Reviewerly/exHarmony huggingface dataset:
WTM: Weighted Temporal Attention Module for Group Activity Recognition

Group Activity Recognition requires spatiotemporal modeling of an exponential number of semantic and geometric relations among various individuals in a scene. Previous attempts model these relations by aggregating independently derived spatial and temporal features. This increases the modeling complexity and results in sparse information due to lack of feature correlation. In this paper, we propose Weighted Temporal Attention Mechanism (WTM), a representational mechanism that combines spatial and temporal features of a local subset of a visual sequence into a single 2D image representation, highlighting areas of a frame where actor motion is significant. Pairwise dense optical flow maps representing the temporal characteristic of individuals over a sequence are used as attention masks over raw RGB images through a multi-layer weighted aggregation. We demonstrate a strong correlation between spatial and temporal features, which helps localize actions effectively in a multi-person scenario. The simplicity of the input representation allows the model to be trained by 2D image classification architectures in a plug-and-play fashion, which outperforms its multi-stream and multi-dimensional counterparts. The proposed method achieves the lowest computational complexity in comparison to other works. We demonstrate the performance of WTM on two widely used public benchmark datasets, namely the Collective Activity Dataset (CAD) and the Volleyball Dataset. and achieve state-of-the-art accuracies of 95.1% and 94.6% respectively. We also discuss the application of this method to other datasets and general scenarios. The code is being made publicly available.
A scientometric analysis on hand gesture recognition

Gesture recognition is an emerging field among researchers throughout the globe. Hand gesture recognition (HGR) is strongly connected to the difficulties of interaction between mute people (dumb and deaf) and ordinary human being. In this research work, scientometric analysis is performed to collect quantitative information about the existing research in the field of hand gesture recognition using scopus database. The overall annual trend and annual trend of four countries viz. China, India, United States and South Korea on the publication of HGR are presented. The keywords network and co-authorship network is shown with the help of VOSviewer software.
Influence of Situational Learning Combining AR and Board Games on Learning Emotion in Health Education

In traditional school education, the content of health education courses cannot be easily linked to daily life experiences.This results in the low application of acquired knowledge and hinders students from gaining hands-on experience and a sense of accomplishment through courses, thereby lowering the learners' engagement and willingness to learn.This study designed a board game integrated with augmented reality (AR) for health education; incorporated the card-game, slides, and learningsheets (CSLS) gamification teaching model into the learning process; and discussed the board game's with augmented reality effectiveness in improving learning outcomes and emotions.The research participants were 52 senior high school students, who were assigned to the experimental (AR health education board game) or control (health education board game) group in the teaching experiment.The research findings revealed the following.The two groups' were significantly different in terms of (1) learning outcomes, (2) negative emotions, (3) flow state in the game.
Modalidade epistémica e persistência

Adding bem (lit. ‘well’) to a modalized proposition, as in it is quite possible that he already left, increases the degree of conviction being conveyed. Apparently, this epistemic reinforcement that results from the presence of bem corresponds to the expression of a higher degree of belief than what is expressed without bem. Concretely, while é possível que p (‘it is possible that p’) indicates that p is a possibility, é bem possível que p (‘it is quite possible that p’) will indicate that p is a good possibility. If so, the meaning of constructions resulting from the addition of bem to a modalized proposition can be captured within the framework of modality analysis in Krazter (1991, a.o.), who considers different degrees of modality, including the notions of possibility and good possibility. This way, it will be understandable why bem can co-occur with weak modals, as the equivalents of possible or may, but not with strong modals, such as the equivalents of must or have to, since the latter already have a strong value, not being able to be reinforced by the addition of bem. However, there are counter-arguments to this hypothesis, which, among other problems, does not explain why bem may co-occur with various types of modal operators or propositional attitude verbs that express a strong epistemic value, such as, e.g., certo (‘right’), as in é bem certo! (‘quite right!’), or to know, as in the equivalent of he knows well that he is late. Thus, two questions arise: (i) how to explain the epistemic reinforcement resulting from the addition of bem to a sentence with an epistemic modal operator? (ii) why can bem combine with some epistemic modal operators, but not with all of them?An alternative hypothesis is presented and explored, according to which bem does not contribute to the truth conditions of the sentence, but functions at the discursive level. Specifically, the proposed hypothesis is that the addition of bem to a modalized proposition indicates the expectation that this proposition will remain valid as discourse flows. That is, bemhas the function of making the proposition in which it occurs persistent. Thus, the meaning of the constructions resulting from the addition of bem to a modalized sentence is best captured by an analysis of modality within dynamic semantics. In dynamic semantics, the meaning of a sentence is its Context Change Potential, its capability to update the information of the context (or information state) relative to which it is asserted. The proposed analysis provides an answer the two aforementioned questions. Epistemic reinforcement conveyed by bem corresponds to expressing the expectation that the modalized proposition will remain valid as discourse flows. The reason why bem can co-occur with some, but not all, epistemic operators is linked to the type of epistemic state described by each sentence. As predicted by the proposed hypothesis, bem cannot co-occur with modal operators expressing an inference that arises from particular information and that may not be maintained as new information is gathered.
Motion detection in a color video sequence with an application to monitoring a baby

