Reviewerly/exHarmony huggingface dataset:
Pengembangan Media Pembelajaran Akuntansi Dasar Kd 3.4 Berbasis Wordpress Untuk Meningkatkan Hasil Belajar Siswa Kelas X Di SMKN 1 Boyolali

The aim of this research are: (1) To develop Basic Accountancy K.D 3.4 Learning Media based on Wordpress for X class students in SMKN 1 Boyolali with Assumption, Principal, and Concept of Basic Accounting subject material (2) To describe students' study results at Basic Accounting 3.4 lesson using Accountancy Learning Media based on Wordpress. The subject of this research are students from X AKL 1 and X AKL 3 class. This research is a research and pretest-posttest control group design development. The analysis from this research points out that the development of product properness could be categorized as proper to use with material expert score 4,15 and media expert score 4,23. The result of students post-test points out the average score are 85.29 for experiment class and 80.06 for control class. The result from the independent sample t-test is t-arithmetic 1.994 or significant standard < 0.05 which has a score of 0.003 < 0,05. It means that there is a difference between students' study results from experiment class and control class. The conclusion from this research is learning media based on Wordpress could increase students' study results in Basic Accountancy subject of Assumption, Principle, and Concept.
Evaluation of Photonic Reservoir Computing for Use in Short Reach PAM-4 Transmission Systems

Artificial neural networks for use in real-time optical communication systems are difficult to realize in hardware due to their complexity. Here, photonic reservoir computing as an extension of the recurrent neural network offers a good tradeoff between performance and feasibility. As a result, some parts of the digital signal processing may be moved to the optical domain. A single laser with a delayed feedback loop can be used for reservoir computing for which we evaluate the equalization performance for data from a 56 GBd single sideband PAM-4 transmission system. We compare the results with the standard Kramers-Kronig reception.
Endpoint Detection of Partially Overlapping Straight Fibers using High Positive Gaussian Curvature in 3D images

This paper introduces a method for detecting endpoints of partially overlapping straight fibers in three-dimensional voxel image data. The novel approach directly determines fiber endpoints without the need for more expansive single-fiber segmentation. In the context of fiber-reinforced polymers, endpoint information is of practical significance as it can indicate potential damage in endless fiber systems, or can serve as input for estimating statistical fiber length distribution. We tackle this challenge by exploiting Gaussian curvature of the surface of the fibers. Fiber endpoints have high positive curvature, allowing one to distinguish them from the rest of a structure. Accuracy data of the proposed method are presented for various data sets. For simulated fiber systems with fiber volume fractions of less than 20 %, true positive rates above 94 % and false positive rates below 5 % are observed. Two well-resolved real data sets show a reduction of the first rate to 90.3 % and an increase of the second rate to 13.1 %.
한국어 의사소통을 위한 사회문화적 배경 지식의 개념과 구성 요소 설정 연구

The purpose of this study is to emphasize that ‘sociocultural competence’ is needed for explaining communicative competence. Also, it investigates the concept of sociocultural competence and the detailed components of sociocultural competence. Sociocultural competence is the ability that senses and interprets the context and sociocultural characteristic in communication and produces appropriate messages thereafter. Besides, we need sociocultural background knowledge to manifest sociocultural competence. For this reason, this study tried to explain the configuration list and process of sociocultural background knowledge to take an approach from reviewing advanced researches and synthesizing opinions from seven Korean education experts including the researcher. As a result, this study explains that there are contexts of socio-cultural background and conversation within sociocultural background knowledge and language is based on these components. The participants of conversation deliver the appropriate message in consideration of a particular conversation context based on sociocultural characteristics. (Gwangju University)
Improved Adaptive Semi-Unsupervised Weighted Oversampling using Sparsity Factor for Imbalanced Datasets

With the incredible surge in data volumes, problems associated with data analysis have been increasingly complicated.In data mining algorithms, imbalanced data is a profound problem in machine learning paradigm.It appears due to desperate nature of data in which, one class with a large number of instances presents the majority class, while the other class with only a few instances is known as minority class.The classifier model biases towards the majority class and neglects the minority class which may happen to be the most essential class; resulting into costly misclassification error of minority class in real-world scenarios.Imbalanced data problem is significantly overcome by using re-sampling techniques, in which oversampling techniques are proven to be more effective than undersampling.This study proposes an Improved Adaptive Semi Unsupervised Weighted Oversampling (IA-SUWO) technique with sparsity factor, which efficiently solves between-the-class and within-the-class imbalances problem.Along with avoiding over-generalization, overfitting problems and removing noise from the data, this technique enhances the number of synthetic instances in the minority sub-clusters appropriately.A comprehensive experimental setup is used to evaluate the performance of the proposed approach.The comparative analysis reveals that the IA-SUWO performs better than the existing baseline oversampling techniques.
INTERÉS DE LOS BACHILLERES ECUATORIANOS POR ESTUDIAR NUEVAS CARRERAS UNIVERSITARIAS EN LA MODALIDAD ABIERTA Y A DISTANCIA

