Search results for: regional anesthesia and analgesia techniques (RAAT)

Authors: Debneil Saha Roy

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Weather forecasting is a complex topic and is well suited for analysis by deep learning approaches. With the wide availability of weather observation data nowadays, these approaches can be utilized to identify immediate comparisons between historical weather forecasts and current observations. This work explores the application of deep learning techniques to weather forecasting in order to accurately predict the weather over a given forecast hori­zon. Three deep neural networks are used in this study, namely, Multi-Layer Perceptron (MLP), Long Short Tunn Memory Network (LSTM) and a combination of Convolutional Neural Network (CNN) and LSTM. The predictive performance of these models is compared using two evaluation metrics. The results show that forecasting accuracy increases with an increase in the complexity of deep neural networks.

Keywords: convolutional neural network, deep learning, long short term memory, multi-layer perceptron

Procedia PDF Downloads 169

Authors: Xing Feng, Yuanbin Li

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Oil spills at sea can cause severe marine environmental damage, including bringing huge hazards to living resources and human beings. In situ burning or chemical dispersant methods can be used to handle the oil spills sometimes, but these approaches will bring secondary pollution and fail in some situations. Oil recovery techniques have also been developed to recover oil using oil skimmer equipment installed on ships, while the hydrodynamic process of the oil flowing through the oil skimmer is very complicated and important for evaluating the recovery efficiency. Based on this, a two-dimensional numerical simulation platform for simulating the hydrodynamic process of the oil flowing through the oil skimmer is established based on the Navier-Stokes equations for viscous, incompressible fluid. Finally, the influence of the design of the flow channel in the curved plane oil skimmer on the hydrodynamic process of the oil flowing through the oil skimmer is investigated based on the established simulation platform.

Keywords: curved plane oil skimmer, flow channel, CFD, VOF

Procedia PDF Downloads 291

Authors: Abder-Rahman Ali, Adélaïde Albouy-Kissi, Manuel Grand-Brochier, Viviane Ladan-Marcus, Christine Hoeffl, Claude Marcus, Antoine Vacavant, Jean-Yves Boire

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In this paper, we present a new segmentation approach for focal liver lesions in contrast enhanced ultrasound imaging. This approach, based on a two-cluster Fuzzy C-Means methodology, considers type-II fuzzy sets to handle uncertainty due to the image modality (presence of speckle noise, low contrast, etc.), and to calculate the optimum inter-cluster threshold. Fine boundaries are detected by a local recursive merging of ambiguous pixels. The method has been tested on a representative database. Compared to both Otsu and type-I Fuzzy C-Means techniques, the proposed method significantly reduces the segmentation errors.

Keywords: defuzzification, fuzzy clustering, image segmentation, type-II fuzzy sets

Procedia PDF Downloads 479

Authors: Ahmed A. Elshami, Stephanie Bonnet, Abdelhafid Khelidj

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Corrosion inhibitors are widely used in concrete industry to reduce the corrosion rate of steel rebar which is present in contact with aggressive environments. The present work aims to using Zamzam water from well located within the Masjid al-Haram in Mecca, Saudi Arabia 20 m (66 ft) east of the Kaaba, the holiest place in Islam as corrosion inhibitor for steel in rain water and simulated acid rain. The effect of Zamzam water was investigated by electrochemical impedance spectroscopy (EIS) and Potentiodynamic polarization techniques in Department of Civil Engineering - IUT Saint-Nazaire, Nantes University, France. Zamzam water is considered to be one of the most important steel corrosion inhibitor which is frequently used in different industrial applications. Results showed that zamzam water gave a very good inhibition for steel corrosion in rain water and simulated acid rain.

Keywords: Zamzam water, corrosion inhibitor, rain water, simulated acid rain

Procedia PDF Downloads 387

Authors: Geoffrey Gilfillan, Peter Barham, Lisa Smallwood, David Harper

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The ‘Welland for People and Wildlife’ project aimed to improve the River Welland’s ecology and water quality, and to make it more accessible to the community of Market Harborough. A joint monitoring project by the Welland Rivers Trust & University of Leicester was incorporated into the design. The techniques that have been used to measure its success are hydrological, geomorphological, and water quality monitoring, species and habitat surveys, and community engagement. Early results show improvements to flow and habitat diversity, water quality and biodiversity of the river environment. Barrier removal has increased stickleback mating activity, and decreased parasitically infected fish in sample catches. The habitats provided by the berms now boast over 25 native plant species, and the river is clearer, cleaner and with better-oxygenated water.

