Search results for: machine learning tools and techniques

Authors: Rahimah Saimin

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Previous research has shown that young children can learn from educational television programmes, videos or other technological media. However, the blending of any of these with traditional printed-based text appears to be omitted. Repeated viewing is an important factor in children's ability to comprehend the content or plot. The present study combined videos with traditional printed-based text and required repeated viewing and is original and distinctive. The first study was a pilot study to explore whether the intervention is implementable in ordinary classrooms. The second study explored whether the curricular embedding is important or whether the video with curricular embedding is effective. The third study explored the effect of “dosage”, i.e. whether a longer/ more intense intervention has a proportionately greater effect on outcomes. Both measured outcomes (comprehension, word sounds, and early word recognition) and unmeasured outcomes (engagement to reading traditional printed-based texts or/and multimodal texts) were obtained from this study. Observation indicated degree of engagement in reading. The theoretical framework was multimodality theory combined with Piaget’s and Vygotsky’s learning theories. An experimental design was used with 4-5-year-old children in nursery schools and primary schools. Six links to video clips exploring non-fiction science content were provided to teachers. The first session is whole-class and subsequent sessions small-group. The teacher then engaged the children in dialogue using supplementary materials. About half of each class was selected randomly for pre-post assessments. Two assessments were used the British Picture Vocabulary Scale (BPVSIII) and the York Assessment of Reading for Comprehension (YARC): Early Reading. Different programme fidelity means were deployed- observations, teacher self-reports attendance logs and post-delivery interviews. Data collection is in progress and results will be available shortly. If this multiphase study show effectiveness in one or other application, then teachers will have other tools which they can use to enhance vocabulary, letter knowledge and word reading. This would be a valuable addition to their repertoire.

Keywords: language skills, literacy skills, multimodality, video

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Authors: Saule Shazhanbayeva, Denise van der Merwe

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Study hypothesis: Nazarbayev Intellectual School of Kyzylorda’s Biology teachers can use STEM-integrated learning to improve students' problem-solving ability and responsibility as global citizens. The significance of this study is to indicate how the use of STEM integrative learning during Biology lessons could contribute to forming globally-minded students who are responsible community members. For the purposes of this study, worldview is defined as a view that is broader than the country of Kazakhstan, allowing students to see the significance of their scientific contributions to the world as global citizens. The context of worldview specifically indicates that most students have never traveled outside of their city or region within Kazakhstan. In order to broaden student understanding, it is imperative that students are exposed to different world views and contrasting ideas within the educational setting of Biology as the science being used for the research. This exposure promulgates students understanding of the significance they have as global citizens alongside the obligations which would rest on them as scientifically minded global citizens. Integrative learning should be Biological Science - with Technology and engineering in the form of problem-solving, and Mathematics to allow improved problem-solving skills to develop within the students of Nazarbayev Intellectual School (NIS) of Kyzylorda. The school's vision is to allow students to realise their role as global citizens and become responsible community members. STEM allows integrations by combining four subject skills to solve topical problems designed by educators. The methods used are based on qualitative analysis: for students’ performance during a problem-solution scenario; and Biology teacher interviews to ascertain their understanding of STEM implementation and willingness to integrate it into current lessons. The research indicated that NIS is ready for a shift into STEM lessons to promote globally responsible students. The only additional need is for proper STEM integrative lesson method training for teachers.

Keywords: global citizen, STEM, Biology, high-school

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Authors: N. M. Zukani, E. O. Adu

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Homeschooling has been a primary method for parents to educate their children. It has become a growing educational phenomenon across the globe. However, homeschooling is, therefore, an alternative form of education in which children are instructed at home rather than in mainstream schools. This study evaluated the effectiveness of homeschooling in East London Education District, looking at the stakeholder’s perceptions, reviewing issues that impact on this as reflected in literature. This is a qualitative study done in selected homeschools. Semi structured interviews were used as a form of collecting data. Data was scrutinized and grouped into themes. The study revealed the importance of differentiation of instruction, and the need for flexibility in the process of homeschooling for children who faced difficulties, special needs in learning in mainstream schooling. It is therefore concluded that the participants in the study clearly showed that homeschooling is an educational choice for parents who have concerns about the quality of education of their children. Furthermore, homeschooling has the potential to be the most learner centered, nurturing educational approach. It was recommended that an effective homeschooling practice mainly, the practice should consider attention to children-parent’s goals and learning structure. Although homeschooling looks at how to overcome the drawbacks of mainstream schooling, there are also cases that reflected, the incompetency of parents or tutors conducting the homeschooling and also a need for the support material and other educational supports from the government.

Keywords: homeschooling, effectiveness, stakeholders, parents, perception

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Authors: Islam Sherif, Ahmed Ashour, Ahmed Hassan, Hatem Osman

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Anterior Cruciate Ligament (ACL) injuries are common among athletes and individuals participating in sports with sudden stops, pivots, and changes in direction. Arthroscopic surgery is the gold standard for ACL reconstruction, aiming to restore knee stability and function. Recent years have witnessed significant advancements in arthroscopic surgery techniques, graft materials, and technological innovations, revolutionizing the field of ACL reconstruction. This presentation delves into the latest advancements in arthroscopic surgery techniques for ACL reconstruction and their potential impact on patient outcomes. Traditionally, autografts from the patellar tendon, hamstring tendon, or quadriceps tendon have been commonly used for ACL reconstruction. However, recent studies have explored the use of allografts, synthetic scaffolds, and tissue-engineered grafts as viable alternatives. This abstract evaluates the benefits and potential drawbacks of each graft type, considering factors such as graft incorporation, strength, and risk of graft failure. Moreover, the application of augmented reality (AR) and virtual reality (VR) technologies in surgical planning and intraoperative navigation has gained traction. AR and VR platforms provide surgeons with detailed 3D anatomical reconstructions of the knee joint, enhancing preoperative visualization and aiding in graft tunnel placement during surgery. We discuss the integration of AR and VR in arthroscopic ACL reconstruction procedures, evaluating their accuracy, cost-effectiveness, and overall impact on surgical outcomes. Beyond graft selection and surgical navigation, patient-specific planning has gained attention in recent research. Advanced imaging techniques, such as MRI-based personalized planning, enable surgeons to tailor ACL reconstruction procedures to each patient's unique anatomy. By accounting for individual variations in the femoral and tibial insertion sites, this personalized approach aims to optimize graft placement and potentially improve postoperative knee kinematics and stability. Furthermore, rehabilitation and postoperative care play a crucial role in the success of ACL reconstruction. This abstract explores novel rehabilitation protocols, emphasizing early mobilization, neuromuscular training, and accelerated recovery strategies. Integrating technology, such as wearable sensors and mobile applications, into postoperative care can facilitate remote monitoring and timely intervention, contributing to enhanced rehabilitation outcomes. In conclusion, this presentation provides an overview of the cutting-edge advancements in arthroscopic surgery techniques for ACL reconstruction. By embracing innovative graft materials, augmented reality, patient-specific planning, and technology-driven rehabilitation, orthopedic surgeons and sports medicine specialists can achieve superior outcomes in ACL injury management. These developments hold great promise for improving the functional outcomes and long-term success rates of ACL reconstruction, benefitting athletes and patients alike.

