Reviewerly/exHarmony huggingface dataset:
Efficiency Measurement and Improvement Suggestions of Urban and Rural Compulsory Education Resources

The rational allocation of educational resources is an essential link in education security.Based on the data of 2013-2014 academic year of China Education tracking survey, this paper uses the data envelopment analysis method to analyze the input-output efficiency of 70 schools in the sample from the perspective of input.The results show that the average value of input-output comprehensive efficiency of the sample is only 0.5825; The average value of input-output pure efficiency is only 0.6871; The average scale efficiency is 0.8370.The inefficiency of educational resource management plays a leading role, which indicates that the allocation of educational resources in the sample is unreasonable or wasteful.In order to avoid the shortage of education resources, this paper gives some suggestions from the aspects of controlling enrollment, unifying standards, training and allocating teachers, so as to achieve the goal of ensuring the balanced allocation of compulsory education resources.
The Challenges of English Language Teaching in Indonesia

The widespread use of English worldwide has brought about a significant impact for human beings to date. In the education sphere mainly, many studies have been conducted to discover the issues in English instruction. Moreover, English teachers in Indonesia were highly encouraged to figure out the best method to teach and cope with any problems encountered by the students to achieve the best learning outcomes. Besides, the government had also tried its best endeavors to accustom the curriculum to the needs in this globalization era. However, the results have not always been as expected since teachers and students possessed divergent points of view linked with the implementation of English language instruction. Therefore, this scientific literature review discussed some issues related to English which included; English in Indonesia, English Language Teaching for Education, Teachers’ Strategies to English Language Teaching, Problems of English Language Teaching, and Students’ Perceptions towards English Language Teaching. Furthermore, the main aim of this paper was to acknowledge to the readers that the teachers and students essentially require English due to its crucial role in the development of Education in Indonesia.
A Study on Applicability of the Scrum Framework for Large Software Projects

The primary objective of this research is to investigate the adaptability of the Scrum framework for large scale projects. A two phase approach has been undertaken towards the goal. The first phase involves conducting a systematic literature review to identify and elaborate scaling practices used in the current industry. The review also identifies the challenges faced by the developers when the Scrum framework is used for the development of large projects. The second phase involves the construction of a simulation model to analyze the dynamic behavior of the Scrum framework for large projects. The systematic literature review revealed that the major challenge while scaling Scrum is ensuring good communication among project members. The communication overhead was incorporated in the system dynamic model of the Scrum framework. The simulation results showed that there is a reduction in work rate when number of personnel is increased due to the increasing communication overhead.
A proof of the conjectured run time of the Hafner-McCurley class group algorithm

<p style='text-indent:20px;'>We present a proof under a generalization of the Riemann Hypothesis that the class group algorithm of Hafner and McCurley runs in expected time <inline-formula><tex-math id="M1">\begin{document}$ e^{\left(3/\sqrt{8}+o(1)\right)\sqrt{\log d\log\log d}} $\end{document}</tex-math></inline-formula> where <inline-formula><tex-math id="M2">\begin{document}$ -d $\end{document}</tex-math></inline-formula> is the discriminant of the input imaginary quadratic order. In the original paper, an expected run time of <inline-formula><tex-math id="M3">\begin{document}$ e^{\left(\sqrt{2}+o(1)\right)\sqrt{\log d\log\log d}} $\end{document}</tex-math></inline-formula> was proven, and better bounds were conjectured. To achieve a proven result, we rely on a mild modification of the original algorithm, and on recent results on the properties of the Cayley graph of the ideal class group.
The Influence Of Flash Card Toward Students’ English Vocabulary Mastery During Covid-19

The purpose of this research is to see how flash cards influence the students' English vocabulary mastery. The researchers of this research used quantitative research methods with posttest only control design of true experimental design. The random sampling method was employed in this research's sampling. The data collected in this research was put to the test (multiple choice test). The researchers of this research gave different treatments for the experimental and control groups. The treatment for the experimental group was learning English with flash card media and the treatment for the control group was learning English conventionally. After the two sample groups were given different treatment, the two sample groups were each given a posttest with an instrument consisting of 20 multiple-choice questions with 4 alternative answer choices that had been tested beforehand and validated empirically. Analysis of research data is descriptive and inferential, which inferentially uses the t test, by first testing the assumptions of data normality and homogeneity of variance. The results showed that flash cards had an influence on students' English vocabulary mastery. Therefore, it can be said that this research has proved that there was a significant result of using Flash Cards towards children's English vocabulary mastery.
Research on the Application of Deep Learning in Artificial Intelligence Courses

With the in-depth reform of education, taking students as the center, letting students master the basic knowledge of the theory, but also training students’ practical skills, is an important goal of the current artificial intelligence curriculum teaching reform. As a new learning method, deep learning is applied to the teaching of artificial intelligence courses, which can not only give play to students’ subjective initiative, but also improve the efficiency of students’ classroom learning. In order to explore the specific application of deep learning in the teaching of artificial intelligence courses, this article analyzes the key points of the application of deep learning in artificial intelligence courses. In addition, further explores the application strategies of deep learning in artificial intelligence courses. As it aims to provide some useful references to improve the actual efficiency of artificial intelligence course teaching.
The concept of theft, coupled with the penetration of housing, other premises or storage

The article analyzes and characterizes the theft, coupled with the penetration of housing, other premises or storage. The concept of “penetration”, “housing”, “other premises”, “storage”. The features of the interpretation of these concepts are highlighted. So, the peculiarity of housing is that it acts as a storehouse, and “another room”, unlike housing and storehouse, has an “open” character, which is expressed in the generally permitted access to it. So, the peculiarity of housing is that it acts as a storehouse, and “another room”, unlike housing and storehouse, has an “open” character, which is expressed in the generally permitted access to it. When interpreting “penetration”, attention is drawn to characteristic objective and subjective features. It is concluded that the “penetration”, being an independent action, for part 3 of Art. 185 of the Criminal Code is of decisive qualifying value, since it complicates the way of theft. This qualifying attribute extends the period of the objective side of the crime in question according to: the nature of the preparation and commission of the act; duration of action with the existing mercenary intent.
Towards the Question on the Zero Subject in English

Introduction . The article considers the case, when no subject is present in an impersonal English sentence. Many linguists believe that the subject in this case is implicit, because the sentence preserves its predicativity. In addition, the subject “it” is sometimes substituted in impersonal English sentences by the formal particle “there”. However, the question whether this particle performs the function of subject is still open. That is why it is rather pertinent to consider all cases of subject, both explicit and implicit one, including the cases, when the sentence contains the formal particle “there”. The objective of this work is to build a formal logical model of implicit subject in impersonal English sentence. Implicit subject is often named as zero subject. Methodology and sources. The research methodology is based on traditional approaches towards studying the phenomenon of zero subject, as well as on the binomiality idea, having been developed since 1993 at ETU. On the material of English the status of the issue, whether it is eligible to consider the implicit subject as the zero one, is investigated. The examples illustrating the functional features of the implicit subject in English sentence were selected by means of the method of continuous sampling from 7 corpora. To represent the structural features of the implicit subject the method of formal logical modelling is applied. Results and discussion. The article presents the diversity of subject structures in English sentence. There is dealt with the question on the functions of the formal particle “there” in hypothetical comparison with the formal particle “it”. In this regard, a formal logical modelling of English subject is undertaken, for declarative and interrogative sentences. Herewith both independent and dependent sentences are modelled. Questions to the subject are out of the present consideration. The implicit subject has been assumed to be a “trace” of the explicit subject and may not be recognized as the absolute zero subject. Conclusion. Linguistics has elaborated a variety of original views on the reasons, why “incomplete” subjects emerge. Our language models allow, however, to come to more original and, as we hope, objective conclusions. Dependent on its environment the subject in English can be implicit fully or partly. If the subject is fully implicit, it is a strong or weak implicit semifinitive, fixed in the weak specifier. If the subject is partly implicit, it is a weak implicit semifinitive, fixed in the strong specifier. The English subject appears to be fully implicit much less frequent, than partly implicit. Making the subject fully implicit is possible by means of additional elements. Making the subject partly implicit is possible by means of the strong specifier “there”; no additional elements are then needed.
Towards a Language Model for Temporal Commonsense Reasoning

Temporal commonsense reasoning is a challenging task as it requires temporal knowledge usually not explicitly stated in text.In this work, we propose an ensemble model for temporal commonsense reasoning.Our model relies on pre-trained contextual representations from transformer-based language models (i.e., BERT), and on a variety of training methods for enhancing model generalization: 1) multistep fine-tuning using carefully selected auxiliary tasks and datasets, and 2) a specifically designed temporal task-adaptive pre-trainig task aimed to capture temporal commonsense knowledge.Our model greatly outperforms the standard fine-tuning approach and strong baselines on the MC-TACO dataset.
Emoji in WhatsApp Group Conversation:

