Reviewerly/exHarmony huggingface dataset:
Fine-Grained Action Recognition Based on Temporal Pyramid Excitation Network

Mining more discriminative temporal features to enrich temporal context representation is considered the key to fine-grained action recognition. Previous action recognition methods utilize a fixed spatiotemporal window to learn local video representation. However, these methods failed to capture complex motion patterns due to their limited receptive field. To solve the above problems, this paper proposes a lightweight Temporal Pyramid Excitation (TPE) module to capture the short, medium, and long-term temporal context. In this method, Temporal Pyramid (TP) module can effectively expand the temporal receptive field of the network by using the multi-temporal kernel decomposition without significantly increasing the computational cost. In addition, the Multi Excitation module can emphasize temporal importance to enhance the temporal feature representation learning. TPE can be integrated into ResNet50, and building a compact video learning framework-TPENet. Extensive validation experiments on several challenging benchmark (Something-Something V1, Something-Something V2, UCF-101, and HMDB51) datasets demonstrate that our method achieves a preferable balance between computation and accuracy.
CO-CREATURE IN THE PROCESS OF MUSICAL AND PERFORMING INTERPRETATION OF AN ARTISTIC IMAGE

The article analyzes the scientific works of famous music educators, in which artistic and performing interpretation is defined as an active creative process, an individual, unique artistic and figurative understanding of the content of a musical work. It has been established that performing interpretation involves a creative search, valuable understanding and evaluation of a musical work, thanks to which an artistic image is created that is adequate, but not identical to the author's vision, containing the full potential of the «I» of the performer's personality in the process of artistic cognition. Therefore, the presence of a high degree of creative independence, the development of a unique associative complex, fantasy, imagination, the art of reincarnation, empathy and co-creation in the artistic- interpretive process contributes to the non-stereotypical solution of creative tasks, "entering" the deep layers of a musical work, dialogicity of artistic communication, artistic dialogue and co-creation with the author of the musical work. Subjectivization of the reproduction of a musical image is a natural phenomenon, since each performer differs in the level of knowledge, skills, development of emotional and empathic culture, performance technique, experience of artistic perception, development of musical abilities and other performance qualities that characterize him as a unique personality and determine individual artistic and interpretive process. It has been proven that precisely thanks to the elements of co-creation, the enrichment of the artistic interpretation process with the extraordinary thinking of the performer, his personal and individual attitude to the work, the artistic interpretation becomes not only adequate and convincing, and personally-convincing, personally-adequate, harmoniously combining the classical interpretation of the work with an individual vision and feeling of its essence, the spiritual-personal potential of the work is realized, a state that contributes to the solution of the personal task is reached. Through co-creation, the dialogue of consciousness, the understanding of the other as oneself, and the experience of the "spirit" of the musical work are carried out. The ability to co-create as a certain way of dialogic communication between the composer and the one who understands the artistic image determines the level of musical performance competence of the future teacher of musical art.
The Relationship Between Bitcoin Returns, Volatility, And Volume Using Asymmetric Garch Modelling

In 2020-2021 where the world experienced a Covid-19 pandemic, the price of Bitcoin increased and there was a fairly high price spike at the turn of the year 2020-2021 and had touched an all-time high (ATH) at the end of 2021. Bitcoin is one of the currencies crypto that is volatile when compared to the exchange rates of widely used currencies. In addition, Bitcoin price movements are difficult to predict. The samples used are Euro, Pound Sterling, Yuan, Yen, Ruble, Franc, and Bitcoin. The data used is in the form of Bitcoin price data and some of these currencies in 2020-2021. This study aims to find the relationship between volatility with Bitcoin trading volume, return with Bitcoin trading volume, and return with Bitcoin volatility for forecasting purposes. The research method used is the Augmented Dickey-Fuller (ADF) stationarity test, then using the ARMA model after that using the EGARCH model to find the relationship. The results of this study indicate that there is a positive relationship between volatility and Bitcoin trading volume. Just like the return and trading volume of Bitcoin there is a positive relationship. However, Bitcoin returns, and volatility have a negative relationship. For further research can use different crypto currency assets with different time periods.&#x0D; Keywords: Volatility, Volume, Returns, Bitcoin, GARCH
Development Of Android-Based PLS.Edu Application Content On Community Education Innovation Materials

