Reviewerly/exHarmony huggingface dataset:
Towards a User-Centric Decentralized Web

The promise of a fully decentralized web is too big to ignore. The bridging of Web2 and Web3 infrastructure is crucial for realizing this decentralized future. However, the current computational and storage demands in blockchain systems often result in challenges for users, leading to reliance on centralized endpoint API services in Web3 application designs. This dependence raises concerns about privacy, availability, and security. This doctoral study aims to enhance the accessibility and decentralization of blockchains, especially by facilitating the participation of resource-constrained devices such as smartphones and browsers. The goal is to facilitate the widespread adoption of decentralized systems that are secure, reliable, and scalable.
Corrigendum: Spread spectrum modulation recognition based on phase diagram entropy

CORRECTION article Front. Signal Process., 24 November 2023Sec. Signal Processing Theory Volume 3 - 2023 | https://doi.org/10.3389/frsip.2023.1334782
PluDG: enhancing task-oriented dialogue system with knowledge graph plug-in module

Task-oriented dialogue systems continue to face significant challenges as they require not only an understanding of dialogue history but also domain-specific knowledge. However, knowledge is often dynamic, making it difficult to effectively integrate into the learning process. Existing large language model approaches primarily treat knowledge bases as textual resources, neglecting to capture the underlying relationships between facts within the knowledge base. To address this limitation, we propose a novel dialogue system called PluDG. We regard the knowledge as a knowledge graph and propose a knowledge extraction plug-in, Kg-Plug, to capture the features of the graph and generate prompt entities to assist the system’s dialogue generation. Besides, we propose Unified Memory Integration, a module that enhances the comprehension of the sentence’s internal structure and optimizes the knowledge base’s encoding location. We conduct experiments on three public datasets and compare PluDG with several state-of-the-art dialogue models. The experimental results indicate that PluDG achieves significant improvements in both accuracy and diversity, outperforming the current state-of-the-art dialogue system models and achieving state-of-the-art performance.
Code-switching and code-mixing in indonesian learning at SMA YP Unila

The purpose of this research is to seek information about the factors causing code switching and code mixing in the post-pandemic learning process of the Indonesian language in class XII Social Sciences at SMA YP Unila. This study uses a descriptive approach. The data collected are in the form of words, pictures, and not numbers. This research leads to an in-depth description of the meaning, clarification, and placement of data in their respective contexts and describes them in the form of words from numbers. The total code-switching in learning interactions is one-word data, two phrases, and five sentences; this shows that students' and teachers' interest in code-switching in both classes is shallow. As in code-switching, the form of code mixing in its interaction is divided into internal code-mixing and external code-mixing. In internal code-mixing, the language used is the insertion of Javanese in Indonesian sentences. Meanwhile, in external code-mixing, the language used is the insertion of English and Arabic in the interaction of Indonesian language learning. The implication aims to make it easier for teachers and students to understand word insertion during learning interactions and quickly understand what other people say when communicating. Keywords: Code-Switching, Code-Mixing, Indonesian Learning
Text Readability Evaluation in Higher Education Using CNNs

The paramountcy of English in the contemporary global landscape necessitates the enhancement of English language proficiency, especially in academic settings. This study addresses the disparate levels of English proficiency among college students by proposing a novel approach to evaluate English text readability, tailored for the higher education context. Employing a deep learning (DL) framework, the research focuses on developing a model based on convolutional neural networks (CNNs) to assess the readability of English texts. This model diverges from traditional methods by evaluating the difficulty of individual sentences and extending its capability to ascertain the readability of entire texts through adaptive weight learning. The methodology's effectiveness is underscored by an impressive 72% accuracy rate in readability assessment, demonstrating its potential as a transformative tool in English language education. The application of this DL-based text readability evaluation model in college English training is explored, highlighting its potential to facilitate a more nuanced understanding of text complexity. Furthermore, the study contributes to the broader discourse on enhancing English language instruction in higher education, proposing a method that not only evaluates text comprehensibility but also aligns with diverse educational needs. The findings suggest that this approach could significantly support the enhancement of English teaching methodologies, thereby promoting a deeper, more accessible learning experience for students with varying levels of proficiency.
Comparing Machine Learning and Deep Learning Techniques for Text Analytics: Detecting the Severity of Hate Comments Online