This research aims to investigate the use of emoji in WhatsApp group conversation to reveal the types and meaning of emojis used in the setting where members from groups communicate online.The participants were 21 students of English Applied Linguistics year 2019.The data were collected from since the WhatsApp group conversation made, surely since August 2019 to September 2021of interaction in the WhatsApp group.The methodology of the research is qualitative descriptive using technical analysis of Roland Barthes semiology.The technique of collecting data is based on two resources.The primary data are collections of screenshot chat that contains of emojis in WhatsApp.The secondary data are references supporting the topic of the research.In validity technique, the primary data are collected based on the topic of the discussion.After that, the data are processed descriptively by explaining, and comparing the information gained from many resources.Then, the data are reduced and presented.The findings showed that all members of WhatsApp group used the following emojis, namely face with tears of joy, rolling on the floor laughing, loudly crying face, grinning face with smiling eyes, frowning face, thumbs up, folded hands, hugging face, smiling face smiling face with hallo and woman facepalming, in the WhatsApp group communication.In terms of real meaning of emoji used by the sender is not entirely accurate with the context of the message, while the researcher could conclude that the meaning of the emoji is constantly shifting based on the real context or situation within the conversation at the group conversations.The findings contribute to research on the use of emojis relatively scarce in WhatsApp corpus.The findings also suggest how to communicate using emojis in forums with members from various group conversations.
Klasifikasi Data Malaria Menggunakan Metode Support Vector Machine

Malaria is a life-threatening disease, caused by a parasite that is transmitted to humans through the bite of an infected female Anopheles mosquito. In 2019, there were an estimated 229 million cases of malaria worldwide and the death toll reached 409,000. The area most frequently affected by malaria, according to WHO, is the African region. Malaria can be detected beforehand by using the information inpatient data and applying machine learning techniques. This study aims to detect and classify severe malaria based on the history of examining patient data using the Support Vector Machine (SVM) method with a normalization technique using min-max on the dataset and a cross-validation technique with several experiments on the K value of the results. This study also compares the Support Vector Machine method with Naïve Bayes (NB) where the accuracy of the SVM model is superior to Nave Bayes with an average accuracy gap of 25%. The accuracy generated by the application of the proposed method is 92.3%.
Computational Intelligence Based Snow Cover Prediction for Photovoltaic Systems

In northern snow-prone areas, photovoltaic (PV) systems are getting more popular. Accumulations of snow on panels after snowfall events, as a major challenge for PV systems’ efficient use in these regions, can attenuate or obstruct solar radiation reaching the surface of the PV cells and cause a significant reduction in the PV system’s power generation. This is an important issue in PV power forecasting (PVPF) for PV-penetrated power systems’ scheduling. To address this issue, data-driven short-term snow cover prediction models for PV systems are proposed in this paper. According to the best of our knowledge, utilizing computational intelligence techniques to predict the presence of a snow cover on PV panels with an hourly resolution solely based on the main meteorological parameters is performed for the first time in the literature. The output of these models can be used as an input for the PVPF stage and help to reduce PVPF errors in snow conditions by enabling the implementation of PVPF approaches compatible with the characteristics of snow-covered PV systems. The study is performed on the historical dataset of electrical and meteorological parameters of a PV system in Canada over 3 years. By applying 5-fold cross-validation and hyperparameter tuning, the best hourly snow cover prediction accuracy, 96%, has been obtained by the developed gradient boosting tree model. Testing this model on the unseen data of 2 other PV systems has resulted in 80% and 78% accuracy for snow cover prediction.
NEW TECHNOLOGY - A NEW APPROACH TO FURTHER VOCATIONAL TRAINING?

