Search results for: hybrid learning

Authors: Xuan Zheng

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China is home to one of the world’s largest Deaf and Hard of Hearing (DHH) populations. In the 1980s, the concept of inclusive education was introduced, giving rise to a unique “learning in regular class (随班就读)” model tailored to local contexts. China’s inclusive education for DHH students is diversifying with innovative models like special education classes at regular schools, regular classes at regular schools, resource classrooms, satellite classes, and bilingual-bimodal projects. The scope extends to preschool and higher education programs. However, the inclusive development of DHH students faces challenges. The prevailing pathological viewpoint on disabilities persists, emphasizing the necessity for favorable auditory and speech rehabilitation outcomes before DHH students can integrate into regular classes. In addition, inadequate support systems in inclusive schools result in poor academic performance and increased psychological disorders among the group, prompting a notable return to special education schools. Looking ahead, China’s inclusive education for DHH students needs a substantial shift from “learning in regular class” to “sharing equal regular education.” Particular attention should be devoted to the effective integration of DHH students who employ sign language into mainstream educational settings. It is crucial to strengthen regulatory frameworks and institutional safeguards, advance the professional development of educators specializing in inclusive education for DHH students, and consistently enhance resources tailored to this demographic. Furthermore, the establishment of a robust, multidimensional, and collaborative support network, engaging both families and educational institutions, is also a pivotal facet.

Keywords: deaf, hard of hearing, inclusive education, China

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Authors: Gobinda Gopal Khan, Ashutosh K. Singh, Debasish Sarkar

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This study reports the facile fabrication of 1D ZnO/α-Fe2O3 semiconductor nano-heterostructures (SNHs), and we investigate the strong interfacial interactions at the heterojunction, resulting in novel multifunctionality in the hybrid structure. ZnO-coated α-Fe2O3 nanowires (NWs) have been prepared by combining electrodeposition and wet chemical methods. Significant improvement in electrical conductivity, photoluminescence, and room temperature magnetic properties have been observed for the ZnO/α-Fe2O3 SNHs over the pristine α-Fe2O3 NWs because of the contribution of the ZnO nanolayer. The increase in electrical conductivity in ZnO/α-Fe2O3 SNHs is because of the increase in free electrons in the conduction band of the SNHs due to the formation of type-II n-n band configuration at the heterojunction. The SNHs are found to exhibit enhanced visible green photoluminescence along with the UV emission at room temperature. The band-gap emission of the α-Fe2O3 NWs coupled to the defect emissions of the ZnO in SNHs can be attributed to the profound enhancement of the visible green luminescence. Ferromagnetism of the SNHs is found to be increased nearly five times in magnitude over the primeval α-Fe2O3 NWs, which can be ascribed to the exchange coupling of the interfacial spin at ZnO/α-Fe2O3 interface, the surface spin of ZnO nanolayer, along with the structural defects like the cation vacancies (VZn) and the singly ionized oxygen vacancies (Vo•) present in SNHs.

Keywords: nano-heterostructures, photoluminescence, electrical property, magnetism

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Authors: Muhammad Abdullah, Asma Rashid Butt, Nauman Raza

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Biomagnetic fluids like blood play key role in different applications of medical science and bioengineering. In this paper, the magnetohydrodynamic flow of a viscous fluid with magnetic particles through a cylindrical tube is investigated. The fluid is electrically charged in the presence of a uniform external magnetic field. The movement in the fluid is produced due to the cylindrical tube. Initially, the fluid and tube are at rest and at time t=0⁺, the tube starts to move along its axis. To obtain the mathematical model of flow with fractional derivatives fractional calculus approach is used. The solution of the flow model is obtained by using Laplace transformation. The Simon's numerical algorithm is employed to obtain inverse Laplace transform. The hybrid technique, we are employing has less computational effort as compared to other methods. The numerical calculations have been performed with Mathcad software. As the special cases of our problem, the solution of flow model with ordinary derivatives and flow without magnetic particles has been procured. Finally, the impact of non-integer fractional parameter alpha, Hartmann number Ha, and Reynolds number Re on flow and magnetic particles velocity is analyzed and depicted by graphs.

Keywords: viscous fluid, magnetic particles, fractional calculus, laplace transformation

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Authors: Taik Kim

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Mathematics anxiety has an important consequence for teacher practices that influence students’ attitudes and achievement. Elementary prospective teachers have the highest levels of mathematics anxiety in comparison with other college majors. In his teaching practice, the researcher developed a highly successful teaching model to reduce pre-service teachers’ higher math anxiety and simultaneously to improve their pedagogical math content knowledge. There were eighty one participants from 2015 to 2018 who took the Mathematics for Elementary Teachers I and II. As the analysis data indicated, elementary prospective teachers’ math anxiety was greatly reduced with improving their math pedagogical knowledge. U.S encounters a critical shortage of well qualified educators. To solve the issue, it is essential to engage students in a long-term commitmentto shape better teachers, who will, in turn, produce k-12 school students that are better-prepared for college students. It is imperative that new instructional strategies are implemented to improve student learning and address declining interest, poor preparedness, a lack of diverse representation, and low persistence of students in mathematics. Many four year college students take math courses from the math department in the College of Arts& Science and then take methodology courses from the College of Education. Before taking pedagogy, many students struggle in learning mathematics and lose their confidence. Since the content course focus on college level math, instead of pre service teachers’ teaching area, per se elementary math, they do not have a chance to improve their teaching skills on topics which eventually they teach. The research, a joint appointment of math and math education, has been involved in teaching content and pedagogy. As the result indicated, participants were able to math content at the same time how to teach. In conclusion, the new initiative to use several teaching strategies was able not only to increase elementary prospective teachers’ mathematical skills and knowledge but also to improve their attitude toward mathematics. We need an innovative teaching strategy which implements evidence-based tactics in redesigning a education and math to improve pre service teachers’math skills and which can improve students’ attitude toward math and students’ logical and reasoning skills. Implementation of these best practices in the local school district is particularly important because K-8 teachers are not generally familiar with lab-based instruction. At the same time, local school teachers will learn a new way how to teach math. This study can be a vital teacher education model expanding throughout the State and nationwide. In summary, this study yields invaluable information how to improve teacher education in the elementary level and, eventually, how to enhance K-8 students’ math achievement.