Keywords: community engagement, ecological monitoring, river restoration, water quality

Procedia PDF Downloads 228

Authors: Denis Jordan, Daniel Golkowski, Mathias Lukas, Katharina Merz, Caroline Mlynarcik, Max Maurer, Valentin Riedl, Stefan Foerster, Eberhard F. Kochs, Andreas Bender, Ruediger Ilg

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Introduction: So far, clinical assessments that rely on behavioral responses to differentiate coma states or even predict outcome in coma patients are unreliable, e.g. because of some patients’ motor disabilities. The present study was aimed to provide prognosis in coma patients using markers from electroencephalogram (EEG), blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) and [18F]-fluorodeoxyglucose (FDG) positron emission tomography (PET). Unsuperwised principal component analysis (PCA) was used for multimodal integration of markers. Methods: Approved by the local ethics committee of the Technical University of Munich (Germany) 20 patients (aged 18-89) with severe brain damage were acquired through intensive care units at the Klinikum rechts der Isar in Munich and at the Therapiezentrum Burgau (Germany). At the day of EEG/fMRI/PET measurement (date I) patients (<3.5 month in coma) were grouped in the minimal conscious state (MCS) or vegetative state (VS) on the basis of their clinical presentation (coma recovery scale-revised, CRS-R). Follow-up assessment (date II) was also based on CRS-R in a period of 8 to 24 month after date I. At date I, 63 channel EEG (Brain Products, Gilching, Germany) was recorded outside the scanner, and subsequently simultaneous FDG-PET/fMRI was acquired on an integrated Siemens Biograph mMR 3T scanner (Siemens Healthineers, Erlangen Germany). Power spectral densities, permutation entropy (PE) and symbolic transfer entropy (STE) were calculated in/between frontal, temporal, parietal and occipital EEG channels. PE and STE are based on symbolic time series analysis and were already introduced as robust markers separating wakefulness from unconsciousness in EEG during general anesthesia. While PE quantifies the regularity structure of the neighboring order of signal values (a surrogate of cortical information processing), STE reflects information transfer between two signals (a surrogate of directed connectivity in cortical networks). fMRI was carried out using SPM12 (Wellcome Trust Center for Neuroimaging, University of London, UK). Functional images were realigned, segmented, normalized and smoothed. PET was acquired for 45 minutes in list-mode. For absolute quantification of brain’s glucose consumption rate in FDG-PET, kinetic modelling was performed with Patlak’s plot method. BOLD signal intensity in fMRI and glucose uptake in PET was calculated in 8 distinct cortical areas. PCA was performed over all markers from EEG/fMRI/PET. Prognosis (persistent VS and deceased patients vs. recovery to MCS/awake from date I to date II) was evaluated using the area under the curve (AUC) including bootstrap confidence intervals (CI, *: p<0.05). Results: Prognosis was reliably indicated by the first component of PCA (AUC=0.99*, CI=0.92-1.00) showing a higher AUC when compared to the best single markers (EEG: AUC<0.96*, fMRI: AUC<0.86*, PET: AUC<0.60). CRS-R did not show prediction (AUC=0.51, CI=0.29-0.78). Conclusion: In a multimodal analysis of EEG/fMRI/PET in coma patients, PCA lead to a reliable prognosis. The impact of this result is evident, as clinical estimates of prognosis are inapt at time and could be supported by quantitative biomarkers from EEG, fMRI and PET. Due to the small sample size, further investigations are required, in particular allowing superwised learning instead of the basic approach of unsuperwised PCA.

Keywords: coma states and prognosis, electroencephalogram, entropy, functional magnetic resonance imaging, machine learning, positron emission tomography, principal component analysis

Procedia PDF Downloads 334

Authors: Minoo Tavakoli, Alireza Kiani Rashid, Abbas Afrasiabi

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An aluminum coating deposited on mild steel substrate by electric arc spray and diffused to the base steel material by diffusion treatment at 800 and 900°C for 1 and 3 hours in a static air. Alloy layers formed by diffusion at both temperatures were investigated, and their features were compared with those of pack cementation aluminized steel. High-temperature oxidation tests were carried out in air at 600 °C for 145 hours. Results indicated that the aluminide coatings obtained from this process have significantly improved the high-temperature oxidation resistance in both methods due to the Al2O3 scale formation. Furthermore, it showed that the isothermal oxidation resistance of arc spray technique is better than pack cementation method. This can be attributed to voids that formed at the intermetallic layer /Al layer interface which is increased in the pack cementation method.

Keywords: electric arc spray, pack cementation, oxidation resistance, aluminized steel

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Authors: Rokhmatul Insani, Hira Laksmiwati Soemitro

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Business Intelligence is a methodology that exploits the data to produce information and knowledge systematically, business intelligence can support the decision-making process. Some methods in business intelligence are data warehouse and data mining. A data warehouse can store historical data from transactional data. For data modelling in data warehouse, we apply dimensional modelling by Kimball. While data mining is used to extracting patterns from the data and get insight from the data. Data mining has many techniques, one of which is segmentation. For profiling of telecommunication customer, we use customer segmentation according to customer’s usage of services, customer invoice and customer payment. Customers can be grouped according to their characteristics and can be identified the profitable customers. We apply K-Means Clustering Algorithm for segmentation. The input variable for that algorithm we use RFM (Recency, Frequency and Monetary) model. All process in data mining, we use tools IBM SPSS modeller.

