Reviewerly/exHarmony huggingface dataset:
HUMAN LIFE SAFETY AS THE METHOD FOR FORMING PROFESSIONAL COMPETENCIES FOR SUSTAINABLE DEVELOPMENT

The article discusses the relevance of studying safety problems and the formation of a safety culture for specialists. In the modern world, with the development of technologies, the need for specialists who have knowledge in the field of sustainable development, are able to ensure the safe implementation of any type of activity, assess the risks and scale of consequences, including analyzing the previous experience of mistakes and wrong decisions, increases. Special attention is paid to educational technologies for the formation of the competencies of safe life in students of higher education institutions in modern conditions.
Hate Speech – What Reduces the Phenomenon in Media

Hate speech can be used as an instrument preferred to exert political influence upon voters during election campaigns. This article provides two examples to support this assumption – the first one is related to a Kirk and Martin’s study on the way main presidential candidates in the USA ran their campaigns in 2016, while the other assumption is related to the current debate in Bulgaria on the National Child Strategy 2019-2030. The present article focuses upon possibilities to reduce the phenomenon’s influence as well as upon some of the challenges researchers and policy makers face in their attempts to limit it.
Research on the Training Mode of Innovative Talents in Finance and Economics from the Perspective of the Integration of Science and Education

In today’s society, under the impact of the tide of informatization, the market urgently needs innovative and compound talents, so it also puts forward high requirements and new requirements for such talents. From the perspective of the integration of science and education, this article takes a case study of financial and economic colleges and universities as an example, on the basis of a practical exposition of the innovative talent training model, it deeply analyzes the innovative talent training model of China’s financial colleges from the perspective of the integration of science and education Some problems in practice, and put forward the realization path.
Using interval type-2 fuzzy logic to analyze Igbo emotion words

Several attempts had been made to analyze emotion words in the fields of linguistics, psychology and sociology; with the advent of computers, the analyses of these words have taken a different dimension. Unfortunately, limited attempts have so far been made to using interval type-2 fuzzy logic (IT2FL) to analyze these words in native languages. This study used IT2FL to analyze Igbo emotion words. IT2F sets are computed using the interval approach method which is divided into two parts: the data part and the fuzzy set part. The data part preprocessed data and its statistics computed for the interval that survived the preprocessing stages while the fuzzy set part determined the nature of the footprint of uncertainty; the IT2F set mathematical models for each emotion characteristics of each emotion word is also computed. The data used in this work was collected from fifteen subjects who were asked to enter an interval for each of the emotion characteristics: Valence, Activation and Dominance on an interval survey of the thirty Igbo emotion words. With this, the words are being analyzed and can be used for the purposes of translation between vocabularies in consideration to context.
The use of digital ICT by teachers and their adaptation to current models

In this article, we present a study intended to verify the importance and adequacy of the use of information and communication technologies (ICT) in the school environment for their greater adaptation to reality This issue is reflected in the general objective, focused on determining the use made by teaching staff of new technologies in classrooms and their impact on the teaching-learning process of their students, taking into account the weaknesses present in the pedagogical foundations put forward by some of the most recent studies on the use and optimization of digital ICT in the classroom The study has a quantitative, non-experimental, descriptive, and correlational design In the study, 100 teachers of Compulsory Secondary Education (ESO) in institutes of Coimbra (Portugal) participated An put forward questionnaire was developed to determine the use and frequency of new technologies in the classroom by the teaching staff The data collected in the questionnaires were analyzed using the Statistical Package for the Social Sciences The main conclusions confirm that there is still a need for an in-depth debate on the epistemological foundations implicit in the use of the new digital tools, and on whether ICTs are an adequate teaching tool, according to the current educational models, in time-cost terms for better student achievement and academic success In fact, the debate is more than ever alive;new technologies have been increasingly implemented in the educational field during COVID-19 pandemics This situation has even implied the suspension of in-person teaching activities that have led to the use of new technologies in the classroom immediately © 2020 Universidad Nacional All rights reserved
An Extensible Framework for Effective Visualizing and Predicting Crimes Using Big Data Analytics

