Reviewerly/exHarmony huggingface dataset:
Pelaksanaan Pernyataan Standar Akuntansi Pemerintah No. 13 (PSAP 13) tentang Penyajian Laporan Keuangan Badan Layanan Umum di Perguruan Tinggi Negeri (Studi pada Badan Layanan Umum Universitas Brawijaya)

Higher Education carries the obligation to improve the competitiveness of the nation through increasing the intellectuality of the nation's successors. Excellent service must be given in order to achieve the vision and mission in improving the quality of education. University autonomy is needed to create more flexible institutional management. One of the autonomy models is the Public Service Agency (BLU). In carrying out its duties, the BLU must use a special pattern in the presentation of its financial statements. The Government Accounting Standards Statement (PSAP) 13 is used to simplify BLU financial reporting. The implementation of PSAP 13 at Universitas Brawijaya was discussed in this study to give an idea of how it was implemented in the Public Service Agency.
THE PEDAGOGICAL EVALUATION OF THE RESPONSIVENESS OF PRE-SERVICE TEACHERS

With the guidelines for pre-school education coming into effect, a paradigm change has occurred in Latvia, focusing on a child-centred educational process. Contradictions can be observed in the professional training of pre-school teachers. Clearly, pre-school educators ensure the transfer of values to the next generation and the stability of the system of education; nevertheless, their activity is often focused on imparting reproductive knowledge and skills and following familiar algorithms and stereotypes. The innovative trend – the development of child’s social and emotional skills – is not always dominant in the work of pre-school teachers. The aim of the research is to analyse the views of students, pre-service teachers, about teacher’s responsiveness in pedagogical activity. The research methods include the theoretical method – the analysis of theoretical literature, regulatory documents and academic studies - and the empirical method – surveys. The data have been processed with SPSS program. 247 full-time and part-time students of the University of Latvia participated in the study. The authors of the article concluded that pre-service teachers’ understanding of teacher’s responsiveness is sufficient. Most students are aware of the importance of teacher’s supportive reactions, responsibility and leadership in the regulation of child’s emotions. Pre-school teacher training plays an important role in the implementation of the social-emotional learning process, paying particular attention to raising students’ awareness of the role of emotions in the development of child’s self-regulation and the advancement of teachers’ skills in building positive and supportive relationships with children and parents.
MARVIN: Identifying Design Requirements for an AI powered Conversational User Interface for Extraterrestrial Space Habitats

In this workshop paper we report on our early work to design a conversational interface for astronaut scientists in an extraterrestrial habitat (e.g. a habitat on Moon or Mars).At the workshop we will report on our initial design and first evaluations of our conversational user interface called MARVIN.Our goal with MARVIN is to support scientists on their missions and during their daily (scientific) routines within and outside the habitat.We are installing our interface in MaMBA.The MaMBA project aims to build a first functional extraterrestrial habitat prototype.
Quantitative robustness of localized support vector machines

The huge amount of available data nowadays is a challenge for kernel-based machine learning algorithms like SVMs with respect to runtime and storage capacities. Local approaches might help to relieve these issues and to improve statistical accuracy. It has already been shown that these local approaches are consistent and robust in a basic sense. This article refines the analysis of robustness properties towards the so-called influence function which expresses the differentiability of the learning method: We show that there is a differentiable dependency of our locally learned predictor on the underlying distribution. The assumptions of the proven theorems can be verified without knowing anything about this distribution. This makes the results interesting also from an applied point of view.
The Art of Foreign Language Teaching for Students at the Technical Universities

This research the main problems in the study of technical English by students of technical universities are examined. In addition, in the following article the main approaches to increase the students' communication competence by developing an interdisciplinary model of teaching technical English are overviewed. In the final part of the study, recommendations are given according to the developed model, where personality-oriented, communicative and competency-based approaches and ICAO requirements for language proficiency are taken into account. In the following article there was made an attempt to simulate the process of forming professional and communicative competence for the future specialists. To build a model, we determined the type and nature of the required product, the type and nature of the source material needed to transform the tools and means, the nature of the individual actions that need to be performed, and their order. In the process of future technical experts training, teaching a foreign language, aimed at developing professional and communicative competence, is often reproductive. This process is complicated by the extremely limited number of hours devoted to professional foreign language training, as well as the fact that the trainees simultaneously perform military service. Therefore, the number of absenteeism classes is large for objective reasons.
From Lines of Development to Scenarios

Abstract After examining the current developments in the field of knowledge and competence requirements, university teaching and technology, and their effects on a digital society through various background studies, this chapter focuses on modeling and developing different scenarios and discussions with regard to technology and social developments. Different economic and social requirements as well as new forms of didactics and learning environments will lead to necessary changes in higher education. It should provide a link between continuing and higher education by identifying new ways of recognizing skills acquired informally. Strong support most notably for new students, should combine performing, developing, and explorative teaching and learning situations. Meanwhile, it will be essential for the didactics of the future to be sensitive to the needs of learners and offer individualized support for student-learning paths, making education independent of time and place. Finally, selected approaches to developing future scenarios in higher education focusing on institutions and governance issues, technology, and social developments are discussed in more detail.
Computational scrutiny of image denoising method found on DBAMF under SPN surrounding

Traditionally, rank order absolute difference (ROAD) has a great similarity capacity for identifying whether the pixel is SPN or noiseless because statistical characteristic of ROAD is desired for a noise identifying objective. As a result, the decision based adaptive median filter (DBAMF) that is found on ROAD technique has been initially proposed for eliminating an impulsive noise since 2010. Consequently, this analyzed report focuses to examine the similarity capacity of denoising method found on DBAMF for diverse SPN Surrounding. In order to examine the denoising capacity and its obstruction of the denoising method found on DBAMF, the four original digital images, comprised of Airplane, Pepper, Girl and Lena, are examined in these computational simulation for SPN surrounding by initially contaminating the SPN with diverse intensity. Later, all contaminated digital images are denoised by the denoising method found on DBAMF. In addition, the proposed denoised image, which is computed by this DBAMF denoising method, is confronted with the other denoised images, which is computed by Standard median filter (SMF), Gaussian Filter and Adaptive median filter (AMF) for demonstrating the DBAMF capacity under subjective measurement aspect.
Online Teaching Practice of Analytical Chemistry Based on the Combination of China University MOOC, MOOC Classroom and QQ Group

The analytical chemistry course team of China University of Geosciences (Wuhan) successfully carried out the online teaching of analytical chemistry course by using national high-quality online open course as the course resource, MOOC classroom as the smart teaching tool, and QQ group as the platform for online teaching and tutoring.The practice shows that online teaching based on the combination of China University MOOC, MOOC classroom and QQ group has been well received and favored by students, who are generally easy to accept and highly motivated to participate.This practice shows good teaching effect at the beginning.
genoDraw: A Web Tool for Developing Pedigree Diagrams Using the Standardized Human Pedigree Nomenclature Integrated with Biomedical Vocabularies.

The integration of genetic information in current clinical routine has raised a need for tools to exploit family genetic knowledge. On the clinical side, an application for managing and visualizing pedigree diagrams could provide genetics specialists with an integrated environment with potential positive impact on their current practice. This article presents a web tool (genoDraw) that provides clinical practitioners with the ability to create, maintain and visualize patients' and their families' information in the form of pedigree diagrams. genoDraw implements a graph-based three-step process for generating diagrams according to a de facto standard in the area and clinical terminologies. It also complies with five characteristics identified as indispensable for the next-generation of pedigree drawing software: comprehensiveness, data-drivenness, automation, interactivity and compatibility with biomedical vocabularies. The platform was implemented and tested, confirming its potential interest to clinical routine.
Alfabetizaciones y prácticas digitales desde agencias juveniles. Desafíos para la educación en Chile.

This article presents a discussion on digital literacy and the practices of young Chilean schoolchildren and their possibilities of agency. Chile has the highest levels of accessibility to Information and Comunication Technologies (ICT) in Latin America, but also one of the most unequal educational systems. Both factors are evident in the evaluations regarding the digital abilities of students made in the country. However, these measurements do not allow us to understand how these differences are expressed concerning youth digital practices. This article proposes a conceptual articulation to generate meaning and guide research on digital literacy, and also presents results of an exploratory study of mixed design, aimed to characterise media practices and skills of adolescents from three educational institutions in Santiago, Chile. In a first quantitative phase, a questionnaire was applied to 143 cases, and then qualitative analysis workshops were held with a sample of 30 students. The quantitative results confirm differences in the use of ICT according to socioeconomic level. The qualitative findings allow us to understand these differences and make the definition of digital literacy more complex in about youth practices and agencies.
The process of developing a child’s self-awareness and motivation

Psychological development of a person, its formation as a person is connected with self-consciousness, self-realization as a physical, spiritual and social being. The development of self-awareness is unique to each child. However, all children usually have signs of self-awareness at the end of the first year of life: the child begins to separate himself or her body from the space that beats him. Further development of self-awareness is related to the child's own perceptions and motivations for their activities in general. Understanding the motivation of their activities can help the child to move to the next level of self-awareness, which is to separate his or her actions. At first the child does not understand himself as a subject of activity.
Predicting the risk of VISIT emergency department (ED) in lung cancer patients using machine learning.

2042 Background: Lung cancer patients commonly need unplanned visits to ED. Many of these visits could be potentially avoidable if it were possible to identify patients at risk when the previous scheduled visit takes place. At that moment, it would be possible to perform elective actions to manage patients at risk to consult the ED in the near future. Methods: Unplanned visits of patients in active cancer therapy (i.e. chemo or immunotherapy) are attended in our own ED facilities. Our Electronic Health Record (EHR) includes specific modules for first visit, scheduled visits and unplanned visits. Lung cancer patients with at least two visits were eligible. The event of interest was patient visit to ED within 21 or 28 days (d) from previous visit. Free text data collected in the three modules were obtained from EHR in order to generate a feature vector composed of the word frequencies for each visit. We evaluate five different machine learning algorithms to predict the event of interest. Area under the ROC curve (AUC), F1 (harmonic mean of precision and recall), True Positive Rate (TPR) and True Negative Rate (TNR) were assessed using 10-fold cross validation. Results: 2,682 lung cancer patients treated between March 2009 and October 2019 were included from which 819 patients were attended at ED. There were 2,237 first visits, 47,465 scheduled visits (per patient: range 1-174; median 12) and 2,125 unplanned visits (per patient: range 1-20; median 2). Mean age at diagnosis was 64 years. The majority of patients had late stage disease (34.24 % III, 51.56 % IV). The Adaptive Boosting Model yields the best results for both 21 d or 28 d prediction. Conclusions: Using unstructured data from real-world EHR enables the possibility to build an accurate predictive model of unplanned visit to an ED within the 21 or 28 following d after a scheduled visit. Such utility would be very useful in order to prevent ED visits related with cancer symptoms and to improve patients care. [Table: see text]
Analysing Compression Performance for Real Time Database Systems

Database compression and decompression is a susceptible problem in the database framework.Database compression is widely used in data management to improve the performance and save storage space.When you have large amounts of data, the cost of the storage subsystem can easily exceed the cost of your data server.Over the last decades, improvements in CPU speed have outpaced improvements in main memory and disk access rates by orders of magnitude, enabling the use of database compression techniques to improve the performance of database systems.In this paper, we outlined the new techniques to analyse the database compression performance for real time database systems.This proposed technique not only reduces space requirements on disk and I/O performance, they also reduce the utilization of memory, thus reducing the number of buffer faults resulting in I/O.This algorithm enables more granular, enhances the compression and decompression performance.
Robust object detection in images corrupted by impulse noise

This paper proposes two effective normalized similarity functions for robust object detection in very high density impulse noisy images.These functions form an integral similarity estimate based on relations of minimum by maximum values for all pairs of analyzed image features.To provide invariance under the constant brightness changes, zero-mean additive modification is used.We explore properties of our functions and compare them with other commonly used for object detection in images corrupted by impulse noise.The efficiency of our approach is illustrated and confirmed by experimental results.
Augmented reality and virtual reality in our daily life

Augmented reality, the new age technology, has widespread applications in every field imaginable. This technology has proven to be an inflection point in numerous verticals, improving lives and improving performance. In this paper, we explore the various possible applications of Augmented Reality (AR) in the field of Medicine. The objective of using AR in medicine or generally in any field is the fact that, AR helps in motivating the user, making sessions interactive and assist in faster learning. In this paper, we discuss about the applicability of AR in the field of medical diagnosis. Augmented reality technology reinforces remote collaboration, allowing doctors to diagnose patients from a different locality. Additionally, we believe that a much more pronounced effect can be achieved by bringing together the cutting edge technology of AR and the lifesaving field of Medical sciences. AR is a mechanism that could be applied in the learning process too. Similarly, virtual reality could be used in the field where more of practical experience is needed such as driving, sports, neonatal care training.
The Effect of Organizational Learning, IT Capability, and Employee Adaptability on Job Performance: A Moderation Model