Keywords: business intelligence, customer segmentation, data warehouse, data mining

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Authors: O. P. Yadav

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Nano-size Ag-N co-doped ZnO/CuO composite photo-catalyst has been synthesized by chemical method and characterized using XRD, TEM, FTIR, AAS and UV-Vis spectroscopic techniques. Photo-catalytic activity of as-synthesized nanomaterial has been studied using degradation of methyl orange as a probe under UV as well as visible radiations. Ag-N co-doped ZnO/CuO composite showed higher photo-catalytic activity than Ag- or N-doped ZnO and undoped ZnO-CuO composite photo-catalysts. The observed highest activity of Ag-N co-doped ZnO-CuO among the studied photo-catalysts is attributed to the cumulative effects of lowering of band-gap energy and decrease of recombination rate of photo-generated electrons and holes owing to doped N and Ag, respectively. Effects of photo-catalyst load, pH and substrate initial concentration on degradation of methyl orange have also been studied. Photo-catalytic degradation of methyl orange follows pseudo first order kinetics.

Keywords: degradation, nanocomposite, photocatalyst, spectroscopy, XRD

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Authors: Sujith Rajashekar Swamy, Meghana Rajashekara Swamy

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Although T1-weighted gadolinium-enhanced imaging (T1-Gd) has its established clinical role in diagnosing brain lesions of infectious and metastatic origins, the use of post-contrast susceptibility-weighted imaging (SWI) has been understudied. This observational study aims to explore and compare the prominence of brain parenchymal lesions between T1-Gd and SWI-Gd images. A cross-sectional study design was utilized to analyze 58 patients with brain parenchymal lesions using T1-Gd and SWI-Gd scanning techniques. Our results indicated that SWI-Gd enhanced the conspicuity of metastatic as well as infectious brain lesions when compared to T1-Gd. Consequently, it can be used as an adjunct to T1-Gd for post-contrast imaging, thereby avoiding additional contrast administration. Improved conspicuity of brain lesions translates directly to enhanced patient outcomes, and hence SWI-Gd imaging proves useful to meet that endpoint.

Keywords: susceptibility weighted, T1 weighted, brain lesions, gadolinium contrast

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Authors: Yiea Funk Te, Daniel Mueller, Irena Pletikosa Cvijikj

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Small and medium enterprises (SMEs) play an important role in the economy of many countries. When the overall world economy is considered, SMEs represent 95% of all businesses in the world, accounting for 66% of the total employment. Existing studies show that the current business environment is characterized as highly turbulent and strongly influenced by modern information and communication technologies, thus forcing SMEs to experience more severe challenges in maintaining their existence and expanding their business. To support SMEs at improving their competitiveness, researchers recently turned their focus on applying data mining techniques to build risk and growth prediction models. However, data used to assess risk and growth indicators is primarily obtained via questionnaires, which is very laborious and time-consuming, or is provided by financial institutes, thus highly sensitive to privacy issues. Recently, web mining (WM) has emerged as a new approach towards obtaining valuable insights in the business world. WM enables automatic and large scale collection and analysis of potentially valuable data from various online platforms, including companies’ websites. While WM methods have been frequently studied to anticipate growth of sales volume for e-commerce platforms, their application for assessment of SME risk and growth indicators is still scarce. Considering that a vast proportion of SMEs own a website, WM bears a great potential in revealing valuable information hidden in SME websites, which can further be used to understand SME risk and growth indicators, as well as to enhance current SME risk and growth prediction models. This study aims at developing an automated system to collect business-relevant data from the Web and predict future growth trends of SMEs by means of WM and data mining techniques. The envisioned system should serve as an 'early recognition system' for future growth opportunities. In an initial step, we examine how structured and semi-structured Web data in governmental or SME websites can be used to explain the success of SMEs. WM methods are applied to extract Web data in a form of additional input features for the growth prediction model. The data on SMEs provided by a large Swiss insurance company is used as ground truth data (i.e. growth-labeled data) to train the growth prediction model. Different machine learning classification algorithms such as the Support Vector Machine, Random Forest and Artificial Neural Network are applied and compared, with the goal to optimize the prediction performance. The results are compared to those from previous studies, in order to assess the contribution of growth indicators retrieved from the Web for increasing the predictive power of the model.

Keywords: data mining, SME growth, success factors, web mining

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Authors: Hanna Zietara

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Gastronomy is one of the oldest forms of commercial activity. It is currently one of the most popular and still dynamically developing branches of business. Socio-economic changes, its widespread occurrence, new techniques, or culinary styles affect the almost unlimited possibilities of its development. Importantly, regardless of the form of business adopted, food service is strongly related to logistics processes, and areas of food service that are closely linked to logistics are of strategic importance. Any inefficiency in logistics processes results in reduced chances for success and achieving competitive advantage by companies belonging to the catering industry. The aim of the paper is to identify the areas of logistic support occurring in the catering business, affecting the scope of the logistic processes implemented. The aim of the paper is realized through a plural homogeneous approach, based on: direct observation, text analysis of current documents, in-depth free targeted interviews.

