Reviewerly/exHarmony huggingface dataset:
Ingesting Structured Descriptive Data into Pandoc

Ever since I found out about Structured Descriptive Data (SDD) I keep coming back to it. Right now I am planning to make two identification keys, one translated and modernized from a 1961 publication for which I have not found a good alternative, and one completely &lt;em&gt;de novo&lt;/em&gt; (well, nearly). In both cases, I started writing out the key in a word processor with a numbered list and tabs and manual alignment etc., but in both cases that experience was pretty bad so far.
Penerapan Feature Selection Pada Algoritma Decision Tree Untuk Menentukan Pola Rekomendasi Dini Konseling

Early detection in providing recommendations for student counseling is very important, therefore you can assess the student's potential, beliefs, and attitude as early as possible. The problem that arises in this case is how to detect a student early so that he or she needs counseling assistance or not so that it can be identified early to minimize the risk of further psychological conditions. This article proposes a data mining model using a decision tree to classify counseling recommendations for students. In addition, to improve the resulting accuracy performance, a feature selection method is proposed using forward selection and genetic algorithms. The stages of the research were carried out by pre-processing the data, implementing algorithms, validating data, and optimizing the model. The experimental results show that the best level of accuracy using the decision tree model is 95.64%. It increases to 96.91% after optimization using the genetic algorithm.
ANALISIS PERBANDINGAN PENDIDIKAN KARAKTER ANTARA NOVEL LASKAR PELANGI DENGAN NOVEL 9 SUMMER 10 AUTUMNS

This study aims to examine the comparison of character education values between the novel Laskar Pelangi and the novel 9 Summer 10 Autumns. The research uses a qualitative approach with a content analysis method. Data collection was carried out using test instruments. The results of this study show that the two novels have similar plots and show that the two novels both tell about struggles from childhood to adulthood to achieve their dreams. Both novels also share the educational value of the characters we researched. The value of character education that we examined in these two novels is on the value of honesty, religious value, tolerance value, discipline value, and hard work value. As a suggestion, both novels are very good to read because they contain the story of children's struggle to achieve their dreams to be successful in the future. These two novels are very inspiring and can foster a sense of enthusiasm, never give up, tolerance, religious observance, loyal friends, cooperation and hard work in living daily life. For the rest more in-depth research needs to be done
Analisis Sentimen Tindakan Pemerintah Indonesia Dalam Penanganan Covid-19 Menggunakan Metode Support Vector Machine

Corona Virus Disease 2019 (Covid-19) which has hit the world including Indonesia since the beginning of 2020 is an outbreak that has become a serious threat to world health. The Indonesian government is taking various actions to deal with this problem, while the public, with the existence of social media, has provided many responses to these government policies. Twitter is one of the social media that is widely used by the public to convey comments in the form of responses, suggestions, to criticism of the government regarding the handling of Covid-19. The comments that appear should be used by the government as part of the reference in evaluating a policy or action taken in handling Covid-19. So that one way that can be used to deal with this is one of the methods that exist in the domain of text mining, namely sentiment analysis. This research was conducted by analyzing sentiment using the Support Vector Machine (SVM) method with the Kernel Radial Basis Function (RBF). Tweets will be classified into positive, negative and neutral sentiments, so that the percentage of each opinion category can be known. This study uses data of 600 tweets obtained from the results of scraping using a Twitter scraper. The result of this study is that the training accuracy rate is 77% in classifying positive, negative, and neutral sentiments. From the results of the data classification, it was found that most of the tweets consisted of negative sentiments.
APPLICATION OF THE APRIORI ALGORITHM TO DETERMINE THE COMBINATION OF POVERTY INDICATORS

Poverty is a society that has not been solved until now. The decline in poverty in Laweyan District from 2000 to 2013 was 5.71%, among the five lowest in the reduction in the percentage of poverty in Central Java Province. The problem of poverty is very complex, and the differences in regional characteristics, as well as the techniques used, also influence the indicators of the causes of poverty and the formulation of policies for poverty alleviation. This study uses Principal Component Analysis as part of data preprocessing, followed by applying association rules with the Apriori Algorithm to explore the relationship pattern of poverty indicators. Based on the research that has been conducted on the poverty dataset, which consists of 46 attributes, it is found that the attributes that have passed the preprocessing data are six attributes, namely the Poor Population, ADHB in the Communication Sector, ADHB in the Mining and Excavation Sector, ADHB in the Agriculture and Food Crops Sector, ADHB in the Plantation Sector. and unemployment. These six attributes are transformed into Ascending, Fixed, and Descending categorical data. The fuzzification process for the increase and decrease categories uses the shoulder-type triangle membership function. Applying the Apriori Algorithm to the poverty dataset with a minimum support of 0.4 and a minimum confidence of 0.8 produces 38 rules that show the relationship between indicators and poverty and 134 rules that show the relationship pattern between indicators.
Open Learning Environment for Multimodal Learning Based on Knowledge Base Technology

