Reviewerly/exHarmony huggingface dataset:
A Study on Follow-up Survey Methodology to Verify the Effectiveness of &lt;Life Sharing Class&gt;

<인생나눔교실>은 인문학적 소양을 갖춘 은퇴세대가 멘토가 되어 후속 세대인 멘티에게 삶의 지혜와 방향을 제시하고 소통의 장을 만들어가는 사업이다. 이와 같은 사업의 평가들은 사업이 진행되는 단기간을 기준으로 하여 정량적, 정성적 평가를 수행하는 것이 일반적이다. 그러나 단기간의 평가는 실제 의미있는 효과를 예측하고 판단하기 어렵다는 한계를 가지고 있다. 이에 <인생나눔교실>에서는 2017년과 2018년 영상추적조사를 통해 본 사업의 핵심 참여자의 질적 변화 추이를 살펴보고자 했다. 이를 위해 연구주제에 적합한 조사방법으로 인터뷰 영상 촬영, 촬영 현장 관찰, 가치부호화를 통한 질적연구방법론을 채택하였다. 결과 분석을 위해서는 인터뷰 내용에서 키워드를 추출, 가치부호화 작업을 진행한다. 이후 인문정신가치를 매칭시켜 변화양상을 확인하고 그 의미를 도출하는 이론적 방법을 활용하였다. 실질적으로 본 연구에서 진행한 연구가 추적조사임에도 불구하고 2년이라는 다소 짧은 시간 동안 변화된 양상을 분석했다는 점이 여전히 한계로 남는다. 하지만 국내외 문화예술교육 사업 분야의 추적조사를 위한 모형을 거의 찾아볼 수 없는 현 시점에 추적조사를 위해서 연구자들이 진행해야하는 방법론을 체계화하고 구체적인 적용 사례를 함께 제시했다는 점에서 유의미성을 찾을 수 있다.<Life Sharing Class> is a project for the senior generation with humanistic knowledge to become a mentor and communicate with them to present the wisdom and direction of life to the new generations of mentees based on various life experiences. <Life Sharing Class> has been expanding since 2015, starting with the pilot operation in 2014. In general, projects such as these are assessed to establish effectiveness indicators to verify effectiveness and to establish project management and development strategies. However, most of the evaluations have been conducted quantitatively and qualitatively based on the short-term duration of the project. Therefore, in the case of continuous projects such as <Life Sharing Class>, especially in the field of culture and arts where long-term effectiveness verification is required, the short-term evaluation is difficult to predict and judge the actual meaningful effects. In this regard, <Life Sharing Class> tried to examine the qualitative change of key participants in this project through the 2017 and 2018 image tracking survey. For this purpose, we adopted qualitative research methodology through interview video shooting, field shooting, and value coding as a research method suitable for the research subject. To analyze the results, first, the interview images were transcribed, keywords were extracted, value encoding works were matched with human psychological values, and the theoretical method was used to identify changes and to derive the meaning. In fact, despite the fact that the study conducted in this study was a follow-up survey, it remained a limitation that it analyzed the changed pattern in a rather short time of 2 years. However, this study systemized the specific methodology that researchers should conduct for follow-up and provided the flow of research at the present time when there is hardly a model for follow-up in the field of culture and arts education business in Korea as well as abroad. Significance can be derived from this point. In addition, it can be said that it has great significance in preparing the detailed system and case of comparative analysis methodology through value coding.
Using a Frustratingly Easy Domain and Tagset Adaptation for Creating Slavic Named Entity Recognition Systems

We present a collection of Named Entity Recognition (NER) systems for six Slavic languages: Bulgarian, Czech, Polish, Slovenian, Russian and Ukrainian. These NER systems have been trained using different BERT models and a Frustratingly Easy Domain Adaptation (FEDA). FEDA allow us creating NER systems using multiple datasets without having to worry about whether the tagset (e.g. Location, Event, Miscellaneous, Time) in the source and target domains match, while increasing the amount of data available for training. Moreover, we boosted the prediction on named entities by marking uppercase words and predicting masked words. Participating in the 3rd Shared Task on SlavNER, our NER systems reached a strict match micro F-score of up to 0.908. The results demonstrate good generalization, even in named entities with weak regularity, such as book titles, or entities that were never seen during the training.
IMPLEMENTATION OF C5.0 ALGORITHM FOR SHAPING PATTERNS OF DIAGNOSIS OF DIABETES MELLITUS DISEASE

