Reviewerly/exHarmony huggingface dataset:
Few-shot Named Entity Recognition: Definition, Taxonomy and Research Directions

Recent years have seen an exponential growth (+98% in 2022 w.r.t. the previous year) of the number of research articles in the few-shot learning field, which aims at training machine learning models with extremely limited available data. The research interest toward few-shot learning systems for Named Entity Recognition (NER) is thus at the same time increasing. NER consists in identifying mentions of pre-defined entities from unstructured text, and serves as a fundamental step in many downstream tasks, such as the construction of Knowledge Graphs, or Question Answering. The need for a NER system able to be trained with few-annotated examples comes in all its urgency in domains where the annotation process requires time, knowledge and expertise (e.g., healthcare, finance, legal), and in low-resource languages. In this survey, starting from a clear definition and description of the few-shot NER (FS-NER) problem, we take stock of the current state-of-the-art and propose a taxonomy which divides algorithms in two macro-categories according to the underlying mechanisms: model-centric and data-centric. For each category, we line-up works as a story to show how the field is moving toward new research directions. Eventually, techniques, limitations, and key aspects are deeply analyzed to facilitate future studies.
Estimating Human Poses Using Deep Learning Model

Over the past decade, extensive research has focused on the extraction of 3D human poses from images. The existing datasets must effectively address common challenges related to pose estimation. These datasets serve as valuable resources for evaluating, informing, and comparing different models. Deep learning models have gained widespread adoption and have demonstrated impressive performance across various domains of research and engineering. In this study, we employ these models, leveraging the open-source libraries OpenCV and Keras. To enhance the diversity and complexity of the training and testing process, we utilize the MPII Human Pose dataset. Specifically, we train and test the ResNet50 and VGG16 models using this dataset, resulting in significant improvements. The model's performance is evaluated based on the validation rate of the dataset and the accuracy of our model was 88.8 percent for VGG16 and 67 percent for ResNet50.
Clinical outcome of patients with diabetes mellitus infected by SARS-COV-2

Introduction: Diabetes, a chronic metabolic disease with high prevalence in Brazil, is a risk factor for severe SARS COV-2 infection. The relationship between previous glycemic control and the prognosis of patients hospitalized with COVID-19 is not fully understood. Objective: analyze the clinical outcome of patients with diabetes mellitus infected by SARS-COV-2. Outlining: A retrospective analysis of medical records was carried out using the Trakcare electronic system of all diabetic patients hospitalized with a confirmatory diagnosis of pneumonia due to COVID-19 in the medical clinic ward of HRAN, from June to August 2021, who, upon admission, performed the glycated hemoglobin test and analyzed it using the SPSS software (20.0). Results: A sample of 52 patients was obtained during the study period. Most patients are female, with a mean age of approximately 58 years. The comorbidity most associated with the participants was systemic arterial hypertension, with most diabetics presenting good prior glycemic control, represented by HbA1c ≤ 7%. The lethality found was 7.7%. Implications: The study shows a high lethality of diabetic patients infected by COVID 19, but no statistical significance was found for HbA1c levels with the increase in length of stay, use of non-rebreathing mask, need for invasive mechanical ventilation or lethality
J. Daniel Subías - In-the-wild Material Appearance Editing using Perceptual Attributes

We rely on an encoder-decoder architecture G that encodes the image x, and manipulates the latent space z together with the target attribute att t to generate the edited image y.We use skip connections with STU cells, a variant of the GRU [1,2], which allow encoder-decoder architectures to keep the relevant information of the input image in the edited output when manipulating the latent space z.High-level overview of our framework.Our generator G is composed of an encoder G enc and a decoder G dec .It is capable of editing the input image x according to the target attribute att t to generate the edited image y.
Transformation of Education: Teaching and Learning during the pandemic and post pandemic

The Covid-19 pandemic and the social distancing that followed have impacted all strolls of society, also education.In order to keep education running, educational institutions have needed to quickly adjust to the circumstances.This has resulted in an exceptional push to online teaching and learning.The student was submersed in Education 3.0.Virtual stages appeared, connectivity and communication between students and teachers expanded, and a more personalized and intelligent learning model was applied.Then again, the key element of Education 4.0 is innovation, and it has profoundly modified the way in which people live, work and establish associations with others.Moreover, before Covid-19, there has been expanding critique of how technology, is rethinking and reducing ideas of teaching and learning.The paper also challenges the account that claims, 'education is broken, and it ought to and can be fixed with technology'.This paper will provide a critical review of the ongoing literature on Education 4.0, distinguishing trends that are arising and the challenges that Education sector might face.We are in a period where trial needs to continue before we can observe the clear implications or outcome (s) of what Education 4.0 might involve for the future of education.
Element-removal global digital image correlation for accurate discontinuous deformation field measurement in fracture mechanics

