Reviewerly/exHarmony huggingface dataset:
Research on Anomaly Detection of Surveillance Video Based on Branch-Fusion Net and CSAM

As the monitor probes are used more and more widely these days, the task of detecting abnormal behaviors in surveillance videos has gained widespread attention. The generalization ability and parameter overhead of the model affect how accurate the detection result is. To deal with the poor generalization ability and high parameter overhead of the model in existing anomaly detection methods, we propose a three-dimensional multi-branch convolutional fusion network, named “Branch-Fusion Net”. The network is designed with a multi-branch structure not only to significantly reduce parameter overhead but also to improve the generalization ability by understanding the input feature map from different perspectives. To ignore useless features during the model training, we propose a simple yet effective Channel Spatial Attention Module (CSAM), which sequentially focuses attention on key channels and spatial feature regions to suppress useless features and enhance important features. We combine the Branch-Fusion Net and the CSAM as a local feature extraction network and use the Bi-Directional Gated Recurrent Unit (Bi-GRU) to extract global feature information. The experiments are validated on a self-built Crimes-mini dataset, and the accuracy of anomaly detection in surveillance videos reaches 93.55% on the test set. The result shows that the model proposed in the paper significantly improves the accuracy of anomaly detection in surveillance videos with low parameter overhead.
Paradoxes of MaxEnt markedness

Over the past two decades, theoretical linguistics has taken a probabilistic turn. Maximum entropy (ME) has been endorsed as a model of probabilistic phonology because of its classical guarantees for grammatical inference. Yet, little is known about the basic organizing principles of ME phonology beyond circumstantial evidence of ME’s ability to fit specific patterns of empirical frequencies. The study of ME typologies is difficult because they consist of infinitely many grammars that cannot be exhaustively listed and directly inspected. Uniform Probability Inequalities (Anttila and Magri 2018) are a new tool that solves the problem: they characterize cases where one phonological mapping has a probability smaller than another mapping and this probability inequality holds uniformly for every grammar in the typology. In other words, uniform probability inequalities are universals of probabilistic grammars. We present a new generalization about ME uniform probability inequalities and argue that they are phonologically paradoxical and prune the set of ME universals down to almost nothing. This suggests that ME is not a suitable model of phonology.
Sentiment Analysis of Online Lectures using K-Nearest Neighbors based on Feature Selection

Online lecture is a distance learning system that utilizes information technology in its implementation. Although it has been agreed, this lecture system has caused controversy. Not infrequently online lectures are considered to bring a variety of new obstacles in lectures, and not a few also consider that online lectures are the most appropriate solution to continue to run lecture activities in the midst of alarming pandemic conditions. In response to this policy, many people expressed various kinds of opinions and views on the implementation of online lectures which are generally stated on social media, one of which is through Twitter. Sentiment analysis is a branch of the science of machine learning that is carried out to obtain useful information or new knowledge by extracting, understanding, and processing text data automatically. Several methods are widely used by researchers to classify sentiment analysis datasets including K-Nearest Neighbor (K-NN). K-NN will be adapted to classify online lecture datasets because K-NN can produce good accuracy on a large number of data. The presence of feature selection also helps machine learning in improving its performance. The purpose of this study was to determine student sentiment toward online lectures and to determine the level of accuracy of the combination of K-NN with various feature selections. Based on 780 tweets data, a classification of 394 positive sentiments, 320 negative sentiments, and 39 neutral sentiments was obtained. So, the results of student opinions are on POSITIVE sentiments. The accuracy result of the K-NN Algorithm was 56% and the accuracy of the K-NN Algorithm + Forward Selection was 51%, the accuracy of the KNN Algorithm + Adabost was 54%, and the accuracy of the KNN Algorithm + Genetic Algorithm was 55%.
Analysis of Prototyping Methods Implementation for Library Information Systems Development in SMAN 3 Bengkalis