Keywords: quality of education and improvement method, teacher education, innovative teaching and learning methodologies, math education

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Authors: Srinivasan Chandrasekaran, R. Nagavinothini

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Offshore platforms for ultra-deep waters are form-dominant by design; hybrid systems with large flexibility in horizontal plane and high rigidity in vertical plane are preferred due to functional complexities. Offshore triceratops is relatively a new-generation offshore platform, whose deck is partially isolated from the supporting buoyant legs by ball joints. They allow transfer of partial displacements of buoyant legs to the deck but restrain transfer of rotational response. Buoyant legs are in turn taut-moored to the sea bed using pre-tension tethers. Present study will discuss detailed dynamic analysis and preliminary design of the chosen geometric, which is necessary as a proof of validation for such design applications. A detailed numeric analysis of triceratops at 2400 m water depth under random waves is presented. Preliminary design confirms member-level design requirements under various modes of failure. Tether configuration, proposed in the study confirms no pull-out of tethers as stress variation is comparatively lesser than the yield value. Presented study shall aid offshore engineers and contractors to understand suitability of triceratops, in terms of design and dynamic response behaviour.

Keywords: offshore structures, triceratops, random waves, buoyant legs, preliminary design, dynamic analysis

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Authors: Hsiao-Chuan Huang, King-Lung Kuo, Mei-Hsin Lo, Hsiao-Yun Chou, Yusen Lin

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The most robust and economical method for laboratory diagnosis of TB is to identify mycobacterial bacilli (AFB) under acid-fast staining despite its disadvantages of low sensitivity and labor-intensive. Though digital pathology becomes popular in medicine, an automated microscopic system for microbiology is still not available. A new AI-assisted automated microscopic system, consisting of a microscopic scanner and recognition program powered by big data and deep learning, may significantly increase the sensitivity of TB smear microscopy. Thus, the objective is to evaluate such an automatic system for the identification of AFB. A total of 5,930 smears was enrolled for this study. An intelligent microscope system (TB-Scan, Wellgen Medical, Taiwan) was used for microscopic image scanning and AFB detection. 272 AFB smears were used for transfer learning to increase the accuracy. Referee medical technicians were used as Gold Standard for result discrepancy. Results showed that, under a total of 1726 AFB smears, the automated system's accuracy, sensitivity and specificity were 95.6% (1,650/1,726), 87.7% (57/65), and 95.9% (1,593/1,661), respectively. Compared to culture, the sensitivity for human technicians was only 33.8% (38/142); however, the automated system can achieve 74.6% (106/142), which is significantly higher than human technicians, and this is the first of such an automated microscope system for TB smear testing in a controlled trial. This automated system could achieve higher TB smear sensitivity and laboratory efficiency and may complement molecular methods (eg. GeneXpert) to reduce the total cost for TB control. Furthermore, such an automated system is capable of remote access by the internet and can be deployed in the area with limited medical resources.

Keywords: TB smears, automated microscope, artificial intelligence, medical imaging

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Authors: Wu Di, Yeo Khoon Seng, Lim Tee Tai

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The typical insects employ a flapping-wing mode of flight. The numerical simulations on free flight of a model fruit fly (Re=143) including hovering and are presented in this paper. Unsteady aerodynamics around a flapping insect is studied by solving the three-dimensional Newtonian dynamics of the flyer coupled with Navier-Stokes equations. A hybrid-grid scheme (Generalized Finite Difference Method) that combines great geometry flexibility and accuracy of moving boundary definition is employed for obtaining flow dynamics. The results show good points of agreement and consistency with the outcomes and analyses of other researchers, which validate the computational model and demonstrate the feasibility of this computational approach on analyzing fluid phenomena in insect flight. The present modeling approach also offers a promising route of investigation that could complement as well as overcome some of the limitations of physical experiments in the study of free flight aerodynamics of insects. The results are potentially useful for the design of biomimetic flapping-wing flyers.

Keywords: free hovering flight, flapping wings, fruit fly, insect aerodynamics, leading edge vortex (LEV), computational fluid dynamics (CFD), Navier-Stokes equations (N-S), fluid structure interaction (FSI), generalized finite-difference method (GFD)

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Authors: Kulveer Sandhu

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Background: In 1999, the Government of Canada legalized the use of cannabis for the therapeutic purpose (CTP); however, its users remain highly vulnerable to stigma and are judged by care providers and nonusers of cannabis. Findings from a literature review suggest health care providers (HCPs), including nurses in palliative care settings, lack knowledge about medical cannabis. For this reason, it is important to enhance HCPs’awarenessand knowledge of medical cannabis. Significance of the Project: Nurses are the first point of contact and spend more time with patients than other care providers; it is, therefore, important for them to be informed about CTPto provide quality and equitable care for medical cannabis users. Although nurses and other HCPs want information on CTP, the topic is rarely included in their educational curriculum. The purpose of this project is to create an evidence informed Package designed to increase knowledge among palliative care nurses about CTP. The information package will empower palliative nurses to help palliative patients make informed decisions about their treatment plan. Method: The information package will include a basic overview of the endocannabinoid system, common cannabis plants and products, and methods of consumption, as well as information to help nurses better understand consumption and harm reduction. The package will also include a set of cannabis fact sheets for nurses. Each fact sheet will comprise a high-level overview with graphics followed by a description of medical cannabis with links and references. At the end of the learning package, there are five self-reflection questions that allow nurses to examine their personal values, attitudes, and practices regarding medical cannabis. These questions will help each nurse understand their personal approach towards CTP and its users.

