Search results for: learning orientation
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7887

Search results for: learning orientation

2277 The Challenge of Teaching French as a Foreign Language in a Multilingual Community

Authors: Carol C. Opara, Olukemi E. Adetuyi-Olu-Francis

Abstract:

The teaching of French language, like every other language, has its numerous challenges. A multilingual community, however, is a linguistic environment housing diverse languages, each with its peculiarity, both pros, and cones. A foreign language will have to strive hard for survival in an environment where various indigenous languages, as well as an established official language, exist. This study examined the challenges and prospects of the teaching of French as a foreign language in a multilingual community. A 22-item questionnaire was used to elicit information from 40 Nigerian Secondary school teachers of French. One of the findings of this study showed that the teachers of the French language are not motivated. Also, the linguistic environment is not favourable for the teaching and learning of French language in Nigeria. One of the recommendations was that training and re-training of teachers of French should be of utmost importance to the Nigerian Federal Ministry of Education.

Keywords: challenges, french as foreign language, multilingual community, teaching

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2276 ChatGPT Performs at the Level of a Third-Year Orthopaedic Surgery Resident on the Orthopaedic In-training Examination

Authors: Diane Ghanem, Oscar Covarrubias, Michael Raad, Dawn LaPorte, Babar Shafiq

Abstract:

Introduction: Standardized exams have long been considered a cornerstone in measuring cognitive competency and academic achievement. Their fixed nature and predetermined scoring methods offer a consistent yardstick for gauging intellectual acumen across diverse demographics. Consequently, the performance of artificial intelligence (AI) in this context presents a rich, yet unexplored terrain for quantifying AI's understanding of complex cognitive tasks and simulating human-like problem-solving skills. Publicly available AI language models such as ChatGPT have demonstrated utility in text generation and even problem-solving when provided with clear instructions. Amidst this transformative shift, the aim of this study is to assess ChatGPT’s performance on the orthopaedic surgery in-training examination (OITE). Methods: All 213 OITE 2021 web-based questions were retrieved from the AAOS-ResStudy website. Two independent reviewers copied and pasted the questions and response options into ChatGPT Plus (version 4.0) and recorded the generated answers. All media-containing questions were flagged and carefully examined. Twelve OITE media-containing questions that relied purely on images (clinical pictures, radiographs, MRIs, CT scans) and could not be rationalized from the clinical presentation were excluded. Cohen’s Kappa coefficient was used to examine the agreement of ChatGPT-generated responses between reviewers. Descriptive statistics were used to summarize the performance (% correct) of ChatGPT Plus. The 2021 norm table was used to compare ChatGPT Plus’ performance on the OITE to national orthopaedic surgery residents in that same year. Results: A total of 201 were evaluated by ChatGPT Plus. Excellent agreement was observed between raters for the 201 ChatGPT-generated responses, with a Cohen’s Kappa coefficient of 0.947. 45.8% (92/201) were media-containing questions. ChatGPT had an average overall score of 61.2% (123/201). Its score was 64.2% (70/109) on non-media questions. When compared to the performance of all national orthopaedic surgery residents in 2021, ChatGPT Plus performed at the level of an average PGY3. Discussion: ChatGPT Plus is able to pass the OITE with a satisfactory overall score of 61.2%, ranking at the level of third-year orthopaedic surgery residents. More importantly, it provided logical reasoning and justifications that may help residents grasp evidence-based information and improve their understanding of OITE cases and general orthopaedic principles. With further improvements, AI language models, such as ChatGPT, may become valuable interactive learning tools in resident education, although further studies are still needed to examine their efficacy and impact on long-term learning and OITE/ABOS performance.

Keywords: artificial intelligence, ChatGPT, orthopaedic in-training examination, OITE, orthopedic surgery, standardized testing

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2275 Psychometric Examination of the QUEST-25: An Online Assessment of Intellectual Curiosity and Scientific Epistemology

Authors: Matthew J. Zagumny

Abstract:

The current study reports an examination of the QUEST-25 (Q-Assessment of Undergraduate Epistemology and Scientific Thinking) online version for assessing the dispositional attitudes toward scientific thinking and intellectual curiosity among undergraduate students. The QUEST-25 consists of scientific thinking (SIQ-25) and intellectual curiosity (ICIQ-25), which were correlated in hypothesized directions with the Religious Commitment Inventory, Curiosity and Exploration Inventory, Belief in Science scale, and measures of academic self-efficacy. Additionally, concurrent validity was established by the resulting significant differences between those identifying the centrality of religious belief in their lives and those who do not self-identify as being guided daily by religious beliefs. This study demonstrates the utility of the QUEST-25 for research, evaluation, and theory development.

