breathy voice is coarticulated with nasality.

Keywords: breathiness, marathi, nasality, voice quality

Procedia PDF Downloads 95

Authors: Gabriel I. Loaiza Ossa, Carlos A. Cadavid Moreno, Juan C. Arango Parra

Abstract:

It is known that the Riemannian manifold determined by the family of inverse Gaussian distributions endowed with the Fisher metric has negative constant curvature κ= -1/2, as does the family of usual Gaussian distributions. In the present paper, firstly, we arrive at this result by following a different path, much simpler than the previous ones. We first put the family in exponential form, thus endowing the family with a new set of parameters, or coordinates, θ₁, θ₂; then we determine the matrix of the Fisher metric in terms of these parameters; and finally we compute this matrix in the original parameters. Secondly, we define the inverse q-Gaussian distribution family (q < 3) as the family obtained by replacing the usual exponential function with the Tsallis q-exponential function in the expression for the inverse Gaussian distribution and observe that it supports two possible geometries, the Fisher and the q-Fisher geometry. And finally, we apply our strategy to obtain results about the Fisher and q-Fisher geometry of the inverse q-Gaussian distribution family, similar to the ones obtained in the case of the inverse Gaussian distribution family.

Keywords: base of changes, information geometry, inverse Gaussian distribution, inverse q-Gaussian distribution, statistical manifolds

Procedia PDF Downloads 244

Authors: Yael Fisher

Abstract:

Little is known about perceived self-efficacy of public preschool teachers, their perception of preschool excellence, or the relations between the two. There were three purposes for this research: defining the professional self-efficacy of preschool teachers (PTSE); defining preschool teachers' perception of preschool excellence (PTPPE); and investigating the relationship between the two. Scales for PTSE and PTPPE were developed especially for this study. Public preschool teachers (N = 202) participated during the 2013 school year. Structural Equation Modeling was performed to test the fit between the research model and the obtained data. PTPSE scale (α = 0.91) was comprised of three subscales: pedagogy (α=0.84), organization (α = 0.85) and staff (α = 0.72). The PTPPE scale (α = 0.92) is also composed of three subscales: organization and pedagogy (α = 0.88), staff (α = 0.84) and parents (α = 0.83). The goodness of fit measures were RMSEA = 0.045, CFI = 0.97, NFI = 0.89, df = 173, χ²=242.94, p= .000, showing GFI = 1.4 (< 3) as a good fit. Understanding self-efficacy of preschool teachers, preschool could and should lead to better professional development (in-service training) of preschool teachers.

Keywords: self-efficacy, public pre schools, preschool excellence, SEM

Procedia PDF Downloads 130

Authors: Ahmed Saeed, Sadok Sassi, Mohammad Roshun

Abstract:

Gears are important components with a vital role in many rotating machines. One of the common gear failure causes is tooth fatigue crack; however, its early detection is still a challenging task. The objective of this study is to develop a numerical model that simulates the effect of teeth cracks on the resulting gears vibrations and permits consequently to perform an early fault detection. In contrast to other published papers, this work incorporates the possibility of multiple simultaneous cracks with different depths. As cracks alter significantly the stiffness of the tooth, finite element software is used to determine the stiffness variation with respect to the angular position, for different combinations of crack orientation and depth. A simplified six degrees of freedom nonlinear lumped parameter model of a one-stage spur gear system is proposed to study the vibration with and without cracks. The model developed for calculating the stiffness with the crack permitted to update the physical parameters of the second-degree-of-freedom equations of motions describing the vibration of the gearbox. The vibration simulation results of the gearbox were by obtained using Simulink/Matlab. The effect of one crack with different levels was studied thoroughly. The change in the mesh stiffness and the vibration response were found to be consistent with previously published works. In addition, various statistical time domain parameters were considered. They showed different degrees of sensitivity toward the crack depth. Multiple cracks were also introduced at different locations and the vibration response along with the statistical parameters were obtained again for a general case of degradation (increase in crack depth, crack number and crack locations). It was found that although some parameters increase in value as the deterioration level increases, they show almost no change or even decrease when the number of cracks increases. Therefore, the use of any statistical parameters could be misleading if not considered in an appropriate way.