Abstract Social media platforms have become an increasingly popular tool for individuals to share their thoughts and opinions with other people. However, very often people tend to misuse social media posting abusive comments. Abusive and harassing behaviours can have adverse effects on people's lives. This study takes a novel approach to combat harassment in online platforms by detecting the severity of abusive comments, that has not been investigated before. The study compares the performance of machine learning models such as Naïve Bayes, Random Forest, and Support Vector Machine, with deep learning models such as Convolutional Neural Network (CNN) and Bi-directional Long Short-Term Memory (Bi-LSTM). Moreover, in this work we investigate the effect of text pre-processing on the performance of the machine and deep learning models, the feature set for the abusive comments was made using unigrams and bigrams for the machine learning models and word embeddings for the deep learning models. The comparison of the models’ performances showed that the Random Forest with bigrams achieved the best overall performance with an accuracy of (0.94), a precision of (0.91), a recall of (0.94), and an F1 score of (0.92). The study develops an efficient model to detect severity of abusive language in online platforms, offering important implications both to theory and practice.
Pendulum Chair: A Research Platform for Cybersickness

Despite advances in VR hardware, cybersickness remains a key barrier to VR. Having a common customizable research platform could help the research community. This paper introduces a cybersickness research platform called Pendulum Chair for “spinning world” (egocentric rotation) experiences. The design of Pendulum Chair is justified and four different conditions are described from a Pendulum Chair study as validation. The conditions were defined as two different background scenes and two conditions of music. Data from 56 participants were collected and results showed that in all four conditions, participants reported cybersickness. The use of the open-source Pendulum Chair Unity project could enable stronger comparisons across cybersickness studies.
A Novel Iterative Fusion Multi-task Learning Framework for Solving Dense Prediction

Dense prediction tasks are hot topics in computer vision that aim to predict each input image pixel, such as Semantic Segmentation, Monocular Depth Estimation, Edge Estimation, etc. With advanced deep learning, many dense prediction tasks have been greatly improved. Multi-task learning is one of the top research lines to boost task performance further. Properly designed multi-task model architectures have better performance and minor memory usage than single-task models. This paper proposes a novel Multi-task Learning (MTL) framework with a Task Pair Interaction Module (TPIM) to tackle several dense prediction tasks. Different from most widely used MTL structures which share features on some specific layer and branch to task-specific layer, the output task-specific features are remixed via a TPIM to get more shared features in this paper. Due to joint learning, tasks are mutually supervised and provide rich shared information to each other for improving final results. The TPIM includes a novel Cross-task Interaction Block (CIB) which comprises two attention mechanisms, self-attention and pixel-wise global attention. In contrast with the commonly used global attention mechanism, an Iterative Fusion Block (IFB) is introduced to effectively fuse affinity information between task pairs. Extensive experiments on two benchmark datasets (NYUD-v2 and PASCAL) demonstrate that our proposal is effective in comparison to existing methods.
Instruction Improvement for Fundamental English Course Based on Assisted Tutoring System

Flipped classroom method is often used to enhance the efficiency of college-level class instruction. However, it seems a bit clumsy when the size of the classroom is large. This study suggests the 'assisted tutoring system' to overcome this unwanted drawback. The system encourages students in English 101 to proactively sign up appointments with the tutor and then the system monitors the improvements of each student. As such doing, a closed-loop feedback mechanism is formed to regulate the development of the English 101 class sized with 180 students. Linear regression and histogram techniques are applied to help see through the massive data. This study observes some significant results which show the method of 'assisted tutoring system' is effective for students' learning in an oversized class.
Gesture Mediated Timbre-Led Design based Music Interface for Socio-musical Interaction

Third-wave HCI broadens technology from traditional settings to everyday life. This wave has also influenced the internet of musical things (IoMusT) and ubiquitous music (ubimus), and these fields are inspired by the idea of including everyday things to act as musical things and become part of the push for ubiquitous computing for musical activities. This multiplies the possibilities in which musical interactions can occur and thus allows participants with various levels of musical experience to engage in musical activities. The interface design that not only supports musical activities but also delivers the experience of the musical activity is a challenging task for IoMusT. This paper presents a gesture-based timbre-led musical interface designed for casual musical activities. Earlier studies with this interface have shown the social aspect of interpersonal interactions in a musical activity. As music has a social role when individuals are connected in a musical activity, it is vital to understand the patterns of these interpersonal interactions. Here, we present a qualitative study that explores this social bond and how individuals perceive their own abilities and participation during such activities. The individual and dyadic musical interactions were structured into two steps and the results are explained to discuss the dimensions of this interaction.
Implementation of Change Islamic Management in Improving the Quality of Scientific Journal Management

