Reviewerly/exHarmony huggingface dataset:
Measurement of highly reflective surface compensating correlated error by sampling window

Wavelength-tuning Fizeau interferometer has been widely applied to measurements of optical surfaces. However, when measuring highly reflective surfaces, such as silicon wafer surfaces, a coupling error between higher harmonics and phase-shift miscalibration, can cause a significant systematic error in the calculated phase. In this study, a new 11-frame phase-extraction algorithm is derived for the suppression of the coupling error. The 11-frame algorithm was visualized in the frequency domain and complex plane, and its compensation capability was confirmed by numerical error analysis. Finally, the surface shape of the silicon wafer was measured by applying the 11-frame algorithm and Fizeau interferometer.
Guest editors’ preface

This paper is concerned with approximation properties of polynomially enriched wavelet systems, so-called quarklet frames. We show that certain model singularities that arise in elliptic boundary value problems on polygonal domains can be approximated from the span of such quarklet systems at inverse-exponential rates. In order to realize these, we combine spatial refinement in the vicinity of the singularities with suitable growth of the polynomial degrees in regions where the solution is smooth, similar to adaptive hp-finite element approximation.
Grounded Theory Analysis of the Awareness of Participation and Behavior in Virtual English Classes

본 연구는 비대면 영어회화 수업에 참여한 대학생들의 인식과 행동을 살펴보고 이와 같은 현상을 확인하고 이를 개념화하기 위해 근거이론을 사용하여 현상학적으로 분석하였다. 본 연구에서는 대학생들이 경험한 비대면 영어회화 수업에 대한 인식과 행동의 변화에 대한 현상에 대해 심층 한 자료에 근거하여 귀납적 접근으로 이론을 도출하였다. 그 과정에서 개방, 축, 선택 코딩의 3단계 분석을 거쳐 통합 틀을 제시하였다. 그 결과 학생들은 다양한 종류의 활동을 통해서 상호적인 의사소통을 하려고 노력하였으며, 비대면 수업 초기에 느꼈던 회의감은 학습동기와 자아실현의 의미를 찾는 방향으로 바뀌어 감을 알 수 있었다. 또한, 상호 전략은 양방향 의사소통의 방법으로부터 학생들의 학습동기를 향상시키기 위해 필요함을 알 수 있었다. 이와 같은 결과를 통해 교수와 학생들 간의 소통의 의미가 다름을 알 수 있었고, 상호간의 공감적 이해가 있어야 함을 알 수 있었다.This study aims to structuralize and identify how the awareness of participation and behaviors of college students in virtual English conversation classes changed. To analyze the awareness of college students in virtual English conversation classes and their behavioral changes, grounded theory was used, and data were collected from in-depth interviews based on the inductive approach and theorizing aforementioned phenomena. For this, an integrated framework was suggested based on core categories with open, axis, and selective coding. Findings showed that, 20 students made an effort in interactive communication through the virtual lessons, and their feelings changed from skepticism towards their virtual-learning college experiences to seek their learning motivation and the meaning of self-realization in virtual English conversation classes. In addition, interactive strategies were required in seeking bi-directional communicative methods to improve students’ learning motivation. It was also found that the students needed to realize how their methods of communication were different from others and to have an empathic understanding of others.
Nigeria – Twitter Ban

Africa Research Bulletin: Political, Social and Cultural SeriesVolume 58, Issue 6 p. 23185A-23185B Full Issue Nigeria – Twitter Ban First published: 30 July 2021 https://doi.org/10.1111/j.1467-825X.2021.10030.xRead the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume58, Issue6July 2021Pages 23185A-23185B RelatedInformation
MUSICAL DRAMATICS OF CHILDREN'S PUPPET SHOW

The musical dramaturgy of a child's puppet show is a unique phenomenon, characterized by brevity, conciseness, minimalism of forms and structures. It relies on the generally accepted laws of theatrical productions, which include the exposition, the outset, the culmination, the denouement, and so on. Specific features of the children's puppet show are manifested in the plot-sense, figurative and genre aspects, as well as in the means of musical and artistic expressiveness. The basis of the puppet show is the genre of the fairy tale, which in the form accessible to the children reveals the main meaning of the artwork. Through the genre of fairy tales, children distinguish good deeds, truth and lies, learn about living and inanimate nature, people, fairy-tale characters, fantasize, ponder, memorize. The imagery that are revealed in the puppet show are actual to the child. The musical side of the performances contributes to his perception. Particular importance is the theater dramaturgy and musical dramaturgy of the children's puppet show. They contribute to the organization of the musical and artistic consciousness of the child, who first gets acquainted with the theater world. The musical dramaturgy of the children's puppet show is based on song and folklore genres. The musical and artistic expressiveness is based on the melody of the word and the structural and rhythmic patterns of verbal speech. The analysis of the integral dramaturgy of the children's puppet show testifies to the birth of original, original genre models – a fairy tale with music, a musical fairy tale and an interactive performance. Children's puppet show is close to the psychology of children's perception. At the same time, it has musical, artistic, teaching and educational significance. Puppet show captivates and helps children enter into real life with the help of artistic-figurative and musical-figurative experiences and impressions. In this process, dramaturgy, as well as various means of musical and artistic expression, a decisive role in the play. Moreover, successful dramaturgic decisions of the play control the perception and consciousness of the audience and lead it to the expected results for the authors of show. With respect to the children's audience, the result should be considered not entertainment, but educational and educational success. It is here that the main meaning of children's puppet shows is concluded, which through the artistic influence form and develop the personality of a small person.
A Verifiable Lossless Multiple Secret Images Sharing Scheme

