Reviewerly/exHarmony huggingface dataset:
직업기초능력 향상을 위한 전문대학 미용과 학생의 프로젝트 수업설계와 적용

The purpose of this study is to find out if it is effective in improving Occupational Key Competencies after designing and applying video production project learning centered on basic hair color learning in the hair beauty department of a junior college. In order to achieve the purpose of the research, 26 first-year students of H University's beauty department located in J City were given project classes under the theme of “Becoming a Hair YouTuber for the Creative Capabilities of the Future Society” according to the design model of PDIE teaching method for seven weeks. Prior to and after the implementation of the class, the basic vocational ability was examined, and the effects of the class were analyzed after the independent sample T-test was conducted using the SPSS 21.0 statistical program. The results of this study showed that project learning has improved the Occupational Key Competencies of students of beauty departments at Junior colleges (personal skills, doctor communication skills, self-development skills, and problem-solving skills). In addition, the evaluation of class participation and attitude showed that class participation and concentration were high on reflective journal writing and students' confidence and satisfaction in class were high. The results of these studies were combined to confirm that video production project learning was one of the teaching-learning methods that were useful to improve Occupational Key Competencies in basic hair color units. This study is meaningful in that it presented a more practical way to foster Occupational Key Competencies by designing and applying video production project classes in response to changes in educational paradigm.
A Novel Binary Texture Pattern’s Based On Facial Expression Classification Using Neural Network

The identification of facial expressions, due to its important academic and commercial ability, is an important topic in artificial intelligence. If we concentrate on the health care, it is an important goal of every healthcare service to identify and handle emotions of patients. Emotional health is important issues for human life. Bad emotions like depression, sad have influences in human life. To improve human social life, we need to identify their emotional conditions. Facial expressions are the most important means of discovering emotions and behavioral analysis. This paper presents framework for extracting the features by means of CS-LOP with gradient and Gabor wavelet feature and GLCM is designed for each method of feature extraction. Feature maps are fused and classified for different emotions
Development and application of best pedagogical practices (experience of higher educational institutions in EU countries)

Teaching at a modern university should be based on the best pedagogical developments, the latest achievements in the educational space. This also applies to the education sector of the European Union. This is what determined the relevance of this article. The study aims to analyze and prove the effectiveness of educational innovations on the example of the introduction of specific pedagogical practices that are relevant and universal for use in integrated teaching in European educational institutions, including the interactive component of the educational process in EU education. The range of research methods (empirical, statistical, and theoretical) was used to achieve the goal and justify the results of the study. The main hypothesis of the study is the assumption that the introduction of the best pedagogical practices in the educational space, such as interactive, universal. The result of the study is to determine the effectiveness of interactive pedagogical practices. A further perspective is the study of new pedagogical practices and detailed development of the algorithm for their implementation, then the collected materials can be further used in the educational process.
중국인 한국어 학습자의 문어 말뭉치에 나타난 조사 누락 오류 연구

This study examines the types and characteristics of particle omission errors made by Chinese learners of Korean based on a learner written corpus compiled by the National Institute of Korean Language. In Chinese, grammatical particles are not available and thus Chinese learners of Korean find it difficult to acquire syntactic and morphological functions of Korean. Unlike Korean, grammatical cases or syntactic relations are marked through word order in Chinese. Thus, it can be inferred that Korean particles can present a special challenge to Chinese learners of Korean. The present study classified particle errors produced by Chinese learners of Korean according to their level of Korean proficiency as well as the types of particles. With respect to case particles, the omission of subject case particles was the most common, followed by adnominal case particles, object case particles, and adverbial case particles. The errors of omission of subject case particles were frequently observed in the sentences/clauses ending in issta/epsta. (‘exist/not exist’). In the case of adnominal case particles, learners made a substantial number of errors by dropping an adnominal case particle where it was required. The errors of omission of object case particles were commonly observed in the sentences/clauses where the predicate was preceded by its modifying words.
ENHANCED SECURITY SERVICES TO SHARE OF PERSONAL HEALTH DATA IN THE CLOUD

The cloud service in the health care zone has evolved in cost effective and suitable exchange of personal health data. Storing the personal health information to cloud is capable to theft (or) report and calls for the evaluation of method that makes sure security to the personal data. Therefore we suggest method called Enhanced Security Services to Share of Personal Health Data in the Cloud. These schemes protect Patient-Centric control on the personal health data and maintain the privacy of the PHR's. Patients store the encrypted data on the cloud servers and they provide access to different users on different parts of the health data. A semi-trusted proxy is set up and re-encryption server (SRS) is present to set up the public and private key pairs and to create the re-encryption keys. This method is secure opposed to insider warnings and implement a forward and backward access control. We formally study and confirm the working of this method with the High Level Petri Nets (HLPN). Performance assessment with regard to time consumption indicates that the personal health data methodology has the ability to securely share data in the cloud.
INVESTIGATION OF IMAGE STITCHING REFINEMENT WITH ENHANCED CORRELATION COEFFICIENT

