Search results for: spatio-temporal data

Authors: Samina Khalid, Shamila Nasreen

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Dimensionality reduction as a preprocessing step to machine learning is effective in removing irrelevant and redundant data, increasing learning accuracy, and improving result comprehensibility. However, the recent increase of dimensionality of data poses a severe challenge to many existing feature selection and feature extraction methods with respect to efficiency and effectiveness. In the field of machine learning and pattern recognition, dimensionality reduction is important area, where many approaches have been proposed. In this paper, some widely used feature selection and feature extraction techniques have analyzed with the purpose of how effectively these techniques can be used to achieve high performance of learning algorithms that ultimately improves predictive accuracy of classifier. An endeavor to analyze dimensionality reduction techniques briefly with the purpose to investigate strengths and weaknesses of some widely used dimensionality reduction methods is presented.

Keywords: age related macular degeneration, feature selection feature subset selection feature extraction/transformation, FSA’s, relief, correlation based method, PCA, ICA

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Authors: Magdalena Hasplova, Katerina Ivanova

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Perinatal palliative care is a relatively young and developing field that includes the care of a fetus or newborn with a life-threatening or limiting defect and his family. However, the training of midwives in perinatal palliative care is insufficient and midwives do not feel prepared for this aspect of their work. This fact can affect the barriers to communication with the mother or family of the endangered child. The main aim was to analyze the awareness of midwifery students on the issue of perinatal palliative care in the Czech Republic. Based on the analysis, draw attention to possible communication barriers that may be caused by insufficient information. The research was carried out using a qualitative method, the method of data collection was a semi-structured interview. Eleven female students took part in the research, and the respondents were selected using the Snowballing method. Some methods of grounded theory (open coding and category creation) were used to analyze the data. Based on the results of the research, questions were set in a questionnaire focused on communication barriers between mothers (family) and health care professionals in the care of newborns with life-threatening or limiting disabilities. Based on the analysis of data, categories 1 were determined. Knowledge of perinatal palliative care 2. Education 3. Practical experience 4. Readiness and concerns in the provision of perinatal palliative care 6. Supervision. The questions in the questionnaire were then derived taking into account the data obtained, and the operationalization of health literacy in the field of perinatal palliative care was performed. The analysis of the interviews revealed that the education of midwives in the Czech Republic in the issue of perinatal palliative care is not uniform. The research confirmed the insufficient knowledge and skills of midwifery students preparing to provide perinatal palliative care. Respondents reported feelings of unpreparedness in the areas of communication with a woman after perinatal loss, psychological support for a woman and her family, the care of a stillborn or dying child, or self-coping with death. The questions in the questionnaire then develop these areas. We assumed that by analyzing and interpreting the data obtained from our research, we will help to better understand the concerns and motivations of students in providing holistic perinatal palliative care. We came to the conclusion that it would be appropriate to set up a unified and comprehensive education on this issue in the Czech Republic. Healthcare professionals are in a unique position that can positively or negatively affect the intensity of perinatal loss. Already properly set up education of health professionals leads to overcoming barriers in communication between health professionals and the family, experiencing perinatal loss.

Keywords: midwife, perinatal loss, perinatal palliative care, communication, barriers, mothers, family

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Authors: Rajendra Chetty

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This paper analyses the experiences of teachers of literacy in underprivileged schools in the Western Cape, South Africa. The purpose is to provide teachers in poorly resourced schools within economically deprived areas an opportunity to voice their experiences of teaching literacy. The paper is based on an empirical study using interviews and classroom observation. A descriptive account of the observation data was followed by an interpretive analysis. The content analysis of the interview data led to the development of themes and patterns for the discussion. The study reveals key factors for literacy underachievement that include lack of critical and emancipatory pedagogies, resources, parental support, lack of teacher knowledge, absence of cognitive activities, and the social complexity of poverty. The paper recommends that a new model of literacy that is underpinned by critical pedagogy challenge inequality and provides strategic and sustained teacher support in disadvantaged schools is crucial in a society emerging from oppression and racism.

