Search results for: partially observed data

Authors: Nidal H. Abu-Zahra, Parisa Khoshnoud, Murtatha Jamel, Subhashini Gunashekar

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PVC foam-fly ash composites (PVC-FA) are characterized for their structural, morphological, mechanical and thermal properties. The tensile strength of the composites increased modestly with higher fly ash loading, while there was a significant increase in the elastic modulus for the same composites. On the other hand, a decrease in elongation at UTS was observed upon increasing fly ash content due to increased rigidity of the composites. Similarly, the flexural modulus increased as the fly ash loading increased, where the composites containing 25 phr fly ash showed the highest flexural strength. Thermal properties of PVC-fly ash composites were determined by Thermo Gravimetric Analysis (TGA). The micro structural properties were studied by Scanning Electron Microscopy (SEM). SEM results confirm that fly ash particles were mechanically interlocked in PVC matrix with good inter facial interaction with the matrix. Particle agglomeration and debonding was observed in samples containing higher amounts of fly ash.

Keywords: PVC foam, polyvinyl chloride, rigid PVC, fly ash composites, polymer composites

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Authors: Merve Ak Efe

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Youth branches in Turkey are one of the sub-fields where political ideologies are intersected with daily life practices. When the youth branches are examined within the framework of daily life practices, a social area can be defined where many types of capital turn into gains. The relationship between politics and capital is not only financial but can also be observed in the form of social, cultural, or emotional capital. This paper examines the political mobilization of young people who are members of the Youth Branch of the Justice and Development Party. The reason why JDP (Adalet ve Kalkınma Partisi) was chosen is that they have been the ruling party for twenty years, and there is a considerable number of young members within the party. Since Bayrampaşa is a district where JDP is politically active, This study is based on Bayrampaşa youth branches. The study examines how young people who are members of the party are mobilized and the everyday life practices and emotions underlying this mobilization. The data was collected through in-depth interviews with 13 young people, and the participant observation method was applied at the weekly meetings of the Justice and Development Party Bayrampaşa Youth Branch. Youth Branches represent a political space in which emotions turn into action for the young people who are involved in the party. During the field study at the micro level, it has been observed that the Bayrampaşa JDP Youth Branch hosted a transformation that incorporates political and social practices into modern tactics. One of the other results shows that being a member of youth branches causes a significant rise in social capital for young people. On the other hand, for the members with low cultural capital, there is an increase in social capital; however, an increase in cultural capital is not prominent.

Keywords: political mobilization, everyday practices, emotional capital, social capital, cultural capital

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Authors: Byeong-Sam Kim, Jongmin Park

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The present work is motivated by the industrial challenge to produce complex composite shapes cost-effectively. The model used an anisotropical thermoviscoelastic is analyzed by an implemented finite element solver. The stress relaxation can be constructed by Prony series for the nonlinear thermoviscoelastic model. The calculation of process induced internal stresses relaxation during the cooling stage of the manufacturing cycle was carried out by the spring back phenomena observed from the part containing a cylindrical segment. The finite element results obtained from the present formulation are compared with experimental data, and the results show good correlations.

Keywords: thermoviscoelastic, springback phenomena, FEM analysis, thermoplastic composite structures

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Authors: Ji Eun Shin, Byung Ho Jung, Dong Hoon Lim

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It is almost impossible to store or analyze big data increasing exponentially with traditional technologies. Hadoop is a new technology to make that possible. R programming language is by far the most popular statistical tool for big data analysis based on distributed processing with Hadoop technology. With RHadoop that integrates R and Hadoop environment, we implemented parallel multiple regression analysis with different sizes of actual data. Experimental results showed our RHadoop system was much faster as the number of data nodes increases. We also compared the performance of our RHadoop with lm function and big lm packages available on big memory. The results showed that our RHadoop was faster than other packages owing to paralleling processing with increasing the number of map tasks as the size of data increases.

Keywords: big data, Hadoop, parallel regression analysis, R, RHadoop

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Authors: Haojie Wang, Xun Li, Rui Yin

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In order to solve the memorization overfitting in the meta-learning MAML algorithm, a method of generating mutually exclusive tasks based on data augmentation is proposed. This method generates a mutex task by corresponding one feature of the data to multiple labels, so that the generated mutex task is inconsistent with the data distribution in the initial dataset. Because generating mutex tasks for all data will produce a large number of invalid data and, in the worst case, lead to exponential growth of computation, this paper also proposes a key data extraction method, that only extracts part of the data to generate the mutex task. The experiments show that the method of generating mutually exclusive tasks can effectively solve the memorization overfitting in the meta-learning MAML algorithm.

Keywords: data augmentation, mutex task generation, meta-learning, text classification.