Image stitching combines multiple overlapping scenes into a panorama. It can be applied in video stitching, super-resolution, and medical imaging. Post-processing routines such as exposure compensation, seam line adjustment, and blending are often performed to increase its visual appeal. Our aim is to increase the registration accuracy between adjacent image pairs in a stitching algorithm. This is done by adding an area-based registration step, namely Enhanced Correlation Coefficient (ECC), which refines the original feature-based image registration. The performance of registrations in the stitching algorithm is evaluated using root-mean-squared error of control points, structural similarity index, and universal image quality index. The Boat and Graffiti datasets from the Oxford Robotics Database are used for experiments. It is found that ECC largely improves registrations in stitching except for a slight increase in root-mean-squared error of control points in the Boat dataset. In addition, ECC’s enhancement makes the registration outperform the ground truth in one image of both datasets.
Compositional data analysis of sedimentological, mineralogical and geochemical data for the evaluation of Austrian loess and loess loam deposits

&amp;lt;p&amp;gt;Austrian loess and loess loam deposits represent an important source of raw materials for the heavy clay industry for centuries. Building material quality of loess and loess loam deposits and their suitability for different applications is significantly influenced by their heterogeneous properties. These depend on the geology of the source area, climatic conditions, geomorphological location, stratigraphic position, intensity of weathering and redeposition potential. The description of occurrences, properties and availability of these raw materials is therefore an important prerequisite to meet the industrial quality requirements. A large number of different sub-datasets exist at the Geological Survey of Austria, which comprise grain-size analysis, bulk rock composition, clay mineralogy, and geochemistry data of loess and loess loam. Within our project, these individual data sets underwent a thorough examination and have been merged into a coherent database to enable the joint regional and statistical analysis of the data. By applying a log-ratio approach the compositional nature of the analysis data has been taken into account for multivariate statistical methods.&amp;amp;#160;&amp;lt;br&amp;gt;Within our study we focused on the classic Austrian loess regions in the Northern Alpine foreland areas of Upper and Lower Austria and in the Vienna Basin. By transferring the results of the statistical analysis to a Geographic Information System (GIS) these served as the fundamental basis for our categorization of the loess and loess loam occurrences. Taking into account previously published approaches based on soil profile classifications as well as trends and patterns derived from the analysis data, we finally were able to delineate different districts of brick raw materials deposits. These will be made publically accessible to the industry and interested parties as part of the web application of the Austrian Interactive Raw Material Information System IRIS-Online.&amp;lt;/p&amp;gt;
DEVELOPING SELF-MANAGEMENT BASIC SKILLS OF FUTURE PRESCHOOL TEACHERS

The article raises the issue of determining the problems of forming the basic self-management of future teachers of preschool education. Scientific works on the problems of the organization of self-development were analyzed and the opinions of scientists who worked on the organization of effective secret management as a direction of self-management were singled out. The urgency of personal problems of students' self-development and the introduction of learning models, which is based on the use of personal skills and intrinsic motivation, were substantiated. The essence of self-management as a component of personality development and the main problems of formation of basic self-management in future specialists of preschool education were determined. The directions of self-management and their content were covered. The analysis of scientific achievements on the studied topic is offered. A comparative description of the content of the concepts of self-management in scientific sources were formed. Effective forms and methods of organization of activity and ways of effective planning of working hours were specified. Testing of future specialists of preschool education was carried out in order to determine the priority of life orientations as components in the process of personal self-development. The results of the study of semantic life orientations according to the method of D. Leontiev, which allowed not only to identify the general level of awareness of life, but also to diagnose a number of additional scales: goals, process, result. The results of five subscales were analyzed. The levels of commitment of future teachers of preschool education, specificities of perception of life and its meaning, vision of effectiveness of life and ability to set long-term goals, locus of control-ME and locus of control of life were clarified. The program of actions on the basis of results of testing which provide both classroom work and extracurricular work of applicants of higher professional education were outlined. The program of development of bases of self-management is revealed. Prospects for further research on certain issues are identified.
Human strategic decision making in parametrized games

