Reviewerly/exHarmony huggingface dataset:
Future Designers’ Professional Competence Formation with the Innovative Technologies Use

The aim of the article is a theoretical substantiation of innovative technologies introduction in the process of future designers’ professional training. Based on scientists’ researches analysis concerning the problem of future specialists’ professional competence formation, it is determined that the introduction of innovative technologies has a positive influence on future specialists’ professional competence formation in the process of studying in higher education institutions. Research methods. Methods of analysis, comparison, and generalization, as well as methods of pedagogical experiment and pedagogical observation were applied. Scientific novelty consists in defining the concept of "project activity" as a specific form of independent learning activity modeling on the basis of the student’s personal choice for cognitive or practical tasks in non-standard situations, which provides the personal content of learning. It is substantiated that the project activity basis is cognitive skills development, ability to independently design knowledge and navigate the information space, development of future designers’ critical thinking. It is emphasized that project activity promotes the formation of professionally relevant knowledge, future designers’ skills, as well as assimilation of a certain structure of project activity, which is important both for professional activity and future designers’ personal development and also provides the formation of positive learning motivation. Conclusions. The necessity of introducing the project activity into the process of future designers preparing is proved, as the project activity contributes to the formation of future designers’ professional competence structure components.
Docker-based Web Server Instructional System

With the rapid development of artificial intelligence, there is an increasing demand for the cultivation of innovative talents in artificial intelligence at the present stage. Based on the cloud services provided by cloud computing, it is an effective practical method to design and develop the integrated system of artificial intelligence and teaching. Docker container, as a lightweight and portable open source engine in cloud computing, provides a great solution in realizing micro-software services, rapid integration, simple operation and maintenance, continuous update and other aspects. Docker container technology can be used to package the instructional system into several mirror applications that are easy to manage. The mirror application and corresponding containers can be used to provide users with SaaS (software as a service), so as to develop a teaching management and learning system with system management, course management and experiment management functions. There is system software, environment configuration and running program required for the normal operation of the system. The instructional system’s development is mainly from PC terminal. PC-side Web mainly adopts B/S-based architecture. The system takes MySQL + Express + AngularJS + NodeJS technology route，named MEAN.JS. All users can directly use the tutorial system from any browser. Combined with relevant literature, this paper analyzes and designs the service mode, technical framework, basic functions, extended application and interactive implementation of the instructional system.
A Novel Approach to Key Management Using Visual Cryptography

Visual Cryptography encrypts the secret or key into 'n' shares or portions and distributes them to a group of 'n' participants.The secret is recovered only when shares of all the participants in the group are stacked upon one another depending on the method used.This technique eliminates complex computations during decryption.It uses simple OR or XOR Boolean operations.Once the secret is revealed, it is no more a secret.So, a new secret acts as a key, that is to be again shared confidentially.The same process is performed and new shares are generated and distributed.The generation and distribution of shares must be done every time when a new secret or a combinational key is shared.In this paper, a trusted third party generates the shares and distributes it to the group of participants.It also generates an extra share for itself.To reveal the secret, the third party's share is also used along with other participants shares.Every time when the secret is to be changed, the third party regenerates its share only, instead of generating shares for all participants.This method reduces the overhead of regeneration and redistribution of shares to all participants with every change of the secret or key.This method of key management also retains the perfect contrast and security.The OR based method leads to noise during recovery.XOR based operations during recovery recovers lossless image.So, XOR operation is more preferable during recovery of the secret.
ANÁLISIS DE ACCESIBILIDAD WEB EN LAS UNIVERSIDADES ECUATORIANAS PARA ATENDER LAS NECESIDADES DE ESTUDIANTES CON DISCAPACIDAD

This article describes a current analysis of the accessibility to portals and web resources of public and private universities in Ecuador. The evaluation was carried out by checking the opinion of students with disabilities and the technical analysis of compliance with the Web content accessibility guidelines established by the World Wide Web Consortium in the WCAG 2.1 recommendation. Unfortunately, the results show that universities have partially accessible websites; that is to say, many of the own technologies developed by the HEIs do not meet the standards and guidelines of accessibility and usability, limiting access to information, communication and quality in learning, as well as personal autonomy especially of students with visual and hearing impairment.
Peer Review of Research Data Submissions to ScholarsArchive@OSU: How can we improve the curation of research datasets to enhance reusability?

