Reviewerly/exHarmony huggingface dataset:
HOW GENERATIVE LANGUAGE MODELS CAN ENHANCE INTERACTIVE LEARNING WITH SOCIAL ROBOTS

The use of social robots in education is a growing area of research and the potential future applications are various.However, the conversational models behind current social robots and chatbot systems often rely on rule-based and retrieval-based methods.This limits the social robot to predefined responses and topics, thus hindering it from fluent communication and interaction.Generative language models such as GPT-3 could be beneficial in this context, e.g. for an improved conversation and open-ended question answering.This article presents an approach to utilizing generative language models to enhance interactive learning with educational social robots.The proposed model combines the technological possibilities of generative language models with the educational tasks of a social robot in the role of a tutor and learning partner.The implementation of the model in practice is illustrated by means of a use case consisting of different learning scenarios.The social robot generates explanations, questions, corrections, and answers based on the pre-trained GPT-3 model.By exploring the potential of generative language models for interactive learning with social robots on different levels of abstraction, the paper also aims to contribute to an understanding of the future relevance and possibilities that generative language models bring into education and educational technologies in general.
MULTIPLE INHERITANCE MECHANISMS IN LOGIC OBJECTS APPROACH BASED ON A MULTIPLE SPECIALISATION OF OBJECTS

This study takes place within the framework of the representation of knowledge by objects and within the framework of our work on the marriage of logic and objects.On the one hand, object-oriented programming has proved to be appropriate for the construction of complex software systems.On the other hand, logic programming is distinguished by its declarative nature, integrated inference and well-defined semantic capabilities.In particular, inheritance is a refinement mechanism whose mode of application leaves a number of design choices.In the context of this marriage, we describe the semantics of multiple inheritance in a non-deterministic approach based on multiple specification of logical objects.We also describe the conceptual choices for integrating multiple inheritance made for the design of the OO-Prolog language (an object-oriented extension of the Prolog language respecting logical semantics).
Smooth Panoramic Walkthrough for Adjacent Panoramic Viewpoints with Dense Spherical Matching Points

A smooth walkthrough between two adjacent view-points in three-dimensional (3-D) space is the key idea for increasing interactive experiences. It is a relatively easy task when we have the fully 3-D structure of two points. However, most people need a lot of effort to collect 3-D data, and using them efficiently is even harder. In this paper, we propose an algorithm that can create a realistic and natural panoramic walkthrough through two 360-degree panorama images. We estimate the correlated keypoints between the two images through feature matching by using 360-degree images of two points selected by the user. These key points are connected to each other to create faces. By using the spherical coordinate system, the existing key points can be expanded and more detailed faces can be determined. Using the characteristics of the panorama image, we predict the movement of keypoints in the spherical coordinate system, and through this, we predict and create a 360-degree panorama image just as the user moves between the two adjacent images. When moving the space between two points, the users can experience a virtual world through a 360-degree image of the space. With this algorithm, we can access the free view of the rotation and translation of the space by using only the 360° panorama image of the two adjacent points. Hence, we validate our result with the MOS test on various walkthrough situations and our proposed algorithm shows the most preference among users compared to prior algorithms.
QCIR

Due to multiple limitations of quantum computers in the NISQ era, quantum compilation efforts are required to efficiently execute quantum algorithms on NISQ devices Program rewriting based on pattern matching can improve the generalization ability of compiler optimization. However, it has rarely been explored for quantum circuit optimization, further considering physical features of target devices.
ACLMHA and FML: A brain-inspired kinship verification framework

As an extended research direction of face recognition, kinship verification based on the face image is an interesting yet challenging task, which aims to determine whether two individuals are kin-related based on their facial images. Face image-based kinship verification benefits many applications in real life, including: missing children search, family photo classification, kinship information mining, family privacy protection, etc. Studies presented thus far provide evidence that face kinship verification still offers many challenges. Hence in this paper, we propose a novel kinship verification architecture, the main contributions of which are as follows: To boost the deep model to capture various and abundant local features from different local face regions, we propose an attention center learning guided multi-head attention mechanism to supervise the learning of attention weights and make different attention heads notice the characteristics of different regions. To combat the misclassification caused by single feature center loss, we propose a family-level multi-center loss to ensure a more proper intra/inter-class distance measurement for kinship verification. To measure the potential similarity of features among relatives better, we propose to introduce the relation comparison module to measure the similarity among features at a deeper level. Extensive experiments are conducted on the widely used kinship verification dataset-Family in the Wild (FIW) dataset. Compared with other state-of-art (SOTA) methods, encouraging results are obtained, which verify the effectiveness of our proposed method.
Suitability of Process Models for Software Development

