Reviewerly/exHarmony huggingface dataset:
Composition and Analysis as Communication. Outline for a Compositional Theory based on “Musical Information”

The concept of “information” in association with music recently re-emerged in music psychology and cognition in the form of statistical learning and as the basis for models of music perception. The first time music and information were associated in a systematic manner was in the 1950s and 60s when, particularly in North American music theory, researchers applied concepts from information theory to analysis and composition. Among the work of the 1950s was Edgar Coons’ and David Kraehenbuehl’s Information as a Measure of Structure in Music (1958). The authors suggested that information could be developed into a useful compositional tool that would aid decisionmaking in terms of form, but would not hamper the composer’s personal style or freedom of choice with regards to musical materials. In this article, the fundamental concepts behind the development of a musical information theory are outlined, giving some simple examples of its possibilities and proposing directions for future development. The outline embraces the necessity for a contemporary musical theory to combine formal, scientific methods and an awareness of contexts and relationships inspired by the New Musicology and the study of music as a cultural activity. As a theory of communication, information theory is presented as a far more subjective and pliable concept than is implied in Claude E. Shannon’s Mathematical Theory of Communication (1948), the work upon which many of the musical information theories in the 1950s were based. A flexible view of information theory and the concept of information must be maintained to enable them to take part in contemporary musicological discourse.
Development of Using Blended Learning Education-Based Game Learning Media Android for Students Basic Electronics

The objectives of this study were to: (1) develop a blended learning model using Android-based learning media for basic electrical electronics subjects; and (2) determine the effectiveness and level of student satisfaction with the developed model. This study used the Research and Development method with the ADDIE development model which consisted of defining, designing, developing, implementing and evaluating stages. The research subjects consisted of 2 media expert validators, 2 material expert validators, and 31 product trial students. The research instrument used a questionnaire for media experts and material experts, as well as tests and questionnaires for students. The level of student satisfaction with the developed model was determined by the percentage technique, while the product testing was carried out with an experimental design (before-after) and a one group pretest-posttest pattern. This study produces a blended learning model using educational game media based on android for basic electrical electronics subjects. The results showed that the product developed obtained a validity score of 82.5% from media experts who were on valid criteria and a score of 93.7% from material experts was in very valid criteria. The model developed can be used effectively for basic learning of electronic electricity in vocational schools, which is shown by the post-test average score of 80.97, which is higher than the pre-test average score of 64.09. The level of student satisfaction with the product developed was very good with an average score of 85.8 on a scale of 100.
Changes in the modern university: challenges and development trends

Relevance. The global coronavirus pandemic has made significant adjustments to the higher education system, inducing the search for optimal teaching methods that will optimize the educational process for all its applicants, and will enable to perform an adequate assessment of the level of knowledge of students.Purpose of work. Determine the best methods of online teaching material for students, depending on their characteristics of perception of information, as well as provide an effective way to control knowledge.Material and methods. During the quarantine period and online training, the Google Meet platform was used to conduct online workshops and seminars. Depending on whether the information channel of information perception prevailed among the majority of students in the group, an individual approach to presenting information with different types of clarity was used. Evaluation of the effectiveness of various methods of presenting the material was carried out through intermediate and current control of knowledge, as well as oral questioning of students at the end of the semester.Results. The highest productivity of information perception was found when combining different teaching methods during one lesson, when students take turns using a sound, visual analyzer, and also holding pre-printed materials in their hands. The use of short scenarios of simulation medicine, when there is an opportunity to improve communicative competence, significantly increases the activity of students during the lesson, manifests itself in the number of "raised hands" and comments in the chat. The ingenuity and perseverance of the teacher makes it possible to objectively assess the knowledge of students, despite the obvious difficulties, online learning brings. Conclusion. During quarantine and distance learning, the most effective are the methods of combined presentation of the material, when students have the opportunity to use all channels of information perception.
Analysis of Indonesian Public Opinion Sentiment on Policy on Twitter Social Media “PPKM” Using K-Nearest Neighbor

