Search results for: text mining analysis

Authors: Ardiana Murtezani, Ilirijana Dallku, Teuta Osmani Vllasolli, Sabit Sllamniku

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Background: The use of foot orthoses are always indicated when there are alterations of the optimal biomechanics' position of the foot. Orthotics are very effective and very suitable for the majority of patients with pain due to overload which can be related to biomechanical disorders. Aim: To assess the frequency of patients requiring foot orthoses, type of orthoses and analysis of their disease leading to the use of foot orthoses. Material and Methods: Our study included 128 patients with various foot pathologies, treated at the outpatient department of the Ortho-Prosthetic Center of Kosovo (OPCK) in Prishtina. Prospective-descriptive clinical method was used during this study. Functional status of patients was examined, and the following parameters are noted: range of motion measurements for the affected joints/lower extremities, manual test for muscular strength below the knee and foot of the affected extremity, perimeter measurements of the lower extremities, measurements of lower extremities, foot length measurement, foot width measurements and size. In order to complete the measurements the following instruments are used: plantogram, pedogram, meter and cork shoe lift appliances. Results: The majority of subjects in this study are male (60.2% vs. 39.8%), and the dominant age group was 0-9 (47.7%), 61 subjects respectively. Most frequent foot disorders were: congenital disease 60.1%, trauma cases 13.3%, consequences from rheumatologic disease 12.5%, neurologic dysfunctions 11.7%, and the less frequented are the infectious cases 1.6%. Congenital anomalies were the most frequent cases, and from this group majority of cases suffered from pes planovalgus (37.5%), eqinovarus (15.6%) and discrepancies between extremities (6.3%). Furthermore, traumatic amputations (2.3%) and arthritis (0.8%). As far as neurologic disease, subjects with cerebral palsy are represented with (3.1%), peroneal nerve palsy (2.3%) and hemiparesis (1.6%). Infectious disease osteomyelitis sequels are represented with (1.6%). Conclusion: Based on our study results, we have concluded that the use of foot orthoses for patients suffering from rheumatoid arthritis and nonspecific arthropaty was effective treatment choice, leading to decrease of pain, less deformities and improves the quality of life.

Keywords: orthoses, epidemiological analysis, rheumatoid arthritis, rehabilitation

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Authors: Leon Mortari

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The Metropolitan East region of Rio de Janeiro state, Brazil, faces a historic water scarcity. Among the alternatives studied to solve this situation, the possibility of adduction of the available water in the reservoir Lagoa de Juturnaíba to supply the region's municipalities stands out. The allocation of a linear engineering project must occur through an evaluation of different aspects, such as altitude, slope, proximity to roads, distance from watercourses, land use and occupation, and physical and chemical features of the soil. This work aims to apply a multi-criteria model that combines geoprocessing techniques, decision-making, and geometric search algorithm to optimize a hypothetical adductor system in the scenario of expanding the water supply system that serves this region, known as Imunana-Laranjal, using the Lagoa de Juturnaíba as the source. It is proposed in this study, the construction of a spatial database related to the presented evaluation criteria, treatment and rasterization of these data, and standardization and reclassification of this information in a Geographic Information System (GIS) platform. The methodology involves the integrated analysis of these criteria, using their relative importance defined by weighting them based on expert consultations and the Analytic Hierarchy Process (AHP) method. Three approaches are defined for weighting the criteria by AHP: the first treats all criteria as equally important, the second considers weighting based on a pairwise comparison matrix, and the third establishes a hierarchy based on the priority of the criteria. For each approach, a distinct group of weightings is defined. In the next step, map algebra tools are used to overlay the layers and generate cost surfaces, that indicates the resistance to the passage of the adductor route, using the three groups of weightings. The Dijkstra algorithm, a geometric search algorithm, is then applied to these cost surfaces to find an optimized path within the geographical space, aiming to minimize resources, time, investment, maintenance, and environmental and social impacts.

Keywords: geometric search algorithm, GIS, pipeline, route optimization, spatial multi-criteria analysis model

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Authors: Lahcen Daoudi, Soukaina Elidrissi, Nathalie Fagel

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The calcareous accumulations in the surface formations of the soil, are a very widespread phenomenon in the arid and semi-arid regions. Many aspects of physical and chemical evolution of these soils were debated for more than one century. The last two decades have witnessed a remarkable interest in the study of the calcrete. In Morocco, as in most Mediterranean countries, soils with carbonate accumulation cover large areas of the territory. The isohumic subtropical soils and red Mediterranean soils include always a horizon of calcrete accumulation. In the lowland of Tensift Al Haouz located in the central part of Morocco, the arable lands are underlain by indurate pedogenic calcrete of various thicknesses; this constitutes a serious handicap for agricultural development in the region. Our aims in this study is to analyze the characteristics of the crusts developed in this area in order to identify the various facies, their geographic distribution and the factors that played a significant role in the differentiation of these calcareous accumulations. The characterizations were based on various techniques including field observations, X-ray diffraction analysis (XRD) for both raw materials and clay fractions, SEM analysis, Calcimetry and Loss On Ignition (LOI). The analysis of encrusting calcrete in a rich and varied observation field as the region of Tensift Al Haouz enabled us to specify the important types of accumulations: diffuse, nodular and massive encrusting. The shape of encrusting as well as their consistency and hardness is clearly related to the contents of CaCO3 of the profiles. Among these facies, the hardpan which results from a complex succession of processes is certainly the most morphologically advanced form of encrusting. The vertical and lateral distribution of these forms in the Tensift Al Haouz area indicates that they do not appear randomly but seem related to well defined environmental conditions. The differentiation and evolution of encrusting is under the influence of two major factors: 1) the availability of carbonate rich solution which is controlled by the topography, the nature and texture of underlying host rock and the detrital processes; 2) the climate which is responsible for the evaporation and crystallization of carbonate.

