Search results for: teaching and learning model

Authors: Björn de Kruijf, Arjen Edzes, Sietske Waslander

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In an ever-quickly changing society, lifelong development is seen as a solution to labor market problems by politicians and policymakers. In this paper, we investigate how policy instruments are used to increase participation in lifelong development and on which behavioral principles policy is based. Digitization, automation, and an aging population change society and the labor market accordingly. Skills that were once most sought after in the workforce can become abundantly present. For people to remain relevant in the working population, they need to continue adapting new skills useful in the current labor market. Many reports have been written that focus on the role of lifelong development in this changing society and how lifelong development can help keep people adapt and stay relevant. Inspired by these reports, governments have implemented a broad range of policies to support participation in lifelong development. The question we ask ourselves is how government policies promote participation in lifelong development. This stems from a complex interplay of policy instruments and learning. Regulation, economic and soft instruments can be combined to promote lifelong development, and different types of education further complex policies on lifelong development. Literature suggests that different stages in people’s lives might warrant different methods of learning. Governments could anticipate this in their policies. In order to influence people’s behavior, the government can tap into a broad range of sociological, psychological, and (behavioral) economic principles. The traditional economic assumption that behavior is rational is known to be only partially true, and the government can use many biases in human behavior to stimulate participation in lifelong development. In this paper, we also try to find which biases the government taps into to promote participation if they tap into any of these biases. The goal of this paper is to analyze government policies intended to promote participation in lifelong development. To do this, we develop a framework to analyze the policies on lifelong development. We specifically incorporate the role of learning and the behavioral principles underlying policy instruments in the framework. We apply this framework to the case of the Netherlands, where we examine a set of policy documents. We single out the policies the government has put in place and how they are vertically and horizontally related. Afterward, we apply the framework and classify the individual policies by policy instrument and by type of learning. We find that the Dutch government focuses on formal and non-formal learning in their policy instruments. However, the literature suggests that learning at a later age is mainly done in an informal manner through experiences.

Keywords: learning, lifelong development, policy analysis, policy instruments

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Authors: Samuel Olugbenga King

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Using a reflective analysis tool to provide both local and global perspectives, this study focuses on the longitudinal evaluation of the Graduate Student Development (GSD) initiative, the Preparing Future Faculty (PFF) program. The reflection process involves examining the past and present to identify challenges, and culminates in the creation of an action plan to address barriers to further growth and teaching development of graduate students, thus positively impacting student experience. The outcomes of the reflective critique of the PFF program indicate that lack of mentoring as well as inadequate feedback and funding are barriers that need to be addressed to positively impact the graduate student experience. Consequently, interventions, such as peer and student evaluations, and alumni surveys are highlighted as pragmatic modes of addressing the inadequate feedback and mentoring barriers. However, funding remains an ongoing challenge. This article is a contribution to the literature on the use of critical reflection approaches to investigate and evaluate specific programming that focuses on enhancing the graduate student experience and development.

Keywords: graduate student experience, longitudinal reflection, quality enhancement, teaching

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Authors: Hong Zhang

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The main purpose of this study is to show that machine translation (MT) post-editing (PE) training can help our Chinese students learn Spanish as a second language. Our hypothesis is that they might make better use of it by learning PE skills specific for foreign language learning. We have developed PE training materials based on the data collected in a previous study. Training material included the special error types of the output of MT and the error types that our Chinese students studying Spanish could not detect in the experiment last year. This year we performed a pilot study in order to evaluate the PE training materials effectiveness and to what extent PE training helps Chinese students who study the Spanish language. We used screen recording to record these moments and made note of every action done by the students. Participants were speakers of Chinese with intermediate knowledge of Spanish. They were divided into two groups: Group A performed PE training and Group B did not. We prepared a Chinese text for both groups, and participants translated it by themselves (human translation), and then used Google Translate to translate the text and asked them to post-edit the raw MT output. Comparing the results of PE test, Group A could identify and correct the errors faster than Group B students, Group A did especially better in omission, word order, part of speech, terminology, mistranslation, official names, and formal register. From the results of this study, we can see that PE training can help Chinese students learn Spanish as a second language. In the future, we could focus on the students’ struggles during their Spanish studies and complete the PE training materials to teach Chinese students learning Spanish with machine translation.

Keywords: machine translation, post-editing, post-editing training, Chinese, Spanish, foreign language learning

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Authors: Amal Machtalay

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In this survey, we aim to review the rapidly growing literature on numerical methods to solve different forms of mean field problems, namely mean field games (MFG), mean field controls (MFC), potential MFGs, and master equations, as well as their corresponding recent applications. Here, we distinguish two families of numerical methods: iterative methods based on mesh generation and those called mesh-free, normally related to neural networking and learning frameworks.

