Reviewerly/exHarmony huggingface dataset:
Planning with Perspectives -- Decomposing Epistemic Planning using Functional STRIPS

In this paper, we present a novel approach to epistemic planning called planning with perspectives (PWP) that is both more expressive and computationally more efficient than existing state-of-the-art epistemic planning tools. Epistemic planning — planning with knowledge and belief — is essential in many multi-agent and human-agent interaction domains. Most state-of-the-art epistemic planners solve epistemic planning problems by either compiling to propositional classical planning (for example, generating all possible knowledge atoms or compiling epistemic formulae to normal forms); or explicitly encoding Kripke-based semantics. However, these methods become computationally infeasible as problem sizes grow. In this paper, we decompose epistemic planning by delegating reasoning about epistemic formulae to an external solver. We do this by modelling the problem using Functional STRIPS, which is more expressive than standard STRIPS and supports the use of external, black-box functions within action models. Building on recent work that demonstrates the relationship between what an agent ‘sees’ and what it knows, we define the perspective of each agent using an external function, and build a solver for epistemic logic around this. Modellers can customise the perspective function of agents, allowing new epistemic logics to be defined without changing the planner. We ran evaluations on well-known epistemic planning benchmarks to compare an existing state-of-the-art planner, and on new scenarios that demonstrate the expressiveness of the PWP approach. The results show that our PWP planner scales significantly better than the state-of-the-art planner that we compared against, and can express problems more succinctly.
The Effect of External Motivation to Study Abroad on the Academic Adjustment and Educational Satisfaction of Foreign Students Studying in Korea

Purpose: The purpose of this study is to not only explore, in regards to the international students studying in Korea, the influence of external motivation for studying abroad on the academic adjustment and the educational satisfaction, but also the infrastructure services, which are currently various external motivations for the inter-national students at each university, thereby preparing the basic data needed to build the customized practical cases appropriate for the future society. Method: In this study, from November 2019 to January 2020, 450 international students enrolled at universi-ties in Daegu and Gyeongbuk were surveyed, and the cluster sampling method was used, and the survey was conducted using the self-administration method. Among the collected questionnaires, 322 questionnaires were used as a valid sample, excluding the data in which the responses were insincere or some of the contents of the survey were omitted, and a questionnaire was conducted on the external motivation, academic adjustment, and educational satisfaction among the international students. For the data processing of the study, using the SPSS 23.0, frequency analysis, Cronbach's α coefficient calculation, factor analysis, correlation analysis, and the mul-tiple regression depending on the purpose of data analysis were used. Results: As a result of the factor analysis and reliability test for external motivation in factor analysis and reliability test, the eigenvalue and reliability of the factor turned out to be 2.873(α=.832) and 2.801(α=.806), and the academic adjustment turned out to be an adjustment factor of 2.942(α=.825), educational satisfaction turned out to be a facility/administrative factor of 2.531(α=.776), and a teaching/class factor of 2.149(α=.766). Overall, it turned out that the external motivation affects the academic adjustment and the educational satisfaction. Conclusion: It is significant in that it examines the correlations between 'motivation to study abroad', 'study adaptation', and 'educational satisfaction' of the international students from the perspective of transnationalism which leads to 'study-employment-immigration'. Accordingly, in order for the international students to adapt to their studies and satisfy their education, the infrastructure services, which are motives outside of studying abroad, must be strengthened.
DIFFERENT WAVELETS, THEIR PROPERTIES AND ADVANTAGES

In this article we discuss the concept of wavelets, different forms of wavelets and their properties, graphs of different wavelets and their Fourier transforms are shown. We have also discussed the comparative advantages of wavelet transforms over Fourier transforms- in analyzing signals.
T.B. Brazelton's Developmental Approach to Learning

Newer understandings of human development and learning are displacing older ones, as the limits of their usefulness and explanatory power are exposed. Development, we now believe, proceeds nonlinearly, through predictable periods of disorganization and reorganization, shaping and shaped by caregiving systems and the larger contexts in which they evolve. Emergent new capacities and competencies build on earlier ones, including attachment, state regulation, and mutual regulation. Their individual manifestations are influenced by and contribute to both differences in temperament and the caregiving system. Through their strong relationships, teachers and parents can help children learn by building on these early developmental phenomena. Keywords: attachment, Brazelton, mutual regulation, parent advocacy and leadership, state regulation, self-regulation, systems theory, scientific revolutions, social justice, touchpoints, temperament, habituation
Modelling and Predicting Quality-of-Experience of Online Gaming Users in 5G Networks

