Reviewerly/exHarmony huggingface dataset:
Image Restoration Using Weibull Particle Filters

Satellite images are frequently degraded throughout the data collection process. Degradation can involve blurring and different sources of noise. Image restoration attempts to reconstruct the original image from the corrupted data. In literature, different approaches depend on Kalman filtering exist for image restoration. However, it has certain limits in terms of stability, adaptability and visibility. In this article, a new technique based on the concept of particle filtering and the Weibull distribution (WPF) is proposed to restore images degraded by noise. Our approach is recursive and handles nonlinear situations. Simulation results are eventually exhibited a good performance of the WPF over conventional particle filters.
School Administration Services Information System At Muhammadiyah DIKDASMEN TEGAL SARI II WEB-BASE

At the time of the current era of technological globalization, the need for the Basic Education Council at the branch level is to be able to manage school business charities for more than 2 schools, with hundreds of teachers and students, so that the implementation of data collection is quite complicated and complex. Data collection that is done manually is considered inefficient considering the large number of teaching staff and schools managed by the head of education and education. One of them is at the Tegal Sari II branch which has 8 schools consisting of Kindergarten, Elementary School, and Junior High School. Online administrative services are considered sufficient to be a solution in the implementation of administration, one of the systems that has been widely developed is a website-based information system. One of the programming languages ​​that can be used in website development is PHP and MySQL. This research uses the R&amp;D (Research and Development) method. Researchers conduct research in advance to collect the required amount of data with interviews, then carry out system development and conduct testing and evaluation of the system created.
Diagnosis Of Cancer Of The Women In The Content Using Bayes Theorem

Uterine cancer is a malignant process an event that occurs in female reproduction, so that the surrounding tissue cannot perform its function properly. This condition is usually accompanied by abnormal vaginal bleeding and discharge, this disease can occur repeatedly. The possibility of uterine cancer can attack the womb for pregnant women as great as those who are not pregnant. The condition of cancer in the uterus or reproduction during pregnancy is not something that is taken lightly so that it is immediately possible to take appropriate action and treatment. For proper treatment, of course, requires an expert who in this case is a doctor. However, it is not uncommon to get service and treatment from a doctor, having to wait a long time. This is because there are few doctors who handle this case but there are many patients who must be treated. This is not to mention the costs incurred are fairly large. With a fairly large cost, it is not uncommon for people to choose traditional medicine. Therefore, to overcome difficult problems and the high cost of treatment, one alternative is to provide an application to diagnose uterine cancer. With an application that can be accessed online, it makes it easier for the public to find out early on and seek treatment. The results of research that adopts an expert system and Bayes' theorem as an alternative are difficult and expensive to treat, so that people are more helped and get education from an early age.
Fast Gaussian Process Emulation of Mars Global Climate Model

The NASA Ames Mars Global Climate Model (MGCM) software has been in steady use at NASA for decades and was recently released to the public.This model simulates the complex interactions of various weather cycles that exist on Mars, namely the Dust Cycle, the CO2 Cycle, and the Water cycle.Utilized by NASA, the MGCM is used to help understand their empirically observed data through the use of sensitivity studies.However, these sensitivity studies are computationally taxing, requiring weeks to run.To address this issue, we have developed a surrogate model using Gaussian processes (GP) that can emulate the output of this model with relatively small amounts of data in a reduced amount of time (on the order of minutes).We demonstrate the effectiveness of our emulator using backward error analysis.
Retracted: Value Analysis of Using Urinary Microalbumin in Artificial Intelligence Medical Institutions to Detect Early Renal Damage in Diabetes

[This retracts the article DOI: 10.1155/2021/6678454.].
ENGLISH EDUCATION STUDENTS’ PERCEPTION OF INSTAGRAM USAGE AS A MEDIUM TO LEARN ENGLISH

The popularity of Instagram made people increasingly use it well, one of which is to learn new languages. English as an international language is a language that is being encouraged to be mastered by people. The objective of this study is to know how EFL students use Instagram as an English learning medium. The data collected was from ELESP students’ batch 19-21 who learn English with Instagram as the learning medium. This study was conducted in a descriptive qualitative method by distributing an open-ended questionnaire. This study result showed that ELESP students have a positive perception of Instagram usage as the learning medium to learn English. ELESP students deliver how Instagram can enhance vocabulary, grammar, and pronunciation knowledge, and also gain new information.
Interactive Teaching Strategies to Develop Oral Expression in a Foreign Language