Keywords: medical cannabis, improve knowledge, cannabis for therapeutic purpose (CTP), patient experience, palliative care

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Authors: Dembele Dembele, Philippe

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Several Second Language Acquisition (SLA) studies have stressed the benefits of Content and Language Integrated Learning (CLIL) and shown how CLIL students outperformed their non-CLIL counterparts in many L2 skills. However, numerous experimental CLIL programs seem to have mainly targeted above-average and rather highly motivated language learners. The need to understand the impact of the student’s language proficiency on code-switching in CLIL instruction motivated this study. Therefore, determining the implications of the students’ low-language proficiency for CLIL methodology, as well as the frequency with which CLIL teachers use the main pedagogical functions of code-switching, seemed crucial for a Spanish CLIL instruction on a large scale. In the mixed-method approach adopted, ten face-to-face interviews were conducted in nine Valencian public secondary education schools, while over 30 CLIL teachers also contributed with their experience in two online survey questionnaires. The results showed the crucial role language proficiency plays in the Valencian CLIL/Plurilingual selection criteria. The presence of a substantial number of low-language proficient students in CLIL groups, which in turn implied important methodological consequences, was another finding of the study. Indeed, though the pedagogical use of L1 was confirmed as an extended practice among CLIL teachers, more than half of the participants perceived that code-switching impaired attaining their CLIL lesson objectives. Therein, the dissertation highlights the need for more extensive empirical research on how code-switching could prove beneficial in CLIL instruction involving low-language proficient students while maintaining the maximum possible exposure to the target language.

Keywords: CLIL methodology, low language proficiency, code switching, selection criteria, code-switching functions

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Authors: Farzad Hosseini Hossein Abadi, Cristina Prieto Sierra, Cesar Álvarez Díaz

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Predicting streamflow accurately in flashy catchments prone to floods is a major research and operational challenge in hydrological modeling. Recent advancements in deep learning, particularly Long Short-Term Memory (LSTM) networks, have shown to be promising in achieving accurate hydrological predictions at daily and hourly time scales. In this work, a multi-timescale LSTM (MTS-LSTM) network was applied to the context of regional hydrological predictions at an hourly time scale in flashy catchments. The case study includes 40 catchments allocated in the Basque Country, north of Spain. We explore the impact of hyperparameters on the performance of streamflow predictions given by regional deep learning models through systematic hyperparameter tuning - where optimal regional values for different catchments are identified. The results show that predictions are highly accurate, with Nash-Sutcliffe (NSE) and Kling-Gupta (KGE) metrics values as high as 0.98 and 0.97, respectively. A principal component analysis reveals that a hyperparameter related to the length of the input sequence contributes most significantly to the prediction performance. The findings suggest that input sequence lengths have a crucial impact on the model prediction performance. Moreover, employing catchment-scale analysis reveals distinct sequence lengths for individual basins, highlighting the necessity of customizing this hyperparameter based on each catchment’s characteristics. This aligns with well known “uniqueness of the place” paradigm. In prior research, tuning the length of the input sequence of LSTMs has received limited focus in the field of streamflow prediction. Initially it was set to 365 days to capture a full annual water cycle. Later, performing limited systematic hyper-tuning using grid search, revealed a modification to 270 days. However, despite the significance of this hyperparameter in hydrological predictions, usually studies have overlooked its tuning and fixed it to 365 days. This study, employing a simultaneous systematic hyperparameter tuning approach, emphasizes the critical role of input sequence length as an influential hyperparameter in configuring LSTMs for regional streamflow prediction. Proper tuning of this hyperparameter is essential for achieving accurate hourly predictions using deep learning models.

Keywords: LSTMs, streamflow, hyperparameters, hydrology

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Authors: Harmel Meriem

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The optoelectronic properties and high power conversion efficiency make lead halide perovskites ideal material for solar cell applications. However, the toxic nature of lead and the instability of organic cation are the two key challenges in the emerging perovskite solar cells. To overcome these challenges, we present our study about finding potential alternatives to lead in the form of A2BX6 perovskite using the first principles DFT-based calculations. The highly accurate modified Becke Johnson (mBJ) and hybrid functional (HSE06) have been used to investigate the Main Document Click here to view linked References to optoelectronic and thermoelectric properties of A2PdBr6 (A = K, Rb, and Cs) perovskite. The results indicate that different A-cations in A2PdBr6 can significantly alter their electronic and optical properties. Calculated band structures indicate semiconducting nature, with band gap values of 1.84, 1.53, and 1.54 eV for K2PdBr6, Rb2PdBr6, and Cs2PdBr6, respectively. We find strong optical absorption in the visible region with small effective masses for A2PdBr6. The ideal band gap and optimum light absorption suggest Rb2PdBr6 and Cs2PdBr6 potential candidates for the light absorption layer in perovskite solar cells. Additionally.