This study applies the C5.0 algorithm to form a decision tree pattern for diagnosing diabetes mellitus. C5.0 algorithm is a decision tree based classification algorithm. This algorithm focuses on the acquisition of information gain on all attributes. The data used is a diabetes mellitus dataset obtained from the Kaggle database website. Data preprocessing is done and data sharing is done 4 times with the distribution of training data 60% 70% 80% and 90%. Data sharing uses stratafied random sampling methods so that the distribution of training and testing data is in accordance with its portion. Calculation of accuracy performance using confusion matrix. Classification performance using C5.0 algorithm. With 90% training data get 72.73% accuracy of rules generated as many as 70 rules. With 80% training data the accuracy value is 74.03%. The rule is 64 rules. With 70% training data get an accuracy value of 76.52% of the rules generated 59 rules. With 60% training data get an accuracy value of 74.59% of the rules generated as many as 53 rules. From all the experiments that have been done, the best accuracy is found in experiments with 70% training data.
Rondas de encuentros en/para la Formación Docente: la construcción de comunidades de aprendizajes en contexto de pandemia

This article reviews a teacher training experience configured at pandemic context: rounds of virtual meetings. Principals and elementary school teachers, teachers and fourth-year students of the teaching career participated in this experience. They met to share ways of doing chores and knowledge of teaching practice in complex contexts. The implementation of the aforementioned teaching device is sustained by Chartier et all (2019) call cultural conversations as encounters in which the participants carry out a shared construction of knowledge in order to constitute themselves as learning communities.
THE DIAGNOSTICS OF JUNIOR STUDENTS’ INTELLECTUAL AND CREATIVE POTENTIAL

The paper deals with the problem of developing and diagnosing intellectual and creative potential of junior students. The intellectual and creative potential is defined as an integral characteristic of a person. It is the prerequisite for the development and is prognostic and systematic in nature. It is usually manifested in some activities in different spheres and is related to personality transformation. The intellectual and creative potential contributes to self-development of a junior student. Three criteria of intellectual and creative potential have been defined as the result of the diagnostics: cognitive, motivational and creative. The author has also identified five levels of junior students’ intellectual and creative potential
SVM Machine Learning Classifier to Automate the Extraction of SRS Elements

The process of extraction of software entities such as system, use case, and actor from an English natural language description of a user’s software requirements is a linguistic and semantic process of a natural language processing application. Entity extraction is known to be a complicated and challenging problem by researchers in the fields of linguistics or computation, due to the ambiguities in natural languages. This paper presents a named entity recognition method called SyAcUcNER (System Actor Use-Case Named Entity Recognizer), for extracting the system, actor, and use case entities from unstructured English descriptions of user requirements for the software. SyAcUcNER uses one of the Machine Learning (ML) approaches, that is, the Support Vector Machine (SVM) as an effective classifier. Also, SyAcUcNER uses a semantic role labeling process to tag the words in the text of user software requirements. SyAcUcNER is the first work that defines the structure of a requirements engineering specialized NER, the first work that uses a specialized NER model as an approach for extracting actor and use case entities from English language requirements description, and the first time an SVM has been used to specify the semantic meanings of words in a certain domain of discourse; that is the Software Requirements Specification (SRS). The performance of SyAcUcNER, which utilizes WEKA’s SVM, is evaluated using a binomial technique, and the results gained from running SyAcUcNER on text corpora from assorted sources give weighted averages of 76.2% for precision, 76%for recall, and 72.1% for the F-measure.
Domain Adaptation for NMT via Filtered Iterative Back-Translation

Domain-specific Neural Machine Translation (NMT) model can provide improved performance, however, it is difficult to always access a domain-specific parallel corpus. Iterative Back-Translation can be used for fine-tuning an NMT model for a domain even if only a monolingual domain corpus is available. The quality of synthetic parallel corpora in terms of closeness to in-domain sentences can play an important role in the performance of the translation model. Recent works have shown that filtering at different stages of the back translation and weighting the sentences can provide state-of-the-art performance. In comparison, in this work, we observe that a simpler filtering approach based on a domain classifier, applied only to the pseudo-training data can consistently perform better, providing performance gains of 1.40, 1.82 and 0.76 in terms of BLEU score for Medical, Law and IT in one direction, and 1.28, 1.60 and 1.60 in the other direction in low resource scenario over competitive baselines. In the high resource scenario, our approach is at par with competitive baselines.
Veronica Robles Cultural Center (VROCC): an NGO’s Journey in Time of Pandemic

Study Level/Applicability This case study is intended for an MBA level audience; however, it can be used for upper-level college students as well. Subject Area This case's main subject areas include the following: organizational strategy, NGO strategic management, strategy and management during pandemic and women entrepreneurs or women-led business. Case Overview This case is about the organizational strategy of the Veronica Robles Cultural Center, an NGO, during the COVID-19 pandemic. The central challenge of this case study is about decision-making for a sustainable future, given limited resources, and thus a great urgency to plan conservatively. The central protagonist of the case is Veronica Robles herself. Veronica is an entrepreneur in both her personal career as a performing and teaching artist as well as the founder and creator of many programs to help spread culture and unite communities, including the Veronica Robles Cultural Center. Expected learning outcomes Students will learn about entrepreneurial strategy, NGO creation and management, strategy to create social value and organizational management during time of pandemic or widespread crisis. Social Implications This case is focused on creating social value through the analysis of a woman-founded and managed NGO. While managing the NGO's strategy through the COVID-19 pandemic of 2020, operations must proceed with the utmost level of sustainability. With a focus on the well-being of the community, Veronica Robles Cultural Center (VROCC) needs to find a way to remain relevant in the short term while building out a sustainable organizational structure to succeed in the long term. Subject code CSS 11: Strategy Supplementary Materials Teaching Notes are available for educators only.
O Arquivo Nacional na gestão de Eugênio Vilhena de Moraes, 1938-1945

