Reviewerly/exHarmony huggingface dataset:
L2 education in the digital era: post-pandemic prospects

This article considers the general rise in the digitalization of second language (L2) education in the world in general and in Russia in particular. A concrete study of the various novel game-changing digital products and solutions being offered on the L2 education market is made, followed by an analysis of their effectiveness and impact on this market. A special emphasis is made on the impact of the COVID-19 pandemic on the acceleration of the development and adoption of digital products and solutions in L2 education and training, together with the prospects for further advancements in the field. Further, an investigation is conducted on the increasingly complex requirements for linguistic skills among professionals working in various industries in the Russian Federation and across the world, and on how various economic structures have raised their demand for these competencies against the background of the rapid globalization of industry and commerce at large.
Dynamics of psychological readiness of students for entrepreneurial activities

Introduction. The relevance of this topic is in the fact that Russia, a modern rapidly developing country, has a problem in preparing young people for entrepreneurship and forming their entrepreneurial readiness. Modern Russia acutely needs entrepreneurs because a developed economy cannot exist without such a sector as entrepreneurship. The current state of this problem indicates the insufficient knowledge of students' readiness for entrepreneurial activity, as well as the ways of its development. The aim of the work: to diagnose psychological readiness for entrepreneurship before and after the implemention of the author's developed training program “The Fundamentals of Entrepreneurship” aimed for students to acquire the necessary theoretical and practical knowledge, skills and abilities. Materials and methods: a pilot study of psychological readiness was conducted (before training under the program “The Fundamentals of Entrepreneurship” and after it). The study involved 102 students in the humanities, aged 19-23 years (boys and girls). A questionnaire by E.K. Klimova "The diagnostics of psychological readiness for entrepreneurship” was used to collect empirical data. Results: the results allow us to conclude that with initially low readiness of students for entrepreneurship, it is possible to successfully improve this level with the help of the developed program “The Fundamentals of Entrepreneurship”. Conclusion. The practical significance of the study lies in the fact that modern universities can implement the training program “The Fundamentals of Entrepreneurship” in their curricula, and prepare students for future entrepreneurial activities.
Mixed reality depth contour occlusion using binocular similarity matching and three-dimensional contour optimisation

Abstract Mixed reality applications often require virtual objects that are partly occluded by real objects. However, previous research and commercial products have limitations in terms of performance and efficiency. To address these challenges, we propose a novel depth contour occlusion (DCO) algorithm. The proposed method is based on the sensitivity of contour occlusion and a binocular stereoscopic vision device. In this method, a depth contour map is combined with a sparse depth map obtained from a two-stage adaptive filter area stereo matching algorithm and the depth contour map of the objects extracted by a digital image stabilisation optical flow method. We also propose a quadratic optimisation model with three constraints to generate an accurate dense map of the depth contour for high-quality real-virtual occlusion. The whole process is accelerated by GPU. To evaluate the effectiveness of the algorithm, we demonstrate a time consumption statistical analysis for each stage of the DCO algorithm execution. To verify the reliability of the real-virtual occlusion effect, we conduct an experimental analysis on single-sided, enclosed, and complex occlusions. Subsequently, we compare it with the occlusion method without quadratic optimisation. With our GPU implementation for real-time DCO, the evaluation indicates that applying the presented DCO algorithm enhances the real-time performance and the visual quality of real-virtual occlusion.
Upaya Meningkatkan Minat dan Hasil Belajar Siswa pada Pembelajaran IPA dengan Menggunakan Ice Breaking di Kelas IV SDN Puspasari – Jasinga

This study uses the classroom action research (CAR) method where researcher directly into the classroom to carry out teaching activities. This classroom action research consists of Pre-Cycle, Cycle I, and Cycle II. Research data in the form of student learning interests are obtained through the distribution of questionnaires while student learning outcomes data are obtained through tests at the end of each cycle. Based on the research data, it can be concluded that the use of ice breaking can increase student interest in learning science for class IV at SDN Puspasari-Jasinga. This can be seen from the increase in the average results of student learning interest questionnaires. The result of the average value of the student learning interest questionnaire in the pre-cycle were 70%, in the fisrt (fisrt) cycle it got an average of 75% and increased in the second (second) cycle to 83% with a very high description. Meanwhile, with KKM value of 70, it shows that in the precycle 9 students complete this 30% in the less level, in the fisrt cycle 25 students complete 50% are still in the Less level and in the second cycle 26 students complete this 87% in the Very Good level means improvement of 12 completed students. From the explanation above, it can be concluded that the use of ice breaking can increase the interest and learning outcomes of fourth-grade students.
360° cinéma montage versus immersive notion: Sam Esmail and the sensory experimentation in Mr. Robot series.