Keywords: guided-inquiry learning, intellectual curiosity, psychometric assessment, scientific thinking

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2274 Influence of Structured Capillary-Porous Coatings on Cryogenic Quenching Efficiency

Authors: Irina P. Starodubtseva, Aleksandr N. Pavlenko

Abstract:

Quenching is a term generally accepted for the process of rapid cooling of a solid that is overheated above the thermodynamic limit of the liquid superheat. The main objective of many previous studies on quenching is to find a way to reduce the total time of the transient process. Computational experiments were performed to simulate quenching by a falling liquid nitrogen film of an extremely overheated vertical copper plate with a structured capillary-porous coating. The coating was produced by directed plasma spraying. Due to the complexities in physical pattern of quenching from chaotic processes to phase transition, the mechanism of heat transfer during quenching is still not sufficiently understood. To our best knowledge, no information exists on when and how the first stable liquid-solid contact occurs and how the local contact area begins to expand. Here we have more models and hypotheses than authentically established facts. The peculiarities of the quench front dynamics and heat transfer in the transient process are studied. The created numerical model determines the quench front velocity and the temperature fields in the heater, varying in space and time. The dynamic pattern of the running quench front obtained numerically satisfactorily correlates with the pattern observed in experiments. Capillary-porous coatings with straight and reverse orientation of crests are investigated. The results show that the cooling rate is influenced by thermal properties of the coating as well as the structure and geometry of the protrusions. The presence of capillary-porous coating significantly affects the dynamics of quenching and reduces the total quenching time more than threefold. This effect is due to the fact that the initialization of a quench front on a plate with a capillary-porous coating occurs at a temperature significantly higher than the thermodynamic limit of the liquid superheat, when a stable solid-liquid contact is thermodynamically impossible. Waves present on the liquid-vapor interface and protrusions on the complex micro-structured surface cause destabilization of the vapor film and the appearance of local liquid-solid micro-contacts even though the average integral surface temperature is much higher than the liquid superheat limit. The reliability of the results is confirmed by direct comparison with experimental data on the quench front velocity, the quench front geometry, and the surface temperature change over time. Knowledge of the quench front velocity and total time of transition process is required for solving practically important problems of nuclear reactors safety.

Keywords: capillary-porous coating, heat transfer, Leidenfrost phenomenon, numerical simulation, quenching

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2273 Comprehensive Studio Tables: Improving Performance and Quality of Student's Work in Architecture Studio

Authors: Maryam Kalkatechi

Abstract:

Architecture students spent most of their qualitative time in studios during their years of study. The studio table’s importance as furniture in the studio is that it elevates the quality of the projects and positively influences the student’s productivity. This paper first describes the aspects considered in designing comprehensive studio table and later details on each aspect. Comprehensive studio tables are meant to transform the studio space to an efficient yet immense place of learning, collaboration, and participation. One aspect of these tables is that the surface transforms to a place of accommodation for design conversations, the other aspect of these tables is the efficient interactive platform of the tools. The discussion factors of the comprehensive studio include; the comprehensive studio setting of workspaces, the arrangement of the comprehensive studio tables, the collaboration aspects in the studio, the studio display and lightings shaped by the tables and lighting of the studio.

Keywords: studio tables, student performance, productivity, hologram, 3D printer

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2272 Evolution of Classroom Languaging over the Years: Prospects for Teaching Mathematics Differently

Authors: Jabulani Sibanda, Clemence Chikiwa

Abstract:

This paper traces diverse language practices representative of equally diverse conceptions of language. To be dynamic with languaging practices, one needs to appreciate nuanced languaging practices, their challenges, prospects, and opportunities. The paper presents what we envision as three major conceptions of language that give impetus to diverse language practices. It examines theoretical models of the bilingual mental lexicon and how they inform language practices. The paper explores classroom languaging practices that have been promulgated and experimented with. The paper advocates the deployment of multisensory semiotic systems to complement linguistic classroom communication and the acknowledgement of learners’ linguistic and semiotic resources as valid in the learning enterprise. It recommends the enactment of specific clauses on language in education policies and curriculum documents that empower classroom interactants to exercise discretion in languaging practices.

Keywords: languaging, monolingual, multilingual, semiotic and linguistic repertoire

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2271 Correlates of Pedagogic Malpractices

Authors: Chinaza Uleanya, Martin Duma, Bongani Gamede

Abstract:

The research investigated pedagogic malpractices by lecturers in sub-Sahara African universities. The population of the study consisted of undergraduates and lecturers in selected universities in Nigeria and South Africa. Mixed method approach was adopted for data collection. The sample population of the study was 480 undergraduate students and 16 lecturers. Questionnaires with 4 point Likert-scale were administered to 480 respondents while interviews were conducted with 6 lecturers. In addition, the teaching strategies of 10 lecturers were observed. Data analyses indicated that poor work environment demotivates lecturers and makes them involved in pedagogic malpractice which is one of the causes of learning challenges faced by undergraduates. The finding of the study also shows that pedagogic malpractice contributes to the high rate of dropout in sub-Sahara African universities. Based on the results, it was recommended that qualified lecturers be employed and given conducive environments to work.

Keywords: malpractice, pedagogy, pedagogic malpractice, correlates

Procedia PDF Downloads 282
2270 Models Development of Graphical Human Interface Using Fuzzy Logic

Authors: Érick Aragão Ribeiro, George André Pereira Thé, José Marques Soares

Abstract:

Graphical Human Interface, also known as supervision software, are increasingly present in industrial processes supported by Supervisory Control and Data Acquisition (SCADA) systems and so it is evident the need for qualified developers. In order to make engineering students able to produce high quality supervision software, method for the development must be created. In this paper we propose model, based on the international standards ISO/IEC 25010 and ISO/IEC 25040, for the development of graphical human interface. When compared with to other methods through experiments, the model here presented leads to improved quality indexes, therefore help guiding the decisions of programmers. Results show the efficiency of the models and the contribution to student learning. Students assessed the training they have received and considered it satisfactory.