Keywords: arthroscopic surgery, ACL, autograft, allograft, graft materials, ACL reconstruction, synthetic scaffolds, tissue-engineered graft, virtual reality, augmented reality, surgical planning, intra-operative navigation

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Authors: A. Vahanyan

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The paper touches upon the problem of revision and modernization of the current curriculum on translation studies at the Armenian Higher Education Institutions (HEIs). In the contemporary world where quality and speed of services provided are mostly valued, certain higher education centers in Armenia though do not demonstrate enough flexibility in terms of the revision and amendment of courses taught. This issue is present for various curricula at the university level and Translation Studies related curriculum, in particular. Technological innovations that are of great help for translators have been long ago smoothly implemented into the global Translation Industry. According to the European Master's in Translation (EMT) framework, translation service provision comprises linguistic, intercultural, information mining, thematic, and technological competencies. Therefore, to form the competencies mentioned above, the curriculum should be seriously restructured to meet the modern education and job market requirements, relevant courses should be proposed. New courses, in particular, should focus on the formation of technological competences. These suggestions have been made upon the author’s research of the problem across various HEIs in Armenia. The updated curricula should include courses aimed at familiarization with various computer-assisted translation (CAT) tools (MemoQ, Trados, OmegaT, Wordfast, etc.) in the translation process, creation of glossaries and termbases compatible with different platforms), which will ensure consistency in translation of similar texts and speeding up the translation process itself. Another aspect that may be strengthened via curriculum modification is the introduction of interdisciplinary and Project-Based Learning courses, which will enable info mining and thematic competences, which are of great importance as well. Of course, the amendment of the existing curriculum with the mentioned courses will require corresponding faculty development via training, workshops, and seminars. Finally, the provision of extensive internship with translation agencies is strongly recommended as it will ensure the synthesis of theoretical background and practical skills highly required for the specific area. Summing up, restructuring and modernization of the existing curricula on Translation Studies should focus on three major aspects, i.e., introduction of new courses that meet the global quality standards of education, professional development for faculty, and integration of extensive internship supervised by experts in the field.

Keywords: competencies, curriculum, modernization, technical literacy, translation studies

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Authors: Omer Cahana, Ofer Levi, Maya Herman

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Magnetic Resonance Imaging (MRI) is a lengthy medical scan that stems from a long acquisition time. Its length is mainly due to the traditional sampling theorem, which defines a lower boundary for sampling. However, it is still possible to accelerate the scan by using a different approach such as Compress Sensing (CS) or Parallel Imaging (PI). These two complementary methods can be combined to achieve a faster scan with high-fidelity imaging. To achieve that, two conditions must be satisfied: i) the signal must be sparse under a known transform domain, and ii) the sampling method must be incoherent. In addition, a nonlinear reconstruction algorithm must be applied to recover the signal. While the rapid advances in Deep Learning (DL) have had tremendous successes in various computer vision tasks, the field of MRI reconstruction is still in its early stages. In this paper, we present an end-to-end method for MRI reconstruction from k-space to image. Our method contains two parts. The first is sensitivity map estimation (SME), which is a small yet effective network that can easily be extended to a variable number of coils. The second is reconstruction, which is a top-down architecture with lateral connections developed for building high-level refinement at all scales. Our method holds the state-of-art fastMRI benchmark, which is the largest, most diverse benchmark for MRI reconstruction.

Keywords: magnetic resonance imaging, image reconstruction, pyramid network, deep learning

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Authors: Ammaarah Gamieldien

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Depression is a very common and serious mental illness that has a significant impact on both the social and economic aspects of sufferers worldwide. This study aimed to investigate the association between body mass index (BMI), blood pressure, and lipid profiles with mental health symptoms in university students. Secondary objectives included the associations between the variables (BMI, blood pressure, and lipids) with themselves, as they are key factors in cardiometabolic disease. Sixty-three (63) students participated in the study. Thirty-two (32) were assigned to the control group (minimal-mild depressive symptoms), while 31 were assigned to the depressive group (moderate to severe depressive symptoms). Montgomery-Asberg Depression Rating Scale (MADRS) and Beck Depression Inventory (BDI) were used to assess depressive scores. Anthropometric measurements such as weight (kg), height (m), waist circumference (WC), and hip circumference were measured. Body mass index (BMI) and ratios such as waist-to-hip ratio (WHR) and waist-to-height ratio (WtHR) were also calculated. Blood pressure was measured using an automated AfriMedics blood pressure machine, while lipids were measured using a CardioChek plus analyzer machine. Statistics were analyzed via the SPSS statistics program. There were no significant associations between anthropometric measurements and depressive scores (p > 0.05). There were no significant correlations between lipid profiles and depression when running a Spearman’s rho correlation (P > 0.05). However, total cholesterol and LDL-C were negatively associated with depression, and triglycerides were positively associated with depression after running a point-biserial correlation (P < 0.05). Overall, there were no significant associations between blood pressure measurements and depression (P > 0.05). However, there was a significant moderate positive correlation between systolic blood pressure and MADRS scores in males (P < 0.05). Depressive scores positively and strongly correlated to how long it takes participants to fall asleep. There were also significant associations with regard to the secondary objectives. This study indicates the importance of determining the prevalence of depression among university students in South Africa. If the prevalence and factors associated with depression are addressed, depressive symptoms in university students may be improved.

