Reviewerly/exHarmony huggingface dataset:
PENERAPAN METODE DRILL UNTUK MENINGKATKAN KEMAMPUAN MENULIS PERMULAAN HURUF CETAK KELAS I SD

This research is based on how low students’ ability of writing the beginning of printed letters on first-grade students in an elementary school in Bandung. Low ability to write the beginning of printed letters because the method that was given by the teacher has not facilitated the beginning of the writing. This research aims  to investigate the implementation of the drill method. The method is used to increase the ability of writing printed letters on first grade students in an elementary school in Bandung. The method used in this research was a  Classroom Action Research (CAR) model designed by Kemmis and Mc. Taggart, used with two cycles. The subject of this research was 30 first grade students in an elementary school in Bandung. The data collection technique used in this research were observation, test, and documentation study. Qualitative data were processed through procedures data collection, data reduction, data presentation, and concluding. While in this research the quantitative data were processing through statistics analysis result of the score, average score, the percentage of completion in the write the beginning of printed letters. In cycles one reaches the average scores at 73.8 with the percentage of graduation is 65% to two that average is 96%. Based on the result, studies should be started with learning implementation plans that refer to Permendikbud No. 22 Thn. 2016. From this research, it can be concluded that the implementation of the Drill Method can improve writing printed letters on first grade students in elementary school in Bandung.
Keeping It Simple: Agile Analysis

Writing reliable software is hard. No matter how determined we all are to avoid it, we do make mistakes and at a fairly predictable rate. What makes a software system reliable is not determined just by the care we take in planning and structuring a design but also by the methods we use in catching those pesky bugs that come along for the ride. For safety-critical code, the use of strong static source code analyzers has become an essential part of the development process. The best analyzers are based on solid theory and maintained by large teams of highly skilled developers. The tools can patiently trace through complex execution paths to reveal a range of subtle bugs, although, of course, only the types of bugs the tools have been trained on. The tools can be slow and costly, though, and the warnings they generate are sometimes difficult for humans to evaluate accurately.
Dynamics of an Atom Cavity Field System in Interacting Fock Space

In this paper, we investigate one-time passing of a $V$-type three-level atom through a single-mode interacting field in a cavity. We extend the idea of elementary Jaynes-Cummings model by assuming that the field vector belongs to interacting Fock space. In the process, we arrive at a state vector which will be analyzed to study the nonclassicality of the evolved state of the system.
On User Interfaces for Large-Scale Document-Level Human Evaluation of Machine Translation Outputs

Recent studies emphasize the need of document context in human evaluation of machine translations, but little research has been done on the impact of user interfaces on annotator productivity and the reliability of assessments. In this work, we compare human assessment data from the last two WMT evaluation campaigns collected via two different methods for document-level evaluation. Our analysis shows that a document-centric approach to evaluation where the annotator is presented with the entire document context on a screen leads to higher quality segment and document level assessments. It improves the correlation between segment and document scores and increases inter-annotator agreement for document scores but is considerably more time consuming for annotators.
Research Guides: Off-Campus Library and Interlibrary Loan Services: How to Find Articles in a Specific Journal

This LibGuide outlines the policies and procedures for off-campus students, faculty & staff utilizing the services and resources of the Shapiro Library.
Effective Contrast Enhancement of Fabric Images Using Adaptive Intensity Transformation

Quality improvement ameliorates the visibility of entity in the picture by increasing the luminance disparity between the substance and their scene. Based on principal intensity rank examination and alterable intensity transfiguration of pictures my work presents a new clarity improvement scheme. In this work, glow alterable amplitude shift expressions estimated in the little occurrence lightness component using wavelet domain and mutates strength standards according to the shifting expression. Discrete wavelet transform (DWT) is applied in fabric images. Low-low sub band of the fabric image is splitted into low, middle, and high intensity layers with the support of log average lightness approach. Using the knee parameters and the gamma parameters intensity conversion values are evaluated based on our need. This estimation is based on the supreme luminance point of each and every layer. After the intensity transfiguration, we obtained the resulting superior image using Inverse Discrete Wavelet Transform. The outcome show that the proposed work boosts the whole quality of the image and perceptibility of general facts better than presented methods.
Unsupervised Approach to Multilingual User Comments Summarization.