Keywords: soil calcrete, characterization, morphology, Tensift Al Haouz, Morocco

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Authors: Chong Wang, Kellem M. Soares, Luis E. Kosteski

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The problem of toughening in brittle materials reinforced by fibers is complex, involving all the mechanical properties of fibers, matrix, the fiber/matrix interface, as well as the geometry of the fiber. An appropriate method applicable to the simulation and analysis of toughening is essential. In this work, we performed simulations and analysis of toughening in brittle matrix reinforced by randomly distributed fibers by means of the discrete elements method. At first, we put forward a mechanical model of the contribution of random fibers to the toughening of composite. Then with numerical programming, we investigated the stress, damage and bridging force in the composite material when a crack appeared in the brittle matrix. From the results obtained, we conclude that: (i) fibers with high strength and low elasticity modulus benefit toughening; (ii) fibers with relatively high elastic modulus compared to the matrix may result in considerable matrix damage (spalling effect); (iii) employment of high-strength synthetic fiber is a good option. The present work makes it possible to optimize the parameters in order to produce advanced ceramic with desired performance. We believe combination of the discrete element method (DEM) with the finite element method (FEM) can increase the versatility and efficiency of the software developed.

Keywords: bridging stress, discrete element method, fiber reinforced composites, toughening

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Authors: Flavio Cordeiro Fontanella, Asla Medeiros e Sá, Moacyr Alvim Horta Barbosa da Silva

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In the present work, we analyse the performance of football results forecasting models. In order to do so, we have performed the data collection from eight different forecasting models during the 2021 Brazilian football season. First, we guide the analysis through visual representations of the data, designed to highlight the most prominent features and enhance the interpretation of differences and similarities between the models. We propose using a 2-simplex triangle to investigate visual patterns from the results forecasting models. Next, we compute the expected points for every team playing in the championship and compare them to the final league standings, revealing interesting contrasts between actual to expected performances. Then, we evaluate forecasts’ accuracy using the Ranked Probability Score (RPS); models comparison accounts for tiny scale differences that may become consistent in time. Finally, we observe that the Wisdom of Crowds principle can be appropriately applied in the context, driving into a discussion of results forecasts usage in practice. This paper’s primary goal is to encourage football forecasts’ performance discussion. We hope to accomplish it by presenting appropriate criteria and easy-to-understand visual representations that can point out the relevant factors of the subject.

Keywords: accuracy evaluation, Brazilian championship, football results forecasts, forecasting models, visual analysis

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Authors: Kholil, Ario Bimo, Hifni Alifahmi, Soecahyadi, Husen Money

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The number of smokers in Indonesia currently reached 66 million (25.09%) of the total number of smokers reaching 264 million. The government (central and local governments) have issued various rules to reduce the number of smokers, but the results are still not effective; in fact, the number of smokers continues to increase every year. This study aims to determine the influence of demographics, economy, health, and the role of government on the awareness of smokers in reducing the dangers of cigarettes. Data collection was carried out through a questionnaire distributed to 255 randomly selected respondents and data analysis using SEM (Structural Equation Model). The results of the analysis show that economic and socio-cultural factors do not directly affect the awareness of reducing the dangers of cigarettes. But indirectly, its influence becomes significant through intervening variables of communication strategies. Meanwhile, health factors and the government's role have a very significant influence both directly and indirectly on reducing the dangers of cigarettes. Thus, the main strategy to build awareness of smokers in reducing the dangers of smoking is building an effective communication strategy through three main factors: (1) health, (2) government regulations and (3) the economy.

Keywords: harm reduction, awareness, communication strategy, SEM

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Authors: Arafan Traore, Teiji Watanabe

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Conakry, the capital city of the Republic of Guinea, has experienced a rapid urban expansion and population increased in the last two decades, which has resulted in remarkable local weather and climate change, raise energy demand and pollution and treating social, economic and environmental development. In this study, the spatiotemporal variation of the land surface temperature (LST) is retrieved to characterize the effect of urban growth on the thermal environment and quantify its relationship with biophysical indices, a normalized difference vegetation index (NDVI) and a normalized difference built up Index (NDBI). Landsat data TM and OLI/TIRS acquired respectively in 1986, 2000 and 2016 were used for LST retrieval and Land use/cover change analysis. A quantitative analysis based on the integration of a remote sensing and a geography information system (GIS) has revealed an important increased in the LST pattern in the average from 25.21°C in 1986 to 27.06°C in 2000 and 29.34°C in 2016, which was quite eminent with an average gain in surface temperature of 4.13°C over 30 years study period. Additionally, an analysis using a Pearson correlation (r) between (LST) and the biophysical indices, normalized difference vegetation index (NDVI) and a normalized difference built-up Index (NDBI) has revealed a negative relationship between LST and NDVI and a strong positive relationship between LST and NDBI. Which implies that an increase in the NDVI value can reduce the LST intensity; conversely increase in NDBI value may strengthen LST intensity in the study area. Although Landsat data were found efficient in assessing the thermal environment in Conakry, however, the method needs to be refined with in situ measurements of LST in the future studies. The results of this study may assist urban planners, scientists and policies makers concerned about climate variability to make decisions that will enhance sustainable environmental practices in Conakry.

Keywords: Conakry, land surface temperature, urban heat island, geography information system, remote sensing, land use/cover change

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Authors: Joanna Bajerska, Sylwia Mildner-Szkudlarz, Pawel Górnas, Dalija Segliņac

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Sour cherry pomace (CP) by-products obtained during fruit processing, was used to replace the wheat flour in muffin formula on the levels 20% (CP20) and 30% (CP30). The sensory profile of this muffins were characterized, and their impact on glycemic response and appetite sensation were studied. Randomized crossover study where test subjects were given either plain muffin (PM) or CP20 or CP30 during 2 different occasions. In the first study test muffins with equivalent of 50 g available carbohydrate were consumed. Blood glucose was measured before and up to 120 min after consuming the test muffins. To study satiety response in the second trial of the test muffins (portion 1700 kJ per serve) were ingested. Sensory analysis was performed earlier by a sensory panel consisting of 10 well-trained individuals. It is acceptable to incorporate CP into a muffin formula at concentrations up to 30%. With the CP muffins treatment, the glucose responses were significantly lower at 30, 45 and 60 min of the intervals also the incremental peak glucose was 0.40 mmol/L and 0.60 mmol/L lower than for PM. CP20 and CP30 also improved satiety as compared to PM. CP can be a good functional ingredient of functional bakery products to assist in managing glucose levels and satiety in healthy individuals.

