Search results for: learning pattern

Authors: Sarathlal Koyiloth Vayalil, Stephan V. Roth, Gonzalo Santoro, Peng Zhang, Matthias Schwartzkopf, Bjoern Beyersdorff

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Nanostructured magnetic thin films have gained significant relevance due to its applications in magnetic storage and recording media. Self-organized arrays of nanoparticles and nanowires can be produced by depositing metal thin films on nano-rippled substrates. The substrate topography strongly affects the film growth giving rise to anisotropic properties (optical, magnetic, electronic transport). Ion-beam erosion (IBE) method can provide large-area patterned substrates with the valuable possibility to widely modify pattern length scale by simply acting on ion beam parameters (i.e. energy, ions, geometry, etc.). In this work, investigation of the growth mechanism of Permalloy thin films on such nano-rippled Si (100) substrates using in situ grazing incidence small angle x-ray scattering measurements (GISAXS) have been done. In situ GISAXS measurements during the deposition of thin films have been carried out at the P03/MiNaXS beam line of PETRA III storage ring of DESY, Hamburg. Nanorippled Si substrates prepared by low energy ion beam sputtering with an average wavelength of 33 nm and 1 nm have been used as templates. It has been found that the film replicates the morphology up to larger thickness regimes and also the growth is highly anisotropic along and normal to the ripple wave vectors. Various growth regimes have been observed. Further, magnetic measurements have been done using magneto-optical Kerr effect by rotating the sample in the azimuthal direction. Strong uniaxial magnetic anisotropy with its easy axis in a direction normal to the ripple wave vector has been observed. The strength of the magnetic anisotropy is found to be decreasing with increasing thin film thickness values. The mechanism of the observed strong uniaxial magnetic anisotropy and its depends on the thickness of the film has been explained by correlating it with the GISAXS results. In conclusion, we have done a detailed growth analysis of Permalloy thin films deposited on nanorippled Si templates and tried to explain the correlation between structure, morphology to the observed magnetic properties.

Keywords: grazing incidence small angle x-ray scattering, magnetic thin films, magnetic anisotropy, nanoripples

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Authors: Wajeeh Daher, Nimer Baya'a

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High Order Thinking Skills (HOTS) are suggested today as essential for the cognitive development of students and as preparing them for real life skills. Teachers are encouraged to use HOTS activities in the classroom to help their students develop higher order skills and deep thinking. So it is essential to prepare pre-service teachers to write and use HOTS activities for their students. This paper describes a model for integrating HOTS activities with GeoGebra in pre-service teachers’ preparation. This model describes four aspects of HOTS activities and working with them: Activity components, preparation procedure, strategies and processes used in writing a HOTS activity and types of the HOTS activities. In addition, the paper describes the pre-service teachers' difficulties in preparing and working with HOTS activities, as well as their perceptions regarding the use of these activities and GeoGebra in the mathematics classroom. The paper also describes the contribution of a HOTS activity to pupils' learning of mathematics, where this HOTS activity was prepared and taught by one pre-service teacher.

Keywords: high order thinking skills, HOTS activities, pre-service teachers, professional development

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Authors: Samuel Olajide Babawale, Jonathan Bridge

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Natural Flood Management (NFM) is promoted as part of sustainable flood management (SFM) in response to climate change adaptation. Stakeholder engagement is central to this approach, and current trends are progressively moving towards a collaborative learning approach where stakeholder participation is perceived as one of the indicators of sustainable development. Within this methodology, participation embraces a diversity of knowledge and values underpinned by a philosophy of empowerment, equity, trust, and learning. To identify barriers to NFM uptake, there is a need for a new understanding of how stakeholder participation could be enhanced to benefit individual and community resilience within SFM. This is crucial in light of climate change threats and scientific reliability concerns. In contributing to this new understanding, this research evaluated the proposed interventions on six (6) UK NFM in a catchment known as the Sheffield Lakeland Partnership Area with reference to the Environment Agency Working with Natural Processes (WWNP) Potentials/Opportunities. Three of the opportunities, namely Run-off Attenuation Potential of 1%, Run-off Attenuation Potential of 3.3% and Riparian Woodland Potential, were modeled. In all the models, the interventions, though they have been proposed or already in place, are not in agreement with the data presented by EA WWNP. Findings show some institutional weaknesses, which are seen to inhibit the development of adequate flood management solutions locally with damaging implications for vulnerable communities. The gap in communication from practitioners poses a challenge to the implementation of real flood mitigating measures that align with the lead agency’s nationally accepted measures which are identified as not feasible by the farm management officers within this context. Findings highlight a dominant top-bottom approach to management with very minimal indication of local interactions. Current WWNP opportunities have been termed as not realistic by the people directly involved in the daily management of the farms, with less emphasis on prevention and mitigation. The targeted approach suggested by the EA WWNP is set against adaptive flood management and community development. The study explores dimensions of participation using the self-reliance and self-help approach to develop a methodology that facilitates reflections of currently institutionalized practices and the need to reshape spaces of interactions to enable empowered and meaningful participation. Stakeholder engagement and resilience planning underpin this research. The findings of the study suggest different agencies have different perspectives on “community participation”. It also shows communities in the case study area appear to be least influential, denied a real chance of discussing their situations and influencing the decisions. This is against the background that the communities are in the most productive regions, contributing massively to national food supplies. The results are discussed concerning practical implications for addressing interagency partnerships and conducting grassroots collaborations that empower local communities and seek solutions to sustainable development challenges. This study takes a critical look into the challenges and progress made locally in sustainable flood risk management and adaptation to climate change by the United Kingdom towards achieving the global 2030 agenda for sustainable development.

