Reviewerly/exHarmony huggingface dataset:
DIGITAL EDUCATIONAL ENVIRONMENT AND DIGITAL TEXTBOOKS

The need for the latest pedagogical technologies in the modern educational environment requires updating educational and methodological products and creating digital forms of textbooks of digital age.This article discusses the issues of definition, requirements, technology and methodology for the development of digital educational resources.In particular, we are talking about the creation of a new digital textbook on the history of modern French literature, which would practically and informatively meet the requirements of modern teaching and education.It is emphasized that the digitalization of higher education does not change its standards by the replacing its content with the digital one: the latter does not in any way affect the subject content of curricula.The digital learning environment is a complement to, but not a replacement for, the traditional learning mode.
Influence of Media Globalization on Denigration of National Values in African Children

Media globalization has eased the availability of entertainment for African Children, particularly via cable-TV. Considering the power of media as socialization_agent, this research appraised proliferation of children shows on DsTv/GoTv via the lens of African cultural particulars, particularly respect for elders and authoritative parenting. Using media_content_analysis methodology and discourse_analysis, findings link global_media influence as the mechanism for the denigration of African values in children, with Social_cognitive_theory framing the implications. Recommendations are stronger national broadcast regulations for reinforcement of family values via television to preserve the identity of society, providing local content for global export and contributing to glocal media content.
Implementation of Graph Colouring Technique in Crime Science

This paper deals with the new method of graph colouring technique implemented in crime science. The graphical investigation uses the elements of graph theory to identify the suspects involved in unlawful act. The research paper focuses on the idea of graph colouring technique in crime problem which provides mathematical clarity for investigation in identifying the suspects. This method helps the crime scientist to expedite the investigation process to reduce time factor in decision making.
An Adaptive Whale Optimization Algorithm Guided Smart City Big Data Feature Identification for Fair Resource Utilization

World improvement is the development of every single province of the world. Smart city implies changed hardware to adjusted individuals. Smart cities have the most indispensable part in altering distinctive regions of human life, touching segments like transportation, wellbeing, vitality, and instruction. Productively to make measurements to improve distinctive smart city benefits huge information frameworks are put away, prepared, and mined in smart cities. For the change and course of action of huge information applications for smart cities, different difficulties are faces. In this paper, we propose a wrapper display based ideal element recognizable proof calculation for ideal use of assets given highlight subset age. Nine component determination techniques used for compelling element extraction. At last, which includes best add to the ideal usage of assets got by means of a novel element recognizable proof calculation made by the application out of a Whale Optimization Algorithm with Adaptive Multi-Population (WOA-AMP) system as inquiry process in a wrapper display driven by the notable relapse demonstrate regression model Random Forest with Support Vector Machine (RF-SVM). Our proposed calculation gives the exact method to choose the most agreeable feature blend, which prompts ideal asset usage.
A Simple And Novel Algorithm For State Estimation Of Continuous Time Linear Stochastic Dynamic Systems Excited By Random Inputs

The major goal of this paper is to explore the effective state estimation algorithm for continuous time dynamic system under the lossy environment without increasing the complexity of hardware realization. Though the existing methods of state estimation of continuous time system provides effective estimation with data loss, the real time hardware realization is difficult due to the complexity and multiple processing. Kalman Filter and Particle Filer are fundamental algorithms for state estimation of any linear and non-linear system respectively, but both have its limitation. The approach adopted here, detect the expected state value and covariance, existed by random input at each stage and filtered the noisy measurement and replace it with predicted modified value for the effective state estimation. To demonstrate the performance of the results, the continuous time dynamics of position of the Aerial Vehicle is used with proposed algorithm under the lossy measurements scenario and compared with standard Kalman filter and smoothed filter. The results show that the proposed method can effectively estimate the position of Aerial Vehicle compared to standard Kalman and smoothed filter under the non-reliable sensor measurements with less hardware realization complexity.
Efficient DWT-based SVD Watermarked 3D Video Transmission over MC-CDMA Wireless Channel

Abstract Abstract Three-Dimensional Video (3DV) communication through wireless channels suffers from bit-streams losses. Therefore, the efficient performance of 3DV transmission techniques over wireless networks is a considerable hot research topic. A high compression ratio must be introduced to meet future bandwidth restriction for optimized 3DV transmission. Unfortunately, the compressed 3DV bit-streams are more sensitive and vulnerable to packet losses. In this paper, we propose the application of chaotic Baker interleaving with equalization and convolution coding for efficient Discrete Wavelet Transform (DWT)-based Singular Value Decomposition (SVD) watermarked 3DV transmission over a Multi-Carrier Code Division Multiple Accesses (MC-CDMA) wireless channel. Firstly, the compressed 3DV frames are watermarking using the DWT+SVD watermarking process. After that, chaotic interleaving is applied to minimize the channel effects on the transported bit-streams and it also adds an encryption to the transported 3DV frames. To test the performance of the proposed hybrid techniques; several experiments on different (DWT+SVD) watermarked 3DV frames have been tested. The experimental results confirm that the received watermarked 3DV frames still have high Peak Signal-to-Noise Ratios (PSNRs) and efficient watermark extraction is possible.
The Effect of Knowledge Sharing on Auditor Innovation Ability Using Work Ethics as Moderating Variable