Keywords: critical pedagogy, disadvantaged schools, literacy, poverty

Procedia PDF Downloads 89

Authors: Amira Rjiba, Mohamed Ghanmi, Tahar Aifa, Achref Boulares

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This study, involving the interpretation of geological outcrops data (structures, and lithostratigraphiec colones) and subsurface structures (seismic and gravimetric data) help us to identify and precise (i) the lithology of the sedimentary formations between the Aptian and the recent formations, (ii) to differentiate the sedimentary formations it from the salt-bearing Triassic (iii) and to specify the major structures though the tectonics effects having affected the region during its geological evolution. By placing our study area placed in the context of Tunisia, located on the southern margin of the Tethys show us through tectonic traces and structural analysis conducted, that this area was submitted during the Triassic perio at an active rifting triggered extensional tectonic events and extensive respectively in the Cretaceous and Paleogene. Lithostratigraphic correlations between outcrops and seismic data sets on those of six oil wells conducted in the region have allowed us to better understand the structural complexity and the role of different tectonic faults having contributed to the current configuration, and marked by the current rifts. Indeed, three directions of NW-SE faults, NNW-SSE to NS and NE-SW to EW had a major role in the genesis of folds and open ditches collapse of NW-SE direction. These results were complemented by seismic reflection data to clarify the geometry of the southern and western areas of Kalaa Khasba ditch. The eight selected seismic lines for this study allowed to characterize the main structures, with isochronous maps, contour and isovitesse of Serdj horizon that presents the main reservoir in the region. The line L2, keyed by the well 6, helped highlight the NW-SE compression that has resulted in persistent discrepancies widely identifiable in its lithostratigraphic column. The gravity survey has confirmed the extension of most of the accidents deep subsurface whose activity seems to go far. Gravimetry also reinforced seismic interpretation confirming, at the L2 well, that both SW and NE flank of the moat are two opposite faults and trace the boundaries of NNW-SSE direction graben whose sedimentation of Mio-Pliocene age and Quaternary.

Keywords: graben, graben collapse, gravity, Kalat Es Senan, seismic, tectogenesis

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Authors: Abhisek Chakrabarty, Subhraprakash Mandal

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Flash flood is one of the catastrophic natural hazards in the mountainous region of India. The recent flood in the Mandakini River in Kedarnath (14-17th June, 2013) is a classic example of flash floods that devastated Uttarakhand by killing thousands of people.The disaster was an integrated effect of high intensityrainfall, sudden breach of Chorabari Lake and very steep topography. Every year in Himalayan Region flash flood occur due to intense rainfall over a short period of time, cloud burst, glacial lake outburst and collapse of artificial check dam that cause high flow of river water. In Sikkim-Derjeeling Himalaya one of the probable flash flood occurrence zone is Teesta Watershed. The Teesta River is a right tributary of the Brahmaputra with draining mountain area of approximately 8600 Sq. km. It originates in the Pauhunri massif (7127 m). The total length of the mountain section of the river amounts to 182 km. The Teesta is characterized by a complex hydrological regime. The river is fed not only by precipitation, but also by melting glaciers and snow as well as groundwater. The present study describes an attempt to model surface runoff in upper Teesta basin, which is directly related to catastrophic flood events, by creating a system based on GIS technology. The main object was to construct a direct unit hydrograph for an excess rainfall by estimating the stream flow response at the outlet of a watershed. Specifically, the methodology was based on the creation of a spatial database in GIS environment and on data editing. Moreover, rainfall time-series data collected from Indian Meteorological Department and they were processed in order to calculate flow time and the runoff volume. Apart from the meteorological data, background data such as topography, drainage network, land cover and geological data were also collected. Clipping the watershed from the entire area and the streamline generation for Teesta watershed were done and cross-sectional profiles plotted across the river at various locations from Aster DEM data using the ERDAS IMAGINE 9.0 and Arc GIS 10.0 software. The analysis of different hydraulic model to detect flash flood probability ware done using HEC-RAS, Flow-2D, HEC-HMS Software, which were of great importance in order to achieve the final result. With an input rainfall intensity above 400 mm per day for three days the flood runoff simulation models shows outbursts of lakes and check dam individually or in combination with run-off causing severe damage to the downstream settlements. Model output shows that 313 Sq. km area were found to be most vulnerable to flash flood includes Melli, Jourthang, Chungthang, and Lachung and 655sq. km. as moderately vulnerable includes Rangpo,Yathang, Dambung,Bardang, Singtam, Teesta Bazarand Thangu Valley. The model was validated by inserting the rain fall data of a flood event took place in August 1968, and 78% of the actual area flooded reflected in the output of the model. Lastly preventive and curative measures were suggested to reduce the losses by probable flash flood event.

Keywords: flash flood, GIS, runoff, simulation model, Teesta river basin

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Authors: Zahra Mirsanjari

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Research in the field of education has widely documented that teachers’ sense of efficacy has strong impacts on various aspects of teaching and learning. The present study is an attempt to examine Iranian EFL teachers’ degree of self-efficacy for teaching English. The data required for the study was gathered from Iranian EFL teachers teaching English as a foreign language in different schools and language institutes in Iran. Data were collected using Teacher’s Sense of Efficacy Scale (TSES). Results identified four dimensions of teachers’ English teaching-specific sense of efficacy: instructional strategies, classroom Management, Student Engagement, and Oral English Language Use.It was also found that teachers rated their self-efficacy in teaching English at a moderate level in the dimensions of instructional strategies, classroom management, and student engagement. Results have implications for language teachers and practitioners.

Keywords: self-efficacy, English Language teaching, EFL teachers, language teachers and practitioners.

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Authors: Saba Ebrahimi, Saeed Ahmadian, Hedie Ashrafi

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World-wide spread of coronavirus grows the concern about planning for the excess demand of hospital services in response to COVID-19 pandemic. The surge in the hospital services demand beyond the current capacity leads to shortage of ICU beds and ventilators in some parts of US. In this study, we forecast the required number of hospital beds and possible shortage of beds in US during COVID-19 pandemic to be used in the planning and hospitalization of new cases. In this paper, we used a data on COVID-19 deaths and patients’ hospitalization besides the data on hospital capacities and utilization in US from publicly available sources and national government websites. we used a novel ensemble modelling of deep learning networks, based on stacking different linear and non-linear layers to predict the shortage in hospital beds. The results showed that our proposed approach can predict the excess hospital beds demand very well and this can be helpful in developing strategies and plans to mitigate this gap.

