Search results for: non-linear dynamics features

Authors: Rania Jradi, Christophe Marvillet, Mohamed Razak Jeday

Abstract:

One of the most frequently encountered problems in industrial heat exchangers is fouling, which degrades the thermal and hydraulic performances of these types of equipment, leading thus to failure if undetected. And it occurs due to the accumulation of undesired material on the heat transfer surface. So, it is necessary to know about the heat exchanger fouling dynamics to plan mitigation strategies, ensuring a sustainable and safe operation. This paper proposes an Artificial Neural Network (ANN) approach to estimate the fouling resistance in a cross-flow heat exchanger by the collection of the operating data of the phosphoric acid concentration loop. The operating data of 361 was used to validate the proposed model. The ANN attains AARD= 0.048%, MSE= 1.811x10⁻¹¹, RMSE= 4.256x 10⁻⁶ and r²=99.5 % of accuracy which confirms that it is a credible and valuable approach for industrialists and technologists who are faced with the drawbacks of fouling in heat exchangers.

Keywords: cross-flow heat exchanger, fouling, estimation, phosphoric acid concentration loop, artificial neural network approach

Procedia PDF Downloads 202

Authors: Loai Abdallah, Malik Yousef

Abstract:

A domain space for the data should reflect the actual similarity between objects. Since objects belonging to the same cluster usually share some common traits even though their geometric distance might be relatively large. In general, the Euclidean distance of data points that represented by large number of features is not capturing the actual relation between those points. In this study, we propose a new method to construct a different space that is based on clustering to form a new distance metric. The new distance space is based on ensemble clustering (EC). The EC distance space is defined by tracking the membership of the points over multiple runs of clustering algorithm metric. Over this distance, we train the decision trees classifier (DT-EC). The results obtained by applying DT-EC on 10 datasets confirm our hypotheses that embedding the EC space as a distance metric would improve the performance.

Keywords: ensemble clustering, decision trees, classification, K nearest neighbors

Procedia PDF Downloads 197

Authors: Xiaoyun Hui, Fiona Gentle, Clemens Engelke, Margaret C. Graham

Abstract:

Although past work has shown that phosphorus (P), an important nutrient, may form complexes with aqueous humic substances (HS), the principal component of natural organic matter, the nature of such interactions is poorly understood. Humic complexation may not only enhance P concentrations but it may change its bioavailability within such waters and, in addition, influence its transport within catchment settings. This project is examining the relationships and associations of P, HS, and iron (Fe) in Loch Meadie, Sutherland, North Scotland, a mesohumic freshwater loch which has been assessed as reference condition with respect to P. The aim is to identify characteristic spectroscopic parameters which can enhance the performance of the model currently used to predict reference condition TP levels for highly-coloured Scottish lochs under the Water Framework Directive. In addition to Loch Meadie, samples from other reference condition lochs in north Scotland and Shetland were analysed. By including different types of reference condition lochs (clear water, mesohumic and polyhumic water) this allowed the relationship between total phosphorus (TP) and HS to be more fully explored. The pH, [TP], [Fe], UV/Vis absorbance/spectra, [TOC] and [DOC] for loch water samples have been obtained using accredited methods. Loch waters were neutral to slightly acidic/alkaline (pH 6-8). [TP] in loch waters were lower than 50 µg L-1, and in Loch Meadie waters were typically <10 µg L-1. [Fe] in loch waters were mainly <0.6 mg L-1, but for some loch water samples, [Fe] were in the range 1.0-1.8 mg L-1and there was a positive correlation with [TOC] (r2=0.61). Lochs were classified as clear water, mesohumic or polyhumic based on water colour. The range of colour values of sampled lochs in each category were 0.2–0.3, 0.2–0.5 and 0.5–0.8 a.u. (10 mm pathlength), respectively. There was also a strong positive correlation between [DOC] and water colour (R2=0.84). The UV/Vis spectra (200-700 nm) for water samples were featureless with only a slight “shoulder” observed in the 270–290 nm region. Ultrafiltration was then used to separate colloidal and truly dissolved components from the loch waters and, since it contained the majority of aqueous P and Fe, the colloidal component was fractionated by gel filtration chromatography method. Gel filtration chromatographic fractionation of the colloids revealed two brown-coloured bands which had distinctive UV/Vis spectral features. The first eluting band had larger and more aromatic HS molecules than the second band, and in addition both P and Fe were primarily associated with the larger, more aromatic HS. This result demonstrated that P was able to form complexes with Fe-rich components of HS, and thus provided a scientific basis for the significant correlation between [Fe] and [TP] that the previous monitoring data of reference condition lochs from Scottish Environment Protection Agency (SEPA) showed. The distinctive features of the HS will be used as the basis for an improved spectroscopic tool.

