Search results for: language learning model

Authors: J. L. Andrade-Pineda, J.M. León-Blanco, M. Calle, P. L. González-R

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The enrollment in current Master's degree programs usually pursues gaining the expertise required in real-life workplaces. The experience we present here concerns the learning process of "Project Management Methodology (PMM)", around a cooperative/collaborative mechanism aimed at affording students measurable learning goals and providing the teacher with the ability of focusing on the weaknesses detected. We have designed a mixed summative/formative evaluation, which assures curriculum engage while enriches the comprehension of PMM key concepts. In this experience we converted the students into active actors in the evaluation process itself and we endowed ourselves as teachers with a flexible process in which along with qualifications (score), other attitudinal feedback arises. Despite the high level of self-affirmation on their discussion within the interactive assessment sessions, they ultimately have exhibited a great ability to review and correct the wrong reasoning when that was the case.

Keywords: cooperative-collaborative learning, educational management, formative-summative assessment, leadership training

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Authors: Saba Rahimi, Ozan Oktay, Javier Alvarez-Valle, Sujeeth Bharadwaj

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Successful application of deep learning in medical image analysis necessitates unprecedented amounts of labeled training data. Unlike conventional 2D applications, radiological images can be three-dimensional (e.g., CT, MRI), consisting of many instances within each image. The problem is exacerbated when expert annotations are required for effective pixel-wise labeling, which incurs exorbitant labeling effort and cost. Active learning is an established research domain that aims to reduce labeling workload by prioritizing a subset of informative unlabeled examples to annotate. Our contribution is a cost-effective approach for U-Net 3D models that uses Monte Carlo sampling to analyze pixel-wise uncertainty. Experiments on the AAPM 2017 lung CT segmentation challenge dataset show that our proposed framework can achieve promising segmentation results by using only 42% of the training data.

Keywords: image segmentation, active learning, convolutional neural network, 3D U-Net

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Authors: Yiran Wang

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As international education continues to expand countries providing such opportunities not only benefit but also face challenges. For traditional destinations, including the United States and the United Kingdom, the number of international students has been falling. At the same time emerging economies, such as China, are witnessing a rapid increase in the number of international students enrolled in their universities. China is, therefore, beginning to play an important role in the competitive global market for higher education. This study analyses and compares the experiences of international students in the UK and China using Transformative Learning theory. While there is an extensive literature on both international higher education and also Transformative Learning theory there are currently three contributions this study makes. First, this research applies the theory to two international student groups: UK students in Chinese universities and Chinese students in UK universities.Second, this study includes a focus on the intercultural learning of Chinese doctoral students in the UK filling a gap in current research. Finally, this investigation has extended the very limited number of current research projects on UK students in China. It is generally acknowledged that international students will experience various challenges when they are in a culturally different context. Little research has focused on how, why, and why not learners are transformed through exposure to their new environment. This study applies Transformative Learning theory to address two research questions: first, do UK international students in Chinese universities and Chinese international students in UK universities experience transformational learning in/during their overseas studies? Second, what factors foster or impede international students’ experience of transformative learning? To answer the above questions, semi-structured interviews were used to investigate international students’ academic and social experiences. Based on the insights provided by Mezirow,Taylor,and previous studies on international students, this study argues that international students’ intercultural experience is a complex process.Transformation can occur in various ways and social and personal perspectives underpin the transformative learning of the students studied. Contributing factors include culture shock, educational conventions,the student’s motivation, expectations, personality, gender and previous work experience.The results reflect the significance of differences in teaching styles in the UK and China and the impact this can have on the student teaching and learning process when they move to a new university.

Keywords: intercultural learning, international higher education, transformative learning, UK and Chinese international students

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Authors: Roberto Cabezas H

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The current work shows the methodology developed to create narrative lighting spaces for the multimedia performance piece 'cluster: the vanished paradise.' This empirical research is focused on exploring unconventional roles for machines in subjective creative processes, by delving into the semantics of data and machine intelligence algorithms in hybrid technological, creative contexts to expand epistemic domains trough human-machine cooperation. The creative process in scenic and performing arts is guided mostly by intuition; from that idea, we developed an approach to embed collective intuition in computational creative systems, by joining the properties of Generative Adversarial Networks (GAN’s) and Fuzzy Clustering based on a semi-supervised data creation and analysis pipeline. The model makes use of GAN’s to learn from phenomenological data (data generated from experience with lighting scenography) and algorithmic design data (augmented data by procedural design methods), fuzzy logic clustering is then applied to artificially created data from GAN’s to define narrative transitions built on membership index; this process allowed for the creation of simple and complex spaces with expressive capabilities based on position and light intensity as the parameters to guide the narrative. Hybridization comes not only from the human-machine symbiosis but also on the integration of different techniques for the implementation of the aided design system. Machine intelligence tools as proposed in this work are well suited to redefine collaborative creation by learning to express and expand a conglomerate of ideas and a wide range of opinions for the creation of sensory experiences. We found in GAN’s and Fuzzy Logic an ideal tool to develop new computational models based on interaction, learning, emotion and imagination to expand the traditional algorithmic model of computation.