The objective of this study was to identify the Ecuadorian students’ interest in taking new academic offers in Open and Distance Modalities at “Tecnica Particular de Loja” University (UTPL). This was a quantitative study, not experimental-descriptive, ex post-facto. An online questionnaire was administered, which was completed by 650 students of different high schools around the country. The results show that, currently, Ecuadorian high school graduates have a greater preference for studying traditional majors, in traditional classrooms, to new majors in distance education. Based on the results of this study, it is concluded that, in Ecuador, there is still a need to promote among high school graduates new academic offers which can meet the current global demand, as well as, new and modern learning methodologies through Open and Distance Education that, in an alternative way, allows them to have access to quality education.
Kesiapan Siswa Kelas XI dalam Menghadapi Ujian Tengah Semester Mata Pelajaran Ekonomi Akuntansi di SMA Negeri 3 Sukoharjo Tahun Ajaran 2018/2019

This study aims to determine the readiness of students and what factors influence students in facing the midterm exam for students of class XI IPS in SMA Negeri 3 Sukoharjo academic year 2018/2019. This type of research is qualitative research with survey design. The subject of the research was students of class XI IPS in SMA 3 Sukoharjo which numbered 5 people and accounting economics subjects. Data collection techniques used include interviews, observation, and documentation. To ensure the validity of the data, triangulation (techniques and data sources) is used. Data analysis techniques using data collection, data reduction, data presentation and conclusion. The results of this study are: 1) Most students are not ready for the knowledge aspect in carrying out the midterm exam because students are only ready if the exam is notified in advance and are not ready if the material is not comprehensive and when the exam is not in accordance with what students learn, 2) In the aspect of students' mental readiness in facing the midterm they are also not ready, it can be seen from students feeling nervous and not focused on facing the midterm exam, 3) Students of class XI IPS have different learning patterns, including study regularly, only learn when there is homework, study when there will be a test / test, or never study, 4) There are several factors that affect the readiness of students in facing midterm, namely: material readiness factors, factors mental states of students, and student learning pattern factors.
Instructional Design Mode under Virtual Reality Technology

With the development of technology, the way of teaching is changing constantly. The year of 2016 was called "VR (virtual reality) year", in which numerous VR software start to be noticed by educators as an important part of teaching. However, because of its immersion, interaction and imagination features, the traditional classroom teaching mode is not suitable for this new technology. This study based on the study of the virtual reality learning environment, expositing the instructional design mode of virtual reality technology curriculum. Then giving an curriculum case to show the model under the guidance of virtual reality instructional design concretely.
Persiguiendo a OpenAIRE : el caso de Arias Montano

We present the work of adaptation to the OpenAIRE guidelines that have been carried out at the Arias Montano Repository of the University of Huelva. OpenAIRE 1 and Open Aire 3 compatibility aand the recently achieved adaptation to OpenAire 4.0 are described. Of importance at the present time, the communication will emphasize the adaptation to OpenAire 4.0 of Arias Montano, one of the first repositories (possibly the first) that achieved the adaptation to OpenAire 4.0, only one month after the approval of the guidelines in November 2018The project included the OAI-PMH exposure of the ORCID author identifiers, the use of new metadata based on COAR vocabularies, typologies, rights and version control, among other actions that will be described in the communication.
Information Retrieval Using Latent Semantic Analysis

This paper deals with Information Retrieval using Latent Semantic Analysis (LSA). In the process of searching for relevant information, user query as well as a set of documents from the corpus is analyzed to extract underlying meaning or concepts in the query and those documents. D-score metric is proposed to determine score of each document. Inverted index is computed to rank the documents according to the degree of relevance. Based on certain threshold value of D-score, the documents are retrieved. As the document search is not purely on the basis of keywords only, rather on the basis of semantic aspects of concepts present in it, the search will be confined, because most of the nonrelevant documents are discarded. Rigorous experiments are carried on various standard datasets such as CACM, LISA, NPL, and TIME.
The effect of noise in the training of convolutional neural networks for text summarisation

In this thesis, we work towards bridging the gap between two distinct areas: noisy text handling and text summarisation. The overall goal of the paper is to examine the effects of noise in the trai ...
독일의 언론보도가 난민 정책변화에 미친 영향과 시사점