Keywords: mean-field games, numerical schemes, partial differential equations, complex systems, machine learning

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Authors: Shiva Abdoli, Daniel T.Semere

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Several researches have been conducted to study consumption of energy in cutting process. Most of these researches are focusing to measure the consumption and propose consumption reduction methods. In this work, the relation between the cutting parameters and the consumption is investigated in order to establish a generalized energy consumption model that can be used for process and production planning in real production lines. Using the generalized model, the process planning will be carried out by taking into account the energy as a function of the selected process parameters. Similarly, the generalized model can be used in production planning to select the right operational parameters like batch sizes, routing, buffer size, etc. in a production line. The description and derivation of the model as well as a case study are given in this paper to illustrate the applicability and validity of the model.

Keywords: process parameters, cutting process, energy efficiency, Material Removal Rate (MRR)

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Authors: Kamolrat Turner, Boontuan Wattanakul

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Critical thinking and creativity are prerequisite skills for working professionals in the 21^st century. A survey conducted in 2014 at the Boromarajonani College of Nursing, Chon Buri, Thailand, revealed that these skills within students across all academic years was at a low to moderate level. An action research study was conducted to develop the EREC IF Model, a framework which includes the concepts of experience, reflection, engagement, culture and language, ICT, and flexibility and fun, to guide pedagogic activities for 75 sophomores of the undergraduate nursing science program at the college. The model was applied to all professional nursing courses. Prior to implementation, workshops were held to prepare lecturers and students. Both lecturers and students initially expressed their discomfort and pointed to the difficulties with the model. However, later they felt more comfortable, and by the end of the project they expressed their understanding and appreciation of the model. A survey conducted four and eight months after implementation found that the critical thinking and creativity skills of the sophomores were significantly higher than those recorded in the pretest. It could be concluded that the EREC IF model is efficient for fostering critical thinking and creativity skills in the undergraduate nursing science program. This model should be used for other levels of students.

Keywords: critical thinking, creativity, undergraduate nursing students, EREC IF model

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Authors: Sora Suh, Catherine Michener

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This paper examines the collaborative forms of advocacy that a group of four public school teachers took for their emergent bilingual students in one public school district. While teacher advocacy takes many forms in and out of the classroom, much advocacy work is done by individuals and less by collective action. As a result, individual teachers risk isolation or marginalization in their school contexts when they advocate for immigrant youth. This paper is intended to contribute to the documentation and understanding of teachers’ advocacy work as a collaborative act in teacher education research. The increase of ELs in US classrooms and a corresponding lack of teacher preparation to meet the needs of ELs has motivated the training of educators in linguistically responsive education (e.g., ESL, sheltered English instruction [SEI], bilingual education). Drawing from educational theories of linguistically responsive teaching for preparing educators, we trace the linguistically responsive advocacy work of the teachers. The paper is a multiple case study that tracks how teachers’ discussions on advocacy during a teacher preparation program leading to collaborative actions in their daily teaching lives in and out of school. Data collected includes online discussion forums on the topic of advocacy, course assignments on the topic of advocacy, video-audio recordings of classroom teaching observations, and video-audio recordings of individual and focus group interviews. The findings demonstrate that the teachers’ understanding of advocacy developed through collaborative partnerships formed in the teacher preparation program and grew into active forms of collaborative advocacy in their teaching practice in and out of school. The teachers formed multi-level and collaborative partnerships with teachers, families, community members, policymakers from the local government, and educational researchers to advocate for their emergent bilingual students by planning advocacy events such as new family orientations for emergent bilinguals, professional development for general education teachers on the topic of linguistically responsive instruction, and family nights hosted by the district. The paper’s findings present types of advocacy work in which teachers engage (pedagogical, curricular, out-of-school work) and provide evidence of collaborative advocacy work by a group of engaged educators. The paper highlights the increased agency and effective advocacy of teachers through teacher education and collaborative partnerships and suggests a need for more research on collaborative forms of teacher advocacy for emergent bilinguals.

Keywords: language education, teacher advocacy, language instruction, teacher education

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Authors: Elham Koohikerade, Silvio Jose Gumiere

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In this research, irrigation is highlighted as crucial for improving both the yield and quality of ‎potatoes due to their high sensitivity to soil moisture changes. The study presents a hybrid Long ‎Short-Term Memory (LSTM) model aimed at optimizing irrigation scheduling in potato fields in ‎Quebec City, Canada. This model integrates model-based and satellite-derived datasets to simulate ‎soil moisture content, addressing the limitations of field data. Developed under the guidance of the ‎Food and Agriculture Organization (FAO), the simulation approach compensates for the lack of direct ‎soil sensor data, enhancing the LSTM model's predictions. The model was calibrated using indices ‎like Surface Soil Moisture (SSM), Normalized Vegetation Difference Index (NDVI), Enhanced ‎Vegetation Index (EVI), and Normalized Multi-band Drought Index (NMDI) to effectively forecast ‎soil moisture reductions. Understanding soil moisture and plant development is crucial for assessing ‎drought conditions and determining irrigation needs. This study validated the spectral characteristics ‎of vegetation and soil using ECMWF Reanalysis v5 (ERA5) and Moderate Resolution Imaging ‎Spectrometer (MODIS) data from 2019 to 2023, collected from agricultural areas in Dolbeau and ‎Peribonka, Quebec. Parameters such as surface volumetric soil moisture (0-7 cm), NDVI, EVI, and ‎NMDI were extracted from these images. A regional four-year dataset of soil and vegetation moisture ‎was developed using a machine learning approach combining model-based and satellite-based ‎datasets. The LSTM model predicts soil moisture dynamics hourly across different locations and ‎times, with its accuracy verified through cross-validation and comparison with existing soil moisture ‎datasets. The model effectively captures temporal dynamics, making it valuable for applications ‎requiring soil moisture monitoring over time, such as anomaly detection and memory analysis. By ‎identifying typical peak soil moisture values and observing distribution shapes, irrigation can be ‎scheduled to maintain soil moisture within Volumetric Soil Moisture (VSM) values of 0.25 to 0.30 ‎m²/m², avoiding under and over-watering. The strong correlations between parcels suggest that a ‎uniform irrigation strategy might be effective across multiple parcels, with adjustments based on ‎specific parcel characteristics and historical data trends. The application of the LSTM model to ‎predict soil moisture and vegetation indices yielded mixed results. While the model effectively ‎captures the central tendency and temporal dynamics of soil moisture, it struggles with accurately ‎predicting EVI, NDVI, and NMDI.‎