Many real-world games contain parameters which can affect payoffs, action spaces, and information states. For fixed values of the parameters, the game can be solved using standard algorithms. However, in many settings agents must act without knowing the values of the parameters that will be encountered in advance. Often the decisions must be made by a human under time and resource constraints, and it is unrealistic to assume that a human can solve the game in real time. We present a new framework that enables human decision makers to make fast decisions without the aid of real-time solvers. We demonstrate applicability to a variety of situations including settings with multiple players and imperfect information.
Towards Navigation by Reasoning over Spatial Configurations

We deal with the navigation problem where the agent follows natural language instructions while observing the environment. Focusing on language understanding, we show the importance of spatial semantics in grounding navigation instructions into visual perceptions. We propose a neural agent that uses the elements of spatial configurations and investigate their influence on the navigation agent's reasoning ability. Moreover, we model the sequential execution order and align visual objects with spatial configurations in the instruction. Our neural agent improves strong baselines on the seen environments and shows competitive performance on the unseen environments. Additionally, the experimental results demonstrate that explicit modeling of spatial semantic elements in the instructions can improve the grounding and spatial reasoning of the model.
A Study of Utilization and Effect of a Map of Memory Replay for Concept Forming at Final Stage of Learning Module

In this study, we tried to express what children understood at a science class in elementary school by using an itemized list in order to clarify the concept formation acquired by children. At this time, the concept of knowledge was linked by using a memory reproduction map, which is an evolution of the semantic network model. The itemized list was analyzed using text mining. We confirmed that conceptualization was promoted by creating a co-occurrence network of KH Coder.
PENGEMBANGAN MODUL BILINGUAL BERGAMBAR BERBASIS MODEL PREDICT, OBSERVE, EXPLAIN (POE) PADA MATERI PELUANG

This research aims to produce a bilingual illustrated module product based on predict, observe, explain (POE) on the probability material for class VIII Junior High School/MTs which is valid and practical. The type of research developed is research and development (Research and Development) which refers to the ADDIE development model which consists of 5 stages, namely analysis, design, development, implementation, and evaluation. The instrument used was the expert expert validation sheet to measure the validity of the module and the questionnaire sheet and student interview guidelines to measure the practicality and ease of use of the module. The results showed that the assessment of the experts was very valid with the average percentage of material experts was 4.47%, the average percentage of language experts was 4.5%, and the average percentage of media experts was 4.89%. The POE-based illustrated bilingual module on the probability material also obtained a percentage value of 83.85% of the student responses in the practical category.
일학습병행제에서 프로그램 특성이 교육훈련 전이에 미치는 영향: 상사지원의 조절효과

Since 2014, Ministry of Employment & Labor and Human Resources Development Service of Korea have enforced the work-learning dual system in Korea. The goal of the system is to cultivate a practical workforce in industrial fields providing corporate customized training based on National Competency Standards(NCS). This system is also designed to reduce unnecessary expenses and resolve job mismatch between job-seekers and companies. It is the result of taking some elements of the apprenticeship system implemented in such countries as Germany and Switzerland and introducing it in a manner suitable to Korean society and labor market.In this study, we attempt to draw strategic implications for improvement in the effectiveness of work-learning dual training programs. Specifically, we try to determine whether the program properties affect the training transfer performance of learning workers who participate in the programs, observe how each variable affects it, and verify the effect of supervisor support on the relationship between them.A survey was conducted on 302 learning workers in work-learning dual training programs in the regions of Ulsan, Gyeongnam, Gyeongbuk and Jeonnam. After analyzing 226 responses, the results are as follows. First, among the properties of work-learning dual training programs, contents and methods of training significantly affect transfer performance. Second, supervior support directly affects transfer performance significantly and positively. Third, the moderating effect of supervisor support on the relationship between program properties and transfer performance is found to be significant only on the relationship between instructors'' ability and transfer performance.The results of this study may imply that, in order to improve the transfer performance of work-learning dual training, it is essential to design an appropriate training program and to provide a sufficient supervisor support. Especially, it is necessary to build an organization-level support system for the corporate field instructors who conduct their jobs and teach their students at the same time. Also, the system should be designed for supervisors to pay more attention to the training program and actively support learning workers.
A Static Gesture Recognition Method Based on Improved SURF Algorithm and Bayesian Regularization BP Neural Network