Keywords: natural flood management, sustainable flood management, sustainable development, working with natural processes, environment agency, run-off attenuation potential, climate change

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Authors: Magdalena Kowalska, Weronika Rupik

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The pancreas is an important organ present in all vertebrate species. It contains two different tissues, exocrine and endocrine, that act as two glands in one. The development and differentiation of the pancreas in reptiles is poorly known in comparison to other vertebrates. Therefore, the aim of this study was to investigate the particular steps concerning the differentiation of the pancreas in the grass snake (Natrix natrix) embryos. For this, histological methods (including hematoxylin and eosin, and Heidenhain's AZAN staining), transmission electron microscopy and three-dimensional (3D) reconstructions from serial paraffin sections were used. The results of this study indicated that the first step of pancreas development in Natrix was the connection of the two pancreatic buds: dorsal and ventral one. Then, duct walls in both buds started to be remodeled from the multilayered to single-layered epithelium. This remodeling started in the dorsal bud and was simultaneously with the differentiation of the duct lumens which occurred by the cavition. During this process, the cells that had no contact with the mesenchyme underwent cell death named anoikis. These findings indicated that the walls of ducts in the embryonic pancreas of the grass snake were initially formed by the abundant principal and single endocrine cells. Later the basal and goblet cells differentiated. Among the endocrine cells, as the first the B and A cells differentiated, then the D and PP cells. The next step of the pancreatic development was the withdrawing of the endocrine cells from the duct walls to form the pancreatic islets. The endocrine cells and islets were found only in the dorsal part of the pancreas in Natrix embryos what is different than in other vertebrate species. The islets were formed mainly by the A cells. Simultaneously, with the differentiation of the endocrine pancreas, the acinar tissue started to differentiate. The source of the acinar cells were pancreatic ducts similar as in other vertebrates. The acini formation began at the proximal part of the pancreas and went towards the caudal direction. Differentiating pancreatic ducts developed into the branched system that can be divided into extralobular, intralobular, and intercalated ducts, similarly as in other vertebrate species. However, the pattern of branching was different. In conclusions, particular steps of the pancreas differentiation in the grass snake were different than in other vertebrates. It can be supposed that these differences are related to the specific topography of the snake’s internal organs and their taxonomy position. All specimens used in the study were captured according to the Polish regulations concerning the protection of wild species. Permission was granted by the Local Ethics Commission in Katowice (41/2010; 87/2015) and the Regional Directorate for Environmental Protection in Katowice (WPN.6401.257.2015.DC).

Keywords: embryogenesis, organogenesis, pancreas, Squamata

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Authors: Swati Arun

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The present paper argues that Balance of Power (BOP) needs to conjugate with certain contingencies like geography. It is evident that sea powers (‘insular’ for better clarity) are not balanced (if at all) in the same way as land powers. Its apparent that artificial insularity that the US has achieved reduces the chances of balancing (constant) and helps it maintain preponderance (variable). But how precise is this approach in assessing the dynamics between China’s rise and reaction of other powers and US. The ‘evolved’ theory can be validated by putting China and US in the equation. Systemic Relation between the nations was explained through the Balance of Power theory much before the systems theory was propounded. The BOP is the crux of functionality of ‘power relation’ dynamics which has played its role in the most astounding ways leading to situations of war and peace. Whimsical; but true that, the BOP has remained a complicated and indefinable concepts since Hans. Morganthau to Kenneth Waltz. A challenge of the BOP, however remains; “ that it has too many meanings”. In the recent times it has become evident that the myriad of expectations generated by BOP has not met the practicality of the current world politics. It is for this reason; the BoP has been replaced by Preponderance Theory (PT) to explain prevailing power situation. PT does provide an empirical reasoning for the success of this theory but fails in a abstract logical reasoning required for making a theory universal. Unipolarity clarifies the current system as one where balance of power has become redundant. It seems to reach beyond the contours of BoP, where a superpower does what it must to remain one. The centrality of this arguments pivots around - an exception, every time BOP fails to operate, preponderance of power emerges. PT does not sit well with the primary logic of a theory because it works on an exception. The evolution of such a pattern and system where BOP fails and preponderance emerges is absent. The puzzle here is- if BOP really has become redundant or it needs polishing. The international power structure changed from multipolar to bipolar to unipolar. BOP was looked at to provide inevitable logic behind such changes and answer the dilemma we see today- why US is unchecked, unbalanced? But why was Britain unchecked in 19th century and why China was unbalanced in 13th century? It is the insularity of the state that makes BOP reproduce “imbalance of power”, going a level up from off-shore balancer. This luxury of a state to maintain imbalance in the region of competition or threat is the causal relation between BOP’s and geography. America has applied imbalancing- meaning disequilibrium (in its favor) to maintain the regional balance so that over time the weaker does not get stronger and pose a competition. It could do that due to the significant parity present between the US and the rest.

Keywords: balance of power, china, preponderance of power, US

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Authors: Nathaniel Bayode Eniolorunda, Murtala Abubakar Gada, Sheikh Danjuma Abubakar

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The challenge of erosion in the study area is persistent, suggesting the need for a better understanding of the mechanisms that drive it. Thus, the study evolved a predictive erosion model (RUSLE_Sok), deploying Remote Sensing (RS) and Geographical Information System (GIS) tools. The nature and pattern of the factors of erosion were characterized, while soil losses were quantified. Factors’ impacts were also measured, and the morphometry of gullies was described. Data on the five factors of RUSLE and distances to settlements, rivers and roads (K, R, LS, P, C, DS DRd and DRv) were combined and processed following standard RS and GIS algorithms. Harmonized World Soil Data (HWSD), Shuttle Radar Topographical Mission (SRTM) image, Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), Sentinel-2 image accessed and processed within the Google Earth Engine, road network and settlements were the data combined and calibrated into the factors for erosion modeling. A gully morphometric study was conducted at some purposively selected sites. Factors of soil erosion showed low, moderate, to high patterns. Soil losses ranged from 0 to 32.81 tons/ha/year, classified into low (97.6%), moderate (0.2%), severe (1.1%) and very severe (1.05%) forms. The multiple regression analysis shows that factors statistically significantly predicted soil loss, F (8, 153) = 55.663, p < .0005. Except for the C-Factor with a negative coefficient, all other factors were positive, with contributions in the order of LS>C>R>P>DRv>K>DS>DRd. Gullies are generally from less than 100m to about 3km in length. Average minimum and maximum depths at gully heads are 0.6 and 1.2m, while those at mid-stream are 1 and 1.9m, respectively. The minimum downstream depth is 1.3m, while that for the maximum is 4.7m. Deeper gullies exist in proximity to rivers. With minimum and maximum gully elevation values ranging between 229 and 338m and an average slope of about 3.2%, the study area is relatively flat. The study concluded that major erosion influencers in the study area are topography and vegetation cover and that the RUSLE_Sok well predicted soil loss more effectively than ordinary RUSLE. The adoption of conservation measures such as tree planting and contour ploughing on sloppy farmlands was recommended.