SMAN 3 Bengkalis Library is a school library with a collection of reading books and lessons located in Bengkalis Regency, Riau Province. Currently, the system that operates in the SMAN 3 Bengkalis library is still conventional and is prone to physical damage. In addition, with current technological advances, the registration system for students as members is also still written using paper cards, plus the difficulties of library staff in procuring and managing library books. Based on these problems, a web-based library information system development is proposed, expected to solve the problems that occur. With prospective system users who are pretty laymen, a particular way is needed to develop the system, especially when carrying out user needs and system design. With this need, a prototyping method is used, which does function to accommodate these needs. Each phase of this method is carried out carefully to produce a product that meets expectations. In this study, an evaluation of the development process was carried out. The evaluation is carried out in several ways, such as UAT and Usability Testing with ISO 9126 and 9241-111. Based on the results of the evaluation, it was found that with the application of this method can produce a library information system product that is good and runs according to functionality and is to the expectations of users in solving the problems they face.
Learning Media Development of Beginner Written Receptions Based on Augmented Reality Applications

This study aims to discuss the development process of augmented reality as a French language learning media which is applied in the reception ecrite debutante course; the augmented reality brings about a product, namely the new livgent red application, textbooks, and manuals for its use. This development process was carried out through material and media feasibilities by four validators, so that the results of this development were feasible to apply to students. Based on the needs analysis, students still need more varied media when studying and adapted to the times, namely the use of technology and communication tools. Therefore, this media is the solution we provide because it has several advantages such as: easy to use, colorful, interactive in 3D, attractive, among others. This media can accommodate text, video, 3D, images and audio and can be used online or offline. This research was adapted from Branch’s ADDIE model (analysis, design, development, implementation, and evaluation), but this paper only reached the development stage. In the material validation process, an average value of 91.2% was obtained, so it was categorized as very good. Meanwhile, in the media validation process, an average value of 92.75% was gained, so it was categorized as very good. Thus, the development of media based on augmented reality applications is proved to be valid or feasible in the students’ learning. Keywords: Development, media, reception ecrite debutante, augmented reality, livgent
The Correlation among Anxiety, Language Learning Strategies and Speaking Skills at SMA Negeri 1 Pagelaran Pringsewu Lampung

This study's research was to determine whether there was a significant correlation among students' anxiety, language learning strategies, and speaking skills at SMA Negeri 1 Pagelaran Pringsewu Lampung. This type of research is a quantitative study. This research was conducted at SMA Negeri 1 Pagelaran Pringsewu Lampung with a population of XI IPA 3 and XI IPA 4 graders with a total of 54 students. Then the population is divided into two classes: the tryout class and the test class as the research sample. The instrument used in this research is a questionnaire on anxiety, language learning strategies, and speaking test. The data were analyzed using Multiple Linear Regression Formula in SPSS 25.0 for windows. The result of T-test 1 showed that the significant value was 0.03. It indicated .000 smaller than the value of α = 0.05, whereas the calculated t value is greater than the table (2.303 &gt; 2064). The result of T test 2 showed that the significant value was 0.02, which is smaller than the value of α = 0.05 (0.02 &lt; 0.05), and the t value is greater than the t table (2.318 &gt; 2. 064). F test showed that the significant value was 0.000 which is smaller than the value of α = 0.05 (0.02 &lt; 0.05) and the F value is greater than F tables (16.729 &gt; 3.39). The result of the R square of coefficients determination was .582, which means the influence of anxiety and language learning strategies on speaking skills was 58.2%. Therefore, the hypothesis of all the results was Ho was rejected, and Ha was accepted. It means there is a correlation among students' anxiety, students' language learning strategies, and their speaking skills. Keywords: Correlation, Anxiety, Language Learning Strategies, Speaking Skills
Exploring various Particle swarm optimization using EDAS Method