Keywords: gastronomy, competitive advantage, logistics, logistics support

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Authors: Igor Bilenko, Artem Shitikov, Michael Gorodetsky

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Optical whispering gallery mode (WGM) resonators combine very high optical quality factor (Q) with small size. Resonators made from low loss crystalline fluorites (CaF2, MgF2) may have Q as high as 1010 that make them unique devices for modern applications including ultrasensitive sensors, frequency control, and precision spectroscopy. While silicon is a promising material transparent from near infrared to terahertz frequencies, fundamental limit for Si WGM quality factor was not reached yet. In our paper, we presented experimental results on the preparation and testing of resonators at 1550 nm wavelength made from crystalline silicon grown and treated by different techniques. Q as high as 3x107 was demonstrated. Future steps need to reach a higher value and possible applications are discussed.

Keywords: optical quality factor, silicon optical losses, silicon optical resonator, whispering gallery modes

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Authors: Zahid Ahmad, Nauman Ali

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This study has estimated the trade between USA and individual members of European Union using Gravity Model of Trade as The USA has a complex trade relationship with the European countries consist of a large number of consumers, which make USA dependent on EU for major of its total world trade. However, among the member of EU, the trade potential of USA with individual members of EU is not known. Panel data techniques e.g. Random Effect, Fixed Effect and Pooled Panel have been applied to secondary quantitative data to analyze the Trade between USA and EU. Trade Potential of USA with individual members of EU has been obtained using the ratio of Actual trade of USA with EU members and the trade as predicted by Gravity Model. The Study concluded that the USA has greater trade potential with 16 members of EU, including Croatia, Portugal and United Kingdom on top. On the other hand, Finland, Ireland, and France are the top countries with which the USA has exhaustive trade potential.

Keywords: analytical technique, economic, gravity, international trade, significant

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Authors: Seyed-Ali Sadegh-Zadeh, Kaveh Kavianpour, Hamed Atashbar, Elham Heidari, Saeed Shiry Ghidary, Amir M. Hajiyavand

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Evaluation metrics play a critical role in assessing the performance of machine learning models. In this review paper, we provide a comprehensive overview of performance measurement approaches for machine learning models. For each category, we discuss the most widely used metrics, including their mathematical formulations and interpretation. Additionally, we provide a comparative analysis of performance measurement approaches for metric combinations. Our review paper aims to provide researchers and practitioners with a better understanding of performance measurement approaches and to aid in the selection of appropriate evaluation metrics for their specific applications.

Keywords: evaluation metrics, performance measurement, supervised learning, unsupervised learning, reinforcement learning, model robustness and stability, comparative analysis

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Authors: Brigita Mieziene, Arunas Emeljanovas, Vida Cesnaitiene, Ingunn Fjortoft, Lise Kjonniksen

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Background. Health-related physical fitness refers to the favorable health status, i.e. ability to perform daily activities with vigor, as well as capacities that are associated with a low risk for development of chronic diseases and premature death. However, in school-aged children it is constantly declining, while some aspects of fitness declined as much as 50 percent during the last two decades, which prognosticates increasingly earlier onset of health problems, decreasing the quality of life of the population and financial burden for the society. Therefore, the goal of the current study was to indicate nationally representative age- and gender-specific reference values of anthropometric measures, musculoskeletal, motor and cardiorespiratory fitness in Lithuanian primary school children from 6 to 10 years. Methods. The study included 3556 students in total, from 73 randomly selected schools. Ethics approval for research by the Kaunas Regional Ethics Committee (No. BE-2-42) was obtained. Physical fitness was measured by the 9-item test battery, developed by Fjørtoft and colleagues. Height and weight were measured and body mass index calculated. Smoothed centile charts were derived using the LMS method. Results. The numerical age- and gender-specific percentile values (3rd, 10th, 25th, 50th, 75th, 90th, and 97th percentile) for anthropometric measures, musculoskeletal, motor and cardiorespiratory fitness were provided. The equivalent smoothed LMS curves were performed. The study indicated 12.5 percent of overweight and 5 percent of obese children in accordance with international gender and age specific norms of body mass index. This data could be used in clinical and educational settings in order to identify the level of individual physical fitness within its different components.

Keywords: fitness, overweight, primary school children, reference values, smoothed percentile curves

Procedia PDF Downloads 158

Authors: Reena Aggarwal

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Wall art is a manifestation of the human mind and an absorbing form of cultural expression. Solapur wall hanging making art reflects cultural values, regional sensibilities, beliefs, and identity and helps to preserve the many different communities. The tango of warp and weft in many ways than one tells the story of civilization itself. Solapur wall hanging is a poem in multicolor, written with the warp and weft having long, rich, and complex history with indigenous design vocabularies made by the Padmasali communities. The wall-hanging weaving of Solapur has remained unaltered for years, from being very basic and monochrome having landscapes and portraits catering only to the local market, thereby becoming a potential family income generation tool. The study focuses on the need for contemporization of the Solapur wall hanging and also deliberates on the fact that wherever the culture of native people has been aided by intervention, in nearly every case, the quality of their craft has began to be enhanced. The study also found the underlying reason for diminishing sales to a declining market, low sales, lack of innovation in design, and product development. Keeping in mind that the artisans of Solapur have heroically always hold on to their ancient beliefs and practices, which give them strength and identity, and a sense of pride, an intervention program was developed with an objective of widening the market and help artisans have a sustaining income which include urban consumers and create designs suitable for the urban market. The process of defining and measuring the advantages of design intervention was achieved by using qualitative research methods. An ethnographic research methodology was adopted, which includes six months of close interface with artisans from ten families engaged in making of wall hanging in Solapur. Design solutions were proposed in terms of product diversification and design extensions of the existing product line for increased variety. A collection of contemporary wall arts (wall decor) and room dividers were designed and developed.