In the recent years, the researchers have proposed several schemes for sharing multiple secret images using less number of shares through different operations in order to save storage memory and network bandwidth consumption. However, the existing schemes suffer from one or more of the following limitations, viz. no verification of reconstructed secret images, no support for resistance against loss of single share, support for sharing only 2 secret images, incompatibility for sharing single secret image, lossy reconstruction of secret images and no support for sharing all types (binary, grayscale and color) of images. The proposed scheme overcomes these existing limitations, and shares \(u-1\) secret images in \(v\) (\(v\ge 2\)) shares out of which at least \(u\) (\(2 \le u\le v\)) shares are required to reconstruct all \(u-1\) secret images. The operations are performed in galois field \( GF(2^{8}) \) during shares generation and secret images reconstruction. The verification of the reconstructed secret images is done by using a random authentication image. The theoretical analysis, comparison and experimental results are provided to indicate the validity, merits and implementability of the proposed scheme.
Tight Bound on NewHope Failure Probability

<monospace>NewHope</monospace> Key Encapsulation Mechanism (KEM) has been presented at USENIX 2016 by Alkim <i>et al.</i> and was one of the lattice-based candidates to the post-quantum standardization initiated by the NIST. However, despite the relative simplicity of the protocol, the bound on the decapsulation failure probability resulting from the original analysis is not tight. In this work we refine this analysis to get a tight upper-bound on this probability which happens to be much lower than what was originally evaluated. As a consequence, we propose a set of alternative parameters, increasing the security and the compactness of the scheme. However using a smaller modulus prevent the use of a full NTT algorithm to perform multiplications of elements in dimension 512 or 1024. Nonetheless, similarly to previous works, we combine different multiplication algorithms and show that our new parameters are competitive on a constant time vectorized implementation. Our most compact parameters bring a speed-up of <inline-formula><tex-math notation="LaTeX">$17\%$</tex-math></inline-formula> (resp. <inline-formula><tex-math notation="LaTeX">$11\%$</tex-math></inline-formula> ) in performance but allow to gain more than <inline-formula><tex-math notation="LaTeX">$19\%$</tex-math></inline-formula> over the bandwidth requirements and to increase the security of <inline-formula><tex-math notation="LaTeX">$10\%$</tex-math></inline-formula> (resp. <inline-formula><tex-math notation="LaTeX">$7\%$</tex-math></inline-formula> ) in dimension 512 (resp. 1024).
Stopping leaks with digital solutions

Under increasing pressure to conserve water reserves and cut leaks, many water companies are turning to digitisation to deliver a solution. Cloud-based technology will enable them to revolutionise their systems and processes, and think and work smarter.
Health Care-Related eCrime Up More Than 2000% During COVID-19

Biomedical Safety & Standards 51(13):p 97-98, July 15, 2021. | DOI: 10.1097/01.BMSAS.0000756524.17668.50
Convergence time analysis of Asynchronous Distributed Artificial Neural Networks

Artificial Neural Networks (ANNs) have drawn academy and industry attention for their ability to represent and solve complex problems. Researchers are studying how to distribute their computation to reduce their training time. However, the most common approaches in this direction are synchronous, letting computational resources sub-utilized. Asynchronous training does not have this drawback but is impacted by staled gradient updates, which have not been extended researched yet. Considering this, we experimentally investigate how stale gradients affect the convergence time and loss value of an ANN. In particular, we analyze an asynchronous distributed implementation of a Word2Vec model, in which the impact of staleness is negligible and can be ignored considering the computational speedup we achieve by allowing the staleness.
Darrell Whitley Awarded as the 2022 Evolutionary Computation Pioneer

Prof. Darrell Whitley has received the 2022 IEEE Pioneer Award on Evolutionary Computation from the IEEE Computational Intelligence Society "For early contributions to the practical implementation and theoretical understanding of evolutionary algorithms."
NFCS: An Efficient Neural Framework for Cold Start Recommendation