Keywords: muffins, postprandial glucose, sensory analysis, satiety sour cherry pomace

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Authors: Rasha Waheeb, Bjorn Andersen, Rafa Shakir

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Purpose The purpose of this study is to avoid delays that occur in emergency reconstruction projects especially in post disaster circumstances whether if they were natural or manmade due to their particular national and humanitarian importance. We presented a theoretical and practical concepts for projects management in the field of construction industry that deal with a range of global and local trails. This study aimed to identify the factors of effective delay in construction projects in Iraq that affect the time and the specific quality cost, and find the best solutions to address delays and solve the problem by setting parameters to restore balance in this study. 30 projects were selected in different areas of construction were selected as a sample for this study. Design/methodology/approach This study discusses the reconstruction strategies and delay in time and cost caused by different delay factors in some selected projects in Iraq (Baghdad as a case study).A case study approach was adopted, with thirty construction projects selected from the Baghdad region, of different types and sizes. Project participants from the case projects provided data about the projects through a data collection instrument distributed through a survey. Mixed approach and methods were applied in this study. Mathematical data analysis was used to construct models to predict delay in time and cost of projects before they started. The artificial neural networks analysis was selected as a mathematical approach. These models were mainly to help decision makers in construction project to find solutions to these delays before they cause any inefficiency in the project being implemented and to strike the obstacles thoroughly to develop this industry in Iraq. This approach was practiced using the data collected through survey and questionnaire data collection as information form. Findings The most important delay factors identified leading to schedule overruns were contractor failure, redesigning of designs/plans and change orders, security issues, selection of low-price bids, weather factors, and owner failures. Some of these are quite in line with findings from similar studies in other countries/regions, but some are unique to the Iraqi project sample, such as security issues and low-price bid selection. Originality/value we selected ANN’s analysis first because ANN’s was rarely used in project management , and never been used in Iraq to finding solutions for problems in construction industry. Also, this methodology can be used in complicated problems when there is no interpretation or solution for a problem. In some cases statistical analysis was conducted and in some cases the problem is not following a linear equation or there was a weak correlation, thus we suggested using the ANN’s because it is used for nonlinear problems to find the relationship between input and output data and that was really supportive.

Keywords: construction projects, delay factors, emergency reconstruction, innovation ANN, post disasters, project management

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Authors: Eleftheria Barouni, Antonia Terpou, Maria Kanellaki, Argyro Bekatorou, Athanasios A.Koutinas

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The aim of the present work was to evaluate the production of cheese using a composite filter of tubular cellulose (TC) with [a] entrapped rennin enzyme and [b] immobilized L.casei and entrapped enzyme. Tubular cellulose from sawdust was prepared after lignin removal with 1% NaOH. The biocatalysts were thermally dried at 38oC and used for milk coagulation. The effect of temperature (5,20,37 oC) of the first dried biocatalyst on the pH kinetics of milk coagulation was examined. The optimum temperature (37oC) of the first biocatalyst was used for milk coagulation with the second biocatalyst prepared by entrapment of both rennin enzyme and probiotic lactic acid bacteria in order to introduce a sour taste in cheeses. This co-biocatalyst was used for milk coagulation. Samples were studied as regards its effect on lactic acid formation and its correlation with taste test results in cheeses. For both biocatalysts samples were analyzed for total acidity and lactic acid formation by HPLC. The quality of the produced cheeses was examined through the determination of volatile compounds by SPME GC/MS analysis. Preliminary taste tests and microbiological analysis were performed and encourage us for further research regarding scale up.

Keywords: tubular cellulose, Lactobacillus casei, rennin enzyme, cheese production

Procedia PDF Downloads 358

Authors: Wei Yaming

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Objective: In order to compare the stress of employees sent overseas with (GRAS) before and after, we used the resource-oriented music listening intervention in this study. We also collected pertinent experimental data. Methods: The experiment involved 47 employees who were sent abroad by the Chinese side. They completed the stress scale test and documented it before the intervention. They tested for stress after five interventions and performed one-on-one interviews. Quantitative data and SPSS software were used to analyze relationships between stress reduction and resource-oriented music listening, as well as Pearson's correlation, multiple regression levels, and ANOVA. For the qualitative analysis, content analysis of one-on-one interviews was performed. Results: A comparison of data from before and after demonstrates how resource-focused music listening activities can lessen and relieve stress in remote workers. In the qualitative study, stress is broken down into six categories: relationship stress, health stress, emotional stress, and frustration stress. External pressures include work pressure and cultural stress. And it has been determined that listening to music that is resource-oriented can better ease internal stress (health, emotion, and dissatisfaction). Conclusion: The Guide Resource-oriented Music Listening (GROML) Program appears to have had some effect on the participants' stress levels. The resources that the participants encountered while listening to music are bravery, calm, letting go, and relaxing.

Keywords: resource-oriented, music listening, oversea dispatch employees, work stress

Procedia PDF Downloads 100

Authors: V. Golubeva, O. Vakhnina, I. Konopkina, N. Gerasimova, N. Taturina, K. Zhogova