Keywords: total phosphorus, humic substances, Scottish loch water, WFD model

Procedia PDF Downloads 546

Authors: Shanshan Yang, Zhengfu Ning, Ying Kang

Abstract:

The competitive adsorption between shale oil and CO₂ in kerogen is of great significance for CO₂ enhanced oil recovery (CO₂-EOR) and CO₂ storage. In this paper, molecular dynamics (MD) method is used to construct dry kerogen model, and grand canonical Monte Carlo (GCMC) method is used to construct shale reservoir kerogen model with different moisture content. Considering the influence of moisture content and shale oil composition, the competitive adsorption behavior of shale oil and CO₂ in kerogen is simulated, and the feasibility of CO₂ storage was evaluated. The results show that the presence of moisture content significantly reduces the ability of CO₂ to replace shale oil. With the increase of moisture content, the adsorption capacity of shale oil decreases, and the effect of CO₂ replacement of shale oil is improved. The adsorption capacity of long chain alkanes in shale oil decreases under moisture condition, and the competitive adsorption effect between short chain alkanes and CO₂ is more obvious. This study provides an effective guide to quantitatively reveal the competitive adsorption between CO₂ and shale oil from the microscopic perspective.

Keywords: competitive adsorption, kerogen, moisture content, shale oil, carbon dioxide, molecular simulation

Procedia PDF Downloads 6

Authors: Burak Kaplan, Ünver Kaynak

Abstract:

Gas turbine engines, crucial for modern aviation and power generation, rely on the efficient operation of turbine blades. However, extreme temperatures and pressures can lead to material degradation and failure. Film cooling, a widely employed technique, injects a coolant onto the blade surface to mitigate the effects of hot gas exposure. This research investigates the impact of film cooling on gas turbine engine performance, focusing on its influence on efficiency, longevity, and overall engine performance. Through a comprehensive literature review, computational fluid dynamics simulations, and thermal performance analysis, this study aims to provide insights into optimizing film cooling configurations for enhanced engine performance. The research explores the thermal performance characteristics of turbine blades with and without film cooling, the influence of various film cooling techniques on engine efficiency, and the design factors that optimize film cooling effectiveness. The findings of this study have the potential to contribute to the development of more efficient and reliable gas turbine engines, ultimately advancing the field of gas turbine technology.

Keywords: gas turbine, engine, cooling, blade, optimization

Procedia PDF Downloads 16

Authors: Mir Shahriar Emami

Abstract:

Although it is fully impossible to ensure that a software system is quite secure, developing an acceptable secure software system in a convenient platform is not unreachable. In this paper, we attempt to analyze software development life cycle (SDLC) models from the hardware systems and circuits point of view. To date, the SDLC models pay merely attention to the software security from the software perspectives. In this paper, we present new features for SDLC stages to emphasize the role of systems and circuits in developing secure software system through the software development stages, the point that has not been considered previously in the SDLC models.

Keywords: SDLC, SSDLC, software security, software process engineering, hardware systems and circuits security

Procedia PDF Downloads 264

Authors: K. Benhabib, X. Pierens, V-D Nguyen, G. Mimanne

Abstract:

The main hypothesis of the dynamics of solid phase microextraction (SPME) is that steady-state mass transfer is respected throughout the SPME extraction process. It considers steady-state diffusion is established in the two phases and fast exchange of the analyte at the solid phase film/water interface. An improved model is proposed in this paper to handle with the situation when the analyte (atrazine) is in contact with colloid suspensions (carboxylate latex in aqueous solution). A mathematical solution is obtained by substituting the diffusion coefficient by the mean of diffusion coefficient between analyte and carboxylate latex, and also thickness layer by the mean thickness in aqueous solution. This solution provides an equation relating the extracted amount of the analyte to the extraction a little more complicated than previous models. It also gives a better description of experimental observations. Moreover, the rate constant of analyte obtained is in satisfactory agreement with that obtained from the initial curve fitting.

Keywords: pesticide, solid-phase microextraction (SPME) methods, steady state, analytical model

Procedia PDF Downloads 492

Authors: Alok Madan, Arshad K. Hashmi

Abstract:

Performance based design (PBD) is an iterative exercise in which a preliminary trial design of the building structure is selected and if the selected trial design of the building structure does not conform to the desired performance objective, the trial design is revised. In this context, development of a fundamental approach for performance based seismic design of masonry infilled frames with minimum number of trials is an important objective. The paper presents a plastic design procedure based on the energy balance concept for PBD of multi-story multi-bay masonry infilled reinforced concrete (R/C) frames subjected to near-field earthquakes. The proposed energy based plastic design procedure was implemented for trial performance based seismic design of representative masonry infilled reinforced concrete frames with various practically relevant distributions of masonry infill panels over the frame elevation. Non-linear dynamic analyses of the trial PBD of masonry infilled R/C frames was performed under the action of near-field earthquake ground motions. The results of non-linear dynamic analyses demonstrate that the proposed energy method is effective for performance based design of masonry infilled R/C frames under near-field as well as far-field earthquakes.