Keywords: soler cell, double perovskite, optoelectronic properties, ab-inotio study

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Authors: Johanna Lundqvist

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Third cycle supervision is a multifaceted and complex task for supervisors in higher education. It progresses over several years and is affected by several proximal and distal factors. It can result in positive learning outcomes for doctoral students and high-quality publications. However, not all doctoral students thrive during their doctoral studies; nor do they all complete their studies. This is problematic for both the individuals themselves as well as society at large: doctoral students are valuable and important in current research, future research and higher education. The aim of this literature review is to elucidate what responsible third cycle supervision can include and be in practice. The question posed is as follows: according to recent literature, what is it that characterises responsible third cycle supervision in which doctoral students can thrive and develop their research knowledge and skills? A literature review was conducted, and the data gathered from the literature regarding responsible third cycle supervision was analysed by means of a thematic analysis. The analysis was inspired by the notion of responsible inclusion outlined by David Mitchell. In this study, the term literature refers to research articles and regulations. The results (preliminary) show that responsible third cycle supervision is associated with a number of interplaying factors (themes). These are as follows: committed supervisors and doctoral students; a clear vision and research problem; an individual study plan; adequate resources; interaction processes and constructive feedback; creativity; cultural awareness; respect and research ethics; systematic quality work and improvement efforts; focus on overall third cycle learning goals; and focus on research presentations and publications. Thus, responsible third cycle supervision can occur if these factors are realized in practice. This literature review is of relevance to evaluators, researchers, and management in higher education, as well as third cycle supervisors.

Keywords: doctoral student, higher education, third cycle supervisors, third cycle programmes

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Authors: Min Bao

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The teacher is at the core of the three fundamental factors in international Chinese language teaching, the other two being the textbook and the method. Professional development of the teacher comprises a self-renewing process that is characterized by knowledge impartment and self-reflection, in which individual agency plays a significant role. Agency makes a positive contribution to teachers’ teaching practice and their life-long learning. This study, taking Chinese teaching and learning in Minsk State Linguistic University of Belarus as an example, attempts to understand agency by investigating the teacher’s strategic adaptation of textbooks to meet local needs. Firstly, through in-depth interviews, teachers’ comments on textbooks are collected and analyzed to disclose their strategies of adapting and localizing textbooks. Then, drawing on the theory of 'The chordal triad of agency', the paper reveals the process in which teacher agency is exercised as well as its rationale. The results verify the theory, that is, given its temporal relationality, teacher agency is constructed through a combination of experiences, purposes and aims, and context, i.e., projectivity, iteration and practice-evaluation as mentioned in the theory. Evidence also suggests that the three dimensions effect differently; It is usually one or two dimensions that are of greater effects on the construction of teacher agency. Finally, the paper provides four specific insights to teacher development in international Chinese language teaching: 1) when recruiting teachers, priority be given on candidates majoring in Chinese language or international Chinese language teaching; 2) measures be taken to assure educational quality of the two said majors at various levels; 3) pre-service teacher training program be tailored for improved quality, and 4) management of overseas Confucius Institutions be enhanced.

Keywords: international Chinese language teaching, teacher agency, textbooks, localization

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Authors: Kwaku Damoah

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The agricultural sector is characterized by continuous transformation, driven by factors such as demographic shifts, evolving consumer preferences, climate change, and migration trends. This dynamic environment presents complex challenges for key stakeholders including farmers, governments, and investors, who must navigate these changes to achieve optimal investment returns. To effectively predict market trends and uncover promising investment opportunities, a systematic, data-driven approach is essential. This paper introduces the Structural Evolution Index (SEI), a machine learning-based methodology. SEI is specifically designed to analyse long-term trends and forecast the potential of emerging agricultural products for investment. Versatile in application, it evaluates various agricultural metrics such as production, yield, trade, land use, and consumption, providing a comprehensive view of the evolution within agricultural markets. By harnessing data from the UN Food and Agricultural Organisation (FAOSTAT), this study demonstrates the SEI's capabilities through Comparative Exploratory Analysis and evaluation of international trade in agricultural products, focusing on Malaysia and Singapore. The SEI methodology reveals intricate patterns and transitions within the agricultural sector, enabling stakeholders to strategically identify and capitalize on emerging markets. This predictive framework is a powerful tool for decision-makers, offering crucial insights that help anticipate market shifts and align investments with anticipated returns.

Keywords: agricultural investment, algorithm, comparative exploratory analytics, machine learning, market trends, predictive analytics, structural evolution index

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Authors: N. Sabiyath Fatima, R. K. Shanmugasundaram

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In Mobile Ad-hoc Networks (MANETS), every node performs both as transmitter and receiver. The existing backoff models do not exactly forecast the performance of the wireless network. Also, the existing models experience elevated packet collisions. Every time a collision happens, the station’s contention window (CW) is doubled till it arrives at the utmost value. The main objective of this paper is to diminish collision by means of contention window Multiplicative Increase Decrease Backoff (CWMIDB) scheme. The intention of rising CW is to shrink the collision possibility by distributing the traffic into an outsized point in time. Within wireless Ad hoc networks, the CWMIDB algorithm dynamically controls the contention window of the nodes experiencing collisions. During packet communication, the backoff counter is evenly selected from the given choice of [0, CW-1]. At this point, CW is recognized as contention window and its significance lies on the amount of unsuccessful transmission that had happened for the packet. On the initial transmission endeavour, CW is put to least amount value (C min), if transmission effort fails, subsequently the value gets doubled, and once more the value is set to least amount on victorious broadcast. CWMIDB is simulated inside NS2 environment and its performance is compared with Binary Exponential Backoff Algorithm. The simulation results show improvement in transmission probability compared to that of the existing backoff algorithm.

