Search results for: microwave component

Authors: Rajendra Kanojia

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Femoral components with inbuilt rotation require thicker flexion resection of the lateral femoral condyle and could potential risk to damage the popliteus tendon especially in the smaller Asian knees. We prospectively evaluated 10 patients with bilateral varus osteoarthritis knee to size the cuts and their location in relation to the popliteus tendon. Two different types of implant were used on either side, one side requires resection in 3° external rotation (group A) and other side femoral component with inbuilt external roation (group B). We had popliteus tendon injury in 3 knees all from group B. Risk of damaging the popliteus tendon was found higher in group B.

Keywords: popliteaus tendon injury, TKA, orthopaedic surgery, biomechanics and clinical applications

Procedia PDF Downloads 336

Authors: George Oliveira, Luana D. Fronza, Luiza Medeiros, Patricia D. M. Plentz

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The research presented in this article is part of a wide project that proposes a scheduling system for multi-robots in intelligent warehouses employing multi-robot path-planning (MPP) and multi-robot task allocation (MRTA) to reconcile multiple restrictions (task delivery time, task priorities, charging capacity, and robots battery capacity). We present the software component capable of interconnecting an open streaming processing architecture and robot operating system (ROS), ensuring communication and message exchange between robots and the environment in which they are inserted. Simulation results show the good performance of our proposed technique for connecting ROS and streaming platforms.

Keywords: complex distributed systems, mobile robots, smart warehouses, streaming platforms

Procedia PDF Downloads 194

Authors: Jasmina Pluncevic Gligoroska, Sanja Manchevska, Vaska Antevska, Lidija Todorovska, Beti Dejanova, Sunchica Petrovska, Ivanka Karagjozova, Elizabeta Sivevska

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Introduction: Anthropometric measurements are integral part of regular medical examinations of athletes. In addition to the quantification of the size of the body, these measurements indicate the quality of the physical status, because of its association with sports performance. The purpose of this study was to examine whether there are differences in anthropometric parameters and body mass components in female athletes who participate in two different types of sports. Methods: A total of 27 athletes, 15 handball players and 12 basketball players, at the average age of 22.7 years (age span from 17 to 30 years) entered the study. Anthropometric method by Matiegka was used for determination of body components. Sixteen anthropometric measures were taken: height, weight, four diameters of joints, four circumferences of limbs and six skin folds. Results: Handball players were 169.6±6.7 cm tall and 63,75±7.5 kg heavy. Their average relative muscle mass (absolute mass in kg) was 51% (32.5kg), while bone component was 16.8% (10.7kg) and fat component was 14.3% (7.74kg). The basketball players were 177.4±8.2cm tall and 70.37±12.1kg heavy. Their average relative muscle mass (absolute mass in kg) was 51.9 % (36.6kg), bone component was 16.37% (11.5kg) and fat component was 15.36% (9.4kg). The comparison of anthropometric values showed that basketball players were statistically significantly higher and heavier than handball players (p<0.05). Statistically significant difference (p<0.05) was observed in the range of upper leg circumference (higher in basketball players) and the forearm skin fold (higher in the basketball players). Conclusion: Handball players and basketball players significantly differed in basic anthropometric measures (height and weight), but the body components had almost identical values. The anthropometric measurements that have been taken did not show significant difference between handball and basketball female players despite the different physical demands of the games.

Keywords: anthropometry, body components, basketball, handball female players

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Authors: Dennis Okora Amima Ondieki

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Fertility transition has been identified to be affected by numerous factors. This research aimed to investigate the most real factors affecting fertility transition in Kenya. These factors were firstly extracted from the literature convened into demographic features, social, and economic features, social-cultural features, reproductive features and modernization features. All these factors had 23 factors identified for this study. The data for this study was from the Kenya Demographic and Health Surveys (KDHS) conducted in 1999-2003 and 2003-2008/9. The data was continuous, and it involved the mean birth order for the ten periods. Principal component analysis (PCA) was utilized using 23 factors. Principal component analysis conveyed religion, region, education and marital status as the real factors. PC scores were calculated for every point. The identified principal components were utilized as forecasters in the multiple regression model, with the fertility level as the response variable. The four components were found to be affecting fertility transition differently. It was found that fertility is affected positively by factors of region and marital and negatively by factors of religion and education. These four factors can be considered in the planning policy in Kenya and Africa at large.

