Reviewerly/exHarmony huggingface dataset:
PEMANFAATAN TEKS MULTIMODAL SEBAGAI INOVASI MATERI PEMBELAJARAN BAHASA INDONESIA PADA MASA PANDEMI COVID-19

Abstract&#x0D; Based on the 2013 Curriculum, Indonesian language learning in SMP is text-based. During this pandemic, learning various texts should take advantage of existing technology with teaching materials in the form of multimodal texts. This study aims to describe the use of multimodal text as an innovation in Indonesian language learning materials in junior high schools and the implementation of learning. This study used descriptive qualitative method. Data collection techniques using observation techniques, interviews, documents, and audiovisual materials. Observation and document techniques were used to observe and document the textbooks used in Indonesian language learning for grade VIII SMP, both from offline and online data. Audiovisual techniques to collect data in the form of multimodal text sourced from the internet and social media. The data validity used data triangulation techniques, researchers, methods, and theories. The data analysis technique was done by reducing the data, presenting the data, and concluding. The results showed that multimodal text learning as an innovation in Indonesian language learning materials in class VIII SMP was beneficial for students to improve their literacy competencies in the era of the industrial revolution 4.0. In addition, it can also introduce students to types of text that are broader, more eye-catching, and less saturating. Students and teachers can explore these materials from the internet or social media in accordance with the teaching material. The teacher must prepare a good and appropriate lesson plan and scenario. &#x0D; Keywords: multimodal text; Indonesian language teaching materials; learning media
Advantages and importance of autonomous learning in teaching english in Kazakhstan

The article considers the advantages and importance of independent learning of a student in English lessons in the process of implementing the features of the updated content of education according to the state educational standard of the Republic of Kazakhstan. Scientific research the purpose of the work is to determine the advantages and importance of independent learning in teaching English to secondary school students by conducting a scientific experiment using empirical methods. The relevance of the study is to show an experimental analysis of the impact of the system of independent learning, which is its main tasks, on the self-regulation of students in English lessons, the rapid acquisition of a new vocabulary through effective methods, the ability to speak English fluently, the development of self-di- rected writing and reading skills of students. The main directions of the study are based on experimental analysis of Secondary School students, monitoring of students ‘ activities during the study. In addition, the educational system of Nazarbayev Intellectual Schools, which are autonomous educational organi- zations in Kazakhstan, includes features of the updated educational program. Within the framework of the studied topic, theoretical and practical studies of world scientists were considered, on the basis of which practical work was carried out in one of the secondary schools of Turkestan with the help of open- closed questions, questionnaires, and methods of interviewing high school students. The data obtained were summarized, analyzed, and cleared up. As a result, the importance of independent learning in the formation of a student as a world competitive person was determined, and recommendations were made to improve the work under study. Key words: self-learning, self-management, responsibility, smart goal, result, competitiveness.
A Co-optimization PSO for Fuzzy Rule-Based Classifier Design Problem Based on Enlarged Hedge Algebras

Fuzzy Rule-Based Classifier (FRBC) design problem has been widely studied due to many practical applications. Hedge Algebras based Classifier Design Methods (HACDMs) are the outstanding and effective approaches because these approaches based on a mathematical formal formalism allowing the fuzzy sets based computational semantics generated from their inherent qualitative semantics of linguistic terms. HACDMs include two phase optimization process. The first phase is to optimize the semantic parameter values by applying an optimization algorithm. Then, in the second phase, the optimal fuzzy rule based system for FRBC is extracted based on the optimal semantic parameter values provided by the first phase. The performance of FRBC design methods depends on the quality of the applied optimization algorithms. This paper presents our proposed co-optimization Particle Swarm Optimization (PSO) algorithm for designing FRBC with trapezoidal fuzzy sets based computational semantics generated by Enlarged Hedge Algebras (EHAs). The results of experiments executed over 23 real world datasets have shown that Enlarged Hedge Algebras based classifier with our proposed co-optimization PSO algorithm outperforms the existing classifiers which are designed based on Enlarged Hedge Algebras methodology with two phase optimization process and the existing fuzzy set theory based classifiers.
P2P Energy Trading Application In Smart Grids Using Blockchain

