Reviewerly/exHarmony huggingface dataset:
Axiological approach in professional pedagogical education

This scientific research examines the issues related to the axiological aspect of the professional training of future teachers. The relevance of the stated research topic is determined by the urgent necessity to increase the importance of high-quality professional training of future representatives of pedagogical professions, in the context of changes taking place in the modern education system. The purpose of this research work is to identify and state the main components of the axiological aspect of the professional training of future workers in the pedagogical industry, which is able to impart integrity to the entire process of their training. The leading approach in this scientific study is a combination of quantitative and qualitative methodological approaches to the study of issues related to the axiological aspect of the professional training of future workers in the pedagogical industry, in order to determine the main components of the factors affecting the quality and effectiveness of this training and further professional activities of teachers. The main results of this research work were: a statement of necessity to develop and take a set of measures to clarify the existing value criteria of the education system to future teachers at the stage of their university preparation.
GCDF1: A Goal- and Context- Driven F-Score for Evaluating User Models

The evaluation of dialogue systems in interaction with simulated users has been proposed to improve turn-level, corpus-based metrics which can only evaluate test cases encountered in a corpus and cannot measure system's ability to sustain multi-turn interactions.Recently, little emphasis was put on automatically assessing the quality of the user model itself, so unless correlations with human studies are measured, the reliability of user model based evaluation is unknown.We propose GCDF1, a simple but effective measure of the quality of semantic-level conversations between a goaldriven user agent and a system agent.In contrast with previous approaches we measure the F-score at dialogue level and consider user and system behaviours to improve recall and precision estimation.We facilitate scores interpretation by providing a rich hierarchical structure with information about conversational patterns present in the test data and tools to efficiently query the conversations generated.We apply our framework to assess the performance and weaknesses of a Convlab2 user model 1 .
Penıngkatan Kognitif Bahasa Inggris Sıswa Dengan Pemanfaatan Media Interaktif Berbasis Metode Pembelajaran CAFE (Content, Activities, Facilitating, Evaluation) Menggunakan Permainan Petualangan

This research aims to proving students' Cognitive English enhancement using interactive multimedia with the utilization of interactive multimedia. This research is carried on the student of 7th class from SMPN 14 Kota Serang. The steps in this multimedia refers to the stages of CAFE learning method. The multimedia development is done through the stages of Research and Development (R&amp;D) method: information gathering, planning, product development, Implementation and assessment. The average score obtained by students at the time of the pretest was 40.41 and the average score obtained by the students at the time of the posttest was 82.34. Based on these results, the average difference between the pretest and posttest values expressed in the gain (G) value is 0.709 with a very good category.
TRAINING FOR THE DEVELOPMENT OF EXTENSIVE MATERIALS IN THE DIGITAL ERA AS A SOLUTION TO FISHERIES EXTENSION ACTIVITIES WITH DIGITAL SUBMITTING OF INFORMATION

Background: snacks or fast food are currently favored by children's and even dominate the food market. This food has penetrated all regions and its development very fast from day to day. This increase in consumption of snacks is not followed by an increase in the nutritional value in them and most of the snacks as children's snacks that are currently circulating contain many substances that are harmful to health, such as dyes, preservatives and excessive MSG. This cannot be allowed to continue because it also affects the intelligence of children. This requires a media as the delivery of information to the public as a whole. One of the media that can convey information globally is information that is connected to the internet network, especially in streaming videos on social media channels. In order to raise awareness of the Indonesian people, especially the people of Tanjungbalai about the benefits and advantages of eating fish, so Department of Fish Processing Technology Polytechnic Tanjungbalai (TPHP POLTAN) carries out training activities for the creation of extension materials in the digital era. The desired result of this activity is that students can create counseling materials through video media, blogs/vlogs that are presented online. Method : The form of this activity consists of providing material and making video demos. The materials provided in this activity are: 1) Fish Product Diversification, 2) Processed Product Quality Management and 3) Video making and editing tutorials. Result : the training process in making video demos of making products from fishery products as a form of counseling material for the community to be able to make their own snacks that are more nutritious and have a delicious taste. The stages in this training are as follows: 1) Participants make video material to be made, 2) Shoot or record videos according to the material, and 3) Participants do video editing to get a good video.
Persistent Cohesion with Advanced Ring Signatures for Shared Data in Cloud