Keywords: irrigation scheduling, LSTM neural network, remotely sensed indices, soil and vegetation ‎monitoring

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Authors: Nahid Nariman

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The prosperity of any nation depends on its ability to use human potential, in particular, to offer an education that builds learners' competencies to become effective workforce participants and true citizens of the world. Ever since the Second World War, the United States has been a dominant player in the world politically, economically, socially, and culturally. The rapid rise of technological advancement and consumer technologies have made it clear that science, technology, engineering, and math (STEM) play a crucial role in today’s world economy. Exploring the top qualities demanded from new hires in the industry—i.e., problem-solving skills, teamwork, dependability, adaptability, technical and communication skills— sheds light on the kind of path that is needed for a successful educational system to effectively support STEM. The focus of 21st century education has been to build student competencies by preparing them to acquire and apply knowledge, to think critically and creatively, to competently use information, be able to work in teams, to demonstrate intellectual and moral values as well as cultural awareness, and to be able to communicate. Many educational reforms pinpoint various 'ideal' pathways toward STEM that educators, policy makers, and business leaders have identified for educating the workforce of tomorrow. This study will explore how problem-based learning (PBL), an instructional strategy developed in the medical field and adopted with many successful results in K-12 through higher education, is the proper approach to stimulate underrepresented high school students' interest in pursuing STEM careers. In the current study, the effect of a problem-based STEM model on students' attitudes and career interests was investigated using qualitative and quantitative methods. The participants were 71 low-income, native Hawaiian high school students who would be first-generation college students. They were attending a summer STEM camp developed as the result of a collaboration between the University of Hawaii and the Upward Bound Program. The project, funded by the National Science Foundation's Innovative Technology Experiences for Students and Teachers (ITEST) program, used PBL as an approach in challenging students to engage in solving hands-on, real-world problems in their communities. Pre-surveys were used before camp and post-surveys on the last day of the program to learn about the implementation of the PBL STEM model. A Career Interest Questionnaire provided a way to investigate students’ career interests. After the summer camp, a representative selection of students participated in focus group interviews to discuss their opinions about the PBL STEM camp. The findings revealed a significantly positive increase in students' attitudes towards STEM disciplines and STEM careers. The students' interview results also revealed that students identified PBL to be an effective form of instruction in their learning and in the development of their 21st-century skills. PBL was acknowledged for making the class more enjoyable and for raising students' interest in STEM careers, while also helping them develop teamwork and communication skills in addition to scientific knowledge. As a result, the integration of PBL and a STEM learning experience was shown to positively affect students’ interest in STEM careers.

Keywords: problem-based learning, science education, STEM, underrepresented students

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Authors: E. N. Jansen van Vuuren

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When visiting Foundation Phase (FP) students during their Teaching Practice at schools in rural Mpumalanga, the lack of music education is evident through the absence of musical sounds, with the exception of a limited repertoire of songs that are sung by all classes everywhere you go. The absence of music teaching resources such as posters and music instruments add to the perception that generalist teachers in the FP are not teaching music. Pre-service students also acknowledge that they have never seen a music class being taught during their teaching practice visits at schools. This lack of music mentoring impacts the quality of teachers who are about to enter the workforce and ultimately results in the perpetuation of no music education in many rural schools. The situation in more affluent schools present a contrasting picture with music education being given a high priority and generalist teachers often being supported by music specialists, paid for by the parents. When student teachers start their music course, they have limited knowledge to use as a foundation for their studies. The aim of the study was to ascertain the music knowledge that students gained throughout their school careers so that the curriculum could be adapted to suit their needs. By knowing exactly what pre-service teachers know about music, the limited tuition time at tertiary level can be used in the most suitable manner and concentrate on filling the knowledge gaps. Many scholars write about the decline of music education in South African schools and mention reasons, but the exact music knowledge void amongst students does not feature in the studies. Knowing the parameters of students’ music knowledge will empower lecturers to restructure their curricula to meet the needs of pre-service students. The research question asks, “what is the extent of the music void amongst rural pre-service teachers in a B.Ed. FP course at an African university?” This action research was done using a pragmatic paradigm and mixed methodology. First year students in the cohort studying for a B.Ed. in FP were requested to complete an online baseline assessment to determine the status quo. This assessment was compiled using the CAPS music content for Grade R to 9. The data was sorted using the elements of music as a framework. Findings indicate that students do not have a suitable foundation in music education despite supposedly having had music tuition from grade R to grade 9. Knowing the content required to fill the lack of knowledge provides academics with valuable information to amend their curricula and to ensure that future teachers will be able to provide rural learners with the same foundations in music as those received by learners in more affluent schools. It is only then that the rich music culture of the African continent will thrive.