Keywords: depression, blood pressure, body mass index, lipid profiles, mental health symptoms

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Authors: Ramzi Farra, Detre Teschner, Marc Willinger, Robert Schlögl

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Introduction: The conventional approach of characterizing solid catalysts under static conditions, i.e., before and after reaction, does not provide sufficient knowledge on the physicochemical processes occurring under dynamic conditions at the molecular level. Hence, the necessity of improving new in situ characterizing techniques with the potential of being used under real catalytic reaction conditions is highly desirable. In situ Prompt Gamma Activation Analysis (PGAA) is a rapidly developing chemical analytical technique that enables us experimentally to assess the coverage of surface species under catalytic turnover and correlate these with the reactivity. The catalytic HCl oxidation (Deacon reaction) over bulk ceria will serve as our example. Furthermore, the in situ Transmission Electron Microscopy is a powerful technique that can contribute to the study of atmosphere and temperature induced morphological or compositional changes of a catalyst at atomic resolution. The application of such techniques (PGAA and TEM) will pave the way to a greater and deeper understanding of the dynamic nature of active catalysts. Experimental/Methodology: In situ Prompt Gamma Activation Analysis (PGAA) experiments were carried out to determine the Cl uptake and the degree of surface chlorination under reaction conditions by varying p(O2), p(HCl), p(Cl2), and the reaction temperature. The abundance and dynamic evolution of OH groups on working catalyst under various steady-state conditions were studied by means of in situ FTIR with a specially designed homemade transmission cell. For real in situ TEM we use a commercial in situ holder with a home built gas feeding system and gas analytics. Conclusions: Two complimentary in situ techniques, namely in situ PGAA and in situ FTIR were utilities to investigate the surface coverage of the two most abundant species (Cl and OH). The OH density and Cl uptake were followed under multiple steady-state conditions as a function of p(O2), p(HCl), p(Cl2), and temperature. These experiments have shown that, the OH density positively correlates with the reactivity whereas Cl negatively. The p(HCl) experiments give rise to increased activity accompanied by Cl-coverage increase (opposite trend to p(O2) and T). Cl2 strongly inhibits the reaction, but no measurable increase of the Cl uptake was found. After considering all previous observations we conclude that only a minority of the available adsorption sites contribute to the reactivity. In addition, the mechanism of the catalysed reaction was proposed. The chlorine-oxygen competition for the available active sites renders re-oxidation as the rate-determining step of the catalysed reaction. Further investigations using in situ TEM are planned and will be conducted in the near future. Such experiments allow us to monitor active catalysts at the atomic scale under the most realistic conditions of temperature and pressure. The talk will shed a light on the potential and limitations of in situ PGAA and in situ TEM in the study of catalyst dynamics.

Keywords: CeO2, deacon process, in situ PGAA, in situ TEM, in situ FTIR

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Authors: H. N. S. Silva, S. N. Silva

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Introduction: The latest WHO data published in 2014 states that Sri Lanka has reached 2,773 of total deaths and over 14000 individuals’ sustained injuries due to RTAs each year. It was noticed in previous studies that policemen, three wheel drivers and also pedestrians were the first to respond to RTAs but the victim’s condition was aggravated due to unskilled attempts made by the responders while management of the victim’s wounds, moving and positioning of the victims and also mainly while transportation of the victims. Objective: To observe the practices of the urban public in Sri Lanka who are encountered with RTAs. Methods: A qualitative study was done to analyze public behavior seen on video recordings of scenes of accidents purposefully selected from social media, news websites, YouTube and Google. Results: The results showed that all individuals who tried to help during the RTA were middle aged men, who were mainly pedestrians, motorcyclists and policemen during that moment. Vast majority were very keen to actively help the victims to get to hospital as soon as possible and actively participated in providing 'aid'. But main problem was the first aid attempts were disorganized and uncoordinated. Even though all individuals knew how to control external bleeding, none of them was aware of spinal prevention techniques or management of limb injuries. Most of the transportation methods and transfer techniques used were inappropriate and more injury prone. Conclusions: The public actively engages in providing aid despite their inappropriate practices in giving first aid.

Keywords: encountered, pedestrians, road traffic accidents, urban public

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Authors: Athena Johnson

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Special education is an important field but often under-researched, particularly for the cause of learning deficiencies. Often times special education looks at the symptoms rather than the cause, and this can lead to many misdiagnoses. Student trauma, as measured by the Adverse Childhood Experiences (ACE) test, is extremely common, often resulting in Post Traumatic Stress Disorder (PTSD). PTSD affects the brain's ability to learn properly, making students have a much more difficult time with auditory learning and memory due to always being in flight or fight mode, and due to this, students with PTSD are often misdiagnosed with Attention Deficit and Hyperactivity Disorder (ADHD). This can lead to them getting the wrong support, with PTSD students needing more counseling than anything else. Through these research papers' methodologies, a literature review on article research from the perspectives of students who were misdiagnosed, and imperial research, the major findings of this study were the importance of trauma-informed care in schools. Trauma-informed care in the school system is crucial for helping the many students who experience traumatic life events and struggle in school due to it. It is important to support students with PTSD so that they are able to integrate and learn better in society and school with trauma-informed school care.

Keywords: ACE test, ADHD, misdiagnoses, special education, trauma, trauma-informed care, PTSD

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Authors: Ruwandika Perera

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Even though the Sri Lankan government provides a reasonable level of support for students at all levels of the school system, for example, free education, textbooks, school uniforms, subsidized public transportation, and school meals, low participation in learning among secondary students is an issue warranting investigation, particularly in low socio-economic districts. This study attempted to determine the levels of motivation and engagement amongst students in a number of schools in two low socio-economic districts of Sri Lanka. This study employed quantitative research design in an attempt to determine levels of motivation and engagement amongst Sri Lankan secondary school students. Motivation and Engagement Scale-Junior School (MES-JS) was administered among 100 Sinhala-medium and 100 Tamil-medium eighth-grade students (50 students from each gender). The mean age of the students was 12.8 years. Schools were represented by type 2 government schools located in Monaragala and Nuwara Eliya districts in Sri Lanka. Confirmatory factor analysis (CFA) was conducted to measure the construct validity of the scale. Since this did not provide a robust solution, exploratory factor analysis (EFA) was conducted. Four factors were identified; Failure Avoidance and Anxiety (FAA), Positive Motivation (PM), Uncertain Control (UC), and Positive Engagement (PE). An independent-samples t-test was conducted to compare PM, PE, FAA, and UC in gender and ethnic groups. There was no significant difference identified for PE, FAA, and UC scales based upon gender. These results indicate that for the participants in this study, there were no significant differences based on gender in the levels of failure avoidance and anxiety, uncertain control, and positive engagement in the school experience. But, the result for the PM scale was close to significant, indicating there may be differences based on gender for positive motivation. A significant difference exists for all scales based on ethnicity, with the mean result for the Tamil students being significantly higher than that for the Sinhala students. These results indicate those Sinhala-medium students’ levels of positive motivation and positive engagement in learning was lower than Tamil-medium students. Also, these results indicate those Tamil-medium students’ levels of failure avoidance, anxiety, and uncertain control was higher than Sinhala-medium students. It could be concluded that male students levels of PM were significantly lower than female students. Also, Sinhala-medium students’ levels of PM and PE was lower than Tamil-medium students, and Tamil-medium students levels of FAA and UC was significantly higher than Sinhala-medium students. Thus, there might be particular school-related conditions affecting this situation, which are related to early adolescents’ motivation and engagement in learning.

