Search results for: panel data analysis

Authors: Ágoston Nagy

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This paper introduces a method of using unsupervised machine learning to visualize the feature space of a dataset in 2D, in order to find most characteristic segments in the set. After dimension reduction, users can select clusters by manual drawing. Selected clusters are recorded into a data model that is used for later predictions, based on realtime data. Predictions are made with supervised learning, using Gesture Recognition Toolkit. The paper introduces two example applications: a semantic audio organizer for analyzing incoming sounds, and a gesture database organizer where gestural data (recorded by a Leap motion) is visualized for further manipulation.

Keywords: gesture recognition, machine learning, real-time interaction, visualization

Procedia PDF Downloads 354

Authors: S. Benchelha, H. C. Aoudjehane, M. Hakdaoui, R. El Hamdouni, H. Mansouri, T. Benchelha, M. Layelmam, M. Alaoui

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The logistic regression (LR) and multivariate adaptive regression spline (MarSpline) are applied and verified for analysis of landslide susceptibility map in Oudka, Morocco, using geographical information system. From spatial database containing data such as landslide mapping, topography, soil, hydrology and lithology, the eight factors related to landslides such as elevation, slope, aspect, distance to streams, distance to road, distance to faults, lithology map and Normalized Difference Vegetation Index (NDVI) were calculated or extracted. Using these factors, landslide susceptibility indexes were calculated by the two mentioned methods. Before the calculation, this database was divided into two parts, the first for the formation of the model and the second for the validation. The results of the landslide susceptibility analysis were verified using success and prediction rates to evaluate the quality of these probabilistic models. The result of this verification was that the MarSpline model is the best model with a success rate (AUC = 0.963) and a prediction rate (AUC = 0.951) higher than the LR model (success rate AUC = 0.918, rate prediction AUC = 0.901).

Keywords: landslide susceptibility mapping, regression logistic, multivariate adaptive regression spline, Oudka, Taounate

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Authors: Wanlapa Kunsongkeit

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When a person gets sick, he or she goes to hospital for the treatment. In the case of severe illness, there might be no hope for some patients to recover. In this state, the patients will face anxiety and fear. These feelings make the patients suffer in mind until the time of death or called bad death. These feeling also directly effect to family members who are loved ones and significant persons of the patients. They can help the dying patients to have good death. From literature reviews, many studies focused on good death in patients and nurses. Little is known about good death in family member. Therefore, the qualitative research based on Heideggerian phenomenology aimed to describe good death as perceived by the critically ill patients’ family members. Five informants who were the critically ill patients’ family members at hospital in Chonburi were purposively selected. Data were collected by in-depth interview, observation and critical reflection during January, 2014 to March, 2014 . Cohen, Kahn and Steeves’s (2000) steps guided data analysis. Trustworthiness was maintained throughout the study following Lincoln and Guba’s guidelines. Four themes were emerged, which were no suffering, acceptance of imminent death, preparing for death, and being with the family. This findings provide deep understanding of good death as perceived by the critically ill patients’ family members. It can be basic information for nurses to provide good death nursing care and further explore for development of knowledge regarding good death nursing care.

Keywords: good death, family member, critically ill patient, phenomenology

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Authors: Rabia Khalil

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The aim of the study is to find out the perception of early childhood education teacher‘s about the role and implementation of information communication technology in early childhood education. The main purpose of the study is to investigate the role of information and communication technology in early childhood education as perceived by early childhood education teachers. The objectives of the study were to identify the roles of ICT in today’s early years and the impacts of Information communication technology in early childhood education. This study is to find out the role of ICT at ECE level & how it will be useful for teachers to implement this technique for the development of student skills. This is a quantitative research in which a survey study was conducted. The Population of the study was the primary teachers of the public and private primary schools of Lahore. By using random sampling technique the sample consists of 300 teachers but only 260 respond from 52 primary schools of Lahore. In this research, questionnaire was developed for primary school teachers. The questionnaires were based on liker type scale which comprises of section of strongly agree to strongly disagree. Data were analyzed by using descriptive analysis. The data was arranged and then entered in computer, having the software package for social sciences (SPSS) version 15. The importance of this study is to find out the role of ICT at ECE level & how it will be useful for teachers to implement this technique for the development of student skills.

Keywords: ECE, ICT, PC, C AI

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Authors: Sourabh Yaduvanshi, Varsha Namdeo, Namrata Yaduvanshi

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This study delves into the design and development intricacies of crafting detailed 2D bar charts via d3.js, recognizing its limitations in generating 3D visuals within the Document Object Model (DOM). The study combines three.js with d3.js, facilitating a smooth evolution from 2D to immersive 3D representations. This fusion epitomizes the synergy between front-end technologies, expanding horizons in data visualization. Beyond technical expertise, it symbolizes a creative convergence, pushing boundaries in visual representation. The abstract illuminates methodologies, unraveling the intricate integration of this fusion and guiding enthusiasts. It narrates a compelling story of transcending 2D constraints, propelling data visualization into captivating three-dimensional realms, and igniting creativity in front-end visualization endeavors.

Keywords: design, development, front-end technologies, visualization

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Authors: K. Tejasri, K. Suvarna Vani, S. Prathyusha, S. Ramya

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Proteins are chained sequences of amino acids which are brought together by the peptide bonds. Many varying formations of the chains are possible due to multiple combinations of amino acids and rotation in numerous positions along the chain. Protein structure prediction is one of the crucial goals worked towards by the members of bioinformatics and theoretical chemistry backgrounds. Among the four different structure levels in proteins, we emphasize mainly the secondary level structure. Generally, the secondary protein basically comprises alpha-helix and beta-sheets. Multi-class classification problem of data with disparity is truly a challenge to overcome and has to be addressed for the beta strands. Imbalanced data distribution constitutes a couple of the classes of data having very limited training samples collated with other classes. The secondary structure data is extracted from the protein primary sequence, and the beta-strands are predicted using suitable machine learning algorithms.