The outcome of the proposed system will help police divisions and law requirement associations to all the more likely comprehend wrongdoing issues and give experiences that will empower them to follow exercises, foresee the probability of occurrences, successfully send assets and improve the dynamic procedure. Crime prediction uses past data and after analyzing data, predict the future crime with location and time. Traditional approaches become less proficient, as their ability to give required outcomes in an opportune way and inside asset limitations. One promising choice to Crime Investigations is to utilize computational devices dependent on cutting edge information examination to forestall and battle wrongdoing. In this way, machine insight and PC displaying ought to be a necessary piece of the Investigations. Computational, as one of the arrangements, brings quick and effective methods for breaking down information to discover minor proof in enormous and unstructured piles of information.
Learning the Independence Movement History Outside School through Participation, Meaning Making, and Communication

This study aims to illuminate the focus of and implication for the current education programs for the Independence Movements in Korea. The out-of-school education programs centered on museums and memorials have encountered students of all ages, which seek to present learning experience by participation, exhibition and learning topics with relevance to learners, and communicative tools with emphasis of meaning making. The Independence Hall of Korea, founded in 1987, has been known as one of the most popular sites for education and commemoration of the Independence Movement. Based on the analysis of the out-of-school education programs, this study suggests that museums and memorials should elaborate ‘doing history’ activities with objects from the collections, and actively wait for students to discover the relevance on their own. Based on critical reflection of the topics and approaches excluded in the current Independence Movement history education, students need to be encouraged to have sufficient free time and opportunities to voluntarily create questions and related themselves with the history of the Independence Movement. By doing so, the chances will increase that students are able to think not only about the period of the Independence Movement in the past, but also about the way their current society celebrates and remembers them in the public history arena and can actively expand their consciousness of history.
Model-Free Energy Distance for Pruning DNNs

We propose a novel method for compressing Deep Neural Networks (DNNs) with competitive performance to state-of-the-art methods. We measure a new model-free information between the feature maps and the output of the network. Model-freeness of our information measure guarantees that no parametric assumptions on the feature distribution are required. The new model-free information is subsequently used to prune a collection of redundant layers in the networks with skip-connections. Numerical experiments on CIFAR-10/100, SVHN, Tiny ImageNet, and ImageNet data sets show the efficacy of the proposed approach in compressing deep models. For instance, in classifying CIFAR-10 images our method achieves respectively 64.50% and 60.31% reduction in the number of parameters and FLOPs for a full DenseNet model with 0.77 million parameters while dropping only 1% in the test accuracy. Our code is available at https://github.com/suuyawu/PEDmodelcompression
Cloud Computing: Security issues

Cloud computing is design for giving figuring administration by means of the web on request and pay per user access to a pool of shared assets specifically organizes, capacity, servers, administrations and applications, without truly obtaining them. So it spares overseeing cost and time for associations. Ordinarily information was put away in Relational Databases on at least one servers situated inside the association and the customers expected to demand information from these server machines. This paper presents point by point investigation of IAAS and its parts. We present how security at IAAS layer should be taken care of cautiously as conveyance models-Platform as a Service and Software as a Service are based upon IAAS layer. We concentrate how IAAS security issues-information insurance and utilization checking, start to finish logging and announcing, foundation solidifying and start to finish encryption should be settled.
Adaptive context-aware correlation filter tracker with multiple detection regions

Correlation filter based tracking algorithms have recently shown favorable performance in terms of high frame rates. However, a significant problem is that the context information is not be fully used which can result in model drift under challenging situations, such as fast motion and occlusion. In this paper, we propose an adaptive context-aware correlation framework which can improve the discriminative power and detect target within a large neighborhood. Firstly, we construct a context-aware correlation filter model and a peak extraction method is proposed to select the context patches adaptively, which can be regarded as hard negative samples mining. Secondly, a simple yet effective multi-region detection strategy is proposed to improve the anti-occlusion ability and prevent model drift. Thirdly, we adopt high-confidence model update method to avoid model corruption. We integrate the proposed framework with the existing DCF tracker, experimental results show that the proposed framework improves the accuracy by 9.1% and the success rate by 7.1%.
전략적 구매관리를 위한 PSM(Purchasing & Supply Management) 프로세스 설계 및 SRM 실행 효과 분석 - SRM시스템 구축 사례 및 성과 중심 -

purpose. This study is about PSM''s process improvement and performance verification in the service and distribution sector. It is intended to present an improvement model for industries that PSM''s process are not settled and overlooked.Methods. In this study, we analyzed PSM methodology, implemented improvements, and analyzed key performance monitoring data to identify the effects expected after the PSM improvement. The dilemma of decision-making for the new supplier evaluation and selection were tested for validity through z-test and Correlation analysisResults. This study shows, After PSM and SRM improvement, quantitative measurement data was obtained that decreased the shortage and order cycle time, increasing work efficiency. The selection and evaluation of supplier through fair procedures increased the satisfaction level of the supplier and increased the level of the supplier creditworthiness. Result of Analyzing the difference in competitiveness between the bidding price and quality of new and long-term supplier, there was no significant difference.Conclusion. The results illustrate that PSM''s procedures can enhance the trust and induce the challenge between buyer-supplier in the service and distribution sector. The management of PSM''s standard work procedures and improving the accuracy of information through the SRM system is a way of strategic purchasing.
Investorsâ€™ Beliefs and Asset Prices: A Structural Model of Cryptocurrency Demand