5G technology will greatly improve quality of human life by enabling new use cases that will fully leverage on the improved throughput, connections, and latency of the 5G networks.Enhanced Mobile Broadband (eMBB), which supports ultra-high throughput, is one of the most important features in 5G networks.This service is expected to improve users' quality of experience (QoE) when using resource-intensive and far more interactive applications such as playing online games.It is widely known that 5G networks can be used for gathering network monitoring data and application metrics; however, the correlation between the data and the users' QoE is not well understood.Since large amount of data can be collected, machine learning approach is well suited for predicting users' QoE when playing online games in 5G networks.In this paper, an artificial neural network (ANN) model is proposed to predict the users' QoE based on the network monitoring data of a 5G network during an online gaming session and the model's performance is evaluated.The ANN model consists of four layers which include one input layer, two hidden layers, and one output layer.The Unified Management Expert (UME) system is used to collect the network monitoring data from a 5G NSA indoor private campus network.The proposed ANN model achieves prediction accuracy of close to 80% using 30 most relevant features derived from the radio access network monitoring data.
Seamless Multiple-Target Tracking Method Across Overlapped Multiple Camera Views Using High-Speed Image Capture

Multiple-target tracking across multiple camera views is required for various practical tracking and surveillance applications. This study proposes a seamless tracking method based on label transfer using high-speed image capture. The proposed method does not require camera calibration to estimate the extrinsic parameters, and can be applied with simple line calibration. Therefore, it is effective for large-scale camera networks. In addition, owing to the features of the high-speed image capture and self-window, our method ensures seamless tracking of objects across multiple camera views. The feasibility of the method is proven through an experiment using a high-speed camera network system.
Development and effect of a picturebook counseling program for the development of socio-emotional competency of elementary school students with special needs: Focusing on the experience of special education teachers

Objectives The purpose of this study is to develop a counseling program using picturebooks to enhance the socio-emotional competency of students who needs special education and who are enrolled in special education classes in elementary schools and to verify the effect through the experience of special education teachers. Methods First, past studies related to picturebook, socio-emotional competency, and counseling program development were analyzed. Second, based on the results of prior research and analysis, the procedures of the program development were determined to enhance the socio-emotional competency of students who needs special education and who are enrolled in special education classes in elementary schools. Third, a picturebook counseling program activity plan(lesson plan) was created. Fourth, peer teachers gave feedback on the lesson plans of this program activity plan(guideline). Then, the researcher revised and complemented them. Fifth, 30 special education students(8 classes) were participated in this picturebook counseling program. It is difficult to collect the self-report questionnaire from the special students. So experience from 8 special education teachers were collected. Finally, the collected experiences of special teachers were analyzed through a qualitative approach of repetitive comparative analysis. Results First, the researcher developed a counseling program to improve socio-emotional competency, using picturebooks in special classes in elementary schools for 5 sessions. Second, the findings revealed the effect of the picturebook counseling program to increase the emotional competency of special education students in elementary school by analyzing the experiences of special education teachers who performed it. Conclusions This study shed lights on the development of the counseling program to strenghten socio-emotional competency using picturebooks, which is applicable to special education students in elementary schools. Finally, the significance and limitations of this study and suggestions for future research were discussed.
The Phenomenological Study on Youth using Metaverse

Objectives The purpose of this study was to explore and characterize the experience of youth using Metaverse. Methods In-depth interview was conducted with 7 teenagers who are attending middle and high school, located in A city, using Colaizzi's phenomenological research method. 7 teenagers have experience using Metaverse. Results As results, 3 essential themes, 6 sub-categories, 14 semantic units were found. Three essential themes were ‘double-edged network’, ‘a third school’, self reflection’. And six sub-categories were ‘unexpected displeasure’, ‘activities extension’, ‘knowledge acquisition’, ‘a free outpouring of emotion’, ‘awareness of mataverse unreality’, ‘self-regulation improvement’. Conclusions The discussion on online education whether to enable Metaverse to be used for the education of teenagers is as follows. First, raise awareness among teenagers that social norms similar as the ones of the real world also exist in the Metaverse. Second, provide opportunities for young people to experience various activities in the Metaverse. Third, provides youth with time and space to express their needs in addition to what the Metaverse has to offer.
Time-varying hurst parameter estimation method based on dynamic step size overlap window