This study aims to investigate the effect of organizational learning, IT capability, and employee adaptability on job performance. Drawing on the organizational support literature, this study proposes a model wherein IT capability moderates the relationship between organizational learning and job performance. Data collection (N = 99) is from the employees of the radio frequency spectrum monitoring in Semarang – Indonesia. Using partial least square (PLS) 3.0 software, the findings support all hypotheses relationships proposed. The results further show that the direct effects of organizational learning on job performance exist when IT capability is high.
Testing Data Binnings

Motivated by the question of data quantization and we revisit the problem of identity testing of discrete probability distributions. Identity testing (a.k.a. one-sample testing), a fundamental and by now well-understood problem in distribution testing, asks, given a reference distribution (model) 𝐪 and samples from an unknown distribution 𝐩, both over [n] = {1,2,… ,n}, whether 𝐩 equals 𝐪, or is significantly different from it.In this paper, we introduce the related question of identity up to binning, where the reference distribution 𝐪 is over k ≪ n elements: the question is then whether there exists a suitable binning of the domain [n] into k intervals such that, once binned, 𝐩 is equal to 𝐪. We provide nearly tight upper and lower bounds on the sample complexity of this new question, showing both a quantitative and qualitative difference with the vanilla identity testing one, and answering an open question of Canonne [Clement L. Canonne, 2019]. Finally, we discuss several extensions and related research directions.
Visual Communication Online Learning Through Poster Media for Plastic Waste Problem

The problem of using plastic has become a very difficult problem, but until now the use of plastic has not been significantly reduced.Through international learning experiences brought by professor aboard, the students tried to make visual communication through poster media so as to give an appeal to the general public to realize how terrible the use of plastic is prolonged.The method of this writing is started from online learning with an aboard professor, then the results of learning are assessed with a workshop brief.From this brief, the students carried out the design process with the guidance of the local institution lecturers.It is hoped that the results of this process can be an invitation to reduce waste use throughout the world.
Sum of gamma and normal distribution

Purpose:The article shows how to model audit errors using mixtures of probability distribution.Design/methodology/approach: In financial accounting, data about the economic activities of a given firm is collected and then summarized and reported in the form of financial statements.Auditing, on the other hand, is the independent verification of the fairness of these financial statements.An item in an audit sample produces two pieces of information: the book (recorded) amount and the audited (correct) amount.The difference between the two is called the error amount.The book amounts are treated as values of a random variable whose distribution is a mixture of the distributions of the correct amount and the true amount contaminated by error.The mixing coefficient is equal to the proportion of the items with non-zero errors amounts.Findings: The sum of normal and gamma distribution can be useful for modeling audit errors.Originality/value: In this paper, the method of moments is proposed to estimate mixtures of probability distribution, and we derive a formulation of the probability distribution of the sum of a normally distributed random variable and one with gamma distribution.This research could be useful in financial auditing.
Backward-Forward Sequence Generative Network for Multiple Lexical Constraints

Advancements in Long Short Term Memory (LSTM) Networks have shown remarkable success in various Natural Language Generation (NLG) tasks. However, generating sequence from pre-specified lexical constraints is a new, challenging and less researched area in NLG. Lexical constraints take the form of words in the language model's output to create fluent and meaningful sequences. Furthermore, most of the previous approaches cater this problem by allowing the inclusion of pre-specified lexical constraints during the decoding process, which increases the decoding complexity exponentially or linearly with the number of constraints. Moreover, some of the previous approaches can only deal with single constraint. Additionally, most of the previous approaches only deal with single constraints. In this paper, we propose a novel neural probabilistic architecture based on backward-forward language model and word embedding substitution method that can cater multiple lexical constraints for generating quality sequences. Experiments shows that our proposed architecture outperforms previous methods in terms of intrinsic evaluation.
Content and Structure of the Distance Course on the Formation of the Information and Library System Literacy of Future Musicians-Teachers in the Process of High School Preparation

The article presents the experience of creating and testing a distance learning course aimed at developing information and library literacy of future musicians-teachers in the process of high school preparation. There are contradictions between the demands of the modern information society and the content of educational programs in higher educational institutions of music and pedagogical profile, which do not currently include courses on the formation of information and library literacy of students. Possible solutions to this problem are considered: holding master classes for first-year students during extracurricular time to get acquainted with the library as a structural unit of the institutions; preparing virtual literature reviews with information about access to new collections on music art and music education in electronic library systems; creating a distance course in the electronic information environment of the institution for self-education of first-year students. The results of implementation of the developed system in the content of university training of musicians-teachers at the music faculty of the Institute of Fine Arts of the Moscow Pedagogical State University are presented.