Abstract: Motivated by the exponential growth and the huge success of cloud data services bring the cloud common place for data to be not only stored in the cloud, but also shared across multiple users. Our scheme also has the added feature of access control in which only valid users are able to decrypt the stored information. Unfortunately, the integrity of cloud data is subject to skepticism due to the existence of hardware/software failures and human errors. Several mechanisms have been designed to allow both data owners and public verifiers to efficiently audit cloud data integrity without retrieving the entire data from the cloud server. However, public auditing on the integrity of shared data with these existing mechanisms will inevitably reveal confidential information—identity privacy—to public verifiers. In this paper, we propose a novel privacy-preserving mechanism that supports public auditing on shared data stored in the cloud. In particular, we exploit ring signatures to compute verification metadata needed to audit the correctness of shared data. With our mechanism, the identity of the signer on each block in shared data is kept private from public verifiers, who are able to efficiently verify shared data integrity without retrieving the entire file. In addition, our mechanism is able to perform multiple auditing tasks simultaneously instead of verifying them one by one. Our experimental results demonstrate the effectiveness and efficiency of our mechanism when auditing shared data integrity. Keywords: Public auditing, privacy-preserving, shared data, cloud computing
Generalized Linear Bandits with Local Differential Privacy

Contextual bandit algorithms are useful in personalized online decision-making. However, many applications such as personalized medicine and online advertising require the utilization of individual-specific information for effective learning, while user's data should remain private from the server due to privacy concerns. This motivates the introduction of local differential privacy (LDP), a stringent notion in privacy, to contextual bandits. In this paper, we design LDP algorithms for stochastic generalized linear bandits to achieve the same regret bound as in non-privacy settings. Our main idea is to develop a stochastic gradient-based estimator and update mechanism to ensure LDP. We then exploit the flexibility of stochastic gradient descent (SGD), whose theoretical guarantee for bandit problems is rarely explored, in dealing with generalized linear bandits. We also develop an estimator and update mechanism based on Ordinary Least Square (OLS) for linear bandits. Finally, we conduct experiments with both simulation and real-world datasets to demonstrate the consistently superb performance of our algorithms under LDP constraints with reasonably small parameters $(\varepsilon, \delta)$ to ensure strong privacy protection.
Precious metal mineralization in the East Pansky layered massif

Three PGE mineralized zones are defined in the western and central parts of the East Pansky intrusion, the zones are controlled by the boundaries of the divisions of layering.Each zone is of complicated geological structure, it can consist of two or more mineralized horizons.These horizons are located mainly at the basement or at the upper contact of olivine-bearing rocks, or move away for dozens meters.As a rule, petrographic control of PGE mineralization is not clear, or is absent.Composition and geochemical characteristics of PGE mineralization change along the cross section of the intrusion: sulfide content decreases from 3-5% in the lower zone to zero in the upper one, and Pd/Pt ratio decreases from 4-6 to <1.
Knowledge Based Deep Inception Model for Web Page Classification

Web Page Classification is decisive for information retrieval and management task and plays an imperative role for natural language processing (NLP) problems in web engineering. Traditional machine learning algorithms excerpt covet features from web pages whereas deep leaning algorithms crave features as the network goes deeper. Pre-trained models such as BERT attains remarkable achievement for text classification and continue to show state-ofthe-art results. Knowledge Graphs can provide rich structured factual information for better language modelling and representation. In this study, we proposed an ensemble Knowledge Based Deep Inception (KBDI) approachfor web page classification by learning bidirectional contextual representation using pre-trained BERT incorporating Knowledge Graph embeddings and fine-tune the target task by applying Deep Inception network utilizing parallel multi-scale semantics. Proposed ensemble evaluates the efficacy of fusing domain specific knowledge embeddings with the pre-trained BERT model. Experimental interpretation exhibit that the proposed BERT fused KBDI model outperforms benchmark baselines and achieve better performance in contrast to other conventional approaches evaluated on web page classification datasets.
A Proposed Architecture of an Intelligent System for Assessing the Student’s UML Class Diagram

Today educational technology and computer applications can enhance the level of impact of the educational process, currently a heavy research has more and more interested in computing technologies and applications. This work presents a proposed architecture of an intelligent system for the automated assessment of student's production when modeling an UML class diagram from textual specification, this assessment becomes really difficult in problem of diagrammatic answers. The main objective is to develop a system to assess the UML class diagrams by defining differences, errors made by the students, grading them and providing critical feedbacks, and this could be easier for any teachers to assess any number of students. To achieve this goal we have to analyze, transform and compare the student’s diagram with the reference’s production provided by teacher.
Designing a Voice-controlled Wheelchair for Persian-speaking Users Using Deep Learning Networks with a Small Dataset

