Reviewerly/exHarmony huggingface dataset:
Psychological and pedagogical conditions for professional motivation of pedagogical specialties students

In our rapidly developing modern world, where there are trends of high growth in science and technology, there is an acute need for professionally motivated and highly qualified specialists. This article discusses the features of professional motivation of students of pedagogical specialties. To determine the specifics of the formation of professional motivation of future teachers, an experimental study was conducted. The research consisted of 256 third-year students in natural sciences at the Abai Kazakh Pedagogical University in Kazakhstan. In forming the structure of professional motivation of students of pedagogical specialties in our research, we relied on the motivation structure developed by Ilyin. The data obtained made it possible to determine the features of the formation of professional motivation of students of pedagogical specialties, depending on the features of vocational training.&#x0D; &#x0D; Keywords: competence-based approach; professional motivation; paradigm of education; project-based activity.
A Novel Coverless Text Steganographic Algorithm Based on Polynomial Encryption

Aiming at the problems of low text utilization rate and ambiguity of secret information extraction in the “tag + keyword” coverless information hiding methods, we propose a coverless information hiding method of Chinese text based on polynomial encryption in this paper. The secret data communication is realized by the analogously forged URLs transmission, which improves the security of mobile computing to avoid the risk that the carrier texts are attacked maliciously. The text utilization rate and retrieval success rate are improved by using tags to select multiple keywords to expand the number of keywords in the index table. The keyword’s location in secret message is obtained through text vocabulary matching, and the tag index and location information are encrypted by polynomial for secret information transmission. The split keywords of secret message can be transmitted in disorder. The experimental result shows that the secret message can be successfully extracted by sorting the extracted keywords according to the frequency and relevance of their combined tags. In our experiments with different test databases, both the hiding success rate and the average hiding capacity are improved with higher test values than other existing methods.
Language Learning Strategy Used among Secondary School ESL Students

The role of English as a Second Language in Malaysia has prompted ESL learners to explore multi techniques and strategies in learning.However, popular strategies applied by secondary students in Malaysia are not much known.Hence, this study aims to identify the language learning strategies employed by successful language learners among secondary school students in Malaysia.This research employs a survey research design that encompasses the strategy inventory for Language Learning (SILL) It includes the six strategies proposed by (Oxford, 1989).About 38 secondary school students from different states were selected through a purposive sampling technique to answer the survey for the data collection.For the finding, it is revealed that the secondary school students use metacognitive strategies the most, followed by cognitive and memory strategies, which are considered the least used among learning learners.As a result, even though all the three strategies are being employed in their language learning process, it appears that the metacognitive strategy is the one that stands out the most thus confirming its interrelations with successful language learners.Therefore, the language learners strategies practised among secondary school varies from metacognitive as the most preferable one, followed by cognitive, and lastly memory strategies hence reflecting their proficiency level as good language learners.
An Integration of IoT and Machine Learning in Smart City Planning

The global population is growing at an unprecedented rate today and many of the cities are going through the disaster of over-population that causes scarcity of resources. As smart technology increases, the Internet of Things (IoT) and machine learning (ML) can be used for planning smart city that could be able to deal with concomitant society. Smart city aims to design environment-friendly applications with optimal use of space and resource along with the promise to give the optimal distribution of benefits in an effective manner. Transforming any city into a smart city requires the active deployment of IoT with ML technologies. IoT with ML combines as smart technology that plays an important role in intelligent parking system, public safety, smart traffic administration, water management plan, smart street lamps, track of air purity level, smart planning of schools, hospitals, roads etc. to examine, manage and control the resources of the smart city.
The Information System Design of Consumables Goods Management in Bandung Kulon District

Consumables are goods that can only use once as the quantity will decrease. These goods will continue to be produced to meet office needs and daily official activities. It is necessary to regularly manage inventory items to obtain valid data and monitor the process of managing goods, especially at the Bandung Kulon District Office. The Bandung Kulon District Office does not use an application/website to manage inventory so that it makes the inventory process takes longer. In additioan, it is riskier in losing data and inefficient of recording stock using goods cards. It also affects PPTK in preparing the reports that will be submitted to BPKA at the end of each semester with a copy from the inspectorate. Therefore, The Information System Design of Consumables Goods Management in Bandung Kulon District is needed. This system was created by the waterfall method and UML (Unified Modeling Language) and for the implementation using PHP and MySql with BlackBox testing. Data collection is through direct observation and interviews with the concerned people and literature studies for references to create an efficient and precise system. Hopefully, the system can make it easier for officers to manage stock and reduce the risk of data loss as well as speed up report generation.&#x0D;
An Augmented Reality on the Introduction of Escherichia Coli Bacteria that Cause Diarrhea Using the Marker Based Tracker Method