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Authors: Rostam Abdi, Ahmad Abdi, Zahra Vahedi Langrodi

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The aim of this study is to investigate four-week resistance exercise and milk supplement on NT-proBNP and plasma troponin I of male students. Concerning the methodology of the study, 21 senior high school students of Ardebil city were selected. The selected subjects were randomly shared in three groups of control, exercise- water and exercise- milk. The exercise program includes resistance exercise for a big muscle group. The subjects of control group rested during the study and did not participate in any training. The subjects of exercise- water experimental group immediately received 400 cc water after exercise and exercise- milk group immediately received 400 cc low fat milk. Control-water groups consumed the same amount of water. 48 hours before and after the last exercise session, the blood sample of the subjects were taken for measuring the variables. NT-proBNP and Troponin I concentrations were measured by ELISA. For data analysis, one-way variance analysis test, correlated t-test and Bonferroni post hoc test were used. The significant difference of p ≤ 0.05 was accepted. Resistance training along with milk consumption leads to increase of plasma NT-proBNP, however; this increase has not reached the significant level. Furthermore, meaningful increase was observed in plasma NT–proBNP in exercise group between pretest and posttest values. Furthermore, no meaningful difference was observed between groups in terms of Troponin I after milk consumption. It seems that endurance exercises lead to change in the structure of heart muscle and is along with an increase of NT-proBNP. Furthermore, there is the possibility that milk consumption can lead to release of heart troponin I. The mechanism through which protein supplements have been put on heart troponin I is unknown and requires more research.

Keywords: resistance exercise, milk, NT-proBNP, Troponin I

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Authors: Hacene Benkhoula, Mohamed Badreddine Benabdella, Hamid Bouzeboudja, Abderrahmane Asraoui

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The wind is a random variable difficult to master, for this, we developed a mathematical and statistical methods enable to modeling and forecast wind power. Gaussian Processes (GP) is one of the most widely used families of stochastic processes for modeling dependent data observed over time, or space or time and space. GP is an underlying process formed by unrecognized operator’s uses to solve a problem. The purpose of this paper is to present how to forecast wind power by using the GP. The Gaussian process method for forecasting are presented. To validate the presented approach, a simulation under the MATLAB environment has been given.

Keywords: wind power, Gaussien process, modelling, forecasting

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Authors: Sifat Rahman Ahona, Rifat Tasnim, Naima Hassan

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Data aggregation is a helpful technique for reducing the data communication overhead in wireless sensor network. One of the important tasks of data aggregation is positioning of the aggregator points. There are a lot of works done on data aggregation. But, efficient positioning of the aggregators points is not focused so much. In this paper, authors are focusing on the positioning or the placement of the aggregation points in wireless sensor network. Authors proposed an algorithm to select the aggregators positions for a scenario where aggregator nodes are more powerful than sensor nodes.

Keywords: aggregation point, data communication, data aggregation, wireless sensor network

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Authors: Paula Simões, Isabel Natário

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This paper reviews a number of theoretical aspects for implementing an explicit spatial perspective in econometrics for modelling non-continuous data, in general, and count data, in particular. It provides an overview of the several spatial econometric approaches that are available to model data that are collected with reference to location in space, from the classical spatial econometrics approaches to the recent developments on spatial econometrics to model count data, in a Bayesian hierarchical setting. Considerable attention is paid to the inferential framework, necessary for structural consistent spatial econometric count models, incorporating spatial lag autocorrelation, to the corresponding estimation and testing procedures for different assumptions, to the constrains and implications embedded in the various specifications in the literature. This review combines insights from the classical spatial econometrics literature as well as from hierarchical modeling and analysis of spatial data, in order to look for new possible directions on the processing of count data, in a spatial hierarchical Bayesian econometric context.

Keywords: spatial data analysis, spatial econometrics, Bayesian hierarchical models, count data

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Authors: M. Lim Haslip

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This quantitative study explores the correlation between child gender and father-child interactions. The author analyzes data from videotaped interactions between African-American fathers and their boy or girl toddler to explain how African-American fathers and toddlers interact with each other and whether these interactions differ by child gender. The purpose of this study is to investigate the research question: 'How, if at all, do fathers’ speech and gestures differ when interacting with their two-year-old sons versus daughters during free play?' The objectives of this study are to describe how child gender impacts African-American fathers’ verbal communication, examine how fathers gesture and speak to their toddler by gender, and to guide interventions for low-income African-American families and their children in early language development. This study involves a sample of 41 low-income African-American fathers and their 24-month-old toddlers. The videotape data will be used to observe 10-minute father-child interactions during free play. This study uses the already transcribed and coded data provided by Dr. Meredith Rowe, who did her study on the impact of African-American fathers’ verbal input on their children’s language development. The Child Language Data Exchange System (CHILDES program), created to study conversational interactions, was used for transcription and coding of the videotape data. The findings focus on the quantity of speech, diversity of speech, complexity of speech, and the quantity of gesture to inform the vocabulary usage, number of spoken words, length of speech, and the number of object pointings observed during father-toddler interactions in a free play setting. This study will help intervention and prevention scientists understand early language development in the African-American population. It will contribute to knowledge of the role of African-American fathers’ interactions on their children’s language development. It will guide interventions for the early language development of African-American children.