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To improve chemical current sources, the ion-conducting electrolytes based on Li halides (LiCl-KCl, LiCl-LiBr-KBr, LiCl-LiBr-LiF) are developed. It is necessary to have chemical analytical methods for determination of halides to control the electrolytes technology. The methods of classical analytical chemistry are of interest, as they are characterized by high accuracy. Using these methods is a difficult task because halides have similar chemical properties. The objective of this work is to develop a titrimetric method for determining the content of bromides, chlorides, and fluorides in their joint presence in an ion-conducting electrolyte. In accordance with the developed method of analysis to determine fluorides, electrolyte sample is dissolved in diluted HCl acid; fluorides are titrated by La(NO₃)₃ solution with potentiometric indication of equivalence point, fluoride ion-selective electrode is used as sensor. Chlorides and bromides do not form a hardly soluble compound with La and do not interfere in result of analysis. To determine the bromides, the sample is dissolved in a diluted H₂SO₄ acid. The bromides are oxidized with a solution of KIO₃ to Br₂, which is removed from the reaction zone by boiling. Excess of KIO₃ is titrated by iodometric method. The content of bromides is calculated from the amount of KIO₃ spent on Br₂ oxidation. Chlorides and fluorides are not oxidized by KIO₃ and do not interfere in result of analysis. To determine the chlorides, the sample is dissolved in diluted HNO₃ acid and the total content of chlorides and bromides is determined by method of visual mercurometric titration with diphenylcarbazone indicator. Fluorides do not form a hardly soluble compound with mercury and do not interfere with determination. The content of chlorides is calculated taking into account the content of bromides in the sample of electrolyte. The validation of the developed analytical method was evaluated by analyzing internal reference material with known chlorides, bromides and fluorides content. The analytical method allows to determine chlorides, bromides and fluorides in case of their joint presence in ion-conducting electrolyte within the range and with relative total error (δ): for bromides from 60.0 to 65.0 %, δ = ± 2.1 %; for chlorides from 8.0 to 15.0 %, δ = ± 3.6 %; for fluorides from 5.0 to 8.0%, ± 1.5% . The analytical method allows to analyze electrolytes and mixtures that contain chlorides, bromides, fluorides of alkali metals and their mixtures (K, Na, Li).

Keywords: bromides, chlorides, fluorides, ion-conducting electrolyte

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Authors: Subrat Partha Sarathi Pattnaik, Rajan N.K.S.

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Integrated rocket ramjet engines are highly suitable for long range missile applications. Designing the fixed geometry intakes for such missiles that can operate efficiently over a range of operating conditions is a highly challenging task. Hence, the present study aims to evaluate the effect of throat design on the performance of a rectangular mixed compression intake for operation in the Mach number range of 1.8 – 2.5. The analysis has been carried out at four different Mach numbers of 1.8, 2, 2.2, 2.5 and two angle-of-attacks of +5 and +10 degrees. For the throat design, three different throat heights have been considered, one corresponding to a 3- external shock design and two heights corresponding to a 2-external shock design leading to different internal contraction ratios. The on-design Mach number for the study is M 2.2. To obtain the viscous flow field in the intake, the theoretical designs have been considered for computational fluid dynamic analysis. For which Favre averaged Navier- Stokes (FANS) equations with two equation SST k-w model have been solved. The analysis shows that for zero angle of attack at on-design and high off-design Mach number operations the three-ramp design leads to a higher total pressure recovery (TPR) compared to the two-ramp design at both contraction ratios maintaining same mass flow ratio (MFR). But at low off-design Mach numbers the total pressure shows an opposite trend that is maximum for the two-ramp low contraction ratio design due to lower shock loss across the external shocks similarly the MFR is higher for low contraction ratio design as the external ramp shocks move closer to the cowl. At both the angle of attack conditions and complete range of Mach numbers the total pressure recovery and mass flow ratios are highest for two ramp low contraction design due to lower stagnation pressure loss across the detached bow shock formed at the ramp and lower mass spillage. Hence, low contraction design is found to be suitable for higher off-design performance.

Keywords: internal contraction ratio, mass flow ratio, mixed compression intake, performance, supersonic flows

Procedia PDF Downloads 108

Authors: Peter J. Fusco, Dave M. Mathew, Chris Mathew, Kenneth H. Levy, Kathryn S. Varghese, Stephanie Salazar-Restrepo, Serena M. Mathew, Sofia Khaja, Eamon Vega, Mia Polizzi, Alyssa Mullane, Adham Ahmed

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Background: Laparoscopic (LS) removal of neuroblastomas in children has been reported to offer favorable outcomes compared to the conventional open thoracotomy (OT) procedure. Critical perioperative measures such as blood loss, operative time, length of stay, and time to postoperative chemotherapy have all supported laparoscopic use rather than its more invasive counterpart. Herein, a pairwise meta-analysis was performed comparing perioperative outcomes between LS and OT in thoracoabdominal neuroblastoma cases. Methods: A comprehensive literature search was performed on PubMed, Ovid EMBASE, and Scopus databases to identify studies comparing the outcomes of pediatric patients with thoracoabdominal neuroblastomas undergoing resection via OT or LS. After deduplication, 4,227 studies were identified and subjected to initial title screening with exclusion and inclusion criteria to ensure relevance. When studies contained overlapping cohorts, only the larger series were included. Primary outcomes include estimated blood loss (EBL), hospital length of stay (LOS), and mortality, while secondary outcomes were tumor recurrence, post-operative complications, and operation length. The “meta” and “metafor” packages were used in R, version 4.0.2, to pool risk ratios (RR) or standardized mean differences (SMD) in addition to their 95% confidence intervals in the random effects model via the Mantel-Haenszel method. Heterogeneity between studies was assessed using the I² test, while publication bias was assessed via funnel plot. Results: The pooled analysis included 209 patients from 5 studies (141 OT, 68 LS). Of the included studies, 2 originated from the United States, 1 from Toronto, 1 from China, and 1was from a Japanese center. Mean age between study cohorts ranged from 2.4 to 5.3 years old, with female patients occupying between 30.8% to 50% of the study populations. No statistically significant difference was found between the two groups for LOS (SMD -1.02; p=0.083), mortality (RR 0.30; p=0.251), recurrence(RR 0.31; p=0.162), post-operative complications (RR 0.73; p=0.732), or operation length (SMD -0.07; p=0.648). Of note, LS appeared to be protective in the analysis for EBL, although it did not reach statistical significance (SMD -0.4174; p= 0.051). Conclusion: Despite promising literature assessing LS removal of pediatric neuroblastomas, results showed it was non-superior to OT for any explored perioperative outcomes. Given the limited comparative data on the subject, it is evident that randomized trials are necessary to further the efficacy of the conclusions reached.