There exist a lot of software development process models for developing a software. There is no single software development model that works for all kinds of software development. It is difficult to analyse the suitability of a specific software development model for a specific application/software, due to lack of clear mechanisms to evaluate different models. We aim to bridge that gap by providing a quantitative approach to evaluate a model. We have defined a set of formulae that evaluate the following characteristics of a model: redundancy, redundancy cost, persistence of learning and flexibility. These formulae are applied for the waterfall model, iterative and incremental model and V-model. This work provides users with a framework to quantitatively evaluate fitness of a model for a particular application/software development and effectively compare different models on the defined characteristics.
THE Effect of Modern Leadership Style on Achieving EFQM 2020 Model Requirements A Field Study from Managers Perspective in Jordanian Civil Service Bureau

The purpose of this study was to examine the effect of modern leadership styles (transformational, transactional, and laissez-faire) on meeting the requirements of the European Foundation for Quality Management (EFQM 2020) model from the perspective of managers in the Jordanian Civil Service Bureau.Depending on the quantitative approach; a questionnaire was distributed to a sample of ( 47) department managers, directorate managers, department heads and division heads within the civil service bureau in Jordan.SPSS was utilised to tackle the collected primary data, and results indicated that the main hypothesis was accepted, confirming that modern leadership facilitates achieving requirements of the EFQM 2020 model within the Jordanian Civil Service Bureau.Also, the study proved that the transformational leadership style is more influential in achieving EFQM 2020 model requirements which are attributed to its ability to be a source for leaders to motivate working individuals and support them to be goal-oriented through empowerment.Based on the results, the study recommended encouraging leaders to be more positive about training and professional issues, further recommendations were presented.
Acceptance Of Ddkoin Blockchain Using Utaut Model: A Customer Perspective Approach

In order to create economic opportunities, DDKOIN has created a community platform.Theirs community has enthusiastically contributed to several blockchain platforms since 2015.Includes UBW, BCMY, BCMY NFC Smart Card, and Dinar Coin (DNC).The Community network has now become active in Malaysia, Singapore, Cambodia, Vietnam, Thailand, Indonesia, Brunei, Philippines, Japan, Yemen, USA, and other countries.With the PLS-SEM model, this study aimed to identify factors that predict behavioural intention to adopt cryptocurrency and develop adoption cryptocurrency using elements from the UTAUT Model.The current study adds trust to the original Unified Theory of Acceptance and Use of Technology (UTAUT2) model.This research used a deductive approach to test a theory that began with a hypothesis.The study got 675 responses.This study used 536 respondents after removing outliers.The outer loadings of FC2, TR12, and BI5 were less than 0.708.A structured questionnaire was created to collect data.The questionnaire was validated by academics and the DDKOIN team.A five-section structured questionnaire was used.Section A collected demographic information, Section B focused on independent variables, Section C on mediators, Section D on dependent variables, and Section E on suggestions.The study concludes that the Measurement Model is good.The results for Convergent Validity and Discriminant Validity are all good.Academics are looking into consumer intent as a proxy for real behaviour.This article proposes a pilot study based on a credible model to assess the intelligence community's readiness and acceptance of blockchain technology.
PERSEPSI SISWA TERHADAP PEMBELAJARAN DARING MATA PELAJARAN EKONOMI PADA MASA PANDEMI COVID-19 KELAS XI SMA NEGERI 1 BONTANG

The purpose of this research is to determine the implementation of online learning on economicslearning during the Covid-19 pandemic by the eleventh grader of social studies major at SMA Negeri 1 Bontang. This research is also to find out students' perceptions of applications, tools, and networks used in online learning. This is a case study researchby using qualitative approach. The data sources in this study were eight students from class XI IPS and oneeconomics teacher. This research used purposive sampling technique. Meanwhile, the data collection techniqueused interview, questionnaires and documentation techniques.The research’s finding showed promising result in terms of availability of tools. Cellphone and laptop are the tools used in online learning. The students also showed the capability to use online learning application such as Whatsapp and Google Classroom. The research also showed that students tend to be more interested in using Google Classroom. Learning process indicators demonstrated the range of student preferences for online learning concepts. There are two dominant concepts. The first is lectures, in which students gain a better understanding of the topic through the teacher's explanation. The second is online learning in the form of videos. The content in the form of a video is more entertaining than reading content.The fulfillment of online learning resources for all students, particularly mobile devices, demonstrates extremely high outcomes in the support indication. Support from schools is also provided, such as internet bundles, textbooks, and instruction on how to utilize online learning media apps. Students are also feeling the support of their parents. The establishment of a parent Whatsapp group by the homeroom teacher is as a school partner in overseeing the student learning process. Keywords: Perception, Online Learning, Covid-19 Pandemic
A Single Smart Ring for Monitoring 20 Kinds of Multi‐Intensity Daily Activities––From Kitchen Work to Fierce Exercises