With the development of Internet technology, multimodal data have become the main data resource in the information age. Multimodal learning mode, as an education and teaching mode developed on multimodal data technology, provides more convenience for multimedia teaching. However, many challenges persist in its actual development and application. Currently, the multimodal learning model is susceptible to classroom noise, lack of teaching information, and other factors, which adversely affect multimodal data collection, teaching application, and achievement output. Thus, this paper optimizes the multimodal learning model in the open learning environment and takes 120 engineering students from a university in Guangxi Province as the research object. First, a sequential modal extraction method is proposed by constructing a multimodal probability generation model and then the data are modeled. Semi-supervised learning is then achieved by analyzing and combining the supervised and unsupervised learning processes. Finally, the knowledge base technology with information fusion characteristics is applied to the multimodal teaching mode. This teaching mode has been proven to improve students’ learning ability and learning achievement and teachers’ teaching effectiveness.
Development of a Target-Based Configurable Business-to-Business Model for Electronic Wholesale Information System in East Java

Until the end of 2021, most of the electronics wholesale market in East Java has found obstacles in contract administration and monitoring of consumers’ sales targets managed conventionally in contract management and sales target monitoring aspects. This phenomenon becomes complicated because most wholesaler systems have specific rules of management. The research discusses information systems that can be configured for various business processes in the wholesale sale of electronic goods. The case-study approach is applied by analyzing, designing, constructing, and validating the new proposed system based on three case studies with different business processes. The result of the analysis phase explains minimum sales value, the number of item variants in sales, verification rules for sales supervisors, and the configuration of user access rights that are highly flexible when applied. This system is developed as web-based to make easy access to multiple platforms to accommodate flexibility. The result summarizes that companies have the power of freedom to customize their target and help them to monitor wholesale store sales to meet sales target achievement. Alternatively, suppose companies create their new sub-companies with different targets and segments. In that case, they can easily configure target sales rules without spending significant money on developing another application.
Analysis of the feasibility of integrating innovative education into higher mathematics education

This paper takes the establishment of coordinate system, the establishment of calculus system and the discovery of t-distribution in advanced mathematics as a case to introduce what is innovation and entrepreneurship education in higher mathematics, further lists the Bertrand theory and other cases to illustrate the diversity of mathematical conclusions, discusses the basis of the integration of higher mathematics education and innovative education, and then expounds the necessity of integrating higher mathematics education with innovative education at the level of Maslow's psychological needs, and finally discusses the strategy of integrating innovative education in higher mathematics education.
Sistem Pengambilan Keputusan Penentuan Jurusan Pada Jenjang Sekolah Menengah Atas Menggunakan Model Yager

Education is very important in supporting the intelligence of each individual, from an early age it starts to recognize many things in each level of education. Knowledge and abilities continue to develop until determining interest in the right major according to the values, abilities, desires and character of each individual student. In reality, the process of determining majors, especially at the high school level, is carried out in grade X, but this process can be done when students register, for example at Dharma Praja Denpasar High School. There are assessment criteria used in the process of determining students' major interests, namely the Average Report Card Score (C1), Science Test Score (C2), Social Science Test Score (C3) and Psychological Test Score. Applying the Yager model so that the process of determining the weight of the criteria can be done with the concept of a pairwise comparison matrix, another advantage is the process of calculating the intersection of alternative values on each alternative so that it can produce suggestions for majoring interests. The study used 5 alternative students with suggestions for majoring in science and social studies. The results showed that the Yager model could provide recommendations for the best majoring options for 5 alternatives, namely alternative A1 for science majors with a value of 2.19067, while alternatives A2, A3, A4 and A5 obtained recommendations for social studies majors. Features of the web-based major determination decision support system produce the ability to manage alternative data, criteria, alternative values, majoring processes, final results and there are test features that students can do on the system, making it easier for students to make majors and schools to recapitulate the process of determining majors. The results of blackbox testing for a total of 8 scenarios show that the system functionality is running well.
Penerapan Framework Bootstrap Dalam Sistem Informasi Rekam Medis Data Posyandu dengan Metode Waterfall