Keywords: fuzzy clustering, generative adversarial networks, human-machine cooperation, hybrid collective data, multimedia performance

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Authors: Latif Yanar, Muharrem Kaçan

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In this study, an Analytic Hierarchy Process and Analytic Network Process Decision Support System (DSS) model for determination of a navy base place in another country is proposed together with a decision support software (DESTEC 1.0) developed using C Sharp programming language. The proposed software also has the ability of performing the fuzzy models (Fuzzy AHP and Fuzzy ANP) of the proposed DSS to cope with the ambiguous and linguistic nature of the model. The AHP and ANP model, for a decision support for selecting the best place among the alternatives, including the criteria and alternatives, is developed and solved by the experts from Turkish Navy and Turkish academicians related to international relations branches of the universities in Turkey. Also, the questionnaires used for weighting of the criteria and the alternatives are filled by these experts.Some of our alternatives are: economic and political stability of the third country, the effect of another super power in that country, historical relations, security in that country, social facilities in the city in which the base will be built, the transportation security and difficulty from a main city that have an airport to the city will have the base etc. Over 20 criteria like these are determined which are categorized in social, political, economic and military aspects. As a result all the criteria and three alternatives are evaluated by different people who have background and experience to weight the criteria and alternatives as it must be in AHP and ANP evaluation system. The alternatives got their degrees all between 0 – 1 and the total is 1. At the end the DSS advices one of the alternatives as the best one to the decision maker according to the developed model and the evaluations of the experts.

Keywords: analytic hierarchical process, analytic network process, fuzzy logic, naval base place selection, multiple criteria decision making

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Authors: Stella Y. Erinosho

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In an attempt to impact on girls’ interest in science, an instructional package on ‘Learn Science by Doing (LSD)’ was developed to support science teachers in teaching integrated science at the junior secondary level in Nigeria. LSD provides an instructional framework aimed at actively engaging girls in beginners’ science through activities that are discovery-oriented and allow for experiential learning. The goal of this study was to show the impact of application of LSD on girls’ performance and interest in science. The major hypothesis that was tested in the study was that students would exhibit higher learning outcomes (achievement and attitude) in science as effect of exposure to LSD instructional package. A quasi-experimental design was adopted, incorporating four all-girls schools. Three of the schools (comprising six classes) were randomly designated as experimental and one as the control. The sample comprised 357 girls (275 experimental and 82 control) and nine science teachers drawn from the experimental schools. The questionnaire was designed to gather data on students’ background characteristics and their attitude toward science while the cognitive outcomes were measured using tests, both within a group and between groups, the girls who had exposure to LSD exhibited improved cognitive outcomes and more positive attitude towards science compared with those who had conventional teaching. The data are consistent with previous studies indicating that interactive learning activities increase student performance and interest.

Keywords: active learning, school science, teaching and learning, Nigeria

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Authors: Irtaza M. Syed, Kaamran Raahemifar

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This paper presents modeling of a Alternating Current (AC) Photovoltaic (PV) module using Matlab/Simulink. The proposed AC-PV module model is simple, realistic, and application oriented. The model is derived on module level as compared to cell level directly from the information provided by the manufacturer data sheet. DC-PV module, MPPT control, BC, VSI and LC filter, all were treated as a single unit. The model accounts for changes in variations of both irradiance and temperature. The AC-PV module proposed model is simulated and the results are compared with the datasheet projected numbers to validate model’s accuracy and effectiveness. Implementation and results demonstrate simplicity and accuracy, as well as reliability of the model.

Keywords: PV modeling, AC PV Module, datasheet, VI curves irradiance, temperature, MPPT, Matlab/Simulink

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Authors: Orla McConnell, Cormac MacMahon, Jen Harvey

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Ireland’s national professional development framework for those who teach in higher education, aims to provide guidance and leadership in the planning, developing and engaging in professional development practices. A series of pilot projects have been initiated to help explore the framework’s likely utility and acceptance by educators and their institutions. These projects require engagement with staff in the interpretation and adaption of the framework within their working contexts. The purpose of this paper is to outline the development of one such project with engineering educators at three Institutes of Technology seeking designation as a technological university. The initiative aims to gain traction in the acceptance of the framework with the engineering education community by linking core and discipline-specific teaching and learning competencies with professional development activities most valued by engineering educators. Informed by three strands of literature: professional development in higher education; engineering education; and teaching and learning training provisions, the project begins with a survey of all those involved in teaching and learning in engineering across the three institutes. Based on engagement with key stakeholders, subsequent qualitative research informs the contextualization of the national framework for discipline-specific and institutional piloting. The paper concludes by exploring engineering educator perceptions of the national framework’s utility based on their engagement with the pilot process. Feedback from the pilot indicates that there is a significant gap between the professional development needs of engineering educators and the current professional development provision in teaching and learning.