Keywords: generalist educators, music education, music curriculum, pre-service teachers

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Authors: Harold Vásquez, Cesar Hernández, Ingrid Páez

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This paper approach cognitive radio technic and applied pure proactive handoff Model to decrease interference between PU and SU and comparing it with reactive handoff model. Through the study and analysis of multivariate models SAW and TOPSIS join to 3 dynamic prediction techniques AR, MA ,and ARMA. To evaluate the best model is taken four metrics: number failed handoff, number handoff, number predictions, and number interference. The result presented the advantages using this type of pure proactive models to predict changes in the PU according to the selected channel and reduce interference. The model showed better performance was TOPSIS-MA, although TOPSIS-AR had a higher predictive ability this was not reflected in the interference reduction.

Keywords: cognitive radio, spectrum handoff, decision making, time series, wireless networks

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Authors: Saad M. Darwish

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Recently, software quality issues have come to be seen as important subject as we see an enormous growth of agencies involved in software industries. However,these agencies cannot guarantee the quality of their products, thus leaving users in uncertainties. Software certification is the extension of quality by means that quality needs to be measured prior to certification granting process. This research participates in solving the problem of software assessment by proposing a model for assessment and certification of software product that uses a fuzzy inference engine to integrate both of process–driven and application-driven quality assurance strategies. The key idea of the on hand model is to improve the compactness and the interpretability of the model’s fuzzy rules via employing an ant colony optimization algorithm (ACO), which tries to find good rules description by dint of compound rules initially expressed with traditional single rules. The model has been tested by case study and the results have demonstrated feasibility and practicability of the model in a real environment.

Keywords: optimization technique, quality assurance, software certification model, software assessment

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Authors: S. F. Wong, S. S. Dol

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Automotive designers have been trying to use dimples to reduce drag in vehicles. In this work, a car model has been applied with dimple surface with a parameter called dimple ratio DR, the ratio between the depths of the half dimple over the print diameter of the dimple, has been introduced and numerically simulated via k-ε turbulence model to study the aerodynamics performance with the increasing depth of the dimples The Ahmed body car model with 25 degree slant angle is simulated with the DR of 0.05, 0.2, 0.3 0.4 and 0.5 at Reynolds number of 176387 based on the frontal area of the car model. The geometry of dimple changes the kinematics and dynamics of flow. Complex interaction between the turbulent fluctuating flow and the mean flow escalates the turbulence quantities. The maximum level of turbulent kinetic energy occurs at DR = 0.4. It can be concluded that the dimples have generated extra turbulence energy at the surface and as a result, the application of dimples manages to reduce the drag coefficient of the car model compared to the model with smooth surface.

Keywords: aerodynamics, boundary layer, dimple, drag, kinetic energy, turbulence

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Authors: Isaac Mugume, Charles Basalirwa, Daniel Waiswa, Mary Nsabagwa, Triphonia Jacob Ngailo, Joachim Reuder, Sch¨attler Ulrich, Musa Semujju

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The Numerical weather prediction (NWP) models are considered powerful tools for guiding quantitative rainfall prediction. A couple of NWP models exist and are used at many operational weather prediction centers. This study considers two models namely the Consortium for Small–scale Modeling (COSMO) model and the Weather Research and Forecasting (WRF) model. It compares the models’ ability to predict rainfall over Uganda for the period 21st April 2013 to 10th May 2013 using the root mean square (RMSE) and the mean error (ME). In comparing the performance of the models, this study assesses their ability to predict light rainfall events and extreme rainfall events. All the experiments used the default parameterization configurations and with same horizontal resolution (7 Km). The results show that COSMO model had a tendency of largely predicting no rain which explained its under–prediction. The COSMO model (RMSE: 14.16; ME: -5.91) presented a significantly (p = 0.014) higher magnitude of error compared to the WRF model (RMSE: 11.86; ME: -1.09). However the COSMO model (RMSE: 3.85; ME: 1.39) performed significantly (p = 0.003) better than the WRF model (RMSE: 8.14; ME: 5.30) in simulating light rainfall events. All the models under–predicted extreme rainfall events with the COSMO model (RMSE: 43.63; ME: -39.58) presenting significantly higher error magnitudes than the WRF model (RMSE: 35.14; ME: -26.95). This study recommends additional diagnosis of the models’ treatment of deep convection over the tropics.