Keywords: wall hanging, Solapur, contemporization, traditional, sustainable

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Authors: Maciej Szeląg, Stanisław Fic

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The impact of elevated temperatures on the construction materials manifests in change of their physical and mechanical characteristics. Stresses and thermal deformations that occur inside the volume of the material cause its progressive degradation as temperature increase. Finally, the reactions and transformations of multiphase structure of cementitious composite cause its complete destruction. A particularly dangerous phenomenon is the impact of thermal shock – a sudden high temperature load. The thermal shock leads to a high value of the temperature gradient between the outer surface and the interior of the element in a relatively short time. The result of mentioned above process is the formation of the cracks and scratches on the material’s surface and inside the material. The article describes the use of computer image analysis techniques to identify and assess the structure of the cluster cracks on the surfaces of modified cement pastes, caused by thermal shock. Four series of specimens were tested. Two Portland cements were used (CEM I 42.5R and CEM I 52,5R). In addition, two of the series contained metakaolinite as a replacement for 10% of the cement content. Samples in each series were made in combination of three w/b (water/binder) indicators of respectively 0.4; 0.5; 0.6. Surface cracks of the samples were created by a sudden temperature load at 200°C for 4 hours. Images of the cracked surfaces were obtained via scanning at 1200 DPI; digital processing and measurements were performed using ImageJ v. 1.46r software. In order to examine the cracked surface of the cement paste as a system of closed clusters – the dispersal systems theory was used to describe the structure of cement paste. Water is used as the dispersing phase, and the binder is used as the dispersed phase – which is the initial stage of cement paste structure creation. A cluster itself is considered to be the area on the specimen surface that is limited by cracks (created by sudden temperature loading) or by the edge of the sample. To describe the structure of cracks two stereological parameters were proposed: A ̅ – the cluster average area, L ̅ – the cluster average perimeter. The goal of this study was to compare the investigated stereological parameters with the mechanical properties of the tested specimens. Compressive and tensile strength testes were carried out according to EN standards. The method used in the study allowed the quantitative determination of defects occurring in the examined modified cement pastes surfaces. Based on the results, it was found that the nature of the cracks depends mainly on the physical parameters of the cement and the intermolecular interactions on the dispersal environment. Additionally, it was noted that the A ̅/L ̅ relation of created clusters can be described as one function for all tested samples. This fact testifies about the constant geometry of the thermal cracks regardless of the presence of metakaolinite, the type of cement and the w/b ratio.

Keywords: cement paste, cluster cracks, elevated temperature, image analysis, metakaolinite, stereological parameters

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Authors: Martina Manenova, Lukas Cirus

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This article introduces research focused on elementary school teachers’ approach to innovations in ICT. The diffusion of innovations theory, which was written by E. M. Rogers, captures the processes of innovation adoption. The research method derived from this theory and the Rogers’ questionnaire focused on the diffusion of innovations was used as the basic research method. The research sample consisted of elementary school teachers. The comparison of results with the Rogers’ results shows that among the teachers in the research sample the so-called early majority, as well as the overall division of the data, was rather central (early adopter, early majority, and later majority). The teachers very rarely appeared on the edge positions (innovator, laggard). The obtained results can be applied to teaching practice and used especially in the implementation of new technologies and techniques into the educational process.

Keywords: innovation, diffusion of innovation, information and communication technology, teachers

Procedia PDF Downloads 287

Authors: Gui Yewei, Du Yanxia, Xiao Guangming, Liu Lei, Wei Dong, Yang Xiaofeng

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A phase change material (PCM) is a substance which absorbs a large amount of energy when undergoing a change of solid-liquid phase. The good physical and chemical properties of C or SiC foam reveal the possibility of using them as a thermal conductivity enhancer for the PCM. C or SiC foam composite PCM has a high effective conductivity and becomes one of the most interesting thermal storage techniques due to its advantage of simplicity and reliability. The paper developed a numerical method to simulate the heat transfer of SiC and C foam composite PCM, a finite volume technique was used to discretize the heat diffusion equation while the phase change process was modeled using the equivalent specific heat method. The effects of the porosity were investigated based on the numerical method, and the effects of the geometric model of the microstructure on the equivalent thermal conductivity was studies.