Keywords: parental engagement, early language development, African-American families, quantity of speech, diversity of speech, complexity of speech and the quantity of gesture

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Authors: Vibha Devi, Shabina Khanam

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Hemp (Cannabis sativa) possesses a rich content of ω-6 linoleic and ω-3 linolenic essential fatty acid in the ratio of 3:1, which is a rare and most desired ratio that enhances the quality of hemp oil. These components are beneficial for the development of cell and body growth, strengthen the immune system, possess anti-inflammatory action, lowering the risk of heart problem owing to its anti-clotting property and a remedy for arthritis and various disorders. The present study employs supercritical fluid extraction (SFE) approach on hemp seed at various conditions of parameters; temperature (40 - 80) °C, pressure (200 - 350) bar, flow rate (5 - 15) g/min, particle size (0.430 - 1.015) mm and amount of co-solvent (0 - 10) % of solvent flow rate through central composite design (CCD). CCD suggested 32 sets of experiments, which was carried out. As SFE process includes large number of variables, the present study recommends the application of resampling techniques for cross-validation of the obtained data. Cross-validation refits the model on each data to achieve the information regarding the error, variability, deviation etc. Bootstrap and jackknife are the most popular resampling techniques, which create a large number of data through resampling from the original dataset and analyze these data to check the validity of the obtained data. Jackknife resampling is based on the eliminating one observation from the original sample of size N without replacement. For jackknife resampling, the sample size is 31 (eliminating one observation), which is repeated by 32 times. Bootstrap is the frequently used statistical approach for estimating the sampling distribution of an estimator by resampling with replacement from the original sample. For bootstrap resampling, the sample size is 32, which was repeated by 100 times. Estimands for these resampling techniques are considered as mean, standard deviation, variation coefficient and standard error of the mean. For ω-6 linoleic acid concentration, mean value was approx. 58.5 for both resampling methods, which is the average (central value) of the sample mean of all data points. Similarly, for ω-3 linoleic acid concentration, mean was observed as 22.5 through both resampling. Variance exhibits the spread out of the data from its mean. Greater value of variance exhibits the large range of output data, which is 18 for ω-6 linoleic acid (ranging from 48.85 to 63.66 %) and 6 for ω-3 linoleic acid (ranging from 16.71 to 26.2 %). Further, low value of standard deviation (approx. 1 %), low standard error of the mean (< 0.8) and low variance coefficient (< 0.2) reflect the accuracy of the sample for prediction. All the estimator value of variance coefficients, standard deviation and standard error of the mean are found within the 95 % of confidence interval.

Keywords: resampling, supercritical fluid extraction, hemp oil, cross-validation

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Authors: Alessandra N. Santos, Max P. Ferreira, Alexandra R. P. Silva, Agda A. R. de Oliveira, Marivalda M. Pereira

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The literature describes experiments, in which ceria nanoparticles in the bioactive glass significantly improve differentiation of stem cells into osteoblasts and increase production of collagen. It is not known whether this effect observed due to the presence of nanoceria can be also observed in the presence of cerium in the bioactive glass network. The effect of cerium into bioactive glasses using the sol–gel route is the focus of this work, with the goal to develop a material for tissue engineering with the potential to enhance osteogenesis. A bioactive glass composition based on 70% SiO2–30% CaO is produced with the addition of cerium. The analyses XRD, FTIR, SEM/EDS, BET/BJH, in vitro bioactivity test and the Cell viability assay were performed. The results show that cerium remains in the bioactive glass structure. The obtained material present in vitro bioactivity and promote the cell viability.

