Search results for: road traffic model

Authors: Samiya Siddique, Taslima Akter Elma, Shahrina Mahzabin, Tamanna Jerin, Mohammed Russedul Islam

Abstract:

In the maneuver and designing of highway engineering, pavement performance is a principal concern. Quality of construction and materials, traffic volume, climate, etc. are the factors that affect the performance of asphalt concrete. Modified asphalt requires to attain greater strength and stability even at inimical circumstances. In this point of view, pyrolytic carbon black (PCB), which is a by-product of waste tire pyrolysis, holds incomparable properties that individualizes it from other conventional fillers by making it an imminent modifier of bitumen. Optimum asphalt content of 60/70 penetration grade asphalt is determined 5% through the Marshall Stability and Flow test for the wearing course of flexible pavement. 5, 10, and 15 percentages of PCB are then used with neat asphalt for modification. Deviations of physical and rheological properties are investigated on both PCB modified and neat asphalt by going through several laboratory tests such as penetration, softening point, and ductility tests. The obtained results reveal that the performance of paving asphalt can be upgraded by modifying it with PCB. With the increasing percentage of PCB, ductility is gradually decreased, and also penetration grade is gradually reduced from 60/70 to 30/40. Furthermore, asphalt mixtures modified with PCB demonstrate higher stability and lower flow values. The research discloses that the apposite percentage of PCB used in asphalt concrete plays a significant role in the advancement of pavement performances and reutilizing of waste tires.

Keywords: asphalt modification, pavement performances, pyrolytic carbon black, marshall stability, wearing course

Procedia PDF Downloads 145

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 547

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 245

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 370

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 483

Authors: Bekhemmas Youcef

Abstract:

The category of the disabled, like other social groups, is considered to have been affected by fate with a disability that led to a reduction in the fulfillment of its social roles to the fullest extent or led to its complete abandonment. Psychological, and until we understand its behavioral methods that express a lot of this complexity and intertwining, and despite all that, this category has not yet received the appropriate great interest from specialized researchers, and even officials, and it is natural that the category of people with disabilities has psychological and social requirements in order to regains their capabilities or some From her, it also needs to prepare the environment in which she lives in order to integrate into society As the motor disability is one of the most common types of disability in the world, and it is constantly increasing, considering the increase in the causes leading to it, such as the traffic accident, and the motor disability often affects individuals from a psychological point of view, but it also affects their social surroundings, whether close or extended, and thus it draws limits and quality For their way of life, as well as determining roles for them as actors of a special kind within their societies. The methodology is similar to the organizational framework for the production of any scientific knowledge and based on the fact that sociology is a project that aims to understand and interpret the social reality scientifically and through the nature of the subject studied in the framework of the reality of the disabled in the city and in order to get closer to the daily life of the physically disabled within the urban center, we adopted the qualitative approach A choice that complies with the spirit of Viberian sociology, especially since Max Weber insists on the need to search for the meaning that the social actor gives to his behavior. Through the results reached in this study, it was found that the city still suffers from several deficiencies at the level of equipment and urban planning in a way that keeps pace with the number of people with disabilities in the city.

Keywords: physically, handicapped, in, the city

Procedia PDF Downloads 66

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 414

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 474

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 102

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 171

Authors: Max Sardou, Patricia Sardou

Abstract:

Now that weight saving is mandatory, to author best knowledge composite springs, that we have invented, are best choice for automotive suspensions, against steel. So, we have created a Joint Ventures called S.ARA, in order to mass produce composite coils springs. Start of Production of composite coils springs was in 2014 for AUDI. As we have demonstrated, on the road, that composite springs are not a sweet dream. The present paper describes all the benefits of ‘C’ springs and ‘S’ springs for high performance vehicles suspension, for rocket stage separation, and for satellite injection into orbit. Developing rocket stage separation, we have developed for CNES (Centre National d’Etudes Spatiales) the following concept. If we call ‘line of action’ a line going from one end of a spring to the other. Our concept is to use for instance two springs inclined. In such a way that their line of action cross together and create at this crossing point a virtual center well above the springs. This virtual center, is pulling from above the top stage and is offering a guidance, perfectly stable and straight. About buildings, our solution is to transfer this rocket technology, creating a ‘virtual center’ of pendulation positioned above the building center of gravity. This is achieved by using tilted composite springs benches oriented in such a way that their line of action converges creating the ‘virtual center’. Thanks to the ‘virtual center’ position, the building behaves as a pendulum, hanged from above. When earthquake happen then the building will oscillate around its ‘virtual center’ and will go back safely to equilibrium after the tremor. ‘C’ springs, offering anti-rust, anti-settlement, fail-safe suspension, plus virtual center solution is the must for long-lasting, perfect protection of buildings against earthquakes.