Keywords: software development models, software quality, supervision software, fuzzy logic

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2269 eTransformation Framework for the Cognitive Systems

Authors: Ana Hol

Abstract:

Digital systems are in the cognitive wave of the eTransformations and are now extensively aimed at meeting the individuals’ demands, both those of customers requiring services and those of service providers. It is also apparent that successful future systems will not just simply open doors to the traditional owners/users to offer and receive services such as Uber for example does today, but will in the future require more customized and cognitively enabled infrastructures that will be responsive to the system user’s needs. To be able to identify what is required for such systems, this research reviews the historical and the current effects of the eTransformation process by studying: 1. eTransitions of company websites and mobile applications, 2. Emergence of new sheared economy business models as Uber and, 3. New requirements for demand driven, cognitive systems capable of learning and just in time decision making. Based on the analysis, this study proposes a Cognitive eTransformation Framework capable of guiding implementations of new responsive and user aware systems.

Keywords: system implementations, AI supported systems, cognitive systems, eTransformation

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2268 Effects of Teaching Strategies on Students Academic Achievement in Secondary Physics Education for Quality Assurance

Authors: Collins Molua

Abstract:

This paper investigated the effect of Teaching Strategies on Academic Achievement in Secondary Physics Education as a quality assurance process for the teaching and learning of the subject. Teaching strategies investigated were the interactive, independent and dependent strategies. Three null hypotheses were tested at p< 0.05 using one instrument, physics achievement test(PAT).The data were analyzed using analysis of covariance (ANCOVA).Results showed that teaching strategies have significant effect on students achievement; the joint effect of the teaching strategies was also significant on students achievement in Physics. The interactive teaching strategies was recommended for teaching the subject and the students should be exposed to practical, computer literacy to stimulate interest and curiosity to enhance quality.

Keywords: quality, assurance, secondary education, strategies, physics

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2267 Photoemission Momentum Microscopy of Graphene on Ir (111)

Authors: Anna V. Zaporozhchenko, Dmytro Kutnyakhov, Katherina Medjanik, Christian Tusche, Hans-Joachim Elmers, Olena Fedchenko, Sergey Chernov, Martin Ellguth, Sergej A. Nepijko, Gerd Schoenhense

Abstract:

Graphene reveals a unique electronic structure that predetermines many intriguing properties such as massless charge carriers, optical transparency and high velocity of fermions at the Fermi level, opening a wide horizon of future applications. Hence, a detailed investigation of the electronic structure of graphene is crucial. The method of choice is angular resolved photoelectron spectroscopy ARPES. Here we present experiments using time-of-flight (ToF) momentum microscopy, being an alternative way of ARPES using full-field imaging of the whole Brillouin zone (BZ) and simultaneous acquisition of up to several 100 energy slices. Unlike conventional ARPES, k-microscopy is not limited in simultaneous k-space access. We have recorded the whole first BZ of graphene on Ir(111) including all six Dirac cones. As excitation source we used synchrotron radiation from BESSY II (Berlin) at the U125-2 NIM, providing linearly polarized (both polarizations p- and s-) VUV radiation. The instrument uses a delay-line detector for single-particle detection up the 5 Mcps range and parallel energy detection via ToF recording. In this way, we gather a 3D data stack I(E,kx,ky) of the full valence electronic structure in approx. 20 mins. Band dispersion stacks were measured in the energy range of 14 eV up to 23 eV with steps of 1 eV. The linearly-dispersing graphene bands for all six K and K’ points were simultaneously recorded. We find clear features of hybridization with the substrate, in particular in the linear dichroism in the angular distribution (LDAD). Recording of the whole Brillouin zone of graphene/Ir(111) revealed new features. First, the intensity differences (i.e. the LDAD) are very sensitive to the interaction of graphene bands with substrate bands. Second, the dark corridors are investigated in detail for both, p- and s- polarized radiation. They appear as local distortions of photoelectron current distribution and are induced by quantum mechanical interference of graphene sublattices. The dark corridors are located in different areas of the 6 Dirac cones and show chirality behaviour with a mirror plane along vertical axis. Moreover, two out of six show an oval shape while the rest are more circular. It clearly indicates orientation dependence with respect to E vector of incident light. Third, a pattern of faint but very sharp lines is visible at energies around 22eV that strongly remind on Kikuchi lines in diffraction. In conclusion, the simultaneous study of all six Dirac cones is crucial for a complete understanding of dichroism phenomena and the dark corridor.

Keywords: band structure, graphene, momentum microscopy, LDAD

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2266 Development of the Academic Model to Predict Student Success at VUT-FSASEC Using Decision Trees

Authors: Langa Hendrick Musawenkosi, Twala Bhekisipho

Abstract:

The success or failure of students is a concern for every academic institution, college, university, governments and students themselves. Several approaches have been researched to address this concern. In this paper, a view is held that when a student enters a university or college or an academic institution, he or she enters an academic environment. The academic environment is unique concept used to develop the solution for making predictions effectively. This paper presents a model to determine the propensity of a student to succeed or fail in the French South African Schneider Electric Education Center (FSASEC) at the Vaal University of Technology (VUT). The Decision Tree algorithm is used to implement the model at FSASEC.

