Search results for: correlated k(CK) model

Authors: Thi Huong Vu, Vijay Jayasena, Zhongxiang Fang, Gary Dykes

Abstract:

Carob kibble has recently received attention due to the presence of high level of polyphenol antioxidants. The capacity of microorganisms to improve antioxidant activities and total phenolics in carob kibble was investigated in the study. Two types of microorganisms including lactic acid bacteria Lactobacillus plantarum (L. plantarum) and yeast Saccharomyces cerevisiae (S. cerevisiae) were used in single and in their combination as starters. The total phenolic content was determined by the Folin–Ciocalteu method. Antioxidant activities were assessed scavenging capacity using 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2′-azinobis-(3-ethylbenzothiazoline-6-sulfonic acid (ABTS). The study found that S. cerevisiae alone considerably improved 55% total phenolics content at 15 h, while L. plantarum caused in a loss of 20% through the process. Antioxidant capacity of the yeast-fermented samples significantly increased by 43 % and 10 % in ABTS and DPPH assays, respectively. However, reduction of 13 % and 32 % inhibition were recorded in the carob treated with L. plantarum. In the combination of S. cerevisiae and L. plantarum (1:1), both total phenolic content and antioxidant activity of carob kibble were a similar trend as these of S. cerevisiae single, but a lower improvement. The antioxidant power of the extracts was linearly correlated to their total phenolic contents (R=0.75). The results suggested that S. cerevisiae alone was the better for enhancement of both total phenolic content and antioxidant activity in carob kibble using submerged fermentation. The efficiency of fermentation reached the highest at 15h. Thus submerged fermentation with S. cerevisiae offers a tool with simple and cost effective to further increase the bioactive potential of carob kibble, which is in use for food, cosmetic and pharmaceutical industries.

Keywords: antioxidant activity, carob kibble, lactobacillus plantarum, saccharomyces cerevisiae, total phenolics

Procedia PDF Downloads 273

Authors: Shahriar Shahbazpanahi, Alaleh Kamgar

Abstract:

So far, the conventional experimental and theoretical analysis in fracture mechanics have been applied to study concrete flexural- cracked beams, which are strengthened using fiber reinforced polymer (FRP) composite sheets. However, there is still little knowledge about the shear capacity of a side face FRP- strengthened shear-cracked beam. A numerical analysis is herein presented to model the fracture mechanics of a four-point RC beam, with two inclined initial notch on the supports, which is strengthened with side face FRP sheets. In the present study, the shear crack is forced to conduct by using an initial notch in supports. The ABAQUS software is used to model crack propagation by conventional cohesive elements. It is observed that the FRP sheets play important roles in preventing the propagation of shear cracks.

Keywords: crack, FRP, shear, strengthening

Procedia PDF Downloads 541

Authors: P. Thachitasing, N. Jansawang, W. Rakrai, T. Santiboon

Abstract:

The aim of this study is to investigate of the comparing the instructional design models between the Think-Pair-Share and Conventional Learning (5E Inquiry Model) Processes to enhance students’ learning achievements and their problem solving skills on stoichiometry issue for concerning the 2-instructional method with a sample consisted of 80 students in 2 classes at the 11th grade level in Chaturaphak Phiman Ratchadaphisek School. Students’ different learning outcomes in chemistry classes with the cluster random sampling technique were used. Instructional Methods designed with the 40-experimenl student group by Think-Pair-Share process and the 40-controlling student group by the conventional learning (5E Inquiry Model) method. These learning different groups were obtained using the 5 instruments; the 5-lesson instructional plans of Think-Pair-Share and STEM Education Method, students’ learning achievements and their problem solving skills were assessed with the pretest and posttest techniques, students’ outcomes of their instructional the Think-Pair-Share (TPSM) and the STEM Education Methods were compared. Statistically significant was differences with the paired t-test and F-test between posttest and pretest technique of the whole students in chemistry classes were found, significantly. Associations between student learning outcomes in chemistry and two methods of their learning to students’ learning achievements and their problem solving skills also were found. The use of two methods for this study is revealed that the students perceive their learning achievements to their problem solving skills to be differently learning achievements in different groups are guiding practical improvements in chemistry classrooms to assist teacher in implementing effective approaches for improving instructional methods. Students’ learning achievements of mean average scores to their controlling group with the Think-Pair-Share Model (TPSM) are lower than experimental student group for the STEM education method, evidence significantly. The E1/E2 process were revealed evidence of 82.56/80.44, and 83.02/81.65 which results based on criteria are higher than of 80/80 standard level with the IOC, consequently. The predictive efficiency (R2) values indicate that 61% and 67% and indicate that 63% and 67% of the variances in chemistry classes to their learning achievements on posttest in chemistry classes of the variances in students’ problem solving skills to their learning achievements to their chemistry classrooms on Stoichiometry issue with the posttest were attributable to their different learning outcomes for the TPSM and STEMe instructional methods.