Keywords: masonry infilled frame, energy methods, near-fault ground motions, pushover analysis, nonlinear dynamic analysis, seismic demand

Procedia PDF Downloads 293

Authors: Jaiden X. Schraut

Abstract:

Medical Imaging Segmentation of Chest X-rays is used for the purpose of identification and differentiation of lung cancer, pneumonia, COVID-19, and similar respiratory diseases. Widespread application of computer-supported perception methods into the diagnostic pipeline has been demonstrated to increase prognostic accuracy and aid doctors in efficiently treating patients. Modern models attempt the task of segmentation and classification separately and improve diagnostic efficiency; however, to further enhance this process, this paper proposes a multi-output network that follows a U-Net architecture for image segmentation output and features an additional CNN module for auxiliary classification output. The proposed model achieves a final Jaccard Index of .9634 for image segmentation and a final accuracy of .9600 for classification on the COVID-19 radiography database.

Keywords: chest X-ray, deep learning, image segmentation, image classification

Procedia PDF Downloads 148

Authors: Chih-Fong Tsai, Ya-Han Hu

Abstract:

The aim of feature selection (or dimensionality reduction) is to filter out unrepresentative features (or variables) making the classifier perform better than the one without feature selection. Since there are many well-known feature selection algorithms, and different classifiers based on different selection results may perform differently, very few studies consider examining the effect of performing different feature selection algorithms on the classification performances by different classifiers over different types of datasets. In this paper, two widely used algorithms, which are the genetic algorithm (GA) and information gain (IG), are used to perform feature selection. On the other hand, three well-known classifiers are constructed, which are the CART decision tree (DT), multi-layer perceptron (MLP) neural network, and support vector machine (SVM). Based on 14 different types of datasets, the experimental results show that in most cases IG is a better feature selection algorithm than GA. In addition, the combinations of IG with DT and IG with SVM perform best and second best for small and large scale datasets.

Keywords: data mining, feature selection, pattern classification, dimensionality reduction

Procedia PDF Downloads 672

Authors: Shuai Zhao, Shalendra D. Sharma, Jin Xu

Abstract:

This research uses advanced machine learning models to learn a number of hypotheses regarding political executives. Specifically, it analyses the impact these powerful leaders have on economic growth by using leaders’ data from the Archigos database from 1835 to the end of 2015. The data is processed by the AutoGluon, which was developed by Amazon. Automated Machine Learning (AutoML) and AutoGluon can automatically extract features from the data and then use multiple classifiers to train the data. Use a linear regression model and classification model to establish the relationship between leaders and economic growth (GDP per capita growth), and to clarify the relationship between their characteristics and economic growth from a machine learning perspective. Our work may show as a model or signal for collaboration between the fields of statistics and artificial intelligence (AI) that can light up the way for political researchers and economists.

Keywords: comparative politics, political executives, leaders’ characteristics, artificial intelligence

Procedia PDF Downloads 89

Authors: Kwame Sarkodie, William Cheung, Andrew R. Fergursson

Abstract:

The characterization of multiphase flow has gained enormous attention for most petroleum and chemical industrial processes. In order to fully characterize fluid phases in a stream or containment, there needs to be a profound knowledge of the existing composition of fluids present. This introduces a problem for real-time monitoring of fluid dynamics such as fluid distributions, and phase fractions. This work presents a simple technique of correlating absorbance spectrums of water, oil and air bubble present in containment. These spectra absorption outputs are derived by using an Fourier Infrared spectrometer. During the testing, air bubbles were introduced into static water column and oil containment and with light absorbed in the infrared regions of specific wavelength ranges. Attenuation coefficients are derived for various combinations of water, gas and oil which reveal the presence of each phase in the samples. The results from this work are preliminary and viewed as a build up to the design of a multiphase flow rig which has an infrared sensor pair to be used for multiphase flow characterization.

Keywords: attenuation, infrared, multiphase, spectroscopy

Procedia PDF Downloads 371

Authors: Clarinda Vitorino Nhangumbe, Ercília Sousa

Abstract:

Weather derivatives are financial products used to cover non catastrophic weather events with a weather index as the underlying asset. The rainfall weather derivative pricing model is modeled based in the assumption that the rainfall dynamics follows Ornstein-Uhlenbeck process, and the partial differential equation approach is used to derive the convection-diffusion two dimensional time dependent partial differential equation, where the spatial variables are the rainfall index and rainfall depth. To compute the approximation solutions of the partial differential equation, the appropriate boundary conditions are suggested, and an explicit numerical method is proposed in order to deal efficiently with the different choices of the coefficients involved in the equation. Being an explicit numerical method, it will be conditionally stable, then the stability region of the numerical method and the order of convergence are discussed. The model is tested for real precipitation data.