We propose an element-removal (ER) global digital image correlation (DIC) method to improve the measurement accuracy of discontinuous deformation fields, such as crack propagation. The occurrence of cracks in materials or structures inevitably deteriorates the tracking accuracy, and, consequently, the strain field accuracy obtained by regular subset and global DIC. The proposed ER-global-DIC algorithm iteratively identifies and removes all the elements covering the crack, during the updating of displacement fields. In the remaining elements, the continuous shape function is applicable for accurate deformation measurement. In principle, although elements that contain the crack are removed, the algorithm preserves the same number of nodes since the nodes are retained by the remaining elements. Synthetically deformed images based on analytical discontinuous displacement fields validate the effectiveness and accuracy of the proposed method. The ER-global-DIC is further applied to measure the discontinuous displacement fields containing a crack deflection, generated from a finite element model with a cohesive zone model. The results demonstrate the potential of the proposed method for discontinuous deformation measurement on advanced materials, e.g., fiber-reinforced composites.
A Need Analysis for Learning English to Young Learners

A growing body of literature has discussed need analysis in a certain domain. The issue raised since English to Young Learners was important to support the process of language learning in the classroom. The present study was employed to investigate student's need analysis, especially for the teaching of English to young learners in the elementary school level. The data were collected through questionnaires, interviews, and analyzing the documents of sample students. Questionnaires were distributed to 25 students of grade 5A and 5B, and interviews were conducted with an English teacher of grade 5 at an elementary school in Jakarta. The findings revealed that the students were expected to master language skills so that they could be more confident in reading and writing. Furthermore, they also have several preferable topics to be discussed in the learning process such as family and friends, foods, or meals. They prefer to have topics that could be related to their daily life and their background knowledge. Moreover, there are several factors that may hinder the teaching of reading and writing. The irrelevant topics to their daily life and interest, lack of vocabulary knowledge, and anxiety in writing were the factors that made them hard to read and write. Therefore, the development of class materials needed to be relevant to students' needs. Keywords: Need Analysis, English to Young Learners, Learning Materials
The Development of TANAKA Android-based Application as an Information Media for Taka Bonerate National Park

This study aims to determine the development of the TANAKA application as an Android-based information media for Taka Bonerate National Park. The quality of the application was evaluated based on the ISO 9126 quality standards. The application was built using Adobe Flash CC software. Data was collected using interview techniques, questionnaires, and documentation. The application was validated by two media experts and two content experts. The application was evaluated by 30 respondents, and the data was analyzed using descriptive statistical analysis techniques. Based on the research results, an application was developed that can be used as an offline Android-based information media for Taka Bonerate National Park. According to the ISO 9126 testing, the following results were obtained: a) functionality testing using black box testing method scored 1 with an excellent category and fulfilled the functionality aspect; b) reliability testing using white box method was free from logical errors; c) portability testing on various types of smartphones and different versions of Android ran smoothly without any issues; d) usability testing with 30 respondents resulted in a percentage of 93.33%, with 28 respondents rating it as excellent and a percentage of 6.67% or 2 respondents rating.
A Genre Analysis of Science and Technology Scopus-Indexed Journal Articles: Does Impact Factor Project Different Rhetorical Moves?

Productivity in conducting research and publishing articles is the obligation of lecturers as academics. However, due to their failure to follow international writing conventions, they have difficulties in writing for international publications. Various studies have investigated the rhetorical move of research articles; however, much still needs to be investigated on the rhetorical move of the research articles written by highly reputable lecturers by comparing their publications in low-impact versus high-impact Scopus-indexed journals. This study aims to analyse the rhetorical structures of research articles in low and high-impact articles written by highly reputable lecturers in one of the universities in West Java in science and technology. Eight research articles were analysed through the framework of the move proposed by Maswana et al. in 2015. The results showed similarities and differences between the two groups. Stating a purpose, methods, and results in the abstract section was obligatory. In the method section, recounting an experimental process was always present in both groups. Interestingly, the difference was shown in stating the research implications in the conclusion part, where high-impact frequently used the move more than low-impact articles. The results show that the impact factor partly projects rhetorical moves in the research articles. This study is expected to be a useful reference for Indonesian lecturers to develop their awareness of writing an impactful research article.
Deep Learning-Based Modulation Identification for OFDM Systems

