Reviewerly/exHarmony huggingface dataset:
ANALISIS EMERGENCY RESPONSE PREPAREDNESS PADA KESELAMATAN SELURUH PENGHUNI KEBUN BINATANG X

Emergency preparedness is one of the readiness of a place to react constructively to threats from the environment by minimizing the negative impact either on the health or safety of individuals. Zoo X has a number of visitors reaching 1000 people per day. The high number of visitors results in the emergence of a risk in the event of an emergency, minimizing this requires emergency response preparedness. The purpose of this study was to analyze the application of emergency response preparedness for the safety of all residents at Zoo X during an emergency. This research is a descriptive study using qualitative methods by conducting in-depth interviews. There are three main informants and one triangulation informant. The results of this study indicate policies and commitments related to safety at Zoo X in the form of providing safety facilities for visitors. Emergency response planning can be divided into emergencies for visitors and emergencies for animals. Implementation of emergency response planning in the form of providing safety facilities such as first aid kits and APAR as well as a special medical team. Emergency training and simulation activities in the form of training in disaster management, accident management, fire management, and wild animals in collaboration with external parties. Evaluation activities are carried out on the implementation of emergency response planning, implementation, training and simulation
Prediction of a singly reinforced concrete beam steel using artificial neural network

Abstract This paper presents the prediction of a singly reinforced concrete beam using Artificial Neural Networks (ANN). The method was adopted for cost optimization of the structural element and compared with the requirements of Eurocode 2 design. The code provisions for the design of a singly reinforced beam can vary from place to place. The use of a system immune from the code variation is an excellent means of predicting the reinforcement’s need of a rectangular concrete beam. In this work, an artificial neural network (ANN) is employed to forecast the reinforcement of such a beam. Artificial neural network has the potential to simulate the data that are hard to produce in arithmetical analysis. The scheme was established using the MATLAB tool kit. The design variables were the depth of the beam, the width of the beam, and the moments. A forward pass supervised backward propagation training. The regression analysis of the results is one to one match. The predicted and target values are completely in accord.
Taxation, foreign aid and political governance in Africa

This study examines the hypothesis that foreign aid dilutes the positive role of taxation on political governance. The empirical evidence is based on the Generalised Method of Moments and 53 African countries for the period 1996-2010. For more policy options, the dataset is disaggregated into fundamental characteristics of African development based on income levels, legal origins, natural resources and landlockedness. While the hypothesis is invalid in baseline Africa, low income and English common law countries of the continent, the research cannot conclude on its validity for other fundamental characteristics of development. Policy implications, caveats and directions for future research are discussed.
The Persistence of Weapons: Global Evidence

This study investigates persistence (or hysteresis) in weapons using a panel of 163 countries for the period 2010 to 2015. The following are some main findings. (i) Compared to countries that are landlocked, persistence in heavy weapons is more apparent in nations that are open to the sea. (ii) Relative to the Middle East & North Africa (MENA), heavy weapons is more persistent in the East Asia and the Pacific countries. This tendency is consistent with “weapons imports”. (vi) Evidence of persistence is not very apparent in “weapons imports” with the exception of the fact that it is higher in low income countries, compared to their high income counterparts. Hence, there is less hysteresis in weapons exports when compared with heavy weapons when weapons exports. (v) The determinants of persistence employed in the conditioning information set are contingent on fundamental characteristics and panels. Policy implications are discussed.
An Analysis of Heterogeneity Effect of Leadership on the Quality of Work Life of Agricultural Extension Staff, Using FIMIX Algorithm

Current empirical research was conducted with the aim of examining the role of leader-member exchange quality on the quality of work life of employees. The statistical population was consisted of employees of the Agricultural extension in Tehran province, among which 51 were selected as the sample. Respondents were selected by simple random sampling method. The research tool was a questionnaire whose validity was verified by face validity, structural validity and discriminant validity, and reliability coefficients including Cronbach's alpha and ordinal tetha showed satisfied reliability. The dominant statistical method was partial least squares modeling which, by calculating its coefficients and using the finite Mixture algorithm, the intangible heterogeneity classes in the research data of the research are explored and by matching the results of the classifier composition of FIMIX on the LMX scale, it became clear that the leader-member action space architecture followed the organizational dual architecture. The results of the research show that in the organization of agricultural extension in the area of leadership task, the employees, who are in the out-of-band environment, experience adverse work life quality and are likely to be exposed to burnout conditions. Therefore, it seems that studying the architecture of organizational leadership space is an important step in improving human resource management. Given that leadership is very important for stimulating social change, improving its organizational leadership can have a significant impact on the social system's preparedness for change. By combining the results of this research with the theory of contingency leadership and transformational leadership, a comprehensive leadership model can be found from the point of view of determining the favorable climate of the leader-member's action and reducing organizational conflicts.
Are Inconclusive Decisions in Forensic Science as Deficient as They Are Said to Be