Keywords: proteins, secondary structure elements, beta-sheets, beta-strands, alpha-helices, machine learning algorithms

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Authors: Amanda J. Burridge, Keith J. Edwards, Paul A. Wilkinson, Tom Batstone, Erik H. Murchie, Lorna McAusland, Ana Elizabete Carmo-Silva, Ivan Jauregui, Tracy Lawson, Silvere R. M. Vialet-Chabrand

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The rate of genetic progress in wheat production must be improved to meet global food security targets. However, past selection for domestication traits has reduced the genetic variation in modern wheat cultivars, a fact that could severely limit the future rate of genetic gain. The genetic variation in agronomically important traits for the wild relatives and progenitors of wheat is far greater than that of the current domesticated cultivars, but transferring these traits into modern cultivars is not straightforward. Between the elite cultivars of wheat, photosynthetic capacity is a key trait for which there is limited variation. Early screening of wheat wild relative and progenitors has shown differences in photosynthetic capacity and efficiency not only between wild relative species but marked differences between the accessions of each species. By identifying wild relative accessions with improved photosynthetic traits and characterising the genetic variation responsible, it is possible to incorporate these traits into advanced breeding programmes by wide crossing and introgression programmes. To identify the potential variety of photosynthetic capacity and efficiency available in the secondary and tertiary genepool, a wide scale survey was carried out for over 600 accessions from 80 species including those from the genus Aegilops, Triticum, Thinopyrum, Elymus, and Secale. Genotype data were generated for each accession using a ‘Wheat Wild Relative’ Single Nucleotide Polymorphism (SNP) genotyping array composed of 35,000 SNP markers polymorphic between wild relatives and elite hexaploid wheat. This genotype data was combined with phenotypic measurements such as gas exchange (CO₂, H₂O), chlorophyll fluorescence, growth, morphology, and RuBisCO activity to identify potential breeding material with enhanced photosynthetic capacity and efficiency. The data and associated analysis tools presented here will prove useful to anyone interested in increasing the genetic diversity in hexaploid wheat or the application of complex genotyping data to plant breeding.

Keywords: wheat, wild relatives, pre-breeding, genomics, photosynthesis

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Authors: P. Massanyi, L. Kichi, T. Slanina, E. Kolesar, J. Danko, N. Lukac, E. Tvrda, R. Stawarz, A. Kolesarova

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Target of this study was the analysis of the impact of crude glycerol on canine spermatozoa motility, morphology, viability, and membrane integrity. Experiments were realized in vitro. In the study, semen from 5 large dog breeds was used. They were typical representatives of large breeds, coming from healthy rearing, regularly vaccinated and integrated to the further breeding. Semen collections were realized at the owners of animals and in the veterinary clinic. Subsequently the experiments were realized at the Department of Animal Physiology of the SUA in Nitra. The spermatozoa motility was evaluated using CASA analyzer (SpermVisionTM, Minitub, Germany) at the temperature 5 and 37°C for 5 hours. In the study, 13 motility parameters were evaluated. Generally, crude glycerol has generally negative effect on spermatozoa motility. Morphological analysis was realized using Hancock staining and the preparations were evaluated at magnification 1000x using classification tables of morphologically changed spermatozoa. Data clearly detected the highest number of morphologically changed spermatozoa in the experimental groups (know twisted tails, tail torso and tail coiling). For acrosome alterations swelled acrosomes, removed acrosomes and acrosomes with undulated membrane were detected. In this study also the effect of crude glycerol on spermatozoa membrane integrity were analyzed. The highest crude glycerol concentration significantly affects spermatozoa integrity. Results of this study show that crude glycerol has effect of spermatozoa motility, viability, and membrane integrity. Detected changes are related to crude glycerol concentration, temperature, as well as time of incubation.

Keywords: dog, semen, spermatozoa, acrosome, glycerol, CASA, viability

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Authors: Xingyu Gao, Qiang Wu, Yuanyuan Liu, Yue Yang