<strong>Objective</strong>: Best practices such as the FAIR Principles (Findability, Accessibility, Interoperability, Reusability) were developed to ensure that published datasets are reusable. While we employ best practices in the curation of datasets, we want to learn how domain experts view the reusability of datasets in our institutional repository, ScholarsArchive@OSU. Curation workflows are designed by data curators based on their own recommendations, but research data is extremely specialized, and such workflows are rarely evaluated by researchers. In this project we used peer-review by domain experts to evaluate the reusability of the datasets in our institutional repository, with the goal of informing our curation methods and ensure that the limited resources of our library are maximizing the reusability of research data. <strong>Methods</strong>: We asked all researchers who have datasets submitted in Oregon State University’s repository to refer us to domain experts who could review the reusability of their data sets. Two data curators who are non-experts also reviewed the same datasets. We gave both groups review guidelines based on the guidelines of several journals. Eleven domain experts and two data curators reviewed eight datasets. The review included the quality of the repository record, the quality of the documentation, and the quality of the data. We then compared the comments given by the two groups. <strong>Results</strong>: Domain experts and non-expert data curators largely converged on similar scores for reviewed datasets, but the focus of critique by domain experts was somewhat divergent. A few broad issues common across reviews were: insufficient documentation, the use of links to journal articles in the place of documentation, and concerns about duplication of effort in creating documentation and metadata. Reviews also reflected the background and skills of the reviewer. Domain experts expressed a lack of expertise in data curation practices and data curators expressed their lack of expertise in the research domain. <strong>Conclusions</strong>: The results of this investigation could help guide future research data curation activities and align domain expert and data curator expectations for reusability of datasets. We recommend further exploration of these common issues and additional domain expert peer-review project to further refine and align expectations for research data reusability. <em>The substance of this article is based upon a panel presentation at RDAP Summit 2019.</em>
A substructural epistemic resource logic: theory and modelling applications

Abstract We present a substructural epistemic logic, based on Boolean BI, in which the epistemic modalities are parametrized on agents’ local resources. The new modalities can be seen as generalizations of the usual epistemic modalities. The logic combines Boolean BI’s resource semantics—we introduce BI and its resource semantics at some length—with epistemic agency. We illustrate the use of the logic in systems modelling by discussing some examples about access control, including semaphores, using resource tokens. We also give a labelled tableaux calculus and establish soundness and completeness with respect to the resource semantics.
Weighted Sampling for Combined Model Selection and Hyperparameter Tuning

The combined algorithm selection and hyperparameter tuning (CASH) problem is characterized by large hierarchical hyperparameter spaces. Model-free hyperparameter tuning methods can explore such large spaces efficiently since they are highly parallelizable across multiple machines. When no prior knowledge or meta-data exists to boost their performance, these methods commonly sample random configurations following a uniform distribution. In this work, we propose a novel sampling distribution as an alternative to uniform sampling and prove theoretically that it has a better chance of finding the best configuration in a worst-case setting. In order to compare competing methods rigorously in an experimental setting, one must perform statistical hypothesis testing. We show that there is little-to-no agreement in the automated machine learning literature regarding which methods should be used. We contrast this disparity with the methods recommended by the broader statistics literature, and identify a suitable approach. We then select three popular model-free solutions to CASH and evaluate their performance, with uniform sampling as well as the proposed sampling scheme, across 67 datasets from the OpenML platform. We investigate the trade-off between exploration and exploitation across the three algorithms, and verify empirically that the proposed sampling distribution improves performance in all cases.
Learning DNFs under product distributions via mu--biased quantum Fourier sampling

We show that DNF formulae can be quantum PAC-learned in polynomial time under product distributions using a quantum example oracle. The current best classical algorithm runs in superpolynomial time. Our result extends the work by Bshouty and Jackson (1998) that proved that DNF formulae are efficiently learnable under the uniform distribution using a quantum example oracle. Our proof is based on a new quantum algorithm that efficiently samples the coefficients of a μ–biased Fourier transform.
Method and Apparatus for Querying Relational and XML Database Using French Language

The extraction of the information from database systems requires the formulation of queries using database query languages, such as Structured Query Language (SQL).This formulation needs the knowledge of the model and the structure of the database.However, non-expert users cannot write such queries.This is why a lot of works have been developed to request the database in natural language.Historically, most of these works were carried out for English language and they were designed for a specific database model.Some of them function independently of database domain.For the French language, all existing contributions are dependent on database domain and model.The aim of this paper is to present a model of an intelligent interface to query databases using the French language.A simulation model was established through the using of linguistic operations and machine learning.The results indicate that the proposed interface functions independently of the database domain and model (relational and XML) and it can translate a very important number of French natural language query into a database query.The findings of this research may serve to improve the interaction between non-expert French users and databases.
MLP and CNN-based Classification for Points of Interest in Side-Channel Attacks

