Reviewerly/exHarmony huggingface dataset:
ON THE QUESTION OF THE FORMATION OF ECONOMIC IDEAS AMONG YOUNGER SCHOOLCHILDREN THROUGH INFORMATION AND COMMUNICATION TECHNOLOGIES IN EXTRACURRICULAR ACTIVITIES

The article deals with the problem of forming economic ideas in younger schoolchildren based on the use of information and communication technologies. The Federal State Educational Standard of Higher Education orients teachers to create an information space for economic education of students not only in the process of regular and extracurricular activities.
An Interpretable Lane Change Detector Algorithm based on Deep Autoencoder Anomaly Detection.

In this paper, we address the challenge of employing Machine Learning (ML) algorithms in safety critical driving functions. Despite ML algorithms demonstrating good performance in various driving tasks, e.g., detecting when other vehicles are going to change lanes, the challenge of validating these methods has been neglected. To this end, we introduce an interpretable Lane Change Detector (LCD) algorithm which takes advantage of the performance of modern ML-based anomaly detection methods. We independently train three Deep Autoencoders (DAEs) on different driving maneuvers: lane keeping, right lane changes, and left lane changes. The lane changes are subsequently detected by observing the reconstruction errors at the output of each DAE. Since the detection is purely based on the reconstruction errors of independently trained DAEs, we show that the classification outputs are completely interpretable. We compare the introduced algorithm with black-box Recurrent Neural Network (RNN)-based classifiers, and train all methods on realistic highway driving data. We discuss both the costs and the benefits of an interpretable classification, and demonstrate the inherent interpretability of the algorithm.
Prediksi Pengguna Broadband di Indonesia sampai Tahun 2024 Menggunakan Pemodelan Crisp-DM dengan Metode Decision Tree dan Algoritma ID3 Studi Kasus di BPS dan APJII

Indonesia is a country with a population of 270.20 million people recorded at the Central Statistics Agency in September 2020. Based on the International Telecommunication Union (ITU) reported, the United Nations (UN) body, the number of world internet users in 2018 was 3.9 billion, exceeding half the world's population. Today the position of the internet continues to be significant in social, economic, and political life in a globalized world. Every year the internet continues to influence human life. Therefore we need research on forecasting the number of broadband users in the future to find out the number of users will increase or decrease as well as planning for Indonesian broadband. This forecasting research uses, using a comparison, namely the double exponential smoothing method with two different alphas and two betas, then the single exponential smoothing method with two different alphas. The double exponential smoothing method with alpha 0.2 betas 0.4 with the result that the MAD, MSE, MAPE values are smaller than single exponential smoothing with the first part alpha 0.8 and the second part alpha 0.5 and smaller than the double method exponential smoothing with alpha 0.6 betas 0.2. After getting the best value from the double exponential smoothing forecasting method, the prediction process is continued using the decision tree method, namely the ID3 algorithm for decision making every year from 2000 to 2024 to expand bandwidth or by not expanding bandwidth with the result that there are 19 years to expand bandwidth and there are 6 years for the decision not to expand the bandwidth.
Domain adaptation under structural causal models

Domain adaptation (DA) arises as an important problem in statistical machine learning when the source data used to train a model is different from the target data used to test the model. Recent advances in DA have mainly been application-driven and have largely relied on the idea of a common subspace for source and target data. To understand the empirical successes and failures of DA methods, we propose a theoretical framework via structural causal models that enables analysis and comparison of the prediction performance of DA methods. This framework also allows us to itemize the assumptions needed for the DA methods to have a low target error. Additionally, with insights from our theory, we propose a new DA method called CIRM that outperforms existing DA methods when both the covariates and label distributions are perturbed in the target data. We complement the theoretical analysis with extensive simulations to show the necessity of the devised assumptions. Reproducible synthetic and real data experiments are also provided to illustrate the strengths and weaknesses of DA methods when parts of the assumptions of our theory are violated.
Ecology and sustainable development issues in RF and the US libraries: On comparative analysis of subject digital resources

The UN Sustainable Development Goals (SDGs) are reviewed from the point of view of libraries. Both Russian and American professional publications cover the issues within their ecological education (EE) and sustainable development education activities which enables to compare them in many aspects. Key groups of relevant sources are determined: publications in professional periodicals, analytical materials on the web-sites of libraries and associations, resources on libraries’ websites, social media, and blogs. Each group of resources is analyzed. The conclusion is made that relevant information sources reflecting similar segments of library activities can be necessarily and possibly determined for further studies.
A Model for Estimating the Scope of the Project: A Pilot Study