The lack of reputable scientific journals in Indonesia has prompted the government to implement bureaucratic reforms for national scientific journal accreditation. This change forces scientific journal managers to change their management model in accordance with technological developments and changing consumer demands. This research was conducted to reveal and explain the implementation of change management in the management of scientific journals in Indonesia, namely: TEFLIN (SCOPUS Q3), Bahasa dan Seni (SINTA 2), and Basindo (SINTA 4). This research uses qualitative approach with a multi-case study method. The result showed that changes in the management of scientific journals from print models to electronic models were possible because they were supported by the following factors: (1) conducive external and internal driving factors, (2) supportive organizational potential, (3) a strong agent of change, and (4) the use of the right strategy.
Analysis of the Influence of Perceived Benefits, Easiness and Risk on Students’ Interest in Using QRIS

Research Aims: This research aims to examine the influence of the perceived benefits, easiness, and risks toward students’ interest in using QRIS among STEI SEBI students. Methodology: This type of research uses descriptive quantitative methods by collecting data through questionnaires and literature. The data obtained is then managed using the SEM-PLS (Structural Equation Modeling-Partial Least Square) tool with the SmartPLS version 4 application which goes through inner model and outer model tests. Research Findings: The results of this study indicate that the perceived usefulness have a positive and significant effect on the intention to use QRIS, the perceived ease of use has a positive and significant effect on the intention to use QRIS, and the perceived risk has a positive and significant effect on the intention to use QRIS. Theoretical Contribution: There have been many studies on interest in using QRIS. However, since this study focused on students’ interest will enrich and strengthen the existing theory. Research limitation and implication: This study limited to student of STEI SEBI. Consequently, the result might be differed with others and biased. Therefore, the future research should enhance the object of study and the variables.
Pedagogical foundations for the development of the culture of managerial activity among cadet unit commanders at military universities

The research aims to elaborate the pedagogical foundations for the development of the culture of managerial activity among cadet unit commanders at military universities. The paper sheds light on the problem of the culture of managerial activity in relation to this category of officers, formulates the authors’ definition of the “culture of managerial activity”, briefly analyzes the main points of view and approaches to the interpretation of the phenomenon under study. The authors describe professionally important qualities of cadet unit commanders that allow them to effectively carry out managerial activities. The main levels of development of the culture of managerial activity in relation to the considered category of officers are identified, their qualitative characteristics are presented. The paper describes the main pedagogical conditions for the development of the phenomenon under study, reflects their specificity in the work situation involving commanders and cadet units. The main ways of developing the culture of managerial activity among cadet unit commanders at military universities are presented. The scientific novelty of the research lies in presenting the authors’ definition of the notion of an officer’s culture of managerial activity and determining its structure and content. As a result of the research, the stages, methods, principles and pedagogical conditions for the development of the culture of managerial activity among cadet unit commanders at military universities have been identified, the need for the development of an officer’s managerial activity to increase the effectiveness of professional tasks performed has been demonstrated.
Body Language of Sellers and Its Impact on Customer Loyalty

The goal of this study was to ascertain, from the perspective of a sample of shoppers at significant commercial shopping centers in the city of Babylon, Iraq, the effects of sellers&amp;#39; body language, as expressed by its five dimensions (body posture, smile, physical appearance, eye contact, and personal space), on customer loyalty. The study data was collected using a questionnaire and an analytical method known as descriptive analysis was employed to achieve the study&amp;#39;s goals. The study sample received 60 electronic surveys via social networking sites, 50 of which were suitable for statistical analysis, then utilizing the statistical program (SPSS), a number of statistical tests were used to assess the data. According to the study&amp;#39;s findings, there is a favorable correlation between the five components of body language and customer loyalty. The results also showed that there are no statistical. differences in customer loyalty due to demographic factors (gender and educational level) and the presence of fundamental differences depending on the age factor. The researcher finally Providing a number of recommendations to researchers on the one hand regarding future studies and to commercial center owners on the other hand to gain customer loyalty and retain them.
Suppressing blooming interference in structured light systems by adaptively reducing camera oversaturated energy

Structured light systems often suffer interference of the fringes by blooming when scanning metal objects. Unfortunately, this problem cannot be reliably solved using conventional methods such as the high dynamic range (HDR) method or adaptive projection technique. Therefore, this study proposes a method to adaptively suppress the oversaturated areas that cause blooming as the exposure time increases and then fuse the multi-exposure time decoding results using a decoding inheritance method. The experimental results demonstrate that the proposed method provides a more effective suppression of blooming interference than existing methods.
Consumers' promotion focus mitigates the negative effects of chatbots on purchase likelihood