Keywords: comparative performance, the COSMO model, the WRF model, light rainfall events, extreme rainfall events

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Authors: Joanna Estkowska

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The Sensory Integration Method is aimed primarily at children with learning disabilities. It can also be used as a complementary method in treatment of children with cerebral palsy, autistic, mentally handicapped, blind and deaf. Autism is holistic development disorder that manifests itself in the specific functioning of a child. The most characteristic are: disorders in communication, difficulties in social relations, rigid patterns of behavior and impairment in sensory processing. In addition to these disorders may occur abnormal intellectual development, attention deficit disorders, perceptual disorders and others. This study was focused on the application sensory integration techniques in science education of autistic students. The lack of proper sensory integration causes problems with complicated processes such as motor coordination, movement planning, visual or auditory perception, speech, writing, reading or counting. Good functioning and cooperation of proprioceptive, tactile and vestibular sense affect the child’s mastery of skills that require coordination of both sides of the body and synchronization of the cerebral hemispheres. These include, for example, all sports activities, precise manual skills such writing, as well as, reading and counting skills. All this takes place in stages. Achieving skills from the first stage determines the development of fitness from the next level. Any deficit in the scope of the first three stages can affect the development of new skills. This ultimately reflects on the achievements at school and in further professional and personal life. After careful analysis symptoms from the emotional and social spheres appear to be secondary to deficits of sensory integration. During our research, the students gained knowledge and skills in the classroom of experience by learning biology, chemistry and physics with application sensory integration techniques. Sensory integration therapy aims to teach the child an adequate response to stimuli coming to him from both the outside world and the body. Thanks to properly selected exercises, a child can improve perception and interpretation skills, motor skills, coordination of movements, attention and concentration or self-awareness, as well as social and emotional functioning.

Keywords: autism spectrum disorder, science education, sensory integration, special educational needs

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Authors: V. Nagaraju, G. Murali, Nagarjunavarma Ganna, Atluri Pavan Kalyan, N. Sree Sai Ganesh, V. S. V. S. Badrinath

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The present work focuses on the development of a mathematical model for the yield obtained by single slope solar still incorporated with cylindrical pipes filled with sand. The mathematical results obtained were validated with the experimental results for the 3 cm of water level at the basin. The mathematical model and results obtained with the experimental investigation are within 11% of deviation. The theoretical model to predict the yield obtained due to the capillary effect was proposed first. And then, to predict the total yield obtained, the thermal effect model was integrated with the capillary effect model. With the obtained results, it is understood that the yield obtained is more in the case of solar stills with sand-filled cylindrical pipes when compared to solar stills without sand-filled cylindrical pipes. And later model was used for predicting yield for 1 cm and 2 cm of water levels at the basin. And it is observed that the maximum yield was obtained for a 1 cm water level at the basin. It means solar still produces better yield with the lower depth of water level at the basin; this may be because of the availability of more space in the sand for evaporation.

Keywords: solar still, cylindrical pipes, still efficiency, mathematical modeling, capillary effect model, yield, solar desalination

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Authors: Chae Hoon Park, Jong Kang Park, Jong Tae Kim

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Electrical characteristics of capacitive touchscreen need to be accurately analyzed to result in better performance for multi-channel capacitance sensing. In this paper, we extracted the panel resistances and capacitances of the touchscreen by comparing measurement data and model data. By employing a lumped RC model for driver-to-receiver paths in touchscreen, we estimated resistance and capacitance values according to the physical lengths of channel paths which are proportional to the RC model. As a result, we obtained the model having 95.54% accuracy of the measurement data.

Keywords: electrical characteristics of capacitive touchscreen, iterative extraction, lumped RC model, physical lengths of channel paths

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Authors: Jiyoung Yoon

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This study examines Spanish textbook explanations of infinitival complements and how they can affect a learner’s second-language acquisition process. Verbs taking infinitival complements are commonly found in the mandate, volition, and emotion verbs, both for Spanish and English. However, while some English verbs take gerunds (María avoids eating/*to eat meat), in Spanish a gerund never functions as the complement of a verb (María evita comer/*comiendo carne). Because of these differences, English learners of Spanish often have difficulty acquiring infinitival complement constructions in Spanish. Specifically, they may employ English-like complement structures, producing such ungrammatical utterances as *Odio comiendo tacos ‘I hate eating tacos.' A compounding factor is that many Spanish textbooks do not emphasize the usages of infinitival complements and, when explanations are provided, they are often vague and insufficient. This study examines Spanish textbook explanations of infinitival complements (intermediate and advanced college-level Spanish textbooks and grammar reference books published in the United States) to determine areas that are problematic and insufficient and how they can affect learners’ second-language acquisition process. In this study, alternative principle-driven explanations are proposed as a replacement.