Keywords: SiC foam, composite, phase change material, heat transfer

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Authors: Magdi Mohamed Eltayeb Zumrawi

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It is quite essential to investigate the causes of pavement deterioration in order to select the proper maintenance technique. The objective of this study was to identify factors cause deterioration of recently constructed roads in Khartoum state. A comprehensive literature concerning the factors of road deterioration, common road defects and their causes were reviewed. Three major road projects with different deterioration reasons were selected for this study. The investigation involved field survey and laboratory testing on those projects to examine the existing pavement conditions. The results revealed that the roads investigated experienced severe failures in the forms of cracks, potholes and rutting in the wheel path. The causes of those failures were found mainly linked to poor drainage, traffic overloading, expansive subgrade soils and the use of low quality materials in construction. Based on the results, recommendations were provided to help highway engineers in selecting the most effective repair techniques for specific kinds of distresses.

Keywords: pavement, deterioration, causes, failures

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Authors: M. Taha, Hala H. Zayed, T. Nazmy, M. Khalifa

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Recently, traffic monitoring has attracted the attention of computer vision researchers. Many algorithms have been developed to detect and track moving vehicles. In fact, vehicle tracking in daytime and in nighttime cannot be approached with the same techniques, due to the extreme different illumination conditions. Consequently, traffic-monitoring systems are in need of having a component to differentiate between daytime and nighttime scenes. In this paper, a HSV-based day/night detector is proposed for traffic monitoring scenes. The detector employs the hue-histogram and the value-histogram on the top half of the image frame. Experimental results show that the extraction of the brightness features along with the color features within the top region of the image is effective for classifying traffic scenes. In addition, the detector achieves high precision and recall rates along with it is feasible for real time applications.

Keywords: day/night detector, daytime/nighttime classification, image classification, vehicle tracking, traffic monitoring

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Authors: Fitih Ademe, Kibebew Kibret, Sheleme Beyene, Mezgebu Getnet, Gashaw Meteke

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Changes in precipitation, temperature and atmospheric CO2 concentration are expected to alter agricultural productivity patterns worldwide. The interactive effects of soil moisture and nutrient availability are the two key edaphic factors that determine crop yield and are sensitive to climatic changes. The study assessed the potential impacts of climate change on maize yield and corresponding water productivity and nutrient use efficiency under climate change scenarios for the Central Rift Valley of Ethiopia by mid (2041-2070) and end century (2071-2100). Projected impacts were evaluated using climate scenarios generated from four General Circulation Models (GCMs) dynamically downscaled by the Swedish RCA4 Regional Climate Model (RCM) in combination with two Representative Concentration Pathways (RCP 4.5 and RCP8.5). Decision Support System for Agro-technology Transfer cropping system model (DSSAT-CSM) was used to simulate yield, water and nutrient use for the study periods. Results indicate that rainfed maize yield might decrease on average by 16.5 and 23% by the 2050s and 2080s, respectively, due to climate change. Water productivity is expected to decline on average by 2.2 and 12% in the CRV by mid and end centuries with respect to the baseline. Nutrient uptake and corresponding nutrient use efficiency (NUE) might also be negatively affected by climate change. Phosphorus uptake probably will decrease in the CRV on average by 14.5 to 18% by 2050s, while N uptake may not change significantly at Melkassa. Nitrogen and P use efficiency indicators showed decreases in the range between 8.5 to 10.5% and between 9.3 to 10.5%, respectively, by 2050s relative to the baseline average. The simulation results further indicated that a combination of increased water availability and optimum nutrient application might increase both water productivity and nutrient use efficiency in the changed climate, which can ensure modest production in the future. Potential options that can improve water availability and nutrient uptake should be identified for the study locations using a crop modeling approach.

Keywords: crop model, climate change scenario, nutrient uptake, nutrient use efficiency, water productivity

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Authors: Fida Isam Abdulhafiz

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Traditional vernacular architecture in the United Arab Emirates constituted namely of adobe houses with a limited number of openings in their facades. The thick mud and rubble walls and wooden window screens protected its inhabitants from the harsh desert climate and provided them with privacy and fulfilled their comfort zone needs to an extent. However, with the rise of the immediate post petroleum era reinforced concrete villas with glass and steel technology has replaced traditional vernacular dwellings. And more load was put on the mechanical cooling systems to ensure the satisfaction of today’s more demanding doweling inhabitants. However, In the early 21at century professionals started to pay more attention to the carbon footprint caused by the built constructions. In addition, many studies and innovative approaches are now dedicated to lower the impact of the existing operating buildings on their surrounding environments. The UAE government agencies started to regulate that aim to revive sustainable and environmental design through Local and international building codes and urban design policies such as Estidama and LEED. The focus in this paper is on the reduction of the emissions resulting from the use of energy sources in the cooling and heating systems, and that would be through using innovative screen designs and façade solutions to provide a green footprint and aesthetic architectural icons. Screens are one of the popular innovative techniques that can be added in the design process or used in existing building as a renovation techniques to develop a passive green buildings. Preparing future architects to understand the importance of environmental design was attempted through physical modelling of window screens as an educational means to combine theory with a hands on teaching approach. Designing screens proved to be a popular technique that helped them understand the importance of sustainable design and passive cooling. After creating models of prototype screens, several tests were conducted to calculate the amount of Sun, light and wind that goes through the screens affecting the heat load and light entering the building. Theory further explored concepts of green buildings and material that produce low carbon emissions. This paper highlights the importance of hands on experience for student architects and how physical modelling helped rise eco awareness in Design studio. The paper will study different types of façade screens and shading devices developed by Architecture students and explains the production of diverse patterns for traditional screens by student architects based on sustainable design concept that works properly with the climate requirements in the Middle East region.

