Search results for: pseudo-geometric version

Authors: A. Noll, J. Roth, M. Scholz

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The importance of written language in a democratic society is non-controversial. Students with physical, learning, cognitive or developmental disabilities often have difficulties in understanding information which is presented in written language only. These students suffer from obstacles in diverse domains. In order to reduce such barriers in educational as well as in out-of-school areas, access to written information must be facilitated. Readability can be enhanced by linguistic simplifications like the application of easy-to-read language. Easy-to-read language shall help people with disabilities to participate socially and politically in society. The authors state, for example, that only short simple words should be used, whereas the occurrence of complex sentences should be avoided. So far, these guidelines were not empirically proved. Another way to reduce reading barriers is the use of visual support, for example, symbols. A symbol conveys, in contrast to a photo, a single idea or concept. Little empirical data about the use of symbols to foster the readability of texts exist. Nevertheless, a positive influence can be assumed, e.g., because of the multimedia principle. It indicates that people learn better from words and pictures than from words alone. A qualitative Interview and Eye-Tracking-Study, which was conducted by the authors, gives cause for the assumption that besides the illustration of single words, the visualization of complete sentences may be helpful. Thus, the effect of photos, which illustrate the content of complete sentences, is also investigated in this study. This leads us to the main research question which was focused on: Does the use of easy-to-read language and/or enriching text with symbols or photos facilitate pupils’ comprehension of learning tasks? The sample consisted of students with learning difficulties (N = 144) and students without SEN (N = 159). The students worked on the tasks, which dealt with introducing fractions, individually. While experimental group 1 received a linguistically simplified version of the tasks, experimental group 2 worked with a variation which was linguistically simplified and furthermore, the keywords of the tasks were visualized by symbols. Experimental group 3 worked on exercises which were simplified by easy-to-read-language and the content of the whole sentences was illustrated by photos. Experimental group 4 received a not simplified version. The participants’ reading ability and their IQ was elevated beforehand to build four comparable groups. There is a significant effect of the different setting on the students’ results F(3,140) = 2,932; p = 0,036*. A post-hoc-analyses with multiple comparisons shows that this significance results from the difference between experimental group 3 and 4. The students in the group easy-to-read language plus photos worked on the exercises significantly more successfully than the students who worked in the group with no simplifications. Further results which refer, among others, to the influence of the students reading ability will be presented at the ICERI 2018.

Keywords: inclusive education, mathematics education, easy-to-read language, photos, symbols, special educational needs

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Authors: Ladan Maijama’a, Jibril D. Jiya, Ejike C. Anene

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This paper presents Differential Evolution Algorithm (DEA) based Variable Structure Position Control (VSPC) of Laboratory DC servomotor (LDCSM). DEA is employed for the optimal tuning of Variable Structure Control (VSC) parameters for position control of a DC servomotor. The VSC combines the techniques of Sliding Mode Control (SMC) that gives the advantages of small overshoot, improved step response characteristics, faster dynamic response and adaptability to plant parameter variations, suppressed influences of disturbances and uncertainties in system behavior. The results of the simulation responses of the VSC parameters adjustment by DEA were performed in Matlab Version 2010a platform and yield better dynamic performance compared with the untuned VSC designed.

Keywords: differential evolution algorithm, laboratory DC servomotor, sliding mode control, variable structure control

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Authors: Vicki R. Voskuil, Jorgie M. Watson

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Despite the well-established health benefits of physical activity (PA), most adolescents do not meet guidelines recommending 60 minutes of moderate to vigorous physical activity (MVPA) each day. Adolescent girls engage in less PA than boys, a difference that increases with age. By the 9th grade, only 20% of girls report meeting recommendations for PA with lower percentages for black and Hispanic girls compared to white girls. The purpose of the study was to explore the physical activity (PA) behavior and needs of adolescent girls. Study aims included assessment of adolescent girls’ PA behavior; facilitators of and barriers to PA, PA needs, and acceptability of the Fitbit-Flex 2 activity tracker. This exploratory study used a qualitative and quantitative approach. The qualitative approach involved a focus group using a semi-structured interview technique. PA was measured using the Fitbit-Flex 2 activity tracker. Steps, distance, and active minutes were recorded for one week. A Fitbit survey was also administered to assess acceptability. SPSS Version 22.0 and ATLAS.ti Version 8 were used to analyze data. Girls in the ninth grade were recruited from a high school in the Midwest (n=11). Girls were excluded if they were involved in sports or other organized PA ≥ 3 days per week, had a health condition that prevented or limited PA, or could not read and write English. Participants received a Fitbit-Flex 2 activity tracker to wear for one week. At the end of the week, girls returned the Fitbit and participated in a focus group. Girls responded to open-ended questions regarding their PA behavior and shared their ideas for future intervention efforts aimed at increasing PA among adolescents. Girls completed a survey assessing their perceptions of the Fitbit. Mean age of the girls was 15.3 years (SD=0.44). On average girls took 6,520 steps and walked 2.73 miles each day. Girls stated their favorite types of PA were walking, riding bike, and running. Most girls stated they did PA for 30 minutes or more at a time once a day or every other day. The top 3 facilitators of PA reported by girls were friends, family, and transportation. The top 3 barriers included health issues, lack of motivation, and weather. Top intervention ideas were community service projects, camps, and using a Fitbit activity tracker. Girls felt the best timing of a PA program would be in the summer. Fitbit survey results showed 100% of girls would use a Fitbit on most days if they had one. Ten (91%) girls wore the Fitbit on all days. Seven (64%) girls used the Fitbit app and all reported they liked it. Findings indicate that PA participation for this sample is consistent with previous studies. Adolescent girls are not meeting recommended daily guidelines for PA. Fitbit activity trackers were positively received by all participants and could be used in future interventions aimed at increasing PA for adolescent girls. PA interventions that take place in the summer with friends and include community service projects may increase PA and be well received by this population.