Keywords: comparisons, students’ learning achievements, think-pare-share model (TPSM), stem education, problem solving skills, chemistry classes, stoichiometry issue

Procedia PDF Downloads 237

Authors: Yekini N. Asafe, Haastrup A. Victor, Lawal N. Olawale, Okikiola F. Mercy

Abstract:

Recent increase in access to personal computer and networking systems have made it feasible to perform much of cumbersome and costly paper-based administration in all organization. Desktop computers, networking systems, high capacity storage devices and telecommunications system is currently allowing the transfer of various format of data to be processed, stored and dissemination for the purpose of decision making. Going paperless is more of benefits compare to full paper-based office. This paper proposed a model for design and implementation of e-administration system (paperless campus) for an institution of learning. If this model is design and implemented it will reduced cost and complexity of educational administration also eliminate menaces and environmental hazards attributed to paper-based administration within schools and colleges.

Keywords: e-administration, educational administration, paperless campus, paper-based administration

Procedia PDF Downloads 358

Authors: Amir Abbas Kamanbedast, Masood Mohammad Shafipor, Amir Ghotboddin

Abstract:

Fish way is a structure that in generally using to migrate to the place where they are spawned and is made near the spillway. Preventing fish spawning or migrating to their original place by fishway structures can affect their lives in the river or even erase one access to intended environment. The main objective of these structures is establishing a safe path for fish migration. In the present study first the hydraulic specifications of Hamidieh diversion dam were assessed and then it is problems were evaluated. In this study the dimensions of the fish way, including velocity of pools, were evaluated by CCHE2D software. Then by change slope in this structure streamlines like velocity in the pools were measured. For calibration can be use measuring local velocities in some pools. The information can be seen the fishway width of 0.3 m has minimum rate of descent in the total number of structures (pools and overflow).

Keywords: fishway, velocity, Hamidieh-Diversion Dam, CCHE2D model

Procedia PDF Downloads 474

Authors: Parastou Kharazmi

Abstract:

Degradation of building materials particularly pipelines causes environmental damage during renovation or replacement and is a time consuming and costly process. Rehabilitation by polymer composites is a solution for renovation of degraded pipeline in heritage buildings and other structures which are less costly, faster and causes less damage to the environment; however, it is still not clear for how long these materials can perform as expected in the field and working condition. To study their service life, two types of composites based on Epoxy and Polyester resins have been evaluated by accelerated exposure and field exposure. The primary degradation agent used in accelerated exposure has been cycling temperature with half of the tests performed in presence of water. Thin films of materials used in accelerated testing were prepared in laboratory by using the same amount of material as well as technique of multi-layers application used in majority of the field installations. Extreme intensity levels of degradation agents have been used only to evaluate materials properties and as also mentioned in ISO 15686, are not directly correlated with degradation mechanisms that would be experienced in service. In the field exposure study, the focus has been to identify possible failure modes, causes, and effects. In field exposure, it has been observed that there are other degradation agents present which can be investigated further such as presence of contaminants and rust before application which prevents formation of a uniform layer of polymer or incompatibility between dissimilar materials. This part of the study also highlighted the importance of application’s quality of the materials in the field for providing the expected performance and service life. Results from extended accelerated exposure and field exposure can help in choosing inspection techniques, establishing the primary degradation agents and can be used for ageing exposure programs with clarifying relationship between different exposure periods and sites.

Keywords: building, renovation, service life, pipelines

Procedia PDF Downloads 180

Authors: Hae-Won Seo, Yong-Gu Lee

Abstract:

Recent progress in the next generation of automobile technology is geared towards incorporating information technology into cars. Collectively called smart cars are bringing intelligence to cars that provides comfort, convenience and safety. A branch of smart cars is connected-car system. The key concept in connected-cars is the sharing of driving information among cars through decentralized manner enabling collective intelligence. This paper proposes a foundation of the information model that is necessary to define the driving information for smart-cars. Road conditions are modeled through a unique data structure that unambiguously represent the time variant traffics in the streets. Additionally, the modeled data structure is exemplified in a navigational scenario and usage using UML. Optimal driving route searching is also discussed using the proposed data structure in a dynamically changing road conditions.

Keywords: connected-car, data modeling, route planning, navigation system

Procedia PDF Downloads 364

Authors: Margarita Zavala, Julio Rolón, Gabriel Chavira, José González, Jorge Orozco, Roberto Pichardo

Abstract:

Adolescence is a neuralgic stage in the formation of every human being, generally at this stage is when the middle school level is studied. In 2006 in Mexico incorporated “mentoring" space to assist students in their integration and participation in life. In public middle schools, is sometimes difficult to be aware of situations that affect students because of the number of them and traditional records management. Whit this they lose the opportunity to provide timely support as a preventive way. In order to provide this support, it is required to know the students by detecting the relevant information that has greater impact on their learning process. This research is looking to check if it is possible to identify student’s relevant information to detect when it is at risk, and then to propose a model to manage in a proper way such information.

Keywords: adolescence, mentoring, middle school students, mentoring system support

Procedia PDF Downloads 402

Authors: Abderrahmen Bouguerra, Kamel Kara, Djamel Saigaa, Samir Zeghlache, Keltoum Loukal

Abstract:

In this paper, a Fault-Tolerant control of 2 DOF Helicopter (TRMS System) Based on Fuzzy Gain-Adaptive PID is presented. In particular, the introduction part of the paper presents a Fault-Tolerant Control (FTC), the first part of this paper presents a description of the mathematical model of TRMS, an adaptive PID controller is proposed for fault-tolerant control of a TRMS helicopter system in the presence of actuator faults, A fuzzy inference scheme is used to tune in real-time the controller gains, The proposed adaptive PID controller is compared with the conventional PID. The obtained results show the effectiveness of the proposed method.