optimization, particle swarm optimization, discrete BSO, Parallel BSO, Orthogonal Learning Particle Swarm Op timization OLPSO, Binary Particle Swarm Optimization, Multivariate Particle Swarm Optimization (MGBSO), Advanced Research Particle Swarm Given the optimization, try to improve it basically a candidate solution quality Upgrade. Particle mass optimization (PSO) is bio-inspired One of the means, and rather than a solution The ideal is the simple one. This is dif ferent optimization methods, for this only the objective function is required and the gradient or subject to objective particle mass optimization No, it is any other form as proposed Does not depend. by Kennedy and Eberhardt in 1995. Estimation Based on the distance from the mean solution (EDAS). has A new and efficient MCDM method. This Method Alternatives are selected from Average solution based on their distance is determined.Alternative:UPSO,FDR, FIPS, and CLPSO. Evalua tion Preference: Sphere, Rosen rock, Quadric, Schwefel, Griewank, Weierstrass. from the result it is seen that Griewank and it got the first rank whereas is the Quadric got is having the lowest rank. the result it is seen that Griewank and it got the first rank whereas is the Quadric got is having the lowest rank.
Evaluation of Machine Learning Algorithms using TOPSIS

Machine Learning Algorithms.A subfield known as artificial intelligence (AI) and machine learning (ML) enables computers to "learn on their own" with training data and clearly planned without progressing over time.Data patterns can be found using machine learning algorithms, which can then be used to generate predictions on their own.The research methods and statistical models that computer systems use that are taught explicitly without a specific implementation of the task are known as machine learning (ML).Many of the programs have learning mechanisms that are used daily.A web search engine like Google is utilized frequently because it has a learning algorithm that learns how to rank websites.Numerous applications, including data mining, image processing, predictive analytics, etc., utilize these algorithms.The fundamental benefit of machine learning is that once an algorithm learns how to use the data, it will carry out its duties automatically.Algorithms that use machine learning can discover hidden patterns in data, forecast results, and get better at what they do with practice.As an example, simple linear regression is used to predict issues like stock market forecasts, while the KNN algorithm is used to solve classification problems.Different algorithms can be employed in machine learning for different purposes.TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) analysis using Algorithm 1, Algorithm 2, Algorithm 3, Algorithm 4, Algorithm 5, Algorithm 6, Algorithm 7 Alternative value and Radiologists 1, Radiologists 2, Radiologists 3, Radiologists 4 Evaluation Parameters in value.Algorithm 1, Algorithm 2, Algorithm 3, Algorithm 4, Algorithm 5, Algorithm 6, Algorithm 7. Radiologists 1, Radiologists 2, Radiologists 3, Radiologists 4. Radiologist 4 got the first rank whereas Radiologist 3, has the lowest rank.
Pedagogical conditions for the effective organization of distance draw learning in the digital space of modern culture

The modern educational situation is characterized by the expansion of opportunities for distance learning in connection with the active development of information and communication technologies. The spread of a new coronavirus infection has also become an important factor in determining the need to turn to remote forms of pedagogy and, in particular, in draw teaching. For the embodiment of distance draw learning in a university, it is important to familiarize yourself with the experience of conducting a variety of online courses on the Internet. The analysis of this experience is carried out in this article. The specificity of distance learning in the preparation of students in the architectural and artistic profile is considered. A comparison of the teaching capabilities of distance and full-time drawing training is carried out. Particular attention is paid to the use of various forms of visualization using information and communication technologies, such as educational presentations, visual aids, video materials, a portfolio of educational and creative works. The pedagogical experiment carried out within the framework of distance draw learning confirmed the effectiveness of the proposed methods of using visual clarity to enhance the educational and creative activity of students.
Nimbo-stratus and Stratus Cloud Atmospheric Electricity Database and Analysis Methods for the Project “Research Studies on the Electricity of Low-Level Layer Clouds for the Pur-pose of Developments in Global Atmospheric Circuit Modelling (ELLEC)”

This paper provides details on meteorological and atmospheric electricity datasets and the methodology of analysis of the atmospheric electric data from the Polish Atmospheric Electricity Observation Network used for the purpose of research studies of the electricity of Nimbostratus and Stratus clouds and their role in the global atmospheric electric circuit.
STUDENTS ERROR IN USING CAPITAL LETTERS AND PUNCTUATION IN WRITING A DESCRIPTIVE TEXT