Keywords: early adolescents, engagement, low socio-economic districts, motivation

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Authors: Yin Yuanling

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A Deep Feedback Recurrent Neural Network (DFRNN) and Bidirectional Long Short-Term Memory (BiLSTM) are designed to address the problem of low accuracy of traditional relationship extraction models. This method combines a deep feedback-based recurrent neural network (DFRNN) with a bi-directional long short-term memory (BiLSTM) approach. The method combines DFRNN, which extracts local features of text based on deep feedback recurrent mechanism, BiLSTM, which better extracts global features of text, and Self-Attention, which extracts semantic information. Experiments show that the method achieves an F1 value of 76.69% on the CEC dataset, which is 0.0652 better than the BiLSTM+Self-ATT model, thus optimizing the performance of the deep learning method in the event relationship extraction task.

Keywords: event relations, deep learning, DFRNN models, bi-directional long and short-term memory networks

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Authors: Liudmyla Vesper

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The problems of modern education are large-scale and diverse. The aspirations of parents, teachers, and experts converge - everyone interested in growing up a generation of whole, well-educated persons. Both the family and society are expected in the future generation to be self-sufficient, desirable in the labor market, and capable of lifelong learning. Today's children have a powerful potential that is difficult to realize in the conditions of traditional school approaches. Focusing on STEM education in practice often ends with the simple use of computers and gadgets during class. "Science", "technology", "engineering" and "mathematics" are difficult to combine within school and university curricula, which have not changed much during the last 10 years. Solving the problems of modern education largely depends on teachers - innovators, teachers - practitioners who develop and implement effective educational methods and programs. Teachers who propose innovative pedagogical practices that allow students to master large-scale knowledge and apply it to the practical plane. Effective education considers the creation of stable neural structures during the learning process, which allow to preserve and increase knowledge throughout life. The author proposed a method of integrated lessons – cases based on the maths patterns for forming a holistic perception of the world. This method and program are scientifically substantiated and have more than 15 years of practical application experience in school and student classrooms. The first results of the practical application of the author's methodology and curriculum were announced at the International Conference "Teaching and Learning Strategies to Promote Elementary School Success", 2006, April 22-23, Yerevan, Armenia, IREX-administered 2004-2006 Multiple Component Education Project. This program is based on the concept of interdisciplinary connections and its implementation in the process of continuous learning. This allows students to save and increase knowledge throughout life according to a single pattern. The pattern principle stores information on different subjects according to one scheme (pattern), using long-term memory. This is how neural structures are created. The author also admits that a similar method can be successfully applied to the training of artificial intelligence neural networks. However, this assumption requires further research and verification. The educational method and program proposed by the author meet the modern requirements for education, which involves mastering various areas of knowledge, starting from an early age. This approach makes it possible to involve the child's cognitive potential as much as possible and direct it to the preservation and development of individual talents. According to the methodology, at the early stages of learning students understand the connection between school subjects (so-called "sciences" and "humanities") and in real life, apply the knowledge gained in practice. This approach allows students to realize their natural creative abilities and talents, which makes it easier to navigate professional choices and find their place in life.

Keywords: science education, maths education, AI, neuroplasticity, innovative education problem, creativity development, modern education problem

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Authors: Wanhyun Cho, Seongchae Seo, Soonja Kang

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In this work, we propose a variational technique for image contrast enhancement which utilizes global and local information around each pixel. The energy functional is defined by a weighted linear combination of three terms which are called on a local, a global contrast term and dispersion term. The first one is a local contrast term that can lead to improve the contrast of an input image by increasing the grey-level differences between each pixel and its neighboring to utilize contextual information around each pixel. The second one is global contrast term, which can lead to enhance a contrast of image by minimizing the difference between its empirical distribution function and a cumulative distribution function to make the probability distribution of pixel values becoming a symmetric distribution about median. The third one is a dispersion term that controls the departure between new pixel value and pixel value of original image while preserving original image characteristics as well as possible. Second, we derive the Euler-Lagrange equation for true image that can achieve the minimum of a proposed functional by using the fundamental lemma for the calculus of variations. And, we considered the procedure that this equation can be solved by using a gradient decent method, which is one of the dynamic approximation techniques. Finally, by conducting various experiments, we can demonstrate that the proposed method can enhance the contrast of colour images better than existing techniques.

Keywords: color image, contrast enhancement technique, variational approach, Euler-Lagrang equation, dynamic approximation method, EME measure

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Authors: April Love Palad, Charita B. Lasala

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Mastery on English language is one of the important goals of all English language teachers. This goal can be seen based from the students’ actual performance using the target language which is English. Learning the English language includes hard work where efforts need to be exerted and this can be attained gradually over a long period of time. It is extremely important for all English language teachers to know the effects of incorporating games in teaching. Whether this strategy can have positive or negative effects in students learning, teachers should always consider what is best for their learners. Games may help and provide confidents language learners. These games help teachers to create context in which the language is suitable and significant. Focusing in accuracy and fluency is the heart of this study and this will be obtain in either teaching English using the traditional method or teaching English using language games. It is very important for all English teachers to know which strategy is effective in teaching English to be able to cope with students’ underachievement in this subject. This study made use of the comparative-experimental method. It made use of the pre-post test design with the aim to explore the effectiveness of the language games as strategy used in language teaching for high school students. There were two groups of students being observed, the controlled and the experimental, employing the two strategies in teaching English –traditional and with the use of language games. The scores obtained by two samples were compared to know the effectiveness of the two strategies in teaching English. In this study, it found out that language games help improve students’ fluency and accuracy in the use of target language and this is very evident in the results obtained in the pre-test and post –test result as well the mean gain scores by the two groups of students. In addition, this study also gives us a clear view on the positive effects on the use of language games in teaching which also supported by the related studies based from this research. The findings of the study served as the bases for the creation of the proposed learning plan that integrated language games that teachers may use in their own teaching. This study further concluded that language games are effective in developing students’ fluency in using the English language. This justifies that games help encourage students to learn and be entertained at the same time. Aside from that, games also promote developing language competency. This study will be very useful to teachers who are in doubt in the use of this strategy in their teaching.