This study provides important insights into German press culture during a crucial period of agenda-setting for today’s refugee and asylum crisis. It explores how German news coverage had an impact on asylum policy change and its implications for Korean asylum policy. Two terrible accidents, in November 2015 Paris terror attack and sexual assaults against the women on 2016 New Year’s Eve firework night in Cologne, which rapidly inflamed German domestic public opinion towards the refugees. Even before these accidents German press played a pivotal role in having bad effects on German’s perceptions of the refugees. German domestic politics were deeply influenced by press news coverage as well as German public opinions, whereupon far-right anti-immigrant party AfD won seats not only in general election but also in German federal election(Bundestagswahl). The end result is that German Chancellor Angela Merkel was forced to compromise with Interior Minister Horst Seehofer on reforming asylum policy. There are two implications for Korea: one is in the long term perspective, reorganizing asylum law in order to provide the refugees various aids as well as preparing a comprehensive amylum policy and the other is improving the skeptical images of the asylums. To this end it is very important for Korean government to cooperate with the mass media.
Multidimensional Projections Analysis Using Performance Evaluation Planning

Among the challenges within the big data era, analyses of high multidimensional data are still an open research area. As a result, several multidimensional projections techniques have been developed to reduce data dimensionality, becoming a powerful visualization and visual analytics tool. In order to ensure the projection quality, it is necessary to assess the lower-dimensional embedding by using different datasets configurations as input and analyzing evaluation metrics. However, it is not always clear to the user how the number of dimensions, instances or clusters, called factors, can affect the projection mapping and its quality regarding different projection techniques and assessment metrics. This work aims to address how much the factors affect each response variable through performance evaluation planning. We present an evaluation approach that carries out a more in-depth multidimensional projection analysis supported by the factorial design. Through the comparison of two multidimensional projections, it allows a better understanding of how distinct dataset properties can influence on quality metrics results.
EL APRENDIZAJE DEBE SER PLACENTERO

In the educational field, it is very common to listen to comments related to the concern and concern for the actions of the learners, their low motivation, integration, participation, interest, negative attitude, little freedom, lack of pleasure, desire to learn, it is very common For this reason, this methodology analyzes the methodology applied by teaching that affects Learning. I also address theoretical aspects related to learning specifically “the pleasurable”, the incidence of factors such as: family, society, economy, emotionality and the methodology applied by teaching in joyful learning.The methodology used, for being a personal life story; the sample is an individual, under a qualitative approach; interpretive paradigm; the techniques were through the story of the experiences; The format used is APA style.The subject is of great relevance in every educational process, since for the accompaniment of the student to fulfill the function of promoting learning for life, it is necessary that they conceive the educational fact as something pleasant. Based on my learning and experience, I have suggested some experiences such as: self-organization, freedom of speech for a creative exhibition, personification of authors, role of the student and relationship of content with practical life.I have concluded that for learning to be pleasant, what the teacher shares with the students must be related to their dreams, their goals and purposes, relating this to practical life or to the reality that surrounds them.
A method of crime rate forecast based on wavelet transform and neural network

Accurate prediction of crime is highly challenging. In order to improve efficiency of situational crime prevention, the temporal distribution of the crime rate within 24 hours was analysed and a forecast model combining discrete wavelet transform and resilient backpropagation neural network (DWT-RBPNN) is presented. First, historical crime incidence sequences obtained by the sliding window were decomposed by discrete wavelet transform. Then RBPNN trained decomposition sequences to predict the incidence of future trends and details. Finally, the trends and details were reconstructed to get the final prediction sequence. The experimental results showed that the proposed model has relatively high accuracy and feasibility on the crime rate prediction compared with single method of BPNN. The utility of the DWTRBPNN model can offer an exciting new horizon to provide crime rate forecasting and early warning in the situational crime prevention.
Techniques for collaboration in Virtual Reality

In this thesis, I worked on an existing Virtual Conference Room that was made during my internship with the collaboration of another EMSE student. During the time I was working on my thesis, I decided to focus on techniques for collaboration in VR and elaborate the existing VR conference room by adding new features to it. Since the main purpose of this project was to create an environment for communication and collaboration, based on my investigations I came to conclusion that non-verbal behaviour is one of the most important aspects of the communication. Therefore, I decided to work on research and implementation of a non-verbal communication in this environment. Additionally, I investigated the potential of VR for managing Agile Practices and having daily meetings in this environment in the second part of the thesis.
Faster and More Accurate Trace-based Policy Evaluation via Overall Target Error Meta-Optimization