Keywords: RUSLE_Sok, Sokoto, google earth engine, sentinel-2, erosion

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Authors: Aber Aboalgasm, Rupert Ward, Ruth Taylor, Jonathan Glazzard

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Teaching art by digital means is a big challenge for the majority of teachers of art and artistic design courses in primary education schools. These courses can clearly identify relationships between art, technology, and creativity in the classroom .The aim of this article is to present a modern way of teaching art, using digital tools in the art classroom in order to improve creative ability in pupils aged between 9 and 11 years; it also presents a conceptual model for creativity based on digital art. The model could be useful for pupils interested in learning drawing and using an e-drawing package, and for teachers who are interested in teaching their students modern digital art, and improving children’s creativity. This model is designed to show the strategy of teaching art through technology, in order for children to learn how to be creative. This will also help education providers to make suitable choices about which technological approaches they should choose to teach students and enhance their creative ability. It is also expected that use of this model will help to develop social interactive qualities that may improve intellectual ability.

Keywords: digital tools, motivation, creative activity, education

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Authors: Justin Reverdi, Sixin Zhang, Saïd Aoues, Fabrice Gamboa, Serge Gratton, Thomas Pellegrini

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In vapor cycle systems, the mass flow sensor plays a key role for different monitoring and control purposes. However, physical sensors can be inaccurate, heavy, cumbersome, expensive, or highly sensitive to vibrations, which is especially problematic when embedded into an aircraft. The conception of a virtual sensor, based on other standard sensors, is a good alternative. This paper has two main objectives. Firstly, a data-driven model using a convolutional neural network is proposed to estimate the mass flow of the compressor. We show that it significantly outperforms the standard polynomial regression model (thermodynamic maps) in terms of the standard MSE metric and engineer performance metrics. Secondly, a semi-automatic segmentation method is proposed to compute the engineer performance metrics for real datasets, as the standard MSE metric may pose risks in analyzing the dynamic behavior of vapor cycle systems.

Keywords: deep learning, convolutional neural network, vapor cycle system, virtual sensor

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Authors: George Kyriakopoulos, Photini Pazartzis, Anthi Koskina, Crystalie Bourcha

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The need for securing safe access to and return from outer space, as well as ensuring the viability of outer space operations, maintains vivid the debate over the promotion of organization of space traffic through a Space Traffic Management System (STM). The proliferation of outer space activities in recent years as well as the dynamic emergence of the private sector has gradually resulted in a diverse universe of actors operating in outer space. The said developments created an increased adverse impact on outer space sustainability as the case of the growing number of space debris clearly demonstrates. The above landscape sustains considerable threats to outer space environment and its operators that need to be addressed by a combination of scientific-technological measures and regulatory interventions. In this context, recourse to recent technological advancements and, in particular, to Artificial Intelligence (AI) and machine learning systems, could achieve exponential results in promoting space traffic management with respect to collision avoidance as well as launch and re-entry procedures/phases. New technologies can support the prospects of a successful space traffic management system at an international scale by enabling, inter alia, timely, accurate and analytical processing of large data sets and rapid decision-making, more precise space debris identification and tracking and overall minimization of collision risks and reduction of operational costs. What is more, a significant part of space activities (i.e. launch and/or re-entry phase) takes place in airspace rather than in outer space, hence the overall discussion also involves the highly developed, both technically and legally, international (and national) Air Traffic Management System (ATM). Nonetheless, from a regulatory perspective, the use of AI for the purposes of space traffic management puts forward implications that merit particular attention. Key issues in this regard include the delimitation of AI-based activities as space activities, the designation of the applicable legal regime (international space or air law, national law), the assessment of the nature and extent of international legal obligations regarding space traffic coordination, as well as the appropriate liability regime applicable to AI-based technologies when operating for space traffic coordination, taking into particular consideration the dense regulatory developments at EU level. In addition, the prospects of institutionalizing international cooperation and promoting an international governance system, together with the challenges of establishment of a comprehensive international STM regime are revisited in the light of intervention of AI technologies. This paper aims at examining regulatory implications advanced by the use of AI technology in the context of space traffic management operations and its key correlating concepts (SSA, space debris mitigation) drawing in particular on international and regional considerations in the field of STM (e.g. UNCOPUOS, International Academy of Astronautics, European Space Agency, among other actors), the promising advancements of the EU approach to AI regulation and, last but not least, national approaches regarding the use of AI in the context of space traffic management, in toto. Acknowledgment: The present work was co-funded by the European Union and Greek national funds through the Operational Program "Human Resources Development, Education and Lifelong Learning " (NSRF 2014-2020), under the call "Supporting Researchers with an Emphasis on Young Researchers – Cycle B" (MIS: 5048145).