Keywords: fertility transition, principal component analysis, Kenya demographic health survey, birth order

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Authors: Chang-Fa Liu, Yi-Ting Wang, Yuan Liu, Hai-Feng Wei, Lei Fang, Jin Li

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Heavy metals in sediments can cause adverse ecological effects while it exceeds a given criteria. The present study investigated sediment environmental quality, pollutant enrichment, ecological risk, and source identification for copper, cadmium, lead, zinc, mercury, and arsenic in the sediments collected from tidal flat marsh of Shuangtai estuary, China. The arithmetic mean integrated pollution index, geometric mean integrated pollution index, fuzzy integrated pollution index, and principal component score were used to characterize sediment environmental quality; fuzzy similarity and geo-accumulation Index were used to evaluate pollutant enrichment; correlation matrix, principal component analysis, and cluster analysis were used to identify source of pollution; environmental risk index and potential ecological risk index were used to assess ecological risk. The environmental qualities of sediment are classified to very low degree of contamination or low contamination. The similar order to element background of soil in the Liaohe plain is region of Sanjiaozhou, Honghaitan, Sandaogou, Xiaohe by pollutant enrichment analysis. The source identification indicates that correlations are significantly among metals except between copper and cadmium. Cadmium, lead, zinc, mercury, and arsenic will be clustered in the same clustering as the first principal component. Copper will be clustered as second principal component. The environmental risk assessment level will be scaled to no risk in the studied area. The order of potential ecological risk is As > Cd > Hg > Cu > Pb > Zn.

Keywords: ecological risk assessment, heavy metals, sediment, marsh, Shuangtai estuary

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Authors: Izadpanh Shaghayegh, Adli Fateme

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Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by motor symptoms, including tremors, bradykinesia, rigidity, and freezing of gait (FOG), which arise from degeneration of the basal ganglia. While pharmacological treatments, particularly dopaminergic therapies, remain the primary approach for managing PD, their long-term effectiveness diminishes due to complications such as dyskinesia and motor fluctuations. Deep brain stimulation (DBS) has emerged as an alternative for symptom management but remains invasive, costly, and associated with significant risks. In light of these challenges, non-invasive brain stimulation (NIBS) techniques are gaining attention as promising alternatives for treating PD. These methods, including transcranial magnetic stimulation (TMS), transcranial direct current stimulation (tDCS), and microwave brain stimulation (MBS), offer advantages such as reduced risk and non-invasiveness while providing targeted modulation of brain activity. Recent innovations, such as hemispherical antenna arrays for focused stimulation and advanced signal patterns like high-frequency prime harmonics and temporal interference (TI), have further enhanced the precision and efficacy of NIBS. These techniques have shown potential in modulating neuronal excitability, improving gait, and reducing motor symptoms in PD patients, with some approaches demonstrating effectiveness in treating FOG. Despite promising results, continued research is necessary to refine these technologies, optimize treatment protocols, and evaluate their long-term impact on PD progression. This review highlights recent advances in non-invasive brain stimulation for PD and discusses their potential as adjunctive therapies for managing motor symptoms and improving quality of life in PD patients.

Keywords: Parkinson’s disease, non-invasive brain stimulation, deep brain stimulation, transcranial magnetic stimulation, transcranial direct current stimulation, freezing of gait, microwave brain stimulation, neuromodulation

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Authors: Dangut Maren David, Skaf Zakwan

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Adequate monitoring of vehicle component in other to obtain high uptime is the goal of predictive maintenance, the major challenge faced by businesses in industries is the significant cost associated with a delay in service delivery due to system downtime. Most of those businesses are interested in predicting those problems and proactively prevent them in advance before it occurs, which is the core advantage of Prognostic Health Management (PHM) application. The recent emergence of industry 4.0 or industrial internet of things (IIoT) has led to the need for monitoring systems activities and enhancing system-to-system or component-to- component interactions, this has resulted to a large generation of data known as big data. Analysis of big data represents an increasingly important, however, due to complexity inherently in the dataset such as imbalance classification problems, it becomes extremely difficult to build a model with accurate high precision. Data-driven predictive modeling for condition-based maintenance (CBM) has recently drowned research interest with growing attention to both academics and industries. The large data generated from industrial process inherently comes with a different degree of complexity which posed a challenge for analytics. Thus, imbalance classification problem exists perversely in industrial datasets which can affect the performance of learning algorithms yielding to poor classifier accuracy in model development. Misclassification of faults can result in unplanned breakdown leading economic loss. In this paper, an advanced approach for handling imbalance classification problem is proposed and then a prognostic model for predicting aircraft component replacement is developed to predict component replacement in advanced by exploring aircraft historical data, the approached is based on hybrid ensemble-based method which improves the prediction of the minority class during learning, we also investigate the impact of our approach on multiclass imbalance problem. We validate the feasibility and effectiveness in terms of the performance of our approach using real-world aircraft operation and maintenance datasets, which spans over 7 years. Our approach shows better performance compared to other similar approaches. We also validate our approach strength for handling multiclass imbalanced dataset, our results also show good performance compared to other based classifiers.