Keywords: Spur gear, cracked tooth, numerical simulation, time-domain parameters

Procedia PDF Downloads 266

Authors: Sonda Jallouli, Omar Hammouda, Imen Ben Dhia, Salma Sakka, Chokri Mhiri, Mohamed Habib Elleuch, Abedlmoneem Yahia, Sameh Ghroubi

Abstract:

Multiple sclerosis (MS) is characterized by gender differences with affecting women two to four times more than men, but the disease progression is faster and more severe in men. Fatigue represents one of the most frequent and disabling symptoms related to MS. Results of previous studies regarding gender differences in fatigue perception in MS persons are contradictory. Besides, fatigue has been shown to affect negatively postural balance and functional mobility in MS persons. However, no study has taken into account gender differences in the response of these physical parameters to a fatiguing protocol in MS persons. Given the reduction of autonomy due to the alteration of these parameters induced by fatigue and the importance of gender differences in postural balance training programs in fatigued men and women with MS, the aim of this study was to investigate the effect of gender difference on unipedal postural balance and functional mobility after performing a fatiguing task in MS adults. Methods: Eleven women (30.29 ± 7.99 years) and seven men (30.91 ± 8.19 years) with relapsing-remitting MS performed a fatiguing protocol: three sets of the 5×sit to stand test (5-STST), six-minute walk test (6MWT) followed by three sets of the 5-STST. Unipedal balance, functional mobility, and fatigue perception were measured prefatigue (T0) and post fatigue (T3) using a clinical unipedal balance test, timed up and go test (TUGT), and analogic visual scale of fatigue (VASF), respectively. Heart rate (HR) and rate of perceived exertion (RPE) were recorded before, during and after the fatiguing task. Results: Compared to women, men showed an impairment of unipedal balance on the dominant leg (p<0.001, d=0.52) and mobility (p<0.001, d=3) via reducing unipedal stance time and increasing duration of TUGT execution, respectively. No gender differences were observed in 6MWT, 5-STST, HR, RPE and VASF scores. Conclusion: Fatiguing protocol negatively affected unipedal postural balance and mobility only in men. These gender differences were inconclusive but can be taken into account in postural balance rehabilitation programs for persons with MS.

Keywords: functional mobility, fatiguing exercises, multiple sclerosis, sex differences, unipedal balance

Procedia PDF Downloads 138

Authors: Fatemeh Sadat Miri, Morteza Ehsani, Seyed Farshid Hosseini

Abstract:

The present research is concerned with the optimization of extrusion parameters of ABS sheets by the Taguchi experimental design method. In this design method, three parameters of % recycling ABS, processing temperature and degassing time on mechanical properties, hardness, HDT, and color matching of ABS sheets were investigated. The variations of this research are the dosage of recycling ABS, processing temperature, and degassing time. According to experimental test data, the highest level of tensile strength and HDT belongs to the sample with 5% recycling ABS, processing temperature of 230°C, and degassing time of 3 hours. Additionally, the minimum level of MFI and color matching belongs to this sample, too. The present results are in good agreement with the Taguchi method. Based on the outcomes of the Taguchi design method, degassing time has the most effect on the mechanical properties of ABS sheets.

Keywords: ABS, process optimization, Taguchi, mechanical properties

Procedia PDF Downloads 73

Authors: Abu Afree Andalib, Rafiur Rahman, Md Mezbah Uddin

Abstract:

The main objective of this work is to anatomize on the various parameters of AGM 88 missile anatomized using FSI module in Ansys. Computational fluid dynamics is used for the study of fluid flow pattern and fluidic phenomenon such as drag, pressure force, energy dissipation and shockwave distribution in water. Using finite element analysis module of Ansys, structural parameters such as stress and stress density, localization point, deflection, force propagation is determined. Separate analysis on structural parameters is done on Abacus. State of the art coupling module is used for FSI analysis. Fine mesh is considered in every case for better result during simulation according to computational machine power. The result of the above-mentioned parameters is analyzed and compared for two phases using graphical representation. The result of Ansys and Abaqus are also showed. Computational Fluid Dynamics and Finite Element analyses and subsequently the Fluid-Structure Interaction (FSI) technique is being considered. Finite volume method and finite element method are being considered for modelling fluid flow and structural parameters analysis. Feasible boundary conditions are also utilized in the research. Significant change in the interaction and interference pattern while the impact was found. Theoretically as well as according to simulation angled condition was found with higher impact.