Keywords: artificial intelligence, space traffic management, space situational awareness, space debris

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Authors: Prudhvinath Reddy Ankireddy, Narasimha Mangadoddy

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Spiral concentrators are commonly used in various industries, including mineral and coal processing, to efficiently separate materials based on their density and size. In these concentrators, a mixture of solid particles and fluid (usually water) is introduced as feed at the top of a spiral channel. As the mixture flows down the spiral, centrifugal and gravitational forces act on the particles, causing them to stratify based on their density and size. Spiral flows exhibit complex fluid dynamics, and interactions involve multiple phases and components in the process. Understanding the behavior of these phases within the spiral concentrator is crucial for achieving efficient separation. An experimental bi-component particle interaction study is conducted in this work utilizing magnetite (heavier density) and silica (lighter density) with different proportions processed in the spiral concentrator. The observation separation reveals that denser particles accumulate towards the inner region of the spiral trough, while a significant concentration of lighter particles are found close to the outer edge. The 5th turn of the spiral trough is partitioned into five zones to achieve a comprehensive distribution analysis of bicomponent particle segregation. Samples are then gathered from these individual streams using an in-house sample collector, and subsequent analysis is conducted to assess component segregation. Along the trough, there was a decline in the concentration of coarser particles, accompanied by an increase in the concentration of lighter particles. The segregation pattern indicates that the heavier coarse component accumulates in the inner zone, whereas the lighter fine component collects in the outer zone. The middle zone primarily consists of heavier fine particles and lighter coarse particles. The zone-wise results reveal that there is a significant fraction of segregation occurs in inner and middle zones. Finer magnetite and silica particles predominantly accumulate in outer zones with the smallest fraction of segregation. Additionally, numerical simulations are also carried out using the computational fluid dynamics (CFD) model based on the volume of fluid (VOF) approach incorporating the RSM turbulence model. The discrete phase model (DPM) is employed for particle tracking, thereby understanding the particle segregation of magnetite and silica along the spiral trough.

Keywords: spiral concentrator, bi-component particle segregation, computational fluid dynamics, discrete phase model

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Authors: Patricia Silva, Iolanda Costa Galinha, Cristina Costa-Lobo

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The present research aims to evaluate, in the context of formal learning, the influence of affections, through subjective well-being, as well as the influence of personality, in the metacognition levels. There are few studies that analyze the influence of affection and personality on metacognition. The sample of this study consists of 300 Portuguese adolescents, male and female, aged between 15 and 17 years. The main variables of this study are affections, personality, ascertained through neuroticism and extraversion, and metacognition, namely the knowledge of cognition and the regulation of cognition. Initially, the sociodemographic questionnaire was constructed and administered to characterize the sample in its variables. To evaluate the affective experience in adolescents was administered PANAS-N, that is a measure of self-assessment of positive and negative affectivity in children and adolescents. To evaluate the personality, in its variables extroversion and neuroticism, the NEO-FFI was applied. The Metacognitive Awareness Inventory, MAI, was used to assess knowledge of cognition and regulation of cognition. The data analysis was performed using the statistical software IBM SPSS 22.0. After analyzing and discussing the results, a set of theoretical interdisciplinary reflection, between the sciences of education and psychology, is concretized, contributing to the reflection on psychoeducational intervention, opening the way for future studies.

Keywords: affections, personality, metacognition, psychoeducational intervention

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Authors: Ismial A. Raji, Blessing Egbezieme Oladejo, Babatunde Kasim Oladele

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The study investigated the influence of leadership succession and tenure on goal attainment in the University of Ibadan. Leadership styles, tenure politics, organization succession, leadership succession, goal attainment in terms of research, teaching and public services were considered. The study adopted a descriptive survey design. The population of the study was 250 consisting 90 academic staff, 100 Senior Non-Teaching Staff and 60 Junior Non-Teaching Staff. Questionnaire was the instrument used to collect data. The instrument reliability coefficient was 0.88. Data collected were analysed with descriptive statistics. The result revealed that a significant relationship exist between leadership succession, tenure and goal attainment (r= .648, 0.466 and 0.479p< .0.5) Also, There was no statistical significant interaction between the effects of leadership tenure and leadership succession on goal attainment, F (38, 131) = 1.356, p = .104. The main influence of the independent variables on goal attainment were significant at F (24, 131) = 1.682, p=.034 and F (26, 131) = 2.182, p=.002. The study concluded that leadership succession and tenure are key factors for goal attainment in the University of Ibadan. The study recommended that an effective leadership succession and tenure processes should be maintained and sustained by higher institutions of learning.

Keywords: leadership tenure, style, succession, institutional goal

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Authors: Jubaida Gulshan Ara, Zebun Nasreen Ahmed

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Urban flood and drought has been a major problem of Dhaka city, particularly in recent years. Continuous increase of the city built up area, and limiting rainwater infiltration zone, are thought to be the main causes of the problem. Proper rainwater management, even at the individual plot level, might bring significant improvement in this regard. As residential use pattern occupies a significant portion of the city surface, the scope of rainwater harvesting (RWH) in residential buildings can be investigated. This paper reports on a research which explored the scope of rainwater harvesting in residential plots, with multifamily apartment buildings, in Dhaka city. The research investigated the basics of RWH, contextual information, i.e., hydro-geological, meteorological data of Dhaka city and the rules and legislations for residential building construction. The study also explored contemporary rainwater harvesting practices in the local and international contexts. On the basis of theoretical understanding, 21 sample case-studies, in different phases of construction, were selected from seven different categories of plot sizes, in different residential areas of Dhaka city. Primary data from the 21 case-study buildings were collected from a physical survey, from design drawings, accompanied by a questionnaire survey. All necessary secondary data were gathered from published and other relevant sources. Collected primary and secondary data were used to calculate and analyze the RWH needs for each case study, based on the theoretical understanding. The main findings have been compiled and compared, to observe residential development trends with regards to building rainwater harvesting system. The study has found that, in ‘Multifamily Apartment Building’ of Dhaka city, storage, and recharge structure size for rainwater harvesting, increases along with occupants’ number, and with the increasing size of the plot. Hence, demand vs. supply ratio remains almost the same for different sizes of plots, and consequently, the size of the storage structure increases significantly, in large-scale plots. It has been found that rainwater can meet only 12%-30% of the total restricted water demand of these residential buildings of Dhaka city. Therefore, artificial groundwater recharge might be the more suitable option for RWH, than storage. The study came up with this conclusion that, in multifamily residential apartments of Dhaka city, artificial groundwater recharge might be the more suitable option for RWH, than storing the rainwater on site.