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In the era of the knowledge economy, the relationship between scientific knowledge and patents has garnered significant attention. Understanding the intricate interplay between the foundations of science and technological innovation has emerged as a pivotal challenge for both researchers and policymakers. This study establishes a coupled network of artificial intelligence patents based on co-cited scientific papers. Leveraging centrality metrics from network analysis offers a fresh perspective on understanding the influence of information flow and knowledge sharing within the network on patent impact. The study initially obtained patent numbers for 446,890 granted US AI patents from the United States Patent and Trademark Office’s artificial intelligence patent database for the years 2002-2020. Subsequently, specific information regarding these patents was acquired using the Lens patent retrieval platform. Additionally, a search and deduplication process was performed on scientific non-patent references (SNPRs) using the Web of Science database, resulting in the selection of 184,603 patents that cited 37,467 unique SNPRs. Finally, this study constructs a coupled network comprising 59,379 artificial intelligence patents by utilizing scientific papers co-cited in patent backward citations. In this network, nodes represent patents, and if patents reference the same scientific papers, connections are established between them, serving as edges within the network. Nodes and edges collectively constitute the patent coupling network. Structural characteristics such as node degree centrality, betweenness centrality, and closeness centrality are employed to assess the scientific connections between patents, while citation count is utilized as a quantitative metric for patent influence. Finally, a negative binomial model is employed to test the nonlinear relationship between these network structural features and patent influence. The research findings indicate that network structural features such as node degree centrality, betweenness centrality, and closeness centrality exhibit inverted U-shaped relationships with patent influence. Specifically, as these centrality metrics increase, patent influence initially shows an upward trend, but once these features reach a certain threshold, patent influence starts to decline. This discovery suggests that moderate network centrality is beneficial for enhancing patent influence, while excessively high centrality may have a detrimental effect on patent influence. This finding offers crucial insights for policymakers, emphasizing the importance of encouraging moderate knowledge flow and sharing to promote innovation when formulating technology policies. It suggests that in certain situations, data sharing and integration can contribute to innovation. Consequently, policymakers can take measures to promote data-sharing policies, such as open data initiatives, to facilitate the flow of knowledge and the generation of innovation. Additionally, governments and relevant agencies can achieve broader knowledge dissemination by supporting collaborative research projects, adjusting intellectual property policies to enhance flexibility, or nurturing technology entrepreneurship ecosystems.

Keywords: centrality, patent coupling network, patent influence, social network analysis

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Authors: Anuj Tyagi, Balwinder Singh, Naveen Kumar B. T., Niraj K. Singh

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Characterization of diverse microbial communities in specific environment plays a crucial role in the better understanding of their functional relationship with the ecosystem. It is now well established that gut microbiome of fish is not the simple replication of microbiota of surrounding local habitat, and extensive species, dietary, physiological and metabolic variations in fishes may have a significant impact on its composition. Moreover, overuse of antibiotics in human, veterinary and aquaculture medicine has led to rapid emergence and propagation of antibiotic resistance genes (ARGs) in the aquatic environment. Microbial communities harboring specific ARGs not only get a preferential edge during selective antibiotic exposure but also possess the significant risk of ARGs transfer to other non-resistance bacteria within the confined environments. This phenomenon may lead to the emergence of habitat-specific microbial resistomes and subsequent emergence of virulent antibiotic-resistant pathogens with severe fish and consumer health consequences. In this study, gut microbiota of freshwater carp (Labeo rohita) was investigated by shotgun metagenomics to understand its taxonomic composition and functional capabilities. Metagenomic DNA, extracted from the fish gut, was subjected to sequencing on Illumina NextSeq to generate paired-end (PE) 2 x 150 bp sequencing reads. After the QC of raw sequencing data by Trimmomatic, taxonomic analysis by Kraken2 taxonomic sequence classification system revealed the presence of 36 phyla, 326 families and 985 genera in the fish gut microbiome. At phylum level, Proteobacteria accounted for more than three-fourths of total bacterial populations followed by Actinobacteria (14%) and Cyanobacteria (3%). Commonly used probiotic bacteria (Bacillus, Lactobacillus, Streptococcus, and Lactococcus) were found to be very less prevalent in fish gut. After sequencing data assembly by MEGAHIT v1.1.2 assembler and PROKKA automated analysis pipeline, pathway analysis revealed the presence of 1,608 Metacyc pathways in the fish gut microbiome. Biosynthesis pathways were found to be the most dominant (51%) followed by degradation (39%), energy-metabolism (4%) and fermentation (2%). Almost one-third (33%) of biosynthesis pathways were involved in the synthesis of secondary metabolites. Metabolic pathways for the biosynthesis of 35 antibiotic types were also present, and these accounted for 5% of overall metabolic pathways in the fish gut microbiome. Fifty-one different types of antibiotic resistance genes (ARGs) belonging to 15 antimicrobial resistance (AMR) gene families and conferring resistance against 24 antibiotic types were detected in fish gut. More than 90% ARGs in fish gut microbiome were against beta-lactams (penicillins, cephalosporins, penems, and monobactams). Resistance against tetracycline, macrolides, fluoroquinolones, and phenicols ranged from 0.7% to 1.3%. Some of the ARGs for multi-drug resistance were also found to be located on sequences of plasmid origin. The presence of pathogenic bacteria and ARGs on plasmid sequences suggested the potential risk due to horizontal gene transfer in the confined gut environment.

Keywords: antibiotic resistance, fish gut, metabolic pathways, microbial diversity

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Authors: Tejasvi Parupudi, Mochen Li, Lakshya Mittal, Ignacio G. Camarillo, Raji Sundararajan

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With breast cancer becoming a global pandemic, it is very important to assess a woman’s risk profile accurately in a timely manner. Providing an estimate of the risk of developing breast cancer to a woman gives her an opportunity to consider options to decrease this risk. Women at low risk may be suggested yearly screenings whereas women with a high risk of developing breast cancer would be candidates for aggressive surveillance. Fortunately, there is a set of risk factors that are used to predict the probability of a woman being diagnosed with breast cancer in the future. Studying risk factors and understanding how they correlate to cancer is important for early diagnosis, prevention and reducing mortality rates. The effect of crucial risk factors among black and white women was compared in this study. The various risk factors analyzed include breast density, age, cancer in a first-degree relative, menopausal status, body mass index (BMI) and prior breast cancer diagnosis, etc. Breast density, age at first full-term birth and BMI were utilized in this study as important risk factors for the comparison of incidence rates between women of black and white races in the USA. Understanding the differences could lead to the development of solutions to reduce disparity in mortality rates among black women by improving overall access to care.

