Reviewerly/exHarmony huggingface dataset:
PeTARY ACCESS CONTROL SYSTEM WITH FACE RECOGNITION

Perpustakaan Tun Abdul Rahman Ya’kub (PeTARY) is the main library of Universiti Malaysia Sarawak (UNIMAS). It provides a lot of resources for its library user. PeTARY allows UNMIAS students and staff to use library resources. However, if the public wish to enter and use the library resources, they need to apply for membership. Therefore, there is always a librarian or security guard at the entrance of PeTARY to check the student’s matric card or public’s membership. It is quite troublesome for them to check the matric card or membership one by one if there is a lot of users enter the library at once.Hence, PeTARY Access Control System with Face Recognition is proposed to help the librarian. Thepurpose of this system is to use the face recognition technology to help in identify legitimate libraryuser, record their time in and time out and generate statistics on the utilization of the library. Forproduce and deliver a workable proposed system, the Waterfall model is applied in the proposed system.In the Waterfall model, each of the stages is described in detail in the proposed system report. The method and technique used to achieve each stage of Waterfall model also discussed in the report. Other than that, the system prototype and detail design of the proposed system also included in the report. After that, the steps in developing the proposed system and technique used for testing the system function also documented in this report. The reporting end with the achievement of the proposed system, limitations of the proposed project and its future enhancements is discussed. In the future, the proposed system would be an efficient and convenient system for the library user to access the PeTARY. Besidesusing in the library, the proposed system can be used in other places where need access control such as laboratory, office and government buildings.
An Empirical Investigation of Online News Classification on an Open-Domain, Large-Scale and High-Quality Dataset in Vietnamese

In this paper, we build a new dataset UIT-ViON (Vietnamese Online Newspaper) collected from well-known online newspapers in Vietnamese. We collect, process, and create the dataset, then experiment with different machine learning models. In particular, we propose an open-domain, large-scale, and high-quality dataset consisting of 260,000 textual data points annotated with multiple labels for evaluating Vietnamese short text classification. In addition, we present the proposed approach using transformer-based learning (PhoBERT) for Vietnamese short text classification on the dataset, which outperforms traditional machine learning (Naive Bayes and Logistic Regression) and deep learning (Text-CNN and LSTM). As a result, the proposed approach achieves the F1-score of 80.62%. This is a positive result and a premise for developing an automatic news classification system. The study is proposed to significantly save time, costs, and human resources and make it easier for readers to find news related to their interesting topics. In future, we will propose solutions to improve the quality of the dataset and improve the performance of classification models.
Role of Meaningful Work in Interpreting the Connections between Motivational Mechanisms and Innovative Behaviour

Research has shown that innovative behaviour is influenced by motivation. However, little is known about the effect of motivational mechanisms on teachers' innovative work behaviour; or the role meaningful work plays in such a relationship between motivational mechanisms and innovative behaviour. It is against this development that this study examined the unique impact of meaningful work in the association between innovative behaviour and the numerous motivational mechanisms. Therefore, using a quantitative approach and a survey research design, consisting of a randomly selected sample of 309 teachers from Federal Colleges in North-Eastern Nigeria, the study was carried out. The data was analysed using Partial Least Square – Structural Equation Modelling (PLS-SEM). The effect of motivational mechanisms on teachers' innovative behaviour was more significant when teachers have high self-belief in their ability to produce creative outcomes. A positive and significant effect was also found when teachers showed the desire to expend efforts to benefit others rather than engage in activities primarily because the job was fascinating. The results also revealed that a perceived sense of meaningfulness at work exerts a robust mediating effect on the motivational mechanisms influencing teachers’ innovative behaviour
예비 지구과학 교사의 교수학습지도안에 나타난 논증 수준 분석

In this study, we apply a lesson design process using an argumentation structure to preservice earth science teachers and analyzed argumentation levels displayed in the lesson plans written by preservice teachers in the process. As a result of the study, the preservice teachers designed a logically structured lesson by reflecting more argumentation components in the final lesson plan than the first one. In addition, in the case of lesson topics in which all argumentation elements were not explicitly presented in textbooks or curriculum, preservice teachers could not clearly reflect some argumentation components in the lesson plan. The conclusions and implications based on the results are as follows: First, it is necessary to use the argumentation structure as a tool to design logical science lessons, considering that argumentation levels of lesson plans written by preservice science teachers were improved by using argumentation structures in instructional design. Next, it is necessary to cultivate the preservice science teacher's ability to reconstruct the curriculum for science lesson design using the argumentation structure since argumentation levels of lesson plans written by preservice science teachers were limited to the argumentation components presented in the textbook and curriculum. Additionally, it is necessary to develop and apply a preservice teacher education program that uses the argumentation structure in the context of actual teaching activities so that preservice science teachers can not only understand argumentation but also improve their class expertise.
LibGuides: Course Clearances For Instructors: Fair Dealing

