Reviewerly/exHarmony huggingface dataset:
Digital Competence of Post-Pandemic Teachers Based on Gender, Work Period, and Certification Factors

Technological developments must be balanced with the skills of mastering these technological products. Digital competence is highly correlated with the use and awareness of teachers in applying technology to their professional activities. This article presents diagnostic results on Teachers' self-perceptions of their digital competence. The digital competency framework based on DigiComp has five dimensions as an evaluation tool. The sample of this study consisted of 11 upper-middle-level teachers with various characteristics. Questionnaires were used to collect teacher response data. Descriptive analysis is used to diagnose teacher competence. The results showed that teachers have good skills in the aspects of information and data literacy as well as communication and collaboration. Digital content creation and problem solving skills related to the use of technology still need improvement efforts through improving soft skills. Increasing digital competency skills really needs to be pursued to integrate technology into the learning process
Partial permutation decoding for ℤ<sub>8</sub>-linear Hadamard codes

In a previous work it was shown that ${\mathbb{Z}_{{p^s}}}$-linear codes, which are the Gray map image of ${\mathbb{Z}_{{p^s}}}$-additive codes (linear codes over ${\mathbb{Z}_{{p^s}}}$), are systematic by giving a systematic encoding. This makes ${\mathbb{Z}_{{p^s}}}$-linear codes and, in particular, ${\mathbb{Z}_8}$-linear codes suitable to apply the permutation decoding method. This technique is also based on the existence of s-PD-sets, which are subsets of the permutation automorphism group of the code. In this paper, we study the permutation automorphism group of ${\mathbb{Z}_8}$-linear Hadamard codes of type (n;t <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</inf> , t <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> , t <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</inf> ) and show how to find s-PD-sets of minimum size s+1, for all s up to an upper bound, to perform a partial permutation decoding for these codes.
Detection model and experiments of pedestrian fall behavior in cross passages using Baidu AI

In public places, the fall behaviors of pedestrians possibly lead to the disturbances of the crowd, and even cause stampedes. This study deals with the problem of identifying anomalous pedestrian behavior in an effort to stop potential stampedes in public areas. In order to detect the fall behavior of pedestrians in public places, Baidu AI was introduced in this paper to detect key skeleton points of pedestrians in a single frame sourced from surveillance videos. The ratio of human height to width and cotangent value of the direction angle of the pedestrian minimum peripheral rectangle are selected as feature vectors. Fall behavior detection model based on SVM is proposed. Experiments are designed and implemented to validate the proposed fall behavior detection model in this paper. This study can provide technical support for early warning and prevention of possible stampede accidents in public places.
A Curriculum Batching Strategy for Automatic ICD Coding with Deep Multi-Label Classification Models

The International Classification of Diseases (ICD) has an important role in building applications for clinical medicine. Extremely large ICD coding label sets and imbalanced label distribution bring the problem of inconsistency between the local batch data distribution and the global training data distribution into the minibatch gradient descent (MBGD)-based training procedure for deep multi-label classification models for automatic ICD coding. The problem further leads to an overfitting issue. In order to improve the performance and generalization ability of the deep learning automatic ICD coding model, we proposed a simple and effective curriculum batching strategy in this paper for improving the MBGD-based training procedure. This strategy generates three batch sets offline through applying three predefined sampling algorithms. These batch sets satisfy a uniform data distribution, a shuffling data distribution and the original training data distribution, respectively, and the learning tasks corresponding to these batch sets range from simple to complex. Experiments show that, after replacing the original shuffling algorithm-based batching strategy with the proposed curriculum batching strategy, the performance of the three investigated deep multi-label classification models for automatic ICD coding all have dramatic improvements. At the same time, the models avoid the overfitting issue and all show better ability to learn the long-tailed label information. The performance is also better than a SOTA label set reconstruction model.
Pengaruh Penggunaan Metode Point Counter Point Terhadap Keterampilan Menulis Teks Eksposisi Siswa Kelas X SMA N 1 Padang Sago

This research is motivated by the students' skill in writing exposition text which is still low. This study has a purpose, namely the objectives of this study are as follows. First, it describes the writing skills of the tenth grade students of SMA N 1 Padang Sago before using the point counter point method. Second, it describes the writing skills of the tenth grade students of SMA N 1 Padang Sago after using the point counter point method. Third, describe the effect of using the point counter point method on the skills of writing expository texts for X grade students of SMA N 1 Padang Sago. This research method is Point Counter Point. The results of this study indicate that tcount 8.52 &gt; ttable 1.71. The benefits of this research. First, for students of SMAN 1 X Padang Sago to train and motivate students to write exposition texts. Second, for Indonesian language teachers, as a teacher reference in using the point counter point method and as a teacher reference in encouraging students who are less interested in writing.
Upaya Meningkatkan Keaktifan dan Hasil Belajar IPA Materi Bioteknologi dan Produksi Pangan Melalui Penerapan Model Pembelajaran Kooperatif Tipe Think Pair Share pada Siswa Kelas IX-8 MTsN 2 Kota Bima Tahun 2020/2021