Keywords: language games, experimental, comparative, strategy, language teaching, methodology

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Authors: Mouna Essaadi, Mohamed Khafallah, Abdallah Saad, Hamid Chaikhy

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This paper presents a comparative analysis between conventional direct torque control (C_DTC), Modified direct torque control (M_DTC) and twelve sectors direct torque control (12_DTC).Those different strategies are compared by simulation in term of torque, flux and stator current performances. Finally, a summary of the comparative analysis is presented.

Keywords: C_DTC, M_DTC, 12_DTC, torque dynamic, stator current, flux, performances

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Authors: Dangut Maren David, Skaf Zakwan

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Adequate monitoring of vehicle component in other to obtain high uptime is the goal of predictive maintenance, the major challenge faced by businesses in industries is the significant cost associated with a delay in service delivery due to system downtime. Most of those businesses are interested in predicting those problems and proactively prevent them in advance before it occurs, which is the core advantage of Prognostic Health Management (PHM) application. The recent emergence of industry 4.0 or industrial internet of things (IIoT) has led to the need for monitoring systems activities and enhancing system-to-system or component-to- component interactions, this has resulted to a large generation of data known as big data. Analysis of big data represents an increasingly important, however, due to complexity inherently in the dataset such as imbalance classification problems, it becomes extremely difficult to build a model with accurate high precision. Data-driven predictive modeling for condition-based maintenance (CBM) has recently drowned research interest with growing attention to both academics and industries. The large data generated from industrial process inherently comes with a different degree of complexity which posed a challenge for analytics. Thus, imbalance classification problem exists perversely in industrial datasets which can affect the performance of learning algorithms yielding to poor classifier accuracy in model development. Misclassification of faults can result in unplanned breakdown leading economic loss. In this paper, an advanced approach for handling imbalance classification problem is proposed and then a prognostic model for predicting aircraft component replacement is developed to predict component replacement in advanced by exploring aircraft historical data, the approached is based on hybrid ensemble-based method which improves the prediction of the minority class during learning, we also investigate the impact of our approach on multiclass imbalance problem. We validate the feasibility and effectiveness in terms of the performance of our approach using real-world aircraft operation and maintenance datasets, which spans over 7 years. Our approach shows better performance compared to other similar approaches. We also validate our approach strength for handling multiclass imbalanced dataset, our results also show good performance compared to other based classifiers.

Keywords: prognostics, data-driven, imbalance classification, deep learning

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Authors: Cesar Vazquez-Gonzalez, Sophie Avila-Foucat, Leonardo Ortiz-Lozano, Patricia Moreno-Casasola, Alejandro Granados-Barba

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In the last twenty years, academic and scientific literature has been focused on understanding the processes and factors of coastal social-ecological systems vulnerability and resilience. Some scholars argue that resilience and vulnerability are isolated concepts due to their epistemological origin, while others note the existence of a strong resilience-vulnerability relationship. Here we present an ordinal logistic regression model based on the analytical framework about dynamic resilience-vulnerability interaction along adaptive cycle of complex systems and disasters process phases (during, recovery and learning). In this way, we demonstrate that 1) during the disturbance, absorptive capacity (resilience as a core of attributes) and external response capacity explain the probability of households capitals to diminish the damage, and exposure sets the thresholds about the amount of disturbance that households can absorb, 2) at recovery, absorptive capacity and external response capacity explain the probability of households capitals to recovery faster (resilience as an outcome) from damage, and 3) at learning, adaptive capacity (resilience as a core of attributes) explains the probability of households adaptation measures based on the enhancement of physical capital. As a result, during the disturbance phase, exposure has the greatest weight in the probability of capital’s damage, and households with absorptive and external response capacity elements absorbed the impact of floods in comparison with households without these elements. At the recovery phase, households with absorptive and external response capacity showed a faster recovery on their capital; however, the damage sets the thresholds of recovery time. More importantly, diversity in financial capital increases the probability of recovering other capital, but it becomes a liability so that the probability of recovering the household finances in a longer time increases. At learning-reorganizing phase, adaptation (modifications to the house) increases the probability of having less damage on physical capital; however, it is not very relevant. As conclusion, resilience is an outcome but also core of attributes that interacts with vulnerability along the adaptive cycle and disaster process phases. Absorptive capacity can diminish the damage experienced by floods; however, when exposure overcomes thresholds, both absorptive and external response capacity are not enough. In the same way, absorptive and external response capacity diminish the recovery time of capital, but the damage sets the thresholds in where households are not capable of recovering their capital.

Keywords: absorptive capacity, adaptive capacity, capital, floods, recovery-learning, social-ecological systems

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Authors: Xianwei Zheng, Yuan Yan Tang

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Classical window Fourier transform has been widely used in signal processing, image processing, machine learning and pattern recognition. The related Gabor transform is powerful enough to capture the texture information of any given dataset. Recently, in the emerging field of graph signal processing, researchers devoting themselves to develop a graph signal processing theory to handle the so-called graph signals. Among the new developing theory, windowed graph Fourier transform has been constructed to establish a time-frequency analysis framework of graph signals. The windowed graph Fourier transform is defined by using the translation and modulation operators of graph signals, following the similar calculations in classical windowed Fourier transform. Specifically, the translation and modulation operators of graph signals are defined by using the Laplacian eigenvectors as follows. For a given graph signal, its translation is defined by a similar manner as its definition in classical signal processing. Specifically, the translation operator can be defined by using the Fourier atoms; the graph signal translation is defined similarly by using the Laplacian eigenvectors. The modulation of the graph can also be established by using the Laplacian eigenvectors. The windowed graph Fourier transform based on these two operators has been applied to obtain time-frequency representations of graph signals. Fundamentally, the modulation operator is defined similarly to the classical modulation by multiplying a graph signal with the entries in each Fourier atom. However, a single Laplacian eigenvector entry cannot play a similar role as the Fourier atom. This definition ignored the relationship between the translation and modulation operators. In this paper, a new definition of the modulation operator is proposed and thus another time-frequency framework for graph signal is constructed. Specifically, the relationship between the translation and modulation operations can be established by the Fourier transform. Specifically, for any signal, the Fourier transform of its translation is the modulation of its Fourier transform. Thus, the modulation of any signal can be defined as the inverse Fourier transform of the translation of its Fourier transform. Therefore, similarly, the graph modulation of any graph signal can be defined as the inverse graph Fourier transform of the translation of its graph Fourier. The novel definition of the graph modulation operator established a relationship of the translation and modulation operations. The new modulation operation and the original translation operation are applied to construct a new framework of graph signal time-frequency analysis. Furthermore, a windowed graph Fourier frame theory is developed. Necessary and sufficient conditions for constructing windowed graph Fourier frames, tight frames and dual frames are presented in this paper. The novel graph signal time-frequency analysis framework is applied to signals defined on well-known graphs, e.g. Minnesota road graph and random graphs. Experimental results show that the novel framework captures new features of graph signals.