Personal real-time video monitoring devices are popular in recent years especially for people living in bigger houses who are taking care of babies.People take advantage of a real-time video monitoring device to monitor the babies' activities while they are occupied by other issues.However, danger happens any time in any situations.It is necessary for a baby monitoring device to have a motion detection function to trigger recording functions or alert the guardians.This paper introduces a solution for the motion detection problem.The solution combines statistical methods, kernel density estimation and histogram analysis methods, and deep learning method for detecting the salient object.The final outputs are both the motion levels indicating the severity of the motions and the bounding boxes indicating the location of the motion happening in the video frame.The different levels of motion can later be used as triggers for different functions built into the device, such as starting video recording, playing sirens, etc., and the bounding boxes can provide reference focus areas for the guardians to check the details of the motion to decide whether to take actions or not.
Faktor Ekonomi Yang Mempengaruhi Penurunan Kriminalitas Di Provinsi Jawa Tengah: Analisis Mikroekonomi

Crime had been decreased in Central Java province since 2015 to 2019.The purpose of this study is to map crime decreasing and to analyze factors causing crime decreasing.The methods are crime decreasing mapping and panel data modelling.The dependent variable is the amount of crime and the independent variables are the per capita income, the unemployment rate, the number of poor people and the Gini Ratio.Data of all variables covers all Central Java province regions from 2017 to 2019.The result shows that the crime decreasing has been mapped based on ranking for all of regions.The result also shows that Central Java Province has reduced the number of crimes by increasing the cost of crime resulting from poverty and inequality anticipation.
Juke Joint: Characters Who Are Moved By Music

We present Juke Joint, a small work of interactive storytelling that demonstrates an extension to the Talk of the Town framework by which characters form thoughts, expressed in natural language, that are elicited by environmental stimuli. Juke Joint takes place in a procedurally generated American small town, in a bar with a haunted jukebox and two patrons facing personal dilemmas; the player is a ghost whose only action is to select which song from the jukebox will play. As the lyrics of the song emanate from the machine, thoughts are elicited in the minds of the patrons, constituting streams of consciousness that may eventually lead them to resolutions of their respective dilemmas. In this paper, we outline the game and also the AI architecture that makes it possible; the latter combines a light simulation of stimulus processing with a novel approach to natural language generation.
The trajectory of professional development of a teacher of foreign languages: European experience

The influence of European integration processes on the formation of a lawyer's communicative competenceThe article analyzes the importance of the formation of communicative competence as a condition for the effective professional activity of lawyers and determines the influence of European integration processes on the content of language courses that future law enforcement officers' study in the process of professional training.Professional communicative competence is considered as an indicator of the formation of communicative skills, a system of professional knowledge, value orientations, general and linguistic culture, which are necessary for high-quality professional activity, as well as communicative competence as an inseparable component of the professional culture of a lawyer.It has been established that communicative competence includes the value attitudes of an individual, and since the European choice of Ukraine proves its commitment to the European values of freedom and democracy, it is especially important to take into account the European integration theme when selecting questions, exercises and texts for the development of communicative abilities and skills of future lawyers.It is emphasized that the strengthening of integration into the general European intellectual and educational environment requires not only the introduction of European norms and standards in education, but also the filling of the content of education with European integration topics.The forms and methods of work aimed at forming the communicative competence of future lawyers, taking into account European integration, are characterized.It was emphasized that in classes and during independent work, it is necessary to focus as much attention on speech (communicative) exercises as possible, to create situations of various types of professional communication, to use such forms and methods of work as disputes, discussions, debates, and to assign tasks to independent work and writing creative works on topics of European integration, related to the future profession of the student/cadet, preparation of project works, etc.Samples of questions, tasks and exercises in the direction of European integration are proposed, which should be used when learning the course "Communicative competence in law enforcement activities" by future lawyers.
Semantics of Anthropomorphic Images on Shamanic Drums of Shors as an Object of Intangible Cultural Heritage