Keywords: FSI (Fluid Surface Interaction), impact, missile, high viscous fluid, CFD (Computational Fluid Dynamics), FEM (Finite Element Analysis), FVM (Finite Volume Method), fluid flow, fluid pattern, structural analysis, AGM-88, Ansys, Abaqus, meshing, k-omega, turbulence model

Procedia PDF Downloads 467

Authors: Siqing Guan, Fumiyo Oshima, Eiji Shimizu, Nozomi Tomita, Toru Takahashi, Hiroaki Kumano

Abstract:

Risk factors for social anxiety in autism spectrum conditions involve executive attention, emotion regulation, and thought regulation as processes of cognitive dysregulation. Social camouflaging behaviors as strategies used to mask and/or compensate for autism characteristics during social interactions in autism spectrum conditions have also been emphasized. However, the role of cognitive dysregulation and social camouflaging related to social anxiety in autism spectrum conditions has not been clarified. Whether these factors are specific to social anxiety in autism spectrum conditions or common to social anxiety independent of autism spectrum conditions needs to be clarified. Here, we explored risk factors specific to social anxiety in autism spectrum conditions and general risk factors for social anxiety independent of autism spectrum conditions. From the Japanese participants in early adulthood (age=18~39) of the online survey in Japan, those who exceeded the Japanese version Autism-Spectrum Quotient cutoff (33 points or more )were divided into the autism spectrum conditions group (ASC; N=255, mean age=32.08, SD age=5.16)and those who did not exceed the cutoff were divided into the non-autism spectrum conditions group (Non-ASC; N=255, mean age=31.70, SD age=5.09). Using the Japanese versions of the Social Phobia Scale, the Social Interaction Anxiety Scale, and the Short Fear of Negative Evaluation Scale, a composite score for social anxiety was calculated using a method of principal. We also measured emotional control difficulties using the Difficulties in Emotion Regulation Scale, executive attention using the Effortful Control Scale for Adults, rumination using the Rumination-Reflection Questionnaire, and worry using the Penn State Worry Questionnaire. This study was passed through the review of the Ethics Committee. No conflicts of interest. Multiple regression analysis with forced entry method was used to predict social anxiety in the ASC and non-ASC groups separately, based on executive attention, emotion dysregulation, worry, rumination, and social camouflage. In the ASC group, emotion dysregulation (β=.277, p<.001), worry (β=.162, p<.05), assimilation (β=.308, p<.001) and masking (β=.275, p<.001) were significant predictors of social anxiety (F (7,247) = 45.791, p <.001, R2=.565). In the non-ASC groups,emotion dysregulation (β=.171, p<.05), worry (β=.344，p <.001), assimilation (β=.366,p <.001) and executive attention (β=-.132,p <.05) were significant predictors of social anxiety (F (7,207) =47.333, p <.001, R2=.615).The findings suggest that masking was shown to be a risk factor for social anxiety specific to autism spectrum conditions, while emotion dysregulation, worry, and assimilation were shown to be common risk factors for social anxiety, regardless of autism spectrum conditions. In addition, executive attention is a risk factor for social anxiety without autism spectrum conditions.

Keywords: autism spectrum, cognitive control, social anxiety, social camouflaging

Procedia PDF Downloads 208

Authors: Angga Pratama Herman, Muhammad Shahbaz, Suzana Yusup

Abstract:

Bottom ash is a solid waste from thermal power plant and it is usually disposed of into landfills and ash ponds. These disposal methods are not sustainable since new lands need to be acquired as the landfills and ash ponds are fill to its capacity. Bottom ash also classified as hazardous material that makes the disposal methods may have contributed to the environmental effect to the area. Hence, more research needs to be done to explore the potential of recycling the bottom ash as more useful product. The objective of this research is to explore the potential of utilizing bottom ash as catalyst in biomass steam gasification. In this research, bottom ash was used as catalyst in gasification of Palm Kernel Shell (PKS) using Thermo Gravimetric Analyzer coupled with mass spectrometry (TGA/MS). The effects of temperature (650 – 750 °C), particle size (0.5 – 1.0 mm) and bottom ash percentage (2 % - 10 %) were studied with and without steam. The experimental arrays were designed using expert method of Central Composite Design (CCD). Results show maximum yield of hydrogen gas was 34.3 mole % for gasification without steam and 61.4 Mole % with steam. Similar trend was observed for syngas production. The maximum syngas yield was 59.5 mole % for without steam and it reached up to 81.5 mole% with the use of steam. The optimal condition for both product gases was temperature 700 °C, particle size 0.75 mm and cool bottom ash % 0.06. In conclusion, the use of bottom ash as catalyst is possible for biomass steam gasification and the product gases composition are comparable with previous researches, however the results need to be validated for bench or pilot scale study.