With the advancement of technology, the demand for improving the quality of life of the elderly and disabled has increased and their hope to overcome their problem is realized by using advanced technologies in the field of rehabilitation.Many existing electrical and electronic devices can be turned into more controllable and more functional devices using artificial intelligence.In every society, some spinal disabled people lack physical and motor abilities such as moving their limbs and they cannot use the normal wheelchair and need a wheelchair with voice control.The main challenge of this project is to identify the voice patterns of disabled people.Audio classification is one of the challenges in the field of pattern recognition.In this paper, a method of classifying ambient sounds based on the sound spectrogram, using deep neural networks is presented to classify Persian speakers sound for building a voice-controlled intelligent wheelchair.To do this, we used Inception-V3 as a convolutional neural network which is pretrained by the ImageNet dataset.In the next step, we trained the network with images that are generated using spectrogram images of the ambient sound of about 50 Persian speakers.The experimental results achieved a mean accuracy of 83.33%.In this plan, there is the ability to control the wheelchair by a third party (such as spouse, children or parents) by installing an application on their mobile phones.This wheelchair will be able to execute five commands such as stop, left, right, front and back.
Meta-Learning for Relative Density-Ratio Estimation

The ratio of two probability densities, called a density-ratio, is a vital quantity in machine learning. In particular, a relative density-ratio, which is a bounded extension of the density-ratio, has received much attention due to its stability and has been used in various applications such as outlier detection and dataset comparison. Existing methods for (relative) density-ratio estimation (DRE) require many instances from both densities. However, sufficient instances are often unavailable in practice. In this paper, we propose a meta-learning method for relative DRE, which estimates the relative density-ratio from a few instances by using knowledge in related datasets. Specifically, given two datasets that consist of a few instances, our model extracts the datasets' information by using neural networks and uses it to obtain instance embeddings appropriate for the relative DRE. We model the relative density-ratio by a linear model on the embedded space, whose global optimum solution can be obtained as a closed-form solution. The closed-form solution enables fast and effective adaptation to a few instances, and its differentiability enables us to train our model such that the expected test error for relative DRE can be explicitly minimized after adapting to a few instances. We empirically demonstrate the effectiveness of the proposed method by using three problems: relative DRE, dataset comparison, and outlier detection.
Pengaruh Tipe Kepribadian Dan Penggunaan Smartphone Terhadap Hasil Belajar Mata Pelajaran Ekonomi

This study examined to describe the effect of personality type and smartphone use on economic learning outcomes in class XI IPS at SMA Negeri 3 Kota Solok for the 2019/2020. Type of this study is associative quantitative. Population in this study is students of class XI IPS at SMA Negeri 3 Kota Solok 2019/2020, and sample in this study obtained using the slovin formula with proportional random sampling technique. Data analyse technique used is descriptive and quantitative analyse with multiple linear regression. The result of this study showed that 1) Personality type have a positive effect and significant on the economic learning outcomes with sig 0,006 &lt; 0,05. 2) Smartphone use have a negative effect and not significan on the economic learning outcomes with sig 0,640 &lt; 0,05. 3) Personality type and smartphone use have together effect on the economic learning outcomes with sig 0,009 &lt; 0,05.Keywords : learning outcomes, personality type, smartphone used
On the Issue of Evaluating the Cost of Objects of Computer Forensics

The rapid development of computer technologies poses new challenges to experts and requires solving new tasks. The article addresses the issue of determining the cost of objects when conducting forensic computer examinations. The author considers some approaches to determining the market value of the most popular objects (computer tools, an organization’s website) at a specific time, particularly at the time of the crime. The author justifies the notion that the resolution of such issues should be a part of a forensic expert’s specialized knowledge of information and computer technologies since this contributes to solving the tasks of this kind of examination and fulfilling the principles of forensic expertise.
Elementi della competenza comunicativa interculturale / Elements of Intercultural Communicative Competence

In this paper, we examine the possibility of teaching intercultural competence in high schools in the Sarajevo Canton. We conducted an analysis of two coursebooks in use in high schools, prescribed by the curriculum. The research objective is to examine the organization of intercultural teaching. In that sense, we first present an overview of teaching culture, as well as political goals elaborated in Europe during the 1990s. We start from the concept of language teaching and proceed with the definition of intercultural competence and its value according to the White Paper on Intercultural Dialogue, the Treaty of Maastricht and the Common European Framework of Reference for Languages (CEFR). Furthermore, we compare the data obtained by the analysis of the manuals with the goals of language teaching in Europe. The goal of the research is to put focus on elements of intercultural communication competence represented in the manuals to verify if it is possible to reach the goals determined by the Council of Europe. With that goal in mind, we conducted a qualitative analysis of the coursebooks with the aid of two tables of analysis which enable us to execute a contrastive analysis of the manuals and to compare intercultural elements with the counsels of the documents issued by the Council of Europe. Our hypothesis is that the manuals prescribed by the Ministry for Education, Science and Youth of the Sarajevo Canton represent the Italian culture in a traditional manner, and that they do not fully implement the CEFR instructions. This research can further be used in determining which manuals will be in use in high schools as well as in the curricular reform processes.
A study on the efficiency analysis between large and mid-sized Korean construction companies using DEA technique.