The article substantiates the significance of the refering to the mythological ideas of the ethnos about the structure of the universe, about the anthropomorphic spirits inhabiting the world. The semantics of images on drums is characterized as one of the categories of intangible cultural heritage that has a material embodiment. The possibility of reconstructing the semantics of anthropomorphic images on the drums of Shor shamans is considered. Interpretation based on the researchers' fixation data is defined as the main method of reconstruction. The results can be used in the cultural and educational activities of the museum. The preferred forms of this activity may be interactive excursions and master classes.
A Case Study: Student’s Anxiety in Learning English at the 7th Grade of SMP Negeri 3 Muara Bungo

This study was carried out to investigate foreign language anxiety of EFL junior secondary school students at the 7th grade of SMPN 3 Muara Bungo. Specifically, it sought to identify what factors that may contribute to anxiety in English learning environment based on the students’ perspectives. The method was used in this study was qualitative method with case study approach. Fifteen anxious students were selected as the participants. The data were gathered through structured interviews and classroom observations. The result of the study showed that speaking in front of the class, being laughed at by others, incomprehensible input, students’ beliefs about language learning, teacher personality, and lack of preparation were the six factors that may contribute to the students’ anxiety in learning English.
Sexual Violence Classification as Hate Speech using Indonesian Tweet

Hate speech is an action in the form of communication either directly or through the media performed by groups or individuals with the aim of provoking, inciting, or insulting a group or other individuals. 3, 640 hate speech spread across various social media. 677 KBGO cases, which were dominated by sexual violence cases spread through online media. Our research aims to produce the best classification model with high accuracy by comparing several combinations of machine learning techniques. We collected 9, 035 twitter user opinions to be used as a dataset. From a total of 6, 089 opinions that were successfully annotated, 5, 102 opinions were classified as non-hate speech and 987 opinions as hate speech. We purpose SVM model classification with TF-IDF (Unigram) as feature extraction method and Oversampling method such as ROS and SMOTE to solve imbalance dataset problem and improve the performance of model classification. The classification model with SVM algorithm reach the best accuracy, which is 0.942 with F1-score of 0.940.
UGDA: Data Augmentation Methods for Uyghur Language Named Entity Recognition

Data augmentation methods can effectively improve model generalization performance and have been widely used to alleviate the overfitting problem in the case of low resources or class imbalance; however, the data noise generated by traditional data augmentation methods can make named entity recognition models sensitive and fragile. To address the above problems, this paper proposes an applicable Uyghur language named entity recognition data augmentation method (UGDA), which improves the traditional data augmentation methods to improve the quality of data augmentation sample generation. It is shown experimentally that using the data augmentation method on a self-constructed Uyghur language dataset improves F1 values by 2.97% compared to the baseline model ( <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\text{BIGRU}+\text{CRF}$</tex> ) and by 1.81% compared to the baseline model ( <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\text{CINO}+\text{CRF}$</tex> ), and the generated augmented samples are also applicable to the pre-trained model, fully demonstrating that the data augmentation method proposed in this paper can generate diverse and information-rich enhanced data, effectively improving the performance of the Uyghur language named entity recognition task.
The Role of Language Communication with The Society and Culture

This research discusses the relationship of language communication with society and culture. Bahasa Indonesia as a language of unity is used in activities to communicate by the wearer community from various tribes and regions. As an effective means of communication the Bahasa Indonesia has an important role in developing and launching various aspects of life and culture. This research uses the method of literature writing (library research). To know the language activities of a person does not merely use the language as communication, but rather describes other aspects outside the linguistic aspect. These aspects may affect the style, dialect, variety, form language it uses and show the user a separate language item that is closely related to the language (social class, ethnic group, nationality and geographical location of the linguist). Linguistically different but still not mentioned as a different language. Such language differences are called language variations.
Troubleshoot Microsoft Teams Phone System (Calling Plan and Direct Routing) Issues

As a Teams admin, you must configure and troubleshoot Microsoft Teams Phone System problems. After completing this chapter, you will be able to deploy, configure, and maintain Teams Phone System. You will also be able to troubleshoot Teams Direct Routing and call plan issues. You will also learn how to enable voice services for users to make and receive calls. You will learn how to facilitate voice services when using Teams Phone System with calling plans and facilitate voice services for users when Direct Routing is configured. This chapter provides the necessary information that you need to troubleshoot Microsoft Teams Phone System issues.
Preface: The 10th International Conference on Applied Science and Technology (ICAST2021)