Navigate copyright requirements related to the use of resources in online and campus classrooms
Numele autorului – o marcă neînregistrată a operei

A work can be made known to the public with the real name of the author or with a pseudonym or in the version of anonymous work. In the current article, we want to highlight the relevance of the author’s name, which can acquire the value of unregistered trademark by analysing this aspect from different perspectives. Three names, three famous authors, three distinct cases that reveal the legal values of the author’s name, which became a symbol in guaranteeing the quality and authenticity of the work.
Facial expression recognition in Brazilian sign language using facial action coding system : Reconhecimento de expressões faciais na língua de sinais brasileira por meio do sistema de códigos de ação facial: Reconhecimento de expressões faciais na língua de sinais brasileira por meio do sistema de códigos de ação facial

Abstract: Deaf people around the world use sign languages to communicate but, despite the wide dissemination of such languages, deaf or hard of hearing individuals still face difficulties in communicating with hearing individuals, in the absence of an interpreter. Such difficulties negatively impact the access of deaf individuals to education, to the job market, and to public services in general. Assistive technologies, such as Automatic Sign Language Recognition (ASLR), aim at overcoming such communication obstacles. However, the development of reliable ASLR systems imposes numerous challenges due the linguistic complexity of sign languages. Sign languages (SLs) are visuospatial linguistic systems that, like any other human language, present global and regional linguistic variations, and a grammatical system. Also, sign languages do not rely only on manual gestures but also non-manual markers, such as facial expressions. In SL, facial expressions may differentiate lexical items, participate in syntactic construction, and contribute to change the intensity of a sentence, among other grammatical and affective functions. Associated with the gesture recognition models, facial expression recognition (FER) is an essential component of ASLR technology. In this work, we propose an automatic facial expression recognition (FER) system for Brazilian Sign Language (Libras). Derived from a literature survey, we present a language study and a different taxonomy for facial expressions of Libras associated with the Facial Action Coding System (FACS). Also, a dataset of facial expressions in Libras was created. An experimental setting was done for the construction of our framework for a preprocessing stage and recognizer model. The features for the classification of the facial actions resulted from the application of a combined region of interest and geometric information given a theoretical basis and better performance than other tested steps. As for classifiers, SqueezeNet returned better accuracy rates. With this, the potential of the proposed model comes from the analysis of 77% of the average accuracy of recognition of Libras' facial expressions. This work contributes to the growth of studies that involve the computational vision and recognition aspects of the structure of sign language facial expressions, and its main focus is the importance of facial action annotation in an automated way
Exploring Opportunistic Meta-knowledge to Reduce Search Spaces for Automated Machine Learning

Machine learning (ML) pipeline composition and optimisation have been studied to seek multi-stage ML models' i.e. preprocessor-inclusive, that are both valid and well-performing. These processes typically require the design and traversal of complex configuration spaces consisting of not just individual ML components and their hyperparameters, but also higher-level pipeline structures that link these components together. Optimisation efficiency and resulting ML-model accuracy both suffer if this pipeline search space is unwieldy and excessively large; it becomes an appealing notion to avoid costly evaluations of poorly performing ML components ahead of time. Accordingly, this paper investigates whether, based on previous experience, a pool of available classifiers/regressors can be preemptively culled ahead of initiating a pipeline composition/opti-misation process for a new ML problem, i.e. dataset. The previous experience comes in the form of classifier/regressor accuracy rankings derived, with loose assumptions, from a substantial but non-exhaustive number of pipeline evaluations; this meta-knowledge is considered ‘opportunistic’. Numerous experiments with the AutoWeka4MCPS package, including ones leveraging similarities between datasets via the relative landmarking method, show that, despite its seeming unreliability, opportunistic meta-knowledge can improve ML outcomes. However, results also indicate that the culling of classifiers/regressors should not be too severe either. In effect, it is better to search through a ‘top tier’ of recommended predictors than to pin hopes onto one previously supreme performer.
Evaluating SPARQL-based model checking: Potentials and limitations