In this article we have illustrated an efficient and effective neural framework referred to as NFCS for cold start recommendation. In this neural network, the average ratings will be as the input, and the missing ratings will be regarded as the dropout rate for the neural network. Therefore, in the output layer ratings will be reconstructed, which could provide an high performance solution for cold start problem. Experimental results also demonstrate that NFCS could outperform state-of-the-art PMF and IRCD-ICS over real life datasets.
PDF Classification Using Logistic Regression and Latent Dirichlet Allocation

Over the past few years, the classification of documents has been a challenging task. For document classification, no effective method or structured process has been developed so far to assign suitable labels to a large set of documents. Hence there is a need to develop an efficient and accurate method for the classification of PDF documents. The paper proposes a novel method which is capable of classifying PDF documents into most appropriate class and subclass. The proposed framework uses Machine learning with logistic regression classifier as a supervised approach along with Latent Dirichlet allocation (LDA). A combination of two different datasets has been used, the first dataset is ARXIV data of more than 31000 research paper meta data dated between 1992 and 2017 and the second one is created by the authors on their own. The method achieved a significant accuracy comparable with the existing approaches.
Text Processing

Scripting languages are great for whipping up scripts that work with text, extract information, render it in some format, or manipulate it in other useful ways. In this chapter, we see how to extract information, identify differences between files, and render static pages to HTML. We will see many basic Raku techniques, as well as be introduced to useful modules in the ecosystem.
SmartPLS mediation moderation model: Integrated the entrepreneurial performance of textile-based small-medium enterprises

The core purpose of this study is to explore the effects of knowledge management practices and the dynamic capabilities of entrepreneurs on the entrepreneurial performance of small-medium enterprises (SMEs). This study gathered the required information using a structured survey from textile-based small-medium enterprises and applied a structural equation model to analyze 486 valid responses from Pakistan. The empirical results show that knowledge management practices, such as knowledge sharing behavior, innovative capacity, and absorptive capacity, are significantly correlated with developing entrepreneurs’ dynamic capability, thus improving their performance. At the same time, this study also confirms that opportunity recognition positively affects the relationship between the dynamic capability and entrepreneurial performance of SMEs. In addition, the findings of this study guide business practitioners and policymakers in strategy formulation envisioned to encourage entrepreneurs who contribute to the country’s sustainable economic growth. This study contributes to the existing literature of knowledge management practices with knowledge sharing behavior, innovative capacity, absorptive capacity, and more intended to involve the role of opportunity recognition.
Machine Learning Approach to Recognize and Classify Indian Sign Language

In these present circumstances, the future for differently abled students is a big question mark. As the education is turning entirely toward online in which the differently abled students are the most affected ones because their principal way of learning was physical, i.e., using gestures. In this present scenario of pan-epidemic siege, the value of time cannot be ignored for the students who are progressive citizens for a better future. During this intricate time, there is a need to sustain the pace of education for every child and the most important for the differently abled children who are always more enthusiastic in taking on the challenges of life. We at this time, pledge to do our best for the rightful e-learning. In the era of technology, providing education on digital platforms, our idea is to provide some assistance in the field of education technology. The idea is to train a model which will help us to identify and classify Indian Sign Language in the most reliable way. In the previously proposed solutions, the user is restricted to have a definite background so as their model could work accurately. In our system, that limitation is withdrawn. The user can be anywhere, and yet our model would perform the most desirable. We are using OpenCV for pre-processing and a machine learning model is used to recognize hand gestures. This model can then be employed in an Android application for greater perks.
Conceptual model for improving maneuverability in borewell rescue devices

This paper deals with mechanisms for improved maneuvering into borewells for rescue operations. The constraints observed in existing borewell devices, such as the size of the borewell, the orientation of the child and the ease of maneuverability were analyzed. The work consists of mechanisms for anchoring, module&#x2019;s translation and rotation, gripper actuation and control. The improved borewell rescue device contains modules that can maneuver through the confined space, stabilize the sway, and aid the gripper to reach the child safely.
STUDENT YOUTH CAREER BUILDING STRATEGY

Abstract n this scientific work, the possibilities and potential of building a career for student youth are studied, a strategy for the application of professional and educational skills through the prism of opportunities and socio-economic relations in society is being worked out. The aim of the work is to develop an effective learning strategy and improve their own skills for student youth in the process of career growth. To achieve the goal, a career development plan for student youth is formed, highlighting the main stages of this development process. A list of subjects of career management and their functions is also formed, taking into account the age characteristics of building a career and defining a system of tasks and values for each generation of citizens.Student youth is a social group of people of a certain age, united by the desire to acquire new knowledge for their further application in building their future life path. The difficulties of perception, learning and building a career depend on the inherent and defining features of this generation, actively combining technologies of digital and physical spaces, which makes us take a fresh look at building a career strategy for people belonging to this generation. The scientific basis of the work is Russian and foreign monographs, opinions and assessments of experts in the field and regulatory legal acts of the Russian Federation.
Saliency Detection Framework Based on Deep Enhanced Attention Network