In this paper, we have proposed a model for the implementation of SP 1.1, “Estimate the Scope of the Project” by utilizing the practitioners’ different experiences of and opinions on such implementation. The model has four elements—, which are plan, create, review meeting, and rework/update—that help practitioners implement SP 1.1 effectively by providing advice. We have identified specific activities within each of these elements that need to be performed when estimating the scope of the project. The model’s initial evaluation revealed its ease of learning and using. It also satisfies stakeholders and can efficiently manage the process of estimating the scope of the project.
Identifying Overly Restrictive Matching Patterns in SMT-based Program Verifiers

Universal quantifiers occur frequently in proof obligations produced by program verifiers, for instance, to axiomatize uninterpreted functions and to express properties of arrays. SMT-based verifiers typically reason about them via E-matching, an SMT algorithm that requires syntactic matching patterns to guide the quantifier instantiations. Devising good matching patterns is challenging. In particular, overly restrictive patterns may lead to spurious verification errors if the quantifiers needed for a proof are not instantiated; they may also conceal unsoundness caused by inconsistent axiomatizations. In this paper, we present the first technique that identifies and helps the users remedy the effects of overly restrictive matching patterns. We designed a novel algorithm to synthesize missing triggering terms required to complete a proof. Tool developers can use this information to refine their matching patterns and prevent similar verification errors, or to fix a detected unsoundness.
Priority-based trimmed median filter for removal of high density salt and pepper noise

This paper proposes an efficient and less complex priority-based trimmed median filter algorithm for restoring images corrupted by high density salt and pepper noise. Noisy pixel is replaced by trimmed median value of the horizontal and vertical adjacent four pixels, through this algorithm. If these four are 0's and 255's, then the next priority diagonal adjacent four pixels are used to calculate trimmed median for replacing noisy pixels. If these four are also found as 0's and 255's, then the noisy pixel is left unchanged until the next iteration. Experimental results on different greyscale and colour images show that the proposed algorithm outperforms the standard median filter, adaptive median filter, decision-based algorithm, modified progressive switching median filter and modified decision-based unsymmetric trimmed median filter.
보여주고 들려주는 붓다 고사 ― 돈황본 ＜八相變＞의 공연 방식과 필사본 제작

Baxiang bian 八相變is a Dunhuang bianwen 敦煌變文based on the Baxiang story of Buddha. A Baxiang story consists of eight stages, from the Buddha’s birth to his death. Since the ‘xiang’ 相of ‘Baxiang’ can be said to be a kind of scene, it is closely related to Buddhist paintings, similar to the ‘xiang’ in ‘bianxiang’ 變相. The relevance of this term to painting is one of the characteristics of the typical Dunhuang bianwen works, so this paper will analyze the characteristics of Baxiang bian from the perspective of pictorial storytelling.One of the important elements in the pictorial storytelling of bianwen is the use of a verse-introductory formula. This formula is a unique phrase used when showing a picture to the audience at the beginning of verses. There are two types of verse-introductory formulas in bianwen: ‘~處, 若爲陳說’ and ‘當爾之時, 道何言語?’, and Baxiang bian uses the latter. Keeping the assumption that the form of the performance of bianwen may vary depending on the verse-introductory formula, this paper suggests that the storytelling of Baxiang bian did not use a picture scroll but rather used a mural scene or a large bianxiang containing several scenesBianwen storytelling was a multimedia performance that included stories, songs, and pictures, and it was very popular at the time. People desire stable possession of popular stories, which leads to the production of works for reading. Since Baxiang bian was also a popular story performance, in this paper, the manuscript of Baxiang bian is considered to be an early form of written work, reflecting its popularity.
High resolution integrated reconstruction of holocene climatic and paleoenvironmental changes in the southern tyrrhenian sea: a coda approach