Model checking is an important task in the BIM collaboration process to prevent expensive planning errors. The submodels of the individual disciplines are transferred into a coordination model. Part of the transfer is a conversion into an exchange format. The exchange format allows the import into the model checking application. In the model checking application routines are performed to check the model against collisions and building regulation violations. During the transfer into the exchange format, information may get lost, especially with parameters that are not yet part of the exchange format supported by the authoring software. In recent years, ontologies have been investigated as a feasible approach to combine the submodels, since they model data in a flexible manner. Hence in the conversion process to an application-specific ontology, the data structure of the submodels can widely persist, which could lead to smaller information loss in comparison to converting the data into a standardized exchange format. The evaluation of the geometric properties of the building is indispensable for detecting and analyzing collisions. The basis for the connection of the different sub models could be the BOT (Building Topology Ontology), which defines the topological structure of a building and can be used to represent further building information by linking it with other ontologies. The relevant geometric relationships for the collision model checks have to be derived with a geometry kernel. For the research in this paper pythonOCC, a wrapper for the geometry kernel Open CASCADE is used with the Semantic Web's own query language SPARQL, queries can be formulated to analyze the collision relationships in combination with other semantic information. These queries can be used to verify model correctness. By connecting the information from different domains, more sophisticated tests are possible than in an exchange format dependent model checking application. The goal is to integrate the developed functionalities into a project platform. This platform is based on an extensive project description in an ontology-based data model and is connected to different authoring tools for the exchange of information.
Learning Distinct Strategies for Heterogeneous Cooperative Multi-agent Reinforcement Learning

Value decomposition has been a promising paradigm for cooperative multi-agent reinforcement learning. Many different approaches have been proposed, but few of them consider the heterogeneous settings. Agents with tremendously different behaviours bring great challenges for centralized training with decentralized execution. In this paper, we provide a formulation for the heterogeneous multi-agent reinforcement learning with some theoretical analysis. On top of that, we propose an efficient two-stage heterogeneous learning method. The first stage refers to a transfer technique by tuning existed homogeneous models to heterogeneous ones, which can accelerate the convergent speed. In the second stage, an iterative learning with centralized training is designed to improve the overall performance. We make experiments on heterogeneous unit micromanagement tasks in StarCraft II. The results show that our method could improve the win rate by around 20% for the most difficult scenario, compared with state-of-the-art methods, i.e., QMIX and Weighted QMIX.
SIGNIFICANCE AND PROMOTION OF RESEARCH AND INNOVATION IN PROFESSIONAL EDUCATION FOR SUSTAINABLE FUTURE

Innovation does not delineate synthesising something from nothing but it anticipates on researching prevailing solutions to come up with a novel hypothesis to test. Research which is an amalgamation of both experience and reasoning is regarded as the most successful loom to the discovery of truth. The chief mileage of research and innovation is to get deep into the topic so that something helpful can be drawn out for everybody, which is long-lasting, ultimately leading to a sustainable future that can be utilized in that particular sector whenever required. It uses all the essential tools to uncover something new and involves a different way of looking at problems and resolving them. These also equip people with the wider knowledge, skills and abilities which are sustainable in order to participate in today’s economy and society, and lead consummate and meaningful lives. In today’s innovation economy, diverse fields of professional education it has become more important for developing the next generation of innovators and divergent thinkers which is also called as sustainable development in education sector. So, the educators have to be well versed with the concept and strategies of the innovative research work of their fields. In this paper the author highlights upon the significance of research and innovation in any professional education which is significant for sustainable development of education as well as enumerates the initiatives been taken by various educational governing bodies such as CSIR, AICTE, UGC, NCERT,SCERT, in promoting and enhancing their innovative research work either with the assistance of technology, finance, e-resources,organizing conferences at National and International levels, Training on Research Methodology with special reference to Action Research, development of Institutional Mechanism for conducting research study by teacher educators, publishing various educational research journals or implementation of various innovative programmes.
E-LEARNING IMPLEMENTATION IN VOCATIONAL TRAINING EDUCATION WITH HANDS-ON LEARNING