Keywords: big data, breast cancer, risk factors, incidence rates, mortality, race

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Authors: Alisha Fisher

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Sex trafficking is a worldwide crisis that requires trauma-informed and survivor-centered media attention to accurate disseminate information. Much of the previous literature on sex trafficking tends to focus on the frequency of incidents, intervention, and support strategies for survivors, with few of them looking to how the media is conducting their reporting on sex trafficking cases to the public. Utilizing data of reports from the media of cases of sex trafficking in the two Canadian provinces with the highest cases of sex trafficking, Ontario and Nova Scotia, the authors sought to analyze the similarities and differences of how sex trafficking cases were being reported. A total of twenty articles were examined, with ten based within the province of Ontario and the remaining ten from the province of Nova Scotia. The authors coded in two processes, first, who the article was about, and second, the framing and content inclusion. The results suggest that there is high usage and reliance of voices and images of authority, with male people of color being shown as the perpetrators and white women being shown as the survivors. These findings can aid in the expansion of trauma-informed, survivor-centered media literacy of reports of sex trafficking to provide accurate insights and further developing robust methods to intersectional approaches to reporting cases of sex trafficking.

Keywords: sex trafficking, media coverage, Canada sex trafficking, content analysis

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Authors: Veronika Solilová, Danuše Nerudová

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The paper examines the interaction between the environmental taxation, size of government spending on environmental protection and greenhouse gas emissions and gross inland energy consumption. The aim is to analyze the effects of environmental taxation and government spending on environmental protection as an environmental policy instruments on greenhouse gas emissions and gross inland energy consumption in the EU15. The empirical study is performed using a VAR approach with the application of aggregated data of EU15 over the period 1995 to 2012. The results provide the evidence that the reactions of greenhouse gas emission and gross inland energy consumption to the shocks of environmental policy instruments are strong, mainly in the short term and decay to zero after about 8 years. Further, the reactions of the environmental policy instruments to the shocks of greenhouse gas emission and gross inland energy consumption are also strong in the short term, however with the deferred effects. In addition, the results show that government spending on environmental protection together with gross inland energy consumption has stronger effect on greenhouse gas emissions than environmental taxes in EU15 over the examined period.

Keywords: VAR analysis, greenhouse gas emissions, environmental taxation, government spending

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Authors: Thitima Plejai

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The practice in the operating room has been continually performed according to standards of services; however, undesirable incidents from surgical services are found such as surgical complications in the operating room. This participation action research aimed to develop practice guidelines for surgical safety management to reduce undesirable incidents from surgical services in the operating room of Songkhla Hospital. The target population was all 84 members of the multidisciplinary team who were involved in surgical services in the operating room consisting of 28 surgeons from five branches of surgery, 27 anesthetists and nurse anesthetists, and 29 surgical nurses. The data were collected through in-depth interviews, and non-participatory observations. The research instrument was tested by three experts, and the steps of the development consisted of four cycles, each consisting of assessment, planning, practice, practice reflection, and improvement until every step is practicable. The data were validated through triangulation research method, analyzed through content analysis and statistical analysis with number and percentage. The results of the development of practice guidelines surgical safety management to reduce undesirable incidents from surgical services could be concluded as follows. 1) The multidisciplinary team in surgery participated in the needs assessment for development of practice guidelines for surgical patient safety, and agreed on adapting the WHO Surgical Safety Checklists for use. 2) The WHO Surgical Safety Checklists was implemented, and meetings were held for the multidisciplinary team in surgery and the organizational risk committee to improve the practice guidelines to make them more practicable. 3) The multidisciplinary team consisting of surgeons from five branches of surgery, anesthetists, nurse anesthetists, surgical nurses, and the organizational risk committee announced policy on safety for surgical patients; the organizational risk committee designated the Surgical Safety Checklist as an instrument for surgical patient safety. The results of the safety management found that the surgical team members who could follow 100 percent of the guidelines were: professional nurses who checked patient identity and information before taking the patient to the operating room and kept complete records of data on the patients; surgical nurses who checked readiness of the patient before surgery; nurse anesthetists who assessed readiness before administering anesthetic drugs, and confirmed correctness of the patient; and circulating perioperative nurses who gave confirmation to the surgical team after completion of the surgery. The rates of undesirable incidents (surgical complications rates) before and after the implementation of the surgical safety management were 1.60 percent and 0.66 percent, respectively. The satisfaction of the surgery-related teams towards the use of the guidelines was 89 percent. The practice guidelines for surgical safety management to reduce undesirable incidents were taken as guidelines for surgical safety that the multidisciplinary team involved in the surgical process implemented correctly and in the same direction and clearly reduced undesirable incidents in surgical patients.

Keywords: practice guidelines, surgical safety management, reduce undesirable incidents, operating Room

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Authors: A. Er-Raki, D. Hartmann, J. P. Belaud, S. Negny