Abstract: This paper helps one to understand the concept of smart grids, blockchain, and their interaction with one another in a real-world application of the energy sector, specifically in the smart grids. Initially, we will focus on the working of smart grids and compare them with traditional models. Formalize a list of existing gaps in the present technology and solve them with the introduction of blockchain technology as the principle solution. In the current energy distribution system, when a supplier produces electricity from a renewable energy source (RES), the distribution process is highly inefficient and mismanaged. The meter readings are first logged onto a spreadsheet and then sent to the registry provider to issue a certificate. Then multiple other intermediaries are involved in the whole process, such as one to broker a deal between producers and consumers. Then another external intermediary is tasked with verifying the certificates. This causes an increase in the operational costs, errors, and multiple third parties/mediators involved, which causes a lack of trust in the system. The current system is also highly centralized, and our proposed system; this is P2P energy trading in smart grids using blockchain aims to eliminate the above drawbacks. Keywords: blockchain, certificates, IoT, smart grid.
Threshold based VM Placement Technique for Load Balanced Resource Provisioning using Priority Scheme in Cloud Computing

The unbalancing load issue is a multi-variation, multi-imperative issue that corrupts the execution and productivity of processing assets. Workload adjusting methods give solutions of load unbalancing circumstances for two bothersome aspects over-burdening and under-stacking. Cloud computing utilizes planning and workload balancing for a virtualized environment, resource partaking in cloud foundation. These two factors must be handled in an improved way in cloud computing to accomplish ideal resource sharing. Henceforth, there requires productive resource, asset reservation for guaranteeing load advancement in the cloud. This work aims to present an incorporated resource, asset reservation, and workload adjusting calculation for effective cloud provisioning. The strategy develops a Priority-based Resource Scheduling Model to acquire the resource, asset reservation with threshold-based load balancing for improving the proficiency in cloud framework. Extending utilization of Virtual Machines through the suitable and sensible outstanding task at hand modifying is then practiced by intensely picking a job from submitting jobs using Priority-based Resource Scheduling Model to acquire resource asset reservation. Experimental evaluations represent, the proposed scheme gives better results by reducing execution time, with minimum resource cost and improved resource utilization in dynamic resource provisioning conditions.
Correlated Weights Neural Layer with external control

The correlated weights neural layer is a generalization of the convolutional layer constituting the core of CNN networks.The CWNL layer takes advantage of weights correlated with coordinates of a neuron and its inputs, calculated by a dedicated neural subnet.In this work, a modified CWNL layer is proposed, which allows the parameterized spatial manipulation (and any other global transformation) of a pattern.The externally controlled CWNL layer can be used in existing neural network architectures, giving them the ability of internal pattern transformation without any modification of the training process.
Solving cubic and quartic equations by radicals

The rule for the solution of a cubic or quartic equation by radicals is obtained from elementary considerations of the geometry of the projective line.
Efektivitas Aplikasi SIAP terhadap Kedisiplinan Pegawai Sekretariat Daerah Kota Sukabumi

ABSTRACTResearch on Employee Attendance Information System Applications (SIAP) on this discipline is motivated by1) low level of employee discipline relating to attendance and punctuality at work, 2) easy application to be manipulated by employees, 3) frequent system disturbances (errors) in the application when used by employees, which have an impact on the ineffectiveness of the SIAP system. Research analysis using Information Systems theory from Davis and Discipline Theory from Singodimedjo.The method used is quantitative with associative models. Respondents were civil servants in the Regional Secretariat of Sukabumi, totaling 160 people. 61 samples were taken using proportionate stratified random sampling technique. The results of data analysis showed a correlation coefficient of 0.918. The coefficient of determination is 84.3%. For this reason, researchers suggest that the local government of Sukabumi City improve the accuracy of the SIAP attendance system by adding a face camera system.Keywords: SIAP Application, Face Camera, Discipline, Information System
Setting Reward Function of Sensor Based DDQN Model

In this study, it is aimed to determine the appropriate reward function of the agent which trained to pass 100 obstacles/objects in Reinforcement Learning (RL) with Double Deep Q Network (DDQN) model.To train the agent, environment is split into sub problems.Several rules and different reward functions defined for the sub problems.A developed mini deep learning library which is called gNet is used for the training.
Feature Extraction of Music Signal Based on Adaptive Wave Equation Inversion