Keywords: engineering education, pilot, professional development, teaching and learning

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Authors: Madushani Rodrigo, Banuka Athuraliya

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In today's world of medical diagnosis and prediction, machine learning stands out as a strong tool, transforming old ways of caring for health. This study analyzes the use of machine learning in the specialized domain of sports medicine, with a focus on the timely and accurate detection of bone fractures in cricket athletes. Failure to identify bone fractures in real time can result in malunion or non-union conditions. To ensure proper treatment and enhance the bone healing process, accurately identifying fracture locations and types is necessary. When interpreting X-ray images, it relies on the expertise and experience of medical professionals in the identification process. Sometimes, radiographic images are of low quality, leading to potential issues. Therefore, it is necessary to have a proper approach to accurately localize and classify fractures in real time. The research has revealed that the optimal approach needs to address the stated problem and employ appropriate radiographic image processing techniques and object detection algorithms. These algorithms should effectively localize and accurately classify all types of fractures with high precision and in a timely manner. In order to overcome the challenges of misidentifying fractures, a distinct model for fracture localization and classification has been implemented. The research also incorporates radiographic image enhancement and preprocessing techniques to overcome the limitations posed by low-quality images. A classification ensemble model has been implemented using ResNet18 and VGG16. In parallel, a fracture segmentation model has been implemented using the enhanced U-Net architecture. Combining the results of these two implemented models, the FracXpert system can accurately localize exact fracture locations along with fracture types from the available 12 different types of fracture patterns, which include avulsion, comminuted, compressed, dislocation, greenstick, hairline, impacted, intraarticular, longitudinal, oblique, pathological, and spiral. This system will generate a confidence score level indicating the degree of confidence in the predicted result. Using ResNet18 and VGG16 architectures, the implemented fracture segmentation model, based on the U-Net architecture, achieved a high accuracy level of 99.94%, demonstrating its precision in identifying fracture locations. Simultaneously, the classification ensemble model achieved an accuracy of 81.0%, showcasing its ability to categorize various fracture patterns, which is instrumental in the fracture treatment process. In conclusion, FracXpert has become a promising ML application in sports medicine, demonstrating its potential to revolutionize fracture detection processes. By leveraging the power of ML algorithms, this study contributes to the advancement of diagnostic capabilities in cricket athlete healthcare, ensuring timely and accurate identification of bone fractures for the best treatment outcomes.

Keywords: multiclass classification, object detection, ResNet18, U-Net, VGG16

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Authors: Zoja Raud, Valery Vodovozov

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Modelling and simulation provide effective way to acquire engineering experience. An active approach to modelling and simulation proposed in the paper involves, beside the compulsory part directed by the traditional step-by-step instructions, the new optional part basing on the human’s habits to design thus stimulating the efforts towards success in active learning. Computer exercises as a part of engineering curriculum incorporate a set of effective activities. In addition to the knowledge acquired in theoretical training, the described educational arrangement helps to develop problem solutions, computation skills, and experimentation performance along with enhancement of practical experience and qualification.

Keywords: modelling, simulation, engineering education, electronics, active learning

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Authors: Teresa Naves, Katy Pallas, Carme Florit, Cristina Anton, Joan Collado, Diana Millan

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Although gender-fair language is relatively novel in Spain, in Catalonia, the Department of Education, as well as LGBT Associations, have been promoting several innovative programmes aimed at implementing gender-inclusive schools. These Rainbow School communities are ideal for looking at how these programmes affect the use of gender-fair language and the balanced representation of gender. The students' and teachers' perceptions and attitudes have been compared to those analysed in schools that have never implemented such programmes in primary or secondary education. Spanish and Catalan, unlike English, are gendered languages in which masculine forms have traditionally been used as the unmarked gender and have been claimed to be inclusive of all genders. While the Royal Spanish Academy (RAE) rejects the use of inclusive language and thus deems all variables of inclusion of double gender as unnecessary, the vast majority of universities are promoting not only inclusive language but also gender-inclusive curricula. Adopting gender-fair language policies and including gender perspective in the curricula is an innovative trend at university level and in primary and secondary school education. Inclusion in education is a basic human right and the foundation for a more just and equal society. Educators can facilitate the process of welcoming by ensuring handbooks, forms, and other communications are inclusive of all family structures and gender identities. Using gendered language such as 'girls and boys' can be alienating for gender non-conforming and gender diverse students; on the other hand, non-gendered words like 'students' are regarded as inclusive of all identities. The paper discusses the results of mixed method research (survey, interviews, and experiment) conducted in Rainbow and non-Rainbow schools in Alacant and Barcelona (Spain). The experiment aimed at checking the role of gender-fair language in learners' perception of gender balance. It was conducted in Spanish, Catalan, and English. Students aged 10 to 16 (N > 600) were asked to draw pictures of people using specific prompts. The prompts in Spanish and Catalan were written using the generic masculine, 'los presidentes' 'els presidents' (presidents); using double gendered language such as 'ninos y ninas', 'nens i nenes' (boys and girls); and using non-gendered words like 'alumnado' 'alumnat' (students). The prompts were subdivided into people in school contexts participants could identify with, such as students and teachers; occupations mostly associated with men, such as pilots and firefighters; and occupations associated with women, such as ballet dancers and nurses. As could be expected, the participants only drew approximately the same percentage of female and male characters when double-gendered language or non-gendered words such as 'students' or 'teachers' were used, regardless of the language used in the experiment. When they were asked to draw people using the so-called generic masculine in Spanish or Catalan, 'los estudiantes' 'els estudiants' (students), less than 35% of the drawings contained female characters. The differences between the results for Rainbow and Non-Rainbow schools will be discussed in the light of the innovative coeducation programmes and learners' perceptions on gender-fair language gathered in the surveys and interviews.