Keywords: prognostics, data-driven, imbalance classification, deep learning

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Authors: Yamini Raju, Parminder S. Kang, Adam Moroz, Ross Clement, Alistair Duffy, Ashley Hopwell

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Accurate prediction of fresh produce demand is one the challenges faced by Small Medium Enterprise (SME) wholesalers. Current research in this area focused on limited number of factors specific to a single product or a business type. This paper gives an overview of the current literature on the variability factors used to predict demand and the existing forecasting techniques of short shelf life products. It then extends it by adding new factors and investigating if there is a time lag and possibility of noise in the orders. It also identifies the most important factors using correlation and Principal Component Analysis (PCA).

Keywords: demand forecasting, deteriorating products, food wholesalers, principal component analysis, variability factors

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Authors: Obafemi Akinwotu, Aylin Tas, Tony Taylor, Bukola Onarinde

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The study was conducted to explore the methods and tools to improve texture and preserve the total phenolic and antioxidant compounds of dysphagia foods produced from carrot-based puree with decolourised Chlorella algae. Textural properties (Texture profile analysis [TPA]; the International Dysphagia Diet Standardization Initiative, particle size test [PST]) and rheological properties (viscosity and viscoelastic properties) of carrot puree defrosted by different treatments (microwave, steamer, oven), were characterised using hydrocolloids (guar gum, k. carrageenan, and xanthan gum), and the results were compared to a level 4 commercial sample. DPPH (2,2-diphenyl-1-picrylhydrazyl) antiradical scavenging radicals and total phenolic contents were employed to evaluate the total phenolics, and radical scavenging properties of defrosted carrot puree sonicated carrot puree (20 Hz, 30 min, 60 oC), and vacuum-dried carrot powder with the addition of algae. Results show that the viscosity, viscoelasticity test, TPA, and PST of the commercial sample were comparable to those of guar gum and xanthan gum containing puree, suggesting that they could be used as dysphagia diets. There was no noticeable decolourisation of the Chlorella pigment. Additionally, the use of the microwave, stemmer, and oven for defrosting treatment had an impact on the textural characteristics of the moulded samples upon cooling and also contributed to the reduction in the total phenolic and antioxidant properties of the samples. Sonication treatments of algae exposure reduced the cloudiness of the green pigment and lightened the colour of the samples containing algae, and they also reduced the drying time from 2.5 to 1.5 hours during the preliminary work. The low-temperature vacuum- and freeze-dried samples increased the concentration of the powder and resulted in an increase in the total phenolic content of the dry samples. The dried products may therefore have the potential to become more nutrient-dense to benefit the health of individuals with dysphagia.

Keywords: dysphagia, elderly, hydrocolloids, carrot puree

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Authors: Piotr-Robert Lazik, Lena Teichmann, Harald Garrecht

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Many concrete technologists are looking for a solution to replace fly ashes as a component that occurs as a major component of many types of concrete. The importance of such a component is clear -it saves cement and reduces the amount of CO₂ in the atmosphere that occurs during cement production. For example, the amount of cement in ultrahigh strength concrete (UHPC) is approximately 700-800 kg/m³ in normal concrete up to 350 kg/m³. For this reason, it is easy to follow that the use of components like fly ashes or wood ashes protect the environment. The newest investigations carried out at the University of Stuttgart have clearly shown that the use of wood ashes with appropriate pre-treatment in concrete has a positive effect. German-wide, there are hundreds of tons of wood ashes, which can be used in a wide range of construction materials. The strengths of the concrete with different types of cement and with wood ashes have given the same or, in some cases, better results than those with the use of fly ashes. There are many areas in building construction, where the clays of wood ashes can be used as a by-product. This does not only require a strength test but also, for example, an examination of structural-physical parameters. Especially the heat and moisture characteristics have an important role in times of energy-efficient construction. These are therefore determined and then compared with the characteristics of the concretes with fly ashes. The University of Stuttgart has decided to investigate the buildings' physical properties of different types of concrete with wood ashes to find their application in construction. After the examination of the buildings' physical properties in combination with strength tests, it is possible to determine in which field of civil engineering, this type of concrete can be used.