Keywords: Dhaka city, rainwater harvesting, residential plots, urban flood

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Authors: Asma A. Alsufyani, Maram A. Alharthi, Maha J. Althobaiti, Manal S. Alharthi, Huda Rizq

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Twitter is one of the most popular microblogging sites that allows users to publish short text messages called 'tweets'. Increasing the number of accounts to follow (followings) increases the number of tweets that will be displayed from different topics in an unclassified manner in the timeline of the user. Therefore, it can be a vital solution for many Twitter users to have their tweets in a timeline classified into general categories to save the user’s time and to provide easy and quick access to tweets based on topics. In this paper, we developed a classifier for timeline tweets trained on a dataset consisting of 3600 tweets in total, which were collected from Saudi Twitter and annotated manually. We experimented with the well-known Bag-of-Words approach to text classification, and we used support vector machines (SVM) in the training process. The trained classifier performed well on a test dataset, with an average F1-measure equal to 92.3%. The classifier has been integrated into an application, which practically proved the classifier’s ability to classify timeline tweets of the user.

Keywords: corpus creation, feature extraction, machine learning, short text classification, social media, support vector machine, Twitter

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Authors: Naman Solanki, Souraj Mondal

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With the world moving towards online communication, the video datastore has exploded in the past few years. Consequently, it has become crucial to analyse participant’s engagement levels in online communication videos. Engagement prediction of people in videos can be useful in many domains, like education, client meetings, dating, etc. Video-level or frame-level prediction of engagement for a user involves the development of robust models that can capture facial micro-emotions efficiently. For the development of an engagement prediction model, it is necessary to have a widely-accepted standard dataset for engagement analysis. DAiSEE is one of the datasets which consist of in-the-wild data and has a gold standard annotation for engagement prediction. Earlier research done using the DAiSEE dataset involved training and testing standard models like CNN-based models, but the results were not satisfactory according to industry standards. In this paper, a multi-level classification approach has been introduced to create a more robust model for engagement analysis using the DAiSEE dataset. This approach has recorded testing accuracies of 0.638, 0.7728, 0.8195, and 0.866 for predicting boredom level, engagement level, confusion level, and frustration level, respectively.

Keywords: computer vision, engagement prediction, deep learning, multi-level classification

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Authors: Davood Vatankhah, Reza Mokhtari Malekabadi, Mohsen Saghaei

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Function of urban transportation systems depends on the existence of the required infrastructures, appropriate placement of different components, and the cooperation of these components with each other. Establishing various neighboring parking spaces in city neighborhood in order to prevent long-term and inappropriate parking of cars in the allies is one of the most effective operations in reducing the crowding and density of the neighborhoods. Every place with a certain application attracts a number of daily travels which happen throughout the city. A large percentage of the people visiting these places go to these travels by their own cars; therefore, they need a space to park their cars. The amount of this need depends on the usage function and travel demand of the place. The study aims at investigating the spatial distribution of the public parking spaces, determining the effective factors in locating, and their combination in GIS environment in Khomeinishahr of Isfahan city. Ultimately, the study intends to create an appropriate pattern for locating parking spaces, determining the request for parking spaces of the traffic areas, choosing the proper places for providing the required public parking spaces, and also proposing new spots in order to promote quality and quantity aspects of the city in terms of enjoying public parking spaces. Regarding the method, the study is based on applied purpose and regarding nature, it is analytic-descriptive. The population of the study includes people of the center of Khomeinishahr which is located on Northwest of Isfahan having about 5000 hectares of geographic area and the population of 241318 people are in the center of Komeinishahr. In order to determine the sample size, Cochran formula was used and according to the population of 26483 people of the studied area, 231 questionnaires were used. Data analysis was carried out by usage of SPSS software and after estimating the required space for parking spaces, initially, the effective criteria in locating the public parking spaces are weighted by the usage of Analytic Hierarchical Process in the Arc GIS software. Then, appropriate places for establishing parking spaces were determined by fuzzy method of Order Weighted Average (OWA). The results indicated that locating of parking spaces in Khomeinishahr have not been carried out appropriately and per capita of the parking spaces is not desirable in relation to the population and request; therefore, in addition to the present parking lots, 1434 parking lots are needed in the area of the study for each day; therefore, there is not a logical proportion between parking request and the number of parking lots in Khomeinishahr.

Keywords: GIS, locating, parking, khomeinishahr

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Authors: Huseyin Guler, Cigdem Kosar

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The aim of this study is to propose Bridge estimator for seasonal unit root tests. Seasonality is an important factor for many economic time series. Some variables may contain seasonal patterns and forecasts that ignore important seasonal patterns have a high variance. Therefore, it is very important to eliminate seasonality for seasonal macroeconomic data. There are some methods to eliminate the impacts of seasonality in time series. One of them is filtering the data. However, this method leads to undesired consequences in unit root tests, especially if the data is generated by a stochastic seasonal process. Another method to eliminate seasonality is using seasonal dummy variables. Some seasonal patterns may result from stationary seasonal processes, which are modelled using seasonal dummies but if there is a varying and changing seasonal pattern over time, so the seasonal process is non-stationary, deterministic seasonal dummies are inadequate to capture the seasonal process. It is not suitable to use seasonal dummies for modeling such seasonally nonstationary series. Instead of that, it is necessary to take seasonal difference if there are seasonal unit roots in the series. Different alternative methods are proposed in the literature to test seasonal unit roots, such as Dickey, Hazsa, Fuller (DHF) and Hylleberg, Engle, Granger, Yoo (HEGY) tests. HEGY test can be also used to test the seasonal unit root in different frequencies (monthly, quarterly, and semiannual). Another issue in unit root tests is the lag selection. Lagged dependent variables are added to the model in seasonal unit root tests as in the unit root tests to overcome the autocorrelation problem. In this case, it is necessary to choose the lag length and determine any deterministic components (i.e., a constant and trend) first, and then use the proper model to test for seasonal unit roots. However, this two-step procedure might lead size distortions and lack of power in seasonal unit root tests. Recent studies show that Bridge estimators are good in selecting optimal lag length while differentiating nonstationary versus stationary models for nonseasonal data. The advantage of this estimator is the elimination of the two-step nature of conventional unit root tests and this leads a gain in size and power. In this paper, the Bridge estimator is proposed to test seasonal unit roots in a HEGY model. A Monte-Carlo experiment is done to determine the efficiency of this approach and compare the size and power of this method with HEGY test. Since Bridge estimator performs well in model selection, our approach may lead to some gain in terms of size and power over HEGY test.