Keywords: fuzzy control, gain-adaptive PID, helicopter model, PID control, TRMS system

Procedia PDF Downloads 463

Authors: Hervice Roméo Fogno Fotsoa, Germaine Djuidje Kenmoe, Claude Vidal Aloyem Kazé

Abstract:

One of the main applications of machine learning is the prediction of time series. But a more accurate prediction requires a more optimal model of machine learning. Several optimization techniques have been developed, but without considering the input variables disposition of the system. Thus, this work aims to present a new machine learning architecture optimization technique based on their optimal input variables disposition. The validations are done on the prediction of wind time series, using data collected in Cameroon. The number of possible dispositions with four input variables is determined, i.e., twenty-four. Each of the dispositions is used to perform the prediction, with the main criteria being the training and prediction performances. The results obtained from a static architecture and a dynamic architecture of neural networks have shown that these performances are a function of the input variable's disposition, and this is in a different way from the architectures. This analysis revealed that it is necessary to take into account the input variable's disposition for the development of a more optimal neural network model. Thus, a new neural network training algorithm is proposed by introducing the search for the optimal input variables disposition in the traditional back-propagation algorithm. The results of the application of this new optimization approach on the two single neural network architectures are compared with the previously obtained results step by step. Moreover, this proposed approach is validated in a collaborative optimization method with a single objective optimization technique, i.e., genetic algorithm back-propagation neural networks. From these comparisons, it is concluded that each proposed model outperforms its traditional model in terms of training and prediction performance of time series. Thus the proposed optimization approach can be useful in improving the accuracy of time series forecasts. This proves that the proposed optimization approach can be useful in improving the accuracy of time series prediction based on machine learning.

Keywords: input variable disposition, machine learning, optimization, performance, time series prediction

Procedia PDF Downloads 88

Authors: Pegah Farokhzad

Abstract:

Family has a crucial role in maintaining the physical, social and mental health of the children. Most of the mental and anxiety problems of children reflects the complex interpersonal situations among family members, especially parents. In other words, anxiety problems of the children is correlated with deficit relationships of family members and improper child rearing styles. The parental child rearing styles leads to positive and negative consequences which affect the children’s mental health. Therefore, the present research was aimed to compare the parental child rearing styles and anxiety of children with stuttering and normal population. It was also aimed to study the relationship between parental child rearing styles and anxiety of children. The research sample included 54 boys with stuttering and 54 normal boys who were selected from the children (boys) of Tehran, Iran in the age range of 5 to 8 years in 2013. In order to collect data, Baumrind Child rearing Styles Inventory and Spence Parental Anxiety Inventory were used. Appropriate descriptive statistical methods and multivariate variance analysis and t test for independent groups were used to test the study hypotheses. Statistical data analyses demonstrated that there was a significant difference between stuttering boys and normal boys in anxiety (t = 7.601, p< 0.01); But there was no significant difference between stuttering boys and normal boys in parental child rearing styles (F = 0.129). There was also not found significant relationship between parental child rearing styles and children anxiety (F = 0.135, p< 0.05). It can be concluded that the influential factors of children’s society are parents, school, teachers, peers and media. So, parental child rearing styles are not the only influential factors on anxiety of children, and other factors including genetic, environment and child experiences are effective in anxiety as well. Details are discussed.

Keywords: child rearing styles, anxiety, stuttering, Iran

Procedia PDF Downloads 482

Authors: Abdulwahab S. Shmailan

Abstract:

The links between the halalan tayyiban dimensions and their impact on the propensity to purchase halal cosmetics in Muslim culture are investigated in this study. The information was gathered by a self-administered questionnaire survey of 207 Saudi Muslim customers using purposive sampling. The suggested model was tested using Pearson correlation coefficients and an ANOVA test. Significant and positive connections were found between halalan tayyiban dimensions, attitudes, and purchasing intent. There were also substantial changes in the study parameters depending on the respondent's work title. This is one of the first empirical tests of the halalan tayyiban, attitudes, and intention to purchase model among Saudi Muslim customers. The study offers helpful recommendations for cosmetics sector marketers as well as strategy formulation.

Keywords: cosmetics, halal cosmetics, halalan tayyiban, halal certificate, customers attitude, intention to purchase

Procedia PDF Downloads 156

Authors: P. Kacejko, M. Wendeker

Abstract:

The fuel consumption of city buses depends on a number of factors that characterize the technical properties of the bus and driver, as well as traffic conditions. This parameter related to greenhouse gas emissions is regulated by law in many countries. This applies to both fuel consumption and exhaust emissions. Simulation studies are a way to reduce the costs of optimization studies. The paper describes simulation research of fuel consumption city bus driving. Parameters of the developed model are based on experimental results obtained on chassis dynamometer test stand and road tests. The object of the study was a city bus equipped with a compression-ignition engine. The verified model was applied to simulate the behavior of a bus during the CUEDC Australian Driving Cycle. The results of the calculations showed a direct influence of driving dynamics on fuel consumption.