Background/Objectives: In this study, we analyze the efficiency of Korean large and mid-sized construction enterprises by utilizing DEA techniques to identify characteristics and review selectable strategies.Methods/Statistical analysis: This study presents a two-stage efficiency analysis methodology in total.The first stage overall DEA calculates the overall efficiency of inputs and outputs.The second stage fundamental DEA calculates the efficiency of individual combinations of inputs and outputs to estimate the variables that fundamentally affect the results of the first stage DEA.As a result, the improvement strategy for becoming an efficient entity is reviewed by deriving inefficient variables.Findings: The first stage DEA found that large/mid-sized construction companies showed different efficiency results.It was analyzed that about 83.5 percent of large construction companies need to scale down, while about 61.1 percent of mid-sized construction firms need to scale up.Statistically, there was also a difference in efficiency analysis of scale between groups of large/mid-sized construction companies.Therefore, it was understood that the efficiency analysis of the construction company should be carried out by considering the differences between the two groups rather than by aggregating them without considering the differences between the groups of scale.On the other hand, the second stage DEA found that even if the overall inputs were more efficient, the partial inputs could be inefficient.That is, the opposite result of the first stage DEA was shown in the second stage DEA.Thus, it was noted that the efficiency analysis of a construction company would need to analyze the second stage fundamental DEA model at the same time, not just the first stage overall DEA model.Improvements/Applications: Although a typical first stage DEA is efficient, a second stage DEA may be different, so it is suggested that a second stage DEA should be combined for efficiency analysis.
FAUST cs-en 0.5

This machine translation test set contains 2223 Czech sentences collected within the FAUST project (https://ufal.mff.cuni.cz/grants/faust, http://hdl.handle.net/11234/1-3308).Each original (noisy) sentence was normalized (clean1 and clean2) and translated to English independently by two translators.
The Intercultural Communication Competence of International Students in Indonesia: A Case Study Approach of Darmasiswa Program

Currently, there are many international students come to Indonesia to learn the language and culture. However, it is undeniable that they experienced a very diverse culture shock when they arrived in Indonesia. There are many differences that they experience ranging from weather, food, different ways of eating, time and delay problems to different type of toilet. This study aims to answer the questions on how they adapt to the new culture, and how to become competent in intercultural communication. This is a qualitative research with a case study approach. Data collection was obtained by semi-structured interviews with 8 international students who are studying language and culture in Indonesia. The results showed that intercultural communication competence can be possessed by international student if they have a motivation to learn that can make them more easily to adapt with new cultures and environment.
On the Convergence of Step Decay Step-Size for Stochastic Optimization

The convergence of stochastic gradient descent is highly dependent on the step-size, especially on non-convex problems such as neural network training. Step decay step-size schedules (constant and then cut) are widely used in practice because of their excellent convergence and generalization qualities, but their theoretical properties are not yet well understood. We provide the convergence results for step decay in the non-convex regime, ensuring that the gradient norm vanishes at an $\mathcal{O}(\ln T/\sqrt{T})$ rate. We also provide the convergence guarantees for general (possibly non-smooth) convex problems, ensuring an $\mathcal{O}(\ln T/\sqrt{T})$ convergence rate. Finally, in the strongly convex case, we establish an $\mathcal{O}(\ln T/T)$ rate for smooth problems, which we also prove to be tight, and an $\mathcal{O}(\ln^2 T /T)$ rate without the smoothness assumption. We illustrate the practical efficiency of the step decay step-size in several large scale deep neural network training tasks.
Enforcing L2 Learner Autonomy in Higher Education: The Top 50 Cited Articles

Learner autonomy as both a pre-condition of self-efficacy and higher achievements in learning and an essential learning outcome has been in the highlight in the higher education domain for many years. This review aims to single out the most influential publications (with 10 citations or more) on foreign language and L2 learner autonomy in tertiary education in the highly reputed journals indexed with the Scopus database, with the publication period limited to the last ten years (2011-2020). The key findings show that the top 50 cited articles on learner autonomy broadly cover conceptual development; self-efficacy and motivation within the learner autonomy concept; educational technologies and web-based activities in fostering learner autonomy; country-specific issues of learner autonomy as the prevailing directions of study in the field of learner autonomy.