Gesture recognition plays an important role in the aspect of human computer interaction (HCI). It has become one of the most challenging tasks in the pattern recognition field. So far, many gesture representations using two-dimensional image have been proposed, but normally they are vulnerable to environmental factors, such as illumination, cluttered backgrounds and so on. In this paper, we propose a static gesture recognition method based on the improved speed up robust feature (SURF) algorithm and the Bayesian regularization back propagation (BP) neural network with the Microsoft Kinect sensor. With the advantages of the Kinect, we can capture the depth data to enhance the robustness of the proposed algorithm. Gesture analysis can be viewed as a two-fold problem, i.e., gesture representation and classification. On the one hand, we implement gesture segmentation by the depth data, and then extract the feature descriptor of the gesture based on the improved SURF algorithm which is optimized through the key point detection and orientation calculation. On the other hand, the method based on the Bayesian regularization BP neural network is used as classifier. Subsequently, in order to further intensify the recognition accuracy, another method of classification of gestures based on maximum angle between fingers is proposed as well. Finally, two kinds of classification results are also combined to get the final classification result. The experimental results show that the proposed method can eliminate the interference of the background, and enhance the robustness and accuracy of the gesture recognition.
Application of Augmented Reality for Introduction Of The Unit Ted (Technical Record & Configuration Management) Structure In PT. GMF Aeroasia.Tbk Based On Android: Application of Augmented Reality for Introduction Of The Unit Ted (Technical Record & Configuration Management) Structure In PT. GMF Aeroasia.Tbk Based On Android

The utilization of augmented reality technology is now more widespread. At present many companies have used the technology to introduce the company and its products to the public. Augmented reality is a picture of a real virtual object in 3D. Augmented reality can be applied to an android smartphone. Here i will make an application to introduce the organizational structure of the TE (Technical Engineering) service especially in the TED (Technical Record & Configuration Management) unit which is divided into 5 sub units within the PT.GMF (Garuda Maintenance Facility) AeroAsia Tbk. the company where I work. In making this Augmented Reality based application, i used Unity and Vuforia. Which later this application will be compiled into an “apk” file that can be installed on our android smartphone.
산후 2주 축약형 모유수유 적응 측정도구의 구성 타당도, 신뢰도와 측정 불변성

Purpose: This study was conducted to evaluate the construct validity, reliability, measurement invariance, and latent mean differences in the Breastfeeding Adaptation Scale-Short Form (BFAS-SF) for use with mothers at 2 weeks postpartum.Methods: This methodological study was designed to evaluate the validity, reliability, and measurement invariance of the BFAS-SF at 2 weeks postpartum, with data collected from 431 breastfeeding mothers. Confirmatory factor analysis and multi-group confirmatory factor analysis were conducted to assess the factor structure and the measurement invariance across employment status, delivery mode, parity, and previous breastfeeding experience, and the latent mean differences were then examined.Results: The goodness of fit of the six-factor model at 2 weeks postpartum was acceptable. Multi-group confirmatory factor analysis supported strict invariance of the BFAS-SF across employment status and delivery mode. Full configural invariance, full metric invariance, and partial scalar invariance across parity and full configural invariance and full metric invariance across previous breastfeeding experience were supported, respectively. The results for latent mean differences suggested that mothers who were employed showed significantly higher scores for breastfeeding confidence. Mothers who had a vaginal delivery showed significantly higher scores for sufficient breast milk and baby’s feeding capability. Multiparous mothers showed significantly higher scores for baby’s feeding capability and baby’s satisfaction with breastfeeding.Conclusion: The validity and reliability of the BFAS-SF at 2 weeks postpartum are acceptable. It can be used to compare mean scores of breastfeeding adaptation according to employment status, delivery mode, and parity.
Integrating earthquake early warning system and a smart robot for post-earthquake automated inspection and emergency response

Abstract The natural hazard, mainly earthquake, has caused substantial economic losses and human life loss to many countries. Taiwan, which is located on the western Circum-Pacific seismic belt, has encountered the problem as mentioned earlier in Meishan, Hsinchu-Taichung, and Chi-Chi earthquakes a few years ago. In this study, the researchers propose a novel robot-event integrated system capable of doing the automated inspection and emergency response due to a significant earthquake. When the household’s earthquake warning receiving device picks up an alert, its built-in wireless communications system will send a signal to the robot. The robot commences inspection of the indoor area via real-time image recognition and tracking. It will approach them upon detecting fallen people, regulating their movements via a robot operating system (ROS) monitoring interface. The robot is designed to operate in a house that remains standing with acceptable damage in which the furniture might falling and injure the occupants after an earthquake hit. The indoor experiment conducted to verify the robot system and operation with a designed condition such as fallen and non-fallen people as a detected object. The robot tested to deliver food or medicine for fallen people while waiting for rescuers to arrive. Tests indicate that the proposed smart robot has prospective implementation to the real-world application with more research and development. The smart robot integrated with an earthquake early warning system has a promising approach to the temporary care of people affected by earthquakes.