Keywords: FSASEC, academic environment model, decision trees, k-nearest neighbor, machine learning, popularity index, support vector machine

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2265 Online Authenticity Verification of a Biometric Signature Using Dynamic Time Warping Method and Neural Networks

Authors: Gałka Aleksandra, Jelińska Justyna, Masiak Albert, Walentukiewicz Krzysztof

Abstract:

An offline signature is well-known however not the safest way to verify identity. Nowadays, to ensure proper authentication, i.e. in banking systems, multimodal verification is more widely used. In this paper the online signature analysis based on dynamic time warping (DTW) coupled with machine learning approaches has been presented. In our research signatures made with biometric pens were gathered. Signature features as well as their forgeries have been described. For verification of authenticity various methods were used including convolutional neural networks using DTW matrix and multilayer perceptron using sums of DTW matrix paths. System efficiency has been evaluated on signatures and signature forgeries collected on the same day. Results are presented and discussed in this paper.

Keywords: dynamic time warping, handwritten signature verification, feature-based recognition, online signature

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2264 BART Matching Method: Using Bayesian Additive Regression Tree for Data Matching

Authors: Gianna Zou

Abstract:

Propensity score matching (PSM), introduced by Paul R. Rosenbaum and Donald Rubin in 1983, is a popular statistical matching technique which tries to estimate the treatment effects by taking into account covariates that could impact the efficacy of study medication in clinical trials. PSM can be used to reduce the bias due to confounding variables. However, PSM assumes that the response values are normally distributed. In some cases, this assumption may not be held. In this paper, a machine learning method - Bayesian Additive Regression Tree (BART), is used as a more robust method of matching. BART can work well when models are misspecified since it can be used to model heterogeneous treatment effects. Moreover, it has the capability to handle non-linear main effects and multiway interactions. In this research, a BART Matching Method (BMM) is proposed to provide a more reliable matching method over PSM. By comparing the analysis results from PSM and BMM, BMM can perform well and has better prediction capability when the response values are not normally distributed.

Keywords: BART, Bayesian, matching, regression

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2263 The Application of a Hybrid Neural Network for Recognition of a Handwritten Kazakh Text

Authors: Almagul Assainova , Dariya Abykenova, Liudmila Goncharenko, Sergey Sybachin, Saule Rakhimova, Abay Aman

Abstract:

The recognition of a handwritten Kazakh text is a relevant objective today for the digitization of materials. The study presents a model of a hybrid neural network for handwriting recognition, which includes a convolutional neural network and a multi-layer perceptron. Each network includes 1024 input neurons and 42 output neurons. The model is implemented in the program, written in the Python programming language using the EMNIST database, NumPy, Keras, and Tensorflow modules. The neural network training of such specific letters of the Kazakh alphabet as ә, ғ, қ, ң, ө, ұ, ү, h, і was conducted. The neural network model and the program created on its basis can be used in electronic document management systems to digitize the Kazakh text.

Keywords: handwriting recognition system, image recognition, Kazakh font, machine learning, neural networks

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2262 Human Capital and the Innovation System: A Case Study of the Mpumalanga Province, South Africa

Authors: Maria E. Eggink

Abstract:

Human capital is one of the essential factors in an innovation system and innovation is the driving force of economic growth and development. Schumpeter focused on the entrepreneur as innovator, but the evolutionary economists shifted the focus to all participants in the innovation system. Education and training institutions are important participants in an innovation system, but there is a gap in literature on competence building as part of the analysis of innovation systems. In this paper the education and training institutions’ competence building role in the innovation system is examined. The Mpumalanga Province of South Africa is used as a case study. It was found that the absence of a university, the level of education, the quality and performance in the education sector and the condition of the education infrastructure have not been conducive to learning.

Keywords: education institutions, human capital, innovation systems, Mpumalanga Province

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2261 The Code-Mixing of Japanese, English, and Thai in Line Chat

Authors: Premvadee Na Nakornpanom

Abstract:

Language mixing in spontaneous speech has been widely discussed, but not in virtual situations; especially in context of the third language learning students. Thus, this study was an attempt to explore the characteristics of the mixing of Japanese, English and Thai in a mobile chat room by students with their background of Japanese, English, and Thai. The result found that Insertion of Thai and English content words was a very common linguistic phenomenon embedded in the utterances. As chatting is to be ‘relational’ or ‘interactional’, it affected the style of lexical choices to be speech-like, more personal and emotional-related. A Japanese sentence-final question particle“か”(ka) was added to the end of the sentence based on Thai grammar rule. Moreover, some unique characteristics were created. The non-verbal cues were represented in personal, Thai styles by inserting textual representations of images or feelings available on the websites into streams of conversations.

Keywords: code-mixing, Japanese, English, Thai, line chat

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2260 A Conceptual Framework for Integrating Musical Instrument Digital Interface Composition in the Music Classroom

Authors: Aditi Kashi

Abstract:

While educational technologies have taken great strides, especially in Musical Instrument Digital Interface (MIDI) composition, teachers across the world are still adjusting to incorporate such technology into their curricula. While using MIDI in the classroom has become more common, limited class time and a strong focus on performance have made composition a lesser priority. The balance between music theory, performance time, and composition learning is delicate and difficult to maintain for many music educators. This makes including MIDI in the classroom. To address this issue, this paper aims to outline a general conceptual framework centered around a key element of music theory to integrate MIDI composition into the music classroom to not only introduce students to digital composition but also enhance their understanding of music theory and its applicability.