Human Activity Recognition In article number 2200204, Yuliang Zhao, Chao Lian, Wen Jung Li and co-workers propose a smart ring to monitor human daily activities driven by a hierarchical decision algorithm. With this portable, reliable, and high-accuracy human activity recognition solution, users only need to wear the ring on the index finger, and then 20 common activities can be accurately identified.
The correlation between self-organization o f educational activity and reflexivity of students depending on gender

The relevance of the study is due to the necessity to develop st udents’ self-organization skills in the process of their education since this competence needs mastering by specialists while their implementing professional activities in modern work conditions. The objective of the study is to establish the correlation between self-organization of educational activities and reflexivity of students, depending on gender. Presumably, the gender characteristics of the correlation between self-organization of educational activity and reflexivity are determined by the extent to which this correlation is manifested. The sample of the research comprises full-time 1st and 2nd year students of Computer Science and Information Technology Department and Economics Department of Saratov State University (Saratov) (N = 106) (70 boys – 66%, 36 girls – 34%) aged 17–19 years. The following methods were used: “Questionnaire of self-organization of activity (QSA)” (E. Yu. Mandrikova), “Questionnaire of reflexivity” (V. N. Karandashev). There have not been found any significant differences between the studied parameters depending on gender. There have been recorded the greatest number of relations between the components of self-organization and the level of reflexivity in the group of young men. Apparently, both in the group of boys and in the group of girls, a high level of reflexivity correlates with a high level of fixation on structuring activities and a low level of perseverance. Correlations between reflexivity and self-organization of activity and its components «Regularity» and «Self-organization» have been found in the sample of young men. The fact that there have been identified certain characteristics of the correlation between self-organization and reflexivity in students at the beginning of their academic university career constitutes the novelty of the research. The applied aspect of the research results is determined by the possibility to use them while creating programs to enhance students’ self-organization of activities in educational practice.
Understanding User Perspective in a University Setting to Improve Biometric Authentication Adoption

Personal devices have become equipped with more sophisticated security methods through biometric authentication, which does not require users to memorize passwords and is inherently unique to the user. However, the nature of biometric inputs can lead to privacy and security concerns. Thus, evaluating the user perspective and finding the balance between ease of use, security, and privacy is imperative. To this aid, we conducted a survey-based study collecting data from 38 university students to see how prevalent these security and usability issues were in the everyday usage of personal devices. The survey assessed the user’s technical experience and then asked general device security questions and those specific to the security, privacy, and usability of biometric authentication if they had ever used it. Our results showed that usability is not a significant problem for most users in a university setting and that ease of use is the primary motivator for utilizing this authentication method; however, some users expressed concerns about losing access to the accounts or having incorrect access to their accounts. Thus, we propose design alterations and security measures to address these issues and the concerns about biometric authentication’s security implications.
A unified view of configurable Markov Decision Processes: Solution concepts, value functions, and operators

In this paper, we provide a unified presentation of the Configurable Markov Decision Process (Conf-MDP) framework. A Conf-MDP is an extension of the traditional Markov Decision Process (MDP) that models the possibility to configure some environmental parameters. This configuration activity can be carried out by the learning agent itself or by an external configurator. We introduce a general definition of Conf-MDP, then we particularize it for the cooperative setting, where the configuration is fully functional to the agent’s goals, and non-cooperative setting, in which agent and configurator might have different interests. For both settings, we propose suitable solution concepts. Furthermore, we illustrate how to extend the traditional value functions for MDPs and Bellman operators to this new framework.
Design of Employee Attendance Data Information System Using Web- Based QR Code at Medan City Election Commission Office