Keywords: adolescents, girls, interventions, physical activity

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Authors: Aymen Laadhari

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We present in this paper a fully implicit finite element method tailored for the numerical modeling of inextensible fluidic membranes in a surrounding Newtonian fluid. We consider a highly simplified version of the Canham-Helfrich model for phospholipid membranes, in which the bending force and spontaneous curvature are disregarded. The coupled problem is formulated in a fully Eulerian framework and the membrane motion is tracked using the level set method. The resulting nonlinear problem is solved by a Newton-Raphson strategy, featuring a quadratic convergence behavior. A monolithic solver is implemented, and we report several numerical experiments aimed at model validation and illustrating the accuracy of the proposed method. We show that stability is maintained for significantly larger time steps with respect to an explicit decoupling method.

Keywords: finite element method, level set, Newton, membrane

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Authors: Xinyue Jiao, Yu-Ren Lin

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Argumentation is an essential aspect of scientific thinking which has been widely concerned in recent reform of science education. The purpose of the present studies was to explore the influences of two variables termed ‘the argumentation strategy’ and ‘the kind of science concept’ on student’s web-based argumentation. The first variable was divided into either monological (which refers to individual’s internal discourse and inner chain reasoning) or dialectical (which refers to dialogue interaction between/among people). The other one was also divided into either descriptive (i.e., macro-level concept, such as phenomenon can be observed and tested directly) or theoretical (i.e., micro-level concept which is abstract, and cannot be tested directly in nature). The present study applied the quasi-experimental design in which 138 7th grade students were invited and then assigned to either monological group (N=70) or dialectical group (N=68) randomly. An argumentation learning program called ‘the PWAL’ was developed to improve their scientific argumentation abilities, such as arguing from multiple perspectives and based on scientific evidence. There were two versions of PWAL created. For the individual version, students can propose argument only through knowledge recall and self-reflecting process. On the other hand, the students were allowed to construct arguments through peers’ communication in the collaborative version. The PWAL involved three descriptive science concept-based topics (unit 1, 3 and 5) and three theoretical concept-based topics (unit 2, 4 and 6). Three kinds of scaffoldings were embedded into the PWAL: a) argument template, which was used for constructing evidence-based argument; b) the model of the Toulmin’s TAP, which shows the structure and elements of a sound argument; c) the discussion block, which enabled the students to review what had been proposed during the argumentation. Both quantitative and qualitative data were collected and analyzed. An analytical framework for coding students’ arguments proposed in the PWAL was constructed. The results showed that the argumentation approach has a significant effect on argumentation only in theoretical topics (f(1, 136)=48.2, p < .001, η2=2.62). The post-hoc analysis showed the students in the collaborative group perform significantly better than the students in the individual group (mean difference=2.27). However, there is no significant difference between the two groups regarding their argumentation in descriptive topics. Secondly, the students made significant progress in the PWAL from the earlier descriptive or theoretical topic to the later one. The results enabled us to conclude that the PWAL was effective for students’ argumentation. And the students’ peers’ interaction was essential for students to argue scientifically especially for the theoretical topic. The follow-up qualitative analysis showed student tended to generate arguments through critical dialogue interactions in the theoretical topic which promoted them to use more critiques and to evaluate and co-construct each other’s arguments. More explanations regarding the students’ web-based argumentation and the suggestions for the development of web-based science learning were proposed in our discussions.

Keywords: argumentation, collaborative learning, scientific concepts, web-based learning

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Authors: Ubu Isaiah, Gambo D.

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Haematological studies are an important diagnosis of nutritional studies. The study investigated the haematological parameters of West African Dwarf (WAD) goats fed a diet containing different levels of sodium humate. Twenty (20) WAD bucks weighing between 8.154 ± 0.340 kg were used for this study. The bucks were randomly allotted to four dietary treatments containing 0, 5, 10, and 15 g/kg diet of sodium humate laid out as a completely randomized design. Data on haematological parameters were obtained and statistically analysed using the generalized linear model (GLM) of the Statistical Package for Social Sciences (SPSS) (version 23). Results showed that sodium humate supplementation (p <0.05) has no significant effect on Neutrophils, Eosinophil, Basophils, and Monocytes, respectively. It was recommended up to 15 g/kg diet supplementation of sodium humate sufficiently enhance the performance of WAD goats as well the improving their haematological indices.

Keywords: haematological indices, goat, sodium humate

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Authors: Arash Ahmadi, Amirreza Kavousizadeh, Sanaz Heidarzadeh

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Stage-discharge curve is one of the conventional methods for continuous river flow measurement. In this paper, an innovative approach is proposed for predicting the stage-discharge relationship using the application of isovel contours. Using the proposed method, it is possible to estimate the stage-discharge curve in the whole section with only using discharge information from just one arbitrary water level. For this purpose, multivariate relationships are used to determine the mean velocity in a cross-section. The unknown exponents of the proposed relationship have been obtained by using the second version of the Strength Pareto Evolutionary Algorithm (SPEA2), and the appropriate equation was selected by applying the TOPSIS (Technique for Order Preferences by Similarity to an Ideal Solution) approach. Results showed a close agreement between the estimated and observed data in the different cross-sections.