This study aims to determine the effect of knowledge sharing on auditor innovation capabilities that are moderated by work ethic.This research was conducted at the Public Accountant Firm in the city of Bandung.Respondents in this study were external auditors.The research method used is research verification survey with a quantitative approach.Sampling was determined by nonprobability sampling technique with a type of purposive sampling, with a sample of 34 respondents.The data analysis technique used is moderate regression analysis.. The results of the tests that have been done show that knowledge sharing has a significant effect on the auditor's innovation ability.Other test results show that work ethic does not have a significant effect on the ability of innovation and work ethic not to moderate the effect of knowledge sharing on the auditor's innovation ability.Based on these studies, auditors who have high innovation capabilities will be able to provide new ideas that can benefit clients.But in making innovations auditors must remain on track, not violate boundaries, and not violate existing rules.It is expected that this research can provide knowledge to auditors to be able to improve their abilities, especially in the audit field so they can maximize their duties as auditors.
GI support of geological exploration of non-ferrous metal ore deposits

Geoinformation technologies are applied, without exaggeration, in all spheres of human activity, and the geological industry is no exception. Geoinformation systems in geology help to solve a number of practical problems. Geologists specializing in mineral exploration use a variety of data sets to search for new, cost-effective deposits, from geological maps, hyperspectral aerial photographs and multispectral satellite imagery to databases of various formats. The geographic information system is an ideal platform for combining such heterogeneous information and its subsequent analysis. The article describes the experience of the national mining company of the Republic of Azerbaijan CJSC AzerGold in the use of geographic information systems in the exploration of non-ferrous metal deposits using the example of the development of the Filizchay and Aghyokhush deposits. The authors considered production problems, described the problems that arise at the stage of exploration and proposed methods for solving them, the need for the integrated use of information systems in exploration when searching for deposits of non-ferrous metals is noted. A database structure has been developed for the purpose of geological exploration of non-ferrous metal ores, including sections such as topography, geochemistry, geophysics, structural geology. The structure of geoinformation support for geological exploration of non-ferrous metal ores is proposed, which combines the functionality of geographic information systems (GIS) and mining geological information systems (MGIS). The stages of geoinformation processing of initial data are illustrated, on the basis of which a geological exploration strategy was formed at the Filizchay pyrite-polymetallic deposit, and then the optimal places and number of wells, coordinates, directions and angles of incidence of wells were determined quickly and with high accuracy, as well as the resource potential was specified. The role of interpolation methods in determining the primary exploration wells in the exploration of the Agyokhush gold deposit is disclosed.
Living Sounds: Live Nature Sound as Online Performance Space

This paper presents Living Sounds, an internet radio station and online venue hosted by nature. The virtual space is animated by live sound from a restored wetland wildlife sanctuary, spatially mixed from dozens of 24/7 streaming microphones across the landscape. The stationâs guests are invited artists and others whose performances are responsive to and contingent upon the ever-changing environmental sound.Â Subtle, sound-active drawings by different visual designers anchor the one-page website. Using low latency, high fidelity WebRTC, our system allows guests to mix themselves in, remix the raw nature streams, or run our multichannel sources fully through their own processors. Created in early 2020 in response to the locked down conditions of the COVID-19 pandemic, the site became a virtual oasis, with usage data showing long duration visits. In collaboration with several festivals that went online in 2020, programmed live content included music, storytelling, and guided meditation. One festival commissioned a local microphone installation, resulting in a second nature source for the station: 5-channels of sound from a small Maine island. Catalyzed by recent events, when many have been separated from environments of inspiration and restoration, we propose Living Sounds as both a virtual nature space for cohabitation and a new kind of contingent online venue.
Understanding the Relationship of Age, ICT Literacy and Knowledge Sharing among Faculties

