Reviewerly/exHarmony huggingface dataset:
TLBIONER: TRANSFER LEARNING BASED NAMED ENTITY RECOGNITION ON MEDICAL LITERATURE DOCUMENTS

Nowadays, Natural Language Processing (NLP) plays a significant role in extracting the concealed information from the unstructured data which is being loaded with voluminous data over the web. Various tasks such as Tokenization, Stemming, Parts-of-Speech identification, Lemmatization, Named Entity Recognition (NER), etc are being popular in NLP research area. In recent years, NER is getting more attention among the researchers to extract the important entities from the huge set of documents. In life science domain NER is playing major role to identify the medical-term entities from the medical related documents such as literature documents, clinical trials, Electronic Medical Record (EMR), etc. This research work aims to provide a new NER approach to get the named entities from the medical literature documents. Instead of build and trained a new model, the proposed model works based on the Transfer Learning. In order to reduce the training time, the pre-trained model is re-trained with the newly annotated entities. The proposed NER produces better accuracy and able to identify a greater number of entities. The NER model is experimented with PubMed articles.
A Survey of Pre-Service English Teachers’ Reading Habits of English Text

Reading should become a habit for pre-service English teachers. The habit gives significant contribution in both academic and teaching performance. The purpose of this study was to determine the habit of reading English texts for pre-service English teachers. Data was collected through surveys and validation interviews. Questionnaires were distributed to 42 students of English Education at a university in Bogor, West Java using random sampling technique. This study found that the pre-service English teachers’ reading habits of English texts are not in the good category. Based on data analysis, it can be said that they have been reading English texts for more than 12 years. However, it turned out that during more than that period they were not used to reading well and some of them had expressed not having a good habit of reading English texts. This is because they do not read English texts regularly; they tend to read Indonesian texts more often. Some obstacles were identified in reading English texts, such as not being used to reading for a long time, and lack of vocabulary. On the other hand, they have a goal in reading, one of which is to increase their knowledge and English skills. This goal can be achieved by reading English texts regularly. Their plan is to read English texts regularly and ensure positive beliefs that are motivated by themselves, for the goals they want to achieve.
Penggunaan Aplikasi Whatsapp Groupping Terhadap Hasil Belajar Menulis Geguritan Di Masa Pandemi Covid-19 Pada Siswa Kelas 9H SMPN 1 Karanggayam, Kebumen

Covid-19 is a big challenge for Indonesians, it affects various aspects, in addition to economic aspects many aspects are also harmed by Covid 19 aspk other aspects, namely aspectsofEducation. This research aims to find out the results of learning to write in the pandemic period in students of grade 9H SMPN 1 Karanggayam, Kebumen in the 2nd semester of the 2020/2021 school year and to find out the learning results of students in using the WhatsApp Grouping application. The method used in this study is a descriptive quantitative research method, with a sample of students of SMPN 1 Karanggayam. This research data collection technique uses observation techniques, questionnaires and recording techniques. The data collection instrument used in the study was an online learning questionnaire. The results of research in the use of WhatsApp media showed that the results of learning to write a rebuke against the results of grades that are not 100% most students have grades that are less or below KKM
Pengaruh Kondisi Sosial Ekonomi Orang Tua terhadap Hasil Belajar IPS Terpadu Siswa

The family environment, especially the parents, is the most important and main dimension. For children's development both physical and psychological development. If the socioeconomic conditions of the parents are good and sufficient. From the results of this simple research, the following conclusions can be drawn: (1) The socio-economic conditions of the class parents 8 SMP Negeri 1 Sambit in the academic year 2020/2021 in general can be said to be in the moderate category, namely with a percentage value of 63%, (2) Learning outcomes in the cognitive domain of Integrated Social Studies subjects students grade 8 SMP Negeri 1 Sambit in the academic year 2020/2021 general it can be said that the cognitive learning outcomes of Integrated Social Studies subjects are grade 8 students of SMPN 1 Sambit is in the medium category, namely with a percentage value of 70%, (3) the socioeconomic conditions of the parents are influential significant.for the results learning in the cognitive realm SMP Negeri 1 Sambit year 2020/2021 school year is indicated by a value because the significance value is 0.000 &lt;0.05, which means that it fails to reject H0.
PROFESSIONAL SELF-DETERMINATION OF SCHOOL STUDENTS IN EARLY ADOLESCENCE

