Reviewerly/exHarmony huggingface dataset:
Secure ReversibleImage Data Hiding (SRIDH) Using LSB Prediction Method

Protecting sensitive data in public networks from prying eyes of unauthorised users has emerged as a critical concern in recent years. To safeguard the confidentiality of digital media, one of the most difficult methods to implement is data concealing. Techniques for the reversible concealment of data in digital photographs have been proposed by us. Textual information, such as that pertaining to weapon designs, map layouts, and satellite specifications, must be sent to and received by the majority of research and defence institutions. In order to complete this task, you will need a text file as well as an image file. In addition to the message, we will have a cover image file. After then, the number of pixels contained within the cover image will be taken into account. That is where each individual piece of the secret text will be embedded. This method will be repeated until the final snippet of the secret text is found. Following this procedure, the data will be masked by the image. After that, we will give this picture file to our client, who will be provided with a reverse process to use in order to extract the original text from the image. In the realm of cyber security, there are a plethora of innovative procedures and algorithms that can hide data. Each method has its own significance, and the least significant bit method is the one that was utilised for this method (LSB).
Automatic Correction of Text Using Probabilistic Error Approach

Continuous research effort has been paid to automatic spelling correction. Although each study provides a quick introduction to the problem, there is a paucity of work that would combine the analytical foundations and provide a summary of the approaches investigated thus far. our study has chosen spelling correction publications from 1991 to 2019 that were indexed in Scopus and Web of Science. The first group follows a predetermined set of guidelines. The second group makes use of an extra context model. The third subset of the survey’s computerized spelling checkers can modify its model to fit the situation. The summary tables identify each system’s application domain, language, context model, and string metrics. To fix the publicly available construction data, this work attempts to create an automated data correction system. The handling of the construction data is hampered by its unstructured character. Due to different types of users, lengthy system operation, and substantial pretraining time, the information management system has a lot of data in inconsistent formats or even erroneous data. The conversion of the construction data into a machine-readable format requires a lot of time and work.
AUGMENTING LANDMARKS: EXTENDING “PLACES” IN THE HYBRID CITY

Several recent technological advancements are substantially altering how we interact with urban spaces.The existing physical space as we know it now encompasses a plethora of emerging realities into which we shift in and out, resulting in what is called Hybrid Spaces.Augmented Reality (AR) today gives way to forms of hybrid realities that are accessible through our handheld devices, and which allow us to engage with our physical reality in a new way.These devices allow us to access and view digital information that is saturating our urban spaces, and yet appear invisible to the naked eye.When this information is localized, it can be used to augment physical space with virtual overlays.These augmentations may become physically linked to the environment, establishing virtual landmarks that could only be accessed via these handheld or wearable digital portals through digital applications.This gives way to new forms of engaging in real-time with our socio-cultural daily activities.The literature shows that urban space is reimagined through augmented reality (AR) which plays a significant role in introducing new augmented "places" supporting our physical ones as hybrid realities.This paper, accordingly, investigates the notion of location-based AR experiences on landmarks in the urban space in accordance with our spatial memory, and how augmented reality through mobile devices, plays an important role as a gateway between our physical space and the virtual one.It also seeks to understand how these augmentations might insert and employ symbolic or personal meanings to the space, based on our different interpretations.In doing so, we conducted an integrative analytical review of the most recent literature, to study the forms of augmentations in multiple cities, and how they are used as agents in our spatial experience.The paper then introduced a framework that could be used to assess users' satisfaction and the design considerations of the AR spatial experience.Finally, the paper adopts a few recent AR practices to be assessed by the proposed framework.
A FRAMEWORK FOR CREATING A HYBRID EXPERIENCE FOR NFT ARTWORKS THROUGH 3D PRINTING