The paper entitled Students Error in Using Capital Letter and Punctuation in Writing a Descriptive Text was written to find out error in using capital letter and punctuation in writing a descriptive text and the cause of it. The method used in this research is descriptive method. The research was conducted to the third semester students of English Education Study Program, Faculty of Teachers Training and Educational Sciences, Pakuan University. The sample of this research is selected by using purposive sampling technique. The data were collected through students work, questionnaire, and interview. The result of the data shows that the most common error in using capital letter is in writing the names of places and persons. For comma, students make error before or after coordinating conjunction and comma at the end of the sentence. For apostrophe, most of students make errors by omitting a letter or letter in contractions. The writer also finds that carelessness is the cause of students error in using capital letter and punctuation in writing a descriptive text
The Advancement Of Audio Visual Technology Based Educational Materials for Social Studies at Madrasah Ibtidaiyah

&lt;p&gt;&lt;span&gt;The advancement of audio visual technology based educational materials &lt;/span&gt;&lt;span lang="EN-US"&gt;that &lt;/span&gt;&lt;span&gt;will be developed against the background of the minimal use of social studies learning media is limited to us&lt;/span&gt;&lt;span lang="EN-US"&gt;e&lt;/span&gt;&lt;span&gt; only textbooks and whiteboards. The goal of this study is to develop teaching materials for product oriented social science in the version of audio-visual-based educational media that is feasible and effective for use in learning. Research and Development (R&amp;amp;D) research methodologies are used in this study. This Research used ADDIE, which has five stages: 1) analyze, 2) design, 3) development, 4) implementation, and 5) evaluation. &lt;/span&gt;&lt;span lang="EN-US"&gt;The Islamic Elementary School &lt;/span&gt;&lt;span&gt;Amaliyah Tanjung Tiga fifth grade students are the subjects in this research. In this study, the data analysis method is qualitative descriptive statistics with questionnaires and tests. In this study, descriptive statistics are used to analyz&lt;/span&gt;&lt;span lang="EN-US"&gt;e&lt;/span&gt;&lt;span&gt;quantitative data. &lt;/span&gt;&lt;span lang="EN-US"&gt;Based on&lt;/span&gt;&lt;span&gt; the findings, the produced teaching media is claimed to be legitimate&lt;/span&gt;&lt;span lang="EN-US"&gt;d&lt;/span&gt;&lt;span&gt; and practicable for use in education, as well as very practica&lt;/span&gt;&lt;span lang="EN-US"&gt;l&lt;/span&gt;&lt;span&gt; for students to use in the learning process, based on validator and classroom teacher&lt;/span&gt;&lt;span lang="EN-US"&gt;s’&lt;/span&gt;&lt;span&gt; evaluation, while also ideas and feedback from materials experts, factorial design, media, and teachers include learning success or student&lt;/span&gt;&lt;span lang="EN-US"&gt;s’&lt;/span&gt;&lt;span&gt; learning completeness. Based on the above calculations, the observations carried out by experts at revision I 79.06 % and after revision II reached 81.52% then revision III 85.13% reached then this score is included in the very valid or very feasible criteria. The validity level is sufficiently valid that generated 81.9%. This development research resulted in a product tha&lt;/span&gt;&lt;span lang="EN-US"&gt;t&lt;/span&gt;&lt;span&gt;met the content, as well as being effectively used to improve student&lt;/span&gt;&lt;span lang="EN-US"&gt;s’&lt;/span&gt;&lt;span&gt; learning outcomes. Including individual mastery learning reached 83.42%, classical learning completeness reached 82.1% with the N-gain percentage reaching 0.75&lt;/span&gt;&lt;span lang="EN-US"&gt;, and&lt;/span&gt;&lt;span&gt; getting a positive response from students&lt;/span&gt;&lt;span&gt; &lt;span lang="EN-US"&gt;reached&lt;/span&gt;&lt;/span&gt;&lt;span&gt; 74.9% with good criteria.&lt;/span&gt;&lt;/p&gt;
Formation features associated with the professional discourse in the modern media environment