Keywords: Australian Driving Cycle, city bus, diesel engine, fuel consumption

Procedia PDF Downloads 105

Authors: Azizah Ismail, Zainab Khalifah, Abbas Mardani

Abstract:

Sustainable community-based tourism through homestay programme is a growing niche market that has impacted destinations in many countries including Malaysia. With demand predicted to continue increasing, the importance of the homestay product will grow in the tourism industry. This research examines the sustainability criteria for homestay programme in Malaysia covering economic, socio-cultural and environmental dimensions. This research applied a two-stage methodology for data analysis. Specifically, the researcher implements a hybrid method which combines two multi-criteria decision making approaches. In the first stage of the methodology, the Decision Making Trial and Evaluation Laboratory (DEMATEL) technique is applied. Then, Analytical Network Process (ANP) is employed for the achievement of the objective of the current research. After factors identification and problem formulation, DEMATEL is used to detect complex relationships and to build a Network Relation Map (NRM). Then ANP is used to prioritize and find the weights of the criteria and sub-criteria of the decision model. The research verifies the framework of multi-criteria for sustainable community-based tourism from the perspective of stakeholders. The result also provides a different perspective on the importance of sustainable criteria from the view of multi-stakeholders. Practically, this research gives the framework model and helps stakeholders to improve and innovate the homestay programme and also promote community-based tourism.

Keywords: community-based tourism, homestay programme, sustainable tourism criteria, sustainable tourism development

Procedia PDF Downloads 117

Authors: Haitham A. Hussein, Rozi Abdullah, Issa Saket, Md. Azlin

Abstract:

The gravitational effect has been extensively applied to separate oil from water in water and wastewater treatment systems. The maximum oil globules removal efficiency is improved by obtaining the best flow uniformity in separator tanks. This study used 2D computational fluid dynamics (CFD) to investigate the effect of different inlet baffle positions inside the separator tank. Laboratory experiment has been conducted, and the measured velocity fields which were by Nortek Acoustic Doppler Velocimeter (ADV) are used to verify the CFD model. Computational investigation results indicated that the construction of an inlet baffle in a suitable location provides the minimum recirculation zone volume, creates the best flow uniformity, and dissipates kinetic energy in the oil and water separator tank. Useful formulas were predicted to design the oil and water separator tanks geometry based on an experimental model.

Keywords: oil/water separator tanks, inlet baffles, CFD, VOF

Procedia PDF Downloads 341

Authors: Zahra Hamedani, Ebrahim Solgi, Henry Skates, Gillian Isoardi

Abstract:

Daylighting plays a pivotal role in promoting productivity and user satisfaction in office spaces. There is an ongoing trend in designing office buildings with a high proportion of glazing which relatively increases the risk of high visual discomfort. Providing a more realistic lighting analysis can be of high value at the early stages of building design when necessary changes can be made at a very low cost. This holistic approach can be achieved by incorporating subjective evaluation and user behaviour in computer simulation and provide a comprehensive lighting analysis. In this research, a detailed computer simulation model has been made using Radiance and Daysim. Afterwards, this model was validated by measurements and user feedback. The case study building is the school of science at Griffith University, Gold Coast, Queensland, which features highly glazed office spaces. In this paper, the visual comfort predicted by the model is compared with a preliminary survey of the building users to evaluate how user behaviour such as desk position, orientation selection, and user movement caused by daylight changes and other visual variations can inform perceptions of visual comfort. This work supports preliminary design analysis of visual comfort incorporating the effects of gaze shift patterns and views with the goal of designing effective layout for office spaces.

Keywords: lighting simulation, office buildings, user behaviour, validation, visual comfort

Procedia PDF Downloads 196

Authors: Pooja Booluck

Abstract:

A U-shaped learning curve entails a three-step process: a good performance followed by a bad performance followed by a good performance again. U-shaped curves have been observed not only in language acquisition but also in various fields such as temperature face recognition object permanence to name a few. Building on previous studies of the curve child language acquisition and Second Language Acquisition this empirical study seeks to investigate the relevance of the U-shaped learning model to the acquisition of the difference between cest and il est in the English Learners of French context. The present study was developed to assess whether older learners of French in the ELF context follow the same acquisition pattern. The empirical study was conducted on 15 English learners of French which lasted six weeks. Compositions and questionnaires were collected from each subject at three time intervals (after one week after three weeks after six weeks) after which students work were graded as being either correct or incorrect. The data indicates that there is evidence of a U-shaped learning curve in the acquisition of cest and il est and students did follow the same acquisition pattern as children in regards to rote-learned terms and subject clitics. This paper also discusses the need to introduce modules on U-shaped learning curve in teaching curriculum as many teachers are unaware of the trajectory learners undertake while acquiring core components in grammar. In addition this study also addresses the need to conduct more research on the acquisition of rote-learned terms and subject clitics in SLA.