Keywords: gender-fair language, gender-inclusive schools, learners’ and teachers’ perceptions and attitudes, rainbow coeducation programmes

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Authors: Paula Lazarim

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As global mobility thrives, researchers emphasize the urgency of global literacy through training qualified counselors to serve internationally in a culturally competent manner. However, the focus thus far has been on how counselors’ preparation to approach international populations fuses with study abroad experiential learning short-term immersions. Looking for better solutions for cultural competency and skills learning related to international counseling, the author of this manuscript examines international counseling's current status, learning scope and goals, and educational opportunities. A guiding framework grounded on relational pedagogy (Reeves & Le Mare, 2017), relational cultural theory (Jordan, 2017), and intercultural education (Nastasi et al., 2020) is applied with four long-term educational modality projects designed to benefit cultural competence, attitude, relational skills development, and learning an intercultural counseling approach. Suggestions that encourage innovative instruction in counselor education and counseling programs at master and doctoral levels, stimulate self-learning, and educate in intercultural relational competence are linked to strategies for engaging in international counseling based on findings of a literature review and training-projects implementation. Ultimately, the author highlights theoretical and practical implications of suitable training to improve counselors' performance and discusses long-term teaching-learning opportunities that positively impact the international counseling community by sending out internationally culturally competent counselors.

Keywords: international counseling, counselor education, counseling, relational pedagogy, intercultural education, counselors’ training

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Authors: Adel Assiri, Ahmed Emam, Hmood Al-Dossari

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Sentiment analysis (SA) has received growing attention in Arabic language research. However, few studies have yet to directly apply SA to Arabic due to lack of a publicly available dataset for this language. This paper partially bridges this gap due to its focus on one of the Arabic dialects which is the Saudi dialect. This paper presents annotated data set of 4700 for Saudi dialect sentiment analysis with (K= 0.807). Our next work is to extend this corpus and creation a large-scale lexicon for Saudi dialect from the corpus.

Keywords: Arabic, sentiment analysis, Twitter, annotation

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Authors: Yanyue Yuan

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In this paper, the author shares the findings of a pilot study that examines students’ creative expressions and their perceptions of creativity when engaged in project-based learning. The study is based on an elective course that the author co-designed and co-taught with a colleague to sixteen grade six and seven students over the spring semester in 2019. Using the Little Prince story as the main prompt, they facilitated students’ original creation of a storytelling concert that integrated script writing, music production, lyrics, songs, and visual design as a result of both individual and collaborative work. The author will share the specific challenges we met during the project, including learning cultures of the school, class management, teachers' and parents’ attitude, process-oriented versus product-oriented mindset, and facilities and logistical resources. The findings of this pilot study will inform the ongoing research initiative of exploring how we can foster creative learning in public schools in the Chinese context. While K-12 schools of China’s public education system are still dominated by exam-oriented and teacher-centered approaches, the author proposes that expression-based learning can be a starting point for promoting students’ creativity and can serve as experimental efforts to initiate incremental changes within the current education framework. The paper will also touch upon insights gained from collaborations between university and K-12 schools.

Keywords: creativity, expression-based learning, K-12, incremental changes

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Authors: Badriah Algarni

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The pedagogy of ‘flipped learning’ is a form of blended instruction which is gaining widespread attention throughout the world. However, there is a lack of research concerning teachers’ professional development (TPD) in teachers who use flipping. The aim of this study was, therefore, to identify teachers’ perspectives on their experience of flipped PD. The study used a qualitative approach. Purposive sampling recruited nineteen teachers who participated in semi-structured, in-depth interviews. Thematic analysis was used to analyse the interview data. Overall, the teachers reported feeling more confident in their knowledge and skills after participating in flipped TPD. The analysis of the interview data revealed five overarching themes:1) increased engagement with the content; 2) better use of resources; 3) a social, collaborative environment; 4) exchange of practices and experiences; and 5) valuable online activities. These findings can encourage educators, policymakers, and trainers to consider flipped TPD as a form of PD to promote the building of teachers’ knowledge and stimulate reflective practices to improve teaching and learning practices.