This article aims to present the main characteristics of the Arquivo Nacional under the management of Eugenio Vilhena de Moraes, in the Estado Novo (1938-1945), a period in which the institution, in addition to internally mirroring part of the centralizing practices of the Vargas government, was also called upon to serve two faces of the new-state nation project: the modernization of the public administration and the exaltation of the nation.
Models of Concept Formation

The position taken in the review of experiments on concept formation is a general one, intended more to comment on the field as a whole than on any one position in particular. When individual items are stored in memory, the concept formation process can abstract information from them, rather than only from items as they are presented. The computational theory of concept formation begins by assuming that episodes are stored in memory, having been encoded by whatever schemata exist for processing the episodes. The purpose of this chapter was to present a summary of the major ideas about concept formation. The second purpose of the chapter was to present a computational theory of concept formation that, the people believe, can serve to integrate the facts from the different research areas. Some general comments were made to illustrate how the computational model would account for some of the results discussed in the part of the chapter.
On the Management of Vocal Music Education in Normal Universities

Vocal music education is an important part of the university general education system. It is of great value to cultivate students' aesthetic sentiment, improve their personal accomplishment and humanistic quality, and enhance their ability to appreciate music and beauty. Only by constructing the management mode of vocal music education in Colleges and universities can the quality of vocal music teaching be improved and students get better vocal music education. However, due to the lack of awareness of the importance of vocal music education, many universities have not yet formed a comprehensive and profound understanding of the teaching management mode of vocal music education, which leads to the outdated and backward mode of vocal music education and teaching management, so as to achieve ideal vocal music teaching effect. The problems existing in the management of vocal music education in normal universities are the key factors restricting the education level. The author analyzes and studies the vocal music education management in normal universities and puts forward some suggestions.
Research Guides: Off-Campus Library and Interlibrary Loan Services: Research Help

This LibGuide outlines the policies and procedures for off-campus students, faculty & staff utilizing the services and resources of the Shapiro Library.
Keepers of Structure: In Conversation with Nathaniel Davis

Interview covers understanding environmental contexts of information; complex information problems; models as a way to express structure; focusing on language to communicate the value of information architecture; maintaining a conversation channel open between academics and practitioners.
Semantic Parsing of Brief and Multi-Intent Natural Language Utterances

Many military communication domains involve rapidly conveying situation awareness with few words. Converting natural language utterances to logical forms in these domains is challenging, as these utterances are brief and contain multiple intents. In this paper, we present a first effort toward building a weakly-supervised semantic parser to transform brief, multi-intent natural utterances into logical forms. Our findings suggest a new “projection and reduction” method that iteratively performs projection from natural to canonical utterances followed by reduction of natural utterances is the most effective. We conduct extensive experiments on two military and a general-domain dataset and provide a new baseline for future research toward accurate parsing of multi-intent utterances.
Art Education as a Model for Overcoming the Crisis in Higher Education

The article is devoted to the analysis of the existential crisis of the higher school teacher in modern Russia, diagnosed by professors P. A. Orekhovsky and V. I. Razumov in the article ‘Carnival Time: Russian Higher School and Science in the Postmodern Era’. Various aspects of the activity of a higher school teacher are considered: economic, social, and psychological. The author diagnoses the inflation of higher education in modern Russia. Due to inflation, there comes its obvious devaluation. At the same time, the development of digital technologies radically simplifies access to information and thereby deprives a teacher of the traditional status of a unique carrier of knowledge. Therefore, in modern conditions, a university teacher can not only be a polymath, transmitting knowledge. It is noted that the most important professional quality of a teacher is to be an expert in their field, to possess inalienable skills that cannot be translated into an objectified form. The presence of inalienable, non-objectifiable skills is the main condition for overcoming (or mitigating) the existential crisis of a higher school teacher. One of the main tasks of the teacher is to give a personal expert assessment of the student’s activities. Personal, non-formalized interaction between the teacher and the student is the basis of education in the art field, and it could be a model for higher education in general, become one of the possible ways out of the current crisis of higher education.
How can journalists protect their mental health from online harassment