Keywords: child language acquisition, rote-learning, subject clitics, u-shaped learning model

Procedia PDF Downloads 282

Authors: X. Li, J. Sundquist, C. Sjöstedt, M. Winkleby, K. S. Kendler, K. Sundquist

Abstract:

Aims: This study examines the association between the incidence of drug abuse (DA) and linking (communal) social capital, a theoretical concept describing the amount of trust between individuals and societal institutions. Methods: We present results from an 8-year population-based cohort study that followed all residents in Sweden, aged 15-44, from 2003 through 2010, for a total of 1,700,896 men and 1,642,798 women. Social capital was conceptualized as the proportion of people in a geographically defined neighborhood who voted in local government elections. Multilevel logistic regression was used to estimate odds ratios (ORs) and between-neighborhood variance. Results: We found robust associations between linking social capital (scored as a three level variable) and DA in men and women. For men, the OR for DA in the crude model was 2.11 [95% confidence interval (CI) 2.02-2.21] for those living in areas with the lowest vs. highest level of social capital. After accounting for neighborhood-level deprivation, the OR fell to 1.59 (1.51-1-68), indicating that neighborhood deprivation lies in the pathway between linking social capital and DA. The ORs remained significant after accounting for age, sex, family income, marital status, country of birth, education level, and region of residence, and after further accounting for comorbidities and family history of comorbidities and family history of DA. For women, the OR decreased from 2.15 (2.03-2.27) in the crude model to 1.31 (1.22-1.40) in the final model, adjusted for multiple neighborhood-level and individual-level variables. Conclusions: Our study suggests that low linking social capital may have important independent effects on DA.

Keywords: drug abuse, social linking capital, environment, family

Procedia PDF Downloads 462

Authors: Faisal Algosair

Abstract:

We examine the role of monetary policy in the presence of commodity price shocks using a Dynamic stochastic general equilibrium (DSGE) model with price and wage rigidities. The model characterizes a commodity exporter by its degree of export diversification, and explores the following monetary regimes: flexible domestic inflation targeting; flexible Consumer Price Index inflation targeting; exchange rate peg; and optimal rule. An increase in the degree of diversification is found to mitigate responses to commodity shocks. The welfare comparison suggests that a flexible exchange rate regime under the optimal rule is preferred to an exchange rate peg. However, monetary policy provides limited stabilization effects in an economy with low degree of export diversification.

Keywords: business cycle, commodity price, exchange rate, global financial cycle

Procedia PDF Downloads 82

Authors: Sara Zadunaisky Ehrlich, Batia Seroussi, Anat Stavans

Abstract:

Text structure is a parameter of text quality. This study investigated the structure of written argumentative texts produced by elementary school age children. We set two objectives: to identify and trace the structural components of the argumentative texts and to investigate whether reading comprehension skills were correlated with text structure. 293 school children from 2nd to 5th grades were asked to write two argumentative texts about informal or everyday life controversial topics and completed two reading tasks that targeted different levels of text comprehension. The findings indicated, on the one hand, significant developmental differences between mature and more novice writers in terms of text length and mean proportion of clauses produced for a better elaboration of the different text components. On the other hand, with certain fluctuations, no meaningful differences were found in terms of presence of text structure: at all grade levels, elementary school children produced the basic and minimal structure that included the writer's argument and reasons or arguments' supports. Counter-arguments were scarce even in the upper grades. While the children captured that essentially an argument must be justified, the more the number of supports produced, the fewer the clauses the children produced. Last, weak to mild relations were found between reading comprehension and argumentative text structure. Nevertheless, children who scored higher on sophisticated questions that require inferential or world knowledge displayed more elaborated structures in terms of text length and size of supports to the writer's argument. These findings indicate how school-age children perceive the basic template of an argument with future implications regarding how to elaborate written arguments.

Keywords: argumentative text, text structure, elementary school children, written argumentations

Procedia PDF Downloads 152

Authors: Beng Yew Low, Cher Liang Cha, Cheng Yong Teoh

Abstract:

Due to a lack of continual assessment or grade related data, identifying first-year engineering students in a polytechnic education at risk of failing is challenging. Our experience over the years tells us that there is no strong correlation between having good entry grades in Mathematics and the Sciences and excelling in hardcore engineering subjects. Hence, identifying students at risk of failure cannot be on the basis of entry grades in Mathematics and the Sciences alone. These factors compound the difficulty of early identification and intervention. This paper describes the development of a predictive analytics model in the early detection of students at risk of failing and evaluates its effectiveness. Data from continual assessments conducted in term one, supplemented by data of student psychological profiles such as interests and study habits, were used. Three classification techniques, namely Logistic Regression, K Nearest Neighbour, and Random Forest, were used in our predictive model. Based on our findings, Random Forest was determined to be the strongest predictor with an Area Under the Curve (AUC) value of 0.994. Correspondingly, the Accuracy, Precision, Recall, and F-Score were also highest among these three classifiers. Using this Random Forest Classification technique, students at risk of failure could be identified at the end of term one. They could then be assigned to a Learning Support Programme at the beginning of term two. This paper gathers the results of our findings. It also proposes further improvements that can be made to the model.

Keywords: continual assessment, predictive analytics, random forest, student psychological profile

Procedia PDF Downloads 119

Authors: Aaditya U. Jhamb

Abstract:

Due to the current energy crisis that many countries are battling, energy-efficient buildings are the subject of extensive research in the modern technological era because of growing worries about energy consumption and its effects on the environment. The paper explores 8 factors that help determine energy efficiency for a building: (relative compactness, surface area, wall area, roof area, overall height, orientation, glazing area, and glazing area distribution), with Tsanas and Xifara providing a dataset. The data set employed 768 different residential building models to anticipate heating and cooling loads with a low mean squared error. By optimizing these characteristics, machine learning algorithms may assess and properly forecast a building's heating and cooling loads, lowering energy usage while increasing the quality of people's lives. As a result, the paper studied the magnitude of the correlation between these input factors and the two output variables using various statistical methods of analysis after determining which input variable was most closely associated with the output loads. The most conclusive model was the Decision Tree Regressor, which had a mean squared error of 0.258, whilst the least definitive model was the Isotonic Regressor, which had a mean squared error of 21.68. This paper also investigated the KNN Regressor and the Linear Regression, which had to mean squared errors of 3.349 and 18.141, respectively. In conclusion, the model, given the 8 input variables, was able to predict the heating and cooling loads of a residential building accurately and precisely.