Keywords: bridge estimators, HEGY test, model selection, seasonal unit root

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Authors: Satien Janpla, Radasa Pojard

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The objective of this study is to study bachelor's degree students’ satisfaction towards the course of Science Project based on education quality assurance. It is a case study of the Faculty of Science and Technology, Suan Sunandha Rajabhat University. The findings can be used as a guideline for analysis and revision of the content and the teaching/learning process of the subject. Moreover, other interesting factors such as teaching method can be developed based on education quality assurance. Population in this study included 267 students in year 3 and year 4 of the Faculty of Science and Technology, Suan Sunandha Rajabhat University who registered in the subject of Science Project in semester 1/2556. The research tool was a questionnaire and the research statistics included arithmetic mean and SD. The results showed that the study of bachelor degree students’ satisfaction towards the subject of Science Project based on education quality assurance reported high satisfaction with the average of 3.51. Students from different departments showed no difference in their satisfaction.

Keywords: satisfaction, science project subject, education quality assurance, students

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Authors: Jameela Ali Alkrimi, Abdul Rahim Ahmad, Azizah Suliman, Loay E. George

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Red blood cells (RBCs) are among the most commonly and intensively studied type of blood cells in cell biology. The lack of RBCs is a condition characterized by lower than normal hemoglobin level; this condition is referred to as 'anemia'. In this study, a software was developed to isolate RBCs by using a machine learning approach to classify anemic RBCs in microscopic images. Several features of RBCs were extracted using image processing algorithms, including principal component analysis (PCA). With the proposed method, RBCs were isolated in 34 second from an image containing 18 to 27 cells. We also proposed that PCA could be performed to increase the speed and efficiency of classification. Our classifier algorithm yielded accuracy rates of 100%, 99.99%, and 96.50% for K-nearest neighbor (K-NN) algorithm, support vector machine (SVM), and neural network ANN, respectively. Classification was evaluated in highly sensitivity, specificity, and kappa statistical parameters. In conclusion, the classification results were obtained for a short time period with more efficient when PCA was used.

Keywords: red blood cells, pre-processing image algorithms, classification algorithms, principal component analysis PCA, confusion matrix, kappa statistical parameters, ROC

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Authors: Miriam Sebastian

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This research focused on the effects of bilingual education as medium of instruction to the academic performance of selected intermediate students of Miriam’s Academy of Valenzuela Inc. . An experimental design was used, with language of instruction as the independent variable and the different literacy skills as dependent variables. The sample consisted of experimental students comprises of 30 students were exposed to bilingual education (Filipino and English) . They were given pretests and were divided into three groups: Monolingual Filipino, Monolingual English, and Bilingual. They were taught different literacy skills for eight weeks and were then administered the posttests. Data was analyzed and evaluated in the light of the central processing and script-dependent hypotheses. Based on the data, it can be inferred that monolingual instruction in either Filipino or English had a stronger effect on the students’ literacy skills compared to bilingual instruction. Moreover, mother tongue-based instruction, as compared to second-language instruction, had stronger effect on the preschoolers’ literacy skills. Such results have implications not only for mother tongue-based (MTB) but also for English as a second language (ESL) instruction in the country

Keywords: bilingualism, effects, monolingual, function, multilingual, mother tongue

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Authors: Alireza Vafaei Sadr, Vida Abedi, Jiang Li, Ramin Zand

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Missing data is a common challenge in medical research and can lead to biased or incomplete results. When the data bias leaks into models, it further exacerbates health disparities; biased algorithms can lead to misclassification and reduced resource allocation and monitoring as part of prevention strategies for certain minorities and vulnerable segments of patient populations, which in turn further reduce data footprint from the same population – thus, a vicious cycle. This study compares the performance of six imputation techniques grouped into Linear and Non-Linear models on two different realworld electronic health records (EHRs) datasets, representing 17864 patient records. The mean absolute percentage error (MAPE) and root mean squared error (RMSE) are used as performance metrics, and the results show that the Linear models outperformed the Non-Linear models in terms of both metrics. These results suggest that sometimes Linear models might be an optimal choice for imputation in laboratory variables in terms of imputation efficiency and uncertainty of predicted values.

Keywords: EHR, machine learning, imputation, laboratory variables, algorithmic bias

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Authors: June Keeling, Christina Athanasiades, Vaiva Hendrixson, Delyth Wyndham