Bootstrap is a combined framework of CSS and JavaScript that is offered as an alternative among other frameworks with the intention of providing consistency to the interface development stage in building a website, one of which is the website at the Posyandu Kemuning Gajah Village. The problems that arise are related to recording visitor data manually in the register book, which is often done because there are so many things that must be recorded such as weight, developmental data for mothers, children under five, maternal development data, other personality data related to pregnant women and toddlers visiting posyandu. . For this reason, it is necessary to support an information system for recording participant activities so that the number of participants does not need to be developed in data processing and re-accessing so that data redundancy does not arise. The system that will be created using the bootstrap framework includes the participant registration process and data processing for posyandu participants, so that they are able to manage data and generate data reports in a valid and correct manner. Testing with the blackbox method shows that the entire system built from the implementation of the login form to the print report shows that everything has been successfully implemented in the system.
ELT in the digitale age: We have come a long way

Educational Applications and Artificial Intelligence (AI) powered tools have been a source of creativity but also controversy in recent years, also in the EFL classroom. From questions of spell checkers to automated text-generating technologies, educators and researchers alike have debated the utility and limitations of AI-powered tools. This paper looks at the historical development of educational technology, mainly the role of AI in ELT and argues for a creative engineering approach to language learning that leverages the best of the analogue and digital world. Taking the example of the Midjourney bot, this article outlines how AI-powered tools can be used as an assistive catalyst for teaching, such as providing linear remedial drills, grading cloze exercises, analyzing texts, but also generating fully coherent, grammatically, and lexically sound texts. It also identifies key competencies, such as interdependency, required to effectively use AI-powered tools. These skills include being able to use language chunks produced by the AI to adapt and remix texts for new activities and contexts, a skill referred to as “creative engineering”. Drawing on examples from specific EFL teaching scenarios, this paper emphasizes the need for teachers to understand and use AI-powered tools in their teaching, pointing to their potential to elevate language learning in the 21st century ELT classroom.
Web Technologies in the Development of Computational Thinking of Students with Mental Disabilities

Computational thinking is an important and necessary part of a modern person’s thinking. It has been proven that the development of this way of thinking in students with mental disabilities allows them to navigate quickly in the modern world, identify problems and create complex solutions. Online schooling during the COVID-19 pandemic demonstrated the possibilities of the usage of web technologies in the education of children with mental disabilities. This study aims to evaluate the impact of web technologies on the development of computational thinking of students with mental disorders. The experiment involved 14 students aged 8-12 and 4 tutors. For 8 weeks children were trained in computational thinking and computer science. Assessment of computational thinking was performed with cCT-test by El-Hamamsi et al. before and after the experiment. After conducting computer science lessons using web technologies the respondents showed a higher level of computational thinking (M=15,7, SD=3,69), compared to the results of preliminary testing (M=5,93, SD=2,3). Web technologies can significantly increase the effectiveness of inclusive pedagogy, which establishes the importance of integrating web technologies into the teaching system in inclusive classes of general education schools.
Technical Perspective: Sortledton: a Universal Graph Data Structure

Graph processing is becoming ubiquitous due to the proliferation of interconnected data in several domains, including life sciences, social networks, cybersecurity, finance and logistics, to name a few. In parallel with the growth of the underlying graph data sources, a plethora of graph workloads have appeared, ranging from graph analytics to graph traversals and graph pattern matching. Graph systems executing both complex and simple graph workloads need to leverage adequate data structures for efficiently processing heterogeneous graph data. While the underlying graph data structures have been extensively studied for the static case, they are less understood for the dynamic case, with the data undergoing several updates per second. Moreover, the existing solutions suffer lack of generality, as they focus on one specific requirement and workload type at a time. Designing a universal data structure that adapts to several kinds of graph workloads in a dynamic setting and achieves significant efficiency on all of them is far from being trivial.
Interaction-Enhanced Textual Similarity Matching Distance Measurement – Exploration on Chinese