Keywords: fly ashes, wood ashes, structural-physical parameters, UHPC

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Authors: Saoussen Dhib, Chris M. Mannaerts, Zoubeida Bargaoui, Ben H. P. Maathuis, Petra Budde

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In this study, a new method to delineate rain areas in northern Tunisia is presented. The proposed approach is based on the blending of the geostationary Meteosat Second Generation (MSG) infrared channel (IR) with the low-earth orbiting passive Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). To blend this two products, we need to apply two main steps. Firstly, we have to identify the rainy pixels. This step is achieved based on a classification using MSG channel IR 10.8 and the water vapor WV 0.62, applying a threshold on the temperature difference of less than 11 Kelvin which is an approximation of the clouds that have a high likelihood of precipitation. The second step consists on fitting the relation between IR cloud top temperature with the TMI rain rates. The correlation coefficient of these two variables has a negative tendency, meaning that with decreasing temperature there is an increase in rainfall intensity. The fitting equation will be applied for the whole day of MSG 15 minutes interval images which will be summed. To validate this combined product, daily extreme rainfall events occurred during the period 2007-2009 were selected, using a threshold criterion for large rainfall depth (> 50 mm/day) occurring at least at one rainfall station. Inverse distance interpolation method was applied to generate rainfall maps for the drier summer season (from May to October) and the wet winter season (from November to April). The evaluation results of the estimated rainfall combining MSG and TMI was very encouraging where all the events were detected rainy and the correlation coefficients were much better than previous evaluated products over the study area such as MSGMPE and PERSIANN products. The combined product showed a better performance during wet season. We notice also an overestimation of the maximal estimated rain for many events.

Keywords: combination, extreme, rainfall, TMI-MSG, Tunisia

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Authors: N. K. Caecar Pratiwi, Yunendah Nur Fuadah, Rita Magdalena, R. D. Atmaja, Sofia Saidah, Ocky Tiaramukti

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Colon cancer or colorectal cancer is a type of cancer that attacks the last part of the human digestive system. Lymphoma and carcinoma are types of cancer that attack human’s colon. Colon cancer causes deaths about half a million people every year. In Indonesia, colon cancer is the third largest cancer case for women and second in men. Unhealthy lifestyles such as minimum consumption of fiber, rarely exercising and lack of awareness for early detection are factors that cause high cases of colon cancer. The aim of this project is to produce a system that can detect and classify images into type of colon cancer lymphoma, carcinoma, or normal. The designed system used 198 data colon cancer tissue pathology, consist of 66 images for Lymphoma cancer, 66 images for carcinoma cancer and 66 for normal / healthy colon condition. This system will classify colon cancer starting from image preprocessing, feature extraction using Principal Component Analysis (PCA) and classification using K-Nearest Neighbor (K-NN) method. Several stages in preprocessing are resize, convert RGB image to grayscale, edge detection and last, histogram equalization. Tests will be done by trying some K-NN input parameter setting. The result of this project is an image processing system that can detect and classify the type of colon cancer with high accuracy and low computation time.

Keywords: carcinoma, colorectal cancer, k-nearest neighbor, lymphoma, principle component analysis

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Authors: Yue Yan, Chang Nyung Kim

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The numerical investigation of the three-dimensional liquid-metal (LM) magnetohydrodynamic (MHD) flows in a curved duct with flow channel insert (FCI) is presented in this paper, based on the computational fluid dynamics (CFD) method. A uniform magnetic field is applied perpendicular to the duct. The interdependency of the flow variables is examined in terms of the flow velocity, current density, electric potential and pressure. The electromagnetic characteristics of the LM MHD flows are reviewed with an introduction of the electric-field component and electro-motive component of the current. The influence of the existence of the FCI on the fluid flow is investigated in detail. The case with FCI slit located near the side layer yields smaller pressure gradient with stable flow field.

Keywords: curved duct, flow channel insert, liquid-metal, magnetohydrodynamic

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Authors: Bin Mu, Site Li, Shijin Yuan

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Under the circumstance of environment deterioration, people are increasingly concerned about the quality of the environment, especially air quality. As a result, it is of great value to give accurate and timely forecast of AQI (air quality index). In order to simplify influencing factors of air quality in a city, and forecast the city’s AQI tomorrow, this study used MATLAB software and adopted the method of constructing a mathematic model of PCA-GABP to provide a solution. To be specific, this study firstly made principal component analysis (PCA) of influencing factors of AQI tomorrow including aspects of weather, industry waste gas and IAQI data today. Then, we used the back propagation neural network model (BP), which is optimized by genetic algorithm (GA), to give forecast of AQI tomorrow. In order to verify validity and accuracy of PCA-GABP model’s forecast capability. The study uses two statistical indices to evaluate AQI forecast results (normalized mean square error and fractional bias). Eventually, this study reduces mean square error by optimizing individual gene structure in genetic algorithm and adjusting the parameters of back propagation model. To conclude, the performance of the model to forecast AQI is comparatively convincing and the model is expected to take positive effect in AQI forecast in the future.