Oral expression is crucial for effective communication in a foreign language that repeatedly generates difficulties for its development, as observed in the French Teaching Bachelor (LEF), where an unsatisfactory level in this skill is registered. Given this situation, the objective is to identify the attributes of role-playing, simulation, debate, and metacognition strategies to promote oral expression in virtual environments based on an educational intervention with situated activities. Methodologically, the study is from a quantitative perspective with a descriptive scope and longitudinal design. The results point to the attributes as triggers of oral expression to reach the B1 level of proficiency and increase the performance of activities with systematized patterns. In conclusion, such strategies represent an innovative methodology for teaching a foreign language with cognitive and metacognitive skills for interaction.
European Education: Phenomenon, Myth, or Project?

The paper discusses issues of reforming the system of higher professional education in Russia. The authors state that the main goals of organizing the European zone of higher education were alien to the Russian educational tradition and were not implemented in Russia over the past two decades. Moreover, these efforts have led to the destruction of the unified educational space of the country, a decline in the quality and accessibility of education, and the loss of value-based worldviews. Analyzing the situation, the authors of the article reveal the underlying causes of failure in the fundamental incompatibility of the socio-cultural paradigms of European and Russian education. A comparative analysis of the activities of European and Russian universities formed the basis for the statement about the necessary and reasonable formation of a national education system capable of a productive dialogue with the Euro-American civilization. The authors speak in favor of the approach would meet the Russian national features and ensure the sustainable development of the Russian educational system.
Strategy exploration of school enterprise cooperation in higher vocational colleges

Based on the low degree of school enterprise cooperation in higher vocational colleges, there is no way to start the first step of cooperation mode. This paper explores from the actual project to discuss how to start the first step of cooperation between enterprises and schools, and how to promote cooperation and collaboration, and finally form mutually beneficial and win-win cooperation. From the school's initiative to seek cooperation to derive equality and mutual benefit, promote the sustainable and healthy operation of school enterprise cooperation.
Classification for Synthetic Aperture Radar Ship Image of the Ship Targets under the Few-shot Condition

Deep learning algorithms have shown outstanding results for the categorization of synthetic aperture radar (SAR) images. But because there is a conflict between the deep learning techniques' broad parameter space and the scanty labeled samples of ship targets, most deep learning models are unable to provide satisfying outcomes under the few-shot scenario. Classification for SAR ship images often faces the few-shot condition because they are sensitive to system parameters, so that the amount of effective SAR images is very low. To this end, this article proposes a method based on graph neural network (GNN). An end-to-end classification model was trained by this method. Moreover, our method extracts multi-scale features of the targets to make classification effect better. The dropout layers are added into the graph convolution layer to reduce the overfitting in few-shot classification. Finally, our model is applied to the mixed dataset of the simulated and real data to verify effectiveness of our method. The experimental findings presented in this research show that our method outperforms other cutting-edge approaches in terms of categorization rate.
Researches advanced in Natural Scenes Text Detection Based on Deep Learning

The research on text detection and recognition in natural scenes is of great significance for obtaining information from scenes. Thanks to the rapid development of convolutional neural networks and the continuous proposal of scene text detection methods based on deep learning, breakthroughs have been made in the recognition accuracy and speed of scene texts. This paper mainly sorts, analyzes and summarizes the scene text detection method based on deep learning and its development. Firstly, the related research background and significance of scene text detection are discussed. Then, the second part is the elaboration of some main technical research routes of scene text detection. According to the timeline of the detection methods, the specific contents of various text detection models are further introduced. Thirdly, this paper compares and analyzes the experimental results of different models. Furthermore, improvements of some models with relationship, effects, advantages and disadvantages and expectations are further introduced. Finally, the challenges and development trends of scene text detection technology based on deep learning are summarized.
Research on the precise recommendation service system of digital library

With the continuous development of big data technology, the service mode of library has changed greatly. This paper proposes a method for building a digital library precise recommendation service system based on user portraits, which improves the recommendation accuracy and efficiency of the digital library. Firstly, systematically sort out the research status of the application of user portrait technology in the field of library and information. Then, the needs of precise recommendation of the digital library under the user portrait technology in terms of recommended content, service positioning, user functions were analyzed. Finally, introduce the construction method of the recommendation service system of the digital library from the three aspects of data module, recommendation module and user module. This research aims to explore an effective transformation and development path for the precise recommendation of digital library.
Researches Advanced in the Development and Application of Information Extraction