Keywords: engagement, flipped learning, teachers’ professional development, collaboration

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Authors: Catherine Maware, Olufemi Adetunji

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The paper is aimed at developing a model to measure the impact of Lean manufacturing deployment on organizational performance. The model will help industry practitioners to assess the impact of implementing Lean constructs on organizational performance. It will also harmonize the measurement models of Lean performance with the house of Lean that seems to have become the industry standard. The sheer number of measurement models for impact assessment of Lean implementation makes it difficult for new adopters to select an appropriate assessment model or deployment methodology. A literature review is conducted to classify the Lean performance model. Pareto analysis is used to select the Lean constructs for the development of the model. The model is further formalized through the use of Structural Equation Modeling (SEM) in defining the underlying latent structure of a Lean system. An impact assessment measurement model developed can be used to measure Lean performance and can be adopted by different industries.

Keywords: impact measurement model, lean bundles, lean manufacturing, organizational performance

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Authors: Denise Levy, Helen J. Khoury

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Nuclear technology is a controversial issue among a great share of the Brazilian population. Misinformation and common wrong beliefs confuse public’s perceptions and the scientific community is expected to offer a wider perspective on the benefits and risks resulting from ionizing radiation in everyday life. Attentive to the need of new approaches between science and society, the Nuclear Energy Museum, in northeast Brazil, is an initiative created to communicate the growing impact of the beneficial applications of nuclear technology in medicine, industry, agriculture and electric power generation. Providing accessible scientific information, the museum offers a rich learning environment, making use of different educational strategies, such as films, interactive panels and multimedia learning tools, which not only increase the enjoyment of visitors, but also maximize their learning potential. Developed according to modern active learning instructional strategies, multimedia materials are designed to present the increasingly role of nuclear science in modern life, transforming science education into a meaningful learning experience. In year 2016, nine different interactive computer-based activities were developed, presenting curiosities about ionizing radiation in different landmarks around the world, such as radiocarbon dating works in Egypt, nuclear power generation in France and X-radiography of famous paintings in Italy. Feedback surveys have reported a high level of visitors’ satisfaction, proving the high quality experience in learning nuclear science at the museum. The Nuclear Energy Museum is the first and, up to the present time, the only permanent museum in Brazil devoted entirely to nuclear science.

Keywords: nuclear technology, multimedia learning tools, science museum, society and education

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Authors: Maria Georgiou

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This study examined whether there was a statistically significant difference between pretest and posttest achievement scores for students who received multimedia-based instructions in science. The paired samples t-test was used to address the research question and to establish whether there was a significant difference between pretest and posttest scores that may have occurred based on the students’ learning experience with multimedia technology. Findings indicated that there was a significant difference in students’ achievement scores before and after a multimedia-based instruction. Students’ achievement scores were increased by approximately two points, after students received multimedia-based instruction. On a paired samples t-test, a high level of significance was found, p = 0.000. Opportunities to learn with multimedia are more likely to result in sustained improvements in student achievement and a deeper understanding of science content. Multimedia can make learning more active and student-centered and activate student motivation.

Keywords: constructivist learning, hyperstudio, multimedia, multimedia-based instruction

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Authors: S. Pesina, T. Solonchak

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Phenomenological analysis is not based on natural language, but ideal language which is able to be a carrier of ideal meanings – eidos representing typical structures or essences. For this purpose, it’s necessary to release from the spatio-temporal definiteness of a subject and then state its noetic essence (eidos) by means of free fantasy generation. Herewith, as if a totally new objectness is created - the universal, confirming the thesis that thinking process takes place in generalizations passing by numerous means through the specific to the general and from the general through the specific to the singular.

Keywords: lexical eidos, phenomenology, noema, polysemantic word, semantic core

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Authors: Darshana Sharma

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Distance Education has emerged as a viable alternative to serve the higher educational needs of the socially and economically disadvantaged people of the remote, rural areas of Jammu region. The University of Jammu is a National Accreditation, and Assessment Council accredited, A+ university and has been accorded graded autonomy by the University Grants Commission. It is a dual mode university offering academic programmes through the regular departments and through the Directorate of Distance Education. The Directorate of Distance Education, University of Jammu still uses printed study material as a mode of instructional delivery. The development of technologies has assured increased interaction and communication for distance learners throughout the distance open learning institutions. Though it is tempting and convenient to adopt technology already being used by others, it may not prove effective for the simple reason that two institutions may be unlike in some respect. The use of technology must be conceived in view of the needs of the learners; geographical socio-economic-cultural and technological contexts and financial, administrative and academic resources of the institution. Mobile learning (m-learning) is a novel approach to knowledge acquisition and dissemination and is gaining global attention. It has evolved as one of the useful channels of distance learning promoting interaction between learners and teachers. It is felt that the Directorate of Distance Education, University of Jammu also needs to adopt new technologies to provide more effective academic and information support to distance learners in order to keep them motivated and also to develop self-learning skills. The chief objective of the research on which this paper is based was to measure the opinion of the distance learners of the DDE, the University of Jammu about the merits of mobile learning. It also explores their preferences for implementing mobile learning. The survey research design of descriptive research has been used. The data was collected from 400 distance learners enrolled with undergraduate and post-graduate programmes using self-constructed questionnaire containing five-point Likert scale items arranging from strongly agree, agree, indifferent, disagree and strongly disagree. Percentages were used to analyze the data. The findings lead to conclude that mobile learning has a great potential for the DDE for reaching out to the rural, remotely located distance learners of the Jammu region and also to improve the teaching-learning environment. The paper also finds out the challenges in the implementation of mobile learning in the region and further makes suggestions for effective implementation of mobile learning in DDE, University of Jammu.