The digitization, analysis, and processing technology of music signals are the core of digital music technology. There is generally a preprocessing process before the music signal processing. The preprocessing process usually includes antialiasing filtering, digitization, preemphasis, windowing, and framing. Songs in the popular wav format and MP3 format on the Internet are all songs that have been processed by digital technology and do not need to be digitalized. Preprocessing can affect the effectiveness and reliability of the feature parameter extraction of music signals. Since the music signal is a kind of voice signal, the processing of the voice is also applicable to the music signal. In the study of adaptive wave equation inversion, the traditional full-wave equation inversion uses the minimum mean square error between real data and simulated data as the objective function. The gradient direction is determined by the cross-correlation of the back propagation residual wave field and the forward simulation wave field with respect to the second derivative of time. When there is a big gap between the initial model and the formal model, the phenomenon of cycle jumping will inevitably appear. In this paper, adaptive wave equation inversion is used. This method adopts the idea of penalty function and introduces the Wiener filter to establish a dual objective function for the phase difference that appears in the inversion. This article discusses the calculation formulas of the accompanying source, gradient, and iteration step length and uses the conjugate gradient method to iteratively reduce the phase difference. In the test function group and the recorded music signal library, a large number of simulation experiments and comparative analysis of the music signal recognition experiment were performed on the extracted features, which verified the time-frequency analysis performance of the wave equation inversion and the improvement of the decomposition algorithm. The features extracted by the wave equation inversion have a higher recognition rate than the features extracted based on the standard decomposition algorithm, which verifies that the wave equation inversion has a better decomposition ability.
Making DL-Lite Planning Practical

Planning in the presence of background ontologies is a topic of long-standing interest in AI. It combines the problems of (1) belief update complexity and (2) state-space combinatorics. DL-Lite offers an attractive solution to (1), with belief updates possible at the ABox level. Indeed, it has been shown that DL-Lite planning can be compiled into the commonly used planning language PDDL. Yet that compilation was previously found to be infeasible for off-the-shelf planning systems. Here we analyze the reasons for this problem and find that the bottleneck lies in the planner pre-processes, in particular in the naïve DNF transformations used to compile the PDDL input into the planners' internal representations. Consequently, we design a PDDL pre-compiler realizing a polynomial DNF transformation. We leverage a particular PDDL language feature ("derived predicates") to avoid the need for excessive control structure. Our pre-compiler turns out to be quite effective: the previous bottleneck disappears, and experiments on a broad range of benchmarks demonstrate the first practical technology for DL-Lite planning.
Factivusszal kidolgozott eredményállapotot tartalmazó rezultatív konstrukciók a magyarban. Kognitív grammatikai elemzés

The paper describes constructions of the process type CAUSED CHANGE OF STATE in a cognitive grammatical framework.In the construction type under study, the end state resulting from a process is symbolized by an adjective or noun in factive case (-VÁ) (valaki valamilyenné/valamivé tesz valamit 'somebody causes something to become so-and-so').The case study is based on attested linguistic data, especially data sampled from the Hungarian National Corpus (HNC v2.0.5) and from the earlier version of HNC by the Mazsola query tool.The paper presents a cognitive linguistic account of the construction type (cf.Broccias 2004).It offers a critical assessment of the analysis whereby the verbal component undergoes "skewing" (Langacker 2009b(Langacker , 2009c)).Under the proposal, skewing should be regarded not as a congruency problem arising when the verb slot is filled, but rather as an aspect of how constructions are integrated.On the basis of cognitive linguistic analyses performed on Hungarian data, the paper identifies verbs (along with their collexemes) that define the resultative construction and delineates its more specific constructional subschemas.
Knowledge-based Hiring Recommender Model for Occasional Services in the Public Sector

Public employees often provide their services under contract for occasional services. This form of employment relationship may undergo the consequences of job instability. Classifying occasional job profiles allows us recommending new jobs for those who suffer from job instability. This research proposes a solution to the posed problem by using a Neutrosophic method to determine job profiles of people for the occasional service contract recommendation in the public sector. Ordered Weighted Averaging Distance (OWAD) operator is proposed for aggregation of similarities measures.
Kirkpatrick's Evaluation and Importance Performance Analysis of Tax Instructor Functional Distance Training

This study evaluates Tax Insructor Functional Distance Learning implementation Class II of 2021 conducted by Yogyakarta Financial Education and Learning Center to to find out how it is organized.The research method is qualitative method which is evaluating the implementation of the class.The evaluation is using Kirkpatrick learning model at level 1 and level 2 and Importance Performance Analysis (IPA).Level 1 Kircpatrick's evaluation showed that the learning implementation performance was conducted very well.IPA analysis shows that all learning participants' perceptions of learning teachers are good and the lecture material is included in quadrant III, which indicates that it is good.Most of participant satisfied with this learning.Level 2 Kircpatrick's evaluation shows that the learning results are promising.Participants who pass have the score 'good' and 'very good.So the result is the Basic Tax Instructor Functional Distance Learning Class II of the 2021 year, conducted by the Yogyakarta Financial Education and Learning Center online from 8 to 17 February 2021 has been well organized, regarding the teachers and the learning metrics.Training participants have also provided excellent evaluation results.However, the long training time until the evening needs to be reconsidered.Smooth internet signal is also still an obstacle in this training.If the situation allows, it is recommended that this training be carried out face-to-face
Motivaton as a principal aspect of distance learning at higher educational establishments of Ukraine