Keywords: finite differences method, ornstein-uhlenbeck process, partial differential equations approach, rainfall derivatives

Procedia PDF Downloads 115

Authors: Chrysanthos Maraveas, Argiris Plesias, Garyfalia G. Triantafyllou, Konstantinos Petronikolos

Abstract:

The current paper presents a structural assessment and proposals for retrofit of the National Youth Foundation Building, an existing reinforced concrete (RC) building in the city of Igoumenitsa, Greece. The building is scheduled to be renovated in order to create a Municipal Cultural Center. The bearing capacity and structural integrity have been investigated in relation to the provisions and requirements of the Greek Retrofitting Code (KAN.EPE.) and European Standards (Eurocodes). The capacity of the existing concrete structure that makes up the two central buildings in the complex (buildings II and IV) has been evaluated both in its present form and after including several proposed architectural interventions. The structural system consists of spatial frames of columns and beams that have been simulated using beam elements. Some RC elements of the buildings have been strengthened in the past by means of concrete jacketing and have had cracks sealed with epoxy injections. Static-nonlinear analysis (Pushover) has been used to assess the seismic performance of the two structures with regard to performance level B1 from KAN.EPE. Retrofitting scenarios are proposed for the two buildings, including type Λ steel bracings and placement of concrete shear walls in the transverse direction in order to achieve the design-specification deformation in each applicable situation, improve the seismic performance, and reduce the number of interventions required.

Keywords: earthquake resistance, pushover analysis, reinforced concrete, retrofit, strengthening

Procedia PDF Downloads 295

Authors: V. Karamzadeh, J. Adhvaryu, A. Chandrasekaran, M. Packirisamy

Abstract:

In Bulk Acoustic Wave (BAW) microfluidics, the throughput of particle sorting is dependent on the complex interplay between the geometric configuration of the channel, the size of the particles, and the properties of the fluid medium, which therefore calls for a detailed modeling and understanding of the fluid-particle interaction dynamics under an acoustic field, prior to designing the system. In this work, we propose a simplified Bulk acoustophoretic system that can be used for size dependent particle sorting. A Finite Element Method (FEM) based analytical model has been developed to study the dependence of particle sizes on channel parameters, and the sorting efficiency in a given fluid medium. Based on the results, the microfluidic system has been designed to take into account all the variables involved with the underlying physics, and has been fabricated using an additive manufacturing technique employing a commercial 3D printer, to generate a simple, cost-effective system that can be used for size sensitive particle sorting.

Keywords: 3D printing, 3D microfluidic chip, acoustophoresis, cell separation, MEMS (Microelectromechanical Systems), microfluidics

Procedia PDF Downloads 177

Authors: Vrushali Guhe, Shailza Singh

Abstract:

Cutaneous leishmaniasis is neglected tropical disease present worldwide caused by the protozoan parasite Leishmania major, the therapeutic armamentarium for leishmaniasis are showing several limitations as drugs are showing toxic effects with increasing resistance by a parasite. Thus identification of novel therapeutic targets is of paramount importance. Previous studies have shown that autophagy, a cellular process, can either facilitate infection or aid in the elimination of the parasite, depending on the specific parasite species and host background in leishmaniasis. In the present study, our objective was to target the essential autophagy protein ATG8, which plays a crucial role in the survival, infection dynamics, and differentiation of the Leishmania parasite. ATG8 in Leishmania major and its homologue, LC3, in Homo sapiens, act as autophagic markers. Present study manifested the crucial role of ATG8 protein as a potential target for combating Leishmania major infection. Through bioinformatics analysis, we identified non-conserved motifs within the ATG8 protein of Leishmania major, which are not present in LC3 of Homo sapiens. Against these two non-conserved motifs, we generated a peptide library of 60 peptides on the basis of physicochemical properties. These peptides underwent a filtering process based on various parameters, including feasibility of synthesis and purification, compatibility with Selective Reaction Monitoring (SRM)/Multiple reaction monitoring (MRM), hydrophobicity, hydropathy index, average molecular weight (Mw average), monoisotopic molecular weight (Mw monoisotopic), theoretical isoelectric point (pI), and half-life. Further filtering criterion shortlisted three peptides by using molecular docking and molecular dynamics simulations. The direct interaction between ATG8 and the shortlisted peptides was confirmed through Surface Plasmon Resonance (SPR) experiments. Notably, these peptides exhibited the remarkable ability to penetrate the parasite membrane and exert profound effects on Leishmania major. The treatment with these peptides significantly impacted parasite survival, leading to alterations in the cell cycle and morphology. Furthermore, the peptides were found to modulate autophagosome formation, particularly under starved conditions, suggesting their involvement in disrupting the regulation of autophagy within Leishmania major. In vitro, studies demonstrated that the selected peptides effectively reduced the parasite load within infected host cells. Encouragingly, these findings were corroborated by in vivo experiments, which showed a reduction in parasite burden upon peptide administration. Additionally, the peptides were observed to affect the levels of LC3II within host cells. In conclusion, our findings highlight the efficacy of these novel peptides in targeting Leishmania major’s ATG8 and disrupting parasite survival. These results provide valuable insights into the development of innovative therapeutic strategies against leishmaniasis via targeting autophagy protein ATG8 of Leishmania major.