Natural language processing (NLP) is an interdisciplinary subject of linguistics and computer science, which processes the language used for human communication into a machine language that can be understood by machines.The task of information extraction is to obtain target information accurately and quickly from a large amount of data and improve the utilization of information. With the rapid development of Internet applications, how to quickly and accurately analyze the really useful information in these text data is particularly critical and urgent. Information extraction has become an important branch of natural language processing. Thanks to the rapid development of deep learning, the performance of information extraction has made breakthroughs in recent years. In this paper, based on the detailed literature analysis, this paper first review the development of information extraction. Secondly, the research progress of key technologies of information extraction is summarized from four aspects: named entity recognition, anaphora resolution, relationship extraction and event extraction. Finally, we analyze some main problems of information extraction and predict the research trend of information extraction.
A Study on the Acceptance Attitudes of Chinese Populations Towards Service Robots in the Midst of an Epidemic

Before the World Health Organization declared novel coronavirus pneumonia (COVID-19) a pandemic in 2019, service robots were already in use and in the process of being further developed. In the wake of the COVID-19 outbreak, frontline service robots became a hot topic of discussion to keep social distance and control the outbreak. And now, as each country adapts to the new crown epidemic normality, China is still pursuing a dynamic clearance policy. In this particular context, and in turn, the analysis online review examines the perceptions and attitudes of the Chinese public towards the application of robots in the service industry. Their evaluations of service robots on five dimensions are summarized. It is concluded that the public is more receptive to service robots, finds them useful for epidemic prevention and control and is amused and curious. This provides a reference for those in charge of many service industries, such as the hospitality tourism industry, to take advantage of this opportunity to develop services as a combination of robots and humans to further broaden the market.
Analysis on Transfer Learning Models and Applications in Natural Language Processing

Assumptions have been established that many machine learning algorithms expect the training data and the testing data to share the same feature space or distribution. Thus, transfer learning (TL) rises due to the tolerance of the different feature spaces and the distribution of data. It is an optimization to improve performance from task to task. This paper includes the basic knowledge of transfer learning and summarizes some relevant experimental results of popular applications using transfer learning in the natural language processing (NLP) field. The mathematical definition of TL is briefly mentioned. After that, basic knowledge including the different categories of TL, and the comparison between TL and traditional machine learning models is introduced. Then, some applications which mainly focus on question answering, cyberbullying detection, and sentiment analysis will be presented. Other applications will also be briefly introduced such as Named Entity Recognition (NER), Intent Classification, and Cross-Lingual Learning, etc. For each application, this study provides reference on transfer learning models for related researches.
TRENDS OF TRANSFER DSLR CAMERA USERS TO MIRORLESS BETWEEN STUDENTS OF THE FACULTY OF COMMUNICATIONS UNIVERSITY OF GUNADARMA KARAWACI

Aims to find out how students of the Faculty of Communication at Gunadarma University as camera users follow the trend of switching from DSLR camera users to Mirrorless.This type of research is qualitative with a descriptive approach.The method used is observation, interviews, literature study, and documentation.The theory used is Theory Uses and Gratifications.The results obtained by the researcher are that the six informants follow the trend of mirrorless cameras by using them as a necessity for lecture activities and all informants have an active and inactive role in using the camera.There is an assumption of using media for special purposes, deliberately choosing to use mirrorless because of the satisfaction of what they are looking for that can meet the needs of their use, using mirrorless is influenced by different people besides that they use mirrorless thanks to the convenience of technology, because the learning media for lectures and as hobbies or work.The conclusion for now is mirrorless cameras as learning media that are easy to understand and easy to carry anywhere without requiring a lot of space, compact size and the same features as DSLR cameras.This trend of mirrorless can be positive or negative because not everyone who understands photography has switched to mirrorless.
Readability of PISA-like Reading Texts: A Lesson Learned from Indonesian Teachers

This article discusses the text readability of Programme for International Student Assessment (PISA)-like reading texts written by Indonesian-English-teachers who are teaching in high schools in Jawa Barat province, Indonesia. The aims of the research are to describe the lexical density, grammatical intricacy, and lexical variation indexes of the PISA-like reading texts compared to PISA reading texts 2018 released field trial new reading items. The method applied is a qualitative with descriptive quantification. The qualitative method is employed to identify and describe both lexical and grammatical words, in addition to specifying the lemmas and ranking clauses in the PISA-like reading texts. Quantifying the indexes of lexical density, grammatical intricacy, and lexical variation are implemented. All analyses utilized are based on the systemic functional linguistic approach. It is reported that, firstly, the texts of PISA reading texts 2018 are lexically denser than the PISA-like reading texts. Secondly, the texts of PISA reading texts 2018 are grammatically more intricate than the PISA-like reading texts. Lastly, PISA-like reading texts have similar index with PISA reading texts 2018.
Rhetorical Moves and Meta-discourse Markers in Abstracts of Indonesian Scopus Indexed Journals Across Academic Disciplines

Rhetorical moves purposes to examine the basic structures of research articles, while meta discourse markers are elements to construct and to establish ideas and arguments. This study compares rhetorical moves and the function of meta discourse markers in research articles abstracts of different academic disciplines published in reputable indexed journals. This study employs (Pho, 2008)’s five-move analysis and the classification of meta discourse marker proposed by (Dafouz-Milne, 2008) as the research framework. The writer took five Indonesian Scopus Q1 and Q2 indexed journals from different academic disciplines. Those are Indonesian Journal Science and Technology (IJoST), Indonesian Journal of Applied Linguistics (IJAL), Journal on Mathematics and Education (JME), Studia Islamika and Forest and Society. The results show that in terms of rhetorical move of abstracts, M2 and M4 became the moves which occur in all journal abstracts. In terms of meta discourse markers, all journal abstracts employ logical markers and code glosses. Sequencers, topicalisers, and illocutionary markers are used in small numbers, while reminders and announcements are not be found in any abstracts. The findings could help students and writers to produce abstracts that fulfill the requirements to be published in Scopus indexed journals.
Occurrence Location and Propagation Inconformity Characteristics of Vibration Events in a Heading Face ofa Coal Mine

The location and characteristics of the vibration event in the heading face of a coal mine are of great significance for the monitoring and early warning of rock burst. The aim of the study is to reveal the occurrence location and propagation characteristics of macro vibration events in a heading face of coal mine. After statistics and analysis, the occurrence location of the events is mostly around the head of heading face revealed by amplitude sequencing and arrival time sequencing. As the vibration event propagates to the rear sensors, the amplitude presents exponential attenuation, which is the same as the ideal state; however, the main frequency does not appear with linear attenuation, which is obviously different from the ideal state. The reason for the inconsistency of the main frequency is probably related to the complex underground environment. The results of the main frequency results in this study are completely opposite to the previous study, indicating that the inconsistency of the main frequency should be regarded carefully when using as an early warning index.
Influence of digital media on student practice of the faculty of philosophy, letters and educational sciences

The objective of this study is to determine the influence of digital media on student practice at the Faculty of Philosophy, Letters and Sciences of Education, given that it is of vital importance to guarantee that the infrastructure of digital media, keeping up with the current development of teaching and learning, in addition, educators and students should be encouraged to enjoy more in the use of these tools. The methodology applied in the research is descriptive, exploratory, field, and explanatory, with a mixed approach, that is, qualitative and quantitative, a structured survey was applied on a Likert scale, applied to 245 students. A high reliability of 0.842 was obtained through the SPSS statistic, which shows that digital media have an influence on student practice, generating benefits in the learning-teaching process.
Development of Media with Pictures for Kindergarteners’ Reading Readiness

This is a developmental study that began with observations of some early childhood children in Siak Sri Indrapura, Indonesia, who lacked reading readiness. Seeing the potential of Malay folklore, a learning media for Malay folklore pictorial stories was developed. The process of creating media begins with the determination of the story and theme, followed by the creation of designs and product models. Validator assessment is feasible and may be used to determine a child's readiness for reading. To determine the effectiveness of the media, this study used a quantitative method with a two-group post-test design. According to the t-test results, a t-observed value of -8,175 with a significance value of 0.000 indicated that there was a difference in reading readiness between the experimental and control groups, indicating that the Malay folklore pictorial story media was effective for early childhood reading readiness in Siak Sri Indrapura.