Abstract Marketers and consumers are adopting chatbots widely. However, the benefits of this technology remain unclear due to a lack of understanding about individual differences in consumers' purchase decisions when interacting with chatbots. This research investigates the influence of individual differences in promotion focus on purchase likelihood for the products recommended by chatbots. Two experiments demonstrated that consumers generally report a lower purchase likelihood for products recommended by chatbots (vs humans). However, compared to consumers with a low promotion focus, consumers with a high promotion focus report a higher purchase likelihood for the products. The findings also suggest that the relationship between consumer individual differences in promotion focus and purchase likelihood is mediated by engagement. By applying both regulatory focus and regulatory fit theories, the present study provides insights into how promotion focus influences purchase likelihood for products recommended by chatbots. Marketers can utilise both chronic and situational promotion focus to improve consumers' reactions to chatbots using segmentation and promotion‐focus‐related words, respectively.
A Multispectral Camera Suite for the Observation of Earth’s Outgoing Radiative Energy

As part of the Earth Climate Observatory space mission concept for the direct observation from space of the Earth Energy Imbalance, we propose an advanced camera suite for the high-resolution observation of the Total Outgoing Radiation of the Earth. For the observation of the Reflected Solar Radiation, we propose the use of two multispectral cameras covering the range from 400 to 950 nm, with a nadir resolution of 1.7 km, combined with a high-resolution RGB camera, with a nadir resolution of 0.57 km. For the observation of the Outgoing Longwave Radiation, we propose the use of six microbolometer cameras, with each a spectral bandwidth of 1 μm in the range from 8 to 14 μm, with a nadir resolution of 2.2 km.
The Role of Information and Communication Technologies (ICT) in Early Childhood Education. Integrating Educational Software into Activity

The importance of using ICT in education has been highlighted and emphasized in the international literature. The main impact of this is at the level of curriculum design and development. The study is based on the integration of information and communication technologies into current training methods, the essence of which is to rethink the way learning takes place and the roles of the two main educational actors: the teacher and the learner. In this new context, this study aims to provide a theoretical and structural perspective on ICT, as well as the role and weight of different components of the curriculum system in the design of learning programmes based on the integration of ICT in training and assessment activities. It is well known that for pre-school children, the element of novelty that emerges in all activities carried out in the instructional-educational process plays a very important role. The more this element is present, the better their attention and memory are stimulated, enabling them to concentrate better on the tasks at hand. It is now a fact that all children are attracted to computer games and all activities involving their use. In order to maximize the time spent in front of the computer for the benefit of children, and because we have educational software suitable for preschoolers, we have formulated the objectives and hypotheses of this work, based on the premise that the attention of children who use this educational package will have a progress of memory in both quantitative and qualitative analysis.
Collection Management in the Cloud: A Guide for Using Cloud Computing Technologies in LibrariesKipps, K. , &amp; Jones, A. K. (2022). <i>Collection Management in the Cloud: A Guide for Using Cloud Computing Technologies in Libraries</i> . Rowman &amp; Littlefield. 161 pp., $95.00, ISBN 9781538151884.

"Kipps, K., & Jones, A. K. (2022). Collection Management in the Cloud: A Guide for Using Cloud Computing Technologies in Libraries." Journal of Web Librarianship, ahead-of-print(ahead-of-print), pp. 1–2
INSERTING LOCAL WISDOM MATERIALS TO ENHANCE STUDENTS CONFIDENCE IN SPEAKING SKILL

Speaking skills are one of the most productive language skills. The ability to speak makes students able to produce utterances so that students can speak using a language. However, in reality there are still many students who are not optimal when asked to speak English well. There are still many students who lack confidence when practicing their speaking skills in front of the class, such as speeches, conversations, small talks, even questions and answers. Therefore, this research aims to increase students' self-confidence in speaking skills through integrating material using local wisdom. This type of research is qualitative by explaining the application of learning through local wisdom in English classes. Data was obtained through a literature study by collecting several sources related to the use of local wisdom material, and interviews with two English teachers. Data was analyzed through data reduction, data display, and conclusion. The research results show that the use of local wisdom can be used as a way to make students feel more confident when speaking English, this is because the material used is familiar and they often encounter it so it is easy for students to explain a description of a place, tourist attraction or object. other. Apart from that, the use of local wisdom material is able to build students' cultural awareness of local culture.