Accurately estimating the self-similar characteristics of time series has great application value for data analysis, prediction and system control. Because of the high mutability of time series, the existing Hurst parameter estimation methods fail to describe the local self-similarity of time series and consider its dynamic change, resulting in low estimation accuracy. Therefore, this paper proposes a time-varying Hurst parameter estimation method based on dynamic step size and overlapping windows (DSSOW-H). The method introduces to the dynamic step size based on the existing sliding window time-varying Hurst parameter estimation method and adjusts the sudden change of data through the change of dynamic step size, in order to effectively estimate the self-similar characteristics of local data when it suddenly changes. MATLAB is used to generate artificial FGN sequences with self-similar characteristics. At the same time, this method compare with the periodic diagram method, R/S method, variance-time diagram method, sliding window time-varying Hurst parameter estimation method (SWTV-H). According to the experimental results, the relative error of DSSOW-H is reduced by 53% compared with SWTV-H, and the relative error of DSSOW-H is 0.9875% when applied to satellite network traffic. Therefore, it is proved that the method in this paper is effective in improving the estimation accuracy and reducing the estimation error when the data has abrupt changes.
Design of gait feature detection system based on STM32

To evaluate the rehabilitation effect of elderly people during walking training on treadmills, a detection system capable of acquiring gait features was designed. Install the flexible force-sensitive sensor on the treadmill table, collect sensor data through STM32F205 microcontroller, and use W5300 Ethernet chip and STM32F205 microcontroller to build a TCP/IP network communication platform to ensure that sensor data can be synchronously transmitted to the host computer through the network port in real-time. The gait characteristics of the elderly are obtained by calculating the sensor data obtained by the host computer. System tests show that the gait characteristics obtained when walking on a treadmill are consistent with previous research results, thus verifying the accuracy of the detection system.
Design of smart car for returning books based on A* Algorithm and inertial navigation

Path planning and navigation and positioning are the key issues in the operation of the book return smart car. The book return smart car system proposed in this paper adopts the improved A^* algorithm and inertial navigation for path planning and navigation and positioning. First, use the camera to identify the map of the library. Secondly, apply the A^* algorithm to solve the optimal path from the initial position to the final position. Finally, the icm20602 six-axis IMU sensor integrates the acceleration during the driving process of the book-returning smart car, and the encoder is used to locate the vehicle's position.
The Effect of Application-based Mathematics Education on Mathematical Ability and App Utilization Attitude of Young Children

Objectives This study is to examine the effects of application-based mathematics education on young children's mathematical ability and attitude to application utilization. Methods The purposes of this study wFor this purpose, 87 children aged 3 to 5 years (45 experimental group and 42 comparative group) were selected from early childhood education institutions in the metropolitan area. The experimental group conducted mathematical activities in the mathematics education application with parents at home, and the comparative group used the activity sheets consisting of the same concept as the contents of the mathematics education experienced by the experimental group. The collected data were statistically processed using the program for SPSS 25.0 Windows. Before and after the experiment, the experimental group, the infant's mathematical ability, and the attitude of using educational applications were measured, and the data were analyzed by conducting covariance analysis (ANCOVA) and independent sample T-test. Results Application-based early childhood mathematics education has a significant effect on young children's mathematical ability and attitude to use applications. The mathematical ability of the children was found to affect the number, operation, geometry, and measurement of the sub-areas, and the attitude of the children's use of educational applications had a positive effect on the competence of the sub-areas. Conclusions This study suggests that application-based mathematics activities can be an effective method for early childhood mathematics education.
Emotional analysis of evaluation discourse in business English translation based on language big data mining of public health environment

This paper conducts sentiment analysis on the evaluation discourse of business English translation based on language big data mining of public health environment, and aims to find a reasonable algorithm to conduct detailed research on all aspects of sentiment analysis.This paper focuses on three areas of sentiment information, extraction, sentiment information retrieval, and sentiment information submission, using scale analysis and feedback analysis, combined with related algorithms of big data mining technology, such as decision trees and clustering algorithms, through the level of emotional words appearing in the corpus, phrase-level, text-level, etc., and combine the text model with the combined reliability to output the evaluation object and evaluation feature separately, and propose an evaluation method to calculate the sensitivity of the evaluation feature, so as to accurately improve the sensitivity of the evaluation feature. It is mainly divided into two categories for data analysis. One is to focus on the public health environment of the characteristics of business English translation itself, and the other is to conduct research on the application of big data mining in the evaluation of translation discourse.The research data show that the smallest gap between the sentiment orientation of the discourse evaluation perspective is the output of the language discourse, and the smallest gap in the attributes of the evaluation object is at the phrase level, and the gap value is 3.5; for the evaluation object, the maximum difference is 3.4.With the development of science and technology and the economy, the public health environment has become more and more complex, and business English translation has received more and more attention. The sentiment analysis of evaluation discourse in this field is a means of expressing language characteristics. In order to enrich research in this field, the study of this article is necessary.This study has a deeper understanding of the affective analysis of evaluation discourse in public health environment business English translation. The clustering algorithm of big data mining technology applied can provide an important guarantee for the actual conclusion of this research and quantitative analysis of the positive evaluation and criticism of evaluation. To solve the various problems encountered in translation, so as to improve the translator's own translation level, and promote the research of translation methods in Chinese translation.
About the Authors

