Reviewerly/exHarmony huggingface dataset:
A Multi-Factor Classification Framework for Completing Users’ Fuzzy Queries (Student Abstract)

Intent identification is the key technology in dialogue system. However, not all online queries are clear or complete. To identify users' intents from those fuzzy queries accurately, this paper proposes a multi-factor classification framework on the query level. Experimental results on our online serving system JIMI demonstrate the effectiveness of our proposed framework.
PENINGKATAN HASIL BELAJAR SISWA MELALUI PENGGUNAAN METODE DEMONTRASI PADA MATA PELAJARAN PKN DI KELAS IV SD NEGERI 101770 TEMBUNG

This study aims to use a demonstration approach in improving student learning outcomes in PKN subjects in grade IV SD Negeri 101770 Tembung, with the aim of improving student learning outcomes in PKN lessons. The subjects in this study were grade IV SD Negeri 101770 Tembung. In the even semester of the 2019/2020 school year (February to April 2020). The subjects in this classroom action research were all fourth grade students of SD Negeri 101770 Tembung, Percut Sei Tuan district, Deli Serdang Regency. For the 2019/2020 academic year, Medan has 28 students in cycle I, with details of 15 students (53.6 percent) getting a complete score and 13 students (46.4 percent) getting an incomplete score with an average score. 64.3. In this case the research was carried out in 2 (two) cycles, with research procedures including: conducting learning improvements, holding pretests (initial tests), providing motivation to students so that their scores meet completeness. The results showed that there was an increase in PKN learning outcomes through the use of the demonstration method.
Detecting Duplicate Questions in Online Forums Using Machine Learning Techniques

Abstract: Online forums like Quora are systems for collecting, sharing information, and discussing between users on a selected subject matter. Users in on-line forums can ask questions about a subject, then other users who're experts on that question would solution the query. However, due to the fact customers can ask questions in diverse methods, every now and then they ask questions that other users have previously requested. Consequently, a version is needed to detect the semantic similarity of questions in online boards. On this study, we're the usage of machine learning algorithms to discover the semantic similarity of questions. To seize the semantic similarity among questions, we're the usage of word embedding. This word embedding vector is used as an enter for neural network, and then the output is compared with other machine learning algorithms.
Anomaly Detection Using Prediction Error with Spatio-Temporal Convolutional LSTM

In this paper, we propose a novel method for video anomaly detection motivated by an existing architecture for sequence-to-sequence prediction and reconstruction using a spatio-temporal convolutional Long Short-Term Memory (convLSTM). As in previous work on anomaly detection, anomalies arise as spatially localised failures in reconstruction or prediction. In experiments with five benchmark datasets, we show that using prediction gives superior performance to using reconstruction. We also compare performance with different length input/output sequences. Overall, our results using prediction are comparable with the state of the art on the benchmark datasets.
Knowledge Compilation Meets Logical Separability

Knowledge compilation is an alternative solution to address demanding reasoning tasks with high complexity via converting knowledge bases into a suitable target language. Interestingly, the notion of logical separability, proposed by Levesque, offers a general explanation for the tractability of clausal entailment for two remarkable languages: decomposable negation normal form and prime implicates. It is interesting to explore what role logical separability on earth plays in problem tractability. In this paper, we apply the notion of logical separability in three reasoning problems within the context of propositional logic: satisfiability check (CO), clausal entailment check (CE) and model counting (CT), contributing to three corresponding polytime procedures. We provide three logical separability based properties: CO- logical separability, CE-logical separability and CT-logical separability. We then identify three novel normal forms: CO-LSNNF, CE-LSNNF and CT-LSNNF based on the above properties. Besides, we show that every normal form is the necessary and sufficient condition under which the corresponding procedure is correct. We finally integrate the above four normal forms into the knowledge compilation map.
C3D and Localization Model for Locating and Recognizing the Actions from Untrimmed Videos (Student Abstract)

In this article, we proposed a technique for action localization and recognition from long untrimmed videos. It consists of C3D CNN model followed by the action mining using the localization model, where the KNN classifier is used. We segment the video into expressible sub-action known as action-bytes. The pseudo labels have been used to train the localization model, which makes the trimmed videos untrimmed for action-bytes. We present experimental results on the recent benchmark trimmed video dataset “Thumos14”.
From Actions to Programs as Abstract Actual Causes