Keywords: energy efficient buildings, heating load, cooling load, machine learning models

Procedia PDF Downloads 81

Authors: Bitewulign Mekonnen

Abstract:

Context: This scientific paper focuses on the use of near-infrared (NIR) spectroscopy to determine glucose concentration in aqueous solutions accurately and rapidly. The study compares six different machine learning methods for predicting glucose concentration and also explores the development of a deep learning model for classifying NIR spectra. The objective is to optimize the detection model and improve the accuracy of glucose prediction. This research is important because it provides a comprehensive analysis of various machine-learning techniques for estimating aqueous glucose concentrations. Research Aim: The aim of this study is to compare and evaluate different machine-learning methods for predicting glucose concentration from NIR spectra. Additionally, the study aims to develop and assess a deep-learning model for classifying NIR spectra. Methodology: The research methodology involves the use of machine learning and deep learning techniques. Six machine learning regression models, including support vector machine regression, partial least squares regression, extra tree regression, random forest regression, extreme gradient boosting, and principal component analysis-neural network, are employed to predict glucose concentration. The NIR spectra data is randomly divided into train and test sets, and the process is repeated ten times to increase generalization ability. In addition, a convolutional neural network is developed for classifying NIR spectra. Findings: The study reveals that the SVMR, ETR, and PCA-NN models exhibit excellent performance in predicting glucose concentration, with correlation coefficients (R) > 0.99 and determination coefficients (R²)> 0.985. The deep learning model achieves high macro-averaging scores for precision, recall, and F1-measure. These findings demonstrate the effectiveness of machine learning and deep learning methods in optimizing the detection model and improving glucose prediction accuracy. Theoretical Importance: This research contributes to the field by providing a comprehensive analysis of various machine-learning techniques for estimating glucose concentrations from NIR spectra. It also explores the use of deep learning for the classification of indistinguishable NIR spectra. The findings highlight the potential of machine learning and deep learning in enhancing the prediction accuracy of glucose-relevant features. Data Collection and Analysis Procedures: The NIR spectra and corresponding references for glucose concentration are measured in increments of 20 mg/dl. The data is randomly divided into train and test sets, and the models are evaluated using regression analysis and classification metrics. The performance of each model is assessed based on correlation coefficients, determination coefficients, precision, recall, and F1-measure. Question Addressed: The study addresses the question of whether machine learning and deep learning methods can optimize the detection model and improve the accuracy of glucose prediction from NIR spectra. Conclusion: The research demonstrates that machine learning and deep learning methods can effectively predict glucose concentration from NIR spectra. The SVMR, ETR, and PCA-NN models exhibit superior performance, while the deep learning model achieves high classification scores. These findings suggest that machine learning and deep learning techniques can be used to improve the prediction accuracy of glucose-relevant features. Further research is needed to explore their clinical utility in analyzing complex matrices, such as blood glucose levels.

Keywords: machine learning, signal processing, near-infrared spectroscopy, support vector machine, neural network

Procedia PDF Downloads 75

Authors: Omar Dib, Rita Yaacoub, Luc Eveleigh, Nathalie Locquet, Hussein Dib, Ali Bassal, Christophe B. Y. Cordella

Abstract:

The potential of front-face fluorescence coupled with chemometric techniques, namely parallel factor analysis (PARAFAC) and multiple linear regression (MLR) as a rapid analysis tool to characterize Lebanese virgin olive oils was investigated. Fluorescence fingerprints were acquired directly on 102 Lebanese virgin olive oil samples in the range of 280-540 nm in excitation and 280-700 nm in emission. A PARAFAC model with seven components was considered optimal with a residual of 99.64% and core consistency value of 78.65. The model revealed seven main fluorescence profiles in olive oil and was mainly associated with tocopherols, polyphenols, chlorophyllic compounds and oxidation/hydrolysis products. 23 MLR regression models based on PARAFAC scores were generated, the majority of which showed a good correlation coefficient (R > 0.7 for 12 predicted variables), thus satisfactory prediction performances. Acid values, peroxide values, and Delta K had the models with the highest predictions, with R values of 0.89, 0.84 and 0.81 respectively. Among fatty acids, linoleic and oleic acids were also highly predicted with R values of 0.8 and 0.76, respectively. Factors contributing to the model's construction were related to common fluorophores found in olive oil, mainly chlorophyll, polyphenols, and oxidation products. This study demonstrates the interest of front-face fluorescence as a promising tool for quality control of Lebanese virgin olive oils.

