Reviewerly/exHarmony huggingface dataset:
A Diagnose of University Education in the Embryonic Period of Metaverse

About two years have passed since the metaverse entered the education world. If you look at the articles in the media, you can see that the metaverse is clearly becoming a big factor in this moving society. It works as a positive or negative factor, and some people welcome it, while others feel uncomfortable toward it. There is no doubt, however, that the metaverse will play an important role in education. At this point, we need to examine how our society perceives the metaverse in relation to education and how the metaverse is being educated in universities. This study looked at what phase the metaverse is in in our society and what kind of educational programs it is operating. And some improvements were suggested in the metaverse education. Through these inspections, Through this check and several suggestions, I hope that a balanced metaverse education in university will come true..
A Study on Cultural Criticism Discourse of “Squid Game” from the Perspective of Korean Culture Education

This article explores the direction of Korean culture education by analyzing overseas critical articles on “Squid Game,” which has recently gained worldwide popularity. To this end, previous studies about Korean culture education and intercultural education were examined, and the framework of analysis was derived as “universality,” “specificity,” and “individuality”. Based on this, cultural factors appearing in 50 English articles on “Squid Game” were analyzed. Then a discourse analysis was conducted by selecting 19 articles corresponding to cultural criticism. As a result, overseas perspectives on “Squid Game” were divided into identity-centered interpretation, difference-centered interpretation, and analogical interpretation. Through the significance and limitations of each interpretation, suggestions for the future direction of Korean cultural education were derived.
An Analysis on the Relationship between the Characteristics of Seoul's Innovative Autonomous School and Teacher Efficacy

Purpose: The purpose of this study was to investigate the complex relationship between teacherefficacy and the characteristics of the Innovative Autonomous School(democratic decision making,teacher learning community, student growth-centered curriculum, principal/administrator leadership,administrative system supporting creative education, support and supervision by the Office of Education,and cooperation of school and community).&#x0D; Methods: A survey was conducted on the perceptions of the teachers at the Innovative AutonomousSchool and path analysis was performed.&#x0D; Results: The research findings are as follows: first, support and supervision by the Office of Educationshowed an indirect effect through administrative system supporting creative education within a schoolon teacher efficacy, democratic decision making, a student growth-centered curriculum, and the teacherlearning community. It could be construed that the support by the Office of Education for schoolautonomy and administrative innovation within the school allowed teachers to focus on their teaching andlearning activities and are major variables affecting teacher efficacy. Second, principal(administrator)leadership showed an indirect effect through the administrative system supporting creative educationwithin a school on teacher efficacy, democratic decision making, student growth-centered curriculum,and the teacher learning community. Principal(administrator) leadership showed a direct effect ondemocratic decision making. The total effect of principal/administrator leadership on democratic decisionmaking was the largest among all pathways. Third, teacher efficacy showed a significant correlationwith democratic decision making, teacher learning community, and a student growth-centered curriculum.&#x0D; Conclusion: Although Innovative Autonomous Schools are similar to Innovative Schools, the formercan be seen as differentiated from the latter in that they actually realize school autonomy and canbe a model for school autonomy.
Digital Payment Solutions: Consumer Privacy and Cybersecurity Concerns

As e-commerce grows in popularity around the world, and consumers seek convenience, speed, and simplicity in their online transactions, digital payments are becoming increasingly indispensable. As more sophisticated payment solutions emerge and with this widespread adoption of digital payments, consumer privacy, and cybersecurity concerns must be addressed. This article examines the obligations of stakeholders such as merchants, payment service providers, and consumers in navigating the use of these disruptive technology solutions. It also explores the measures that these stakeholders should take to protect personal data and mitigate cybersecurity risks. Ultimately, this article provides insight into how stakeholders can protect personal data during online transactions and ensure the reliability of digital payments.
LBS privacy protection scheme based on searchable encryption

With the development of the 5th Generation Mobile Communication Technology (5G), the 5G network can more accurately locate the user's location. This enables location-based services to provide users with more personalized services, but it also brings more challenges to user location privacy protection. Aiming at the leakage of location privacy and query privacy in LBS, a LBS privacy protection scheme based on searchable encryption is proposed. The scheme uses thresholds to replace the private information queried by users, thereby reducing the risk of location information leakage during user service requests; it reduces the storage space of the server through attribute-based encryption and improves query efficiency. Finally, the correctness of the ciphertext search of the scheme is proved.
Path planning research for mobile robots in dynamic environments