User commenting is a valuable feature of many news outlets, enabling them a contact with readers and enabling readers to express their opinion, provide different viewpoints, and even complementary information. Yet, large volumes of user comments are hard to filter, let alone read and extract relevant information. The research on the summarization of user comments is still in its infancy, and human-created summarization datasets are scarce, especially for less-resourced languages. To address this issue, we propose an unsupervised approach to user comments summarization, which uses a modern multilingual representation of sentences together with standard extractive summarization techniques. Our comparison of different sentence representation approaches coupled with different summarization approaches shows that the most successful combinations are the same in news and comment summarization. The empirical results and presented visualisation show usefulness of the proposed methodology for several languages.
A New Approach to Arabic Tense Form-Content Mismatch in Four Translations of the Qurʾan

Abstract The tense systems in English and Arabic are markedly similar, but one striking feature makes the two-part ways: Arabic boasts the capacity of expressing the past and the future in forms that are not tallied with what English does. Arabic and English can express the future and the past in the present form. Yet Arabic, especially Qurʾanic Arabic, has the singular capacity for expressing the future in past form and the past in present form. The mismatch in the Arabic tense system in the English translation of the Qurʾan is given due attention in the present paper, and a new approach is presented to address this significant problem. The four translations selected are Arberry’s, Yusuf Ali’s, Pickthall’s and Asad’s. A model is proposed to analyze significant selections of such mismatches, based on graphical representations of TOC, TOE and linking form. The study concludes that the most inconsistent translation is Pickthall’s, while Arberry’s is the most consistent of all. It also reveals that although Asad is not fully proficient in English like Arberry, he succeeds in clearing the hurdle of translating tense form-content mismatch most of the time.
Multimodal deformable registration based on unsupervised learning

Multimodal deformable registration is designed to solve dense spatial transformations and is used to align images of two different modalities It is a key issue in many medical image analysis applications Multimodal image registration based on traditional methods aims to solve the optimization problem of each pair of images, and usually achieves excellent registration performance, but the calculation cost is high and the running time is long The deep learning method greatly reduces the running time by learning the network used to perform registration These learning-based methods are very effective for single-modality registration However, the intensity distribution of different modal images is unknown and complex Most existing methods rely heavily on label data Faced with these challenges, this paper proposes a deep multimodal registration framework based on unsupervised learning Specifically, the framework consists of feature learning based on matching amount and deformation field learning based on maximum posterior probability, and realizes unsupervised training by means of spatial conversion function and differentiable mutual information loss function In the 3D image registration tasks of MRI T1, MRI T2 and CT, the proposed method is compared with the existing advanced multi-modal registration methods In addition, the registration performance of the proposed method is demonstrated on the latest COVID-19 CT data A large number of results show that the proposed method has a competitive advantage in registration accuracy compared with other methods, and greatly reduces the calculation time © 2021, Editorial Board of JBUAA All right reserved
Microchips work on numbers and images addressed in the paired number framework

A chip is a PC processor where the information handling rationale and control is remembered for a solitary incorporated circuit, or few coordinated circuits. The microchip is a multipurpose, clock-driven, register-based, advanced incorporated circuit that acknowledges twofold information as information, measures it as indicated by directions put away in its memory, and gives results (likewise in paired structure) as yield. Microchips contain both combinational rationale and successive computerized rationale. Microchips
『논어(論語)』의 혼종적 글쓰기의 의미와 작용

The Analects is multi hybrid text comprising anecdote, proverbs and prose, etc. Anecdote in The Analects makes readers to read it conveniently, entices reader’s empathy and offers readers to be thoughtful because the description of daily life is the basis of significant philosophic thoughts. However, only anecdote is not able to form philosophic contexts and thoughts. They should be completed only when integrated thoughts are activated by relating proverbs including normal words and prose depicting Confucius’ daily life.The Analects is fundamentally the discourse forum of disciples because they recorded and edited it. Accordingly, the voices of various characters, including the Confucius and disciples’ voices, the polyphony, acts as another major factor in the hybrid writings. There used to be focus on Confucius when reading The Analects but presently there should be focus on multi opinions. That is because various voices make up a series of narratives, helping to reflect on the truth of human morality and life more specifically in everyday life than any other philosophical discourse.
COVID-19 and creative university learning spaces. Research trends

COVID-19 has disrupted the lives of humans causing devastating health effects and life of a large part of the world population, affecting the social, economic and educational spheres of the planet. The scientific community is facing one of its greatest challenges to solve a global health problem such as the COVID-19 pandemic. This situation has generated an unprecedented volume of publications. The impact of COVID-19 on teaching has meant that moments of social contact have disappeared in exchange for meetings, classes, exams or virtual meetings. In this scenario, the university classrooms when reopened will not be the same, nor will their campuses or spaces in the educational field, should contribute creativity in organizing and using them. The objective of the study was to identify scientific publications related to the effects of COVID-19 in university classrooms during the period 2019 to the present. For this, a bibliometric analysis of the scientific literature was performed. Thus, 676 documents were identified on this subject. The results of the analysis revealed that scientific productivity has increased since January 2020 with more than 650 articles on the disease, verifying the deep interest in COVID-19 in all disciplines. The main research trends include the impact of returning to the classroom with the effects on the cognitive processes, motivations and academic performance of students.
COMPARATIVE ANALYSIS METHODS FUZZY TIME SERIES AND FUZZY TIME SERIES CHENG ON CORN PREDICTION