As a result of the rapid changes in the labour market and available career paths, people need to reshape their skills and competencies.The World Economy Forum has calculated that new technology will transform over 1 billion jobs worldwide in the next decade, and as such, there is a tremendous need to reskill the workforce.Until now, further vocational training of the workforce has taken place in educational institutions.Now, to a greater extent, big companies such as Google, Apple, Hilton, and start-ups especially, are training their own workforce.So, what is the role of higher education in the future?How could company and higher education institutions work in co-operation to reskill and train the workforce using new technology?Virtual technology (VR) is one of the emerging technologies that is changing the training landscapes both in companies and in educational institutions.Previous research has shown VR's potential in the educational domains, especially in medicine, aviation, arts, journalism and entertainment, but its full potential in work-based education or further vocational training and in the process by which collaborating companies and higher education institutions design, develop and create VR-based training materials have not been researched to an adequate extent.In this paper, we discuss how companies in health care, hospitality, the home furniture and home accessories industry, the cleaning services sector, and higher education (HE) can collaboratively develop, produce and test vocational training materials created using VR technology.Our objective is to understand VR's potential as a tool for work-based training and to design the model and process of how to create training material collaboratively using the living lab method.We have chosen our example industries because they offer suitable entry-level positions to immigrants with a lack of language skills.The other challenge is that the professional background of immigrants varies quite a lot.Health care, hospitality, furniture and home accessories industries, and the cleaning services sector are suffering from labour shortages, and at the same time, we are facing the challenge of inadequate employment of immigrants.
Semantic Search for Scientific Articles by Language Using Cosine Similarity Algorithm and Weighted Tree Similarity

The activity of writing scientific articles by academics at universities is one of the activities that is often carried out, but when writing scientific articles problems arise regarding the difficulty of finding ideas, literature studies, and reference sources that you want to use as references when writing. Sometimes when searching on a search engine, we have trouble finding the right document, because usually, the keywords we are looking for are not in the title section but another part of the structure. Since most search engines only match titles, other structures are usually excluded from matching. So that the search results that we do sometimes don't match what we want. In addition, usually, each scientific article has many language differences in its structure as found in the abstract section. To detect similarities through the structure of scientific articles, an algorithm is used, namely weighted tree similarity, and to detect language using the N-gram algorithm, then the cosine similarity algorithm can be used to check the level of similarity in keyword text with text in scientific articles.
Robust control of quantum systems by quantum systems

Quantum systems can be controlled by other quantum systems in a reversible way, without any information leaking to the outside of the system-controller compound. Such coherent quantum control is deterministic, is less noisy than measurement-based feedback control, and has potential applications in a variety of quantum technologies, including quantum computation, quantum communication, and quantum metrology. Here we introduce a coherent feedback protocol, consisting of a sequence of identical interactions with controlling quantum systems, that steers a quantum system from an arbitrary initial state towards a target state. We determine the broad class of such coherent feedback channels that achieve convergence to the target state, and then stabilize as well as protect it against noise. Our results imply that also weak system-controller interactions can counter noise if they occur with suitably high frequency. We present an example of a control scheme that does not require knowledge of the target state encoded in the controllers, which could be the result of a quantum computation. It thus provides a mechanism for autonomous, purely quantum closed-loop control.
Upper bounds on the length function for covering codes with covering radius $ R $ and codimension $ tR+1 $

The length function $ \ell_q(r,R) $ is the smallest length of a $ q $-ary linear code with codimension (redundancy) $ r $ and covering radius $ R $. In this work, new upper bounds on $ \ell_q(tR+1,R) $ are obtained in the following forms:$ \begin{equation*} \begin{split} &amp;(a)\; \ell_q(r,R)\le cq^{(r-R)/R}\cdot\sqrt[R]{\ln q},\; R\ge3,\; r = tR+1,\; t\ge1,\\ &amp;\phantom{(a)\; } q\;{\rm{ is \;an\; arbitrary \;prime\; power}},\; c{\rm{ \;is\; independent \;of\; }}q. \end{split} \end{equation*} $$ \begin{equation*} \begin{split} &amp;(b)\; \ell_q(r,R)&lt; 3.43Rq^{(r-R)/R}\cdot\sqrt[R]{\ln q},\; R\ge3,\; r = tR+1,\; t\ge1,\\ &amp;\phantom{(b)\; } q\;{\rm{ is \;an\; arbitrary\; prime \;power}},\; q\;{\rm{ is \;large\; enough}}. \end{split} \end{equation*} $In the literature, for $ q = (q')^R $ with $ q' $ a prime power, smaller upper bounds are known; however, when $ q $ is an arbitrary prime power, the bounds of this paper are better than the known ones.For $ t = 1 $, we use a one-to-one correspondence between $ [n,n-(R+1)]_qR $ codes and $ (R-1) $-saturating $ n $-sets in the projective space $ \mathrm{PG}(R,q) $. A new construction of such saturating sets providing sets of small size is proposed. Then the $ [n,n-(R+1)]_qR $ codes, obtained by geometrical methods, are taken as the starting ones in the lift-constructions (so-called '$ q^m $-concatenating constructions') for covering codes to obtain infinite families of codes with growing codimension $ r = tR+1 $, $ t\ge1 $.