Keywords: bioactive glass, bioactivity, cerium salt, material characterization, sol-gel method

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Authors: Gueidi Afef, Gharsellaoui Hamza, Ben Ahmed Samir

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This paper deals with the secret of the continual progression data that new data management solutions have been emerged: The NoSQL databases. They crossed several areas like personalization, profile management, big data in real-time, content management, catalog, view of customers, mobile applications, internet of things, digital communication and fraud detection. Nowadays, these database management systems are increasing. These systems store data very well and with the trend of big data, a new challenge’s store demands new structures and methods for managing enterprise data. The new intelligent machine in the e-learning sector, thrives on more data, so smart machines can learn more and faster. The robotics are our use case to focus on our test. The implementation of NoSQL for Robotics wrestle all the data they acquire into usable form because with the ordinary type of robotics; we are facing very big limits to manage and find the exact information in real-time. Our original proposed approach was demonstrated by experimental studies and running example used as a use case.

Keywords: NoSQL databases, database management systems, robotics, big data

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Authors: I. V. Pinto, M. R. Sooriyarachchi

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It can be frequently observed that the data arising in our environment have a hierarchical or a nested structure attached with the data. Multilevel modelling is a modern approach to handle this kind of data. When multilevel modelling is combined with a binary response, the estimation methods get complex in nature and the usual techniques are derived from quasi-likelihood method. The estimation methods which are compared in this study are, marginal quasi-likelihood (order 1 & order 2) (MQL1, MQL2) and penalized quasi-likelihood (order 1 & order 2) (PQL1, PQL2). A statistical model is of no use if it does not reflect the given dataset. Therefore, checking the adequacy of the fitted model through a goodness-of-fit (GOF) test is an essential stage in any modelling procedure. However, prior to usage, it is also equally important to confirm that the GOF test performs well and is suitable for the given model. This study assesses the suitability of the GOF test developed for binary response multilevel models with respect to the method used in model estimation. An extensive set of simulations was conducted using MLwiN (v 2.19) with varying number of clusters, cluster sizes and intra cluster correlations. The test maintained the desirable Type-I error for models estimated using PQL2 and it failed for almost all the combinations of MQL. Power of the test was adequate for most of the combinations in all estimation methods except MQL1. Moreover, models were fitted using the four methods to a real-life dataset and performance of the test was compared for each model.

Keywords: goodness-of-fit test, marginal quasi-likelihood, multilevel modelling, penalized quasi-likelihood, power, quasi-likelihood, type-I error

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Authors: Shan Faiz, Arfat Anis, Saeed M. Al-Zarani

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High density polyethylene (HDPE) and poly benzimidazole fiber (PBI) composites were prepared by melt blending in a twin screw extruder (TSE). The thermo-mechanical properties of PBI fiber reinforced HDPE composite samples (1%, 4% and 8% fiber content) of fiber lengths 3 mm and 6 mm were investigated using differential scanning calorimeter (DSC), universal testing machine (UTM), rheometer and scanning electron microscopy (SEM). The effect of fiber content and fiber lengths on the thermo-mechanical properties of the HDPE-PBI composites was studied. The DSC analysis showed decrease in crystallinity of HDPE-PBI composites with the increase of fiber loading. Maximum decrease observed was 12% at 8% fiber length. The thermal stability was found to increase with the addition of fiber. T50% was notably increased to 40oC for both grades of HDPE using 8% of fiber content. The mechanical properties were not much affected by the increase in fiber content. The optimum value of tensile strength was achieved using 4% fiber content and slight increase of 9% in tensile strength was observed. No noticeable change was observed in flexural strength. In rheology study, the complex viscosities of HDPE-PBI composites were higher than the HDPE matrix and substantially increased with even minimum increase of PBI fiber loading i.e. 1%. We found that the addition of the PBI fiber resulted in a modest improvement in the thermal stability and mechanical properties of the prepared composites.

Keywords: PBI fiber, high density polyethylene, composites, melt blending

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Authors: C. B. Le, V. N. Pham

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In modern data analysis, multi-source data appears more and more in real applications. Multi-source data clustering has emerged as a important issue in the data mining and machine learning community. Different data sources provide information about different data. Therefore, multi-source data linking is essential to improve clustering performance. However, in practice multi-source data is often heterogeneous, uncertain, and large. This issue is considered a major challenge from multi-source data. Ensemble is a versatile machine learning model in which learning techniques can work in parallel, with big data. Clustering ensemble has been shown to outperform any standard clustering algorithm in terms of accuracy and robustness. However, most of the traditional clustering ensemble approaches are based on single-objective function and single-source data. This paper proposes a new clustering ensemble method for multi-source data analysis. The fuzzy optimized multi-objective clustering ensemble method is called FOMOCE. Firstly, a clustering ensemble mathematical model based on the structure of multi-objective clustering function, multi-source data, and dark knowledge is introduced. Then, rules for extracting dark knowledge from the input data, clustering algorithms, and base clusterings are designed and applied. Finally, a clustering ensemble algorithm is proposed for multi-source data analysis. The experiments were performed on the standard sample data set. The experimental results demonstrate the superior performance of the FOMOCE method compared to the existing clustering ensemble methods and multi-source clustering methods.