Keywords: graph signals, windowed graph Fourier transform, windowed graph Fourier frames, vertex frequency analysis

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Authors: Juan-Pedro Rica-Peromingo

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Teachers constantly need to innovate and redefine materials for their lectures, especially in areas such as Language for Specific Purposes (LSP) and Translation Studies (TS). It is therefore essential for the lecturers to be technically skilled to handle the never-ending evolution in software and technology, which are necessary elements especially in certain courses at university level. This need becomes even more evident in Audiovisual Translation (AVT) Modules and Courses. AVT has undergone considerable growth in the area of teaching and learning of languages for academic purposes. We have witnessed the development of a considerable number of masters and postgraduate courses where AVT becomes a tool for L2 learning. The teaching and learning of different AVT modes are components of undergraduate and postgraduate courses. Universities, in which AVT is offered as part of their teaching programme or training, make use of professional or free software programs. This paper presents an approach in AVT withina specific university context, in which technology is used by means of professional and nonprofessional software. Students take an AVT subject as part of their English Linguistics Master’s Degree at the Complutense University (UCM) in which they are using professional (Spot) and nonprofessional (Subtitle Workshop, Aegisub, Windows Movie Maker) software packages. The students are encouraged to develop their tasks and projects simulating authentic professional experiences and contexts in the different AVT modes: subtitling for hearing and deaf and hard of hearing population, audio description and dubbing. Selected scenes from TV series such as X-Files, Gossip girl, IT Crowd; extracts from movies: Finding Nemo, Good Will Hunting, School of Rock, Harry Potter, Up; and short movies (Vincent) were used. Hence, the complexity of the audiovisual materials used in class as well as the activities for their projects were graded. The assessment of the diverse tasks carried out by all the students are expected to provide some insights into the best way to improve their linguistic accuracy and oral and written productions with the use of different AVT modes in a very specific ESP university context.

Keywords: ESP, audiovisual translation, technology, university teaching, teaching

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Authors: Korbinian Schmidtner, Rudolf Sailer, Perry Bartelt, Wolfgang Fellin, Jan-Thomas Fischer, Matthias Granig

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This study focuses on the evaluation of snow avalanche simulations, based on a survey that has been carried out among avalanche experts. In the last decades, the application of avalanche simulation tools has gained recognition within the realm of hazard management. Traditionally, avalanche runout models were used to predict extreme avalanche runout and prepare avalanche maps. This has changed rather dramatically with the application of numerical models. For safety regulations such as road safety simulation tools are now being coupled with real-time meteorological measurements to predict frequent avalanche hazard. That places new demands on model accuracy and requires the simulation of physical processes that previously could be ignored. These simulation tools are based on a deterministic description of the avalanche movement allowing to predict certain quantities (e.g. pressure, velocities, flow heights, runout lengths etc.) of the avalanche flow. Because of the highly variable regimes of the flowing snow, no uniform rheological law describing the motion of an avalanche is known. Therefore, analogies to fluid dynamical laws of other materials are stated. To transfer these constitutional laws to snow flows, certain assumptions and adjustments have to be imposed. Besides these limitations, there exist high uncertainties regarding the initial and boundary conditions. Further challenges arise when implementing the underlying flow model equations into an algorithm executable by a computer. This implementation is constrained by the choice of adequate numerical methods and their computational feasibility. Hence, the model development is compelled to introduce further simplifications and the related uncertainties. In the light of these issues many questions arise on avalanche simulations, on their assets and drawbacks, on potentials for improvements as well as their application in practice. To address these questions a survey among experts in the field of avalanche science (e.g. researchers, practitioners, engineers) from various countries has been conducted. In the questionnaire, special attention is drawn on the expert’s opinion regarding the influence of certain variables on the simulation result, their uncertainty and the reliability of the results. Furthermore, it was tested to which degree a simulation result influences the decision making for a hazard assessment. A discrepancy could be found between a large uncertainty of the simulation input parameters as compared to a relatively high reliability of the results. This contradiction can be explained taking into account how the experts employ the simulations. The credibility of the simulations is the result of a rather thoroughly simulation study, where different assumptions are tested, comparing the results of different flow models along with the use of supplemental data such as chronicles, field observation, silent witnesses i.a. which are regarded as essential for the hazard assessment and for sanctioning simulation results. As the importance of avalanche simulations grows within the hazard management along with their further development studies focusing on the modeling fashion could contribute to a better understanding how knowledge of the avalanche process can be gained by running simulations.

Keywords: expert interview, hazard management, modeling, simulation, snow avalanche

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Authors: Gabriela V. Angeles Perez, Jose Castillejos Lopez, Araceli L. Reyes Cabello, Emilio Bravo Grajales, Adriana Perez Espinosa, Jose L. Quiroz Fabian

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Road traffic accidents are among the principal causes of traffic congestion, causing human losses, damages to health and the environment, economic losses and material damages. Studies about traditional road traffic accidents in urban zones represents very high inversion of time and money, additionally, the result are not current. However, nowadays in many countries, the crowdsourced GPS based traffic and navigation apps have emerged as an important source of information to low cost to studies of road traffic accidents and urban congestion caused by them. In this article we identified the zones, roads and specific time in the CDMX in which the largest number of road traffic accidents are concentrated during 2016. We built a database compiling information obtained from the social network known as Waze. The methodology employed was Discovery of knowledge in the database (KDD) for the discovery of patterns in the accidents reports. Furthermore, using data mining techniques with the help of Weka. The selected algorithms was the Maximization of Expectations (EM) to obtain the number ideal of clusters for the data and k-means as a grouping method. Finally, the results were visualized with the Geographic Information System QGIS.