Keywords: directorate of distance education, mobile learning, national accreditation and assessment council, university of Jammu

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Authors: Mahshid Arabi

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With the rapid expansion of digital technologies and the internet, information security has become a critical priority for organizations and individuals. The widespread use of digital tools such as smartphones and internet networks facilitates the storage of vast amounts of data, but simultaneously, vulnerabilities and security threats have significantly increased. The aim of this study is to examine and analyze modern methods of information security management and to develop a comprehensive model to counteract threats and information misuse. This study employs a mixed-methods approach, including both qualitative and quantitative analyses. Initially, a systematic review of previous articles and research in the field of information security was conducted. Then, using the Delphi method, interviews with 30 information security experts were conducted to gather their insights on security challenges and solutions. Based on the results of these interviews, a comprehensive model for information security management was developed. The proposed model includes advanced encryption techniques, machine learning-based intrusion detection systems, and network security protocols. AES and RSA encryption algorithms were used for data protection, and machine learning models such as Random Forest and Neural Networks were utilized for intrusion detection. Statistical analyses were performed using SPSS software. To evaluate the effectiveness of the proposed model, T-Test and ANOVA statistical tests were employed, and results were measured using accuracy, sensitivity, and specificity indicators of the models. Additionally, multiple regression analysis was conducted to examine the impact of various variables on information security. The findings of this study indicate that the comprehensive proposed model reduced cyber-attacks by an average of 85%. Statistical analysis showed that the combined use of encryption techniques and intrusion detection systems significantly improves information security. Based on the obtained results, it is recommended that organizations continuously update their information security systems and use a combination of multiple security methods to protect their data. Additionally, educating employees and raising public awareness about information security can serve as an effective tool in reducing security risks. This research demonstrates that effective and up-to-date information security management requires a comprehensive and coordinated approach, including the development and implementation of advanced techniques and continuous training of human resources.

Keywords: data protection, digital technologies, information security, modern management

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Authors: Mohit Gupta, Chialing Wei, Thomas Czerniawski

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In this paper, we have built a neural network that can detect walls on 2D sheets and subsequently create a 3D model in Revit using Dynamo. The training set includes 3500 labeled images, and the detection algorithm used is YOLO. Typically, engineers/designers make concentrated efforts to convert 2D cad drawings to 3D models. This costs a considerable amount of time and human effort. This paper makes a contribution in automating the task of 3D walls modeling. 1. Detecting Walls in 2D cad and generating 3D pop-ups in Revit. 2. Saving designer his/her modeling time in drafting elements like walls from 2D cad to 3D representation. An object detection algorithm YOLO is used for wall detection and localization. The neural network is trained over 3500 labeled images of size 256x256x3. Then, Dynamo is interfaced with the output of the neural network to pop-up 3D walls in Revit. The research uses modern technological tools like deep learning and artificial intelligence to automate the process of generating 3D walls without needing humans to manually model them. Thus, contributes to saving time, human effort, and money.

Keywords: neural networks, Yolo, 2D to 3D transformation, CAD object detection

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Authors: Charlotte Entwistle, Ryan Boyd

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Recent developments in information retrieval techniques and natural language processing have allowed for greater exploration of psychological and social processes. Linguistic analysis methods for understanding behaviour have provided useful insights within the field of mental health. One area within mental health that has received little attention though, is borderline personality disorder (BPD). BPD is a common mental health disorder characterised by instability of interpersonal relationships, self-image and affect. It also manifests through maladaptive behaviours, such as impulsivity and self-harm. Examination of language patterns associated with BPD could allow for a greater understanding of the disorder and its links to maladaptive thoughts and behaviours. Language analysis methods could also be used in a predictive way, such as by identifying indicators of BPD or predicting maladaptive thoughts, emotions and behaviours. Additionally, associations that are uncovered between language and maladaptive thoughts and behaviours could then be applied at a more general level. This study explores linguistic characteristics of BPD, and their links to maladaptive thoughts and behaviours, through the analysis of social media data. Data were collected from a large corpus of posts from the publicly available social media platform Reddit, namely, from the ‘r/BPD’ subreddit whereby people identify as having BPD. Data were collected using the Python Reddit API Wrapper and included all users which had posted within the BPD subreddit. All posts were manually inspected to ensure that they were not posted by someone who clearly did not have BPD, such as people posting about a loved one with BPD. These users were then tracked across all other subreddits of which they had posted in and data from these subreddits were also collected. Additionally, data were collected from a random control group of Reddit users. Disorder-relevant behaviours, such as self-harming or aggression-related behaviours, outlined within Reddit posts were coded to by expert raters. All posts and comments were aggregated by user and split by subreddit. Language data were then analysed using the Linguistic Inquiry and Word Count (LIWC) 2015 software. LIWC is a text analysis program that identifies and categorises words based on linguistic and paralinguistic dimensions, psychological constructs and personal concern categories. Statistical analyses of linguistic features could then be conducted. Findings revealed distinct linguistic features associated with BPD, based on Reddit posts, which differentiated these users from a control group. Language patterns were also found to be associated with the occurrence of maladaptive thoughts and behaviours. Thus, this study demonstrates that there are indeed linguistic markers of BPD present on social media. It also implies that language could be predictive of maladaptive thoughts and behaviours associated with BPD. These findings are of importance as they suggest potential for clinical interventions to be provided based on the language of people with BPD to try to reduce the likelihood of maladaptive thoughts and behaviours occurring. For example, by social media tracking or engaging people with BPD in expressive writing therapy. Overall, this study has provided a greater understanding of the disorder and how it manifests through language and behaviour.