Keywords: virtual center of tilt, composite springs, fail safe springs, antiseismic suspention

Procedia PDF Downloads 242

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 127

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 359

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 204

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 290

Authors: Jigg L. Pelayo, Ricardo G. Villar, Einstine M. Opiso

Abstract:

The advances of aerial laser scanning in the Philippines has open-up entire fields of research in remote sensing and machine vision aspire to provide accurate timely information for the government and the public. Rapid mapping of polygonal roads and roof boundaries is one of its utilization offering application to disaster risk reduction, mitigation and development. The study uses low density LiDAR data and high resolution aerial imagery through object-oriented approach considering the theoretical concept of data analysis subjected to machine learning algorithm in minimizing the constraints of feature extraction. Since separating one class from another in distinct regions of a multi-dimensional feature-space, non-trivial computing for fitting distribution were implemented to formulate the learned ideal hyperplane. Generating customized hybrid feature which were then used in improving the classifier findings. Supplemental algorithms for filtering and reshaping object features are develop in the rule set for enhancing the final product. Several advantages in terms of simplicity, applicability, and process transferability is noticeable in the methodology. The algorithm was tested in the different random locations of Misamis Oriental province in the Philippines demonstrating robust performance in the overall accuracy with greater than 89% and potential to semi-automation. The extracted results will become a vital requirement for decision makers, urban planners and even the commercial sector in various assessment processes.

Keywords: feature extraction, machine learning, OBIA, remote sensing

Procedia PDF Downloads 357

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 468

Authors: Ahmad Idris, Armaya`u Suleiman Labo, Ado Yusuf Abdulfatah, Murtala Umar

Abstract:

Super pave is the short form of Superior Performing Asphalt Pavement and represents a basis for specifying component materials, asphalt mixture design and analysis, and pavement performance prediction. This new technology is the result of long research projects conducted by the strategic Highway Research program (SHRP) of the Federal Highway Administration. This research was aimed at examining the suitability of Aggregates found in Kano for used in super pave design method. Aggregates samples were collected from different sources in Kano Nigeria and their Engineering properties, as they relate to the SUPERPAVE design requirements were determined. The average result of Coarse Aggregate Angularity in Kano was found to be 87% and 86% of one fractured face and two or more fractured faces respectively with a standard of 80% and 85% respectively. Fine Aggregate Angularity average result was found to be 47% with a requirement of 45% minimum. A flat and elongated particle which was found to be 10% has a maximum criterion of 10%. Sand equivalent was found to be 51% with the criteria of 45% minimum. Strength tests were also carried out, and the results reflect the requirements of the standards. The tests include Impact value test, Aggregate crushing value and Aggregate Abrasion tests and the results are 27.5%, 26.7% and 13% respectively with a maximum criteria of 30%. Specific gravity was also carried out and the result was found to have an average value of 2.52 with a criterion of 2.6 to 2.9 and Water absorption was found to be 1.41% with maximum criteria of 0.6%. From the study, the result of the tests indicated that the aggregates properties have met the requirements of Super pave design method based on the specifications of ASTMD 5821, ASTM D 4791, AASHTO T176, AASHTO T33 and BS815.