Together with all global transformations, caused by SARS-CoV-2 pandemic, Ukrainian system of education is undergoing great changes, as distance learning is becoming more and more popular.The goal of this research is to consider the necessity of distance learning application at higher educational establishments, its benefits and drawbacks; to study the motivational aspect of distance learning and Keller's ARCS model in particular.In this article, distance learning is considered as an alternative form of education, its advantages and disadvantages are studied; the issue of motivation in distance learning, as a main prerequisite of good results in studies, is investigated.The application of J. Keller's ARCS model to distance learning courses at higher educational establishments of Ukraine is considered.Taking into consideration the point that distance learning is a rather new form of education at higher educational establishments of Ukraine, it was reasonable to study the following issues: distance learning, its advantages and disadvantages; motivation and its influence on students' results in studies; motivation in distance learning; J. Keller's ARCS model application.All global changes lead to crucial changes in the education process worldwide.Distance learning and blended learning are most likely to become alternative forms of education in the nearest time.That's why it's necessary to take into consideration their advantages and disadvantages, and get all the participants of educational process ready to all possible changes.Young people are very flexible, and will adjust themselves to any changes, if they are properly motivated.The goal of teachers is to develop training materials in order to make the distance learning course substantive and easy to understand, attractive and relevant to students' interests and future career.All these tasks are impossible without students' eagerness to learn.So, the problem of motivation is of utmost importance.Though this problem is to be further investigated, proper application of Keller's model will help in its solution.
EFL Students’ Perceptions and Attitudes toward Using Communicative Activities in CLT Classroom

In this study, the effects of using the communicative activities in communicative language teaching (CLT) classroom to improve students’ speaking performance and reduce their difficulties in speaking skill were investigated. Classroom action research (CAR) was considered as the research design. A quantitative method was followed in this study. The researcher intended to improve the students’ speaking ability by using the Communicative Language Teaching Method, communicative activities. The teaching and learning process was divided into ten cycles and was carried out in ten weeks. Each cycle consisted of four interconnected stages: Planning, Action, Observation, and Reflection. Overall, students favored activities that provided a competitive classroom environment and led to a high level of classroom participation. The findings revealed the effectiveness of speaking classes because students were significantly more satisfied with their speaking ability after the interventions. Statistically significant differences were found in students’ perceptions and attitudes toward using communicative activities.
Digital Competences in the Profile of Teaching Education: Context of Remote Education of Peru

Education developed in the virtual context becomes remote today both because of the distance in which school groups are served far from the city, as well as the distance that teachers and students have to reach technological resources to educate and educate themselves, and the resources that affect a higher quality digital education. In this sense, it is understood that digital skills are essential to generate relevant, comprehensive, inclusive and cooperative virtual educational methodologies, especially during the pandemic, which requires mastery of teaching techniques and mastery of these digital skills. The objective was to determine the causality of digital competencies on the teacher teaching profile. The methodology developed was quantitative, causal, correlational and transactional. The sample consisted of 200 active teachers in Basic Education from a Latin American city. These developed their teaching during the onset of the pandemic (2020) until the middle of the year 2021. The variables were evaluated with Likert-type scales. The reports conclude that the scores in digital competencies present moderate intensity of causality and correlation on the teaching profile of those evaluated. Similar effects were found from digital skills on the cognitive and affective characteristics of the profile, although there are common causal effects on motivation. It is suggested to include other variables in a multi-causal analysis, considering vulnerable contexts in evaluating teachers and their execution during the pandemic.
Challenges to Representing Personal Names and Language Names in Language Archives: Examples from Northeast India

Language archives are not only a valuable resource for language communities to tell their stories and to create lasting records of their ways of life, but also for those interested in anthropology, linguistics, agriculture, or art history. This recent emphasis on archiving primary datasets in linguistics has resulted in an abundance of datasets online; however, of the languages of South Asia, only a small percentage are represented in digital language archives or described thoroughly. Though several of these languages are being documented, this material is at risk of being lost or inaccessible without concerted attention paid to long-term preservation. There are several obstacles to documenting and archiving language materials from this area, including political instability and lack of access to infrastructure. This submission reviews one particular challenge to data management relevant to South Asia, which is the complexity of names (of individuals, groups, and languages). We provide examples from Northeast India and recommendations based on experience from CoRSAL (Computational Resource for South Asia).