Keywords: rating curves, SPEA2, natural rivers, bed roughness distribution

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Authors: K. Djellabi, M. E. H. Latreche

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The induction heating phenomenon depends on various factors, making the problem highly nonlinear. The mathematical analysis of this problem in most cases is very difficult and it is reduced to simple cases. Another knowledge of induction heating systems is generated in production environments, but these trial-error procedures are long and expensive. The numerical models of induction heating problem are another approach to reduce abovementioned drawbacks. This paper deals with the simulation model of induction heating problem. The simulation model of induction heating system in COMSOL Multiphysics is created. In this work we present results of numerical simulations of induction heating process in pieces of cylindrical shapes, in an inductor with four coils. The modeling of the inducting heating process was made with the software COMSOL Multiphysics Version 4.2a, for the study we present the temperature charts.

Keywords: induction heating, electromagnetic field, inductor, numerical simulation, finite element

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Authors: Fares Hedayatit, Arnauld Joly, Panagiotis Papadimitriou

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Many machine learning tasks such as text annotation usually require training over very big datasets, e.g., millions of web documents, that can be represented in a sparse input space. State-of the-art tree-based ensemble algorithms cannot scale to such datasets, since they include operations whose running time is a function of the input space size rather than a function of the non-zero input elements. In this paper, we propose an efficient splitting algorithm to leverage input sparsity within decision tree methods. Our algorithm improves training time over sparse datasets by more than two orders of magnitude and it has been incorporated in the current version of scikit-learn.org, the most popular open source Python machine learning library.

Keywords: big data, sparsely representable data, tree-based models, scalable learning

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Authors: Chunduru Amareswara Prasad

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The main aim of this proposal it to reveal the secrets of the universe by accelerating neutrons. The proposal idea in its abridged version speaks about the possibility of making neutrons accelerate with help of thermal energy and magnetic energy under controlled conditions. Which is helpful in revealing the hidden secrets of the universe namely dark energy and in finding properties of Higgs boson. The paper mainly speaks about accelerating neutrons to near velocity of light in a LINAC, using magnetic energy by magnetic pressurizers. The center of mass energy of two colliding neutron beams is 94 GeV (~0.5c) can be achieved using this method. The conventional ways to accelerate neutrons has some constraints in accelerating them electromagnetically as they need to be separated from the Tritium or Deuterium nuclei. This magnetic gradient method provides efficient and simple way to accelerate neutrons.

Keywords: neutron, acceleration, thermal energy, magnetic energy, Higgs boson

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Authors: Dirk V. H. K. Franco

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For many of us a lot of phenomena are considered a risk. Examples are: climate change, decrease of biodiversity, amount of available, clean water and the decreasing variety of living organism in the oceans. On the other hand a lot of people perceive the following trends as catastrophic: the sea level, the melting of the pole ice, the numbers of tornado’s, floods and forest fires, the national security and the potential of 192 million climate migrants in 2060. The interest for climate, health and the possible solutions is large and common. The 5th IPCC states that the last decades especially human activities (and in second order natural emissions) have caused large, mainly negative impacts on our ecological environments. Chris Stringer stated that we represent, nowadays after evolution, the only one version of the possible humanity. At this very moment we are faced with an (over) crowded planet together with global climate changes and a strong demand for energy and material resources. Let us hope that we can counter these difficulties either with better application of existing technologies or by inventing new (applications of) clean technologies together with new business models.

Keywords: clean technologies, catastrophic, climate, possible solutions

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Authors: Matthew J. Zagumny

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The current study reports an examination of the QUEST-25 (Q-Assessment of Undergraduate Epistemology and Scientific Thinking) online version for assessing the dispositional attitudes toward scientific thinking and intellectual curiosity among undergraduate students. The QUEST-25 consists of scientific thinking (SIQ-25) and intellectual curiosity (ICIQ-25), which were correlated in hypothesized directions with the Religious Commitment Inventory, Curiosity and Exploration Inventory, Belief in Science scale, and measures of academic self-efficacy. Additionally, concurrent validity was established by the resulting significant differences between those identifying the centrality of religious belief in their lives and those who do not self-identify as being guided daily by religious beliefs. This study demonstrates the utility of the QUEST-25 for research, evaluation, and theory development.

Keywords: guided-inquiry learning, intellectual curiosity, psychometric assessment, scientific thinking