Keywords: Spanish, teaching, second language, infinitival complement, textbook

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Authors: A. Dinelka Panagoda, Bathiya Bandara, Chamod Wijetunga, Chathura Malinda, Lakmal Rupasinghe, Chethana Liyanapathirana

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This research takes us forward with the concepts of Federated Learning and Software-Defined Networking (SDN) to introduce an efficient malware detection technique and provide a mitigation mechanism to give birth to a resilient and automated healthcare sector network system by also adding the feature of extended privacy preservation. Due to the daily transformation of new malware attacks on hospital Integrated Clinical Environment (ICEs), the healthcare industry is at an undefinable peak of never knowing its continuity direction. The state of blindness by the array of indispensable opportunities that new medical device inventions and their connected coordination offer daily, a factor that should be focused driven is not yet entirely understood by most healthcare operators and patients. This solution has the involvement of four clients in the form of hospital networks to build up the federated learning experimentation architectural structure with different geographical participation to reach the most reasonable accuracy rate with privacy preservation. While the logistic regression with cross-entropy conveys the detection, SDN comes in handy in the second half of the research to stack up the initial development phases of the system with malware mitigation based on policy implementation. The overall evaluation sums up with a system that proves the accuracy with the added privacy. It is no longer needed to continue with traditional centralized systems that offer almost everything but not privacy.

Keywords: software-defined network, federated learning, privacy, integrated clinical environment, decentralized learning, malware detection, malware mitigation

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Authors: Vikram Saini, Lillie Dewan

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This paper presents the iterative schemes based on Least square, Hierarchical Least Square and Stochastic Approximation Gradient method for the Identification of Wiener model with parametric structure. A gradient method is presented for the parameter estimation of wiener model with noise conditions based on the stochastic approximation. Simulation results are presented for the Wiener model structure with different static non-linear elements in the presence of colored noise to show the comparative analysis of the iterative methods. The stochastic gradient method shows improvement in the estimation performance and provides fast convergence of the parameters estimates.

Keywords: hard non-linearity, least square, parameter estimation, stochastic approximation gradient, Wiener model

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Authors: Deepa Kapoor, Rajshree Singh

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This paper appreciates the emergence and growing importance as a new production factor makes the development of technologies, methodologies and strategies for measurement, creation, and diffusion into one of the main priorities of the organizations in the knowledge society. There are many models for creation and management of knowledge and diverse and varied perspectives for study, analysis, and understanding. In this article, we will conduct a theoretical approach to the type of models for the creation and management of knowledge; we will discuss some of them and see some of the difficulties and the key factors that determine the success of the processes for the creation and management of knowledge.

Keywords: knowledge creation, knowledge management, organizational development, organization learning

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Authors: Sabrina Ladjama, Aicha Rizi, Azzedine Abbaci

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In this work, we use the crossover model to formulate a comprehensive fundamental equation of state for the thermodynamic properties for several n-alkanes in the critical region that extends to the classical region. This equation of state is constructed on the basis of comparison of selected measurements of pressure-density-temperature data, isochoric and isobaric heat capacity. The model can be applied in a wide range of temperatures and densities around the critical point for n-heptane. It is found that the developed model represents most of the reliable experimental data accurately.

Keywords: crossover model, critical region, fundamental equation, n-heptane

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Authors: Mamani Acurio Alex, Aguilar Alonso Igor

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The lack of interest and the lack of motivation are related. The lack of both in school generates serious problems such as school dropout or a low level of learning. Augmented reality has been very useful in different areas, and in this research, it was implemented in the area of education. Information necessary for the correct development of this mobile application with augmented reality was searched using six different research repositories. It was concluded that the application must be immersive, attractive, and fun for students, and the necessary technologies for its construction were defined.

Keywords: augmented reality, Vuforia, school interest, learning

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Authors: Ming-Yue Zhai

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Due to the multipath and pulse noise nature, power line communications(PLC) channel can be modelled as a memory one with the finite states Markov model(FSMC). As the most important parameter modelling a Markov channel,the memory order in an FSMC is not solved in PLC systems yet. In the paper, the mutual information is used as a measure of the dependence between the different symbols, treated as the received SNA or amplitude of the current channel symbol or that of previous symbols. The joint distribution probabilities of the envelopes in PLC systems are computed based on the multi-path channel model, which is commonly used in PLC. we confirm that given the information of the symbol immediately preceding the current one, any other previous symbol is independent of the current one in PLC systems, which means the PLC channels is a Markov chain with the first-order. The field test is also performed to model the received OFDM signals with the help of AR model. The results show that the first-order AR model is enough to model the fading channel in PLC systems, which means the amount of uncertainty remaining in the current symbol should be negligible, given the information corresponding to the immediately preceding one.