Keywords: clustering ensemble, multi-source, multi-objective, fuzzy clustering

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Authors: Gabriel P. Fife, Saeyong Lee, David M. O'Sullivan

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Introduction: Although investigations into injury characteristics are represented well in the literature, few have investigated the biomechanical characteristics associated with head impacts in Taekwondo. Therefore, the purpose of this study was to identify the kinematic characteristics of head impacts due to taekwondo kicks among non-elite practitioners. Participants: Male participants (n= 11, 175 + 5.3 cm, 71 + 8.3 kg) with 7.5 + 3.6 years of taekwondo training volunteered for this study. Methods: Participants were asked to perform five repetitions of each technique (i.e., turning kick, spinning hook kick, spinning back kick, front axe kick, and clench axe kick) aimed at the Hybrid III head with their dominant kicking leg. All participants wore a protective foot pad (thickness = 12 mm) that is commonly used in competition and training. To simulate head impact in taekwondo, the target consisted of a Hybrid III 50th Percentile Crash Test Dummy (Hybrid III) head (mass = 5.1 kg) and neck (fitted with taekwondo headgear) secured to an aluminum support frame and positioned to each athlete’s standing height. The Hybrid III head form was instrumented with a 500 g tri-axial accelerometer (PCB Piezotronics) mounted to the head center of gravity to obtain resultant linear accelerations (RLA). Rotational accelerations were collected using three angular rate sensors mounted orthogonally to each other (Diversified Technical Systems ARS-12 K Angular Rate Sensor). The accelerometers were interfaced via a 3-channel, battery-powered integrated circuit piezoelectric sensor signal conditioner (PCB Piezotronics) and connected to a desktop computer for analysis. Acceleration data were captured using LABVIEW Signal Express and processed in accordance with SAE J211-1 channel frequency class 1000. Head injury criteria values (HIC) were calculated using the VSRSoftware. A one-way analysis of variance was used to determine differences between kicks, while the Tukey HSD test was employed for pairwise comparisons. The level of significance was set to an effect size of 0.20. All statistical analyses were done using R 3.1.0. Results: A statistically significant difference was observed in RLA (p = 0.00075); however, these differences were not clinically meaningful (η² = 0.04, 95% CI: -0.94 to 1.03). No differences were identified with ROTA (p = 0.734, η² = 0.0004, 95% CI: -0.98 to 0.98). A statistically significant difference (p < 0.001) between kicks in HIC was observed, with a medium effect (η2= 0.08, 95% CI: -0.98 to 1.07). However, the confidence interval of this difference indicates uncertainty. Tukey HSD test identified differences (p < 0.001) between kicking techniques in RLA and HIC. Conclusion: This study observed head impact levels that were comparable to previous studies of similar objectives and methodology. These data are important as impact measures from this study may be more representative of impact levels experienced by non-elite competitors. Although the clench axe kick elicited a lower RLA, the ROTA of this technique was higher than levels from other techniques (although not large differences in reference to effect sizes). As the axe kick has been reported to cause severe head injury, future studies may consider further study of this kick important.

Keywords: Taekwondo, head injury, biomechanics, kicking

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Authors: Ian Marc G. Cabugsa, Zarine M. Hermita

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Phytoextraction capability of T. catappa in contaminated soils was done in the improvised greenhouse. The plant samples were planted to the soil which contained different concentrations of copper. Chelating agent EDTA was added to observe the uptake and translocation of copper in the plant samples. Results showed a significant increase of copper accumulation with the addition of EDTA at 250 and 1250 mgˑkg-1 concentration of copper in the contaminated soils (p<0.05). While translocation of copper was observed in all treatments, translocation of copper is not significantly enhanced by the addition of EDTA (p>0.05). Uptake and translocation were not directly affected the presence of EDTA. Furthermore, this study suggests that the T. catappa is not a hyperaccumulator of copper, and there is no relationship observed between the length of the plant and the copper uptake in all treatments.

Keywords: chelating agent EDTA, hyperaccumulator, phytoextraction, phytoremediation, terminalia catappa

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Authors: Sang Heon Han, Daejun Chang, Won Yang

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NOx reduction characteristics of syngas fuel were numerically investigated for the 2MW pilot scale heavy oil furnace of KITECH (Korea Institute of Industrial Technology). The secondary fuel and syngas was fed into the furnace with two purposes- partial replacement of main fuel and reburning of NOx. Some portion of syngas was fed into the flame zone to partially replace the heavy oil, while the other portion was fed into the furnace downstream to reduce NOx generation. The numerical prediction was verified by comparing it with the experimental results. Syngas of KITECH’s experiment, assumed to be produced from biomass, had very low calorific value and contained 3% hydrocarbon. This study investigated the precise behavior of NOx generation and NOx reduction as well as thermo-fluidic characteristics inside the furnace, which was unavailable with experiment. In addition to 3% hydrocarbon syngas, 5%, and 7% hydrocarbon syngas were numerically tested as reburning fuels to analyze the effect of hydrocarbon proportion to NOx reduction. The prediction showed that the 3% hydrocarbon syngas is as much effective as 7% hydrocarbon syngas in reducing NOx.