Keywords: COVID-19, deep learning, ensembled models, hospital capacity planning

Procedia PDF Downloads 137

Authors: Sara Ignoto, Elena M. Scalisi, Carmen Sica, Martina Contino, Greta Ferruggia, Antonio Salvaggio, Santi C. Pavone, Gino Sorbello, Loreto Di Donato, Roberta Pecoraro, Maria V. Brundo

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The new fifth generation technology (5G), which should favor high data-rate connections (1Gbps) and latency times lower than the current ones (<1ms), has the characteristic of working on different frequency bands of the radio wave spectrum (700 MHz, 3.6-3.8 GHz and 26.5-27.5 GHz), thus also exploiting higher frequencies than previous mobile radio generations (1G-4G). The higher frequency waves, however, have a lower capacity to propagate in free space and therefore, in order to guarantee the capillary coverage of the territory for high reliability applications, it will be necessary to install a large number of repeaters. Following the introduction of this new technology, there has been growing concern in recent years about the possible harmful effects on human health and several studies were published using several animal models. This study aimed to observe the possible short-term effects induced by 5G-millimeter waves on heartbeat of early life stages of Danio rerio using DanioScope software (Noldus). DanioScope is the complete toolbox for measurements on zebrafish embryos and larvae. The effect of substances can be measured on the developing zebrafish embryo by a range of parameters: earliest activity of the embryo’s tail, activity of the developing heart, speed of blood flowing through the vein, length and diameters of body parts. Activity measurements, cardiovascular data, blood flow data and morphometric parameters can be combined in one single tool. Obtained data are elaborate and provided by the software both numerical as well as graphical. The experiments were performed at 27 GHz by a no commercial high gain pyramidal horn antenna. According to OECD guidelines, exposure to 5G-millimeter waves was tested by fish embryo toxicity test within 96 hours post fertilization, Observations were recorded every 24h, until the end of the short-term test (96h). The results have showed an increase of heartbeat rate on exposed embryos at 48h hpf than control group, but this increase has not been shown at 72-96 h hpf. Nowadays, there is a scant of literature data about this topic, so these results could be useful to approach new studies and also to evaluate potential cardiotoxic effects of mobile radiofrequency.

Keywords: Danio rerio, DanioScope, cardiotoxicity, millimeter waves.

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Authors: Yihua Wang, Yunru Lai

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Statistical process control has been successfully applied in a variety of industries. In some applications, the quality of a process or product is better characterized and summarized by a functional relationship between a response variable and one or more explanatory variables. A collection of this type of data is called a profile. Profile monitoring is used to understand and check the stability of this relationship or curve over time. The independent assumption for the error term is commonly used in the existing profile monitoring studies. However, in many applications, the profile data show correlations over time. Therefore, we focus on a general linear regression model with a first-order autocorrelation between profiles in this study. We propose an exponentially weighted moving average charting scheme to monitor this type of profile. The simulation study shows that our proposed methods outperform the existing schemes based on the average run length criterion.

Keywords: autocorrelation, EWMA control chart, general linear regression model, profile monitoring

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Authors: Andrea Giacomelli, Luciano Massetti, Elena Maggi, Antonio Raschi

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The presentation will report the activities managed during the Summer of 2017 by a team composed by staff from a University Department, a National Research Council Institute, and an outreach NGO, collecting measurements of night sky brightness and other information on artificial lighting, in order to characterize light pollution issues on portions of the Tuscan coast, in Central Italy. These activities combine measurements collected by the principal scientists, citizen science observations led by students, and outreach events targeting a broad audience. This campaign aggregates the efforts of three actors: the BuioMetria Partecipativa project, which started collecting light pollution data on a national scale in 2008 with an environmental engineering and free/open source GIS core team; the Institute of Biometeorology from the National Research Council, with ongoing studies on light and urban vegetation and a consolidated track record in environmental education and citizen science; the Department of Biology from the University of Pisa, which started experiments to assess the impact of light pollution in coastal environments in 2015. While the core of the activities concerns in situ data, the campaign will account also for remote sensing data, thus considering heterogeneous data sources. The aim of the campaign is twofold: (1) To test actions of citizen and student engagement in monitoring sky brightness (2) To collect night sky brightness data and test a protocol for applications to studies on the ecological impact of light pollution, with a special focus on marine coastal ecosystems. The collaboration of an interdisciplinary team in the study of artificial lighting issues is not a common case in Italy, and the possibility of undertaking the campaign in Tuscany has the added value of operating in one of the territories where it is possible to observe both sites with extremely high lighting levels, and areas with extremely low light pollution, especially in the Southern part of the region. Combining environmental monitoring and communication actions in the context of the campaign, this effort will contribute to the promotion of night skies with a good quality as an important asset for the sustainability of coastal ecosystems, as well as to increase citizen awareness through star gazing, night photography and actively participating in field campaign measurements.

