Reviewerly/exHarmony huggingface dataset:
La competencia digital docente del profesor universitario 3.0

espanolEste articulo se acerca a los conceptos de competencia digital y alfabetismo digital, cuya primitiva confusion ha supuesto una limitacion a la hora de presentar un protocolo de actuacion en la formacion digital docente. Se presta atencion concreta a la realidad del profesor universitario y a la situacion existente en la educacion superior. Para ello, se ha llevado a cabo una investigacion, preeminentemente cualitativa, que deja en evidencia la importante fractura que surge entre las destrezas que se le exigen al docente actual y la carente o poco efectiva formacion academica que recibe para alcanzarlas. EnglishThis article approaches to the concepts of digital competence and digital literacy, whose primitive confusion has meant a limitation when presenting an action protocol in digital teacher training. Concrete attention is given to the reality of the university professor and the situation in higher education. For this, a pre-eminently qualitative investigation has been carried out, which shows the important fracture that arises between the skills required of the current teacher and the lack or ineffective academic training received to achieve them.
Swarm Programming Using Moth-Flame Optimization and Whale Optimization Algorithms

Automatic programming (AP) is an important area of Machine Learning (ML) where computer programs are generated automatically. Swarm Programming (SP), a newly emerging research area in AP, automatically generates the computer programs using Swarm Intelligence (SI) algorithms. This paper presents two grammar-based SP methods named as Grammatical Moth-Flame Optimizer (GMFO) and Grammatical Whale Optimizer (GWO). The Moth-Flame Optimizer and Whale Optimization algorithm are used as search engines or learning algorithms in GMFO and GWO respectively. The proposed methods are tested on Santa Fe Ant Trail, quartic symbolic regression, and 3-input multiplexer problems. The results are compared with Grammatical Bee Colony (GBC) and Grammatical Fireworks algorithm (GFWA). The experimental results demonstrate that the proposed SP methods can be used in automatic computer program generation.
Attributes Based Storage System for Secure De-Duplication of Encrypt Data in Cloud

These days, Cloud storage is gaining importance among individual and institutional users. Individual and foundations looks for cloud server as a capacity medium to diminish their capacity load under nearby devices. In such storage services, it is necessary to avoid duplicate content/repetitive storage of same data to be avoided. By reducing the duplicate content in cloud storage reduces storage cost. De-duplication is necessary when multiple data owner outsource the same data, issues related to security and ownership to be considered. As the cloud server is always considered to be non trusted, as it is maintained by third party, thus the data stored in cloud is always encrypted and uploaded, thus randomization property of encryption affects de-duplication. It is necessary to propose a serverside de-duplication scheme for handling encrypted data. The proposed scheme allows the cloud server to control access to outsourced data even when the ownership changes dynamically.
Glanceable AR: Evaluating Information Access Methods for Head-Worn Augmented Reality

Augmented reality head-worn displays (AR HWDs) have the potential to assist personal computing and the acquisition of everyday information. In this research, we propose Glanceable AR, an interaction paradigm for accessing information in AR HWDs. In Glanceable AR, secondary information resides at the periphery of vision to stay unobtrusive and can be accessed by a quick glance whenever needed. We propose two novel hands-free interfaces: head-glance, in which virtual contents are fixed to the user’s body and can be accessed by head rotation, and in which contents can be summoned into central vision by eye-tracked gazing at the periphery. We compared these techniques with a baseline heads-up display (HUD), which we call interface in two dual-task scenarios. We found that the head-glance and eye-glance interfaces are more preferred and more efficient than the gaze-summon interface for discretionary information access. For a continuous monitoring task, the eye-glance interface was preferred. We discuss the implications of our findings for designing Glanceable AR interfaces in AR HWDs.
New Estonian Words and Senses: Detection and Description

The Web era has intensified the need for the automatic monitoring of language, including the extraction of new words and senses. In this paper, we first give a brief overview of the unified dictionary system Ekilex, the starting point for all new lexicographic tasks at the Institute of the Estonian Language since 2019. We describe the existing databases meant for manual collecting and registering new words and meanings. Next we describe an experimental study on semi-automatic new word detection on the basis of the small media corpus and existing dictionaries carried out in 2018 at the Institute of the Estonian Language. The goal of the experiment was to develop a workflow for new word detection, to test the reliability of the tools for Estonian language processing, and to compile the new word candidate list. The experiment was focused on single word detection. The results revealed that in order to make new word discovery more effective we need more advanced tools for automatic language processing, and we perceive an urgent need to set up an infrastructure for (semi-) automatic new word detection.
AN APPROACH TOWARDS SOIL EROSION MONITORING SYSTEM USING SATELLITE IMAGES THROUGH DATA MINING AND PATTERN MINING TECHNIQUES