The results of the convergence of the information environment of modern society have formed its characteristic features: asynchrony, space-time compression, and anonymity, reversal of authorship, cross- and multimedia. As a result of the evolution of communication models, a new, “psychobiological” model is being formed, which is characterized by mediation of technical de-vices and the specific sociality of its participants. New communicative conditions make significant adjustments to the process of forming professional discourse. In the new digital information environment, professional discourse is becoming one of the most important tools, a technology for the formation of professional identity and the reputation of a specialist. In turn, the reputational digital trail of a specialist opens up limitless networking opportunities and increases the level of professional demand. As a result, successful professional identification, reflected in professional discourse, allows for an objective selection of content, improving the quality of the dialogue between scientific and applied knowledge, educational practices and becomes a marker of constructive references in the process of socialization for the users of network resources.
Analysis of The Effort of The Local Government in Improving Education in Hasang Village

Education is the foundation of hope for improving the quality of human resources. Children are the main priority in education, because they will be the successors of the nation and religion. Education is a human right as well as a means to realize other human rights. As an enabling right, education is the main target through which adults and especially children who are economically and socially marginalized can lift themselves out of poverty and find ways to be involved in their communities, because education plays an important role in empowering women, protecting children from hazardous work and sexual exploitation. The encouragement factor from family, environment, and teachers is very influential in the spirit of taking education in Hasang Village. In Hasang Village, there are some parents who still lack awareness of the importance of education, plus the damaged road access in this village reduces the enthusiasm of the residents in taking education to a higher level. The purpose of this study is to analyze the local government's efforts to improve education in Hasang Village. This research is descriptive using survey and observation methods. So it can be concluded that the government.&#x0D;
Semi-supervised Domain Generalization for Cardiac Magnetic Resonance Image Segmentation with High Quality Pseudo Labels

Developing a deep learning method for medical segmentation tasks heavily relies on a large amount of labeled data. However, the annotations require professional knowledge and are limited in number. Recently, semi-supervised learning has demonstrated great potential in medical segmentation tasks. Most existing methods related to cardiac magnetic resonance images only focus on regular images with similar domains and high image quality. A semi-supervised domain generalization method was developed in [2], which enhances the quality of pseudo labels on varied datasets. In this paper, we follow the strategy in [2] and present a domain generalization method for semi-supervised medical segmentation. Our main goal is to improve the quality of pseudo labels under extreme MRI Analysis with various domains. We perform Fourier transformation on input images to learn low-level statistics and cross-domain information. Then we feed the augmented images as input to the double cross pseudo supervision networks to calculate the variance among pseudo labels. We evaluate our method on the CMRxMotion dataset [1]. With only partially labeled data and without domain labels, our approach consistently generates accurate segmentation results of cardiac magnetic resonance images with different respiratory motions. Code will be available after the conference.
Computing Through Cloud Computing Technology using The PROMETHEE Method

cloud computing technology Users of Internet connected devices By storage, files, software and access to servers Offers: Computers, Smartphones, Tablets and wearables.Cloud computing providers, Separate from end users They store and process data locally.Cloud computing is computing is to provide resources as a service, That means the cloud rather than the end user Resources are owned by the provider and managed.In those sources Browser based software Apps like TikTok or Netflix Third party for photos Data storage and other digital media Like iCloud or Dropbox or computing infrastructure Third-party servers used to support are included.a business, research or personal project.Promethee is a priority for assessment enrichment Ranking system and its interactive help Descriptive complementary geometric analysis known as Promethee methods.In this The PROMETHEE method is the best solution from the analysis The shorter the distance and the longer the negative-ideal solution Determines the solution with the distance, but of these distances The comparison was not considered significant.Alternative: Amazon Cloud, Google