Keywords: data mining, k-means, road traffic accidents, Waze, Weka

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Authors: Omer Cahana, Maya Herman, Ofer Levi

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Magnetic resonance imaging (MRI) is a long medical scan that stems from a long acquisition time. This length is mainly due to the traditional sampling theorem, which defines a lower boundary for sampling. However, it is still possible to accelerate the scan by using a different approach, such as compress sensing (CS) or parallel imaging (PI). These two complementary methods can be combined to achieve a faster scan with high-fidelity imaging. In order to achieve that, two properties have to exist: i) the signal must be sparse under a known transform domain, ii) the sampling method must be incoherent. In addition, a nonlinear reconstruction algorithm needs to be applied to recover the signal. While the rapid advance in the deep learning (DL) field, which has demonstrated tremendous successes in various computer vision task’s, the field of MRI reconstruction is still in an early stage. In this paper, we present an extension of the state-of-the-art model in MRI reconstruction -VarNet. We utilize VarNet by using dilated convolution in different scales, which extends the receptive field to capture more contextual information. Moreover, we simplified the sensitivity map estimation (SME), for it holds many unnecessary layers for this task. Those improvements have shown significant decreases in computation costs as well as higher accuracy.

Keywords: MRI, deep learning, variational network, computer vision, compress sensing

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Authors: Edmund M. Muthigani

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Innovation in the construction industry has been characterized by new products and processes especially in slum upgrading. The need for low cost housing has motivated stakeholders to think outside the box in coming up with solutions. This paper explored innovative construction technologies that have been used in slum upgrading. The main objectives of the paper was to examine innovations in the construction housing sector and to show how incremental derived demand for decent housing has led to adoption of innovative technologies and materials. Systematic literature review was used to review studies on innovative construction technologies in slum upgrading. The review revealed slow process of innovations in the construction industry due to risk aversion by firms and the hesitance to adopt by firms and individuals. Low profit margins in low cost housing and lack of sufficient political support remain the major hurdles to innovative techniques adoption that can actualize right to decent housing. Conventional construction materials have remained unaffordable to many people and this has negated them decent housing. This has necessitated exploration of innovative materials to realize low cost housing. Stabilized soil blocks and sisal-cement roofing blocks are some of the innovative construction materials that have been utilized in slum upgrading. These innovative materials have not only lowered the cost of production of building elements but also eased costs of transport as the raw materials to produce them are readily available in or within the slum sites. Despite their shortcomings in durability and compressive strength, they have proved worthwhile in slum upgrading. Production of innovative construction materials and use of innovative techniques in slum upgrading also provided employment to the locals.

Keywords: construction, housing, innovation, slum, technology

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Authors: Vladimir Simovic, Matija Varga, Tonco Marusic

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This research paper shows matrix technology models and examples of information systems in education (in the Republic of Croatia and in the Germany) in support of business, education (when learning and teaching) and e-learning. Here we researched and described the aims and objectives of the main process in education and technology, with main matrix classes of data. In this paper, we have example of matrix technology with detailed description of processes related to specific data classes in the processes of education and an example module that is support for the process: ‘Filling in the directory and the diary of work’ and ‘evaluation’. Also, on the lower level of the processes, we researched and described all activities which take place within the lower process in education. We researched and described the characteristics and functioning of modules: ‘Fill the directory and the diary of work’ and ‘evaluation’. For the analysis of the affinity between the aforementioned processes and/or sub-process we used our application model created in Visual Basic, which was based on the algorithm for analyzing the affinity between the observed processes and/or sub-processes.

Keywords: designing, education management, information systems, matrix technology, process affinity

Procedia PDF Downloads 436

Authors: Denis Jordan, Daniel Golkowski, Mathias Lukas, Katharina Merz, Caroline Mlynarcik, Max Maurer, Valentin Riedl, Stefan Foerster, Eberhard F. Kochs, Andreas Bender, Ruediger Ilg

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Introduction: So far, clinical assessments that rely on behavioral responses to differentiate coma states or even predict outcome in coma patients are unreliable, e.g. because of some patients’ motor disabilities. The present study was aimed to provide prognosis in coma patients using markers from electroencephalogram (EEG), blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) and [18F]-fluorodeoxyglucose (FDG) positron emission tomography (PET). Unsuperwised principal component analysis (PCA) was used for multimodal integration of markers. Methods: Approved by the local ethics committee of the Technical University of Munich (Germany) 20 patients (aged 18-89) with severe brain damage were acquired through intensive care units at the Klinikum rechts der Isar in Munich and at the Therapiezentrum Burgau (Germany). At the day of EEG/fMRI/PET measurement (date I) patients (<3.5 month in coma) were grouped in the minimal conscious state (MCS) or vegetative state (VS) on the basis of their clinical presentation (coma recovery scale-revised, CRS-R). Follow-up assessment (date II) was also based on CRS-R in a period of 8 to 24 month after date I. At date I, 63 channel EEG (Brain Products, Gilching, Germany) was recorded outside the scanner, and subsequently simultaneous FDG-PET/fMRI was acquired on an integrated Siemens Biograph mMR 3T scanner (Siemens Healthineers, Erlangen Germany). Power spectral densities, permutation entropy (PE) and symbolic transfer entropy (STE) were calculated in/between frontal, temporal, parietal and occipital EEG channels. PE and STE are based on symbolic time series analysis and were already introduced as robust markers separating wakefulness from unconsciousness in EEG during general anesthesia. While PE quantifies the regularity structure of the neighboring order of signal values (a surrogate of cortical information processing), STE reflects information transfer between two signals (a surrogate of directed connectivity in cortical networks). fMRI was carried out using SPM12 (Wellcome Trust Center for Neuroimaging, University of London, UK). Functional images were realigned, segmented, normalized and smoothed. PET was acquired for 45 minutes in list-mode. For absolute quantification of brain’s glucose consumption rate in FDG-PET, kinetic modelling was performed with Patlak’s plot method. BOLD signal intensity in fMRI and glucose uptake in PET was calculated in 8 distinct cortical areas. PCA was performed over all markers from EEG/fMRI/PET. Prognosis (persistent VS and deceased patients vs. recovery to MCS/awake from date I to date II) was evaluated using the area under the curve (AUC) including bootstrap confidence intervals (CI, *: p<0.05). Results: Prognosis was reliably indicated by the first component of PCA (AUC=0.99*, CI=0.92-1.00) showing a higher AUC when compared to the best single markers (EEG: AUC<0.96*, fMRI: AUC<0.86*, PET: AUC<0.60). CRS-R did not show prediction (AUC=0.51, CI=0.29-0.78). Conclusion: In a multimodal analysis of EEG/fMRI/PET in coma patients, PCA lead to a reliable prognosis. The impact of this result is evident, as clinical estimates of prognosis are inapt at time and could be supported by quantitative biomarkers from EEG, fMRI and PET. Due to the small sample size, further investigations are required, in particular allowing superwised learning instead of the basic approach of unsuperwised PCA.

Keywords: coma states and prognosis, electroencephalogram, entropy, functional magnetic resonance imaging, machine learning, positron emission tomography, principal component analysis

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Authors: Vishwas Goel, Kapil Surve, Somnath Basu

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In-situ alloying in steel during the electro-slag remelting (ESR) process has already been achieved by the addition of necessary ferroalloys into the electro-slag remelting mold. However, the use of commercially available ferroalloys during ESR processing is often found to be financially less favorable, in comparison with the conventional alloying techniques. However, a process of alloying steel with elements like chromium and manganese using the electro-slag remelting route is under development without any ferrochrome addition. The process utilizes in-situ reduction of refined mineral chromite (Cr₂O₃) and resultant enrichment of chromium in the steel ingot produced. It was established in course of this work that this process can become more advantageous over conventional alloying techniques, both economically and environmentally, for applications which inherently demand the use of the electro-slag remelting process, such as manufacturing of superalloys. A key advantage is the lower overall CO₂ footprint of this process relative to the conventional route of production, storage, and the addition of ferrochrome. In addition to experimentally validating the feasibility of the envisaged reactions, a mathematical model to simulate the reduction of chromium (III) oxide and transfer to chromium to the molten steel droplets was also developed as part of the current work. The developed model helps to correlate the amount of chromite input and the magnitude of chromium alloying that can be achieved through this process. Experiments are in progress to validate the predictions made by this model and to fine-tune its parameters.

Keywords: alloying element, chromite, electro-slag remelting, ferrochrome

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Authors: Fitria Ningsih

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This study concerns on the process of making corpus obtained from Indonesian year 4 students’ free writing compared to the vocabulary taught in English language textbooks. 369 students’ sample writings from 19 public elementary schools in Malang, East Java, Indonesia and 5 selected English textbooks were analyzed through corpus in linguistics method using AdTAT -the Adelaide Text Analysis Tool- program. The findings produced wordlists of the top 100 words most frequently used by students and the top 100 words given in English textbooks. There was a 45% match between the two lists. Furthermore, the classifications of the top 100 most frequent words from the two corpora based on part of speech found that both the Indonesian and English languages employed a similar use of nouns, verbs, adjectives, and prepositions. Moreover, to see the contextualizing the vocabulary of learning materials towards the students’ need, a depth-analysis dealing with the content and the cultural views from the vocabulary taught in the textbooks was discussed through the criteria developed from the checklist. Lastly, further suggestions are addressed to language teachers to understand the students’ background such as recognizing the basic words students acquire before teaching them new vocabulary in order to achieve successful learning of the target language.

Keywords: corpus, frequency, English, Indonesian, linguistics, textbooks, vocabulary, wordlists, writing

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Authors: Bunindro Nameirakpam, Sonia Sougrapakam, Shannon B. Olsson, Rajashekar Yallappa

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Natural sources for new pesticidal compounds hold promise in view of their eco-friendly nature, selectivity and mammalian safety. Despite a large number of plants that show insecticidal activity and diversity of natural chemistry with inherent eco-friendly nature, newer classes of insecticides have eluded discovery. Artemisia vulgaris, known as Mugwort, is a universal herb used for folk medicine and religious purposes throughout the ancient world. In India, the essential oils of Artemisia vulgaris are used for its insecticidal, anti parasiticidal and antimicrobial properties. Traditionally, the dried leaves of Artemisia vulgaris are used to repel insects as well as rats in and around the granaries in the North-East India. Artemisia vulgaris collected during November from different ecological sites were studied for the bio-pesticidal utility against the stored grain pests. The insecticidal activities were found in the crude extracts of n-hexane and methanol from the samples collected in Sikkim and Manipur respectively. Using silica gel column chromatography protocol, we have isolated one novel bioactive molecule from the aerial parts of Artemisia vulgaris L based on various physical-chemical and spectroscopic techniques (IR, 1H NMR, 13C NMR and mass). The novel bioactive molecule is highly toxic and very low concentration (4.35 µg/l) is needed to control the stored product insects. In additional experiment results clearly showed the involvement of sodium pumps inhibition in the insecticidal action of purified compound in the Sitophilus oryzae. The knockdown activity of the purified compound is concomitant with the in vivo inhibition of Na+/ K+- ATPase. Further, our study showed insignificant differences in the seed germination of control and the treated grains. The lack of adverse effect of the novel bioactive molecule on the seed germination is highly desirable for seed/grain protectant and showing the potential to be developed as possible natural fumigants for the control of stored grain pests. The novel bioactive molecule is selective insecticide with a high margin of safety to mammals and showed promise as novel biopesticide candidate for grain protection. It is believed that Bio-pesticides can serve as the most important pest management tools as far as global safety is concerned.

Keywords: Indian traditional plant, Artemisia vulgaris, bio-pesticides, Na+/ K+- ATPase, seed germination

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Authors: P. Phenpun, S. Wareewan

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This qualitative study aimed to describe the opinions in relation to humanized care emerging from the volunteer activities of nursing students at Boromarajonani College of Nursing, Chonburi, Thailand. One hundred and twenty-seven second-year nursing students participated in this study. The volunteer activity model was composed of preparation, implementation, and evaluation through a learning log, in which students were encouraged to write their daily activities after completing practical training at the healthcare center. The preparation content included three main categories: service minded, analytical thinking, and client participation. The preparation process took over three days that accumulates up to 20 hours only. The implementation process was held over 10 days, but with a total of 70 hours only, with participants taking part in volunteer work activities at a healthcare center. A learning log was used for evaluation and data were analyzed using content analysis. The findings were as follows. With service minded, there were two subcategories that emerged from volunteer activities, which were service minded towards patients and within themselves. There were three categories under service minded towards patients, which were rapport, compassion, and empathy service behaviors, and there were four categories under service minded within themselves, which were self-esteem, self-value, management potential, and preparedness in providing good healthcare services. In line with analytical thinking, there were two components of analytical thinking, which were analytical skill for their works and analytical thinking for themselves. There were four subcategories under analytical thinking for their works, which were evidence based thinking, real situational thinking, cause analysis thinking, and systematic thinking, respectively. There were four subcategories under analytical thinking for themselves, which were comparative between themselves, towards their clients that leads to the changing of their service behaviors, open-minded thinking, modernized thinking, and verifying both verbal and non-verbal cues. Lastly, there were three categories under participation, which were mutual rapport relationship; reconsidering client’s needs services and providing useful health care information.

Keywords: humanized care service, volunteer activity, nursing student, learning log

Procedia PDF Downloads 302