Abstract. The article discusses the issues of a stable idea of themselves, about their capabilities, their preferences, this, in turn, is called "self-determination". This topic of professional self-determination of a schoolboy has always gained attention. The choice of profession depends in the future, what kind of person you will become, how the environment reacts to you, or realize yourself as a "person". Currently, "self-determination" can be considered as a psychological neoplasm of adolescence. As already mentioned, the term "self-determination" is used in different meanings. We can assert this in family, religious, professional, moral self-determination. The changes that are taking place in our country in the labor market require some modernization to solve the problem of professional self-determination of a modern student. Therefore, at the school level, this problem still remains open with vocational guidance and the choice of profession. Therefore, it is a task to correct the needs of the economy and society, to enjoy the profession. To solve these problems is called part of the propaganda, but it cannot be argued that professional enlightenment is based only on propaganda. The planned work, which is carried out at the school on campaigning and propaganda, should be carried out in accordance with the previously conceived professional organization, on the basis of such approaches it is possible to carry out appropriate work with schoolchildren and direct to sobriety of consciousness in the direction of choosing a profession. Enlightenment is based on the needs of this profession in society. Thus, it is necessary to introduce certain preparatory courses, where students are prepared for the choice of profession, take into account the skills and abilities, help to obtain an initial qualified category from a certain profession. Also, an acquaintance with the profession is carried out in order to learn it well and understand it.
Permissions access meta-management implementation using BML in the BlockSet project

Development of a web-resource today is a very frequent and not always simple task. Especially if we are not talking about a static one-page website, but about a dynamic web application with an unlimited number of pages, as well as the ability to withstand heavy loads, typical of such projects. To solve these problems, there are very few ready-made solutions. Of the best ones, perhaps, only WebDSL can be distinguished, but even it has a number of drawbacks inherited from the Java project implementation language, such as, for example, low flexibility, high performance costs and the need to install a java-machine. The development process was carried out using a relatively low-level C++ general purpose programming language, which saved the project from the problems that its competitors faced, ensured high interpreter performance and cross-platform system-wide. The authors described in detail the selected means of the meta-management of the access rights of the BlockSet project, as well as the syntax of their use in the declarative highly abstract subject-oriented language BML, using simple and accessible examples to demonstrate the conciseness, but the constructiveness of the selected syntax solutions. The results obtained are of great value, as they significantly simplify the further process of administering a web resource, which is also one of the main tasks of the BlockSet project. Thus, the BML language, together with the system of access rights, provides flexible, powerful, and at the same time fairly simple and understandable methods for organizing the required system, which corresponds to the project’s paradigms on flexibility and a low threshold of entry, and also significantly optimizes the development process.
Image Recognition Technology with Its Application in Defect Detection and Diagnosis Analysis of Substation Equipment

Detection of substation equipment can promptly and effectively discover equipment overheating defects and prevent equipment failures. Traditional manual diagnosis methods are difficult to deal with the massive infrared images generated by the autonomous inspection of substation robots and drones. At present, most of the infrared image defect recognition is based on traditional machine learning algorithms, with low recognition accuracy and poor generalization capability. Therefore, this paper develops a method for identifying infrared defects of substation equipment based on the improvement of traditional ones. First, based on the Faster RCNN, target detection is performed on 6 types of substation equipment including bushings, insulators, wires, voltage transformers, lightning rods, and circuit breakers to achieve precise positioning of the equipment. Afterwards, different classes are identified based on the sparse representation-based classification (SRC), so the actual label of the input sample can be obtained. Finally, based on the temperature threshold discriminant algorithm, defects are identified in the equipment area. The measured infrared images are used for experiments. The average detection accuracy achieved by the proposed method for the 6 types of equipment reaches 92.34%. The recognition rate of different types of equipment is 98.57%, and the defect recognition accuracy reaches 88.75%. The experimental results show the effectiveness and accuracy of the proposed method.
Approach to Prediction of Unmasked Face from Masked Face using Deep Learning

Due to the outbreak of COVID-19, it has become mandatory for each and every person to step outside only with a face mask on.This has raised the security and safety concerns among people as faces of criminals, burglars, etc are not recognisable through the CCTVs and security cameras.This problem can be tackled with the help of deep learning.In this paper, a model that can predict the unmasked face of a person from a masked face input image, giving an unmasked face image as the output was implemented.The accuracy achieved by the model is 91%.This paper ends with a review of the model"s usefulness and its scope for further development and improved results in the future.
Development of a management system for an R&amp;D terminology dictionary