Many quarters of forensic science use reporting formats such as “identification,” “inconclusive,” and “exclusion.” These types of conclusions express opinions as to whether or not a particular person or object is the source of the material or traces of unknown source that is of interest in a given case. Rendering an “inconclusive” conclusion is sometimes criticized as being inadequate because — supposedly — it does not provide recipients of expert information with helpful directions. In this paper, we critically examine this claim using decision theory. We present and defend the viewpoint according to which deciding to render an “inconclusive” conclusion is, on a formal account, not as inadequate as may commonly be thought. Using elements of decision theory from existing accounts on the topic, we show that inconclusive conclusions can actually be viable alternatives with respect to other types of conclusions, such as “identification.”
A Characterization of Dante Alighieri: An NLP approach to The Divine Comedy

The main goal of this research is to offer a new perspective of Dante Alighieri and his most famous work: The Divine Comedy based on natural language processing. We seek to provide rigorous evidence to enhance literary analysis on The Divine Comedy. We utilized sentiment analysis, text classification and topic modeling. We analyzed both the original Divine Comedy written in Italian, and the Divine Comedy translated to English. We also used natural language processing to compare the Divine Comedy to a variety of Shakespeare’s plays and poems.
The Impact of Problem Solving Style on Innovative Behavior - Focused on Moderating Effects of Core Self-Evaluation and Perceived Supervisory Support -

As the competition among the firms, the conventional way of firms became useless for the competition and tried to search for innovation. In pursuing innovation, firm realized that firms’ innovation starts from individual members’ behaviors and created the concept of innovative behavior. Innovative behavior draw lots of attention and a large number of studies has been conducted up to now. Recent Kwon & Kim’s (2020) literature review on innovative behavior showed little attention to individual trait like personality. In this background, our study shortly reviewed on the studies about the relationship between personal trait and innovative behavior and set the direction of this study. After short review, we found that there is not a few studies about the relationship between personality and innovative behavior but little about the relationship between innovative behavior and the personal traits except personality. So we focused on the problem solving style which drew the attention as antecedents of innovative behavior at early stage of research on innovative behavior and core self-evaluation which are suggested relatively recently and very limitedly studied as the antecedents of innovative behavior. The studies on personal traits pay attention not only to their effects on consequences but also to the relevant situation that can activate the relationship between trait and trait relevant behavior following trait activation theory. In the vein, we also considered in the supervisory support as the potential moderating variables on the relationship between problem solving style and innovative behavior. For the empirical test, we collected data from the 228employees belong to Chinese public companies with survey and analyzed the relationship with hierarchical regression analysis. First, only intuitive problem solving style except systematic problem solving style showed significant positive effect on innovative behavior. Second, in the case of core self-evaluation, its main effect on innovative behavior was supported but none of its moderating effects on the two path from problem solving style to innovative behavior. Last, in the case of supervisory support, its main effect on innovative behavior was supported and the moderating effect on the path from intuitive problem solving style to innovative behavior was supported. On these results. We discussed the theoretical and practical implications.
Annotating Hate and Offenses on Social Media.

This paper describes a corpus annotation process to support theidentification of hate speech and offensive language in social media. Inaddition, we provide the first robust corpus this kind for the BrazilianPortuguese language. The corpus was collected from Instagram pages of politicalpersonalities and manually annotated, being composed by 7,000 documentsannotated according to three different layers: a binary classification(offensive versus non-offensive language), the level of offense (highlyoffensive, moderately offensive and slightly offensive messages), and theidentification regarding the target of the discriminatory content (xenophobia,racism, homophobia, sexism, religion intolerance, partyism, apology to thedictatorship, antisemitism and fat phobia). Each comment was annotated by threedifferent annotators, which achieved high inter-annotator agreement. Theproposed annotation approach is also language and domain independent,nevertheless, it was currently applied for Brazilian Portuguese.
Econometric Approach of the Nexus between Remittances and Economic Growth in Western Balkans