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Recognition and education in violence, abuse, and neglect for medical and healthcare practitioners (REVAMP) is a trans-European project aiming to introduce a training programme that has been specifically developed by partners across seven European countries to meet the needs of medical and healthcare practitioners. Amalgamating the knowledge and experience of clinicians, researchers, and educators from interdisciplinary and multi-professional backgrounds, REVAMP has tackled the under-resourced and underdeveloped area of domestic violence and abuse. The team designed an online training programme to support medical and healthcare practitioners to recognise and respond appropriately to survivors of domestic violence and abuse at their point of contact with a health provider. The REVAMP partner countries include Europe: France, Lithuania, Germany, Greece, Iceland, Norway, and the UK. The training is delivered through a series of interactive online modules, adapting evidence-based pedagogical approaches to learning. Capturing and addressing the complexities of the project impacted the methodological decisions and approaches to evaluation. The challenge was to find an evaluation methodology that captured valid data across all partner languages to demonstrate the extent of the change in knowledge and understanding. Co-development by all team members was a lengthy iterative process, challenged by a lack of consistency in terminology. A mixed methods approach enabled both qualitative and quantitative data to be collected, at the start, during, and at the conclusion of the training for the purposes of evaluation. The module content and evaluation instrument were accessible in each partner country's language. Collecting both types of data provided a high-level snapshot of attainment via the quantitative dataset and an in-depth understanding of the impact of the training from the qualitative dataset. The analysis was mixed methods, with integration at multiple interfaces. The primary focus of the analysis was to support the overall project evaluation for the funding agency. A key project outcome was identifying that the trans-European approach posed several challenges. Firstly, the project partners did not share a first language or a legal or professional approach to domestic abuse and neglect. This was negotiated through complex, systematic, and iterative interaction between team members so that consensus could be achieved. Secondly, the context of the data collection in several different cultural, educational, and healthcare systems across Europe challenged the development of a robust evaluation. The participants in the pilot evaluation shared that the training was contemporary, well-designed, and of great relevance to inform practice. Initial results from the evaluation indicated that the participants were drawn from more than eight partner countries due to the online nature of the training. The primary results indicated a high level of engagement with the content and achievement through the online assessment. The main finding was that the participants perceived the impact of domestic abuse and neglect in very different ways in their individual professional contexts. Most significantly, the participants recognised the need for the training and the gap that existed previously. It is notable that a mixed-methods evaluation of a trans-European project is unusual at this scale.

Keywords: domestic violence, e-learning, health professionals, trans-European

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Authors: Chi-Cheng Cheng, Che-Hsin Lin, Yu-Jen Wang, Chua-Chin Wang

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The project-oriented capstone course has become a required element for most engineering educational units. It is not only because the capstone course is an important criterion for international accreditation of engineering degree programs under Washington Accord, but also the capstone course provides an opportunity for students to apply what they have learned in their school years to actual engineering problems. Nevertheless, most project-oriented capstone courses are conducted with one single project for all students or teams. In other words, students work to reach the same or similar goals by coming up with different layouts and approaches. It appears not suitable for a multidisciplinary engineering department. Therefore, a one-year multidisciplinary project-oriented capstone course was designed for the junior year of the undergraduate program. About one-half of faculty members in the department needs to be involved in generating as many projects as possible to meet different students' interests and specialties. Project achievement has to be displayed and demonstrated in the annual exposition and competition at the end of this course. Significant success in attracting attention and hardworking of students on projects was witnessed for the past two pilot years. Analysis of course evaluation demonstrates positive impact on all perspectives despite of slightly negative influence due to poor communication and collaboration between students and their project supervisors.

Keywords: Capstone course, CDIO, engineering education, project-oriented learning

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Authors: Ebasa Girma, Nathnael Minyelshowa, Lebsework Negash

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The use of unmanned aerial vehicles (UAVs) in precision agriculture has seen a huge increase recently. As such, systems that aim to apply various algorithms on the field need a structured framework of abstractions. This paper defines the various tasks of the UAVs in precision agriculture and models them into an architectural framework. The presented architecture is built on the context that there will be minimal physical intervention to do the tasks defined with multiple coordinated and cooperative UAVs. Various tasks such as image processing, path planning, communication, data acquisition, and field mapping are employed in the architecture to provide an efficient system. Besides, different limitation for applying Multi-UAVs in precision agriculture has been considered in designing the architecture. The architecture provides an autonomous end-to-end solution, starting from mission planning, data acquisition, and image processing framework that is highly efficient and can enable farmers to comprehensively deploy UAVs onto their lands. Simulation and field tests show that the architecture offers a number of advantages that include fault-tolerance, robustness, developer, and user-friendliness.

Keywords: deep learning, multi-UAVs, precision agriculture, UAVs architecture

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Authors: Sadeq Al Yaari, Muhammad Alkhunayn, Adham Al Yaari, Montaha Al Yaari, Ayman Al Yaari, Aayah Al Yaari, Sajedah Al Yaari, Fatehi Eissa

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Introduction: Like many dialects, the Arabic dialect of Yemen (ADY) exhibited utterance phonemic distinction- vowel deletion, lengthening, and insertion- that were investigated using speakers from different dialectal backgrounds, with particular focus on the difference typically developing and achieving speakers and those suffering linguistic problems make. Phonological variations were found to be inevitable, suggesting further investigation of consonants to see to what extent they are prone to such phonemic changes. This study investigates the patterns of consonant substitution in ADY by examining if there is a clear-cut line between normal and pathological consonants to decide which of these consonants is substituted more. Methods: A total of hundred and twenty nine Yemeni male participants (age= 6-13) were enrolled in this study. Participants were preassigned into two groups (Articulation disorders (AD) group= 42 and typically developing and achieving group (TD) = 70), each of which consists of five sub-groups in decided sociolinguistic classification. In a 45 minute-session, 180 pictures of commonly used verbs (4 pics/m.) were presented to participants who were asked to impulsively describe these verbs before their production was psychoneurolinguistically and statistically analyzed. Results: There was a pattern of consonant substitution in some dialects that participants from both groups have in common: Voiceless consonants (/t/, /ṣ/,/s/, /ḥ, /k/, /ʃ/, /f//, and /k/) in northern and eastern dialects; voiced consonants (/q/, /gh/, /Ʒ/, /g/,/ḍ/, /b/, and /d/) in southern, eastern, western and central dialects; and voiceless and voiced consonants(/t/, /f/, /Ø/, /ṣ/, /s/, /q/, /gh/, /Ʒ/, /g/,/ḍ/, and /b/) in southern dialect. Voiceless consonants (/t/, /ṣ/,/s/, /ḥ, /k/, /ʃ/, /f//, /Ø/and /k/) found to be substituted more by ADY speakers of both AD and TD groups followed by voiced consonants (/q/, /gh/, /Ʒ/, /g/,/ḍ/,/d/ /b/, and /ð/), nasals (/m/, /n/), mute (/h/), semi-vowels (/w/ and /j/) and laterals (/l/ and /r/). Unexpectedly, a short vowel (/æ/) and two long vowels (/u: and /a:/) were found to substitute consonants in ADY both by AD and TD participants. Conclusions: AD and TD participants of ADY substitute consonants in their dialectal speech. Consonant substitution processes cover not only consonants but extend to include monophthongs. The finding that speakers of ADY substitute consonants in multisyllabic words is probably due to the fact that the sociolinguistic factor plays a pivotal role in the problematic substitution of consonants in ADY speakers. Larger longitudinal studies are necessary to further investigate the effect of sociolinguistic background on phonological variations, notably sound change in the speech of Yemeni TD speakers compared to those with linguistic impairments.