Causality plays a central role in reasoning about observations. In many cases, it might be useful to define the conditions under which a non-deterministic program can be called an actual cause of an effect in a setting where a sequence of programs are executed one after another. There can be two perspectives, one where at least one execution of the program leads to the effect, and another where all executions do so. The former captures a ''weak'' notion of causation and is more general than the latter stronger notion. In this paper, we give a definition of weak potential causes. Our analysis is performed within the situation calculus basic action theories and we consider programs formulated in the logic programming language ConGolog. Within this setting, we show how one can utilize a recently developed abstraction framework to relate causes at various levels of abstraction, which facilitates reasoning about programs as causes.
Covid-19 pandemic impacts on postoperative patients of bariatric surgery / Impactos da pandemia da Covid-19 em pacientes no período de pós-operatório da cirurgia bariátrica

The World Health Organization declared a global pandemic for the new coronavirus on March 11, 2020. The present study aims at describing the impact of coping with the COVID-19 pandemic on bariatric post-surgery patients. This is a cross-sectional study with a qualitative approach in which data were collected through semi-structured interviews. The sample consisted of bariatric post-surgery patients from the bariatric surgery service of a university hospital as well as from a private health service. Four major thematic axes were established from the set of questions to the participants and their answers were analyzed and classified into categories after the transcription of the interviews was done. The results reveal that there are impacts on coping with the pandemic when it comes to emotional and dietary issues and physical exercise. It also shows the emergence of fears for having experienced a post-operative period of bariatric surgery during a pandemic scenario.
Cyber Espionage in National and Global Perspective: How Indonesia Deal with this issue?

Cyber Crime is the most frightening crime in today's technological developments. Attacks that do not know the target and time for a particular purpose. The privacy of a person or institution can be threatened by cyber crime. Mobile technology and supported by adequate communication network facilities turn a positive image into a dilemma. Someone should in dealing with it keep thinking positive. Increasing self-awareness and acting ethically will not result in something fatal. Any excessive action can backfire. Increasing knowledge in the use of technology is very necessary. Mobilization that is too widespread makes it easier to access information. Cyber crime will not happen if we do not do strange and disturbing things.
DAMPAK PENGGUNAAN MEDIA BERBASIS ANDROID DALAM AKTIVITAS PEMBELAJARAN SEJARAH KEBUDAYAAN ISLAM

This study aims to determine the effect of using Android-based application on student activities in learning Islamic Cultural History. This classroom action research method is carried out in two cycles, where each cycle begins with planning, action, observation, and reflection. The data in this study are in form of assessments obtained in their activities and assessments at the end of the cycle. Then, the data is analyzed to obtain an overview of learning effectiveness that has been carried out. There are seven indicators that are measured to determine student activity in the learning process by applying the use of android-based media. The results showed that based on the seven indicators, there was an effect on increasing student learning activities in learning the subject of Islam spread in the archipelago by using an Android-based application. Before the action, only 37.62% students were actively involved in learning. In the first cycle, the average student learning activity increased to 56.19%. In the second cycle, the average student learning activity increased again reaching 76.16%. The conclusion is that the use of android-based media is very instrumental and suitable for increasing student activity in learning Islamic Cultural History at MTs Al-Ma'arif Cilageni, Garut.
Geological potential of antimony, bauxite, fluorite, and magnesite of the Central Dinarides (Bosnia and Herzegovina): exploration and exploitation perspective

This paper presents the critical raw materials (CRM) potential of antimony, bauxite, fluorite, and magnesite deposits in Bosnia and Herzegovina, discusses their metallogeny and joint geological features, and explains the methodology of the InvestRM application and evaluation criteria for the selected commodities in the following steps: (1) preparation of the geological data templates, (2) evaluation and verification of the geological data, (3) ranking of deposits according to the geological data relating to quality and quantity, and (4) identification of the 10+ perspective deposits. Existing geological datasets show the existence of significant potential in primary CRM such as bauxite (56 Mt), magnesite (4 Mt), and antimony (0.2 Mt) in Bosnia and Herzegovina (BiH). The geological settings of BiH provide favourable metallogenetic conditions primarily for bauxite and magnesite deposits but also for antimony within polymetallic deposits, while fluorspar is rather rare. Our methodology described herein led to the selection of the following fourteen deposits for further geological prospection and investment: the polymetallic antimony deposits Čemernica and Podhrusanj, antimony fields Srebrenica and Rupice; magnesite fields Kladanj, Banja Luka, Teslić and Novi Šeher and bauxite regions Vlasenica-Srebrenica, Grmeč Mountain deposits in Una-Sana region and South Bosnia regions from Posušje to Trebinje. A basic economic calculation based on the world producer ranking and a self-sustainability and economic contribution assessment shows that further investments in geological exploration and mining of antimony, magnesite, and bauxite CRM could place BiH on the list of important producers of these commodities in Europe.
Whisper to Neutral Mapping Using I-Vector Space Likelihood and a Cosine Similarity Based Iterative Optimization for Whispered Speaker Verification