Temporal-Difference (TD) learning is a standard and very successful reinforcement learning approach, at the core of both algorithms that learn the value of a given policy, as well as algorithms which learn how to improve policies. TD-learning with eligibility traces provides a way to boost sample efficiency by temporal credit assignment, i.e. deciding which portion of a reward should be assigned to predecessor states that occurred at different previous times, controlled by a parameter $\lambda$. However, tuning this parameter can be time-consuming, and not tuning it can lead to inefficient learning. For better sample efficiency of TD-learning, we propose a meta-learning method for adjusting the eligibility trace parameter, in a state-dependent manner. The adaptation is achieved with the help of auxiliary learners that learn distributional information about the update targets online, incurring roughly the same computational complexity per step as the usual value learner. Our approach can be used both in on-policy and off-policy learning. We prove that, under some assumptions, the proposed method improves the overall quality of the update targets, by minimizing the overall target error. This method can be viewed as a plugin to assist prediction with function approximation by meta-learning feature (observation)-based $\lambda$ online, or even in the control case to assist policy improvement. Our empirical evaluation demonstrates significant performance improvements, as well as improved robustness of the proposed algorithm to learning rate variation.
Handwritten digits recognition using convolution neural networks

Convolution Neural Networks (CNNs) have been successfully used to solve variety of problems in computer vision and pattern recognition applications. In this paper, we explore the use of CNN to provide a model for handwritten digits recognition (HCCR). Various CNN architecture were explored with various data size to develop the minimum required data size that can produce optimal performance. We utilized the MNIST database of handwritten digits. The recognition results are promising.
Robust Object Tracking Based on Complementary Feature Fusion and Channel Reliability

In this letter, a robust object tracking method is proposed, which is divided into two parts: robust tracker based on complementary feature fusion with channel reliability, and reliable validator based on convolutional neural network. Compared with the existing tracking algorithms, our algorithm tracks the target more robustly and accurately, and suppresses template drift problems effectively. Experimental results on the standard benchmark show that our algorithm can compete with advanced algorithms and achieve a better level.
Key Aspects of Preparing College Graduates for a Competitive Job Market

Today the threat of unemployment is one of the most pressing socio-economic problems for young professionals. The article examines the current state of the educational curriculum as well as infl uential factors, which determine the level of training competitive specialists must receive in order to succeed. Methods are proposed for solving the problem of employment and increasing the competitiveness of graduates in the job market. One of the main priorities for universities should be a creation of favorable conditions for students to acquire a number of specifi c skills, i.e. personal leadership, development of confi dent behavior skills, business communication, stress management, knowledge of general legal, economic and fundamental aspects. These skills will help in future activities to perform their basic daily duties. For this purpose, the methodology of implementing extracurricular activities is defined and the ways to integrate them into a higher educational program are proposed.
Integer partitions probability distributions

Two closely related discrete probability distributions are introduced. In each case the support is a set of vectors in Rn obtained from the partitions of the fixed positive integer n. These distributions arise naturally when considering equally-likely random permutations on the set of n letters. For one of the distributions, the expectation vector and covariance matrix is derived. For the other distribution, conjectures for several elements of the expectation vector are provided.
Image clarity of membrane diffractive imaging system using total-scale Retinex

Transmissive membrane diffractive optic can be used in space optical telescope or long-distance sensing to reduce the size and mass of imaging system. However, images of membrane diffractive imaging system are inevitably affected by diffraction efficiency and atmospheric propagation, which leads to low utilization ratio of light energy and image blur. Clarity of this degraded data is a challenging task. In this paper, an effective post-processing method based on total-scale Retinex (TSR) is proposed to address this problem. First, we design a self-adaptive scale surround function model that is guided by the optical transmission rate to estimate illumination component. Then, we embed the estimated-illumination into Retinex model for directly estimating the final clarity component. Moreover, the proposed method is capable of quasi real-time processing video using temporal coherence. Our method extends the multi-scale Retinex model while it avoids color artifacts in transmission model that can appear due to incorrect depth estimation. The experimental results show that our approach obtains better performance than the other state-of-art methods with respect to contrast enhancement and color-cast correction.
Sistem Informasi Puskesmas Karangrayung 2 Berbasis Web

Center is an institution that is moving in the field of health. Puskesmas is losing the first center of development, coaching and health services that are located closest to the community. Puskesmas has an important role in the management of public health. Technological developments have influenced all aspects of life. Today's communities prefer to do browsing to get information from on having to ask people. Thus this information system was built to facilitate the officers to record and present information easily using computer systems and databases as a means of storage. This information system is built using the PHP and Mysql programming languages as a database. The research methods are used by analysts, design, implementation and testing. With the information system Puskesmas Karangrayung 2 This web-based, will facilitate the community and the Puskesmas officers in accessing information and data easily.