Keywords: AQI forecast, principal component analysis, genetic algorithm, back propagation neural network model

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Authors: Andra Costache, Rădiţa Alexe

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The analysis of the spatial disparities of social marginalization is a requirement in the present-day socio-economic and political context of Romania, an East-European state, member of the European Union since 2007, at present faced with the imperatives of the growth of its territorial cohesion. The main objective of this article is to develop a methodology for the assessment of social marginalization, in order to understand the intensity of the marginalization phenomenon at different spatial scales. The article proposes a social marginalization index (SMI), calculated through the integration of ten indicators relevant for the two components of social marginalization: the material component and the symbolical component. The results highlighted a strong connection between the total degree of social marginalization and the dependence on social benefits, unemployment rate, non-inclusion in the compulsory education, criminality rate, and the type of pension insurance.

Keywords: Romania, social marginalization index, territorial disparities, EU

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Authors: Rasha S. Kamal, Nehal S. Ahmed, Amal M. Nassar, Nour E. A. Abd El-Sattar

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In the present work, some lube oil antioxidants based on ester of some aromatic thiourea derivative were prepared by two steps: the first step is the reaction of succinyl chloride with ammonium thiocyanate in addition to anthranilic acid as three component system to prepare thiourea derivative (A); the second step is esterification of compound (A) by different alcohol (decyl C₁₀, tetradecyl C₁₄, and octadecyl C₁₈) alcohol. The structures of the prepared compounds were confirmed by infra-red spectroscopy, nuclear magnetic resonance, elemental analysis and determination of the molecular weights. All the prepared compounds were soluble in lube oil. The efficiency of the prepared compounds as antioxidants lube oil additives was investigated and it was found that these prepared compounds give good result as lube oil antioxidant.

Keywords: antioxidant lube oil, three component system, aromatic thiourea derivatives, esterification

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Authors: Ashfaque Hossain Khan, Brian Thomson, Ratan Debnath, Abhishek Motayed, Mulpuri V. Rao

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Though the efforts had been made, the problem of cross-sensitivity for a single metal oxide-based sensor can’t be fully eliminated. In this work, a sensor array has been designed and fabricated comprising of platinum (Pt), copper (Cu), and silver (Ag) decorated TiO2 and ZnO functionalized GaN nanowires using industry-standard top-down fabrication approach. The metal/metal-oxide combinations within the array have been determined from prior molecular simulation study using first principle calculations based on density functional theory (DFT). The gas responses were obtained for both single and mixture of NO2, SO2, ethanol, and H2 in the presence of H2O and O2 gases under UV light at room temperature. Each gas leaves a unique response footprint across the array sensors by which precise discrimination of cross-sensitive gases has been achieved. An unsupervised principal component analysis (PCA) technique has been implemented on the array response. Results indicate that each gas forms a distinct cluster in the score plot for all the target gases and their mixtures, indicating a clear separation among them. In addition, the developed array device consumes very low power because of ultra-violet (UV) assisted sensing as compared to commercially available metal-oxide sensors. The nanowire sensor array, in combination with PCA, is a potential approach for precise real-time gas monitoring applications.

Keywords: cross-sensitivity, gas sensor, principle component analysis (PCA), sensor array

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Authors: Morar (Bumbu) Nicoleta Ileana

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Located in the northeastern part of Romania in a cross-border area, Bucovina region, due to historical events that took place here, is characterized by the cohabitation in the same area of a significant number of ethnic communities, represented in 54% by rural population. In addition to providing the natural, economic history and decision makers, the demographic component is responsible for the region's development trajectory to which it belongs. The influence that people exert on rural development is shown by the values of the different demographic indicator. This study will analyze the demographic indicators obtained against a strong database, emphasizing the indicators that favor the rural development of the region and those that prevent it. The study is useful in defining the rightful directions that rural economic development can focus on, also representing an important tool in developing strategies for the development of rural settlements of Bucovina region.

Keywords: Bucovina, development directions, demographic indicators, rural development

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Authors: Damian Gordon, Paul Doyle, Anna Becevel, Tina Baloh

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The goal of this research is to explore the evolution of the concept of “blended learning” over a twenty-year period, to see whether or not the conceptualization has remained consistent or if it has become either more specific or more general. To achieve this goal, the term “blended learning” (and variations) was searched for in various bibliographical repositories for each year 2003-2022 to locate a highly cited paper that is not behind a paywall, to locate unique definitions that would be freely available to all academics each year. Each of the twenty unique definitions is explored to identify how they categorize both the Classroom Component and the Computer Component of blended learning, as well as identify which discipline each definition originates from and which country it comes from to see if there are any significant geographical variations. Based on this analysis, trends that appear in the definitions are noted, as well as an overall interpretation of the notion of “Blended Learning.”