The purpose of this research is to develop and determine the validity and practicality of the content of public education innovation materials on the Android-based PLS.edu application in the Public Education Study Program, FKIP Sriwijaya University. The research method used is research and development using the ADDIE development model with the research subject being 5th semester students who take the Diffusion of Educational Innovation course. The results showed that the validation results obtained a feasibility value by material experts by 78%, linguists by 52% and media experts by 84%. Furthermore, based on the results of product practicality trials, namely individual trials, the feasibility score was 82.67 % and small group trials were 86.40 %. So that the overall average percentage of eligibility is 76.61 with "Good" criteria. These results indicate that the content of public education innovation material on the Android-based PLS.edu application developed in this study is valid and practical so that it is declared feasible to be used in learning.Keywords: Content development, Community education innovation, Android
Study of A. Tchaikovsky in 7 th grade: methodological aspect

The article deals with the problem of introducing critical thinking technology into the education process. In this regard, the essence of technology, as well as methods of developing critical thinking of students of general secondary education institutions, are revealed. The author proposed examples of the use of these methods in the lesson of Ukrainian literature in the 7th grade when studying the work of A. Tchaikovsky.
Data Visualization Of House Of Worship Distribution In The IKN Nusantara Region Using Python

Nusantara, Indonesia's new capital, has a land area 256,142 ha and a marine area 68,189 ha. Transmigrant residents in the North Penajam Paser Regency region has increased as a result. The difficulty of finding a place of worship in the closest location because they are unfamiliar with their location or the nearby roadways. We can utilize data visualization to show the distribution of places of worship in order to solve this issue. Analysis was done on several types of houses of worship, including mosques, churches, and musholla. Python is the programming language, and the libraries used are NumPy, Pandas, Matplotlib, Seaborn, RegEx, and Folium. Muslims for the majority of places of worship in IKN Nusantara (91.26%), musholla making up 57.92% of the total and mosques making up 33.33% and 8.74% are owned by Christians. Sukaraja Village, Semoi Dua Village, Argo Mulyo Village, and Tengin Baru Village have the highest concentration. Keywords: Data Visualization, House of Worship, IKN Nusantara, Python
Research on multi-source data fusion for aviation support system

Aviation Support System (ASS) is a typical kind of complex system for supporting aircraft take-off and landing. The operation of ASS involves with man-machine-resource-environment system. The sensing data from ASS shows the multi-source characteristics. It is difficult to characterize the ASS status accurately and efficiently using such data source. Aiming at building intelligent ASS to improve efficiency and safety in complex environment, a multi-source data fusion method for ASS is proposed. According to the functional requirements in real-time perception, a unified architecture of multi-source data fusion for ASS is designed. The data fusion architecture is integrated with data preprocessing, association and aggregation. Finally a case study is proposed to verify the data fusion method for ASS.
Bug localization with semantic guidance using pseudo-Siamese network

Information retrieval (IR) based bug location technology is a relatively recognized lightweight bug location method at present. Most IR bug location methods solve the problem of semantic difference between natural language and code language in the bug report based on code semantic intelligibility, and use semantic similarity to construct IR model to locate source code errors through bug report. However, most IR localization studies take error report description as the guidance for code semantic generation, ignoring the difference between error report and error semantics. Due to the irregular submission of error reports and the ambiguity of error descriptions, this kind of research faces the problem of low location accuracy. We found that the code data is the data written in the specification and verified by the program compilation. Compared with the bug data submitted by the tester, the semantic ambiguity is relatively weaker. Therefore, we use code data as the semantic generation of teacher network training bug data to form SGBL method. In addition, based on the bug data set composed by Jena and other projects, we evaluated the effectiveness of our method and explained the relationship between the semantic extraction method and the bug location accuracy. The experimental results show the effectiveness of the proposed method.
Detection of Clips Failures in Manufacturing using Audio Signals

In industrial manufacturing processes, such as plugging small connectors in, where visual verification is difficult, workers may experience difficulties in detecting failures. Artificial intelligence algorithms can be used to detect and identify the sound of these connectors and mitigate human error. In this work, sound samples of correctly plugged-in connectors and ordinary background noise of the workplace were collected using a recording setup fastened to workers' hand. In order to discriminate anomalies that represent failures, autoencoder models were trained and tested in an unsupervised manner. Experiments with different deep learning architectures for anomaly detection are conducted. Our CNNAE-FT model achieved best results and yielded a ROC-AUC score of 0.85.
Preliminary Design and Prototype Development of an Air-ground Carrier Platform

In recent years, amphibious or tri-amphibious UAVs have gradually received more attention. They have two or three loading methods, which can overcome the limitations of a single carrier method. Compared to existing amphibious or triphibious drones, this study presents a design for an air-ground carrier platform and has made a physical model. This study innovatively proposes a mechanical structure that uses a single lead screw and connecting rod mechanism to simultaneously drive four arms. Additionally, this study also proposes an integrated solution for the drone landing gear and vehicle chassis. This paper discusses the composition, working principle, sub-system structure, key functional design calculations, and field flight tests of the air-ground carrier platform. The results show that the air-ground carrier platform proposed in this study has a simple and reliable deformation structure. The modular drone and vehicle chassis reduces the later maintenance costs. This paper has important practical significance for the research and development of multi-mode drones.
Online Trajectory Generation for Aerial Manipulator Subject to Multi-tasks and Inequality Constraints

This article tackles the problem of generating coordinated trajectory for unmanned aerial manipulator (UAM) system. The kinematic redundancy nature of this class of system makes it challenging to design constraints-satisfied trajectories of both the aerial vehicle and the robotic arm simultaneously that can accomplish a series of tasks with varying levels of priority. This paper presents a redundancy utilized trajectory generation method based on hierarchical quadratic programming (HQP). The method is computationally inexpensive to execute online, allowing the UAM to dynamically adjust its configuration within inequality constraints (e.g. velocity bounds) to execute multi-tasks such as end-effector tracking, joint limits avoidance, and center of gravity (CoG) alignment. An experiment case study, where UAM is assigned to track and grasp a moving target, has been reported to illustrate the effectiveness of our approach.
Semantic Data Augmentation for Long-tailed Facial Expression Recognition

Facial Expression Recognition has a wide application prospect in social robotics, health care, driver fatigue monitoring, and many other practical scenarios. Automatic recognition of facial expressions has been extensively studied by the Computer Vision research society. But Facial Expression Recognition in real-world is still a challenging task, partially due to the long-tailed distribution of the dataset. Many recent studies use data augmentation for Long-Tailed Recognition tasks. In this paper, we propose a novel semantic augmentation method. By introducing randomness into the encoding of the source data in the latent space of VAE-GAN, new samples are generated. Then, for facial expression recognition in RAF-DB dataset, we use our augmentation method to balance the long-tailed distribution. Our method can be used in not only FER tasks, but also more diverse data-hungry scenarios.
Using a Machine Learning Approach to Model a Chatbot for Ceylon Electricity Board Website

&#x0D; Customer support is one of the main aspects of the user experience for online services. However, the rise of natural language processing techniques, the industry is looking at automated chatbot solutions to provide quality services to an ever-growing user base. In Sri Lanka, Ceylon Electricity Board website is one of the largest websites that customers use always to get information about electricity services. Hence, a chatbot system is very essential in CEB website. This paper presents a study about implementing and evaluating of a chatbot model for CEB website. This study implements virtual conversation agent based on deep learning algorithm which is multilayer perceptron neural network and a special text dataset for conversations about CEB services. The conversation agent model is made by utilizing the natural language processing techniques to facilitate the processing of user messages. The output of this research is the response from the chatbot and identify the best testing method to get highest accuracy for chatbot model. The chatbot model achieves the highest accuracy with the number of epochs set to 2000 and the learning rate value of 0.01 on response context data training so that it gets 78.8% accuracy.&#x0D; Keywords: Natural language processing, chatbot, deep learning, multilayer perceptron neural network, Monte Carlo cross validation, k-fold cross validation
Handwritten Digits and Optical Characters Recognition

The process of transcribing a language represented in its spatial form of graphical characters into its symbolic representation is called handwriting recognition. Each script has a collection of characters or letters, often known as symbols, that all share the same fundamental shapes. Handwriting analysis aims to correctly identify input characters or images before being analysed by various automated process systems. Recent research in image processing demonstrates the significance of image content retrieval. Optical character recognition (OCR) systems can extract text from photographs and transform that text to ASCII text. OCR is beneficial and essential in many applications, such as information retrieval systems and digital libraries.
THE APPLICATION OF THE FLIPPED LEARNING MODEL IN HIGHER EDUCATION

The present article was developed at the Polytechnics of Chimborazo in the city of Riobamba, Ecuador, with the objective of determining the relationship between the teaching model with the results of the summative and diagnostic evaluations obtained by the students, of the Thesis Design subject, of the Graphic Design Engineering career. For this quantitative study, a quasi-experimental design was used, in which a pre-test and post-test were applied, using the Likert-type data collection instrument previously validated by experts, on the perception of two teaching methods: the traditional one (focused on the teacher) and Flipped Learning, in a sample of thirty (30) students. The results had an important tendency to activities through Flipped Learning, highlighting the criteria that evaluated the link between the academic goals with the teaching model as well as the role of the teacher in promoting it. The conclusion is that it is necessary to constantly research educational innovations worldwide, in this sense, the Flipped Learning model was perceived satisfactorily by the students, due to the effectiveness of modifying the order of teaching processes and materials, which are important for the achievement of academic goals and the consolidation of learning.
Development of An Interactive Digital Module Using the Canva Application In Traumatic Counselin Course for Students Of Department Guidance and Counseling Faculty of Education, Universitas Negeri Medan