The field of this research is the reconstruction of paleoenvironmental changes used complex methods obtained by Compositional Data Analysis statistical methods (CoDA), so in the result to develop new transfer functions (mathematical methods to obtain data to reconstruct paleoenvironmental changes) due to which we can observe the paleoclimatic and paleoenvironmental changes and volcanic activities during The Late Glacial and Holocene in the Gulf of Naples and Gulf of Salerno in collaboration with IAMC (CNR) and University of Girona (statistical methods). One of the main objectives of the thesis is to elaborate statistical methods under the framework of CoDa (Compositional data analysis: CoDa; Aitchison, 1986) to obtain the SST (sea surface temperatures) from counting of fossil assemblages. Two approaches were considered:1) The modern analogue technique (CoDaMAT)– the revised method adopts the Aitchison distance, obtained from isometric log-ratio coordinates of relative abundances, as a natural measure of similarity among assemblages. The number of analogues from which obtain the estimates was determined through leave-one-out verification of modern assemblages. Mean distances and local outlier factor are considered to evaluate the quality of palaeoestimates. The method has been tested on Atlantic Ocean and Mediterranean planktonic foraminiferal assemblages to reconstruct past sea surface temperatures (SST). The MAT compares fossil assemblages with modern ones using a distance measure or a similarity coefficient. The palaeoenvironmental estimates are obtained from the environmental parameters measured at the location of the most similar modern assemblages. For each fossil samples the nearest modern ones are found by adopting an appropriate distance (d).2) Regression-based methods - standard and robust Partial Least Squares Regression (PLSR) and Principal Component Regression (PCR), applied to the log-ratio coordinates of percentage data of Atlantic Ocean and Mediterranean Sea planktonic foraminifera assemblages. Due to the presence of groups, it was preferred to model separately high latitude and mid to low latitude assemblages. The application of the obtained transfer function involves cluster, MANOVA and discriminant analysis applied to the log-ratio transformed fossil assemblage’s composition.
FEATURES OF EDUCATIONAL AND PROFESSIONAL ATTITUDES OF TECHNICAL TRAINING AREAS STUDENTS IN THE CONTEXT OF THE COVID-19 PANDEMIC

FEATURES OF EDUCATIONAL AND PROFESSIONAL ATTITUDES OF TECHNICAL TRAINING AREAS STUDENTS IN THE CONTEXT OF THE COVID-19 PANDEMIC
HASIL PENILAIAN SEJAWAT SEBIDANG Jurnal: Opinion Mining About Parfum On E-Commerce Bukalapak.Com Using The Naïve Bayes Algorithm

HASIL PENILAIAN SEJAWAT SEBIDANG Jurnal: Opinion Mining About Parfum On E-Commerce Bukalapak.Com Using The Naive Bayes Algorithm
APLIKASI PENCARIAN ORANG HILANG (PORTALANG) MENGGUNAKAN PEMINDAI WAJAH BERBASIS ANDROID

Artificial intelligence (AI) , is clear evidence that today's technology is very advanced, this technology can be used in any fields that require artificial intelligence. Such as medicine, tourism, industry, even government and tools that help us in our daily work. One example of Artificial Intelligence is Face Recognition which will recognize recognized faces (added). This technology will be used to help find missing people, who need facial data, which requires an Android smartphone to capture facial images through the camera, which will then be processed by TensorFlow Machine Learning which will immediately store the data. received (input). The light intensity factor, image clarity, will play an important role in the results of the Tensor Flow process, the better the light intensity, the clarity of the image, the more accurate facial recognition will be.
Lightning Prediction Model Based on Humidity, Pressure, Temperature and Wind Speed Dataset Using Machine Learning: Tan Kok Bin, Khairul Hamimah Abas*, Ruzairi Abdul Rahim

Malaysia resulted in high number of lightning occurrence throughout the year due to its tropical climate and location. This paper presents the application of machine learning in predicting the occurrence of lightning events in KLIA region based on historical sensed lightning and meteorological data. Logistic regression and artificial neural network (ANN) are two prediction models utilized in this study to make a comparison in terms of accuracy of prediction. A three-layer neural network has been developed and the most suitable network with highest accuracy had been obtained after several testing of different structures. Meteorological data used in this paper are acquired from humidity sensor, pressure sensor, temperature sensor and wind speed sensor. These four variables are inputs to the prediction model. The output of the prediction model is a binary classification which indicates lightning occurrence or no lightning occurrence. The performance of the prediction model is evaluated using k-fold cross validation.
The Application of Educational Management Psychology in the Management of College Students in the New Era

Among the disciplines of psychology in China, educational management psychology occupies an important position. With the progress of the times and social development, China’s educational management psychology has achieved a good integration between organizational management, psychology and other disciplines, and has made great achievements. Therefore, in the process of student management in colleges and universities, teachers should use scientific and reasonable methods to realize the extensive application of the theoretical content of educational psychology in the process of student management, fully understand and master the psychological changes of college students, and clarify their code of conduct, in order to ensure the quality and practical effect of college student management. In such an environment, colleges and universities should make full use of educational management psychology to ensure the actual effect of student management. Based on this, this paper summarizes educational management psychology and analyzes the application measures of educational management psychology in college student management in the new period, so as to provide theoretical reference for the development of relevant research in the future, ensure the quality and effect of college student management, and promote the healthy growth and all-round development of college students.
The Coronavirus Conversation on Reddit: A Mixed Methods Approach