Keywords: syngas, reburning, heavy oil, furnace

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Authors: Eui-Jin Kim, Hasik Lee, Su-Jin Park, Dong-Kyu Kim

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Smart-card data are expected to provide information on activity pattern as an alternative to conventional person trip surveys. The focus of this study is to propose a method for training the person trip surveys to supplement the smart-card data that does not contain the purpose of each trip. We selected only available features from smart card data such as spatiotemporal information on the trip and geographic information system (GIS) data near the stations to train the survey data. XGboost, which is state-of-the-art tree-based ensemble classifier, was used to train data from multiple sources. This classifier uses a more regularized model formalization to control the over-fitting and show very fast execution time with well-performance. The validation results showed that proposed method efficiently estimated the trip purpose. GIS data of station and duration of stay at the destination were significant features in modeling trip purpose.

Keywords: activity pattern, data fusion, smart-card, XGboost

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Authors: Dileep Kumar Gupta, Rajendra Prasad, Pradeep Kumar, Varun Narayan Mishra, Ajeet Kumar Vishwakarma, Prashant K. Srivastava

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An approach was evaluated for the retrieval of soil moisture of bare soil surface using bistatic scatterometer data in the angular range of 200 to 700 at VV- and HH- polarization. The microwave data was acquired by specially designed X-band (10 GHz) bistatic scatterometer. The linear regression analysis was done between scattering coefficients and soil moisture content to select the suitable incidence angle for retrieval of soil moisture content. The 250 incidence angle was found more suitable. The support vector regression analysis was used to approximate the function described by the input-output relationship between the scattering coefficient and corresponding measured values of the soil moisture content. The performance of support vector regression algorithm was evaluated by comparing the observed and the estimated soil moisture content by statistical performance indices %Bias, root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE). The values of %Bias, root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE) were found 2.9451, 1.0986, and 0.9214, respectively at HH-polarization. At VV- polarization, the values of %Bias, root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE) were found 3.6186, 0.9373, and 0.9428, respectively.

Keywords: bistatic scatterometer, soil moisture, support vector regression, RMSE, %Bias, NSE

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Authors: Vladimir Simovic, Matija Varga, Tonco Marusic

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This research paper shows matrix technology models and examples of information systems in education (in the Republic of Croatia and in the Germany) in support of business, education (when learning and teaching) and e-learning. Here we researched and described the aims and objectives of the main process in education and technology, with main matrix classes of data. In this paper, we have example of matrix technology with detailed description of processes related to specific data classes in the processes of education and an example module that is support for the process: ‘Filling in the directory and the diary of work’ and ‘evaluation’. Also, on the lower level of the processes, we researched and described all activities which take place within the lower process in education. We researched and described the characteristics and functioning of modules: ‘Fill the directory and the diary of work’ and ‘evaluation’. For the analysis of the affinity between the aforementioned processes and/or sub-process we used our application model created in Visual Basic, which was based on the algorithm for analyzing the affinity between the observed processes and/or sub-processes.

Keywords: designing, education management, information systems, matrix technology, process affinity

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Authors: Giselda Cristina Ferreira, Carlos Alberto Kamienski, Ana Lígia Scott

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The COVID-19 pandemic has enhanced the anti-vaccination movement in Brazil, supported by unscientific theories and false news and the possibility of wide communication through social networks such as Twitter, Facebook, and YouTube. The World Health Organization (WHO) classified the large volume of information on the subject against COVID-19 as an Infodemic. In this paper, we present a protocol to identify polarizing users (called polarizers) and study the profiles of Brazilian polarizers on Twitter (renamed to X some weeks ago). We analyzed polarizing interactions on Twitter (in Portuguese) to identify the main polarizers and how the conflicts they caused influenced the COVID-19 vaccination rate throughout the pandemic. This protocol uses data from this social network, graph theory, Java, and R-studio scripts to model and analyze the data. The information about the vaccination rate was obtained in a public database for the government called OpenDataSus. The results present the profiles of Twitter’s Polarizer (political position, gender, professional activity, immunization opinions). We observed that social and political events influenced the participation of these different profiles in conflicts and the vaccination rate.