Keywords: building’s screens modeling, façade design, sustainable architecture, sustainable dwellings, sustainable education

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Authors: Diego Santibañez Oyarce, Fernanda Bravo Cornejo, Camilo Cerda Sarabia, Belén Díaz Díaz, Esteban Gómez Terán, Hugo Osses Prado, Raúl Caulier-Cisterna, Jorge Vergara-Quezada, Ana Moya-Beltrán

Abstract:

The advent of high-throughput sequencing technologies has revolutionized genomics, generating vast amounts of genetic data that challenge traditional bioinformatics methods. Machine learning addresses these challenges by leveraging computational power to identify patterns and extract information from large datasets. However, biological sequence data, being symbolic and non-numeric, must be converted into numerical formats for machine learning algorithms to process effectively. So far, some encoding methods, such as one-hot encoding or k-mers, have been explored. This work proposes additional approaches for encoding DNA sequences in order to compare them with existing techniques and determine if they can provide improvements or if current methods offer superior results. Data from the 16S rRNA gene, a universal marker, was used to analyze eight bacterial groups that are significant in the pulmonary environment and have clinical implications. The bacterial genes included in this analysis are Prevotella, Abiotrophia, Acidovorax, Streptococcus, Neisseria, Veillonella, Mycobacterium, and Megasphaera. These data were downloaded from the NCBI database in Genbank file format, followed by a syntactic analysis to selectively extract relevant information from each file. For data encoding, a sequence normalization process was carried out as the first step. From approximately 22,000 initial data points, a subset was generated for testing purposes. Specifically, 55 sequences from each bacterial group met the length criteria, resulting in an initial sample of approximately 440 sequences. The sequences were encoded using different methods, including one-hot encoding, k-mers, Fourier transform, and Wavelet transform. Various machine learning algorithms, such as support vector machines, random forests, and neural networks, were trained to evaluate these encoding methods. The performance of these models was assessed using multiple metrics, including the confusion matrix, ROC curve, and F1 Score, providing a comprehensive evaluation of their classification capabilities. The results show that accuracies between encoding methods vary by up to approximately 15%, with the Fourier transform obtaining the best results for the evaluated machine learning algorithms. These findings, supported by the detailed analysis using the confusion matrix, ROC curve, and F1 Score, provide valuable insights into the effectiveness of different encoding methods and machine learning algorithms for genomic data analysis, potentially improving the accuracy and efficiency of bacterial classification and related genomic studies.

Keywords: DNA encoding, machine learning, Fourier transform, Fourier transformation

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Authors: Mohammed Al Awadh

Abstract:

In order for businesses to take advantage of the opportunities for expanded production and trade that have arisen as a result of globalization and increased levels of competition, productivity growth is required. The number of available sources is decreasing with each passing day, which results in an ever-increasing demand. In response to this, there will be an increased demand placed on firms to improve the efficiency with which they utilise their resources. As a scientific method, work and time research techniques have been employed in all manufacturing and service industries to raise the efficiency of use of the factors of production. These approaches focus on work and time. The goal of this research is to improve the productivity of a manufacturing industry's production system by looking at ways to measure work. The work cycles were broken down into more manageable and quantifiable components. On the observation sheet, these aspects were noted down. The operation has been properly analysed in order to identify value-added and non-value-added components, and observations have been recorded for each of the different trails.

Keywords: time study, work measurement, work study, efficiency

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Authors: A. Chenafa, S. Boulenouar, M. Zitouni, M. Boukouria

Abstract:

The sterilization of medical devices constitutes for all the medical professions, an inescapable obligation. It has for objective to prevent the infectious risk, both for the patient and for the medical team. The Dental surgeon as every healthcare professional has to master perfectly this subject and to train his staff to the various techniques of sterilization. It is the only way to assure the patients all the security for which they are entitled to wait when they undergo a dental care. It’s for it, that we undertook to lead an investigation aiming at estimating the sterilization practice at the dental surgeon of Sidi bel Abbes. The survey result showed a youth marked with the profession with a majority use of autoclave with cycle B and an almost total absence of the sterilization controls (test of Bowie and Dick). However, the majority of the dentists control and validate their sterilizers. Finally, our survey allowed us to describe some practices which must be improved regarding control, regarding qualification and regarding staff training. And suggestions were made in this sense.