In this paper, we determine a data mining techniques on agricultural land for soil erosion monitoring. We used the spatial data and pattern mining tool used herein the time series of satellite images. The first thing we use in time series of satellite images is to get the input images and it is processed and spatial mining is used. Pattern mining we use consists of a lot of processes the data are taken and some pre-processing happen, we use image segmentation on the satellite images, we used pattern theory and last;y the resulted are collected in order for forming visualization to get the better data results considering the soil erosion on agricultural land.
Microblogging Hashtag Recommendation Considering Additional Metadata

Microblogging is used to broadcast short messages in form of text, pictures, links, and videos to the followers or subscribers on the Internet. The hashtag is the keyword or metadata that is used to mark messages, which allow users to classify or find the related posts easily. However, posts in microblogging environment are not properly tagged due to data sparsity and finding the popularly used relevant hashtag for the tweets. In this paper, hash tag recommender (HTR) is the proposed method using matrix factorization with tweet’s tags for user input text. To eliminate data sparsity, hashtag recommendations are generated from similar tweets. Hashtags based on the current trends, time, and location are recommended for the short messages of input by the user. To achieve this, the proposed method calculates the score for each tags, which are identified for similar tweets, and recommendations are generated. Results of this study show that hashtag recommendation outperforms the previous methods. The significance of the proposed HTR for twitter data set is more accurate on considering various metadata such as time and location.
Facebook. Una herramienta 2.0 al servicio de la docencia universitaria

The education system has undergone a substantial change, it has gone from a teaching 1.0, centered on the teacher as a transmitter of knowledge, to a 2.0 system in which the student assumes an active role. Moreover we could even say that we are in a scenario 3.0, where communication manifests itself in all directions, with a growing role of the exchange of knowledge among equals through participatory and collaborative teaching. The implementation of this system requires new means and this is where the use of social networks takes center of the stage in the teaching-learning process. Facebook is revealed as the most popular social media among university students. Its application in teaching through this experience of innovation, has allowed to measure the positive impact of its use in the acquisition of competences in the Degree in Business Administration and Management. This could be applied extendable to other university studies.
Bi-direction Context Propagation Network for Real-time Semantic Segmentation.

Spatial details and context correlations are two types of important information for semantic segmentation. Generally, shallow layers tend to contain more spatial details, while deep layers are rich in context correlations. Aiming to keep both advantages, most of current methods choose to forward-propagate the spatial details from shallow layers to deep layers, which is computationally expensive and substantially lowers the model's execution speed. To address this problem, we propose the Bi-direction Context Propagation Network (BCPNet) by leveraging both spatial and context information. Different from the previous methods, our BCPNet builds bi-directional paths in its network architecture, allowing the backward context propagation and the forward spatial detail propagation simultaneously. Moreover, all the components in the network are kept lightweight. Extensive experiments show that our BCPNet has achieved a good balance between accuracy and speed. For accuracy, our BCPNet has achieved 68.4 \% mIoU on the Cityscapes test set and 67.8 \% mIoU on the CamVid test set. For speed, our BCPNet can achieve 585.9 FPS (or 1.7 ms runtime per image) at $360 \times 640$ size based on a GeForce GTX TITAN X GPU card.
Bridging Natural Language Processing AI techniques and Corporate Communications: towards an integrative model

Digitalisation and technological innovations have confused our traditional theories of reading; key-concepts of literacy (e.g., reading and writing, text and context, comprehension, reception, and interpretation) have become slurred and vexed, including teaching and assessing reading. This confusion resulted in a debate that, among other issues, has provoked the question of whether digital reading can be considered as reading, or it is just a distraction from reading. (Coyle 2008; Badulescu 2016) To decide on this dilemma, I suggest three attributes: (1) act, (2) reading material, and (3) device that can determine the reading. Concerning their relation, the device (the third attribute) determines the reading material (the second attribute) and the act of reading (first attribute). The consideration of the significance of the device is in harmony with McLuhan 1967’s ideas about the determining role of medium and technological determinism; however, it is not a necessary presumption of my ideas. Based on the above three attributes, I claim that digital reading is reading, but a special, extended version. Digital reading shows various similarities to print reading but also differences as well; however, these latter are not that significant that could validate the exclusion of digital reading from the category of reading or qualify it as a mere distraction. Moreover, applying digital devices for reading besides traditional reading means a new opportunity for comprehension and cognitive development, and these are essentials in improving the reading skills of future generations. Engaging children in the complex mental, physical, and sensual experience that reading can give, irrespectively of the type of reading, is the biggest challenge to accomplish in the field of reading in the 21 st century.
Comparison of Problem-Based Learning and Discovery Learning Model