Keywords: Twitter, polarization, vaccine, Brazil

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Authors: Haojie Wang, Xun Li, Rui Yin

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In order to solve the memorization overfitting in the model-agnostic meta-learning MAML algorithm, a method of generating mutually exclusive tasks based on data augmentation is proposed. This method generates a mutex task by corresponding one feature of the data to multiple labels so that the generated mutex task is inconsistent with the data distribution in the initial dataset. Because generating mutex tasks for all data will produce a large number of invalid data and, in the worst case, lead to an exponential growth of computation, this paper also proposes a key data extraction method that only extract part of the data to generate the mutex task. The experiments show that the method of generating mutually exclusive tasks can effectively solve the memorization overfitting in the meta-learning MAML algorithm.

Keywords: mutex task generation, data augmentation, meta-learning, text classification.

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Authors: T. Zitoun, M. Bouhadef

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When a partially or completely immersed solid moves in a liquid such as water, it undergoes a force called hydrodynamic drag. Reducing this force has always been the objective of hydrodynamic engineers to make water slide better on submerged bodies. This paper deals with the examination of the different terms composing the analytical solution of the flow over an obstacle embedded at the bottom of a hydraulic channel. We have chosen to use a linear method to study a two-dimensional flow over an obstacle, in order to understand the evolution of the drag. We set the following assumptions: incompressible inviscid fluid, irrotational flow, low obstacle height compared to the water height. Those assumptions allow overcoming the difficulties associated with modelling these waves. We will mathematically formulate the equations that allow the determination of the stream function, and then the free surface equation. A similar method is used to determine the exact analytical solution for an obstacle in the shape of a sinusoidal arch.

Keywords: analytical solution, free-surface wave, hydraulic channel, inviscid fluid

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Authors: Saurav Dhawan, Sanchit Bansal

Abstract:

Background T-MACS is a computer-based decision aid that ‘rules in’ and ‘rules out’ ACS using a combination of the presence or absence of six clinical features with only one biomarker measured on arrival: hs-cTnT. T-MACS had 99.3% negative predictive value and 98.7% sensitivity for ACS, ‘ruling out’ ACS in 40% of patients while ‘ruling in’ 5% at the highest risk. We aim at benchmarking the use of T-MACS which could help to conserve healthcare resources, facilitate early discharges, and ensure safe practice. Methodology Randomized retrospective data collection (n=300) was done from ED electronic records across 3 hospital sites within MFT over a period of 2 months. Data was analysed and compared by percentage for the usage of T-MACS, number of admissions/discharges, and in days for length of stay in hospital. Results MRI A&E had the maximum compliance with the use of T-MACS in the trust at 66%, with minimum admissions (44%) and an average length of stay of 1.825 days. NMG A&E had an extremely low compliance rate (8 %), with 75% admission and 3.387 days as the average length of stay. WYT A&E had no TMACS recorded, with a maximum of 79% admissions and the longest average length of stay at 5.07 days. Conclusion All three hospital sites had a RAG rating of ‘RED’ as per the compliance levels. The assurance level was calculated as ‘Very Limited’ across all sites. There was a positive correlation observed between compliance with TMACS and direct discharges from ED, thereby reducing the average length of stay for patients in the hospital.

Keywords: ACS, discharges, ED, T-MACS

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Authors: Milind Chaudhari, Suhail Balasinor

Abstract:

Due to massive deforestation and an ever-increasing population, the organic content of the soil is depleting at a much faster rate. Due to this, there is a big chance that the entire food production in the world will drop by 40% in the next two decades. Vertical farming can help in aiding food production by leveraging big data and cloud computing to ensure plants are grown naturally by providing the optimum nutrients sunlight by analyzing millions of data points. This paper outlines the most important parameters in vertical farming and how a combination of big data and AI helps in calculating and analyzing these millions of data points. Finally, the paper outlines how different organizations are controlling the indoor environment by leveraging big data in enhancing food quantity and quality.

Keywords: big data, IoT, vertical farming, indoor farming

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Authors: Hamouda M. Mousa, M. Obaid, Chan Hee Park, Cheol Sang Kim

Abstract:

The rate of copper cementation on iron rod was investigated. The study was mainly dedicated to illustrate the effect of application of electromagnetic field (EMF) on the rate of cementation. The magnetic flux was placed parallel to the iron rod and different magnetic field strength was studied. The results showed that without EMF, the rate of mass transfer was correlated by the equation: Sh= 1.36 Re0. 098 Sc0.33. The application of EMF enhanced the time required to reach high percentage copper cementation by 50%. The rate of mass transfer was correlated by the equation: Sh= 2.29 Re0. 95 Sc0.33, with applying EMF. This work illustrates that the enhancement of copper recovery in presence of EMF is due to the induced motion of Fe+n in the solution which is limited in the range of rod rotation speed of 300~900 rpm. The calculation of power consumption of EMF showed that although the application of EMF partially reduced the cementation time, the reduction of power consumption due to utilization of magnetic field is comparable to the increase in power consumed by introducing magnetic field of 2462 A T/m.