This article revied the literature related to e-learning implementation. The purpose of this research is to further explore the use and impact of e-learning. Systematic Literature Review (SLR) is used as a method in this research. The influx of the 4th Industrial Revolution resulted in the loss of some existing work today. This happened in the era of the previous industrial revolution. Nowadays, human activity cannot be separated from digital media. All human activity uses the help of digital technology. Digital technology is a technology that does not use the capabilities of humans that are often called manuals. Improved technological developments in the various areas of life such as finance, business, health, and education have increased. In the field of education also finally develop rapidly in the use of E-Learning adoption. E-Learning has been viewed as a very effective way to improve the quality of teaching and learning in VET schools because of their various forms. The use of e-learning can be in the form of websites or mobile. The use of technology like this in learning makes it easy for teachers and students. In addition to the use of e-learning, these uses have many benefits, such as following the development of education in accordance with the Industrial Revolution of 4.0. It supports environmentally friendly programs because it can reduce the use of paper. The amount of benefits gained from this e-learning use does not cover the likelihood of any other impact in its use.
Augmented and Virtual Reality and its Potential in Higher Education in the Fields of Tourism, STEM, and Medicine

Teaching and learning has dramatically changed over the years. Web-based education and training has become a global phenomenon and E-Learning is becoming the forefront of many higher education institutes (Giovanis, 2015). E-learning refers to the use of technological tools that are either Web-based, Web-distributed or Web-capable for the purposes of education (Nicols, 2003) and uses such technologies to access educational curriculum outside of a traditional classroom (Gul, 2015). Electronic technologies in this sense include both hardware (such as smart-boards, IT support, virtual reality headsets) and software. In recent years, technologies related to Virtual Reality (VR) and Augmented Reality (AR) have gained momentum and have started to find their ways into higher education practices. This chapter provides an overview of the development of VR and AR technologies in general and its applications in higher education, in particular. Furthermore, we examine the potential of VR and AR practices for the Pacific Island countries by giving reference to tourism and hospitality, Science, Technology, Engineering and Mathematics (STEM), and medical studies.
Impact of Online Teaching among College Students in Weifang Institute of Technology

Affected by the COVID-19 epidemic, Weifang Institute of Technology, at the call of the Ministry of Education, organized various forms of online teaching activities in the second semester of the 2019-2020 academic year from March 2020 to July 2020, replacing offline teaching. This study focuses on the influence of network teaching on college students, finds out the difficulties in network learning and puts forward some suggestions. The change of teaching method has some influence on students. This study uses the school education management platform to study the effect of online learning on students. The questionnaire survey shows that about one third of students think that the effect of online teaching is better than that of offline teaching, and more than one third of students hope to use offline teaching method to teach in school. In order to solve this problem, this study adopts the quantitative and qualitative methods, questionnaire investigation, interview method, studied the present situation of online learning, such as online learning found some problems, such as students do not adapt to the network teaching, such as poor online interactive teaching and learning time cannot guarantee lead to study the effect not beautiful, more than 80% of the students think that the main reason for the poor learning effect is not adapt to the new teaching method, students' self control ability is poor, the interference factor that the network environment. This paper analyzes the causes of students' online learning problems from the students' point of view, and puts forward practical suggestions to improve the effect of Weifang Institute of Technology students' online learning.
Senior High School Students Perspective On The Use Of Youtube in Teaching Narative Listening

AbstractSelecting a good medium to teach English is very important. The phenomena that the teacher uses particular textbook, which are stated in the curriculum, without trying to find some other suitable sources. Narrative will be more difficult if they study this text with listening approach. To decrease this problem, teachers are suggested to use teaching media, namely YouTube media. The objectives of the research as follows: 1) To know Senior High School students’ perceptions on the use of YouTube in teaching narrative listening, 2) To find out the advantages and disadvantages of YouTube in teaching narrative listening for Senior High School students. This research was qualitative descriptive. The object of the research is class of X.IPS.2. Technique analysis in this research is data reduction, data display, and conclusion drawing/ verification. The results of this research are as follows: 1) The tenth grade students' perspectives on the use of YouTube in teaching narrative listening was very positive and good; 2) The advantages are a) more interesting, b) students become more focused and happier, c) learning process becomes more fun, d) the students can understand more quickly. The disadvantages are a) the videos are not all suitable, b) it takes time for preparation, c) limited data quota for downloading YouTube videos.Key words: perspective, YouTube, narrative, listening