There are lots of different sample points in a single trace, the each sample point containing some leakage information is useful to obtain the key when a chip encrypt plaintext with the key, these points of interest in a trace could be extracted and a new trace is formed sequentially. If using this shorter trace could improve the performance of classification in neural networks during side-channel attacks and to reduce the amount of traces required in the classification, and it means that these sample points are indeed useful and contain lots of information needed for side-channel attacks. In this paper, different amount of points of interest extracted from traces in ASCAD to form a new kind of traces as input data feed into neural networks including Multi-Layer Perceptron, Convolutional Neural Networks. In order to compare with the result of POI-traces, Principal Components Analysis was also used to shorter the length of the original trace in ASCAD, so that its length is the same as POI-traces'. About the results, the classification results with ASCAD traces are the worst using MLP or CNN, the results of PCA-traces which contain only 100 sample points using MLP are the best, and the results of POI-traces containing 300 sample points are the best result using CNN. So when using neural networks to assist side-channel attacks, the transformation of traces or the reduction of its length is advantageous to a certain extent.
An Overview of Path Planning and Obstacle Avoidance Algorithms in Mobile Robots

An Overview of Path Planning and Obstacle Avoidance Algorithms in Mobile Robots - written by Basavanna. M , Dr. Shivakumar. M published on 2019/12/26 download full article with reference data and citations
Dual language programme: The perceptions and challenges of teachers and students in Klang, Selangor

Dual Language Programme (DLP) was introduced to improve the level of English proficiency among students. This has become a hot topic since the Ministry of Education (MOE) was requested to review the implementation of DLP as the teachers and students face challenges in teaching and learning of Science and Mathematics in English. Thus, this study aims to identify the teachers’ and students’ insights on DLP and the challenges they faced after the implementation. The data were obtained through a questionnaire. A total of 146 DLP students consisting of Form 1 and Form 2 students and 8 teachers from four secondary schools in Klang, Selangor participated in this study. Besides, semi-structured interviews were carried out among the teachers as well. The finding shows that most of the teachers and students have positive views towards the implementation of DLP, although they faced some challenges. Moreover, students are keen to learn Science and Mathematics in English even though their English proficiency still at the unsatisfying level.
The actor-network theory of B. Latur and porcelain services of classicism: the relevance of a museological discussion

In this article an attempt is made to tell about the actor-network theory of the French sociologist B. Latur in application to the history of the creation and existence of ceremonial services of the second half of the 18 th century.For demonstration of separate provisions of the theory of Latur, the most known porcelain and faience services of the German, French, English and Russian manufactories from the era of early and strict classicism were chosen.The author tells about the transition of motives and forms from the Sevres "Service with cameos" and the "Berlin" service to Russian "Arabeskovy", "Kabinetsky", "The Dowry" and other services.The article mentions the silver services executed by the Parisian masters J.-N.Roettiers, R.-J.Auguste, etc., for the brothers Orlov, who helped Catherine II to occupy the throne, and also silver services for deputies of the new provinces founded by the Russian empress.The history of the creation of services illustrates a continuous chain of administrative reforms, military conflicts, political and personal events and also changes in artistic taste.By means of the ceremonial objects on which ware was carried for ceremonial lunches, the European monarchs not only subtly affected style and fashion in Russia, but also skillfully played politics.While Catherine II accepted gifts and made large orders for European and domestic production, she successfully engaged with her closest partners in diplomacy and economy, waged information war, and made dynastic plans.Many facts specified in the article prove that Bruno Latur's concept about the active impact of things on social and political relations is confirmed in practice.Latur's approach to studying material monuments, artifacts, and decorative arts is demanded by the modern science of history of art.
E2E Verifiable Electronic Voting System for Shareholders