This study aims to compare the problem-based learning and discovery learning models in terms of curiosity, high-level thinking skills, and student competencies. This research is a quantitative study using a quasi-experimental design. The population in this study were 270 students, while for a sample of 90 students were taken by side random technique. The method of data collection is done by interviews, observations, documentation, and questionnaires. Analysis of the data used is descriptive and inferential statistics. The results showed that the problem-based learning model was more effective than the discovery learning model in terms of curiosity, the problem-based learning model was as effective as the discovery learning model in terms of high-level thinking ability, and the problem-based learning model was more effective compared to discovery learning model learning in terms of student competencies. Based on the results of the study, it can be concluded that the problem-based learning model is more effective than the discovery learning model in terms of curiosity and student competencies, but in terms of high-level thinking ability both problem-based learning and discovery learning models provide effective effectiveness same.
A Self-adaptive Mechanism Embedded Gravitational Search Algorithm

Gravitational search algorithm (GSA) has attracted more and more attention in dealing with complex optimization problems. However, it still suffers from some major drawbacks, such as poor exploitation. This paper has proposed a novel self-adaptive chaotic search mechanism embedded GSA (SA-GSA), in which different chaotic maps are utilized to guide the local search in a self-adaptive way. Specifically, instead of defining the search range randomly and arbitrarily, the distance between distinct individuals has been utilized in the current population as the search range. Thus the search range will decrease synchronously according to the convergence speed of the population, which is thought to improve the exploitation ability of GSA effectively. To evaluate the performance of SA-GSA, we compare it with classic GSA and the classic chaotic GSA (CGSA) on 23 benchmark optimization problems. The experimental results and statistic analysis verify that SA-GSA is superior to its competitors in terms of convergence speed and solution accuracy rate.
Machine-learning-based column selection for column generation

Column generation (CG) is widely used for solving large-scale optimization problems. This article presents a new approach based on a machine learning (ML) technique to accelerate CG. This approach,...
A Novel Image Encryption Algorithm Based on Secure Hash Function and Galois Field

A novel image encryption algorithm based on secure hash function and Galois filed is proposed in this paper. We design a keystream generator based on SHA-512 for creating a matrix validated for the randomness by NIST tests. This matrix is used as a key matrix of the proposed encryption and decryption algorithms. Applying the multiplication operations between plain-image and key matrix on Galois field GF(28) to conceal pixels information. Two scrambling matrices are generated by ascending the rows and columns of the key matrix, respectively, to change the positions of pixels. Experimental simulations and security analysis demonstrate that the proposed algorithm has high security and sensitivity to resist brute-force attacks, statistical attack, differential attack, etc.
Cryptosystems using an improving hiding technique based on latin square and magic square

&lt;p&gt;Hackers should be prevented from disclosing sensitive data when sent from one device to another over the network. Therefore, the proposed method was established to prevent the attackers from exploiting the vulnerabilities of the redundancy in the ciphertext and enhances the substitution and permutation operations of the encryption process .the solution was performed by eliminates these duplicates by hiding the ciphertext into a submatrix 4 x4 that chooses randomly from magic square 16x16 in each ciphering process. Two techniques of encrypted and hiding were executed in the encryption stage by using a magic square size 3 × 3 and Latin square size 3 × 3 to providing more permutation and also to ensure an inverse matrix of decryption operation be available. In the hiding stage, the ciphertext was hidden into a 16×16 matrix that includes 16 sub-magic squares to eliminate the duplicates in the ciphertext. Where all elements that uses were polynomial numbers of a finite field of degree Galois Fields GF ( ). The proposed technique is robust against disclosing the repetition encrypted data based on the result of Avalanche Effect in an accepted ratio (62%) and the results of the output of the proposed encryption method have acceptable randomness based on the results of the p-values (0.629515) of the National Institute of Standards and Technology (NIST) randomness tests. The work can be considered significant in the field of encrypting databases because the repetition of encrypted data inside databases is considered an important vulnerability that helps to guess the plaintext from the encrypted text.&lt;/p&gt;
Books of the 18th century in the collection of the Tambov regional universal scientific library named after A.S. Pushkin