This study aims to describe the activities of teachers and students in improving science learning outcomes material Biotechnology and Food Production for class IX-8 MTsN 2 Bima City by applying a Think Pair Share (TPS) cooperative model. This research is a Classroom Action Research (CAR). The subjects of this study were students of class IX-8 MTsN 2 Bima City totaling 32 students. This study was designed based on the Kemmis &amp; Mc. Taggart. The stages of classroom action research developed are: planning, action, observation, and reflection. Data were collected using observation, assessment or test techniques, and documentation. Data analysis used qualitative descriptive analysis techniques that were sourced from data from observations of student activities and data from learning outcomes. The results of this study indicate (a) The application of the Think Pair Share method in learning science of biotechnology and food production is able to increase student activity. This is evidenced by the increase in learning activity from 18.75% or 6 students in the initial study to 43.75% or 14 students, and at the end of the second cycle to 96.88% or all students are active in learning; (b) The application of the Think Pair Share method in science learning of Biotechnology and Food Production is able to improve student learning outcomes. This is evidenced by the class average value continues to increase from 57.81 in the initial study to 62.50 in the first cycle, and at the end of the second cycle to 74.06, and is supported by an increase in learning mastery from 18.75% or 6 students in the initial study, became 14 students or 43.75% in the first cycle, and 96.88% in the second cycle or 31 students completed from the total number of students as many as 32 students
Kesiapan Perpustakaan Sekolah Dalam Pengembangan Koleksi Untuk Menunjang Prestasi Siswa

Planning a good collection development will affect the improvement of students' insight and references to get good achievements. In addition, the fulfillment of the collection will be able to translate the lessons taught by the teachers. In this case, library readiness is needed to support the school's vision and mission to improve student achievement. This study aims to determine the effect of library management on student achievement at SMA Negeri 8 Jakarta. This type of research is quantitative with a simple linear regression analysis approach. This study uses probability sampling where the population is class XI students as many as 354 students and class XII as many as 360 students so that the total population becomes 714 students. The sources of this research come from questionnaires, document studies and interviews. The results of the study found that there was a positive influence between library management and student achievement at SMA Negeri 8 Jakarta. This can be seen from the data processing of SPSS ver 22 calculation results, through statistical testing of the t test. the results of the t count value of 2,915 and t table of 1,998 with a significance of 0,005. With the test criteria t count &gt; t table and if the significance is &lt; (0.05), then H0 is rejected, then in the calculation of the coefficient of determination it is known that the influence of library management on student achievement at SMA Negeri 8 Jakarta is 9% while the remaining 91 percents is influenced by other factors. not researched. The readiness of libraries to increase student predation begins with developing electronic-based library collections and providing access to collections by utilizing OPAC. In addition, to improve information literacy, the library held a workshop on writing scientific papers by inviting well-known writers.
Pemanfaatan Otomatisasi Perpustakaan Dengan Aplikasi SLiMS Versi 9.0 Bulian Dalam Menunjang Kegiatan Pelayanan di SMAN 1 Kertosono

Utilization of information technology is very important to provide the best service in the library and satisfy the information needs of customers who are increasingly complex. The purpose of this research is to find out how the process of utilizing automation in libraries and what obstacles are faced by library managers. This study uses a qualitative research with a descriptive approach which basically wants to explain and describe the truth of a provisional answer. The method used in this study is a survey method that uses interview guidelines as a data collection tool. The data collection techniques used observation, interview and documentation techniques. The data analysis technique in this study uses the Miles and Huberman data model, there are 3 important components in this analysis, including data reduction, data presentation and conclusion drawing. The results of this study indicate that the use of automation in SMA Negeri 1 Kertosono has not run optimally, there are still many obstacles faced by library managers. The obstacles faced by the manager are the media, the internet, workers who do not have a background in the library and software that has not been mastered to the fullest. Utilization of automation at SMA Negeri 1 Kertosono still needs a lot of repairs before it's too late, seeing the many obstacles that exist but it is balanced with the willingness of the managers to be able to change for the better, because for now if you don't follow modern times the library will be far behind the others, especially now that everything is digital.
The Return to the Classroom after the Lockdown: New Challenges and New Education for a New Society