Keywords: consonant substitution, Arabic dialect of Yemen, phonetics, phonology, syllables, articulation disorders

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Authors: Rahul Mohite, Lahcen Ouarbya

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This paper focuses on the interplay between humans and computer systems and the ability of these systems to understand and respond to human emotions, including non-verbal communication. Current emotion recognition systems are based solely on either facial or verbal expressions. The limitation of these systems is that it requires large training data sets. The paper proposes a system for recognizing human emotions that combines both speech and emotion recognition. The system utilizes advanced techniques such as deep learning and image recognition to identify facial expressions and comprehend emotions. The results show that the proposed system, based on the combination of facial expression and speech, outperforms existing ones, which are based solely either on facial or verbal expressions. The proposed system detects human emotion with an accuracy of 86%, whereas the existing systems have an accuracy of 70% using verbal expression only and 76% using facial expression only. In this paper, the increasing significance and demand for facial recognition technology in emotion recognition are also discussed.

Keywords: facial reputation, expression reputation, deep gaining knowledge of, photo reputation, facial technology, sign processing, photo type

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Authors: G. Anjan Babu, G. Sumana, M. Rajasekhar

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Many inherited diseases and non-hereditary disorders are common in the development of renal cystic diseases. Polycystic kidney disease (PKD) is a disorder developed within the kidneys in which grouping of cysts filled with water like fluid. PKD is responsible for 5-10% of end-stage renal failure treated by dialysis or transplantation. New experimental models, application of molecular biology techniques have provided new insights into the pathogenesis of PKD. Researchers are showing keen interest for developing an automated system by applying computer aided techniques for the diagnosis of diseases. In this paper a multi-layered feed forward neural network with one hidden layer is constructed, trained and tested by applying back propagation learning rule for the diagnosis of PKD based on physical symptoms and test results of urinanalysis collected from the individual patients. The data collected from 50 patients are used to train and test the network. Among these samples, 75% of the data used for training and remaining 25% of the data are used for testing purpose. Furthermore, this trained network is used to implement for new samples. The output results in normality and abnormality of the patient.

Keywords: dialysis, hereditary, transplantation, polycystic, pathogenesis

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Authors: Ritesh Kumar, Gitanjali Chhetri, Mandira Bhatia, Mohit Mishra, Abhijith Bailur, Abhinav

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The prevalence of the internet and technology in our day to day lives is creating more security issues than ever. The need for protecting and providing a secure access to private and business data has led to the development of many security systems. One of the potential solutions is to employ the bio-metric authentication technique. In this paper we present an innovative biometric authentication method that utilizes a person’s EEG signal, which is acquired in response to an auditory stimulus,and transferred wirelessly to a computer that has the necessary ANN algorithm-Multi layer perceptrol neural network because of is its ability to differentiate between information which is not linearly separable.In order to determine the weights of the hidden layer we use Gaussian random weight initialization. MLP utilizes a supervised learning technique called Back propagation for training the network. The complex algorithm used for EEG classification reduces the chances of intrusion into the protected public or private data.

Keywords: EEG signal, auditory evoked potential, biometrics, multilayer perceptron neural network, back propagation rule, Gaussian random weight initialization

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Authors: Ivy Jeralyn T. Andres, Eva B. Macugay

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Using a descriptive research design utilizing the Research and Development (R&D) methodology, this study focused on the development of Reproductive Health Education (RHE) Toolkit for Science Teachers that provides a guide in teaching reproductive health. Based on the findings, the teacher-respondents identified nine topics that can be included in the development of the RHE toolkit. The topics included are The Male Reproductive System, The Female Reproductive System, The Roles of Hormones in Male and Female Reproductive System, Menstrual Cycle, Fertilization, Pregnancy and Childbirth, Breastfeeding, Human Reproductive and Developmental Concerns and Reproductive Health Management and Diseases. The developed RHE Toolkit is remarked as very highly valid and very highly acceptable learning material. The validators and evaluators acknowledged the developed RHE toolkit as clear, creative, and academically useful supplemental material for educating reproductive health. Moreover, it follows the principles of SMART objectives, factual, timely, and relevant content for both learners and the community as a whole. Science teachers should employ the RHE Toolkit in teaching reproductive health education into their respective classes. It is also suggested that the developed RHE toolkit can be implemented to elementary pupils and the community, particularly in rural areas.

Keywords: reproductive health education, toolkit, science teachers, supplemental material

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Authors: Cynthia A. Gallardo, Kelly S. Hall, Kristopher Garza, Linda Challoo, Mais Nijim

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Dual-enrollment programs have become more prevalent in college and high school settings. Also known as early college programs, dual-enrollment programs help students acquire a head start in earning college credit for post-secondary studies. The number and percentage of high school students who take college courses while in high school is growing. However, little is known about how dual-enrolled students fare. The classroom environment is important to learning. This study compares dually enrolled high school students who take courses that yield college credit either within their high school or at some other location. Mann-Whitney U was the statistical test used. Mean proportions were compared for each of the five standard letter grades earned across the state of Texas. Results indicated that students earn similar passing A, B, and C grades when they take dual-enrollment courses at their high school location but are more likely to fail if they take dual-enrollment courses at non-high school locations. Implications of results are that student success rate of dual-enrollment college courses may have a significant difference between the locations and student performance.

Keywords: educational leadership, dual-enrollment, student performance, college

Procedia PDF Downloads 80