Keywords: aggregates, construction, road design, super pave

Procedia PDF Downloads 236

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 91

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 128

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 90

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 87

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 450

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 246

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 130

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 211

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 343

Authors: Tingyu Zhang

Abstract:

The cross-basin ecological compensation mechanism is key to stimulating active participation in ecological protection across the entire basin. This study constructs an evolutionary game model of cross-basin ecological compensation in the Yangtze River Economic Belt (YREB), introducing a central government constraint and incentive mechanism (CGCIM) to explore the conditions for achieving strategies of protection and compensation that meet societal expectations. Furthermore, using a water quality-water quantity model combined with factual data from the YREB in 2020, the amount of ecological compensation is calculated. The results indicate that the stability of the evolutionary game model of the upstream and downstream governments in the YREB is closely related to the CGCIM. When the sum of the central government's reward amount to the upstream government and the penalty amount to both sides simultaneously is greater than 39.948 billion yuan, and the sum of the reward amount to the downstream government and the penalty amount to only the lower reaches is greater than 1.567 billion yuan, or when the sum of the reward amount to the downstream government and the penalty amount to both sides simultaneously is greater than 1.567 billion yuan, and the sum of the reward amount to the upstream government and the penalty amount to only the upstream government is greater than 399.48 billion yuan, the protection and compensation become the only evolutionarily stable strategy for the evolutionary game system composed of the upstream and downstream governments in the YREB. At this point, the total ecological compensation that the downstream government of the YREB should pay to the upstream government is 1.567 billion yuan, with Hunan paying 0.03 billion yuan, Hubei 2.53 billion yuan, Jiangxi 0.18 billion yuan, Anhui 1.68 billion yuan, Zhejiang 0.75 billion yuan, Jiangsu 6.57 billion yuan, and Shanghai 3.93 billion yuan. The research results can provide a reference for promoting the improvement and perfection of the cross-basin ecological compensation system in the YREB.

Keywords: ecological compensation, evolutionary game model, central government constraint and incentive mechanism, Yangtze river economic belt

Procedia PDF Downloads 59

Authors: James Alberto Ortega Morales, Nelson Andrés Martínez Marín

Abstract:

The bulding industry is one of the most important sectors all around the world in terms of contribution to index like GDP and labor. On the other hand, it is a major contributor to Greenhouse Gases (GHG) and waste generation contributing to global warming. In this sense, it is necessary to establish sustainable practices both from the strategic point of view to the operations point of view as well in all business and industries. Business models don’t scape to this reality attending it´s mediator role between strategy and operations. Business models can turn from the traditional practices searching economic benefits to sustainable bussines models that generate both economic value and value for society and the environment. Recent advances in the analysis of sustainable business models find different classifications that allow finding potential triple bottom line (economic, social and environmental) solutions applicable in every business sector. Into the metioned Advances have been identified, 11 groups and 45 patterns of sustainable business models have been identified; such patterns can be found either in the business models as a whole or found concurrently in their components. This article presents the analysis of a case study, seeking to identify the components and elements that are part of it, using the ECO CANVAS conceptual model. The case study allows showing the concurrent existence of different patterns of business models for sustainability empirically, serving as an example and inspiration for other Latin American companies interested in integrating sustainability into their new and existing business models.

Keywords: sustainable business models, business sustainability, business model patterns, case study, construction industry

Procedia PDF Downloads 109

Authors: Joselito Medina-Marin, Alexandr Karelin, Ana Tarasenko, Juan Carlos Seck-Tuoh-Mora, Norberto Hernandez-Romero, Eva Selene Hernandez-Gress

Abstract:

A production line designer faces with several challenges in manufacturing system design. One of them is the assignment of buffer slots in between every machine of the production line in order to maximize the throughput of the whole line, which is known as the Buffer Allocation Problem (BAP). The BAP is a combinatorial problem that depends on the number of machines and the total number of slots to be distributed on the production line. In this paper, we are proposing a Petri Net (PN) Model to obtain the throughput in unreliable production lines, based on PN mathematical tools and the decomposition method. The results obtained by this methodology are similar to those presented in previous works, and the number of machines is not a hard restriction.

Keywords: buffer allocation problem, Petri Nets, throughput, production lines

Procedia PDF Downloads 300