Keywords: front-face fluorescence, Lebanese virgin olive oils, multiple Linear regressions, PARAFAC analysis

Procedia PDF Downloads 439

Authors: Ayşe Yurdakul, Eckehard Schnieder

Abstract:

Because of the growing multidisciplinarity and multilinguality, communication problems in different technical fields grows more and more. Therefore, each technical field has its own specific language, terminology which is characterised by the different definition of terms. In addition to definition problems, there are also relation problems between terms. Among these problems of relation, there are the synonymy, antonymy, hypernymy/hyponymy, ambiguity, risk of confusion, and translation problems etc. Thus, the terminology management system iglos of the Institute for Traffic Safety and Automation Engineering of the Technische Universität Braunschweig has the target to solve these problems by a methodological standardisation of term definitions with the aid of the iglos sign model and iglos relation types. The focus of this paper should be on solving definition and relation problems between terms in English navigation terminology.

Keywords: iglos, iglos sign model, methodological resolutions, navigation terminology, common language, technical language, positioning, definition problems, relation problems

Procedia PDF Downloads 317

Authors: Zahra Yazdani Paraii, Zohreh Yazdani Paraei

Abstract:

Many urban designers and planners have been involved in the design of environmentally friendly or nature adaptable urban development models due to increase in urban populations in the recent century, limitation on natural resources, climate change, and lack of enough water and food. Ecological city is one of the latest models proposed to accomplish the latter goal. In this work, the existing establishing indicators of the ecological city are used regarding energy, water, land use and transportation issues. The model is used to compare the function of traditional settlements of Iran. The result of investigation shows that the specifications and functions of the traditional settlements of Iran fit well into the ecological city model. It is found that the inhabitants of the old cities and villages in Iran had founded ecological cities based on their knowledge of the environment and its natural opportunities and limitations.

Keywords: ecological city, traditional city, urban design, environment

Procedia PDF Downloads 234

Authors: Imme Petersen, Wiebke Sick, Regine Kollek

Abstract:

In systems medicine, high-throughput technologies produce large amounts of data on different biological and pathological processes, including (disturbed) gene expressions, metabolic pathways and signaling. The large volume of data of different types, stored in separate databases and often located at different geographical sites have posed new challenges regarding data handling and processing. Tools based on bioinformatics have been developed to resolve the upcoming problems of systematizing, standardizing and integrating the various data. However, the heterogeneity of data gathered at different levels of biological complexity is still a major challenge in data analysis. To build multilayer disease modules, large and heterogeneous data of disease-related information (e.g., genotype, phenotype, environmental factors) are correlated. Therefore, a great deal of attention in systems medicine has been put on data standardization, primarily to retrieve and combine large, heterogeneous datasets into standardized and incorporated forms and structures. However, this data-centred concept of standardization in systems medicine is contrary to the debate in science and technology studies (STS) on standardization that rather emphasizes the dynamics, contexts and negotiations of standard operating procedures. Based on empirical work on research consortia that explore the molecular profile of diseases to establish systems medical approaches in the clinic in Germany, we trace how standardized data are processed and shaped by bioinformatics tools, how scientists using such data in research perceive such standard operating procedures and which consequences for knowledge production (e.g. modeling) arise from it. Hence, different concepts and meanings of standardization are explored to get a deeper insight into standard operating procedures not only in systems medicine, but also beyond.

Keywords: data, science and technology studies (STS), standardization, systems medicine

Procedia PDF Downloads 326

Authors: Abirami Baleswaran, Christel Couderc, Loubnah Belahcen, Jean Dayde, Hélène Tormo, Gwénaëlle Jard

Abstract:

Cheeses are often reported to be spoiled by Pseudomonas spp., responsible for defects in appearance, texture, taste, and smell, leading to their non-marketing and even their destruction. Despite preventive actions, problems linked to Pseudomonas spp. are difficult to control by the lack of knowledge and control of these contaminants during the cheese manufacturing. Lactic goat cheese producers are not spared by this problem and are looking for solutions to decrease the number of spoiled cheeses. To explore different hypotheses, experiments are needed. However, cheese-making experiments at the pilot scale are expensive and time consuming. Thus, there is a real need to develop a miniature cheeses model system under controlled conditions. In a previous study, several miniature cheese models corresponding to different type of commercial cheeses have been developed for different purposes. The models were, for example, used to study the influence of milk, starters cultures, pathogen inhibiting additives, enzymatic reactions, microflora, freezing process on cheese. Nevertheless, no miniature model was described on the lactic goat cheese. The aim of this work was to develop a miniature cheese model system under controlled laboratory conditions which resembles commercial lactic goat cheese to study Pseudomonas spp. spoilage during the manufacturing and ripening process. First, a protocol for the preparation of miniature cheeses (3.5 times smaller than a commercial one) was designed based on the cheese factorymanufacturing process. The process was adapted from “Rocamadour” technology and involves maturation of pasteurized milk, coagulation, removal of whey by centrifugation, moulding, and ripening in a little scale cellar. Microbiological (total bacterial count, yeast, molds) and physicochemical (pH, saltinmoisture, moisture in fat-free)analyses were performed on four key stages of the process (before salting, after salting, 1st day of ripening, and end of ripening). Factory and miniature cheeses volatilomewere also obtained after full scan Sift-MS cheese analysis. Then, Pseudomonas spp. strains isolated from contaminated cheeses were selected on their origin, their ability to produce pigments, and their enzymatic activities (proteolytic, lecithinasic, and lipolytic). Factory and miniature curds were inoculated by spotting selected strains on the cheese surface. The expression of cheese spoilage was evaluated by counting the level of Pseudomonas spp. during the ripening and by visual observation and under UVlamp. The physicochemical and microbiological compositions of miniature cheeses permitted to assess that miniature process resembles factory process. As expected, differences involatilomes were observed, probably due to the fact that miniature cheeses are made usingpasteurized milk to better control the microbiological conditions and also because the little format of cheese induced probably a difference during the ripening even if the humidity and temperature in the cellar were quite similar. The spoilage expression of Pseudomonas spp. was observed in miniature and factory cheeses. It confirms that the proposed model is suitable for the preparation of miniature cheese specimens in the spoilage study of Pseudomonas spp. in lactic cheeses. This kind of model could be deployed for other applications and other type of cheese.