Keywords: power line communication, channel model, markovian, information theory, first-order

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Authors: Shinji Ukita, Naohiro Nakamura, Yuji Miyazu

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In considering the dynamic characteristics of structure, natural frequency and damping ratio are useful indicator. When performing dynamic design, it's necessary to select an appropriate initial damping model and hysteretic model. In the linear region, the setting of initial damping model influences the response, and in the nonlinear region, the combination of initial damping model and hysteretic model influences the response. However, the dynamic characteristics of structure in the nonlinear region remain unclear. In this paper, we studied the effect of setting of initial damping model and hysteretic model on the dynamic characteristics of structure. On initial damping model setting, Initial stiffness proportional, Tangent stiffness proportional, and Rayleigh-type were used. On hysteretic model setting, TAKEDA model and Normal-trilinear model were used. As a study method, dynamic analysis was performed using a lumped mass model of base-fixed. During analysis, the maximum acceleration of input earthquake motion was gradually increased from 1 to 600 gal. The dynamic characteristics were calculated using the ARX model. Then, the characteristics of 1st and 2nd natural frequency and 1st damping ratio were evaluated. Input earthquake motion was simulated wave that the Building Center of Japan has published. On the building model, an RC building with 30×30m planes on each floor was assumed. The story height was 3m and the maximum height was 18m. Unit weight for each floor was 1.0t/m2. The building natural period was set to 0.36sec, and the initial stiffness of each floor was calculated by assuming the 1st mode to be an inverted triangle. First, we investigated the difference of the dynamic characteristics depending on the difference of initial damping model setting. With the increase in the maximum acceleration of the input earthquake motions, the 1st and 2nd natural frequency decreased, and the 1st damping ratio increased. Then, in the natural frequency, the difference due to initial damping model setting was small, but in the damping ratio, a significant difference was observed (Initial stiffness proportional≒Rayleigh type>Tangent stiffness proportional). The acceleration and the displacement of the earthquake response were largest in the tangent stiffness proportional. In the range where the acceleration response increased, the damping ratio was constant. In the range where the acceleration response was constant, the damping ratio increased. Next, we investigated the difference of the dynamic characteristics depending on the difference of hysteretic model setting. With the increase in the maximum acceleration of the input earthquake motions, the natural frequency decreased in TAKEDA model, but in Normal-trilinear model, the natural frequency didn’t change. The damping ratio in TAKEDA model was higher than that in Normal-trilinear model, although, both in TAKEDA model and Normal-trilinear model, the damping ratio increased. In conclusion, in initial damping model setting, the tangent stiffness proportional was evaluated the most. In the hysteretic model setting, TAKEDA model was more appreciated than the Normal-trilinear model in the nonlinear region. Our results would provide useful indicator on dynamic design.

Keywords: initial damping model, damping ratio, dynamic analysis, hysteretic model, natural frequency

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Authors: Panudet Saengseedam, Nanthachai Kantanantha

Abstract:

This paper proposes a linear mixed model (LMM) with spatial effects to forecast rice and cassava yields in Thailand at the same time. A multivariate conditional autoregressive (MCAR) model is assumed to present the spatial effects. A Bayesian method is used for parameter estimation via Gibbs sampling Markov Chain Monte Carlo (MCMC). The model is applied to the rice and cassava yields monthly data which have been extracted from the Office of Agricultural Economics, Ministry of Agriculture and Cooperatives of Thailand. The results show that the proposed model has better performance in most provinces in both fitting part and validation part compared to the simple exponential smoothing and conditional auto regressive models (CAR) from our previous study.

Keywords: Bayesian method, linear mixed model, multivariate conditional autoregressive model, spatial time series

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Authors: N. Pritchard

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Within architectural education, students arrive fore-armed with; their life-experience; knowledge gained from subject-based learning; their brains and more specifically their imaginations. The learning-by-doing that they embark on in studio-based/project-based learning calls for supervision that allows the student to proactively undertake research and experimentation with design solution possibilities. The degree to which this supervision includes direction is subject to debate and differing opinion. It can be argued that if the student is to learn-by-doing, then design decision making within the design process needs to be instigated and owned by the student so that they have the ability to personally reflect on and evaluate those decisions. Within this premise lies the problem that the student's endeavours can become unstructured and unfocused as they work their way into a new and complex activity. A resultant weakness can be that the design activity is compartmented and not holistic or comprehensive, and therefore, the student's reflections are consequently impoverished in terms of providing a positive, informative feedback loop. The construct proffered in this paper is that a supportive 'armature' or 'Heuristic-Framework' can be developed that facilitates a holistic approach and reflective learning. The normal explorations of architectural design comprise: Analysing the site and context, reviewing building precedents, assimilating the briefing information. However, the student can still be compromised by 'not knowing what they need to know'. The long-serving triad 'Firmness, Commodity and Delight' provides a broad-brush framework of considerations to explore and integrate into good design. If this were further atomised in subdivision formed from the disparate aspects of architectural design that need to be considered within the design process, then the student could sieve through the facts more methodically and reflectively in terms of considering their interrelationship conflict and alliances. The words facts and sieve hold the acronym of the aspects that form the Heuristic-Framework: Function, Aesthetics, Context, Tectonics, Spatial, Servicing, Infrastructure, Environmental, Value and Ecological issues. The Heuristic could be used as a Hermeneutic Model with each aspect of design being focused on and considered in abstraction and then considered in its relation to other aspect and the design proposal as a whole. Importantly, the heuristic could be used as a method for gathering information and enhancing the design brief. The more poetic, mysterious, intuitive, unconscious processes should still be able to occur for the student. The Heuristic-Framework should not be seen as comprehensive prescriptive formulaic or inhibiting to the wide exploration of possibilities and solutions within the architectural design process.