At present, due to the COVID-19, China's social and economic development has slowed down. Some life service e-commerce platforms have successively launched "contactless delivery" services, which can effectively curb the spread of the epidemic. Robot distribution is the current mainstream, but robots are different from people and need to have accurate program settings. Both path planning and obstacle avoidance are currently top issues. This requires the mobile robot to successfully arrive at the destination while minimizing the impact on the surrounding environment and pedestrians, and avoiding encroachment on the movement space of pedestrians. Therefore, the mobile robot needs to be able to actively avoid moving pedestrians in a dynamic environment, in addition to avoiding static obstacles, and safely and efficiently integrate into the pedestrian movement environment. In this paper, the path planning problem of unmanned delivery robot is studied, and the path of mobile robot in the crowd is determined by global planning and local planning, and the matlab simulation is used for verification.
Inference in Bayesian Network in Modelling Word Sense Disambiguation for Sesotho sa Leboa

The main problem in the study of Word Sense Disambiguation (WSD) is linking context and senses to an ambiguous word. WSD is the problem of conveying suitable connotation (sense) to a given word in a transcript. Determining the ambiguity of words is a fundamental problem for understanding requirements and their related tasks. WSD is an open Natural Language Processing (NLP) problem, despite enthusiastic determination in probing the problem, the fact remains that no large solution exists in Sesotho Sa Leboa language to date, and no reported accurate WSD system has been built. The paper describes the challenges faced in making the linkage using Bayesian Network to model context and senses for an ambiguous word. The Bayesian Network (BN) is a depiction of a joint probability distribution of a collection of arbitrary variables as well as a probable underlying link. The objective of this study is to model joint conditional probability distribution of the output variable after examining the latest evidence of the lexical ambiguity of the word. In this research, BN is constructed manually with acquaintance of the fundamental sphere. Hence, it computes the probability of WSD when polysemy and homonymy is observed using variable elimination (VE) algorithm as a modest and universal inference technique. Probability graphic model with python library outperforms joint probability distribution computation using chain rule and direct method that multiply CPT and sum out variables.
Erroneous Patient Tissue Contaminants in 1574 Surgical Pathology Slides: Impact on Diagnostic Error and a Novel Framework for Floater Management

Context.— Tissue contaminants on histology slides represent a serious risk of diagnostic error. Despite their pervasive presence, published peer-reviewed criteria defining contaminants are lacking. The absence of a standardized diagnostic workup algorithm for contaminants contributes to variation in management, including investigation and reporting by pathologists. Objective.— To study the frequency and type of tissue contaminants on microscopic slides using standardized criteria. Using these data, we propose a taxonomy and algorithm for pathologists on “floater” management, including identification, workup, and reporting, with an eye on patient safety. Design.— A retrospective study arm of 1574 histologic glass slides as well as a prospective study arm of 50 slide contamination events was performed. Using these data we propose a structured classification taxonomy and guidelines for the workup and resolution of tissue contamination events. Results.— In the retrospective arm of the study, we identified reasonably sized benign tissue contaminants on 52 of 1574 slides (3.3%). We found size to be an important parameter for evaluation, among other visual features including location on the slide, folding, ink, and tissue of origin. The prospective arm of the study suggested that overall, pathologists tend to use similar features when determining management of potentially actionable contaminants. We also report successfully used case-based ancillary testing strategies, including fluorescence in situ hybridization analysis of chromosomes and DNA fingerprinting. Conclusions.— Tissue contamination events are underreported and represent a patient safety risk. Use of a reproducible classification taxonomy and a standardized algorithm for contaminant workup, management, and reporting may aid pathologists in understanding and reducing risk.
Counting and Characterization of Platelets Using Mathematical Morphology

Platelets, medically also termed as “Thrombocytes” are diminutive, achromatic fragments of cell in our vital fluid, blood, that form clots and prevents or stops bleeding. Various techniques and methodologies have been introduced and implemented apart from the conventional microscopic techniques to detect and count them, as platelets are one of the important cells in the bloodstream. The previously introduced techniques cannot determine the irregular and overlapped cells. This project proposes the Otsu Threshold Algorithm as an efficient algorithm that returns an exclusive intensity threshold that separates the pixels into two classes which are named as foreground and background. Mathematical Morphologies like dilation and erosion will help to smoothen the edges of the binary image from the otsu threshold output. For detecting circles or improper shapes, an algorithm named Circular Hough Transformation or CHT using various extraction techniques in digital image processing will be implemented. As a result, this project will classify and enumerate the platelet cells according to their shape and size (circular, non-circular, size, overlapped and negligible) and determine the count of the cells using Circular Hough Transformation (CHT) in raw microscopic images with a classification accuracy of 97%.
Review of the State-of-the-Art of Data Gloves

Human-machine interaction has been the focus of recent research, with data gloves as one of the approaches gaining popularity for their high accuracy and convenience. This paper summarizes the latest research status of data gloves with a focus on the area of glove-based gesture recognition. The core technology of gesture recognition is described in detail from data processing to classification, and a quantitative analysis of the recent research is conducted. We found that though studies on applications and algorithms are the mainstream, the hardware design also accounts for a pretty large proportion of about 30%. Moreover, the number of gestures, subjects, and algorithms for majority of relevant studies has been summarized.
Machine learning approaches to detect online harassment using bag of words

Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Twitter Facebook Reddit LinkedIn Tools Icon Tools Reprints and Permissions Cite Icon Cite Search Site Citation Noor Amer, Ban N. Dhannoon; Machine learning approaches to detect online harassment using bag of words. AIP Conference Proceedings 2 February 2023; 2457 (1): 040009. https://doi.org/10.1063/5.0118599 Download citation file: Ris (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 ContentAIP Publishing PortfolioAIP Conference Proceedings Search Advanced Search |Citation Search
Steganography algorithm based on public key cryptosystem

Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Twitter Facebook Reddit LinkedIn Tools Icon Tools Reprints and Permissions Cite Icon Cite Search Site Citation Najlae Falah Hameed Al Saffar; Steganography algorithm based on public key cryptosystem. AIP Conference Proceedings 2 February 2023; 2457 (1): 020011. https://doi.org/10.1063/5.0118555 Download citation file: Ris (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 ContentAIP Publishing PortfolioAIP Conference Proceedings Search Advanced Search |Citation Search
Formats and Codecs

An MP3 audio file can be identified by its “.mp3” file extension. Similarly, an MP4 video file can be identified by the “.mp4” extension. The file extensions of multimedia files do not provide any kind of surety about the format. Even the format name is merely a notion. If you need to process audio and video content, you need to go beyond file extensions. You need to be familiar with multimedia concepts such as containers, codecs, encoders, and decoders. In this chapter, you will gain some basic information about all that and more.
The Role of Libraries and LIS Professionals in Changing the Open Access Landscape during COVID-19 Crisis

The COVID-19 has made us realize the importance of “R4: information must reach the ‘right information’ ‘in right time’ ‘to right person’ and ‘through a right channel or platforms’ and eventually witnessed to the era of ‘teach for all’ ‘learn by all’ ‘learn without a wall, without teacher’ ‘service on finger’ and ‘information on devices.’ The unexpected outbreak of COVID-19 infections in 2020 has a global impact without any man-women, aged-child, color, rich-poor, literate-illiterate, and other geographical and ethnographical differentiation. As non-profit service centers of libraries, geographic locality and size are learning the facts about this global health crisis, informing the different communities and adapting community-centric emerging services and facilities to meet changing community information needs and expectations during these health emergencies. It is time to realize and remind the social communities of the essentialness of libraries and their library professionals to collect, organize, preserve, and disseminate information through different virtual platforms to fulfill the remotely scattered library users due to the shocking spread of COVID-19 deadly disease. This paper researcher has demonstrated the role of libraries and library professionals in selecting, collecting, organizing, preserving, and disseminating information along with challenges of library professionals to restricting library services, facilities, and other ‘user-centric’ functional activities to move on user door-steps and fulfill existing information needs.
A Learnable Graph Convolutional Neural Network Model for Relation Extraction

Relation extraction is the task of extracting the semantic relationships between two named entities in a sentence. The task relies on semantic dependencies relevant to named entities. Recently, graph convolutional neural networks have shown great potential in supporting this task, wherein dependency trees are usually adopted to learn semantic dependencies between entities. However, the requirement of external toolkits to parse sentences poses a problem, owing to them being error prone. Furthermore, entity relations and parsing structures vary in semantic expressions. Therefore, manually designed rules are required to prune the structure of the dependency trees. This study proposed a novel learnable graph convolutional neural network model (L-GCN) that directly encodes every word of a sentence as nodes of a graph neural network. Then, the L-GCN uses a learnable adjacency matrix to encode dependencies between nodes. The model offers the advantage of automatically learning high-order abstract representations of the semantic dependencies between words. Moreover, a fusion module was designed to aggregate the global and local semantic structure information of sentences. Further, the proposed L-GCN was evaluated on the ACE 2005 English dataset and Chinese Literature Text Corpus. The experimental results confirmed the effectiveness of L-GCN in learning the semantic dependencies of a relation instance. Moreover, it clearly outperformed previous dependency-tree-based models.
An Efficient Way of Hybridizing Edge Detectors Depending on Embedding Demand