Purpose: The purpose of this research paper is to highlight the importance of remittances in the economic development of a country, with special emphasis in Western Balkan countries. Design/Methodology/Approach: This paper is based on the study of theoretical issues, OLS model, fixed (FE) and random (RE) effect model. In addition Hausman test has been applied to determine the appropriate model among Fixed and Random effects. Revealing the results of the Hausman test the Random effect model is considered as the appropriate model, and it implies the existence of positive and significant relationship between remittances and GDP per capita growth in the Western Balkan countries for the time period 2000 - 2018. Findings: Results based in OLS model findings reveal a positive relationship between remittances and GDP per capita growth. Also the results of the random and fixed effect model reveal positive and significant effect of remittances on the economic growth, thus by increasing remittances the GDP per capita will increase. The results also present that Gross Fixed Capital Formation has a positive impact on the economic growth, where by increasing Gross Fixed Capital Formation, the GDP per capita will increase. Practical Implications: The results of this research are supportive regarding the relationship between remittances and economic growth, yet will contribute to the existing literature as well as for further policy recommendations by the Western Balkan countries. Originality/Value: This research paper is an empirical analysis based on the data provided by the World Bank, for the time period 2000-2018.
Intelligent Management Mode of College Counselors in the “Internet Thinking” Era

With the continuous growth of Internet information technology, almost everyone in today's society is affected by the Internet. As young people in the new era, college students are at the forefront and influenced by the Internet. Therefore, college counselors should also change the traditional management mode, and actively adopt the intelligent management generated by the “Internet thinking” to create a more harmonious learning environment for students.
ПРОБЛЕМЫ ИСПОЛЬЗОВАНИЯ ОСНОВНЫХ ДОСТУПНЫХ ОБРАЗОВАТЕЛЬНЫХ ПЛАТФОРМ НЕОБХОДИМЫХ ДЛЯ ОРГАНИЗАЦИИ УЧЕБНОГО ПРОЦЕССА В ДИСТАНЦИОННОЙ ФОРМЕ В УСЛОВИЯХ COVID -2019

The implementation of the distance education system is not possible without the use of modern educational platforms. The functions and tools for the implementation of modern educational platforms should be linked to the main pedagogical tasks facing the teachers and the educational institution as a whole. Exploring the problems of introducing educational platforms into the activities of modern Russian educational institutions, the authors note a number of difficulties that have intensified during the COVID-2019 pandemic. The authors believe that the real answer to the difficulties that arise is the need for Russian educational institutions to focus not on the use of individual tools and platforms, but on the construction of educational ecosystems. Such a choice will require from Russian universities not only the accumulation of the available internal resources, but also the solution of long-standing problems in the field of staffing of distance education, as well as in the field of copyright protection for the content created within the framework of distance work formats.
Prevention of Sexual Harassment through the Information Services Using the Contextual Teaching and Learning Approach in the Senior High School

This article discusses the prevention of sexual harassment through information services using the contextual teaching and learning approach. The research was conducted using quantitative method with experimental approach. This study population of high school students, whose samples were taken using cluster random sampling. Data were collected using a sexual harassment questionnaire as well as data analysis with Wilcoxon signed ranks test and a 't' test. After the research found that information service using contextual teaching and learning approach is effective in preventing teenage sexual abuse in high school. Teenagers from high school do sexual harassment as much as 27.37%. The most sexual abuse conducted by adolescents is verbal sexual abuse as much as 66.66%, visual as much as 62.69% and physical as much as 44.83%.
Text Complexity Dynamics in Russian Textbooks on “Environmental Studies”. The Case of the 2nd Grade

To comprehend an academic text is one of the main tasks for pupils of both elementary and secondary schools. Developing of reading skills is viewed as one of the most important questions for teachers, scientists and is a cause for concern to schoolchildren's parents. The aim of the present research is to investigate the dynamics of text complexity in the textbook “Environmental studies” (written by A. Pleshakov, 2012) for pupils of the second grade of comprehensive schools. The textbook consists of two parts, with twelve texts in Part I and sixteen texts in Part II. The corpus compiled for the research comprises twenty-eight texts from the stated textbook. The academic year of second class pupils is divided into four quarters. Consequently, the first part of the textbook, that is 12 texts, is studied in the first two quarters – from September to December. The second part – 16 texts - in the third and fourth quarters: from January till May. The texts differ in syntactic structure and length. Syntactic simplicity was evaluated on the basis of the mean number of words in the sentence, number of syntactic structures, number of words before the predicate, and the number of simple and composite sentences. Contrastive analysis of texts in both parts did not reveal obvious dynamics in complexity. The texts in both parts tend to have similar quantity of simple and composite sentences. However, the texts from the first part of the textbook are shorter, but sentences are longer and they are more elaborated than sentences of the second part. Syntactic simplicity of texts varies across the textbook.
SWOT Analysis of TCFL Courses in MOOC Platform of Chinese Universities