In this paper we propose an end-to-end (E2E) verifiable online shareholder voting system. Our system allows different voters to have different weights associated with their votes. These weights are dependent upon the number of shares owned by voters in an organization. In our system, the voters cast their votes over the Internet using a personal computing device, say a smart-phone. The voting client interacts with an online voting server which generates encrypted ballots for the chosen candidates with a receipt. Every encrypted ballot comes with a non-interactive zero-knowledge proof to prove the well-formedness of the ciphertext. In addition, the voting system allows the voters to verify their votes are cast as intended through voter initiated auditing. All the encrypted ballots and non-interactive proofs are made available on a publicly readable bulletin board. By checking the receipt against the bulletin board, voters are assured that their votes as recorded as cast. Finally, this e-voting scheme allows everyone including third-party observers to verify all votes are tallied as recorded without involving any tallying authorities. Once the polling concludes, the tallying result is available immediately on the bulletin board with publicly verifiable audit data to allow everyone including third-party observers to verify the tallying integrity of the entire election.
Automatic text summarization of Swedish news articles

With an increasing amount of textual information available there is also an increased need to make this information more accessible. Our paper describes a modified TextRank model and investigates t ...
Robot Collision Detection and Distinction Based on Convolution Filtering Dynamic Model

With the increasing application of human-robot interaction, collision detection between robot and unknown environments, along with further distinction from the intentional contact between human and robot, have become urgent problems to be solved.In this paper, a new collision detection algorithm is proposed, and a collision distinction method is further designed on the basis of this algorithm.The generalized momentum and the convolution method are used to develop the robot convolution filtering dynamic model.Then, the force-sensing observer that uses only proprioceptive sensors is designed to observe the torque deviation of the joint online to realize robot collision detection.At the same time, the performance of the forcesensing observer is improved by compensating for joint friction.The proposed algorithm does not need any external sensors; it overcomes the disadvantage of calculation errors owing to the acquisition of joint acceleration information.The filter can be flexibly selected in the algorithm according to the actual application of the robot.Moreover, two force-sensing observers are adopted in the collision distinction method.The contact or collision between a human and a robot can be further distinguished after setting the appropriate thresholds and filtering parameters.The collision detection algorithm can be easily adapted to different types of robot to ensure human safety, and the proposed collision distinction method can be used to improve the work efficiency of the robot.External force sensing experiments show that the low-pass and bandpass observers work well and different force signals can be observed.The collision detection and human-robot interaction experiments are performed to verify that the collision detection algorithm and collision distinction method are reasonable and effective.
Statistical Models in Forensic Voice Comparison

This chapter describes a number of signal-processing and statistical-modeling techniques that are commonly used to calculate likelihood ratios in human-supervised automatic approaches to forensic voice comparison. Techniques described include mel-frequency cepstral coefficients (MFCCs) feature extraction, Gaussian mixture model - universal background model (GMM-UBM) systems, i-vector - probabilistic linear discriminant analysis (i-vector PLDA) systems, deep neural network (DNN) based systems (including senone posterior i-vectors, bottleneck features, and embeddings / x-vectors), mismatch compensation, and score-to-likelihood-ratio conversion (aka calibration). Empirical validation of forensic-voice-comparison systems is also covered. The aim of the chapter is to bridge the gap between general introductions to forensic voice comparison and the highly technical automatic-speaker-recognition literature from which the signal-processing and statistical-modeling techniques are mostly drawn. Knowledge of the likelihood-ratio framework for the evaluation of forensic evidence is assumed. It is hoped that the material presented here will be of value to students of forensic voice comparison and to researchers interested in learning about statistical modeling techniques that could potentially also be applied to data from other branches of forensic science.
PENGEMBANGAN LEMBAR KERJA PESERTA DIDIK (LKPD) MENULIS CERPEN BERBASIS APLIKASI ANDROID

This study aims to produce a valid,pratical and effective student worksheet (LKPD) based on Android applications for short writing material in Indonesia language learning. Development research was designed using research methods of modification and collaboration development theory proposed by Jolly Bolitho,Dick,Carey and Carey (2005). This LKPD frame work consists of the homepage menu, material, traning,assessment criteria, and development. To obtain information on the feasibility of the LKPD, expert validation was carried out covering aspects of material, language, and media feasibility. To test the practicality of LKPD, one on one and small group trials were conducted with data collection techniques through questionnaires. Finally, to find out the effective of LKPD field trials were carried out through experiments with data collection techniques using tests. Based on data analysis,it can be concluded that the LKPD writing short stories developed very valid is very practical and very effective as a learning facility for students. The resulting LKPD can be used as teaching materials to improve the quality of the process and learning out comes of writing short stories.