To provide advanced information retrieval and intelligent services using AI and big data processing technologies in R&D sectors, an R&D terminology dictionary that reflects classification information in national R&D fields is required.This study proposes the R&D terminology dictionary construction processes and develops a management system based on these processes.The proposed system supports efficient terminology extraction and cleansing by applying step-by-step processes for establishing R&D terms that reflect research field information using keywords and the Science and Technology Standard Classification of national R&D projects.After automatically extracting and cleansing keywords from the project information, the frequency of each term is calculated.Subsequently, a terminology dictionary is automatically constructed based on these frequencies, and term searching and merging via cleansing criteria functions are utilized for terms subject to manual cleansing.At NTIS(National Science &Technology Information Service), information concerning approximately 57,000 projects is collected yearly.Therefore, the step-by-step terminology dictionary construction and cleansing processes of the R&D terminology dictionary management system proposed in this study can be used to include new terms that occur each year.The proposed system enables users to select the terms related to the desired R&D field of R&D information via the search function of the developed terminology dictionary and perform an extended search using Korean-English terms or related words.As such, the system allows the users to accurately and efficiently find desired information.
Assessment of Computational Complexity and Methodologies of Pattern Matching Algorithms

Complexity Theory is a formal mathematical theory, in which we study computational problems and algorithms to solve those problems.In complexity theory we need to analyse the program in terms of the efficiency of the program, lines of the code, finding out that the program is able to find out the correct answer or output, figuring out whether one program is better than the other program.An algorithm here means the programming code through which the given problem will be solved.It is step by step procedure to perform a desired task.
The Inclusion of Differentiation in Literacy Lessons in the First and Second Grades of Slovenian Primary School

In the modern educational process, teachers adapt lessons to the student’s individual abilities, prior knowledge, interests and social skills. The present study, whose aim is to examine the inclusion of differentiation in literacy lessons in the first and second grades of Slovenian primary schools, was carried out on a smaller scale (N = 79). It aims to determine the views of first- and second-grade primary school teachers on differentiation, and to find out how differentiation takes place in literacy lessons and which factors affect student performance in class. The results show that the inclusion of differentiation in literacy lessons is present in the entire initial literacy teaching process, and that Slovenian teachers undergo regular training and professional development courses in this area, thus contributing to the educational success of students and affecting their personal growth and development. Teachers estimate that the intertwining of individual abilities, family environment, engagement in co-curricular activities and well-developed social skills represents a key factor in student success. It was expected that internal differentiation would be more effective than external differentiation. Surprisingly, however, teachers report that heterogeneous groups do not enhance educational efficiency.
Higher Order Thinking Skills of Children Aged 4-6 Years in Early Language Learning Based on Lesson Study

This study aims to describe the higher order thinking skills of children aged 4-6 years in early language learning based on lesson study. The research method used descriptive qualitative. The subjects of this study were B group students of Telkom Preschool Ternate in 2020/2021 academic year. Data collection was carried out using direct observation, in-depth interviews and documentation that explored children's abilities of critical and creative thinking aspects. Data were analyzed which followed to the three main steps; data reduction, data presentation and verification, and concluding. The study found that early language learning based-on lesson study activities can stimulate children's abilities in critical aspect; 18 students (81.8%) answered questions and retold and 4 students (18.2%) are able to interpret stories. Meanwhile, in creative thinking aspects 10 students (45.5%) have criteria that often appear of completing assignments in the form of the work given by the teacher. The children identify the problem, giving various responses and comments; become active learner both collaboratively in completing sharing and jumping tasks on ‘ profession’
Library Human Resources Management Concept a Perspective of Lasa HS Thinking on Richard E Rubin

Background of the study: Library human resource management is a very important part of the continuity and development of librarians. The librarian must have a constructive and dynamic concept of thinking so that the role that is raised is the result of a structured implementation. Through his work, Lasa HS has succeeded in formulating this theory in his book "Library Human Resource Management" which has close analysis with Richard E. Rubin's "Human Resource Management in Libraries Theory and Practice".&#x0D; Purpose: The purpose of this study is to examine the perspective of human resource management in the Lasa HSlibrary on one of Richard E Rubin's works entitled Human Resource Management in Libraries Theory and Practice.&#x0D; Method: Through a library research approach (library research) which is supported by interviews&#x0D; Findings: Research results show that there is a relevance of the theory proposed by Lasa HS to the work of Richard. E Rubin in the aspect of measuring the performance of human resources.&#x0D; Conclusion: It can be concluded that through the books that have been written, both have explained the theory in a structured manner with the dynamics of different cultural approaches so that they complement each other in providing reviews on library human resource management.
Robust Deep Interpretable Features for Binary Image Classification