This paper deals with a deep learning (DL)-based automatic modulation classification (AMC) method for orthogonal frequency division multiplexing (OFDM) systems. Among DL methods for AMC, convolution neural network (CNN) has been widely studied to classify the modulation scheme used in the OFDM systems. Although conventional CNN has performed well in previous studies, its classification performance can be degraded when an additional modulation scheme is considered. In this paper, we investigate the CNN-based AMC for the OFDM systems to improve the classification performance by using a deeper CNN model with a residual connection. Through computer simulations, we show that the proposed model outperforms the conventional CNN model for various ranges of training signal-to-noise ratios in terms of classification accuracy.
PENGEMBANGAN MEDIA PEMBELAJARAN APLIKASI ANDROID INTERAKTIF BERBASIS PPT PADA MATERI TEKS PERSUASI KELAS VIII

This research was conducted to answer problems and provide solutions for schools based on the results of interviews and analysis of student needs. The purpose of this research is to produce a product and find out the feasibility of developing ppt-based interactive android application learning media on class VIII persuasive text material. This study uses a research and development approach or R&amp;D (Research and Development) with data collection techniques, namely interviews and questionnaires. The test subjects involved 18 teachers/practitioners and class VIII students to assess the feasibility of learning media. The results of the material expert validation test were 95%, media experts were 97.5%, linguists were a percentage of 80%. The overall rating average is 90.8%, which is in the proper category to use. The results of the teacher's response questionnaire obtained a percentage of 97.5% and the student response questionnaire of 80.8% included in the appropriate category and could be used as a learning medium during the teaching and learning process in class
ANALISIS KEMAMPUAN GURU DALAM MENINGKATKAN MOTIVASI BELAJAR SISWA PADA PEMBELAJARAN PKN SDN X BATUSANGKAR

In an effort to boost the learning motivation of high school elementary school students, the teacher's efforts to leave this learning open at the end of the PKN semester. Understanding and improving student learning outcomes in PKN learning can be supplemented by increasing learning motivation. The aim of this study was to identify teacher tools to increase the learning motivation of high school elementary students during PKN classes. This study uses a qualitative case study methodology. The method used to gather information for this study is called objective sampling. In this research instrument, the researchers themselves collected data using observation techniques, questionnaires, and document analysis. Data analysis techniques use data collection, editorial, display, and conclusion steps. The guarantor of the validity of the data in this third study combines the method of collecting data by combining triangulation. The results of the study indicated the need for greater motivation to teach high grade students during Internship classes. One of the factors that causes students' learning motivation to be lower than it should be is their exposure to less than ideal learning environments and less than ideal teaching methods. Therefore the advice given by the teacher to increase student learning motivation is to use teaching strategies that can do this. This includes offering counselling services and using ice-breaker activities such as games and ice hockey.
Analysis of student management path optimization in higher education institutions with ISM

Abstract With the national emphasis on vocational education and the reform of the examination and enrollment system of higher vocational education, the scale of students in higher vocational colleges and universities has been expanding, and the enrollment channels and student source types have been diversified, especially the characteristics of student source in local higher vocational colleges and universities are more prominent. The traditional student management mode has been difficult to meet the needs of students’ development and talent training mode. As an important part of education and teaching in colleges and universities, the effectiveness of student management determines the success or failure of ideological and political education of college students and the safety and stability of colleges and universities and is also related to the cultivation of high-quality technical and skilled talents needed by the society. Therefore, taking Jiyuan Vocational and Technical College as an example, this paper finds that 66% of the teachers and students think that the student management concept is backward, 58% think that the student management mode is single, 74% think that the student management system is not perfect, 58% think that the student management mode is rigid, and 59% think that the student management personnel are not of high professional quality in student management. The analysis of the results shows that using the hierarchical student management model based on ISM analysis makes the student management model with reasonable and effective articulation and operation, scientific and smooth implementation, and builds a set of effective student management systems in higher vocational institutions, which has certain theoretical and practical significance for the implementation of student management in higher vocational schools.
Identifying the Accuracy and Comprehensibility of Students’ English Word By Word Pronunciation at North Lombok Senior High School