In recent years, RGB-D based salient object detection has received increasing attention. Most of the previous models are based on early fusion and late fusion to fuse the input RGB-D images. Such an approach cannot effectively explore the complementary information on RGB-D images, and thus information loss and incomplete fusion can occur. To address these problems, we propose a novel framework for RGB-D salient object detection (DEANet). Our framework uses Siamese networks to extract features of RGB-D images to mine the similarity between the two modal data onto a shared-weight manner. Specifically, we propose the Channel-Spatial Fusion Block (CSF) for feature condensation of the extracted Depth features, which can capture the spatial and channel dependencies on RGB-D images from both spatial and dimensional perspectives, thus better mining the complementary information between the two modal images and enables the thoroughness and completeness of the features for which useful information is extracted. In addition, we propose an edge-optimization loss (EL) to obtain smoother salient object edges by supervising the edges of the objects. Comprehensive experiments on four popular evaluation metrics show that our DEANet is able to generate RGB-D saliency detectors with high robustness and generalization ability. In particular, DEANet outperforms thirteen current state-of-the-art methods in terms of four evaluation metrics on six challenging datasets.
A Spatial-Temporal Adaptive Video Denoising Algorithm

Nowadays, video media is gaining increasing preference by the general public, and video denoising methods are paid lots of attention. In this paper, we present a novel Spatial-temporal Adaptive Denoising Algorithm, which adaptively changing denoising strategies according to the scene change of the micro block. The proposed method automatically chooses bilateral filter for a scene changing block and temporal filter for a relatively static block. Furthermore, our method adopts a fast motion estimation algorithm, which reduces the computational cost by adaptively adjusting the searching strategy based on the texture of micro blocks. Especially, the problem of the failure of temporal filter is alleviated with the scene changing frames. Experiments demonstrate that our method achieves satisfactory visual quality and PSNR (Peak Signal Noise Ratio) improvement.
Blue Nodules: Use of Acoustic Emission Technology for an Inline Characterisation of Hydraulic Material Streams

A major global political issue and a raw materials policy priority of the European Union is securing reliable and sustainable long-term access to raw materials. This endeavour is based on the trends in population growth, increasing prosperity, technical progress and the resulting increasing demand for raw materials. Consequently, increasingly complex deposits are moving into focus to meet the global demand for rare raw materials.
Pelatihan Pembuatan Bahan Ajar Speaking Berbasis Rekayasa Faktor Kognitif (Task Complexity) bagi Guru-Guru SMA/SMK Di Kabupaten Pringsewu

Task complexity-based learning approaches have been widely adopted in countries especially where English is a foreign language, Chinese, Japanese, Arabic, Iranian, and Korean. However, most English teachers do not yet understand the method of learning English based on task complexity so they lack confidence in applying the method.. Therefore, this community service activity aims to increase insight and knowledge about the development / creation of a speaking learning model based on cognitive factor engineering (task complexity). This activity will target English teachers at high school / vocational school in Pringsewu Regency and is expected to improve their professionalism to improve the quality of the English learning process, especially speaking. This activity will be carried out with lecture methods, discussions, practices, and simulations that will begin with a pre-test and end with a post-test. Based on initial and final abilities, there are quite real differences before and after the training is done. To that end, this training has been able to improve the insight and Manufacture of Teaching Materials Based on Cognitive Factor Engineering (Task Complexity). Some participants showed that the enthusiasm and belief of the participants that the Manufacture of Speaking Teaching Materials Based on Cognitive Factor Engineering (Task Complexity) has a positive impact to develop students' ability to master their English learning in the classroom.
Preface

Le Van Trung, Vo Le Phu, Armando A. Apan, Marc Descloitres, Tanita Suepa, Nguyen Nhat Huy, Ho Tuan Duc, Ha Quang Khai, Pham Tan Thi (Editors) Environment, Resources, and Earth Sciences Proceedings of the International Conference on Environment, Resources, and Earth Sciences 2021 (ICERES 2021) List of Environment, Resources, and Earth Sciences, Preface, List of Scientific Committees are available in this pdf.
Reduce Computational Complexity! Inspiration from Flies

Inspired by the clustered typologies of arthropod corneal nanostructures, we study optical preprocessing. We use topological defects to enhance optical encoders. These encoders enable shallow neural networks to process visual data with reduced computational complexity.