Keywords: dental surgeon, medical devices, sterilization, survey

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Authors: Samane Sharifi Monfared, Lavdie Rada

Abstract:

Nowadays, autonomous vehicles are developing rapidly toward facilitating human car driving. One of the main issues is road lane detection for a suitable guidance direction and car accident prevention. This paper aims to improve and optimize road line detection based on a combination of camera calibration, the Hough transform, and Canny edge detection. The video processing is implemented using the Open CV library with the novelty of having a scale able region masking. The aim of the study is to introduce automatic road lane detection techniques with the user’s minimum manual intervention.

Keywords: hough transform, canny edge detection, optimisation, scaleable masking, camera calibration, improving the quality of image, image processing, video processing

Procedia PDF Downloads 86

Authors: Tsao Jui-Jung

Abstract:

Previous research findings have shown that most students do not fully utilize the written corrective feedback provided by teachers (Stone, 2014). This common phenomenon results in the ineffective utilization of teachers' written corrective feedback. As Ellis (2010) points out, the effectiveness of written corrective feedback depends on the level of student engagement with it. Therefore, it is crucial to understand how students utilize the written corrective feedback from their teachers. Previous studies have confirmed the positive impact of teacher-student writing conferences on students' engagement in the writing process and their writing abilities (Hum, 2021; Nosratinia & Nikpanjeh, 2019; Wong, 1996; Yeh, 2016, 2019). However, due to practical constraints such as time limitations, this instructional activity is not fully utilized in writing classrooms (Alfalagg, 2020). Therefore, to address this research gap, the purpose of this study was to explore several aspects of teacher-student writing conferences, including the frequency of meaning negotiation (i.e., comprehension checks, confirmation checks, and clarification checks) and teacher scaffolding techniques (i.e., feedback, prompts, guidance, explanations, and demonstrations) in teacher-student writing conferences, examining students’ self-assessment of their writing strengths and weaknesses in post-conference journals and their experiences with teacher-student writing conferences (i.e., interaction styles, communication levels, how teachers addressed errors, and overall perspectives on the conferences), and gathering insights from their responses to open-ended questions in the final stage of the study (i.e., their preferences and reasons for different written corrective feedback techniques used by teachers and their perspectives and suggestions on teacher-student writing conferences). Data collection methods included transcripts of audio recordings of teacher-student writing conferences, students’ post-conference journals, and open-ended questionnaires. The participants of this study were sophomore students enrolled in an English writing course for a duration of one school year. Key research findings are as follows: Firstly, in terms of meaning negotiation, students attempted to clearly understand the corrective feedback provided by the teacher-researcher twice as often as the teacher-researcher attempted to clearly understand the students' writing content. Secondly, the most commonly used scaffolding technique in the conferences was prompting (indirect feedback). Thirdly, the majority of participants believed that teacher-student writing conferences had a positive impact on their writing abilities. Fourthly, most students preferred direct feedback from the teacher-research as it directly pointed out their errors and saved them time in revision. However, some students still preferred indirect feedback, as they believed it encouraged them to think and self-correct. Based on the research findings, this study proposes effective teaching recommendations for English writing instruction aimed at optimizing teaching strategies and enhancing students' writing abilities.

Keywords: written corrective feedback, student engagement, teacher-student writing conferences, action research

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Authors: Syed Hammad Ali, Rijan Bhakta Kayastha, Danial Hashmi, Richard Armstrong, Ahuti Shrestha, Iram Bano, Javed Hassan

Abstract:

This paper presents the results of a semi-distributed modified positive degree-day model (MPDDM) for estimating snow and ice melt contributions to discharge from the glacierized Hunza River basin, Pakistan. The model uses daily temperature data, daily precipitation data, and positive degree day factors for snow and ice melt. The model is calibrated for the period 1995-2001 and validated for 2002-2013, and demonstrates close agreements between observed and simulated discharge with Nash–Sutcliffe Efficiencies of 0.90 and 0.88, respectively. Furthermore, the Weather Research and Forecasting model projected temperature, and precipitation data from 2016-2050 are used for representative concentration pathways RCP4.5 and RCP8.5, and bias correction was done using a statistical approach for future discharge estimation. No drastic changes in future discharge are predicted for the emissions scenarios. The aggregate snow-ice melt contribution is 39% of total discharge in the period 1993-2013. Snow-ice melt contribution ranges from 35% to 63% during the high flow period (May to October), which constitutes 89% of annual discharge; in the low flow period (November to April) it ranges from 0.02% to 17%, which constitutes 11 % of the annual discharge. The snow-ice melt contribution to total discharge will increase gradually in the future and reach up to 45% in 2041-2050. From a sensitivity analysis, it is found that the combination of a 2°C temperature rise and 20% increase in precipitation shows a 10% increase in discharge. The study allows us to evaluate the impact of climate change in such basins and is also useful for the future prediction of discharge to define hydropower potential, inform other water resource management in the area, to understand future changes in snow-ice melt contribution to discharge, and offer a possible evaluation of future water quantity and availability.

Keywords: climate variability, future discharge projection, positive degree day, regional climate model, water resource management

Procedia PDF Downloads 287