COVID-19 or Coronavirus disease 2019 is currently a pandemic that is spreading very quickly throughout the world, including Indonesia. Various handling and policies have been carried out, one of which is called “PPKM” policy or what can also be called the Enforcement of Restrictions on Community Activities issued by the Indonesian government. “PPKM” is currently one of the topics that is often discussed by the public, one of which is on the Twitter social media platform. The existence of opinions given by the community, it is necessary to have a sentiment analysis. Sentiment analysis is an analytical process obtained from various social media platforms and the internet. The aim is to find out how the public's sentiment towards the implementation of “PPKM” policies in Indonesia is through tweets and comments on the Twitter social media platform. In this study, the process of analyzing public opinion regarding the “PPKM” policy will be carried out by classifying opinions into 3 sentiments, namely positive, negative or neutral. Classification is done using the K-Nearest Neighbor algorithm. The K-Nearest Neighbor (K-NN) algorithm is a classification method for a set of data based on previously classified data learning. Included in supervised learning, where the results of the new query instance are classified based on the majority of the distance proximity of the categories in K-NN. The results of data preprocessing and sentiment classification, in the first test positive sentiment 37.6% of 261 data, negative sentiment 65.9% of 636 data and neutral sentiment 9.
The Screen Space in the Composite Multi-Angle Television Frame

The relevance of this research is connected with the technical revolution that is unfolding in the field of electronic mass media, in particular, television. There appear new forms of presenting visual information, as well as many opportunities and tasks for those creating the television image. The principles of modeling the visual reality of the television frame are becoming increasingly complex, as compared to several decades ago. How to find an effective compositional, coloristic and expository balance between several images simultaneously presented on the screen and correctly weave the visual fabric of a television frame? What is a multi-angle shot and non-spatiality? Why do we have to deal with multi-scale and time-diversity in a frame? In this article, the importance of studying multi-angle visualization of reality in the discourse of screen space is highlighted. The author aims at analyzing a viewer’s position in front of the screen and their priority order of image viewing, like a straight splice of television shots, but within a multi-screen. Additionally, he describes the functionality of a simultaneous display of an action shot from different angles and provides examples of multi-vector screen time within a single frame when modeling an image by different technical means. The article discusses the principles of image projection and acquisition of properties of an object of augmented screen reality by an element of additional visualized information. The analysis of the visual multilayer structure of screen space has both theoretical and practical significance. In theoretical terms, it provides definitions of a multi-angle shot, non-spatiality, multi-scale, and time-diversity and specifies the properties of these concepts. Its practical value lies in studying the feasibility of creating screen space in a modern media environment. The author brings intermediate results of research the main focus of which is the study of the visual structure of screen space in television news material.
INVESTIGATING FACTORS AFFECTING READING COMPREHENSION, PERCEPTIONS OF READING TASK-TYPES AND STRATEGIES

Reading can be a crucial skill in studying a language as it helps record a plethora of knowledge in the world. Reading can be an entertaining activity or it can be a task. This study aims at investigating the task as this is commonly seen in studying a language. More specifically, the study targets three different objectives and 30 first-year English majors were recruited to answer the survey questions. They were asked about the factors that they thought to have the greatest effects on reading comprehension. The second section asked them about their opinion about difficult reading comprehension task-types. The third section elicited their opinion about reading comprehension strategies which they thought to be difficult to apply in doing comprehension tasks. The results revealed that most of the participants posited that they had obstacles in vocabulary, grammatical structures and unfamiliarity of the topic and vocabulary was seen as the most problematic. Then, grammatical structures were seen as the second most difficult. Furthermore, they thought that true/false questions, sentence completion questions; tasks like summary/table completion; and multiple-choice questions hindered them from understanding the reading comprehension tasks. Next, guessing the meaning from the context was found to be the most difficult strategy while spotting the specific information to answer the questions was seen as the second difficulty. Some limitations of the study were also concluded.&lt;p&gt; &lt;/p&gt;&lt;p&gt;&lt;strong&gt; Article visualizations:&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;img src="/-counters-/edu_01/0926/a.php" alt="Hit counter" /&gt;&lt;/p&gt;
SRFS-NET: Few Shot Learning Combined with the Salient Region

Few shot learning aims to recognize novel categories with only few labeled data in each class. We can utilize it to solve the problem of insufficient samples during training. Recently, many methods based on meta-learning have been proposed in few shot learning and have achieved excellent results. However, unlike the human visual attention mechanism, these methods are weak in filtering critical regions automatically. The main reason is meta-learning usually treats images as black boxes. Therefore, inspired by the human visual attention mechanism, we introduce the salient region into the few shot learning and propose the SRFS-Net. In addition, considering the introduction of the salient region, we also modify the embedding function to improve the feature extraction capabilities of the network. Finally, the experimental results in miniImagenet dataset show that our model performs better in 5-way 1-shot than few shot learning models in recent years.
Musical Improvisational Interactions in the Digital Era