The traumatic counseling interactive module is an important innovation in traumatic counseling that can help students understand and overcome trauma-related problems more effectively.Canva application is a graphic design application that can be used to create attractive and interactive graphic designs.This study aims to develop an interactive module of traumatic counseling using Canva application for students of the Department of Guidance and Counseling, Faculty of Education, Universitas Negeri Medan.The method used in this research is the Research and Development (R&D) method developed by Borg and Gall.Data analysis used is descriptive analysis and inferential analysis.The result of this study is an interactive module of traumatic counseling that can be accessed easily by students and can be adapted according to individual needs.The feasibility test by users was conducted to evaluate the effectiveness and feasibility of the interactive module of traumatic counseling developed from the perspective of experts and users (students).The results of the feasibility test show that the interactive module of traumatic counseling using Canva application is effective and very feasible to be used by students of the
PENGGUNAAN BAHASA INGGRIS DI BAGIAN IZIN TINGGAL DI KANTOR IMIGRASI CILACAP

The purpose of this study were to find out the use of English in the stay permit section, and to find out the solution to deal with the obstacles of using English in the stay permit section to improve the quality of information services in the immigration office. The Author use several methods such as observation, literature studies, and interviews. The use of English in the stay permit information service is good enough but there are some additions so that the information to be conveyed can be fully conveyed by by giving information about stay permit requirements, immigration stay permit flow, and to fill out the forms. The obstacles and solutions such as limitations in international language, and information. The solution to this problem is to increase vocabulary, often practice listening to the accents of other countries, and using body language. The second is a limitation of information is by finding out in conveying information to provide good and clear information to visitors.
ENGLISH PROMOTION ON INSTAGRAM TO PROMOTE SERULINGMAS BANJARNEGARA INTERACTIVE ZOO

The purposes of this study is to make English promotion content on Instagram account @serulingmas_zoo, to know the problem and to overcome the problems in making English promotion content on Serulingmas Banjarnegara Interactive Zoo’s official Instagram account. The data was collected through direct practice method, observation method, documentation method and interview method. There were five contents uploaded on Instagram, three photos in the feed, one video in the feed and one Insta story which includes bilingual promotion content. Several obstacles found in the making English promotion on Instagram such as writing short captions that include all the information needed, choosing the diction and writing bilingual captions. However, there are also solutions to overcome those problems such as writing effective sentences, looking for references and using conversational sentences. The engagement of English promotion on Instagram increased. It can be seen from the increasing number of likes in the posts.
Development of Maranatha E-signature Application

Using digital signature in a document, especially in work from home situation, becomes crucial to misuse. The digital signature is a schema to identify somebody uniquely and to prove the originality of a document. The development of information technology allows digital signatures as a tool to ensure the originality of information. The aim of the study is to develop an application that uses Quick Response (QR) Code as a digital signature. So QR Code can work as a tool to authenticate the leader’s signature or document verification. After the application was built and applied, users’ evaluation was performed through questionnaires. The result shows that 44% of users state that the application has been well used and beneficial. There are some suggestions for application revision from 34% of users, whereas 22% have no comment.
Evaluasi Sistem Informasi Akademik Satya Wacana Menerapkan Model for Mandatory Use of Software Technologies

There are many theories and methods that can be used to evaluate information systems. For example TAM, Wixom and Todd, DeLone and McLean, etc. These models are not suitable to evaluate information systems that are implemented in mandatory environments where the users have to use the system whether they prefer to use it or not. This study aims to explore the variables that can affect the level of use of SIASAT (Satya Wacana Academic Information System). This research was carried out to find out how significant the influence of the factors that can influence SIASAT users. This study using BSR (Behavioral Science Research) approach with quantitative methods through data collection using questionnaire. For data analysis, statistical analysis was carried out using PLS-SEM through SmartPLS 4 software. Based on the results of the study it can be interpreted that there is a significant relationship between performance expectations and user attitudes in SIASAT usage. This can be seen from the relationship between the variables PE -&gt; AT which has the highest T-Statistic value, 24,877. Variabel with highest effect is the Information Satisfaction variable with an R-Square value of 0.655. Of the eight hypotheses tested, it was concluded that six of them were accepted and two were rejected. This is because the two hypotheses using the Use variable with a Cronbach's Alpha value below 0.7 (0.576) these variables considered unreliable thus two hypotheses are rejected.