Keywords: laparoscopy, neuroblastoma, thoracoabdominal, thoracotomy

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Authors: Bitewulign Mekonnen

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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

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Authors: Mia Françoise

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This report aims to develop a strategy for assisting short-term investors to benefit from the current economic climate in South Africa by utilizing technical analysis techniques and predictive analytics. As part of this research, value investing and technical analysis principles will be combined to maximize returns for South African investors while optimizing volatility. As an emerging market, South Africa offers many opportunities for high growth in sectors where other developed countries cannot grow at the same rate. Investing in South African companies with significant growth potential can be extremely rewarding. Although the risk involved is more significant in countries with less developed markets and infrastructure, there is more room for growth in these countries. According to recent research, the offshore market is expected to outperform the local market over the long term; however, short-term investments in the local market will likely be more profitable, as the Johannesburg Stock Exchange is predicted to outperform the S&P500 over the short term. The instabilities in the economy contribute to increased market volatility, which can benefit investors if appropriately utilized. Price prediction and portfolio optimization comprise the two primary components of this methodology. As part of this process, statistics and other predictive modeling techniques will be used to predict the future performance of stocks listed on the Johannesburg Stock Exchange. Following predictive data analysis, Modern Portfolio Theory, based on Markowitz's Mean-Variance Theorem, will be applied to optimize the allocation of assets within an investment portfolio. By combining different assets within an investment portfolio, this optimization method produces a portfolio with an optimal ratio of expected risk to expected return. This methodology aims to provide a short-term investment with a stock portfolio that offers the best risk-to-return profile for stocks listed on the JSE by combining price prediction and portfolio optimization.

Keywords: financial stocks, optimized asset allocation, prediction modelling, South Africa

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Authors: S. J. Yune, S. Y. Lee, S. J. Im, B. S. Kam, S. Y. Baek

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This study aimed to determine the reliability of clinical performance assessments, having been emphasized by ability-based education, and professors overall assessment methods. We addressed the following problems: First, we try to find out whether there is a difference in what we consider to be the main variables affecting the clinical performance test according to the evaluator’s working period and the number of evaluation experience. Second, we examined the relationship among the global rating score (G), analytic global rating score (Gc), and the sum of the analytical checklists (C). What are the main factors affecting clinical performance assessments in relation to the numbers of times the evaluator had administered evaluations and the length of their working period service? What is the relationship between overall assessment score and analytic checklist score? How does analytic global rating with 6 components in OSCE and 4 components in sub-domains (Gc) CPX: aseptic practice, precision, systemic approach, proficiency, successfulness, and attitude overall assessment score and task-specific analytic checklist score sum (C) affect the professor’s overall global rating assessment score (G)? We studied 75 professors who attended a 2016 Bugyeoung Consortium clinical skills performances test evaluating third and fourth year medical students at the Pusan National University Medical school in South Korea (39 prof. in OSCE, 36 prof. in CPX; all consented to participate in our study). Each evaluator used 3 forms; a task-specific analytic checklist, subsequent analytic global rating scale with sub-6 domains, and overall global scale. After the evaluation, the professors responded to the questionnaire on the important factors of clinical performance assessment. The data were analyzed by frequency analysis, correlation analysis, and hierarchical regression analysis using SPSS 21.0. Their understanding of overall assessment was analyzed by dividing the subjects into groups based on experiences. As a result, they considered ‘precision’ most important in overall OSCE assessment, and ‘precise accuracy physical examination’, ‘systemic approaches to taking patient history’, and ‘diagnostic skill capability’ in overall CPX assessment. For OSCE, there was no clear difference of opinion about the main factors, but there was for CPX. Analytic global rating scale score, overall rating scale score, and analytic checklist score had meaningful mutual correlations. According to the regression analysis results, task-specific checklist score sum had the greatest effect on overall global rating. professors regarded task-specific analytic checklist total score sum as best reflecting overall OSCE test score, followed by aseptic practice, precision, systemic approach, proficiency, successfulness, and attitude on a subsequent analytic global rating scale. For CPX, subsequent analytic global rating scale score, overall global rating scale score, and task-specific checklist score had meaningful mutual correlations. These findings support explanations for validity of professors’ global rating in clinical performance assessment.

Keywords: global rating, clinical performance assessment, medical education, analytic checklist

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Authors: Iman Janghorban Esfahani

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Due to the increased use of irrigation in agriculture, the importance and need for highly reliable water pumping systems have significantly increased. The pumping of the groundwater is essential to provide water for both drip and furrow irrigation to increase the agricultural yield, especially in arid regions that suffer from scarcities of surface water. The most common irrigation pumping systems (IPS) consume conventional energies through the use of electric motors and generators or connecting to the electricity grid. Due to the shortage and transportation difficulties of fossil fuels, and unreliable access to the electricity grid, especially in the rural areas, and the adverse environmental impacts of fossil fuel usage, such as greenhouse gas (GHG) emissions, the need for renewable energy sources such as photovoltaic systems (PVS) as an alternative way of powering irrigation pumping systems is urgent. Integration of the photovoltaic systems with irrigation pumping systems as the Photovoltaic Powered-Irrigation Pumping System (PVP-IPS) can avoid fossil fuel dependency and the subsequent greenhouse gas emissions, as well as ultimately lower energy costs and improve efficiency, which made PVP-IPS systems as an environmentally and economically efficient solution for agriculture irrigation in every region. The greatest problem faced by integration of PVP with IPS systems is matching the intermittence of the energy supply with the dynamic water demand. The best solution to overcome the intermittence is to incorporate a storage system into the PVP-IPS to provide water-on-demand as a highly reliable stand-alone irrigation pumping system. The water storage tank (WST) is the most common storage device for PVP-IPS systems. In the integrated PVP-IPS with a water storage tank (PVP-IPS-WST), a water storage tank stores the water pumped by the IPS in excess of the water demand and then delivers it when demands are high. The Freshwater pinch analysis (FWaPA) as an alternative to mathematical modeling was used by other researchers for retrofitting the off-grid battery less photovoltaic-powered reverse osmosis system. However, the Freshwater pinch analysis has not been used to integrate the photovoltaic systems with irrigation pumping system with water storage tanks. In this study, FWaPA graphical and numerical tools were used for retrofitting an existing PVP-IPS system located in Salahadin, Republic of Iraq. The plant includes a 5 kW submersible water pump and 7.5 kW solar PV system. The Freshwater Composite Curve as the graphical tool and Freashwater Storage Cascade Table as the numerical tool were constructed to determine the minimum required outsourced water during operation, optimal amount of delivered electricity to the water pump, and optimal size of the water storage tank for one-year operation data. The results of implementing the FWaPA on the case study show that the PVP-IPS system with a WST as the reliable system can reduce outsourced water by 95.41% compare to the PVP-IPS system without storage tank.