Keywords: backoff, contention window, CWMIDB, MANET

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Authors: Marwa M. Ibrahim

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The objective of this research is to study the technical and economic performance of wind/diesel/battery (W/D/B) off-grid system supplying a small remote gathering of four families using the HOMER software package. The second objective is to study the effect of wind energy system on the cost of generated electricity considering the cost of reducing CO₂ emissions as external benefit of wind turbines, no pollutant emission through the operational phase. The system consists of a small wind turbine, battery storage, and diesel generator. The electrical energy is to cater to the basic needs for which the daily load pattern is estimated at 8 kW peak. Net Present Cost (NPC) and Cost of Energy (COE) are used as economic criteria, while the measure of performance is % of power shortage. Technical and economic parameters are defined to estimate the feasibility of the system under study. Optimum system configurations are estimated for the selected site in Egypt. Using HOMER software, the simulation results shows that W/D/B systems are economical for the assumed community site as the price of generated electricity is about 0.285 $/kWh, without taking external benefits into considerations and 0.221 if CO₂ emissions taken into consideration W/D/B systems are more economical than alone diesel system as the COE is 0.432 $/kWh for diesel alone.

Keywords: renewable energy, hybrid energy system, on-off grid system, simulation, optimization and environmental impacts

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Authors: Seyedmajid Mehrnia, Maximilan Kuhr, Peter F. Pelz

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Molecular Dynamics (MD) simulation is a proven method to inspect behaviours of lubricant oils in nano-scale gaps. However, most MD simulations on tribology have been performed with atomically smooth walls to determine wall slip and friction properties. This study will investigate the effect of porosity, specifically nano-porous walls, on wall slip properties of hydrocarbon oils confined between two walls in a Couette flow. Different pore geometries will be modelled to investigate the effect on wall slip and bulk shear. In this paper, the Polyalphaolefin (PAO) molecules are confined to a stationary and a moving wall. A hybrid force field consisting of different potential energy functions was employed in this MD simulation. Newton’s law defines how those forces will influence the atoms' movements. The interactions among surface atoms were simulated with an Embedded Atom Method (EAM) potential function which can represent the characteristics of metallic arrangements very strongly. We implemented NERD forcefield for intramolecular potential energy function. Also, Lennard-Jones potential was employed for nonbonded intermolecular interaction.

Keywords: slip length, molecular dynamics, critical shear rate, Couette flow

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Authors: C. Fernandez-Plaza, I. Abad, E. Diaz, I. Diaz

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Births occurring before the 37th week of gestation are considered preterm births. A threat of preterm is defined as the beginning of regular uterine contractions, dilation and cervical effacement between 23 and 36 gestation weeks. To author's best knowledge, the factors that determine the beginning of the birth are not completely defined yet. In particular, the incidence of sleep habits on preterm births is weekly studied. The aim of this study is to develop a model to predict the factors affecting premature delivery on pregnancy, based on the above potential risk factors, including those derived from sleep habits and light exposure at night (introduced as 12 variables obtained by a telephone survey using two questionnaires previously used by other authors). Thus, three groups of variables were included in the study (maternal, fetal and sleep habits). The study was approved by Research Ethics Committee of the Principado of Asturias (Spain). An observational, retrospective and descriptive study was performed with 481 births between January 1, 2015 and May 10, 2016 in the University Central Hospital of Asturias (Spain). A statistical analysis using SPSS was carried out to compare qualitative and quantitative variables between preterm and term delivery. Chi-square test qualitative variable and t-test for quantitative variables were applied. Statistically significant differences (p < 0.05) between preterm vs. term births were found for primiparity, multi-parity, kind of conception, place of residence or premature rupture of membranes and interruption during nights. In addition to the statistical analysis, machine learning methods to look for a prediction model were tested. In particular, tree based models were applied as the trade-off between performance and interpretability is especially suitable for this study. C5.0, recursive partitioning, random forest and tree bag models were analysed using caret R-package. Cross validation with 10-folds and parameter tuning to optimize the methods were applied. In addition, different noise reduction methods were applied to the initial data using NoiseFiltersR package. The best performance was obtained by C5.0 method with Accuracy 0.91, Sensitivity 0.93, Specificity 0.89 and Precision 0.91. Some well known preterm birth factors were identified: Cervix Dilation, maternal BMI, Premature rupture of membranes or nuchal translucency analysis in the first trimester. The model also identifies other new factors related to sleep habits such as light through window, bedtime on working days, usage of electronic devices before sleeping from Mondays to Fridays or change of sleeping habits reflected in the number of hours, in the depth of sleep or in the lighting of the room. IF dilation < = 2.95 AND usage of electronic devices before sleeping from Mondays to Friday = YES and change of sleeping habits = YES, then preterm is one of the predicting rules obtained by C5.0. In this work a model for predicting preterm births is developed. It is based on machine learning together with noise reduction techniques. The method maximizing the performance is the one selected. This model shows the influence of variables related to sleep habits in preterm prediction.