Keywords: behaviour analysis, borderline personality disorder, natural language processing, social media data

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Authors: Gayathri Nagarajan, L. D. Dhinesh Babu

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Health care is one of the prominent industries that generate voluminous data thereby finding the need of machine learning techniques with big data solutions for efficient processing and prediction. Missing data, incomplete data, real time streaming data, sensitive data, privacy, heterogeneity are few of the common challenges to be addressed for efficient processing and mining of health care data. In comparison with other applications, accuracy and fast processing are of higher importance for health care applications as they are related to the human life directly. Though there are many machine learning techniques and big data solutions used for efficient processing and prediction in health care data, different techniques and different frameworks are proved to be effective for different applications largely depending on the characteristics of the datasets. In this paper, we present a framework that uses ensemble machine learning technique gradient boosted trees for data classification in health care big data. The framework is built on Spark platform which is fast in comparison with other traditional frameworks. Unlike other works that focus on a single technique, our work presents a comparison of six different machine learning techniques along with gradient boosted trees on datasets of different characteristics. Five benchmark health care datasets are considered for experimentation, and the results of different machine learning techniques are discussed in comparison with gradient boosted trees. The metric chosen for comparison is misclassification error rate and the run time of the algorithms. The goal of this paper is to i) Compare the performance of gradient boosted trees with other machine learning techniques in Spark platform specifically for health care big data and ii) Discuss the results from the experiments conducted on datasets of different characteristics thereby drawing inference and conclusion. The experimental results show that the accuracy is largely dependent on the characteristics of the datasets for other machine learning techniques whereas gradient boosting trees yields reasonably stable results in terms of accuracy without largely depending on the dataset characteristics.

Keywords: big data analytics, ensemble machine learning, gradient boosted trees, Spark platform

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Authors: Kishor T. Zingre, Seshadhri Srinivasan

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Energy consumption by the building sector is increasing at an alarming rate throughout the world and leading to more building-related CO₂ emissions into the environment. In buildings, the main contributors to energy consumption are heating, ventilation, and air-conditioning (HVAC) systems, lighting, and electrical appliances. It is hypothesised that the energy efficiency in buildings can be achieved by implementing sustainable technologies such as i) enhancing the thermal resistance of fabric materials for reducing heat gain (in hotter climates) and heat loss (in colder climates), ii) enhancing daylight and lighting system, iii) HVAC system and iv) occupant localization. Energy performance of various sustainable technologies is highly dependent on climatic conditions. This paper investigated the use of machine learning techniques for accurate prediction of air-conditioning energy in seasonal climates. The data required to train the machine learning techniques is obtained using the computational simulations performed on a 3-story commercial building using EnergyPlus program plugged-in with OpenStudio and Google SketchUp. The EnergyPlus model was calibrated against experimental measurements of surface temperatures and heat flux prior to employing for the simulations. It has been observed from the simulations that the performance of sustainable fabric materials (for walls, roof, and windows) such as phase change materials, insulation, cool roof, etc. vary with the climate conditions. Various renewable technologies were also used for the building flat roofs in various climates to investigate the potential for electricity generation. It has been observed that the proposed technique overcomes the shortcomings of existing approaches, such as local linearization or over-simplifying assumptions. In addition, the proposed method can be used for real-time estimation of building air-conditioning energy.

Keywords: building energy efficiency, energyplus, machine learning techniques, seasonal climates

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Authors: T. Sahbani, M. Bouteraa, R. Wamkeue

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Wind Turbine are considered to be one of the more efficient system of energy production nowadays, a reason that leads the main industrial companies in wind turbine construction and researchers in over the world to look for better performance and one of the ways for that is the use of the synchronous permanent magnet generator. In this context, this work is about developing an analytical model that could simulate different situation in which the synchronous generator may go through, and of course this model match perfectly with the numerical and experimental model.

Keywords: MATLAB, synchronous permanent magnet generator, wind turbine, analytical model

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Authors: Ratun Rahman, Rafid Islam, Akin Ahmed, Kamrul Hasan, Hasan Mahmud

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Malware is becoming more prevalent, and several threat categories have risen dramatically in recent years. This paper provides a bird's-eye view of the world of malware analysis. The efficiency of five different machine learning methods (Naive Bayes, K-Nearest Neighbor, Decision Tree, Random Forest, and TensorFlow Decision Forest) combined with features picked from the retrieval of Android permissions to categorize applications as harmful or benign is investigated in this study. The test set consists of 1,168 samples (among these android applications, 602 are malware and 566 are benign applications), each consisting of 948 features (permissions). Using the permission-based dataset, the machine learning algorithms then produce accuracy rates above 80%, except the Naive Bayes Algorithm with 65% accuracy. Of the considered algorithms TensorFlow Decision Forest performed the best with an accuracy of 90%.

Keywords: android malware detection, machine learning, malware, malware analysis

Procedia PDF Downloads 157

Authors: Yasser Y. Lenis, Amy Jo Montgomery, Diego F. Carrillo-Gonzalez

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Introduction: The use of didactic instruments in different learning environments plays a pivotal role in enhancing the level of knowledge in veterinary science students. The direct instruction of basic animal reproduction concepts in students enrolled in veterinary medicine programs allows them to elucidate the biological and molecular mechanisms that perpetuate the animal species in an ecosystem. Therefore, universities must implement didactic strategies that facilitate the teaching and learning processes for students and, in turn, enrich learning environments. Objective: to evaluate the effect of the use of a didactic textbook on the level of theoretical knowledge in embryo-maternal recognition for veterinary medicine students. Methods: the participants (n=24) were divided into two experimental groups: control (Ctrl) and treatment (Treat). Both groups received 4 hours of theoretical training regarding the basic concepts in bovine embryo-maternal recognition. However, the Treat group was also exposed to a guided lecture and the activity play-to-learn from a cow reproduction didactic textbook. A pre-test and a post-test were applied to assess the prior and subsequent knowledge in the participants. Descriptive statistics were applied to identify the success rates for each of the tests. Afterwards, a repeated measures model was applied where the effect of the intervention was considered. Results: no significant difference (p>0,05) was observed in the number of right answers for groups Ctrl (54,2%±12,7) and Treat (40,8%±16,8) in the pre-test. There was no difference (p>0,05) compering the number of right answers in Ctrl pre-test (54,2%±12,7) and post-test (60,8±18,8). However, the Treat group showed a significant (p>0,05) difference in the number of right answers when comparing pre-test (40,8%±16,8) and post-test (71,7%±14,7). Finally, after the theoretical training and the didactic activity in the Treat group, an increase of 10.9% (p<0,05) in the number of right answers was found when compared with the Ctrl group. Conclusion: the use of didactic tools that include guided lectures and activities like play-to-learn from a didactic textbook enhances the level of knowledge in an animal reproduction course for veterinary medicine students.

Keywords: animal reproduction, pedagogic, level of knowledge, learning environment

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Authors: Lowai Abed

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The differences in languages play a big role in cross-cultural communication. If meanings are not translated accurately, the risk can be crucial not only on an interpersonal level, but also on the international and political levels. The use of metaphorical language by politicians can cause great confusion, often leading to statements being misconstrued. In these situations, it is the translators who struggle to put forward the intended meaning with clarity and this makes translation an important field to study and analyze when it comes to cross-cultural communication. Owing to the growing importance of language and the power of translation in politics, this research analyzes part of President Bush’s speech in 2001 in which he used the word “Crusade” which caused his statement to be misconstrued. The research uses a discourse analysis of cross-cultural communication literature which provides answers supported by historical, linguistic, and communicative perspectives. The first finding indicates that the word ‘crusade’ carries different meaning and significance in the narratives of the Western world when compared to the Middle East. The second one is that, linguistically, maintaining cultural meanings through translation is quite difficult and challenging. Third, when it comes to the cross-cultural communication perspective, the common and frequent usage of literal translation is a sign of poor strategies being followed in translation training. Based on the example of Bush’s speech, this paper hopes to highlight the weak practices in translation in cross-cultural communication which are still commonly used across the world. Translation studies have to take issues such as this seriously and attempt to find a solution. In every language, there are words and phrases that have cultural, historical and social meanings that are woven into the language. Literal translation is not the solution for this problem because that strategy is unable to convey these meanings in the target language.

Keywords: crusade, metaphor, mistranslation, war in terror

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Authors: David N. Prihoda

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This paper charts the history of the English word Tempest from its origins in Proto-Indo European to its modern usage as a term for storms, both literal and metaphorical. It does so by way of considering the word’s morphology, semiotics, and phonetics. It references numerous language studies and dictionaries to chronicle the word’s many steps along that path, from demarcation of measurement to assessment of time, all the way to an observation about the weather or the human psyche. The conclusive findings show that tempest has undergone numerous changes throughout its history, and these changes interestingly parallel its connotations as a symbol for both chaotic weather and the chaos of the human spirit

Keywords: Tempest, etymology, language origins, English

Procedia PDF Downloads 107