Reviewerly/exHarmony huggingface dataset:
중국 대학생의 성취목표지향성, 자아탄력성, 학습몰입의 구조적 관계

It is hard to make Chinese university students, who have never been exposed to absolute economic poverty, participate in learning only with external rewards for learning. Thus, it is important for them to experience the state of intrinsic engagement with the goal to master the learning task itself. This author has examined how achievement goal orientation of Chinese university students would influence their learning engagement and how self-resilience would mediate between their achievement goal orientation and learning engagement. For this purpose, this author has collected data of 524 students of Hebei University in China and analyzed it by structural equation modeling. With this analysis, this author has found that their mastery goal orientation has influenced a significant positive effect on learning engagement and that their performance avoiding orientation has a significant negative impact, and that performance approach orientation has not significant effect. In addition, in effect of how performance approach orientation and mastery goal orientation has influenced learning engagement, there have been partial mediated effects of self-reliance. But in relation between performance avoidance orientation and performance avoidance orientation, there have been no mediated effects of self-resilience. The results of this study have showed that learners with performance avoidanceorientation would be hard to experience learning engagement. In addition, self-resilience is an important variable to help learners experience learning engagement, especially it has mediated for learners with mastery goal orientation. Therefore, this author has concluded that it would be necessary to make an environment in which Chinese university students could have their mastery goals and to support programs that would improve students’ self-resilience.
LoRRaL: Facial Action Unit Detection Based on Local Region Relation Learning

End-to-end convolution representation learning has been proved to be very effective in facial action unit (AU) detection. Considering the co-occurrence and mutual exclusion between facial AUs, in this paper, we propose convolution neural networks with Local Region Relation Learning (LoRRaL), which can combine latent relationships among AUs for an end-to-end approach to facial AU occurrence detection. LoRRaL consists of 1) use bi-directional long short-term memory (BiLSTM) to dynamically and sequentially encode local AU feature maps, 2) use self-attention mechanism to dynamically compute correspondences from local facial regions and to re-aggregate AU feature maps considering AU co-occurrences and mutual exclusions, 3) use a continuous-state modern Hopfield network to encode and map local facial features to more discriminative AU feature maps, that all these networks take the facial image as input and map it to AU occurrences. Our experiments on the challenging BP4D and DISFA Benchmarks without any external data or pre-trained models results in F1-scores of 63.5% and 61.4% respectively, which shows our proposed networks can lead to performance improvement on the AU detection task.
Latin-Spanish Neural Machine Translation: from the Bible to Saint Augustine

Although there are several sources where to find historical texts, they usually are available in the original language that makes them generally inaccessible. This paper presents the development of state-of-the-art Neural Machine Systems for the low-resourced Latin-Spanish language pair. First, we build a Transformer-based Machine Translation system on the Bible parallel corpus. Then, we build a comparable corpus from Saint Augustine texts and their translations. We use this corpus to study the domain adaptation case from the Bible texts to Saint Augustine’s works. Results show the difficulties of handling a low-resourced language as Latin. First, we noticed the importance of having enough data, since the systems do not achieve high BLEU scores. Regarding domain adaptation, results show how using in-domain data helps systems to achieve a better quality translation. Also, we observed that it is needed a higher amount of data to perform an effective vocabulary extension that includes in-domain vocabulary.
An empirical wave forecasting model based on the neural network

A multiple regression model based on the neural network is applied to short-term wave forecasting. Three-layered neural network and back-propagation learning rule are used to develop the forecasting model. A series of learning data, which is necessary to construct the network, consist of difference of atmospheric pressure (input) and significant wave height (output). The forecasting models are made with respect to 4 points along the coast of the Japan Sea. The results show that the problem of the usual regression models is solved fairly.
Matrix Function for Solving Optimal Game Pass Strategy Summary

The breakthrough is to quantify the amount of water, food and money carried by people in the desert and to construct a discrete function with the number of days as a time variable, optimal Planning and design for the outflow of desert-walking resources and the introduction of resources and funds from the starting point, villages and mining areas, these resources and funds are fitted by the Adjacency Matrix and the coherent knowledge of probability to describe their dynamic changes with time (days). According to the restriction of the rules of the game, we try to find the optimal solution by computer software (Matlab) in order to reduce the computation of human brain.
Yale University Library Research Guides: Grammars for Linguists: Boolean Operators

Information on locating reference (and other) grammars for use in linguistics, with an emphasis on ebooks.
PENINGKATAN PROSES PEMBELAJARAN IPS MENGGUNAKAN MODEL MAKE A MATCH DI KELAS V SD NEGERI 21 PPA SOLOK