This article engages in a methodological discussion on how to consider affordances in the context of digital environments, focusing on the r/coronavirus community on Reddit. To underline how affordances might affect social interaction, Reddit and its voting system offer a privileged ground to observe how social dynamics intersect with technical features to guide expression. I will consider a vast dataset of comments, including those deleted by their own authors, through non-participant ethnographic observation and automated text analysis. It is shown how the r/coronavirus community fluidly negotiates social norms by enforcing them through affordances, that are employed to sanction social behaviour that does not conform to broader situated cultural norms. This intertwines with moderation practices, as they concur to define what is considered socially proper within an environment, as well as functioning as discursive tools to legitimise a specific view of the world. Based on this experience, the implications of a mixed methods approach for the study of online communities are briefly presented, underlining how it might aid reflexivity for researchers embedded in their research environment.
Impact of Knowledge Capacity on the Employees Performance and Competitive Advantage

The aim of this particular study is to examine the direct influences of knowledge capacity factors (training & development, knowledge sharing, quality of academic qualification, and quality of professional qualification) on the organizational competitive advantage and indirectly through the employees’ performance among the Syrian ICT private sector. The proposed model have four independent variables from the knowledge capacity and organizational competitive advantage as the dependent variable. The study is deductive approach by using quantitative methods to perform PLS-SEM statistical analysis of the original data that collected from 335 participants. The sampling selection technique is quota sampling to choose the suitable samples from 2615 senior executives from the Syrian ICT sector. Results of the main dependent variable, competitive advantage (CA), illustrate a moderate predictive power; the prediction constructs can explain 68.7% of the competitive advantage (CA) variance. Knowledge capacity have the highest impact (beta = 0.257), followed by quality of professional qualification (beta = 0.155), then quality of academic qualification (beta = 0.105). However, training and development have no direct significant impact but it has and indirect impact through the employee performance. The four antecedents have significant relationships to the employees’ performance and can indirectly impact the competitive advantages. Future, studies can replicate the study in different domains.
Balancing the Interest of Copyright Holder – A Case Analysis of Delhi University’s Photocopy Case

Indian copyright law is at parity with the international standards as contained in TRIPS. The (Indian) Copyright Act, 1957, pursuant to the amendments in 1999, 2002 and 2012, fully reflects the Berne Convention for Protection of Literary and Artistic Works, 1886 and the Universal Copyrights Convention, to which India is a party. India is also a party to the Geneva Convention for the Protection of Rights of Producers of Phonograms and is an active member of the World Intellectual Property Organization (WIPO) and United Nations Educational, Scientific and Cultural Organization (UNESCO).Work protected in India,Under the Copyright Act, 1957 the term includes an artistic work comprising of a painting, a sculpture, a drawing (including a diagram, a map, a chart or plan), an engraving, a photograph, a work of architecture or artistic craftsmanship, dramatic work, literary work (including computer programmes, tables, compilations and computer databases), musical work (including music as well as graphical notations), sound recording and cinematographic film.
Analisa Kepuasan Konsumen Menggunakan Algoritma C4.5

Consumer satisfaction is a very important measure for the sustainability of a business. One example is the business in the food sector. This business requires active consumers because it is related to consumer taste and satisfaction. Bakso Akbar as a business in the food sector certainly has many competitors. For the sustainability of this business, it is necessary to review what things make consumers satisfied and dissatisfied. One way is to analyze customer satisfaction with Service variables with Good or Not Good, Speed, Location Access with Easy or Difficult options, Cleanliness with Clean or Not options, Taste with Good, Not bad or Not good choices and the last one is Price with Expensive or Cheap stuffing. These variables will be filled in by consumers from the distributed questionnaires, which will then be recorded and processed using Data Mining. The C4.5 algorithm is considered to be one of the Data Mining algorithms that is able to give good results because it produces decision tree rules. The results showed that the Rasa variable got the first highest gain with a value of 0.3659. Subsequent calculations obtained the Cleanliness variable with a value of Gain 1. The resulting rule is 4, 2 rules resulting in a decision of Satisfaction with the condition if the taste is good, the consumer is satisfied and if the taste is good and the cleanliness is clean then the consumer is satisfied. The purpose of this analysis is so that the Bakso Akbar business can retain its customers and fix any shortcomings based on consumer assessments.
Identifying Gaps in Cybersecurity Teaching and Learning

This paper explores perceptions and expectations of privacy when using computer-mediated communication and social media. In this paper we present the results of an empirical survey into this topic and explore the pedagogic implications for the teaching of cybersecurity. The study asked undergraduate students about their habits, expectations, and beliefs about the media they use and interact with. The aim was to capture and to inform the state of the art in cybersecurity teaching through identifying students' perceptions and views on privacy, security and whose responsibility these are. The academic provision for the teaching of cyber-security is a critical contemporary requirement. To improve this teaching, it is necessary to get some idea of the necessary requirements for such a course. Based upon the results of our survey, we go on to identify some of the key issues for such courses to address.