Information and Communication Technology (ICT) is a buzz word in each and every walk of life. Everything nowadays is amalgamated with the proficient use of ICT and not surprisingly the engineering teaching institutes are one among them. It is the need of the time that the engineering faculties should be well-equipped with the ICT literacy. ICT literacy can depend on a number of variables and age; an important demographic variable no doubt can affect the faculties ICT Literacy (knowledge, access and competence). In the meantime, being ICT literate is not sufficient for a knowledge intensive sector like engineering institutes, it is also how well the faculties share this knowledge in the organization with other stakeholders. In this backdrop this study is a descriptive study with an objective to know the relationship of age with the ICT literacy and Knowledge Sharing (KS) behaviour of the faculties teaching in the engineering institutes. A total sample size of 230 is collected from the five eastern states of India, through online convenience sampling method. The descriptive and correlational analysis showed that although age has significant and positive relationship with knowledge of ICT but it doesn’t have any significant relationship with the ICT literacy and KS behaviour in the institutes.
Suffix trees

The suffix tree is a fundamental data structure when it comes to string algorithms. It captures the structure of a string via all the string’s suffixes and uses this structure as the basis of many algorithms. We will only use it for searching, where it provides linear search for a pattern after a linear preprocessing of the string we search in.
PENGARUH MODEL KOOPERATIF TIPE JIGSAW TERHADAP HASIL BELAJAR PKN DI SEKOLAH DASAR

The recearch is aimed to know about the influence of using of cooperative jigsaw type model toward the result of PKn student in grade V at SDN 10 sapiran Bukittinggi. The research design of the research is quasy exsperimental design. Sample of the research is class VA and VB. The coubting result of research of data that used is t test founded t count &amp;gt; ttable 2, t-test 2,7577 &amp;gt; 2,0128 at α level of 0.05. So that, it can be concluded that there is a significant influence in using cooperative model in jigsaw type toward the result of student’s PKn study in grade V SDN 10 Sapiran Bukittinggi
Kleinberg’s Hyper-Richness Based Fuzzy Partition Clustering for Efficient Bi-Temporal Data

Clustering is the process used for partitioning the total dataset into different classes of similar objects. The group contains knowledge about their members and also helps to understand the structure of the dataset very easily. Clustering the bitemporal data is one of the major tasks in data mining since the bitemporal datasets are very large with various attribute counts. Hence the accurate clustering is still challenging tasks. In order to improve the clustering accuracy with less complexity, Kleinberg’s Hyper-richness Bitemporal property based fuzzy c means partition Clustering (KHBP-FCMPC) technique is introduced. The KHBP-FCMPC technique partition the bitemporal dataset into number of possible groups with an improved performance rate based on a distance metric. At first, the ‘c’ numbers of clusters are initialized. The KHBP-FCMPC technique uses the core data point module and authority sector module to minimize the execution time of clustering the data points. Core data point module served as the centroid of the cluster. Each cluster contains one core data point. After that, the distance is computed with the membership function. The authority sector module assigns the data points into the cluster with minimum distance. After that, the centroid is updated and the process iterated until the convergence is met. Finally, the Kleinberg’s Hyper-richness Bitemporal property is applied to verify the total dataset equals the partition of all the data points. This property used to group the entire data points into the cluster with higher accuracy. Experimental evaluation is carried out using a temporal dataset with different factors such as clustering accuracy, false positive rate, time complexity and space complexity with a number of data points. The experimental results show that the proposed KHBP-FCMPC technique increases the bitemporal data clustering accuracy with less false positive rate, time complexity as well as space complexity. Based on the results observations, KHBP-FCMPC technique is more efficient than the state-of-the-art methods.
An Integrated Methods for Refined Facial-Image Retrieval using Sift and Click-Through Data

In the modern era, the emergence of social networking sites paved the way to the people to upload lot of images online. Social sites like Instagram and Flickr allow users to add semantic information to the images in the form of tags. Often these tags are the firsthand semantic data for retrieving the images from the Internet. When a user searches for images in the web, the images with tags relevant to user query are retrieved. Most of the time, these semantic data are not relevant to the content of the image and hence the user gets irrelevant images in contrast to their intended search. This is more common in facial image search. In this paper, we propose an integrated approach to refine the relevance of retrieved facial images. Using Scale Invariant Feature Extraction (SIFT) the facial features of semantically most relevant image and click-through data of all the retrieved images are used to rank and present a meaningful search result. Along with facial features and click through information, the co-occurrence of related tags is also considered. Also we propose the construction of inverted index structure to improve the search performance.
An Effective Bicubic Convolution Interpolation-Based Iterative Luma Optimization for Enhancing Quality in Chroma Subsampling