Keywords: machine learning, noise reduction, preterm birth, sleep habit

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Authors: Mirriam M. Moleko, Sekanse A. Ntsala

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Language in mathematics instruction enables the teacher to communicate mathematical knowledge to the learners with precision. It also enables the learner to deal with mathematical activities effectively. This scholarly piece was motivated by the fact that mathematics performance in the South African primary classrooms has not been satisfactory, and English, which is a Language of Learning and Teaching (LoLT) for the majority of the learners, has been singled out as one of the major impediments. This is not only on the part of the learners, but also on the part of the teachers as well. The study thus focused on the lack of competency in English among the primary school teachers as one of the possible causes of poor performance in mathematics in primary classrooms. The qualitative processes, which were premised on the social interaction theory as a lens, sourced the narratives of 10 newly qualified primary school mathematics teachers from the disadvantaged schools on the matter. This was achieved through the use of semi-structured interviews and focus group discussions. The data, which were analyzed thematically, highlighted the actuality that the challenges cut across the pre-service stage to the in-service stage. The findings revealed that the undergraduate mathematics courses in the number of the institutions neglect the importance of language. The study further revealed that the in-service mathematics teachers lack adequate linguistic command, thereby finding it difficult to successfully teach some mathematical concepts, or even to outline instructions clearly. The study thus suggests the need for training institutions to focus on improving the teachers’ English language competency. The need for intensive in-service training targeting the problem areas was also highlighted. The study thus contributes to the body of knowledge by providing suggestions on how the mathematics teachers’ language incompetency can be mitigated.

Keywords: Competency, English language proficiency, language of learning and teaching, primary mathematics teachers

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Authors: D. P. Lawrence, T. M. M. D. Ariyarathna, W. N. K. De Silva, M. D. S. C. De Silva, Lasantha Abeysiri, Pradeep Abeygunawardhna

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Safari traveling is one of the most famous hobbies all over the world. In Sri Lanka, 'Yala' is the second-largest national park, which is a better place to go for a safari. Many number of local and foreign travelers are coming to go for a safari in 'Yala'. But 'Yala' does not have a mobile application that is made to facilitate the traveler with some important features that the traveler wants to achieve in the safari experience. To overcome these difficulties, the proposed mobile application by adding those identified features to make travelers, guiders, and administration's works easier. The proposed safari traveling guidance mobile application is called 'SMART SAFARI' for the 'Yala' National Park in Sri Lanka. There are four facilities in this mobile application that provide for travelers as well as the guiders. As the first facility, the guider and traveler can view the created map of the park, and the guider can add temporary locations of animals and special locations on the map. This is a Geographic Information System (GIS) to capture, analyze, and display geographical data. And as the second facility is to generate optimal paths according to the travelers' requirements through the park by using machine learning techniques. In the third part, the traveler can get information about animals using an animal identification system by capturing the animal. As in the other facility, the traveler will be facilitated to add reviews and a rate and view those comments under categorized sections and pre-defined score range. With those facilities, this user-friendly mobile application provides the user to get a better experience in safari traveling, and it will probably help to develop tourism culture in Sri Lanka.

Keywords: animal identification system, geographic information system, machine learning techniques, pre defined score range

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Authors: A. Javorova, M. Matusova, K. Velisek

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The article summarizes the experience of laboratory technical subjects teaching methodologies using a number of software products. The main aim is to modernize the teaching process in accordance with the requirements of today - based on information technology. Increasing of the study attractiveness and effectiveness is due to the introduction of CA technologies in the learning process. This paper discussed the areas where individual CA system used. Environment using CA systems are briefly presented in each chapter.

Keywords: education, CA systems, simulation, technology

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Authors: Bussabamintra Chalauisaeng

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The creative writing skill of Thai fourth year university learners majoring in English at Khon Kaen University, Thailand has been enhanced in an English creative writing course through the implementation of creative thinking process. The creative writing assignments cover writing a variety of short poems and a short story, bibliography and short play scripts. However, this study focuses mainly on writing short poems and short stories through the implementation of creative thinking process via action research design with on-going needs analysis and feedbacks to meet their learning needs for 45 hours. At the end of the course, forty two learners’ creative writing skill appeared to be significantly improved. Through the research instruments such as the tasks assigned both inside and outside the class as self –study including class observation, semi-conversational interviews and teacher feedback both in persons and on line including peer feedbacks. The research findings show that the target learners could produce better short poems and short story assessed by the set of criteria such as the creative and innovative short poems and short stories with complete and interesting elements of a short story like plot, theme, setting, symbolism and so on. This includes a higher level of the awareness of the pragmatic use of English writing in terms of word choices, grammar rules and writing styles. All of these outcomes reflect positive trends of success in terms of the learners’ improved creative writing skill as well as better attitudes to and motivation for learning to write English for pleasure. More interestingly, many learners claimed that this innovative teaching method through the implementation of creative thinking process integrated with creative writing help stretch their imaginations and inspire them to become a writer in the future.

Keywords: creative thinking process, creative writing skill, enhancing, implementing

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Authors: Neha Toppo

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Plans and programs for successful secondary education are incomplete without the inclusion of teaching English as an important area. Even after sixteen years of the formation of Jharkhand as a separate state, the students are still struggling to achieve quality education of English. This paper intends to account the present condition of teaching English in Jharkhand board secondary level schools through discussion on various issues of English language teaching, language need and learning challenges of its students. The study is to analyze whether the learning environment, teaching methods and materials, teaching resources, goals of language curriculum are appropriately convincing for the students of the board or require to be reanalyzed and also to provide appropriate suggestions for improvement. Immediate attention must be drawn towards the problem for benefitting those students, who despite their knowledge and talent are lagging behind in numerous fields only due to the lack of proficiency in English. The data and discussion provided are on the basis of a survey, in which semi structured interview with teachers, students and administrators in several schools including both rural and urban area has been taken. Questionnaire, observation and testing were used as important tools. The survey has been conducted in Ranchi district, as it covers large geographical area which includes number of villages and at the same time several towns. The district primarily possesses tribes as well as different class of people including immigrants from all over and outside Jharkhand with their social, economical strata. The observation makes it clear that the English language teaching at the state board is not complementing its context and the whole language teaching system should be re-examined to establish learner oriented environment.