First Page
THE IMPLEMENTATION OF PICTURES AS MEDIA TO IMPROVE STUDENTS’ DESCRIPTIVE WRITING ABILITY SMP 1 PRINGSEWU

The objective of this research is to find out whether there is any significant improvement in students’ descriptive writing ability after the implementation of pictures as media. This research is a quantitative research, which use a one-group pre-test and post-test design. The population of this research is the seventh grade students of Junior High School 1 Pringsewu. The sample for this research is class 7.1 which consisted of 30 students. The writing test is administered as the instrument of the research. The data is analyzed by using the Paired Sample T-test. It is used to prove the hypothesis in this research. The result of the T-test in this research shows that the value of the significant level is lower than the alpha level (0.00&lt;0.05). It means that H1 is accepted that there is a difference in students’ writing ability after the implementation of pictures as media. The difference indicates that there is an improvement after the implementation of pictures. Thus, it can be concluded that pictures can be applied to improve students’ descriptive writing ability. Based on the result of the research, it is suggested to the teachers to practice the use of pictures as teaching media in writing descriptive text since it would develop students’ writing skills. Keywords: pictures, writing ability,descriptive text
Exploring the Role of Social Media towards Employees Work Place Relation

The study titled as "Exploring the Role of Social Media towards Employees Work Place Relation".Survey research method was selected to complete this study.The objectives i.e. to examine risks of social media at workplace.Through questionnaire as tool, survey was conducted.Tool of data collection was created on Likert scale format.The data regarding all faculty members in six faculties (as universe of study) under study was taken from respective registrar offices of the university.In this study through convenient sampling technique data was collected.For calculation of representative sample, Raosoft sampling calculator has been used.Total sample was found equal to 227 out of 552.When the researcher collected all the data from the given respondents then it was analyzed and run systematically by a computer program name SPSS (Statistical Package for Social Sciences).Hence, Majority i.e., (55.9) % respondents use WhatsApp.Overall, WhatsApp was the most used social networking site..Maximum respondents agreed that Social media diverts attention of employees from assigned tasks.Maximum respondents agreed that Social media is being used for making propaganda against other employees.Maximum respondents agreed that Social media is breach of confidentiality for employees.
Detection of Camera Model Inconsistency and the Existence of Optical Image Stabilization System

Cameras becomes more ubiquitous on mobile devices which pave the way for Augment Reality (AR) applications. AR’s enabling technology is the underlying visual-inertial Simultaneous Localization and Mapping (SLAM) package which requires a precise camera model for mapping purpose. Due to manufacturing inconsistency and device aging over time, the preciseness is often hard to maintain over time. On the other hand, those cameras are often equipped with optical image stabilization (OIS) system. OIS changes camera intrinsic parameters and being aware of its existence is important before a high-order SLAM model is applied. Here we present a two-step approach to detect if an image conforms to a given camera model (distortion coefficient and intrinsic matrix) by developing two statistical hypothesis testings. We have implemented the algorithm and test it in physical experiments. Results show that our algorithm successfully detects model inconsistency and the existence of OIS system with 85.4% recall and 100% precision.
Multifidelity data fusion in convolutional encoder/decoder assembly networks for computational fluid dynamics.

image from this reduced representation via transposed convolutional layers. Not only are ED models a general tool for random noise removal, but their application to low signal-to-noise data can enhance the data’s quantitative usage since they are able to learn the functional form of the signal. We demonstrate that the CNN-ED models trained on real-world experimental data help to effectively extract equilibrium dynamics’ parameters from two-time correlation functions, containing statistical noise and dynamic heterogeneities. Strategies for optimizing the models’ performance and their applicability limits are discussed.
Comparative Assessment of Angstrom Sunshine-Base Models for Estimation of Global Solar Radiation in Owerri, Nigeria

Comparative assessment of the average monthly global solar radiation on horizontal surface for Owerri has been carried out with the use of five Angstrom sunshine base models. Thirty years (1992 - 2022) of average monthly global solar radiation and sunshine hours are sourced from NASA and NIMET, respectively. The sunshine-base models are evaluated with the use of geographical and metrological data of Owerri and comparison is made based on estimated statistical error indices of Mean Bias Error (MBE), Root Mean Square Error (RMSE), Mean Percentage Error (MPE), Coefficient of Determination (R2) and percentage error to assess the applicability accuracy of the models. Results obtained shows that regression equations of Fagbenle and Page models satisfied viability criterion of MBE, RMSE, and MPE being close to zero, the R2 values are reasonably close to unity and the percentage error agreed to within ± 10% of the measured average monthly global solar radiation on a horizontal surface in Owerri. Rietveld model closely followed with less prediction accuracy to those of Fagbenle and Page models, while, Glower and McCulloh and Turton models yield poor estimation of the average monthly global solar radiation on horizontal surface.