This paper takes MOOC (Massive Open Online Courses) platform of Chinese Universities as an example to study the development of Teaching of Chinese as a Foreign Language (TCFL) courses, and uses SWOT analysis to analyze its strengths, weaknesses, opportunities and threats. Finally, it suggests that to help more Chinese learners, it is necessary to further build online open courses based on MOOC.
SCIENCE IN THE MEDIA: RECONNECTING STUDENTS TO REALITY

Appears in: INTED2021 Proceedings Publication year: 2021Pages: 4827-4830ISBN: 978-84-09-27666-0ISSN: 2340-1079doi: 10.21125/inted.2021.0975Conference name: 15th International Technology, Education and Development ConferenceDates: 8-9 March, 2021Location: Online Conference
Feature Selection Using Ensemble Techniques

Data used in Machine Learning tasks need to be pre-processed and prepared to improve its quality. Features or variables in data play a major role in the results obtained after applying Machine Learning models. The features which are irrelevant to the domain should be discarded with the objective of improving the accuracy and validity of results. For this purpose, Feature Selection is used. It is a way of reducing the size, the purpose of settling down to the right element from the original elements by removing the negative, redundant or noisy features. Feature selection can often result in better learning performance, such as, lower computational cost, and better model translation. It is very important to shed some light on the nature of feature selection for student performance measurement, because constructive educational approaches can be found in the appropriate set of features. Feature selection plays a major role in refining the quality of the data models. Increased data quality can produce better results and therefore based options for such quality data can increase the quality of education by predicting performance. In the light of the aforementioned fact, it is necessary to carefully stabilize the selection of the algorithm. Feature selection key can directly affect classification accuracy and simplify operation. Several data experiments were performed to demonstrate the effectiveness of the proposed method. Selective bias may also be the term used in data analytics. In this paper, two ensemble techniques namely, Random Forests and Gradient Boosting Machines have been applied on a dataset, for the purpose of Feature Selection. Experimental results show that Gradient Boosting Machines are better at Feature Selection.
A Study of Programming Languages and Their Bug Resolution Characteristics

IEEE Bug resolution is an essential part of software development. The impact of programming language on bug resolution has been a topic of much debate. Taking Python as an example, some hold the view that bugs in the language are easy to handle because its code is easy to read and understand, while others believe that the absence of static typing leads to more bug-handling effort. This paper presents the first large-scale study that investigates the connection between programming language and bug resolution characteristics. It follows the recent trend of empirical scientific reformulation of long-standing, but hitherto anecdotal, `great debates' about the influence of programming language and paradigm on software engineering concerns. We analyse bug resolution data from over 70 million SLOC drawn from 3 million commits to 600 GitHub projects in 10 languages. The results suggest that statistically significant differences in resolution time and patch size exist between different languages and language categories. In particular, Java bug resolution consumes less elapsed time from raise to resolve, while Ruby consumes more. We also found that patches tend to touch significantly more files for strongly typed and for static languages (as one might expect given the need to maintain type annotations). However, despite this apparent extra effort, we found evidence for a significantly lower elapsed resolution time for bug resolution committed to projects constructed from statically typed languages. This finding sheds further empirical light on the debate about the importance of static typing. Indeed, more generally, we found no evidence for any correlation between bug-resolution time and size (lines or files touched), nor any evidence for correlation with other potential confounding factors, such as problem features (e.g., size, age, and commit number) and target domain.
Graph Sampling with Distributed In-Memory Dataflow Systems.

Given a large graph, a graph sample determines a subgraph with similar characteristics for certain metrics of the original graph. The samples are much smaller thereby accelerating and simplifying the analysis and visualization of large graphs. We focus on the implementation of distributed graph sampling for Big Data frameworks and in-memory dataflow systems such as Apache Spark or Apache Flink. We evaluate the scalability of the new implementations and analyze to what degree the sampling approaches preserve certain graph metrics compared to the original graph. The latter analysis also uses comparative graph visualizations. The presented methods will be open source and be integrated into Gradoop, a system for distributed graph analytics.