Reviewerly/exHarmony huggingface dataset:
Impact of low cost data &amp; calling in telecom services on the lifestyle of students

In the course of recent years there is an upsurge of utilization of web on cell phones in human existence. Web clients can speak with any piece of globe, to shop on the web, to involve it as a mean of schooling, to work from a distance and to manage monetary exchanges. Web get its own upheaval human everyday existence (science, training, data, diversion) taking out the distances and offering prompt and effectively admittance to data and correspondence. The endless conceivable outcomes that are advertised We are directing an observational review among 200 understudies to discover the effect of minimal expense information and approaching the way of life of understudies. The review is led over a term of 90 days. The paper manages the recent concern of way of life change related with accessibility of web for minimal price. It endeavors to sum up key useful result for understudies just as some significant ominous results. Observational Study.
The Public Libraries in India: A Scenario

This paper discuss some of the problems of public libraries and their role in digital era with some possible solution for improving their states. In India majority of people live in rural areas and new technologies are not accessible from remote villages, therefore a wide-gapes has been evolved between the libraries of knowledge haves and knowledge have-notes. Today internet and web technologies open up new ways of interactive communication between public libraries and the civil societies. So we can say a proposal for ICT driven public libraries for Indian states with suitable library extension programmes to help the entire rural as well as urban community especially unprivileged masses.
Study on Incident Detection and Management of Vehicular OBD Data on Blockchain

A majority of the research on accident detection systems involves increasing the precision at which it can be detected. This approach proposes a test-bed for a vehicular incident detection system that uses real time data collected from OBD -II port of automobiles and later passed on to Edge devices within vehicles to detect an accident or other rash driving behavior patterns. Machine learning algorithms are developed and deployed onto edge devices like Jetsonnano for real time pattern recognition. Once an incident like accident or rash driving is triggered, the data is cached and written onto Inter Planetary File Systems (IPFS) a distributed file storage system and put onto Ethereum Blockchain for later analysis and documentation by various stakeholders like police, RTO, law, forensic team etc. Blockchain acts as an immutable ledger providing proof of all incidents. Further using the obtained data, dashboards of the incident can be generated for further visualization and understandability to the concerned stakeholder
Periodic Census with Graphical Representation and Authentication

With advances in information and communication technology, online transaction over the Internet has become an integral part of day-to-day life. An online census is the web- based application which allows respondents to complete the census via the internet. This paper aims at upgrading and integrating the efficiency of census data collection management system. Traditionally, census data collection demands an authorized enumerator, who collects the census data manually which is time consuming and waste of resource. As enhancement in project, we are working on key aspects i.e. SMS system will be get added to system, and Email service feature will be there. Visual studio is being used as an integrated environment for development of web-based system, were served as the programming language, SQL server served as a relational data base.
Ecology and Biodiversity Ontology Alignment for Smart Environment via Adaptive Compact Evolutionary Algorithm

Smart Environment (SE) focuses on the initiatives for healthy living, where ecological issues and biodiversity play a vital role in the environment and sustainability. To manage the knowledge on ecology and biodiversity and preserve the ecosystem and biodiversity simultaneously, it is necessary to align the data entities in different ecology and biodiversity ontologies. Since the problem of Ecology and Biodiversity Ontology Alignment (EBOA) is a large-scale optimization problem with sparse solutions, finding high-quality EBOA is an open challenge. Evolutionary Algorithm (EA) is a state-of-the-art technique in the ontology aligning domain, and this study further proposes an Adaptive Compact EA (ACEA) to address the problem of EBOA, which uses semantic reasoning to reduce searching space and adaptively guides searching direction to improve the algorithm's performance. In addition, we formally model the problem of EBOA as a discrete optimization problem, which maximizes the alignment's completeness and correctness through determining an optimal entity corresponding set. After that, a hybrid entity similarity measure is presented to distinguish the heterogeneous data entities, and an ACEA-based aligning technique is proposed. The experiment uses the famous Biodiversity and Ecology track to test ACEA's performance, and the experimental results show that ACEA-based aligning technique statistically outperforms other EA-based and state-of-the-art aligning techniques.
The Level of Digital Competence of Students as a Condition for the Readiness of Future Teachers to Use Digital Technologies in the Educational Process

The article analyzes Russian and foreign approaches to establishing the relationship between the level of digital competence of students as a condition for the readiness of future teachers to use digital technologies in the educational process. &#x0D; The purpose of this study is to diagnose the level of digital competencies among students and interpret the data obtained. &#x0D; Based on the analysis of Russian and foreign experience in the development of digital competencies among university students, a questionnaire was developed to assess the level of formation of digital skills and abilities. Data collection was carried out through an online survey of pedagogical university students using a structured questionnaire. The data obtained allowed us to conclude that the students of the pedagogical university demonstrated a sufficiently high level of digital competence. &#x0D; Future teachers demonstrated high results in such competencies as the use of digital solutions for effective communication with both teachers and students; the creation of their educational materials and assignments on subjects using a computer; modification and exchange of digital materials; the use of the Internet to search for information resources, comparison, evaluation and selection of digital resources; knowledge of the basics of digital security; the use of digital technologies at different stages of training and in the implementation of various organizational forms of training (lectures, practical classes, consultations, tests, exams, individual and group work, including on a project), including for self-organization and self-control and creative (productive) solutions of educational tasks.
Ingenious AI Visual Identification

In our software Ingenious AI Visual Identification using facial recognition we&#x0027;re primarily focused on stating the remaining platform for attendance, in which a person can first provide their required non-public information and be enrolled for automatic attendance via our software. As a result, we want to make this system software well-suited for any organization on the route to replacing the old and out-of-date attendance-taking system with our new output. We&#x0027;re essentially that specialize in citing the remaining platform for attendance wherein a man or woman can to begin with feed their required non-public facts and get them enrolled for the Automatic Attendance via our Software. There through we have the desire to make this software program well matched for each and every Organization on the way to update the vintage and outdated attendance taking process with our new output.
Rereading the Narrative Paradox for Virtual Reality Theatre

We examined several key issues around audience autonomy in VR theatre. Informed by a literature review and a qualitative user study (grounded theory), we developed a conceptual model that enables a quantifiable evaluation of audience experience in VR theatre. A second user study inspired by the &#x2018;narrative paradox&#x2019;, investigates the relationship between spatial exploration and narrative comprehension in two VR performances. Our results show that although navigation distracted the participants from following the full story, they were more engaged, attached and had a better overall experience as a result of their freedom to move and interact.
Emo-Tts:Parallel Transformer-based Text-to-Speech Model with Emotional Awareness

One of the pillars of human social interaction is the ability to communicate one&#x0027;s feelings and emotions. In recent years, there has been a fast growth in research on the subject of emotional voice synthesis. Regardless, the results leave something to be desired in terms of the clarity of the emotions expressed. In this study, we propose Emo-Tts, a parallel transformer-based text-to-speech (TTS) model modified to model emotions in speech. We use a conformer-based architecture that has been augmented with speaker and emotion embedding. An external speech emotion recognition (SER) model is utilized to incorporate classification loss and perceptual loss into the TTS model, which improves emotional expressiveness and allows it to train in a self-supervised way when no emotion ground truth is available. Improving speaker embedding is critical for training hundreds of speakers with minimal valid data, allowing us to generate realistic-sounding emotional voices with only minutes of audio. By combining effective emotion and speaker embedding, we may be able to model emotions for speakers with unseen emotions. Achieving strong emotional expressiveness with a small amount of viable data could significantly improve many fields, including automated audio-book reading and possibly replacing voice actors. We achieve an accuracy of 80&#x0025; on a combination of 5 datasets in our SER task.
The correlation algorithm based on jittering structured light with multiple reflection imaging

Abstract As a three-dimensional reconstruction method, the structured light formed by multiple reflection of neutral beam splitter mirror can effectively solve the problem caused by high reflectivity. In order to obtain more stripes, the jittering mechanism is used in the system. In addition, the linear algorithm can not make full use of the information between different structured light, which will produce a large error and inaccurate result. To solve this problem, we propose a correlation algorithm. In this algorithm, we use two structured light as the independent variables to obtain spatial information, and a related items is calculated to take full advantage of the information between different structured light. Experimental results show that the overall measurement error is reduced by 20-30% and the repetition accuracy of the system reaches 0.02 mm.
Using breakout rooms as a teaching strategy to develop english oral production in online classes

Online education is becoming more widely recognized as a tool for educational modernization. Due to the Covid-19 virus, however, this e-learning method began to spread; unknowingly, students and teachers at all levels watched in astonishment as their homes were transformed into classrooms, breaking the entire old system of regular instruction. Through the experiences of students and English teachers, this study intends to examine the impact of breakout rooms on boosting oral English production. This research was done in Unidad Educativa Franciscana San Jose, Milagro Ecuador. It was applied to second and third courses as Technical as science specialization. Based on the shyness and little students’ class participation in the online English classes. The activities were used in the first, second and third parts in the academic year of 2021-2022. In this case, look for a different way to encourage pupils and teachers to use the Zoom platform break out rooms to motivate to better learning and teaching approach. There were many topics based on student’s preferences. A survey with multiple choice and close questions were used to determine the level of satisfaction generated by the interaction in the tasks completed by students in speaking lessons. This work analyses the result of different topics used by teachers to develop oral skill production.
Comparison of bio-statistics software platform: SAS, SPSS, and R language

With the development of society in bio-statistics, the amount of data that data analysts need to process has become heavier. In this regard, the choice of auxiliary platforms for data processing has become more critical. This article will mainly make a preliminary analysis of SAS, R language, and SPSS and conclude that a data processing platform is more suitable for students or scholars before entering enterprises or large-scale projects.
Formation and Diagnostics of Reading Literacy in the Russian Language Lesson

The article presents and comments on a set of tasks for the formation of reading literacy of students in the Russian language lesson. Answers and criteria for evaluating tasks are given. The results of practical application and diagnostics of the results of completing tasks for the formation of reading literacy, identified by the author in the course of participant observation, are presented and summarized.
Enhancing the Convergence Speed and Accuracy of Particle Swarm Optimizers through Adaptive Learning

Particle swarm optimization (PSO) comes from a family of swarm optimization techniques that work iteratively to obtain an optimum solution for single or multi objective systems. For instance, teacher learner-based optimization (TLbO) when combined with PSO, fuses swarm intelligence behaviour with teacher-learner relationship for speeding up the learning process. However most of these algorithms do not modify the original PSO learning factors, due to which their performance is limited. In this work, a novel adaptive learning-based TLbO inspired PSO model is proposed. This model aims at improving the convergence speed and reduce solution error via adaptively learning from previous iteration error and modifying social and cognitive learning behaviour of the underlying PSO. The proposed model is 20&#x0025; more efficient in terms of convergence delay, and 25&#x0025; efficient in terms of final solution error when compared with existing highly efficient TLbO-PSO models.
Self Co-articulation Removal in Mid-air Gesticulated Trajectories via a Sequence-to-Sequence Based Classification Approach using LSTM

The inability of the acquisition device to differentiate the actual gesticulation (true stroke) from intentional movements (self co-articulation) results in the formed trajectory to incorporate both strokes. The presence of self co-articulated strokes results in confusion among the gesticulated characters at the recognition stage. Removal of these self co-articulated strokes needs to be invariant to motion characteristics (velocity/acceleration), as individuals may gesticulate at their arbitrary speed. Hence, LSTM based self co-articulation approach is proposed by considering the input gesticulated trajectory as a sequence. Motion invariant features were extracted by selecting the co-ordinates of either x-axes/y-axes based on initial gesticulation. It was observed that the proposed approach of sequence-to-sequence classification at the co-ordinate level is able to detect the self co-articulated points with a mean error rate of ∼4.03. A relative improvement of 1.82% is achieved over the state-of-the-art models used for self co-articulation removal. The proposed approach is able to overcome the dependency on hard threshold rules/motion characteristics and make the system speed invariant
MultiModal Sarcasm Detection: A Survey

Deciphering sarcasm can be arduous at times as the literal meaning is contrary to what is intended. Sarcasm in very simple terms is a form of expression where one expresses himself/herself while trying to poke fun, take a jibe or simply make a joke as the intended meaning is in stark contrast to what has been actually said. Sarcasm detection is a trickier task as some background information or the context is required in order to get the intended meaning. In today's fast paced world where social media is scaling great heights day by day, sarcasm detection has become a need of the hour as it can have a lot of use cases and can eventually take drastic forms like bullying, harassment etc. In that case detection of sarcasm on various social media platforms is one of the important issues which needs to be handled. So far most of the work has been done using only textual data, but as per the present day scenario where users can express themselves via multiple modes of data, in order to understand the message clearly it is not enough to focus on just texts as other modes can provide important clues that aren't clear from the text. In this paper we will explore various researches in the field of sarcasm detection using multimodal data. We will analyze different datasets and go through the various methodologies proposed. In the end, we show a comparative analysis of the results from various models which use accuracy and F1-Score as metrics to measure the performance.
Capture the Flag Based Assignment Algorithm for Tracking Task of Multi-UAVs

In order to solve the problem of real-time target allocation in the multi-UAVs task for cooperative tracking the moving targets on ground, based on the behavior model of capture the flag, this paper proposes a dynamic assignment algorithm, which has fast convergence performance, for cluster UAVs. Based on satisfaction and total flight distance, the proposed algorithm constructs the assignment target function, and the optimal value of the target function is achieved quickly and the uniform saturation tracking is realized for the target group through the behavior model of grabbing flags. Finally, compared with traditional genetic algorithm, the simulation results show that the algorithm has a significant improvement in convergence speed and single assignment imply operation speed with the increase of the number of assigned targets and cluster UAVs
Research on Intelligent Target Tracking Algorithm Based on MDNet under Artificial Intelligence

Target tracking is an important subject in computer vision technology, which has developed rapidly in recent ten years, and its application have become wider and wider. In this process, it has transferred from a simple experimental tracking environment to a complex real scene where more challenges need to be solved. The rapid development of deep learning has promoted the research progress of digital vision. Target tracking technology is an important foundation of digital vision research, which makes it develop from academia to industry. In this paper, a method of target tracking using MDNet is introduced. Starting with the attention mechanism, two attention mechanisms are added to extract and integrate the better features. Case partitioning is used to reduce the investment of tracking module and minimize the network size during tracking, and its result can be prevented from getting worse. Finally, the experiment is analyzed in detail.
Presentational Copy of the Little-Known Edition of Petrine Age

The archival collection 17 of the Russian State Archives of Ancient Documents (RGADA) contains the only copy in Russia of a rare Petrine age edition. It is the panegyrical poem printed on silk in Hamburg in 1715 by order of Russian resident J.F. Böttiger. The poem is devoted to the two events of the end of 1715: namely, the births of the Tsar’s grandson Petr Alexeevich (the future Peter II) and the younger son Petr Petrovich. The anonymous author’s rejoicing is accompanied by praise of the infants’ mothers and especially the Tsarina Catherine I. Both the contents and the physical execution of the copy provide reasons to classify it as presentational copy intended for the Tsar or member of his family. Earlier, only one copy of the edition was known. It is kept in the Duke Augustus Library in Wolfenbüttel and has been briefly described by M.I. Fundaminski in his review article on Böttiger’s publishing activities. In this article, the author provides a detailed description of the RGADA’s copy, as well as the analysis of its textual content and the circumstances of its creation. The author makes conclusions about Böttiger’s private initiative to publish the panegyric and the reasons for destroying the most part of the print run (which probably included copies on plain paper). The appendix to the article contains the text of the poem.
Stochastic ARX Algorithms: a New Look at Related Keys Analysis

The paper is devoted to the problem of a related keys security analysis of ARX stochastic algorithms. The authors provide a new related key function. A new method to analysis has been developed — non-cyclic analysis. An estimate for the number of cyclic shift operations in such algorithms that are resistant to the non-cyclic analysis has been proved. The application of non-cyclic analysis towards modern stochastic ARX algorithms is considered.
Shadows Behind the Keyboard

Understanding the psychology of cyberattacks is critical for finding ways to minimize their efficacy and harm. Specifically, there are multiple types of attackers, and different attackers have different goals and varied approaches. Through the study of individual differences, we can better understand not only who is most likely to engage in criminal activity in cyberspace but the dispositional tendencies towards specific types of online attacks. Thus, by understanding the psychology of malevolent characters, we can better understand (a) how different attackers go about launching their attacks, (b) who these attackers are likely to target, and (c) the tactics and strategies these different attackers are likely to use.
Media Syi’ar Islam Interaktif Berbasis Animasi 3D di Masa Pandemi

Along with the rise of the Covid-19 outbreak, it is increasingly difficult for humans to convey the symbols of Islam, especially the scholars and preachers. One way to overcome limitations in conveying Islamic symbols is by utilizing interactive media based on 3D animation. The interactive media built can provide information about Islamic symbols with the theme of juvenile delinquency aimed at the general public, especially teenagers. This 3D animation is designed using Blender software. The manufacturing process starts from determining story ideas, making storyboards, object modeling, giving textures, moving animations, dams to rendering. The final result of this animation is an interactive video equipped with background music and sound from the object. Interactive Islamic syi'ar media based on 3D animation during this pandemic as education to overcome juvenile delinquency in the community, so that this media can be useful and useful for teenagers