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This paper has a double purpose: firstly, a literature review of the life cycle analysis (LCA) and secondly a comparison between conventional (static) LCA and multi-level dynamic LCA on the following items: (i) inventories evolution with time (ii) temporal evolution of the databases. The first part of the paper summarizes the state of the art of the static LCA approach. The different static LCA limits have been identified and especially the non-consideration of the spatial and temporal evolution in the inventory, for the characterization factors (FCs) and into the databases. Then a description of the different levels of integration of the notion of temporality in life cycle analysis studies was made. In the second part, the dynamic inventory has been evaluated firstly for a single nuclear plant and secondly for the entire French nuclear power fleet by taking into account the construction durations of all the plants. In addition, the databases have been adapted by integrating the temporal variability of the French energy mix. Several iterations were used to converge towards the real environmental impact of the energy mix. Another adaptation of the databases to take into account the temporal evolution of the market data of the raw material was made. An identification of the energy mix of the time studied was based on an extrapolation of the production reference values of each means of production. An application to the construction of the French nuclear power plants from 1971 to 2000 has been performed, in which a dynamic inventory of raw material has been evaluated. Then the impacts were characterized by the ILCD 2011 characterization method. In order to compare with a purely static approach, a static impact assessment was made with the V 3.4 Ecoinvent data sheets without adaptation and a static inventory considering that all the power stations would have been built at the same time. Finally, a comparison between static and dynamic LCA approaches was set up to determine the gap between them for each of the two levels of integration. The results were analyzed to identify the contribution of the evolving nuclear power fleet construction to the total environmental impacts of the French energy mix during the same period. An equivalent strategy using a dynamic approach will further be applied to identify the environmental impacts that different scenarios of the energy transition could bring, allowing to choose the best energy mix from an environmental viewpoint.

Keywords: LCA, static, dynamic, inventory, construction, nuclear energy, energy mix, energy transition

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Authors: Gurubasavaraju T. M.

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The magnetorheological (MR) damper could provide variable damping force with respect to the different input magnetic field. The damping force could be estimated through computational analysis using finite element and computational fluid dynamics analysis. The double-ended damper operates without changing the total volume of fluid. In this paper, damping force of double ended damper under different magnetic field is computed. Initially, the magneto-statics analysis carried out to evaluate the magnetic flux density across the fluid flow gap. The respective change in the rheology of the MR fluid is computed by using the experimentally fitted polynomial equation of shear stress versus magnetic field plot of MR fluid. The obtained values are substituted in the Herschel Buckley model to express the non-Newtonian behavior of MR fluid. Later, using computational fluid dynamic (CFD) analysis damping characteristics in terms of force versus velocity and force versus displacement for the respective magnetic field is estimated. The purpose of the present approach is to characterize the preliminary designed MR damper before fabricating.

Keywords: MR fluid, double ended MR damper, CFD, FEA

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Authors: Bharat P. Modi, Jayesh M. Patel

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Mobile Internet is acting as a major source of data. As the number of web pages continues to grow the Mobile web provides the data miners with just the right ingredients for extracting information. In order to cater to this growing need, a special term called Mobile Web mining was coined. Mobile Web mining makes use of data mining techniques and deciphers potentially useful information from web data. Web Usage mining deals with understanding the behavior of users by making use of Mobile Web Access Logs that are generated on the server while the user is accessing the website. A Web access log comprises of various entries like the name of the user, his IP address, a number of bytes transferred time-stamp etc. A variety of Log Analyzer tools exists which help in analyzing various things like users navigational pattern, the part of the website the users are mostly interested in etc. The present paper makes use of such log analyzer tool called Mobile Web Log Expert for ascertaining the behavior of users who access an astrology website. It also provides a comparative study between a few log analyzer tools available.

Keywords: mobile web access logs, web usage mining, web server, log analyzer

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Authors: Shreyas S. Hegde, Anindya Deb, Suresh Nagesh

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Computational bio-mechanics is developing rapidly as a non-invasive tool to assist the medical fraternity to help in both diagnosis and prognosis of human body related issues such as injuries, cardio-vascular dysfunction, atherosclerotic plaque etc. Any system that would help either properly diagnose such problems or assist prognosis would be a boon to the doctors and medical society in general. Recently a lot of work is being focused in this direction which includes but not limited to various finite element analysis related to dental implants, skull injuries, orthopedic problems involving bones and joints etc. Such numerical solutions are helping medical practitioners to come up with alternate solutions for such problems and in most cases have also reduced the trauma on the patients. Some work also has been done in the area related to the use of computational fluid mechanics to understand the flow of blood through the human body, an area of hemodynamics. Since cardio-vascular diseases are one of the main causes of loss of human life, understanding of the blood flow with and without constraints (such as blockages), providing alternate methods of prognosis and further solutions to take care of issues related to blood flow would help save valuable life of such patients. This project is an attempt to use computational fluid dynamics (CFD) to solve specific problems related to hemodynamics. The hemodynamics simulation is used to gain a better understanding of functional, diagnostic and theoretical aspects of the blood flow. Due to the fact that many fundamental issues of the blood flow, like phenomena associated with pressure and viscous forces fields, are still not fully understood or entirely described through mathematical formulations the characterization of blood flow is still a challenging task. The computational modeling of the blood flow and mechanical interactions that strongly affect the blood flow patterns, based on medical data and imaging represent the most accurate analysis of the blood flow complex behavior. In this project the mathematical modeling of the blood flow in the arteries in the presence of successive blockages has been analyzed using CFD technique. Different cases of blockages in terms of percentages have been modeled using commercial software CATIA V5R20 and simulated using commercial software ANSYS 15.0 to study the effect of varying wall shear stress (WSS) values and also other parameters like the effect of increase in Reynolds number. The concept of fluid structure interaction (FSI) has been used to solve such problems. The model simulation results were validated using in vivo measurement data from existing literature

Keywords: computational fluid dynamics, hemodynamics, blood flow, results validation, arteries