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Authors: Shotiros Protong

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The incidents of sudden landslides in Thailand during the past decade have occurred frequently and more severely. It is necessary to focus on the principal parameters used for analysis such as land cover land use, rainfall values, characteristic of soil and digital elevation model (DEM). The combination of intense rainfall and severe monsoons is increasing due to global climate change. Landslide occurrences rapidly increase during intense rainfall especially in the rainy season in Thailand which usually starts around mid-May and ends in the middle of October. The rain-triggered landslide hazard analysis is the focus of this research. The combination of geotechnical and hydrological data are used to determine permeability, conductivity, bedding orientation, overburden and presence of loose blocks. The regional landslide hazard mapping is developed using the Slope Stability Index SINMAP model supported on Arc GIS software version 10.1. Geological and land use data are used to define the probability of landslide occurrences in terms of geotechnical data. The geological data can indicate the shear strength and the angle of friction values for soils above given rock types, which leads to the general applicability of the approach for landslide hazard analysis. To address the research objectives, the methods are described in this study: setup and calibration of the SINMAP model, sensitivity of the SINMAP model, geotechnical laboratory, landslide assessment at present calibration and landslide assessment under future climate simulation scenario A2 and B2. In terms of hydrological data, the millimetres/twenty-four hours of average rainfall data are used to assess the rain triggered landslide hazard analysis in slope stability mapping. During 1954-2012 period, is used for the baseline of rainfall data at the present calibration. The climate change in Thailand, the future of climate scenarios are simulated by spatial and temporal scales. The precipitation impact is need to predict for the climate future, Statistical Downscaling Model (SDSM) version 4.2, is used to assess the simulation scenario of future change between latitude 16o 26’ and 18o 37’ north and between longitude 98o 52’ and 103o 05’ east by SDSM software. The research allows the mapping of risk parameters for landslide dynamics, and indicates the spatial and time trends of landslide occurrences. Thus, regional landslide hazard mapping under present-day climatic conditions from 1954 to 2012 and simulations of climate change based on GCM scenarios A2 and B2 from 2013 to 2099 related to the threshold rainfall values for the selected the study area in Uttaradit province in the northern part of Thailand. Finally, the landslide hazard mapping will be compared and shown by areas (km2 ) in both the present and the future under climate simulation scenarios A2 and B2 in Uttaradit province.

Keywords: landslide hazard, GIS, slope stability index (SINMAP), landslides, Thailand

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Authors: Petros Roussos

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The present study focused on students' statistical reasoning related to Null Hypothesis Statistical Testing and p-values. Its objective was to test the hypothesis that neither the place (classroom, at a distance, online) nor the medium that actually supports the learning (ICT, internet, books) has an effect on understanding of statistical concepts. In addition, it was expected that students' attitudes towards statistics would not predict understanding of statistical concepts. The sample consisted of 385 undergraduate and postgraduate students from six state and private universities (five in Greece and one in Cyprus). Students were administered two questionnaires: a) the Greek version of the Survey of Attitudes Toward Statistics, and b) a short instrument which measures students' understanding of statistical significance and p-values. Results suggest that attitudes towards statistics do not predict students' understanding of statistical concepts, whereas the medium did not have an effect.

Keywords: attitudes towards statistics, blended learning, e-learning, statistical reasoning

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Authors: Susan Evans, Janna Gordon-Elliott, Katarzyna Wyka, Virginia Mutch

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During the rise of the COVID-19 pandemic, healthcare workers needed an intervention that could address their profound acute stress. Mindfulness-based stress reduction (MBSR) is a program that has long established effectiveness for mental and physical health outcomes. In recent years, MBSR has been modified such that the duration of both class time and number of sessions has been abbreviated, and its delivery has been adapted for online dissemination, thus increasing the likelihood that individuals who could most benefit from the program would do so. We sought to investigate whether a brief, online version of MBSR could be feasible and acceptable for health care workers (HCW) in acute stress in response to the COVID-19 pandemic. Participants were recruited via an email sent to all hospital employees, which spans residents, physicians, nurses, housekeeping, lab technicians, administrators, and others. Participating HCW were asked about their previous experience with mindfulness and asked to commit to a minimum of 3 sessions. They were then provided with four weekly 1-hour sessions online that included the major mindfulness exercises taught during traditional MBSR programs (i.e., body scan, sitting meditation, mindful eating, and yoga). Participants were provided with supporting slides, videos, demonstrations and asked to track their practice. Hospital staff enrolled in the program; by the end of the first day of recruitment, 40 had applied; by the start date, about 100 were enrolled, and n attended a minimum of 3 sessions, supporting feasibility. Hospital staff also participated and practiced the mindfulness exercises (n=42), thus supporting acceptability. Participants reported that the program was logical, successful, and worth recommending both before starting the program and after completing it (M= 22.02 and M=21.76, respectively, possible range 0-27). There was a slight decline in the belief in improvement in health and well-being due to the program (ES=.37, p=.021). Secondary hypotheses regarding participants’ self-reported stress and levels of mindfulness were also supported, such that participants reported improvements in perceived stress (ES=.45, p=.006), compassion satisfaction, burnout, and secondary traumatic stress (ES=.41, ES=.31, ES=.35, respectively, p<.05). Participants reported significant improvements in the describing facet of mindfulness (ES=.49, p=.004), while all other facets (observing, acting with awareness, nonjudging of inner experience, nonreactivity to inner experience) remained unchanged pre- to post-program. Results from this study suggest that an abridged, online version of MBSR is feasible and accessible to health care workers in acute stress and provides benefits expected from traditional MBSR programs. The lack of a randomized control group limits generalizability. We intend to provide a structure, framework, and lessons learned to hospital administrators and clinical staff seeking to support their employees in acute stress.

Keywords: acute stress, health care workers, mindfulness, online interventions

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Authors: Stylianos Kampakis

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This paper presents a new algorithm for neural networks called “Input Dropout with Aggressive Re-weighting” (IDAR) aimed specifically at datasets with many useless features. IDAR combines two techniques (dropout of input neurons and aggressive re weighting) in order to eliminate the influence of noisy features. The technique can be seen as a generalization of dropout. The algorithm is tested on two different benchmark data sets: a noisy version of the iris dataset and the MADELON data set. Its performance is compared against three other popular techniques for dealing with useless features: L2 regularization, LASSO and random forests. The results demonstrate that IDAR can be an effective technique for handling data sets with many useless features.