The purpose of this study was to describe and increase in student learning process in social studies learning by using the Make a Match model in the fifth grade of elementary school. Types of this research was classroom action research with qualitative and quantitative approach. The research subject was 24 grade V students. The research procedure consistend of planning, implementing, observing, and reflecting. The result of the study showed and increase in aspects: (a) RPP cycle I with an average of 76,77% and cycle II 92,85%, (b) implementation on the aspect of the teacher cycle I with an average of 82,81% and the second cycle 87,50%, (c) implementation on the aspect of the students of the first cycle with an average 79,68% and cycle II 87,50%,. The conclusions from the result of the research conducted are using the Make a Match model can improve student learning process in social studies learning in class V SD Negeri 21 PPA Solok.
PERAN PUSTAKAWAN PERGURUAN TINGGI DALAM MELAKSANAKAN BIMBINGAN LITERASI DIGITAL DI ERA WORK FROM HOME

This study aims to develop a model of information literacy guidance related to the role of college librarians during the Covid 19 pandemic. The source of the data is obtained by observing the college repository access model, and conducting a library study of students' information literacy abilities in finding reference sources scientific to support the lecture process. Samples were taken from college which were included in cluster 1 of Indonesian college clustering which were released by Kemristekdikti in 2019. The results showed that most of the college repositories still applied limited access and closed access. In addition, the ability of digital literacy of students is still low, even though they are already classified as a native digital generation. This research concludes that the digital literacy learning model that is compiled needs to consider the behavior and habits of the user during their online lectures and learning from home, by utilizing information technology, and social media as a media for publication and promotion.
IDENTIFY FAQ KNOWLEDGE GAP IN IT HELPDESK USING KNOWLEDGE MAPPING CASE STUDY: HALOSIS BPS-STATISTICS

One important feature of IT HelpDesk, such as HaloSIS, is knowledge base. This feature disseminate knowledge about problem solving knowledge. This knowledge base goals were to assist service desk for giving fast solution to problem reported by user call and to facilitate learning about problem solving for new member of technical support team. To improve problem solving performance, technical support team can update or add this knowledge base with new problem solving knowledge. However, until this day this knowledge base was not updated. This can lead HaloSIS into tacit knowledge problem. This tacit knowledge remain in technical support head and not documented to knowledge base. To identify new knowledge that was not yet transferred to knowledge base, HaloSIS team need to identify knowledge gap that happen in HaloSIS knowledge base. There is a tool of knowledge management that can be used for identifying knowledge gap. This tool is knowledge mapping. Knowledge map can be used to representing the incompleteness of the current knowledge network that will enable to attain a sustainable future. This study propose knowledge map building from troubleshooting log in HaloSIS. This study build current knowledge map based on FAQ knowledge and merge it with knowledge found in troubleshooting log. The methodology to build knowledge map was the 6-step method from Kim's research. The data analysis method used is qualitative data analysis method using thematic analysis. From this knowledge map this study found 15 new know-how knowledge and recomendation to update 7 know-how knowledge. However, there are some limitations of this study which only maps the online presence system. For future research, it is necessary to build a knowledge map for all services in HaloSIS comprehensively to maintain, renewal, and seeking for knowledge.
Unambiguous measurement range and error tolerance in dual-wavelength interferometry

In dual or multiwavelength interferometry, the traditional equivalent wavelength method is widely used for phase recovery to enlarge the unambiguous measurement range (UMR). In fact, however, this method ignores information of size and sign (positive or negative) of single wavelength wrapped phases, and the extension of the UMR is not sufficient. For the reflective measurement, the largest UMR of the dual or multiwavelength interferometry is half of the least-common multiple (LCM) of single wavelengths, called the LCM effective wavelength, which is often several times the equivalent wavelength. But why do we often use the equivalent wavelength and seldom use the larger UMR in practice? Existing research reveals that the actual UMR is related to the measurement error of single-wavelength-wrapped phases, and half of the LCM effective wavelength is only the theoretical value. But how do errors affect the UMR? We think the quantitative analysis and description are lacking. In this paper, we continue to study this problem, analyze it in a graphical method, and give quantitative descriptions. The simulation experiments are carried out and verify our analysis.
Translating Knowledge Representations with Monolingual Word Embeddings: the Case of a Thesaurus on Corporate Non-Financial Reporting