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Authors: Lexi Li

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This study aims to contribute to the field of how computer technology can be exploited to enhance EFL textbook design. Specifically, the study demonstrates how computerized native and learner corpora can be used to enhance modal verb treatment in EFL textbooks. The linguistic focus is will, would, can, could, may, might, shall, should, must. The native corpus is the spoken component of BNC2014 (hereafter BNCS2014). The spoken part is chosen because the pedagogical purpose of the textbooks is communication-oriented. Using the standard query option of CQPweb, 5% of each of the nine modals was sampled from BNCS2014. The learner corpus is the POS-tagged Ten-thousand English Compositions of Chinese Learners (TECCL). All the essays under the “secondary school” section were selected. A series of five secondary coursebooks comprise the textbook corpus. All the data in both the learner and the textbook corpora are retrieved through the concordance functions of WordSmith Tools (version, 5.0). Data analysis was divided into two parts. The first part compared the patterns of modal verbs in the textbook corpus and BNC2014 with respect to distributional features, semantic functions, and co-occurring constructions to examine whether the textbooks reflect the authentic use of English. Secondly, the learner corpus was compared with the textbook corpus in terms of the use (distributional features, semantic functions, and co-occurring constructions) in order to examine the degree of influence of the textbook on learners’ use of modal verbs. Moreover, the learner corpus was analyzed for the misuse (syntactic errors, e.g., she can sings*.) of the nine modal verbs to uncover potential difficulties that confront learners. The results indicate discrepancies between the textbook presentation of modal verbs and authentic modal use in natural discourse in terms of distributions of frequencies, semantic functions, and co-occurring structures. Furthermore, there are consistent patterns of use between the learner corpus and the textbook corpus with respect to the three above-mentioned aspects, except could, will and must, partially confirming the correlation between the frequency effects and L2 grammar acquisition. Further analysis reveals that the exceptions are caused by both positive and negative L1 transfer, indicating that the frequency effects can be intercepted by L1 interference. Besides, error analysis revealed that could, would, should and must are the most difficult for Chinese learners due to both inter-linguistic and intra-linguistic interference. The discrepancies between the textbook corpus and the native corpus point to a need to adjust the presentation of modal verbs in the textbooks in terms of frequencies, different meanings, and verb-phrase structures. Along with the adjustment of modal verb treatment based on authentic use, it is important for textbook writers to take into consideration the L1 interference as well as learners’ difficulties in their use of modal verbs. The present study is a methodological showcase of the combination both native and learner corpora in the enhancement of EFL textbook language authenticity and appropriateness for learners.

Keywords: EFL textbooks, learner corpus, modal verbs, native corpus

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Authors: Yahaya Abdullahi, Ben Coetzee, Linda Van Den Berg

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The study aimed at establishing the global positioning system (GPS) determined singles match characteristics that act as predictors of successful and less-successful male singles badminton players’ group classification. Twenty-two (22) male single players (aged: 23.39 ± 3.92 years; body stature: 177.11 ± 3.06cm; body mass: 83.46 ± 14.59kg) who represented 10 African countries participated in the study. Players were categorised as successful and less-successful players according to the results of five championships’ of the 2014/2015 season. GPS units (MinimaxX V4.0), Polar Heart Rate Transmitter Belts and digital video cameras were used to collect match data. GPS-related variables were corrected for match duration and independent t-tests, a cluster analysis and a binary forward stepwise logistic regression were calculated. A Receiver Operating Characteristic Curve (ROC) was used to determine the validity of the group classification model. High-intensity accelerations per second were identified as the only GPS-determined variable that showed a significant difference between groups. Furthermore, only high-intensity accelerations per second (p=0.03) and low-intensity efforts per second (p=0.04) were identified as significant predictors of group classification with 76.88% of players that could be classified back into their original groups by making use of the GPS-based logistic regression formula. The ROC showed a value of 0.87. The identification of the last-mentioned GPS-related variables for the attainment of badminton performances, emphasizes the importance of using badminton drills and conditioning techniques to not only improve players’ physical fitness levels but also their abilities to accelerate at high intensities.

Keywords: badminton, global positioning system, match analysis, inertial movement analysis, intensity, effort

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Authors: DEVASHISH KHULBE, MANU PATHAK

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The rise in popularity of major social media platforms have enabled people to share photos and textual information about their daily life. One of the popular topics about which information is shared is food. Since a lot of media about food are attributed to particular locations and restaurants, information like spatio-temporal popularity of various cuisines can be analyzed. Tracking the popularity of food types and retail locations across space and time can also be useful for business owners and restaurant investors. In this work, we present an approach using off-the shelf machine learning techniques to identify trends and popularity of cuisine types in an area using geo-tagged data from social media, Google images and Yelp. After adjusting for time, we use the Kernel Density Estimation to get hot spots across the location and model the dependencies among food cuisines popularity using Bayesian Networks. We consider the Manhattan borough of New York City as the location for our analyses but the approach can be used for any area with social media data and information about retail businesses.

Keywords: Web Mining, Geographic Information Systems, Business popularity, Spatial Data Analyses

Procedia PDF Downloads 117

Authors: Nahla Khatib

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This study investigated several learning difficulties that affected the classroom learning experience of preservice students who are studying general science and methods of teaching science students at Faculty of Educational Studies at the Arab Open University (AOU) in Amman, Jordan. The focus questions for this study were to find answers for the following: 1. What are the main areas of learning difficulty among preservice students towards science education? 2. What are the main aspects of reducing obstacles towards success in science education? To achieve this goal, the researcher prepared a questionnaire which included 30 items to point out the learning difficulties among preservice students towards science education. The questionnaire was distributed among students enrolled in the general science courses 1&2 and methods of teaching science courses at the beginning of the spring semester of year (2013-2014). After collecting the filled questionnaire a descriptive statistical analysis was carried out (means and standard deviation) for the items of the questionnaire. After analyzing the data statistically our findings showed that student control–factors as well as course controlled factor, factors related to the nature of science, and factors related to the role of instructor affected student success toward science education. The study was concluded with a number of recommendations.