We explore the impact of investorsâ€™ beliefs on cryptocurrency demand and prices using three new individual-level surveys. We find that younger individuals with lower income and education are more optimistic about the future value of cryptocurrencies, as are late investors. We then estimate the cryptocurrency demand functions using a structural model with rich heterogeneity in investorsâ€™ beliefs and preferences. To identify the model, we combine observable beliefs with an instrumental variable strategy that exploits variation in the amount of energy required for the production of the different cryptocurrencies. We find that beliefs explain a large fraction of the cross-sectional variance of returns. A counterfactual exercise shows that banning entry of late investors leads to a decrease in the price of Bitcoin by about $3,500, or approximately 30% of the price during the boom in January 2018. Late investorsâ€™ optimism alone can explain about a third of the decline.
MIN 23 Aceh Besar لترقية سيطرة التلاميذ على المفردات بــــ Card Sort استخدام وسيلة

The problem found by researcher in class V (B) MIN 23 Aceh Besar is that students are less interested in learning Arabic and make students not active in learning, so mastery in the vocabulary is low, as well the teacher does not use varied media in the learning process. Because of that the researcher tries to overcome these problems with applying cards sort media to improve students’ ability is mastering the vocabulary. The purposes of this research are to identify the effectiveness and student’s responses the application of card sort media to improve ability in mastering the vocabulary. The research method used by researcher is a pre experiment with “one group pre-test and post-test” design, and for data collection, the research used test and questionnaire. The researcher used percentage to analyze student’s responses and the T test to obtain the value of effectiveness. The results of T test to show that the application of card sort media is effective to improve the ability of students in mastering the vocabulary. The result of (T-Test) (-6.077) and the level of significance (sig) which the results. (.000) obtained meaning smaller than the value of the provisions (0.000) &lt; (0.05). And the result of questionnaire showed that the students’ responses to the vocabulary learning by using card sort media is at a high level of 3,67.
Extent scales are licensed by atomic Incremental Theme objects: evidence from begin DP

Dynamic event predicates denote ordered change in some scalar property corresponding to the theme participant. In particular, Change of State predicates map onto property scales (e.g. TEMPERATURE), while Incremental Theme predicates are measured out by the extent of their objects. In terms of VP composition, Rappaport Hovav (2008) proposes that property scales are hard-wired into the lexical semantics of verbs (e.g. heat), whereas extent scales are licensed by Incremental Theme objects. In this paper, I provide new evidence for this hypothesis. The relevant data come from VPs like begin the book, which have only an underspecified Incremental Theme reading. I then turn to examples like begin eight films, which are obligatorily distributive. I use this fact to argue for an even stronger hypothesis: extent scales are licensed by atomic Incremental Themes.
Research and Implemention of System of Electric Business Expanding Installation Process Based on Graph Database

The expansion and installation of electric transformer plays a very important role in the marketing management of electric company, which is closely related to the quality of electric services. With the rapid improvement of the level of science and technology, higher requirements are put forward for the expansion and installation of the electric industry. It is necessary for the expansion and installation of electric transformer to work out a more reasonable and efficient plan with the help of scientific and technological means. The graph database has technical advantages of high efficiency of topological data organization, low redundancy of topological data storage, strong expansibility of topological data model and high efficiency of topological analysis and calculation, which can meet the needs of rapid topological analysis and efficient calculation in the expansion and installation of electric transformer. The results show that the auxiliary system based on graph database can greatly improve the service quality of electric company.
ECP2.5D - Person Localization in Traffic Scenes.