Keywords: ATG8, leishmaniasis, surface plasmon resonance, MD simulation, molecular docking, peptide designing, therapeutics

Procedia PDF Downloads 92

Authors: Moein Izadi, Ali Mohammadzadeh

Abstract:

Detection of damaged parts of roads after earthquake is essential for coordinating rescuers. In this study, an approach is presented for the semi-automatic detection of damaged roads in a city using pre-event vector maps and both pre- and post-earthquake QuickBird satellite images. Damage is defined in this study as the debris of damaged buildings adjacent to the roads. Some spectral and texture features are considered for SVM classification step to detect damages. Finally, the proposed method is tested on QuickBird pan-sharpened images from the Bam City earthquake and the results show that an overall accuracy of 81% and a kappa coefficient of 0.71 are achieved for the damage detection. The obtained results indicate the efficiency and accuracy of the proposed approach.

Keywords: SVM classifier, disaster management, road damage detection, quickBird images

Procedia PDF Downloads 627

Authors: Marta Gràcia, Ana Luisa Adam-Alcocer, Jesús M. Alvarado, Verónica Quezada, Tere Zarza, Priscila Garza

Abstract:

In secondary education, integrating linguistic content and reflection on it is a crucial challenge that should be included in course plans to enhance students' oral communication competence. In secondary education classrooms, a continuum can be identified in relation to teaching methodologies: 1) the traditional teacher-dominated transmission approach, which is described as that in which teachers transmit content to students unidirectionally; 2) dialogical, bidirectional teaching approach that encourages students to adopt a critical vision of the information provided by the teacher or that is generated through students’ discussion. In this context, the EVALOE-DSS (Assessment Scale of Oral Language Teaching in the School Context-Decision Support System) digital instrument has emerged to help teachers in transforming their classes into spaces for communication, dialogue, reflection, evaluation of the learning process, teaching linguistic contents, and to develop curricular competencies. The tool includes various resources, such as a tutorial with the objectives and an initial screen for teachers to describe the class to be evaluated. One of the main resources of the digital instrument consists of 30 items-actions with three qualitative response options (green, orange, and red face emoji) grouped in five dimensions. In the context of the participation of secondary education teachers in a professional development program using EVALOE-DSS, a digital tool resource aimed to generate more participatory, interactive, dialogic classes, the objectives of the study were: 1) understanding the changes in classrooms’ dynamics and in the teachers’ strategies during their participation in the professional developmental program; 2) analyzing the impact of these changes in students’ oral language development according to their teachers; 3) Deeping on the impact of these changes in the students’ assessment of the classes and the self-assessment of oral competence; 4) knowing teachers’ assessment and reflections about their participation in the professional developmental program. Participants were ten teachers of different subjects and 250 students of secondary education (16-18 years) schools in Spain. The principal instrument used was the digital tool EVALOE-DSS. For 6 months, teachers used the digital tool to reflect on their classes, assess them (their actions and their students’ actions), make decisions, and introduce changes in their classes to be more participatory, interactive, and reflective about linguistic contents. Other collecting data instruments and techniques used during the study were: 1) a questionnaire to assess students’ oral language competence before and at the end of the study, 2) a questionnaire for students’ assessment of the characteristics of classes, 3) teachers’ meetings during the professional developmental program to reflect collaboratively on their experience, 4) questionnaire to assess teacher’s experience during their participation in the professional developmental program, 5) focus group meetings between the teachers and two researchers at the end of the study. The results showed relevant changes in teaching strategies, in the dynamics of the classes, which were more interactive, participative, dialogic and self-managed by the students. Both teachers and students agree about the progressive classes’ transformation into spaces for communication, discussion, and reflection on the language, its development, and its use as an essential instrument to develop curricular competencies.

Keywords: digital tool, individual and collaborative reflection, oral language competence, professional development program, secondary education

Procedia PDF Downloads 42

Authors: Joud Tayeb, Dunia Moussa, Rafal Al-Khawlani, Huda Elyas

Abstract:

This research delves into the intricate AI features of Jenni, an AI-powered chatbot designed to offer personalized and engaging conversations. We explore the fundamental technologies driving Jenni's capabilities, including natural language processing (NLP), machine learning, and deep learning. Through a meticulous analysis of these technologies, we aim to unravel how Jenni effectively processes and understands user queries, generates contextually relevant responses, and continuously learns from interactions. To gain deeper insights into user experiences and satisfaction, a comprehensive survey was conducted. By analyzing the collected data, we determine that consumers mostly like Jenni AI and reported that it has improved their essay writing process, yet the algorithm needs to improve certain aspects, such as accuracy.