Keywords: educational framework, education technology, MIDI, music education

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2259 Coastal Modelling Studies for Jumeirah First Beach Stabilization

Authors: Zongyan Yang, Gagan K. Jena, Sankar B. Karanam, Noora M. A. Hokal

Abstract:

Jumeirah First beach, a segment of coastline of length 1.5 km, is one of the popular public beaches in Dubai, UAE. The stability of the beach has been affected by several coastal developmental projects, including The World, Island 2 and La Mer. A comprehensive stabilization scheme comprising of two composite groynes (of lengths 90 m and 125m), modification to the northern breakwater of Jumeirah Fishing Harbour and beach re-nourishment was implemented by Dubai Municipality in 2012. However, the performance of the implemented stabilization scheme has been compromised by La Mer project (built in 2016), which modified the wave climate at the Jumeirah First beach. The objective of the coastal modelling studies is to establish design basis for further beach stabilization scheme(s). Comprehensive coastal modelling studies had been conducted to establish the nearshore wave climate, equilibrium beach orientations and stable beach plan forms. Based on the outcomes of the modeling studies, recommendation had been made to extend the composite groynes to stabilize the Jumeirah First beach. Wave transformation was performed following an interpolation approach with wave transformation matrixes derived from simulations of a possible range of wave conditions in the region. The Dubai coastal wave model is developed with MIKE21 SW. The offshore wave conditions were determined from PERGOS wave data at 4 offshore locations with consideration of the spatial variation. The lateral boundary conditions corresponding to the offshore conditions, at Dubai/Abu Dhabi and Dubai Sharjah borders, were derived with application of LitDrift 1D wave transformation module. The Dubai coastal wave model was calibrated with wave records at monitoring stations operated by Dubai Municipality. The wave transformation matrix approach was validated with nearshore wave measurement at a Dubai Municipality monitoring station in the vicinity of the Jumeirah First beach. One typical year wave time series was transformed to 7 locations in front of the beach to count for the variation of wave conditions which are affected by adjacent and offshore developments. Equilibrium beach orientations were estimated with application of LitDrift by finding the beach orientations with null annual littoral transport at the 7 selected locations. The littoral transport calculation results were compared with beach erosion/accretion quantities estimated from the beach monitoring program (twice a year including bathymetric and topographical surveys). An innovative integral method was developed to outline the stable beach plan forms from the estimated equilibrium beach orientations, with predetermined minimum beach width. The optimal lengths for the composite groyne extensions were recommended based on the stable beach plan forms.

Keywords: composite groyne, equilibrium beach orientation, stable beach plan form, wave transformation matrix

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2258 Towards a Model of Support in the Areas of Services of Educational Assistance and Mentoring in Middle Education in Mexico

Authors: Margarita Zavala, Gabriel Chavira, José González, Jorge Orozco, Julio Rolón, Roberto Pichardo

Abstract:

Adolescence is a neuralgic stage in the formation of every human being, generally this stage is when the middle school level is studied. In 2006, Mexico incorporated 'mentoring' space to assist students in their integration and participation in life. In public middle schools, it is sometimes difficult to be aware of situations that affect students because of the number of them and traditional records management. With this, they lose the opportunity to provide timely support as a preventive way. In order to provide this support, it is required to know the students by detecting the relevant information that has greater impact on their learning process. This research is looking to check if it is possible to identify student’s relevant information to detect when it is at risk, and then to propose a model to manage in a proper way such information.

Keywords: adolescence, mentoring, middle school students, mentoring system support

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2257 The Active Social Live of #Lovewins: Understanding the Discourse of Homosexual Love and Rights in Thailand

Authors: Tinnaphop Sinsomboonthong

Abstract:

The hashtag, #LoveWins, has been widely used for celebrating the victory of the LGBTQ movement since June 2015 when the US Supreme Court enacted the rights of same-sex marriage. Nowadays, the hashtag is generally used among active social media users in many countries, including Thailand. Amidst the political conflict between advocates of the junta-backed legislation related to same-sex marriage laws, known as ‘Thailand’s Civil Partnership Draft Bills,’ and its detractors, the hashtag becomes crucial for Thailand’s 2019 national election season and shortly afterward as it was one of the most crucial parts of a political campaign to rebrand many political parties’ image, create an LGBT-friendly atmosphere and neutralize the bi-polarized politics of the law. The use of the hashtag is, therefore, not just an online entertainment but a politico-discursive tool, used by many actors for many purposes. Behind the confrontation between supporters and opposers of the law, the hashtag is used by both sides to highlight the Western-centric normativity of homosexual love, closely associated with Eurocentric modernity and heteronormativity. As an online ethnographical study, this paper aims to analyze how #LoveWins is used among Thai social media users in late 2018 to mid-2019 and how it is signified by Thai social media users during the Drafted-Bills period and the 2019 national election. A number of preliminary surveys of data on Twitter were conducted in December 2018 and, more intensely, in January 2019. Later, the data survey was officially conducted twice during February and April 2019, while the data collection was done during May-June 2019. Only public posts on Twitter that include the hashtag, #LoveWins, or any hashtags quoting ‘love’ and ‘wins’ are the main targets of this research. As a result of this, the use of the hashtag can be categorized into three levels, including banal decoration, homosexual love celebration, and colonial discourse on homosexual love. Particularly in the third type of the use of the hashtag, discourse analysis is applied to reveal that this hashtag is closely associated with the discourse of development and modernity as most of the descriptive posts demonstrate aspirations to become more ‘developed and modernized’ like many Western countries and Taiwan, the LGBT capital in Asia. Thus, calls for the ‘right to homosexual love’ and the ‘right to same-sex marriage’ in Thailand are shaped and formulated within the discursive linkage between modernity, development, and love. Also, the use of #LoveWins can be considered as a de-queering process of love as only particular types of gender identity, sexual orientation, and relationships that reflect Eurocentric modernity and heteronormativity are acceptable and advocated. Due to this, more inclusive queer loves should be supported rather than a mere essentialist-traditionalist homosexual love. Homonormativity must be deconstructed, and love must no longer be reserved for only one particular type of relationship that is standardized from/by the West. It must become more inclusive.