Montage will allow Cinema to find it’s identity, progressively moving away from arts from which it took root, such as oral tradition, literature or theater. It’s practice will change in time, often linked to technological innovation like television broadcasting or camera enhancement and miniaturization.Understanding this evolution in montage when we are interested in 360° cinema innovation, makes us wonder about the meaning of the concept itself and how it seems to disappear, among the written theory and experimentation on the subject. We must acknowledge that montage as used in a standard frame Cinema it’s not viable in a highly immersive sensory environment. There are numerous reasons to explain this issue, going from troubles linked to internal hearing creating motion sickness to how difficult it becomes to attract public attention towards the zone in the film where action takes place and give sense to narrative.In this text we will mostly focus on Sam Esmail’s work on Mr. Robot series and how he not only proposes an immersive 360° cinematic experience of the series, but he also uses 360° devices to achieve what seams to be technically impossible shots or at least very difficult to achieve in a conventional shooting way. Sam Esmail’s experimentation it’s just an example among others that makes us consider an important renewal in montage domain and storytelling.
CHANTS, RHYMES AND POEMS: IMPORTANCE IN TEACHING- LEARNING PROCESS

Students are learning new skills in second language.It is very hard to teach them speaking or communication.English is as second language in primary classes and students are totally unknown about it.It is very difficult to create interest in learning and taking part in this process, teacher may have many difficulties in student's speaking, especially pronunciation of the words.They don't know the correct pronunciation of the words at beginning so chants, rhymes and poems are most useful to develop speaking skills as well as pronunciation.Chants are the short Mantras of four or six lines poems.It is repeated again and again.Rhymes have rhyming words and a particular rhythm so students sing in proper way.Poems have a meaning and sometimes rhythm too.All that things helps students to pronounce of words.It is very hard to give practice individual but in groups all the students take part.Especially those students, who are shy, slow learners and timid in the classroom.Teacher may use these chants, rhymes and poems starting of the lesson.Use actions or gestures to understand the meaning of the words or sentences.Using chants, rhymes and poems early in the lesson is useful not only for teachers but also students.
Quantum circuits generating four-qubit maximally entangled states

We describe quantum circuits generating four-qubit maximally entangled states, the amount of entanglement being quantified by using the absolute value of the Cayley hyperdeterminant as an entanglement monotone. More precisely, we show that this type of four-qubit entangled states can be obtained by the action of a family of CNOT circuits on some special states of the LU orbit of the state |0000 >.
IMPLEMENTASI FUZZY C-MEAN DAN ALGORITMA PARTICLE SWARM OPTIMIZATION UNTUK CLUSTERING KABUPATEN/KOTA DI INDONESIA BERDASARKAN INDIKATOR INDEKS PEMBANGUNAN MANUSIA

This research is aimed to determine conduct clustering in accordance with the conditions of districts / cities throughout Indonesia based on the IPM indicator and to determine the performance comparison of Fuzzy C-Means using particle swarm optimization compared to ordinary fuzzy c mean. The study uses 514 district / city data in Indonesia based on four IPM indicators. The research show 4 clusters that describe the condition of the Indonesian region and based on the results of cluster validation shows that there are differences in the ordinary Fuzzy C-Means mean algorithm and Fuzzy C-Means using particle swarm optimization.
Moderating Effect of Financial Innovations on the Relationship Between GDP Per Capita and Financial Performance of Commercial Banks in Kenya

Profitability of commercial banks in Kenya have been declining since 2010 which was largely attributed to macro-economic factors, fiscal policies introduced by central bank of Kenya and market activities such as issuance of bonds and capping of interest rates. There has also been increased integration due to embracement of financial innovations in the banking sector however the moderating effects of financial innovations on the relationship between GDP per capita and financial performance is still uncertain.&nbsp; The objective of this study was to investigate the moderating effect of financial innovation on the relationship between GDP per capita and financial performance of commercial banks in Kenya. The study was based on two theories: Keynesian Economics theory and Constraint Induced Financial Innovation Theory. The study utilized secondary data for 10-year period as from 2011 to 2020. The target population of the study was 42 commercial banks that are licensed and supervised by the Central Bank of Kenya. Secondary panel data on financial performance of Commercial Banks was obtained from the individual institutions’ financial reports while data on macroeconomic factors was obtained from both Central Bank of Kenya and Kenya National Bureau of Statistics. Return on assets was used to measure financial performance. &nbsp;The study found a significant and positive relationship (b=0.594, t=2.939, p=0.022) between GDP per capita and ROA.&nbsp; The study found no moderating effect of financial innovations on the relationship between GDP per capita and financial performance of commercial banks.&nbsp; The study recommends that banks should implement the highest degree of innovations, which will enable them achieve very high ROA. Keywords: Financial Innovations, GDP per capita, Financial Performance, Commercial Banks, Moderating effect.
ENHANCEMENT OF DESIGN AND INTERFACE ORIENTATION IN HUMAN- COMPUTER-INTERACTION