Keywords: natural language processing, machine learning, deep learning, artificial intelligence, Jenni

Procedia PDF Downloads 16

Authors: Arum Kingsley Chinedu, Ugwuowo Fidelis Ifeanyi, Oranye Henrietta Ebele

Abstract:

The Poisson regression model (PRM) is a nonlinear model that belongs to the exponential family of distribution. PRM is suitable for studying count variables using appropriate covariates and sometimes experiences the problem of multicollinearity in the explanatory variables and outliers on the response variable. This study aims to address the problem of multicollinearity and outliers jointly in a Poisson regression model. We developed an estimator called the robust modified jackknife PCKL parameter estimator by combining the principal component estimator, modified jackknife KL and transformed M-estimator estimator to address both problems in a PRM. The superiority conditions for this estimator were established, and the properties of the estimator were also derived. The estimator inherits the characteristics of the combined estimators, thereby making it efficient in addressing both problems. And will also be of immediate interest to the research community and advance this study in terms of novelty compared to other studies undertaken in this area. The performance of the estimator (robust modified jackknife PCKL) with other existing estimators was compared using mean squared error (MSE) as a performance evaluation criterion through a Monte Carlo simulation study and the use of real-life data. The results of the analytical study show that the estimator outperformed other existing estimators compared with by having the smallest MSE across all sample sizes, different levels of correlation, percentages of outliers and different numbers of explanatory variables.

Keywords: jackknife modified KL, outliers, multicollinearity, principal component, transformed M-estimator.

Procedia PDF Downloads 71

Authors: H. Yousefnia, SJ. Ahmadi, S. Sajadi, S. Zolghadri, A. Bahrami-Samani, M. Bagherzadeh

Abstract:

Nowadays, superparamagnetic iron oxide nanoparticles (SPIONs) as the multitask agents have showed advantageous characteristics. The aim of this study was the preparation and quality control of 153Sm-DTPA-DA-SPION complex. Samarium-153 was produced by neutron irradiation of the enriched 152Sm2O3 in a research reactor for 5 d. For radiolabeling purposes, 8 mg of the ligand was added to the vial containing 153SmCl3 and the mixture was sonicated 30 min, while pH was adjusted to 7-8. The radiochemical purity of the complex was checked by the ITLC method using NH4OH:MeOH:H2O (0.2:2:4) as the mobile phase. This new radiolabeled complex was prepared with a radiochemical purity of higher than 98% in 30 min at the optimized condition. The complex was kept at room temperature and in human serum at 37 °C for 48 h, showed no loss of 153Sm from the complex. Considering all of these features, this new radiolabeled complex can be considered as a good therapeutic agent; however, further studies on its biological behavior are still needed.

Keywords: iron nanoparticles, preparation, quality control, 153Sm

Procedia PDF Downloads 334

Authors: Houssem Ayari

Abstract:

Sheet molding compounds (SMC) are high strength thermoset moulding materials reinforced with glass treated with thermocompression. SMC composites combine fibreglass resins and polyester/phenolic/vinyl and unsaturated acrylic to produce a high strength moulding compound. These materials are usually formulated to meet the performance requirements of the moulding part. In addition, the vinyl ester resins used in the new advanced SMC systems (A-SMC) have many desirable features, including mechanical properties comparable to epoxy, excellent chemical resistance and tensile resistance, and cost competitiveness. In this paper, a proposed model is used to take into account the Young modulus evolutions of advanced SMC systems (A-SMC) composite under fatigue tests. The proposed model and the used approach are in good agreement with the experimental results.

Keywords: composites SFRC, damage, fatigue, Mori-Tanaka

Procedia PDF Downloads 121

Authors: Chuhan Zhang

Abstract:

As a typical mountainous city in the world, with the rise of shared transportation, cycling behavior in Chongqing is undergoing a role change from a traditional leisure activity to an important transportation mode. However, with the rapid increase in people's cycling demand, the built environment with mountainous features in Chongqing has become a key constraint hindering the further development of bicycle traffic. Based on the above background, the research summarizes the current development contradictions of bicycle traffic in Chongqing, analyses the global experience in the construction of bicycle-friendly cities with mountain characteristics, and combines the characteristics of bicycle traffic in Chongqing to further propose the planning method of the bicycle in mountain cities, to improve the bikability of Chongqing from the perspective of urban planning.

Keywords: bicycle traffic, mountainous city, bicycle-friendly, bikability, Chongqing

Procedia PDF Downloads 104

Authors: R. B. Knudsen, O. T. Rasmussen, R. A. Alphinas

Abstract:

The reason for conducting this research is to develop an algorithm that is capable of classifying news articles from the automobile industry, according to the competitive actions that they entail, with the use of Text Mining (TM) methods. It is needed to test how to properly preprocess the data for this research by preparing pipelines which fits each algorithm the best. The pipelines are tested along with nine different classification algorithms in the realm of regression, support vector machines, and neural networks. Preliminary testing for identifying the optimal pipelines and algorithms resulted in the selection of two algorithms with two different pipelines. The two algorithms are Logistic Regression (LR) and Artificial Neural Network (ANN). These algorithms are optimized further, where several parameters of each algorithm are tested. The best result is achieved with the ANN. The final model yields an accuracy of 0.79, a precision of 0.80, a recall of 0.78, and an F1 score of 0.76. By removing three of the classes that created noise, the final algorithm is capable of reaching an accuracy of 94%.