Keywords: #LoveWins, homosexual love, LGBT rights, same-sex marriage

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2256 Using Computer Vision and Machine Learning to Improve Facility Design for Healthcare Facility Worker Safety

Authors: Hengameh Hosseini

Abstract:

Design of large healthcare facilities – such as hospitals, multi-service line clinics, and nursing facilities - that can accommodate patients with wide-ranging disabilities is a challenging endeavor and one that is poorly understood among healthcare facility managers, administrators, and executives. An even less-understood extension of this problem is the implications of weakly or insufficiently accommodative design of facilities for healthcare workers in physically-intensive jobs who may also suffer from a range of disabilities and who are therefore at increased risk of workplace accident and injury. Combine this reality with the vast range of facility types, ages, and designs, and the problem of universal accommodation becomes even more daunting and complex. In this study, we focus on the implication of facility design for healthcare workers suffering with low vision who also have physically active jobs. The points of difficulty are myriad and could span health service infrastructure, the equipment used in health facilities, and transport to and from appointments and other services can all pose a barrier to health care if they are inaccessible, less accessible, or even simply less comfortable for people with various disabilities. We conduct a series of surveys and interviews with employees and administrators of 7 facilities of a range of sizes and ownership models in the Northeastern United States and combine that corpus with in-facility observations and data collection to identify five major points of failure common to all the facilities that we concluded could pose safety threats to employees with vision impairments, ranging from very minor to severe. We determine that lack of design empathy is a major commonality among facility management and ownership. We subsequently propose three methods for remedying this lack of empathy-informed design, to remedy the dangers posed to employees: the use of an existing open-sourced Augmented Reality application to simulate the low-vision experience for designers and managers; the use of a machine learning model we develop to automatically infer facility shortcomings from large datasets of recorded patient and employee reviews and feedback; and the use of a computer vision model fine tuned on images of each facility to infer and predict facility features, locations, and workflows, that could again pose meaningful dangers to visually impaired employees of each facility. After conducting a series of real-world comparative experiments with each of these approaches, we conclude that each of these are viable solutions under particular sets of conditions, and finally characterize the range of facility types, workforce composition profiles, and work conditions under which each of these methods would be most apt and successful.

Keywords: artificial intelligence, healthcare workers, facility design, disability, visually impaired, workplace safety

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2255 The Interconnection between Curriculum Development and ICT

Authors: Hanane Sarnou, Sabri Koç

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In this paper, the interconnection between curriculum development for basic education and the use of information and communication technologies (ICTs) in the classroom referring to the Licence, Master's and Doctorate (LMD) benefits under such link will be presented and analysed. This study seeks to achieve to what extent LMD, competency-based approach (CBA) and ICTs use are interrelated. Likewise, the data collected from the responses of our teachers and learners who are concerned with LMD impact on their learning and teaching through interviews will be discussed, analysed, and classified. This paper is divided into two sections. The first section is about the curriculum development for basic education and its relation with higher education under the LMD and its link with ICTs in the university while the second section is about the classification of learners’ and teachers’ positive/negative responses concerning their positive or negative attitudes towards the ICT integration. The focus will be on the positive aspects of students’ expectations, opinions and assumptions regarding the integration of ICTs into the classroom under LMD and CBA.

Keywords: LMD system, CBA approach, curriculum development, ICT

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2254 Exploring the Nature and Meaning of Theory in the Field of Neuroeducation Studies

Authors: Ali Nouri

Abstract:

Neuroeducation is one of the most exciting research fields which is continually evolving. However, there is a need to develop its theoretical bases in connection to practice. The present paper is a starting attempt in this regard to provide a space from which to think about neuroeducational theory and invoke more investigation in this area. Accordingly, a comprehensive theory of neuroeducation could be defined as grouping or clustering of concepts and propositions that describe and explain the nature of human learning to provide valid interpretations and implications useful for educational practice in relation to philosophical aspects or values. Whereas it should be originated from the philosophical foundations of the field and explain its normative significance, it needs to be testable in terms of rigorous evidence to fundamentally advance contemporary educational policy and practice. There is thus pragmatically a need to include a course on neuroeducational theory into the curriculum of the field. In addition, there is a need to articulate and disseminate considerable discussion over the subject within professional journals and academic societies.