Indonesian current educational curriculum demands learning media for the high school degree. The use of learning tools that utilize technology nowadays is more emphasized to get better learning comprehension. Augmented reality (AR) is virtual information to a direct or indirect view of a physical object. This study aims to apply Augmented Reality technology using the Marker Based Tracking method, which is intended as a learning tool for introducing bacteria, especially Escherichia Coli bacteria, to make it easier and fun to understand. This study uses data collection methods that include literature study, interviews, and questionnaires. Approach methods include designing, creating, and testing Augmented Reality. The results of this Augmented app can help both teachers and students in the teaching and learning process as well as inspire the students to learn Biology for Escherichia Coli bacteria material.
Problems of material incentives for the labor of university teachers

This article aims to study the problems of material incentives for labor in education in the general motivation system of Kazakhstani universities’ teaching staff. In current conditions, when there is simultaneously an increase in demand for higher education and a decrease in the social status and prestige of a teacher, the improvement of organizational and economic mechanisms for stimulating the work of the teaching staff should come to the fore. The article analyzes the level of wages in the education system, which for a long time lags behind the average level of wages in the country’s economy. This fact significantly undermines the incentives to work in the field of education, which, in turn, determines the quality of education. The limitations of the existing system of material incentives for the work of the teaching staff in modern universities are revealed. The necessity of managing labor motivation based on various types of incentives for teachers to achieve higher and better results of labor activity is shown. The study used secondary statistical data from official sources and traditional methods: graphical, system analysis and synthesis, the method of scientific observation, comparison, etc.
The Motor Action Analysis Based on Deep Learning

For the slow speed and low accuracy of slow motor action recognition methods, this study proposes a motor action analysis method based on the CNN network and the softmax classification model. First, in order to obtain motor action feature information, by using static spatial features of BN-inception based on CNN network extracted actions and high-dimensional features of 3D ConvNet, then based on softmax classifier structure and realizing taxonomic recognition of the motor actions. Finally, through the decision-layer fusion and time semantic continuity optimization strategy, the motion action recognition accuracy is further improved and the more efficient motion action classification recognition is realized. The results show that the proposed method can complete the motor action analysis and achieve the classification recognition accuracy to 83.11%, which has certain practical value.
Types of ores of gold-silver deposits of volcano-plutonic complexes in folded belts and methodological aspects of their isolation

The study covers the ores of the three gold-silver type deposits, namely, Lichkvaz-Tei (Armenia), Nevenrekan and Perevalnoe (Russia). These differ in both geological structure and ore localization conditions. Detailed mineralogical studies of these ores were conducted to establish their natural types. The material composition for the ore types, their structural and textural features, the mineral balance of valuable components, and the grain-size composition of their constituent minerals may be used to predict the processing properties of ores at early exploration stages. Along with the traditional approaches, the method of sample pre-classification by factor analysis based on geochemical associations of ore-forming elements was tested. This enabled the development of an algorithm for identifying certain types in each sample and, consequently, the preparation of composite samples for further mineralogical studies. With due account of the geochemical associations, four ore-geochemical types of ores were identified for the Lichkvaz-Tei deposit based on the statistical analysis. These are the gold-arsenide, gold-copper-base metal, copper-zinc, and gold-silver arsenide-antimonide-sulfide types. For all the objects studied, a general ore-mineral parageneses formation sequence has been established: the early pyrite type is replaced by arsenopyrite-pyrite and chalcopyrite-sphalerite types, then by intermediate gold-chalcopyrite-galena-fahlite silver-bearing and late gold-silver-sulfosaline-fahlite and marcasite types. A wide range of natural types of ores have been established, such as: pyrite-arsenopyrite, gold-arsenopyrite, gold-galena-sphalerite, chalcopyritesphalerite types for the Lichkvaz-Tei deposit; gold-pyrite-sulfosaline and oxidized gold-pyrite types for the Nevenrekan mineral occurrence; silver-fahlite-chalcopyrite-galena-sphalerite type for the Perevalnoe deposit. This diversity is due to the different quantitative ratios of ore-mineral parageneses in the composition of the ores.
Design of Information System Archiving for Disbursement of Funds at the Regional Treasury Web-Based (Case Study of the Regional Asset Finance Agency of West Bandung Regency)