Keywords: citizen science, light pollution, marine coastal biodiversity, environmental education

Procedia PDF Downloads 158

Authors: Jiwan Kumar, Pooja, Sandeep Negi, Anjum Rouf, Amit Kumar, Naveen Lakra

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In modern times where, health issues are increasing day by day, breast cancer is also one of them, which is very crucial and really important to find in the early stages. Doctors can use this model in order to tell their patients whether a cancer is not harmful (benign) or harmful (malignant). We have used the knowledge of machine learning in order to produce the model. we have used algorithms like Logistic Regression, Random forest, support Vector Classifier, Bayesian Network and Radial Basis Function. We tried to use the data of crucial parts and show them the results in pictures in order to make it easier for doctors. By doing this, we're making ML better at finding breast cancer, which can lead to saving more lives and better health care.

Keywords: Bayesian network, radial basis function, ensemble learning, understandable, data making better, random forest, logistic regression, breast cancer

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Authors: Stefanie Rukavina, Sascha Gruss, Steffen Walter, Holger Hoffmann, Harald C. Traue

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OPEN-EmoRecII is an open multimodal corpus with experimentally induced emotions. In the first half of the experiment, emotions were induced with standardized picture material and in the second half during a human-computer interaction (HCI), realized with a wizard-of-oz design. The induced emotions are based on the dimensional theory of emotions (valence, arousal and dominance). These emotional sequences - recorded with multimodal data (mimic reactions, speech, audio and physiological reactions) during a naturalistic-like HCI-environment one can improve classification methods on a multimodal level. This database is the result of an HCI-experiment, for which 30 subjects in total agreed to a publication of their data including the video material for research purposes. The now available open corpus contains sensory signal of: video, audio, physiology (SCL, respiration, BVP, EMG Corrugator supercilii, EMG Zygomaticus Major) and mimic annotations.

Keywords: open multimodal emotion corpus, annotated labels, intelligent interaction

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Authors: Fahsai Pawapootanont, Sasithon Yuwakosol

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The objectives of this research study are as follows: 1) Study the information-seeking behavior of followers of influencers on Facebook in making hotel booking decisions and 2) Study the characteristics of travel influencers that affect their followers' hotel booking decisions. The Data was collected by interviewing 35 key informants, consisting of 25 Thai tourists who were followers of travel influencers and 10 travel influencers, as well as collecting data using online questionnaires from a sample of 400 Thai tourists and using statistical data analysis: percentage, standard deviation, mean, T-Test and One-Way Analysis of Variance: ANOVA. The results of the influence of travel influencers on Facebook on hotel booking decisions in Thailand revealed the following: People in different age groups have different information-seeking behaviours. Depends on experience and aptitude in using technology. The sample group did not seek information from only one source. There is also a search for information from various places in order to get comparative information and the most truthful information to make decisions. In addition, travel influencers should be those who present honest, clear, and complete content. And present services honestly. In addition to the characteristics of travel influencers affecting hotel booking decisions, Presentation formats and platforms also affect hotel booking decisions. But it must be designed and presented to suit the behavior of the group of people we want. As for the influence of travel influencers, it can be concluded that The influence of travel influencers can influence their followers' interests and hotel booking decisions. However, it was found that there are other factors that followers of travel influencers on Facebook will factor into their decision to book a hotel, such as Whether the hotel's comfort meets your needs or not; location, price, and promotions also play an important role in deciding to book a hotel.

Keywords: influencer, travel, facebook, hotel booking decisions, Thailand

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Authors: Tahereh Samenian

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There is ample evidence that source and goal are disproportionately expressed in languages, and goal usually plays a more prominent role than source. The results show that the mismatch between the goal and the source is not entirely rooted in non-linguistic behaviors, i.e. that linguistic descriptions also show the focus of the goal on the source in events; Non-verbal memory for events, on the other hand, indicates that the focus of the goal is only on events that are purposefully moving and the actor is alive. In the present study, an attempt is made to examine the principle of priority of the goal over the source by focusing on Persian directional motion verbs. For this purpose, 117 Persian directional motion verbs have been selected from the dictionary and data for them have been collected from the body of Bijan Khan and the components of goal and source have been identified in sentences and the prominence of the components of goal and source has been shown in the form of diagrams. As it was obtained from the data, Persian motion-directional verbs also showed the bias of the goal over source in motion events.