Keywords: atomistic, hermeneutic, holistic, approach architectural design studio education

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Authors: Saeedullah J. Mandokhail, Shamsher Sadiq, Meer H. Khan

Abstract:

This paper presents the comparison of excess pore water pressure ratio (ru) predicted by using accumulated stress based pore pressure model and plasticity model. One dimensional effective stress site response analyses were performed on a 30 m deep sand column (consists of a liquefiable layer in between non-liquefiable layers) using accumulated stress based pore pressure model in Deepsoil and PDMY2 (PressureDependentMultiYield02) model in Opensees. Three Input motions with different peak ground acceleration (PGA) levels of 0.357 g, 0.124 g, and 0.11 g were used in this study. The developed excess pore pressure ratio predicted by the above two models were compared and analyzed along the depth. The time history of the ru at mid of the liquefiable layer and non-liquefiable layer were also compared. The comparisons show that the two models predict mostly similar ru values. The predicted ru is also consistent with the PGA level of the input motions.

Keywords: effective stress, excess pore pressure ratio, pore pressure model, site response analysis

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Authors: Nicholas V. Scott, Jack McCarthy

Abstract:

Military, law enforcement, and counter terrorism organizations are often tasked with target detection and image characterization of scenes containing explosive materials in various types of environments where light scattering intensity is high. Mitigation of this photonic noise using classical digital filtration and signal processing can be difficult. This is partially due to the lack of robust image processing methods for photonic noise removal, which strongly influence high resolution target detection and machine learning-based pattern recognition. Such analysis is crucial to the delivery of reliable intelligence. Polarization filters are a possible method for ambient glare reduction by allowing only certain modes of the electromagnetic field to be captured, providing strong scene contrast. An experiment was carried out utilizing a polarization lens attached to a hyperspectral imagery camera for the purpose of exploring the degree to which an imaged polarized scene of potassium, phosphorus, and nitrogen mixture allows for improved target detection and image segmentation. Preliminary imagery results based on the application of machine learning algorithms, including competitive leaky learning and distance metric analysis, to polarized hyperspectral imagery, suggest that polarization filters provide a slight advantage in image segmentation. The results of this work have implications for understanding the presence of explosive material in dry, desert areas where reflective glare is a significant impediment to scene characterization.

Keywords: explosive material, hyperspectral imagery, image segmentation, machine learning, polarization

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Authors: Ahmedou Moulaye Idriss, Yahya Tfeil

Abstract:

Medical imaging technology has become an indispensable tool in many branches of the biomedical, health area, and research and is vitally important for the training of professionals in these fields. It is not only about the tools, technologies, and knowledge provided but also about the community that this training project proposes. In order to be able to raise the level of anatomy teaching in the medical school of Nouakchott in Mauritania, it is necessary and even urgent to facilitate access to modern technology for African countries. The role of technology as a key driver of justifiable development has long been recognized. Anatomy is an essential discipline for the training of medical students; it is a key element for the training of medical specialists. The quality and results of the work of a young surgeon depend on his better knowledge of anatomical structures. The teaching of anatomy is difficult as the discipline is being neglected by medical students in many academic institutions. However, anatomy remains a vital part of any medical education program. When anatomy is presented in various planes medical students approve of difficulties in understanding. They do not increase their ability to visualize and mentally manipulate 3D structures. They are sometimes not able to correctly identify neighbouring or associated structures. This is the case when they have to make the identification of structures related to the caudate lobe when the liver is moved to different positions. In recent decades, some modern educational tools using digital sources tend to replace old methods. One of the main reasons for this change is the lack of cadavers in laboratories with poorly qualified staff. The emergence of increasingly sophisticated mathematical models, image processing, and visualization tools in biomedical imaging research have enabled sophisticated three-dimensional (3D) representations of anatomical structures. In this paper, we report our current experience in the Faculty of Medicine in Nouakchott Mauritania. One of our main aims is to create a local learning community in the fields of anatomy. The main technological platform used in this project is called 3D Slicer. 3D Slicer platform is an open-source application available for free for viewing, analysis, and interaction with biomedical imaging data. Using the 3D Slicer platform, we created from real medical images anatomical atlases of parts of the human body, including head, thorax, abdomen, liver, and pelvis, upper and lower limbs. Data were collected from several local hospitals and also from the website. We used MRI and CT-Scan imaging data from children and adults. Many different anatomy atlases exist, both in print and digital forms. Anatomy Atlas displays three-dimensional anatomical models, image cross-sections of labelled structures and source radiological imaging, and a text-based hierarchy of structures. Open and free online anatomical atlases developed by our anatomy laboratory team will be available to our students. This will allow pedagogical autonomy and remedy the shortcomings by responding more fully to the objectives of sustainable local development of quality education and good health at the national level. To make this work a reality, our team produced several atlases available in our faculty in the form of research projects.

Keywords: anatomy, education, medical imaging, three dimensional

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