Edge detection-based image steganography schemes usually embed data in edge pixels only.However, some schemes embed data in non-edge pixels as well.In that case, the schemes embed more bits in the edges than in the smoothed areas.In all cases, the schemes perform large changes in a tiny area of the image during small data embedding.Detecting such local modifications is comparatively easier for a steganalyzer.As a result, it is preferable to distribute bits evenly across the image.Again, the schemes struggle to hide large messages in a cover image due to the algorithmic approach of hiding a fixed number of bits per pixel.In this research, we have overcome that problem by employing multiple edge detectors in generating a resultant edge image.Depending on the embedding needs, we have checked whether a single edge detector is sufficient to help in conceiving all bits or not.If it is not possible for a single-edge detector, we have hybridized them.Hybridization of edge images is performed either by logical AND, OR or OR with dilation.When the message size is very small, we have generated the resultant edge image by doing a logical AND operation among the edge images.That strategy have reduced the number of edge pixels as well as helped in distributing the to-be-embedded bits over the image in a more evenly manner.Similarly, to meet a larger embedding demand, we have performed a logical OR operation among the same edge images to increase the number of edge pixels.Even, to meet more embedding demand, we have dilated the OR-resultant image.These processes were carried out dynamically in the research according to an embedding demand.The experimental results deduce that this scheme embeds 92.37%, 73.92%, 74.78%, and 9.60% more bits than four competing methods.Similarly, for small embedding demand, the proposed scheme demonstrates 37.45%, 46.87%, 44.21%, and 55.56% higher PSNR values than the others.Moreover, statistical analyses state that this scheme demonstrates stronger security against attacks.
It's time to define the pet homelessness crisis

There have been few serious attempts to understand how many companion animals there are globally, let alone how many are left homeless. Accurate data are essential to manage and address any crisis, yet even our definition of what constitutes a ‘homeless’ companion animal has been unclear. If we are to address the pet homelessness crisis, we must first define it.
Agile Methodology Brazilian Workshop - Agile Brazil: A Decade of Software Testing

Due to concerns with agile testing scenario in Brazil, this paper presents the mapping (2010–2019) and analysis of the research on software testing published on Agile Methodology Brazilian Workshop (WBMA), Agile Brazil throughout these years. Such work aims to verify the development, the diversity of papers related to software testing and arising from the concerns with the studies of the testing scenario in agile methods in Brazil; this paper presents the mapping (2010–2019) and analysis on the development of research in software testing in papers published in the Brazilian Workshop on Agile Methods (WBMA), Agile Brazil. The paper used systematic literature review practices, enabling qualitative and quantitative analysis of the collected evidence. This effort aims to verify the growth, the diversity of approaches linked to the use of testing in the broader context of agile methodologies and to make notes on the profile of the papers, given the strengthening of studies in the area in the last decade, in spaces of academic discussion and applications in industry. We conclude that the number of publications has been growing over the years. However, the absolute number of papers published in all event editions is still not so expressive, especially considering the large number of software testing topics that exist or need improvement. As a result of this work, some points emerge about the relationship of authors and institutions with software testing research.
The Effectiveness of Using REACT Model for Teaching Literary Texts to EFL Preparatory School Students

Literature is generally used in English language teaching for the development of knowledge about the language . REACT (Relating, Experiencing, Applying, Cooperating and Transferring) model has been used as a model in teaching English literary texts . This study aims at investigating its effectiveness for teaching literary texts to EFL preparatory school students through:&#x0D; 1-assessing the average level of the 5th year preparatory school students' achievement in English literary texts.&#x0D; 2-finding out whether there is any significant difference between students' achievement of the experimental group and that of the control group in the posttest.&#x0D; 3- finding out whether there is any significant difference between the students' achievement at the recognition level and that at the production level of the posttest.&#x0D; 4- finding out whether there is any significant difference between the experimental group's achievement in the pretest and posttest.&#x0D; A sample of ninety EFL fifth year preparatory school students have been randomly selected from Al-Kansaa Preparatory School for Girls during the academic year(2021-2022), that represents (73.17) of its original population and divided into two equal groups, i.e. experimental and control groups. Both groups have been equalized in their age, their parents’ educational achievement, and their previous year achievement in English.&#x0D; The required data has been collected and analyzed statistically. The obtained results indicates that REACT model is more effective than using the conventional method for teaching literary texts. Finally, the study ends up with some conclusions and recommendations.