&#x0D; This paper considers the issue of musical improvisational interactions in the digital era by pursuing the following three steps. 1) I will raise the question of the meaning and value of liveness, and in particular of live musical improvisation, in the age of the internet and discuss some effects of the so-called digital revolution on improvisation practices. 2) Then I will suggest that the interactions made possible by the web can be understood as kinds of live improvisational practices and I will briefly outline how such practices also involve musical improvisation. 3) Finally, I will focus on some aesthetic and philosophical aspects of new kinds of live improvisation made possible by recent progress in artificial intelligence research. &#x0D;
ANALYSIS OF STUDENT RESPONSES IN LEARNING WITH ANDROID-BASED MEDIA

The author will try to do research by developing android-based interactive learning media on BTA learning materials, the author wants to try to find out the response of UIN SAIZU students to the learning media. This study aims to determine student responses to android-based interactive learning media at UIN SAIZU by using the observation method and learning test results. Data collection teaching. The results of the study were obtained based on the results of students’ responses to learning media based on Android on BTA material getting an average percentage of 78.21% in the first observation test with good categories and observation test. The research will try to prove that Android-based BTA learning is very effective because it can be used for all circles, both students and people who are very busy because learning can be done anywhere besides being practical, Android can be used for all positive things. conclusions can be drawn from this discussion as follows:&#x0D; &#x0D; Applications for learning tajwid based on android can be used by Muslims as an alternative to learning tajwid independently.&#x0D; With the application of learning tajwid which is equipped with examples of images and sounds, as well as quizzes to test abilities, users are expected to be able to maximize this mobile application as a medium for learning tajwid that is easy to use and easy to reach.&#x0D; Tajweed science applications can be run via smartphones with the Android operating system.&#x0D; The application of tajwid is made using the Java programming language and designed with an easy display.&#x0D;
Comparative Analysis on Chinese and Canadian Primary School Mathematics Estimation Education Differences

Mathematics is one of the most important topics in school and in the community in twenty-first century, a pupil who is good at mathematical seems to have the capacity to alter the progress of their very own state's financial, governmental, and social issues [1].Estimation is regarded as among the top 3 objectives of teaching maths since it is "an action that pervades both kid's and grownups' lifestyles" [2], [3].In concerns of shaping a student's ' attitudes regarding mathematics, caregivers play an essential part in the primary level [2].The aim of this study is to look at mathematics estimation education differences in Canada and China in general to find out the differences between the two systems.This article analyses the national mathematics curriculum of obligatory schools for Canada and China for estimating opportunities for students, recognizing that the capacity to evaluate has significant implications both for subsequent mathematics learning and for real world functions.Framed by four modes of evaluation (number line, quantity, computation and, measurement) that are theoretically and technically distinct, each using mathematics differently [2].Findings are that both countries' curriculum, especially those in Canada, provide students with ample and clear chances to acquire whatever kind of estimating abilities they may need.A comparison of the two educational methods also indicates that a hybrid of the two approaches should be explored in order to optimize students' results.
Comparing Machine Learning and Human Judge in SATU Indonesia Awarding Processes

For more than ten years, SATU Indonesia Awards, with PT. Astra International Tbk's support is given to inspiring young Indonesians. Every year, more than 10,000 nominations must be short-listed to 90 nominations within one week with five (5) assessment parameters. The research contributions are (1) creating a machine learning mechanism for the awarding process from ten years of the SATU Indonesia Awards nomination archive, (2) creating two (2) models of training data for the five (5) assessed parameters, namely motivation, obstacle, outcome, outreach, and sustainability, and (3) compare machine learning prediction with 2021 judge's assessment. TEMPO Data and Analysis Center (PDAT) extracts the corpus training data from ten years' SATU Indonesia Awards data in six months. The corpus training data contains nomination texts with Judges' scores on motivation, obstacle, outcome, outreach, and sustainability. Two (2) corpus training data and two models were generated with, namely, (1) the average Judges' parameter value per instance and (2) the Judges' smallest value and stored in two (2) corpus of 1220 instances each. The classification model was generated by Random Forest, which has the slightest error among the classification algorithms tested. The first model aims to predict the nomination assessment parameters. The second model is to detect the outlier in the incoming nominees for extraordinary nominees. The machine learning predictions were compared and found to be similar to the 2021 judge's assessment in the awarding processes at SATU Indonesia Awards. The average Judges' pre-final 2021 nominees' scores are compared to the Random Forest's predictions and found to be reasonably similar, with a small RMSE error around 1.1 to 1.6 for all assessment parameters. The smallest RMSE was obtained in the Sustainability parameter. The Obstacle parameter was found to have the largest RMSE.
RANCANGAN MARKETPLACE HEWAN TERNAK APPLICATION