The problem of interpretability for binary image classification is considered through the lens of kernel two-sample tests and generative modeling. A feature extraction framework coined Deep Interpretable Features (DIF) is developed, which is used in combination with IntroVAE, a generative model capable of high-resolution image synthesis. Experimental results on a variety of datasets, including COVID-19 chest x-rays demonstrate the benefits of combining deep generative models with the ideas from kernel-based hypothesis testing in moving towards more robust interpretable deep generative models.
Mysteries of the Epicenter and Magnitude of China’s Mount Taishan Earthquake Solved

The Mount Taishan earthquake, which named after Mount Taishan, occurred in 1831 BCE.It was the earliest historical earthquake recorded by historical writing-materials in China.However, seismic geologists have been unable to find any seismic-geological records or traces of the historical earthquake in the Taishan area and its surroundings.The epicenter and magnitude of this earthquake have remained unsolved mysteries.Through seismic and geological investigation and research, authors identified seismic records with soft-sediment deformation structures from the Holocene Heituhu Formation(Q4H) of the limnetic facies with soft soil layers in the Anqiu area (about 200 km from Mount Taishan) of the Yishu fault zone in the middle segment of the Tan-Lu fault zone, including seismic subsidence syncline, pinch-and-swell structure, as well as co-seismic micro-fault, and so on.Seismic subsidence
Writing Skill in Teaching English: An Overview

Writing skill is a hard skill among others because it has to be a concern more about it, and we need to follow some rules that related to every single step, they are word choice, coherent, correlation, and grammar. The students should choose the proper word to express meaning so that the readers catch what information they wrote. The information of each paragraph, main idea, and the argumentation of the researcher should be coherent. Grammar also plays important role in writing. The use of correct grammar will not be confusing the readers. Moreover, the error of using grammar will make a serious misunderstanding toward the readers. The successful of learning writing is not merely depending on the students, but it needs a teacher contribution to reach the learning of English writing.
ANALYSIS OF THE UTILIZATION OF E-LEARNING BY LECTURERS AT PANCA SAKTI BEKASI UNIVERSITY

This study aims to describe qualitatively about e-learning management in the current Covid-19 pandemic era. This research is a descriptive qualitative study that aims to define and describe phenomena that appear natural or artificial, focusing more on examining the character, quality, and phenomenon. Besides, the e-learning approach is an approach using technology distance learning. The e-learning utilization that is arranged using an electronic internet system that supports learning activities. The method used in this research is qualitative with descriptive analysis. Research subjects are Informantss who provide research data through interviews, observation, and documents. The Informantss in this study were lecturers at Panca Sakti Bekasi University. The Informantss were determined by purposive sampling technique. At the same time, the data analysis used in this research is descriptive. This research results in the finding that lecturers have carried out web e-learning with Moodle and face-to-face with zoom or google meet in managing learning during the Covid-19 pandemic. as numerous as 80% of speakers expressed that they utilized zoom, this was on the grounds that it was simpler to apply it straightforwardly, like instructing up close and personal classes. At that point, as numerous as 55% of Google Meet clients, the instructor expressed that Google Meet is not difficult to actualize on the grounds that the video is straightforwardly associated on the off chance that you as of now have a Google Mail account straightforwardly. Lastly, as numerous as 85% of teachers use Moodle, on the grounds that Moodle gives more highlights to learning exercises.
Efficient Sparse Representation based Action Recognition in video

Human Action Recognition (HAR) is an interesting and helpful topic in various real-life applications such as surveillance based security system, computer vision and robotics. The selected features and feature representation methods, classification algorithms decides the accuracy of the HAR systems. A new feature called, Skeletonized STIP (Spatio Temporal Interest Points) is identified and used in this work. The skeletonization on the action video’s foreground frames are performed and the new feature is generated as STIP values of the skeleton frame sequence. Then the feature set is used for initial dictionary construction in sparse coding. The data for action recognition is huge, since the feature set is represented using the sparse representation. To refine the sparse representation the max pooling method is used and the action recognition is performed using SVM classifier. The proposed approach outperforms on the benchmark datasets.