In this work, we propose an iterative optimization algorithm to learn a feature mapping (FM) from the whispered to neutral speech features. Such an FM can be used to improve the performance of speaker verification (SV) systems when presented with a whispered speech. In one of previous works, the equal error rate (EER) in an SV task has been shown to improve by ~24%. based on an FM network trained using a cosine similarity based loss function over that using a mean squared error based objective function. As the mapped whispered features obtained in this manner may not lie in the trained i-vector space, we, in this work, iteratively optimize the i-vector space likelihood (by updating T-matrix) and a cosine similarity based loss function for learning the parameters of the FM network. The proposed iterative optimization improves the EER by ~26% compared to when the FM network parameters are learned based on only cosine similarity based loss function without any T-matrix update, which is a special case of the proposed iterative optimization.
Multi-View Adjacency-Constrained Nearest Neighbor Clustering (Student Abstract)

Most existing multi-view clustering methods have problems with parameter selection and high computational complexity, and there have been very few works based on hierarchical clustering to learn the complementary information of multiple views. In this paper, we propose a Multi-view Adjacency-constrained Nearest Neighbor Clustering (MANNC) and its parameter-free version (MANNC-PF) to overcome these limitations. Experiments tested on eight real-world datasets validate the superiority of the proposed methods compared with the 13 current state-of-the-art methods.
ANALISIS KESALAHAN BERBAHASA TATARAN SINTAKSIS PADA TEKS BERITA SISWA KELAS VIII SMPN 2 PANGENAN CIREBON TAHUN PELAJARAN 2021/2022

This research is a qualitative descriptive study with the subject of this research in the form of a document of the results of the VIII grade students of SMPN 2 Pangenan Cirebon. Data collection techniques used by researchers in this study are in the form of documentation techniques and note-taking techniques. Meanwhile, the validity checking technique used triangulation technique. The data analysis used in this study used the agih method and continued using the basic technique for direct elements or the BUL technique. After using the basic technique, it was continued using advanced techniques, namely by using the lesap technique, the replacement technique, the reverse technique, and the extension technique to facilitate data analysis. The results of this study are in the form of a description of the analysis of language errors at the syntactic level in the student news text. The results are 39 forms of phrase errors and 11 forms of sentence errors. With the results of the analysis of language errors at the syntactic level, educators should be able to obtain an overview of appropriate learning models, methods, and media to support the improvement of students' writing skills, especially in the field of syntax.. Keywords: Language Error, Syntax, News Text
Subject matter and methodological competencies of mathematics teachers revealed in the digital transformation of education

Introduction. Creating conditions and opportunities for self-realization and reveal of each person’s talent in the conditions of digital transformation actualized the problems of improving the quality and competitiveness of Russian education in the modern world. The priority of developing the competencies of a teacher of general education organization at different stages of professional career was also determined. The purpose of this article is to monitor and analyze the formation of subject matter and methodological competencies of teachers of mathematics, revealed in the process of teaching activities in the conditions of digital transformation of continuing teacher education. Materials and methods. The survey involved 919 mathematics teachers from 7 regions of the Russian Federation. The survey considered such characteristics of the respondents as place of work, amount of workload, gender, age, teaching experience. Results of the study. The research showed the following professional deficits of the surveyed mathematics teachers in the area of subject matter and methodical competencies, manifested in the conditions of digital transformation of education: from 20% to 55% of teachers have difficulties in organizing subject teaching in different conditions of transferring typical algorithms to a new situation, about 25% have problems when analyzing educational and life situations that require application of mathematical apparatus, 34% do not know the ways of criterial evaluation of learning outcomes About 20% of the teachers with up to 10 years of experience show insufficient ability to select subject and meta-disciplinary content of the learning material required to solve mathematical problems, as well as the ability to build logical reasoning in mathematical contexts together with students, which is a potentially problematic area. Conclusion. Several recommendations were given based on the results of the conducted survey of teachers. Monitoring of the formation of professional subject matter and methodological competencies of teachers of mathematics should be systematic in nature and have clear range of tools. It is advisable to conduct a separate monitoring of the formation of professional competencies of students of the 3rd-5th courses, studying on the basic educational programs of training future teachers at the bachelor level. It is necessary to conduct a more in-depth analysis of problematic topics in terms of the identified professional deficits and to develop and implement individual and group programs of methodological support for teachers based on this analysis, including professional development and professional retraining, in order to eliminate the identified deficits with the objectives of digital transformation of continuing teacher education. It is necessary to actively implement comprehensive programs to develop the system of teaching mentoring at the regional and general education levels.
Formative assessment as a mechanism for achieving planned educational results: professional readiness of teachers