&lt;div&gt;Traditionally, prior to compressing an RGB full-color image, for each converted 2x2 CbCr block B&lt;sup&gt;CbCr&lt;/sup&gt;, chroma subsampling only downsamples B&lt;sup&gt;CbCr&lt;/sup&gt;, but without changing the luma block B&lt;sup&gt;Y&lt;/sup&gt; at all. In the current research, a special linear interpolation-based, namely the COPY-based, chroma subsampling-first luma modification (CSFLM) study has attempted to change the luma block for enhancing the quality of the reconstructed RGB full-color image. In this paper, a fast and effective nonlinear interpolation, namely the bicubic convolution interpolation (BCI), based iterative luma modification method for CSFLM is proposed. In our iterative method, a BCI-based distortion function and its convex property proof are first provided. Next, based on the proposed convex distortion function, a pseudoinverse technique is applied to obtain the initial luma modification solution, and then an iterative method is proposed to improve the initial luma modification solution. Based on five testing image datasets, namely the IMAX, Kodak, SCI (screen content images), CI (classical images), and Video datasets, the thorough experimental results have demonstrated that on the newly released Versatile Video Coding (VVC) platform VTM-12.0, our iterative luma modification method achieves substantial quality, execution-time, and quality-bitrate tradeoff improvements when compared with the existing state-of-the-art methods.&lt;/div&gt;
Characteristics of Dental Note taking: A material based Themed analysis of Swedish Dental Students

Abstract Background: The transition from upper secondary to higher education and from higher education to professional practice requires that students adapt to new literacy practices, academic and professional. However, there is a gap of knowledge regarding literacy practices in dental education. Therefore, the aim of this study was to identify what characterizes dental students’ notetaking and secondarily to determine what dental students express regarding their notetaking. Methods: To analyze students' perspectives about the purposes of notetaking and to examine their written notes in depth, three volunteer students, out of the 24 students that voluntarily and anonymously handed in their notes, were interviewed. The three undergraduate dental students that participated in this material-based, semi-structured interview study, framed within a New Literacy Studies approach, were on their third year (6 th semester). The focus of these material-based interviews was on each student’s notes. Questions prepared for semi-structured interviews were open-ended and allowed for individual follow-up questions related to the interviewee’s answer. To analyze the outcome of the interviews a thematic analysis was used. Results: From the material-based interviews eight themes that relate to what , how and for what purpose students write were discerned. These eight themes include professional vocabulary, core content as well as clinical examples that belong to what students read and write; multimodal accentuation as well as synthesis that belong to how students read and write; and mnemonic strategies, academic purposes, and professional purposes that belong to for what purpose students read and write. Conclusions: Findings from the interviews indicate that the digital development, offering a variety of available tools, has expanded the notion of notetaking. This study identified that dental students’ notetaking has changed during their education from initially being synchronous, to also include multimodal and asynchronous writing, making notetaking more of a writing practice. Further, students’ writing practices seem to be motivated by their knowledge formation in relation to a subject matter, but also in relation to their experiences during clinical training. Although, our hypothesis was that the main purpose of notetaking and writing was to pass their course examinations, this study showed that students that were half-way through their dental education, are aware that literacy practices are for learning for their future profession, and not only for passing their exams.
Guidelines for the Development of Immersive Virtual Reality Software for Cognitive Neuroscience and Neuropsychology: The Development of Virtual Reality Everyday Assessment Lab (VR-EAL), a Neuropsychological Test Battery in Immersive Virtual Reality

Virtual reality (VR) head-mounted displays (HMD) appear to be effective research tools, which may address the problem of ecological validity in neuropsychological testing. However, their widespread implementation is hindered by VR induced symptoms and effects (VRISE) and the lack of skills in VR software development. This study offers guidelines for the development of VR software in cognitive neuroscience and neuropsychology, by describing and discussing the stages of the development of Virtual Reality Everyday Assessment Lab (VR-EAL), the first neuropsychological battery in immersive VR. Techniques for evaluating cognitive functions within a realistic storyline are discussed. The utility of various assets in Unity, software development kits, and other software are described so that cognitive scientists can overcome challenges pertinent to VRISE and the quality of the VR software. In addition, this pilot study attempts to evaluate VR-EAL in accordance with the necessary criteria for VR software for research purposes. The VR neuroscience questionnaire (VRNQ; Kourtesis et al., 2019b) was implemented to appraise the quality of the three versions of VR-EAL in terms of user experience, game mechanics, in-game assistance, and VRISE. Twenty-five participants aged between 20 and 45 years with 12–16 years of full-time education evaluated various versions of VR-EAL. The final version of VR-EAL achieved high scores in every sub-score of the VRNQ and exceeded its parsimonious cut-offs. It also appeared to have better in-game assistance and game mechanics, while its improved graphics substantially increased the quality of the user experience and almost eradicated VRISE. The results substantially support the feasibility of the development of effective VR research and clinical software without the presence of VRISE during a 60-min VR session.