Information systems at this time will continue to grow from various aspects, to take advantage of the progress in this era of information systems into a need that must be owned by every agency.One of them is the filing information system, each agency needs to keep documents as important records of various activities.Therefore, the archive must be managed properly so that it is not difficult when searching for the required information.In addition, the archive system can be used in the long term so as to avoid some obstacles that often occur in the management of archives such as damaged, scattered or lost.This archive system was created to facilitate the filing process, because Kasda BKAD archiving is still manually.Therefore, in this study was carried out the design of a filing information system for Disbursement Warrants (SP2D) in Regional Cash (Kasda) in BKAD West Bandung Regency. The development of this system uses waterfall methods and functional design using UML (Unified Modelling Language), the results of black box system testing are obtained valid results..This research produces a web-based information system that is expected to make it easier to manage archives.
Removing Partial Mismatches in Unsupervised Image Captioning

Unsupervised image captioning is a task to describe images without the supervision of image–sentence pairs. With the support of pre-trained object detectors, previous work assigned pseudo-captions, i.e., sentences that contain the detected object labels, to a given image. They focused on aligning the pseudo-captions with input images at the sentence level. However, pseudo-captions contain many words that are irrelevant to a given image. To shed light on the problem of partial mismatches between images and pseudo-captions, we focus on removing mismatched words from image–sentence alignment. We propose a simple gating mechanism that is trained to align image features with only the most reliable words in pseudo-captions: the detected object labels. The superior performance of our method empirically demonstrates the importance of removing the partial mismatches. Detailed analysis elucidates that our method successfully improves its performance in predicting the words likely to be mismatched during training. Furthermore, we show that using our method as an initialization method significantly boosts the performance of the previous sentence-level alignment method. These results confirm the importance of careful alignment in word-level details.
A Model for Requirements Validation through Viewpoint Control

While requirements analysis is the process of building a conceptual model of part of reality, requirements validation involves maximizing one's confidence that the resulting conceptual model 'mirrors' the stake holders' original intent.In particular, validation involves assessing the model for correctness, completeness, and internal consistency.This paper describes an approach to the very early validation of requirements based on learning about the viewpoints and building models of their behavior.The paper is part of the work reported by the author in [1].
Coherent vs incoherent filtering of optical signals: application to quantum communication

The recently demonstrated concept of a quantum pulse gate enables coherent filtering of an individual well-defined optical mode from a noisy signal. This contrasts with the standard technique of spectral filtering followed by temporal gating, which exhibits an inherent trade-off between the efficiency and the noise rejection level. Here we compare the performance of the two techniques in application to quantum key distribution using entangled photon pairs. It shown that coherent filtering may lead to a nearly 10 dB enhancement of the key rate.
Living Science, or Amusing Economic Nobelistics

Unlike the classics of economic thought, it was not until the 1990s that Russia's wide readership became familiar with the Western economists of the 20th century. Special place in the flow of publications devoted to consideration of their life path and analysis of theories created by them holds the literature on Nobel prize winners in economics as leaders of the world economics science. In the post-Soviet period in the domestic historiography of economics science there actually emerged a peculiar section — economic Nobelistics, which uses a wide range of genres: from strictly scientific, or academic, to popular science. In the review on the book “Nobel Prize Winners in Economics (1991–2020)” by Yuri P. Voronov, which analyses achievements of Nobel prize-winners in economics in the last thirty years, an attempt is made to draw readers' attention to such an aspect of this monograph as original presentation of Nobel economists' theories by the author. It is noted that the distinctive feature of the book is accessible, fascinating presentation of the scientific material. At the same time, entertainment in the book, playing the role of stimulus of cognitive interest, essentially performs two functions: a means of teaching and a means of popularization of scientific knowledge. Such features as literary language, author's digressions, original and intriguing titles create the effect of “lively” science. At the same time, entertainment in the book, which plays the role of a stimulus of cognitive interest, essentially performs two functions: a means of teaching and a means of popularizing scientific knowledge. And such features of the work as the literary expressiveness of the language, author's digressions, original and intriguing section titles create the effect of “live” science.
A Deep Learning Method Based on Partition Modeling Forreconstructing Temperature Field