Keywords: material, method, secondary level, teaching resources

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Authors: Khadija Rafi, Neha Jamil, Laiba Khalid, Meerub Nawaz, Mahwish Farooq

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Speech articulation is a complex process to produce intelligible sounds with the help of precise movements of various structures within the vocal tract. All these structures in the vocal tract are named as articulators, which comprise lips, teeth, tongue, and palate. These articulators work together to produce a range of distinct phonemes, which happen to be the basis of language. It starts with the airstream from the lungs passing through the trachea and into oral and nasal cavities. When the air passes through the mouth, the tongue and the muscles around it form such coordination it creates certain sounds. It can be seen when the tongue is placed in different positions- sometimes near the alveolar ridge, soft palate, roof of the mouth or the back of the teeth which end up creating unique qualities of each phoneme. We can articulate vowels with open vocal tracts, but the height and position of the tongue is different every time depending upon each vowel, while consonants can be pronounced when we create obstructions in the airflow. For instance, the alphabet ‘b’ is a plosive and can be produced only by briefly closing the lips. Articulation disorders can not only affect communication but can also be a hurdle in speech production. To improve articulation skills for such individuals, doctors often recommend speech therapy, which involves various kinds of exercises like jaw exercises and tongue twisters. However, this disorder is more common in children who are going through developmental articulation issues right after birth, but in adults, it can be caused by injury, neurological conditions, or other speech-related disorders. In short, speech articulation is an essential aspect of productive communication, which also includes coordination of the specific articulators to produce different intelligible sounds, which are a vital part of spoken language.

Keywords: linguistics, speech articulation, speech therapy, language learning

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Authors: Sukhleen Kaur

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In security groundwork, Intrusion Detection System (IDS) has become an important component. The IDS has received increasing attention in recent years. IDS is one of the effective way to detect different kinds of attacks and malicious codes in a network and help us to secure the network. Data mining techniques can be implemented to IDS, which analyses the large amount of data and gives better results. Data mining can contribute to improving intrusion detection by adding a level of focus to anomaly detection. So far the study has been carried out on finding the attacks but this paper detects the malicious files. Some intruders do not attack directly, but they hide some harmful code inside the files or may corrupt those file and attack the system. These files are detected according to some defined parameters which will form two lists of files as normal files and harmful files. After that data mining will be performed. In this paper a hybrid classifier has been used via Naive Bayes and Ripper classification methods. The results show how the uploaded file in the database will be tested against the parameters and then it is characterised as either normal or harmful file and after that the mining is performed. Moreover, when a user tries to mine on harmful file it will generate an exception that mining cannot be made on corrupted or harmful files.

Keywords: data mining, association, classification, clustering, decision tree, intrusion detection system, misuse detection, anomaly detection, naive Bayes, ripper

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Authors: Omer Shujat Bhatti, Afshan Huma

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Online educational system were considered a great opportunity for distance learning. In recent days of COVID19 pandemic, it enable the continuation of educational activities at all levels of education, from primary school to the top level universities. One of the key considered element in supporting the online educational system is video lectures. The current research explored the usefulness of the video lectures delivered to technical students of masters level with a focus on MSc Sustainable Environmental design students who have diverse backgrounds in the formal educational system. Hence they were unable to cope right away with the online system and faced communication and understanding issues in the lecture session due to internet and allied connectivity issues. Researcher used self prepared video lectures for respective subjects and provided them to the students using Youtube channel and subject based Whatsapp groups. Later, students were asked about the usefulness of the lectures towards a better understanding of the subject and an overall enhanced learning experience. More than 80% of the students appreciated the effort and requested it to be part of the overall system. Data collection was done using an online questionnaire which was prior briefed to the students with the purpose of research. It was concluded that video lectures should be considered an integral part of the lecture sessions and must be provided prior to the lecture session, ensuring a better quality of delivery. It was also recommended that the existing system must be upgraded to support the availability of these video lectures through the portal. Teachers training must be provided to help develop quality video content ensuring that is able to cover the content and courses taught.

Keywords: video lectures, online distance education, synchronous instruction, asynchronous communication

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Authors: Mary Cheptanui Sambu

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Teaching practice is an integral component of students who are training to be teachers, as it provides them with an opportunity to gain experience in an actual teaching and learning environment. This study explored the experiences of trainee teachers from a local university in Kenya, undergoing a three-month teaching practice in Special Secondary schools in the country. The main aim of the study was to understand the trainees’ experiences, their expectations, and the realities encountered during the teaching practice period. The study focused on special secondary schools for learners with hearing impairment. A descriptive survey design was employed and a sample size of forty-four respondents from special secondary schools for learners with hearing impairment was purposively selected. A questionnaire was administered to the respondents and the data obtained analysed using the Statistical Package for the Social Sciences (SPSS). Preliminary analysis shows that challenges facing special secondary schools include inadequate teaching and learning facilities and resources, low academic performance among learners with hearing impairment, an overloaded curriculum and inadequate number of teachers for the learners. The study findings suggest that the Kenyan government should invest more in the education of special needs children, particularly focusing on increasing the number of trained teachers. In addition, the education curriculum offered in special secondary schools should be tailored towards the needs and interest of learners. These research findings will be useful to policymakers and curriculum developers, and will provide information that can be used to enhance the education of learners with hearing impairment; this will lead to improved academic performance, consequently resulting in better transitions and the realization of Vision 2030.