Keywords: copper cementation, electromagnetic field, copper ions, iron cylinder

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Authors: Mabrouka Al-Werfalli

Abstract:

This paper aims to highlight reasons beyond the prevalence of “culture of corruption” amongst Libyans. One of the most prominent reason for the Libyan revolution in February 2011 was the pervasiveness of corruption. Corruption in Libya remained a significant problem despite harsh legislation and a robust anti-corruption discourse undertaken by the previous regime. The long-standing political corruption in Libya has offered ample opportunity for the evolution of a structure of negative values and morals. This has formed what is termed as a “culture of corruption”, which has induced people to accept and justify corrupt behaviour. The paper is a part of a study concerns the phenomenon of political alienation in Libya which was based on a survey conducted in 2001 in the city of Benghazi. The finding shows that abuse of power looms large within all activities. Embezzlement and misuse of public funds for personal enrichment is thought to be rife within public bodies, institutions, companies, factories, banks and enterprises owned entirely or partially by the state.

Keywords: corruption, culture of corruption, participation in corruption, abuse of power, embezzlement, political alienation, anti-corruption

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Authors: Georgina Cherry, Taranpreet Rai, Luke Boyden, Sitira Williams, Andrea Wright, Richard Brown, Viva Chu, Alasdair Cook, Kevin Wells

Abstract:

Estimating population-level burden, abilities of pet-parents to identify disease and demand for veterinary services worldwide is challenging. The purpose of this study is to compare a feline pruritus survey with social media listening (SML) data discussing this condition. Surveys are expensive and labour intensive to analyse, but SML data is freeform and requires careful filtering for relevancy. This study considers data from a survey of owner-observed symptoms of 156 pruritic cats conducted using Pet Parade® and SML posts collected through web-scraping to gain insights into the characterisation and management of feline pruritus. SML posts meeting a feline body area, behaviour and symptom were captured and reviewed for relevance representing 1299 public posts collected from 2021 to 2023. The survey involved 1067 pet-parents who reported on pruritic symptoms in their cats. Among the observed cats, approximately 18.37% (n=196) exhibited at least one symptom. The most frequently reported symptoms were hair loss (9.2%), bald spots (7.3%) and infection, crusting, scaling, redness, scabbing, scaling, or bumpy skin (8.2%). Notably, bald spots were the primary symptom reported for short-haired cats, while other symptoms were more prevalent in medium and long-haired cats. Affected body areas, according to pet-parents, were primarily the head, face, chin, neck (27%), and the top of the body, along the spine (22%). 35% of all cats displayed excessive behaviours consistent with pruritic skin disease. Interestingly, 27% of these cats were perceived as non-symptomatic by their owners, suggesting an under-identification of itch-related signs. Furthermore, a significant proportion of symptomatic cats did not receive any skin disease medication, whether prescribed or over the counter (n=41). These findings indicate a higher incidence of pruritic skin disease in cats than recognized by pet owners, potentially leading to a lack of medical intervention for clinically symptomatic cases. The comparison between the survey and social media listening data revealed bald spots were reported in similar proportions in both datasets (25% in the survey and 28% in SML). Infection, crusting, scaling, redness, scabbing, scaling, or bumpy skin accounted for 31% of symptoms in the survey, whereas it represented 53% of relevant SML posts (excluding bumpy skin). Abnormal licking or chewing behaviours were mentioned by pet-parents in 40% of SML posts compared to 38% in the survey. The consistency in the findings of these two disparate data sources, including a complete overlap in affected body areas for the top 80% of social media listening posts, indicates minimal biases in each method, as significant biases would likely yield divergent results. Therefore, the strong agreement across pruritic symptoms, affected body areas, and reported behaviours enhances our confidence in the reliability of the findings. Moreover, the small differences identified between the datasets underscore the valuable insights that arise from utilising multiple data sources. These variations provide additional depth in characterising and managing feline pruritus, allowing for more comprehensive understanding of the condition. By combining survey data and social media listening, researchers can obtain a nuanced perspective and capture a wider range of experiences and perspectives, supporting informed decision-making in veterinary practice.

Keywords: social media listening, feline pruritus, surveys, felines, cats, pet owners

Procedia PDF Downloads 125