Keywords: irrigation, photovoltaic, pinch analysis, pumping, solar energy

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Authors: H. Nikzad, S. Yoshitomi

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This study investigates and develops the structural optimization method. The effect of size constraints on practical solution of reinforced concrete (RC) building structure with shear wall is proposed. Cross-sections of beam and column, and thickness of shear wall are considered as design variables. The objective function to be minimized is total cost of the structure by using a simple and efficient automated MATLAB platform structural optimization methodology. With modification of mathematical formulations, the result is compared with optimal solution without size constraints. The most suitable combination of section sizes is selected as for the final design application based on linear static analysis. The findings of this study show that defining higher value of upper bound of sectional sizes significantly affects optimal solution, and defining of size constraints play a vital role in finding of global and practical solution during optimization procedures. The result and effectiveness of proposed method confirm the ability and efficiency of optimal solutions for 3D RC shear wall-frame structure.

Keywords: structural optimization, linear static analysis, ETABS, MATLAB, RC shear wall-frame structures

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Authors: Evans Iyamu

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Genes encoding hydrophobins play distinct roles at different stages of the life cycle of fungi, and they foster hyphal attachment to surfaces. The hydrophobin Sc4 is known to provide a hydrophobic membrane lining of the gas channels within Schizophyllum commune fruiting bodies. Here, we cultivated non-fruiting, monokaryotic S. commune 12-43 on glass surfaces that could be verified by micrography. Differential gene expression profiling of nine hydrophobin genes and the hydrophobin-like sc15 gene by quantitative PCR showed significant up-regulation of sc4 when S. commune was attached to glass surfaces, also confirmed with RNA-Seq data analysis. Another silicate, namely quartz sand, was investigated, and induction of sc4 was seen as well. The up-regulation of the hydrophobin gene sc4 may indicate involvement in S. commune hyphal attachment to glass as well as quartz surfaces. We propose that the covering of hyphae by Sc4 allows for direct interaction with the hydrophobic surfaces of silicates and that differential functions of specific hydrophobin genes depend on the surface interface involved. This study could help with the clarification of the biological functions of hydrophobins in natural surroundings, including hydrophobic surface attachment. Therefore, the analysis of growth on glass serves as a basis for understanding S. commune interaction with glass surfaces while providing the possibility to visualize the interaction microscopically.

Keywords: hydrophobin, structured glass surfaces, differential gene expression, quartz sand

Procedia PDF Downloads 128

Authors: Vita Strazdina, Aleksandrs Jemeljanovs, Vita Sterna

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Not all proteins have the same nutritional value, since protein quality strongly depends on its amino acid composition and digestibility. The meat of game animals could be a high protein source because of its well-balanced essential amino acids composition. Investigations about biochemical composition of game meat such as wild boar (Sus scrofa scrofa), roe deer (Capreolus capreolus) and beaver (Castor fiber) are not very much. Therefore, the aim of the investigation was evaluate protein composition of game meat hunted in Latvia. The biochemical analysis, evaluation of connective tissue and essential amino acids in meat samples were done, the amino acids score were calculate. Results of analysis showed that protein content 20.88-22.05% of all types of meat samples is not different statistically. The content of connective tissue from 1.3% in roe deer till 1.5% in beaver meat allowed classified game animal as high quality meat. The sum of essential amino acids in game meat samples were determined 7.05–8.26g100g-1. Roe deer meat has highest protein content and lowest content of connective tissues among game meat hunted in Latvia. Concluded that amino acid score for limiting amino acids phenylalanine and tyrosine is high and shows high biological value of game meat.

Keywords: dietic product, game meat, amino acids, scores

Procedia PDF Downloads 326

Authors: Kimberly Samaha

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In order to attract new types of investors into the emerging Bio-Economy, new methodologies to analyze investment risk are needed. The Bio-Hub Ecosystem model was developed to address a critical area of concern within the global energy market regarding the use of biomass as a feedstock for power plants. This study looked at repurposing existing biomass-energy plants into Circular Zero-Waste Bio-Hub Ecosystems. A Bio-Hub model that first targets a ‘whole-tree’ approach and then looks at the circular economics of co-hosting diverse industries (wood processing, aquaculture, agriculture) in the vicinity of the Biomass Power Plants facilities. This study modeled the economics and risk strategies of cradle-to-cradle linkages to incorporate the value-chain effects on capital/operational expenditures and investment risk reductions using a proprietary techno-economic model that incorporates investment risk scenarios utilizing the Monte Carlo methodology. The study calculated the sequential increases in profitability for each additional co-host on an operating forestry-based biomass energy plant in West Enfield, Maine. Phase I starts with the base-line of forestry biomass to electricity only and was built up in stages to include co-hosts of a greenhouse and a land-based shrimp farm. Phase I incorporates CO2 and heat waste streams from the operating power plant in an analysis of lowering and stabilizing the operating costs of the agriculture and aquaculture co-hosts. Phase II analysis incorporated a jet-fuel biorefinery and its secondary slip-stream of biochar which would be developed into two additional bio-products: 1) A soil amendment compost for agriculture and 2) A biochar effluent filter for the aquaculture. The second part of the study applied the Monte Carlo risk methodology to illustrate how co-location derisks investment in an integrated Bio-Hub versus individual investments in stand-alone projects of energy, agriculture or aquaculture. The analyzed scenarios compared reductions in both Capital and Operating Expenditures, which stabilizes profits and reduces the investment risk associated with projects in energy, agriculture, and aquaculture. The major findings of this techno-economic modeling using the Monte Carlo technique resulted in the masterplan for the first Bio-Hub to be built in West Enfield, Maine. In 2018, the site was designated as an economic opportunity zone as part of a Federal Program, which allows for Capital Gains tax benefits for investments on the site. Bioenergy facilities are currently at a critical juncture where they have an opportunity to be repurposed into efficient, profitable and socially responsible investments, or be idled and scrapped. The Bio-hub Ecosystems techno-economic analysis model is a critical model to expedite new standards for investments in circular zero-waste projects. Profitable projects will expedite adoption and advance the critical transition from the current ‘take-make-dispose’ paradigm inherent in the energy, forestry and food industries to a more sustainable Bio-Economy paradigm that supports local and rural communities.

Keywords: bio-economy, investment risk, circular design, economic modelling

Procedia PDF Downloads 102

Authors: Youn Young Shim, Ji Hye Kim, Jae Youl Cho, Martin J. T. Reaney

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Flaxseed (Linum usitatissimum L.) is gaining popularity in the food industry as a superfood due to its health-promoting properties. The flax plant synthesizes an array of biologically active cyclic peptides or linusorbs (LOs, a.k.a. cyclolinopeptides) from three or more ribosome-derived precursors. [1–9-NαC]-linusorb B3 and [1–9-NαC]-linusorb B2, suppress immunity, induce apoptosis in human epithelial cancer cell line (Calu-3) cells, and inhibit T-cell proliferation, but the mechanism of LOs action is unknown. Using gene expression analysis in nematode cultures and human cancer cell lines, we have observed that LOs exert their activity, in part, through induction of apoptosis. Specific LOs’ properties include: 1) distribution throughout the body after flaxseed consumption; 2) induce heat shock protein (HSP) 70A production as an indicator of stress and address the issue in Caenorhabditis elegans (exposure of nematode cultures to [1–9-NαC]-linusorb B3 induced a 30% increase in production of the HSP 70A protein); 3) induce apoptosis in Calu-3 cells; and 4) modulate regulatory genes in microarray analysis. These diverse activities indicate that LOs might induce apoptosis in cancer cells or act as versatile platforms to deliver a variety of biologically active molecules for cancer therapy.

Keywords: flaxseed, linusorb, cyclic peptide, orbitides, heat shock protein, apoptosis, anti-cancer

Procedia PDF Downloads 139

Authors: Inna V. Krotova

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The study pays special attention to the definition of the psychological potential of a specialist-defectologist, which determines his desire to increase the level of his or her professional competence. The group included participants of the educational environment – an additional professional program 'Technologies of psychological and pedagogical assistance for children with complex developmental disabilities' implemented by the department of defectology and clinical psychology of the KFU jointly with the Support Fund for the Deafblind people 'Co-Unity'. The purpose of our study was to identify the psychological aspects of the readiness of the specialist-defectologist to his or her professional development. The study assessed the indicators of psychological preparedness, and its four components were taken into account: motivational, cognitive, emotional and volitional. We used valid and standardized tests during the study. As a result of the factor analysis of data received (from Extraction Method: Principal Component Analysis, Rotation Method: Varimax with Kaiser Normalization, Rotation converged in 12 iterations), there were identified three factors with maximum factor load from 24 indices, and their correlation coefficients with other indicators were taken into account at the level of reliability p ≤ 0.001 and p ≤ 0.01. Thus the system making factor was determined – it’s a 'motivation to achieve success'; it formed a correlation galaxy with two other factors: 'general internality' and 'internality in the field of achievements', as well as with such psychological indicators as 'internality in the field of family relations', 'internality in the field of interpersonal relations 'and 'low self-control-high self-control' (the names of the scales used is the same as names in the analysis methods. In conclusion of the article, we present some proposals to take into account the psychological model of readiness of specialists-defectologists for their professional development, to stimulate the growth of their professional competence. The study has practical value for all providers of special education and organizations that have their own specialists-defectologists, teachers-defectologists, teachers for correctional and ergotherapeutic activities, specialists working in the field of correctional-pedagogical activity (speech therapists) to people with special needs who need true professional support.

Keywords: psychological readiness, defectologist, professional development, psychological factors, special education, professional competence, innovative educational environment

Procedia PDF Downloads 175

Authors: Nazia Shehzad

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An icebreaker is a facilitation exercise intended to help a group to begin the process of forming themselves into a team. Icebreakers are commonly presented as a game to ‘warm up’ the group by helping the members to get to know each other. They often focus on sharing personal information such as names, hobbies, etc. Challenging icebreakers also have the ability to allow a group to be better prepared to complete its assigned tasks. For example, if the team's objective is to redesign a business process such as Accounts Payable, the icebreaker activity might take the team through a process analysis. The analysis could include the identification of failure points, challenging assumptions, and development of new solutions — all in a simpler and ‘safer’ setting where the team can practice the group dynamics which they will use to solve the assigned problem. Icebreakers help establish a positive environment and provide an opportunity for students to get to know one another and the instructor. Both are critical to the retention and success of students. There are a number of benefits of using ice-breakers activities in the classroom. It reduces both student and instructor anxiety prior to introducing the course, fosters in a powerful way both student-student and faculty-student interactions. It creates an environment where the learner is expected to participate and the instructor is willing to listen, actively engage students from the onset. It conveys the message that the instructor cares about getting to know the students and makes it easier for students to form relationships early in the semester so they can work together both in and out of class.

Keywords: actively engages students, facilitation exercise, faculty- student interactions, group dynamics, warm up

Procedia PDF Downloads 351

Authors: Misbah Khan, Jian Wen, Muhammad Asif Shakoori

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The Organic Rankine Cycle (ORC) plays an important role in converting low-temperature heat sources into electrical power by using refrigerants as working fluids. The thermophysical properties of working fluids are essential for designing ORC. HFO-1336mzz(Z) (cis-1,1,1,4,4,4-hexafluoro-2-butene) considered as working fluid and have almost 99% low GWP and relatively same thermophysical properties used as a replacement of HFC-245fa (1,1,1,3,3-pentafluoro-propane). The environmental, safety, healthy and thermophysical properties of HFO-1336mzz(Z) are needed to use it in a practical system. In this paper, Molecular dynamics simulations were used to investigate the Homogeneous condensation, thermophysical and structural properties of HFO-1336mzz(Z) and HFC-245fa. The effect of various temperatures and pressures on thermophysical properties and condensation was extensively investigated. The liquid densities and isobaric heat capacities of this refrigerant was simulated at 273.15K to 353.15K temperatures and pressure0.5-4.0MPa. The simulation outcomes were compared with experimental data to validate our simulation method. The mean square displacement for different temperatures was investigated for dynamical analysis. The variations in potential energies and condensation rate were simulated to get insight into the condensation process. The radial distribution function was simulated at the micro level for structural analysis and revealed that the phase transition of HFO-1336mzz(Z) did not affect the intramolecular structure.

Keywords: homogenous condensation, refrigerants, molecular dynamics simulations, organic rankine cycle

Procedia PDF Downloads 155

Authors: Sadia Rafiq, Md. Ashab Siddique Zaki, Ananya Roy

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Mountain cycling is a type of off-road bicycle racing that typically takes place on rocky, arid, or other challenging terrains on specially-made mountain cycles. Professional cyclists race while attempting to stay on their bikes in a variety of locales across the world. For safety measures in mountain cycling, as there we have a high chance of injury in case of tire puncture, it’s a preferable way to use an airless tire instead of a pneumatic tire. As airless tire does not tend to go flat, it needs to be replaced less frequently. The airless tire replaces the pneumatic tire, wheel, and tire system with a single unit. It consists of a stiff hub connected to a shear band by flexible, pliable spokes, which is made of poly-composite and a tread band, all of which work together as a single unit to replace all of the components of a normal radial tire. In this paper, an analysis of airless tires in the mountain cycle is shown along with structure and material study. We will be taking the Honeycomb and Diamond Structure of spokes to compare the deformation in both cases and choose our preferable structure. As we know, the tread and spokes deform with the surface roughness and impact. So, the tire tread thickness and the design of spokes can control how much the tire can distort. Through the simulation, we can come to the conclusion that the diamond structure deforms less than the honeycomb structure. So, the diamond structure is more preferable.

Keywords: airless tire, diamond structure, honeycomb structure, deformation

Procedia PDF Downloads 83

Authors: Behnam Zahednejad, Saeed Kosari

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Widespread deployment of Internet of Things (IoT) has raised security and privacy issues in this environment. Designing a secure two-factor authentication scheme between the user and server is still a challenging task. In this paper, we focus on Cancelable Biometric (CB) as an authentication factor in IoT. We show that previous CB-based scheme fail to provide real two-factor security, Perfect Forward Secrecy (PFS) and suffer database attacks and traceability of the user. Then we propose our improved scheme based on CB and Physically Unclonable Functions (PUF), which can provide real two-factor security, PFS, user’s unlinkability, and resistance to database attack. In addition, Key Compromise Impersonation (KCI) resilience is achieved in our scheme. We also prove the security of our proposed scheme formally using both Real-Or-Random (RoR) model and the ProVerif analysis tool. For the usability of our scheme, we conducted a performance analysis and showed that our scheme has the least communication cost compared to the previous CB-based scheme. The computational cost of our scheme is also acceptable for the IoT environment.

Keywords: IoT, two-factor security, cancelable biometric, key compromise impersonation resilience, perfect forward secrecy, database attack, real-or-random model, ProVerif

Procedia PDF Downloads 103

Authors: Anita Khadka, Gregory Epiphaniou, Carsten Maple

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There is a dramatic surge in the adoption of machine learning (ML) techniques in many areas, including the nuclear industry (such as fault diagnosis and fuel management in nuclear power plants), autonomous systems (including self-driving vehicles), space systems (space debris recovery, for example), medical surgery, network intrusion detection, malware detection, to name a few. With the application of learning methods in such diverse domains, artificial intelligence (AI) has become a part of everyday modern human life. To date, the predominant focus has been on developing underpinning ML algorithms that can improve accuracy, while factors such as resiliency and robustness of algorithms have been largely overlooked. If an adversarial attack is able to compromise the learning method or data, the consequences can be fatal, especially but not exclusively in safety-critical applications. In this paper, we present an in-depth analysis of five adversarial attacks and three defence methods on a crack detection ML model. Our analysis shows that it can be dangerous to adopt machine learning techniques in security-critical areas such as the nuclear industry without rigorous testing since they may be vulnerable to adversarial attacks. While common defence methods can effectively defend against different attacks, none of the three considered can provide protection against all five adversarial attacks analysed.

Keywords: adversarial machine learning, attacks, defences, nuclear industry, crack detection

Procedia PDF Downloads 160

Authors: Hatice Karakoyun, Mustafa Akdag

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This study has been made to examine the attitudes of pre-school teachers towards values education. The study has been made as a general scanning model. The study’s working group contains 108 pre-school teachers who worked in Diyarbakır, Turkey. In this study Values Education Attitude Scale (VEAS), which developed by Yaşaroğlu (2014), was used. In order to analyze the data for sociodemographic structure, percentage and frequency values were examined. The Kolmogorov-Smirnov method was used in determination of the normal distribution of data. During analyzing the data, KolmogorovSimirnov test and the normal curved histograms were examined to determine which statistical analyzes would be applied on the scale and it was found that the distribution was not normal. Thus, the Mann Whitney U analysis technique which is one of the nonparametric statistical analysis techniques were used to test the difference of the scores obtained from the scale in terms of independent variables. According to the analyses, it seems that pre-school teachers’ attitudes toward values education are positive. According to the scale with the highest average, it points out that pre-school teachers think that values education is very important for students’ and children’s future. The variables included in the scale (gender, seniority, age group, education, school type, school place) seem to have no effect on the pre-school teachers’ attitude grades which joined to the study.

Keywords: attitude scale, pedagogy, pre-school teacher, values education

Procedia PDF Downloads 249