Keywords: motion-directional verbs, priority of goal over source principle, cognitive factors, linguistic factors

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Authors: Tooraj Karimi, Mohammadreza Sadeghi Moghadam

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Grey set theory has the advantage of using fewer data to analyze many factors, and it is therefore more appropriate for system study rather than traditional statistical regression which require massive data, normal distribution in the data and few variant factors. So, in this paper grey clustering and entropy of coefficient vector of grey evaluations are used to analyze energy consumption in buildings of the Oil Ministry in Tehran. In fact, this article intends to analyze the results of energy audit reports and defines most favorable characteristics of system, which is energy consumption of buildings, and most favorable factors affecting these characteristics in order to modify and improve them. According to the results of the model, ‘the real Building Load Coefficient’ has been selected as the most important system characteristic and ‘uncontrolled area of the building’ has been diagnosed as the most favorable factor which has the greatest effect on energy consumption of building. Grey clustering in this study has been used for two purposes: First, all the variables of building relate to energy audit cluster in two main groups of indicators and the number of variables is reduced. Second, grey clustering with variable weights has been used to classify all buildings in three categories named ‘no standard deviation’, ‘low standard deviation’ and ‘non- standard’. Entropy of coefficient vector of Grey evaluations is calculated to investigate greyness of results. It shows that among the 38 buildings surveyed in terms of energy consumption, 3 cases are in standard group, 24 cases are in ‘low standard deviation’ group and 11 buildings are completely non-standard. In addition, clustering greyness of 13 buildings is less than 0.5 and average uncertainly of clustering results is 66%.

Keywords: energy audit, grey set theory, grey incidence matrixes, grey clustering, Iran oil ministry

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Authors: Makrina Tindangen

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The problems faced by participants of teacher profession program in Faculty of teaching and education Mulawarman University is professional and pedagogic competence. Professional competence related to the mastery of teaching materials, while pedagogic competence related with the ability to plan and to implement learning. Based on the problems, the purpose of the research is to maximize the role of companion teacher for the achievement of professional and pedagogic competencies in the workshop of the participants of teacher professional education in the Faculty of Teaching and Education of Mulawarman University. Qualitative research method with interview guidance and document to get in-depth data on how to maximize the role of companion teachers in the achievement of professional and pedagogic competencies in the workshop participants of professional education participants. Location of this research is on the Faculty of Teaching and Education of Mulawarman University, Samarinda City, East Kalimantan Province. Research respondents were 12 teachers of workshop facilitator. Descriptive data analysis is through interpretation of interview data. The conclusion of the research result, how to maximize the role of assistant teachers in workshop activities for the professional competence and pedagogic competence of professional teacher training program participants, through facilitation activities conducted by teachers of companion related to real problems faced by students in school, so that the workshop participants have professional competence and pedagogic as an initial competence before carrying out practical activities of field experience in school.

Keywords: companion teacher, professional and pedagogical competence, activities, workshop participants

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Authors: Ciara Pienaar, J. W. Odendaal, J. Joubert, J. C. Smit

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Radar cross section (RCS) of dielectric objects play an important role in many applications, such as low observability technology development, drone detection, and monitoring as well as coastal surveillance. Various materials are used to construct the targets of interest such as metal, wood, composite materials, radar absorbent materials, and other dielectrics. Since simulated datasets are increasingly being used to supplement infield measurements, as it is more cost effective and a larger variety of targets can be simulated, it is important to have a high level of confidence in the predicted results. Confidence can be attained through validation. Various computational electromagnetic (CEM) methods are capable of predicting the RCS of dielectric targets. This study will extend previous studies by validating full-wave and asymptotic RCS simulations of dielectric targets with measured data. The paper will provide measured RCS data of a number of canonical dielectric targets exhibiting different material properties. As stated previously, these measurements are used to validate numerous CEM methods. The dielectric properties are accurately characterized to reduce the uncertainties in the simulations. Finally, an analysis of the sensitivity of oblique and normal incidence scattering predictions to material characteristics is also presented. In this paper, the ability of several CEM methods, including method of moments (MoM), and physical optics (PO), to calculate the RCS of dielectrics were validated with measured data. A few dielectrics, exhibiting different material properties, were selected and several canonical targets, such as flat plates and cylinders, were manufactured. The RCS of these dielectric targets were measured in a compact range at the University of Pretoria, South Africa, over a frequency range of 2 to 18 GHz and a 360° azimuth angle sweep. This study also investigated the effect of slight variations in the material properties on the calculated RCS results, by varying the material properties within a realistic tolerance range and comparing the calculated RCS results. Interesting measured and simulated results have been obtained. Large discrepancies were observed between the different methods as well as the measured data. It was also observed that the accuracy of the RCS data of the dielectrics can be frequency and angle dependent. The simulated RCS for some of these materials also exhibit high sensitivity to variations in the material properties. Comparison graphs between the measured and simulation RCS datasets will be presented and the validation thereof will be discussed. Finally, the effect that small tolerances in the material properties have on the calculated RCS results will be shown. Thus the importance of accurate dielectric material properties for validation purposes will be discussed.

Keywords: asymptotic, CEM, dielectric scattering, full-wave, measurements, radar cross section, validation

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Authors: Matthieu-P. Schapranow

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Recruitment of participants for clinical trials requires the screening of a big number of potential candidates, i.e. the testing for trial-specific inclusion and exclusion criteria, which is a time-consuming and complex task. Today, a significant amount of time is spent on identification of adequate trial participants as their selection may affect the overall study results. We introduce a unique patient eligibility metric, which allows systematic ranking and classification of candidates based on trial-specific filter criteria. Our web application enables real-time analysis of patient data and assessment of candidates using freely definable inclusion and exclusion criteria. As a result, the overall time required for identifying eligible candidates is tremendously reduced whilst additional degrees of freedom for evaluating the relevance of individual candidates are introduced by our contribution.

Keywords: in-memory technology, clinical trials, screening, eligibility metric, data analysis, clustering

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Authors: Thomas Yeboah, Gifty Akouko Sarpong

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Every learner has a specific learning style that helps him/her to study best. This means that any learning method (e-learning method or traditional face-to-face method) a learner chooses should address the learning style of the learner. Therefore, the main purpose of this research is to investigate whether learners’ grade achievement in e-learning environment is improved for learners with a particular learning style. In this research, purposive sampling technique was employed for selecting the sample size of three hundred and twenty (320) students studying a course UGRC 140 Science and Technology in our Lives at Christian Service University College. Data were analyzed by using, percentages, T -test, and one-way ANOVA. A thorough analysis was done on the data collected and the results revealed that learners with the Assimilator learning style and the converger learning style obtained higher grade achievement than both diverger learning style and accommodative learning style. Again, the results also revealed that accommodative learning style was not good enough for e-learning method.

Keywords: e-learning, learning style, grade achievement, accomodative, divergent, convergent, assimilative

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Authors: Mohd Noah A. Rahman, Afzaal H. Seyal, Sharul T. Tajuddin, Hartiny Md Azmi

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Taking into consideration the real time situation specifically the higher academic institutions, small, medium to large companies, public to private sectors and the remaining sectors, do experience the inventory or asset shrinkages due to theft, loss or even inventory tracking errors. This happening is due to a zero or poor security systems and measures being taken and implemented in their organizations. Henceforth, implementing the Radio Frequency Identification (RFID) technology into any manual or existing web-based system or web application can simply deter and will eventually solve certain major issues to serve better data retrieval and data access. Having said, this manual or existing system can be enhanced into a mobile-based system or application. In addition to that, the availability of internet connections can aid better services of the system. Such involvement of various technologies resulting various privileges to individuals or organizations in terms of accessibility, availability, mobility, efficiency, effectiveness, real-time information and also security. This paper will look deeper into the integration of mobile devices with RFID technologies with the purpose of asset tracking and control. Next, it is to be followed by the development and utilization of MongoDB as the main database to store data and its association with RFID technology. Finally, the development of a web based system which can be viewed in a mobile based formation with the aid of Hypertext Preprocessor (PHP), MongoDB, Hyper-Text Markup Language 5 (HTML5), Android, JavaScript and AJAX programming language.

Keywords: RFID, asset tracking system, MongoDB, NoSQL

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Authors: Saad Alkentar, Abdulkareem Assalem

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Recognizing small targets has always posed a significant challenge in image analysis. Over long distances, the image signal-to-noise ratio tends to be low, limiting the amount of useful information available to detection systems. Consequently, visual target recognition becomes an intricate task to tackle. In this study, we introduce a Track Before Detect (TBD) approach that leverages target trajectory information (coordinates) to effectively distinguish between noise and potential targets. By reframing the problem as a multivariate time series classification, we have achieved remarkable results. Specifically, our TBD method achieves an impressive 97% accuracy in separating target signals from noise within a mere half-second time span (consisting of 10 data points). Furthermore, when classifying the identified targets into our predefined categories—airplane, drone, and bird—we achieve an outstanding classification accuracy of 96% over a more extended period of 1.5 seconds (comprising 30 data points).

Keywords: small targets, drones, trajectory information, TBD, multivariate time series

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Authors: Chakraborty Sudipta, A. R. Kambekar, Sarma Arnab

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Sea-level rise being one of the most important impacts of anthropogenic induced climate change resulting from global warming and melting of icebergs at Arctic and Antarctic, the investigations done by various researchers both on Indian Coast and elsewhere during the last decade has been reviewed in this paper. The paper aims to ascertain the propensity of consistency of different suggested methods to predict the near-accurate future sea level rise along the coast of Mumbai. Case studies at East Coast, Southern Tip and West and South West coast of India have been reviewed. Coastal Vulnerability Index of several important international places has been compared, which matched with Intergovernmental Panel on Climate Change forecasts. The application of Geographic Information System mapping, use of remote sensing technology, both Multi Spectral Scanner and Thematic Mapping data from Landsat classified through Iterative Self-Organizing Data Analysis Technique for arriving at high, moderate and low Coastal Vulnerability Index at various important coastal cities have been observed. Instead of data driven, hindcast based forecast for Significant Wave Height, additional impact of sea level rise has been suggested. Efficacy and limitations of numerical methods vis-à-vis Artificial Neural Network has been assessed, importance of Root Mean Square error on numerical results is mentioned. Comparing between various computerized methods on forecast results obtained from MIKE 21 has been opined to be more reliable than Delft 3D model.

Keywords: climate change, Coastal Vulnerability Index, global warming, sea level rise

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Authors: I. Ketut Yoga Adityawira, Putu Ayu Novia Viorica, Komang Rahayu Indrawati

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In addition to work and take care of the family, Balinese women also have a role to participate in social activities in Bali. So this will have an impact on the quality of work life of Balinese women. One way to reduce the impact of the fulfillment of the role of Balinese women namely through emotional support. The aim of this research is to find out the effect of emotional support towards the quality of work life on Balinese working women. Data were retrieved by quasi-experimental method with pretest-posttest design. Data were analyzed by Analysis of Variance (ANOVA) through SPSS 17.0 for Windows. The number of subjects in this research is 30 people with the criteria: Balinese Women, aged 27 to 55 years old, have a minimum of two years experience of work and has been married. The analysis showed that there is no effect of emotional support towards the quality of work life on Balinese working women, with information there is no significant of probability value p = 0.304 (p > 0.05).

Keywords: Balinese women, emotional support, quality of work life, working women

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Authors: Chuanqiao Zheng, Wei Zeng, Haozhen Lin

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As of March 2020, the number of Chinese netizens has reached 904 million. The proportion of Internet users accessing the Internet through mobile phones is as high as 99.3%. Under the background of 'Internet +', tourists have a stronger sense of independence in the choice of tourism destinations and tourism products. Tourists are more inclined to learn about the relevant information on tourism destinations and other tourists' evaluations of tourist products through the Internet. The search engine, as an integrated platform that contains a wealth of information, is highly valuable to the analysis of the characteristics of the Internet attention given to various tourism destinations, through big data mining and analysis. This article uses the Baidu Index as the data source, which is one of the products of Baidu Search. The Baidu Index is based on big data, which collects and shares the search results of a large number of Internet users on the Baidu search engine. The big data used in this article includes search index, demand map, population profile, etc. The main research methods used are: (1) based on the search index, analyzing the Internet attention given to the tourism in five cities in Northeast Sichuan at different times, so as to obtain the overall trend and individual characteristics of tourism development in the region; (2) based on the demand map and the population profile, analyzing the demographic characteristics and market positioning of the tourist groups in these cities to understand the characteristics and needs of the target groups; (3) correlating the Internet attention data with the permanent population of each province in China in the corresponding to construct the Boston matrix of the Internet attention rate of the Northeast Sichuan tourism, obtain the tourism target markets, and then propose development strategies for different markets. The study has found that: a) the Internet attention given to the tourism in the region can be categorized into tourist off-season and peak season; the Internet attention given to tourism in different cities is quite different. b) tourists look for information including tour guide information, ticket information, traffic information, weather information, and information on the competing tourism cities; with regard to the population profile, the main group of potential tourists searching for the keywords of tourism in the five prefecture-level cities in Northeast Sichuan are youth. The male to female ratio is about 6 to 4, with males being predominant. c) through the construction of the Boston matrix, it is concluded that the star market for tourism in the Northeast Sichuan Economic Zone includes Sichuan and Shaanxi; the cash cows market includes Hainan and Ningxia; the question market includes Jiangsu and Shanghai; the dog market includes Hubei and Jiangxi. The study concludes with the following planning strategies and recommendations: i) creating a diversified business format that integrates cultural and tourism; ii) creating a brand image of niche tourism; iii) focusing on the development of tourism products; iv) innovating composite three-dimensional marketing channels.

Keywords: Baidu Index, big data, internet attention, tourism

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Authors: Pitimanus Bunlue

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This research aim (1) to determine the content of communication, social capital and cultural capital to promote tourism in the province to create awareness, motivation and desire to tourists visiting Thailand (2) to evaluate the performance of innovation communication social capital and cultural capital to promote tourism southern of Thailand. This research is a qualitative research. A research synthesis projects on social capital and cultural capital by use focus group discussions with media professionals and academics to communicate using a random sample specific. The result show that (1) Innovative communication, social capital and cultural capital and effective communication innovations after everyone wants to travel to Ranong province is the very highest level. (2) Information and experience about Ranong at a high level. (3) The data shows the strengths of each of the attractions at a high level. (4) The data shows a lifestyle that is unique to the province is moderate.

Keywords: innovative communication, promoting tourism, southern of Thailand, social capital

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Authors: Bidzina Matsaberidze

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It is known that, in emergency situations, multi-attribute group decision-making (MAGDM) models are characterized by insufficient objective data and a lack of time to respond to the task. Evidence theory is an effective tool for describing such incomplete information in decision-making models when the expert and his knowledge are involved in the estimations of the MAGDM parameters. We consider an emergency decision-making model, where expert assessments on humanitarian aid from distribution centers (HADC) are represented in q-rung ortho-pair fuzzy numbers, and the data structure is described within the data body theory. Based on focal probability construction and experts’ evaluations, an objective function-distribution centers’ selection ranking index is constructed. Our approach for solving the constructed bicriteria partitioning problem consists of two phases. In the first phase, based on the covering’s matrix, we generate a matrix, the columns of which allow us to find all possible partitionings of the HADCs with the service centers. Some constraints are also taken into consideration while generating the matrix. In the second phase, based on the matrix and using our exact algorithm, we find the partitionings -allocations of the HADCs to the centers- which correspond to the Pareto-optimal solutions. For an illustration of the obtained results, a numerical example is given for the facility location-selection problem.