Keywords: blended learning, definitions of blended learning, e-learning, thematic searches

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Authors: Etienne Gaborit, Dorothy Durnford, Daniel Deacu, Marco Carrera, Nathalie Gauthier, Camille Garnaud, Vincent Fortin

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A new experimental streamflow forecasting system was recently implemented at the Environment and Climate Change Canada’s (ECCC) Canadian Centre for Meteorological and Environmental Prediction (CCMEP). It relies on CaLDAS (Canadian Land Data Assimilation System) for the assimilation of surface variables, and on a surface prediction system that feeds a routing component. The surface energy and water budgets are simulated with the SVS (Soil, Vegetation, and Snow) Land-Surface Scheme (LSS) at 2.5-km grid spacing over Canada. The routing component is based on the Watroute routing scheme at 1-km grid spacing for the Great Lakes and Nelson River watersheds. The system is run in two distinct phases: an analysis part and a forecast part. During the analysis part, CaLDAS outputs are used to force the routing system, which performs streamflow assimilation. In forecast mode, the surface component is forced with the Canadian GEM atmospheric forecasts and is initialized with a CaLDAS analysis. Streamflow performances of this new system are presented over 2019. Performances are compared to the current ECCC’s operational streamflow forecasting system, which is different from the new experimental system in many aspects. These new streamflow forecasts are also compared to persistence. Overall, the new streamflow forecasting system presents promising results, highlighting the need for an elaborated assimilation phase before performing the forecasts. However, the system is still experimental and is continuously being improved. Some major recent improvements are presented here and include, for example, the assimilation of snow cover data from remote sensing, a backward propagation of assimilated flow observations, a new numerical scheme for the routing component, and a new reservoir model.

Keywords: assimilation system, distributed physical model, offline hydro-meteorological chain, short-term streamflow forecasts

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Authors: Siavash Mirahmadizoghi, Steven Bell, David Simpson

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In this work a new independent component analysis (ICA) based method for noise reduction in evoked potentials is evaluated on for auditory late responses (ALR) captured with a 63-channel electroencephalogram (EEG) from 10 normal-hearing subjects. The performance of the new method is compared with a single channel alternative in terms of signal to noise ratio (SNR), the number of channels with an SNR above an empirically derived statistical critical value and an estimate of the effect of attention on the major components in the ALR waveform. The results show that the multichannel signal processing method can significantly enhance the quality of the ALR signal and also detect the effect of the attention on the ALR better than the single channel alternative.

Keywords: auditory late response (ALR), attention, EEG, independent component analysis (ICA), multichannel signal processing

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Authors: Kirill Filianin, Satu-Pia Reinikainen, Tuomo Sainio

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Frequent measurements of product steam quality create a data overload that becomes more and more difficult to handle. In the current study, plant history data with multiple variables was successfully treated by principal component analysis to detect abnormal process behavior, particularly, in copper solvent extraction. The multivariate model is based on the concentration levels of main process metals recorded by the industrial on-stream x-ray fluorescence analyzer. After mean-centering and normalization of concentration data set, two-dimensional multivariate model under principal component analysis algorithm was constructed. Normal operating conditions were defined through control limits that were assigned to squared score values on x-axis and to residual values on y-axis. 80 percent of the data set were taken as the training set and the multivariate model was tested with the remaining 20 percent of data. Model testing showed successful application of control limits to detect abnormal behavior of copper solvent extraction process as early warnings. Compared to the conventional techniques of analyzing one variable at a time, the proposed model allows to detect on-line a process failure using information from all process variables simultaneously. Complex industrial equipment combined with advanced mathematical tools may be used for on-line monitoring both of process streams’ composition and final product quality. Defining normal operating conditions of the process supports reliable decision making in a process control room. Thus, industrial x-ray fluorescence analyzers equipped with integrated data processing toolbox allows more flexibility in copper plant operation. The additional multivariate process control and monitoring procedures are recommended to apply separately for the major components and for the impurities. Principal component analysis may be utilized not only in control of major elements’ content in process streams, but also for continuous monitoring of plant feed. The proposed approach has a potential in on-line instrumentation providing fast, robust and cheap application with automation abilities.