Keywords: Artificial Neural network, Competitive dynamics, Logistic Regression, Text classification, Text mining

Procedia PDF Downloads 128

Authors: Yesim Sucullu Karadag, Pinar Kurt, Sule Bilen, Nese Subutay Oztekin, Fikri Ak

Abstract:

Background: Primary cervical dystonia is thought to be a purely motor disorder. But recent studies revealed that patients with dystonia had additional non-motor features. Sensory and psychiatric disturbances could be included into the non-motor spectrum of dystonia. The Basal Ganglia receive inputs from all cortical areas and throughout the thalamus project to several cortical areas, thus participating to circuits that have been linked to motor as well as sensory, emotional and cognitive functions. However, there are limited studies indicating cognitive impairment in patients with cervical dystonia. More evidence is required regarding neurocognitive functioning in these patients. Objective: This study is aimed to investigate neurocognitive profile of cervical dystonia patients in comparison to healthy controls (HC) by employing a detailed set of neuropsychological tests in addition to self-reported instruments. Methods: Totally 29 (M/F: 7/22) cervical dystonia patients and 30 HC (M/F: 10/20) were included into the study. Exclusion criteria were depression and not given informed consent. Standard demographic, educational data and clinical reports (disease duration, disability index) were recorded for all patients. After a careful neurological evaluation, all subjects were given a comprehensive battery of neuropsychological tests: Self report of neuropsychological condition (by visual analogue scale-VAS, 0-100), RAVLT, STROOP, PASAT, TMT, SDMT, JLOT, DST, COWAT, ACTT, and FST. Patients and HC were compared regarding demographic, clinical features and neurocognitive tests. Also correlation between disease duration, disability index and self report -VAS were assessed. Results: There was no difference between patients and HCs regarding socio-demographic variables such as age, gender and years of education (p levels were 0.36, 0.436, 0.869; respectively). All of the patients were assessed at the peak of botulinum toxine effect and they were not taking an anticholinergic agent or benzodiazepine. Dystonia patients had significantly impaired verbal learning and memory (RAVLT, p<0.001), divided attention and working memory (ACTT, p<0.001), attention speed (TMT-A and B, p=0.008, 0.050), executive functions (PASAT, p<0.001; SDMT, p= 0.001; FST, p<0.001), verbal attention (DST, p=0.001), verbal fluency (COWAT, p<0.001), visio-spatial processing (JLOT, p<0.001) in comparison to healthy controls. But focused attention (STROOP-spontaneous correction) was not different between two groups (p>0.05). No relationship was found regarding disease duration and disability index with any neurocognitive tests. Conclusions: Our study showed that neurocognitive functions of dystonia patients were worse than control group with the similar age, sex, and education independently clinical expression like disease duration and disability index. This situation may be the result of possible cortical and subcortical changes in dystonia patients. Advanced neuroimaging techniques might be helpful to explain these changes in cervical dystonia patients.

Keywords: cervical dystonia, neurocognitive impairment, neuropsychological test, dystonia disability index

Procedia PDF Downloads 424

Authors: Yu Qin

Abstract:

In order to tackle the ever-growing problem of the lack of parking space, this paper presents the design and implementation of a smart unmanned parking system that is based on RFID (radio frequency identification) technology and Wireless communication technology. This system uses RFID technology to achieve the identification function (transmitted by 2.4 G wireless module) and is equipped with an STM32L053 micro controller as the main control chip of the smart vehicle. This chip can accomplish automatic parking (in/out), charging and other functions. On this basis, it can also help users easily query the information that is stored in the database through the Internet. Experimental tests have shown that the system has the features of low power consumption and stable operation, among others. It can effectively improve the level of automation control of the parking lot management system and has enormous application prospects.

Keywords: RFID, embedded system, unmanned, parking management

Procedia PDF Downloads 334

Authors: Adrian Rettig, Silvan Schneider, Reto Tamburini, Mirko Kleingries, Ulf Christian Muller

Abstract:

Industrial adsorption processes are, mainly due to si-multaneous heat and mass transfer, characterized by a high level of complexity. The conception of such processes often does not take place systematically; instead scale-up/down respectively number-up/down methods based on existing systems are used. This paper shows how Modelica® can be used to develop a transient model enabling a more systematic design of such ad- and desorption components and processes. The core of this model is a lumped-element submodel of a single adsorbent grain, where the thermodynamic equilibria and the kinetics of the ad- and desorption processes are implemented and solved on the basis of mass-, momentum and energy balances. For validation of this submodel, a fixed bed adsorber, whose characteristics are described in detail in the literature, was modeled and simulated. The simulation results are in good agreement with the experimental results from the literature. Therefore, the model development will be continued, and the extended model will be applied to further adsorber types like rotor adsorbers and moving bed adsorbers.