Human computer interaction is an area of applied congnitive science and engineering design HCI has emerged as a important field of research directed at a large attention towards "Innovation , Design And Interaction Over Interface" AI based technology and construction of new kinds of various interaction technology .We often argue how HCI has emerged as a new technology world for humans but the understanding of such an attitude to research in terms of philosophical, theoretical and practical understanding level seems relatively poor in such kind of vast IT meadow .Thus this Research paper we have Focused on how HCI can become more effective and advanced in aspects of Designing, interacting , development of interface , technological advancements and many more.HCI theories and rules that human being employ to communicate with computer .Thus in conclusion we have try to give view on how to explore creative ways of Designing computer based interfaces , innovative designs and technological foremost changes to improve the usability and the quality of user experience for better tomorrow if Human-Computer-Interaction.
Application of data analysis and game theory to competitive Pokémon battle sets

&lt;p&gt;This paper analyzes a scenario where two hypothetical Pokémon trainers each have 3 Pokémon and each send out 1 to battle. We form an experiment through repeated battles between each Pokémon matchup to create payoff values for each Pokémon. Game theory and the process of finding a Nash equilibrium are applied to this scenario to determine both the best outcome for both trainers, and how the results state which trainer has more powerful Pokémon sets. Iterated dominance, best responses, and mixed strategies are used routinely to solve for the Nash equilibrium solution. The application of game theory, Nash equilibrium, and data analysis to economics is briefly discussed. &lt;/p&gt;
Software Supply Chains

Software supply chains face several challenges that are often more difficult to address compared to other supply chains. This special issue highlights such challenges, ways of addressing them, the latest advances, and experiences related to software supply chains.
A Case Study of Non-contact Service Learning Operation in University Liberal Arts Classes: Focusing on H University &lt;Thinking and Expression(SL)&gt;

The purpose of this study is to examine the design of classes combining non-contact speaking classes and face-to-face community services in the Covid situation and the effects thereof, and to seek the methods of effective curriculum management. As a form of experiential education, service learning is an educational method that integrates professional knowledge education in schools and practical training in the field to pursue student learning and community outcomes and values. After the course operation, a class satisfaction survey was conducted on students and volunteers to find out the effects of the service learning teaching method and the class operation method, and the reflection log and in-depth interview results were reviewed using the Giorgi's phenomenological analysis method. In this study, it was possible to confirm the positive educational effect of the proposed methods through the high satisfaction of students with the class, the learning effect that the students themselves were aware of, and their internal growth and capacity building. It was also found that the strategy had a significantly positive effect on students' learning and team volunteer work. It is considered necessary to continuously seek flexible and effective teaching strategies and measures to respond to the changing educational environment in the post-Covid era. Therefore, the results of this study are meaningful in that they can be used as reference materials for the development of service learning and its related subjects and various types of classes related to volunteer activities.
Spatiotemporal satellite data imputation using sparse functional data analysis

Many scientific applications and signal processing algorithms require complete satellite images. However, missing data in satellite images is very common due to various reasons such as cloud cover and sensor-specific problems. This paper introduces a general spatiotemporal satellite image imputation method based on sparse functional data analytic techniques. To handle observations consisting of a few longitudinally repeated satellite images that are themselves partially observed and noise-contaminated, we propose a multistep imputation method by following the best linear unbiased prediction principle and pooling information across all available locations and time points. Theoretical properties are established for the proposed approach under a new observation model for functional data that covers the dataset in question as a special case. Practical analysis on the Landsat data are conducted to illustrate and validate our algorithm which also shows that the proposed method considerably outperforms existing algorithms in terms of prediction accuracy. An efficient implementation using R and Rcpp is made available in the R package stfit.
Influence of Grades of Cement on Strength of Concrete as per IS 10262-2019

Abstract: Concrete is the most used material in the world for construction. As we know Cement is the major constituent of concrete which is produced by natural raw materials like limestone rock, clay and chalk etc. Cement is produced in various grades and types used for construction according to the requirement. According to various grades used the strength of the concrete is influenced. The present investigation deals with the development of mix design of concrete using the IS 10262 - 2019. The study mainly focuses on the discussion of strength characteristics of concrete when various grades of cements used with reduction of 5% &amp; 10% to understand if the concrete reaches the required target strength. It also focuses on understanding as to which grade of cement would be able to reach the required strength with less cement content. Compression test and Split Tensile test were conducted for strength analysis. The research evaluates the variation in Mix Design Guidelines between IS 10262-2009 &amp; IS 10262-2019; strength factors of hardened concrete, by using various grades of cement at different percentages for M30 grade concrete at different ages. From this study it can be concluded that, 53 grade gives the better compressive strength with lesser amount of cement content, hence it is suggested that 53 grade cement can be used wherever bulk or mass concreting is done or concrete is produced
Bayesian Bi-clustering Methods with Applications in Computational Biology