Keywords: neural networks, feature selection, regularization, aggressive reweighting

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Authors: Moqbil S. Alenazi, Magdy. M. Elkhateeb

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A comprehensive photometric study and evolutionary state for the newly discovered Beta Lyr systems V0487 Lac, V0566 Hya, and V0666 Lac were carried out by means of their first photometric observations. New times of minima were estimated from the observed light curves, and first (O-C) curves were established for all systems. A windows interface version of the Wilson and Devinney code (W-D) based on model atmospheres and a pass band prescription have been used for the radiative treatment. The accepted models reveal some absolute parameters for the studied systems, which are used in adopting the spectral type of the system's components and their evolutionary status. Distances to each system were calculated, and physical properties were estimated. Locations of the systems on the theoreticalmass–luminosity and mass–radius relations revealed a good fit for all systems components except for the secondary component of the system V0487 Lac.

Keywords: eclipsing binaries, light curve modelling, evolutionary state

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Authors: Siti Nadiah Nuwawi, Roshidah Hassan

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Dialect is one of the language variants emerge due to certain factors. One of the distinctive dialects spoken by people in Malaysia is the one spoken by those who reside in the inland area of the East Peninsular Malaysia; Hulu Terengganu, which is known as Ulu Terengganu Malay dialect. This dialect is unique since it possesses ancient elements in its phonology elements, which makes it is hard to be understood by people who come from other states. There is dearth of acoustic studies of the dialect in which this paper aims to attain by describing the quality of the monophthongs found in the dialect instrumentally based on their first and second formant values. The hertz values are observed and recorded from the waveforms and spectrograms depicted in PRAAT version 6.0.43 software. The findings show that Ulu Terengganu Malay speakers produced ten monophthongs namely /ɛ/, /e/, /a/, /ɐ/, /ɞ/, /ɔ/, /i/, /o/, /ɵ/ and /ɘ/ which applauds a few monophthongs suggested by past researchers which were based on auditory impression namely /ɛ/, /e/, /a/, ɔ/, and /i/. It also discovers the other five monophthongs of the dialect which are unknown before namely /ɐ/, /ɞ/, /o/, /ɵ/ and /ɘ/.

Keywords: acoustic analysis, dialect, formant values, monophthongs, Ulu Terengganu Malay

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Authors: Matthew McArthur, Margaret Friend

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The COVID-19 pandemic disrupted the stability of the home environment for families across the world. Potential disruptions include parent work modality (in-person vs. remote), levels of health anxiety, family routines, and caregiving. These disruptions may have interfered with the processes of early vocabulary acquisition, carrying lasting effects over the life course. Our justification for this research is as follows: First, early, stable, caregiver-child reciprocal interactions, which may have been disrupted during the pandemic, contribute to the development of the brain architecture that supports language, cognitive, and social-emotional development. Second, early vocabulary predicts several cognitive outcomes, such as numeracy, literacy, and executive function. Further, disruption in the home is associated with adverse cognitive, academic, socio-emotional, behavioral, and communication outcomes in young children. We are interested in how disruptions related to the COVID-19 pandemic are associated with vocabulary acquisition in children born during the first two waves of the pandemic. We are conducting a moderated online experiment to assess this question. Participants are 16 children (10F) ranging in age from 19 to 39 months (M=25.27) and their caregivers. All child participants were screened for language background, health history, and history of language disorders, and were typically developing. Parents completed a modified version of the COVID-19 Family Stressor Scale (CoFaSS), a published measure of COVID-19-related family stressors. Thirteen items from the original scale were replaced to better capture change in family organization and stability specifically related to disruptions in income, anxiety, family relations, and childcare. Following completion of the modified CoFaSS, children completed a Web-Based version of the Computerized Comprehension Task and the Receptive One Word Picture Vocabulary if 24 months or older or the MacArthur-Bates Communicative Development Inventory if younger than 24 months. We report our preliminary data as a partial correlation analysis controlling for age. Raw vocabulary scores on the CCT, ROWPVT-4, and MCDI were all negatively associated with pandemic-related disruptions related to anxiety (r12=-.321; r1=-.332; r9=-.509), family relations (r12=-.590*; r1=-.155; r9=-.468), and childcare (r12=-.294; r1=-.468; r9=-.177). Although the small sample size for these preliminary data limits our power to detect significance, this trend is in the predicted direction, suggesting that increased pandemic-related disruption across multiple domains is associated with lower vocabulary scores. We anticipate presenting data on a full sample of 50 monolingual English participants. A sample of 50 participants would provide sufficient statistical power to detect a moderate effect size, adhering to a nominal alpha of 0.05 and ensuring a power level of 0.80.

Keywords: COVID-19, early vocabulary, home environment, language acquisition, multiple measures

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Authors: Glauberto S. Quirino, Emanuelly V. Pereira, Amana S. Figueiredo, Antonia T. F. Santos, Paulo R. A. Firmino, Denise F. F. Barbosa, Caroline B. Q. Aquino, Eveliny S. Martins, Cinthia G. P. Calou, Ana K. B. Pinheiro