3D localization of persons from a single image is a challenging problem, where advances are largely data-driven. In this paper, we enhance the recently released EuroCity Persons detection dataset, a large and diverse automotive dataset covering pedestrians and riders. Previously, only 2D annotations and image data were provided. We introduce an automatic 3D lifting procedure by using additional LiDAR distance measurements, to augment a large part of the reasonable subset of 2D box annotations with their corresponding 3D point positions (136K persons in 46K frames of day- and night-time). The resulting dataset (coined ECP2.5D), now including Li-DAR data as well as the generated annotations, is made publicly available for (non-commercial) benchmarking of camera-based and/or LiDAR 3D object detection methods. We provide baseline results for 3D localization from single images by extending the YOLOv3 2D object detector with a distance regression including uncertainty estimation.
A year like no other – the ICA during the pandemic

Institutions are important during times of crisis. The pandemic we are experiencing, the worst in over 100 years, has altered our daily lives in every way. Our personal lives are in a defensive pos...
Exploring Optimal Adaptive Activation Functions for Various Tasks

An activation function is a key component of artificial neural networks (ANNs). It has a great impact on the performance and convergence of neural networks. In this work, a self-adapting methodology is proposed to explore the optimal adaptive activation functions for various tasks based on S-shaped or ReLu-shaped activation functions, which are regulated only by introducing several parameters. To verify the effectiveness of the proposed methodology, a series of comparison experiments are performed with MLP, CNN and RNN network structure on the benchmark datasets of image, text and audio. The experimental results are encouraging, and show that the proposed methodology can locate the optimal activation functions for various tasks. Nevertheless, the obtained functions are competitive and the improvements on network performance are significant compared with other popular activation functions, such as ELU, PReLU, ReLU, and Sigmoid.
Practical application and advantages of information technology training in the educational process of higher education

The article considers possibilities of application of information and communication technologies in higher education. The main objective of the article is to justify and substantiate distance learning as a new form of learning. In the article the analysis of forms of education, the main directions of development of distance learning, the differences of distance learning from the traditional. Highlighted problems to be solved by students and teachers in distance education. It is shown that the effectiveness of distance learning is determined by the use of pedagogical techniques that underlie the design and implementation of online courses. It is concluded that distance learning can be considered as an independent form of learning.
A Study on Core Competencies and Perceptions according to Comparison and Participation in the Extra-Curriculum

In this study, the core competencies and the perception of extra-curriculum are conducted a survey to find out the difference between the participating students and non-participating students in the extra-curriculum. The results of a comparison of K-university students on the core competencies and the perception of the extra-curriculum participating students are as follows. First, although the students who participated in the extra-curriculum had higher core competencies than those who did not, the participation of extra-curriculum program were not significantly correlated. Second, it was confirmed that the core competencies of students have been increasing for three years from 2018. Third, students who participated in the extra-curriculum understand the extra-curriculum better, perceive participation more positively, recognize that they are operating properly, and have a better image than non-participating students. In addition, students who participated in the extra-curriculum perceive the degree of improvement lower than non-participating students. Fourth, the students who participated in online extra-curriculum are perceived the effect of the extra-curriculum more highly than non-participating students. Fifth, the students who participated in the extra-curriculum perceive the satisfaction, accessibility, and convenience in the core competency online management system more positively than non-participating students. The discussion and suggestions for this study are as follows. First, participation and encouragement of the online extra-curriculum is necessary. Second, the content of the online extra-curriculum should be highly connected to the subject as required by students. Finally, a systematic exploration of the online extra-curriculum"s quality improvement and participation method is needed.
Simulator String yang Diterima Finite State Automata (FSA) Berbasis Android

Automata is an abstract machine that can recognize (recognize), accept (accept), or generate a sentence in a particular language. There are two types of Deterministic Finite Automata (DFA) and Non-deterministic Finite Automata (NFA). Simulator Finite State Automata is a device that can be used to check the string input in Finite State Automata. The way the simulator works still does not know much about it, through the simulator it is hoped that users are more aware of it.
Attribute Adaptive Margin Softmax Loss using Privileged Information.

We present a novel framework to exploit privileged information for recognition which is provided only during the training phase. Here, we focus on recognition task where images are provided as the main view and soft biometric traits (attributes) are provided as the privileged data (only available during training phase). We demonstrate that more discriminative feature space can be learned by enforcing a deep network to adjust adaptive margins between classes utilizing attributes. This tight constraint also effectively reduces the class imbalance inherent in the local data neighborhood, thus carving more balanced class boundaries locally and using feature space more efficiently. Extensive experiments are performed on five different datasets and the results show the superiority of our method compared to the state-of-the-art models in both tasks of face recognition and person re-identification.