The article considers the current conditions for the formation of key competencies that are necessary and in demand in the XXI century in accordance with the objectives of state policy in the field of education. The analysis showed that it is possible to ensure the improvement of the quality of education by developing a system of their assessment with the help of new, dynamic solutions, including the introduction of one of the educational technologies – formative assessment. The paper uses the results of a regional study «The attitude of teachers of the Altai territory to the development of formative assessment technology». Based on the results of a study conducted among teachers of General education organizations in the Altai territory, the author developed a textbook «Paths of formative assessment» as part of the author’s team.
THE USE OF UNDERCOVER GAME TO ENHANCE STUDENTS’ VOCABULARY ACHIEVEMENT

This study aimed to find empirical evidence of the use of undercover games on students’ vocabulary achievement. The study used a quantitative method with a quasi-experimental design and purposive sampling technique. The total sample of this study was 70 students divided into two classes: experimental and controlled classes. The population of this study was the eighth-grade students of SMPN 108 Jakarta. The data was gained through pre-test and post-test. Both data from the tests were analyzed using a t-test in SPSS 25. The mean score in the post-test showed significant improvement between the pre-test and post-test. In the pre-test, the experimental class gained 65.82, while the controlled class gained 70.23. In post-test, the experimental class gained 78.20, and the controlled class gained 77.08. The test of the hypothesis showed that sig. 2 tailed was 0.076 while the determined alpha ? was 0.05, which meant that 0.076&gt;0.05. It is supported by the result of effect size, which was 1.02 as well. It can be said that the Ho (Null Hypothesis) was rejected, and the Ha (Alternative Hypothesis) was accepted. Therefore, the undercover game strongly affected students’ vocabulary achievement.
Construction of Enterprise English Adaptive Learning Platform Based on Big Data Analysis

With the rise of “Internet+” as a national strategy, traditional industries have accelerated their integration with the Internet, and the education industry has also begun to seek innovative development. The fast-paced life of modern people makes time for learning more fragmented, and the high pressure of life makes people want to avoid excessive pressure from learning. These give opportunities and advantages to the development of online education, which is more adaptable to fragmentation and light weight. Online learning effectively solves the drawbacks of imbalance between supply and demand of offline education by solving the problems of time, distance, capacity, and scarcity of educational resources. In this paper, we take H International Education Group as the research subject. The paper combines the practice of precise English teaching theory and big data technology analysis tools to study the optimization of English teaching strategies in the K12 English training product market of H International Education Group. The materials prevalent in the English vocabulary market today are “one-size-fits-all,” presenting the same vocabulary resources to all learners without taking into account the differences in learning styles, learning preferences, and original cognitive structures of different learners.
Augmentation of Chinese Character Representations with Compositional Graph Learning (Student Abstract)

Chinese characters have semantic-rich compositional information in radical form. While almost all previous research has applied CNNs to extract this compositional information, our work utilizes deep graph learning on a compact, graph-based representation of Chinese characters. This allows us to exploit temporal information within the strict stroke order used in writing characters. Our results show that our stroke-based model has potential for helping large-scale language models on some Chinese natural language understanding tasks. In particular, we demonstrate that our graph model produces more interpretable embeddings shown through word subtraction analogies and character embedding visualizations.
Psychology Analysis of Main Character in the Novel Gitanjali by Febrialdi R

This study aims to describe the psychology of main characters in the novel Gitanjali by Febrialdi R. In detail, the purpose of this study is to describe the psyche of the main character when facing various kinds of problems in his life. This research uses the library method. The subject of this research is a novel entitled Gitanjali by Febrialdi R which was published by mediakita publisher in 2018. This study focuses on problems related to the psychological conflict experienced by the main character. The results showed that: First, the main character of the novel Gitanjali received injustice. An accident that happened when he worked at a restaurant made him dismissed from the restaurant because of his disability. Second, the main character experiences despair in his life and love relationship. He feels hopeless about his love relationship which is not going well due to the demanding parents of his partner. It made him insecure, moreover his partner was a lecturer while he was just an ordinary man. Third, the main character lives alone because since childhood he never knew his biological parents and only lived in an orphanage. Fourth, the main character is depressed due to the problems that come his way.