Pronunciation is an important component of language learning that must be well mastered in order to support the development of students' competence in language skills, particularly speaking skills. This descriptive research aims to evaluate the accuracy and comprehensibility of English pronunciation among tenth-grade IPS students consisting of 30 students at SMAN 1 Bayan in North Lombok. Qualitative methods were employed, using student voice recordings as primary data and relevant documents as secondary data. The data analysis technique in this study uses the concept of qualitative data analysis developed by Miles and Huberman in (1994), including data reduction, data display and conclusions drawing. The results showed that while some students demonstrated excellent proficiency in English pronunciation, others faced significant challenges in accurately articulating vowel and consonant sounds. These findings highlight the importance of targeted interventions to support struggling students and improve the pronunciation skills of all students. The research questions are focused on the accuracy and comprehensibility of English pronunciation among students in North Lombok. Through our evaluation, we found that the level of accuracy in common words varied among students, with some struggling to pronounce even basic words accurately.
THE SEROK RIVER CATCHMENT FLOOD HYDROGRAPH

Global climate change is expected to cause an increase in the intensity and duration of extreme rainfall events that occur today. The leading cause of flooding in various world regions, including flat coastal areas such as the Serok River catchment in Kota Pontianak, influenced by tides, is excessive rainfall. This article presents the results of an analysis of the impact of extreme precipitation on the peak discharge of flood hydrographs in the Serok River catchment, Kota Pontianak.Maximum daily rainfall data for 2009-2020 recorded at PTK-11 Pontianak Station were selected using the Annual Maximum Series Method. Frequency analysis was conducted using the best distribution method selected from Normal, Log Normal, Log Pearson Type III, and Gumbel Type I to obtain the design rainfall. The design rainfall was transformed into flood hydrographs at the next stage using the Snyder Synthetic Unit Hydrograph based on several return periods.The results of the analysis show that there are changes in flood discharge in the Serok River catchment area for each return period. The location of land use and the value of rain intensity significantly affect the calculation of plan discharge; the more significant the land area and the higher the rain intensity, the greater the resulting release. The most considerable flood discharge (Qmax) in the 2, 5, and 10 years return occurs at STA 1 + 100, w.290 m3/s, 0.347 m3/s, and 0.377 m3/s, respectively. Thus, this causes periodic flooding/inundation conditions, especially in areas that have low elevations.
ANALYSIS OF THE TYPES AND CHARACTERISTICS OF THE TIDES USING THE ADMIRALTY METHOD ON TWO RIVERS IN THE KUBU RAYA DISTRICT

A study of the tides in the river has been carried out in this paper. The rivers studied are the Jawi River (Kakap) and the Nipah River. The two rivers are located in Kubu Raya Regency, West Kalimantan. This study aims to determine the type of tides and water level elevation in the two rivers. This study uses the Admiralty method to analyze existing tidal data. This method is commonly used in tide analysis. The results show that the tidal type of the Jawi River is a diurnal tide. The water level in the Jawi River is HHWL of 1.4 m (+0.86 m from MSL) and LLWL of –0.319 m (-0.859 m from MSL). Meanwhile, the tidal type of the Nipah River is a mixed tide prevailing diurnal. In addition, the water level is HHWL of 1.167 m (+0.82 m from MSL) and LLWL of –0.473 m (-0.82 m from MSL). This study is expected to be helpful as a reference for infrastructure development in the research area.
Blockchain-based data management mechanism for virtual power plants

Abstract With the gradual deepening of power-related research and the expansion of power data volume, power data-oriented research and applications have fully entered the era of big data and cloud storage. The huge amount of heterogeneous data samples also bring a huge impact on traditional data processing methods. Therefore, let each virtual power plant participate in the electricity market externally as a unified power plant, and build a blockchain structure of multiple virtual power plants in the form of a slice. The structured data such as the basic information of the account is stored in the enterprise database in a relational data model and managed through an identity verification policy. The mechanism of off-chain negotiation and on-chain settlement is used to manage the transaction data. The management mechanism is further improved by combining an encryption scheme and a security evaluation method. After the practical test of the management mechanism, the time consumed for one and two parallel operations reaches 23 seconds and 8 seconds, and 4 seconds and 9 seconds or less for three and four times, respectively. In the case of nine users’ data distortion, the root means the square value of the blockchain data management mechanism is only 0.82, which is significantly less than 1. It shows that the blockchain-based data management mechanism, as a new generation of power data management means, can not only effectively integrate the power grid information data and relieve the pressure of the power grid system, but also avoid data leakage and strengthen power security.