Domestic maize production for several years has not been able to meet the needs on a national scale. Many aspects affect this. This problem can be overcome by increasing production. One of the efforts to increase production is to predict future annual maize production using time series data. The time series data in question is data on corn production taken from the Ministry's Website. In this study, there are two prediction methods used to determine the annual maize yield for the coming year. Fuzzy Time Series and Fuzzy Time Series Cheng methods are the best prediction methods to be used in time series data where there are different stages between the two methods at the time of the formation of FLRG. In addition, researchers also used MAPE to compare the results of the accuracy of predicting corn production against the two methods. The corn production data used during 1970-2019 were 48 data. From the results of the tests carried out, the prediction results using the fuzzy time series method have a higher level of accuracy with the results of the corn accuracy value is 95.12% with a MAPE of 4.88% compared to the Fuzzy Time Series Cheng method with a result of 91,37%. with a MAPE of 8,63%.
OCR BASED IMAGE TEXT TO SPEECH CONVERSION

Optical Character Recognition (OCR) is used for the purpose of extracting text from an image. The main agenda of an OCR is to make easy viewed & editable documents from existing paper documents or image files. That can be used to translate images of any format to the text format. This website helps one to convert the texts in image files into editable text files. So that we have to convert bulk of pages converted into editable text in a simple way.
Enforced Isolation Deep Network For Anomaly Detection In Images

Challenges in anomaly detection include the implicit definition of anomaly, benchmarking against human intuition and scarcity of anomalous examples. We introduce a novel approach designed to enforce separation of normal and abnormal samples in an embedded space using a refined Triple Loss Function, within the paradigm of Deep Networks. Training is based on randomly sampled triplets to manage datasets with small proportion of anomalous data. Results for a range of proportions between normal and anomalous data are presented on the MNIST, CIFAR10 and Concrete Cracks datasets and compared against the current state of the art.
The Importance of an Interdisciplinary Approach to Teaching Philosophy

In this article analyzedthe relevance of using an interdisciplinary approach during the teaching of philosophy. The author of this article paid attention to the points of the connection of philosophy and science.
Sistem Informasi Absensi Pegawai Berbasis Web Pada Dinas Perhubungan Kota Palembang (Bagian TJR)

The problem at the Palembang City Transportation Agency is that the fingerprint attendance system cannot be used during the current pandemic because it can cause viruses to stick to spread employees, so now the Palembang City Transportation Service uses a manual attendance system which is less effective because it can impact on employee discipline and performance as well as mistakes often occur in entering employee info. With these problems, it is necessary to create a web-based attendance information system at the Palembang City Transportation Agency. The method used is the waterfall method which includes: needs analysis, design, coding, testing and implementation. The resulting web-based employee attendance application can provide convenience in the process of attendance, data search and attendance recap calculations, as well as minimize the loss and loss of attendance data recording at the Palembang City Transportation Agency.
PENGARUH PENGGUNAAN INTERNET TERHADAP PENYELASAIAN TUGAS (PR) MAHASISWA UNIVERSITAS QUALITY PROGRAM STUDI PGSD PADA MATA KULIAH KONSEP DASAR IPA

This study aims to determine the effect of internet use on task completion (PR) of PGSD University Quality Study Program Students in Science Concept Basic Subjects 2019/2020 Academic Year. This type of research is expostfacto with quantitative methods. The results of the average value obtained by the class 2B11 82.74 namely the class that uses the Internet for completing assignments and class 2B12 74.05 ie the class that does not use the internet for task completion. Table frequency of final grade test scores that use the internet for completing assignments and classes that do not use internet for completing assignments can be distributed in a relative frequency table then drawn into a histogram to determine the comparison of students completing assignments using the internet and students completing assignments not using Internet. Hypothesis testing using t test with a significant level of α = 0.05 and dk = (obtained 36.68 (0.975) (76) = 1.73. From the results of hypothesis testing the data can be concluded that there is an effect of task completion on task completion (PR) Quality University Students PGSD Study Program in Science Basic Concept Courses. Keywords: Task Completion, Internet Usage, Expostfacto
The Model of Formation of a Stochastic Worldview of High School Students in the Context of the Digitalization of Mathematics Education