Journalists have always been in the spotlight and now, with the rise of the use of social media, they are one of the main targets for online harassment. ...
Information Assurance and Allied Aspects Emphasizing IT Risk Management

Information Assurance is the prime move for security and privacy practice. There are huge information generation and development has been done in recent past and on other hand issues related to the privacy and security also a major concern. The growing cyber crime and assurance lead to different types of professional viz. Cyber security analyst, Cyber security expert, IT Manager, IT security analyst, Cyber forensic expert, Ethical hacker, Data security analyst, Web security analyst, Network Analyst, etc. Due to the requirement of manpower different universities have started various wings, centers, schools for the secure Cyber Infrastructure development and Information Assurance practice. Information Assurance is the broader domain in the IT and Computing Security space. The smallest one is cryptography; few other subjects in this context include Computer Security, IT Security, Cyber Security, Information Assurance etc. The paper also talks about Information Assurance including learning, to find out the needs, function and challenges of Information Assurance. The paper highlighted the concept and affairs on IT Risk Management as well.
MEDIATION EFFECT OF WORK ENGAGEMENT ON THE RELATIONSHIP BETWEEN ORGANIZATIONAL LEARNING AND EMPLOYEES’ PERFORMANCE IN KENYAN CONTEXT

The objective of this study was to examine the mediating effect of work engagement on the relationship between organizational learning and employees’ performance in the context of hospitality firms in Kenya. Descriptive and explanatory research designs were adopted for determining the relationships between variables and establishing models of these relationships. Using stratified random sampling, a sample of 225 participants drawn from classified hospitality firms in Kenya was selected. A cross-sectional design was adopted for data collection using a semi-structured questionnaire. Data was analyzed and interpreted using descriptive and inferential statistics. M ultiple regression and correlation analyses were used to measure causal relationship between and among study constructs and test hypotheses. The findings of this study provide evidence that work engagement has positive correlational relationship with organizational learning and employees’ performance and has partial mediation effect on the relationship between organizational learning and employees’ performance. The study established that work engagement is connected to employees’ motivation, morale and job satisfaction. Therefore, firms should manage effectively job level elements such as decision making, scope of responsibility and autonomy in order to create a climate for engaged workers. Keywords : Employees’ Performance, Organizational Learning, Work Engagement CITATION: Njoroge, P, T., Bula, H. &amp; Wanyoike, R. (2021). Mediation effect of work engagement on the relationship between organizational learning and employees’ performance in Kenyan context. The Strategic Journal of Business &amp; Change Management, 8 (2), 29 – 44.
Artificial Intelligence, Machine Learning and Real-time Probabilistic Data for Cyber Risk (Super) – Forecasting

Multiple governmental agencies and private organisations have made commitments for the colonisation of Mars. Such colonisation requires complex systems and infrastructure that could be very costly to repair or replace in cases of cyber-attacks. This paper surveys deep learning algorithms, IoT cyber security and risk models, and established mathematical formulas to identify the best approach for developing a dynamic and self-adapting system for predictive cyber risk analytics supported with Artificial Intelligence and Machine Learning and real-time intelligence in edge computing. The paper presents a new mathematical approach for integrating concepts for cognition engine design, edge computing and Artificial Intelligence and Machine Learning to automate anomaly detection. This engine instigates a step change by applying Artificial Intelligence and Machine Learning embedded at the edge of IoT networks, to deliver safe and functional real-time intelligence for predictive cyber risk analytics. This will enhance capacities for risk analytics and assists in the creation of a comprehensive and systematic understanding of the opportunities and threats that arise when edge computing nodes are deployed, and when Artificial Intelligence and Machine Learning technologies are migrated to the periphery of the internet and into local IoT networks.
Image Forgery Detection using Statistical Moments

Information security is inevitable and indispensable in today’s world. It is found that we have more interactions in online. The threats involved in these transactions make information security necessary. Information security intends to protect the content getting revealed and/or modification of content. Attacks are categorized as active and passive attacks. For active attacks changes the content. Hence security measures against active attacks involve detection of attack. Modification of content generally involves copy-move-forge attack, image re-sampling and image forgery through splicing. This paper deals with identification of image forgery using statistical parameters of the image. Hu moment features are extracted from the image and are used for detection of forgery. In addition local features and global features are used for detection of forgery in the image. Insertion attack, deletion attack and copy-move-forge attack are detected and the detection performances are compared with Difference expansion based methods and evaluated.Keywords- copy-move-forge attack, statistical moments, feature vector
Design of Multipath Waveform Generator Based on FPGA

In order to design a programmable multipath waveform generator, VHDL is used to design every module. It is consisted with the waveform input, FPGA module, digital-to-analog conversion (D/A) module, display circuit. By pressing the keys, eight waves can be chosen and shown in the oscilloscope. With the characteristics of low cost, portable and expandable, it can be widely used in electronic circuit system.