Keywords: bottom ash, biomass steam gasification, catalyst, lab scale

Procedia PDF Downloads 298

Authors: Eser Yarar, Fahri Vatansever, A. Tamer Erturk, Sedat Karabay

Abstract:

In this study, drilling behavior of multi-layer orthotropic polyester composites reinforced with woven polyester fiber and PTFE particle was investigated. Conventional drilling methods have low cost and ease of use. Therefore, it is one of the most preferred machining methods. The increasing range of use of composite materials in many areas has led to the investigation of the machinability performance of these materials. The drilling capability of the synthetic polymer composite material was investigated by measuring the cutting forces using different tool diameters, feed rate and high cutting speed parameters. Cutting forces were measured using a dynamometer in the experiments. In order to evaluate the results of the experiment, the Taguchi experimental design method was used. According to the results, the optimum cutting parameters were obtained for 0.1 mm/rev, 1070 rpm and 2 mm diameter drill bit. Verification tests were performed for the optimum cutting parameters obtained according to the model. Verification experiments showed the success of the established model.

Keywords: cutting force, drilling, polimer composite, Taguchi

Procedia PDF Downloads 162

Authors: Sohaibullah Zarghoon, Syed Yousaf, Cyril Belavy, Stanislav Duris, Samuel Emebu, Radek Matusu

Abstract:

Induction heating is extensively employed in industrial furnaces due to its swift response and high energy efficiency. Designing and optimising these furnaces necessitates the use of computer-aided simulations. This study aims to develop an accurate temperature field model for a rectangular steel billet in an induction furnace by leveraging various parameters in COMSOL Multiphysics software. The simulation analysis incorporated temperature dynamics, considering skin depth, temperature-dependent, and constant parameters of the steel billet. The resulting data-driven model was transformed into a state-space model using MATLAB's System Identification Toolbox for the purpose of designing a linear quadratic regulator (LQR). This controller was successfully implemented to regulate the core temperature of the billet from 1000°C to 1200°C, utilizing the distributed parameter system circuit.

Keywords: induction heating, LQR controller, skin depth, temperature field

Procedia PDF Downloads 41

Authors: B. Touati, A. Saad, B. Lips, A. Abdenbi, M. Mokhtari.

Abstract:

The purpose of this study is an application of experiment design method for dimensioning of a solar drying system. NIMROD software was used to build up the matrix of experiments and to analyze the results. The software has the advantages of being easy to use and consists of a forced way, with some choices about the number and range of variation of the parameters, and the desired polynomial shape. The first design of experiments performed concern the drying with constant input characteristics of the hot air in the dryer and a second design of experiments in which the drying chamber is coupled with a solar collector. The first design of experiments allows us to study the influence of various parameters and get the studied answers in a polynomial form. The correspondence between the polynomial thus determined, and the model results were good. The results of the polynomials of the second design of experiments and those of the model are worse than the results in the case of drying with constant input conditions. This is due to the strong link between all the input parameters, especially, the surface of the sensor and the drying chamber, and the mass of the product.

Keywords: solar drying, experiment design method, NIMROD, mint leaves

Procedia PDF Downloads 503

Authors: Mehdi Moayyedian, Kazem Abhary, Romeo Marian

Abstract:

This paper presents an evaluation of a plastic defect in injection molding before it occurs in the process; it is known as the short shot defect. The evaluation of different parameters which affect the possibility of short shot defect is the aim of this paper. The analysis of short shot possibility is conducted via SolidWorks Plastics and Taguchi method to determine the most significant parameters. Finite Element Method (FEM) is employed to analyze two circular flat polypropylene plates of 1 mm thickness. Filling time, part cooling time, pressure holding time, melt temperature and gate type are chosen as process and geometric parameters, respectively. A methodology is presented herein to predict the possibility of the short-shot occurrence. The analysis determined melt temperature is the most influential parameter affecting the possibility of short shot defect with a contribution of 74.25%, and filling time with a contribution of 22%, followed by gate type with a contribution of 3.69%. It was also determined the optimum level of each parameter leading to a reduction in the possibility of short shot are gate type at level 1, filling time at level 3 and melt temperature at level 3. Finally, the most significant parameters affecting the possibility of short shot were determined to be melt temperature, filling time, and gate type.

Keywords: injection molding, plastic defects, short shot, Taguchi method

Procedia PDF Downloads 218

Authors: Ghofrane Rehaiem, Hamza Gharsellaoui, Samir Benahmed

Abstract:

In this study, Artificial Neural Networks (ANNs) were used for modeling the parameters that allow the real-time scheduling of embedded systems under resources constraints designed for real-time applications running. The objective of this work is to implement a neural networks based approach for real-time scheduling of embedded systems in order to handle real-time constraints in execution scenarios. In our proposed approach, many techniques have been proposed for both the planning of tasks and reducing energy consumption. In fact, a combination of Dynamic Voltage Scaling (DVS) and time feedback can be used to scale the frequency dynamically adjusting the operating voltage. Indeed, we present in this paper a hybrid contribution that handles the real-time scheduling of embedded systems, low power consumption depending on the combination of DVS and Neural Feedback Scheduling (NFS) with the energy Priority Earlier Deadline First (PEDF) algorithm. Experimental results illustrate the efficiency of our original proposed approach.

Keywords: optimization, neural networks, real-time scheduling, low-power consumption

Procedia PDF Downloads 371

Authors: Ziyun Li, Jiudi Zhong, June Zhang

Abstract:

Background: The diagnosis and treatment of lung cancer lead to varying degrees of psychological and social maladjustment among patients with lung cancer. Understanding psychosocial adjustment (PA) and its influencing factors in young and middle-aged lung cancer patients is essential to help them return to society and lead a normal life. Objectives: This study aims to examine the mediating role of resilience in the association between stigma and psychosocial adjustment among young and middle-aged patients with lung cancer. Methods: A total of 235 patients with lung cancer were recruited from a tertiary grade A cancer center in southern China and investigated using a self-designed general information questionnaire, Psychosocial Adjustment to Illness Scale Self-Report, Social Impact Scale, and Conner-Davidson Resilience Scale. Results: The mean score of PA was (32.61±14.75), and its influencing factors included treatment modalities, stigma, and resilience. The total effect of stigma on PA was significant (total effect=0.418, SE=0.045, 95%CI [0.310-0.497]), and a positive indirect effect was identified for stigma on PA via resilience (indirect effect=0.143, SE=0.041, 95% CI [0.075-0.236]). Conclusion: Stigma and resilience are significantly associated with PA, and resilience is also a mediating variable between stigma and PA. This study suggests that individualized interventions can be made to improve the PA by alleviating their stigma, or by enhancing their resilience in young and middle-aged lung cancer patients.

Keywords: psychosocial adjustment, lung cancer, cancer caring, nursing, young and middle-aged

Procedia PDF Downloads 92

Authors: Bechir Hbibi, Lamine Mili

Abstract:

Understanding the condition of comatose patients can be difficult, but it is crucial to their optimal treatment. Consequently, numerous scoring systems have been developed around the world to categorize patient states based on physiological assessments. Although validated and widely adopted by medical communities, these scores still present numerous limitations and obstacles. Even with the addition of additional tests and extensions, these scoring systems have not been able to overcome certain limitations, and it appears unlikely that they will be able to do so in the future. On the other hand, physiological tests are not the only way to extract ideas about comatose patients. EEG signal analysis has helped extensively to understand the human brain and human consciousness and has been used by researchers in the classification of different levels of disease. The use of EEG in the ICU has become an urgent matter in several cases and has been recommended by medical organizations. In this field, the EEG is used to investigate epilepsy, dementia, brain injuries, and many other neurological disorders. It has recently also been used to detect pain activity in some regions of the brain, for the detection of stress levels, and to evaluate sleep quality. In our recent findings, our aim was to use multifractal analysis, a very successful method of handling multifractal signals and feature extraction, to establish a state of awareness scale for comatose patients based on their electrical brain activity. The results show that this score could be instantaneous and could overcome many limitations with which the physiological scales stock. On the contrary, multifractal analysis stands out as a highly effective tool for characterizing non-stationary and self-similar signals. It demonstrates strong performance in extracting the properties of fractal and multifractal data, including signals and images. As such, we leverage this method, along with other features derived from EEG signal recordings from comatose patients, to develop a scale. This scale aims to accurately depict the vigilance state of patients in intensive care units and to address many of the limitations inherent in physiological scales such as the Glasgow Coma Scale (GCS) and the FOUR score. The results of applying version V0 of this approach to 30 patients with known GCS showed that the EEG-based score similarly describes the states of vigilance but distinguishes between the states of 8 sedated patients where the GCS could not be applied. Therefore, our approach could show promising results with patients with disabilities, injected with painkillers, and other categories where physiological scores could not be applied.

Keywords: coma, vigilance state, EEG, multifractal analysis, feature extraction

Procedia PDF Downloads 67