Keywords: neuroeducation studies, neuroeducational theory, theory building, neuroeducation research

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2253 Embedded Semantic Segmentation Network Optimized for Matrix Multiplication Accelerator

Authors: Jaeyoung Lee

Abstract:

Autonomous driving systems require high reliability to provide people with a safe and comfortable driving experience. However, despite the development of a number of vehicle sensors, it is difficult to always provide high perceived performance in driving environments that vary from time to season. The image segmentation method using deep learning, which has recently evolved rapidly, provides high recognition performance in various road environments stably. However, since the system controls a vehicle in real time, a highly complex deep learning network cannot be used due to time and memory constraints. Moreover, efficient networks are optimized for GPU environments, which degrade performance in embedded processor environments equipped simple hardware accelerators. In this paper, a semantic segmentation network, matrix multiplication accelerator network (MMANet), optimized for matrix multiplication accelerator (MMA) on Texas instrument digital signal processors (TI DSP) is proposed to improve the recognition performance of autonomous driving system. The proposed method is designed to maximize the number of layers that can be performed in a limited time to provide reliable driving environment information in real time. First, the number of channels in the activation map is fixed to fit the structure of MMA. By increasing the number of parallel branches, the lack of information caused by fixing the number of channels is resolved. Second, an efficient convolution is selected depending on the size of the activation. Since MMA is a fixed, it may be more efficient for normal convolution than depthwise separable convolution depending on memory access overhead. Thus, a convolution type is decided according to output stride to increase network depth. In addition, memory access time is minimized by processing operations only in L3 cache. Lastly, reliable contexts are extracted using the extended atrous spatial pyramid pooling (ASPP). The suggested method gets stable features from an extended path by increasing the kernel size and accessing consecutive data. In addition, it consists of two ASPPs to obtain high quality contexts using the restored shape without global average pooling paths since the layer uses MMA as a simple adder. To verify the proposed method, an experiment is conducted using perfsim, a timing simulator, and the Cityscapes validation sets. The proposed network can process an image with 640 x 480 resolution for 6.67 ms, so six cameras can be used to identify the surroundings of the vehicle as 20 frame per second (FPS). In addition, it achieves 73.1% mean intersection over union (mIoU) which is the highest recognition rate among embedded networks on the Cityscapes validation set.

Keywords: edge network, embedded network, MMA, matrix multiplication accelerator, semantic segmentation network

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2252 Model of Optimal Centroids Approach for Multivariate Data Classification

Authors: Pham Van Nha, Le Cam Binh

Abstract:

Particle swarm optimization (PSO) is a population-based stochastic optimization algorithm. PSO was inspired by the natural behavior of birds and fish in migration and foraging for food. PSO is considered as a multidisciplinary optimization model that can be applied in various optimization problems. PSO’s ideas are simple and easy to understand but PSO is only applied in simple model problems. We think that in order to expand the applicability of PSO in complex problems, PSO should be described more explicitly in the form of a mathematical model. In this paper, we represent PSO in a mathematical model and apply in the multivariate data classification. First, PSOs general mathematical model (MPSO) is analyzed as a universal optimization model. Then, Model of Optimal Centroids (MOC) is proposed for the multivariate data classification. Experiments were conducted on some benchmark data sets to prove the effectiveness of MOC compared with several proposed schemes.

Keywords: analysis of optimization, artificial intelligence based optimization, optimization for learning and data analysis, global optimization

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2251 Climate Change and Landslide Risk Assessment in Thailand

Authors: Shotiros Protong

Abstract:

The incidents of sudden landslides in Thailand during the past decade have occurred frequently and more severely. It is necessary to focus on the principal parameters used for analysis such as land cover land use, rainfall values, characteristic of soil and digital elevation model (DEM). The combination of intense rainfall and severe monsoons is increasing due to global climate change. Landslide occurrences rapidly increase during intense rainfall especially in the rainy season in Thailand which usually starts around mid-May and ends in the middle of October. The rain-triggered landslide hazard analysis is the focus of this research. The combination of geotechnical and hydrological data are used to determine permeability, conductivity, bedding orientation, overburden and presence of loose blocks. The regional landslide hazard mapping is developed using the Slope Stability Index SINMAP model supported on Arc GIS software version 10.1. Geological and land use data are used to define the probability of landslide occurrences in terms of geotechnical data. The geological data can indicate the shear strength and the angle of friction values for soils above given rock types, which leads to the general applicability of the approach for landslide hazard analysis. To address the research objectives, the methods are described in this study: setup and calibration of the SINMAP model, sensitivity of the SINMAP model, geotechnical laboratory, landslide assessment at present calibration and landslide assessment under future climate simulation scenario A2 and B2. In terms of hydrological data, the millimetres/twenty-four hours of average rainfall data are used to assess the rain triggered landslide hazard analysis in slope stability mapping. During 1954-2012 period, is used for the baseline of rainfall data at the present calibration. The climate change in Thailand, the future of climate scenarios are simulated by spatial and temporal scales. The precipitation impact is need to predict for the climate future, Statistical Downscaling Model (SDSM) version 4.2, is used to assess the simulation scenario of future change between latitude 16o 26’ and 18o 37’ north and between longitude 98o 52’ and 103o 05’ east by SDSM software. The research allows the mapping of risk parameters for landslide dynamics, and indicates the spatial and time trends of landslide occurrences. Thus, regional landslide hazard mapping under present-day climatic conditions from 1954 to 2012 and simulations of climate change based on GCM scenarios A2 and B2 from 2013 to 2099 related to the threshold rainfall values for the selected the study area in Uttaradit province in the northern part of Thailand. Finally, the landslide hazard mapping will be compared and shown by areas (km2 ) in both the present and the future under climate simulation scenarios A2 and B2 in Uttaradit province.