Keywords: hearing impairment, special secondary schools, trainee, teaching practice

Procedia PDF Downloads 156

Authors: Md. Abu Sufian, Robiqul Islam, Imam Hossain Shajid, Mahesh Hanumanthu, Jarasree Varadarajan, Md. Sipon Miah, Mingbo Niu

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Coronary Heart Disease (CHD) remains a principal cause of global morbidity and mortality, characterized by atherosclerosis—the build-up of fatty deposits inside the arteries. The study introduces an innovative methodology that leverages cloud-based platforms like AWS Live Streaming and Artificial Intelligence (AI) to early detect and prevent CHD symptoms in web applications. By employing novel simulation processes and AI algorithms, this research aims to significantly mitigate the health and societal impacts of CHD. Methodology: This study introduces a novel simulation process alongside a multi-phased model development strategy. Initially, health-related data, including heart rate variability, blood pressure, lipid profiles, and ECG readings, were collected through user interactions with web-based applications as well as API Integration. The novel simulation process involved creating synthetic datasets that mimic early-stage CHD symptoms, allowing for the refinement and training of AI algorithms under controlled conditions without compromising patient privacy. AWS Live Streaming was utilized to capture real-time health data, which was then processed and analysed using advanced AI techniques. The novel aspect of our methodology lies in the simulation of CHD symptom progression, which provides a dynamic training environment for our AI models enhancing their predictive accuracy and robustness. Model Development: it developed a machine learning model trained on both real and simulated datasets. Incorporating a variety of algorithms including neural networks and ensemble learning model to identify early signs of CHD. The model's continuous learning mechanism allows it to evolve adapting to new data inputs and improving its predictive performance over time. Results and Findings: The deployment of our model yielded promising results. In the validation phase, it achieved an accuracy of 92% in predicting early CHD symptoms surpassing existing models. The precision and recall metrics stood at 89% and 91% respectively, indicating a high level of reliability in identifying at-risk individuals. These results underscore the effectiveness of combining live data streaming with AI in the early detection of CHD. Societal Implications: The implementation of cloud-based AI for CHD symptom detection represents a significant step forward in preventive healthcare. By facilitating early intervention, this approach has the potential to reduce the incidence of CHD-related complications, decrease healthcare costs, and improve patient outcomes. Moreover, the accessibility and scalability of cloud-based solutions democratize advanced health monitoring, making it available to a broader population. This study illustrates the transformative potential of integrating technology and healthcare, setting a new standard for the early detection and management of chronic diseases.

Keywords: coronary heart disease, cloud-based ai, machine learning, novel simulation techniques, early detection, preventive healthcare

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Authors: Deyadeen Ali Alshibani

Abstract:

In the literature, the multi-armed bandit problem as a statistical decision model of an agent trying to optimize his decisions while improving his information at the same time. There are several different algorithms models and their applications on this problem. In this paper, we evaluate the Regret-regression through comparing with Q-learning method. A simulation on determination of optimal treatment regime is presented in detail.

Keywords: optimal, bandit problem, optimization, dynamic programming

Procedia PDF Downloads 450

Authors: Yu-Jia Jian, Emily Chia-Yu Su, Hui-Ling Hsu, Jian-Jhih Chen

Abstract:

Coronary artery is the major supplier of myocardial blood flow. When fat and cholesterol are deposit in the coronary arterial wall, narrowing and stenosis of the artery occurs, which may lead to myocardial ischemia and eventually infarction. According to the World Health Organization (WHO), estimated 740 million people have died of coronary heart disease in 2015. According to Statistics from Ministry of Health and Welfare in Taiwan, heart disease (except for hypertensive diseases) ranked the second among the top 10 causes of death from 2013 to 2016, and it still shows a growing trend. According to American Heart Association (AHA), the risk factors for coronary heart disease including: age (> 65 years), sex (men to women with 2:1 ratio), obesity, diabetes, hypertension, hyperlipidemia, smoking, family history, lack of exercise and more. We have collected a dataset of 421 patients from a hospital located in northern Taiwan who received coronary computed tomography (CT) angiography. There were 300 males (71.26%) and 121 females (28.74%), with age ranging from 24 to 92 years, and a mean age of 56.3 years. Prior to coronary CT angiography, basic data of the patients, including age, gender, obesity index (BMI), diastolic blood pressure, systolic blood pressure, diabetes, hypertension, hyperlipidemia, smoking, family history of coronary heart disease and exercise habits, were collected and used as input variables. The output variable of the prediction module is the degree of coronary artery stenosis. The output variable of the prediction module is the narrow constriction of the coronary artery. In this study, the dataset was randomly divided into 80% as training set and 20% as test set. Four machine learning algorithms, including logistic regression, stepwise regression, neural network and decision tree, were incorporated to generate prediction results. We used area under curve (AUC) / accuracy (Acc.) to compare the four models, the best model is neural network, followed by stepwise logistic regression, decision tree, and logistic regression, with 0.68 / 79 %, 0.68 / 74%, 0.65 / 78%, and 0.65 / 74%, respectively. Sensitivity of neural network was 27.3%, specificity was 90.8%, stepwise Logistic regression sensitivity was 18.2%, specificity was 92.3%, decision tree sensitivity was 13.6%, specificity was 100%, logistic regression sensitivity was 27.3%, specificity 89.2%. From the result of this study, we hope to improve the accuracy by improving the module parameters or other methods in the future and we hope to solve the problem of low sensitivity by adjusting the imbalanced proportion of positive and negative data.

Keywords: decision support, computed tomography, coronary artery, machine learning

Procedia PDF Downloads 224