Keywords: nature of science, preservice teachers, science education, learning difficulties

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Authors: Michael Aupetit, Mahmoud Al-ismail, Khaled Mohamed

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Cancer is a major public health problem all over the world. Breast cancer has the highest incidence rate over all cancers for women in Qatar making its study a top priority of the country. Human cancer is a dynamic disease that develops over an extended period through the accumulation of a series of genetic alterations. A Darwinian process drives the tumor cells toward higher malignancy growing the branches of a progression tree in the space of genes expression. Although it is not possible to track these genetic alterations dynamically for one patient, it is possible to reconstruct the progression tree from the aggregation of thousands of tumor cells’ genetic profiles from thousands of different patients at different stages of the disease. Analyzing the progression tree is a way to detect pivotal molecular events that drive the malignant evolution and to provide a guide for the development of cancer diagnostics, prognostics and targeted therapeutics. In this work we present the development of a Visual Analytic web platform CanVis enabling users to upload gene-expression data and analyze their progression tree. The server computes the progression tree based on state-of-the-art techniques and allows an interactive visual exploration of this tree and the gene-expression data along its branching structure helping to discover potential driver genes.

Keywords: breast cancer, progression tree, visual analytics, web platform

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Authors: Marina Sartor Hoffer

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The multicultural composition of today's societies poses new challenges to educational contexts. Schools are therefore called first to develop dialogic aptitudes and communicative skills adapted to the complex reality of post-modern societies. It is indispensable for educators and for young people to learn theoretical and practical tools during their scholastic path, in order to allow the knowledge of themselves and of the others with the aim of recognizing the value of the others regardless of their culture. Dialogic Skills help to understand and manage individual differences by allowing the solution of problems and preventing conflicts. The Educational Sector of Eric Berne’s Transactional Analysis offers a range of methods and techniques for this purpose. Educational Transactional Analysis is firmly anchored in the Personalist Philosophy and deserves to be promoted as a theoretical frame suitable to face the challenges of contemporary education. The goal of this paper is therefore to outline some conceptual and methodological signposts for the education to dialogue by drawing concepts and methodologies from educational transactional analysis.

Keywords: dialogic process, education to dialogue, educational transactional analysis, personalism, the good of the relationship

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Authors: Juliana Lukša, Bazilė Ravoitytė, Elena Servienė, Saulius Serva

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Totiviridae L-A virus is a persistent Saccharomyces cerevisiae dsRNA virus. It encodes the major structural capsid protein Gag and Gag-Pol fusion protein, responsible for virus replication and encapsulation. These features also enable the copying of satellite dsRNAs (called M dsRNAs) encoding a secreted toxin and immunity to it (known as killer toxin). Viral capsid pore presumably functions in nucleotide uptake and viral mRNA release. During cell division, sporogenesis, and cell fusion, the virions remain intracellular and are transferred to daughter cells. By employing high throughput RNA sequencing data analysis, we describe the influence of solely L-A virus on the expression of genes in three different S. cerevisiae hosts. We provide a new perception into Totiviridae L-A virus-related transcriptional regulation, encompassing multiple bioinformatics analyses. Transcriptional responses to L-A infection were similar to those induced upon stress or availability of nutrients. It also delves into the connection between the cell metabolism and L-A virus-conferred demands to the host transcriptome by uncovering host proteins that may be associated with intact virions. To better understand the virus-host interaction, we applied differential proteomic analysis of virus particle-enriched fractions of yeast strains that harboreither complete killer system (L-A-lus and M-2 virus), M-2 depleted orvirus-free. Our analysis resulted in the identification of host proteins, associated with structural proteins of the virus (Gag and Gag-Pol). This research was funded by the European Social Fund under the No.09.3.3-LMT-K-712-19-0157“Development of Competences of Scientists, other Researchers, and Students through Practical Research Activities” measure.

Keywords: totiviridae, killer virus, proteomics, transcriptomics

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Authors: Farhad Fakoursevom

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Heart disease is one of the diseases which is found in abundance today. Various types of surgeries, such as bypasses, angiography, angioplasty, etc., are used to treat patients. People may receive such surgeries, some of which are invasive and some non-invasive, throughout their lives. People might cope with pre-surgery anxiety and stress, which can disrupt their normal life and even reduce the effects of the surgery, so the desired result can not be achieved in surgery. Considering this issue, the present study aimed to do a comparative assessment of people who received sedatives before surgery and people who did not receive sedatives. In terms of the purpose, this is an applied research and descriptive survey in terms of method. The statistical population included patients who underwent surgeries in the specialist heart hospitals of Mashhad, Iran; 60 people were considered as a statistical population, 30 of them received sedatives before surgery, and 30 others had not received sedatives before surgery. Valid and up-to-date articles were systematically used to collect theoretical bases, and a researcher-made questionnaire was used to examine the level of stress and anxiety of people. The questionnaire content validity was assessed by a panel of experts in psychology and medicine. The construct validity was tested using the software. Cronbach's alpha and composite reliability were used for reliability, which shows the appropriate reliability of the questionnaire. SPSS software was used to compare the research results between two groups, and the research findings showed that there is no significant association between the people who received sedatives and those who did not receive sedatives in terms of the amount of stress and anxiety. The longer the time of taking the drugs before the surgery, the more the mental peace of the patients will be. According to the results, it can be said that if we don't need to have an emergency operation and need more time, we have to use sedative drugs with different doses compared to the severity of the surgery, and also in case of a medical emergency such as heart surgery due to a stroke, we have to take advantage of psychological services during and before the operation and sedative drugs so that the patients can control their stress and anxiety and achieve better outcomes.