We analyze the qualitative and quantitative composition of the book collection of the civil press of the 18th century, which are in the collection of the Tambov regional universal library named after A.S. Pushkin (hereinafter TRUL). The relevance of the work is connected with the need to restore an objective picture of the creation and functioning of manor libraries of the late 18th century as an element of the cultural environment. The implementation of the Russian Foundation for Basic Research project allowed showing the world of the Tambov book of the 18th century in all its diversity. The novelty of the work lies in a system approach to the study of the array of books in Russian and foreign languages of pre-revolutionary libraries of the Russian province. We consider Tambov collections of foreign books of the 18th century, system information of which is currently absent in historiography and appears only as separate mentions in the works of local historians. The work with the existing repertoire of the library showed the key importance of Derzhavin library for the formation of modern Tambov collections of rare books of the 18th century. It is shown that the main array of the identified publications reflects the products of the Capital printing houses of the 18th century. The variety of thematic composition of the revealed collections is demonstrated. Among these collections of TRUL books there are publications on history, literature, philosophy, religion and natural sciences. The research proves that the study of the composition of the book collections of civil press of the 18th century gives important information for the study of book culture of the Tambov province, allows to analyze the appearance of the book works in the region and to find out the degree of attention to foreign and Russian media. Also it allows to detect the role of the book in the structure of cultural environment.
Understanding Teacher Gaze Patterns for Robot Learning

Human gaze is known to be a strong indicator of underlying human intentions and goals during manipulation tasks. This work studies gaze patterns of human teachers demonstrating tasks to robots and proposes ways in which such patterns can be used to enhance robot learning. Using both kinesthetic teaching and video demonstrations, we identify novel intention-revealing gaze behaviors during teaching. These prove to be informative in a variety of problems ranging from reference frame inference to segmentation of multi-step tasks. Based on our findings, we propose two proof-of-concept algorithms which show that gaze data can enhance subtask classification for a multi-step task up to 6% and reward inference and policy learning for a single-step task up to 67%. Our findings provide a foundation for a model of natural human gaze in robot learning from demonstration settings and present open problems for utilizing human gaze to enhance robot learning.
Language barriers to effective communication

ABSTRACTGlobalization and communication technology are bringing the world closer together in a global village, including language barriers. The things that prevent us from understanding each other's constitute a common challenge to individuals, groups, international companies, governments, nations, and the whole world. This qualitative study aimed at exploring the factors that cause language barriers, their types, and their impact on effective communication and our life as well as ways to make people aware of the importance of overcoming them. The study concluded that language or semantic barriers arise from different subjects such as meanings and uses of words, symbols, images, gestures, languages and dialects.RESUMENLa globalizacion y la tecnologia de la comunicacion estan uniendo al mundo en una aldea global, incluyendo barreras del idioma. Las cosas que nos impiden entendernos constituyen un desafio comun para las personas, los grupos, las companias internacionales, los gobiernos, las naciones y el mundo entero. Este estudio cualitativo tuvo como objetivo explorar los factores que causan las barreras del idioma, sus tipos y su impacto en la comunicacion efectiva y nuestra vida, asi como las formas de sensibilizar a las personas sobre la importancia de superarlas. El estudio concluyo que el lenguaje o las barreras semanticas surgen de diferentes temas, como significados y usos de palabras, simbolos, imagenes, gestos, idiomas y dialectos.
CULTURAL VALUE IN PHATIC COMMUNICATION OF MINANGKABAU SOCIETY

&lt;p&gt;&lt;em&gt;The idea of phatic communion was introduced by Malinowski where the phrase is refered to the language used to unite the union with other members of the community. As Minangkabau community is well known for their Phatic Communication ‘Baso-Basi’. This research was conducted to describe the cultural value of phatic communication of Minangkabau society in the form, the function, and the factors that affected on the use of phatic cmmunicatin. This research is descriptive qualitative research which used the socio-pragmatics approach. The respondents were chosen among native Minangkabau community. The result shows that Phatic communion occurs for in formal or informal situation and the relationship between the participants can be intimate or distant. It can be found in both higher and lower status. The function of phatic communication is to establish and maintain social relationship between people in society. The influenced factors of the use of phatic communication are: (1) Differences in situation; (2) Difference in relatives; (3) Differences in age, (4) Differences in position, (5) Differences in social status, (6) Gender differences, (7) Marital status, (8) Relationship intimacy, and (9) The purpose of conversation&lt;/em&gt;&lt;em&gt;.&lt;/em&gt;&lt;/p&gt;
Code-mixed parse trees and how to find them

In this paper, we explore the methods of obtaining parse trees of code-mixed sentences and analyse the obtained trees. Existing work has shown that linguistic theories can be used to generate code-mixed sentences from a set of parallel sentences. We build upon this work, using one of these theories, the Equivalence-Constraint theory to obtain the parse trees of synthetically generated code-mixed sentences and evaluate them with a neural constituency parser. We highlight the lack of a dataset non-synthetic code-mixed constituency parse trees and how it makes our evaluation difficult. To complete our evaluation, we convert a code-mixed dependency parse tree set into “pseudo constituency trees” and find that a parser trained on synthetically generated trees is able to decently parse these as well.