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Introduction: During pregnancy there are adjustments in the physical, emotional, existential and sexual areas, which may contribute to changes in sexual behavior. The objective was to analyze the sexual behavior of pregnant women. Methods: Quantitative, exploratory-descriptive study, approved by the Ethics and Research Committee of the Regional University of Cariri. For data collection, it was used the Sexuality Questionnaire in Gestation and Sexual Quotient - Female Version. It was carried out in public institutions in the urban and rural areas of three municipalities of the Metropolitan Region of Cariri, south of Ceará, Brazil from February to September 2016. The sampling was proportional stratified by convenience. A total of 815 pregnant women who were literate and aged 20 years or over were broached. 461 pregnant women were excluded because of high risk, adolescence, saturation of the extract, incomplete filling of the instrument, mental and physical handicap, without sexual partner, and the sample was 354 pregnant. The data were grouped, organized and analyzed in the statistical program R Studio (version 386 3.2.4). Descriptive frequency statistics and non-parametric tests were used to analyze the variables, and the results were shown in graphs and tables. Results: The women presented a minimum age of 20, maximum 35 and average of 26.9 years, predominantly urban area residents, with a monthly income of up to one minimum wage (US$ 275,00), high school, catholic, with fixed partner, heterosexuals, multiparous, multiple sexual partners throughout life and with the beginning of sexual life in adolescence (median age 17 years). There was a reduction in sexual practices (67%) and when they were performed, they were more frequent in the first trimester (79.7%) and less frequent in the third trimester (30.5%). Preliminary sexual practices did not change and were more frequent in the second trimester (46.6%). Throughout the gestational trimesters, the partner was referred as the main responsible for the sexual initiative. The women performed vaginal sex (97.7%) and provided greater pleasure (42.8%) compared to non-penetrative sex (53.9%) (oral sex and masturbation). There was also a reduction in the sexual disposition of pregnant women (90.7%) and partner (72.9%), mainly in the first trimester (78.8%), and sexual positions. Sexual performance ranged from regular to good (49.7%). Level of schooling, marital status, sexual orientation of the pregnant woman and the partner, sexual practices and positions, preliminaries, frequency of sexual practices and importance attributed to them were variables that influenced negatively sexual performance and satisfaction. It is concluded that pregnancy negatively changes the sexual behavior of the women and it is suggested to further investigations and approach of the partner, in order to clarify the influence of these variables on the sexual function and subsidize intervention strategies, with a view to the integrality of sexual and reproductive health.

Keywords: obstetric nursing, pregnant women, sexual behavior, women's health

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Authors: Jodie Lee, Lorena Chan, Esther Tong

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Hong Kong students face a unique learning environment. Starting from the 2010/2011 school year, The Education Bureau (EDB) of the Government of the Hong Kong Special Administrative Region implemented the fine-tuned Medium of Instruction (MOI) arrangements for secondary schools. Since then, secondary schools in Hong Kong have been given the flexibility to decide the most appropriate MOI arrangements for their schools and under the new academic structure for senior secondary education, particularly on the compulsory part of the mathematics curriculum. In 2019, Hong Kong Diploma of Secondary Education Examination (HKDSE), over 40% of school day candidates attempted the Mathematics Compulsory Part examination in the Chinese version while the rest took the English version. Moreover, only 14.38% of candidates sat for one of the extended Mathematics modules. This results in a serious of intricate issues to students’ learning in post-secondary education programmes. It is worth to note that when students further pursue to an higher education in Hong Kong or even oversea, they may facing substantial difficulties in transiting learning from learning mathematics in their mother tongue in Chinese-medium instruction (CMI) secondary schools to an English-medium learning environment. Some students understood the mathematics concepts were found to fail to fulfill the course requirements at college or university due to their learning experience in secondary study at CMI. They are particularly weak in comprehending the mathematics questions when they are doing their assessment or attempting the test/examination. A government funded project was conducted with the aims of providing integrated learning context and language support to students with a lower level of numeracy and/or with CMI learning experience. By introducing this “integrated concept + language mapping approach”, students can cope with the learning challenges in the compulsory English-medium mathematics and statistics subjects in their tertiary education. Ultimately, in the hope that students can enhance their mathematical ability, analytical skills, and numerical sense for their lifelong learning. The “Concept + Language Mapping “(CLM) approach was adopted and tried out in the bridging courses for students with a lower level of numeracy and/or with CMI learning experiences. At the beginning of each class, a pre-test was conducted, and class time was then devoted to introducing the concepts by CLM approach. For each concept, the key thematic items and their different semantic relations are presented using graphics and animations via the CLM approach. At the end of each class, a post-test was conducted. Quantitative data analysis was performed to study the effect on students’ learning via the CLM approach. Stakeholders' feedbacks were collected to estimate the effectiveness of the CLM approach in facilitating both content and language learning. The results based on both students’ and lecturers’ feedback indicated positive outcomes on adopting the CLM approach to enhance the mathematical ability and analytical skills of CMI students.

Keywords: mathematics, Concept+Language Mapping, level of numeracy, medium of instruction

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Authors: Kuhelee Chandel, Julia Åhlén, Stefan Seipel

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This study evaluates the accuracy of Microsoft HoloLens (Version 1) for small-scale industrial activities, comparing its measurements to ground truth data from a Kuka Robotics arm. Two experiments were conducted to assess its position-tracking capabilities, revealing that the HoloLens device is effective for measuring the position of dynamic objects with small dimensions. However, its precision is affected by the velocity of the trajectory and its position within the device's field of view. While the HoloLens device may be suitable for small-scale tasks, its limitations for more complex and demanding applications requiring high precision and accuracy must be considered. The findings can guide the use of HoloLens devices in industrial applications and contribute to the development of more effective and reliable position-tracking systems.

Keywords: augmented reality (AR), Microsoft HoloLens, object tracking, industrial processes, manufacturing processes

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Authors: Precious Barnes, Abraham Mensah, Leonard Derkyi-Kwarteng, Benjamin Amoani, George Adjei, Ernest Adankwah, Faustina Pappoe, Kwabena Dankwah, Daniel Amoako-Sakyi, Samuel Victor Nuvor, Dorcas Obiri-Yeboah, Ewura Seidu Yahaya, Patrick Kafui Akakpo, Roland Osei Saahene

Abstract:

Context: Breast cancer is a prevalent and aggressive type of cancer among African women, with high mortality rates in Ghana. Nuclear factor kappa B (NF-kB) is a transcription factor that has been associated with tumor progression in breast cancer. However, there is a lack of published data on NF-kB in breast cancer patients in Ghana or other African countries. Research Aim: The aim of this study was to assess the prognostic significance of NF-kB (p65) expression and its association with various clinicopathological features in breast cancer patients at the Cape Coast Teaching Hospital in Ghana. Methodology: A total of 90 formalin-fixed breast cancer tissues and 15 normal breast tissues were used in this study. The expression level of NF-kB (p65) was examined using immunohistochemical techniques. Correlation analysis between NF-kB (p65) expression and clinicopathological features was performed using SPSS version 25. Findings: The study found that NF-kB (p65) was expressed in 86.7% of breast cancer tissues. There was a significant relationship between NF-kB (p65) expression and tumor grade, proliferation index (Ki67), and molecular subtype. High-level expression of NF-kB (p65) was more common in tumor grade 3 compared to grade 1, and Ki67 > 20 had higher expression of NF-kB (p65) compared to Ki67 ≤ 20. Triple-negative breast cancer patients had the highest overexpression of NF-kB (p65) compared to other molecular subtypes. There was no significant association between NF-kB (p65) expression and other clinicopathological parameters. Theoretical Importance: This study provides important insights into the expression of NF-kB (p65) in breast cancer patients in Ghana, particularly in relation to tumor grade and proliferation index. The findings suggest that NF-kB (p65) could serve as a potential biological marker for cancer stage, progression, prognosis and as a therapeutic target. Data Collection and Analysis Procedures: Formalin-fixed breast cancer tissues and normal breast tissues were collected and analyzed using immunohistochemical techniques. Correlation analysis between NF-kB (p65) expression and clinicopathological features was performed using SPSS version 25. Question Addressed: This study addressed the question of the prognostic significance of NF-kB (p65) expression and its association with clinicopathological features in breast cancer patients in Ghana. Conclusion: This study, the first of its kind in Ghana, demonstrates that NF-kB (p65) is highly expressed among breast cancer patients at the Cape Coast Teaching Hospital, especially in triple-negative breast cancer patients. The expression of NF-kB (p65) is associated with tumor grade and proliferation index. NF-kB (p65) could potentially serve as a biological marker for cancer stage, progression, prognosis, and as a therapeutic target.

Keywords: breast cancer, Ki67, NF-kB (p65), tumor grade

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Authors: O. Arbouche, Y. Benallou, K. Amara

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We report a first-principles study of structural, electronic and magnetic properties of ternary plumbides (rare earth-transition metal-Plumb) Dy2Ni2Pb crystallizes with the orthorhombic structure of the Mn2AlB2 type (space group Cmmm), were studied by means of the full-relativistic version of the full-potential augmented plane wave plus local orbital method within the frame work of spin-polarized density functional theory (SP-DFT). The electronic exchange-correlation energy is described by generalized gradient approximation (GGA). We have calculated the lattice parameters, bulk modulii and the first pressure derivatives of the bulk modulii, total densities of states and magnetic properties. The calculated total magnetic moment is found to be equal to 9.52 μB.

Keywords: spin-polarized, magnetic properties, Dy2Ni2Pb, Density functional theory

Procedia PDF Downloads 269

Authors: Itiola Kehinde Adeniran

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The study examined the effect of employees’ training on the performance of small scale enterprises in Oyo State. A structured questionnaire was used to collect data from 150 respondents through purposive sampling method. Linear regression was used with the aid of statistical package for social science (SPSS) version 20 to analyze the data collected in order to examine the effect of independent variable, employees’ training on dependent variable, performance (profit) of small scale enterprises. The result revealed that employees’ training has a significant effect on the performance of small scale enterprises. It was concluded that predictor variable namely (training) is 55.5% variance of enterprises performance (profitability). Therefore, the paper recommended that all small scale enterprises in Nigeria should embrace manpower training and development in order to improve employees’ performance leading to organizational profitability.

Keywords: training, employee performance, small scale enterprise, organizational profitability

Procedia PDF Downloads 341

Authors: Zine-Eddine Bouras, Abdelouaheb Talai

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During the last two decades, the software evolution community has intensively tackled the software merging issue whose main objective is to merge in a consistent way different versions of software in order to obtain a new version. Well-established approaches, mainly based on the dependence analysis techniques, have been used to bring suitable solutions. These approaches concern the source code or software architectures. However, these solutions are more expensive due to the complexity and size. In this paper, we overcome this problem by operating at a high level of abstraction. The objective of this paper is to investigate the software merging at the level of UML activity diagrams, which is a new interesting issue. Its purpose is to merge activity diagrams instead of source code. The proposed approach, based on dependence analysis techniques, is illustrated through an appropriate case study.

Keywords: activity diagram, activity diagram slicing, dependency analysis, software merging

Procedia PDF Downloads 297

Authors: Ching-Yu Lin

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The number of patients with aphasia has been gradually increasing; however, public awareness of aphasia is still limited. Moreover, surveys about public awareness of aphasia have been conducted in several countries, but there is no research about public awareness of aphasia in Taiwan so far. Therefore, this study aims at the investigation of public awareness of aphasia in Taiwan. In this pilot study, the original English-version questionnaire will be translated into Mandarin Chinese by a speech therapist (the author), and 100 Taiwanese over 18 years old will be recruited to finish the questionnaire. People with an occupation about health or medical will be excluded. In order to reach more people, the questionnaire will be an Internet survey by Google Forms, and the URL of the survey will be distributed by messaging, i.e. e-mail, Facebook Messenger, Instagram DM, or Line. Data will be analyzed via PASW Statistic 18. Descriptive statistics will be used to summarize what proportion of the public have heard of aphasia and what proportion of the public have basic knowledge of aphasia in Taiwan. The sources of information about aphasia will also be investigated. Further, differences in awareness of aphasia due to age, gender, and education level will be discussed.

Keywords: aphasia, public awareness, public knowledge, taiwan

Procedia PDF Downloads 69

Authors: Joseph Kwame Sarfo-Adu

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Social protection programs have been rolled out by successive governments in the quest of bridging the inequality gap in Ghana. Despite notable positive impacts of these programs across the country, there still remains worrying experience of the exclusion of the poor and vulnerable especially in rural Ghana Notwithstanding the rhetoric of participation within the discussion of social protection programs, less attention has been given to the design of these programs. In view of this, the study seeks to address how social protection programs are designed to address the needs of the poor. This study focused on five selected social protection programs in Ghana because they are programs with nationwide coverage. Qualitative thematic analysis was applied to analyze our data with the use of the Nvivo 12 version. We found out that there is a strong link between policy design and poverty alleviation. Our findings revealed that a well-designed program can significantly alleviate poverty, a poorly designed program can create more damage.

Keywords: social protection, poverty alleviation, policy design, effective outcome

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Authors: Badr M. Alshammari, T. Guesmi

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This study presents a modified version of the artificial bee colony (ABC) algorithm by including a local search technique for solving the non-convex economic power dispatch problem. The local search step is incorporated at the end of each iteration. Total system losses, valve-point loading effects and prohibited operating zones have been incorporated in the problem formulation. Thus, the problem becomes highly nonlinear and with discontinuous objective function. The proposed technique is validated using an IEEE benchmark system with ten thermal units. Simulation results demonstrate that the proposed optimization algorithm has better convergence characteristics in comparison with the original ABC algorithm.

Keywords: economic power dispatch, artificial bee colony, valve-point loading effects, prohibited operating zones

Procedia PDF Downloads 225

Authors: Ali Kazemi

Abstract:

Those within the volatile and interconnected international economic markets, appropriately predicting market trends, hold substantial fees for traders and financial establishments. Traditional device mastering strategies have made full-size strides in forecasting marketplace movements; however, monetary data's complicated and networked nature calls for extra sophisticated processes. This observation offers a groundbreaking method for monetary marketplace prediction that leverages the synergistic capability of Graph Convolutional Networks (GCNs) and Long Short-Term Memory (LSTM) networks. Our suggested algorithm is meticulously designed to forecast the traits of inventory market indices and cryptocurrency costs, utilizing a comprehensive dataset spanning from January 1, 2015, to December 31, 2023. This era, marked by sizable volatility and transformation in financial markets, affords a solid basis for schooling and checking out our predictive version. Our algorithm integrates diverse facts to construct a dynamic economic graph that correctly reflects market intricacies. We meticulously collect opening, closing, and high and low costs daily for key inventory marketplace indices (e.g., S&P 500, NASDAQ) and widespread cryptocurrencies (e.g., Bitcoin, Ethereum), ensuring a holistic view of marketplace traits. Daily trading volumes are also incorporated to seize marketplace pastime and liquidity, providing critical insights into the market's shopping for and selling dynamics. Furthermore, recognizing the profound influence of the monetary surroundings on financial markets, we integrate critical macroeconomic signs with hobby fees, inflation rates, GDP increase, and unemployment costs into our model. Our GCN algorithm is adept at learning the relational patterns amongst specific financial devices represented as nodes in a comprehensive market graph. Edges in this graph encapsulate the relationships based totally on co-movement styles and sentiment correlations, enabling our version to grasp the complicated community of influences governing marketplace moves. Complementing this, our LSTM algorithm is trained on sequences of the spatial-temporal illustration discovered through the GCN, enriched with historic fee and extent records. This lets the LSTM seize and expect temporal marketplace developments accurately. Inside the complete assessment of our GCN-LSTM algorithm across the inventory marketplace and cryptocurrency datasets, the version confirmed advanced predictive accuracy and profitability compared to conventional and opportunity machine learning to know benchmarks. Specifically, the model performed a Mean Absolute Error (MAE) of 0.85%, indicating high precision in predicting day-by-day charge movements. The RMSE was recorded at 1.2%, underscoring the model's effectiveness in minimizing tremendous prediction mistakes, which is vital in volatile markets. Furthermore, when assessing the model's predictive performance on directional market movements, it achieved an accuracy rate of 78%, significantly outperforming the benchmark models, averaging an accuracy of 65%. This high degree of accuracy is instrumental for techniques that predict the course of price moves. This study showcases the efficacy of mixing graph-based totally and sequential deep learning knowledge in economic marketplace prediction and highlights the fee of a comprehensive, records-pushed evaluation framework. Our findings promise to revolutionize investment techniques and hazard management practices, offering investors and economic analysts a powerful device to navigate the complexities of cutting-edge economic markets.

Keywords: financial market prediction, graph convolutional networks (GCNs), long short-term memory (LSTM), cryptocurrency forecasting

Procedia PDF Downloads 19