Technology has become a fundamental part of our environment, yet the borders between the physical and virtual realms become even more blurred.The introduction of the Metaverse is one of the most recent and notable innovations.It, just as any other technological advances, adapts to evolution in user needs serving as a link between the real and digital realms.While people can buy goods and services with a certain currency in the physical realm, cryptocurrencies and non-fungible tokens (NFTs) are used for transactions in the Metaverse.NFT provides customers a certificate of ownership, which means that their virtual commodities or assets such as lands or objects cannot be replicated.They may also be used to represent social standing, just like tangible goods and services.It has become increasingly common to come across museums displaying artworks or artists who sell their artworks as Non-fungible tokens (NFTs) on digital platforms such as Rarible, Mintable or OpenSea.This research discusses the 3D printability of NFTs and proposes a framework in order to create a hybrid experience for 3D printed NFT artworks.The results have shown that 3D printing of NFTs provided users/customers a hybrid experience in both realms, maintaining the artworks' uniqueness and rarity, proof of ownership, as well as physical copies in hand.Moreover, the artists who were afraid of publicly displaying their artworks for the concern of being copied have created 3D printable designs that enabled them to easily and safely promote their designs to the public.
Peer Review Statement

All papers published in this volume have been reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing. • Type of peer review : Single Anonymous • Conference submission management system : Morressier • Number of submissions received : 175 • Number of submissions sent for review : 140 • Number of submissions accepted : 84 • Acceptance Rate (Submissions Accepted / Submissions Received × 100) : 48 • Average number of reviews per paper : 2 • Total number of reviewers involved : 13 • Contact person for queries : Name : Novizar Nazir Email : nazir_novizar@ae.unand.ac.id Affiliation : Andalas University, Indonesia
Research Library of Tomsk State University and the mythologeme of the development of Siberia: The main milestones (1878–1934)

The Research Library of Tomsk State University, which is now one of the largest university libraries in Russia, was established simultaneously with the university. Along with the first museums, the Botanical Garden and other university departments, it was almost immediately incorporated into the process of developing the transboundary Siberian space. To date, the history of the TSU Research Library is presented in generalizing and individual works dedicated to its employees, funds and collections, practices of interaction with readers and partners. At the same time, it seems relevant to identify the role of the Research Library as an actor involved in the process of constructing images of Siberia. This is due to the institutional involvement of the library in the complex of interactions within and around the university that has developed over decades. This involvement also makes the library a “memory space”, participating in the formation of images of the past, present and future at various levels – material, symbolic and functional. The aim of this work is to reveal the features of the formation of images of Siberia in the narrative about the Research Library, which is part of the substantiating myth about the first Siberian University. The lower chronological limit was chosen due to the fact that it is in the first years of the existence of the library that the core of its fund is formed and the main patterns of perception are laid; the upper limit because in 1936 the university library was given the status of a “research library”, which marked a key milestone in its development as the largest university library in Siberia. In the pre-revolutionary period, key ideas were laid down that were reflected in the construction of the image of Siberia as a region rich in various resources suitable for study – the library as part of the university that accumulates and preserves heritage, including the Siberian one. Conventionally, these ideas can be represented as binary structures: Siberia as an undeveloped, wild territory – the library as a tool for its development, cultivation; Siberia as a region with rich various resources suitable for exploration – the library as part of the university accumulating and preserving the heritage, including the Siberian one. In early Soviet times, there was a further development and discovery of ideas related to the perception of Siberia and the library as an instrument for exploring the region and familiarizing it with world culture and history. The library is a tool for collecting information, preserving and saving book collections of the past, and bibliographic ordering of the scattered Siberian information space.
The Use of Gesture to Overcome Misunderstanding in Teaching English

Gesture is a type of non-verbal communication that is very influential in teaching and learning activities and interactions between teachers and students. It is not only can convey the speakers’ intention more specifically and adequately, clarify the teaching instruction, encourage the students’ interest, maximize English teaching’s goal but also can help improve the students’ skill in speaking, writing, reading and listening . This study aims to improve students' speaking, writing, reading, listening and interest in English lessons through the use of gestures at SMA Negeri 1 Batang Natal.The method used was descriptive qualitative. The subjects were 2 teachers and 25 students of 11th grade of SMA Negeri 1 Batang Natal The research instruments used were interviews and observations. The results of this study suggests that the use of movement has positive and negative sides for students. The positive side is that the teacher must be able to use the right movements according to the needs of their students. Creating a comfortable atmosphere and considering the most effective method so that students are activated in participating the lessons. While negative side was using too many movements or being too serious when teaching would not create a comfortable classroom atmosphere.&#x0D;
THE INTERNAL RULES OF THE EXAMPLE DATABASE DESIGN

One of the internal rules of the example-based translation is the dependence of the translation quality on the length and representation of translation examples. These are managed by an example database, for which the linguist should answer two questions when s/he intends to design it: (1) what is the representation chosen for the translation example? and (2) what are the possibilities to generalize the translation examples stored in the database? In this paper my intent is to propose two answers, in fact – a synergetical research direction for Romanian, English and French language. I will consider the representation of the translation examples as depedency trees and I will generalize them by means of the semantic information described by Levin’s verb classes.
Prospects for Research on New-Form International Chinese Language Textbooks

Textbook is one of the “three teachings”, and it is an important basis and carrier of teaching. The new form of textbooks is a product of the intelligent age and an important embodiment of the modernization of teaching materials. In the context of the intelligent era, the development of new forms textbooks is an important content of academic concern. We found that there are not many studies on new forms of international Chinese textbooks, and most of the textbooks have not yet entered the stage of integrated construction. The three-dimensional textbooks such as Great Wall Chinese are still an exception. In this regard, we believe that it is necessary to take the creation of three-dimensional teaching materials as the course, closely follow Chinese Proficiency Grading Standards for International Chinese Language Education, and multi-party construction teams go hand in hand to implement the dynamic update of international Chinese teaching materials resources.
Encrypting the Colored Image by Diagonalizing 3D Non-linear Chaotic Map

Nowadays data transmission takes up several other forms as compared to simple text data; images are one of the prominent modes of data transmission. The transmission of digital data in the form of images results in image encryption and decryption is of prime interest for recent research work. Protecting the image during transmission from several attacks and unauthorized access is very important. Images are of the most eye-catching class of information in the security field where efficient encryption and decryption mechanisms need to be devised. To enhance the security of the system and to decrease the probability of attacks on image encryption a large key space-based approach is designed. This proposed technique uses a 3D nonlinear chaotic map by using the diagonalization of the cubic map and logistic map. The proposed system enhances overall security by utilizing the randomness of the trilinear interpolation chaotic system.
AI Generated Art.

Human-robot interaction (HRI) through the practice of different types of art is bringing to the table new perspectives on innovative interactions where the cooperation between artists and robots not only deliver original works of art but also novel communication mechanisms beyond spoken and written-based forms. Generative art, that is, artworks mediated by the interaction with computers in codes and art generated by artificial intelligence (AI), are having a profound impact in different fields of the arts, including visual arts, performative arts, music and literature. This research proposes to establish some fundamental logics behind the interaction between artists and AI-art generators in order to advance in the understanding of how the intersection of art and technology can transform the ways in which humans relate to robots and its impacts in the arts, the artistic community and their identities and community building.
A temporally quantized distribution of pupil diameters as a new feature for cognitive load classification

In this paper, we present a new feature that can be used to classify cognitive load based on pupil information. The feature consists of a temporal segmentation of the eye tracking recordings. For each segment of the temporal partition, a probability distribution of pupil size is computed and stored. These probability distributions can then be used to classify the cognitive load. The presented feature significantly improves the classification accuracy of the cognitive load compared to other statistical values obtained from eye tracking data, which represent the state of the art in this field. The applications of determining Cognitive Load from pupil data are numerous and could lead, for example, to pre-warning systems for burnouts.
Word Familiarity Classification From a Single Trial Based on Eye-Movements. A Study in German and English

Identifying processing difficulty during reading due to unfamiliar words has promising applications in automatic text adaptation. We present a classification model that predicts whether a word is (un)known to the reader based on eye-movement measures. We examine German and English data and validate our model on unseen subjects and items achieving a high accuracy in both languages.
Area of interest adaption using feature importance

In this paper, we present two approaches and algorithms that adapt areas of interest (AOI) or regions of interest (ROI), respectively, to the eye tracking data quality and classification task. The first approach uses feature importance in a greedy way and grows or shrinks AOIs in all directions. The second approach is an extension of the first approach, which divides the AOIs into areas and calculates a direction of growth, i.e. a gradient. Both approaches improve the classification results considerably in the case of generalized AOIs, but can also be used for qualitative analysis. In qualitative analysis, the algorithms presented allow the AOIs to be adapted to the data, which means that errors and inaccuracies in eye tracking data can be better compensated for. A good application example is abstract art, where manual AOIs annotation is hardly possible, and data-driven approaches are mainly used for initial AOIs.
One step closer to EEG based eye tracking

In this paper, we present two approaches and algorithms that adapt areas of interest. We present a new deep neural network (DNN) that can be used to directly determine gaze position using EEG data. EEG-based eye tracking is a new and difficult research topic in the field of eye tracking, but it provides an alternative to image-based eye tracking with an input data set comparable to conventional image processing. The presented DNN exploits spatial dependencies of the EEG signal and uses convolutions similar to spatial filtering, which is used for preprocessing EEG signals. By this, we improve the direct gaze determination from the EEG signal compared to the state of the art by 3.5 cm MAE (Mean absolute error), but unfortunately still do not achieve a directly applicable system, since the inaccuracy is still significantly higher compared to image-based eye trackers.
Facial Biometrics-Based Attendance Tracking System

Abstract: Facial attendance using face recognition and detection technology is a modern method of recording attendance based on facial features. This method is commonly used in automated attendance management systems and is efficient in tracking employee or student attendance without physical interaction. Face recognition has numerous applications such as security, surveillance, and human-computer interaction. This research aims to compare the performance of two popular face recognition techniques: HOG and KNN. The HOG algorithm extracts feature from an image using pixel intensity gradients while the KNN algorithm matches a test image with the most similar image in the training dataset. The study was conducted using the Labeled Faces in the Wild dataset available at https://vis-www.cs.umass.edu/lfw/. The results of the investigation show that the KNN algorithm outperforms the HOG algorithm in terms of accuracy. This research provides valuable insights into the effectiveness of different face recognition algorithms, helping researchers and developers choose the most suitable algorithm for their specific requirements.
A Communication Translator Interface for Sign Language Interpretation

Abstract: Sign language is an essential means of communication for deaf and hard-of-hearing individuals. However, unlike spoken languages which have a universal language, every country has its own native sign language. In India, the Indian Sign Language (ISL) is used. This survey aims to provide an overview of the recognition and translation of essential Indian sign language. While significant research has been conducted in American Sign Language (ASL), the same cannot be said for Indian Sign Language due to its unique characteristics. The proposed method focuses on designing a tool for translating ISL hand gestures to help the deaf-mute community convey their ideas. A self-created ISL dataset was used to train the model for gesture recognition. The literature contains a plethora of methods for extracting features and classifying sign language, with a majority of them utilizing machine learning techniques. However, this article proposes the adoption of a deep learning method by designing a Convolution Neural Network (CNN) model for the purpose of extracting sign language features and recognizing them accurately. This CNN model is specifically designed to identify complex patterns in the data and use them to efficiently recognize sign language features. By adopting this approach, it is expected that the recognition of sign language will improve significantly, providing a more effective means of communication for the deaf and hard-of-hearing community.
Social Media Platform having Bully Free Environment

Abstract: One of the most pernicious consequences of social media Is the Rise Of Cyberbullying And Tends To Be More Evil than traditional bullying because online records are usually available Lived on the Internet for a long time and are hard to reach Control. This article presents a three-phase algorithm. Called BullyNet to detect cyberbullying on the Social media Communication network. Use your bullying tendencies to make powerful suggestions Instructions for building a cyberbullying signed network (SN). Analyze Social media to determine their relevance to cyberbullying Considering the context in which social media exist in succession Optimize your bully score. Also, suggest centrality Measures detect and display cyberbullying from cyberbullying SNs Better than other existing metrics
Retracted: Nursing Care Systematization with Case-Based Reasoning and Artificial Intelligence

[This retracts the article DOI: 10.1155/2022/1959371.].
Linguistic support for the formation of a consolidated information resource of social memory institutions

In the article it is analyzed the role of linguistic means as the most important, system-forming elements of any information and library system, including a consolidated information resource of social memory institutions. Metadata of library digital electronic resources, archives and museums is characterized as a fundamental linguistic support of consolidation process of these resources and simultaneously as means of human and machine interaction in the development and operation of a consolidated information resource. It is outlined the criteria for choosing linguistic means of the development of machine-readable descriptions of information resources for the consolidated information resource of social memory institutions in a smart city