The article is devoted to the study of the peculiarities of the stochastic worldview of high school students. Stochastic world outlook lays the landmarks of creative and practical activities, helps to create favorable conditions for development of intellectual potential of a pupil. &#x0D; Digitalization in education determines the dominant nature of both the active use of modern methods, tools and technologies of education, and the formation of students' digital skills, training in data processing and analysis, which is closely related to the teaching of stochastics and indicates the relevance of research. In this regard, the untapped potential of stochasticity is greater than any other field of knowledge. Widely used probabilistic-statistical methods contribute to the study of variability and complexity of political, economic, social processes. In this regard, a model of formation of stochastic worldview of high school students in the conditions of digitalization of mathematical education is developed. This model is a set of educational and digital information content, which gives the results of the educational process a new quality of education, allows you to realize the integrity of the worldview, values and motivational constructs, creates the necessary conditions under which it becomes possible to generate knowledge by students themselves based on self-development and self-actualization, their active and productive creativity.
A STUDY OF SELF CONCEPT AND ACADEMIC ACHIEVEMENT AMONG STUDENTS AT HIGHER SECONDARY LEVEL STUDENTS

It is an important term for both social psychology and humanism. The scholastic achievement for learning outcome that a student gains in his school is known as academic achievement. The way that pupils apply themselves is an important factor in life. In this rapidly changing world and with the growing advancement good academic achievement helps pupils for their proper development. This study focuses on the important psychological variables like self-concept and academic achievement. Normative survey method was used for the research. Sample includes higher secondary students. Stratified sampling technique was used. The statistical technique used was correlation and t test.
The Role of AI in Cloud Computing

Cloud computing is a method of delivering computer services over the internet. Artificial intelligence (AI) is one of the methods for intelligently automating tasks using computer resources. Cloud computing can be an AI platform, and AI can automate the management and operation of cloud computing, but they are both just a means to each other.Artificial intelligence (AI) is a type of technology that is expected to boost current cloud platforms and drive next-generation cloud computing technologies. The most critical is that, in an era where we are dealing with a growing amount of available data, we need technology that can quickly summarise, analyse, and act on this data in order to enhance processes and outcomes. This paper provides an overview of what are the benefits of combining AI and Cloud computing.
Музыкальные фигуры в отечественных славильных сочинениях

This article deals about stable musical figures in Russian Glorifying music. They are in sustainable complex of musical means and have quasi-metaphorical way, are to be found in music of different composers. Russian glorifying music is a genre group encompassing a number of genres of vocalinstrumental compositions. Over three centuries of its existence certain musical means have been continuously present. The article discusses the following tropes in pre-Revolutionary music: «triumph», «jubilation», «exaltation», «fanfare», «proclamation». It also attempts to classify the musical devices found in Soviet music. A four-part trope classification is suggested: melodic, figurative, affective, and grammatical tropes.
Automatic Post-Editing for Translating Chinese Novels to Vietnamese.

Automatic post-editing (APE) is an important remedy for reducing errors of raw translated texts that are produced by machine translation (MT) systems or software-aided translation. In this paper, we present the first attempt to tackle the APE task for Vietnamese. Specifically, we construct the first large-scale dataset of 5M Vietnamese translated and corrected sentence pairs. We then apply strong neural MT models to handle the APE task, using our constructed dataset. Experimental results from both automatic and human evaluations show the effectiveness of the neural MT models in handling the Vietnamese APE task.
Organization and conducting the integrated lesson "Geoinformation systems in our life" in the distance learning context

The article deals with the problem of developing methodological support and organizing lessons in a modern school in the context of distance learning. As practice shows, modern Russian schools for the most part do not have significant experience in organizing and conducting online lessons. Many teachers were not ready to organize distance learning, because they had never conducted such lessons before. In this regard, the relevance of this work is due to the contradiction between the lack of high-quality teaching materials for organizing and conducting lessons in a distance form and the need to conduct online lessons in the context of the coronavirus pandemic. The article presents the integrated lesson "Geoinformation systems in our life" at the junction of two subject areas: informatics and geography. An approach to organizing and conducting such a lesson for 9th grade students in gymnasium 9, Krasnoyarsk in the usual learning environment (as part of the educational process in the school) is described, as well as the possibility of organizing and conducting this lesson in a distance format. The experience described in the article is intended to help teachers adapt the materials for standard lessons to use in online lessons. The materials presented in the article can be replicated in educational organizations at middle school, and also used to improve the skills of informatics teachers.