A common method of structuring information extracted from textual data is using a knowledge model (e.g. a thesaurus) to organise the information semantically. Creating and managing a knowledge model is already a costly task in terms of human effort, not to mention making it multilingual. Multilingual knowledge modelling is a common problem for both transnational organisations and organisations providing text analytics that want to analyse information in more than one language. Many organisations tend to develop their language resources first in one language (often English). When it comes to analysing data sources in other languages, either a lot of effort has to be invested in recreating the same knowledge base in a different language or the data itself has to be translated into the language of the knowledge model. In this paper, we propose an unsupervised method to automatically induce a given thesaurus into another language using only comparable monolingual corpora. The aim of this proposal is to employ cross-lingual word embeddings to map the set of topics in an already-existing English thesaurus into Spanish. With this in mind, we describe different approaches to generate the Spanish thesaurus terms and offer an extrinsic evaluation by using the obtained thesaurus, which covers non-financial topics in a multi-label document classification task, and we compare the results across these approaches.
Estado del arte de las telecomunicaciones en Colombia en tiempos de pandemia Covid-19

This work refers to the services that the telecommunications has provided in order to face the current pandemic, denominated as Covid-19 by the OMS, which enquired the Colombian government to take extraordinary measures, limiting the concentration of people in public and private areas, taking the decision to suspend in person work as well as classes in all educative institutions, all these decisions caused people to migrate to new online work strategies and virtual learning. The following paper compiles the search of different articles related to information technology, that gives small glimpses to the diverse services that are being presented, and the benefits that provides the implementation of work and study without interruption or even with a greater level of technological satisfaction, experimenting demanding changes and aquiring new abilities in this versatile world.
Signal Rich Art: Improvements and Extensions

Signal rich art is an application of watermarking technology to communicate information using visible artistic patterns. In this paper we show new methods of generating signal carrying patterns, simplifications of earlier methods, how to embed a vector watermark signal in applications and how to use signal symmetries to expand the detection envelope of a watermark reader.
PENGARUH KINERJA PEGAWAI DAN FASILITASPERPUSTAKAAN TERHADAP KEPUASAN MAHASISWADI PERPUSTAKAAN UNIVERSITAS KHAIRUN TERNATE

The purpose of this study is to determine the Influence and Employees and Library Space in general or simultaneously to the Student Satisfaction at the University Library Khairun Ternate. The analysis model used to test multiple linear regression hypothesis, and research method which is the research with the number of samples and the number of respondents as much as 99 respondents. With data processing techniques using SPSS 16 for windows. The results of the study found that: (1) Employee Performance has a positive and significant influence on student satisfaction in the library of Khairun University of Ternate, which  means  that  the  higher  the  employee  performance,  the  higher  the  student satisfaction level, (2) The library facilities have a positive and significant impact on student satisfaction in the library of the University of Khairun Ternate, which means that with good facilities and adequate to provide learning outcomes to students, (3) Performance and Space Library against students at the University Khairun Ternate, which means that the higher performance and equipped with facilities adequate, the higher the level of student satisfaction   in   the   library   of  Khairun   University   of   Ternate.   With  the   result   of simultaneously both positive and significant variable to student satisfaction with R2  value (R Square) corrected by 0,559 or 55,9%.
미래 공동체를 위한 안드라고지로서 시민교육의 재고(再考)

The purpose of this study was to analyze the civic education that has been carried out so far in a socio-philosophy, find and deconstructed the problem, and apply it to “Andragogy” as a new paradigm. In addition, the future community to which civic education will be applied as an Andragogy was defined as a vacant lot and presented its contents. Our civic education shows both the possibility and the limit at the same time. The reason why limitations arise here was due to pedagogic civic education. Pedagogic civic education overlooked internalization and physical erudition, and regarded only the recognition of text as the core of civic education. Civic education has been pushed aside from other subjects in its content priorities, and has created an awkward situation for adults. To overcome this, Andragogy, the prototype of education for human life, is needed. Andragogy is an educational paradigm based on erudition. As an Andragogy, civic education is for all members of society, regardless of any age or institution. The future community pursued by civic education as an Andragogy should be a community as conviviality, not a democracy. Community as conviviality pursues the well-being and happiness of all members of the community. Civic education for community as conviviality should be erudition to foster autonomy, authenticity, and activity. As a Andragogy for the community as conviviality, civic education is the key to the future and the hope of our education.
Peningkatan Kemampuan Menyusun Kalimat Efektif melalui Teknik Menyusun Unsur Kalimat pada Siswa Kelas XI SMA