Keywords: cheese, miniature, model, pseudomonas spp, spoilage

Procedia PDF Downloads 123

Authors: V. Keim, J. Spachtholz, J. Hammer

Abstract:

The importance of fibre reinforced plastics continually increases due to the excellent mechanical properties, low material and manufacturing costs combined with significant weight reduction. Today, components are usually designed and calculated numerically by using finite element methods (FEM) to avoid expensive laboratory tests. These programs are based on material models including material specific deformation characteristics. In this research project, material models for short glass fibre reinforced plastics are presented to simulate the visco-elasto-plastic deformation behaviour. Prior to modelling specimens of the material EMS Grivory HTV-5H1, consisting of a Polyphthalamide matrix reinforced by 50wt.-% of short glass fibres, are characterized experimentally in terms of the highly time dependent deformation behaviour of the matrix material. To minimize the experimental effort, the cyclic deformation behaviour under tensile and compressive loading (R = −1) is characterized by isothermal complex low cycle fatigue (CLCF) tests. Combining cycles under two strain amplitudes and strain rates within three orders of magnitude and relaxation intervals into one experiment the visco-elastic deformation is characterized. To identify visco-plastic deformation monotonous tensile tests either displacement controlled or strain controlled (CERT) are compared. All relevant modelling parameters for this complex superposition of simultaneously varying mechanical loadings are quantified by these experiments. Subsequently, two different material models are compared with respect to their accuracy describing the visco-elasto-plastic deformation behaviour. First, based on Chaboche an extended 12 parameter model (EVP-KV2) is used to model cyclic visco-elasto-plasticity at two time scales. The parameters of the model including a total separation of elastic and plastic deformation are obtained by computational optimization using an evolutionary algorithm based on a fitness function called genetic algorithm. Second, the 12 parameter visco-elasto-plastic material model by Launay is used. In detail, the model contains a different type of a flow function based on the definition of the visco-plastic deformation as a part of the overall deformation. The accuracy of the models is verified by corresponding experimental LCF testing.

Keywords: complex low cycle fatigue, material modelling, short glass fibre reinforced polyphthalamides, visco-elasto-plastic deformation

Procedia PDF Downloads 204

Authors: Rajesh Kumar Suman, Ipseeta Ray Mohanty, Manjusha K. Borde, Ujjawala maheswari, Y. A. Deshmukh

Abstract:

Background: Metabolic syndrome encompasses cluster of risk factors for cardiovascular disease which includes abdominal obesity, dyslipidemia, hypertension, and hyperglycemia. The incidence of metabolic syndrome is on the rise globally. Objective: The present study was designed to develop a unique animal model that will mimic the pathological features seen in a large pool of individuals with diabetes and metabolic syndrome; suitable for pharmacological screening of drugs beneficial in this condition. Material and Methods: A combination of high fat diet (HFD) and low dose of streptozotocin (STZ) at 30, 35 and 40 mg/kg was used to induce metabolic syndrome co-existing with diabetes mellitus in Wistar rats. Results: The 40 mg/kg STZ produced sustained hyperglycemia and the dose was thus selected for our study to induce diabetes mellitus. Rat fed HFD (HF-DC) group showed significant (p < 0.001) increase in body weight on 4th and 7th week as compared with NC (Normal Control) group rats. However, the increase in body weight of HF-DC group rats was not sustained at the end of 10th weeks. Various components of metabolic syndrome such as dyslipidemia {(Increased Triglyceride, total Cholesterol, LDL Cholesterol and decreased HDL Cholesterol)}, diabetes mellitus (Blood Glucose, HbA1c, Serum Insulin, C-peptide), hypertension {Systolic Blood pressure (p < 0.001)} were mimicked in the developed model of metabolic syndrome co existing with diabetes mellitus. In addition significant cardiac injury as indicated by CPK-MB levels, artherogenic index, hs-CRP. The decline in hepatic function {(p < 0.01) increase in the level of SGPT (U/L)} and renal function {(increase in creatinine levels (p < 0.01)} when compared to NC group rats. The histopathological assessment confirmed presence of edema, necrosis and inflammation in Heart, Pancreas, Liver and Kidney of HFD-DC group as compared to NC. Conclusion: The present study has developed a unique rodent model of metabolic syndrome; with diabetes as an essential component.

Keywords: diabetes, metabolic syndrome, high fat diet, streptozotocin, rats

Procedia PDF Downloads 334