Keywords: adsorption, desorption, linear driving force, dynamic model, Modelica®, integral equation approach

Procedia PDF Downloads 376

Authors: Anjula Negi, Sanjay Gupta

Abstract:

Paradigms studied inform inadequacies of financial resources, be it to finance metro rails for construction or to meet operational revenues or to derive profits in the long term. Funding sustainability is far and wide for much-needed public transport modes, like urban rail or metro rails, to be successfully operated. India embarks upon a sustainable transport journey and has proposed metro rail systems countrywide. As an emerging economic leader, its fiscal constraints are paramount, and the land value capture (LVC) mechanism provides necessary support and innovation toward development. India’s metro rail policy promotes multiple methods of financing, including private-sector investments and public-private-partnership. The critical question that remains to be addressed is what factors can make such mechanisms work. Globally, urban rail is a revolution noted by many researchers as future mobility. Researchers in this study deep dive by way of literature review and empirical assessments into factors that can lead to the adoption of LVC mechanisms. It is understood that the adoption of LVC methods is in the nascent stages in India. Research posits numerous challenges being faced by metro rail agencies in raising funding and for incremental value capture. A few issues pertaining to land-based financing, inter alia: are long-term financing, inter-institutional coordination, economic/ market suitability, dedicated metro funds, land ownership issues, piecemeal approach to real estate development, property development legal frameworks, etc. The question under probe is what are the parameters that can lead to success in the adoption of land value capture (LVC) as a financing mechanism. This research provides insights into key parameters crucial to the adoption of LVC in the context of Indian metro rails. Researchers have studied current forms of LVC mechanisms at various metro rails of the country. This study is significant as little research is available on the adoption of LVC, which is applicable to the Indian context. Transit agencies, State Government, Urban Local Bodies, Policy makers and think tanks, Academia, Developers, Funders, Researchers and Multi-lateral agencies may benefit from this research to take ahead LVC mechanisms in practice. The study deems it imperative to explore and understand key parameters that impact the adoption of LVC. Extensive literature review and ratification by experts working in the metro rails arena were undertaken to arrive at parameters for the study. Stakeholder consultations in the exploratory factor analysis (EFA) process were undertaken for principal component extraction. 43 seasoned and specialized experts participated in a semi-structured questionnaire to scale the maximum likelihood on each parameter, represented by various types of stakeholders. Empirical data was collected on chosen eighteen parameters, and significant correlation was extracted for output descriptives and inferential statistics. Study findings reveal these principal components as institutional governance framework, spatial planning features, legal frameworks, funding sustainability features and fiscal policy measures. In particular, funding sustainability features highlight sub-variables of beneficiaries to pay and use of multiple revenue options towards success in LVC adoption. Researchers recommend incorporation of these variables during early stage in design and project structuring for success in adoption of LVC. In turn leading to improvements in revenue sustainability of a public transport asset and help in undertaking informed transport policy decisions.

Keywords: Exploratory factor analysis, land value capture mechanism, financing metro rails, revenue sustainability, transport policy

Procedia PDF Downloads 87

Authors: Ayyoub Jamali, Alena Kozlova

Abstract:

The Russian invasion of Ukraine has tested the mettle of the international community, prompting not only States but also non-state actors to take deterrent action in response. Indeed, international sports organisations, namely FIFA and UEFA, have been rather successful in shifting the power dynamics by introducing a complete ban on the Russian national and club teams. This article aims to inquire into the human rights implications of such actions taken by international sports organisations. First, the article departs from an assessment of the legal status of FIFA and UEFA under international law and reflects on how a legal link could be established vis-à-vis their human rights obligations. Second, it examines the human rights aspects of the impugned measures by FIFA and UEFA on the part of the Russian athletes, further scrutinising them against the international human rights law principle of non-discrimination through a proportionality test. Last, it draws basic pathways for how possible human rights violations committed in the context of measures adopted by such organisations could be remedied, outlining the challenges of arbitration and litigation in Switzerland.

Keywords: FIFA, UEFA, FUR, ban, human rights, Russia, Ukraine, non-state actors

Procedia PDF Downloads 88

Authors: Zhidong Zhang, Yingchen Yang

Abstract:

In this study, a diagnostic assessment model for Mastery Engineering Learning was established based on a group of undergraduate students who studied in an engineering course. A diagnostic assessment model can examine both students' learning process and report achievement results. One very unique characteristic is that the diagnostic assessment model can recognize the errors and anything blocking students in their learning processes. The feedback is provided to help students to know how to solve the learning problems with alternative strategies and help the instructor to find alternative pedagogical strategies in the instructional designs. Dynamics is a core course in which is a common course being shared by several engineering programs. This course is a very challenging for engineering students to solve the problems. Thus knowledge acquisition and problem-solving skills are crucial for student success. Therefore, developing an effective and valid assessment model for student learning are of great importance. Diagnostic assessment is such a model which can provide effective feedback for both students and instructor in the mastery of engineering learning.

Keywords: diagnostic assessment, mastery learning, engineering, bayesian network model, learning processes

Procedia PDF Downloads 155