Keywords: abnormal process behavior, failure detection, principal component analysis, solvent extraction

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Authors: Attila Vámosi, Tamás Mankovits, Dávid Huri, Imre Kocsis, Tamás Szabó

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Non-linear FEM calculations are indispensable when important technical information like operating performance of a rubber component is desired. Rubber bumpers built into air-spring structures may undergo large deformations under load, which in itself shows non-linear behavior. The changing contact range between the parts and the incompressibility of the rubber increases this non-linear behavior further. The material characterization of an elastomeric component is also a demanding engineering task. The shape optimization problem of rubber parts led to the study of FEM based calculation processes. This type of problems was posed and investigated by several authors. In this paper the time demand of certain calculation methods are studied and the possibilities of time reduction is presented.

Keywords: rubber bumper, data acquisition, finite element analysis, support vector regression

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Authors: Kamran Siddique, Hiroyuki Asada, Yoshifumi Ogami

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Micro gas turbine (MGT) nowadays has a wide variety of applications from drones to hybrid electric vehicles. As microfabrication technology getting better, the size of MGT is getting smaller. Overall performance of MGT is dependent on the individual components. Each component’s performance is dependent and interrelated with another component. Therefore, careful consideration needs to be given to each and every individual component of MGT. In this study, the focus is on improving the performance of the compressor in order to improve the overall performance of MGT. Computational Fluid Dynamics (CFD) is being performed using the software FLUENT to analyze the design of a micro compressor. Operating parameters like mass flow rate and RPM, and design parameters like inner blade angle (IBA), outer blade angle (OBA), blade thickness and number of blades are varied to study its effect on the performance of the compressor. Pressure ratio is used as a tool to measure the performance of the compressor. Higher the pressure ratio, better the design is. In the study, target mass flow rate is 0.2 g/s and RPM to be less than or equal to 900,000. So far, a pressure ratio of above 3 has been achieved at 0.2 g/s mass flow rate with 5 rotor blades, 0.36 mm blade thickness, 94.25 degrees OBA and 10.46 degrees IBA. The design in this study differs from a regular centrifugal compressor used in conventional gas turbines such that compressor is designed keeping in mind ease of manufacturability. So, this study proposes a compressor design which has a good pressure ratio, and at the same time, it is easy to manufacture using current microfabrication technologies.

Keywords: computational fluid dynamics, FLUENT microfabrication, RPM

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Authors: Bouchra Nadji, Elaid Bouchetob

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PV systems are common in residential and industrial settings because of their low, upfront costs and operating costs throughout their lifetimes. Buck or boost converters are used in photovoltaic systems, regardless of whether the system is autonomous or connected to the grid. These converters became less appealing because of their low efficiency, inadequate power density, and use of silicon for their power components. Traditional devices based on Si are getting close to reaching their theoretical performance limits, which makes it more challenging to improve the performance and efficiency of these devices. GaN and SiC are the two types of WBG semiconductors with the most recent technological advancements and are available. Tolerance to high temperatures and switching frequencies can reduce active and passive component size. Utilizing high-efficiency dc-dc boost converters is the primary emphasis of this work. These converters are for photovoltaic systems that use wave energy.

Keywords: component, Artificial intelligence, PV System, ANN MPPT, DC-DC converter

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Authors: Abdelhak-Djamel Seriai, Selim Kebir, Allaoua Chaoui

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During the last decades, object oriented program- ming has been massively used to build large-scale systems. However, evolution and maintenance of such systems become a laborious task because of the lack of object oriented programming to offer a precise view of the functional building blocks of the system. This lack is caused by the fine granularity of classes and objects. In this paper, we use a post object-oriented technology namely software components, to propose an approach based on the identification of the functional building blocks of an object oriented system by analyzing its source code. These functional blocks are specified as software components and the result is a multi-layer component based software architecture.

Keywords: software comprehension, software component, object oriented, software architecture, reverse engineering

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Authors: Anjushi Verma, Tirthankar Gayen

Abstract:

Although, reliability is an important attribute of quality, especially for mission critical systems, yet, there does not exist any versatile model even today for the reliability assessment of component-based software. The existing Black Box models are found to make various assumptions which may not always be realistic and may be quite contrary to the actual behaviour of software. They focus on observing the manner in which the system behaves without considering the structure of the system, the components composing the system, their interconnections, dependencies, usage frequencies, etc.As a result, the entropy (uncertainty) in assessment using these models is much high.Though, there are some models based on operation profile yet sometimes it becomes extremely difficult to obtain the exact operation profile concerned with a given operation. This paper discusses the drawbacks, deficiencies and limitations of Black Box approaches from the perspective of various authors and finally proposes a conceptual model for the reliability assessment of software.

Keywords: black box, faults, failure, software reliability

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Authors: Krasimir Ivanov, Elitsa Kolentsova, Dimitar Dimitrov

Abstract:

The development of active and stable catalysts without noble metals for low temperature oxidation of exhaust gases remains a significant challenge. The purpose of this study is to determine the influence of the preparation method on the catalytic activity of the supported copper-manganese mixed oxides in terms of VOCs oxidation. The catalysts were prepared by impregnation of γ-Al2O3 with copper and manganese nitrates and acetates and the possibilities for CO, CH3OH and dimethyl ether (DME) oxidation were evaluated using continuous flow equipment with a four-channel isothermal stainless steel reactor. Effect of the support, Cu/Mn mole ratio, heat treatment of the precursor and active component loading were investigated. Highly active alumina supported Cu-Mn catalysts for CO and VOCs oxidation were synthesized. The effect of preparation conditions on the activity behavior of the catalysts was discussed. The synergetic interaction between copper and manganese species increases the activity for complete oxidation over mixed catalysts. Type of support, calcination temperature and active component loading along with catalyst composition are important factors, determining catalytic activity. Cu/Mn molar ratio of 1:5, heat treatment at 450oC and 20 % active component loading are the best compromise for production of active catalyst for simultaneous combustion of CO, CH3OH and DME.

Keywords: copper-manganese catalysts, CO, VOCs oxidation, exhaust gases

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Authors: Elmabruk Laias, Abdalla M. Hanashi, Mohammed Alnas

Abstract:

Worldwide Interoperability for Microwave Access (WiMAX) became one of the most challenging issues, since it was responsible for distributing available resources of the network among all users this leaded to the demand of constructing and designing high efficient scheduling algorithms in order to improve the network utilization, to increase the network throughput, and to minimize the end-to-end delay. In this study, the proposed algorithm focuses on an efficient mechanism to serve non-real time traffic in congested networks by considering channel status.

Keywords: WiMAX, Quality of Services (QoS), OPNE, Diff-Serv (DS).

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Authors: Anna S. Tolkacheva, Sergey N. Shkerin, Kirill G. Zemlyanoi, Olga G. Reznitskikh, Pavel D. Khavlyuk

Abstract:

Calcium oxovanadates with garnet related structure are multifunctional oxides in various fields like photoluminescence, microwave dielectrics, and magneto-dielectrics. For example, vanadate garnets are self-luminescent compounds. They attract attention as RE-free broadband excitation and emission phosphors and are candidate materials for UV-based white light-emitting diodes (WLEDs). Ca₅M₄(VO₄)₆ (M = Mg, Zn, Co, Ni, Mn) compounds are also considered promising for application in microwave devices as substrate materials. However, the relation between their structure, composition and physical/chemical properties remains unclear. Given the above-listed observations, goals of this study are to synthesise Ca₅M₄(VO₄)₆ (M = Mg, Zn, Ni) and to study their thermal and electrical properties. Solid solutions Ca₅Mg₄₋ₓMₓ(VO₄)₆ (0 ≤ x ≤ 4) where M is Zn and Ni have been synthesized by sol-gel method. The single-phase character of the final products was checked by powder X-ray diffraction on a Rigaku D/MAX-2200 X-ray diffractometer using Cu Kα radiation in the 2θ range from 15° to 70°. The dependence of thermal properties on chemical composition of solid solutions was studied using simultaneous thermal analyses (DSC and TG). Thermal analyses were conducted in a Netzch simultaneous analyser STA 449C Jupiter, in Ar atmosphere, in temperature range from 25 to 1100°C heat rate was 10 K·min⁻¹. Coefficients of thermal expansion (CTE) were obtained by dilatometry measurements in air up to 800°C using a Netzsch 402PC dilatometer; heat rate was 1 K·min⁻¹. Impedance spectra were obtained via the two-probe technique with an impedance meter Parstat 2273 in air up to 700°C with the variation of pH₂O from 0.04 to 3.35 kPa. Cation deficiency in Ca and Mg sublattice under the substitution of MgO with ZnO up to 1/6 was observed using Rietveld refinement of the crystal structure. Melting point was found to decrease with x changing from 0 to 4 in Ca₅Mg₄₋ₓMₓ(VO₄)₆ where M is Zn and Ni. It was observed that electrical conductivity does not depend on air humidity. The reported study was funded by the RFBR Grant No. 17–03–01280. Sample attestation was carried out in the Shared Access Centers at the IHTE UB RAS.

Keywords: garnet structure, electrical conductivity, thermal expansion, thermal properties

Procedia PDF Downloads 156