The purpose of this study is (1) obtaining an objective description of the increase in the ability of students of the XI-SMA class in composing effective sentences after the student has been given a provision to compose the sentence element and (2) obtained an objective description of the change in student behaviour during the study.  , one way that can be pursued is by increasing the ability to compose effective sentences. The results showed that there was an increase in the ability to compose effective sentences through the technique of arranging the elements of the sentence appears in the results of pretes on composing elements of sentences obtained by the students with an average score of class 5.85, while the results of pretes on the ability to compose effective sentences with the average score of class reaches 6.35. The test results on the sentence element in cycle I reached an average score of 6.58 which means an increase of 0.73 or 1.83%, while the test results on the effective sentence on the I cycle achieved an average score of 7.59 which means an increase of 0.91 or 2.28%, while the test result on effective sentences in cycle II was obtained an average score of 8.01 which means an increase of 0.42 or 1.05%Keywords: increased ability, compose effective sentences, techniques for composing sentence elements.
KERANGKA MODEL KONSEPTUAL PENERIMAAN APLIKASI PLAGIARISM CHECKER UNTUK PENINGKATAN KUALITAS KARYA ILMIAH

Improving the quality of scientific papers has become a concern of many circles, especially by universities. Various universities in Indonesia have now subscribed to applications or technology-based systems that are used to detect the level of similarity of a paper with other existing works. This paper aims to provide a conceptual framework model for application acceptance or a plagiarism checker system based on a review of various relevant writings and literature. The model of academic integrity and belief in technology is considered to have significance for the acceptance of the academic community towards the implementation of the plagiarism checker application or system. This model is based on reading and analyzing various relevant writings or literature. Based on these results, universities need to instill the importance of having academic integrity and providing technical skills to increase the acceptance of the academic community towards the application of plagiarism checkers to improve the quality of the scientific work produced.
Analyse sémantique robuste par apprentissage antagoniste pour la généralisation de domaine (Robust Semantic Parsing with Adversarial Learning for Domain Generalization ).

Nous presentons des resumes en francais et en anglais de l’article (Marzinotto et al., 2019) presente a la conference North American Chapter of the Association for Computational Linguistics : Human Language Technologies en 2019.
Special issue on new trends and challenges of bio‐inspired computational intelligence algorithms in massively complex systems

Massively complex systems, such as social networks (Camacho, Panizo-LLedot, Bello-Orgaz, Gonzalez-Pardo, & Cambria, 2020; Lara-Cabrera et al., 2017), renewable energy problems (Twidell & Weir, 2015), or Internet-of-Things problems (Lin et al., 2017), generate massive amounts of data. These massively complex systems have attracted the attention of both industrial and research communities, because the analysis of data can generate valuable knowledge about the specific domain. But at the same time, the amount of data generated and the complexity of the problems mean that classical algorithms and approaches do not provide suitable solutions. In this case, it is quite common for computational intelligence (CI) techniques to extract the knowledge. CI can be defined as a set of bio-inspired research areas focused on the study of adaptive mechanisms to enable, or facilitate, intelligent behaviour in complex and changing environments. There are several research fields that compose CI, including swarm intelligence (Gonzalez-Pardo, Jung, & Camacho, 2017), and evolutionary computation (Salcedo-Sanz, Ortiz-Garcýa, Ángel M. Pérez-Bellido, Portilla-Figueras, & Prieto, 2011). This special issue is focused on the application of bio-inspired algorithms to massively complex systems, ranging from concepts and theoretical developments to advances technologies and innovative applications. This special issue welcomed submissions of original papers introducing research results on all the aspects covering the application of CI algorithms to massively complex systems, ranging from concepts and theoretical developments to advanced technologies and innovative applications. This issue presents expanded versions of the best papers presented at the 19th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2018), which was held in Madrid (Spain). As the special issue editors, we would like to take this opportunity to thank the various authors for their papers and the reviewers for their work. We are also grateful to Jon Hall, Editor-in-Chief of the Wiley journal Expert Systems. We would like to particularly thank the IDEAL'18 programme committee members for their hard work and dedication.
Sky Segmentation for Enhanced Depth Reconstruction and Bokeh Rendering with Efficient Architectures

We present a high-quality sky segmentation model for depth refinement and investigate residual architecture performance to inform optimally shrinking the network. We describe a model that runs in near real-time on mobile device, present a new, highquality dataset, and detail a unique weighing to trade off false positives and false negatives in binary classifiers. We show how the optimizations improve bokeh rendering by correcting stereo depth misprediction in sky regions. We detail techniques used to preserve edges, reject false positives, and ensure generalization to the diversity of sky scenes. Finally, we present a compact model and compare performance of four popular residual architectures (ShuffleNet, MobileNetV2, Resnet-101, and Resnet-34-like) at constant computational cost.
SQL Developer Web

Now that we have a deep understanding of the various Oracle Cloud Infrastructure (OCI) Always Free resources and created some, let us now explore how we can create web applications to make the best use of them. For Part 4 of this book, please create the following OCI resources: