Search results for: teaching report writing for innovative learning

Authors: Jimena Alarcon, Andrea Llorens, Gabriel Hernandez, Maritza Palma, Lucia Navarrete

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The research has funding from the Government of Chile and is focused on defining the design of rural primary classroom that stimulates creativity. The relevance of the study consists of its capacity to define adequate educational spaces for the implementation of the design-based learning (DBL) methodology. This methodology promotes creativity and teamwork, generating a meaningful learning experience for students, based on the appreciation of their environment and the generation of projects that contribute positively to their communities; also, is an inquiry-based form of learning that is based on the integration of design thinking and the design process into the classroom. The main goal of the study is to define the design characteristics of rural primary school classrooms, associated with the implementation of the DBL methodology. Along with the change in learning strategies, it is necessary to change the educational spaces in which they develop. The hypothesis indicates that a change in the space and equipment of the classrooms based on the emotions of the students will motivate better learning results based on the implementation of a new methodology. In this case, the pedagogical dynamics require an important interaction between the participants, as well as an environment favorable to creativity. Methodologies from Kansei engineering are used to know the emotional variables associated with their definition. The study is done to 50 students between 6 and 10 years old (average age of seven years), 48% of men and 52% women. Virtual three-dimensional scale models and semantic differential tables are used. To define the semantic differential, self-applied surveys were carried out. Each survey consists of eight separate questions in two groups: question A to find desirable emotions; question B related to emotions. Both questions have a maximum of three alternatives to answer. Data were tabulated with IBM SPSS Statistics version 19. Terms referred to emotions are grouped into twenty concepts with a higher presence in surveys. To select the values obtained as part of the implementation of Semantic Differential, a number expected of 'chi-square test (x2)' frequency calculated for classroom space is considered lower limit. All terms over the N expected a cut point, are included to prepare tables for surveys to find a relation between emotion and space. Statistic contrast (Chi-Square) represents significance level ≥ 0, indicator that frequencies appeared are not random. Then, the most representative terms depend on the variable under study: a) definition of textures and color of vertical surfaces is associated with emotions such as tranquility, attention, concentration, creativity; and, b) distribution of the equipment of the rooms, with emotions associated with happiness, distraction, creativity, freedom. The main findings are linked to the generation of classrooms according to diverse DBL team dynamics. Kansei engineering is the appropriate methodology to know the emotions that students want to feel in the classroom space.

Keywords: creativity, design-based learning, education spaces, emotions

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Authors: Santi Gopal Maji, R. A. J. Syngkon

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The changing attitude of the corporate enterprises from maximizing economic benefit to corporate sustainability after the publication of Brundtland Report has attracted the interest of researchers to investigate the sustainability practices of firms and its impact on financial performance. To enrich the empirical literature in Asian context, this study examines the disclosure pattern of corporate sustainability and the influence of sustainability reporting on financial performance of firms from four Asian countries (Japan, South Korea, India and Indonesia) that are publishing sustainability report continuously from 2009 to 2016. The study has used content analysis technique based on Global Reporting Framework (3 and 3.1) reporting framework to compute the disclosure score of corporate sustainability and its components. While dichotomous coding system has been employed to compute overall quantitative disclosure score, a four-point scale has been used to access the quality of the disclosure. For analysing the disclosure pattern of corporate sustainability, box plot has been used. Further, Pearson chi-square test has been used to examine whether there is any difference in the proportion of disclosure between the countries. Finally, quantile regression model has been employed to examine the influence of corporate sustainability reporting on the difference locations of the conditional distribution of firm performance. The findings of the study indicate that Japan has occupied first position in terms of disclosure of sustainability information followed by South Korea and India. In case of Indonesia, the quality of disclosure score is considerably less as compared to other three countries. Further, the gap between the quality and quantity of disclosure score is comparatively less in Japan and South Korea as compared to India and Indonesia. The same is evident in respect of the components of sustainability. The results of quantile regression indicate that a positive impact of corporate sustainability becomes stronger at upper quantiles in case of Japan and South Korea. But the study fails to extricate any definite pattern on the impact of corporate sustainability disclosure on the financial performance of firms from Indonesia and India.

Keywords: corporate sustainability, quality and quantity of disclosure, content analysis, quantile regression, Asian countries

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Authors: R Palson Kennedy, P.Kiran Sai

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This article introduces machine learning (ML) researchers to the hurdles that geoscience problems present, as well as the opportunities for improvement in both ML and geosciences. This article presents a review from the data life cycle perspective to meet that need. Numerous facets of geosciences present unique difficulties for the study of intelligent systems. Geosciences data is notoriously difficult to analyze since it is frequently unpredictable, intermittent, sparse, multi-resolution, and multi-scale. The first half addresses data science’s essential concepts and theoretical underpinnings, while the second section contains key themes and sharing experiences from current publications focused on each stage of the data life cycle. Finally, themes such as open science, smart data, and team science are considered.

Keywords: Data science, intelligent system, machine learning, big data, data life cycle, recent development, geo science

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Authors: Ahmed Negm, George Aggidis, Xiandong Ma

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With the diverse nature of urban cities, customer demand patterns, landscape topologies or even seasonal weather trends; managing our water distribution networks (WDNs) has proved a complex task. These unpredictable circumstances manifest as pipe failures, intermittent supply and burst events thus adding to water loss, energy waste and increased carbon emissions. Whilst these events are unavoidable, advanced pressure management has proved an effective tool to control and mitigate them. Henceforth, water utilities have struggled with developing a real-time control method that is resilient when confronting the challenges of water distribution. In this paper we use deep reinforcement learning (DRL) algorithms as a novel pressure control strategy to minimise pressure violations and leakage under both burst and background leakage conditions. Agents based on asynchronous actor critic (A2C) and recurrent proximal policy optimisation (Recurrent PPO) were trained and compared to benchmarked optimisation algorithms (differential evolution, particle swarm optimisation. A2C manages to minimise leakage by 32.48% under burst conditions and 67.17% under background conditions which was the highest performance in the DRL algorithms. A2C and Recurrent PPO performed well in comparison to the benchmarks with higher processing speed and lower computational effort.

Keywords: deep reinforcement learning, pressure management, water distribution networks, leakage management

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Authors: Ahn Christine Myunghee, Sim Wonjin, Cho Kristina, Ahn Mira, Hong Yeju, Kwok Jihae, Lim Sooyeon, Park Hansol

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With a sharp increase in the prevalence rate for mental health issues in Korea, there is a need for specific and effective intervention strategies in counseling and psychotherapy for use with Korean clients. With the cultural emphasis on restraining emotional expression and not disclosing personal and familial problems to outsiders, clients often find it difficult to discuss their emotional issues even to therapists. Exploring a client’s internal psychological processes bypassing this culture-specific mode of therapeutic communication often becomes a challenge in the therapeutic setting. Given this socio-cultural context, the purpose of the current study was to investigate the effectiveness of using dream work to individuals in Korea. The current study conducted one 60-90 minute dream session and analyzed the dream content of 39 Korean young adults to evaluate the effectiveness of the Hill dream model in accessing the intra-psychic materials, determining essential emotional themes, and learning how the individuals interpreted the contents of their dreams. The transcribed data, which included a total of 39 sessions from 39 volunteer university students, were analyzed by the Consensus Qualitative Research (CQR) approach in terms of domains and core ideas. Self-report measures on Dream Salience, Gains from Dream Interpretations and the Session Evaluation Scale were administered before and after each of their dream sessions. The results indicated that dream work appears to be an effective way to understand unconscious motivations, thoughts, and feelings related to a person’s sense of self, and also how these people relate to other people. Current findings need to be replicated with clients referred for counseling and psychotherapy to determine if the dream work is an appropriate and useful intervention in counseling settings. Limitations of the current study and suggestions for future follow-ups are included in the discussion.

Keywords: dream work, dream interpretation, Korean, young adults, CQR

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Authors: Mustafa Tevfik Hebebci, Ismail Sahin, Sirin Kucuk, Ismail Celik, Ahmet Oguz Akturk

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ADDIE is an instructional design model which has the five core elements: analyze, design, develop, implement, and evaluate. The ADDIE approach provides a systematic process for the analysis of instructional needs, the design and development of instructional programs and materials, implementation of a program, and the evaluation of the effectiveness of an instruction. The case-based study is an instructional design model that is a variant of project-oriented learning. Collecting and analyzing stories can be used in two primary ways -perform task analysis and as a learning support during instruction- by instructional designers. Besides, teachers use technology to develop students’ thinking, enriching the learning environment and providing permanent learning. The purpose of this paper is to introduce an interactive online case-study library website developed in a national project. The design goal of the website is to provide interactive, enhanced, case-based and online educational resource for educators through the purpose and within the scope of a national project. The ADDIE instructional design model was used in the development of the website for the interactive case-based library. This web-based library contains the navigation menus as the follows: “Homepage”, "Registration", "Branches", "Aim of The Research", "About TPACK", "National Project", "Contact Us", etc. This library is developed on a web-based platform, which is important in terms of manageability, accessibility, and updateability of data. Users are able to sort the displayed case-studies by their titles, dates, ratings, view counts, etc. In addition, they encouraged to rate and comment on the case-studies. The usability test is used and the expert opinion is taken for the evaluation of the website. This website is a tool to integrate technology in education. It is believed that this website will be beneficial for pre-service and in-service teachers in terms of their professional developments.

Keywords: design, ADDIE, case based library, technology integration

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Authors: Amparo Camacho

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ABET accredited programs must assess the development of student learning outcomes (SOs) in engineering programs. Different institutions implement different strategies for this assessment, and they are usually designed “in house.” This paper presents a proposal for including standardized tests to complement the ABET assessment model in an engineering college made up of six distinct engineering programs. The engineering college formulated a model of quality assurance in education to be implemented throughout the six engineering programs to regularly assess and evaluate the achievement of SOs in each program offered. The model uses diverse techniques and sources of data to assess student performance and to implement actions of improvement based on the results of this assessment. The model is called “Assessment Process Model” and it includes SOs A through K, as defined by ABET. SOs can be divided into two categories: “hard skills” and “professional skills” (soft skills). The first includes abilities, such as: applying knowledge of mathematics, science, and engineering and designing and conducting experiments, as well as analyzing and interpreting data. The second category, “professional skills”, includes communicating effectively, and understanding professional and ethnical responsibility. Within the Assessment Process Model, various tools were used to assess SOs, related to both “hard” as well as “soft” skills. The assessment tools designed included: rubrics, surveys, questionnaires, and portfolios. In addition to these instruments, the Engineering College decided to use tools that systematically gather consistent quantitative data. For this reason, an in-house exam was designed and implemented, based on the curriculum of each program. Even though this exam was administered during various academic periods, it is not currently considered standardized. In 2017, the Engineering College included three standardized tests: one to assess mathematical and scientific reasoning and two more to assess reading and writing abilities. With these exams, the college hopes to obtain complementary information that can help better measure the development of both hard and soft skills of students in the different engineering programs. In the first semester of 2017, the three exams were given to three sample groups of students from the six different engineering programs. Students in the sample groups were either from the first, fifth, and tenth semester cohorts. At the time of submission of this paper, the engineering college has descriptive statistical data and is working with various statisticians to have a more in-depth and detailed analysis of the sample group of students’ achievement on the three exams. The overall objective of including standardized exams in the assessment model is to identify more precisely the least developed SOs in order to define and implement educational strategies necessary for students to achieve them in each engineering program.

Keywords: assessment, hard skills, soft skills, standardized tests

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Authors: Mohammed Aijaz

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In industries, to transfer fragile materials like glasses, a holding, lifting, and manipulation system are required. In this report, we designed and analysed a suction cup holding, lifting, and manipulation system that is attached to a head plate and must be able to grip/hold securely, the largest glass panel with 3m x 2.5m x 20mm thick with a mass of 115 kg. The system is able to rotate the panel through 180 degrees in the X, Y, and Z axis in any direction from the outer reach of the robotic arm. The structural analysis is performed to verify the structural strength of the suction cup’s head plate system.

Keywords: designing, mechanical, engineering, suction

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Authors: Rodrigo S. Piera, Jailson Sales Ara´ujo, Gabriela B. Lemos, Matthew B. Weiss, John B. DeBrota, Gabriel H. Aguilar, Jacques L. Pienaar

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The Born rule was historically viewed as an independent axiom of quantum mechanics until Gleason derived it in 1957 by assuming the Hilbert space structure of quantum measurements [1]. In subsequent decades there have been diverse proposals to derive the Born rule starting from even more basic assumptions [2]. In this work, we demonstrate that a simple reinforcement-learning algorithm, having no pre-programmed assumptions about quantum theory, will nevertheless converge to a behaviour pattern that accords with the Born rule, when tasked with predicting the output of a quantum optical implementation of a symmetric informationally-complete measurement (SIC). Our findings support a hypothesis due to QBism (the subjective Bayesian approach to quantum theory), which states that the Born rule can be thought of as a normative rule for making decisions in a quantum world [3].

Keywords: quantum Bayesianism, quantum theory, quantum information, quantum measurement

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Authors: Salsabila Meutia Meutia

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Indonesia as one of the countries that agreed to SDG's must commit to achieve this SDG's goal until the deadline of 2030. The government has tried hard to realize all the goals in the SDG’s, but there is still something that has not been achieved, especially the goal in number 4 which is to ensure that every human being has a decent and inclusive education and encourages lifelong learning opportunities for everyone. Teenagers who are the golden generation for Indonesia are starting to feel dependent on Youtube. The addictive virus of teenagers about using YouTube is both good news and bad news for the sustainability of government programs in achieving goals in SDG’s, especially in term of education. One popular YouTube channel among high school teenagers is Nihongo Mantappu which has 1.8 million followers. This channel contains interesting but quality content that can have a positive influence for the audience. This research was conducted to determine the effectiveness of the Nihongo Mantappu channel on Youtube as a means of fostering enthusiasm and awareness of learning in tenth graders of SMA Muhammadiyah 10 GKB, as well as how it affected in achieving quality educational goals as an effort to succeed in the Sustainable Development Goals of 2030. The objectives of this study were carried out with distributing questionnaires to tenth graders of SMA Muhammadiyah 10 GKB and observing objects in the real life. Then the data obtained are analyzed and described properly so that this research is a descriptive study. The results of the study mentioned that YouTube as one of the websites for viewing and sharing videos is a very effective media for disseminating information, especially among teenagers. The Nihongo Mantappu channel is also considered to be a very effective channel in building enthusiasm and awareness of learning in tenth graders of SMA Muhammadiyah 10 GKB. Students as the main subject of education have a great influence on the achievement of one of SDG’s fourth goals, named quality education. Students who are always on fire in the spirit and awareness of learning will greatly help the achievement of quality education goals in the Sustainable Development Goals by 2030.

Keywords: Youtube, Nihongo, Mantappu, SDG's

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Authors: Yaojun Wang, Yaoqing Wang

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Stock selection is an important decision-making problem. Many machine learning and data mining technologies are employed to build automatic stock-selection system. A profitable stock-selection system should consider the stock’s investment value and the market timing. In this paper, we present a hybrid system including both engage for stock selection. This system uses a case-based reasoning (CBR) model to execute the stock classification, uses a decision-tree model to help with market timing and stock selection. The experiments show that the performance of this hybrid system is better than that of other techniques regarding to the classification accuracy, the average return and the Sharpe ratio.

Keywords: case-based reasoning, decision tree, stock selection, machine learning

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Authors: Tamal Roy, Anuradha Bhat

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Cognitive abilities aid fishes in foraging, avoiding predators & locating mates. Factors like predation pressure & habitat complexity govern learning & memory in fishes. This study aims to compare spatial learning & memory across four natural populations of zebrafish. Zebrafish, a small cyprinid inhabits a diverse range of freshwater habitats & this makes it amenable to studies investigating role of native environment in spatial cognitive abilities. Four populations were collected across India from waterbodies with contrasting ecological conditions. Habitat complexity of the water-bodies was evaluated as a combination of channel substrate diversity and diversity of vegetation. Experiments were conducted on populations under controlled laboratory conditions. A square shaped spatial testing arena (maze) was constructed for testing the performance of adult zebrafish. The square tank consisted of an inner square shaped layer with the edges connected to the diagonal ends of the tank-walls by connections thereby forming four separate chambers. Each of the four chambers had a main door in the centre. Each chamber had three sections separated by two windows. A removable coloured window-pane (red, yellow, green or blue) identified each main door. A food reward associated with an artificial plant was always placed inside the left-hand section of the red-door chamber. The position of food-reward and plant within the red-door chamber was fixed. A test fish would have to explore the maze by taking turns and locate the food inside the right-side section of the red-door chamber. Fishes were sorted from each population stock and kept individually in separate containers for identification. At a time, a test fish was released into the arena and allowed 20 minutes to explore in order to find the food-reward. In this way, individual fishes were trained through the maze to locate the food reward for eight consecutive days. The position of red door, with the plant and the reward, was shuffled every day. Following training, an intermission of four days was given during which the fishes were not subjected to trials. Post-intermission, the fishes were re-tested on the 13th day following the same protocol for their ability to remember the learnt task. Exploratory tendencies and latency of individuals to explore on 1st day of training, performance time across trials, and number of mistakes made each day were recorded. Additionally, mechanism used by individuals to solve the maze each day was analyzed across populations. Fishes could be expected to use algorithm (sequence of turns) or associative cues in locating the food reward. Individuals of populations did not differ significantly in latencies and tendencies to explore. No relationship was found between exploration and learning across populations. High habitat-complexity populations had higher rates of learning & stronger memory while low habitat-complexity populations had lower rates of learning and much reduced abilities to remember. High habitat-complexity populations used associative cues more than algorithm for learning and remembering while low habitat-complexity populations used both equally. The study, therefore, helped understand the role of natural ecology in explaining variations in spatial learning abilities across populations.

Keywords: algorithm, associative cue, habitat complexity, population, spatial learning

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Authors: Monia Hejaiej

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The fable has lent itself to memorable imitations and reinventions. The writing of fables, in prose and verse, was widely cultivated not only in pre-Islamic Arabia but also in the middle ages, reaching its culmination with the Egyptian poet and man of letters Ahmad Shawqī (1989-1932), who revived the ancient tradition, a relatively minor and unexploited genre in the modern era, and re-wrote rimed fables with an Arab Islamic flavor, articulating a set of modern ethico-political concepts and sensibilities such as a belief in good judgment in governance, individual liberty, democracy, a sense of the brotherhood of man and justice. This essay aims to restore the 20th Century poet to his rightful place in the international pantheon of literary achievement, and offers an examination of the Arabian fabulist tradition as it appears in Arabic literature, and a treatment of this genre re-visiting a few representative samples of Ahmad Shawqī collection of fables and their implications for contemporary politics in the Middle East.

Keywords: fable, politcs, governace, democracy, ethics of care

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Authors: Yelena Mazour-Matusevich, Jean-Robert Ancheta

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This study is based on more than fifteen years of experience of teaching a foreign language, in my case French, to the English-speaking students. It represents a qualitative research on foreign language learners’ reaction and their gains in terms of vocabulary and listening comprehension through repeatedly viewing foreign feature films with the original sountrack but without English subtitles. The initial idea emerged upon realization that the first challenge faced by my students when they find themselves in a francophone environment has been their lack of listening comprehension. Their inability to understand colloquial speech affects not only their academic performance, but their psychological health as well. To remedy this problem, I have designed and applied for many years my own teaching method based on one particular French film, exceptionally suited, for the reasons described in detail in the paper, for the intermediate-advanced level foreign language learners. This project, conducted together with my undergraduate assistant and mentoree J-R Ancheta, aims at showing how the paralinguistic features, such as characters’ facial expressions, settings, music, historical background, images provided before the actual viewing, etc., offer crucial support and enhance students’ listening comprehension. The study, based on students’ interviews, also offers special pedagogical techniques, such as ‘anticipatory’ vocabulary lists and exercises, drills, quizzes and composition topics that have proven to boost students’ performance. For this study, only the listening proficiency and vocabulary gains of the interviewed participants were assessed.

Keywords: comprehension, film, listening, subtitles, vocabulary

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Authors: B. R. Phanikumar, Sana Suri

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Expansive soils swell when they absorb water and shrink when water evaporates from them. Hence, lightly loaded civil engineering structures found in these soils are subjected to severe distress. Therefore, there is a need to ameliorate or improve these swelling soils through some innovative methods. This paper discusses chemical stabilisation of expansive soils, a technique in which chemical reagents such as lime and calcium chloride are added to expansive soils to reduce the volumetric changes occurring in expansive soils and also to improve their engineering behaviour.

Keywords: expansive soils, swelling, shrinkage, amelioration, lime, calcium chloride

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Authors: Eunice H. Li

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This paper discusses and analyses a small portion of the literature that has been reviewed for research work in Distance Education (DE) pedagogies that I am currently undertaking. It begins by presenting a brief overview of Taylor's (2001) five-generation models of Distance Education. The focus of the discussion will be on the 5th generation, Intelligent Flexible Learning Model. For this generation, educational and other institutions make portal access and interactive multi-media (IMM) an integral part of their operations. The paper then takes a brief look at current trends in technologies – for example smart-watch wearable technology such as Apple Watch. The emergent trends in technologies carry many new features. These are compared to former DE generational features. Also compared is the time span that has elapsed between the generations that are referred to in Taylor's model. This paper is a work in progress. The paper therefore welcome new insights, comparisons and critique of the issues discussed.

Keywords: distance education, e-learning technologies, pedagogy, generational models

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Authors: Rita Alfattal, Maryam Alfarhan, Adeeb M. Algaith, Buthaina Albash, Reem M. Elshafie, Asma Alshammari, Ahmad Alahmad, Fatima Dashti, Rasha Alsafi, Hind Alsharhan

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Defects of respiratory chain complex III (CIII) result in characteristic but rare mitochondrial disorders associated with distinct neuroradiological findings. The underlying molecular defects affecting mitochondrial CIII assembly factors are few and yet to be identified. LYRM7 assembly factor is required for proper CIII assembly where it acts as a chaperone for the Rieske iron‐sulfur (UQCRFS1) protein in the mitochondrial matrix and stabilizing it. We present here the seventeenth individual with LYRM7-associated mitochondrial leukoencephalopathy harboring a previously reported rare pathogenic homozygous LYRM 7 variant, c.2T>C, (p.Met1?). Like previously reported individuals, our 4-year-old male proband presented with recurrent metabolic and lactic acidosis, encephalopathy, and myopathy. Further, he has additional, previously unreported features, including an acute stroke like episode with bilateral central blindness and optic neuropathy, recurrent hyperglycemia and hypertension associated with metabolic crisis. However, he has no signs of psychomotor regression. He has been stable clinically with residual left-sided reduced visual acuity and amblyopia, and no more metabolic crises for 2-year-period while on the mitochondrial cocktail. Although the reported brain MRI findings in other affected individuals are homogenous, it is slightly different in our index, revealing evidence of bilateral almost symmetric multifocal periventricular T2 hyperintensities with hyperintensities of the optic nerves, optic chiasm, and corona radiata but with no cavitation or cystic changes. This report describes new clinical and radiological findings of LYRM7-associated disease. The report also summarizes the clinical and molecular data of previously reported individuals describing the full phenotypic spectrum.

Keywords: LYRM7 gene defect, mitochondrial disease, , lactic acidosis, , genetic disorder

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Authors: Zory Marantz

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Hybrid flexible (HyFlex) is a pedagogical methodology whereby an instructor delivers content in three modalities, i.e. live in-person (LIP), live online synchronous (LOS), and non-live online asynchronous (nLOaS). HyFlex is focused on providing the largest level of flexibility needed to achieve a cohesive environment across all modalities and incorporating four basic principles – learner’s choice, reusability, accessibility, and equivalency. Much literature has focused on the advantages of this methodology in providing students with the flexibility to choose their learning modality as best suits their schedules and learning styles. Initially geared toward graduate-level students, the concept has been applied to undergraduate studies, particularly during our national pedagogical response to the COVID19 pandemic. There is still little literature about the practicality and feasibility of HyFlex for hardware laboratory intensive engineering technology programs, particularly in dense, urban commuter institutions of higher learning. During a semester of engineering, a lab-based course was taught in the HyFlex modality, and students were asked to complete a survey about their experience. The data demonstrated that there is no single mode that is preferred by a majority of students and the usefulness of any modality is limited to how familiar the student and instructor are with the technology being applied. The technology is only as effective as our understanding and comfort with its functionality. For HyFlex to succeed in its implementation in an engineering technology environment within an urban commuter institution, faculty and students must be properly introduced to the technology being used.

Keywords: education, HyFlex, technology, urban, commuter, pedagogy

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Authors: Narash Narasimman, Calvin Leong Jia Jun, Raksha Karthik, Paul Englert

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Background: Project Grit, a 12-week youth resilience program implemented by Impart and Spartans Boxing Club, aimed to help at-risk adolescents develop resilience through psychoeducation and mental health techniques for dealing with everyday stressors and adversity. The programme consists of two parts-1.5 hours of group therapy followed by 1 hour of boxing. Due to the novelty of the study, 6 male participants, aged 13 to 18, were recruited to participate in the study. Aim: This case study aims to examine the effectiveness of Project Grit in building resilience among at-risk adolescents. Methods: A case study design was employed to capture the complexity and uniqueness of the intervention, without oversimplifying or generalizing it. A 15-year-old male participant with a history of behavioural challenges, delinquency and gang involvement was selected for the study. Teacher, parent and child versions of the Strengths and Difficulties Questionnaire (SDQ) were administered to the facilitators, parents and participants respectively before and after the programme. Relevant themes from the qualitative interviews will be discussed. Results: Scores from all raters revealed improvements in most domains of the SDQ. Total difficulties scores across all raters improved from “very high” to “close to average”. High interrater reliability was observed (κ= .81). The participant reported learning methods to effectively deal with his everyday concerns using healthy coping strategies, developing a supportive social network, and building on his self efficacy. Themes from the subject’s report concurred with the improvement in SDQ scores. Conclusions: The findings suggest that Project Grit is a promising intervention for promoting resilience among at-risk adolescents. The teleological behaviourism framework and the combination of sports engagement and future orientation may be particularly effective in fostering resilience among this population. Further studies need to be conducted with a larger sample size to further validate the effectiveness of Project Grit.

Keywords: resilience, project grit, adolescents, at-risk, boxing, future orientation

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Authors: Mehran Asadi, Afrand Agah

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In data mining, partitioning is used as a fundamental tool for classification. With the help of partitioning, we study the structure of data, which allows us to envision decision rules, which can be applied to classification trees. In this research, we used online social network dataset and all of its attributes (e.g., Node features, labels, etc.) to determine what constitutes an above average chance of being a divergent node. We used the R statistical computing language to conduct the analyses in this report. The data were found on the UC Irvine Machine Learning Repository. This research introduces the basic concepts of classification in online social networks. In this work, we utilize overfitting and describe different approaches for evaluation and performance comparison of different classification methods. In classification, the main objective is to categorize different items and assign them into different groups based on their properties and similarities. In data mining, recursive partitioning is being utilized to probe the structure of a data set, which allow us to envision decision rules and apply them to classify data into several groups. Estimating densities is hard, especially in high dimensions, with limited data. Of course, we do not know the densities, but we could estimate them using classical techniques. First, we calculated the correlation matrix of the dataset to see if any predictors are highly correlated with one another. By calculating the correlation coefficients for the predictor variables, we see that density is strongly correlated with transitivity. We initialized a data frame to easily compare the quality of the result classification methods and utilized decision trees (with k-fold cross validation to prune the tree). The method performed on this dataset is decision trees. Decision tree is a non-parametric classification method, which uses a set of rules to predict that each observation belongs to the most commonly occurring class label of the training data. Our method aggregates many decision trees to create an optimized model that is not susceptible to overfitting. When using a decision tree, however, it is important to use cross-validation to prune the tree in order to narrow it down to the most important variables.

Keywords: online social networks, data mining, social cloud computing, interaction and collaboration

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Authors: Ons Slimene, Aroua Taamallah, Maha Khemaja

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In recent years, human activity recognition (HAR) has been a key area of research due to its diverse applications. It has garnered increasing attention in the field of computer vision. HAR plays an important role in people’s daily lives as it has the ability to learn advanced knowledge about human activities from data. In HAR, activities are usually represented by exploiting different types of sensors, such as embedded sensors or visual sensors. However, these sensors have limitations, such as local obstacles, image-related obstacles, sensor unreliability, and consumer concerns. Recently, several deep learning-based approaches have been proposed for HAR and these approaches are classified into two categories based on the type of data used: vision-based approaches and sensor-based approaches. This research paper highlights the importance of multimodal data fusion from skeleton data obtained from videos and data generated by embedded sensors using deep neural networks for achieving HAR. We propose a deep multimodal fusion network based on a twostream architecture. These two streams use the Convolutional Neural Network combined with the Bidirectional LSTM (CNN BILSTM) to process skeleton data and data generated by embedded sensors and the fusion at the feature level is considered. The proposed model was evaluated on a public OPPORTUNITY++ dataset and produced a accuracy of 96.77%.

Keywords: human activity recognition, action recognition, sensors, vision, human-centric sensing, deep learning, context-awareness

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Authors: Shyam lamsal

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Introduction: Karnali Academy of Health Sciences (KAHS) has been established in 2011, by an Act of parliament of Nepal, in Jumla, to provide health services in easy way in backward areas, to produce skilled health professionals & conduct research. The backward areas mentioned in act of KAHS are Humla, Jumla, Kalikot, Dolpa, Mugu districts of Karnali zone, Jajarkot district of Bheri zone & Bajura, Baghang & Achham districts of Seti zone in Nepal occupying around 25 % of the total national geography. Backward area of Nepal is specific to having worst health indicators with life expectancy (47 years), HDI (0.35), Literacy rate (58%), global acute malnutrition (13%), crude birth rate (33.6), crude death rate (9.6), Total fertility rate (4.2), infant mortality rate (61.5 per 1000 live births), under five mortality rate (59 per 1000 live births) and maternal mortality ratio (400 per 1000 live births). History of health facilities in backward region: All the nine districts of this region have a district hospital with very few grass root level health manpower. Government of Nepal regularly deploys one or two medical officers to each district who generally are not regular to their care. Jumla district itself was having one medical officer before the establishment of KAHS. Development activities: Establishment of 100 bedded specialty teaching hospital with 10 medical officers and five specialists, accredited its own nursing school for running diploma nursing programme, started “Karnali health survey” which covers 55 thousand households of backward region, started community care and school health camps, planning phase completed for 300 bedded teaching hospital construction. Future Plan: Expansion of the teaching hospital to 300 beds within 3 years, start health assistant and bachelor midwifery course in 2015 AD, start bachelor in laboratory and bachelor in public health course in 2016 AD and start MBBS course in 2018 AD. Deploy the medical officers and family physicians to all the district hospitals within 3 years. KAHS provides reservation up to 45% students from backward region with the commitment to stay for at least five years of their service period. Conclusion: This institution may be the example for the rest of the world in providing nursing care, education in remote areas as well as the best model for nursing manpower retention in remote areas of developing countries.

Keywords: backward area, nursing school

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Authors: Harshit Garg, Shakshi Gupta

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One of the major problems in today’s world is the growing pollution. The cause for all environmental problems is the increasing pollution rate. Looking upon the statistics, one can find out that most of the pollution is caused by the vehicular pollution which is more than 70 % of the total pollution, effecting the environment as well as human health proportionally. One is aware of the fact that vehicles run on roads so why not having the roads which could adsorb that pollution, not only once but a number of times. Every problem has a solution which can be solved by the state of art of technology, that is one can use the innovative ideas and thoughts to make technology as a solution to the problem of vehicular pollution on roads. Solving the problem up to a certain limit/ percentage can be formulated into a new term called ECO ROADS.

Keywords: environment, pollution, roads, sustainibility

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Authors: Sabine A. Zauchner-Studnicka

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As the term indicates, reverse-mentoring flips the classical roles of mentoring: In school, students take over the role of mentors for adults, i.e. teachers or parents. Originally reverse-mentoring stems from US enterprises, which implemented this innovative method in order to benefit from the resources of skilled younger employees for the enhancement of IT competences of senior colleagues. However, reverse-mentoring in schools worldwide is rare. Based on empirical studies and theoretical approaches, in this article an implementation model for reverse-mentoring is developed in order to bring the significant potential reverse-mentoring has for education into practice.

Keywords: reverse-mentoring, innovation in education, implementation model, school education

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Authors: Jill Steel

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Introduction: Animal-assisted learning (AAL) interventions are increasing exponentially, yet a paucity of quality research in the field exists. The aim of this study was to evaluate how the promotion of emotional wellbeing, through AAL, in this case, a dog, may support children’s engagement with reading in a Primary 1 classroom. Research indicates that dogs can provide emotional support to children; by forming a trusting attachment with a non-critical ‘friend’ who confers unconditional positive regard on the child, confidence may be boosted and anxiety reduced. By promoting emotional wellbeing through interactions with the dog, it is hoped that children begin to associate reading with feelings of wellbeing, which then results in increased engagement with reading. Methodology: A review of the literature was conducted. The relationship between emotional wellbeing and learning was explored, followed by an examination of the literature relating to Animal-Assisted Therapy and AAL. Scottish educational policy and legislation were analysed to establish the extent to which AAL might be suitable for the Scottish pedagogical context. An empirical study was conducted in a mainstream Primary 1 classroom over a four-week period. An inclusive approach was adopted whereby all children that wanted to interact with the dog were given the opportunity to do so, and all 25 children subsequently chose to participate. Children were not withdrawn from the classroom. Primary methods included interviews, observations, and questionnaires. Three focus children were selected for closer study. Main Results: Results were remarkably close to previous research and literature. Children’s emotional wellbeing was boosted, and engagement in reading improved. Principal Conclusions and Implications for Field: It was concluded that AAL could support emotional wellbeing and, in turn, promote children’s engagement with reading. The main limitation of the study was its short-term nature, and a longer randomised controlled trial with a larger sample, currently being undertaken by the author, would provide a fuller answer to the research question. Barriers to AAL include health and safety concerns and steps to ensure the welfare of the dog.

Keywords: animal-assisted learning, emotional wellbeing, reading, reading to dogs

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Authors: Eva Tolmeijer, Emmanuelle Peters, Veena Kumari, Liam Mason

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Cognitive behavioral therapy for psychosis (CBTp) is effective in many but not all patients, making it important to better understand the factors that determine treatment outcomes. To date, no studies have examined whether neuroimaging can make clinically useful predictions about who will respond to CBTp. To this end, we used machine learning methods that make predictions about symptom improvement at the individual patient level. Prior to receiving CBTp, 22 patients with a diagnosis of schizophrenia completed a social-affective processing task during functional MRI. Multivariate pattern analysis assessed whether treatment response could be predicted by brain activation responses to facial affect that was either socially threatening or prosocial. The resulting models did significantly predict symptom improvement, with distinct multivariate signatures predicting psychotic (r=0.54, p=0.01) and affective (r=0.32, p=0.05) symptoms. Psychotic symptom improvement was accurately predicted from relatively focal threat-related activation across hippocampal, occipital, and temporal regions; affective symptom improvement was predicted by a more dispersed profile of responses to prosocial affect. These findings enrich our understanding of the neurobiological underpinning of treatment response. This study provides a foundation that will hopefully lead to greater precision and tailoring of the interventions offered to patients.

Keywords: cognitive behavioral therapy, machine learning, psychosis, schizophrenia

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Authors: Valeria Cotza

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School drop-out is a multifactorial phenomenon that in Italy concerns all those underage students who, at different school stages (up to 16 years old) or training (up to 18 years old), manifest educational difficulties from dropping out of compulsory education without obtaining a qualification to repetition rates and absenteeism. From the 1980s to the 2000s, there was a progressive attenuation of the economic and social model towards a multifactorial reading of the phenomenon, and the European Commission noted the importance of learning about the phenomenon through approaches able to integrate large-scale quantitative surveys with qualitative analyses. It is not a matter of identifying the contextual factors affecting the phenomenon but problematising them by means of systemic and comprehensive in-depth analysis. So, a privileged point of observation and field of intervention are those schools that propose alternative models of teaching and learning to the traditional ones, such as popular and second-chance schools. Alternative schools and interventions grew in these years in Europe as well as in the US and Latin America, working in the direction of greater equity to create the conditions (often absent in conventional schools) for everyone to achieve educational goals. Against extensive Anglo-Saxon and US literature on this topic, there is yet no unambiguous definition of alternative education, especially in Europe, where second-chance education has been most studied. There is little literature on a second chance in Italy and almost none on alternative education (with the exception of method schools, to which in Italy the concept of “alternative” is linked). This research aims to fill the gap by systematically surveying the alternative interventions in the area and beginning to explore some models of popular and second-chance schools and experiences through a mixed methods approach. So, the main research objectives concern the spread of alternative education in the Lombardy region, the main characteristics of these schools and interventions, and their effectiveness in terms of students’ well-being and school results. This paper seeks to answer the first point by presenting the preliminary results of the first phase of the project dedicated to mapping. Through the Google Forms platform, a questionnaire is being distributed to all schools in Lombardy and some schools in the rest of Italy to map the presence of alternative schools and interventions and their main characteristics. The distribution is also taking place thanks to the support of the Milan Territorial and Lombardy Regional School Offices. Moreover, other social realities outside the school system (such as cooperatives and cultural associations) can be questioned. The schools and other realities to be questioned outside Lombardy will also be identified with the support of INDIRE (Istituto Nazionale per Documentazione, Innovazione e Ricerca Educativa, “National Institute for Documentation, Innovation and Educational Research”) and based on existing literature and the indicators of “Futura” Plan of the PNRR (Piano Nazionale di Ripresa e Resilienza, “National Recovery and Resilience Plan”). Mapping will be crucial and functional for the subsequent qualitative and quantitative phase, which will make use of statistical analysis and constructivist grounded theory.

Keywords: school drop-out, alternative education, popular and second-chance schools, map

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Authors: Anshika Kankane, Dongshik Kang

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Marine debris has a significant influence on coastal environments, damaging biodiversity, and causing loss and damage to marine and ocean sector. A functional cost-effective and automatic approach has been used to look up at this problem. Computer vision combined with a deep learning-based model is being proposed to identify and categorize marine debris of seven kinds on different beach locations of Japan. This research compares state-of-the-art deep learning models with a suggested model architecture that is utilized as a feature extractor for debris categorization. The model is being proposed to detect seven categories of litter using a manually constructed debris dataset, with the help of Mask R-CNN for instance segmentation and a shape matching network called HOGShape, which can then be cleaned on time by clean-up organizations using warning notifications of the system. The manually constructed dataset for this system is created by annotating the images taken by fixed KaKaXi camera using CVAT annotation tool with seven kinds of category labels. A pre-trained HOG feature extractor on LIBSVM is being used along with multiple templates matching on HOG maps of images and HOG maps of templates to improve the predicted masked images obtained via Mask R-CNN training. This system intends to timely alert the cleanup organizations with the warning notifications using live recorded beach debris data. The suggested network results in the improvement of misclassified debris masks of debris objects with different illuminations, shapes, viewpoints and litter with occlusions which have vague visibility.

Keywords: computer vision, debris, deep learning, fixed live camera images, histogram of gradients feature extractor, instance segmentation, manually annotated dataset, multiple template matching

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Authors: Dilek Bilgiç

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Configuration Management (CM) is a discipline assuring the consistency between product information the reality all along the product lifecycle. Although the extensive benefits of this discipline, such as the direct impact on increasing return on investment, reducing lifecycle costs, are realized by most organizations. It is worth evaluating that CM functions might be successfully implemented in some organized anarchies. This paper investigates how to manage ambiguity in CM processes as an opportunity within an environment that has different types of complexities and choice arenas. It is not explained how to establish a configuration management organization in a company; more specifically, it is analyzed how to apply configuration management processes when different types of streams exist. From planning to audit, all the CM functions may provide different organization learning opportunities when those applied with the right leadership methods.

Keywords: configuration management, leadership, organizational analysis, organized anarchy, cm process, organizational learning, organizational maturity, configuration status accounting, leading innovation, change management

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Authors: Bruno Trstenjak, Dzenana Donko

Abstract:

Data mining and classification of objects is the process of data analysis, using various machine learning techniques, which is used today in various fields of research. This paper presents a concept of hybrid classification model improved with the expert knowledge. The hybrid model in its algorithm has integrated several machine learning techniques (Information Gain, K-means, and Case-Based Reasoning) and the expert’s knowledge into one. The knowledge of experts is used to determine the importance of features. The paper presents the model algorithm and the results of the case study in which the emphasis was put on achieving the maximum classification accuracy without reducing the number of features.

Keywords: case based reasoning, classification, expert's knowledge, hybrid model

Procedia PDF Downloads 357