Keywords: sedative drugs, stress, anxiety, surgery

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Authors: Zhu Zhizheng, Huang Yong, Li Tong

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In the context of land and space development and resource environmental protection. Due to its special geographical location, mountain-plain transition zones are limited by many factors such as topography, mountain forest protection, etc., and their ecology is also more sensitive, with the characteristics of disaster susceptibility and resource gradient. Taking Dujiangyan City, Chengdu as an example, this paper establishes resilience evaluation indicators on the basis of ecological suitability evaluation through the analysis of current situation data and relevant policies: water conservation evaluation, soil and water conservation evaluation, biodiversity evaluation, soil erosion sensitivity evaluation, etc. Based on GIS spatial analysis, the ecological suitability and resilience evaluation results of Dujiangyan city were obtained by disjunction operation. The ecological resilience level of Dujiangyan city was divided into three categories: high, medium and low, with an area ratio of 50.81%, 16.4% and 32.79%, respectively. This paper can provide ideas for solving the contradiction between man and land in the mountain-plain transition zones, and also provide a certain basis for the construction of regional ecological protection and the delineation of three zones and three lines.

Keywords: urban and rural planning, ecological resilience, dujiangyan city, mountain-plain transition zones

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Authors: Vineetha Bettaiah, Heggere S. Ranganath

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This paper presents a Hierarchical Piecewise Linear Approximation (HPLA) for the representation of time series data in which the time series is treated as a curve in the time-amplitude image space. The curve is partitioned into segments by choosing perceptually important points as break points. Each segment between adjacent break points is recursively partitioned into two segments at the best point or midpoint until the error between the approximating line and the original curve becomes less than a pre-specified threshold. The HPLA representation achieves dimensionality reduction while preserving prominent local features and general shape of time series. The representation permits course-fine processing at different levels of details, allows flexible definition of similarity based on mathematical measures or general time series shape, and supports time series data mining operations including query by content, clustering and classification based on whole or subsequence similarity.

Keywords: data mining, dimensionality reduction, piecewise linear representation, time series representation

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Authors: T. S. Beerenahally, S. Amruthavalli, C. M. Munegowda, Leelavathi, Nagarathna

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Introduction: In majority of urban India, the health system is split between different authorities being responsible for the health care of urban population. We believe that, apart from poor awareness and financial barriers to care, there are other health system barriers which affect quality and access to care for people with diabetes. In this paper, we attempted to identify health system complexity that determines access to public health system for diabetes care in KG Halli, a poor urban neighborhood in Bengaluru. The KG Halli has been a locus of a health systems research from 2009 to 2015. Methodology: The source of data is from the observational field-notes written by research team as part of urban health action research project (UHARP). Field notes included data from the community and the public primary care center. The data was generated by the community health assistants and the other research team members during regular home visits and interaction with individuals who self-reported to be diabetic over four years as part of UHARP. Results: It emerged during data analysis that the patients were not keen on utilizing primary public health center for many reasons. Patient has felt that the service provided at the center was not integrated. There was lack of availability of medicines, with a regular stock out of medicines in a year and laboratory service for investigation was limited. Many of them said that the time given by the providers was not sufficient and there was also a feeling of providers not listening to them attentively. The power dynamics played a huge role in communication. Only the consultation was available for free of cost at the public primary care center. The patient had to spend for the investigations and the major portion for medicine. Conclusion: Diabetes is a chronic disease that poses an important emerging public health concern. Most of the financial burden is borne by the family as the public facilities have failed to provide free care in India. Our study indicated various factors including individual beliefs, stigma and financial constraints affecting compliance to diabetes care.

Keywords: diabetes care, disintegrated health system, quality of care, urban health

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Authors: Hary Aprianto Wijaya Siahaan, Bayu Edo Pratama

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Sea fishery's potential to become one of the nation's assets which very contributed to Indonesia's economy. This fishery potential not in spite of the availability of the chlorophyll in the territorial waters of Indonesia. The research was conducted using three methods, namely: statistics, comparative and analytical. The data used include MODIS sea temperature data imaging results in Aqua satellite with a resolution of 4 km in 2002-2015, MODIS data of chlorophyll-a imaging results in Aqua satellite with a resolution of 4 km in 2002-2015, and Imaging results data ASCAT on MetOp and NOAA satellites with 27 km resolution in 2002-2015. The results of the processing of the data show that the incidence of upwelling in the south of East Java Sea began to happen in June identified with sea surface temperature anomaly below normal, the mass of the air that moves from the East to the West, and chlorophyll-a concentrations are high. In July the region upwelling events are increasingly expanding towards the West and reached its peak in August. Chlorophyll-a concentration prediction using multiple linear regression equations demonstrate excellent results to chlorophyll-a concentrations prediction in 2002 until 2015 with the correlation of predicted chlorophyll-a concentration indicate a value of 0.8 and 0.3 with RMSE value. On the chlorophyll-a concentration prediction in 2016 indicate good results despite a decline in the value of the correlation, where the correlation of predicted chlorophyll-a concentration in the year 2016 indicate a value 0.6, but showed improvement in RMSE values with 0.2.

Keywords: satellite, sea surface temperature, upwelling, wind stress

Procedia PDF Downloads 158