One of the government organizations tasked with planning general elections honestly in order to carry out elections is the Medan City KPU Office.The issue is that fingerprints are still used in the attendance system used by staff members at the KPU office in Medan.However, the fingerprint machine frequently has issues, for instance, when there is a power outage, employees are unable to use the fingerprint scanner, which can affect attendance.In order to avoid having employees wait in line to check their attendance at work using fingerprints, this study suggests a web-based application to record and arrange all types of attendance data collecting or attendance hours into the information system using a QR Code.In order to avoid having employees wait in line to check their attendance at work using fingerprints, this study suggests a web-based application to record and arrange all types of attendance data collecting or attendance hours into the information system using a QR Code.The PHP programming language and MySQL database are used in stages of the Waterfall approach for system development.Using the QR Code, the author will create a web-based application that will serve as an attendance data information system.It is intended that the application that is created would make it easier and faster to recapture staff attendance, making the process more ideal, efficient, and successful.
Efektivitas Pembelajaran menggunakan Learning Management System Berbasis Moodle

This research was conducted with the aim of looking at the effectiveness of learning using a moodle-based Learning Management System (LMS) in the subject of electrical lighting installations in the electrical department of class XI TITL SMK N 2 Payakumbuh. The research subjects are students of class XI TITL in the academic year 2022/2023. The purpose of this study was to determine the increase in the effectiveness of learning using a Moodle-based Learning Management System (LMS) in the subject of Electrical Lighting Installation (IPL) at SMK N 2 Payakumbuh. The type of research used is quantitative research with pre-experimental design method using one group pretest-posttest. The data analysis technique used normality test and homogeneity test, classical completeness, t-test, effect size, and normalized gain score. Learning using a moodle-based learning management system (LMS) can be said to be effective, the results of the classical completeness test are effective because they exceed the minimum completeness criteria limit of 85%. The result of the effect size test is 1.62 including the large and effective category. The results of the N-Gain test score of the control class of 0.29 are in the low category but have increased learning outcomes, the experimental class of 0.41 is in the medium category because of the increase in learning outcomes. Based on data analysis, learning using a moodle-based learning management system (LMS) is categorized as effective for learning.
Correlation Monitoring Method and model of Science-Technology-Industry in the AI Field: A Case of the Neural Network

This article aims to analyze the correlation status and development trend among science, technology and industry in the Artificial Intelligence (AI) subfield. First, it constructs the classification system and retrieval strategy for the AI subfield, and performs data cleaning and data finishing. Second, it designs the criteria and judgment method of the Industry Development Stages (IDS) in the AI subfield with the Delphi survey method. Third, it designs the monitoring method and model of the Science-Technology-Industry (STI) correlation with the methods of scientometrics and clustering, which involves three dimensions: science and IDS, technology and IDS, science &amp; technology clustering and IDS; especially the monitoring with the global and national perspectives. Finally, it conducts empirical application in the field of neural network. The results illustrate that the correlation monitoring method can be conducive to grasp accurately the development opportunity and trend, the advantage subfield, and the development status of Science and Technology (S&amp;T) for the dominant countries. The United States leads the global development in the empirical field. The proposed correlation monitoring method in this article can also be applied in other fields.
AutoDistiller: An Automatic Compression Method for Multi-task Language Models

In recent years, model compression techniques have greatly advanced the use of large-scale language models in industry. However, the structure of existing compressed models mostly relies on manual design, which may result in loss or overfitting of real scene data distributions. In addition, the existing compression model is usually only effective for a single task, but in real scenarios, multiple tasks are often complex and changeable or appear at the same time, so the practical role of the single-task compression model is very limited. In this work we propose AutoDistiller, an automatic compression method for multi-task language models. We build a meta-network that generates the structure of the compression model, including encoder units generated based on Transformer layer sampling method and Bernoulli distributed sampling training method. Our automatic distiller implements the process of learning data distribution on multiple tasks from large-scale language models and transferring knowledge to a compressed model end-to-end. Preliminary results from fine-tuning text categorization tasks suggest that AutoDistiller can help automate the compression of large-scale language models.
A Study on Human Motor Learning through Force-Feedback Behavior Instruction Using High-speed Visual Sensing

We have proposed a human-machine system in which a teleoperation robot realizes movements that transcend the athletic ability of the operator, based on a visual prediction that predicts the future a little ahead. In this paper, we investigate whether the system affects human motor learning through subject experiments. The results of the subject experiments suggest that motor learning can be enhanced by presenting motor sensations that greatly exceed the learning capacity of humans.