Physical field reconstruction is highly desirable for the measurement and control of engineering systems. The reconstruction of the temperature field from limited observation plays a crucial role in thermal management for electronic equipment. Deep learning has been employed in physical field reconstruction, whereas the accurate estimation for the regions with large gradients is still diffcult. To solve the problem, this work proposes a novel deep learning method based on partition modeling to reconstruct the temperature field of electronic equipment accurately from limited observation. Firstly, the temperature field reconstruction (TFR) problem of the electronic equipment is modeled mathematically and transformed as an image-to-image regression task. Then a partition modeling and inferring framework consisting of an adaptive UNet and a shallow multilayer perceptron (MLP) is developed to establish the mapping from the observation to the temperature field. The adaptive UNet is utilized to reconstruct the whole temperature field while the MLP is designed to predict the patches with large temperature gradients. Experiments employing finite element simulation data are conducted to demonstrate the accuracy of the proposed method. Furthermore, the generalization is evaluated by investigating cases under different heat source layouts, different power intensities, and different observation point locations. The maximum absolute errors of the reconstructed temperature field are less than 1K under the partition modeling approach.
Money-prospects of Cryptocurrencies - A Bibliometric Review

The status of the money-prospects of cryptocurrencies in both conventional and Shari’ah based literature remains hotly debated and largely indecisive. We apply/used the bibliometric approach to review the literature on/regarding the money-prospects of cryptocurrencies. We selected 264 articles published during the years 2011-2021 from Web of Science (WoS) through systematic screening to explore their influential and intellectual aspects. Bibliometric citation analysis was conducted to present/identify influential research categories, leading authors, top articles, prominent countries, and major journals within the sample. We also highlighted the trend of annual scientific production to show sustained growth in the area under research. Furthermore, keyword analysis and bibliometric coupling analysis were applied/carried out to generate networks to highlight the intellectual aspects of the money-prospects of cryptocurrencies. We used the networks of emerging themes and main clusters to conduct content analysis further. We included and reviewed studies which discussed the money-prospects of cryptocurrencies in the light of Shari’ah precepts in relevant clusters. We also identified potential future research areas (cluster-wise). Theis study helps the researchers to understand the evolution, dimensions, and emerging themes regarding the money-prospects of cryptocurrencies.
Creating Attractive Prescription Smart Eyewear - without looking like a character from Star Trek

Today it is possible to 3D print lenses in volume, enabling unique benefits for traditional prescription lenses and for smart eyewear. With 3D printing lenses can be printed with spheres, aspheres, cylinders, prisms, bifocals, trifocals, progressives and anything in-between. It is possible to integrate devices inside these prescription lenses for example, waveguides, films, sensors, lcd or anything else you can think off. It is possible to create airgaps or to print directly on the device. The device can be glass or plastic. The latest innovation is that we can print not only on flat but also on curved surfaces.
Diagnostics of internal affairs officers’ motivation during the assimilation period

The authors represent a research material describing the specificity of motivation of young specialists during the assimilation period at internal affairs agencies as an important factor in the field of HR management, which is the research subject of this article. According to the research subject, the authors formulate the goal to conduct a psycho-diagnostic research of 150 young employees studying at a subordinate education institution. To detect the peculiarities of motivation, the authors use the following methods: interview, test, and association experiment. For the interview, the authors prepared a set of questions about the reasons for enrolling at law-enforcement agencies. For testing, the authors use the questionnaires &amp;laquo;Labor activity motivation structure&amp;raquo; and &amp;laquo;Diagnostics of motivational structure of a personality&amp;raquo;. The authors use the method of association experiment to study self-motivation. In the result of the research, the authors arrive at the following conclusions: &amp;nbsp; Young employees don&amp;rsquo;t have enough motivation, particularly self-motivation as self-actualization, at the same time they declare external positive motivation as a need for a paid job allowing them to supply their capital needs. It is necessary to form motivation, especially self-motivation, of young employees during their assimilation period as internal affairs officers using such methods as assimilation and motivation training, business simulation, psycho-diagnostics, conversation, discussion, and many others. The scientific novelty of the research consists in the study of external and internal motivation of young officers of internal affairs agencies during their assimilation period, the analysis of peculiarities of manifestation of their external and internal motivation, and the formulation of the ways to form their motivation, particularly self-motivation, promoting the development of their professional skills. &amp;nbsp;