Other| October 01 2022 About the Authors Music and the Moving Image (2022) 15 (3): 60. https://doi.org/10.5406/19407610.15.3.04 Cite Icon Cite Share Icon Share Facebook Twitter LinkedIn Email Permissions Search Site Citation About the Authors. Music and the Moving Image 1 October 2022; 15 (3): 60. doi: https://doi.org/10.5406/19407610.15.3.04 Download citation file: Zotero Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All Scholarly Publishing CollectiveUniversity of Illinois PressMusic and the Moving Image Search Advanced Search heidi hart is an art and humanities fellow at SixtyEight Art Institute in Copenhagen. She holds an MFA from Sarah Lawrence College and a PhD in German Studies from Duke University (2016). She completed a postdoc at Utah State University and is a regular guest instructor at Linnaeus University in Sweden. She has received an ACLS-Mellon fellowship and several grants for environmental curriculum development. Heidi's publications include the monographs Hanns Eisler's Art Songs: Arguing with Beauty (Camden House, 2018) and Music and the Environment in Dystopian Narrative: Sounding the Disaster (Palgrave Studies in Music and Literature, 2018). Her curatorial book Climate Thanatology is forthcoming in 2022 (Really Simple Syndication Press).kaapo huttunen is currently a PhD student at the University of Turku, the Faculty of Humanities. He conducts research on the role of music and sound design in the aesthetics of Nordic noir, the crime fiction style from the... You do not currently have access to this content.
Possible Adoption Options of Virtual and Augmented Reality Technologies in Open Universities during the Covid-19 Era

The paper explores the use of Virtual and Augmented Reality (VAR) in response to the Covid-19 Pandemic, that is, the role VAR can play during the Covid-19 crisis and beyond, for business continuity. VAR solutions are needed to help maintain continuity in teaching and learning following disruption caused by Covid-19 by allowing learners to continue to benefit similar physical teaching and learning experience by applying VAR solutions. The paper therefore reviews various solutions suitable for adoption in Open Universities.
Exploring the Role of Repertoire in Library Reference Interactions

&#x0D; &#x0D; &#x0D; &#x0D; Using experience to interpret a user’s information need is embedded in the process of every library reference transaction. Reference workers need to constantly grow and update their base of knowledge to have a deep understanding of a variety of resources and subjects (Miller, 2011). The expert reference worker not only has knowledge of specific subjects and resources, but also has an additional level of professional knowledge regarding the successes and failures of past reference interactions. In other fields, like design, bodies of knowledge iteratively built from previous experiences are known as repertoire. Designers develop repertoire over time by integrating information from previous situations into new ones (Goldschmidt &amp; Porter 2010). Research shows that designers with broader and more diverse repertoires make better design decisions and demonstrate greater expertise (Salmon &amp; Gritzer 1992; Wahl &amp; Baxter 2008). Much like designers, reference workers often deal with problems that are complex and benefit from previous experience and expertise, as well as diverse and individual perspectives built into a reference worker’s personal repertoire. Our research aims to understand how, over time, reference workers collect and reflect on experiences to develop their repertoires to deal with complex inquiries and how diverse and extensive the personal repertory knowledge of reference workers is.&#x0D; &#x0D; &#x0D; &#x0D;
Software aging prediction framework based on optimized TCN model with grey correlation analysis

The temporal convolutional network (TCN) model has the characteristics of strong parallelism and stable gradient in time series processing. The structural depth of the model is related to the input length, convolution kernel and dilation factor. In order to further improve the accuracy of prediction, this paper proposes a software aging prediction framework based on TCN model optimized by grey relational analysis. Collecting available memory data as the input of the framework, determine the length of the input nodes of the TCN model through gray correlation analysis, and then conduct training and prediction, and evaluate the efficiency of the model by checking the average error between the predicted output memory and the actual memory. Then change the length of the input chunk to carry out a comparative experiment, which verifies the effectiveness of the grey relational degree analysis.