In December 2019, the World Health Organization (WHO) reported the presence of a variant of the SARS-CoV2 coronavirus initially discovered in the city of Wuhan, the People’s Republic of China. With astonishment, the world observed as the increasing contagion curved parallel to the increase in the number of deaths in Asia, Europe, Africa, and America. The pandemic forced everyone to change their lifestyle; all areas of society were affected, especially education at all levels. The confinement responded to the extremely dangerous pandemic with the transformation from face-to-face classes to distance classes, the sudden implementation of digital skills for teachers and students, and the restructuring of courses to correspond to a new reality. In 2022, despite continuing to fight against variants (such as the very contagious Omicron) with the strength that science and vaccines have given it, society has decided to face it and restart its activities, little by little, with a vision of returning to regular activity during 2022 and 2023. In this chapter, we address how this new reality has affected teaching methods in Higher Education, the perspective of education, current theories, and new approaches, and needs that will have to be addressed. Social reality requires the acquisition of new skills now required by employers, the creation of new programmes, and the creation of new evaluation systems.
ANALISIS KESULITAN BELAJAR PESERTA DIDIK KELAS VIII SMP NEGERI 2 MAMBORO

ABSTRACT&#x0D; This study aims to explain the learning difficulties of external factors in class VIII students of SMP Negeri 2 Mamboro, using a survey of 30 respondents who were selected purposively. The approach used is descriptive and quantitative, with data collection using questionnaires and documentation. Furthermore, the data were analyzed descriptively.&#x0D; Data analysis showed that on average each student of Class VIII of SMP Negeri 2 Mamboro had learning difficulties externally of 35.27. Five indicators, namely parenting, study habits in class, class/school conditions, interpersonal relationships, and mental stress contribute to learning by&gt;50%. Two other indicators, namely parental guidance, and family economics contributed &lt;50%. It was concluded that students had learning difficulties caused by factors outside of the students themselves. It is necessary to carry out diagnostic tests and provide guidance counseling for Class VIII students of SMP Negeri 2 Mamboro.&#x0D; Keywords: Learning Analysis
Analysis of School Grouping Against Educational Teachers in NTB Using K-Prototypes Method

The shortage of teaching staff is still a problem in education in Indonesia, resulting in the number of teachers and students being unbalanced. It is very significant based on data from the Analysis of the Distribution of Teachers in Region 3T, which shows that the national ratio of teachers per school is 18.41, and many still have a ratio of teachers per school lower than the national. Therefore, it is necessary to group the data in one of the 3T regions, especially in the Province of West Nusa Tenggara (NTB). The data used for this study were 4997 schools from 8 districts and two cities. The results of this study were conducted to determine whether the grouping ratio of the number of teachers and students is ideal or not ideal. The data used are categorical and numeric data types, so the clustering analysis method used is K-Prototypes. Each cluster produces a different range of teachers and students. Cluster 1, which obtained the High category almost followed the ideal, while Cluster 2 and the Cluster 3 were still far from ideal. This needs to be considered to increase the number of teaching staff in the Education Office in each district.
The Effect of Computer Simulation on Student Performance in High School Chemistry Learning on Chemical Equations

Chemical equations have been identified as a complicated topic in the Nigerian School Certificate. This study investigates the effect of computer simulations on student performance in high school chemistry courses on the topic of chemical equations in Offa, Nigeria. This study adopted a quasi-experimental research design with a pre-test, post-test, and non-randomized control group. The population is all high school students totaling 756 students. The sample was selected purposively, namely 136 students. Chemical Equation Performance Test (CEPT), Online Computer Simulation of Chemical Equations (OCSCE), and Cognitive Force Checklist (CSC) with reliability coefficients of 0.76, 0.81, and 0.78, respectively, were used as instruments for the study. The results of this study are that there are differences in the performance of students who are taught using computer simulations, between the performance of male and female students, and differences in performance between students who score low, medium, and high. It was concluded that computer simulation affected the performance of high school students. It was supposed that computer simulation affected the performance of high school students. It is recommended that future researchers apply computer simulations to other learning.
The doubt behind knowing, and insights in sci-fi: Books in brief

Andrew Robinson reviews five of the best science picks. Andrew Robinson reviews five of the best science picks.
A Chinese text similarity algorithm based on Yake and neural network

Traditional text similarity algorithm has the disadvantage of a large amount of text data and high complexity. Keywords are highly concentrated thematic ideas in the text. Extracting them can reduce the complexity of text similarity calculation. Therefore, this paper proposes a Chinese text similarity calculation method that integrates improved YAKE and neural network(YANN). With Aim to the problem that Yet Another Keyword Extractor(YAKE) algorithm is not suitable for Chinese text keyword extraction, keyword candidate stage. First the new feature value of words is calculated by using word span, position, frequency, word context relevance, and the number of different sentences. Next we calculate the keyword score of each candidate word after synthesizing all the features values, and output the keywords in the ascending order of the score. Finally, the keyword set is inputted into the trained word2vec model for vectorization. Summation and averaging where the keyword vector values are derived from the trained word2vec model, and the similarity between different texts is calculated by cosine similarity. The experimental results show that the method proposed in this paper has better performance than other algorithms in Chinese text keyword extraction, and the similarity calculation results prove the merit of the method used.
CONTEMPORARY TRENDS AND ISSUES OF HIGHER EDUCATION

Contemporary trends and issues of higher educationAccording to statistical data [27], the number of students of higher educational institutions of Ukraine decreased by ~ 10% compared to 2009, but compared to the data for 1999, it increased by almost 35%.However, the reasons for students to get an education 10 years ago were somewhat different.At that time, higher education in Ukrainian society was a sign of a certain status.However, now young people are getting higher education for the purpose of self-expression and self-realization, to achieve the set goal, to build a successful career in the chosen professional field.So, the process of achieving the set goals is perceived in a completely different way, and at the same time, requirements for the training, conducting classes and teaching staff are changing.A modern student is more focused on independent work and work in a
Feature Perception and Refinement Network for Salient Object Detection

To solve the issues that existing salient object detection approaches can not make use of the location advantages of deep semantic information for feature representation and learning, we propose a feature perception and refinement network for salient object detection. Our proposed approach is based upon ResNet-50 to extract multi-level side-output features. Firstly, we utilize three convolution layers to enhance features. And then, we design a global information perception module to extract multi-scale global features. Moreover, we propose to directly fuse the semantic features from deeper layer and the detailed information from shallower layers and refine the saliency features by spatial attention. Finally, the final saliency map is generated by progressively combining different level saliency maps in a coarse-to-fine manner. We compare our proposed model with 12 state-of-the-art methods on four benchmark datasets and evaluate them in term of PR curves, F-measure curves, weight F-measure, mean absolute error and S-measure. The experimental results show that our proposed model is robust and can produce saliency maps with uniform interiors and explicit boundaries in complex scenes.
Stack Overflow Assistant Chatbot Using NLP Techniques

Searching on the Stack Overflow website, a platform for the programming community that features questions and answers on an extensive range of computer programming topics, can be arduous, laborious, and time-consuming at times. Aimed to address this issue, this paper proposes a conversational chatbot to assist with Stack Overflow search. The dialogue chatbot will answer questions related to programming and simulate dialogue and chit-chat on all non-programming-related questions, thus helping users find answers to programming questions present on the Stack Overflow website and also holding conversations with them. Using an access token, the bot is integrated with the Telegram messenger application that serves as a medium for a user to ask questions and for the bot to respond to them. This integration enables us to talk to the bot in Telegram. Results show that the selected algorithms are in accordance with the implementation of the chatbot approach with good test accuracies.
On the Thermal Field Characteristics and Evaluation Method of Intelligent Logistics Storage Space

Intelligent logistics can effectively improve the intelligent analysis and decision-making and automatic operation execution capabilities of the logistics system. In order to optimize the design of the thermal environment of the intelligent logistics storage space and ensure the quality of stored goods and the physical and mental health of logistics and warehousing workers, it is especially important to analyze the thermal field characteristics of the intelligent logistics storage space and work out a reasonable and scientific evaluation method. This paper studies the thermal field characteristics and evaluation method of intelligent logistics storage space. First, based on the five characteristic factors of the thermal environment, a derivation process of the principle of heat transfer in the thermal field of the intelligent logistics storage space was demonstrated. Then, a specific research framework was given for evaluating the thermal environment of storage space, the average number of votes predicted was selected as the main evaluation indicator, and an adaptive model considering factors such as psychology, behavior, and physiology of the workers in the storage space was constructed. Finally, the corresponding analysis and evaluation results were provided.
Digital Image Features Stabilization for Several Different Rotation Modes

Gray and color digital images are used in many vital applications; such as fingerprint or face recognition. These applications require dealing with the digital image as a single image, even if this image is rotated with different rotation angles. This paper deals with using the digital image histogram to set image features and for multiple models of image rotation. A detailed study and analysis of wavelet packet tree decomposition will be introduced; various experiments will be done to show how to stabilize the image features for multiple modes of the image.