Keywords: landslide hazard, GIS, slope stability index (SINMAP), landslides, Thailand

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2250 Slope Stability Assessment in Metasedimentary Deposit of an Opencast Mine: The Case of the Dikuluwe-Mashamba (DIMA) Mine in the DR Congo

Authors: Dina Kon Mushid, Sage Ngoie, Tshimbalanga Madiba, Kabutakapua Kakanda

Abstract:

Slope stability assessment is still the biggest challenge in mining activities and civil engineering structures. The slope in an opencast mine frequently reaches multiple weak layers that lead to the instability of the pit. Faults and soft layers throughout the rock would increase weathering and erosion rates. Therefore, it is essential to investigate the stability of the complex strata to figure out how stable they are. In the Dikuluwe-Mashamba (DIMA) area, the lithology of the stratum is a set of metamorphic rocks whose parent rocks are sedimentary rocks with a low degree of metamorphism. Thus, due to the composition and metamorphism of the parent rock, the rock formation is different in hardness and softness, which means that when the content of dolomitic and siliceous is high, the rock is hard. It is softer when the content of argillaceous and sandy is high. Therefore, from the vertical direction, it appears as a weak and hard layer, and from the horizontal direction, it seems like a smooth and hard layer in the same rock layer. From the structural point of view, the main structures in the mining area are the Dikuluwe dipping syncline and the Mashamba dipping anticline, and the occurrence of rock formations varies greatly. During the folding process of the rock formation, the stress will concentrate on the soft layer, causing the weak layer to be broken. At the same time, the phenomenon of interlayer dislocation occurs. This article aimed to evaluate the stability of metasedimentary rocks of the Dikuluwe-Mashamba (DIMA) open-pit mine using limit equilibrium and stereographic methods Based on the presence of statistical structural planes, the stereographic projection was used to study the slope's stability and examine the discontinuity orientation data to identify failure zones along the mine. The results revealed that the slope angle is too steep, and it is easy to induce landslides. The numerical method's sensitivity analysis showed that the slope angle and groundwater significantly impact the slope safety factor. The increase in the groundwater level substantially reduces the stability of the slope. Among the factors affecting the variation in the rate of the safety factor, the bulk density of soil is greater than that of rock mass, the cohesion of soil mass is smaller than that of rock mass, and the friction angle in the rock mass is much larger than that in the soil mass. The analysis showed that the rock mass structure types are mostly scattered and fragmented; the stratum changes considerably, and the variation of rock and soil mechanics parameters is significant.

Keywords: slope stability, weak layer, safety factor, limit equilibrium method, stereography method

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2249 Tips for Effective Intercultural Collaboration on the Evaluation of an International Program

Authors: Athanase Gahungu, Karen Freeman

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Different groups of stakeholders expect the evaluation of an international, grant-funded program to inform them of the worth of the program - the funder, the agency operating the program and its community, and the citizens of the country where the program is implemented. This paper summarizes the challenges that intercultural teams of researchers faced as they crisscrossed a host country while evaluating a teaching and learning materials program, and offers useful tips for effective collaboration. Firstly, was recommended that the teams be representative of the cultures involved, and have the required research and program evaluation skills. Secondly, cultures involved must consistently establish and maintain a shared performance system. Thirdly, successful team members must be self-aware, inter-culturally knowledgeable, not just in communication, but in conceptualizing the political and social context of international grant-funded projects.

Keywords: program evaluation, international collaboration, intercultural, shared performance

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2248 Predicting OpenStreetMap Coverage by Means of Remote Sensing: The Case of Haiti

Authors: Ran Goldblatt, Nicholas Jones, Jennifer Mannix, Brad Bottoms

Abstract:

Accurate, complete, and up-to-date geospatial information is the foundation of successful disaster management. When the 2010 Haiti Earthquake struck, accurate and timely information on the distribution of critical infrastructure was essential for the disaster response community for effective search and rescue operations. Existing geospatial datasets such as Google Maps did not have comprehensive coverage of these features. In the days following the earthquake, many organizations released high-resolution satellite imagery, catalyzing a worldwide effort to map Haiti and support the recovery operations. Of these organizations, OpenStreetMap (OSM), a collaborative project to create a free editable map of the world, used the imagery to support volunteers to digitize roads, buildings, and other features, creating the most detailed map of Haiti in existence in just a few weeks. However, large portions of the island are still not fully covered by OSM. There is an increasing need for a tool to automatically identify which areas in Haiti, as well as in other countries vulnerable to disasters, that are not fully mapped. The objective of this project is to leverage different types of remote sensing measurements, together with machine learning approaches, in order to identify geographical areas where OSM coverage of building footprints is incomplete. Several remote sensing measures and derived products were assessed as potential predictors of OSM building footprints coverage, including: intensity of light emitted at night (based on VIIRS measurements), spectral indices derived from Sentinel-2 satellite (normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), soil-adjusted vegetation index (SAVI), urban index (UI)), surface texture (based on Sentinel-1 SAR measurements)), elevation and slope. Additional remote sensing derived products, such as Hansen Global Forest Change, DLR`s Global Urban Footprint (GUF), and World Settlement Footprint (WSF), were also evaluated as predictors, as well as OSM street and road network (including junctions). Using a supervised classification with a random forest classifier resulted in the prediction of 89% of the variation of OSM building footprint area in a given cell. These predictions allowed for the identification of cells that are predicted to be covered but are actually not mapped yet. With these results, this methodology could be adapted to any location to assist with preparing for future disastrous events and assure that essential geospatial information is available to support the response and recovery efforts during and following major disasters.

Keywords: disaster management, Haiti, machine learning, OpenStreetMap, remote sensing

Procedia PDF Downloads 107