The marketplace of livestock is engaged in the business of selling and purchasing which broadly has the activities of selling and purchasing animals. Usually have several system admins who work and control an application system by handling also the development of businessmen in the application, including making reports and managing master data. In this study business process observations were made from observations of free-range applications which have become a unique marketplace specifically for livestock. The business process that is happening right now, that an application provides a place for various pet shops to pour their sales business activities in accordance with the dimensions of the animals they sell, on the other hand also receives intensive care services for animal development for farmers. It takes a long time for a common marketplace application to get a service maintenance partner, and time brackets along with maintenance service wages that are proportional to the value of feed prices, an increase in the amount of food, and season conditions for a sales activity there is no precise analysis. Based on the needs of this matter, a design of new marketplace application design is needed which is equivalent to a marketplace in general, which only has the ability to sell and purchase. In the analysis phase of modeling using Business Process Modeling Notation (BPMN), while the design stage uses Unified Modeling Language (UML). The design of this application will be a guideline in implementing software in future research.
Seismic risk assessment for the Historical center of Quito and Validation

Quito is the capital of Ecuador and due to its importance for the country, it requires an updated seismic risk assessment study that addresses models of exposure, seismic hazard, and structure vulnerability.The purpose of this paper is to evaluate the seismic risk assessment model of the Historical Center of Quito (from now HCQ) by comparing it with collected information from previous punctual seismic events.To establish the seismic hazard model, we based on probabilistic studies of two punctual past seismic events.The first one was on March 5, 1987, and the second on August 11, 1990.In addition, the Ground Motion Prediction Equations (GMPE) used in this study are: AkkarBommer2010 (Akkar & Bommer, 2010), BooreAtkinson2008 (Boore & Atkinson, 2008), and ZhaoEtAl2006 (Zhao et al, 2006).The exposure model was generated from the Quito Geoportal and the Metropolitan Cadastre Data Base, compiling information such as the construction material, the lateral load resistance system, among others for 1183 residential and commercial structures.On the other hand, the vulnerability parameter was analyzed through fragility curves that determine the economic losses of 12 types of structures defined and developed by Martins and Silva (2020).The seismic risk assessment model was built by using OpenQuake software developed by the Global Earthquake Model association (GEM).The model was validated by comparing it with the PGA obtained from the seismic catalogs.Both the model and reality show a PGA of 0.06g for the 1987 event and 0.18g for the 1990 event.The results of the analysis showed structural losses of 2'272,082.5USD for the 1987 event and 288,283 USD for the 1990 event, where 61.5% (1987) and 57.12% (1990) of the losses were to structures whose lateral load resistant system is not ductile and are from 1 to 4 stories, mainly built with Adobe walls.
A Channeled Multilayer Perceptron as Multi-Modal Approach for Two Time-Frames Algo-Trading Strategy

FOREX (Foreign Exchanges) is a 24H open market with an enormous daily volume.Most of the used Trading strategies, used individually, are not providing accurate signals.In this paper, we are proposing an automated trading strategy that fits random market behaviors.It is based on neural networks applying triple exponential weighted moving average (EMA) as a trend indicator, Bollinger bands as a volatility indicator, and stochastic RSI as a momentum reversal indicator to prevent false indications in a short time frame.This approach is based on trend, volatility, and momentum reversal patterns combined with a market adaptive and a distributed multi-layer perceptron (MLP).It is called channeled multi-layer perceptron (CMLP) that is a neural network using channels and routines trained by previous profit/loss earned by triple EMA crossover, Bollinger Bands, and Stochastic RSI signals.Instead of using classic computations and Back-propagation for adjusting MLP parameters, we established a channeled multi-layer perceptron inspired by a multi-modal learning approach where each group of modalities (Channel) has its That stands for a dynamic channel coefficient to produce a multi-processed feed-forward neural network that prevents uncertain trading signals depending on trend-volatility-momentum random patterns.CMLP has been compared to Multi-Modal GARCH-ARIMA and has proven its efficiency in unstable markets.
Website-Based Application for Flood Event Prediction Using Machine Learning Method In Cilacap District

Floods are the most common natural disasters, both in terms of their intensity at a place and the num- ber of locations of events in the amount of 40% among other natural disasters. The impact of flooding on the area in general is temporary housing in rural areas caused by flooding in addition to settlement as well as agriculture which can have an impact on the food security of the area and also a national level that is higher than the magnitude of the country. Based on data from the Central Statistics Agency of Cilacap Regency, the number of flood victims in Cilacap Regency in 2018 reached 771 people and arranged for them to flee from the flood. To solve this problem, do research to create a web-based application using the classification of the Support vector machine or Random Forest to predict flood events and compare the accuracy values of the two algorithms to get better prediction results.