Bi-clustering is a useful approach in analyzing biological data when observations come from heterogeneous groups and have a large number of features. We outline a general Bayesian approach in tackling bi-clustering problems in moderate to high dimensions, and propose three Bayesian bi-clustering models on categorical data, which increase in complexities in their modeling of the distributions of features across bi-clusters. Our proposed methods apply to a wide range of scenarios: from situations where data are cluster-distinguishable only among a small subset of features but masked by a large amount of noise, to situations where different groups of data are identified by different sets of features or data exhibit hierarchical structures. Through simulation studies, we show that our methods outperform existing (bi-)clustering methods in both identifying clusters and recovering feature distributional patterns across bi-clusters. We apply our methods to two genetic datasets, though the area of application of our methods is even broader.
Best-First Width Search for Multi Agent Privacy-preserving Planning

In multi-agent planning, preserving the agents' privacy has become an increasingly popular research topic. For preserving the agents' privacy, agents jointly compute a plan that achieves mutual goals by keeping certain information private to the individual agents. Unfortunately, this can severely restrict the accuracy of the heuristic functions used while searching for solutions. It has been recently shown that, for centralized planning, the performance of goal oriented search can be improved by combining goal oriented search and width-based search. The combination of these techniques has been called best-first width search. In this paper, we investigate the usage of best-first width search in the context of (decentralised) multi-agent privacy-preserving planning, addressing the challenges related to the agents' privacy and performance. In particular, we show that best-first width search is a very effective approach over several benchmark domains, even when the search is driven by heuristics that roughly estimate the distance from goal states, computed without using the private information of other agents. An experimental study analyses the effectiveness of our techniques and compares them with the state-of-the-art.
Euclidean Distance-Optimal Post-Processing of Grid-Based Paths

Paths planned over grids can often be suboptimal in an Euclidean space and contain a large number of unnecessary turns. Consequently, researchers have looked into post-processing techniques to improve the paths after they are planned. In this paper, we propose a novel post-processing technique, called Homotopic Visibility Graph Planning (HVG) which differentiates itself from existing post-processing methods in that it is guaranteed to shorten the path such that it is at least as short as the provably shortest path that lies within the same topological class as the initially computed path. We propose the algorithm, provide proofs and compare it experimentally against other post-processing methods and any-angle planning algorithms.
Preprocessing and Future Extraction for Visual Underwater Odometry

Distortion of underwater images can impair the accuracy and robustness of visual odometry algorithms, leading, in particular, to a decrease in the number of detected conjugate key points on pairs of images. In this regard, image preprocessing, the selection of key points and the odometry algorithms themselves are important questions in solving underwater robotics problems. The paper considers on real data the influence of various algorithms for preprocessing and constructing key points on the properties of video odometry algorithms in conditions of underwater and uncontrolled camera movement. It is shown that the number of key points determined on the sequence of images, and, consequently, the accuracy of obtaining the trajectory of the camera movement can depend radically on both preprocessing and the detector used.
Moving Objects Tracking using Motion Vectors with Implementation on a Real ADAS Platform

The basic tasks of Advanced Driver-Assistance Systems (ADASs) are object detection and tracking. Although these tasks can be performed by processing signals from various in-vehicle sensors, the most used is the image captured by the in-vehicle camera. For an autonomous vehicle to know which action needs to be taken at a given moment, very useful data is about the speed and direction of movement of objects in their surroundings. Once objects are detected, different methods can be used to track them. Although there are various methods for object tracking based on computer vision and machine learning, they are very often not suitable for implementation on the real embedded ADAS platforms that have limited memory and computing resources. Therefore, this paper deals with the motion vectors (MVs) estimation between adjacent frames and their grouping with the goal of identifying and tracking objects around the ego-vehicle, all accompanied by the implementation of the proposed solutions onto a real embedded ADAS platform. Different methods for MV estimation and grouping are examined. Special attention was given to the efficient implementation of each task on the ADAS platform. The proposed solution achieves high performance in terms of accuracy when tested on real-life traffic videos. It is important to note that the solution is able to process 64 frames per second for the input images with a resolution of 1280x720 pixels.