Keywords: emergency MAGDM, q-rung orthopair fuzzy sets, evidence theory, HADC, facility location problem, multi-objective combinatorial optimization problem, Pareto-optimal solutions

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Authors: Faiza Babur Khan, Sohail Asghar

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With an emergence of distributed environment, cloud computing is proving to be the most stimulating computing paradigm shift in computer technology, resulting in spectacular expansion in IT industry. Many companies have augmented their technical infrastructure by adopting cloud resource sharing architecture. Cloud computing has opened doors to unlimited opportunities from application to platform availability, expandable storage and provision of computing environment. However, from a security viewpoint, an added risk level is introduced from clouds, weakening the protection mechanisms, and hardening the availability of privacy, data security and on demand service. Issues of trust, confidentiality, and integrity are elevated due to multitenant resource sharing architecture of cloud. Trust or reliability of cloud refers to its capability of providing the needed services precisely and unfailingly. Confidentiality is the ability of the architecture to ensure authorization of the relevant party to access its private data. It also guarantees integrity to protect the data from being fabricated by an unauthorized user. So in order to assure provision of secured cloud, a roadmap or model is obligatory to analyze a security problem, design mitigation strategies, and evaluate solutions. The aim of the paper is twofold; first to enlighten the factors which make cloud security critical along with alleviation strategies and secondly to propose an intrusion detection model that identifies the attackers in a preventive way using machine learning Random Forest classifier with an accuracy of 99.8%. This model uses less number of features. A comparison with other classifiers is also presented.

Keywords: cloud security, threats, machine learning, random forest, classification

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Authors: Yusef Karimi, Masoomeh Esmaeily, Razgar Mohammadi

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Following the events of September 11th, one of the most important concerns of governments, politicians and, researchers has been to answer the question that why does an ordinary person become fundamentalism? One of the major controversies in past researches was about as to whether a fundamentalist person is normal or abnormal. In this regard, the purpose of this research is to investigate whether a Salafi-jihadi individual is normal or abnormal. The participants included 6 Jihadi Salafism individuals who were living in the Middle East and had been purposefully selected. This research is a qualitative study which examines these people′s retrospective experience of their lives. The data were collected through collaborative observation and interview. This continued till data saturation. Unlike the introduced concepts of fundamentalist personality in the previous studies such as self-fascination, aggression, paranoid personality and psychopathic, participants in this study had no abnormal symptoms of mental disorders. Hence, in the context of recognizing the fundamentalist personality, we must seek other personality and positional variables.

Keywords: abnormal, fundamentalism, normal, personality, Salafi

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Authors: Laleh Boroumand, Muhammad Shiraz, Abdullah Gani, Rashid Hafeez Khokhar

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Cloud computing being the use of hardware and software that are delivered as a service over a network has its application in the area of health care. Due to the emergency cases reported in most of the medical centers, prompt for an efficient scheme to make health data available with less response time. To this end, we propose a mobile global healthcare village (MGHV) model that combines the components of three deployment model which include country, continent and global health cloud to help in solving the problem mentioned above. In the creation of continent model, two (2) data centers are created of which one is local and the other is global. The local replay the request of residence within the continent, whereas the global replay the requirements of others. With the methods adopted, there is an assurance of the availability of relevant medical data to patients, specialists, and emergency staffs regardless of locations and time. From our intensive experiment using the simulation approach, it was observed that, broker policy scheme with respect to optimized response time, yields a very good performance in terms of reduction in response time. Though, our results are comparable to others when there is an increase in the number of virtual machines (80-640 virtual machines). The proportionality in increase of response time is within 9%. The results gotten from our simulation experiments shows that utilizing MGHV leads to the reduction of health care expenditures and helps in solving the problems of unqualified medical staffs faced by both developed and developing countries.

Keywords: cloud computing (MCC), e-healthcare, availability, response time, service broker policy

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Authors: Dany Ng Cheong Vee, Preethee Nunkoo Gonpot, Noor Sookia

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In this paper, we consider the application of Extreme Value Theory as a risk measurement tool. The Value at Risk, for a set of indices, from six Stock Exchanges of Frontier markets is calculated using the Peaks over Threshold method and the performance of the model index-wise is evaluated using coverage tests and loss functions. Our results show that 'fat-tailedness' alone of the data is not enough to justify the use of EVT as a VaR approach. The structure of the returns dynamics is also a determining factor. This approach works fine in markets which have had extremes occurring in the past thus making the model capable of coping with extremes coming up (Colombo, Tunisia and Zagreb Stock Exchanges). On the other hand, we find that indices with lower past than present volatility fail to adequately deal with future extremes (Mauritius and Kazakhstan). We also conclude that using EVT alone produces quite static VaR figures not reflecting the actual dynamics of the data.

Keywords: extreme value theory, financial crisis 2008, value at risk, frontier markets

Procedia PDF Downloads 262