Textual similarity matching is one of the most valuable tasks in natural language processing. Meanwhile, due to the wide development of applications and increase in requirements, various subtasks are proposed and expected to be resolved. In addition, Chinese, which owns the largest population of native speakers, introduced more challenges because of its different grammar and characteristics. In this project, we explore the best design of representation, interaction, and prediction layers for Chinese textual similarity matching by extensive experiments on two public datasets. Results prove that the precise interaction paradigm and unlearnable distance metric is more suitable for matching task considering effectiveness and efficiency. And for the option of representation structure, we should simultaneously consider textual information distribution within datasets and computational cost.
An Efficient Single and Double Error Correcting Block Codes with Low Redundancy for Digital Communications

In digital communication there are various single and double bit error correcting and detecting codes are available. The efficiency of an error correcting code is evaluated by its errors correction capabilities and redundancy. This paper presents a new single bit and double bit error correcting codes which have lower redundancy compare to the other existing codes. In this paper the number of parity bits over the message bits for Hamming, BCH,RS Code, and DEC are examined and overhead is calculated. The proposed codes having less parity bits compared to other existing and having up to double bit error correction capabilities and minimize the encoding/decoding time delay.
University Training in Response to the Requirements of Industry 4.0

In the context of Industry 4.0, university training is supposed to provide learners with the qualities and skills necessary to live and work in the digital environment. A relatively new issue for Vietnamese universities is how to train human resources to meet the requirements of working in the digital environment. In order to meet the training requirements, many difficulties are posed, ranging from awareness and identification of the elements of citizens' digital competence to technical infrastructure, training programs, and pressure on lecturers and managers. The article introduces digital competence and the digital capacity frameworks for citizens and for students based on existing studies. It thereby assesses the common difficulties and challenges of higher education and proposes a number of solutions to train human resources to work in the digital environment. This immediately aims to implement the Prime Minister's Decision No. 749/QD-TTg approving the "National Digital Transformation Program until 2025, with orientations until 2030".
Mortar Trajectory Estimation by a Deep Error-State Kalman Filter in a GNSS-Denied Environment

This paper presents a Deep Error State Kalman Filter (Deep ES-KF) to estimate a projectile trajectory using only the embedded Inertial Measurement Unit (IMU) composed by a triaxial accelerometer, gyrometer and magnetometer. The ES-KF evolution model is evaluated by a Long Short-Term Memory (LSTM) to predict the projectile trajectory, i.e. projectile positions, velocities and Euler angles. Then, the ES-KF prediction step evaluates the trajectory errors from accelerometer and gyrometer measurements and corrects them during the update step using magnetometer measurements and the reference magnetic field. Finally, the LSTM predicted trajectory is corrected by the ES-KF updates. The LSTM input data are the embedded IMU, the reference magnetic field, flight parameters specific to the projectile considered and a time vector. A transfer learning method is used to ensure an optimal accuracy. The Deep ES-KF accuracy is compared to a classical Dead-Reckoning, to the ES-KF without neural network and to the pre-trained LSTM on mortar fire simulations. The Root Mean Square Error (RMSE), the Mean Absolute Error (MAE) and the success rate are evaluated. The LSTM contribution is clearly highlighted as the Deep ES-KF and the pre-trained LSTM exhibit considerably less relevant errors than the ES-KF and the Dead-Reckoning to estimate mortar positions and velocities. However, deep learning-based methods are not the optimal solution to estimate the projectile orientation. However, among the four compared methods, the Deep ES-KF presents the best position and velocity estimation and provides an accurate long-term navigation solution.
Strategi Guru Ekonomi Dalam Mengatasi Kesulitan Belajar Siswa Di MAN Purwakarta

This research is motivated by learning difficulties that occur in economics subjects, therefore the teacher's strategy in overcoming student learning difficulties in economics subjects is very necessary. The purpose of this study was to determine the economics teacher's strategy in overcoming students' learning difficulties at MAN Purwakarta. The method used in this research is descriptive qualitative. The results of the study show that the strategy used by economics teachers in overcoming economic learning difficulties is by using an expository strategy, namely a strategy that emphasizes the process of delivering material verbally from the teacher to a group of students with the intention that students can master the subject matter optimally. Just as the teacher takes a personal approach and provides additional lessons, if there are students who are really difficult to understand the material the teacher is more focused on helping these students, thus the teacher can find out what difficulties students are experiencing and motivate students to leave. of the problems experienced. The conclusion of this study is that the role of the teacher is very large in overcoming student learning difficulties.